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Purpose – The aim of this study is to identify and rank the factors of innovation capability (IC) in Indian micro, small and medium enterprises (MSMEs). This study focuses on ascertaining the important factors that help in enhancing the IC with an emblematic focus on the MSME sector of India. Design/methodology/approach – This paper proposes a multicriteria decision-making methodology, which is based on fuzzy analytic hierarchical process to prioritize the factors that enhance the IC of MSMEs. Finally, sensitivity analysis is conducted to examine the ranking stability. Findings – Knowledge management is the most important enabler, followed by creativity and idea management and organizational culture. Practical implications – Several organizations promote the strategic measures for enhancing the IC. To increase their capability to innovate, there is a need to identify, acknowledge and implement the drivers of IC into practice. Originality/value – Prioritization done in the study facilitates the entrepreneurs to determine the most important factors that need crucial attention in dealing with sensitive issues of IC. Entrepreneurs can take several steps to implement the most important factors for enhancing the IC into practices for meeting the needs of the consumers, generating profits and enhancing the competitiveness. Keywords India, MCDM, Fuzzy AHP, MSMEs, Innovation capability (IC) Paper type Research paper 1. Introduction Innovation is an attractive, yet ambiguous goal for several organizations. It promises to enhance the profits, satisfy the needs of the customers, increase market exposure, gain the competitive advantage, provide sustainable development and give better performance (Chen et al., 2018; Srivastava et al.,2017; Swann, 2018; Gunday et al., 2011; Kuratko et al., 2005; Teece, 2007; Stock et al.,2002). The reason innovation is so valuable is that it is rare. The present scenario of globalization, multifaceted business environment, smaller product life cycle and vertical integration has elevated the significance of innovation for all © Juhi Raghuvanshi and Chandra Prakash Garg. Published in Asia Pacific Journal of Innovation and Entrepreneurship. Published by Emerald Publishing Limited. This article is published under the Asia Pacific Journal of Innovation Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and and Entrepreneurship create derivative works of this article (for both commercial and non-commercial purposes), subject to pp. 279-299 Emerald Publishing Limited full attribution to the original publication and authors. The full terms of this licence may be seen at 2398-7812 http://creativecommons.org/licences/by/4.0/legalcode DOI 10.1108/APJIE-06-2018-0041 organizations and particularly for micro, small and medium enterprises (MSMEs). APJIE Disruptions are unpredictable in a dynamic business environment. For enhancing the 12,3 sustainability and competitiveness of a business, the process of innovation capability (IC) must be intended in such a way that it will produce effective and efficient innovations, thereby making it capable of generating higher returns and increased market exposure (Stock et al., 2002). The process of IC is multidimensional and aims at developing more and more innovations for reducing vulnerability. The potential to generate the innovation is called IC (Neely et al., 2001). It can be enhanced by enhancing the capability to innovate (Fruhling and Siau, 2007; Saunila and Ukko, 2012). In a turbulent business environment, an enterprise must possess the ability to reconstruct, renew and recreate the available resources to develop the IC. The IC of enterprises can be described in several perspectives. Thus, according to Bergendahl et al. (2008), IC includes the ability to adapt to the new environment, technical learning and organizational learning and work procedures. Lawson and Samson (2001) identify seven constructs (''vision and strategy, harnessing the competence base, organizational intelligence, creativity and idea management, organizational structure and systems, culture and climate, and the management of technology'') of IC and claim that organizations that explicitly generate and invest in these seven constructs are able to achieve sustainable innovation outcomes. Whereas, Olsson et al. (2009) identified six elements of an innovative organization. These elements explain the benefits as well as challenges attached while approaching IC. The key to enhance IC is the identification of all the possible factors that may help in generating the capability to innovate. Proactive application of the strategies to enhance the probability of developing the IC (even in uncertainty) and effective planning for enhancing IC provide deep insights for an effective decision-making process. Factors enhancing the IC should be primarily addressed for enabling innovation in an