Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

Samad  M. E. Sepasgozar; Reyhaneh Karimi; Sara Shirowzhan; Mohammad Mojtahedi; Sabbar Ebrahimzadeh; David McCarthy

doi:10.3390/buildings9090191

Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

Sepasgozar, Samad M. E.;Karimi, Reyhaneh;Shirowzhan, Sara;Mojtahedi, Mohammad;Ebrahimzadeh, Sabbar;McCarthy, David 2019-08-26 00:00:00 buildings Review Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK 1 , 2 1 1 Samad M. E. Sepasgozar * , Reyhaneh Karimi , Sara Shirowzhan , Mohammad Mojtahedi , 3 4 Sabbar Ebrahimzadeh and David McCarthy Faculty of Built Environment, The University of New South Wales, Sydney, NSW 2052, Australia Department of Art and Architecture, The University of Science and Culture, Tehran 1461968151, Iran Department of Law, Quaemshahr Azad University, Qaemshahr 4765161964, Iran KPMG Major Projects Advisory, Sydney 2000, NSW, Australia * Correspondence: samad.sepasgozar@gmail.com; Tel.: +61-(02)-469628400 Received: 30 June 2019; Accepted: 22 August 2019; Published: 26 August 2019 Abstract: Delay is one of the main challenges of construction projects, and there is still much to overcome in order to reach near zero delay in all construction projects. This project aims to conduct a systematic critical review including a bibliography analysis on delay literature in construction. The main questions consider what has been learnt from a decade investigating delay causes and eects in the construction literature and what factors have been missed in the literature. This paper also presents a new and challenging question regarding how digital tools and associated technologies may prevent any delay in construction projects, which can change the research direction from delay investigations to identifying prevention factors. The paper identiﬁes the delay dataset, including 493 papers investigating delay in construction, and establishes a speciﬁc dataset of papers focusing on delay eects and causes (DEC), including 94 selected papers covering dierent factors examined in over 29 countries such as Iran, India, Turkey, Bangladesh, Saudi Arabia, the United Arab Emirates (UAE), Cambodia, Oman, Malaysia, Taiwan, China, Vietnam, the US, the UK, and Egypt. In addition, the paper identiﬁes 30 critical factors with the frequency of occurrences over three times in the DEC dataset and computes their medians of ranking. This paper also discusses digital tools and methods that can be used for delay analysis and preventions, including MS Project, Oracle Primavera P6, and Open Plan by Deltek. The paper discusses the project schedule delay analysis from project management methodology perspectives. It also discusses the current method’s limitations and future directions, which are based on the identiﬁcation of the deﬁciency areas. In total, four overlooked factors are identiﬁed and suggested, including faulty data analysis, unmatched structure of the research questionnaires with new knowledge and standards [e.g., Project Management Body of Knowledge (PMBOK)], overlooked eects of digital technologies [e.g., Digital twin, Navisworks, Building Information Model (BIM), Geographic Information System (GIS), and Integrated Project Delivery (IPD)], and ignored job-site technologies. In addition, the paper presents the DEC model for future studies, including four main key factors. These factors are resources (e.g., project budgets, labour, material, equipment, and digital tool), project context, stakeholders performance (e.g., owner/client, consultant/designer, contractor, vendor/supplier), and external factors (e.g., ground condition, site location, regulation, natural disaster), which may signiﬁcantly aect delay prevention and should be concurrently considered in the future delay investigations, since they may be required for designing an eective mitigation strategy when these proof points are identiﬁed. This would signiﬁcantly help to utilise digital systems to prevent time overruns in dierent construction contexts. Buildings 2019, 9, 191; doi:10.3390/buildings9090191 www.mdpi.com/journal/buildings Buildings 2019, 9, 191 2 of 37 Keywords: delay; time overruns; cost overruns; scheduling; PMBOK construction extension; PMI scheduling standards; Microsoft projects; primavera; BIM; GIS; risk analysis; IPD 1. Introduction Disruptive technologies have been increasingly introduced to construction businesses in recent years, even though the industry continues to lag behind all other industries in its adoption of technology. However, there is not enough awareness of the current and best practices in project time management. The applications of these technologies for delay monitoring have not been fully examined regarding, for example, how intelligent or smart contracts can reduce disputes and delays in projects. While there is an urgent need to identify the application of new digital technologies and tools for preventing delay in a project, most papers still try to identify delay analysis techniques using the traditional approaches [1], such as conducting a survey including common factors determined many years ago [2,3]. This paper aims to review the literature over the past decade and develop directions for future studies in delay investigations in construction projects. The main objectives of the paper are: to identify the delay eects and causes (DEC) dataset; to identify key critical factors causing delay in construction projects in the previous decade; to identify dominant methods used in the delay literature; to review the current digital technology capacity for preventing delay; and to identify deﬁciency areas, present a conceptual DEC model, and map the future directions. These objectives are important to project management scholars to base their future investigations on a comprehensive critical analysis of a one-decade endeavour of delay investigations in dierent countries. Project managers are able to plan the construction sequence, monitor the status of project activities, and update the project progress to identify the project delays by using project controls software systems, particularly software that is professionally developed for project time and cost management. Speciﬁcally, project scheduling software systems are able to manage changes to the schedule baseline to accomplish the planned project completion data. However, site logs in construction projects or periodical progress reports (e.g., daily or weekly) are required to capture the status of the project as an input into the project scheduling software. Applications or platforms developed for project time management are instrumental tools for evaluating the project deviation from the planned baseline. Project scheduling software can be used to compare the actual project progress compared to the planned baseline. The actual start and ﬁnish dates for project activities form the basis for actual progress calculations and document the as-built schedule information. Project scheduling software monitors the progress of all the project’s activities with the order of the critical path, the near-critical path, and the non-critical path activities to evaluate the impact of delay on project schedule. If critical path activities slip, they immediately cause project delay. The components of a project schedule can be monitored by a variety of techniques such as ﬂoat dissipation or erosion of ﬂoat, missed start and ﬁnish dates, actual duration analysis, and earned value management using a project controls software system. Project scheduling software predominantly uses the critical path method (CPM) for its scheduling practice. Its use is often the focus of contract claims due to project time impacts and delays to the contract completion date. Schedule progress is measured against the contract planned dates. The baseline is an important reference in all scheduling software if contract and progress delay disputes arise between stakeholders involved in projects. A baseline is a complete copy of a project plan that we can compare to the current schedule to evaluate progress in all scheduling software. As a project progresses, certain types of project data are likely to change. When a project is in progress and data changes, the original baseline created for the project may not accurately measure performance against the current project. Empirical evidence suggests that, during these events, the project schedule needs to be re-baselined to reﬂect the revised plan to achieve the estimated completion date. Likewise, creating a new baseline may not yield accurate results for measuring performance, because some data change during the life of the project, which should be measured against the original project data [4]. Buildings 2019, 9, 191 3 of 37 The key terms and concepts used in the delay literature are brieﬂy presented in Table 1. The deﬁnitions of these terms are signiﬁcant, since they create alignment in thinking of speciﬁc delay causes, tools, and standards in the construction ﬁeld. Some of the terms are interdisciplinary and are borrowed from dierent contexts such as Building Information Modeling (BIM), Integrated Project Delivery (IPD), and Geographic Information Systems (GIS). Table 2 shows several examples of delay in dierent contexts and countries. Delay may signiﬁcantly aect project cost and may raise disputes, arbitration, litigation, and abandonment. Table 1. Key terms and deﬁnitions that may be used in the delay literature. Term/ Concept Deﬁnition The dierence between estimated and actual completion time [5], also known as Delay/Time Overruns time overrun [6] or extended time [7], mainly due to contractor, owner, or joint of all stakeholders tasks and actions [8]. The dierence between estimated and actual cost results in increasing the total Cost Overruns project cost, also known as budget overrun, due to unforeseen costs or underestimation of task’s actual cost [9]. Scheduling A control structure based on planning and dispatching [10]. Project Management Body of Knowledge (PMBOK) guide, including principals PMBOK and knowledge required for project management [11]. Focuses on construction projects by providing supplemental knowledge about Construction Extension project health, safety, security, and environmental management and project ﬁnancial management and good practices. Project Management Institute (PMI) refers to good practice methods for PMI Scheduling scheduling. Good practices are based on a general agreement on appropriate Standards use of skills, tools, and techniques for enhancing the success chances of dierent projects. Microsoft (MS) Projects A tool for project planning and control [12]. Primavera A tool for scheduling and project risk analysis [13]. Both Building Information Modelling (BIM) and Geographic Information Building Information Systems (GIS) [14] are analytical and visualisation systems. Model (BIM) BIM is used for designing and sharing collaboratively generated rich data [15]. Both Building Information Modelling (BIM) and Geographic Information Geographic Systems (GIS) [14] are analytical and visualisation systems. Information System GIS is used for map processing, database visualisation, and spatial analysis and (GIS) can be integrated with other systems [16,17]. Analysis of adverse events at dierent stages, including planning and Risk Analysis programming, to enrich decisions [18]. Integrated Project Delivery (IPD) intends to increase the success of a project by Integrated Project addressing waste and ineciency issues and adversarial relations in Delivery (IPD) construction [19]. Buildings 2019, 9, 191 4 of 37 Table 2. Delay in dierent contexts, including the percentages of the delay reported in the literature. Delay cases reported in the literature Evidence of delay in percentage UK: (1) 2017; construction projects in general [20]; (1) About 30% of projects were delayed [20]; (2) the (2) 1993-1994; government construction projects average time overrun was 23.2% [21]; (3) 70% of [21]; (3) 2001; government construction projects [22] projects were delayed [22]. 109 senior leaders of public and private organisations from across the globe, 26% from (1) Just 25% of construction projects came within 10% public bodies such as government agencies with the of their original deadlines [23] remainder represented by private enterprises [23] Philippines: 2010–2017; public–private partnership 92.8% of projects were delayed [24]. (PPP) projects Malaysia: (1) 2005; government contract projects (1) 17.3% were delayed for over 3 months. [25]; (2) [25]; (2) 2010–2014; Kuala Lumpur Airport Terminal caused extra USD $2 billion to the ﬁnal costs [26]. 2 [26] Oman: 2010–2013; A major public organisation 62% within their schedule [27]. Africa: (1) 2009–2012; Rwanda; public [28]; (2) (1) 65.7% of projects were delayed [28]; (2) 70% were 2000–2011; Ghana; roads [29]; (3) 1999–2005; Benin delayed for average of 17 months [29]; (3) 22% of [30]; (4) 1970– 1998; Ghana; groundwater projects were delayed for more than 2 years [30]; (4) construction [30] 70% of projects were delayed [30]. India: 2012; central sector infrastructure projects Approximately 57% of projects were delayed [31]. UAE: 1995–2005; construction projects in general 50% of projects were delayed [32]. (1) 70% of projects were delayed from 10% to 30% of Saudi Arabia: (1) 2004; private and public projects estimated time [6]; (2) time overrun decreased from [6]; (2) construction of water and sewage works [33] 59% in 1994 [33] to 40% in 2004 [34]. (1) The percentage of delay in 2001, 2002 and 2003 Iran: (1) projects for government [35]; (2) Khuzestan were respectively 30%, 74.5% and 75%. [35]; (2) the steel company [36] project duration is approximately 150% of project estimated duration [36]. (1) Projects were respectively delayed for 2.5 weeks US: (1) general projects of US and England [37]; (2) and approximately a month [37]; (2) the time overrun 2001; highway projects [38] of projects was 25% of their contract duration [38]. 56% of projects were delayed, approximately 54% Kuwait: 1990–2000; private residential housing were delayed for four months or more, and 30% were projects [39] delayed for more than six months [39]. (1) 70% were delayed and caused 51.51% cost overrun Nigeria: (1) 1991–1996; housing projects [40]; (2) [40]; (2) time overrun was in average 51% of the 2000; most projects in Lagos city [41] predicted duration [41]. Jordan: 1990–1997; public construction projects [42] 81.5% of projects were delayed [42]. Hong Kong: (1) 1990–1993; government projects (1) Only 40% within schedule [43]; (2) only 23% [43]; (2) 1990–1993; private sector projects within schedule [43]. Western Canada: civil, institutional, high rise Several cases of 24 projects were delayed more than apartment building, and petrochemical 100% of contract duration [44]. Indonesia 38% of projects were delayed [37]. Projects of 20 nations (Europe, North America, and Time and cost overruns were, on average, 70% and other); during last 70 years; rail, ﬁxed link (bridges 28%, respectively [45,46]. and tunnels), and road Rich democracies (Denmark, Germany, Japan, South Korea, Netherlands, Norway, Spain, Sweden, Average schedule overrun of projects was 42.7% [47]. UK, and US); during last three decades; infrastructure projects Buildings 2019, 9, 191 5 of 37 This paper ﬁrst systematically identiﬁes articles investigating delay and time overrun in construction and then conducts a content analysis to review relevant articles in detail and provide a comprehensive understanding of the current literature. Finally, it identiﬁes the gap in the literature and suggests future studies. 2. Review Method Based on the initial review of the current practices in the literature, a set of strings was developed to Buildings 2019, 8, x FOR PEER REVIEW 5 of 36 select the ﬁnal search criteria. The search string was selected as “delay overrun” or “time overrun” and Based on the initial review of the current practices in the literature, a set of strings was developed “construction industry” or “construction project” and applied on the Scopus database, which resulted to select the final search criteria. The search string was selected as “delay overrun” or “time overrun" in 493 records using the search criteria, as shown in Appendix A. and "construction industry" or "construction project"’ and applied on the Scopus database, which The search was limited to articles investigating causes and eects in the past ten years, from 2009 resulted in 493 records using the search criteria, as shown in Appendix A. to 2018. Therefore, “cause” and “eect” were also included in the search criteria. Applying the criteria The search was limited to articles investigating causes and effects in the past ten years, from 2009 resulted in developing the delay eects/causes (DEC) database in construction with 94 records using to 2018. Therefore, “cause” and “effect” were also included in the search criteria. Applying the criteria the search criteria shown in Appendix A. Dierent tools and techniques including VOS Viewer and resulted in developing the delay effects/causes (DEC) database in construction with 94 records using clustering algorithms were used for visualisation and conducting the present systematic review. the search criteria shown in Appendix A. Different tools and techniques including VOS Viewer and clustering algorithms were used for visualisation and conducting the present systematic review. 3. Bibliography Analysis 3. Bibliography Analysis This section reports the results of a quantitative analysis focusing on bibliographic attributes, including Thi co-citations s section re for port identifying s the resultinter s of aconnections quantitative of an the alysi delay s focu literatur sing on e bibl within iograselected phic attributes articles , and including co-citations for identifying interconnections of the delay literature within selected articles their corresponding citations. The systematic analysis alleviates bias during search, article selection, and their corresponding citations. The systematic analysis alleviates bias during search, article and bibliography analysis. The employed bibliometric method assists in identifying similarities and selection, and bibliography analysis. The employed bibliometric method assists in identifying possible patterns of inquiry based on citation records and cited references [48,49]. similarities and possible patterns of inquiry based on citation records and cited references [48,49]. Figure 1 shows the result of co-authorship analysis using the full counting method. The minimum Figure 1 shows the result of co-authorship analysis using the full counting method. The number of papers of an author was considered as one, thus 1179 authors and co-authors of 493 selected minimum number of papers of an author was considered as one, thus 1179 authors and co-authors articles were included and are visualised in Figure 1. Figure 2 shows the co-authorship network for all of 493 selected articles were included and are visualised in Figure 1. Figure 2 shows the co-authorship 259 co-authors using the full counting method based on the DEC dataset including 94 papers. network for all 259 co-authors using the full counting method based on the DEC dataset including 94 papers. Figure 1. Visualisation of co-authorship network for all 1179 co-authors using the full counting Figure 1. Visualisation of co-authorship network for all 1179 co-authors using the full counting method method based on the first bibliographic dataset including 493 papers. based on the ﬁrst bibliographic dataset including 493 papers. Buildings 2019, 9, 191 6 of 37 Buildings 2019, 8, x FOR PEER REVIEW 6 of 36 Buildings 2019, 8, x FOR PEER REVIEW 6 of 36 Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method based baseon d on the thdelay e delae y effect ects and s and causes causes(DEC) (DEC)dataset dataset including including 9 94 4 pa papers. pers. For each of the 1179 authors, the total strength of the co-authorship links with all authors and For each of the 1179 authors, the total strength of the co-authorship links with all authors and co-authors co-authorwer s were e calcu calcula lated, ted,and andthe the gr gre eatest atest li link nk str stre ength ngth wa was s cconsider onsidered ed fo for r th the e visu visualisation alisation of of Figur Figure e 1. In 1. addition, In additi di on ,er d ent iffer numbers ent num of be papers rs of pa from pers an from author anwer auth e selected or werefor sefutur lected e investigation. for future investigation. The results show that, for the minimums of two, three, and four papers of an author, The results show that, for the minimums of two, three, and four papers of an author, 138, 43, 138, 43, and 12 authors met the criteria. This shows that a limited number of authors continuously or Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method and 12 authors met the criteria. This shows that a limited number of authors continuously or frequently based on the delay effects and causes (DEC) dataset including 94 papers. frequently contribute to the delay literature, including Lee, H. S. [50–53], Park, M. [50–53], Yap, J. B. contribute to the delay literature, including Lee, H. S. [50–53], Park, M. [50–53], Yap, J. B. H. [54–58], H. [54–58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61–69]. This shows that, among a large Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61–69]. This shows that, among a large set of scholars For each of the 1179 authors, the total strength of the co-authorship links with all authors and set of scholars investigating delay in construction, only a limited number of authors are regularly co- investigating delay in construction, only a limited number of authors are regularly co-authoring in the co-authors were calculated, and the greatest link strength was considered for the visualisation of authoring in the delay area. This is also limited in the DEC dataset where the criteria are applied and delay arFi ea. gure This 1. is In also additi limited on, difin ferent the n DEC umbedataset rs of pawher pers e from the a criteria n authoar r e were applied selecte and d fo the r future focus of the the focus of the literature is effect and cause. investigation. The results show that, for the minimums of two, three, and four papers of an author, literature is eect and cause. 138, 43, and 12 authors met the criteria. This shows that a limited number of authors continuously or Figure 3 shows the co-occurrence analytical map of keywords based on the ﬁrst bibliographic frequently contribute to the delay literature, including Lee, H. S. [50–53], Park, M. [50–53], Yap, J. B. dataset. For this visualisation a minimum number of 2 was selected for co-occurrence visualisation and H. [54–58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61–69]. This shows that, among a large a total of 713 keywords out of the sample of 2926 keywords are shown in Figure 3. The normalisation set of scholars investigating delay in construction, only a limited number of authors are regularly co- method of LinLog was used in VOS Viewer. authoring in the delay area. This is also limited in the DEC dataset where the criteria are applied and the focus of the literature is effect and cause. Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset. With the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords are shown. Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset. With Figure 3. Co-occurrence analytical map of keywords created on the ﬁrst bibliographic dataset. With the the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords keywords are shown. are shown. Buildings 2019, 8, x FOR PEER REVIEW 7 of 36 Figure 3 shows the co-occurrence analytical map of keywords based on the first bibliographic Buildings 2019, 9, 191 7 of 37 dataset. For this visualisation a minimum number of 2 was selected for co-occurrence visualisation and a total of 713 keywords out of the sample of 2926 keywords are shown in Figure 3. The norma Figur lis ea4 tio also n mshows ethod o the f Lco-occurr inLog waence s used analytical in VOS Vie map wer. of keywor ds based on the ﬁrst bibliographic Figure 4 also shows the co-occurrence analytical map of keywords based on the first dataset, but the minimum number of co-occurrence was selected as ﬁve to identify the most frequent bibliographic dataset, but the minimum number of co-occurrence was selected as five to identify the concepts. Of the sample of 2926 keywords, 176 keywords are shown in Figure 4. most frequent concepts. Of the sample of 2926 keywords, 176 keywords are shown in Figure 4. Figure 4. Co-occurrence analytical map of keywords created in the ﬁrst dataset. With the minimum Figure 4. Co-occurrence analytical map of keywords created in the first dataset. With the minimum number of co-occurrence set as ﬁve, a total of 176 keywords out of the sample of 2926 keywords are number of co-occurrence set as five, a total of 176 keywords out of the sample of 2926 keywords are shown. (a) All keywords co-occurrence network map; (b) scheduling co-occurrence network map; (c) shown. (a) All keywords co-occurrence network map; (b) scheduling co-occurrence network map; (c) risk assessment co-occurrence network map. risk assessment co-occurrence network map. Figure 4 shows that risk management has become more important in recent years. This also shows Figure 4 shows that risk management has become more important in recent years. This also that the recent publications may tend to oer suggestions to monitor and prevent delay. In addition, shows that the recent publications may tend to offer suggestions to monitor and prevent delay. In it shows that using questionnaire surveys is the traditional method of delay analysis. Figure 5 also addition, it shows that using questionnaire surveys is the traditional method of delay analysis. Figure shows the key concepts used in the DEC database (with questionnaire surveys being a dominant method from 2014) and that risk management has become a focus in literature more recently. Buildings 2019, 8, x FOR PEER REVIEW 8 of 36 5 also shows the key concepts used in the DEC database (with questionnaire surveys being a Buildings 2019, 9, 191 8 of 37 dominant method from 2014) and that risk management has become a focus in literature more recently. Figure 5. Co-occurrence analytical map of keywords created on the ﬁrst dataset. With the minimum Figure 5. Co-occurrence analytical map of keywords created on the first dataset. With the minimum number of co-occurrence set as ﬁve, a total of 25 keywords out of the sample of 550 keywords are shown. number of co-occurrence set as five, a total of 25 keywords out of the sample of 550 keywords are 4. Content Analysis and Data Mining shown. This section critically reviews the content of the DEC dataset by investigating topics, keywords, 4. Content Analysis and Data Mining and themes. First, the entire DEC dataset was grouped into ﬁve main clusters with each cluster against This section critically reviews the content of the DEC dataset by investigating topics, keywords, three criteria (the gap identiﬁcation criteria). Figure 6 shows that there were three clusters within an the d th DEC emes. dataset First, based the enti on re the DEC wor d dasimilarity taset was of gro the upe articles, d into f which ive ma wer in clu e separately sters withanalysed each cluusing ster against three criteria (the gap identification criteria). Figure 6 shows that there were three clusters thematic analysis techniques. Based on the results and the similarity of the words, the papers were wi assigned thin the DEC into ﬁve data clusters. set based The onDEC the wo dataset rd sim could ilarity also of th bee classiﬁed articles, wh based ich were on these sepa ﬁndings. rately an A aly car sed eful using thematic analysis techniques. Based on the results and the similarity of the words, the papers content analysis showed that there were at least three dierent types of ﬁndings within the DEC were dataset: assig(i) ned the inﬁrst to five group clusof terpapers s. The DEC investigating dataset ccauses ould als of o delay be class [70 ifie ], e d ba ects sed of odelay n these [71 fin ], d mitigation ings. A careful content analysis showed that there were at least three different types of findings within the strategies, and/or all causes and eects with appropriate mitigation strategies [72,73]; (ii) the second DEC group data investigating set: (i) the first the e gro ect up of ofone pape special rs inve factor stigat on ing delay causes [74o ];f (iii) dela the y [thir 70],d ef gr fec oup ts o pr f oposing delay [71 and ], mitigation strategies, and/or all causes and effects with appropriate mitigation strategies [72,73]; (ii) evaluating methods and/or models for identifying, ranking, and estimating delays [75]. the second group investigating the effect of one special factor on delay [74]; (iii) the third group proposing and evaluating methods and/or models for identifying, ranking, and estimating delays [75]. Buildings 2019, 9, 191 9 of 37 Buildings 2019, 8, x FOR PEER REVIEW 9 of 36 Cluster 1 Cluster 2 Cluster 3 Figure 6. Five branches of papers in the DEC, including three clusters of the main relevant articles for Figure 6. Five branches of papers in the DEC, including three clusters of the main relevant articles for the content analysis. the content analysis. 5. Current Practices in Delay and Time Overrun Investigations Buildings 2019, 9, 191 10 of 37 5. Current Practices in Delay and Time Overrun Investigations Buildings 2019, 8, x FOR PEER REVIEW 10 of 36 We ﬁrst investigated the publications in the past three years to identify the current practices in We first investigated the publications in the past three years to identify the current practices in this ﬁeld. Tables 3–5 show that most of them used questionnaires and focused on developing countries, this field. Tables 3, 4, and 5 show that most of them used questionnaires and focused on developing and Figure 7 shows word clouds created for dierent sources based on stemmed words. countries, and Figure 7 shows word clouds created for different sources based on stemmed words. (a) (b) (c) (d) (e) (f) Figure 7. Word cloud created for dierent sources based on stemmed words. (a) All DEC dataset; Figure 7. Word cloud created for different sources based on stemmed words. (a) All DEC dataset; (b) (b) cluster 1; (c) cluster 2; (d) cluster 3; (e) published papers from 2009 to 2011; (f) published papers cluster 1; (c) cluster 2; (d) cluster 3; (e) published papers from 2009 to 2011; (f) published papers from from 2016 to 2018. 2016 to 2018. Table 3. Summary of selected articles of cluster 1 of delay investigations from 2015 to 2018. Table 3. Summary of selected articles of cluster 1 of delay investigations from 2015 to 2018. Focus of the Study, Method; Sample Size Number of Examined Delay Factors and Method; sample Location, and Sector and Participants List of the Selected Factors Identiﬁed Focus of the study, Number of examined delay factors and list of the size and Questionnaire; 30; 24, inexperienced workforce, shortage of location, and sector selected factors identified Prioritize delay factors [76], participants academics, clients, structural connections for prefabricated China, prefabricated Prioritize delay factors Questionnacontractors, ire; 30; and 24, inexpecomponents, rienced workf poor orce, communication shortage of str among uctural concrete building government. participants, and low productivity. [76], China, academics, clients, connections for prefabricated components, poor prefabricated concrete contractors, and communica 78, tio client-r n amo elated ng pacauses, rticipan labour ts, and and low Comparative delay analysis Questionnaire; 175; equipment causes, contractor-related building government. productivity. techniques with the Society clients, consultants, and causes, material-related causes, Comparative delay of Construction Law’s (SCL) 78, client-related causes, labour and equipment causes, contractors design-related causes, external causes, and analysis tec pr hotocol niques [72 wi ],th Iran Questionnaire; 175; consultant-related causes. contractor-related causes, material-related causes, the Society of clients, consultants, design-related causes, external causes, and consultant- Construction Law’s and contractors related causes. (SCL) protocol [72], Iran Fuzzy assessment model 83, inexperienced contractor, poor project planning and Interviews to estimate the scheduling, weak supervision and site management, questionnaire; 64; probability of delay [77], changes in design, unreliable subcontractors, consultants, Turkey, public and inexperienced labour, changes in orders, slowness in site contractors private delivery, late design documents approval, delay in Buildings 2019, 9, 191 11 of 37 Table 3. Cont. Focus of the Study, Method; Sample Size Number of Examined Delay Factors and Location, and Sector and Participants List of the Selected Factors Identiﬁed 83, inexperienced contractor, poor project planning and scheduling, weak supervision and site management, changes in design, Fuzzy assessment model to Interviews questionnaire; unreliable subcontractors, inexperienced estimate the probability of 64; consultants, labour, changes in orders, slowness in site delay [77], Turkey, public contractors employees, delivery, late design documents approval, and private and designers delay in payment, material delivery, weak communication and coordination between parties, and unqualiﬁed team. Payment, project ﬁnancing, cash ﬂow, Finance and delays [78], Questionnaire; 78 economic issues, project planning, and cost Ghana, highway project control. Delayed approval, design and scope changes, Structural equation model poor protocol and subcontractor changes, Questionnaire; 77; clients, for investigating factors technical ability of head contractor, contractors and aecting delay [79], India, scheduling, labour productivity, weather designers or architects public conditions, proper planning and controlling of projects. 73, problems in funding (75%); poor site management (66%); weak project planning Time overrun model by Questionnaire; 90, (58%). Owner: values of contract (70%); late using fuzzy logic [80], Iraq, owners, consultants, decision-making (63%); contract duration private and government supervising engineers (61%). Consultant: design delays and design sectors and contractors mistakes (46%); improper design management (45%). External: topographic characteristics of site (41%). 72, inadequate fuel, inadequate contractor Questionnaire; 45; clients, cash-ﬂow, inadequate foreign currency, Causes of delay [81], Malawi, contractors and payment, inadequate equipment, inadequate road consultants materials, inadequate technical workforce, and site mobilization slowness. 35, ﬁnancial diculties, subcontractor ’s weak Prioritize delay factors [30], performance, material provision, drawing Questionnaire; 175; Benin, public projects: changes, scheduling by contractor, late contractor, owner, departmental hospital, inspections by the consultant, unavailability consultant and architect school, administration oce of equipment by contractor, and acceptance of improper design drawings. 89, ﬁnancial issues are the major delay factors, Causes of delay [36], Questionnaire; 35; as well as drilling allowance, long Khuzestan, Iran, steel owners, consultants and administrative cycle to renew, and steady company contractors production of steel. 50, ﬁnancial issues, policies and weakness of laws, competence of project management, Risk analysis of schedule Questionnaire; 246; ﬁnancial ability and management of delays using a structural project managers, contractor, competence of design team, equation model [82], supervisors, from sub-contractor ’s selection and management, Vietnam, highway projects contractors and owners economical changes, and competence of supervision team. Buildings 2019, 9, 191 12 of 37 Table 3. Cont. Focus of the Study, Method; Sample Size Number of Examined Delay Factors and Location, and Sector and Participants List of the Selected Factors Identiﬁed Uncertainties and changes, regulation Delay causes for BOT Workshop; 11; variation, budget shortage, changes in orders, Projects [70], Turkey, consultants, the private changes in urban plan, changes in policy and public–private partnership sector, and the public regulations, lack of bidder, inadequate laws projects (PPP) sector about usage of land, ﬁnance. A method for risk managers to address Climate and construction climatic agents and required extra time to Case study; 6; bridges delays [83], Chile, bridge minimize adverse weather conditions and time delays. 180, unreal duration imposed by clients, Questionnaire; 208; unﬁnished design, change orders, scheduling, Proﬁling causative factors clients, consultant and weak project control, slow permission process leading to delays [84], UAE contractors from authorities, low labour productivity, delays in decisions, poor site management. 36, ﬁnance shortage, weak planning, weak Questionnaire; 400; Analysis of delays using site management, unavailability of material, clients, contractors and transaction cost economics unpredicted site condition, delays in test consultants using (TCE) approach [85], approvals, preparation of drawings, Structural Equation Tanzania communication between parties, skills Modelling shortage, availability of equipment. Table 4. Summary of selected articles of cluster 2 of delay investigations from 2015 to 2018. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants 37, delayed payments, low bids, weak Delay analysis [86], China, performance of subcontractors, and Questionnaire; 115; Beijing, Shanghai, communication issues. Comparative analysis clients, consultants, and Chongqing and Shenzhen, shows diculty in claiming penalty and contractors Design-bid-build projects unreasonable upfront capital demanded by client. Lack of experienced managers, lowest bidder, Delays [87], Bangladesh, Interviews; 70; shortage of fund, scheduling, lack of skilled privately funded large stakeholders labour, site constraints, weak cost control, and building contractor cash ﬂow problem. Building material, rerouting electrical and Interviews; 14; project Delay Factors [88], Mataf, mechanical utilities, safe access, conditions of and construction Mecca, Saudi Arabia, site, taking down archaeological and managers and senior site reconstruction project antiquity elements, back-propping works, engineers design changes, conﬂict between workforce. 26, improper funding cost, mistakes or Schedule delay [89], Questionnaire; architects, negligence in consultant material quality, and Denmark, public surveyors mistakes. 66, using qualiﬁed and experienced managers, Questionnaire; 100; A framework to reduce using suitable and enough tools and people engaged in delays [73], Sudan, road equipment, and suitable technical planning construction before starting the projects. Identiﬁed eects are time overrun, cost The eect of delays [71], Questionnaire; 256; overrun, and blockage of economic and Libya, Tripoli, road stakeholders country development. Buildings 2019, 9, 191 13 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Weak scheduling, poor decision process, The top 10 universal delay Questionnaire; 202; internal administrative procedures and factors [90], Norway, clients, contractors and bureaucracy, poor resources, weak parties’ hospitals, schools, hotels, etc. consultants communication, slow inspection, changes, parties’ lack of commitment and goals. 59, delays in utility services (such as power A model of delay factors [91], Questionnaire; 256; lines, water, etc.), project budget diculties, Libya, road stakeholders short duration, delayed payments, and subsurface condition impacts conditions. Project ﬁnancial diculties, improper planning and scheduling, contractor ’s poor A dynamic model of Questionnaire; 100; communication and coordination, conﬂict contractor-induced delays Project managers, between parties and use of improper methods [92], India, buildings, roads, architects, engineers, for construction, providing enough project bridges, railways, power designers, consultants, ﬁnances and cash ﬂow, proper planning and plants, and industrial surveyors, contractors, scheduling, using proper methods for complex projects and owners construction, and considering the reworks in the schedule. 58, reworks, suspension of construction, A hybrid System Dynamics- delayed payment, poor project planning and Decision Making Trial and Questionnaire; 63; scheduling, labour ’s low productivity, Evaluation Laboratory consultants, contractors, changes in orders, and construction mistakes, (SD-DEMATEL) approach to and clients costs of implementation, acceleration in develop a delay model [93], conduction of biding, and notiﬁcation of Iran contract and schedule pressure. 31, identiﬁed factors are manpower (21% of Time overrun risks [94], Questionnaire; 112; contribution), materials (18% of contribution), India, residential, industrial, project managers and scheduling and control related problems and commercial (18% of contribution). Poor communication, late payment, weak Aggregation of factors controlling, delays in decisions, changes in causing cost overruns and order, reworks, weak labour and material Analysis of a literature time delays: trends and planning, equipment shortage, project selection implications [95], large complexity, psychological positive interest, public projects fraud, bad weather conditions, and ground conditions. 9, ﬁnancial limitation by government, weak Beyond the causes: supervision and project planning, change rethinking mitigating Check list; 7; quantity orders, insucient allowance of contingency, measures to avert cost and surveyors, architects, and weak administration of contract, qualiﬁes time overruns [96], Ghana, engineers team of project, poor coordination, risk public related to cultural and political issues. 31, materials shortage, unreal scheduling, late material delivery, labour shortage, project Causes of delay [97], Questionnaire complexity, delayed payment, weak site Cambodia, residential management, delay by subcontractor, and accidents because of weak site safety. 