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A Bibliometric Network Analysis of Green Information Technology and Green Information Systems Research

A Bibliometric Network Analysis of Green Information Technology and Green Information Systems... Background: In recent years, the concepts of Green Information Technology and Green Information Systems (Green IT/IS) have attracted the attention of many researchers. Several environmental and sustainability studies have suggested that smart usage of Green IT/IS is one of the most important enablers for sustainable development in organizations and plays an essential role in greening the planet. Objectives: This paper aims to examine the development of the Green IT/IS field based on the published works. The focus is on analysing the keywords of related papers obtained from the Web of Science database. Methods/Approach: Based on the two- mode network of papers and keywords, the analysis of co-occurrence of keywords is provided. The most frequent keywords discovered by the temporal network analysis are presented from the perspective of the most prominent journals. Results: The main pillars of knowledge in Green IT/IS research are highlighted, and a chronological map of the field is provided. Conclusions: Green IT/IS's studied field shows constant growth in the last decades, and the results indicate the trends of future development in the field. The paper is one of the first studies that apply the bibliographic network analysis approach to the field of Green IT/IS. Keywords: Green Information System; Green Information Technology; bibliographic networks JEL classification: D85 Paper type: Research article Received: Apr 08, 2021 Accepted: Aug 09, 2021 Acknowledgments: This research was supported by the Slovenian Research Agency; Program No. P5-0018 – Decision Support Systems in Digital Business. Citation: Žnidaršič, A., Maltseva, D., Brezavšček, A., Maletič, M., Baggia, A. (2021), “A Bibliometric Network Analysis of Green Information Technology and Green Information Systems Research”, Business Systems Research, Vol. 12, No. 2, pp. 17-45. DOI: https://doi.org/10.2478/bsrj-2021-0017 Business Systems Research | Vol. 12 No. 2 |2021 Introduction In the last two decades, organizations have strived to achieve higher levels of sustainable development to contribute to the greening of the planet, primarily through the advanced use of information technology (IT) and information systems (IS) (Melville, 2010; Watson et al., 2008). The role of smart use of IT/IS in contributing to environmentally responsible human activities has become an attractive field of research and is therefore highly discussed in the literature. Consequently, aligned with the practical use in organizations, the discussions and research on these topics, two main concepts, Green Information Technology (Green IT) and Green Information Systems (Green IS), have become notable terms in professional and academic publications. Due to the growing interest in the Green IT/IS research field, several studies have been published in recent years that deal with the related research topics. Esfahani et al. (2015) noted that the earliest study in this area was published back in 2007. Initially, the studies focused on Green IT, where the term Green IS was first introduced by Melville (2010). This work described the concept of information systems innovation for environmental sustainability and was included in the 20 most cited studies on green innovation (Albort-Morant et al., 2017). Later, Brooks et al. (2012) identified the main streams of Green IT/IS-related studies and provided a review of the literature from practitioners and academics. The authors reveal that most of the research focused on the concepts of Green IT, probably due to its popularity among practitioners. In addition, Loeser (2013) extended the literature search to the AIS electronic library using the keywords green IS and green IT and related terms such as sustain*, green or environmental. It was found that professional studies were ahead of academic ones, as most Green IT/IS papers were published in conference proceedings, while publications in top IS journals were rare. On the other hand, Wang et al. (2015) significantly expanded the list of search terms (i.e., keywords). They classified Green IT/IS-related papers into four categories: initiation, enterprise strategies and practices, adoption framework, and outcomes. Further, Singh et al. (2020) examine five segments in the Green IS research area: Green IS concept, innovation and technology, the impact of green initiatives, measures and policies, and global context. Moreover, Esfahani et al. (2015) provided a review of research questions already addressed and the current state of research, while Bokolo (2016) used a set of search terms related to the concepts of Green IT/IS and retrieved 137 papers published in journals as well as conference proceedings. Based on this literature review, the authors provided a set of determinants that encourage/discourage organizations from incorporating Green IT/IS practices. One of the systematic literature reviews was provided by Muhammad et al. (2017), who used different search terms to retrieve Green IT/IS-related publications from various databases. The authors found that good search strings are difficult to formulate; they applied the snowballing method to complement the database search. All these studies provide high-level research agendas and have opened new possibilities for future Green IT/IS research. One of the most important findings from the systematic Green IT/IS literature reviews concludes that the terms Green IT/IS have been vague concepts for several years. Both fundamental terms have often been used interchangeably without recognizing the differences, leading to confusion in professional and academic societies. While several authors attempted to present a clear distinction between the two terms (Brooks et al., 2012; Deng et al., 2015; Muhammad et al., 2017), Loeser (2013) distinguishes the terms based on the differences in the scopes. Following Loeser (2013), it is now clearly defined that the term “Green IT refers to measures and initiatives which decrease the negative Business Systems Research | Vol. 12 No. 2 |2021 environmental impact of manufacturing, operations, and disposal of Information Technology (IT) equipment and infrastructure”, while the term Green IS refers to “practices which determine the investment in, deployment, use and management of information systems (IS) in order to minimize the negative environmental impacts of IS, business operations, and IS-enabled products and services”. Besides the academic contribution, the research outcomes in Green IT/IS are also essential from the managerial implications point of view. Namely, Green IT/IS that are oriented to minimize the negative environmental impact is one of the key enablers of sustainable digital transformation in any contemporary organization (Gils et al., 2020). To assure organizations the valuable information for decision making for aligning the digital transformation activities with the sustainable development goals, up-to-date direction for proper use of Green IT/IS is needed. Therefore, the findings of already mentioned reviews on Green IT/IS literature are more than valuable. However, to gain a comprehensive overview of development directions, it would be worthwhile to supplement the qualitative literature research techniques with an appropriate quantitative attempt. This paper aims to provide a comprehensive literature review on Green IT/IS to examine the development of the research field of Green IT/IS based on the published papers. Aligned this objective, the following research question was formulated: RQ: How have scientific publications on Green IT /IS research evolved over the past decades? In addition to conventional search engines for literature analysis, advanced social network analysis (SNA) methods are applied. Our investigation will be based on Green IT/IS-related papers published in the Web of Science (WoS) database until 2020. When searching for the papers, the basic keywords Green information technology and Green information systems are expanded with various queries such as: ”green information system*”, ”sustain* information system”, ”environment* information system*”, ”environmental informatics”, ”energy informatics”, ”green software”, ”green computing”, ”green information communication technology*”, and ”information system* for sustainable development”. The justification for selecting the listed keywords is presented under Methodology Section. From the obtained set of works in WoS, the complete descriptions were extracted considering the authors, the keyword list, and the work titles. Together with the initial hits, their citing articles were also obtained. Details on the data collection phase, converting raw data to network format, and analyses are presented in the Methodology section. The paper is organized as follows; first, the process of bibliometric data collection and the preparation of the working set of keywords is presented, followed by the description of the derived networks, the normalized networks, and the temporal networks. The results start with the analyses of a two-mode network of works and keywords, followed by analyses of the keyword co-occurrence network. Furthermore, the selected journals that publish Green IT/IS topics were identified, and networks of emerging keywords within these journals were constructed and analysed. The Analysis employed enables the representation of the most frequently used keywords in the Green IT/IS research area through the lens of the most prominent journals. Moreover, the results provide a chronological mapping of the research field and show its future development trends. In the conclusions, an overview of the main findings is given, and our contribution to this research field and gaps for future research are identified. Business Systems Research | Vol. 12 No. 2 |2021 Methodology In the research design and data analyses we followed similar bibliographic research (e.g., Batagelj et al. 2013, 2014, 2019, 2020). For the analyses of publication practices on Green IT/IS, we analysed works included in WoS. We used the computer program WoS2Pajek to transform data into a network format to analyse the obtained data. The computer program Pajek for network analyses and Python libraries Nets and TQ for analyses of temporal networks. Data collection Data was collected from WoS Core Collection until 2020 using the following queries: ”green information system*”, ”sustain* information system”, ”environment* information system*”, ”environmental informatics”, ”energy informatics”, ”green software”, ”green information technology*”; ”green computing”, ”green information communication technology*”, ”information system* for sustainable development”. The justification of the ten selected queries is presented below. • green information system* (and the abbreviation Green IS*) • green information technology* (and abbreviation green IT*) • sustain* information system*: Diverse functionalities can characterize IS as Green. According to Chowdhury (2012), one of the characteristics is the change in software development life-cycle, which aims to reduce the potential negative environmental impacts of the system. Aligned with this definition, the term sustainable information system has to be classified as a type of Green IS, whereas it is often used interchangeably. • environment* information system*, also known as an environmental management information system, is used to track, measure, and monitor the environmental variables: emission, waste, toxicity, and carbon footprint (Sanita et al., 2017). • environmental informatics: In the 1990s, the new concept of Environmental informatics emerged, focused on the techniques of effective collection, storage, retrieval, and processing of complex environmental data (Avouris et al., 1995), which was later classified as Green IS. • energy informatics: The concept of energy informatics was introduced by (Watson et al., 2010), describing the discipline dealing with the role of IS in the reduction of energy consumption. • talking about green computing or rather green information communication technology (Green ICT) mainly sets the focus on hardware issues while software issues are directly named green software (Kern, 2018). • information system* for sustainable development: The term Information system for sustainable development (Hilty et al., 2015) was used to describe various information systems supporting green initiatives. Based on the search queries listed, the original hits and additional articles citing those hits were obtained. Construction of network data Using the computer program WoS2Pajek 1.5 (Batagelj, 2017), we converted the raw text WoS file into a collection of different networks. The program WoS2Pajek 1.5 transforms phrases from the raw WoS file into individual words when constructing networks (e.g., the phrase green information system is split into three keywords Green, information, and system). The obtained works include papers in scientific journals, papers in conference proceedings, reports, books, etc. We obtained one-mode Business Systems Research | Vol. 12 No. 2 |2021 citation network 𝐶𝑖 𝑡 𝑒 of works and three two-mode networks: the authorship network on works  authors ( ), the journal network on works  journals ( ), and the keywords network on works  keywords ( ). The authors were identified from the AU field in the WoS entry, the journals from the field CR or J9, the keywords from the fields of Author Keywords (DE field), Keywords Plus (given by ID field), and the document title from the field TI. Two types of works were extracted from WoS: works with full descriptions (referred as hits) and with partial description (referred as terminal). In the case of terminal works the journal name, the first author, the year of publication, the issue of the journal, and the first-page number were available. Keywords, abstract, and citations are missing in the case of terminal works. Loops and multiple lines were removed from all networks, and we obtained the basic networks labelled as 𝑒𝐶𝑖𝑡 , , , and . Sizes of the networks are presented in Table 1. Since all terminal works (320 586) contain only partial information (without keywords and citations), we excluded them from the analyses. Since we aim to analyse the keywords of the works from the WoS on selected queries, we also removed all 9 530 citing articles. The resulting reduced networks (of hits) without citing articles are as follows: 𝑒𝑅𝐶𝑖𝑡 , 𝐴𝑟𝑊 , 𝐽𝑟𝑊 , and 𝐾𝑟𝑊 . Sizes of the sets of these networks are presented in Table 1. Table 1 Number of vertices in obtained and reduced networks Networks Business Performance Basic from WoS Reduced to hits Number of works 332 047 1 931 Number of keywords 13 635 4 017 Number of authors 148 348 4 342 Number of journals 26 806 669 Source: Author’s work Derived networks A rectangular two-mode matrix is usually used to represent the two-mode network. Using matrix multiplication of two matrices of compatible dimensions a new network can be constructed. More precisely, two rectangular matrices can be multiplied if the number of columns of the first matrix corresponds to the number of rows of the second matrix. Details on construction of networks can be found in Batagelj et al. (2013, 2014). Following this procedure two derived networks, described below were constructed. First, the network of co-occurrence of keywords (keywords times keywords ( )) = 𝐾𝑟𝑊 ∗ 𝐾𝑟𝑊 (1) The weight of an edge in between two nodes 𝑤 [𝑘 1; 𝑘 2] represents the number of works in which the selected keywords 𝑘 1 and 𝑘 2 were mentioned together. Second, the network of journals and keywords was obtained with the following multiplication: = 𝐽𝑟𝑊 ∗ 𝐾𝑟𝑊 (2) The edge in a network indicates how many times the journal 𝑗 contained the keyword 𝑘 . In the following sections, the detailed descriptions of the calculated networks as well as the result of the analyses are presented. 