organization. Factors of IC are somewhat interlinked. One driver of IC may have a direct positive influence over the other driver. To identify the factors of IC, they must be prioritized based on their overall influence over the other driver. The primary objective of the study is to prioritize the enablers of IC in the MSME sector of India. The original contribution of this study is the application of the technique and its managerial implications. The fuzzy analytic hierarchical process (AHP) technique has been applied in this study to determine the rank of the factors of IC in the MSME sector. As the drivers of IC are interlinked, entrepreneurs must rank their selection, application, review and maintenance on those drivers that are extremely important. The rationale of the study is to provide a better understanding on enablers of innovation, especially for MSMEs, on one platform by providing the ranking of the enablers and to provide the future scope related to this area, which will help scholars, entrepreneurs, managers and policymakers. Author claims that this study will provide a path for future research in generating IC with the proper application of appropriate factors of IC. Finally, to ensure the robustness of the findings, sensitivity analysis was also performed. This study is organized into six sections. Section 1 describes the introduction of the study. Section 2 explains the factors of IC and its related literature, followed by MSMEs in India. In Section 3, methodology used in the study is explained. Section 4 provides the results of this study, followed by Section 5, which deals with sensitivity analysis and managerial implication. This paper will end with conclusion and future scope in Section 6. 2. Literature review 2.1 Existing literature related to innovation capability As mentioned earlier, IC is one area on which significant research has been carried out. Studies have examined the relationship that IC shares with various organizational variables in different contexts. Organizations with well-defined constructs of IC perform better Innovation because knowledge of such constructs makes it easier to identify which areas need attention capability in to develop IC; organizations without such knowledge would not know where to invest in the Indian MSMEs first place (Lawson and Samson, 2001; Olsson et al., 2009). The authors in this study have identified seven enablers of IC from available literature. Majority of these drivers are those that have been mentioned most frequently by researchers. Resources are defined as the available assets in an organization that include knowledge, organizational features, skills, potential, etc. These are controlled by the organizations, as it enables them to conceive and execute and implement the strategies that help in enhancing the efficiency and effectiveness of innovation in the market (Barney and Clark, 2007). Resources are divided in two groups: operant resources and operand resources (Constantin and Lusch, 1994). Hunt (2004) defined the operant resources as human skills, knowledge and information, be it about the technologies, customers, competitors, etc., as well as the relational and organizational knowledge, like routines and control mechanism, whereas the operand resources are physical (tangible) resources. It is reported that the operant resources are more vital for IC than the operand resources (Lin, 2007; Du Plessis, 2007; Camps and Marques, 2014). According to Kamath et al. (2016), knowledge management (KM) has also been identified as the most important enabler of IC. Capabilities constitute knowledge that acts as a tool to enhance skills where the skills refer to the ability to do things with expertise. According to Wood et al. (1976), skills can be defined as operant’s capabilities, whereas knowledge is a mental frame. Lin (2007) has identified a positive relationship between knowledge sharing and IC of an organization. Fang et al. (2014) claimed that not only internal resources but also inter-firm innovation networks play a crucial role in attaining the competitive advantage. Moreover, collaboration that assists in enhancing the firm’s IC is important. It was found that networking capabilities have four antecedents: openness of the culture, experience with network capabilities, IT maturity and the management system involved (Fang et al., 2014), which have been empirically validated. Romijn and Albaladejo (2002) and Kallio et al. (2012) posit the importance of collaboration for enhancing IC. Camps and Marques (2014), Yang (2012) and Saleh and Wang (1993) claimed that the propensity to take risk was one of the drivers that increased the IC of an organization. It is very important for every organization to develop openness to criticism and failure and the ability to tolerate ambiguity. Song and Di Benedetto (2006), Wagner and Hoegl (2006) and Hartley et al. (1997) cited supplier involvement as one of the important