6, Indian: market culture, large delay due to Organisational culture in Questionnaire; 84; contractors. US: clan culture, less delay due to delay [74], US and India contractors owners. Buildings 2019, 9, 191 14 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Delayed payment, inexperienced contractor, Questionnaires; 123; Exploring critical delay scope changes, delayed furnish and site stakeholders and site factors [29], Ghana, road delivery to the contractor, and inﬂexible sta funding. 75, low bid, main contractor ’s ﬁnancial condition, delays in making decisions by The causes, impacts and Questionnaire; 53; clients, client, and weak planning by the main mitigations of delay [98], consultants, and contractor. Eects are extra cost and time Oman, Sultanate, contractors overrun. Mitigation: experienced contractors megaprojects and consultant, proper planning, and suitable supervision. 32, insucient planning, poor information ﬂow and communication, poor decisions, The professionals’ ineective management, poor control, Interviews; 41; seniors of perspectives on the causes of ﬁnancial problems, unclear scopes, design developers, consultants, project delay [99], UK, all problems, inappropriate risks transfer, lack of clients, and contractors sectors knowledge and competence, health and safety restrictions, poor resources and logistics management Delayed payment to contractor or supplier, inﬂation and price ﬂuctuation, price growth Questionnaire; 31; Analyzing delay causes and in materials, insucient funds of sponsors or architects, surveyors, eects [100], Ghana, state clients, changes in orders, and weak ﬁnancial engineers, managers, housing or capital market. Identiﬁed eects are cost land economists overrun, time overrun, litigation, discontinuity by client, and arbitration. 44, weak supervision, contractor ’s insucient Causes of delay [27], Gulf Questionnaire; 59; clients, planning and scheduling, delay in delivery of cooperation council contractors, and materials, poor communication among countries (Oman), oil and consultants project parties, and weak interaction with gas industry vendors. Suggested to validate ﬁndings. 65, safety measures, laws and bureaucracy variations by government, holidays, lowest Questionnaire; 134; bidder weak performance, changes in design Causes of delay [101], Iraq, clients, contractors, and by owner and consultants, delayed payments public consultants by the owner, problems with local community, inexperienced owner in construction and economic and local and global conditions. 35, lower bid, changes in material, Risk matrix for delay Causes Questionnaire; 51; management of contract, contract duration, [102], Saudi Arabia consultants ﬂuctuations in materials’ price, changes in design, weak planning, pressure of inﬂation. 64, working during rainy season, ﬂooding, Analyzing delays: causes Questionnaire; 153; eect on people’s land, lowest bidder and eects [103], Cambodia, contractor and consultant selection, repeated breakdowns of equipment, road weak site arrangement. Buildings 2019, 9, 191 15 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Extreme weather, site blockage, corruption, war, labour ’s low productivity, custom Causes of delays [104], clearance issues, changing in route of supply countries with high Window delay analysis chains, materials stealing; natural dangers, geopolitical risks, power method (detailed review late approvals, change orders, design transmission lines, of 36 projects), interviews mistakes, obscure work scope, cash ﬂow, infrastructure (utilities) and with 18 experts rental equipment inadequacy, delays in site roadway ownership, inadequate owner ’s site utilities, changing in supply chains. 35, ﬁnancial diculties, absence of Delay factor analysis [105], Questionnaire; 197 responsibilities, changes in design, and Vietnam, hospital inexperienced contractor. 27, contractor ’s ﬁnancial ability, owner ’s Empirical study of factors Questionnaire; 140; ﬁnancial diculties, availability of equipment inﬂuencing schedule delays clients, contractors, and by contractor, delayed payment for ﬁnished [106], Burkina Faso, public consultants work, and weak performance of subcontractor. 293, political situations, segmentation of the Questionnaire; 186; west bank and limited movements between Exploring delay causes [107], consultants, contractors, areas, award project to lowest bid price, Egypt, road and engineers progress payment delay by owner, and shortage of equipment. 45, manpower shortage, late approvals, Factors aecting delays [108], Questionnaire; 120; materials shortage, and relation between Jordan, private stakeholders dierent subcontractors. Weak communication, slowness of material Delay factors [109], Malaysia, Interviews; 10; contractor delivery, wrong selection of contractor, low Perak, Vale minerals project and client sta productivity, weak management, and equipment mobilization. Delay and cost overrun [110], Regulation (31%), owners (27%), consultant Questionnaire; 86 Iran (25%), and contractor (17%). Risk and relationship Environmental issues, resource issues, and Questionnaire; 212; between delay factors [111], coordination issues. Suggests longitudinal stakeholders Malaysia study and speciﬁc infrastructure projects. 112, ﬁnance issues, non-payment for Causes of delays [112], Saudi Questionnaire; 86; contractor claims, inexperienced contractor, Arabia, public stakeholders weak scheduling, delay in decisions and approvals, lack of material and labours. Finance diculties, economic and payments Cost escalation and schedule Questionnaire; 60; problems, materials preparation, contract and delays [113], Zambia, road stakeholders drawing changes, inadequate stang and equipment, weak supervision. 110, strikes and closures of border, shortages Delays and cost overruns Questionnaire; 114; of materials in markets and in delivery to the [114], Gaza Strip stakeholders site. Financial-related causes Questionnaire and Cash ﬂow, inadequate ﬁnancial resources, contributing to project delays interviews; 110; loan gaining diculties, and inﬂation. [115], Malaysia stakeholders 52, political situation, lowest bidder, payment Questionnaire; 64; Causes of delay [116], and inadequate equipment; improper ground contractors and Palestine, road condition, inadequate controllers, unsuitable consultants design, natural hazards. Buildings 2019, 9, 191 16 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants 34, changes in design and material, delayed Questionnaire; 71; project Causes of delays [117], payments, problems in cash ﬂow, contractor ’s managers and site Turkey problems in ﬁnance, and low labour managers productivity. Questionnaire; 17; 34, risks associated with reduced site Leadership in Energy disturbance, innovative waste water Cost and time overrun and Environmental technologies, renewable energy, waste analysis [118], India, green Design (LEED) management, indoor chemical and pollutant construction projects professionals and other source control, and LEED— accredited green experts professional. Schedule delay causes [119], Case study; 79 litigation Change in orders and scopes, late handover Taiwan cases of site, and weather. Time performance [120], Planning, subcontract, materials, labour, Residential case study; 2 Santiago, Chile design, execution, and weather. Suggests connecting the function of Delays, penalties, and project Phone interviews; 30; marketing with project management, but it quality [121], Slovenia managers, questionnaire reports that marketing management does not minimize ﬁnes and delays. Causes of delays and cost Interview, case study; Variations in work scope, delays in payments, overruns [122], Uganda, questionnaire; 247; weak control and monitoring, capital’s high public stakeholders cost, political ﬂuctuation, and insecurity. 43, material, cost, and currency variations, Analyzing delay causes Questionnaire; 33; ﬁnancial, site condition, inexperienced [123], Egypt stakeholders consultants, ﬁnancing, low productivity, incompetent workforce, and change orders. Design [124], Taiwan, Questionnaire; 36; 21, decision making and budget constraints, high-tech facility engineers managers design duration. 28, ﬁnancial issues, inappropriate planning, Questionnaire; 84; Causes of delays [35], Iran site and contract management, and poor stakeholders communication Table 5. Summary of selected articles of cluster 3 of delay investigations from 2015 to 2018. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants This article proposes a method that is a tool for Productivity and delay A new method and a calculating the schedule impacts that happen analysis [125] case study when there is a problem in lost productivity. Analysis eects of delays on the critical path that Critical path eect based Hypothetical case performs delay analysis accurately and uses a delay analysis method [126] studies process-based analysis approach to solve simultaneous delays. Improper design and owner ’s neglect, changes in Arbitration awards, Factors inﬂuencing delay orders, weather and site conditions, delayed court cases, and claims [127], India delivery, economic conditions, and quantity professionals growth. Understanding construction In-depth interview; Complexity, cost, and time. Emphasizes the delay analysis and the role of experienced importance of baseline programs for resolving preconstruction construction planning delay claims. programming [128], UK engineers Buildings 2019, 9, 191 17 of 37 Table 5. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Client’s attitude, experience of the delay analyst, reputation and neutrality of the delay analyst, Factors inﬂuencing the project complexity, and cost and timing of selection of delay analysis Interviews; 8; experts; performing the analysis. Time Impact analysis method [129], UAE, a hotel, limited to case studies (TIA) and Impacted as Planned (IAP) are two an international school in the period of commonly used Delay Analyzing Methods complex, a highway, sewage 2007–2012 DAMs. The ethnographical approach is treatment plant, and a suggested, since it provides the opportunity to residential tower capture real and live states of knowledge on the selection and the use of DAMs. Visualisation of delay claim This article shows that 4D simulation is a reliable analysis using 4D simulation method for analyzing delay claim. [130] This article proposes the Stochastic Delay Analysis and Forecast (SDAF) method, which is Stochastic delay analysis and Shi’s method an informative analytical method and predicts forecast method [131] the eect of a single activity’s delay with probability for overall project delay. Semi structured Decision-making model for This article proposes the Digital Multimeter interviews and selecting the optimum (DMM) objective tool, which can reduce the questionnaire; 74; method of delay analysis potential for disputes and conﬂicts arising from contactors and [75], UAE, Dubai delays in construction projects. consultants Key Factors Identiﬁed in the Delay Literature Tables 5–7 show a comprehensive list of factors and the priority of each factor in Asian and African countries. This helps us to understand the importance of current factors in the literature. These two tables are also used for identifying the frequency and the median of each factor. Most of the articles extracted a number of delay factors from the literature. Next, they evaluated each factor or validated them in their context by conducting a survey, and they ﬁnally presented the top ranked factors. For example, Al-kharashi and Skitmore [112] identiﬁed 112 delay factors from literature. Then, they conducted a survey and presented the 30 important factors from the results. Al-kharashi and Skitmore [112] reported only ten factors out of 30 and reported them in the abstract of their paper. Thus, this paper reported the top ten factors reported by them. Among the DEC dataset, only 63 articles included the causes/main cause of delay. A total of 55 articles were investigated in a certain region or country, which are presented in Tables 5–7. Buildings 2019, 9, 191 18 of 37 Table 6. Priority list of delay factors within DEC literature for Asian countries, mainly Middle Eastern. India Bangladesh Saudi Arabia Iraq Turkey Iran UAE Oman Jordan Palestine Factors 18 20 26 66 76 6 7 41 54 13 38 15 40 63 19 51 44 30 37 32 49 56 62 [92] [94] [74] [79] [127] [87] [88] [102] [112] [80] [101] [70] [77] [117] [93] [110] [36] [84] [27] [98] [108] [114] [116] Scheduling issues + 3 2 5 + + 7 2 4 1 4&5 3 4 4 Payment delay + + 6 6 2 3 4 Design changes 1 1 1 + 5 + 4 1 8 Manpower issues 1 6 + + 7 10 8 1 Financing diculties + 4 + 3 3 1 Poor supervision 1&4 + 3 3 12 9 1 Lack of materials 2 5 5 5 3 2 Contractor cash ﬂow 10 + 1 4 5 3 2 Poor communication + + 6 Owner cash ﬂow 3 + Subcontractors 6 6 2 2 4 Change orders 4 + 9 6 3 Equipment issues 5 14 5 Natural risks 5 2 8 Labour productivity 2 + 5 5 6 Culture and politics + 1 1&2 Approval delays 1 4 + 7 4 6 2 Resources shortage 3 1 Economic conditions 9 Lowest bidder 2 + 1 3 Design problems 1 Delay in site delivery 1 + 10 Late change issues 2 2 Contract issues + 2 4 Security 2 1 Inﬂationary issues + 10 Lack of protocol 1 Inaccurate pricing + 4 + 6 Cost control 9 10 Estimation issues 7 5 1 Note: design problems are a general factor that contain items such as errors in drawings and improper/inadequate design documents. Buildings 2019, 9, 191 19 of 37 Table 7. Priority list of delay factors within DEC literature for selected Asian countries. Cambodia Malaysia Taiwan Palestine China Vietnam Factors 24 42 50 52 57 59 67 56 62 3 5 29 31 46 [97] [103] [109] [111] [115] [132] [119] [114] [116] [76] [86] [133] [82] [105] Scheduling issues 2 1 Payment delay 7 10 2 4 1 Design changes 2 2 5 Manpower issues 4 9 1 4 Financing diculties 3&6 + Poor supervision 8 7 5 3 8 Lack of materials 3&1 2 2 Contractor cash ﬂow 4 Poor communication 1 3 2 4 2 Owner cash ﬂow 5 1 Subcontractors 9 3 3 Change orders 1&4 1 Equipment issues 5 1 Natural risks 2 1 4 Labour productivity 11 4 3 Culture and politics 1 1&2 Approval delays Resources shortage 6 2 Economic conditions 7 Lowest bidder 4 3 2 Design problems Delay in site delivery 3 Late change issues Contract issues Security 10 Inﬂationary issues 7 Lack of protocol 2 Inaccurate pricing Cost control Estimation issues Based on the information collected from Tables 6–8, the frequency and the median of each factor were calculated. Table 9 shows that the most frequent factors contributing to project delay are scheduling issues, payment delay, design changes, manpower issues, and ﬁnancing diculties. Uganda; 72 [122] Benin; 70 [30] Malawi; 69 [81] Denmark; 8 [89] Zambia; 55 [113] Burkina Faso; 47 [106] 73 [123] Egypt 48 [107] Chile [120] UK; 33 [99] 61 [134] US 26 [74] 28 [78] 36 [100] Ghana 27 [29] 23 [96] Tanzania; 22 [85] Norway; 12 [90] Libya; 17 [91] Sudan: 1 [73] Buildings 2019, 9, 191 20 of 37 Table 8. Priority list of delay factors within DEC literature for African and other countries. Factors Scheduling issues + 2 2 + 1 1 6 Payment delay 4 1 1 + 4 3 4 1 4 2 Design changes + 3 5 10 9 5 1 Manpower issues 3,5 9 6 4 9 7 9 Financing 1 2 1,4 5 5 + 6 1 4 diculties Poor supervision 2 3 2 4 9 Material issues 4 3 1 5 7 4 Change orders + 3 8 5 2 9 Contractor ’s 9 + 7 1 2 2 1 ﬁnancial problems Poor 4 + 8 7 2 11 communication Owner ’s ﬁnancial 1 4 + 3 2 2 2 problem Subcontractors 2 5 3 Equipment issues 10 5 3 8 5 8 Approval delays + 6 7 Natural risks 5 + 6 Labour productivity 8 Culture and politics 8 + 5 Resources shortage + 5 Economic conditions + 2 2 4 3 Lowest bidder 3 Delay in site delivery Drawing issues + 7 6 Contract issues 5 3 Security Inﬂationary issues 2 Lack of protocol + 10 Inaccurate pricing Controlling 5 3 Estimation issues 3 Buildings 2019, 9, 191 21 of 37 Table 9. Summary of important factors including frequency and median. Source Issue (Cause) Description Reference Frequency * Median (Article) Improper resource planning, inaccurate Scheduling budgeting, procurement, unreal 81 1769 25 2 scheduling Payment delay Delays in payment to labours/contractor 58 764 21 3.5 Design and scope changes/lack of clarity Design 77 1697 20 3.5 (by owner, contractor, or architect) Using unqualiﬁed personnel, lack of skilled workers/designers, poor Manpower issues 70 990 20 6 qualiﬁcation of the technical sta, stang problems Cash ﬂow problems, inﬂexible funding, Financing and cash insucient contingency allowance, 60 466 19 3.5 ﬂow loan gaining problems, ﬁnancial disputes, capital high costs, penalties Lack of experienced construction Supervision 53 281 18 4 managers, poor supervisor Material change, late delivery, Material 76 1358 16 3 unavailability and lack of materials Change order Design problems (by owner or others) 18 54 16 3 Contractor ’s Cash ﬂow/funding problems 15 4 ﬁnancial problems Communication Poor coordination, poor team working 59 357 15 2 Owner ’s ﬁnancial Cash ﬂow/funding problems 12 3 problems Unreliability, delays, being Subcontractor 56 361 11 4 inexperienced Using inappropriate and inadequate Equipment 69 888 11 5 tools and equipment, : : : Approval delays in submission and Approval inspection process of design, materials, 67 366 11 5 completed work Natural dangers (environmental related issues, extreme weather conditions, Natural risks 33 77 10 5 ﬂooding, precipitation, temperature, soil temperature, and wind velocity) Labour - 41 124 10 2 productivity Organisational culture, war, strikes and Culture and closures of border, political ﬂuctuations, 55 510 8 6 politics restricted movement between areas Resources shortage, inadequacy/delays Resources in human resources, material and 75 617 7 3 equipment thefts Local or global economic, cost and “Economic” currency variations, inadequate foreign 75 634 7 3.5 conditions currency to import materials and equipment Lowest bid Select lower bidder 15 30 7 2.5 Delay in site Late delivery/ handover of site 3 8 5 3.5 delivery Late/unﬁnished/changes issues of Drawing 58 292 5 4 drawing Weak contract management, wrong Contract duration of contract period, contract 31 71 5 3.5 management changes, contract values, old standards Buildings 2019, 9, 191 22 of 37 Table 9. Cont. Source Issue (Cause) Description Reference Frequency * Median (Article) Weak site safety, health restriction, Security 25 85 4 2 alternative safe access Inﬂation pressure, lack of attention to Inﬂationary 2 7 4 7 inﬂation Lack of severe organisational Protocol 14 54 4 2 protocol/policy directives/ strategies Wrong pricing and bidding, low Pricing 59 423 4 5 performance of bidder, lack of bidder Improper monitoring and Controlling 71 471 4 7 controlling/cost control Estimation Inaccurate time and cost estimation 71 442 4 4 Diculties in obtaining work permits Permits 38 161 4 4 (drilling permits or tests) Note: * frequency refers to the number of occurrences that the issue presented by researchers as an important cause of delay in the DEC dataset; the order of issues is based on the frequency values. Source refers to the number of papers mentioned in the selected issue; reference refers to the frequency of the selected issue within the DEC dataset; median refers to the value separating the higher half of the important factors presented as important in the DEC datasets by researchers. Unique factors (with the frequency of three or less) are: “‘Slow decision making process by owner” in Norway [90], UAE [84], and Oman [98]; “Changes in material types and speciﬁcations during construction” in Saudi Arabia [102], Turkey [117], and Zambia [113]; “Change/selection of subcontractors in the project” in India [79], Saudi Arabia [112], and Vietnam [105]; “Mobilization delay” in India [127], Malaysia [109], and Malawi [81]; “Site constraints (site blockage, impact of other ’s land)” in Bangladesh [87], Cambodia [103], and countries with high geopolitical risks [104]; “Impact of subsurface (underground) conditions” in Libya [91], Cambodia [103], and Egypt [123]; “Conﬂict between parties’ in Iran [101], Turkey [70], and Egypt [107]; ”Errors in construction” in Iran [93], Zambia [113], and Denmark [89]; “Fluctuation in price of materials” in Saudi Arabia [102] and Ghana [100]; ”Conﬂict between labours” in Saudi Arabia [88] and Zambia [113]; ”Labour strikes” in countries with high geopolitical risks [104] and Zambia [113]; ”Using inappropriate construction methods” in India [92] and Iran [110]; ”Insucient/inaccurate document preparation” in Turkey [70] and Iran [110]; “Inaccurate ﬁrst drafts/plan” in Iran [110] and Taiwan [132]; ”Delay/weak interaction due to vendor” in India [127] and Oman [27]; ”Unsuitable site location due to ignoring feasibility studies” in Iran [110] and Cambodia [103]; ”Rework (by labours, consultant’s workforce)” in Saudi Arabia [102] and Iran [93]; ”Suspension of work (by the owner)” in Saudi Arabia [112] and Iran [93]; “Slow decision making by owner” in Saudi Arabia [112] and Iran [93]; ”Owners’ experience” in Saudi Arabia [112] and Cambodia [103]; ”Consultant’s experience (competence)” in Libya [91] and countries with high geopolitical risks [104]; ”Contractor ’s experience” in Norway [90] and the UK [99]; “Project complexity” in Norway [90] and the UK [99]; ”Wrong evaluation and selection procedure (wrong selection of contractor)” in Turkey [70] and Malaysia [109]; ”Working during rainy season” in Cambodia [103]; ”Changing in route of supply chains” in countries with high geopolitical risks [104]; ”Weak management of contractor ’s schedule” in Oman [27]; ”Long time between design and construction” in Saudi Arabia [102]; ”Interference of the execution (by owner)” in Saudi Arabia [112]; ”Delays in ownership” in countries with high geopolitical risks [104]; ”Oce issues” in Norway [90]; ”User issues” in Norway [90]; ”Ocial and non-ocial holidays” in Iran [101]; ”Problems with local community” in Iran [101]; ”Unpredicted quantity growth” in Turkey [70]; ”Old cost lists’ items” in Iran [110]; ”slow steel production” in [36]; ”Poor information (lack of knowledge)” in the UK [99]; “Unsuitable commercial decisions” in the UK [99]; ”Unforeseen circumstances” in the UK [99]; ”Corruption” in countries with high geopolitical risks [104]; “Custom clearance issues” Buildings 2019, 9, 191 23 of 37 in [104]; ”Inadequate fuel” in Malawi [81]; and “Delayed compensation paid to land owners” in Malawi [81]. 6. Technology Applications for Time Control and Risk Management Scheduling issues were identiﬁed as one of the most frequent factors causing delay in projects (refer to Table 9). A good project schedule can serve as a key management tool for making decisions and predicting whether the project will ﬁnish on time and within budget. Regular updates to the project schedule are essential to record progress and identify potential problems. There are various project scheduling software systems, such as Microsoft Project, Oracle Primavera P6, Open Plan Professional (OPP), FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Smartsheet, and many other software, packages, and platforms. Each of these project schedule software options has dierent strengths, but they oer the best options for a variety of management needs. Project scheduling software has been developed to communicate what work needs to be performed, which resources of the organisation will perform the work, and the timeframes in which that work needs to be performed. The project scheduling software should reﬂect all the work associated with delivering the project on time. However, Microsoft Project, Oracle Primavera P6, and Open Plan by Deltek are the most practical, powerful, and common software in practice. Table 10 compares the strengths and the features of these three. Table 10. Project delay analysis feature comparison between Microsoft (MS) Project, Primavera P6, and Open Plan by Deltek. Delay Analysis MS Project Oracle Primavera P6 Open Plan by Deltek Feature **** *** We can update the We can update the schedule the project by ***** schedule project by updating individual task We can update project updating individual task progress. Open plan can Updating and progress by applying actual progress and then integrate with excel rescheduling for data to activities directly in a rescheduling all the Comma Separated delay analysis project or by using timesheet uncompleted tasks to Values (CSV) ﬁles to updates from the Progress start after the status date. import project status Reporter module Auto schedule is also data provided the correct available. table structure is created within Open Plan. ***** **** *** Ability to split, stretch, To handle scheduling Resource levelling is only and re-proﬁle activities conﬂicts that may occur available at a single for resource scheduling. during levelling, we can add Resource levelling project level, and MS Resources ﬁles are priorities that specify which and delay analysis Project is not able to shared across projects project or activity is levelled handle levelling when assigned at the activity ﬁrst. This module is only interdependency with level and are levelling available at Oracle another project exists. prioritise assigned at the Primavera software. activity level. Buildings 2019, 9, 191 24 of 37 Table 10. Cont. Delay Analysis MS Project Oracle Primavera P6 Open Plan by Deltek Feature **** The integrated risk management feature *** identiﬁes, categorizes, and Provides the ability to MS Project only prioritizes potential risks calculate three point considers deterministic associated with speciﬁc estimates at the activity tasks duration, and it Risk and delay work breakdown structure level, along with mean assumes the analysis (WBS) elements and and standard deviations relationships among resources. Able to create risk for early dates, late dates, tasks are deterministic, control plans and assign a and ﬂoat. Risks are then thus uncertainty analysis probability of occurrence able to be exported via is not available. and an organisational spreadsheet risk views. breakdown structure (OBS) element to risks. ***** *** Earned value can be deﬁned Earned value Earned value analysis is * at both WBS and activity management available in MS Project; Not available and needs levels. Able to compute (EVM) and delay however, Oracle to be integrated with performance percent analysis Primavera P6 can Deltek Cobra. complete and estimate to manage EVM. complete (ETC). ****: The advantage of each software across the selected features. In order to use scheduling software for project delay analysis, the following questions need to be asked before using scheduling software: What data need to be assembled as inputs to record the delay events for the update, and what methods will be used to collect the data? How often should projects be updated? Are resources local or osite? Which project teams are resources participating in? Who on each team will be gathering the information used for the project update, and with what frequency are the data updated within the schedule? Who needs to see the results of the update, and when do they need to see them? What types of information need to be generated after each update to communicate progress before the next update? The answers to these questions help determine how the project management oce, the project managers, and the project planning function uses the module to update projects. Careful details of events are developed in the project schedule to identify delays coupled with an accurate assessment of the source of the delay, thus the responsibility can be assigned. Activity late ﬁnish date is one the main components of each scheduling software to calculate schedule delays. Activity late ﬁnish date is the latest possible point in time in which the schedule activity can be completed without violating schedule constraint or delaying the project end date (PMBOK). The late ﬁnish date is the point at which the schedule activity contains no ﬂoat. Progress curves are used as a basis for comparing the schedule baseline. When the project schedule, the work breakdown structure (WBS), or both are modiﬁed through integrated change control, the progress curves are revised to indicate the new progress curve information. Figure 8 shows the ﬂoat analysis for identifying schedule delays as a basis of S-curve updates in project scheduling software. Buildings 2019, 8, x FOR PEER REVIEW 23 of 36 A good project schedule can serve as a key management tool for making decisions and predicting whether the project will finish on time and within budget. Regular updates to the project schedule are essential to record progress and identify potential problems. There are various project scheduling software systems, such as Microsoft Project, Oracle Primavera P6, Open Plan Professional (OPP), FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Smartsheet, and many other software, packages, and platforms. Each of these project schedule software options has different strengths, but they offer the best options for a variety of management needs. Project scheduling software has been developed to communicate what work needs to be performed, which resources of the organisation will perform the work, and the timeframes in which that work needs to be performed. The project scheduling software should reflect all the work associated with delivering the project on time. However, Microsoft Project, Oracle Primavera P6, and Open Plan by Deltek are the most practical, powerful, and common software in practice. Table 10 compares the strengths and the features of these three. In order to use scheduling software for project delay analysis, the following questions need to be asked before using scheduling software: • What data need to be assembled as inputs to record the delay events for the update, and what methods will be used to collect the data? • How often should projects be updated? • Are resources local or offsite? • Which project teams are resources participating in? • Who on each team will be gathering the information used for the project update, and with what frequency are the data updated within the schedule? • Who needs to see the results of the update, and when do they need to see them? • What types of information need to be generated after each update to communicate progress before the next update? The answers to these questions help determine how the project management office, the project managers, and the project planning function uses the module to update projects. Careful details of events are developed in the project schedule to identify delays coupled with an accurate assessment of the source of the delay, thus the responsibility can be assigned. Activity late finish date is one the main components of each scheduling software to calculate schedule delays. Activity late finish date is the latest possible point in time in which the schedule activity can be completed without violating schedule constraint or delaying the project end date (PMBOK). The late finish date is the point at which the schedule activity contains no float. Progress curves are used as a basis for comparing the schedule baseline. When the project schedule, the work breakdown structure (WBS), or both are modified through integrated change control, the progress curves are revised to indicate the new progress curve information. Figure 8 shows the float analysis for identifying schedule delays as a basis of S-curve updates in project Buildings 2019, 9, 191 25 of 37 scheduling software. Figure 8. Float analysis and progress curves basis for schedule delays [adopted from Management Body of Knowledge (PMBOK)]. Progress updates are used to calculate delays by using scheduling software. The network schedules are updated on a regular basis, and the agreed timings for updates are generally agreed upon within the special conditions of contract. For example, monthly updates based on the latest schedule baseline are common. Generally, the construction management team updates the schedule with a marking up of the changes from the previous month and provides these details for the project planning function to enter into the scheduling software (e.g., MS Project or Oracle Primavera P6). It is sent to the contractor ’s project controls team for review until the cut-o date. The project control manager checks and reviews the updated schedule with the project manager. Upon completion of the input work, time calculation and analysis are done within the review process as follows: Total ﬂoat consuming status compared with the previous month schedule. Critical path schedule analysis. Based on the above analysis, if problem areas are found, these are identiﬁed and reported to the project manager. The project control manager implements suggested countermeasures in conjunction with the related managers and under the project managers’ instruction. Once the project manager approves the counter measures, they are incorporated in the schedule. Close monitoring is made to meet the corrective action plan. Until a decision on the countermeasures is made, the schedule is not changed. The updated schedule is issued to each project management oce (PMO), project control department, or project manager as an updated project control for their work and for the next monthly update. When compared with the initial estimate, the updated information may indicate some variances in the scheduling basis. On the other hand, along with the project progress, schedule deviations may be detected from the initial scenario caused by various factors. 6.1. Progress Measurement Method in Scheduling Software The progress is calculated based on milestones, which are deﬁned. Each work package is weighed; this physical weight factor is calculated according to supplier contract price. The assessment of planned progress between milestones is obtained by assuming linear progress development between milestones; see Equation (1): %complete weight i=1 i %Complete = P (1) weight i=1 n Each activity weight is calculated based on an activity attribute, such as man-hours, material, or cost applied. For example, the length of time for earthwork is a function of the volume of soil cutting and ﬁlling in the speciﬁc area of the project site. Buildings 2019, 9, 191 26 of 37 6.2. Primavera P6 and Delay Analysis Schedule delay analysis is a method used to determine the extent of impact from potential delay to the agreed milestones. The schedule analysis method in Primavera P6 involves inserting additional activities indicating delays or changes into an updated schedule representing progress up to the point when a delay event occurs to determine the impact of those delay activities. Saving a project baseline plays a crucial role in delay analysis and is a fundamental step in Primavera P6 for schedule delay analysis. Figure 9 shows the baseline in the blue bar and the actual timeline in the yellow bar; as can be seen, a ﬁve-day delay in EC160 activity occurred. Buildings 2019, 8, x FOR PEER REVIEW 25 of 36 Buildings 2019, 8, x FOR PEER REVIEW 25 of 36 Figure 9. Baseline in blue bar and actual timeline in yellow bar. Figure 9. Baseline in blue bar and actual timeline in yellow bar. Figure 9. Baseline in blue bar and actual timeline in yellow bar. Primavera Primavera P6 P6 is is powerful powerful sof softwar tware e to to analyse analyse pr pro oject ject d delays, elays, sch schedule edule va variances, riances, sch schedule edule performance index, estimate to completion, and other aspects of earned value management. Figure performance index, estimate to completion, and other aspects of earned value management. Figure 10 Primavera P6 is powerful software to analyse project delays, schedule variances, schedule 10 shows the earned value feature of the Primavera P6 and respective diagrams. shows the earned value feature of the Primavera P6 and respective diagrams. performance index, estimate to completion, and other aspects of earned value management. Figure Figure 10. Earned value analysis using Primavera P6. Figure 10. Earned value analysis using Primavera P6. Figure 10. Earned value analysis using Primavera P6. In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that should have started, progressed, or finished between the previous data date and the new data date In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that in the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for should have started, progressed, or finished between the previous data date and the new data date should have started, progressed, or ﬁnished between the previous data date and the new data date in identifying the delayed activities. in the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for identifying identifying the delayed activities. the delayed activities. Figure 11. Primavera P6 Progress Spotlight. Figure 11. Primavera P6 Progress Spotlight. 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives Buildings 2019, 8, x FOR PEER REVIEW 25 of 36 Figure 9. Baseline in blue bar and actual timeline in yellow bar. Primavera P6 is powerful software to analyse project delays, schedule variances, schedule performance index, estimate to completion, and other aspects of earned value management. Figure 10 shows the earned value feature of the Primavera P6 and respective diagrams. Figure 10. Earned value analysis using Primavera P6. In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that Buildings should 2019 have , 9, s 191 tarted, progressed, or finished between the previous data date and the new data da 27 te of 37 in the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for Figure 11. Primavera P6 Progress Spotlight. Figure 11. Primavera P6 Progress Spotlight. 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives 7.1. Project Management Body of Knowledge (PMBOK) Based on the guide to project management body of knowledge [135], project time management encompasses the processes required to manage the project in a timely manner. Project time management has six main processes: (1) plan schedule management; (2) deﬁne activities; (3) sequence activities; (4) estimate activity durations; (5) develop schedule; and (6) control schedule. Project Management Body of Knowledge (PBMOK) also emphasises that the schedule baseline is the pillar of delay analysis in projects. A schedule baseline is the approved project timeline upon which any actual dates and changes need to be compared with the schedule baseline for analysing the delays in the schedule model. Updating the project schedule requires maintaining the actual data for project time performance. Any change to the critical path within the schedule baseline leads to delay. In addition, project time management in construction projects needs to focus particularly on other subjects as well as resource deﬁnition, allocation and resource levelling, activities to capture contingency allowances, weightage deﬁnition, progress curves, monitoring and schedule control procedures, and conditions for owner acceptance approval [136]. 7.2. Practice Standard for Scheduling Practice Standard for Scheduling is a Project Management Institute’s (PMI’s) standard with the detailed focus on project time management processes, project scheduling models, and techniques. This practice standard expands on information contained in the PMBOK guide. The main goal of this standard is to develop schedule models that are appropriate and ﬁt for purposes of projects. This practice standard introduces schedule model creation by selecting a scheduling approach and a scheduling tool. Based on this practice standard, project work breakdown structure and project-speciﬁc data are incorporated within the scheduling technique to develop a unique schedule model. Practice Standard for Scheduling has many hints and techniques for managing delays in the project schedule. For example, when the work on an activity is delayed, it is beneﬁcial for the activity to be split into two or more activities at natural break points. In another example, lags and leads also play important roles in managing the impact of delays on the overall project schedule. In addition, assigning a ﬁnish date to the end milestone can help the project schedule to better manage delays and changes in the project master schedule [137]. 7.3. Agile Practice Guide Agile planning focuses on shorter build cycles and tangible results at frequent and incremental intervals. An important part of agile scheduling is using multiple iterations instead of shifting from one Buildings 2019, 9, 191 28 of 37 phase to another, which makes the scheduling more complex but more ecient. Scrum and Kanban are two main agile frameworks for planning. Both frameworks are used to break down the work into small and manageable pieces. For controlling the project schedule developed by agile approaches, Burndown charts are typically used. Burndown charts are the most applicable agile tracking and controlling mechanisms used by project teams. The main characteristic of a Burndown chart is tracking the remaining work overtime. Caution should be taken when using agile approach delays because rework is high. Agile planning is a suitable project planning technique for a short-term project such as a software development project but is not recommended for construction projects [135,138]. 8. Discussion and the DEC conceptual model This paper, unlike other reviews, identiﬁed critical common factors and developed the DEC conceptual model for future investigations. The present review contributes to the body of knowledge in two main ways: (i) it identiﬁes the gaps and the deﬁciency areas in the DEC literature; and (ii) it develops a conceptual model that can be used to design a questionnaire for further investigations in dierent contexts. These contributions are discussed below and are presented in Table 8 and Figure 12, respectively. Buildings 2019, 8, x FOR PEER REVIEW 28 of 36 Figure Figure 12. 