𝐽𝐾𝑟 𝐽𝐾𝑟 𝐾𝐾𝑟 𝐾𝐾𝑟 𝐾𝐾𝑟 𝑊𝐾 𝑊𝐽 𝑊𝐴 𝑊𝐾 𝑊𝐽 𝑊𝐴 Business Systems Research | Vol. 12 No. 2 |2021 Normalization of derived networks Derived networks may have some disadvantages, as, for example, works with a large number of authors or keywords may be overrated in terms of the contribution of such a work. To overcome this issue, we used the fractional approach in our analyses (Batagelj et al., 2013; 2019; Gauffriau et al., 2007). The importance of these works was normalized so that the sum of all weights in the calculating network is equal to 1. We can illustrate this situation with the following example. In the (rectangular) two- mode network of works  keywords (𝐾𝑟𝑊 ) an out-degree of a particular work is equal to the number of work’s keywords, and an indegree of a selected keyword is equal to the number of works which included that word among the listed keyword. If the normalization is employed for the network, the weight of each arc is divided by the out-degree of a selected node which is equal to the sum of the weights of all the arcs pointing from that node. The contribution of each paper is normalized and the 𝑛𝑊𝐾 is calculated as follows: 𝑊𝑟𝐾 [𝑤 ,𝑘 ] 𝑛𝑊𝐾 [𝑤 , 𝑘 ] = (3) ( ) max (1,𝑢𝑑𝑒𝑔𝑜𝑡 𝑤 ) where 𝑤 is work and 𝑘 is a keyword. The proposed normalization approach can be applied to different two-mode networks. In addition, for the normalization of the network, the term frequency- inverse document frequency (TF–IDF) approach was used (Robertson, 2004). Using this approach, the importance of a word to a document in a corpus of documents can be considered. Temporal networks Temporal networks have time quantities in their description specifying which links (or/and nodes) are active at certain points in time. Based on the WKr network with combined time quantities, temporal networks were constructed (Batagelj et al., 2016, 2020) using the Python libraries (Batagelj et al., 2014). Two types of temporal networks can be constructed – instantaneous (where values are given for each year) WKins, and cumulative (where cumulative values over the years are calculated) 𝑢𝑚𝐾𝑐𝑊 . With multiplication and normalization procedures employed on temporal networks described above, we can calculate various new temporal networks. Results This section presents the results of different analyses performed to reach the research objective. First, with the analysis of the network, we identify the most frequent keywords and their distribution over the years. Second, the most important journals where Green IT/IS topics are published are identified, and subtopics published inside those journals are investigated. Analyses of the WK network The works cited only (also known as terminal) do not have any keywords. In our case, the network consists of 96,5% of such works. Therefore, we will focus on analysing the reduced network of hits 𝐾𝑟𝑊 . In the works with complete description (𝐾𝑟𝑊 network) the number of keywords ranges from 2 to 57. The distribution of keywords is presented in Figure 1. Works contain 4 017 different keywords, and more than half of them (2 105) are mentioned only once, while 604 keywords are mentioned twice. 𝑊𝐾 𝑊𝐾 𝐽𝐾 𝑊𝐾 Business Systems Research | Vol. 12 No. 2 |2021 Figure 1 Frequency distribution of the keywords Source: Author’s illustration Eight of the most frequent vertices in the 𝐾𝑟𝑊 network are green, system, information, technology, energy, computing, environmental, and management (Table 2). The word green occurs 1 226 times. This is expected since we use these words in phrases of the search query. Based on the most frequent keywords, the research field of Green IT/IS could be mapped. As expected, the research field consists of informatics or technically oriented keywords such as data (in tables and figures, the singular form of the noun is used - datum), compute, cloud, base, communication, software, network, center, algorithm, application, while also environmental aspects sustainability, consumption, sustainable, environment, etc. and organization performance efficiency, performance, optimization, process, etc. are also covered. Several words are closely related to research: analysis, study, approach, framework, etc. Some words also have a different meaning related to the context, e.g., center, issue, column, etc. At the same time, their identification within a particular journal might reveal the specific scope or specialization of the journal. Business Systems Research | Vol. 12 No. 2 |2021 Table 2 The frequencies of the most used keywords in the nWKr network Rank Value Keyword Rank Value Keyword Rank Value Keyword 1 1 226 green 35 105 approach 68 62 assessment 2 936 information 36 103 study 69 60 adoption 3 767 system 37 102 virtual 70 59 behavior 4 668 energy 38 96 framework 71 57 save 5 633 technology 39 92 impact 72 56 sensor 6 559 computing 40 90 machine 73 54 carbon 7 413 environmental 41 86 optimization 74 54 integrate 8 378 management 42 84 scheduling 75 53 monitoring 9 313 datum 43 84 process 76 52 social 10 299 compute 44 82 server 77 52 infrastructure 11 298 cloud 45 81 strategy 78 51 challenge 12 291 model 46 78 dynamic 79 51 cluster 13 267 power 47 78 architecture 80 50 simulation 14 248 sustainability 48 77 smart 81 50 policy 15 245 base 49 76 virtualization 82 50 control 16 241 efficiency 50 76 case 83 49 gi 17 217 performance 51 75 decision 84 49 method 18 213 communication 52 74 research 85 48 multi 19 209 consumption 53 72 support 86 47 waste 20 187 sustainable 54 71 practice 87 47 grid 21 184 software 55 70 perspective 88 46 informatics 22 182 network 56 68 innovation 89 45 issue 23 182 environment 57 68 distribute 90 44 scale 24 177 efficient 58 68 web 91 43 computer 25 163 center 59 66 business 92 42 emission 26 162 use 60 64 time 93 42 industry 27 161 resource 61 64 internet 94 42 eco 28 149 aware 62 64 theory 95 42 quality 29 147 algorithm 63 64 allocation 96 42 change 30 143 development 64 64 implementation 97 42 migration 31 142 design 65 63 engineering 98 41 user 32 137 analysis 66 62 evaluation 99 41 factor 33 137 service 67 62 mobile 100 41 consolidation 34 127 application Note: As a keyword in works, a plural form data is used Source: Author’s work Temporal analysis of the keywords We looked at the temporal distributions of the number of all keywords and unique (different) keywords used in Green IT/IS (Figure 12). Keywords on Green IT/IS first appeared in the 1990s, while the number of publications started increasing in 2010. During the last few years, there have been around 3 000 publications in WoS on that topic. From 2013, around 1 000 unique keywords on IT/IS are published per year. Business Systems Research | Vol. 12 No. 2 |2021 Figure 2 Distributions of keywords on Green IT/IS Source: Author’s illustration To determine the importance of a particular keyword over time, we calculated a proportion (ranging from 0% to 100%) of a particular keyword occurrence according to the keyword with the highest occurrence for each year based on the 𝑛𝑠𝐾𝑖𝑊 network (Figure 3). We created green, system, information, technology, energy, computing, environmental, and management pictures. Some of the keywords shown in Figure 3 have been used for a long time, as their first appearance dates back to the 1970s (e.g., system, information, and environmental). Some words appear around 1995 (energy, technology, and management), while Green becomes popular after 2005. It is quite reasonable to expect the keywords system and information to reach the maximal level of usage (or importance) in almost all years after their introduction, with a small decline after 2010, probably due to the more sophisticated subdomains of usage and the broader set of keywords used, as shown in Figure 2. Other information systems keywords appear from 2000, and their usage (or importance) is the most extensive around 2015 (e.g., computing). The keyword environmental has been used since 1975, and it became extremely popular in 1990. There is a small drop in 2010, but its occurrence is still around 30% of the most popular words each year. The keyword green is a newly developed concept related to IS and IT, which appeared in 2009. Business Systems Research | Vol. 12 No. 2 |2021 Figure 3 Distribution of keyword appearance proportion considering the eight most frequent keywords Source: Author’s illustration Keywords co-occurrence network By column projection of the normalized hits 𝑟𝑛𝑊𝐾 network, the normalized one-mode network 𝑛𝐾𝐾𝑟 was calculated as follows: 𝑛𝐾𝐾𝑟 = n𝐾𝑟𝑊 ∗ 𝑟𝑛𝑊𝐾 (4) After the deletion of loops and the transformation of bidirectional arcs to edges, the calculated network 𝑛𝐾𝐾𝑟 consists of 4 017 nodes and 126 639 edges. In this new calculated network, the weight on the edges between the keywords is equal to the fractional co-occurrence of keywords 𝑖 and 𝑗 in the same works. According to Batagelj et al. (2019) the 𝑛𝐾𝐾𝑟 network is symmetric: 𝑛𝐾𝐾𝑟 [𝑖 ; 𝑗 ] = 𝑛𝐾𝐾𝑟 [ 𝑗 ; 𝑖 ] (5) Furthermore, value 1 of a particular work is redistributed over the keywords: ∑ 𝑛𝐾𝐾𝑟 [𝑖 ; 𝑗 ] = |𝑊 | (6) 1,𝑗 Since 𝑛𝐾𝐾 ℎ is a valued network, we employed the Line Island approach (Batagelj et al., 2014) and searched for the islands of sizes 2 to 75. We obtained 13 islands, 10 of Business Systems Research | Vol. 12 No. 2 |2021 which consist of only one pair of vertices. Figure 4 represents the largest island with 75 vertices. The width and greyscale are proportional to the line weight, calculated based on the fractional co-occurrence approach described in the following subsection. Strongly associated (with the largest line weights) are green - computing, green - technology, green - information, system - information, and environmental - information. This was expected since these words are included in our search queries. Therefore, we removed the first 8 most frequent keywords from the network and repeated the Line Island approach. We obtained 73 islands ranging in size from 2 to 50 vertices, 78% of which consist of only one pair of vertices. The largest island is represented in Figure 6 and is described below. When we compare the island with 75 vertices obtained from the 𝑛𝐾𝐾𝑟 network (Figure 5) instead of its non-normalized version ( ) (Figure 4) the following words appeared to be more important: nature, education, challenge, sensor, monitoring, database, special, issue, wireless, greening, introduction, while some others were not included in this island (e.g., adoption, behavior, social, theory, time). Figure 4 Line Island of network on 75 vertices Source: Author’s illustration 𝐾𝐾𝑟 𝐾𝐾𝑟 Business Systems Research | Vol. 12 No. 2 |2021 Figure 5 Line Island of 𝑛𝐾𝐾𝑟 network on 75 vertices Source: Author’s illustration The above exploratory analysis results show that 8 of the most frequent keywords (green, system, information, technology, energy, computing, environmental, management) are connected to many other vertices. We excluded them from the network to obtain connection patterns between other keywords and again applied the Line Island approach. Figure 6 represents the largest island with 50 vertices. The most central part of the network is a pair of keywords compute and cloud, and both vertices are connected to the datum and center. Other vertices are efficiency, scheduling, application, resource, allocation, algorithm, virtual, machine... Other keywords that came up are virtual - machine, sustainable - development, and power - consumption. Around sustainability and development, the keywords software, communication, and sustainability also stand out. Business Systems Research | Vol. 12 No. 2 |2021 Figure 6 The largest line island (size 50) of 𝑛𝐾𝐾𝑟 network with removed 8 vertices Source: Author’s illustration Smaller islands (Figure 7) identify some concepts related to the information systems domain (core - multy - agent, cloudstack - simulation - nanodevice), others are enterprise-oriented (make - decision - support, cause - partnership - stakeholder - unified - create - common) or environmentally oriented (biodiversity - endanger - species, emission - footprint - carbon). Further analyses of the 2-vertices islands show that some common phrases with limited value appeared in the information systems domain, e.g., publish-subscribe, special-issue, column-response, real-time, e-waste, etc. To get a deeper insight into those keywords, we will present them in the context of the most popular journals from the field (see the next section). Figure 7 Line islands of size 3 to 6 of 𝑛𝐾𝐾𝑟 network with removed 8 vertices Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Keywords and journals First, the analysis of 𝐽𝑟𝑊 shows the most important journals in which Green IT/IS topics are published (Table 3). Table 3 Journals with the highest number of works on Green IT/IS Rank Title # of Abbreviated title & ISSN JIF SNIP works 1 Lecture Notes in Computer Science LECT NOTES COMPUT SC 48 √ 0302-9743 2 IFIP Advances in Information and IFIP ADV INF COMM 35 √ Communication Technology 1868-4238 3 Sustainable Computing-Informatics & SUSTAIN COMPUT-INFOR 29 √ √ Systems 2210-5379 4 Studies in Systems, Decision, and STUD SYST DECIS CONT 23 √ Control 2198-4182 5 Advanced Intelligent Systems ADV INTELL SYST 21 2640-4567 6 Communications in Computer and COMM COM INF SC 20 √ Information Science 1865-0929 7 Environmental Modelling & Software ENVIRON MODELL SOFTW 19 √ √ 1364-8152 8 Future Generation Computer Systems FUTURE GENER COMP SY 19 √ √ 0167-739X 9 Computer COMPUTER 15 √ √ 0018-9162 10 Sustainability SUSTAINABILITY-BASEL 15 √ √ 2071-1050 11 It Professional IT PROF 12 √ 1520-9202 12 Procedia Computer Science PROCEDIA COMPUT SCI 12 √ 1877-0509 13 Cluster Computing CLUSTER COMPUT 11 √ √ 1386-7857 14 Journal of Supercomputing J SUPERCOMPUT 11 √ √ 0920-8542 15 Information Systems Frontiers INFORM SYST FRONT 10 √ √ 1387-3326 16 Journal of Cleaner Production J CLEAN PROD 10 √ √ 0959-6526 17 Advanced Science Letters ADV SCI LETT 8 √ 1936-6612 18 Computer Networks COMPUT NETW 8 √ √ 1389-1286 19 Journal of Strategic