drivers of IC. Involving customers and the suppliers in the process of production helps in enhancing the capability to innovate. To build customer loyalty, maximize profits and attract new customers, customer involvement in the process of innovation is important (Feng et al., 2010). Morrison et al. (2000) also concluded that in developed economies, majority of technological innovations had been generated through involvement of customers in the innovation processes. Several previous research works claimed that involvement of the supplier is important for the development of innovations. Song and Di Benedetto (2008) identified a positive relationship between supplier participation and radical innovation. Wagner and Hoegl (2006) also posit that supplier involvement in new product development is vital and even inevitable in some organizations. But, several issues must be taken care of. First, the criteria for selecting suppliers (Wagner and Hoegl, 2006; Wynstra et al.,2003) is an important issue in the case of supplier involvement. The appropriate time for involving the supplier is another crucial issue that must be taken into account. McGinnis and Vallopra (1999, p. 14) suggested that organizations must engage suppliers only at the time of need and for developmental aspects. Hartley et al. (1997) stressed on the participation of suppliers in the APJIE initial stage of the product development process, whereas Eisenhardt and Tabrizi (1995) 12,3 pointed out that it depends on the situation. Technology management is vital for every organization in the current business environment. Lawson and Samson (2001) claimed that innovative organizations were those that were able to link their innovation and business strategies with technological strategy. Adoption of new technology helps in developing the capability to innovate by maintaining a database of suppliers and customers along with their preferences. Yang (2012) and Castro et al. (2013) also asserted that investment in appropriate technologies helped in enhancing IC. Other research work conducted by Tarafdar and Gordon (2007) and Khosrow-Pour (2006) identified the positive relationship between technology management and IC. Beliefs, norms, values and assumptions determine the climate of an organization. Martensen et al. (2007) and Neely et al. (2001) claimed that the organizational climate (OC) facilitated the culture of innovation in an organization and helped in increasing the number of innovations. Smith et al. (2008); Wan et al. (2005) and Lawson and Samson (2001) emphasized the importance of the OC in facilitating proper communication in organizations, supporting that OC enhanced collaboration with other organizations (Smith et al., 2000), which in turn helped in developing the IC of an organization. Several other authors, such as Slater et al. (2014); Saunila and Ukko (2013); Sharifirad and Ataei (2012); Kallio et al. (2012); Rujirawanich et al. (2011); Skarzynski and Gibson (2008); Leskovar-Spacapan and Bastic (2007) and Lawson and Samson (2001), have also stressed the importance of the OC in developing IC. Creativity, defined as a process of generating novel ideas (Amabile et al.,1996), is an important construct of IC (Lawson and Samson, 2001; Ahlin et al.,2014; Camps and Marques, 2014). Every organization must explicitly encourage creativity because only through enhancement of creativity, the organization will have better chances of achieving sustainable innovation. It was also concluded that knowledge sharing within the organization influences IC by supporting creativity (Perry-Smith and Shalley, 2003) and encouraging novel ideas and knowledge (Aragon-Correa et al.,2007). The summary of these enablers is given in Table I. 2.2 Micro, small and medium enterprises in India In India, there are approximately 46 million MSMEs across the several industries employing more than 106 million people. Maximum numbers (94 per cent) of enterprises in this sector are unregistered. In India, after agriculture, this sector provides employment to the maximum number of people and plays a very crucial role in the industrialization of rural as well as urban areas. The MSME sector complements the larger organizations and significantly contributes to the economic and social prosperity of the country. The contribution of this sector was very significant in the past decades, as it stands at approximately 40 per cent of the total nation export to 45 per cent of the total manufacturing output with 8 per cent of the gross domestic product. This particular sector of the economy holds the significant potential to enhance the industrial growth of the nation. Further, this sector contributes in the development of the nation through contribution to operational flexibility, contribution toward defense production, technology-oriented industries, location- wise mobility, capacities to develop appropriate indigenous technology, import