12. Th The e DEC DECco conceptual nceptual mod model el incincluding luding maimain n cons constr tructs ucts of res of ources resour , pr ces, ojec pr t oject contex context, t, and and stak stakeholders. eholders. Table 10 shows that four factors were overlooked in the DEC dataset. The data analysis and In contrast to traditional investigations, the DEC model suggests that future studies should the interpretations are not always valid or reliable due to small samples of participants, low quality carefully measure the effect of new “digital tools” and technologies in delay. Sepasgozar and Davis of data, unmatched structure of the research questionnaire with the current DEC literature or the [140] discussed different technology types in construction, which can be further detailed and case class study ified ba context, sed onoverlooking their applica the tioe n ects in tiof me technology management. adoption The ef by fecall ts constr of new uction digita stakeholders, l tools and or ignoring jobsite upgraded equipment. The overlooked factor (OF) refers to the data and the lack technologies on delay have not been evaluated in the literature. Some of the key digital technologies of are evaluating listed as fo new llows technologies : in delay analysis (Table 11). For example, OF1 is the quality of data collected • Di frgi om tal questionnair design comes, muwhich nication cannot tools:be Digeneralised gital Twin, as Buil a d valid ing In ﬁnding formatio ofncritical Systems factors (BIMof ) including Revit, ArchiCAD, Navisworks, BIMx, BricsCAD, Archibus, Constructor, construction projects all over the world. In fact, a major part of the DEC dataset focuses on developing IntelliCAD, VisualARQ, Revizto; Geographic Information Systems (GIS) including QGIS, countries; still, some of them suggested more investigations to understand the project complexity at ArcGIS, and ArcMap [17]. The literature frequently reports that design mistakes, errors, dierent strategic, operational, and project levels in these countries [84]. This small dataset cannot changing orders and scopes, later approvals, and late technical decision makings were the represent all key practitioners with a real understanding of delay causes and eects. Some studies main causes of delay in different contexts [95,99,104]. recruited a limited number of respondents (less than 150), which cannot represent all projects of a • Digital communication systems: cloud-based tools, emails, smart phones, and radio country and suers from lack of validation [27]. This leads to bias in the ﬁndings of some studies. communication systems. Some studies report that the communication and the coordination In some cases, the survey participants were selected carefully, while some cases were supposed to between different parties were poor [27,95,96,99,109]. be selected randomly, but in reality, their strategy of randomness was never clariﬁed. Some of the • Digital scheduling and planning tools: Microsoft Project, Oracle Primavera P6, FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Open Plan by Deltek, Smartsheet, and other software, packages, and platforms. • Digital progress monitoring and job-site controlling tools: laser scanner [141], lidar [142–146], Internet of Things sensors, and photography camera [147]. • Digital contract management tools: intelligent or smart contracts. The literature shows that many projects suffer from weak administration of contracts [96]. • Digital devices to increase the productivity of heavy equipment: real-time locating systems, Global Positioning System (GPS), and radar. • Digital production technologies: 3D printers [148]. New questionnaires can be designed based on the factors shown in Figure 12. Future studies also should identify the relationship between different causes and their effects on delay [79]. The visibility, the real-time monitoring, and the flexibility of the project using a wider range of digital technologies may mitigate the negative effects of resource and coordination issues. In case of using advanced and digital technologies, vendors have a significant role in successful technology adoption and implementation processes in the project [149–153], which can also mitigate the negative effects of productivity and coordination issues. Appropriate interaction between contractors and vendors Buildings 2019, 9, 191 29 of 37 studies used Analytic Hierarchy Process (AHP) or SD-DEMATEL [93] questionnaires to provide a consistency ratio to increase the reliability of the ﬁndings, but these studies suer from a limited number of factors measured and a limited number of participants. The literature also suggests that comparison studies among developing countries [110] and longitudinal studies in delay analysis should be conducted to examine the relationships of factors and stakeholders in an extended period [111]. In addition, the future studies should focus on more speciﬁc types of construction projects, such as utility, highway construction, and dam construction projects, to ﬁnd proper strategies to mitigate the eects of environmental issues [111]. Table 11. Future directions based on deﬁciencies of the current delay investigations. Suggestions for Future Overlooked Factors (OF) Examples Directions (FD) FD1: mix methods using Mostly faulty surveys in-depth interviews and OF1: faulty data analysis and (questionnaires) due to size case studies; interpretations and participants FD2: investigate dierent projects such as PPP OF2: unmatched structure of the Questionnaires are FD3: a set of factors should research questionnaires with based on similar factors be developed based on a new new knowledge and standards frequently asked conceptual proven model. (e.g., PMBOK) FD4: technology adoption OF3: overlooked eect of digital The DEC database does not [139] may aect projects tools and technologies (e.g. appear to be linked to these duration and should Digital twin, Navisworks, BIM, digital technologies be investigated in GIS, and IPD) dierent contexts. FD5: the application of advanced job-site The DEC database does not OF4: ignored job-site technologies such as analyse the eect of new technologies and equipment, advanced cranes, robotics, job-site technologies and 3D printing should be investigated. Figure 12 shows the main constructions of the conceptual DEC model for analysing the causes and the eects of delay in construction projects. The key constructs are resources, project context, and stakeholders. In contrast to traditional investigations, the DEC model suggests that future studies should carefully measure the eect of new “digital tools” and technologies in delay. Sepasgozar and Davis [140] discussed dierent technology types in construction, which can be further detailed and classiﬁed based on their application in time management. The eects of new digital tools and technologies on delay have not been evaluated in the literature. Some of the key digital technologies are listed as follows: Digital design communication tools: Digital Twin, Building Information Systems (BIM) including Revit, ArchiCAD, Navisworks, BIMx, BricsCAD, Archibus, Constructor, IntelliCAD, VisualARQ, Revizto; Geographic Information Systems (GIS) including QGIS, ArcGIS, and ArcMap [17]. The literature frequently reports that design mistakes, errors, changing orders and scopes, later approvals, and late technical decision makings were the main causes of delay in dierent contexts [95,99,104]. Digital communication systems: cloud-based tools, emails, smart phones, and radio communication systems. Some studies report that the communication and the coordination between dierent parties were poor [27,95,96,99,109]. Buildings 2019, 9, 191 30 of 37 Digital scheduling and planning tools: Microsoft Project, Oracle Primavera P6, FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Open Plan by Deltek, Smartsheet, and other software, packages, and platforms. Digital progress monitoring and job-site controlling tools: laser scanner [141], lidar [142–146], Internet of Things sensors, and photography camera [147]. Digital contract management tools: intelligent or smart contracts. The literature shows that many projects suer from weak administration of contracts [96]. Digital devices to increase the productivity of heavy equipment: real-time locating systems, Global Positioning System (GPS), and radar. Digital production technologies: 3D printers [148]. New questionnaires can be designed based on the factors shown in Figure 12. Future studies also should identify the relationship between dierent causes and their eects on delay [79]. The visibility, the real-time monitoring, and the ﬂexibility of the project using a wider range of digital technologies may mitigate the negative eects of resource and coordination issues. In case of using advanced and digital technologies, vendors have a signiﬁcant role in successful technology adoption and implementation processes in the project [149–153], which can also mitigate the negative eects of productivity and coordination issues. Appropriate interaction between contractors and vendors (e.g., materials, equipment, or technology suppliers) during both design and construction phases aects delay [27]. Additional evidence is required to validate the results of surveys, which will be conducted in the future. Many delay cause factors can be explored using project evidence and digital data generated during the project, and the questionnaires used to collect participant views cannot be considered as accurate and should only be used as tools to explore delay causes and eects. However, the best way (as suggested by this paper) is to adopt a mixed method of big data generated during the project along with the questionnaire developed based on the factors presented in Figure 12. 9. Conclusions and an Agenda for Future This paper aimed to identify the most relevant papers of delay causes and eects and to develop the DEC database for future critical analysis. The content of the DEC dataset was systematically analysed using bibliographic, cluster, and thematic analyses. This paper presented the DEC literature, including key ﬁndings of delay over the years. This study carefully conducted a systematic content analysis, resulting in four main overlooked factors and deﬁciency areas, which should be addressed in the future studies. The four factors are faulty data analysis and interpretations due to small samples of participants or low data reliability, unmatched structure of research questionnaires with the current policies or standards, overlooking the eects of technology adoption by construction stakeholders, and ignoring jobsite upgraded equipment. The key deﬁciencies were identiﬁed as faulty of data analysis and interpretations due to small sample of participants or low data reliability, unmatched structure of research questionnaires with the current policies or standards, overlooking the eects of technology adoption by construction stakeholders, and ignoring jobsite upgraded equipment. The overlooked factor refers to the data and the lack of evaluating new technologies in delay analysis. For example, OF1 refers to the quality of data collected from questionnaires, which cannot be generalised as a valid ﬁnding of critical factors of construction projects all over the world. In fact, a major part of the DEC dataset focuses on developing countries. This small dataset cannot represent all key practitioners with a real understanding of the delay causes and eects. Some studies recruited a limited number of respondents (less than 150), which cannot represent all projects of a country. This leads to bias in the ﬁndings of some studies. In some cases, the survey participants were selected carefully, and in some cases, they were supposed to be selected randomly, but in reality, it is not clear what their strategy of randomness was. Some studies used AHP questionnaires to provide a consistency ratio to increase the reliability of the ﬁndings, but these studies suer from a limited number of factors measured and a limited number of participants. Buildings 2019, 9, 191 31 of 37 Author Contributions: Conceptualization and Methodology, S.M.; Formal Analysis and Investigation, all authors; Writing-Original Draft Preparation and Writing-Review & Editing, all authors. Funding: This research received no external funding. Conﬂicts of Interest: The authors declare no conﬂict of interest. Appendix A The search string was selected as “delay overrun” or “time overrun“, and ‘“construction industry” or “construction project”’ and was applied on the Scopus database using the following search criteria: ( TITLE-ABS-KEY ( delay OR “time overrun” ) AND TITLE-ABS-KEY ( “construction industry” OR “Construction project” ) ) AND ( LIMIT-TO ( DOCTYPE , “ar” ) OR LIMIT-TO ( DOCTYPE , “re” ) ) AND ( LIMIT-TO ( LANGUAGE , “English” ) ) AND ( LIMIT-TO ( SRCTYPE , “j” ) ) AND ( EXCLUDE ( PUBYEAR , 2019 ) ) AND ( EXCLUDE ( SUBJAREA , "MATE" ) OR EXCLUDE ( SUBJAREA , "MATH" ) OR EXCLUDE ( SUBJAREA , “ARTS” ) OR EXCLUDE ( SUBJAREA , “CENG” ) OR EXCLUDE ( SUBJAREA , "AGRI" ) OR EXCLUDE ( SUBJAREA , "BIOC" ) OR EXCLUDE ( SUBJAREA , “MEDI” ) OR EXCLUDE ( SUBJAREA , “CHEM” ) OR EXCLUDE ( SUBJAREA , “PHYS” ) OR EXCLUDE ( SUBJAREA , “HEAL” ) OR EXCLUDE ( SUBJAREA , “NURS” ) OR EXCLUDE ( SUBJAREA , “PSYC” ) OR EXCLUDE ( SUBJAREA , “Undeﬁned” ) ) AND ( LIMIT-TO ( PUBYEAR , 2018 ) OR LIMIT-TO ( PUBYEAR , 2017 ) OR LIMIT-TO ( PUBYEAR , 2016 ) OR LIMIT-TO ( PUBYEAR , 2015 ) OR LIMIT-TO ( PUBYEAR , 2014 ) OR LIMIT-TO ( PUBYEAR , 2013 ) OR LIMIT-TO ( PUBYEAR , 2012 ) OR LIMIT-TO ( PUBYEAR , 2011 ) OR LIMIT-TO ( PUBYEAR , 2010 ) OR LIMIT-TO ( PUBYEAR , 2009 ) ) AND ( EXCLUDE ( SUBJAREA , “ENVI” ) OR EXCLUDE ( SUBJAREA , “ENER” ) OR EXCLUDE ( SUBJAREA , “EART” ) ) The search limited to articles investigating causes and eects in the recent ten years from 2009 to 2018. Therefore, ’cause’ and ‘eect’ also were included in the following search criteria: ( TITLE ( delay OR “time overrun” ) AND TITLE-ABS-KEY ( “construction industry” OR “Construction project” ) AND TITLE-ABS-KEY ( cause OR eect ) ) AND ( LIMIT-TO ( DOCTYPE , “ar” ) ) AND ( LIMIT-TO ( LANGUAGE , “English” ) ) AND ( LIMIT-TO ( SRCTYPE , “j” ) ) AND ( LIMIT-TO ( PUBYEAR , 2019 ) OR LIMIT-TO ( PUBYEAR , 2018 ) OR LIMIT-TO ( PUBYEAR , 2017 ) OR LIMIT-TO ( PUBYEAR , 2016 ) OR LIMIT-TO ( PUBYEAR , 2015 ) OR LIMIT-TO ( PUBYEAR , 2014 ) OR LIMIT-TO ( PUBYEAR , 2013 ) OR LIMIT-TO ( PUBYEAR , 2012 ) OR LIMIT-TO ( PUBYEAR , 2010 ) OR LIMIT-TO ( PUBYEAR , 2009 ) ) AND ( LIMIT-TO ( SUBJAREA , “ENGI” ) OR LIMIT-TO ( SUBJAREA , “BUSI” ) OR LIMIT-TO ( SUBJAREA , “DECI” ) OR LIMIT-TO ( SUBJAREA , “ECON” ) OR LIMIT-TO ( SUBJAREA , “SOCI” ) OR LIMIT-TO ( SUBJAREA , “MULT” ) ) References 1. Magdy, M.; Georgy, M.; Osman, H.; Elsaid, M. Delay Analysis Methodologies Used by Engineering and Construction Firms in Egypt. J. Leg. A. Disput. Resolut. Eng. Constr. 2019, 11, 1–11. [CrossRef] 2. Soomro, F.A.; Memon, M.J.; Chandio, A.F.; Sohu, S.; Soomro, R. Causes of Time Overrun in Construction of Building Projects in Pakistan. Eng. Technol. Appl. Sci. Res. 2019, 9, 3762–3764. 3. Abdelmaguid, T.F.; Elrashidy, W. Halting decisions for gas pipeline construction projects using AHP: A case study. Oper. Res. 2019, 19, 179–199. [CrossRef] 4. Harris, P.E. Planning and Control Using Oracle Primavera P6 Versions 8, 15 & 16 PPM Professional 2016; Eastwood Harris Pty Ltd: Melbourne, Australia, 2016. 5. Chan, A.P. Time–cost relationship of public sector projects in Malaysia. Int. J. Proj. Manag. 2001, 19, 223–229. [CrossRef] 6. Assaf, S.A.; Al-Hejji, S. Causes of delay in large construction projects. Int. J. Proj. Manag. 2006, 24, 349–357. [CrossRef] 7. Bramble, B.B.; Callahan, M.T. Construction Delay Claims; Taylor & Francis US: Oxfordshire, UK, 2004. 8. Aibinu, A.; Jagboro, G. The eects of construction delays on project delivery in Nigerian construction industry. Int. J. Proj. Manag. 2002, 20, 593–599. [CrossRef] Buildings 2019, 9, 191 32 of 37 9. Vaardini, S.; Karthiyayini, S.; Ezhilmathi, P. Study on cost overruns in construction projects: A review. Int. J. Appl. Eng. Res. 2016, 11, 356–363. 10. McKay, K.N.; Wiers, V.C. Planning, Scheduling and Dispatching Tasks in Production Control; Cognition, Technology & Work: London, England, 2003; Volume 5, pp. 82–93. 11. Gasik, S. An analysis of knowledge management in PMBOK®guide. PM World J. 2015, 4, 1–13. 12. Marmel, E. Microsoft Project 2007 Bible; John Wiley & Sons: Hoboken, NJ, USA, 2011; Volume 767. 13. Van Dorp, J.; Duey, M. Statistical dependence in risk analysis for project networks using Monte Carlo methods. Int. J. Prod. Econ. 1999, 58, 17–29. [CrossRef] 14. Irizarry, J.; Karan, E.P.; Jalaei, F. Integrating BIM and GIS to improve the visual monitoring of construction supply chain management. Autom. Constr. 2013, 31, 241–254. [CrossRef] 15. Naamane, A.; Boukara, A. A Brief Introduction to Building Information Modelling (BIM) and its interoperability with TRNSYS. Renew. Energy Sustain. Dev. 2015, 1, 126–130. 16. Maguire, D.J. An overview and deﬁnition of GIS. Geogr. Inf. Syst. Princ. Appl. 1991, 1, 9–20. 17. Shirowzhan, S.; Sepasgozar, S.M. Spatial Analysis Using Temporal Point Clouds in Advanced GIS: Methods for Ground Elevation Extraction in Slant Areas and Building Classiﬁcations. Isprs Int. J. Geo-Inf. 2019, 8, 120. [CrossRef] 18. Dziadosz, A.; Rejment, M. Risk analysis in construction project-chosen methods. Procedia Eng. 2015, 122, 258–265. [CrossRef] 19. Ghassemi, R.; Becerik-Gerber, B. Transitioning to Integrated Project Delivery: Potential barriers and lessons learned. Lean Constr. J. 2011, 2011, 32–52. 20. The chartered Institute of Procurement and Supply Chain. Delays in Construction Projects; IHS Markit/Chartered Institute of Purchasing and Supply Purchasing Managers Index: London, UK, 2017. 21. Bordoli, D.W.; Baldwin, A.N. A methodology for assessing construction project delays. Constr. Manag. Econ. 1998, 16, 327–337. [CrossRef] 22. Lowsley, S.; Linnett, C. About Time-: Delay Analysis in Construction; RICS: London, UK, 2006. 23. KPMG. Climbing the Curve: 2015 Global Construction Project Owner ’s Survey. In KPMG’s 2015 Global Construction Survey; Gilge, C., Ed.; KPMG International Cooperative: Switzerland Amstelveen, Netherlands, 24. Industry Trend Analysis-PPP Failures Highlight Project Execution Risks. 2017. Available online: http://www.infrastructure-insight.com/industry-trend-analysis-ppp-failures-highlight-project- execution-risks-feb-2017 (accessed on 3 July 2019). 25. Sambasivan, M.; Soon, Y.W. Causes and eects of delays in Malaysian construction industry. Int. J. Proj. Manag. 2007, 25, 517–526. [CrossRef] 26. Beckers, F.; Chiara, N.; Flesch, A.; Maly, J.; Silva, E.; Stegemann, U. A Risk-management Approach to A Successful Infrastructure Project; Mckinsey Work. Pap. Risk: New York, NY, USA, 2013; Volume 52, p. 18. 27. Ruqaishi, M.; Bashir, H.A. Causes of delay in construction projects in the oil and gas industry in the gulf cooperation council countries: A case study. J. Manag. Eng. 2013, 31, 05014017. [CrossRef] 28. Amandin, M.M.; Kule, J.W. Project delays on cost overrun risks: A study of Gasabo district construction projects Kigali, Rwanda. Abc J. Adv. Res. 2016, 5, 21–34. 29. Amoatey, C.T.; Ankrah, A.N.O. Exploring critical road project delay factors in Ghana. J. Facil. Manag. 2017, 15, 110–127. [CrossRef] 30. Akogbe, R.-K.T.; Feng, X.; Zhou, J. Importance and ranking evaluation of delay factors for development construction projects in Benin. Ksce J. Civ. Eng. 2013, 17, 1213–1222. [CrossRef] 31. IPMD. Infrastructure and Project Monitoring Division of Ministry of Statistics and Programme Implementation; Programme implementation division of the MOSPI: Delhi, India, 2012. 32. Faridi, A.S.; El-Sayegh, S.M. Signiﬁcant factors causing delay in the UAE construction industry. Constr. Manag. Econ. 2006, 24, 1167–1176. [CrossRef] 33. Al-Khalil, M.I.; Al-Ghaﬂy, M.A. Delay in public utility projects in Saudi Arabia. Int. J. Proj. Manag. 1999, 17, 101–106. [CrossRef] 34. Falqi, I. Delays in project completion: A comparative study of construction delay factors in Saudi Arabia and the United Kingdom. Master ’s Thesis, School of the Built Environment, Heriot-Watt University, December 2004, Unpublished. Buildings 2019, 9, 191 33 of 37 35. Khoshgoftar, M.; Bakar, A.H.A.; Osman, O. Causes of delays in Iranian construction projects. Int. J. Constr. Manag. 2014, 10, 53–69. [CrossRef] 36. Saeb, S.; Khayat, N.; Telvari, A. Causes of delay in Khuzestan Steel Company construction projects. Ind. Eng. Manag. Syst. 2016, 15, 335–344. [CrossRef] 37. Zack, J.G. Schedule delay analysis; is there agreement? In Proceedings of the PMI-CPM College of Performance Spring Conference, New Orleans, NY, USA, 7–9 May 2003; Project Management Institute—College of Performance Management. 38. Ellis, R.D.; Thomas, H.R. The root causes of delays in highway construction. In Proceedings of the 82nd Annual Meeting of the Transportation Research Board, Citeseer, Washington DC, USA, 12–16 January 2003. 39. Koushki, P.; Al-Rashid, K.; Kartam, N. Delays and cost increases in the construction of private residential projects in Kuwait. Constr. Manag. Econ. 2005, 23, 285–294. [CrossRef] 40. Odeyinka, H.A.; Yusif, A. The causes and eects of construction delays on completion cost of housing projects in Nigeria. J. Financ. Manag. Prop. Constr. 1997, 2, 31–44. 41. Iyer, K.; Jha, K. Critical factors aecting schedule performance: Evidence from Indian construction projects. J. Constr. Eng. Manag. 2006, 132, 871–881. [CrossRef] 42. Sweis, G.J. Factors aecting time overruns in public construction projects: The case of Jordan. Int. J. Bus. Manag. 2013, 8, 120. [CrossRef] 43. Chan, D.W.; Kumaraswamy, M.M. A study of the factors aecting construction durations in Hong Kong. Constr. Manag. Econ. 1995, 13, 319–333. [CrossRef] 44. Semple, C.; Hartman, F.T.; Jergeas, G. Construction claims and disputes: Causes and cost/time overruns. J. Constr. Eng. Manag. 1994, 120, 785–795. [CrossRef] 45. Flyvbjerg, B.; Holm, M.S.; Buhl, S. Underestimating costs in public works projects: Error or lie? J. Am. Plan. Assoc. 2002, 68, 279–295. [CrossRef] 46. Flyvbjerg, B.; Skamris Holm, M.K.; Buhl, S.L. How common and how large are cost overruns in transport infrastructure projects? Transp. Rev. 2003, 23, 71–88. [CrossRef] 47. Ansar, A.; Flyvbjerg, B.; Budzier, A.; Lunn, D. Does infrastructure investment lead to economic growth or economic fragility? Evidence from China. Oxf. Rev. Econ. Policy 2016, 32, 360–390. [CrossRef] 48. Sepasgozar, S.M.; Li, H.; Shirowzhan, S.; Tam, V.W.Y. Methods for monitoring construction o-road vehicle emissions: A critical review for identifying deﬁciencies and directions. Environ. Sci. Pollut. Res. 2019, 26, 15779–15794. [CrossRef] 49. Zhong, B.; Wu, H.; Li, H.; Sepasgozar, S.; Luo, H.; He, L. A scientometric analysis and critical review of construction related ontology research. Autom. Constr. 2019, 101, 17–31. [CrossRef] 50. Kim, H.; Lee, H.S.; Park, M.; Ahn, C.R.; Hwang, S. Productivity forecasting of newly added workers based on time-series analysis and site learning. J. Constr. Eng. Manag. 2015, 141. [CrossRef] 51. Jung, M.; Park, M.; Lee, H.S.; Kim, H. Weather-delay simulation model based on vertical weather proﬁle for high-rise building construction. J. Constr. Eng. Manag. 2016, 142. [CrossRef] 52. Kwon, N.; Park, M.; Lee, H.S.; Ahn, J.; Kim, S. Construction Noise Prediction Model Based on Case-Based Reasoning in the Preconstruction Phase. J. Constr. Eng. Manag. 2017, 143. [CrossRef] 53. Lee, K.P.; Lee, H.S.; Park, M.; Kim, D.Y.; Jung, M. Management-Reserve Estimation for International Construction Projects Based on Risk-Informed k-NN. J. Manag. Eng. 2017, 33. [CrossRef] 54. Yap, J.B.H.; Lock, A. Analysing the beneﬁts, techniques, tools and challenges of knowledge management practices in the Malaysian construction SMEs. J. Eng. Des. Technol. 2017, 15, 803–825. [CrossRef] 55. Yap, J.B.H.; Abdul-Rahman, H.; Chen, W. Collabourative model: Managing design changes with reusable project experiences through project learning and eective communication. Int. J. Proj. Manag. 2017, 35, 1253–1271. [CrossRef] 56. Yap, J.B.H.; Skitmore, M. Investigating design changes in Malaysian building projects. Archit. Eng. Des. Manag. 2018, 14, 218–238. [CrossRef] 57. Yap, J.B.H.; Abdul-Rahman, H.; Wang, C. Preventive Mitigation of Overruns with Project Communication Management and Continuous Learning: PLS-SEM Approach. J. Constr. Eng. Manag. 2018, 144. [CrossRef] 58. Yap, J.B.H.; Low, P.L.; Wang, C. Rework in Malaysian building construction: Impacts, causes and potential solutions. J. Eng. Des. Technol. 2017, 15, 591–618. [CrossRef] 59. Abdul-Rahman, H.; Berawi, M.A.; Berawi, A.R.; Mohamed, O.; Othman, M.; Yahya, I.A. Delay mitigation in the Malaysian construction industry. J. Constr. Eng. Manage. 2006, 132, 125–133. [CrossRef] Buildings 2019, 9, 191 34 of 37 60. Alashwal, A.M.; Abdul-Rahman, H.; Radzi, J. Knowledge utilization process in highway construction projects. J. Manag. Eng. 2016, 32. [CrossRef] 61. Enshassi, A.; Abdul-Aziz, A.R.; Abushaban, S. Analysis of contractors performance in Gaza strip construction projects. Int. J. Constr. Manag. 2012, 12, 65–79. [CrossRef] 62. Enshassi, A.; Arain, F.; Al-Raee, S. Causes of variation orders in construction projects in the Gaza Strip. J. Civ. Eng. Manag. 2010, 16, 540–551. [CrossRef] 63. Enshassi, A.; Choudhry, R.M.; El-ghandour, S. Contractors' perception towards causes of claims in construction projects. Int. J. Constr. Manag. 2009, 9, 79–92. [CrossRef] 64. Enshassi, A.; Mohamed, S.; Mustafa, Z.A.; Mayer, P.E. Factors aecting labour productivity in building projects in the Gaza strip. J. Civ. Eng. Manage. 2007, 13, 245–254. [CrossRef] 65. Enshassi, A.; Mohamed, S.; Abushaban, S. Factors aecting the performance of Construction projects in the Gaza Strip. J. Civ. Eng. Manag. 2009, 15, 269–280. [CrossRef] 66. Enshassi, A.; Arain, F.; Tayeh, B. Major causes of problems between contractors and subcontractors in the Gaza Strip. J. Financ. Manag. Prop. Constr. 2012, 17, 92–112. [CrossRef] 67. Enshassi, A.; Mohamed, S.; El-Ghandour, S. Problems associated with the process of claim management in Palestine: Contractors’ perspective. Eng. Constr. Arch. Manag. 2009, 16, 61–72. [CrossRef] 68. Enshassi, A.; Kumaraswamy, M.; Jomah, A.N. Signiﬁcant factors causing time and cost overruns in construction projects in the gaza strip: Contractors’ perspective. Int. J. Constr. Manag. 2010, 10, 35–60. [CrossRef] 69. Enshassi, A.; Kochendoerfer, B.; Abed, K. Trends in productivity improvement in construction projects in Palestine. Rev. Ing. Constr. 2013, 28, 173–206. [CrossRef] 70. Budayan, C. Evaluation of Delay Causes for BOT Projects Based on Perceptions of Dierent Stakeholders in Turkey. J. Manag. Eng. 2018, 35, 04018057. [CrossRef] 71. Alfakhri, A.Y.; Ismail, A.; Khoiry, M.A. The eects of delays in road construction projects in Tripoli, Libya. Int. J. Technol. 2018, 9, 766–774. [CrossRef] 72. Shahsavand, P.; Marefat, A.; Parchamijalal, M. Causes of delays in construction industry and comparative delay analysis techniques with SCL protocol. Eng. Constr. Archit. Manag. 2018, 25, 497–533. [CrossRef] 73. Khair, K.; Mohamed, Z.; Mohammad, R.; Farouk, H.; Ahmed, M.E. A Management Framework to Reduce Delays in Road Construction Projects in Sudan. Arab. J. Sci. Eng. 2018, 43, 1925–1940. [CrossRef] 74. Arditi, D.; Nayak, S.; Damci, A. Eect of organisational culture on delay in construction. Int. J. Proj. Manag. 2017, 35, 136–147. [CrossRef] 75. Perera, N.A.; Sutrisna, M.; Yiu, T.W. Decision-making model for selecting the optimum method of delay analysis in construction projects. J. Manag. Eng. 2016, 32, 04016009. [CrossRef] 76. Ji, Y.; Qi, L.; Liu, Y.; Liu, X.; Li, H.; Li, Y. Assessing and Prioritising Delay Factors of Prefabricated Concrete Building Projects in China. Appl. Sci. 2018, 8, 2324. [CrossRef] 77. Gunduz, M.; Nielsen, Y.; Ozdemir, M. Fuzzy assessment model to estimate the probability of delay in Turkish construction projects. J. Manag. Eng. 2015, 31, 04014055. [CrossRef] 78. Edwards, D.J.; Owusu-Manu, D.-G.; Baiden, B.; Badu, E.; Love, P.E. Financial distress and highway infrastructure delays. J. Eng. Des. Technol. 2017, 15, 118–132. [CrossRef] 79. Doloi, H.; Sawhney, A.; Iyer, K. Structural equation model for investigating factors aecting delay in Indian construction projects. Constr. Manag. Econ. 2012, 30, 869–884. [CrossRef] 80. Hasan, M.F.; Mohammed, M.S. Time overrun model for construction projects in Iraq by using fuzzy logic. Int. J. Civ. Eng. Technol. 2018, 9, 2593–2607. 81. Kamanga, M.; Steyn, W. Causes of delay in road construction projects in Malawi. J. S. Afr. Inst. Civ. Eng. 2013, 55, 79–85. 82. Vu, H.A.; Cu, V.H.; Min, L.X.; Wang, J.Q. Risk analysis of schedule delays in international highway projects in Vietnam using a structural equation model. Eng. Constr. Archit. Manag. 2017, 24, 1018–1039. [CrossRef] 83. Ballesteros-Pérez, P.; del Campo-Hitschfeld, M.L.; González-Naranjo, M.A.; González-Cruz, M.C. Climate and construction delays: Case study in Chile. Eng. Constr. Archit. Manag. 2015, 22, 596–621. [CrossRef] 84. Mpofu, B.; Ochieng, E.G.; Moobela, C.; Pretorius, A. Proﬁling causative factors leading to construction project delays in the United Arab Emirates. Eng. Constr. Archit. Manag. 2017, 24, 346–376. [CrossRef] Buildings 2019, 9, 191 35 of 37 85. Sambasivan, M.; Deepak, T.; Salim, A.N.; Ponniah, V. Analysis of delays in Tanzanian construction industry: Transaction cost economics (TCE) and structural equation modelling (SEM) approach. Eng. Constr. Archit. Manag. 2017, 24, 308–325. [CrossRef] 86. Wang, T.-K.; Ford, D.N.; Chong, H.-Y.; Zhang, W. Causes of delays in the construction phase of Chinese building projects. Eng. Constr. Archit. Manag. 2018, 25, 1534–1551. [CrossRef] 87. Islam, M.S.; Suhariadi, B.T. Construction delays in privately funded large building projects in Bangladesh. Asian J. Civ. Eng. 2018, 19, 1–15. [CrossRef] 88. Khatib, B.; Poh, Y.; El-Shaﬁe, A. Delay Factors in Reconstruction Projects: A Case Study of Mataf Expansion Project. Sustainability 2018, 10, 4772. [CrossRef] 89. Larsen, J.K.; Shen, G.Q.; Lindhard, S.M.; Brunoe, T.D. Factors aecting schedule delay, cost overrun, and quality level in public construction projects. J. Manag. Eng. 2015, 32, 04015032. [CrossRef] 90. Zidane, Y.J.-T.; Andersen, B. The top 10 universal delay factors in construction projects. Int. J. Manag. Proj. Bus. 2018, 11, 650–672. [CrossRef] 91. Alfakhri, A.Y.; Ismail, A.; Khoiry, M.A.; Arhad, I.; Irtema, H.I.M. A conceptual model of delay factors aecting road construction projects in Libya. J. Eng. Sci. Technol. 2017, 12, 3286–3298. 92. Das, D.K.; Emuze, F. A Dynamic Model of Contractor-Induced Delays in India. J. Constr. Dev. Ctries. 2017, 22, 21–39. [CrossRef] 93. Parchami Jalal, M.; Shoar, S. A hybrid SD-DEMATEL approach to develop a delay model for construction projects. Eng. Constr. Archit. Manag. 2017, 24, 629–651. [CrossRef] 94. Renuka, S.; Kamal, S.; Umarani, C. A model to estimate the time overrun risk in construction projects. Empir. Res. Urban Manag. 2017, 12, 64–76. 95. Adam, A.; Josephson, P.-E.B.; Lindahl, G. Aggregation of factors causing cost overruns and time delays in large public construction projects: Trends and implications. Eng. Constr. Archit. Manag. 2017, 24, 393–406. [CrossRef] 96. Asiedu, R.O.; Adaku, E.; Owusu-Manu, D.-G. Beyond the causes: Rethinking mitigating measures to avert cost and time overruns in construction projects. Constr. Innov. 2017, 17, 363–380. [CrossRef] 97. Durdyev, S.; Omarov, M.; Ismail, S. Causes of delay in residential construction projects in Cambodia. Cogent Eng. 2017, 4, 1291117. [CrossRef] 98. Oyegoke, A.S.; Al Kiyumi, N. The causes, impacts and mitigations of delay in megaprojects in the Sultanate of Oman. J. Financ. Manag. Prop. Constr. 2017, 22, 286–302. [CrossRef] 99. Agyekum-Mensah, G.; Knight, A.D. The professionals’ perspective on the causes of project delay in the construction industry. Eng. Constr. Archit. Manag. 2017, 24, 828–841. [CrossRef] 100. Amoatey, C.T.; Ameyaw, Y.A.; Adaku, E.; Famiyeh, S. Analysing delay causes and eects in Ghanaian state housing construction projects. Int. J. Manag. Proj. Bus. 2015, 8, 198–214. [CrossRef] 101. Bekr, G.A. Causes of delay in public construction projects in Iraq. Jordan J. Civ. Eng. 2015, 159, 1–14. 102. Mahamid, I.; Al-Ghonamy, A.; Aichouni, M. Research Article Risk Matrix for Delay Causes in Construction Projects in Saudi Arabia. Res. J. Appl. Sci. Eng. Technol. 2015, 9, 665–670. [CrossRef] 103. Santoso, D.S.; Soeng, S. Analyzing delays of road construction projects in Cambodia: Causes and eects. J. Manag. Eng. 2016, 32, 05016020. [CrossRef] 104. Kadry, M.; Osman, H.; Georgy, M. Causes of construction delays in countries with high geopolitical risks. J. Constr. Eng. Manag. 2016, 143, 1–11. 105. Kim, S.-Y.; Tuan, K.N. Delay factor analysis for hospital projects in Vietnam. KSCE J. Civ. Eng. 2016, 20, 519–529. [CrossRef] 106. Bagaya, O.; Song, J. Empirical study of factors inﬂuencing schedule delays of public construction projects in Burkina Faso. J. Manag. Eng. 2016, 32, 05016014. [CrossRef] 107. Aziz, R.F.; Abdel-Hakam, A.A. Exploring delay causes of road construction projects in Egypt. Alex. Eng. J. 2016, 55, 1515–1539. [CrossRef] 108. Assbeihat, J.M. Factors Aecting Delays on Private Construction Projects. Technology 2016, 7, 22–33. 109. Nawi, M.N.M.N.; Lee, A. Factors inﬂuencing project delay: A case study of the vale malaysia minerals project (VMMP). Int. J. Supply Chain Manag. 2016, 5, 178–184. 110. Samarghandi, H.; Mousavi, S.; Taabayan, P.; Mir Hashemi, A.; Willoughby, K. Studying the Reasons for Delay and Cost Overrun in Construction Projects: The Case of Iran. J. Constr. Dev. Ctries. 2016, 21, 51–84. [CrossRef] Buildings 2019, 9, 191 36 of 37 111. Zailani, S.; Arin, H.A.M.; Iranmanesh, M.; Moeinzadeh, S.; Iranmanesh, M. The moderating eect of project risk mitigation strategies on the relationship between delay factors and construction project performance. J. Sci. Technol. Policy Manag. 2016, 7, 346–368. [CrossRef] 112. Al-Kharashi, A.; Skitmore, M. Causes of delays in Saudi Arabian public sector construction projects. Constr. Manag. Econ. 2009, 27, 3–23. [CrossRef] 113. Kaliba, C.; Muya, M.; Mumba, K. Cost escalation and schedule delays in road construction projects in Zambia. Int. J. Proj. Manag. 2009, 27, 522–531. [CrossRef] 114. Enshassi, A.; Al-Najjar, J.; Kumaraswamy, M. Delays and cost overruns in the construction projects in the Gaza Strip. J. Financ. Manag. Prop. Constr. 2009, 14, 126–151. [CrossRef] 115. Abdul-Rahman, H.; Takim, R.; Min, W.S. Financial-related causes contributing to project delays. J. Retail Leis. Prop. 2009, 8, 225–238. [CrossRef] 116. Mahamid, I.; Bruland, A.; Dmaidi, N. Causes of delay in road construction projects. J. Manag. Eng. 2011, 28, 300–310. [CrossRef] 117. Kazaz, A.; Ulubeyli, S.; Tuncbilekli, N.A. Causes of delays in construction projects in Turkey. J. Civ. Eng. Manag. 2012, 18, 426–435. [CrossRef] 118. Chandramohan, A.; Narayanan, S.L.; Gaurav, A.; Krishna, N. Cost and time overrun analysis for green construction projects. Int. J. Green Econ. 2012, 6, 167–177. [CrossRef] 119. Yang, J.-B.; Chu, M.-Y.; Huang, K.-M. An empirical study of schedule delay causes based on Taiwan’s litigation cases. Proj. Manag. J. 2013, 44, 21–31. [CrossRef] 120. González, P.; González, V.; Molenaar, K.; Orozco, F. Analysis of causes of delay and time performance in construction projects. J. Constr. Eng. Manag. 2013, 140, 04013027. [CrossRef] 121. Golob, K.; Bastic, ˇ M.; Pšunder, I. Inﬂuence of project and marketing management on delays, penalties, and project quality in slovene organisations in the construction industry. J. Manag. Eng. 2012, 29, 495–502. [CrossRef] 122. Alinaitwe, H.; Apolot, R.; Tindiwensi, D. Investigation into the causes of delays and cost overruns in Uganda’s public sector construction projects. J. Constr. Dev. Ctries. 2013, 18, 33. 123. Marzouk, M.M.; El-Rasas, T.I. Analyzing delay causes in Egyptian construction projects. J. Adv. Res. 2014, 5, 49–55. [CrossRef] 124. Wang, W.-C.; Lin, C.-L.; Wang, S.-H.; Liu, J.-J.; Lee, M.-T. Application of importance-satisfaction analysis and inﬂuence-relations map to evaluate design delay factors. J. Civ. Eng. Manag. 2014, 20, 497–510. [CrossRef] 125. Yang, J.-B.; Huang, K.-M.; Lee, C.-H.; Chiu, C.-T. Incorporating lost productivity calculation into delay analysis for construction projects. KSCE J. Civ. Eng. 2014, 18, 380–388. [CrossRef] 126. Yang, J.-B.; Kao, C.-K. Critical path eect based delay analysis method for construction projects. Int. J. Proj. Manag. 2012, 30, 385–397. [CrossRef] 127. Chaphalkar, N.B.; Iyer, K. Factors inﬂuencing decisions on delay claims in construction contracts for Indian scenario. Constr. Econ. Build. 2014, 14, 32–44. [CrossRef] 128. Braimah, N. Understanding construction delay analysis and the role of preconstruction programming. J. Manag. Eng. 2013, 30, 04014023. [CrossRef] 129. Abdelhadi, Y.; Dulaimi, M.F.; Bajracharya, A. Factors inﬂuencing the selection of delay analysis methods in construction projects in UAE. Int. J. Constr. Manag. 2018, 19, 329–340. [CrossRef] 130. Guévremont, M.; Hammad, A. Visualisation of Delay Claim Analysis Using 4D Simulation. J. Leg. A. Disput. Resolut. Eng. Constr. 2018, 10, 05018002. [CrossRef] 131. Yang, J.-B.; Teng, Y.-L. Theoretical development of stochastic delay analysis and forecast method. J. Chin. Inst. Eng. 2017, 40, 391–400. [CrossRef] 132. Yang, J.-B.; Wei, P.-R. Causes of delay in the planning and design phases for construction projects. J. Archit. Eng. 2010, 16, 80–83. [CrossRef] 133. Chen, G.-X.; Shan, M.; Chan, A.P.; Liu, X.; Zhao, Y.-Q. Investigating the causes of delay in grain bin construction projects: The case of China. Int. J. Constr. Manag. 2019, 19, 1–14. [CrossRef] 134. Apipattanavis, S.; Sabol, K.; Molenaar, K.R.; Rajagopalan, B.; Xi, Y.; Blackard, B.; Patil, S. Integrated framework for quantifying and predicting weather-related highway construction delays. J. Constr. Eng. Manag. 2010, 136, 1160–1168. [CrossRef] 135. Project Management Institute. A Guide to the Project Managemnet Body of Knowledge (PMBOK Guide), 6th ed.; Project Management Institute: Newtown Square, PA, USA, 2017. Buildings 2019, 9, 191 37 of 37 136. Project Management Institute. Construction Extension to the PMBOK, 2nd ed.; Project Management Institute: Newtown Square, PA, USA, 2016. 137. PMI. Practice Standard for Scheduling, Project Management Institute, 3rd ed.; Project Management Institute: Newtown Square, PA, USA, 2019. 138. Project Management Institute. Agile Practice Guide; Project Management Institute: Newtown Square, PA, USA, 2017. 139. Sepasgozar, S.M.E.; Razkenari, M.A.; Barati, K. The Importance of New Technology for Delay Mitigation in Construction Projects. Am. J. Civ. Eng. Archit. 2015, 3, 15–20. [CrossRef] 140. Sepasgozar, S.M.E.; Davis, S. Digital Construction Technology and Job-site Equipment Demonstration: Modelling Relationship Strategies for Technology Adoption. Buildings 2019, 9, 158. [CrossRef] 141. Sepasgozar, S.M.; Lim, S.; Shirowzhan, S. Implementation of Rapid As-built Building Information Modelling Using Mobile LiDAR. In Proceedings of the ASCE Construction Research Congress 2014, Construction in a Global Network, Atlanta, Georgia, 19–21 May 2014. 142. Shirowzhan, S.; Sepasgozar, S.M.; Li, H.; Trinder, J.; Tang, P. Comparative analysis of machine learning and point-based algorithms for detecting 3D changes in buildings over time using bi-temporal lidar data. Autom. Constr. 2019, 105, 102841. [CrossRef] 143. Shirowzhan, S.; Sepasgozar, S.M.E.; Li, H.; Trinder, J. Spatial compactness metrics and Constrained Voxel Automata development for analyzing 3D densiﬁcation and applying to point clouds: A synthetic review. Autom. Constr. 2018, 96, 236–249. [CrossRef] 144. Shirowzhan, S.; Trinder, J. Building classiﬁcation from lidar data for spatio-temporal assessment of 3D urban developments. Procedia Eng. 2017, 180, 1453–1461. [CrossRef] 145. Shirowzhan, S.; Lim, S.; Trinder, J. Enhanced autocorrelation-based algorithms for ﬁltering airborne lidar data over urban areas. J. Surv. Eng. 2016, 142, 04015008. [CrossRef] 146. Shirowzhan, S.; Lim, S. Autocorrelation statistics-based algorithms for automatic ground and non-ground classiﬁcation of Lidar data. In Proceedings of the ISARC. International Symposium on Automation and Robotics in Construction, Sydney, Australia, 9–11 July 2014; Vilnius Gediminas Technical University, Department of Construction Economics: Vilnius, Lithuania, 2014. [CrossRef] 147. Sepasgozar, S.M.; Forsythe, P.J.; Shirowzhan, S. Scanners and Photography: A Combined Framework. In Proceedings of the 40th Australasian Universities Building Education Association (AUBEA) 2016 Conference, Cairns, Australia, 6–8 July 2016; Central Queensland University: Cairns, Australia, 2016. 148. Tahmasebinia, F.; Niemelä, M.; Ebrahimzadeh Sepasgozar, S.; Lai, T.; Su, W.; Reddy, K.; Shirowzhan, S.; Sepasgozar, S.; Marroquin, F. Three-Dimensional Printing Using Recycled High-Density Polyethylene: Technological Challenges and Future Directions for Construction. Buildings 2018, 8, 165. [CrossRef] 149. Sepasgozar, S.M.; Davis, S.R.; Li, H.; Luo, X. Modelling the Implementation Process for New Construction Technologies: Thematic Analysis Based on Australian and US Practices. J. Manag. Eng. 2018, 34, 05018005. [CrossRef] 150. Sepasgozar, S.M.; Davis, S. Construction Technology Adoption Cube: An Investigation on Process, Factors, Barriers, Drivers and Decision Makers Using NVivo and AHP Analysis. Buildings 2018, 8, 74. [CrossRef] 151. Sepasgozar, S.M.; Davis, S.R.; Loosemore, M. Dissemination Practices of Construction Sites’ Technology Vendors in Technology Exhibitions. J. Manag. Eng. 2018, 34, 04018038. [CrossRef] 152. Sepasgozar, S.M.; Davis, S.; Loosemore, M.; Bernold, L. An investigation of modern building equipment technology adoption in the Australian construction industry. Eng. Constr. Archit. Manag. 2018, 25, 1075–1091. [CrossRef] 153. Sepasgozar, S.M.E.; Loosemore, M. The role of customers and vendors in modern construction equipment technology diusion. Eng. Constr. Archit. Manag. 2017, 24, 1203–1221. [CrossRef] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Buildings Multidisciplinary Digital Publishing Institute http://www.deepdyve.com/lp/multidisciplinary-digital-publishing-institute/delay-causes-and-emerging-digital-tools-a-novel-model-of-delay-UHP0NhDG7N