Information J STRATEGIC INF SYST 8 √ √ Systems 0963-8687 20 Fujitsu Scientific & Technical Journal FUJITSU SCI TECH J 8 √ √ 0016-2523 21 Proceedings of the Hawaii P ANN HICSS 8 International Conference on System N/A Sciences 22 Concurrency Computation Practice CONCURR COMP-PRACT E 8 √ √ and Experience 1532-0626 23 Advanced Materials Research ADV MATER RES-SWITZ 8 1662-8985 24 Advances in Computer Science ACSR ADV COMPUT 8 Research 2352-538X Note: ISSN is not-applicable. Book series, different ISSN for each volume Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table 3 presents 24 journals with the highest number of published papers among our hits along with the information whether they have the Journal Impact Factor (JIF) (Clavrivate, 2019) or the Source Normalized Impact per Paper (SNIP) factor (Elsevier B.V., 2019) to reveal publishing culture among the authors. There were 48 papers published in the journal Lecture notes in computer science (LECT NOTES COMPUT SC), followed by 35 papers in the journal IFIP Advances in Information and Communication Technology (IFIP ADV INF COMM) and 29 papers in the journal Sustainable Computing- Informatics & Systems (SUSTAIN COMPUT-INFOR). The construction of network and its normalization is presented below. First, the derived network of journals  keywords was obtained by multiplying two two- mode networks = ∗ (7) To analyse keywords inside journals, two types of normalization were used: fractional approach and term frequency-inverse document frequency (TF-IDF). Fractional normalization The normalized reduced networks 𝑟𝑛𝑊𝐽 and 𝑟𝑛𝑊𝐾 were used to calculate a new normalized network of journals and keywords as follows: 𝑛𝐽𝐾 = 𝑛𝑊𝐽 ∗ 𝑛𝑊𝐾 (8) In the new network 𝑛𝐽𝐾 , the weight on the edges between the nodes 𝑗 and 𝑘 is equal to the fractional contribution of a journal 𝑗 for a given keyword 𝑘 ; or of a group of journals 𝐶 : [ ] ∑ 𝐶 , 𝑘 = [𝑗 , 𝑘 ] (9) 𝑗 ∈𝐶 Term frequency-inverse document frequency (TF-IDF) 𝑇𝐹 − 𝐼𝐷𝐹 approach, proposed by Robertson (2004), was employed to the network. In the normalization procedure the importance of a keyword for within a journal is considered. We used reduced networks 𝐽𝑟𝑊 and 𝐾𝑟𝑊 for network construction, 𝑇𝐹 and 𝐼𝐷𝐹 were defined (and calculated) as follows. 𝑇𝐹 represents the number of times a keyword appears in a selected journal, divided by the total number of (all different) keywords in the journal. 𝐼𝐷𝐹 is defined as the logarithm of the number of the journals in the corpus divided by the number of journals in which the specific keyword occurs. We calculated 𝑇𝐹 − 𝐼𝐷𝐹 indices for the keywords were calculated in the following way: 𝑇𝐹 − 𝐼𝐷𝐹 [𝑘 , 𝐽 ] = 𝑇𝐹 [𝑘 , 𝑗 ] ∗ 𝐼𝐷𝐹 [𝑘 ] (10) # times 𝑘 appeared in 𝐽 [ ] 𝑇𝐹 𝑘 , 𝑗 = (11) total # 𝐾 in 𝑗 # 𝐽 [ ] 𝐼𝐷𝐹 𝑘 = (12) # 𝐽 with 𝑘 where 𝑘 is a keyword, 𝐾 – all the keywords, 𝑗 – a journal, and 𝐽 – all the journals. 𝑙𝑜𝑔 𝐽𝐾𝑟 𝐽𝐾𝑟 𝐽𝐾 𝐽𝐾 𝐽𝐾 𝑊𝐾 𝑊𝐽 𝐽𝐾 𝐾𝐽 Business Systems Research | Vol. 12 No. 2 |2021 Keywords in the selected journals To analyse the most frequent or important keywords on Green IT/IS, we selected nine top journals (denoted with bold in Table 3) according to the number of papers received and their influence measured by JIF or SNIP. Three journals with the highest number of published works are Lecture Notes in Computer Science (LECT NOTES COMPUT SC), IFIP Advances in Information and Communication Technology (IFIP ADV INF COMM), and Sustainable Computing- Informatics & Systems (SUSTAIN COMPUT-INFOR). All three journals are indexed in Scopus, and the third one is also indexed in JIF. In companion to these three journals, we selected five other prestigious journals with the highest JIF among the received journals: Information Systems Frontiers (INFORM SYST FRONT), Future Generation Computer Systems (FUTURE GENER COMP SY), Environmental modeling & software (ENVIRON MODELL SOFTW), Journal of Cleaner Production (J CLEAN PROD), and Computer (COMPUTER). The analysis of the co-occurrence of keywords in the selected journals is presented below. TF-IDF indices approach for keywords in selected journals We employed the TF-IDF approach for nine selected journals. According to TF-IDF, the most important keywords are presented in Table 4 - Table 6. Table 4 The most important keywords according to TF-IDF indices (journals LECT NOTES COMPUT SC, INFORM SYST FRONT, FUTURE GENER COMP SY) LECT NOTES COMPUT SC INFORM SYST FRONT FUTURE GENER COMP SY Rank Value Keyword Value Keyword Value Keyword 1 0,063 energy 0,176 business 0,128 compute 2 0,059 compute 0,094 modernization 0,103 efficiency 3 0,056 design 0,088 supply 0,101 aware 4 0,053 technology 0,087 chain 0,091 distribute 5 0,052 cloud 0,077 value 0,089 energy 6 0,052 spatio 0,072 performance 0,083 cloud 7 0,051 science 0,072 sustainability 0,079 center 8 0,051 aware 0,069 technology 0,070 computing 9 0,049 computing 0,069 organization 0,069 exploit 10 0,049 service 0,064 alignment 0,067 scheduling 11 0,047 temporal 0,061 environmental 0,064 management 12 0,047 datum 0,060 determinant 0,063 performance 13 0,046 base 0,058 innovation 0,062 power 14 0,046 efficiency 0,057 small 0,060 resource 15 0,046 green 0,056 theory 0,056 datum 16 0,045 application 0,056 strategic 0,054 hardware 17 0,043 system 0,054 management 0,053 optimal 18 0,043 research 0,050 ecological 0,051 hpc 19 0,043 consumption 0,047 pea 0,050 heuristic 20 0,042 information 0,047 carrot 0,049 consumption 21 0,040 community 0,047 just 0,048 green 22 0,037 performance 0,047 complementarity 0,047 parallel 23 0,037 sustainability 0,047 doi 0,044 application 24 0,037 provision 0,047 pvt 0,043 indicator 25 0,036 management 0,047 midlands 0,043 cost 26 0,035 platform 0,047 gratification 0,042 protein 27 0,035 environmental 0,046 eco routine 28 0,035 smart 0,046 informatics fip 29 0,034 conservation 0,046 make backtracking 30 0,034 process 0,045 firm datacentre Note: Several keywords have the same value; not all are listed here. Source: Author’s work The keyword green is the most important keyword in 6 out of 9 journals, while in the other three journals, the first place belongs to the keyword information. Most of the Business Systems Research | Vol. 12 No. 2 |2021 most important keywords within the journals are related to information systems, while in two journals, specificity is shown in the publication culture. Two important keywords within the Computer (COMPUTER) journals are column and response, indicating that the authors write replies to the initial columns (papers). Similarly, four of the most important keywords in the journal Sustainable Computing-Informatics & Systems (SUSTAIN COMPUT-INFOR) are related to publishing: special - issue, conference - paper. The connections between the keywords specific to the journal are presented in the following subsection. Table 5 The most important keywords according to TF-IDF indices (journals ENIVORN MODELL SOFTW, J CLEAN PROD, IFIP ADV INF COMM TE) ENVIRON MODELL SOFTW J CLEAN PROD IFIP ADV INF COMM TE Rank Value Keyword Value Keyword Value Keyword 1 0,118 environmental 0,070 travel 0,125 environmental 2 0,117 integrate 0,070 meeting 0,112 semantic 3 0,112 integration 0,064 corporate 0,094 portal 4 0,110 ei 0,062 eco 0,085 semantics 5 0,105 support 0,056 financial 0,077 search 6 0,101 decision 0,055 environmental 0,074 web 7 0,084 service 0,053 company 0,071 information 8 0,076 ogc 0,052 collaboration 0,071 architecture 9 0,074 web 0,052 innovation 0,063 system 10 0,074 system 0,050 program 0,056 infotercio 11 0,071 design 0,050 technology 0,056 sise 12 0,065 information 0,048 management 0,056 ho 13 0,060 interface 0,048 practice 0,056 diagram 14 0,058 example 0,046 communication 0,056 subsystem 15 0,057 management 0,044 empirical 0,056 link 16 0,055 open 0,043 public 0,055 open 17 0,053 architecture 0,042 appraisal 0,052 infrastructure 18 0,052 software hide 0,050 discovery 19 0,050 use ema 0,050 datum 20 0,047 datum willing 0,048 sustainable 21 0,047 component logit 0,047 rest 22 0,046 spatial valuation 0,047 czech 23 0,045 application contingent 0,046 technology 24 0,045 access premium 0,044 balance 25 0,043 navigator videoconference 0,043 life 26 uwedat swedish 0,042 microservice 27 abatement responsive 0,042 user 28 enviroinfo publicly 0,041 series 29 spread circular 0,041 office 30 maintain ghanaian 0,041 generic Note: Several keywords have the same value, not all are listed here. Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table 6 The most important keywords according to TF-IDF indices (journals SUSTAIN COMPUT- INFOR, COMPUTER, STUD SYST DECIS CONT) SUSTAIN COMPUT-INFOR COMPUTER STUD SYST DECIS CONT Rank Value Keyword Value Keyword Value Keyword 1 0,172 special 0,145 column 0,206 engineering 2 0,148 issue 0,106 technology 0,115 concept 3 0,126 conference 0,089 response 0,082 technology 4 0,124 papers 0,074 green 0,074 complex 5 0,122 computing 0,073 computing 0,069 development 6 0,118 introduction 0,072 accountability 0,062 preface 7 0,118 international 0,072 generalize 0,061 implementation 8 0,104 igcc 0,072 fear 0,058 thing 9 0,095 select 0,072 wild 0,052 fpga 10 0,076 reduction 0,072 shine 0,052 taxonomy 11 0,075 software 0,072 let 0,051 network 12 0,075 energy 0,072 sun 0,051 model 13 0,069 power 0,072 showcase 0,051 green 14 0,066 green 0,072 joule 0,049 logic 15 0,059 server 0,072 hurdle 0,048 physical 16 0,058 agile 0,072 modularity 0,047 information 17 0,057 efficiency 0,072 bloat 0,047 internet 18 0,054 compute 0,072 1680 0,046 function 19 0,052 ieee 0,072 odd 0,045 operation 20 0,049 renewable 0,072 oddity 0,044 computing 21 0,045 aspect 0,072 design 0,043 classification 22 0,044 allocation 0,069 computer 0,042 fuzzy 23 0,040 consumption 0,065 information 0,041 component 24 0,039 datum 0,065 fi 0,041 optimization 25 0,039 platform 0,065 wi 0,038 adaptive 26 0,038 optimization 0,065 speedup 0,037 energy 27 0,037 improve 0,065 creative meronymous 28 0,037 enterprise 0,060 amdahl spiral 29 0,037 technique 0,060 modular specialized 30 0,172 special 0,145 column engineering Note: Several keywords have the same value; not all are listed here. Source: Author’s work Important keywords in the normalized nJK networks of selected journals Before applying the Line Island approach to the obtained normalized networks with the fractional approach 𝑛𝐽𝐾 , we removed the 8 most frequent keywords (green, system, information, technology, energy, computing, environmental, and management). We want to investigate the connection patterns among other keywords within the selected journal and thus reveal the differences in subfields of the journals’ scope. The keywords most frequently associated with the corresponding journals are shown in the Appendices, Figure 9 and Figure 10. The keywords reflecting the LECT NOTES COMPUT SC (Figure 8a) is related to energy, compute, design, technology, cloud, spatial, science, aware, computing, etc. A closer look at this publishing outlet reveals several conference proceedings series related merely to technological aspects of green sustainability. For instance, the main topics identified in this publication outlet are green and cloud computing, data analytics, renewable energy, energy informatics, and similar topics. We can highlight similarities by comparing this set of keywords with another book series (i.e., IFIP ADV INF COMM TE). Both publication outlets are primarily concerned with IT. However, some studies aim to bridge IT and green aspects, particularly addressing the potential of IT to reduce the negative impact on the environment. Given the keywords in SUSTAIN COMPUT-INFOR (Figure 10a), one can identify the technological dimensions of Green IT/IS (such as computing, software, server, Business Systems Research | Vol. 12 No. 2 |2021 platform), the environmental dimension (reduction, energy, power, efficiency, renewable, allocation, consumption, improvement, etc.) and the organizational dimension (such as enterprise, technique, aware). Several works in this journal are related to green and sustainable computing, green high-performance computing (green HPC), and green IT. This journal is dedicated to scientific work related to the interplay between computer science and engineering and sustainability. In addition, this journal has several special issues devoted to green computing. Regarding the ENVIRON MODELL SOFTW (Figure 9a), the keywords such as environment, integration, support, decision, information, interface, management, architecture, and software can be emphasized. Examining the papers within this journal, we can outline the green infrastructure as one of the streamlined topics. Furthermore, contrary to the publications mentioned above, the journal COMPUTER (Figure 10b) focuses predominantly on green energy and smart grid as far as green aspects are concerned. The keywords do not show a similar pattern compared to other publication outlets included in our study. Considering the FUTURE GENER COMP SY (Figure 8c), we can emphasize some similarities with other publication outlets such as LECT NOTES COMPUT SC and SUSTAIN COMPUT-INFOR. Green renewable energy, green computing, green data centers, and green IT are among the most notable research areas identified in FUTURE GENER COMP SY (Figure 8c). INFORM SYST FRONT (Figure 8b) also publishes the papers associated with Green IS practices and other non-technological aspects of Green IT/IS, such as attitudes towards Green IT, sustainability performance, etc. The keywords such as business, performance, sustainability, organization, innovation, strategy, and management also support the notation mentioned earlier on Green IS. While the scope of J CLEAN PROD (Figure 9b) is not related to IT or IS, there are also some papers on green technology in this journal, especially related to Green IT. The keywords indicate that attention is given to corporate/organizational sustainability and green technology, either information or energy, building, and other technologies. Business Systems Research | Vol. 12 No. 2 |2021 Figure 8 Keywords inside the journals LECT NOTES COMPUT SC, INFORM SYST FRONT, FUTURE GENER COMP SY Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Figure 9 Keywords inside journals ENIVORN MODELL SOFTW, J CLEAN PROD, IFIP ADV INF COMM TE Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Figure 10 Keywords inside journals SUSTAIN COMPUT-INFOR, COMPUTER, STUD SYST DECIS CONT Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Discussion and Conclusions Despite various barriers organizations face in implementing green operations (Alves et al., 2020), there are significant literature on Green IS/IT, its adoption, and practices. We aimed to identify the topics of Green IT/IS research published in scientific journals. This study makes an important contribution to the Green IT/IS literature and provides valuable information for policymakers in public administration and organizations about the advances and orientation of the Green IT/IS research topic to follow the sustainable goals of digital transformation. Our main contribution is to outline the