substitution, low-investment requirements, low-intensive imports, domestic production, significant export earnings and competitiveness in national and international markets, thereby creating new entrepreneurs by providing training and knowledge. Innovation Innovation capability in Sr. no. capability enablers References Description Indian MSMEs 1 Knowledge Taherparvar et al. (2014), Yusur et al. The improvement of knowledge management (KM) (2014), Levi-Jakšic et al. (2013), Yesil generation or transfer through et al. (2013), Kumar and Che Rose knowledge acquisition, (2012), Lopez-Nicolás and Meroño- assimilation and dissemination, Cerdán (2011), Lin (2007), Miller et al. technological knowledge, prior 283 (2007), Rollins and Halinen (2005), related knowledge and customer Subramaniam and Youndt (2005), and employee knowledge Gibbert et al. (2002), Romijn and management Albaladejo (2002), Cohen and Levinthal (1989, 1994) 2 Risk-taking (RT) Jaworski and Kohli (1993), Hurley and Ability to try new methods and Hult (1998), Calantone et al. (2002), approaches without any control Guan and Ma (2003), Akman and over the consequences Yilmaz (2008), Hull and Covin (2010), Forsman (2011), Camps and Marques (2014) 3 Actor’s Jeng and Pak (2014), Ahlin et al. (2014), Actor’s participation includes participation (AP) Camps and Marques (2014), Saunila participation of customers, and Ukko (2014), Kallio et al. (2012), suppliers and employees in the Sharifirad et al. (2012), Martinez-Roman process of innovation et al. (2011), Feng et al. (2010), Olsson et al. (2009), Song and Di Benedetto (2006), Wagner and Hoegl (2006), Wan et al. (2005), Lawson and Samson (2001), Morrison et al. (2000), Hartley et al. (1997) 4 Creativity and idea Tang (1998, 1999), Kallio et al. (2012), It includes the idea generation, management (CIM) Lawson and Samson (2001), Smith et al. improvement, selection and (2008), Flynn et al. (2003), Sandstrom implementation and Bjork (2010), Alessi et al. (2015) 5 Information and Castro et al. (2013), Yang (2012), Technology-based CRM, use of technology Tarafdar and Gordon (2007), Gordon information technology and ability management (ITM) and Tarafdar (2007), Khosrow-Pour to adapt to latest technology (2006), Lawson and Samson (2001), Dyche (2001) 6 Organizational Donkor et al. (2018), Russell (1990), It includes level of decentralization climate (OC) Damanpour (1991), Nonaka and (decision-making power), control Takeuchi (1995), Hurley and Hult and supervision (hierarchical (1998), Tang (1998, 1999), Neely et al. power), presence of communication (2001), Lawson and Samson (2001), system and liaison resources in an Guan and Ma (2003), Brockman and organization, organizational Morgan (2003), Wan et al. (2005), Li and structure and culture and reward Kozhikode (2009), Hull and Covin system. Values, beliefs and norms (2010), Wonglimpiyarat (2010), also determine the organizational Martinez-Roman et al. (2011), Kallio climate et al. (2012), Saunila and Ukko (2013), Slater et al. (2014) Table I. 7 Collaboration (CO) Romijn and Albaladejo (2002), Kallio Collaboration with research Innovation capability et al. (2012), Fang et al. (2014) institutes, universities, enablers from government, nongovernment organizations and other industries literature review But on the other hand, the Indian MSME sector faces numerous challenges, such as insufficient APJIE skilled manpower, technological obsolescence, working capital shortages, not getting trade 12,3 receivables from large and multinational companies on time, turbulent and uncertain market scenario, sub-optimal scale of operation, change in manufacturing strategies, supply chain inefficiencies and increasing domestic and global competition. Owing to these challenges, there is a need for MSMEs to adopt innovative approaches in their day-to-day operation. MSMEs that are inventive, creative, global in their business point of view and innovative and have a robust technological base, competitive strength or a willingness and ability to reconstruct, recreate or restructure themselves can only survive in the present dynamic business environment and come out successfully to contribute more in the nation's gross domestic product. 2.3 Definition of micro, small and medium enterprises in India Every economy has their own criteria for defining MSMEs. Some defined MSMEs in terms of number of employees; some defined it in terms of annual sales and turnover, whereas some defined it in terms of investment in plant and machinery. In India, MSMEs are defined in terms of investment in plant and machinery by MSMED Act 2006.This act classified enterprises in two categories: one is manufacturing enterprises and the other is service enterprises (Table II). 