Loading next page...

References (149)

A. Enshassi, S. Mohamed, Saleh Abushaban (2009)
Factors affecting the performance of construction projects in the Gaza Strip
Journal of Civil Engineering and Management, 15
A. Enshassi, S. Mohamed, S. El-Ghandour (2009)
Problems associated with the process of claim management in Palestine: Contractors' perspective
Engineering, Construction and Architectural Management, 16
Karen Crombrugghe (2014)
Critical path effect based delay analysis method for construction projects
Kwang-Pyo Lee, Hyun-soo Lee, Moonseo Park, D. Kim, M. Jung (2017)
Management-Reserve Estimation for International Construction Projects Based on Risk-Informed k-NN
Journal of Management in Engineering, 33
P. Koushki, K. Al-Rashid, N. Kartam (2005)
Delays and cost increases in the construction of private residential projects in Kuwait
Construction Management and Economics, 23
Wei-Chih Wang, Chia-Li Lin, Shih-Hsu Wang, Jang-Jeng Liu, Ming-Tsung Lee (2014)
APPLICATION OF IMPORTANCE-SATISFACTION ANALYSIS AND INFLUENCE-RELATIONS MAP TO EVALUATE DESIGN DELAY FACTORS
Journal of Civil Engineering and Management, 20
C. Semple, Francis Hartman, George Jergeas (1994)
Construction Claims and Disputes: Causes and Cost/Time Overruns
Journal of Construction Engineering and Management-asce, 120
S. Sepasgozar, M. Loosemore (2017)
The role of customers and vendors in modern construction equipment technology diffusion
Engineering, Construction and Architectural Management, 24
A. Alashwal, H. Abdul-Rahman, Juwita Radzi (2016)
Knowledge Utilization Process in Highway Construction Projects
Journal of Management in Engineering, 32
Moses Kamanga, W. Steyn (2013)
Causes of delay in road construction projects in Malawi
Journal of The South African Institution of Civil Engineering, 55
M. Al-Khalil, Mohammed Al-Ghafly (1999)
Delay in public utility projects in Saudi Arabia
International Journal of Project Management, 17
(2017)
Industry Trend Analysis-PPP Failures Highlight Project Execution Risks
Tamer Abdelmaguid, Waleed Elrashidy (2019)
Halting decisions for gas pipeline construction projects using AHP: a case study
Operational Research, 19
I. Mahamid, A. Bruland, Nabil Dmaidi (2012)
Causes of Delay in Road Construction Projects
Journal of Management in Engineering, 28
H. Alinaitwe, R. Apolot (2013)
Investigation into the Causes of Delays and Cost Overruns in Uganda's Public Sector Construction Projects
(2017)
The chartered Institute of Procurement and Supply Chain
S. Sepasgozar, P. Forsythe, S. Shirowzhan (2016)
Scanners and Photography: A combined framework
F. Tahmasebinia, Marjo Niemelä, Sanee Sepasgozar, T. Lai, Winson Su, K. Reddy, S. Shirowzhan, S. Sepasgozar, F. Marroquin (2018)
Three-Dimensional Printing Using Recycled High-Density Polyethylene: Technological Challenges and Future Directions for Construction
Buildings
Ousseni Bagaya, Jinbo Song (2016)
Empirical Study of Factors Influencing Schedule Delays of Public Construction Projects in Burkina Faso
Journal of Management in Engineering, 32
Ksenija Golob, M. Bastic, I. Pšunder (2013)
Influence of Project and Marketing Management on Delays, Penalties, and Project Quality in Slovene Organizations in the Construction Industry
Journal of Management in Engineering, 29
A. Enshassi, S. Mohamed, Z. Mustafa, P. Mayer (2007)
FACTORS AFFECTING LABOUR PRODUCTIVITY IN BUILDING PROJECTS IN THE GAZA STRIP
Journal of Civil Engineering and Management, 13
B. Khatib, Y. Poh, Ahmed El-Shafie (2018)
Delay Factors in Reconstruction Projects: A Case Study of Mataf Expansion Project
Sustainability
Jyh-Bin Yang, Pei-Rei Wei (2010)
Causes of Delay in the Planning and Design Phases for Construction Projects
Journal of Architectural Engineering, 16
R. Aziz, Asmaa Abdel-Hakam (2016)
Exploring delay causes of road construction projects in Egypt
alexandria engineering journal, 55
J. Dorp, M. Duffey (1999)
Statistical dependence in risk analysis for project networks using Monte Carlo methods
International Journal of Production Economics, 58
Ghanim Bekr (2015)
Causes of Delay in Public Construction Projects in Iraq
K. Iyer, K. Jha (2006)
Critical Factors Affecting Schedule Performance: Evidence from Indian Construction Projects
Journal of Construction Engineering and Management-asce, 132
M. Magdy, M. Georgy, H. Osman, M. El-Said (2019)
Delay Analysis Methodologies Used by Engineering and Construction Firms in Egypt
Journal of Legal Affairs and Dispute Resolution in Engineering and Construction
Michel Guévremont, A. Hammad (2018)
Visualization of Delay Claim Analysis Using 4D Simulation
Journal of Legal Affairs and Dispute Resolution in Engineering and Construction
D. Santoso, Sothy Soeng (2016)
Analyzing Delays of Road Construction Projects in Cambodia: Causes and Effects
Journal of Management in Engineering, 32
R. Ghassemi, B. Becerik-Gerber (2011)
Transitioning to Integrated Project Delivery: Potential barriers and lessons learned
Y. Zidane, B. Andersen (2018)
The top 10 universal delay factors in construction projects
International Journal of Managing Projects in Business, 11
S. Renuka, S. Kamal, C. Umarani (2017)
A Model to Estimate the Time Overrun Risk in Construction Projects
Theoretical and Empirical Researches in Urban Management, 12
F. Soomro, M. Memon, A. Chandio, S. Sohu, R. Soomro (2019)
Causes of Time Overrun in Construction of Building Projects in Pakistan
Engineering, Technology & Applied Science Research
D. Arditi, Shruti Nayak, Atilla Damci (2017)
Effect of organizational culture on delay in construction
International Journal of Project Management, 35
Mohammed Ruqaishi, Hamdi Bashir (2015)
Causes of Delay in Construction Projects in the Oil and Gas Industry in the Gulf Cooperation Council Countries: A Case Study
Journal of Management in Engineering, 31
A. Enshassi, F. Arain, Sadi Al‐Raee (2010)
Causes of variation orders in construction projects in the Gaza Strip
Journal of Civil Engineering and Management, 16
Arshi Faridi, S. El-Sayegh (2006)
Significant factors causing delay in the UAE construction industry
Construction Management and Economics, 24
A. Dziadosz, M. Rejment (2015)
Risk Analysis in Construction Project - Chosen Methods
Procedia Engineering, 122
D. Das, F. Emuze (2017)
A Dynamic Model of Contractor-Induced Delays in India
, 22
(2003)
Schedule delay analysis; is there agreement
S. Sepasgozar, Heng Li, S. Shirowzhan, V. Tam (2019)
Methods for monitoring construction off-road vehicle emissions: a critical review for identifying deficiencies and directions
Environmental Science and Pollution Research, 26
S. Shirowzhan, J. Trinder (2017)
Building Classification from Lidar Data for Spatio-temporal Assessment of 3D Urban Developments
Procedia Engineering, 180
A. Alfakhri, A. Ismail, Khoiry Azry, Ishak Arhad, Hamza Irtema (2017)
A conceptual model of delay factors affecting road construction projects in Libya
journal of engineering science and technology, 12
M. Kadry, H. Osman, M. Georgy (2017)
Causes of Construction Delays in Countries with High Geopolitical Risks
Journal of Construction Engineering and Management-asce, 143
Jyh-Bin Yang, Chih-Kuei Kao (2012)
Critical path effect based delay analysis method for construction projects
International Journal of Project Management, 30
S. Sepasgozar, Steven Davis (2018)
Construction Technology Adoption Cube: An Investigation on Process, Factors, Barriers, Drivers, and Decision Makers using NVivo and AHP Analysis
Buildings, 8
C. Kaliba, M. Muya, Kanyuka Mumba (2009)
Cost escalation and schedule delays in road construction projects in Zambia
International Journal of Project Management, 27
Daniel Chan, M. Kumaraswamy (1995)
A study of the factors affecting construction durations in Hong Kong
Construction Management and Economics, 13
(1991)
An overview and deﬁnition of GIS
J. Yap, H. Abdul-Rahman, Chen Wang (2018)
Preventive Mitigation of Overruns with Project Communication Management and Continuous Learning: PLS-SEM Approach
Journal of Construction Engineering and Management-asce, 144
B. Flyvbjerg, M. Holm, Søren Buhl (2002)
Underestimating Costs in Public Works Projects: Error or Lie?
Journal of the American Planning Association, 68
S. Shirowzhan, Samsung Lim (2014)
Autocorrelation Statistics-Based Algorithms for Automatic Ground and Non-Ground Classification of Lidar Data
J. Yap, Anna Lock (2017)
Analysing the benefits, techniques, tools and challenges of knowledge management practices in the Malaysian construction SMEs
Journal of Engineering, Design and Technology, 15
H. Abdul-Rahman, M. Berawi, Abdur Berawi, O. Mohamed, M. Othman, Imran Yahya (2006)
Delay Mitigation in the Malaysian Construction Industry
Journal of Construction Engineering and Management-asce, 132
(2004)
Delays in project completion: A comparative study of construction delay factors in Saudi Arabia and the United Kingdom
J. Yap, H. Abdul-Rahman, Wang Chen (2017)
Collaborative model: Managing design changes with reusable project experiences through project learning and effective communication
International Journal of Project Management, 35
G. Chen, M. Shan, A. Chan, Xu Liu, Yi-qing Zhao (2019)
Investigating the causes of delay in grain bin construction projects: the case of China
International Journal of Construction Management, 19
Cenk Budayan (2019)
Evaluation of Delay Causes for BOT Projects Based on Perceptions of Different Stakeholders in Turkey
Journal of Management in Engineering
A. Ansar, B. Flyvbjerg, Alexander Budzier, Daniel Lunn (2016)
Does Infrastructure Investment Lead to Economic Growth or Economic Fragility? Evidence from China
ERN: Debt; Debt Management (Topic)
M. Jalal, Shahab Shoar (2017)
A hybrid SD-DEMATEL approach to develop a delay model for construction projects
Engineering, Construction and Architectural Management, 24
(2016)
Construction Extension to the PMBOK , 2nd ed.; Project Management Institute: Newtown Square, PA, USA
C. Amoatey, Alfred Ankrah (2017)
Exploring critical road project delay factors in Ghana
Journal of Facilities Management, 15
J. Irizarry, E. Karan, Farzad Jalaei (2013)
Integrating BIM and GIS to improve the visual monitoring of construction supply chain management
Automation in Construction, 31
(2015)
the Curve: 2015 Global Construction Project Owner’s Survey
S. Sepasgozar, Steven Davis (2019)
Digital Construction Technology and Job-site Equipment Demonstration: Modelling Relationship Strategies for Technology Adoption
Buildings
S. Sepasgozar, Steven Davis, Heng Li, Xian-qiong Luo (2018)
Modeling the Implementation Process for New Construction Technologies: Thematic Analysis Based on Australian and U.S. Practices
Journal of Management in Engineering, 34
J. Yap, Pak Low, Chen Wang (2017)
Rework in Malaysian building construction: impacts, causes and potential solutions
Journal of Engineering, Design and Technology, 15
Romuald-Kokou Akogbe, Xin-An Feng, Jing Zhou (2013)
Importance and ranking evaluation of delay factors for development construction projects in Benin
KSCE Journal of Civil Engineering, 17
S. Zailani, Hazrina Ariffin, M. Iranmanesh, S. Moeinzadeh, M. Iranmanesh (2016)
The moderating effect of project risk mitigation strategies on the relationship between delay factors and construction project performance
, 7
A. Enshassi, Bernd Kochendoerfer, Karem Abed (2013)
Trends in productivity improvement in construction projects in Palestine
, 28
(2013)
A Risk-management Approach to A Successful Infrastructure Project ; Mckinsey Work
S. Sepasgozar, Mohamad Razkenari, K. Barati (2015)
The Importance of New Technology for Delay Mitigation in Construction Projects
American Journal of Civil Engineering and Architecture, 3
S. Shirowzhan, Samsung Lim, J. Trinder (2016)
Enhanced Autocorrelation-Based Algorithms for Filtering Airborne Lidar Data over Urban Areas
Journal of Surveying Engineering-asce, 142
M. Marzouk, Tarek El-Rasas (2013)
Analyzing delay causes in Egyptian construction projects
Journal of Advanced Research, 5
Y. Abdelhadi, M. Dulaimi, Arun Bajracharya (2019)
Factors influencing the selection of delay analysis methods in construction projects in UAE
International Journal of Construction Management, 19
S. Shirowzhan, S. Sepasgozar, Heng Li, J. Trinder (2018)
Spatial compactness metrics and Constrained Voxel Automata development for analyzing 3D densification and applying to point clouds: A synthetic review
Automation in Construction
M. Sambasivan, T. Deepak, A. Salim, V. Ponniah (2017)
Analysis of delays in Tanzanian construction industry
Engineering, Construction and Architectural Management, 24
R. Ellis (2003)
THE ROOT CAUSES OF DELAYS IN HIGHWAY CONSTRUCTION
B. Flyvbjerg, Mette holm, Søren Buhl (2003)
How common and how large are cost overruns in transport infrastructure projects?
Transport Reviews, 23
J. Larsen, G. Shen, S. Lindhard, T. Brunoe (2016)
Factors Affecting Schedule Delay, Cost Overrun, and Quality Level in Public Construction Projects
Journal of Management in Engineering, 32
C. Amoatey, Yaa Ameyaw, Ebenezer Adaku, Samuel Famiyeh (2015)
Analysing delay causes and effects in Ghanaian state housing construction projects
International Journal of Managing Projects in Business, 8
A. Kazaz, S. Ulubeyli, Nihan Tuncbilekli (2012)
Causes of delays in construction projects in Turkey
Journal of Civil Engineering and Management, 18
P. Ballesteros-Pérez, Maria Campo-Hitschfeld, Manuel González-Naranjo, M. González-Cruz (2015)
Climate and construction delays: Case study in Chile
Engineering, Construction and Architectural Management, 22
M. Khoshgoftar, A. Bakar, O. Osman (2010)
Causes of Delays in Iranian Construction Projects
International Journal of Construction Management, 10
S. Shirowzhan, S. Sepasgozar, Heng Li, J. Trinder, P. Tang (2019)
Comparative analysis of machine learning and point-based algorithms for detecting 3D changes in buildings over time using bi-temporal lidar data
Automation in Construction
K. McKay, V. Wiers (2003)
Planning, scheduling and dispatching tasks in production control
Cognition, Technology & Work, 5
A. Chan (2001)
Time–cost relationship of public sector projects in Malaysia
International Journal of Project Management, 19
J. Yap, M. Skitmore (2017)
Investigating design changes in Malaysian building projects
Architectural Engineering and Design Management, 14
Bekithemba Mpofu, E. Ochieng, C. Moobela, Adri Pretorius (2017)
Profiling causative factors leading to construction project delays in the United Arab Emirates
Engineering, Construction and Architectural Management, 24
Khalid Khair, Z. Mohamed, Rafiuddin Mohammad, H. Farouk, Mohammed Ahmed (2018)
A Management Framework to Reduce Delays in Road Construction Projects in Sudan
Arabian Journal for Science and Engineering, 43
S. Sepasgozar, Samsung Lim, S. Shirowzhan (2014)
Implementation of Rapid As-built Building Information Modeling Using Mobile LiDAR
B. Bramble, M. Callahan (1992)
Construction Delay Claims
Somkiat Apipattanavis, K. Sabol, K. Molenaar, B. Rajagopalan, Y. Xi, B. Blackard, S. Patil (2010)
Integrated Framework for Quantifying and Predicting Weather-Related Highway Construction Delays
Journal of Construction Engineering and Management-asce, 136
M. Sambasivan, Y. Soon (2007)
Causes and effects of delays in Malaysian construction industry
International Journal of Project Management, 25
George Agyekum-Mensah, A. Knight (2017)
The professionals’ perspective on the causes of project delay in the construction industry
Engineering, Construction and Architectural Management, 24
S. Durdyev, M. Omarov, S. Ismail (2017)
Causes of delay in residential construction projects in Cambodia
Cogent Engineering, 4
M. Jung, Moonseo Park, Hyun-soo Lee, Hyunsoo Kim (2016)
Weather-Delay Simulation Model Based on Vertical Weather Profile for High-Rise Building Construction
Journal of Construction Engineering and Management-asce, 142
R. Asiedu, Ebenezer Adaku, D. Owusu-Manu (2017)
Beyond the causes: Rethinking mitigating measures to avert cost and time overruns in construction projects
Construction Innovation: Information, Process, Management, 17
Hyunsoo Kim, Hyun-soo Lee, Moonseo Park, C. Ahn, Sungjoo Hwang (2015)
Productivity Forecasting of Newly Added Workers Based on Time-Series Analysis and Site Learning
Journal of Construction Engineering and Management-asce, 141
Adel Al‐Kharashi, M. Skitmore (2009)
Causes of delays in Saudi Arabian public sector construction projects
Construction Management and Economics, 27
S. Sepasgozar, Steven Davis, M. Loosemore (2018)
Dissemination Practices of Construction Sites’ Technology Vendors in Technology Exhibitions
Journal of Management in Engineering
A. Enshassi, F. Arain, Bassam Tayeh (2012)
Major causes of problems between contractors and subcontractors in the Gaza Strip
Journal of Financial Management of Property and Construction, 17
S. Shirowzhan, S. Sepasgozar (2019)
Spatial Analysis Using Temporal Point Clouds in Advanced GIS: Methods for Ground Elevation Extraction in Slant Areas and Building Classifications
ISPRS Int. J. Geo Inf., 8
M. Nawi, R. Deraman, M. Hasmori, M. Azimi, Angela Lee (2016)
Factors Influencing Project Delay: A Case Study of the Vale Malaysia Minerals Project (VMMP)
International Journal of Supply Chain Management, 5
Elaine Marmel (2000)
Microsoft Project 2007 Bible
Soo-Yong Kim, Kiet Tuan, Van Luu (2016)
Delay factor analysis for hospital projects in Vietnam
KSCE Journal of Civil Engineering, 20
B. Zhong, Haitao Wu, Heng Li, S. Sepasgozar, Hanbin Luo, Ling He (2019)
A scientometric analysis and critical review of construction related ontology research
Automation in Construction
P. González, V. González, K. Molenaar, F. Orozco (2014)
Analysis of Causes of Delay and Time Performance in Construction Projects
Journal of Construction Engineering and Management-asce, 140
A. Enshassi, Abdul-Rashid Abdul-Aziz, Saleh Abushaban (2012)
Analysis of Contractors Performance in Gaza Strip Construction Projects
International Journal of Construction Management, 12
Jyh-Bin Yang, Kuei-Mei Huang, Chang-Hung Lee, C. Chiu (2014)
Incorporating lost productivity calculation into delay analysis for construction projects
KSCE Journal of Civil Engineering, 18
A. Enshassi, Jomah Al-Najjar, M. Kumaraswamy (2009)
Delays and cost overruns in the construction projects in the Gaza Strip
Journal of Financial Management of Property and Construction, 14
H. Vu, Viet Cu, Lianxing Min, Jian Wang (2017)
Risk analysis of schedule delays in international highway projects in Vietnam using a structural equation model
Engineering, Construction and Architectural Management, 24
D. Edwards, D. Owusu-Manu, B. Baiden, E. Badu, P. Love (2017)
Financial distress and highway infrastructure delays
Journal of Engineering, Design and Technology, 15
A. Chandramohan, S. Narayanan, Ashish Gaurav, N. Krishna (2012)
Cost and time overrun analysis for green construction projects
International Journal of Green Economics, 6
P. Harris (2016)
Planning & Control Using Oracle Primavera P6 Versions 8, 15 & 16 PPM Professional
Ting Wang, David Ford, H. Chong, Wei Zhang (2018)
Causes of delays in the construction phase of Chinese building projects
Engineering, Construction and Architectural Management
Ghaleb Sweis (2013)
Factors Affecting Time Overruns in Public Construction Projects: The Case of Jordan
International Journal of Biometrics, 8
(2018)
Time overrun model for construction projects in Iraq by using fuzzy logic
(2017)
Project Management Institute
Parvaneh Shahsavand, A. Marefat, Majid Parchamijalal (2018)
Causes of delays in construction industry and comparative delay analysis techniques with SCL protocol
Engineering, Construction and Architectural Management, 25
Nahyun Kwon, Moonseo Park, Hyun-soo Lee, Joseph Ahn, Sooyoung Kim (2017)
Construction Noise Prediction Model Based on Case-Based Reasoning in the Preconstruction Phase
Journal of Construction Engineering and Management-asce, 143
Jyh-Bin Yang, Mei-Yi Chu, Kuei-Mei Huang (2013)
An Empirical Study of Schedule Delay Causes Based on Taiwan's Litigation Cases
Project Management Journal, 44
A. Enshassi, M. Kumaraswamy, Jomah Al-Najjar (2010)
Significant Factors Causing Time and Cost Overruns in Construction Projects in the Gaza Strip: Contractors’ Perspective
International Journal of Construction Management, 10
S. Sepasgozar, Steven Davis, M. Loosemore, L. Bernold (2018)
An investigation of modern building equipment technology adoption in the Australian construction industry
Engineering, Construction and Architectural Management
H. Doloi, A. Sawhney, K. Iyer (2012)
Structural equation model for investigating factors affecting delay in Indian construction projects
Construction Management and Economics, 30
S. Assaf, Sadiq Al-Hejji (2006)
Causes of delay in large construction projects
International Journal of Project Management, 24
A. Oyegoke, Naseer Kiyumi (2017)
The causes, impacts and mitigations of delay in megaprojects in the Sultanate of Oman
Journal of Financial Management of Property and Construction, 22
Muhammad Islam, B. Suhariadi (2018)
Construction delays in privately funded large building projects in Bangladesh
Asian Journal of Civil Engineering, 19
A. Alfakhri, A. Ismail, M. Khoiry (2018)
The Effects of Delays in Road Construction Projects in Tripoli, Libya
International Journal of Technology
(1997)
The causes and e ﬀ ects of construction delays on completion cost of housing projects in Nigeria
A. Aibinu, G. Jagboro (2002)
The effects of construction delays on project delivery in Nigerian construction industry
International Journal of Project Management, 20
Yingbo Ji, Lin Qi, Yan Liu, Xinnan Liu, Hong Li, Yan Li (2018)
Assessing and Prioritising Delay Factors of Prefabricated Concrete Building Projects in China
Applied Sciences
A. Enshassi, R. Choudhry, S. El-Ghandour (2009)
Contractors’ Perception towards Causes of Claims in Construction Projects
International Journal of Construction Management, 9
A. Adam, Per-Erik Josephson, G. Lindahl (2017)
Aggregation of factors causing cost overruns and time delays in large public construction projects: Trends and implications
Engineering, Construction and Architectural Management, 24
D. Bordoli, A. Baldwin (1998)
A methodology for assessing construction project delays
Construction Management and Economics, 16
(2017)
A Guide to the Project Managemnet Body of Knowledge (PMBOK Guide) , 6th ed.
A. Naamane, A. Boukara (2015)
A Brief Introduction to Building Information Modeling (BIM) and its interoperability with TRNSYS
Renewable Energy and Sustainable Development
Sajjad Saeb, Navid Khayat, Abdulrasoul Telvari (2016)
Causes of Delay in Khuzestan Steel Company Construction Projects
Industrial Engineering and Management Systems, 15
N. Perera, M. Sutrisna, T. Yiu (2016)
Decision-making model for selecting the optimum method of delay analysis in construction projects
Journal of Management in Engineering, 32
Hamed Samarghandi, S. Mousavi, Pouria Taabayan, A. Hashemi, Keith Willoughby (2016)
STUDYING THE REASONS FOR DELAY AND COST OVERRUN IN CONSTRUCTION PROJECTS: THE CASE OF IRAN
H. Abdul-Rahman, R. Takim, Wong Min (2009)
Financial-related causes contributing to project delays
Journal of Retail & Leisure Property, 8
Murat Gunduz, Y. Nielsen, M.Caglar Ozdemir (2015)
Fuzzy Assessment Model to Estimate the Probability of Delay in Turkish Construction Projects
Journal of Management in Engineering, 31
Musirikare Amandin, J. Kule (2016)
Project Delays on Cost Overrun Risks: A Study of Gasabo District Construction Projects Kigali, Rwanda
, 5
N. Braimah (2014)
Understanding construction delay analysis and the role of pre-construction programming
Journal of Management in Engineering, 30
N. Chaphalkar, K. Iyer (2014)
Factors influencing decisions on delay claims in construction contracts for Indian scenario
Australasian Journal of Construction Economics and Building, 14
I. Mahamid, A. Al-Ghonamy, M. Aichouni (2015)
Risk Matrix for Delay Causes in Construction Projects in Saudi Arabia
Research Journal of Applied Sciences, Engineering and Technology, 9
Jyh-Bin Yang, Yanhua Teng (2017)
Theoretical development of stochastic delay analysis and forecast method
Journal of the Chinese Institute of Engineers, 40
(2015)
An analysis of knowledge management in PMBOK®guide