Green IT/IS research area development from 1975. It should be noted that our research goes beyond the traditional qualitative review. A quantitative approach to SNA, which we undertook by applying keyword analysis, provides a more objective overview of the research area and its development. Therefore, the main contribution of this quantitative approach to literature review can be conceived to understand better the scientific discipline of Green IT/IS and open future research avenues. We portrayed the development of the Green IT/IS research area and emphasized how the greening of this emerging field has been incorporated into the IT/IS literature. We have highlighted the main knowledge pillars on which the Green IT/IS research streams are built (e.g., green computing, green infrastructure, green energy, green data centers, etc.). Temporal analysis of the words associated with the Green IT/IS revealed the rapid increase of Green IT-related keywords from 2000 onwards. Indeed, the interdisciplinary field of Green IT/IS has also developed accordingly. Interestingly, not all journals publishing Green IT/IS topics are IS-oriented, showing the importance and widespread interest in the topic. The scope of journals publishing Green IT/IS-related scholarly work extends beyond the information systems research field. J CLEAN PROD, one of the most eminent journals publishing research on sustainable development, has also published many Green IT/IS-related works. This is a clear signal that Green IT/IS has become interested in a wider research audience. The journal with the highest number of works related to Green IT/IS, LECT NOTES COMPUT SC, publishes many conference proceedings series. These research works focus more on technological aspects of green sustainability and less on academic discussions, which shows that there are still opportunities for academic research on Green IT/IS. The main contributions of this paper can be summarized as follows: (1) Successful implementation of quantitative methodology that can be applied to different research fields; (2) Comprehensive overview of the literature on the Green IT/IS topic; (3) Identification of the trends in the advancement of publications related to Green IT/IS over the past decades. The research provides an exhaustive overview of the keywords used in Green IT/IS research, their evolution, and orientation. It provides IT management in companies’ guidelines for their future activities and strategical decisions on IT investments related to sustainable development. This unbiased Green IT/IS literature review guides companies in preparing a solid background for their digital transformation process aligned with the sustainable development goals. From a management perspective, there are many innovative solutions to Green IT/IS challenges, and there is growing momentum to develop more Green IT /IS solutions that can be successfully marketed. Further on, the opportunities for future research that can be outlined are related to the Green IT/IS investigation in more depth. Focusing more on non-technological aspects of Green IT/IS is bound to become even more significant in light of the evolution of this literature stream. For example, the investigation of the factors influencing the internalization of Green IT/IS is currently not sufficiently grounded in theories of Green IT/IS. This could entail the investigation of Green IT/IS's underlying Business Systems Research | Vol. 12 No. 2 |2021 practices by integrating Green IT/IS into the management system of organizations, the development of Green IT/IS policies, objectives, procedures, etc. Moreover, the domains of the firm's resource-based view (RBV) and knowledge-based theory (KBV) of the firm are considered theoretical lenses that could shape the future development of Green IT/IS research. The Green IT /IS field is still in its infancy stage. Nevertheless, there is a growing scientific interest in the Green IT/IS phenomenon. In this sense, based on the results of our study, we argue that rigorous theory development should be the focus of research on Green IT/IS. Our study showed that Green IT/IS is not narrowly specialized but is rather an interdisciplinary-oriented research stream. We anticipate that the research field will gradually mature as more multidisciplinary and interdisciplinary studies are conducted. In addition, studies that focus on different contexts would enrich this line of research. For example, IT/IS research could be linked to the circular economy research, or future studies could expand the green perspective to a broader sustainability perspective with a balanced focus on sustainability dimensions. Besides, future research could delve into which specific aspects of Green IT/IS offer significant benefits in terms of improved business value. While this study contributes to the Green IT/IS literature in several ways, certain limitations need further attention. The analysis is based on the data derived from the WoS, and incorporating additional bibliographic sources could further increase the generalizability of the results. 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(2015), “A review of green is research and directions for future studies”, Communications of the Association for Information Systems, Vol. 37, pp. 395-429. 29. Watson, R. T., Boudreau, M.-C., Chen, A. J. (2010), “Information systems and environmentally sustainable development: energy informatics and new directions for the is community”, MIS Quarterly, Vol. 34 No. 1, pp. 23-38. 30. Watson, R. T., Boudreau, M.-C., Chen, A. J., Huber, M. (2008), “Green IS: Building Sustainable Business Practices”, Information Systems Journal, Vol. 76, pp. 1-15. Business Systems Research | Vol. 12 No. 2 |2021 Appendices Table A1 Vertices within the selected journals (I.) LECT NOTES COMPUT SC INFORM SYST FRONT FUTURE GENER COMP SY Rank Value Keyword Value Keyword Value Keyword 1 2.429 green 0.445 information 1.254 green 2 1.780 energy 0.445 green 0.921 energy 3 1.737 information 0.445 technology 0.846 computing 4 1.692 system 0.386 system 0.743 compute 5 1.255 technology 0.337 business 0.539 efficiency 6 1.114 computing 0.284 environmental 0.530 cloud 7 0.907 compute 0.274 management 0.453 management 8 0.893 cloud 0.271 performance 0.432 aware 9 0.779 base 0.248 sustainability 0.353 technology 10 0.758 environmental 0.184 supply 0.352 datum 11 0.681 datum 0.184 chain 0.352 center 12 0.627 management 0.147 model 0.350 power 13 0.608 service 0.134 organization 0.336 performance 14 0.597 efficiency 0.133 theory 0.298 information 15 0.564 aware 0.133 innovation 0.294 distribute 16 0.536 design 0.131 value 0.291 system 17 0.510 research 0.108 ecological 0.286 scheduling 18 0.498 sustainability 0.108 modernization 0.250 resource 19 0.491 resource 0.095 small 0.250 special 20 0.466 consumption 0.091 strategy 0.250 section 21 0.452 performance 0.090 energy 0.234 consumption 22 0.448 application 0.090 informatics 0.167 software 23 0.444 database 0.079 make 0.166 application 24 0.383 informatics 0.077 strategic 0.150 virtual 25 0.377 efficient 0.077 process 0.148 cluster 26 0.370 spatio 0.076 alignment 0.138 cost 27 0.370 temporal 0.074 determinant 0.136 parallel 28 0.347 analysis firm 0.136 task 29 0.335 algorithm adoption 0.133 virtualization 30 0.319 science development 0.130 hpc Several keywords have the same value, not all are listed here. Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table A2 Vertices within the selected journals (II.) ENVIRON MODELL SOFTW J CLEAN PROD IFIP ADV INF COMM TE Rank Value Keyword Value Keyword Value Keyword 1 1.254 green 0.484 information 2.402 information 2 0.921 energy 0.379 green 2.065 environmental 3 0.846 computing 0.379 technology 1.850 system 4 0.743 compute 0.288 environmental 0.918 technology 5 0.539 efficiency 0.273 management 0.722 green 6 0.530 cloud 0.235 system 0.630 datum 7 0.453 management 0.193 communication 0.559 sustainable 8 0.432 aware 0.182 model 0.532 architecture 9 0.353 technology 0.134 practice 0.463 model 10 0.352 datum 0.130 travel 0.439 management 11 0.352 center 0.130 business 0.411 semantic 12 0.350 power 0.130 collaboration 0.390 web 13 0.336 performance 0.130 meeting 0.375 analysis 14 0.298 information 0.130 virtual 0.321 service 15 0.294 distribute 0.123 corporate 0.320 search 16 0.291 system 0.101 innovation 0.306 sustainability 17 0.286 scheduling 0.101 performance 0.305 development 18 0.250 resource 0.101 sustainability 0.294 integrate 19 0.250 special 0.101 eco 0.283 user 20 0.250 section 0.100 public 0.283 infrastructure 21 0.234 consumption 0.099 company 0.260 support 22 0.167 software 0.097 framework 0.254 innovation 23 0.166 application 0.091 perspective 0.250 environment 24 0.150 virtual 0.083 impact 0.234 policy 25 0.148 cluster 0.083 implementation 0.227 open 26 0.138 cost 0.081 program 0.226 issue 27 0.136 parallel 0.071 videoconference 0.224 portal 28 0.136 task 0.071 swedish 0.223 semantics 29 0.133 virtualization 0.071 agency 0.220 experience 30 0.130 hpc 0.071 web 0.205 way Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table A3 Vertices within the selected journals (III.) SUSTAIN COMPUT-INFOR COMPUTER STUD SYST DECIS CONT Rank Value Keyword Value Keyword Value Keyword 1 2.368 green 2.644 green 1.546 green 2 1.728 computing 1.255 information 1.131 technology 3 1.063 energy 1.255 technology 1.040 information 4 0.946 issue 1.238 computing 0.985 engineering 5 0.869 special 0.533 response 0.747 system 6 0.688 software 0.450 column 0.531 computing 7 0.576 introduction 0.405 energy 0.478 energy 8 0.504 international 0.250 trading 0.478 model 9 0.504 conference 0.200 accountability 0.419 concept 10 0.485 power 0.200 solve 0.411 development 11 0.461 technology 0.200 measure 0.411 network 12 0.461 compute 0.200 issue 0.353 implementation 13 0.393 papers 0.200 society 0.261 complex 14 0.393 select 0.200 future 0.245 consumption 15 0.378 efficiency 0.188 design 0.245 software 16 0.375 system 0.167 odd 0.238 thing 17 0.344 information 0.167 oddity 0.238 internet 18 0.308 datum 0.167 2.000 0.236 component 19 0.293 igcc 0.143 simulation 0.227 datum 20 0.288 management 0.143 system 0.217 cloud 21 0.288 consumption 0.143 introduction 0.211 preface 22 0.270 server 0.143 power 0.211 architecture 23 0.265 performance 0.143 smart 0.199 design 24 0.260 model 0.143 modeling 0.177 control 25 0.254 aspect 0.121 development 0.176 compute 26 0.243 cloud 0.117 computer 0.170 optimization 27 0.228 reduction 0.091 visualization 0.170 algorithm 28 0.222 engineering language 0.168 efficient 29 0.219 sustainable fi 0.156 base 30 0.219 renewable wi 0.154 power Several keywords have the same value, not all are listed here Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 About the authors Anja Žnidaršič, Ph.D., received a Ph.D. in statistics from the University of Ljubljana, Slovenia, in 2012. From 2007 to 2013, she was a Teaching Assistant with the Department for Quantitative Methods at the Faculty of Organizational Sciences and, since 2018, an Associate Professor. Her research interests include technology acceptance, students’ performance, multivariate methods, missing data, and social network analysis. She has been a program committee member of several international scientific conferences and is actively involved in several bilateral and industry projects. She is a Slovenian statistical association and European Courses in Advanced Statistics member. The author can be contacted at anja.znidarsic@um.si. Alenka Brezavšček is an Associate Professor at the Faculty of Organizational Sciences, the University of Maribor in Slovenia. She received her Ph.D. in Quality Management from the University of Maribor. Her research interests are stochastic processes (theory and applications), system reliability and availability, maintenance optimization, and information/cybersecurity. At the Faculty of Organizational Sciences, she is a chair of the Methodological Department. She was involved in several applied projects focusing on the production process and maintenance optimization and conducted professional seminars on information/cybersecurity for various target groups. The author can be contacted at alenka.brezavscek@um.si. Matjaž Maletič is an Assistant Professor at the Faculty of Organizational Sciences, University of Maribor. His research focus can be assigned to the following research areas: quality management, asset management, and organizational sustainability. Apart from general research directions, he intends to link the research with innovation and organizational performance paradigms. He obtained his Ph.D. degree in Quality Management from the University of Maribor, Faculty of Organizational Sciences. He has been involved in several research projects and is a member of various professional associations, including the technical committee of the Slovenian Institute for Standardization. The author can be contacted at matjaz.maletic@um.si. Alenka Baggia, Ph.D., received a Ph.D. degree in management information systems from the University of Maribor, Slovenia. She is an Assistant Professor at the Faculty of Organizational Sciences, University of Maribor. Her research interests include green information systems, discrete event simulation, technology acceptance, scheduling, and group dynamics. She has been a program committee member of several international scientific conferences. She has been actively involved in several national, international (EU, CE, cross-border, bilateral), and industry projects. She is a member of Slovenian society Informatika. The author can be contacted at alenka.baggia@um.si. Daria Maltseva, Ph.D., is a Senior Research Fellow and Deputy Head at the International Laboratory for Applied Network Research, National Research University Higher School of Economics, Russia. She received a Ph.D. at the Faculty of Sociology of the Russian State University for the Humanities. During her internships at the Centre for Methodology and Informatics, Faculty of Social Sciences, University of Ljubljana, she was also educated. Her main research interests are social network analysis, network approach in sociology, bibliographic studies, and sociology of science. She is actively engaged in several national scientific projects. The author can be contacted at dmaltseva@hse.ru. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Business Systems Research Journal de Gruyter

A Bibliometric Network Analysis of Green Information Technology and Green Information Systems Research

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de Gruyter
Copyright
© 2021 Anja Žnidaršič et al., published by Sciendo
ISSN
1847-9375
eISSN
1847-9375
DOI
10.2478/bsrj-2021-0017
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Abstract