3. Research methodology In this paper, given methodology has been applied for evaluation and ranking the innovation enablers. This paper used the fuzzy analytical hierarchical process to get weights of criteria and prioritize to find the final rank. Fuzzy analytical hierarchical process (FAHP) is a multicriteria decision-making (MCDM) tool. By using the fuzzy concept, vagueness and uncertainty can be managed. This method is suitable in such a complex multicriteria decision environment. Figure 1 shows a graphic map of the proposed research methodology. The proposed outline of this research work is illustrated through Figure 1. Initially, identification of IC factors was done through an in-depth literature analysis and followed by discussions with industrial experts. After that, pairwise comparison through a questionnaire are obtained for listed factors. Hereafter, specific factors are evaluated and respective weights of the factors are determined by using FAHP. If the weights are consistent, then they are approved, as shown through the symbol Y, where “Y” stands for yes. Otherwise, they are revised, as shown through the symbol N, where “N” stands for no. After that, factors are prioritized and analyzed further, as highlighted through the figure. 3.1 Fuzzy AHP The AHP approach pioneered by Saaty (1980) is a mathematical approach of MCDM. AHP has some limitations in usability because of certainty and the subjective nature of the used scale. This problem can be minimized if AHP is integrated with the fuzzy concept (Garg, 2016; Prakash and Barua, 2016a, 2016b, 2016c, Prakash and Barua, 2015a, Prakash et al., Manufacturing sector (investment in plant Enterprises and machinery) Service sector (investment in equipment) Table II. Definition of micro, Micro enterprises Up to Rs 25 lakhs Up to Rs 10 lakhs small and medium Small enterprises Rs 25 lakhs to 5 crores Rs 10 lakhs to 2 crores enterprises Medium enterprises More than Rs 5 crores Rs 2 crores to 5 crores Identification of innovation capability factors through literature Innovation Fig. 1 denotes a rre ep vi re ew se ntation of the research capability in Indian MSMEs Finalizing the innovation capability factors by industrial experts Questionnaire design and data collection from experts Calculate weights of the factors using FAHP Approve Weight s Figure 1. Proposed FAHP methodology for innovation capability factors assessment Prioritize and analyze the factors of innovation capability 2015b). The fuzzy AHP methodology includes uncertainty and vagueness of the expert’s judgments through linguistic variables. Various researchers have used this approach in different areas like urban planning, education, finance, transportation, politics, economics, marketing, logistics and reverse supply chain (Garg et al., 2017; Kumar and Garg, 2017; Prakash and Barua, 2015c; Prakash et al., 2015a, 2015b, 2014). Chang’s extent analysis (1992) presented the fuzzy AHP process; according to this approach, the values of extent method for each criterion are derived. The steps of Chang’s analysis have been used. This approach was also used by Prakash et al. (2015a, 2015b, 2015c) and Prakash and Barua (2016b). Step 1: The fuzzy synthetic extent value (E ) with respect to the ith criterion is defined as: "# m n m X X X j j E ¼ M M (3.1) g g i i j¼1 i¼1 j¼1 M =1,2,3,4, 5 .. . ... ., m are allotted triangular fuzzy number (TFN) presented in Table III. Step 2: The possibility degree of E =(a ,b ,c ) E =(a ,b ,c )is defined as below, 2 2 2 2 1 1 1 1 where a# b# c. sup VEðÞ E ¼½min m a ; m ðÞ b and a and b denote respective membership ðÞ 2 1 b a S S 1 2 function value. Linguistic variables Assigned TFN Equal (1, 1, 1) Very low (1, 2, 3) Low (2, 3, 4) Medium (3, 4, 5) Table III. High (4, 5, 6) TFN of linguistic Very high (5, 6, 7) Excellent (7, 8, 9) comparison matrix For comparison between E and E , we need to determine V(E E ) and V(E E ). APJIE 1 2 1 2 2 1 Step 3: A convex fuzzy number E to be greater than l convex fuzzy numbers E (i =1, 12,3 2,.. .., l) can be defined by: VEðÞ E ; E ; .. ... . :; E 1 2 ¼VEðÞ E andðÞ E E and . ... .. :: andðÞ E E 1 2 l (3.2) ¼ minVEðÞ E ; i ¼ 1; 2; .. .. . . :; l ðÞ Suppose that p A ¼ minVEðÞ E i i l For l =1, 2, .. ., n, l= i, and weight vectors are given in equation (3.3) as: 0 0 0 0 ðÞ ðÞ ðÞ W ¼ p A ; p A ; .. .. .. :; p A (3.3) 1 2 m Step 4: After normalization, the normalized weight vectors can be obtained in equation (3.4) as: W ¼ pAðÞ; pAðÞ; .. .. .. :;pAðÞ (3.4) 1 2 m 3.2 Calculation of the value of fuzzy synthetic extent The value of fuzzy synthetic extent is calculated from the fuzzy pair-wise comparison matrix (Table IV) by using the equation (3.1). For illustration purpose, the calculation procedure is demonstrated for the innovation enablers as discussed in Table I. Let fuzzy synthetic values with respect to seven IC factors be denoted by IC ,IC ,IC ,IC ,IC ,IC and IC : 1 2 3 4 5 6 7 IC ¼ M ¼ðÞ 1; 1; 1 þðÞ 3; 4; 5 þðÞ 2; 3; 4 þðÞ 2; 3; 4 þðÞ 3; 4; 5 j¼1 þðÞ 0:333; 0:5; 1 þðÞ 3; 4; 5 ¼ðÞ 14:333; 19:50; 25 ðÞ IC ¼ 7:85; 10:08; 12:5 IC ¼ðÞ 5:95; 8:25; 10:83 Similarly, IC = (11.58, 15.58, 20.5), IC = (5.93, 