Publisher: Multidisciplinary Digital Publishing Institute
Copyright: © 1996-2019 MDPI (Basel, Switzerland) unless otherwise stated Terms and Conditions Privacy Policy
ISSN: 2075-5309
DOI: 10.3390/buildings9090191
Publisher site: See Article on Publisher Site

Abstract

buildings Review Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK 1 , 2 1 1 Samad M. E. Sepasgozar * , Reyhaneh Karimi , Sara Shirowzhan , Mohammad Mojtahedi , 3 4 Sabbar Ebrahimzadeh and David McCarthy Faculty of Built Environment, The University of New South Wales, Sydney, NSW 2052, Australia Department of Art and Architecture, The University of Science and Culture, Tehran 1461968151, Iran Department of Law, Quaemshahr Azad University, Qaemshahr 4765161964, Iran KPMG Major Projects Advisory, Sydney 2000, NSW, Australia * Correspondence: samad.sepasgozar@gmail.com; Tel.: +61-(02)-469628400 Received: 30 June 2019; Accepted: 22 August 2019; Published: 26 August 2019 Abstract: Delay is one of the main challenges of construction projects, and there is still much to overcome in order to reach near zero delay in all construction projects. This project aims to conduct a systematic critical review including a bibliography analysis on delay literature in construction. The main questions consider what has been learnt from a decade investigating delay causes and eects in the construction literature and what factors have been missed in the literature. This paper also presents a new and challenging question regarding how digital tools and associated technologies may prevent any delay in construction projects, which can change the research direction from delay investigations to identifying prevention factors. The paper identiﬁes the delay dataset, including 493 papers investigating delay in construction, and establishes a speciﬁc dataset of papers focusing on delay eects and causes (DEC), including 94 selected papers covering dierent factors examined in over 29 countries such as Iran, India, Turkey, Bangladesh, Saudi Arabia, the United Arab Emirates (UAE), Cambodia, Oman, Malaysia, Taiwan, China, Vietnam, the US, the UK, and Egypt. In addition, the paper identiﬁes 30 critical factors with the frequency of occurrences over three times in the DEC dataset and computes their medians of ranking. This paper also discusses digital tools and methods that can be used for delay analysis and preventions, including MS Project, Oracle Primavera P6, and Open Plan by Deltek. The paper discusses the project schedule delay analysis from project management methodology perspectives. It also discusses the current method’s limitations and future directions, which are based on the identiﬁcation of the deﬁciency areas. In total, four overlooked factors are identiﬁed and suggested, including faulty data analysis, unmatched structure of the research questionnaires with new knowledge and standards [e.g., Project Management Body of Knowledge (PMBOK)], overlooked eects of digital technologies [e.g., Digital twin, Navisworks, Building Information Model (BIM), Geographic Information System (GIS), and Integrated Project Delivery (IPD)], and ignored job-site technologies. In addition, the paper presents the DEC model for future studies, including four main key factors. These factors are resources (e.g., project budgets, labour, material, equipment, and digital tool), project context, stakeholders performance (e.g., owner/client, consultant/designer, contractor, vendor/supplier), and external factors (e.g., ground condition, site location, regulation, natural disaster), which may signiﬁcantly aect delay prevention and should be concurrently considered in the future delay investigations, since they may be required for designing an eective mitigation strategy when these proof points are identiﬁed. This would signiﬁcantly help to utilise digital systems to prevent time overruns in dierent construction contexts. Buildings 2019, 9, 191; doi:10.3390/buildings9090191 www.mdpi.com/journal/buildings Buildings 2019, 9, 191 2 of 37 Keywords: delay; time overruns; cost overruns; scheduling; PMBOK construction extension; PMI scheduling standards; Microsoft projects; primavera; BIM; GIS; risk analysis; IPD 1. Introduction Disruptive technologies have been increasingly introduced to construction businesses in recent years, even though the industry continues to lag behind all other industries in its adoption of technology. However, there is not enough awareness of the current and best practices in project time management. The applications of these technologies for delay monitoring have not been fully examined regarding, for example, how intelligent or smart contracts can reduce disputes and delays in projects. While there is an urgent need to identify the application of new digital technologies and tools for preventing delay in a project, most papers still try to identify delay analysis techniques using the traditional approaches [1], such as conducting a survey including common factors determined many years ago [2,3]. This paper aims to review the literature over the past decade and develop directions for future studies in delay investigations in construction projects. The main objectives of the paper are: to identify the delay eects and causes (DEC) dataset; to identify key critical factors causing delay in construction projects in the previous decade; to identify dominant methods used in the delay literature; to review the current digital technology capacity for preventing delay; and to identify deﬁciency areas, present a conceptual DEC model, and map the future directions. These objectives are important to project management scholars to base their future investigations on a comprehensive critical analysis of a one-decade endeavour of delay investigations in dierent countries. Project managers are able to plan the construction sequence, monitor the status of project activities, and update the project progress to identify the project delays by using project controls software systems, particularly software that is professionally developed for project time and cost management. Speciﬁcally, project scheduling software systems are able to manage changes to the schedule baseline to accomplish the planned project completion data. However, site logs in construction projects or periodical progress reports (e.g., daily or weekly) are required to capture the status of the project as an input into the project scheduling software. Applications or platforms developed for project time management are instrumental tools for evaluating the project deviation from the planned baseline. Project scheduling software can be used to compare the actual project progress compared to the planned baseline. The actual start and ﬁnish dates for project activities form the basis for actual progress calculations and document the as-built schedule information. Project scheduling software monitors the progress of all the project’s activities with the order of the critical path, the near-critical path, and the non-critical path activities to evaluate the impact of delay on project schedule. If critical path activities slip, they immediately cause project delay. The components of a project schedule can be monitored by a variety of techniques such as ﬂoat dissipation or erosion of ﬂoat, missed start and ﬁnish dates, actual duration analysis, and earned value management using a project controls software system. Project scheduling software predominantly uses the critical path method (CPM) for its scheduling practice. Its use is often the focus of contract claims due to project time impacts and delays to the contract completion date. Schedule progress is measured against the contract planned dates. The baseline is an important reference in all scheduling software if contract and progress delay disputes arise between stakeholders involved in projects. A baseline is a complete copy of a project plan that we can compare to the current schedule to evaluate progress in all scheduling software. As a project progresses, certain types of project data are likely to change. When a project is in progress and data changes, the original baseline created for the project may not accurately measure performance against the current project. Empirical evidence suggests that, during these events, the project schedule needs to be re-baselined to reﬂect the revised plan to achieve the estimated completion date. Likewise, creating a new baseline may not yield accurate results for measuring performance, because some data change during the life of the project, which should be measured against the original project data [4]. Buildings 2019, 9, 191 3 of 37 The key terms and concepts used in the delay literature are brieﬂy presented in Table 1. The deﬁnitions of these terms are signiﬁcant, since they create alignment in thinking of speciﬁc delay causes, tools, and standards in the construction ﬁeld. Some of the terms are interdisciplinary and are borrowed from dierent contexts such as Building Information Modeling (BIM), Integrated Project Delivery (IPD), and Geographic Information Systems (GIS). Table 2 shows several examples of delay in dierent contexts and countries. Delay may signiﬁcantly aect project cost and may raise disputes, arbitration, litigation, and abandonment. Table 1. Key terms and deﬁnitions that may be used in the delay literature. Term/ Concept Deﬁnition The dierence between estimated and actual completion time [5], also known as Delay/Time Overruns time overrun [6] or extended time [7], mainly due to contractor, owner, or joint of all stakeholders tasks and actions [8]. The dierence between estimated and actual cost results in increasing the total Cost Overruns project cost, also known as budget overrun, due to unforeseen costs or underestimation of task’s actual cost [9]. Scheduling A control structure based on planning and dispatching [10]. Project Management Body of Knowledge (PMBOK) guide, including principals PMBOK and knowledge required for project management [11]. Focuses on construction projects by providing supplemental knowledge about Construction Extension project health, safety, security, and environmental management and project ﬁnancial management and good practices. Project Management Institute (PMI) refers to good practice methods for PMI Scheduling scheduling. Good practices are based on a general agreement on appropriate Standards use of skills, tools, and techniques for enhancing the success chances of dierent projects. Microsoft (MS) Projects A tool for project planning and control [12]. Primavera A tool for scheduling and project risk analysis [13]. Both Building Information Modelling (BIM) and Geographic Information Building Information Systems (GIS) [14] are analytical and visualisation systems. Model (BIM) BIM is used for designing and sharing collaboratively generated rich data [15]. Both Building Information Modelling (BIM) and Geographic Information Geographic Systems (GIS) [14] are analytical and visualisation systems. Information System GIS is used for map processing, database visualisation, and spatial analysis and (GIS) can be integrated with other systems [16,17]. Analysis of adverse events at dierent stages, including planning and Risk Analysis programming, to enrich decisions [18]. Integrated Project Delivery (IPD) intends to increase the success of a project by Integrated Project addressing waste and ineciency issues and adversarial relations in Delivery (IPD) construction [19]. Buildings 2019, 9, 191 4 of 37 Table 2. Delay in dierent contexts, including the percentages of the delay reported in the literature. Delay cases reported in the literature Evidence of delay in percentage UK: (1) 2017; construction projects in general [20]; (1) About 30% of projects were delayed [20]; (2) the (2) 1993-1994; government construction projects average time overrun was 23.2% [21]; (3) 70% of [21]; (3) 2001; government construction projects [22] projects were delayed [22]. 109 senior leaders of public and private organisations from across the globe, 26% from (1) Just 25% of construction projects came within 10% public bodies such as government agencies with the of their original deadlines [23] remainder represented by private enterprises [23] Philippines: 2010–2017; public–private partnership 92.8% of projects were delayed [24]. (PPP) projects Malaysia: (1) 2005; government contract projects (1) 17.3% were delayed for over 3 months. [25]; (2) [25]; (2) 2010–2014; Kuala Lumpur Airport Terminal caused extra USD $2 billion to the ﬁnal costs [26]. 2 [26] Oman: 2010–2013; A major public organisation 62% within their schedule [27]. Africa: (1) 2009–2012; Rwanda; public [28]; (2) (1) 65.7% of projects were delayed [28]; (2) 70% were 2000–2011; Ghana; roads [29]; (3) 1999–2005; Benin delayed for average of 17 months [29]; (3) 22% of [30]; (4) 1970– 1998; Ghana; groundwater projects were delayed for more than 2 years [30]; (4) construction [30] 70% of projects were delayed [30]. India: 2012; central sector infrastructure projects Approximately 57% of projects were delayed [31]. UAE: 1995–2005; construction projects in general 50% of projects were delayed [32]. (1) 70% of projects were delayed from 10% to 30% of Saudi Arabia: (1) 2004; private and public projects estimated time [6]; (2) time overrun decreased from [6]; (2) construction of water and sewage works [33] 59% in 1994 [33] to 40% in 2004 [34]. (1) The percentage of delay in 2001, 2002 and 2003 Iran: (1) projects for government [35]; (2) Khuzestan were respectively 30%, 74.5% and 75%. [35]; (2) the steel company [36] project duration is approximately 150% of project estimated duration [36]. (1) Projects were respectively delayed for 2.5 weeks US: (1) general projects of US and England [37]; (2) and approximately a month [37]; (2) the time overrun 2001; highway projects [38] of projects was 25% of their contract duration [38]. 56% of projects were delayed, approximately 54% Kuwait: 1990–2000; private residential housing were delayed for four months or more, and 30% were projects [39] delayed for more than six months [39]. (1) 70% were delayed and caused 51.51% cost overrun Nigeria: (1) 1991–1996; housing projects [40]; (2) [40]; (2) time overrun was in average 51% of the 2000; most projects in Lagos city [41] predicted duration [41]. Jordan: 1990–1997; public construction projects [42] 81.5% of projects were delayed [42]. Hong Kong: (1) 1990–1993; government projects (1) Only 40% within schedule [43]; (2) only 23% [43]; (2) 1990–1993; private sector projects within schedule [43]. Western Canada: civil, institutional, high rise Several cases of 24 projects were delayed more than apartment building, and petrochemical 100% of contract duration [44]. Indonesia 38% of projects were delayed [37]. Projects of 20 nations (Europe, North America, and Time and cost overruns were, on average, 70% and other); during last 70 years; rail, ﬁxed link (bridges 28%, respectively [45,46]. and tunnels), and road Rich democracies (Denmark, Germany, Japan, South Korea, Netherlands, Norway, Spain, Sweden, Average schedule overrun of projects was 42.7% [47]. UK, and US); during last three decades; infrastructure projects Buildings 2019, 9, 191 5 of 37 This paper ﬁrst systematically identiﬁes articles investigating delay and time overrun in construction and then conducts a content analysis to review relevant articles in detail and provide a comprehensive understanding of the current literature. Finally, it identiﬁes the gap in the literature and suggests future studies. 2. Review Method Based on the initial review of the current practices in the literature, a set of strings was developed to Buildings 2019, 8, x FOR PEER REVIEW 5 of 36 select the ﬁnal search criteria. The search string was selected as “delay overrun” or “time overrun” and Based on the initial review of the current practices in the literature, a set of strings was developed “construction industry” or “construction project” and applied on the Scopus database, which resulted to select the final search criteria. The search string was selected as “delay overrun” or “time overrun" in 493 records using the search criteria, as shown in Appendix A. and "construction industry" or "construction project"’ and applied on the Scopus database, which The search was limited to articles investigating causes and eects in the past ten years, from 2009 resulted in 493 records using the search criteria, as shown in Appendix A. to 2018. Therefore, “cause” and “eect” were also included in the search criteria. Applying the criteria The search was limited to articles investigating causes and effects in the past ten years, from 2009 resulted in developing the delay eects/causes (DEC) database in construction with 94 records using to 2018. Therefore, “cause” and “effect” were also included in the search criteria. Applying the criteria the search criteria shown in Appendix A. Dierent tools and techniques including VOS Viewer and resulted in developing the delay effects/causes (DEC) database in construction with 94 records using clustering algorithms were used for visualisation and conducting the present systematic review. the search criteria shown in Appendix A. Different tools and techniques including VOS Viewer and clustering algorithms were used for visualisation and conducting the present systematic review. 3. Bibliography Analysis 3. Bibliography Analysis This section reports the results of a quantitative analysis focusing on bibliographic attributes, including Thi co-citations s section re for port identifying s the resultinter s of aconnections quantitative of an the alysi delay s focu literatur sing on e bibl within iograselected phic attributes articles , and including co-citations for identifying interconnections of the delay literature within selected articles their corresponding citations. The systematic analysis alleviates bias during search, article selection, and their corresponding citations. The systematic analysis alleviates bias during search, article and bibliography analysis. The employed bibliometric method assists in identifying similarities and selection, and bibliography analysis. The employed bibliometric method assists in identifying possible patterns of inquiry based on citation records and cited references [48,49]. similarities and possible patterns of inquiry based on citation records and cited references [48,49]. Figure 1 shows the result of co-authorship analysis using the full counting method. The minimum Figure 1 shows the result of co-authorship analysis using the full counting method. The number of papers of an author was considered as one, thus 1179 authors and co-authors of 493 selected minimum number of papers of an author was considered as one, thus 1179 authors and co-authors articles were included and are visualised in Figure 1. Figure 2 shows the co-authorship network for all of 493 selected articles were included and are visualised in Figure 1. Figure 2 shows the co-authorship 259 co-authors using the full counting method based on the DEC dataset including 94 papers. network for all 259 co-authors using the full counting method based on the DEC dataset including 94 papers. Figure 1. Visualisation of co-authorship network for all 1179 co-authors using the full counting Figure 1. Visualisation of co-authorship network for all 1179 co-authors using the full counting method method based on the first bibliographic dataset including 493 papers. based on the ﬁrst bibliographic dataset including 493 papers. Buildings 2019, 9, 191 6 of 37 Buildings 2019, 8, x FOR PEER REVIEW 6 of 36 Buildings 2019, 8, x FOR PEER REVIEW 6 of 36 Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method based baseon d on the thdelay e delae y effect ects and s and causes causes(DEC) (DEC)dataset dataset including including 9 94 4 pa papers. pers. For each of the 1179 authors, the total strength of the co-authorship links with all authors and For each of the 1179 authors, the total strength of the co-authorship links with all authors and co-authors co-authorwer s were e calcu calcula lated, ted,and andthe the gr gre eatest atest li link nk str stre ength ngth wa was s cconsider onsidered ed fo for r th the e visu visualisation alisation of of Figur Figure e 1. In 1. addition, In additi di on ,er d ent iffer numbers ent num of be papers rs of pa from pers an from author anwer auth e selected or werefor sefutur lected e investigation. for future investigation. The results show that, for the minimums of two, three, and four papers of an author, The results show that, for the minimums of two, three, and four papers of an author, 138, 43, 138, 43, and 12 authors met the criteria. This shows that a limited number of authors continuously or Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method and 12 authors met the criteria. This shows that a limited number of authors continuously or frequently based on the delay effects and causes (DEC) dataset including 94 papers. frequently contribute to the delay literature, including Lee, H. S. [50–53], Park, M. [50–53], Yap, J. B. contribute to the delay literature, including Lee, H. S. [50–53], Park, M. [50–53], Yap, J. B. H. [54–58], H. [54–58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61–69]. This shows that, among a large Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61–69]. This shows that, among a large set of scholars For each of the 1179 authors, the total strength of the co-authorship links with all authors and set of scholars investigating delay in construction, only a limited number of authors are regularly co- investigating delay in construction, only a limited number of authors are regularly co-authoring in the co-authors were calculated, and the greatest link strength was considered for the visualisation of authoring in the delay area. This is also limited in the DEC dataset where the criteria are applied and delay arFi ea. gure This 1. is In also additi limited on, difin ferent the n DEC umbedataset rs of pawher pers e from the a criteria n authoar r e were applied selecte and d fo the r future focus of the the focus of the literature is effect and cause. investigation. The results show that, for the minimums of two, three, and four papers of an author, literature is eect and cause. 138, 43, and 12 authors met the criteria. This shows that a limited number of authors continuously or Figure 3 shows the co-occurrence analytical map of keywords based on the ﬁrst bibliographic frequently contribute to the delay literature, including Lee, H. S. [50–53], Park, M. [50–53], Yap, J. B. dataset. For this visualisation a minimum number of 2 was selected for co-occurrence visualisation and H. [54–58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61–69]. This shows that, among a large a total of 713 keywords out of the sample of 2926 keywords are shown in Figure 3. The normalisation set of scholars investigating delay in construction, only a limited number of authors are regularly co- method of LinLog was used in VOS Viewer. authoring in the delay area. This is also limited in the DEC dataset where the criteria are applied and the focus of the literature is effect and cause. Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset. With the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords are shown. Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset. With Figure 3. Co-occurrence analytical map of keywords created on the ﬁrst bibliographic dataset. With the the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords keywords are shown. are shown. Buildings 2019, 8, x FOR PEER REVIEW 7 of 36 Figure 3 shows the co-occurrence analytical map of keywords based on the first bibliographic Buildings 2019, 9, 191 7 of 37 dataset. For this visualisation a minimum number of 2 was selected for co-occurrence visualisation and a total of 713 keywords out of the sample of 2926 keywords are shown in Figure 3. The norma Figur lis ea4 tio also n mshows ethod o the f Lco-occurr inLog waence s used analytical in VOS Vie map wer. of keywor ds based on the ﬁrst bibliographic Figure 4 also shows the co-occurrence analytical map of keywords based on the first dataset, but the minimum number of co-occurrence was selected as ﬁve to identify the most frequent bibliographic dataset, but the minimum number of co-occurrence was selected as five to identify the concepts. Of the sample of 2926 keywords, 176 keywords are shown in Figure 4. most frequent concepts. Of the sample of 2926 keywords, 176 keywords are shown in Figure 4. Figure 4. Co-occurrence analytical map of keywords created in the ﬁrst dataset. With the minimum Figure 4. Co-occurrence analytical map of keywords created in the first dataset. With the minimum number of co-occurrence set as ﬁve, a total of 176 keywords out of the sample of 2926 keywords are number of co-occurrence set as five, a total of 176 keywords out of the sample of 2926 keywords are shown. (a) All keywords co-occurrence network map; (b) scheduling co-occurrence network map; (c) shown. (a) All keywords co-occurrence network map; (b) scheduling co-occurrence network map; (c) risk assessment co-occurrence network map. risk assessment co-occurrence network map. Figure 4 shows that risk management has become more important in recent years. This also shows Figure 4 shows that risk management has become more important in recent years. This also that the recent publications may tend to oer suggestions to monitor and prevent delay. In addition, shows that the recent publications may tend to offer suggestions to monitor and prevent delay. In it shows that using questionnaire surveys is the traditional method of delay analysis. Figure 5 also addition, it shows that using questionnaire surveys is the traditional method of delay analysis. Figure shows the key concepts used in the DEC database (with questionnaire surveys being a dominant method from 2014) and that risk management has become a focus in literature more recently. Buildings 2019, 8, x FOR PEER REVIEW 8 of 36 5 also shows the key concepts used in the DEC database (with questionnaire surveys being a Buildings 2019, 9, 191 8 of 37 dominant method from 2014) and that risk management has become a focus in literature more recently. Figure 5. Co-occurrence analytical map of keywords created on the ﬁrst dataset. With the minimum Figure 5. Co-occurrence analytical map of keywords created on the first dataset. With the minimum number of co-occurrence set as ﬁve, a total of 25 keywords out of the sample of 550 keywords are shown. number of co-occurrence set as five, a total of 25 keywords out of the sample of 550 keywords are 4. Content Analysis and Data Mining shown. This section critically reviews the content of the DEC dataset by investigating topics, keywords, 4. Content Analysis and Data Mining and themes. First, the entire DEC dataset was grouped into ﬁve main clusters with each cluster against This section critically reviews the content of the DEC dataset by investigating topics, keywords, three criteria (the gap identiﬁcation criteria). Figure 6 shows that there were three clusters within an the d th DEC emes. dataset First, based the enti on re the DEC wor d dasimilarity taset was of gro the upe articles, d into f which ive ma wer in clu e separately sters withanalysed each cluusing ster against three criteria (the gap identification criteria). Figure 6 shows that there were three clusters thematic analysis techniques. Based on the results and the similarity of the words, the papers were wi assigned thin the DEC into ﬁve data clusters. set based The onDEC the wo dataset rd sim could ilarity also of th bee classiﬁed articles, wh based ich were on these sepa ﬁndings. rately an A aly car sed eful using thematic analysis techniques. Based on the results and the similarity of the words, the papers content analysis showed that there were at least three dierent types of ﬁndings within the DEC were dataset: assig(i) ned the inﬁrst to five group clusof terpapers s. The DEC investigating dataset ccauses ould als of o delay be class [70 ifie ], e d ba ects sed of odelay n these [71 fin ], d mitigation ings. A careful content analysis showed that there were at least three different types of findings within the strategies, and/or all causes and eects with appropriate mitigation strategies [72,73]; (ii) the second DEC group data investigating set: (i) the first the e gro ect up of ofone pape special rs inve factor stigat on ing delay causes [74o ];f (iii) dela the y [thir 70],d ef gr fec oup ts o pr f oposing delay [71 and ], mitigation strategies, and/or all causes and effects with appropriate mitigation strategies [72,73]; (ii) evaluating methods and/or models for identifying, ranking, and estimating delays [75]. the second group investigating the effect of one special factor on delay [74]; (iii) the third group proposing and evaluating methods and/or models for identifying, ranking, and estimating delays [75]. Buildings 2019, 9, 191 9 of 37 Buildings 2019, 8, x FOR PEER REVIEW 9 of 36 Cluster 1 Cluster 2 Cluster 3 Figure 6. Five branches of papers in the DEC, including three clusters of the main relevant articles for Figure 6. Five branches of papers in the DEC, including three clusters of the main relevant articles for the content analysis. the content analysis. 5. Current Practices in Delay and Time Overrun Investigations Buildings 2019, 9, 191 10 of 37 5. Current Practices in Delay and Time Overrun Investigations Buildings 2019, 8, x FOR PEER REVIEW 10 of 36 We ﬁrst investigated the publications in the past three years to identify the current practices in We first investigated the publications in the past three years to identify the current practices in this ﬁeld. Tables 3–5 show that most of them used questionnaires and focused on developing countries, this field. Tables 3, 4, and 5 show that most of them used questionnaires and focused on developing and Figure 7 shows word clouds created for dierent sources based on stemmed words. countries, and Figure 7 shows word clouds created for different sources based on stemmed words. (a) (b) (c) (d) (e) (f) Figure 7. Word cloud created for dierent sources based on stemmed words. (a) All DEC dataset; Figure 7. Word cloud created for different sources based on stemmed words. (a) All DEC dataset; (b) (b) cluster 1; (c) cluster 2; (d) cluster 3; (e) published papers from 2009 to 2011; (f) published papers cluster 1; (c) cluster 2; (d) cluster 3; (e) published papers from 2009 to 2011; (f) published papers from from 2016 to 2018. 