Background: In recent years, the concepts of Green Information Technology and Green Information Systems (Green IT/IS) have attracted the attention of many researchers. Several environmental and sustainability studies have suggested that smart usage of Green IT/IS is one of the most important enablers for sustainable development in organizations and plays an essential role in greening the planet. Objectives: This paper aims to examine the development of the Green IT/IS field based on the published works. The focus is on analysing the keywords of related papers obtained from the Web of Science database. Methods/Approach: Based on the two- mode network of papers and keywords, the analysis of co-occurrence of keywords is provided. The most frequent keywords discovered by the temporal network analysis are presented from the perspective of the most prominent journals. Results: The main pillars of knowledge in Green IT/IS research are highlighted, and a chronological map of the field is provided. Conclusions: Green IT/IS's studied field shows constant growth in the last decades, and the results indicate the trends of future development in the field. The paper is one of the first studies that apply the bibliographic network analysis approach to the field of Green IT/IS. Keywords: Green Information System; Green Information Technology; bibliographic networks JEL classification: D85 Paper type: Research article Received: Apr 08, 2021 Accepted: Aug 09, 2021 Acknowledgments: This research was supported by the Slovenian Research Agency; Program No. P5-0018 – Decision Support Systems in Digital Business. Citation: Žnidaršič, A., Maltseva, D., Brezavšček, A., Maletič, M., Baggia, A. (2021), “A Bibliometric Network Analysis of Green Information Technology and Green Information Systems Research”, Business Systems Research, Vol. 12, No. 2, pp. 17-45. DOI: https://doi.org/10.2478/bsrj-2021-0017 Business Systems Research | Vol. 12 No. 2 |2021 Introduction In the last two decades, organizations have strived to achieve higher levels of sustainable development to contribute to the greening of the planet, primarily through the advanced use of information technology (IT) and information systems (IS) (Melville, 2010; Watson et al., 2008). The role of smart use of IT/IS in contributing to environmentally responsible human activities has become an attractive field of research and is therefore highly discussed in the literature. Consequently, aligned with the practical use in organizations, the discussions and research on these topics, two main concepts, Green Information Technology (Green IT) and Green Information Systems (Green IS), have become notable terms in professional and academic publications. Due to the growing interest in the Green IT/IS research field, several studies have been published in recent years that deal with the related research topics. Esfahani et al. (2015) noted that the earliest study in this area was published back in 2007. Initially, the studies focused on Green IT, where the term Green IS was first introduced by Melville (2010). This work described the concept of information systems innovation for environmental sustainability and was included in the 20 most cited studies on green innovation (Albort-Morant et al., 2017). Later, Brooks et al. (2012) identified the main streams of Green IT/IS-related studies and provided a review of the literature from practitioners and academics. The authors reveal that most of the research focused on the concepts of Green IT, probably due to its popularity among practitioners. In addition, Loeser (2013) extended the literature search to the AIS electronic library using the keywords green IS and green IT and related terms such as sustain*, green or environmental. It was found that professional studies were ahead of academic ones, as most Green IT/IS papers were published in conference proceedings, while publications in top IS journals were rare. On the other hand, Wang et al. (2015) significantly expanded the list of search terms (i.e., keywords). They classified Green IT/IS-related papers into four categories: initiation, enterprise strategies and practices, adoption framework, and outcomes. Further, Singh et al. (2020) examine five segments in the Green IS research area: Green IS concept, innovation and technology, the impact of green initiatives, measures and policies, and global context. Moreover, Esfahani et al. (2015) provided a review of research questions already addressed and the current state of research, while Bokolo (2016) used a set of search terms related to the concepts of Green IT/IS and retrieved 137 papers published in journals as well as conference proceedings. Based on this literature review, the authors provided a set of determinants that encourage/discourage organizations from incorporating Green IT/IS practices. One of the systematic literature reviews was provided by Muhammad et al. (2017), who used different search terms to retrieve Green IT/IS-related publications from various databases. The authors found that good search strings are difficult to formulate; they applied the snowballing method to complement the database search. All these studies provide high-level research agendas and have opened new possibilities for future Green IT/IS research. One of the most important findings from the systematic Green IT/IS literature reviews concludes that the terms Green IT/IS have been vague concepts for several years. Both fundamental terms have often been used interchangeably without recognizing the differences, leading to confusion in professional and academic societies. While several authors attempted to present a clear distinction between the two terms (Brooks et al., 2012; Deng et al., 2015; Muhammad et al., 2017), Loeser (2013) distinguishes the terms based on the differences in the scopes. Following Loeser (2013), it is now clearly defined that the term “Green IT refers to measures and initiatives which decrease the negative Business Systems Research | Vol. 12 No. 2 |2021 environmental impact of manufacturing, operations, and disposal of Information Technology (IT) equipment and infrastructure”, while the term Green IS refers to “practices which determine the investment in, deployment, use and management of information systems (IS) in order to minimize the negative environmental impacts of IS, business operations, and IS-enabled products and services”. Besides the academic contribution, the research outcomes in Green IT/IS are also essential from the managerial implications point of view. Namely, Green IT/IS that are oriented to minimize the negative environmental impact is one of the key enablers of sustainable digital transformation in any contemporary organization (Gils et al., 2020). To assure organizations the valuable information for decision making for aligning the digital transformation activities with the sustainable development goals, up-to-date direction for proper use of Green IT/IS is needed. Therefore, the findings of already mentioned reviews on Green IT/IS literature are more than valuable. However, to gain a comprehensive overview of development directions, it would be worthwhile to supplement the qualitative literature research techniques with an appropriate quantitative attempt. This paper aims to provide a comprehensive literature review on Green IT/IS to examine the development of the research field of Green IT/IS based on the published papers. Aligned this objective, the following research question was formulated: RQ: How have scientific publications on Green IT /IS research evolved over the past decades? In addition to conventional search engines for literature analysis, advanced social network analysis (SNA) methods are applied. Our investigation will be based on Green IT/IS-related papers published in the Web of Science (WoS) database until 2020. When searching for the papers, the basic keywords Green information technology and Green information systems are expanded with various queries such as: ”green information system*”, ”sustain* information system”, ”environment* information system*”, ”environmental informatics”, ”energy informatics”, ”green software”, ”green computing”, ”green information communication technology*”, and ”information system* for sustainable development”. The justification for selecting the listed keywords is presented under Methodology Section. From the obtained set of works in WoS, the complete descriptions were extracted considering the authors, the keyword list, and the work titles. Together with the initial hits, their citing articles were also obtained. Details on the data collection phase, converting raw data to network format, and analyses are presented in the Methodology section. The paper is organized as follows; first, the process of bibliometric data collection and the preparation of the working set of keywords is presented, followed by the description of the derived networks, the normalized networks, and the temporal networks. The results start with the analyses of a two-mode network of works and keywords, followed by analyses of the keyword co-occurrence network. Furthermore, the selected journals that publish Green IT/IS topics were identified, and networks of emerging keywords within these journals were constructed and analysed. The Analysis employed enables the representation of the most frequently used keywords in the Green IT/IS research area through the lens of the most prominent journals. Moreover, the results provide a chronological mapping of the research field and show its future development trends. In the conclusions, an overview of the main findings is given, and our contribution to this research field and gaps for future research are identified. Business Systems Research | Vol. 12 No. 2 |2021 Methodology In the research design and data analyses we followed similar bibliographic research (e.g., Batagelj et al. 2013, 2014, 2019, 2020). For the analyses of publication practices on Green IT/IS, we analysed works included in WoS. We used the computer program WoS2Pajek to transform data into a network format to analyse the obtained data. The computer program Pajek for network analyses and Python libraries Nets and TQ for analyses of temporal networks. Data collection Data was collected from WoS Core Collection until 2020 using the following queries: ”green information system*”, ”sustain* information system”, ”environment* information system*”, ”environmental informatics”, ”energy informatics”, ”green software”, ”green information technology*”; ”green computing”, ”green information communication technology*”, ”information system* for sustainable development”. The justification of the ten selected queries is presented below. • green information system* (and the abbreviation Green IS*) • green information technology* (and abbreviation green IT*) • sustain* information system*: Diverse functionalities can characterize IS as Green. According to Chowdhury (2012), one of the characteristics is the change in software development life-cycle, which aims to reduce the potential negative environmental impacts of the system. Aligned with this definition, the term sustainable information system has to be classified as a type of Green IS, whereas it is often used interchangeably. • environment* information system*, also known as an environmental management information system, is used to track, measure, and monitor the environmental variables: emission, waste, toxicity, and carbon footprint (Sanita et al., 2017). • environmental informatics: In the 1990s, the new concept of Environmental informatics emerged, focused on the techniques of effective collection, storage, retrieval, and processing of complex environmental data (Avouris et al., 1995), which was later classified as Green IS. • energy informatics: The concept of energy informatics was introduced by (Watson et al., 2010), describing the discipline dealing with the role of IS in the reduction of energy consumption. • talking about green computing or rather green information communication technology (Green ICT) mainly sets the focus on hardware issues while software issues are directly named green software (Kern, 2018). • information system* for sustainable development: The term Information system for sustainable development (Hilty et al., 2015) was used to describe various information systems supporting green initiatives. Based on the search queries listed, the original hits and additional articles citing those hits were obtained. Construction of network data Using the computer program WoS2Pajek 1.5 (Batagelj, 2017), we converted the raw text WoS file into a collection of different networks. The program WoS2Pajek 1.5 transforms phrases from the raw WoS file into individual words when constructing networks (e.g., the phrase green information system is split into three keywords Green, information, and system). The obtained works include papers in scientific journals, papers in conference proceedings, reports, books, etc. We obtained one-mode Business Systems Research | Vol. 12 No. 2 |2021 citation network 𝐶𝑖 𝑡 𝑒 of works and three two-mode networks: the authorship network on works  authors ( ), the journal network on works  journals ( ), and the keywords network on works  keywords ( ). The authors were identified from the AU field in the WoS entry, the journals from the field CR or J9, the keywords from the fields of Author Keywords (DE field), Keywords Plus (given by ID field), and the document title from the field TI. Two types of works were extracted from WoS: works with full descriptions (referred as hits) and with partial description (referred as terminal). In the case of terminal works the journal name, the first author, the year of publication, the issue of the journal, and the first-page number were available. Keywords, abstract, and citations are missing in the case of terminal works. Loops and multiple lines were removed from all networks, and we obtained the basic networks labelled as 𝑒𝐶𝑖𝑡 , , , and . Sizes of the networks are presented in Table 1. Since all terminal works (320 586) contain only partial information (without keywords and citations), we excluded them from the analyses. Since we aim to analyse the keywords of the works from the WoS on selected queries, we also removed all 9 530 citing articles. The resulting reduced networks (of hits) without citing articles are as follows: 𝑒𝑅𝐶𝑖𝑡 , 𝐴𝑟𝑊 , 𝐽𝑟𝑊 , and 𝐾𝑟𝑊 . Sizes of the sets of these networks are presented in Table 1. Table 1 Number of vertices in obtained and reduced networks Networks Business Performance Basic from WoS Reduced to hits Number of works 332 047 1 931 Number of keywords 13 635 4 017 Number of authors 148 348 4 342 Number of journals 26 806 669 Source: Author’s work Derived networks A rectangular two-mode matrix is usually used to represent the two-mode network. Using matrix multiplication of two matrices of compatible dimensions a new network can be constructed. More precisely, two rectangular matrices can be multiplied if the number of columns of the first matrix corresponds to the number of rows of the second matrix. Details on construction of networks can be found in Batagelj et al. (2013, 2014). Following this procedure two derived networks, described below were constructed. First, the network of co-occurrence of keywords (keywords times keywords ( )) = 𝐾𝑟𝑊 ∗ 𝐾𝑟𝑊 (1) The weight of an edge in between two nodes 𝑤 [𝑘 1; 𝑘 2] represents the number of works in which the selected keywords 𝑘 1 and 𝑘 2 were mentioned together. Second, the network of journals and keywords was obtained with the following multiplication: = 𝐽𝑟𝑊 ∗ 𝐾𝑟𝑊 (2) The edge in a network indicates how many times the journal 𝑗 contained the keyword 𝑘 . In the following sections, the detailed descriptions of the calculated networks as well as the result of the analyses are presented. 