8.25, 11), IC = (8.53, 12.75, 17.33) and IC = 4 5 6 7 (5.85, 8.08, 10.5): "# n m X X ðÞðÞðÞ M ¼ 60:03 ; 82:75 ; 107:7 i¼1 j¼1 "# m n m X X X j j S ¼ M M g g i i j¼1 i¼1 j¼1 Innovation capability in Indian MSMEs Table IV. Fuzzy pair matrix for innovation capability enablers KM RT AP CIM ITM OC CO Knowledge management (KM) (1, 1, 1) (3, 4, 5) (2, 3, 4) (2, 3, 4) (3, 4, 5) (0.333, 0.5, 1) (3, 4, 5) Risk-taking (RT) (0.2, 0.25, 0.333) (1, 1, 1) (0.2, 0.25, 0.333) (0.25, 0.333, 0.5) (3, 4, 5) (3, 4, 5) (0.25, 0.333, 0.5) Actor’s participation (AP) (0.25, 0.333, 0.5) (3, 4, 5) (1, 1, 1) (0.2, 0.25, 0.333) (1, 2, 3) (0.25, 0.333, 0.5) (0.25, 0.333, 0.5) Creativity and idea Management (CIM) (0.25, 0.333, 0.5) (2, 3, 4) (3, 4, 5) (1, 1, 1) (3, 4, 5) (0.333, 0.5, 1) (2, 3, 4) Information and technology management (ITM) (0.2, 0.25, 0.333) (0.2, 0.25, 0.333) (0.333, 0.5, 1) (0.2, 0.25, 0.333) (1, 1, 1) (1, 2, 3) (3, 4, 5) Organizational culture (OC) (1, 2, 3) (0.2, 0.25, 0.333) (2, 3, 4) (1, 2, 3) (0.333, 0.5, 1) (1, 1, 1) (3, 4, 5) Collaboration (CO) (0.2, 0.25, 0.333) (2, 3, 4) (2, 3, 4) (0.25, 0.333, 0.5) (0.2, 0.25, 0.333) (0.2, 0.25, 0.333) (1, 1, 1) APJIE ðÞðÞ ðÞ IC ¼ðÞ 14:333; 19:50; 25 *60:03 ; 82:75 ; 107:7 12,3 ¼ðÞ 0:133; 0:235; 0:416 ðÞðÞ ðÞ Similarly IC ¼ðÞ 7:85; 10:08; 12:5 *60:03 ; 82:75 ; 107:7 ðÞ ¼ 0:072; 0:121; 0:208 ðÞðÞ ðÞ IC ¼ðÞ 5:95; 8:25; 10:83 *60:03 ; 82:75 ; 107:7 ¼ðÞ 0:055; 0:099; 0:180 ðÞ ðÞðÞ ðÞ IC ¼ 11:58; 15:58; 20:5 *60:03 ; 82:75 ; 107:7 ¼ðÞ 0:107; 0:191; 0:341 ðÞðÞ ðÞ IC ¼ðÞ 5:93; 8:25; 11 *60:03 ; 82:75 ; 107:7 ¼ðÞ 0:055; 0:098; 0:183 ðÞðÞ ðÞ IC ¼ðÞ 8:53; 12:75; 17:33 *60:03 ; 82:75 ; 107:7 ¼ðÞ 0:079; 0:154; 0:288 ðÞðÞ ðÞ IC ¼ðÞ 4:1; 5:42; 7 *60:03 ; 82:75 ; 107:7 ¼ðÞ 0:054; 0:097; 0:174 The degree of possibility of IC =(lC ,m ,u ) IC = (IC ,m ,u )is calculated by using 2 2 2 2 1 1 1 1 equation (3.2): VIðÞ C IC ¼ 1;ðÞ i ¼ 2; 3; 4; 5; 6; 7 and 1 i 0:133 0:208 VIðÞ C IC ¼ 2 1 ðÞðÞ 0:121 0:208 0:235 0:133 VIðÞ C IC ¼ 0:397 2 1 0:107 0:208 VIðÞ C IC ¼ 1; andVIðÞ C IC ¼ 2 3 2 4 ðÞðÞ 0:121 0:208 0:188 0:107 ðÞ VIC IC ¼ 0:591 2 4 Similarly, other calculations have been done by the same procedure, by using equations (3.2) to (3.4). V values are calculated are shown in Table V. Then, we determined the minimum degree of possibility by using equation (3.2)as: Innovation capability in Indian MSMEs Table V. The V values and minimum value Degree of possibility Min value IC1 = (0.133, 0.235, 0.416) IC1 > IC2 = 1 IC1 > IC3 = 1 IC1 > IC4 = 1 IC1 > IC5 = 1 IC1 > IC6 = 1 IC1 > IC7 = 1 1 IC2 = (0.072, 0.121, 0.208) IC2 > IC1 = 0.397 IC2 > IC3 = 1 IC2 > IC4 = 0.591 IC2 > IC5 = 1 IC2 > IC6 = 0.80 IC2 > IC7 = 1 0.397 IC3 = (0.055, 0.099, 0.180) IC3 > IC1 = 0.258 IC3 > IC2 = 0.829 IC3 > IC4 = 0.442 IC3 > IC5 = 1 IC3 > IC6 = 0.650 IC3 > IC7 = 1 0.258 IC4 = (0.107, 0.188, 0.341) IC4 > IC1 = 0.824 IC4 > IC2 = 1 IC4 > IC3 = 1 IC4 > IC5 = 1 IC4 > IC6 = 1 IC4 > IC7 = 1 0.824 IC5 = (0.055, 0.098, 0.183) IC5 > IC1 = 0.267 IC5 > IC2 = 0.826 IC5 > IC3 = 0.992 IC5 > IC4 = 0.449 IC5 > IC6 = 0.652 IC5 > IC7 = 1 0.264 IC6 = (0.079, 0.154, 0.288) IC6 > IC1 = 0.656 IC6 > IC2 = 1 IC6 > IC3 = 1 S6 > S4 = 0.829 IC6 > IC5 = 1 IC6 > IC7 = 1 0.656 IC7 = (0.054, 0.097, 0.174) IC7 > IC1 = 0.232 IC7 > IC2 = 0.808 IC7 > IC3 = 0.983 S7 > S4 = 0.418 IC7 > IC5 = 0.983 IC7 > IC6 = 0.629 0.232 ðÞ mKE ¼ minVðÞ IC IC ¼ minðÞ 1; 1; 1; 1; 1; 1 ¼ 1 APJIE 1 k 12,3 ðÞ mRT ¼ minVðÞ IC IC ¼ minðÞ 0:397; 0:931; 0:60; 1; 0:796; 1 ¼ 0:397 2 k ðÞ ðÞ ðÞ ðÞ ðÞ Similarly m AP ¼ 0:258; mIM ¼ 0:824; m ITM ¼ 0:267; mOC ¼ 0:656; mCO ¼ 0:232: Then, the weight vector is given by: W ¼ðÞ 1; 0:397 ; 0:258; 0:824; 0:267; 0:656; 0:232 After normalization of W , we get final weight vectors as: W ¼ðÞ 0:275; 0:109; 0:070; 0:226; 0:073; 0:180; 0:063 Final ranking is done for IC enablers in the descending order as shown in Table VI. 4. Results and discussions Our results show the ranking of various innovation enablers by using fuzzy AHP. The prioritization of the IC factors has been done by observing the highest weightage value, which shows that KM with the weightage value of 0.25751 is the most important factor that helps in enhancing the IC of the MSME sector. In the current business scenario, organizations, especially MSMEs, are fighting for their survival. To be innovative at local, national and global markets, there is a need to develop and enhance organizations’ capabilities. For that, KM must be an integral part of developing and enhancing the ICs of MSMEs, as KM includes the improvement of knowledge generation or transfer through knowledge acquisition, assimilation and dissemination. Knowledge can be enhanced by sharing it within and outside an organization. Knowledge sharing means collecting and donating knowledge, which can be done by capturing, managing and transferring based on experience that exists within an organization (Lin, 2007). The second important factor for developing IC in MSMEs is creativity and