2016 to 2018. Table 3. Summary of selected articles of cluster 1 of delay investigations from 2015 to 2018. Table 3. Summary of selected articles of cluster 1 of delay investigations from 2015 to 2018. Focus of the Study, Method; Sample Size Number of Examined Delay Factors and Method; sample Location, and Sector and Participants List of the Selected Factors Identiﬁed Focus of the study, Number of examined delay factors and list of the size and Questionnaire; 30; 24, inexperienced workforce, shortage of location, and sector selected factors identified Prioritize delay factors [76], participants academics, clients, structural connections for prefabricated China, prefabricated Prioritize delay factors Questionnacontractors, ire; 30; and 24, inexpecomponents, rienced workf poor orce, communication shortage of str among uctural concrete building government. participants, and low productivity. [76], China, academics, clients, connections for prefabricated components, poor prefabricated concrete contractors, and communica 78, tio client-r n amo elated ng pacauses, rticipan labour ts, and and low Comparative delay analysis Questionnaire; 175; equipment causes, contractor-related building government. productivity. techniques with the Society clients, consultants, and causes, material-related causes, Comparative delay of Construction Law’s (SCL) 78, client-related causes, labour and equipment causes, contractors design-related causes, external causes, and analysis tec pr hotocol niques [72 wi ],th Iran Questionnaire; 175; consultant-related causes. contractor-related causes, material-related causes, the Society of clients, consultants, design-related causes, external causes, and consultant- Construction Law’s and contractors related causes. (SCL) protocol [72], Iran Fuzzy assessment model 83, inexperienced contractor, poor project planning and Interviews to estimate the scheduling, weak supervision and site management, questionnaire; 64; probability of delay [77], changes in design, unreliable subcontractors, consultants, Turkey, public and inexperienced labour, changes in orders, slowness in site contractors private delivery, late design documents approval, delay in Buildings 2019, 9, 191 11 of 37 Table 3. Cont. Focus of the Study, Method; Sample Size Number of Examined Delay Factors and Location, and Sector and Participants List of the Selected Factors Identiﬁed 83, inexperienced contractor, poor project planning and scheduling, weak supervision and site management, changes in design, Fuzzy assessment model to Interviews questionnaire; unreliable subcontractors, inexperienced estimate the probability of 64; consultants, labour, changes in orders, slowness in site delay [77], Turkey, public contractors employees, delivery, late design documents approval, and private and designers delay in payment, material delivery, weak communication and coordination between parties, and unqualiﬁed team. Payment, project ﬁnancing, cash ﬂow, Finance and delays [78], Questionnaire; 78 economic issues, project planning, and cost Ghana, highway project control. Delayed approval, design and scope changes, Structural equation model poor protocol and subcontractor changes, Questionnaire; 77; clients, for investigating factors technical ability of head contractor, contractors and aecting delay [79], India, scheduling, labour productivity, weather designers or architects public conditions, proper planning and controlling of projects. 73, problems in funding (75%); poor site management (66%); weak project planning Time overrun model by Questionnaire; 90, (58%). Owner: values of contract (70%); late using fuzzy logic [80], Iraq, owners, consultants, decision-making (63%); contract duration private and government supervising engineers (61%). Consultant: design delays and design sectors and contractors mistakes (46%); improper design management (45%). External: topographic characteristics of site (41%). 72, inadequate fuel, inadequate contractor Questionnaire; 45; clients, cash-ﬂow, inadequate foreign currency, Causes of delay [81], Malawi, contractors and payment, inadequate equipment, inadequate road consultants materials, inadequate technical workforce, and site mobilization slowness. 35, ﬁnancial diculties, subcontractor ’s weak Prioritize delay factors [30], performance, material provision, drawing Questionnaire; 175; Benin, public projects: changes, scheduling by contractor, late contractor, owner, departmental hospital, inspections by the consultant, unavailability consultant and architect school, administration oce of equipment by contractor, and acceptance of improper design drawings. 89, ﬁnancial issues are the major delay factors, Causes of delay [36], Questionnaire; 35; as well as drilling allowance, long Khuzestan, Iran, steel owners, consultants and administrative cycle to renew, and steady company contractors production of steel. 50, ﬁnancial issues, policies and weakness of laws, competence of project management, Risk analysis of schedule Questionnaire; 246; ﬁnancial ability and management of delays using a structural project managers, contractor, competence of design team, equation model [82], supervisors, from sub-contractor ’s selection and management, Vietnam, highway projects contractors and owners economical changes, and competence of supervision team. Buildings 2019, 9, 191 12 of 37 Table 3. Cont. Focus of the Study, Method; Sample Size Number of Examined Delay Factors and Location, and Sector and Participants List of the Selected Factors Identiﬁed Uncertainties and changes, regulation Delay causes for BOT Workshop; 11; variation, budget shortage, changes in orders, Projects [70], Turkey, consultants, the private changes in urban plan, changes in policy and public–private partnership sector, and the public regulations, lack of bidder, inadequate laws projects (PPP) sector about usage of land, ﬁnance. A method for risk managers to address Climate and construction climatic agents and required extra time to Case study; 6; bridges delays [83], Chile, bridge minimize adverse weather conditions and time delays. 180, unreal duration imposed by clients, Questionnaire; 208; unﬁnished design, change orders, scheduling, Proﬁling causative factors clients, consultant and weak project control, slow permission process leading to delays [84], UAE contractors from authorities, low labour productivity, delays in decisions, poor site management. 36, ﬁnance shortage, weak planning, weak Questionnaire; 400; Analysis of delays using site management, unavailability of material, clients, contractors and transaction cost economics unpredicted site condition, delays in test consultants using (TCE) approach [85], approvals, preparation of drawings, Structural Equation Tanzania communication between parties, skills Modelling shortage, availability of equipment. Table 4. Summary of selected articles of cluster 2 of delay investigations from 2015 to 2018. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants 37, delayed payments, low bids, weak Delay analysis [86], China, performance of subcontractors, and Questionnaire; 115; Beijing, Shanghai, communication issues. Comparative analysis clients, consultants, and Chongqing and Shenzhen, shows diculty in claiming penalty and contractors Design-bid-build projects unreasonable upfront capital demanded by client. Lack of experienced managers, lowest bidder, Delays [87], Bangladesh, Interviews; 70; shortage of fund, scheduling, lack of skilled privately funded large stakeholders labour, site constraints, weak cost control, and building contractor cash ﬂow problem. Building material, rerouting electrical and Interviews; 14; project Delay Factors [88], Mataf, mechanical utilities, safe access, conditions of and construction Mecca, Saudi Arabia, site, taking down archaeological and managers and senior site reconstruction project antiquity elements, back-propping works, engineers design changes, conﬂict between workforce. 26, improper funding cost, mistakes or Schedule delay [89], Questionnaire; architects, negligence in consultant material quality, and Denmark, public surveyors mistakes. 66, using qualiﬁed and experienced managers, Questionnaire; 100; A framework to reduce using suitable and enough tools and people engaged in delays [73], Sudan, road equipment, and suitable technical planning construction before starting the projects. Identiﬁed eects are time overrun, cost The eect of delays [71], Questionnaire; 256; overrun, and blockage of economic and Libya, Tripoli, road stakeholders country development. Buildings 2019, 9, 191 13 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Weak scheduling, poor decision process, The top 10 universal delay Questionnaire; 202; internal administrative procedures and factors [90], Norway, clients, contractors and bureaucracy, poor resources, weak parties’ hospitals, schools, hotels, etc. consultants communication, slow inspection, changes, parties’ lack of commitment and goals. 59, delays in utility services (such as power A model of delay factors [91], Questionnaire; 256; lines, water, etc.), project budget diculties, Libya, road stakeholders short duration, delayed payments, and subsurface condition impacts conditions. Project ﬁnancial diculties, improper planning and scheduling, contractor ’s poor A dynamic model of Questionnaire; 100; communication and coordination, conﬂict contractor-induced delays Project managers, between parties and use of improper methods [92], India, buildings, roads, architects, engineers, for construction, providing enough project bridges, railways, power designers, consultants, ﬁnances and cash ﬂow, proper planning and plants, and industrial surveyors, contractors, scheduling, using proper methods for complex projects and owners construction, and considering the reworks in the schedule. 58, reworks, suspension of construction, A hybrid System Dynamics- delayed payment, poor project planning and Decision Making Trial and Questionnaire; 63; scheduling, labour ’s low productivity, Evaluation Laboratory consultants, contractors, changes in orders, and construction mistakes, (SD-DEMATEL) approach to and clients costs of implementation, acceleration in develop a delay model [93], conduction of biding, and notiﬁcation of Iran contract and schedule pressure. 31, identiﬁed factors are manpower (21% of Time overrun risks [94], Questionnaire; 112; contribution), materials (18% of contribution), India, residential, industrial, project managers and scheduling and control related problems and commercial (18% of contribution). Poor communication, late payment, weak Aggregation of factors controlling, delays in decisions, changes in causing cost overruns and order, reworks, weak labour and material Analysis of a literature time delays: trends and planning, equipment shortage, project selection implications [95], large complexity, psychological positive interest, public projects fraud, bad weather conditions, and ground conditions. 9, ﬁnancial limitation by government, weak Beyond the causes: supervision and project planning, change rethinking mitigating Check list; 7; quantity orders, insucient allowance of contingency, measures to avert cost and surveyors, architects, and weak administration of contract, qualiﬁes time overruns [96], Ghana, engineers team of project, poor coordination, risk public related to cultural and political issues. 31, materials shortage, unreal scheduling, late material delivery, labour shortage, project Causes of delay [97], Questionnaire complexity, delayed payment, weak site Cambodia, residential management, delay by subcontractor, and accidents because of weak site safety. 6, Indian: market culture, large delay due to Organisational culture in Questionnaire; 84; contractors. US: clan culture, less delay due to delay [74], US and India contractors owners. Buildings 2019, 9, 191 14 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Delayed payment, inexperienced contractor, Questionnaires; 123; Exploring critical delay scope changes, delayed furnish and site stakeholders and site factors [29], Ghana, road delivery to the contractor, and inﬂexible sta funding. 75, low bid, main contractor ’s ﬁnancial condition, delays in making decisions by The causes, impacts and Questionnaire; 53; clients, client, and weak planning by the main mitigations of delay [98], consultants, and contractor. Eects are extra cost and time Oman, Sultanate, contractors overrun. Mitigation: experienced contractors megaprojects and consultant, proper planning, and suitable supervision. 32, insucient planning, poor information ﬂow and communication, poor decisions, The professionals’ ineective management, poor control, Interviews; 41; seniors of perspectives on the causes of ﬁnancial problems, unclear scopes, design developers, consultants, project delay [99], UK, all problems, inappropriate risks transfer, lack of clients, and contractors sectors knowledge and competence, health and safety restrictions, poor resources and logistics management Delayed payment to contractor or supplier, inﬂation and price ﬂuctuation, price growth Questionnaire; 31; Analyzing delay causes and in materials, insucient funds of sponsors or architects, surveyors, eects [100], Ghana, state clients, changes in orders, and weak ﬁnancial engineers, managers, housing or capital market. Identiﬁed eects are cost land economists overrun, time overrun, litigation, discontinuity by client, and arbitration. 44, weak supervision, contractor ’s insucient Causes of delay [27], Gulf Questionnaire; 59; clients, planning and scheduling, delay in delivery of cooperation council contractors, and materials, poor communication among countries (Oman), oil and consultants project parties, and weak interaction with gas industry vendors. Suggested to validate ﬁndings. 65, safety measures, laws and bureaucracy variations by government, holidays, lowest Questionnaire; 134; bidder weak performance, changes in design Causes of delay [101], Iraq, clients, contractors, and by owner and consultants, delayed payments public consultants by the owner, problems with local community, inexperienced owner in construction and economic and local and global conditions. 35, lower bid, changes in material, Risk matrix for delay Causes Questionnaire; 51; management of contract, contract duration, [102], Saudi Arabia consultants ﬂuctuations in materials’ price, changes in design, weak planning, pressure of inﬂation. 64, working during rainy season, ﬂooding, Analyzing delays: causes Questionnaire; 153; eect on people’s land, lowest bidder and eects [103], Cambodia, contractor and consultant selection, repeated breakdowns of equipment, road weak site arrangement. Buildings 2019, 9, 191 15 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Extreme weather, site blockage, corruption, war, labour ’s low productivity, custom Causes of delays [104], clearance issues, changing in route of supply countries with high Window delay analysis chains, materials stealing; natural dangers, geopolitical risks, power method (detailed review late approvals, change orders, design transmission lines, of 36 projects), interviews mistakes, obscure work scope, cash ﬂow, infrastructure (utilities) and with 18 experts rental equipment inadequacy, delays in site roadway ownership, inadequate owner ’s site utilities, changing in supply chains. 35, ﬁnancial diculties, absence of Delay factor analysis [105], Questionnaire; 197 responsibilities, changes in design, and Vietnam, hospital inexperienced contractor. 27, contractor ’s ﬁnancial ability, owner ’s Empirical study of factors Questionnaire; 140; ﬁnancial diculties, availability of equipment inﬂuencing schedule delays clients, contractors, and by contractor, delayed payment for ﬁnished [106], Burkina Faso, public consultants work, and weak performance of subcontractor. 293, political situations, segmentation of the Questionnaire; 186; west bank and limited movements between Exploring delay causes [107], consultants, contractors, areas, award project to lowest bid price, Egypt, road and engineers progress payment delay by owner, and shortage of equipment. 45, manpower shortage, late approvals, Factors aecting delays [108], Questionnaire; 120; materials shortage, and relation between Jordan, private stakeholders dierent subcontractors. Weak communication, slowness of material Delay factors [109], Malaysia, Interviews; 10; contractor delivery, wrong selection of contractor, low Perak, Vale minerals project and client sta productivity, weak management, and equipment mobilization. Delay and cost overrun [110], Regulation (31%), owners (27%), consultant Questionnaire; 86 Iran (25%), and contractor (17%). Risk and relationship Environmental issues, resource issues, and Questionnaire; 212; between delay factors [111], coordination issues. Suggests longitudinal stakeholders Malaysia study and speciﬁc infrastructure projects. 112, ﬁnance issues, non-payment for Causes of delays [112], Saudi Questionnaire; 86; contractor claims, inexperienced contractor, Arabia, public stakeholders weak scheduling, delay in decisions and approvals, lack of material and labours. Finance diculties, economic and payments Cost escalation and schedule Questionnaire; 60; problems, materials preparation, contract and delays [113], Zambia, road stakeholders drawing changes, inadequate stang and equipment, weak supervision. 110, strikes and closures of border, shortages Delays and cost overruns Questionnaire; 114; of materials in markets and in delivery to the [114], Gaza Strip stakeholders site. Financial-related causes Questionnaire and Cash ﬂow, inadequate ﬁnancial resources, contributing to project delays interviews; 110; loan gaining diculties, and inﬂation. [115], Malaysia stakeholders 52, political situation, lowest bidder, payment Questionnaire; 64; Causes of delay [116], and inadequate equipment; improper ground contractors and Palestine, road condition, inadequate controllers, unsuitable consultants design, natural hazards. Buildings 2019, 9, 191 16 of 37 Table 4. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants 34, changes in design and material, delayed Questionnaire; 71; project Causes of delays [117], payments, problems in cash ﬂow, contractor ’s managers and site Turkey problems in ﬁnance, and low labour managers productivity. Questionnaire; 17; 34, risks associated with reduced site Leadership in Energy disturbance, innovative waste water Cost and time overrun and Environmental technologies, renewable energy, waste analysis [118], India, green Design (LEED) management, indoor chemical and pollutant construction projects professionals and other source control, and LEED— accredited green experts professional. Schedule delay causes [119], Case study; 79 litigation Change in orders and scopes, late handover Taiwan cases of site, and weather. Time performance [120], Planning, subcontract, materials, labour, Residential case study; 2 Santiago, Chile design, execution, and weather. Suggests connecting the function of Delays, penalties, and project Phone interviews; 30; marketing with project management, but it quality [121], Slovenia managers, questionnaire reports that marketing management does not minimize ﬁnes and delays. Causes of delays and cost Interview, case study; Variations in work scope, delays in payments, overruns [122], Uganda, questionnaire; 247; weak control and monitoring, capital’s high public stakeholders cost, political ﬂuctuation, and insecurity. 43, material, cost, and currency variations, Analyzing delay causes Questionnaire; 33; ﬁnancial, site condition, inexperienced [123], Egypt stakeholders consultants, ﬁnancing, low productivity, incompetent workforce, and change orders. Design [124], Taiwan, Questionnaire; 36; 21, decision making and budget constraints, high-tech facility engineers managers design duration. 28, ﬁnancial issues, inappropriate planning, Questionnaire; 84; Causes of delays [35], Iran site and contract management, and poor stakeholders communication Table 5. Summary of selected articles of cluster 3 of delay investigations from 2015 to 2018. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants This article proposes a method that is a tool for Productivity and delay A new method and a calculating the schedule impacts that happen analysis [125] case study when there is a problem in lost productivity. Analysis eects of delays on the critical path that Critical path eect based Hypothetical case performs delay analysis accurately and uses a delay analysis method [126] studies process-based analysis approach to solve simultaneous delays. Improper design and owner ’s neglect, changes in Arbitration awards, Factors inﬂuencing delay orders, weather and site conditions, delayed court cases, and claims [127], India delivery, economic conditions, and quantity professionals growth. Understanding construction In-depth interview; Complexity, cost, and time. Emphasizes the delay analysis and the role of experienced importance of baseline programs for resolving preconstruction construction planning delay claims. programming [128], UK engineers Buildings 2019, 9, 191 17 of 37 Table 5. Cont. Focus of the Study, Method; Sample Size Number of Factors Measured and Findings Location, and Sector and Participants Client’s attitude, experience of the delay analyst, reputation and neutrality of the delay analyst, Factors inﬂuencing the project complexity, and cost and timing of selection of delay analysis Interviews; 8; experts; performing the analysis. Time Impact analysis method [129], UAE, a hotel, limited to case studies (TIA) and Impacted as Planned (IAP) are two an international school in the period of commonly used Delay Analyzing Methods complex, a highway, sewage 2007–2012 DAMs. The ethnographical approach is treatment plant, and a suggested, since it provides the opportunity to residential tower capture real and live states of knowledge on the selection and the use of DAMs. Visualisation of delay claim This article shows that 4D simulation is a reliable analysis using 4D simulation method for analyzing delay claim. [130] This article proposes the Stochastic Delay Analysis and Forecast (SDAF) method, which is Stochastic delay analysis and Shi’s method an informative analytical method and predicts forecast method [131] the eect of a single activity’s delay with probability for overall project delay. Semi structured Decision-making model for This article proposes the Digital Multimeter interviews and selecting the optimum (DMM) objective tool, which can reduce the questionnaire; 74; method of delay analysis potential for disputes and conﬂicts arising from contactors and [75], UAE, Dubai delays in construction projects. consultants Key Factors Identiﬁed in the Delay Literature Tables 5–7 show a comprehensive list of factors and the priority of each factor in Asian and African countries. This helps us to understand the importance of current factors in the literature. These two tables are also used for identifying the frequency and the median of each factor. Most of the articles extracted a number of delay factors from the literature. Next, they evaluated each factor or validated them in their context by conducting a survey, and they ﬁnally presented the top ranked factors. For example, Al-kharashi and Skitmore [112] identiﬁed 112 delay factors from literature. Then, they conducted a survey and presented the 30 important factors from the results. Al-kharashi and Skitmore [112] reported only ten factors out of 30 and reported them in the abstract of their paper. Thus, this paper reported the top ten factors reported by them. Among the DEC dataset, only 63 articles included the causes/main cause of delay. A total of 55 articles were investigated in a certain region or country, which are presented in Tables 5–7. Buildings 2019, 9, 191 18 of 37 Table 6. Priority list of delay factors within DEC literature for Asian countries, mainly Middle Eastern. India Bangladesh Saudi Arabia Iraq Turkey Iran UAE Oman Jordan Palestine Factors 18 20 26 66 76 6 7 41 54 13 38 15 40 63 19 51 44 30 37 32 49 56 62 [92] [94] [74] [79] [127] [87] [88] [102] [112] [80] [101] [70] [77] [117] [93] [110] [36] [84] [27] [98] [108] [114] [116] Scheduling issues + 3 2 5 + + 7 2 4 1 4&5 3 4 4 Payment delay + + 6 6 2 3 4 Design changes 1 1 1 + 5 + 4 1 8 Manpower issues 1 6 + + 7 10 8 1 Financing diculties + 4 + 3 3 1 Poor supervision 1&4 + 3 3 12 9 1 Lack of materials 2 5 5 5 3 2 Contractor cash ﬂow 10 + 1 4 5 3 2 Poor communication + + 6 Owner cash ﬂow 3 + Subcontractors 6 6 2 2 4 Change orders 4 + 9 6 3 Equipment issues 5 14 5 Natural risks 5 2 8 Labour productivity 2 + 5 5 6 Culture and politics + 1 1&2 Approval delays 1 4 + 7 4 6 2 Resources shortage 3 1 Economic conditions 9 Lowest bidder 2 + 1 3 Design problems 1 Delay in site delivery 1 + 10 Late change issues 2 2 Contract issues + 2 4 Security 2 1 Inﬂationary issues + 10 Lack of protocol 1 Inaccurate pricing + 4 + 6 Cost control 9 10 Estimation issues 7 5 1 Note: design problems are a general factor that contain items such as errors in drawings and improper/inadequate design documents. Buildings 2019, 9, 191 19 of 37 Table 7. Priority list of delay factors within DEC literature for selected Asian countries. Cambodia Malaysia Taiwan Palestine China Vietnam Factors 24 42 50 52 57 59 67 56 62 3 5 29 31 46 [97] [103] [109] [111] [115] [132] [119] [114] [116] [76] [86] [133] [82] [105] Scheduling issues 2 1 Payment delay 7 10 2 4 1 Design changes 2 2 5 Manpower issues 4 9 1 4 Financing diculties 3&6 + Poor supervision 8 7 5 3 8 Lack of materials 3&1 2 2 Contractor cash ﬂow 4 Poor communication 1 3 2 4 2 Owner cash ﬂow 5 1 Subcontractors 9 3 3 Change orders 1&4 1 Equipment issues 5 1 Natural risks 2 1 4 Labour productivity 11 4 3 Culture and politics 1 1&2 Approval delays Resources shortage 6 2 Economic conditions 7 Lowest bidder 4 3 2 Design problems Delay in site delivery 3 Late change issues Contract issues Security 10 Inﬂationary issues 7 Lack of protocol 2 Inaccurate pricing Cost control Estimation issues Based on the information collected from Tables 6–8, the frequency and the median of each factor were calculated. Table 9 shows that the most frequent factors contributing to project delay are scheduling issues, payment delay, design changes, manpower issues, and ﬁnancing diculties. Uganda; 72 [122] Benin; 70 [30] Malawi; 69 [81] Denmark; 8 [89] Zambia; 55 [113] Burkina Faso; 47 [106] 73 [123] Egypt 48 [107] Chile [120] UK; 33 [99] 61 [134] US 26 [74] 28 [78] 36 [100] Ghana 27 [29] 23 [96] Tanzania; 22 [85] Norway; 12 [90] Libya; 17 [91] Sudan: 1 [73] Buildings 2019, 9, 191 20 of 37 Table 8. Priority list of delay factors within DEC literature for African and other countries. Factors Scheduling issues + 2 2 + 1 1 6 Payment delay 4 1 1 + 4 3 4 1 4 2 Design changes + 3 5 10 9 5 1 Manpower issues 3,5 9 6 4 9 7 9 Financing 1 2 1,4 5 5 + 6 1 4 diculties Poor supervision 2 3 2 4 9 Material issues 4 3 1 5 7 4 Change orders + 3 8 5 2 9 Contractor ’s 9 + 7 1 2 2 1 ﬁnancial problems Poor 4 + 8 7 2 11 communication Owner ’s ﬁnancial 1 4 + 3 2 2 2 problem Subcontractors 2 5 3 Equipment issues 10 5 3 8 5 8 Approval delays + 6 7 Natural risks 5 + 6 Labour productivity 8 Culture and politics 8 + 5 Resources shortage + 5 Economic conditions + 2 2 4 3 Lowest bidder 3 Delay in site delivery Drawing issues + 7 6 Contract issues 5 3 Security Inﬂationary issues 2 Lack of protocol + 10 Inaccurate pricing Controlling 5 3 Estimation issues 3 Buildings 2019, 9, 191 21 of 37 Table 9. Summary of important factors including frequency and median. Source Issue (Cause) Description Reference Frequency * Median (Article) Improper resource planning, inaccurate Scheduling budgeting, procurement, unreal 81 1769 25 2 scheduling Payment delay Delays in payment to labours/contractor 58 764 21 3.5 Design and scope changes/lack of clarity Design 77 1697 20 3.5 (by owner, contractor, or architect) Using unqualiﬁed personnel, lack of skilled workers/designers, poor Manpower issues 70 990 20 6 qualiﬁcation of the technical sta, stang problems Cash ﬂow problems, inﬂexible funding, Financing and cash insucient contingency allowance, 60 466 19 3.5 ﬂow loan gaining problems, ﬁnancial disputes, capital high costs, penalties Lack of experienced construction Supervision 53 281 18 4 managers, poor supervisor Material change, late delivery, Material 76 1358 16 3 unavailability and lack of materials Change order Design problems (by owner or others) 18 54 16 3 Contractor ’s Cash ﬂow/funding problems 15 4 ﬁnancial problems Communication Poor coordination, poor team working 59 357 15 2 Owner ’s ﬁnancial Cash ﬂow/funding problems 12 3 problems Unreliability, delays, being Subcontractor 56 361 11 4 inexperienced Using inappropriate and inadequate Equipment 69 888 11 5 tools and equipment, : : : Approval delays in submission and Approval inspection process of design, materials, 67 366 11 5 completed work Natural dangers (environmental related issues, extreme weather conditions, Natural risks 33 77 10 5 ﬂooding, precipitation, temperature, soil temperature, and wind velocity) Labour - 41 124 10 2 productivity Organisational culture, war, strikes and Culture and closures of border, political ﬂuctuations, 55 510 8 6 politics restricted movement between areas Resources shortage, inadequacy/delays Resources in human resources, material and 75 617 7 3 equipment thefts Local or global economic, cost and “Economic” currency variations, inadequate foreign 75 634 7 3.5 conditions currency to import materials and equipment Lowest bid Select lower bidder 15 30 7 2.5 Delay in site Late delivery/ handover of site 3 8 5 3.5 delivery Late/unﬁnished/changes issues of Drawing 58 292 5 4 drawing Weak contract management, wrong Contract duration of contract period, contract 31 71 5 3.5 management changes, contract values, old standards Buildings 2019, 9, 191 22 of 37 Table 9. Cont. Source Issue (Cause) Description Reference Frequency * Median (Article) Weak site safety, health restriction, Security 25 85 4 2 alternative safe access Inﬂation pressure, lack of attention to Inﬂationary 2 7 4 7 inﬂation Lack of severe organisational Protocol 14 54 4 2 protocol/policy directives/ strategies Wrong pricing and bidding, low Pricing 59 423 4 5 performance of bidder, lack of bidder Improper monitoring and Controlling 71 471 4 7 controlling/cost control Estimation Inaccurate time and cost estimation 71 442 4 4 Diculties in obtaining work permits Permits 38 161 4 4 (drilling permits or tests) Note: * frequency refers to the number of occurrences that the issue presented by researchers as an important cause of delay in the DEC dataset; the order of issues is based on the frequency values. Source refers to the number of papers mentioned in the selected issue; reference refers to the frequency of the selected issue within the DEC dataset; median refers to the value separating the higher half of the important factors presented as important in the DEC datasets by researchers. Unique factors (with the frequency of three or less) are: “‘Slow decision making process by owner” in Norway [90], UAE [84], and Oman [98]; “Changes in material types and speciﬁcations during construction” in Saudi Arabia [102], Turkey [117], and Zambia [113]; “Change/selection of subcontractors in the project” in India [79], Saudi Arabia [112], and Vietnam [105]; “Mobilization delay” in India [127], Malaysia [109], and Malawi [81]; “Site constraints (site blockage, impact of other ’s land)” in Bangladesh [87], Cambodia [103], and countries with high geopolitical risks [104]; “Impact of subsurface (underground) conditions” in Libya [91], Cambodia [103], and Egypt [123]; “Conﬂict between parties’ in Iran [101], Turkey [70], and Egypt [107]; ”Errors in construction” in Iran [93], Zambia [113], and Denmark [89]; “Fluctuation in price of materials” in Saudi Arabia [102] and Ghana [100]; ”Conﬂict between labours” in Saudi Arabia [88] and Zambia [113]; ”Labour strikes” in countries with high geopolitical risks [104] and Zambia [113]; ”Using inappropriate construction methods” in India [92] and Iran [110]; ”Insucient/inaccurate document preparation” in Turkey [70] and Iran [110]; “Inaccurate ﬁrst drafts/plan” in Iran [110] and Taiwan [132]; ”Delay/weak interaction due to vendor” in India [127] and Oman [27]; ”Unsuitable site location due to ignoring feasibility studies” in Iran [110] and Cambodia [103]; ”Rework (by labours, consultant’s workforce)” in Saudi Arabia [102] and Iran [93]; ”Suspension of work (by the owner)” in Saudi Arabia [112] and Iran [93]; “Slow decision making by owner” in Saudi Arabia [112] and Iran [93]; ”Owners’ experience” in Saudi Arabia [112] and Cambodia [103]; ”Consultant’s experience (competence)” in Libya [91] and countries with high geopolitical risks [104]; ”Contractor ’s experience” in Norway [90] and the UK [99]; “Project complexity” in Norway [90] and the UK [99]; ”Wrong evaluation and selection procedure (wrong selection of contractor)” in Turkey [70] and Malaysia [109]; ”Working during rainy season” in Cambodia [103]; ”Changing in route of supply chains” in countries with high geopolitical risks [104]; ”Weak management of contractor ’s schedule” in Oman [27]; ”Long time between design and construction” in Saudi Arabia [102]; ”Interference of the execution (by owner)” in Saudi Arabia [112]; ”Delays in ownership” in countries with high geopolitical risks [104]; ”Oce issues” in Norway [90]; ”User issues” in Norway [90]; ”Ocial and non-ocial holidays” in Iran [101]; ”Problems with local community” in Iran [101]; ”Unpredicted quantity growth” in Turkey [70]; ”Old cost lists’ items” in Iran [110]; ”slow steel production” in [36]; ”Poor information (lack of knowledge)” in the UK [99]; “Unsuitable commercial decisions” in the UK [99]; ”Unforeseen circumstances” in the UK [99]; ”Corruption” in countries with high geopolitical risks [104]; “Custom clearance issues” Buildings 2019, 9, 191 23 of 37 in [104]; ”Inadequate fuel” in Malawi [81]; and “Delayed compensation paid to land owners” in Malawi [81]. 