𝐽𝐾𝑟 𝐽𝐾𝑟 𝐾𝐾𝑟 𝐾𝐾𝑟 𝐾𝐾𝑟 𝑊𝐾 𝑊𝐽 𝑊𝐴 𝑊𝐾 𝑊𝐽 𝑊𝐴 Business Systems Research | Vol. 12 No. 2 |2021 Normalization of derived networks Derived networks may have some disadvantages, as, for example, works with a large number of authors or keywords may be overrated in terms of the contribution of such a work. To overcome this issue, we used the fractional approach in our analyses (Batagelj et al., 2013; 2019; Gauffriau et al., 2007). The importance of these works was normalized so that the sum of all weights in the calculating network is equal to 1. We can illustrate this situation with the following example. In the (rectangular) two- mode network of works  keywords (𝐾𝑟𝑊 ) an out-degree of a particular work is equal to the number of work’s keywords, and an indegree of a selected keyword is equal to the number of works which included that word among the listed keyword. If the normalization is employed for the network, the weight of each arc is divided by the out-degree of a selected node which is equal to the sum of the weights of all the arcs pointing from that node. The contribution of each paper is normalized and the 𝑛𝑊𝐾 is calculated as follows: 𝑊𝑟𝐾 [𝑤 ,𝑘 ] 𝑛𝑊𝐾 [𝑤 , 𝑘 ] = (3) ( ) max (1,𝑢𝑑𝑒𝑔𝑜𝑡 𝑤 ) where 𝑤 is work and 𝑘 is a keyword. The proposed normalization approach can be applied to different two-mode networks. In addition, for the normalization of the network, the term frequency- inverse document frequency (TF–IDF) approach was used (Robertson, 2004). Using this approach, the importance of a word to a document in a corpus of documents can be considered. Temporal networks Temporal networks have time quantities in their description specifying which links (or/and nodes) are active at certain points in time. Based on the WKr network with combined time quantities, temporal networks were constructed (Batagelj et al., 2016, 2020) using the Python libraries (Batagelj et al., 2014). Two types of temporal networks can be constructed – instantaneous (where values are given for each year) WKins, and cumulative (where cumulative values over the years are calculated) 𝑢𝑚𝐾𝑐𝑊 . With multiplication and normalization procedures employed on temporal networks described above, we can calculate various new temporal networks. Results This section presents the results of different analyses performed to reach the research objective. First, with the analysis of the network, we identify the most frequent keywords and their distribution over the years. Second, the most important journals where Green IT/IS topics are published are identified, and subtopics published inside those journals are investigated. Analyses of the WK network The works cited only (also known as terminal) do not have any keywords. In our case, the network consists of 96,5% of such works. Therefore, we will focus on analysing the reduced network of hits 𝐾𝑟𝑊 . In the works with complete description (𝐾𝑟𝑊 network) the number of keywords ranges from 2 to 57. The distribution of keywords is presented in Figure 1. Works contain 4 017 different keywords, and more than half of them (2 105) are mentioned only once, while 604 keywords are mentioned twice. 𝑊𝐾 𝑊𝐾 𝐽𝐾 𝑊𝐾 Business Systems Research | Vol. 12 No. 2 |2021 Figure 1 Frequency distribution of the keywords Source: Author’s illustration Eight of the most frequent vertices in the 𝐾𝑟𝑊 network are green, system, information, technology, energy, computing, environmental, and management (Table 2). The word green occurs 1 226 times. This is expected since we use these words in phrases of the search query. Based on the most frequent keywords, the research field of Green IT/IS could be mapped. As expected, the research field consists of informatics or technically oriented keywords such as data (in tables and figures, the singular form of the noun is used - datum), compute, cloud, base, communication, software, network, center, algorithm, application, while also environmental aspects sustainability, consumption, sustainable, environment, etc. and organization performance efficiency, performance, optimization, process, etc. are also covered. Several words are closely related to research: analysis, study, approach, framework, etc. Some words also have a different meaning related to the context, e.g., center, issue, column, etc. At the same time, their identification within a particular journal might reveal the specific scope or specialization of the journal. Business Systems Research | Vol. 12 No. 2 |2021 Table 2 The frequencies of the most used keywords in the nWKr network Rank Value Keyword Rank Value Keyword Rank Value Keyword 1 1 226 green 35 105 approach 68 62 assessment 2 936 information 36 103 study 69 60 adoption 3 767 system 37 102 virtual 70 59 behavior 4 668 energy 38 96 framework 71 57 save 5 633 technology 39 92 impact 72 56 sensor 6 559 computing 40 90 machine 73 54 carbon 7 413 environmental 41 86 optimization 74 54 integrate 8 378 management 42 84 scheduling 75 53 monitoring 9 313 datum 43 84 process 76 52 social 10 299 compute 44 82 server 77 52 infrastructure 11 298 cloud 45 81 strategy 78 51 challenge 12 291 model 46 78 dynamic 79 51 cluster 13 267 power 47 78 architecture 80 50 simulation 14 248 sustainability 48 77 smart 81 50 policy 15 245 base 49 76 virtualization 82 50 control 16 241 efficiency 50 76 case 83 49 gi 17 217 performance 51 75 decision 84 49 method 18 213 communication 52 74 research 85 48 multi 19 209 consumption 53 72 support 86 47 waste 20 187 sustainable 54 71 practice 87 47 grid 21 184 software 55 70 perspective 88 46 informatics 22 182 network 56 68 innovation 89 45 issue 23 182 environment 57 68 distribute 90 44 scale 24 177 efficient 58 68 web 91 43 computer 25 163 center 59 66 business 92 42 emission 26 162 use 60 64 time 93 42 industry 27 161 resource 61 64 internet 94 42 eco 28 149 aware 62 64 theory 95 42 quality 29 147 algorithm 63 64 allocation 96 42 change 30 143 development 64 64 implementation 97 42 migration 31 142 design 65 63 engineering 98 41 user 32 137 analysis 66 62 evaluation 99 41 factor 33 137 service 67 62 mobile 100 41 consolidation 34 127 application Note: As a keyword in works, a plural form data is used Source: Author’s work Temporal analysis of the keywords We looked at the temporal distributions of the number of all keywords and unique (different) keywords used in Green IT/IS (Figure 12). Keywords on Green IT/IS first appeared in the 1990s, while the number of publications started increasing in 2010. During the last few years, there have been around 3 000 publications in WoS on that topic. From 2013, around 1 000 unique keywords on IT/IS are published per year. Business Systems Research | Vol. 12 No. 2 |2021 Figure 2 Distributions of keywords on Green IT/IS Source: Author’s illustration To determine the importance of a particular keyword over time, we calculated a proportion (ranging from 0% to 100%) of a particular keyword occurrence according to the keyword with the highest occurrence for each year based on the 𝑛𝑠𝐾𝑖𝑊 network (Figure 3). We created green, system, information, technology, energy, computing, environmental, and management pictures. Some of the keywords shown in Figure 3 have been used for a long time, as their first appearance dates back to the 1970s (e.g., system, information, and environmental). Some words appear around 1995 (energy, technology, and management), while Green becomes popular after 2005. It is quite reasonable to expect the keywords system and information to reach the maximal level of usage (or importance) in almost all years after their introduction, with a small decline after 2010, probably due to the more sophisticated subdomains of usage and the broader set of keywords used, as shown in Figure 2. Other information systems keywords appear from 2000, and their usage (or importance) is the most extensive around 2015 (e.g., computing). The keyword environmental has been used since 1975, and it became extremely popular in 1990. There is a small drop in 2010, but its occurrence is still around 30% of the most popular words each year. The keyword green is a newly developed concept related to IS and IT, which appeared in 2009. Business Systems Research | Vol. 12 No. 2 |2021 Figure 3 Distribution of keyword appearance proportion considering the eight most frequent keywords Source: Author’s illustration Keywords co-occurrence network By column projection of the normalized hits 𝑟𝑛𝑊𝐾 network, the normalized one-mode network 𝑛𝐾𝐾𝑟 was calculated as follows: 𝑛𝐾𝐾𝑟 = n𝐾𝑟𝑊 ∗ 𝑟𝑛𝑊𝐾 (4) After the deletion of loops and the transformation of bidirectional arcs to edges, the calculated network 𝑛𝐾𝐾𝑟 consists of 4 017 nodes and 126 639 edges. In this new calculated network, the weight on the edges between the keywords is equal to the fractional co-occurrence of keywords 𝑖 and 𝑗 in the same works. According to Batagelj et al. (2019) the 𝑛𝐾𝐾𝑟 network is symmetric: 𝑛𝐾𝐾𝑟 [𝑖 ; 𝑗 ] = 𝑛𝐾𝐾𝑟 [ 𝑗 ; 𝑖 ] (5) Furthermore, value 1 of a particular work is redistributed over the keywords: ∑ 𝑛𝐾𝐾𝑟 [𝑖 ; 𝑗 ] = |𝑊 | (6) 1,𝑗 Since 𝑛𝐾𝐾 ℎ is a valued network, we employed the Line Island approach (Batagelj et al., 2014) and searched for the islands of sizes 2 to 75. We obtained 13 islands, 10 of Business Systems Research | Vol. 12 No. 2 |2021 which consist of only one pair of vertices. Figure 4 represents the largest island with 75 vertices. The width and greyscale are proportional to the line weight, calculated based on the fractional co-occurrence approach described in the following subsection. Strongly associated (with the largest line weights) are green - computing, green - technology, green - information, system - information, and environmental - information. This was expected since these words are included in our search queries. Therefore, we removed the first 8 most frequent keywords from the network and repeated the Line Island approach. We obtained 73 islands ranging in size from 2 to 50 vertices, 78% of which consist of only one pair of vertices. The largest island is represented in Figure 6 and is described below. When we compare the island with 75 vertices obtained from the 𝑛𝐾𝐾𝑟 network (Figure 5) instead of its non-normalized version ( ) (Figure 4) the following words appeared to be more important: nature, education, challenge, sensor, monitoring, database, special, issue, wireless, greening, introduction, while some others were not included in this island (e.g., adoption, behavior, social, theory, time). Figure 4 Line Island of network on 75 vertices Source: Author’s illustration 𝐾𝐾𝑟 𝐾𝐾𝑟 Business Systems Research | Vol. 12 No. 2 |2021 Figure 5 Line Island of 𝑛𝐾𝐾𝑟 network on 75 vertices Source: Author’s illustration The above exploratory analysis results show that 8 of the most frequent keywords (green, system, information, technology, energy, computing, environmental, management) are connected to many other vertices. We excluded them from the network to obtain connection patterns between other keywords and again applied the Line Island approach. Figure 6 represents the largest island with 50 vertices. The most central part of the network is a pair of keywords compute and cloud, and both vertices are connected to the datum and center. Other vertices are efficiency, scheduling, application, resource, allocation, algorithm, virtual, machine... Other keywords that came up are virtual - machine, sustainable - development, and power - consumption. Around sustainability and development, the keywords software, communication, and sustainability also stand out. Business Systems Research | Vol. 12 No. 2 |2021 Figure 6 The largest line island (size 50) of 𝑛𝐾𝐾𝑟 network with removed 8 vertices Source: Author’s illustration Smaller islands (Figure 7) identify some concepts related to the information systems domain (core - multy - agent, cloudstack - simulation - nanodevice), others are enterprise-oriented (make - decision - support, cause - partnership - stakeholder - unified - create - common) or environmentally oriented (biodiversity - endanger - species, emission - footprint - carbon). Further analyses of the 2-vertices islands show that some common phrases with limited value appeared in the information systems domain, e.g., publish-subscribe, special-issue, column-response, real-time, e-waste, etc. To get a deeper insight into those keywords, we will present them in the context of the most popular journals from the field (see the next section). Figure 7 Line islands of size 3 to 6 of 𝑛𝐾𝐾𝑟 network with removed 8 vertices Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Keywords and journals First, the analysis of 𝐽𝑟𝑊 shows the most important journals in which Green IT/IS topics are published (Table 3). Table 3 Journals with the highest number of works on Green IT/IS Rank Title # of Abbreviated title & ISSN JIF SNIP works 1 Lecture Notes in Computer Science LECT NOTES COMPUT SC 48 √ 0302-9743 2 IFIP Advances in Information and IFIP ADV INF COMM 35 √ Communication Technology 1868-4238 3 Sustainable Computing-Informatics & SUSTAIN COMPUT-INFOR 29 √ √ Systems 2210-5379 4 Studies in Systems, Decision, and STUD SYST DECIS CONT 23 √ Control 2198-4182 5 Advanced Intelligent Systems ADV INTELL SYST 21 2640-4567 6 Communications in Computer and COMM COM INF SC 20 √ Information Science 1865-0929 7 Environmental Modelling & Software ENVIRON MODELL SOFTW 19 √ √ 1364-8152 8 Future Generation Computer Systems FUTURE GENER COMP SY 19 √ √ 0167-739X 9 Computer COMPUTER 15 √ √ 0018-9162 10 Sustainability SUSTAINABILITY-BASEL 15 √ √ 2071-1050 11 It Professional IT PROF 12 √ 1520-9202 12 Procedia Computer Science PROCEDIA COMPUT SCI 12 √ 1877-0509 13 Cluster Computing CLUSTER COMPUT 11 √ √ 1386-7857 14 Journal of Supercomputing J SUPERCOMPUT 11 √ √ 0920-8542 15 Information Systems Frontiers INFORM SYST FRONT 10 √ √ 1387-3326 16 Journal of Cleaner Production J CLEAN PROD 10 √ √ 0959-6526 17 Advanced Science Letters ADV SCI LETT 8 √ 1936-6612 18 Computer Networks COMPUT NETW 8 √ √ 1389-1286 19 Journal of Strategic Information J STRATEGIC INF SYST 8 √ √ Systems 0963-8687 20 Fujitsu Scientific & Technical Journal FUJITSU SCI TECH J 8 √ √ 0016-2523 21 Proceedings of the Hawaii P ANN HICSS 8 International Conference on System N/A Sciences 22 Concurrency Computation Practice CONCURR COMP-PRACT E 8 √ √ and Experience 1532-0626 23 Advanced Materials Research ADV MATER RES-SWITZ 8 1662-8985 24 Advances in Computer Science ACSR ADV COMPUT 8 Research 2352-538X Note: ISSN is not-applicable. Book series, different ISSN for each volume Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table 3 presents 24 journals with the highest number of published papers among our hits along with the information whether they have the Journal Impact Factor (JIF) (Clavrivate, 2019) or the Source Normalized Impact per Paper (SNIP) factor (Elsevier B.V., 2019) to reveal publishing culture among the authors. There were 48 papers published in the journal Lecture notes in computer science (LECT NOTES COMPUT SC), followed by 35 papers in the journal IFIP Advances in Information and Communication Technology (IFIP ADV INF COMM) and 29 papers in the journal Sustainable Computing- Informatics & Systems (SUSTAIN COMPUT-INFOR). The construction of network and its normalization is presented below. First, the derived network of journals  keywords was obtained by multiplying two two- mode networks = ∗ (7) To analyse keywords inside journals, two types of normalization were used: fractional approach and term frequency-inverse document frequency (TF-IDF). Fractional normalization The normalized reduced networks 𝑟𝑛𝑊𝐽 and 𝑟𝑛𝑊𝐾 were used to calculate a new normalized network of journals and keywords as follows: 𝑛𝐽𝐾 = 𝑛𝑊𝐽 ∗ 𝑛𝑊𝐾 (8) In the new network 𝑛𝐽𝐾 , the weight on the edges between the nodes 𝑗 and 𝑘 is equal to the fractional contribution of a journal 𝑗 for a given keyword 𝑘 ; or of a group of journals 𝐶 : [ ] ∑ 𝐶 , 𝑘 = [𝑗 , 𝑘 ] (9) 𝑗 ∈𝐶 Term frequency-inverse document frequency (TF-IDF) 𝑇𝐹 − 𝐼𝐷𝐹 approach, proposed by Robertson (2004), was employed to the network. In the normalization procedure the importance of a keyword for within a journal is considered. We used reduced networks 𝐽𝑟𝑊 and 𝐾𝑟𝑊 for network construction, 𝑇𝐹 and 𝐼𝐷𝐹 were defined (and calculated) as follows. 