idea management (CIM). In MSMEs, there is a need to drive some combination of creative ideas and the ability for their execution. No doubt, the present business environment is dynamic and multifaceted. This scenario demands improved dynamism of approach. Only the organizations that are discerning are able to handle and manage the changes that are inherent in the current business Innovation capability enablers Final weights Rank Knowledge management (KM) 0.275179 1 Risk-taking (RT) 0.109246 4 Actors participation (AP) 0.070996 6 Table VI. Creativity and idea management (CIM) 0.226747 2 Final ranking of Information and technology management (ITM) 0.073473 5 innovation capability Organizational culture (OC) 0.180517 3 enablers Collaboration (CO) 0.063841 7 environment. So, it is very important to manage the ideas effectively and efficiently in the Innovation MSME sector. Based on the weightage value, OC is the third most important factor that capability in helps in generating and developing ICs. Martinez-Roman et al. (2011) claim cross-functional Indian MSMEs communication and hierarchical power and reward system, whereas Smith et al. (2008) highlight the importance of level of decentralization as the determinants of IC, which constitutes OC. At the fourth place, risk-taking (RT) with the weightage value of 0.109246 plays an important role in the process of innovation. Generally, RT is considered as a negative concept. No doubt, some risks are not fruitful but some are well paid off. RT ability leads to learning about new things, approaches, attitude and thinking. RT does not mean doing things without planning; the chances of success will be more if an entrepreneur takes calculated risk. Innovation means developing new things, and RT is also associated with newness and unexplored things, which means without risk, an organization will not generate innovations. Information and technology management (ITM) is at the fifth place with the weightage value of 0.073473. Participation of the actors (customer, suppliers and employees), which stood at sixth rank, is another important factor for enhancing the ICs in the MSME sector. The last factor identified for enhancing the IC of MSMEs is collaboration (CO). Collaboration means working together for the benefit of the team or organization. In a healthy team, every entity is connected and shares a relationship of cooperation. Innovation is a result of sharing of organizational resources, knowledge and time. In many research and development activities, enterprises have to be involved with other organizations and go for interorganizational agreement in the field of research. Only those industries that are active in collaborating with the universities, research institutes and other industries can easily achieve innovation. Other factors for innovation like RT and knowledge enhancement require the ability to change according to different situations. This factor prepares entrepreneurs to perform in a highly dynamic environment with the support of other entities as well. Generally, innovation is considered to be a solution to a problem that requires quick thinking, shifting priorities and going for an alternative course of action. 5. Sensitivity analysis and managerial implications Among all categories of enablers, the creative environment enabler receives the highest priority weight. This enabler ranked as the highest among the other enablers carries the potential to influence other enablers. Hence, it is recommended to test the final ranking by varying the weights of all enablers (Vishwakarma et al., 2015, 2016a, 2016b; Prakash and Barua, 2016a). To illustrate the sensitivity analysis, the effect of an incremental change in value from 0.1 to 0.9, to KM, was determined, as shown in Table VII. The results of the sensitivity analysis indicate that the maximum relative change happened in KM (for details, please see Table VII and Figure 2). Further, owing to variation in the enabler weights, the Knowledge management values in performing the sensitivity analysis test Identified enablers 0.1 0.2 Normalized (0.2751) 0.3 0.4 0.5 0.6 0.7 0.8 0.9 KM 62 1 1111111 Table VII. RT 34 4 4444444 Ranking for specific AP 56 6 6666666 factors by sensitivity CIM 11 2 2222222 analysis when ITM 45 5 5555555 knowledge OC 23 3 3333333 CO 77 7 7777777 management varies 1 APJIE 12,3 10 2 KM 0.8 0.6 RT 0.4 9 3 AP 0.2 CIM 8 4 ITM OC Figure 2. 