6. Technology Applications for Time Control and Risk Management Scheduling issues were identiﬁed as one of the most frequent factors causing delay in projects (refer to Table 9). A good project schedule can serve as a key management tool for making decisions and predicting whether the project will ﬁnish on time and within budget. Regular updates to the project schedule are essential to record progress and identify potential problems. There are various project scheduling software systems, such as Microsoft Project, Oracle Primavera P6, Open Plan Professional (OPP), FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Smartsheet, and many other software, packages, and platforms. Each of these project schedule software options has dierent strengths, but they oer the best options for a variety of management needs. Project scheduling software has been developed to communicate what work needs to be performed, which resources of the organisation will perform the work, and the timeframes in which that work needs to be performed. The project scheduling software should reﬂect all the work associated with delivering the project on time. However, Microsoft Project, Oracle Primavera P6, and Open Plan by Deltek are the most practical, powerful, and common software in practice. Table 10 compares the strengths and the features of these three. Table 10. Project delay analysis feature comparison between Microsoft (MS) Project, Primavera P6, and Open Plan by Deltek. Delay Analysis MS Project Oracle Primavera P6 Open Plan by Deltek Feature **** *** We can update the We can update the schedule the project by ***** schedule project by updating individual task We can update project updating individual task progress. Open plan can Updating and progress by applying actual progress and then integrate with excel rescheduling for data to activities directly in a rescheduling all the Comma Separated delay analysis project or by using timesheet uncompleted tasks to Values (CSV) ﬁles to updates from the Progress start after the status date. import project status Reporter module Auto schedule is also data provided the correct available. table structure is created within Open Plan. ***** **** *** Ability to split, stretch, To handle scheduling Resource levelling is only and re-proﬁle activities conﬂicts that may occur available at a single for resource scheduling. during levelling, we can add Resource levelling project level, and MS Resources ﬁles are priorities that specify which and delay analysis Project is not able to shared across projects project or activity is levelled handle levelling when assigned at the activity ﬁrst. This module is only interdependency with level and are levelling available at Oracle another project exists. prioritise assigned at the Primavera software. activity level. Buildings 2019, 9, 191 24 of 37 Table 10. Cont. Delay Analysis MS Project Oracle Primavera P6 Open Plan by Deltek Feature **** The integrated risk management feature *** identiﬁes, categorizes, and Provides the ability to MS Project only prioritizes potential risks calculate three point considers deterministic associated with speciﬁc estimates at the activity tasks duration, and it Risk and delay work breakdown structure level, along with mean assumes the analysis (WBS) elements and and standard deviations relationships among resources. Able to create risk for early dates, late dates, tasks are deterministic, control plans and assign a and ﬂoat. Risks are then thus uncertainty analysis probability of occurrence able to be exported via is not available. and an organisational spreadsheet risk views. breakdown structure (OBS) element to risks. ***** *** Earned value can be deﬁned Earned value Earned value analysis is * at both WBS and activity management available in MS Project; Not available and needs levels. Able to compute (EVM) and delay however, Oracle to be integrated with performance percent analysis Primavera P6 can Deltek Cobra. complete and estimate to manage EVM. complete (ETC). ****: The advantage of each software across the selected features. In order to use scheduling software for project delay analysis, the following questions need to be asked before using scheduling software: What data need to be assembled as inputs to record the delay events for the update, and what methods will be used to collect the data? How often should projects be updated? Are resources local or osite? Which project teams are resources participating in? Who on each team will be gathering the information used for the project update, and with what frequency are the data updated within the schedule? Who needs to see the results of the update, and when do they need to see them? What types of information need to be generated after each update to communicate progress before the next update? The answers to these questions help determine how the project management oce, the project managers, and the project planning function uses the module to update projects. Careful details of events are developed in the project schedule to identify delays coupled with an accurate assessment of the source of the delay, thus the responsibility can be assigned. Activity late ﬁnish date is one the main components of each scheduling software to calculate schedule delays. Activity late ﬁnish date is the latest possible point in time in which the schedule activity can be completed without violating schedule constraint or delaying the project end date (PMBOK). The late ﬁnish date is the point at which the schedule activity contains no ﬂoat. Progress curves are used as a basis for comparing the schedule baseline. When the project schedule, the work breakdown structure (WBS), or both are modiﬁed through integrated change control, the progress curves are revised to indicate the new progress curve information. Figure 8 shows the ﬂoat analysis for identifying schedule delays as a basis of S-curve updates in project scheduling software. Buildings 2019, 8, x FOR PEER REVIEW 23 of 36 A good project schedule can serve as a key management tool for making decisions and predicting whether the project will finish on time and within budget. Regular updates to the project schedule are essential to record progress and identify potential problems. There are various project scheduling software systems, such as Microsoft Project, Oracle Primavera P6, Open Plan Professional (OPP), FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Smartsheet, and many other software, packages, and platforms. Each of these project schedule software options has different strengths, but they offer the best options for a variety of management needs. Project scheduling software has been developed to communicate what work needs to be performed, which resources of the organisation will perform the work, and the timeframes in which that work needs to be performed. The project scheduling software should reflect all the work associated with delivering the project on time. However, Microsoft Project, Oracle Primavera P6, and Open Plan by Deltek are the most practical, powerful, and common software in practice. Table 10 compares the strengths and the features of these three. In order to use scheduling software for project delay analysis, the following questions need to be asked before using scheduling software: • What data need to be assembled as inputs to record the delay events for the update, and what methods will be used to collect the data? • How often should projects be updated? • Are resources local or offsite? • Which project teams are resources participating in? • Who on each team will be gathering the information used for the project update, and with what frequency are the data updated within the schedule? • Who needs to see the results of the update, and when do they need to see them? • What types of information need to be generated after each update to communicate progress before the next update? The answers to these questions help determine how the project management office, the project managers, and the project planning function uses the module to update projects. Careful details of events are developed in the project schedule to identify delays coupled with an accurate assessment of the source of the delay, thus the responsibility can be assigned. Activity late finish date is one the main components of each scheduling software to calculate schedule delays. Activity late finish date is the latest possible point in time in which the schedule activity can be completed without violating schedule constraint or delaying the project end date (PMBOK). The late finish date is the point at which the schedule activity contains no float. Progress curves are used as a basis for comparing the schedule baseline. When the project schedule, the work breakdown structure (WBS), or both are modified through integrated change control, the progress curves are revised to indicate the new progress curve information. Figure 8 shows the float analysis for identifying schedule delays as a basis of S-curve updates in project Buildings 2019, 9, 191 25 of 37 scheduling software. Figure 8. Float analysis and progress curves basis for schedule delays [adopted from Management Body of Knowledge (PMBOK)]. Progress updates are used to calculate delays by using scheduling software. The network schedules are updated on a regular basis, and the agreed timings for updates are generally agreed upon within the special conditions of contract. For example, monthly updates based on the latest schedule baseline are common. Generally, the construction management team updates the schedule with a marking up of the changes from the previous month and provides these details for the project planning function to enter into the scheduling software (e.g., MS Project or Oracle Primavera P6). It is sent to the contractor ’s project controls team for review until the cut-o date. The project control manager checks and reviews the updated schedule with the project manager. Upon completion of the input work, time calculation and analysis are done within the review process as follows: Total ﬂoat consuming status compared with the previous month schedule. Critical path schedule analysis. Based on the above analysis, if problem areas are found, these are identiﬁed and reported to the project manager. The project control manager implements suggested countermeasures in conjunction with the related managers and under the project managers’ instruction. Once the project manager approves the counter measures, they are incorporated in the schedule. Close monitoring is made to meet the corrective action plan. Until a decision on the countermeasures is made, the schedule is not changed. The updated schedule is issued to each project management oce (PMO), project control department, or project manager as an updated project control for their work and for the next monthly update. When compared with the initial estimate, the updated information may indicate some variances in the scheduling basis. On the other hand, along with the project progress, schedule deviations may be detected from the initial scenario caused by various factors. 6.1. Progress Measurement Method in Scheduling Software The progress is calculated based on milestones, which are deﬁned. Each work package is weighed; this physical weight factor is calculated according to supplier contract price. The assessment of planned progress between milestones is obtained by assuming linear progress development between milestones; see Equation (1): %complete weight i=1 i %Complete = P (1) weight i=1 n Each activity weight is calculated based on an activity attribute, such as man-hours, material, or cost applied. For example, the length of time for earthwork is a function of the volume of soil cutting and ﬁlling in the speciﬁc area of the project site. Buildings 2019, 9, 191 26 of 37 6.2. Primavera P6 and Delay Analysis Schedule delay analysis is a method used to determine the extent of impact from potential delay to the agreed milestones. The schedule analysis method in Primavera P6 involves inserting additional activities indicating delays or changes into an updated schedule representing progress up to the point when a delay event occurs to determine the impact of those delay activities. Saving a project baseline plays a crucial role in delay analysis and is a fundamental step in Primavera P6 for schedule delay analysis. Figure 9 shows the baseline in the blue bar and the actual timeline in the yellow bar; as can be seen, a ﬁve-day delay in EC160 activity occurred. Buildings 2019, 8, x FOR PEER REVIEW 25 of 36 Buildings 2019, 8, x FOR PEER REVIEW 25 of 36 Figure 9. Baseline in blue bar and actual timeline in yellow bar. Figure 9. Baseline in blue bar and actual timeline in yellow bar. Figure 9. Baseline in blue bar and actual timeline in yellow bar. Primavera Primavera P6 P6 is is powerful powerful sof softwar tware e to to analyse analyse pr pro oject ject d delays, elays, sch schedule edule va variances, riances, sch schedule edule performance index, estimate to completion, and other aspects of earned value management. Figure performance index, estimate to completion, and other aspects of earned value management. Figure 10 Primavera P6 is powerful software to analyse project delays, schedule variances, schedule 10 shows the earned value feature of the Primavera P6 and respective diagrams. shows the earned value feature of the Primavera P6 and respective diagrams. performance index, estimate to completion, and other aspects of earned value management. Figure Figure 10. Earned value analysis using Primavera P6. Figure 10. Earned value analysis using Primavera P6. Figure 10. Earned value analysis using Primavera P6. In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that should have started, progressed, or finished between the previous data date and the new data date In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that in the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for should have started, progressed, or finished between the previous data date and the new data date should have started, progressed, or ﬁnished between the previous data date and the new data date in identifying the delayed activities. in the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for identifying identifying the delayed activities. the delayed activities. Figure 11. Primavera P6 Progress Spotlight. Figure 11. Primavera P6 Progress Spotlight. 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives Buildings 2019, 8, x FOR PEER REVIEW 25 of 36 Figure 9. Baseline in blue bar and actual timeline in yellow bar. Primavera P6 is powerful software to analyse project delays, schedule variances, schedule performance index, estimate to completion, and other aspects of earned value management. Figure 10 shows the earned value feature of the Primavera P6 and respective diagrams. Figure 10. Earned value analysis using Primavera P6. In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that Buildings should 2019 have , 9, s 191 tarted, progressed, or finished between the previous data date and the new data da 27 te of 37 in the Gantt Chart view. Figure 11 shows the Spotlight feature in Primavera P6 software for Figure 11. Primavera P6 Progress Spotlight. Figure 11. Primavera P6 Progress Spotlight. 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives 7. Project Schedule Delay Analysis from Project Management Methodology Perspectives 7.1. Project Management Body of Knowledge (PMBOK) Based on the guide to project management body of knowledge [135], project time management encompasses the processes required to manage the project in a timely manner. Project time management has six main processes: (1) plan schedule management; (2) deﬁne activities; (3) sequence activities; (4) estimate activity durations; (5) develop schedule; and (6) control schedule. Project Management Body of Knowledge (PBMOK) also emphasises that the schedule baseline is the pillar of delay analysis in projects. A schedule baseline is the approved project timeline upon which any actual dates and changes need to be compared with the schedule baseline for analysing the delays in the schedule model. Updating the project schedule requires maintaining the actual data for project time performance. Any change to the critical path within the schedule baseline leads to delay. In addition, project time management in construction projects needs to focus particularly on other subjects as well as resource deﬁnition, allocation and resource levelling, activities to capture contingency allowances, weightage deﬁnition, progress curves, monitoring and schedule control procedures, and conditions for owner acceptance approval [136]. 7.2. Practice Standard for Scheduling Practice Standard for Scheduling is a Project Management Institute’s (PMI’s) standard with the detailed focus on project time management processes, project scheduling models, and techniques. This practice standard expands on information contained in the PMBOK guide. The main goal of this standard is to develop schedule models that are appropriate and ﬁt for purposes of projects. This practice standard introduces schedule model creation by selecting a scheduling approach and a scheduling tool. Based on this practice standard, project work breakdown structure and project-speciﬁc data are incorporated within the scheduling technique to develop a unique schedule model. Practice Standard for Scheduling has many hints and techniques for managing delays in the project schedule. For example, when the work on an activity is delayed, it is beneﬁcial for the activity to be split into two or more activities at natural break points. In another example, lags and leads also play important roles in managing the impact of delays on the overall project schedule. In addition, assigning a ﬁnish date to the end milestone can help the project schedule to better manage delays and changes in the project master schedule [137]. 7.3. Agile Practice Guide Agile planning focuses on shorter build cycles and tangible results at frequent and incremental intervals. An important part of agile scheduling is using multiple iterations instead of shifting from one Buildings 2019, 9, 191 28 of 37 phase to another, which makes the scheduling more complex but more ecient. Scrum and Kanban are two main agile frameworks for planning. Both frameworks are used to break down the work into small and manageable pieces. For controlling the project schedule developed by agile approaches, Burndown charts are typically used. Burndown charts are the most applicable agile tracking and controlling mechanisms used by project teams. The main characteristic of a Burndown chart is tracking the remaining work overtime. Caution should be taken when using agile approach delays because rework is high. Agile planning is a suitable project planning technique for a short-term project such as a software development project but is not recommended for construction projects [135,138]. 8. Discussion and the DEC conceptual model This paper, unlike other reviews, identiﬁed critical common factors and developed the DEC conceptual model for future investigations. The present review contributes to the body of knowledge in two main ways: (i) it identiﬁes the gaps and the deﬁciency areas in the DEC literature; and (ii) it develops a conceptual model that can be used to design a questionnaire for further investigations in dierent contexts. These contributions are discussed below and are presented in Table 8 and Figure 12, respectively. Buildings 2019, 8, x FOR PEER REVIEW 28 of 36 Figure Figure 12. 12. Th The e DEC DECco conceptual nceptual mod model el incincluding luding maimain n cons constr tructs ucts of res of ources resour , pr ces, ojec pr t oject contex context, t, and and stak stakeholders. eholders. Table 10 shows that four factors were overlooked in the DEC dataset. The data analysis and In contrast to traditional investigations, the DEC model suggests that future studies should the interpretations are not always valid or reliable due to small samples of participants, low quality carefully measure the effect of new “digital tools” and technologies in delay. Sepasgozar and Davis of data, unmatched structure of the research questionnaire with the current DEC literature or the [140] discussed different technology types in construction, which can be further detailed and case class study ified ba context, sed onoverlooking their applica the tioe n ects in tiof me technology management. adoption The ef by fecall ts constr of new uction digita stakeholders, l tools and or ignoring jobsite upgraded equipment. The overlooked factor (OF) refers to the data and the lack technologies on delay have not been evaluated in the literature. Some of the key digital technologies of are evaluating listed as fo new llows technologies : in delay analysis (Table 11). For example, OF1 is the quality of data collected • Di frgi om tal questionnair design comes, muwhich nication cannot tools:be Digeneralised gital Twin, as Buil a d valid ing In ﬁnding formatio ofncritical Systems factors (BIMof ) including Revit, ArchiCAD, Navisworks, BIMx, BricsCAD, Archibus, Constructor, construction projects all over the world. In fact, a major part of the DEC dataset focuses on developing IntelliCAD, VisualARQ, Revizto; Geographic Information Systems (GIS) including QGIS, countries; still, some of them suggested more investigations to understand the project complexity at ArcGIS, and ArcMap [17]. The literature frequently reports that design mistakes, errors, dierent strategic, operational, and project levels in these countries [84]. This small dataset cannot changing orders and scopes, later approvals, and late technical decision makings were the represent all key practitioners with a real understanding of delay causes and eects. Some studies main causes of delay in different contexts [95,99,104]. recruited a limited number of respondents (less than 150), which cannot represent all projects of a • Digital communication systems: cloud-based tools, emails, smart phones, and radio country and suers from lack of validation [27]. This leads to bias in the ﬁndings of some studies. communication systems. Some studies report that the communication and the coordination In some cases, the survey participants were selected carefully, while some cases were supposed to between different parties were poor [27,95,96,99,109]. be selected randomly, but in reality, their strategy of randomness was never clariﬁed. Some of the • Digital scheduling and planning tools: Microsoft Project, Oracle Primavera P6, FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Open Plan by Deltek, Smartsheet, and other software, packages, and platforms. • Digital progress monitoring and job-site controlling tools: laser scanner [141], lidar [142–146], Internet of Things sensors, and photography camera [147]. • Digital contract management tools: intelligent or smart contracts. The literature shows that many projects suffer from weak administration of contracts [96]. • Digital devices to increase the productivity of heavy equipment: real-time locating systems, Global Positioning System (GPS), and radar. • Digital production technologies: 3D printers [148]. New questionnaires can be designed based on the factors shown in Figure 12. Future studies also should identify the relationship between different causes and their effects on delay [79]. The visibility, the real-time monitoring, and the flexibility of the project using a wider range of digital technologies may mitigate the negative effects of resource and coordination issues. In case of using advanced and digital technologies, vendors have a significant role in successful technology adoption and implementation processes in the project [149–153], which can also mitigate the negative effects of productivity and coordination issues. Appropriate interaction between contractors and vendors Buildings 2019, 9, 191 29 of 37 studies used Analytic Hierarchy Process (AHP) or SD-DEMATEL [93] questionnaires to provide a consistency ratio to increase the reliability of the ﬁndings, but these studies suer from a limited number of factors measured and a limited number of participants. The literature also suggests that comparison studies among developing countries [110] and longitudinal studies in delay analysis should be conducted to examine the relationships of factors and stakeholders in an extended period [111]. In addition, the future studies should focus on more speciﬁc types of construction projects, such as utility, highway construction, and dam construction projects, to ﬁnd proper strategies to mitigate the eects of environmental issues [111]. Table 11. Future directions based on deﬁciencies of the current delay investigations. Suggestions for Future Overlooked Factors (OF) Examples Directions (FD) FD1: mix methods using Mostly faulty surveys in-depth interviews and OF1: faulty data analysis and (questionnaires) due to size case studies; interpretations and participants FD2: investigate dierent projects such as PPP OF2: unmatched structure of the Questionnaires are FD3: a set of factors should research questionnaires with based on similar factors be developed based on a new new knowledge and standards frequently asked conceptual proven model. (e.g., PMBOK) FD4: technology adoption OF3: overlooked eect of digital The DEC database does not [139] may aect projects tools and technologies (e.g. appear to be linked to these duration and should Digital twin, Navisworks, BIM, digital technologies be investigated in GIS, and IPD) dierent contexts. FD5: the application of advanced job-site The DEC database does not OF4: ignored job-site technologies such as analyse the eect of new technologies and equipment, advanced cranes, robotics, job-site technologies and 3D printing should be investigated. Figure 12 shows the main constructions of the conceptual DEC model for analysing the causes and the eects of delay in construction projects. The key constructs are resources, project context, and stakeholders. In contrast to traditional investigations, the DEC model suggests that future studies should carefully measure the eect of new “digital tools” and technologies in delay. Sepasgozar and Davis [140] discussed dierent technology types in construction, which can be further detailed and classiﬁed based on their application in time management. The eects of new digital tools and technologies on delay have not been evaluated in the literature. Some of the key digital technologies are listed as follows: Digital design communication tools: Digital Twin, Building Information Systems (BIM) including Revit, ArchiCAD, Navisworks, BIMx, BricsCAD, Archibus, Constructor, IntelliCAD, VisualARQ, Revizto; Geographic Information Systems (GIS) including QGIS, ArcGIS, and ArcMap [17]. The literature frequently reports that design mistakes, errors, changing orders and scopes, later approvals, and late technical decision makings were the main causes of delay in dierent contexts [95,99,104]. Digital communication systems: cloud-based tools, emails, smart phones, and radio communication systems. Some studies report that the communication and the coordination between dierent parties were poor [27,95,96,99,109]. Buildings 2019, 9, 191 30 of 37 Digital scheduling and planning tools: Microsoft Project, Oracle Primavera P6, FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Open Plan by Deltek, Smartsheet, and other software, packages, and platforms. Digital progress monitoring and job-site controlling tools: laser scanner [141], lidar [142–146], Internet of Things sensors, and photography camera [147]. Digital contract management tools: intelligent or smart contracts. The literature shows that many projects suer from weak administration of contracts [96]. Digital devices to increase the productivity of heavy equipment: real-time locating systems, Global Positioning System (GPS), and radar. Digital production technologies: 3D printers [148]. New questionnaires can be designed based on the factors shown in Figure 12. Future studies also should identify the relationship between dierent causes and their eects on delay [79]. The visibility, the real-time monitoring, and the ﬂexibility of the project using a wider range of digital technologies may mitigate the negative eects of resource and coordination issues. In case of using advanced and digital technologies, vendors have a signiﬁcant role in successful technology adoption and implementation processes in the project [149–153], which can also mitigate the negative eects of productivity and coordination issues. Appropriate interaction between contractors and vendors (e.g., materials, equipment, or technology suppliers) during both design and construction phases aects delay [27]. Additional evidence is required to validate the results of surveys, which will be conducted in the future. Many delay cause factors can be explored using project evidence and digital data generated during the project, and the questionnaires used to collect participant views cannot be considered as accurate and should only be used as tools to explore delay causes and eects. However, the best way (as suggested by this paper) is to adopt a mixed method of big data generated during the project along with the questionnaire developed based on the factors presented in Figure 12. 