𝑇𝐹 represents the number of times a keyword appears in a selected journal, divided by the total number of (all different) keywords in the journal. 𝐼𝐷𝐹 is defined as the logarithm of the number of the journals in the corpus divided by the number of journals in which the specific keyword occurs. We calculated 𝑇𝐹 − 𝐼𝐷𝐹 indices for the keywords were calculated in the following way: 𝑇𝐹 − 𝐼𝐷𝐹 [𝑘 , 𝐽 ] = 𝑇𝐹 [𝑘 , 𝑗 ] ∗ 𝐼𝐷𝐹 [𝑘 ] (10) # times 𝑘 appeared in 𝐽 [ ] 𝑇𝐹 𝑘 , 𝑗 = (11) total # 𝐾 in 𝑗 # 𝐽 [ ] 𝐼𝐷𝐹 𝑘 = (12) # 𝐽 with 𝑘 where 𝑘 is a keyword, 𝐾 – all the keywords, 𝑗 – a journal, and 𝐽 – all the journals. 𝑙𝑜𝑔 𝐽𝐾𝑟 𝐽𝐾𝑟 𝐽𝐾 𝐽𝐾 𝐽𝐾 𝑊𝐾 𝑊𝐽 𝐽𝐾 𝐾𝐽 Business Systems Research | Vol. 12 No. 2 |2021 Keywords in the selected journals To analyse the most frequent or important keywords on Green IT/IS, we selected nine top journals (denoted with bold in Table 3) according to the number of papers received and their influence measured by JIF or SNIP. Three journals with the highest number of published works are Lecture Notes in Computer Science (LECT NOTES COMPUT SC), IFIP Advances in Information and Communication Technology (IFIP ADV INF COMM), and Sustainable Computing- Informatics & Systems (SUSTAIN COMPUT-INFOR). All three journals are indexed in Scopus, and the third one is also indexed in JIF. In companion to these three journals, we selected five other prestigious journals with the highest JIF among the received journals: Information Systems Frontiers (INFORM SYST FRONT), Future Generation Computer Systems (FUTURE GENER COMP SY), Environmental modeling & software (ENVIRON MODELL SOFTW), Journal of Cleaner Production (J CLEAN PROD), and Computer (COMPUTER). The analysis of the co-occurrence of keywords in the selected journals is presented below. TF-IDF indices approach for keywords in selected journals We employed the TF-IDF approach for nine selected journals. According to TF-IDF, the most important keywords are presented in Table 4 - Table 6. Table 4 The most important keywords according to TF-IDF indices (journals LECT NOTES COMPUT SC, INFORM SYST FRONT, FUTURE GENER COMP SY) LECT NOTES COMPUT SC INFORM SYST FRONT FUTURE GENER COMP SY Rank Value Keyword Value Keyword Value Keyword 1 0,063 energy 0,176 business 0,128 compute 2 0,059 compute 0,094 modernization 0,103 efficiency 3 0,056 design 0,088 supply 0,101 aware 4 0,053 technology 0,087 chain 0,091 distribute 5 0,052 cloud 0,077 value 0,089 energy 6 0,052 spatio 0,072 performance 0,083 cloud 7 0,051 science 0,072 sustainability 0,079 center 8 0,051 aware 0,069 technology 0,070 computing 9 0,049 computing 0,069 organization 0,069 exploit 10 0,049 service 0,064 alignment 0,067 scheduling 11 0,047 temporal 0,061 environmental 0,064 management 12 0,047 datum 0,060 determinant 0,063 performance 13 0,046 base 0,058 innovation 0,062 power 14 0,046 efficiency 0,057 small 0,060 resource 15 0,046 green 0,056 theory 0,056 datum 16 0,045 application 0,056 strategic 0,054 hardware 17 0,043 system 0,054 management 0,053 optimal 18 0,043 research 0,050 ecological 0,051 hpc 19 0,043 consumption 0,047 pea 0,050 heuristic 20 0,042 information 0,047 carrot 0,049 consumption 21 0,040 community 0,047 just 0,048 green 22 0,037 performance 0,047 complementarity 0,047 parallel 23 0,037 sustainability 0,047 doi 0,044 application 24 0,037 provision 0,047 pvt 0,043 indicator 25 0,036 management 0,047 midlands 0,043 cost 26 0,035 platform 0,047 gratification 0,042 protein 27 0,035 environmental 0,046 eco routine 28 0,035 smart 0,046 informatics fip 29 0,034 conservation 0,046 make backtracking 30 0,034 process 0,045 firm datacentre Note: Several keywords have the same value; not all are listed here. Source: Author’s work The keyword green is the most important keyword in 6 out of 9 journals, while in the other three journals, the first place belongs to the keyword information. Most of the Business Systems Research | Vol. 12 No. 2 |2021 most important keywords within the journals are related to information systems, while in two journals, specificity is shown in the publication culture. Two important keywords within the Computer (COMPUTER) journals are column and response, indicating that the authors write replies to the initial columns (papers). Similarly, four of the most important keywords in the journal Sustainable Computing-Informatics & Systems (SUSTAIN COMPUT-INFOR) are related to publishing: special - issue, conference - paper. The connections between the keywords specific to the journal are presented in the following subsection. Table 5 The most important keywords according to TF-IDF indices (journals ENIVORN MODELL SOFTW, J CLEAN PROD, IFIP ADV INF COMM TE) ENVIRON MODELL SOFTW J CLEAN PROD IFIP ADV INF COMM TE Rank Value Keyword Value Keyword Value Keyword 1 0,118 environmental 0,070 travel 0,125 environmental 2 0,117 integrate 0,070 meeting 0,112 semantic 3 0,112 integration 0,064 corporate 0,094 portal 4 0,110 ei 0,062 eco 0,085 semantics 5 0,105 support 0,056 financial 0,077 search 6 0,101 decision 0,055 environmental 0,074 web 7 0,084 service 0,053 company 0,071 information 8 0,076 ogc 0,052 collaboration 0,071 architecture 9 0,074 web 0,052 innovation 0,063 system 10 0,074 system 0,050 program 0,056 infotercio 11 0,071 design 0,050 technology 0,056 sise 12 0,065 information 0,048 management 0,056 ho 13 0,060 interface 0,048 practice 0,056 diagram 14 0,058 example 0,046 communication 0,056 subsystem 15 0,057 management 0,044 empirical 0,056 link 16 0,055 open 0,043 public 0,055 open 17 0,053 architecture 0,042 appraisal 0,052 infrastructure 18 0,052 software hide 0,050 discovery 19 0,050 use ema 0,050 datum 20 0,047 datum willing 0,048 sustainable 21 0,047 component logit 0,047 rest 22 0,046 spatial valuation 0,047 czech 23 0,045 application contingent 0,046 technology 24 0,045 access premium 0,044 balance 25 0,043 navigator videoconference 0,043 life 26 uwedat swedish 0,042 microservice 27 abatement responsive 0,042 user 28 enviroinfo publicly 0,041 series 29 spread circular 0,041 office 30 maintain ghanaian 0,041 generic Note: Several keywords have the same value, not all are listed here. Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table 6 The most important keywords according to TF-IDF indices (journals SUSTAIN COMPUT- INFOR, COMPUTER, STUD SYST DECIS CONT) SUSTAIN COMPUT-INFOR COMPUTER STUD SYST DECIS CONT Rank Value Keyword Value Keyword Value Keyword 1 0,172 special 0,145 column 0,206 engineering 2 0,148 issue 0,106 technology 0,115 concept 3 0,126 conference 0,089 response 0,082 technology 4 0,124 papers 0,074 green 0,074 complex 5 0,122 computing 0,073 computing 0,069 development 6 0,118 introduction 0,072 accountability 0,062 preface 7 0,118 international 0,072 generalize 0,061 implementation 8 0,104 igcc 0,072 fear 0,058 thing 9 0,095 select 0,072 wild 0,052 fpga 10 0,076 reduction 0,072 shine 0,052 taxonomy 11 0,075 software 0,072 let 0,051 network 12 0,075 energy 0,072 sun 0,051 model 13 0,069 power 0,072 showcase 0,051 green 14 0,066 green 0,072 joule 0,049 logic 15 0,059 server 0,072 hurdle 0,048 physical 16 0,058 agile 0,072 modularity 0,047 information 17 0,057 efficiency 0,072 bloat 0,047 internet 18 0,054 compute 0,072 1680 0,046 function 19 0,052 ieee 0,072 odd 0,045 operation 20 0,049 renewable 0,072 oddity 0,044 computing 21 0,045 aspect 0,072 design 0,043 classification 22 0,044 allocation 0,069 computer 0,042 fuzzy 23 0,040 consumption 0,065 information 0,041 component 24 0,039 datum 0,065 fi 0,041 optimization 25 0,039 platform 0,065 wi 0,038 adaptive 26 0,038 optimization 0,065 speedup 0,037 energy 27 0,037 improve 0,065 creative meronymous 28 0,037 enterprise 0,060 amdahl spiral 29 0,037 technique 0,060 modular specialized 30 0,172 special 0,145 column engineering Note: Several keywords have the same value; not all are listed here. Source: Author’s work Important keywords in the normalized nJK networks of selected journals Before applying the Line Island approach to the obtained normalized networks with the fractional approach 𝑛𝐽𝐾 , we removed the 8 most frequent keywords (green, system, information, technology, energy, computing, environmental, and management). We want to investigate the connection patterns among other keywords within the selected journal and thus reveal the differences in subfields of the journals’ scope. The keywords most frequently associated with the corresponding journals are shown in the Appendices, Figure 9 and Figure 10. The keywords reflecting the LECT NOTES COMPUT SC (Figure 8a) is related to energy, compute, design, technology, cloud, spatial, science, aware, computing, etc. A closer look at this publishing outlet reveals several conference proceedings series related merely to technological aspects of green sustainability. For instance, the main topics identified in this publication outlet are green and cloud computing, data analytics, renewable energy, energy informatics, and similar topics. We can highlight similarities by comparing this set of keywords with another book series (i.e., IFIP ADV INF COMM TE). Both publication outlets are primarily concerned with IT. However, some studies aim to bridge IT and green aspects, particularly addressing the potential of IT to reduce the negative impact on the environment. Given the keywords in SUSTAIN COMPUT-INFOR (Figure 10a), one can identify the technological dimensions of Green IT/IS (such as computing, software, server, Business Systems Research | Vol. 12 No. 2 |2021 platform), the environmental dimension (reduction, energy, power, efficiency, renewable, allocation, consumption, improvement, etc.) and the organizational dimension (such as enterprise, technique, aware). Several works in this journal are related to green and sustainable computing, green high-performance computing (green HPC), and green IT. This journal is dedicated to scientific work related to the interplay between computer science and engineering and sustainability. In addition, this journal has several special issues devoted to green computing. Regarding the ENVIRON MODELL SOFTW (Figure 9a), the keywords such as environment, integration, support, decision, information, interface, management, architecture, and software can be emphasized. Examining the papers within this journal, we can outline the green infrastructure as one of the streamlined topics. Furthermore, contrary to the publications mentioned above, the journal COMPUTER (Figure 10b) focuses predominantly on green energy and smart grid as far as green aspects are concerned. The keywords do not show a similar pattern compared to other publication outlets included in our study. Considering the FUTURE GENER COMP SY (Figure 8c), we can emphasize some similarities with other publication outlets such as LECT NOTES COMPUT SC and SUSTAIN COMPUT-INFOR. Green renewable energy, green computing, green data centers, and green IT are among the most notable research areas identified in FUTURE GENER COMP SY (Figure 8c). INFORM SYST FRONT (Figure 8b) also publishes the papers associated with Green IS practices and other non-technological aspects of Green IT/IS, such as attitudes towards Green IT, sustainability performance, etc. The keywords such as business, performance, sustainability, organization, innovation, strategy, and management also support the notation mentioned earlier on Green IS. While the scope of J CLEAN PROD (Figure 9b) is not related to IT or IS, there are also some papers on green technology in this journal, especially related to Green IT. The keywords indicate that attention is given to corporate/organizational sustainability and green technology, either information or energy, building, and other technologies. Business Systems Research | Vol. 12 No. 2 |2021 Figure 8 Keywords inside the journals LECT NOTES COMPUT SC, INFORM SYST FRONT, FUTURE GENER COMP SY Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Figure 9 Keywords inside journals ENIVORN MODELL SOFTW, J CLEAN PROD, IFIP ADV INF COMM TE Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Figure 10 Keywords inside journals SUSTAIN COMPUT-INFOR, COMPUTER, STUD SYST DECIS CONT Source: Author’s illustration Business Systems Research | Vol. 12 No. 2 |2021 Discussion and Conclusions Despite various barriers organizations face in implementing green operations (Alves et al., 2020), there are significant literature on Green IS/IT, its adoption, and practices. We aimed to identify the topics of Green IT/IS research published in scientific journals. This study makes an important contribution to the Green IT/IS literature and provides valuable information for policymakers in public administration and organizations about the advances and orientation of the Green IT/IS research topic to follow the sustainable goals of digital transformation. Our main contribution is to outline the Green IT/IS research area development from 1975. It should be noted that our research goes beyond the traditional qualitative review. A quantitative approach to SNA, which we undertook by applying keyword analysis, provides a more objective overview of the research area and its development. Therefore, the main contribution of this quantitative approach to literature review can be conceived to understand better the scientific discipline of Green IT/IS and open future research avenues. We portrayed