7 5 CO Results of sensitivity analysis specific enabler weights and their final ranking also varied. In sensitivity analysis, when creative environment enabler value is 0.1, the firstrankisacquiredbyKM, whereasCO holds the last rank. Facto KM holds highest rank until the value of KM reaches to the value (i.e. 0.200). At normalized level, when KM value is 0.2751, then same enabler KM gets first rank and factor CO continues to obtain the last rank. From this point, KM values varied from 0.3 to 0.9, the first rank is acquired by knowledge management, however first rank is obtained by itself and the ranks of other enablers vary in the same manner (for details, please see Table VI and Figure 3). At this instance, it may be concluded that KM is very important in adopting and managing and enhancing the IC of MSMEs and, so, needs greater managerial concentration. If the managers are able to manage the KM factor and its related concerns in an effective manner, it will be quite useful in maintaining and implementing the innovation in MSMEs. KM RT AP CIM ITM OC Figure 3. CO Ranking of enablers obtained in sensitivity analysis run Ranking Implications of our study rest on understanding the importance of various enablers of Innovation IC in MSMEs and the manner in which enablers influence the capability to innovate. capability in For entrepreneurs, enhancing the innovation begins with a clear and specific Indian MSMEs definition of the strategy of the firm. Entrepreneurs and policymakers should consider the various opportunities to develop the innovation to achieve the desired results (Tables VII and VIII). This finding highlights the fact that MSME entrepreneurs in India must possess necessary knowledge and skills with the help of which they acquire essential resources, including being able to take calculated and informed risk and to develop innovative and creative solutions, remain aware of government initiatives and must possess the ability to sense future changes in the market. The importance of KM for developing IC is also highlighted by Al-Ahbabi et al. (2017) and Hussein et al. (2016). 6. Conclusions Enhancing the IC of MSMEs is a very complex and crucial process. In this study, we have explored the factors that act as a catalyst for ICs in MSMEs. In today’s dynamic and multifaceted business environment, it is very imperative to enhance the performance of MSMEs so that they can offer a more innovative product and service that can compete with that offered by its global competitor. However, the question is how MSMEs can identify which factor is important for developing their capability to innovate. For that, it is very imperative to prioritize the factors influencing the IC of an organization. This study presents prioritization of the IC factors by identifying the enablers based on literature, industry experts and industry associates. Our study has confirmed the complexity and importance by prioritizing the various enablers of IC, especially in MSMEs. In addition to the identification of various factors enhancing IC, our results give the ranking to all the enablers. The priority-wise concern for the results of our study highlights several factors that would help entrepreneurs and policymakers to enhance innovation and researchers/ scholars to better channelize their efforts to understand and study the phenomena. 6.1 Limitations and scope of future work We have used the fuzzy AHP approach for prioritizing the factors influencing IC to improve the performance of Indian MSMEs. All pair comparisons in fuzzy AHP have been assigned by experts. From the relevant literature and experts’ views in detail, other IC enablers can be identified and ranked. As it is natural, views of decision-makers may be subjective and vary. Different MCDM approaches may be applied using several approaches such as analytic network process, interpretative structure modeling, interpretative ranking process, decision- making trial and evaluation laboratory and multiple attribute utility theory for the similar problem and outcomes/results can be matched in the further studies. Knowledge management (KM) enabler values in performing the sensitivity run Identified enablers 0.1 0.2 Normalized (0.2751) 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Table VIII. RT 0.138 0.122 0.109 0.105 0.088 0.072 0.055 0.028 0.016 0.010 Weights for specific AP 0.100 0.084 0.071 0.067 0.050 0.034 0.017 0.013 0.009 0.001 enablers by CIM 0.256 0.239 0.227 0.223 0.206 0.189 0.173 0.127 0.093 0.069 sensitivity analysis ITM 0.103 0.086 0.073 0.069 0.053 0.036 0.019 0.013 0.010 0.001 when knowledge OC 0.210 0.193 0.181 0.176 0.160 0.143 0.126 0.110 0.067 0.019 CO 0.093 0.076 0.064 0.060 0.043 0.026 0.010 0.008 0.005 0.000 management varies References APJIE Ahlin, B., Drnovšek, M. and Hisrich, R.D. (2014), “Entrepreneurs’ creativity and firm innovation: the 12,3 moderating role of entrepreneurial self-efficacy”, Small Business Economics, Vol. 43 No. 1, pp. 101-117. Akman, G. and Yilmaz, C. 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Corresponding author Juhi Raghuvanshi can be contacted at: juhiraghuvanshi.iitr@gmail.com For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: permissions@emeraldinsight.com
Asia Pacific Journal of Innovation and Entrepreneurship – Emerald Publishing
Published: Dec 11, 2018
Keywords: India; MCDM; Fuzzy AHP; MSMEs; Innovation capability (IC)
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