9. Conclusions and an Agenda for Future This paper aimed to identify the most relevant papers of delay causes and eects and to develop the DEC database for future critical analysis. The content of the DEC dataset was systematically analysed using bibliographic, cluster, and thematic analyses. This paper presented the DEC literature, including key ﬁndings of delay over the years. This study carefully conducted a systematic content analysis, resulting in four main overlooked factors and deﬁciency areas, which should be addressed in the future studies. The four factors are faulty data analysis and interpretations due to small samples of participants or low data reliability, unmatched structure of research questionnaires with the current policies or standards, overlooking the eects of technology adoption by construction stakeholders, and ignoring jobsite upgraded equipment. The key deﬁciencies were identiﬁed as faulty of data analysis and interpretations due to small sample of participants or low data reliability, unmatched structure of research questionnaires with the current policies or standards, overlooking the eects of technology adoption by construction stakeholders, and ignoring jobsite upgraded equipment. The overlooked factor refers to the data and the lack of evaluating new technologies in delay analysis. For example, OF1 refers to the quality of data collected from questionnaires, which cannot be generalised as a valid ﬁnding of critical factors of construction projects all over the world. In fact, a major part of the DEC dataset focuses on developing countries. This small dataset cannot represent all key practitioners with a real understanding of the delay causes and eects. Some studies recruited a limited number of respondents (less than 150), which cannot represent all projects of a country. This leads to bias in the ﬁndings of some studies. In some cases, the survey participants were selected carefully, and in some cases, they were supposed to be selected randomly, but in reality, it is not clear what their strategy of randomness was. Some studies used AHP questionnaires to provide a consistency ratio to increase the reliability of the ﬁndings, but these studies suer from a limited number of factors measured and a limited number of participants. Buildings 2019, 9, 191 31 of 37 Author Contributions: Conceptualization and Methodology, S.M.; Formal Analysis and Investigation, all authors; Writing-Original Draft Preparation and Writing-Review & Editing, all authors. Funding: This research received no external funding. Conﬂicts of Interest: The authors declare no conﬂict of interest. Appendix A The search string was selected as “delay overrun” or “time overrun“, and ‘“construction industry” or “construction project”’ and was applied on the Scopus database using the following search criteria: ( TITLE-ABS-KEY ( delay OR “time overrun” ) AND TITLE-ABS-KEY ( “construction industry” OR “Construction project” ) ) AND ( LIMIT-TO ( DOCTYPE , “ar” ) OR LIMIT-TO ( DOCTYPE , “re” ) ) AND ( LIMIT-TO ( LANGUAGE , “English” ) ) AND ( LIMIT-TO ( SRCTYPE , “j” ) ) AND ( EXCLUDE ( PUBYEAR , 2019 ) ) AND ( EXCLUDE ( SUBJAREA , "MATE" ) OR EXCLUDE ( SUBJAREA , "MATH" ) OR EXCLUDE ( SUBJAREA , “ARTS” ) OR EXCLUDE ( SUBJAREA , “CENG” ) OR EXCLUDE ( SUBJAREA , "AGRI" ) OR EXCLUDE ( SUBJAREA , "BIOC" ) OR EXCLUDE ( SUBJAREA , “MEDI” ) OR EXCLUDE ( SUBJAREA , “CHEM” ) OR EXCLUDE ( SUBJAREA , “PHYS” ) OR EXCLUDE ( SUBJAREA , “HEAL” ) OR EXCLUDE ( SUBJAREA , “NURS” ) OR EXCLUDE ( SUBJAREA , “PSYC” ) OR EXCLUDE ( SUBJAREA , “Undeﬁned” ) ) AND ( LIMIT-TO ( PUBYEAR , 2018 ) OR LIMIT-TO ( PUBYEAR , 2017 ) OR LIMIT-TO ( PUBYEAR , 2016 ) OR LIMIT-TO ( PUBYEAR , 2015 ) OR LIMIT-TO ( PUBYEAR , 2014 ) OR LIMIT-TO ( PUBYEAR , 2013 ) OR LIMIT-TO ( PUBYEAR , 2012 ) OR LIMIT-TO ( PUBYEAR , 2011 ) OR LIMIT-TO ( PUBYEAR , 2010 ) OR LIMIT-TO ( PUBYEAR , 2009 ) ) AND ( EXCLUDE ( SUBJAREA , “ENVI” ) OR EXCLUDE ( SUBJAREA , “ENER” ) OR EXCLUDE ( SUBJAREA , “EART” ) ) The search limited to articles investigating causes and eects in the recent ten years from 2009 to 2018. Therefore, ’cause’ and ‘eect’ also were included in the following search criteria: ( TITLE ( delay OR “time overrun” ) AND TITLE-ABS-KEY ( “construction industry” OR “Construction project” ) AND TITLE-ABS-KEY ( cause OR eect ) ) AND ( LIMIT-TO ( DOCTYPE , “ar” ) ) AND ( LIMIT-TO ( LANGUAGE , “English” ) ) AND ( LIMIT-TO ( SRCTYPE , “j” ) ) AND ( LIMIT-TO ( PUBYEAR , 2019 ) OR LIMIT-TO ( PUBYEAR , 2018 ) OR LIMIT-TO ( PUBYEAR , 2017 ) OR LIMIT-TO ( PUBYEAR , 2016 ) OR LIMIT-TO ( PUBYEAR , 2015 ) OR LIMIT-TO ( PUBYEAR , 2014 ) OR LIMIT-TO ( PUBYEAR , 2013 ) OR LIMIT-TO ( PUBYEAR , 2012 ) OR LIMIT-TO ( PUBYEAR , 2010 ) OR LIMIT-TO ( PUBYEAR , 2009 ) ) AND ( LIMIT-TO ( SUBJAREA , “ENGI” ) OR LIMIT-TO ( SUBJAREA , “BUSI” ) OR LIMIT-TO ( SUBJAREA , “DECI” ) OR LIMIT-TO ( SUBJAREA , “ECON” ) OR LIMIT-TO ( SUBJAREA , “SOCI” ) OR LIMIT-TO ( SUBJAREA , “MULT” ) ) References 1. Magdy, M.; Georgy, M.; Osman, H.; Elsaid, M. Delay Analysis Methodologies Used by Engineering and Construction Firms in Egypt. J. Leg. A. Disput. Resolut. Eng. Constr. 2019, 11, 1–11. [CrossRef] 2. Soomro, F.A.; Memon, M.J.; Chandio, A.F.; Sohu, S.; Soomro, R. Causes of Time Overrun in Construction of Building Projects in Pakistan. Eng. Technol. Appl. Sci. Res. 2019, 9, 3762–3764. 3. Abdelmaguid, T.F.; Elrashidy, W. Halting decisions for gas pipeline construction projects using AHP: A case study. Oper. Res. 2019, 19, 179–199. [CrossRef] 4. Harris, P.E. Planning and Control Using Oracle Primavera P6 Versions 8, 15 & 16 PPM Professional 2016; Eastwood Harris Pty Ltd: Melbourne, Australia, 2016. 5. Chan, A.P. Time–cost relationship of public sector projects in Malaysia. Int. J. Proj. Manag. 2001, 19, 223–229. [CrossRef] 6. Assaf, S.A.; Al-Hejji, S. Causes of delay in large construction projects. Int. J. Proj. Manag. 2006, 24, 349–357. [CrossRef] 7. Bramble, B.B.; Callahan, M.T. Construction Delay Claims; Taylor & Francis US: Oxfordshire, UK, 2004. 8. Aibinu, A.; Jagboro, G. The eects of construction delays on project delivery in Nigerian construction industry. Int. J. Proj. Manag. 2002, 20, 593–599. [CrossRef] Buildings 2019, 9, 191 32 of 37 9. Vaardini, S.; Karthiyayini, S.; Ezhilmathi, P. Study on cost overruns in construction projects: A review. Int. J. Appl. Eng. Res. 2016, 11, 356–363. 10. McKay, K.N.; Wiers, V.C. Planning, Scheduling and Dispatching Tasks in Production Control; Cognition, Technology & Work: London, England, 2003; Volume 5, pp. 82–93. 11. Gasik, S. An analysis of knowledge management in PMBOK®guide. PM World J. 2015, 4, 1–13. 12. Marmel, E. Microsoft Project 2007 Bible; John Wiley & Sons: Hoboken, NJ, USA, 2011; Volume 767. 13. Van Dorp, J.; Duey, M. Statistical dependence in risk analysis for project networks using Monte Carlo methods. Int. J. Prod. Econ. 1999, 58, 17–29. [CrossRef] 14. Irizarry, J.; Karan, E.P.; Jalaei, F. Integrating BIM and GIS to improve the visual monitoring of construction supply chain management. Autom. Constr. 2013, 31, 241–254. [CrossRef] 15. Naamane, A.; Boukara, A. A Brief Introduction to Building Information Modelling (BIM) and its interoperability with TRNSYS. Renew. Energy Sustain. Dev. 2015, 1, 126–130. 16. Maguire, D.J. An overview and deﬁnition of GIS. Geogr. Inf. Syst. Princ. Appl. 1991, 1, 9–20. 17. Shirowzhan, S.; Sepasgozar, S.M. Spatial Analysis Using Temporal Point Clouds in Advanced GIS: Methods for Ground Elevation Extraction in Slant Areas and Building Classiﬁcations. Isprs Int. J. Geo-Inf. 2019, 8, 120. [CrossRef] 18. Dziadosz, A.; Rejment, M. Risk analysis in construction project-chosen methods. Procedia Eng. 2015, 122, 258–265. [CrossRef] 19. Ghassemi, R.; Becerik-Gerber, B. Transitioning to Integrated Project Delivery: Potential barriers and lessons learned. Lean Constr. J. 2011, 2011, 32–52. 20. The chartered Institute of Procurement and Supply Chain. Delays in Construction Projects; IHS Markit/Chartered Institute of Purchasing and Supply Purchasing Managers Index: London, UK, 2017. 21. Bordoli, D.W.; Baldwin, A.N. A methodology for assessing construction project delays. Constr. Manag. Econ. 1998, 16, 327–337. [CrossRef] 22. Lowsley, S.; Linnett, C. About Time-: Delay Analysis in Construction; RICS: London, UK, 2006. 23. KPMG. Climbing the Curve: 2015 Global Construction Project Owner ’s Survey. In KPMG’s 2015 Global Construction Survey; Gilge, C., Ed.; KPMG International Cooperative: Switzerland Amstelveen, Netherlands, 24. Industry Trend Analysis-PPP Failures Highlight Project Execution Risks. 2017. Available online: http://www.infrastructure-insight.com/industry-trend-analysis-ppp-failures-highlight-project- execution-risks-feb-2017 (accessed on 3 July 2019). 25. Sambasivan, M.; Soon, Y.W. Causes and eects of delays in Malaysian construction industry. Int. J. Proj. Manag. 2007, 25, 517–526. [CrossRef] 26. Beckers, F.; Chiara, N.; Flesch, A.; Maly, J.; Silva, E.; Stegemann, U. A Risk-management Approach to A Successful Infrastructure Project; Mckinsey Work. Pap. Risk: New York, NY, USA, 2013; Volume 52, p. 18. 27. Ruqaishi, M.; Bashir, H.A. Causes of delay in construction projects in the oil and gas industry in the gulf cooperation council countries: A case study. J. Manag. Eng. 2013, 31, 05014017. [CrossRef] 28. Amandin, M.M.; Kule, J.W. Project delays on cost overrun risks: A study of Gasabo district construction projects Kigali, Rwanda. Abc J. Adv. Res. 2016, 5, 21–34. 29. Amoatey, C.T.; Ankrah, A.N.O. Exploring critical road project delay factors in Ghana. J. Facil. Manag. 2017, 15, 110–127. [CrossRef] 30. Akogbe, R.-K.T.; Feng, X.; Zhou, J. Importance and ranking evaluation of delay factors for development construction projects in Benin. Ksce J. Civ. Eng. 2013, 17, 1213–1222. [CrossRef] 31. IPMD. Infrastructure and Project Monitoring Division of Ministry of Statistics and Programme Implementation; Programme implementation division of the MOSPI: Delhi, India, 2012. 32. Faridi, A.S.; El-Sayegh, S.M. Signiﬁcant factors causing delay in the UAE construction industry. Constr. Manag. Econ. 2006, 24, 1167–1176. [CrossRef] 33. Al-Khalil, M.I.; Al-Ghaﬂy, M.A. Delay in public utility projects in Saudi Arabia. Int. J. Proj. Manag. 1999, 17, 101–106. [CrossRef] 34. Falqi, I. Delays in project completion: A comparative study of construction delay factors in Saudi Arabia and the United Kingdom. Master ’s Thesis, School of the Built Environment, Heriot-Watt University, December 2004, Unpublished. Buildings 2019, 9, 191 33 of 37 35. Khoshgoftar, M.; Bakar, A.H.A.; Osman, O. Causes of delays in Iranian construction projects. Int. J. Constr. Manag. 2014, 10, 53–69. [CrossRef] 36. Saeb, S.; Khayat, N.; Telvari, A. Causes of delay in Khuzestan Steel Company construction projects. Ind. Eng. Manag. Syst. 2016, 15, 335–344. [CrossRef] 37. Zack, J.G. Schedule delay analysis; is there agreement? In Proceedings of the PMI-CPM College of Performance Spring Conference, New Orleans, NY, USA, 7–9 May 2003; Project Management Institute—College of Performance Management. 38. Ellis, R.D.; Thomas, H.R. The root causes of delays in highway construction. In Proceedings of the 82nd Annual Meeting of the Transportation Research Board, Citeseer, Washington DC, USA, 12–16 January 2003. 39. Koushki, P.; Al-Rashid, K.; Kartam, N. Delays and cost increases in the construction of private residential projects in Kuwait. Constr. Manag. Econ. 2005, 23, 285–294. [CrossRef] 40. Odeyinka, H.A.; Yusif, A. The causes and eects of construction delays on completion cost of housing projects in Nigeria. J. Financ. Manag. Prop. Constr. 1997, 2, 31–44. 41. Iyer, K.; Jha, K. Critical factors aecting schedule performance: Evidence from Indian construction projects. J. Constr. Eng. Manag. 2006, 132, 871–881. [CrossRef] 42. Sweis, G.J. Factors aecting time overruns in public construction projects: The case of Jordan. Int. J. Bus. Manag. 2013, 8, 120. [CrossRef] 43. Chan, D.W.; Kumaraswamy, M.M. A study of the factors aecting construction durations in Hong Kong. Constr. Manag. Econ. 1995, 13, 319–333. [CrossRef] 44. Semple, C.; Hartman, F.T.; Jergeas, G. Construction claims and disputes: Causes and cost/time overruns. J. Constr. Eng. Manag. 1994, 120, 785–795. [CrossRef] 45. Flyvbjerg, B.; Holm, M.S.; Buhl, S. Underestimating costs in public works projects: Error or lie? J. Am. Plan. Assoc. 2002, 68, 279–295. [CrossRef] 46. Flyvbjerg, B.; Skamris Holm, M.K.; Buhl, S.L. How common and how large are cost overruns in transport infrastructure projects? Transp. Rev. 2003, 23, 71–88. [CrossRef] 47. Ansar, A.; Flyvbjerg, B.; Budzier, A.; Lunn, D. Does infrastructure investment lead to economic growth or economic fragility? Evidence from China. Oxf. Rev. Econ. Policy 2016, 32, 360–390. [CrossRef] 48. Sepasgozar, S.M.; Li, H.; Shirowzhan, S.; Tam, V.W.Y. Methods for monitoring construction o-road vehicle emissions: A critical review for identifying deﬁciencies and directions. Environ. Sci. Pollut. Res. 2019, 26, 15779–15794. [CrossRef] 49. Zhong, B.; Wu, H.; Li, H.; Sepasgozar, S.; Luo, H.; He, L. A scientometric analysis and critical review of construction related ontology research. Autom. Constr. 2019, 101, 17–31. [CrossRef] 50. Kim, H.; Lee, H.S.; Park, M.; Ahn, C.R.; Hwang, S. Productivity forecasting of newly added workers based on time-series analysis and site learning. J. Constr. Eng. Manag. 2015, 141. [CrossRef] 51. Jung, M.; Park, M.; Lee, H.S.; Kim, H. Weather-delay simulation model based on vertical weather proﬁle for high-rise building construction. J. Constr. Eng. Manag. 2016, 142. [CrossRef] 52. Kwon, N.; Park, M.; Lee, H.S.; Ahn, J.; Kim, S. Construction Noise Prediction Model Based on Case-Based Reasoning in the Preconstruction Phase. J. Constr. Eng. Manag. 2017, 143. [CrossRef] 53. Lee, K.P.; Lee, H.S.; Park, M.; Kim, D.Y.; Jung, M. Management-Reserve Estimation for International Construction Projects Based on Risk-Informed k-NN. J. Manag. Eng. 2017, 33. [CrossRef] 54. Yap, J.B.H.; Lock, A. Analysing the beneﬁts, techniques, tools and challenges of knowledge management practices in the Malaysian construction SMEs. J. Eng. Des. Technol. 2017, 15, 803–825. [CrossRef] 55. Yap, J.B.H.; Abdul-Rahman, H.; Chen, W. Collabourative model: Managing design changes with reusable project experiences through project learning and eective communication. Int. J. Proj. Manag. 2017, 35, 1253–1271. [CrossRef] 56. Yap, J.B.H.; Skitmore, M. Investigating design changes in Malaysian building projects. Archit. Eng. Des. Manag. 2018, 14, 218–238. [CrossRef] 57. Yap, J.B.H.; Abdul-Rahman, H.; Wang, C. Preventive Mitigation of Overruns with Project Communication Management and Continuous Learning: PLS-SEM Approach. J. Constr. Eng. Manag. 2018, 144. [CrossRef] 58. Yap, J.B.H.; Low, P.L.; Wang, C. Rework in Malaysian building construction: Impacts, causes and potential solutions. J. Eng. Des. Technol. 2017, 15, 591–618. [CrossRef] 59. Abdul-Rahman, H.; Berawi, M.A.; Berawi, A.R.; Mohamed, O.; Othman, M.; Yahya, I.A. Delay mitigation in the Malaysian construction industry. J. Constr. Eng. Manage. 2006, 132, 125–133. [CrossRef] Buildings 2019, 9, 191 34 of 37 60. Alashwal, A.M.; Abdul-Rahman, H.; Radzi, J. Knowledge utilization process in highway construction projects. J. Manag. Eng. 2016, 32. [CrossRef] 61. Enshassi, A.; Abdul-Aziz, A.R.; Abushaban, S. Analysis of contractors performance in Gaza strip construction projects. Int. J. Constr. Manag. 2012, 12, 65–79. [CrossRef] 62. Enshassi, A.; Arain, F.; Al-Raee, S. Causes of variation orders in construction projects in the Gaza Strip. J. Civ. Eng. Manag. 2010, 16, 540–551. [CrossRef] 63. Enshassi, A.; Choudhry, R.M.; El-ghandour, S. Contractors' perception towards causes of claims in construction projects. Int. J. Constr. Manag. 2009, 9, 79–92. [CrossRef] 64. Enshassi, A.; Mohamed, S.; Mustafa, Z.A.; Mayer, P.E. Factors aecting labour productivity in building projects in the Gaza strip. J. Civ. Eng. Manage. 2007, 13, 245–254. [CrossRef] 65. Enshassi, A.; Mohamed, S.; Abushaban, S. Factors aecting the performance of Construction projects in the Gaza Strip. J. Civ. Eng. Manag. 2009, 15, 269–280. [CrossRef] 66. Enshassi, A.; Arain, F.; Tayeh, B. Major causes of problems between contractors and subcontractors in the Gaza Strip. J. Financ. Manag. Prop. Constr. 2012, 17, 92–112. [CrossRef] 67. Enshassi, A.; Mohamed, S.; El-Ghandour, S. Problems associated with the process of claim management in Palestine: Contractors’ perspective. Eng. Constr. Arch. Manag. 2009, 16, 61–72. [CrossRef] 68. Enshassi, A.; Kumaraswamy, M.; Jomah, A.N. Signiﬁcant factors causing time and cost overruns in construction projects in the gaza strip: Contractors’ perspective. Int. J. Constr. Manag. 2010, 10, 35–60. [CrossRef] 69. Enshassi, A.; Kochendoerfer, B.; Abed, K. Trends in productivity improvement in construction projects in Palestine. Rev. Ing. Constr. 2013, 28, 173–206. [CrossRef] 70. Budayan, C. Evaluation of Delay Causes for BOT Projects Based on Perceptions of Dierent Stakeholders in Turkey. J. Manag. Eng. 2018, 35, 04018057. [CrossRef] 71. Alfakhri, A.Y.; Ismail, A.; Khoiry, M.A. The eects of delays in road construction projects in Tripoli, Libya. Int. J. Technol. 2018, 9, 766–774. [CrossRef] 72. Shahsavand, P.; Marefat, A.; Parchamijalal, M. Causes of delays in construction industry and comparative delay analysis techniques with SCL protocol. Eng. Constr. Archit. Manag. 2018, 25, 497–533. [CrossRef] 73. Khair, K.; Mohamed, Z.; Mohammad, R.; Farouk, H.; Ahmed, M.E. A Management Framework to Reduce Delays in Road Construction Projects in Sudan. Arab. J. Sci. Eng. 2018, 43, 1925–1940. [CrossRef] 74. Arditi, D.; Nayak, S.; Damci, A. Eect of organisational culture on delay in construction. Int. J. Proj. Manag. 2017, 35, 136–147. [CrossRef] 75. Perera, N.A.; Sutrisna, M.; Yiu, T.W. Decision-making model for selecting the optimum method of delay analysis in construction projects. J. Manag. Eng. 2016, 32, 04016009. [CrossRef] 76. Ji, Y.; Qi, L.; Liu, Y.; Liu, X.; Li, H.; Li, Y. Assessing and Prioritising Delay Factors of Prefabricated Concrete Building Projects in China. Appl. Sci. 2018, 8, 2324. [CrossRef] 77. Gunduz, M.; Nielsen, Y.; Ozdemir, M. Fuzzy assessment model to estimate the probability of delay in Turkish construction projects. J. Manag. Eng. 2015, 31, 04014055. [CrossRef] 78. Edwards, D.J.; Owusu-Manu, D.-G.; Baiden, B.; Badu, E.; Love, P.E. Financial distress and highway infrastructure delays. J. Eng. Des. Technol. 2017, 15, 118–132. [CrossRef] 79. Doloi, H.; Sawhney, A.; Iyer, K. Structural equation model for investigating factors aecting delay in Indian construction projects. Constr. Manag. Econ. 2012, 30, 869–884. [CrossRef] 80. Hasan, M.F.; Mohammed, M.S. Time overrun model for construction projects in Iraq by using fuzzy logic. Int. J. Civ. Eng. Technol. 2018, 9, 2593–2607. 81. Kamanga, M.; Steyn, W. Causes of delay in road construction projects in Malawi. J. S. Afr. Inst. Civ. Eng. 2013, 55, 79–85. 82. Vu, H.A.; Cu, V.H.; Min, L.X.; Wang, J.Q. Risk analysis of schedule delays in international highway projects in Vietnam using a structural equation model. Eng. Constr. Archit. Manag. 2017, 24, 1018–1039. [CrossRef] 83. Ballesteros-Pérez, P.; del Campo-Hitschfeld, M.L.; González-Naranjo, M.A.; González-Cruz, M.C. Climate and construction delays: Case study in Chile. Eng. Constr. Archit. Manag. 2015, 22, 596–621. [CrossRef] 84. Mpofu, B.; Ochieng, E.G.; Moobela, C.; Pretorius, A. Proﬁling causative factors leading to construction project delays in the United Arab Emirates. Eng. Constr. Archit. Manag. 2017, 24, 346–376. [CrossRef] Buildings 2019, 9, 191 35 of 37 85. Sambasivan, M.; Deepak, T.; Salim, A.N.; Ponniah, V. Analysis of delays in Tanzanian construction industry: Transaction cost economics (TCE) and structural equation modelling (SEM) approach. Eng. Constr. Archit. Manag. 2017, 24, 308–325. [CrossRef] 86. Wang, T.-K.; Ford, D.N.; Chong, H.-Y.; Zhang, W. Causes of delays in the construction phase of Chinese building projects. Eng. Constr. Archit. Manag. 2018, 25, 1534–1551. [CrossRef] 87. Islam, M.S.; Suhariadi, B.T. Construction delays in privately funded large building projects in Bangladesh. Asian J. Civ. Eng. 2018, 19, 1–15. [CrossRef] 88. Khatib, B.; Poh, Y.; El-Shaﬁe, A. Delay Factors in Reconstruction Projects: A Case Study of Mataf Expansion Project. Sustainability 2018, 10, 4772. [CrossRef] 89. Larsen, J.K.; Shen, G.Q.; Lindhard, S.M.; Brunoe, T.D. Factors aecting schedule delay, cost overrun, and quality level in public construction projects. J. Manag. Eng. 2015, 32, 04015032. [CrossRef] 90. Zidane, Y.J.-T.; Andersen, B. The top 10 universal delay factors in construction projects. Int. J. Manag. Proj. Bus. 2018, 11, 650–672. [CrossRef] 91. Alfakhri, A.Y.; Ismail, A.; Khoiry, M.A.; Arhad, I.; Irtema, H.I.M. A conceptual model of delay factors aecting road construction projects in Libya. J. Eng. Sci. Technol. 2017, 12, 3286–3298. 92. Das, D.K.; Emuze, F. A Dynamic Model of Contractor-Induced Delays in India. J. Constr. Dev. Ctries. 2017, 22, 21–39. [CrossRef] 93. Parchami Jalal, M.; Shoar, S. A hybrid SD-DEMATEL approach to develop a delay model for construction projects. Eng. Constr. Archit. Manag. 2017, 24, 629–651. [CrossRef] 94. Renuka, S.; Kamal, S.; Umarani, C. A model to estimate the time overrun risk in construction projects. Empir. Res. Urban Manag. 2017, 12, 64–76. 95. Adam, A.; Josephson, P.-E.B.; Lindahl, G. Aggregation of factors causing cost overruns and time delays in large public construction projects: Trends and implications. Eng. Constr. Archit. Manag. 2017, 24, 393–406. [CrossRef] 96. Asiedu, R.O.; Adaku, E.; Owusu-Manu, D.-G. Beyond the causes: Rethinking mitigating measures to avert cost and time overruns in construction projects. Constr. Innov. 2017, 17, 363–380. [CrossRef] 97. Durdyev, S.; Omarov, M.; Ismail, S. Causes of delay in residential construction projects in Cambodia. Cogent Eng. 2017, 4, 1291117. [CrossRef] 98. Oyegoke, A.S.; Al Kiyumi, N. The causes, impacts and mitigations of delay in megaprojects in the Sultanate of Oman. J. Financ. Manag. Prop. Constr. 2017, 22, 286–302. [CrossRef] 99. Agyekum-Mensah, G.; Knight, A.D. The professionals’ perspective on the causes of project delay in the construction industry. Eng. Constr. Archit. Manag. 2017, 24, 828–841. [CrossRef] 100. Amoatey, C.T.; Ameyaw, Y.A.; Adaku, E.; Famiyeh, S. Analysing delay causes and eects in Ghanaian state housing construction projects. Int. J. Manag. Proj. Bus. 2015, 8, 198–214. [CrossRef] 101. Bekr, G.A. Causes of delay in public construction projects in Iraq. Jordan J. Civ. Eng. 2015, 159, 1–14. 102. Mahamid, I.; Al-Ghonamy, A.; Aichouni, M. Research Article Risk Matrix for Delay Causes in Construction Projects in Saudi Arabia. Res. J. Appl. Sci. Eng. Technol. 2015, 9, 665–670. [CrossRef] 103. Santoso, D.S.; Soeng, S. Analyzing delays of road construction projects in Cambodia: Causes and eects. J. Manag. Eng. 2016, 32, 05016020. [CrossRef] 104. Kadry, M.; Osman, H.; Georgy, M. Causes of construction delays in countries with high geopolitical risks. J. Constr. Eng. Manag. 2016, 143, 1–11. 105. Kim, S.-Y.; Tuan, K.N. Delay factor analysis for hospital projects in Vietnam. KSCE J. Civ. Eng. 2016, 20, 519–529. [CrossRef] 106. Bagaya, O.; Song, J. Empirical study of factors inﬂuencing schedule delays of public construction projects in Burkina Faso. J. Manag. Eng. 2016, 32, 05016014. [CrossRef] 107. Aziz, R.F.; Abdel-Hakam, A.A. Exploring delay causes of road construction projects in Egypt. Alex. Eng. J. 2016, 55, 1515–1539. [CrossRef] 108. Assbeihat, J.M. Factors Aecting Delays on Private Construction Projects. Technology 2016, 7, 22–33. 109. Nawi, M.N.M.N.; Lee, A. Factors inﬂuencing project delay: A case study of the vale malaysia minerals project (VMMP). Int. J. Supply Chain Manag. 2016, 5, 178–184. 110. Samarghandi, H.; Mousavi, S.; Taabayan, P.; Mir Hashemi, A.; Willoughby, K. Studying the Reasons for Delay and Cost Overrun in Construction Projects: The Case of Iran. J. Constr. Dev. Ctries. 2016, 21, 51–84. [CrossRef] Buildings 2019, 9, 191 36 of 37 111. Zailani, S.; Arin, H.A.M.; Iranmanesh, M.; Moeinzadeh, S.; Iranmanesh, M. The moderating eect of project risk mitigation strategies on the relationship between delay factors and construction project performance. J. Sci. Technol. Policy Manag. 2016, 7, 346–368. [CrossRef] 112. Al-Kharashi, A.; Skitmore, M. Causes of delays in Saudi Arabian public sector construction projects. Constr. Manag. Econ. 2009, 27, 3–23. [CrossRef] 113. Kaliba, C.; Muya, M.; Mumba, K. Cost escalation and schedule delays in road construction projects in Zambia. Int. J. Proj. Manag. 2009, 27, 522–531. [CrossRef] 114. Enshassi, A.; Al-Najjar, J.; Kumaraswamy, M. Delays and cost overruns in the construction projects in the Gaza Strip. J. Financ. Manag. Prop. Constr. 2009, 14, 126–151. [CrossRef] 115. Abdul-Rahman, H.; Takim, R.; Min, W.S. Financial-related causes contributing to project delays. J. Retail Leis. Prop. 2009, 8, 225–238. [CrossRef] 116. Mahamid, I.; Bruland, A.; Dmaidi, N. Causes of delay in road construction projects. J. Manag. Eng. 2011, 28, 300–310. [CrossRef] 117. Kazaz, A.; Ulubeyli, S.; Tuncbilekli, N.A. Causes of delays in construction projects in Turkey. J. Civ. Eng. Manag. 2012, 18, 426–435. [CrossRef] 118. Chandramohan, A.; Narayanan, S.L.; Gaurav, A.; Krishna, N. Cost and time overrun analysis for green construction projects. Int. J. Green Econ. 2012, 6, 167–177. [CrossRef] 119. Yang, J.-B.; Chu, M.-Y.; Huang, K.-M. An empirical study of schedule delay causes based on Taiwan’s litigation cases. Proj. Manag. J. 2013, 44, 21–31. [CrossRef] 120. González, P.; González, V.; Molenaar, K.; Orozco, F. Analysis of causes of delay and time performance in construction projects. J. Constr. Eng. Manag. 2013, 140, 04013027. [CrossRef] 121. Golob, K.; Bastic, ˇ M.; Pšunder, I. Inﬂuence of project and marketing management on delays, penalties, and project quality in slovene organisations in the construction industry. J. Manag. Eng. 2012, 29, 495–502. [CrossRef] 122. Alinaitwe, H.; Apolot, R.; Tindiwensi, D. Investigation into the causes of delays and cost overruns in Uganda’s public sector construction projects. J. Constr. Dev. Ctries. 2013, 18, 33. 123. Marzouk, M.M.; El-Rasas, T.I. Analyzing delay causes in Egyptian construction projects. J. Adv. Res. 2014, 5, 49–55. [CrossRef] 124. Wang, W.-C.; Lin, C.-L.; Wang, S.-H.; Liu, J.-J.; Lee, M.-T. Application of importance-satisfaction analysis and inﬂuence-relations map to evaluate design delay factors. J. Civ. Eng. Manag. 2014, 20, 497–510. [CrossRef] 125. Yang, J.-B.; Huang, K.-M.; Lee, C.-H.; Chiu, C.-T. Incorporating lost productivity calculation into delay analysis for construction projects. KSCE J. Civ. Eng. 2014, 18, 380–388. [CrossRef] 126. Yang, J.-B.; Kao, C.-K. Critical path eect based delay analysis method for construction projects. Int. J. Proj. Manag. 2012, 30, 385–397. [CrossRef] 127. Chaphalkar, N.B.; Iyer, K. Factors inﬂuencing decisions on delay claims in construction contracts for Indian scenario. Constr. Econ. Build. 2014, 14, 32–44. [CrossRef] 128. Braimah, N. Understanding construction delay analysis and the role of preconstruction programming. J. Manag. Eng. 2013, 30, 04014023. [CrossRef] 129. Abdelhadi, Y.; Dulaimi, M.F.; Bajracharya, A. Factors inﬂuencing the selection of delay analysis methods in construction projects in UAE. Int. J. Constr. Manag. 2018, 19, 329–340. [CrossRef] 130. Guévremont, M.; Hammad, A. Visualisation of Delay Claim Analysis Using 4D Simulation. J. Leg. A. Disput. Resolut. Eng. Constr. 2018, 10, 05018002. [CrossRef] 131. Yang, J.-B.; Teng, Y.-L. Theoretical development of stochastic delay analysis and forecast method. J. Chin. Inst. Eng. 2017, 40, 391–400. [CrossRef] 132. Yang, J.-B.; Wei, P.-R. Causes of delay in the planning and design phases for construction projects. J. Archit. Eng. 2010, 16, 80–83. [CrossRef] 133. Chen, G.-X.; Shan, M.; Chan, A.P.; Liu, X.; Zhao, Y.-Q. Investigating the causes of delay in grain bin construction projects: The case of China. Int. J. Constr. Manag. 2019, 19, 1–14. [CrossRef] 134. Apipattanavis, S.; Sabol, K.; Molenaar, K.R.; Rajagopalan, B.; Xi, Y.; Blackard, B.; Patil, S. Integrated framework for quantifying and predicting weather-related highway construction delays. J. Constr. Eng. Manag. 2010, 136, 1160–1168. [CrossRef] 135. Project Management Institute. A Guide to the Project Managemnet Body of Knowledge (PMBOK Guide), 6th ed.; Project Management Institute: Newtown Square, PA, USA, 2017. Buildings 2019, 9, 191 37 of 37 136. Project Management Institute. Construction Extension to the PMBOK, 2nd ed.; Project Management Institute: Newtown Square, PA, USA, 2016. 137. PMI. Practice Standard for Scheduling, Project Management Institute, 3rd ed.; Project Management Institute: Newtown Square, PA, USA, 2019. 138. Project Management Institute. Agile Practice Guide; Project Management Institute: Newtown Square, PA, USA, 2017. 139. Sepasgozar, S.M.E.; Razkenari, M.A.; Barati, K. The Importance of New Technology for Delay Mitigation in Construction Projects. Am. J. Civ. Eng. Archit. 2015, 3, 15–20. [CrossRef] 140. Sepasgozar, S.M.E.; Davis, S. Digital Construction Technology and Job-site Equipment Demonstration: Modelling Relationship Strategies for Technology Adoption. Buildings 2019, 9, 158. [CrossRef] 141. Sepasgozar, S.M.; Lim, S.; Shirowzhan, S. Implementation of Rapid As-built Building Information Modelling Using Mobile LiDAR. In Proceedings of the ASCE Construction Research Congress 2014, Construction in a Global Network, Atlanta, Georgia, 19–21 May 2014. 142. Shirowzhan, S.; Sepasgozar, S.M.; Li, H.; Trinder, J.; Tang, P. Comparative analysis of machine learning and point-based algorithms for detecting 3D changes in buildings over time using bi-temporal lidar data. Autom. Constr. 2019, 105, 102841. [CrossRef] 143. Shirowzhan, S.; Sepasgozar, S.M.E.; Li, H.; Trinder, J. Spatial compactness metrics and Constrained Voxel Automata development for analyzing 3D densiﬁcation and applying to point clouds: A synthetic review. Autom. Constr. 2018, 96, 236–249. [CrossRef] 144. Shirowzhan, S.; Trinder, J. Building classiﬁcation from lidar data for spatio-temporal assessment of 3D urban developments. Procedia Eng. 2017, 180, 1453–1461. [CrossRef] 145. Shirowzhan, S.; Lim, S.; Trinder, J. Enhanced autocorrelation-based algorithms for ﬁltering airborne lidar data over urban areas. J. Surv. Eng. 2016, 142, 04015008. [CrossRef] 146. Shirowzhan, S.; Lim, S. Autocorrelation statistics-based algorithms for automatic ground and non-ground classiﬁcation of Lidar data. In Proceedings of the ISARC. International Symposium on Automation and Robotics in Construction, Sydney, Australia, 9–11 July 2014; Vilnius Gediminas Technical University, Department of Construction Economics: Vilnius, Lithuania, 2014. [CrossRef] 147. Sepasgozar, S.M.; Forsythe, P.J.; Shirowzhan, S. Scanners and Photography: A Combined Framework. In Proceedings of the 40th Australasian Universities Building Education Association (AUBEA) 2016 Conference, Cairns, Australia, 6–8 July 2016; Central Queensland University: Cairns, Australia, 2016. 148. Tahmasebinia, F.; Niemelä, M.; Ebrahimzadeh Sepasgozar, S.; Lai, T.; Su, W.; Reddy, K.; Shirowzhan, S.; Sepasgozar, S.; Marroquin, F. Three-Dimensional Printing Using Recycled High-Density Polyethylene: Technological Challenges and Future Directions for Construction. Buildings 2018, 8, 165. [CrossRef] 149. Sepasgozar, S.M.; Davis, S.R.; Li, H.; Luo, X. Modelling the Implementation Process for New Construction Technologies: Thematic Analysis Based on Australian and US Practices. J. Manag. Eng. 2018, 34, 05018005. [CrossRef] 150. Sepasgozar, S.M.; Davis, S. Construction Technology Adoption Cube: An Investigation on Process, Factors, Barriers, Drivers and Decision Makers Using NVivo and AHP Analysis. Buildings 2018, 8, 74. [CrossRef] 151. Sepasgozar, S.M.; Davis, S.R.; Loosemore, M. Dissemination Practices of Construction Sites’ Technology Vendors in Technology Exhibitions. J. Manag. Eng. 2018, 34, 04018038. [CrossRef] 152. Sepasgozar, S.M.; Davis, S.; Loosemore, M.; Bernold, L. An investigation of modern building equipment technology adoption in the Australian construction industry. Eng. Constr. Archit. Manag. 2018, 25, 1075–1091. [CrossRef] 153. Sepasgozar, S.M.E.; Loosemore, M. The role of customers and vendors in modern construction equipment technology diusion. Eng. Constr. Archit. Manag. 2017, 24, 1203–1221. [CrossRef] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Journal

Buildings – Multidisciplinary Digital Publishing Institute

Published: Aug 26, 2019

Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

References (149)

Abstract

Journal

Recommended Articles

There are no references for this article.

Our policy towards the use of cookies