the development of the Green IT/IS research area and emphasized how the greening of this emerging field has been incorporated into the IT/IS literature. We have highlighted the main knowledge pillars on which the Green IT/IS research streams are built (e.g., green computing, green infrastructure, green energy, green data centers, etc.). Temporal analysis of the words associated with the Green IT/IS revealed the rapid increase of Green IT-related keywords from 2000 onwards. Indeed, the interdisciplinary field of Green IT/IS has also developed accordingly. Interestingly, not all journals publishing Green IT/IS topics are IS-oriented, showing the importance and widespread interest in the topic. The scope of journals publishing Green IT/IS-related scholarly work extends beyond the information systems research field. J CLEAN PROD, one of the most eminent journals publishing research on sustainable development, has also published many Green IT/IS-related works. This is a clear signal that Green IT/IS has become interested in a wider research audience. The journal with the highest number of works related to Green IT/IS, LECT NOTES COMPUT SC, publishes many conference proceedings series. These research works focus more on technological aspects of green sustainability and less on academic discussions, which shows that there are still opportunities for academic research on Green IT/IS. The main contributions of this paper can be summarized as follows: (1) Successful implementation of quantitative methodology that can be applied to different research fields; (2) Comprehensive overview of the literature on the Green IT/IS topic; (3) Identification of the trends in the advancement of publications related to Green IT/IS over the past decades. The research provides an exhaustive overview of the keywords used in Green IT/IS research, their evolution, and orientation. It provides IT management in companies’ guidelines for their future activities and strategical decisions on IT investments related to sustainable development. This unbiased Green IT/IS literature review guides companies in preparing a solid background for their digital transformation process aligned with the sustainable development goals. From a management perspective, there are many innovative solutions to Green IT/IS challenges, and there is growing momentum to develop more Green IT /IS solutions that can be successfully marketed. Further on, the opportunities for future research that can be outlined are related to the Green IT/IS investigation in more depth. Focusing more on non-technological aspects of Green IT/IS is bound to become even more significant in light of the evolution of this literature stream. For example, the investigation of the factors influencing the internalization of Green IT/IS is currently not sufficiently grounded in theories of Green IT/IS. This could entail the investigation of Green IT/IS's underlying Business Systems Research | Vol. 12 No. 2 |2021 practices by integrating Green IT/IS into the management system of organizations, the development of Green IT/IS policies, objectives, procedures, etc. Moreover, the domains of the firm's resource-based view (RBV) and knowledge-based theory (KBV) of the firm are considered theoretical lenses that could shape the future development of Green IT/IS research. The Green IT /IS field is still in its infancy stage. Nevertheless, there is a growing scientific interest in the Green IT/IS phenomenon. In this sense, based on the results of our study, we argue that rigorous theory development should be the focus of research on Green IT/IS. Our study showed that Green IT/IS is not narrowly specialized but is rather an interdisciplinary-oriented research stream. We anticipate that the research field will gradually mature as more multidisciplinary and interdisciplinary studies are conducted. In addition, studies that focus on different contexts would enrich this line of research. For example, IT/IS research could be linked to the circular economy research, or future studies could expand the green perspective to a broader sustainability perspective with a balanced focus on sustainability dimensions. Besides, future research could delve into which specific aspects of Green IT/IS offer significant benefits in terms of improved business value. While this study contributes to the Green IT/IS literature in several ways, certain limitations need further attention. The analysis is based on the data derived from the WoS, and incorporating additional bibliographic sources could further increase the generalizability of the results. 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Melville, N. P. (2010), “Information Systems Innovation for Environmental Sustainability”, MIS Quaterly, Vol. 34 No. 1, pp. 1-21. 24. Muhammad, S., Jusoh, Y. Y. A. H., Din, J., Nor, R. N. H. (2017), “Green Information Systems Design Framework: a Systematic Literature Review”, Journal of Theoretical and Applied Information Technology, Vol. 95 No. 6, pp. 1338-1346. 25. Robertson, S. (2004), “Understanding inverse document frequency: On theoretical arguments for IDF”, Journal of Documentation, Vol. 60 No. 5, pp. 503-520. 26. Sanita, F., Mohamed Udin, Z., Hasnan, N. (2017), “Green IT/S adoption within GSCM in Indonesian construction industry: An elucidation and practice”, Journal of Information System and Technology Management, Vol. 2 No. 6, pp. 84-104. 27. Singh, M., Sahu, G. P. (2020), “Towards adoption of Green IS: A literature review using classification methodology”, International Journal of Information Management, Vol. 54, 28. Wang, X., Brooks, S., Sarker, S. (2015), “A review of green is research and directions for future studies”, Communications of the Association for Information Systems, Vol. 37, pp. 395-429. 29. Watson, R. T., Boudreau, M.-C., Chen, A. J. (2010), “Information systems and environmentally sustainable development: energy informatics and new directions for the is community”, MIS Quarterly, Vol. 34 No. 1, pp. 23-38. 30. Watson, R. T., Boudreau, M.-C., Chen, A. J., Huber, M. (2008), “Green IS: Building Sustainable Business Practices”, Information Systems Journal, Vol. 76, pp. 1-15. Business Systems Research | Vol. 12 No. 2 |2021 Appendices Table A1 Vertices within the selected journals (I.) LECT NOTES COMPUT SC INFORM SYST FRONT FUTURE GENER COMP SY Rank Value Keyword Value Keyword Value Keyword 1 2.429 green 0.445 information 1.254 green 2 1.780 energy 0.445 green 0.921 energy 3 1.737 information 0.445 technology 0.846 computing 4 1.692 system 0.386 system 0.743 compute 5 1.255 technology 0.337 business 0.539 efficiency 6 1.114 computing 0.284 environmental 0.530 cloud 7 0.907 compute 0.274 management 0.453 management 8 0.893 cloud 0.271 performance 0.432 aware 9 0.779 base 0.248 sustainability 0.353 technology 10 0.758 environmental 0.184 supply 0.352 datum 11 0.681 datum 0.184 chain 0.352 center 12 0.627 management 0.147 model 0.350 power 13 0.608 service 0.134 organization 0.336 performance 14 0.597 efficiency 0.133 theory 0.298 information 15 0.564 aware 0.133 innovation 0.294 distribute 16 0.536 design 0.131 value 0.291 system 17 0.510 research 0.108 ecological 0.286 scheduling 18 0.498 sustainability 0.108 modernization 0.250 resource 19 0.491 resource 0.095 small 0.250 special 20 0.466 consumption 0.091 strategy 0.250 section 21 0.452 performance 0.090 energy 0.234 consumption 22 0.448 application 0.090 informatics 0.167 software 23 0.444 database 0.079 make 0.166 application 24 0.383 informatics 0.077 strategic 0.150 virtual 25 0.377 efficient 0.077 process 0.148 cluster 26 0.370 spatio 0.076 alignment 0.138 cost 27 0.370 temporal 0.074 determinant 0.136 parallel 28 0.347 analysis firm 0.136 task 29 0.335 algorithm adoption 0.133 virtualization 30 0.319 science development 0.130 hpc Several keywords have the same value, not all are listed here. Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table A2 Vertices within the selected journals (II.) ENVIRON MODELL SOFTW J CLEAN PROD IFIP ADV INF COMM TE Rank Value Keyword Value Keyword Value Keyword 1 1.254 green 0.484 information 2.402 information 2 0.921 energy 0.379 green 2.065 environmental 3 0.846 computing 0.379 technology 1.850 system 4 0.743 compute 0.288 environmental 0.918 technology 5 0.539 efficiency 0.273 management 0.722 green 6 0.530 cloud 0.235 system 0.630 datum 7 0.453 management 0.193 communication 0.559 sustainable 8 0.432 aware 0.182 model 0.532 architecture 9 0.353 technology 0.134 practice 0.463 model 10 0.352 datum 0.130 travel 0.439 management 11 0.352 center 0.130 business 0.411 semantic 12 0.350 power 0.130 collaboration 0.390 web 13 0.336 performance 0.130 meeting 0.375 analysis 14 0.298 information 0.130 virtual 0.321 service 15 0.294 distribute 0.123 corporate 0.320 search 16 0.291 system 0.101 innovation 0.306 sustainability 17 0.286 scheduling 0.101 performance 0.305 development 18 0.250 resource 0.101 sustainability 0.294 integrate 19 0.250 special 0.101 eco 0.283 user 20 0.250 section 0.100 public 0.283 infrastructure 21 0.234 consumption 0.099 company 0.260 support 22 0.167 software 0.097 framework 0.254 innovation 23 0.166 application 0.091 perspective 0.250 environment 24 0.150 virtual 0.083 impact 0.234 policy 25 0.148 cluster 0.083 implementation 0.227 open 26 0.138 cost 0.081 program 0.226 issue 27 0.136 parallel 0.071 videoconference 0.224 portal 28 0.136 task 0.071 swedish 0.223 semantics 29 0.133 virtualization 0.071 agency 0.220 experience 30 0.130 hpc 0.071 web 0.205 way Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 Table A3 Vertices within the selected journals (III.) SUSTAIN COMPUT-INFOR COMPUTER STUD SYST DECIS CONT Rank Value Keyword Value Keyword Value Keyword 1 2.368 green 2.644 green 1.546 green 2 1.728 computing 1.255 information 1.131 technology 3 1.063 energy 1.255 technology 1.040 information 4 0.946 issue 1.238 computing 0.985 engineering 5 0.869 special 0.533 response 0.747 system 6 0.688 software 0.450 column 0.531 computing 7 0.576 introduction 0.405 energy 0.478 energy 8 0.504 international 0.250 trading 0.478 model 9 0.504 conference 0.200 accountability 0.419 concept 10 0.485 power 0.200 solve 0.411 development 11 0.461 technology 0.200 measure 0.411 network 12 0.461 compute 0.200 issue 0.353 implementation 13 0.393 papers 0.200 society 0.261 complex 14 0.393 select 0.200 future 0.245 consumption 15 0.378 efficiency 0.188 design 0.245 software 16 0.375 system 0.167 odd 0.238 thing 17 0.344 information 0.167 oddity 0.238 internet 18 0.308 datum 0.167 2.000 0.236 component 19 0.293 igcc 0.143 simulation 0.227 datum 20 0.288 management 0.143 system 0.217 cloud 21 0.288 consumption 0.143 introduction 0.211 preface 22 0.270 server 0.143 power 0.211 architecture 23 0.265 performance 0.143 smart 0.199 design 24 0.260 model 0.143 modeling 0.177 control 25 0.254 aspect 0.121 development 0.176 compute 26 0.243 cloud 0.117 computer 0.170 optimization 27 0.228 reduction 0.091 visualization 0.170 algorithm 28 0.222 engineering language 0.168 efficient 29 0.219 sustainable fi 0.156 base 30 0.219 renewable wi 0.154 power Several keywords have the same value, not all are listed here Source: Author’s work Business Systems Research | Vol. 12 No. 2 |2021 About the authors Anja Žnidaršič, Ph.D., received a Ph.D. in statistics from the University of Ljubljana, Slovenia, in 2012. From 2007 to 2013, she was a Teaching Assistant with the Department for Quantitative Methods at the Faculty of Organizational Sciences and, since 2018, an Associate Professor. Her research interests include technology acceptance, students’ performance, multivariate methods, missing data, and social network analysis. She has been a program committee member of several international scientific conferences and is actively involved in several bilateral and industry projects. She is a Slovenian statistical association and European Courses in Advanced Statistics member. The author can be contacted at anja.znidarsic@um.si. Alenka Brezavšček is an Associate Professor at the Faculty of Organizational Sciences, the University of Maribor in Slovenia. She received her Ph.D. in Quality Management from the University of Maribor. Her research interests are stochastic processes (theory and applications), system reliability and availability, maintenance optimization, and information/cybersecurity. At the Faculty of Organizational Sciences, she is a chair of the Methodological Department. She was involved in several applied projects focusing on the production process and maintenance optimization and conducted professional seminars on information/cybersecurity for various target groups. The author can be contacted at alenka.brezavscek@um.si. Matjaž Maletič is an Assistant Professor at the Faculty of Organizational Sciences, University of Maribor. His research focus can be assigned to the following research areas: quality management, asset management, and organizational sustainability. Apart from general research directions, he intends to link the research with innovation and organizational performance paradigms. He obtained his Ph.D. degree in Quality Management from the University of Maribor, Faculty of Organizational Sciences. He has been involved in several research projects and is a member of various professional associations, including the technical committee of the Slovenian Institute for Standardization. The author can be contacted at matjaz.maletic@um.si. Alenka Baggia, Ph.D., received a Ph.D. degree in management information systems from the University of Maribor, Slovenia. She is an Assistant Professor at the Faculty of Organizational Sciences, University of Maribor. Her research interests include green information systems, discrete event simulation, technology acceptance, scheduling, and group dynamics. She has been a program committee member of several international scientific conferences. She has been actively involved in several national, international (EU, CE, cross-border, bilateral), and industry projects. She is a member of Slovenian society Informatika. The author can be contacted at alenka.baggia@um.si. Daria Maltseva, Ph.D., is a Senior Research Fellow and Deputy Head at the International Laboratory for Applied Network Research, National Research University Higher School of Economics, Russia. She received a Ph.D. at the Faculty of Sociology of the Russian State University for the Humanities. During her internships at the Centre for Methodology and Informatics, Faculty of Social Sciences, University of Ljubljana, she was also educated. Her main research interests are social network analysis, network approach in sociology, bibliographic studies, and sociology of science. She is actively engaged in several national scientific projects. The author can be contacted at dmaltseva@hse.ru.

Journal

Business Systems Research Journalde Gruyter

Published: Dec 1, 2021

Keywords: Green Information System; Green Information Technology; bibliographic networks; D85

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