- Email: [email protected]
Explaining sustainable supply chain performance using a total interpretive structural modeling approach
Accepted Manuscript Explaining sustainable supply chain performance using a total interpretive structural modeling approach
K.T. Shibin, Angappa Gunasekaran, Rameshwar Dubey
PII: DOI: Reference:
S2352-5509(17)30021-0 http://dx.doi.org/10.1016/j.spc.2017.06.003 SPC 97
To appear in:
Sustainable Production and Consumption
Received date : 20 January 2017 Revised date : 10 June 2017 Accepted date : 21 June 2017 Please cite this article as: Shibin, K.T., Gunasekaran, A., Dubey, R., Explaining sustainable supply chain performance using a total interpretive structural modeling approach. Sustainable Production and Consumption (2017), http://dx.doi.org/10.1016/j.spc.2017.06.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Explaining Sustainable Supply Chain Performance Using a Total Interpretive Structural Modeling Approach
Highlights 1. The antecedents of the sustainable supply chain performance have been proposed. 2. The Graph Theory Approach has been proposed to develop a theoretical framework. 3. The TISM model and MICMAC output should be integrated to develop a testable framework. K.T. Shibin Symbiosis International University, Lavale, Pune-412115, Maharashtra, India Email: [email protected]
Angappa Gunasekaran (Corresponding author) School of Business and Public Administration California State University, Bakersfield 9001 Stockdale Highway Bakersfield, CA 93311-1022 USA Tel: (661) 654-2184 Fax: (661) 654-2207 E-mail: [email protected]
Rameshwar Dubey Montpellier Business School Montpellier Research in Management 2300 Avenue des Moulins 34000 Montpellier France E-mail: [email protected]/[email protected]
2
Explaining Sustainable Supply Chain Performance Using a Total Interpretive Structural Modeling Approach Abstract: In this paper, we have attempted to develop a theoretical framework to explain sustainable supply chain performance (SSCP) using a total interpretive structural modeling (TISM) technique, an alternative method for generating theories. We have identified the enablers of SSCP using two organizational theories: resource-based view (RBV) and institutional theory (IT). Next, we have developed an instrument (structural self-interaction matrix) to capture the inputs of the respondents. Following graph theory logic, the directed graphs used for joining two nodes were converted into binary digit matrix (reachability matrix). Finally, the reachability matrix has been used to develop a total interpretive structural model (TISM) following Sushil’s (2012) guidelines, and further corrected existing inconsistencies in the previous TISM works using Sushil’s (2016) correction suggested for TISM-based models. The current study contributes to our understanding of SSCP and the enablers of SSCP. This study also contributes to the body of alternative research methods that have been used for generating management theories. Our study also provides guidance to the practitioners who are engaged in management of the sustainable supply chain performance in their organizations. Finally, our study also outlines the limitations of the current study and future research directions to expand the current study to a next level. Key words: Sustainable supply chain management (SSCM), TISM, institutional theory, resource-based view theory, sustainability measurements, sustainability operations 1. Introduction In this highly competitive era, the competition is “supply chain versus supply chain” rather than “company versus company” (Boyer et al., 2005; Ketchen and Guinipero, 2004; Ketchen and Hult, 2007). The one nation, one world concept of globalization makes today’s supply chain far more complex (Reuter et al., 2010). Greenhouse gas emissions (Birchall, 2010), inequality (Easterly, 2007), and social injustice (Stiglitz, 2013) are a few of the issues that have affected the global supply chains. Empirical evidence from academic literature is significant to demolish the traditional thought process that the organizational actions and policies of successful enterprises are only guided by economic efficiency considerations (Kauppi, 2013; Min and Galle, 1997, 2001). Environment, society, and economy are the three widely accepted components of
3
sustainability (Garbie, 2014; Carter and Easton, 2011; Dyllick and Hockerts, 2002). Improved sustainable supply chain performance adds long-term corporate financial benefits (Ortas et al., 2014; Wang and Sarkis, 2013; Zailani et al., 2012) and competitive advantage (Forman and Jrgensen, 2004; Preuss, 2007) to the organization. Development of a strategic framework for sustainable supply chain performance by successfully aligning economic goals with environmental and social goals is critical for organizations (Pagell and Wu, 2009). Thus, it is crystal clear that more attention needs to be paid to the sustainability aspect of supply chain and on enhancing the SSCP of supply chains. The literature focusing on sustainable supply chain management (SSCM) has attracted enormous interest among academics (e.g., Winter and Knemeyer, 2013; Touboulic and Walker, 2015; Dubey et al., 2016; Silvestre, 2015a, b). The prior studies have found a significant relationship between sustainability practices and SSCP (Golicic and Smith, 2013; Grekova et al., 2016) and between SSCP and organizational performance (De Brito et al., 2008; Esfahbodi et al., 2016; Wang and Sarkis, 2013). However, little research has been carried out to measure and manage the sustainable supply chain performance (Schaltegger and Burritt, 2014). Despite increasing contributions from academics, theory-focused research in SSCM is relatively rare (Carter and Easton, 2011; Carter and Rogers, 2008; Mollenkopf et al., 2010; Hoejmose and Adrien-Kirby, 2012; Touboulic and Walker, 2015). Winter and Knemeyer (2013) argue that the researchers must go in deep to analyze the theory behind the selection of the constructs used for building a theoretical model. Identifying the critical contextual factors of SSCP is very important, and there is a pressing need to have further research on this front (Halldorsson et al., 2009; Hervani et al., 2005; Forman and Jrgensen, 2004; Preuss, 2007). Use of alternate methods for theory development has received much endorsement among operations management research community in the very recent past (Barratt et al., 2011; Taylor and Taylor, 2009). Moreover, in many cases, a theoretical framework using inductive approaches may remain untested (Hyde, 2000), and deductive approaches may fail to generate new theories (Markman and Krause, 2014). Thus, we draw guiding research questions to address these research gaps: RQ1: What are the most important enablers of sustainable supply chain performance based on the resource-based view theory and institutional theory? RQ2: How they are interlinked to each other?
4
RQ3: What are the levels of these enablers in the conceptual framework of sustainable supply chain performance? Hence, in this context, a total interpretive structural modeling (TISM) approach may be considered as an alternative method for addressing our three research questions (Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012). Hence, our study attempts to develop an SSCP framework by using a multi-methods approach that includes qualitative interpretive logic and graph theory approach (Luo et al., 2017). TISM is one of the methods, which attempts to answer three basic questions of theory development: “what,” by showing the nods as variables, and “why” and “how,” by showing interlinks (Sushil, 2012, 2016; Dubey et al., 2017; Luo et al., 2017). Following Sushil’s (2012) contribution, the TISM method has achieved significant popularity as an effective alternate method for building models (Mangla et al., 2014; Sarma and Pramod, 2015; Dubey et al., 2015b; Singh and Sharma, 2015; Madaan and Choudhary, 2015; Shibin et al., 2016; Yadav and Barve, 2016; Bag, 2016; Dubey et al., 2017). Although there are efforts from emerging economies researchers to build an SSCP framework (see Avittathur and Jayaram, 2016; Esfahbodi et al., 2016; Silvestre, 2015a, b), the contribution is scant. Hence, we have noted this as another important research gap that we try to address through this study in the context of the automotive industry in India. The remaining portion of this paper is as follows. In the next section, we present an extensive literature review. In the third section, we outline the research methodology adopted in our study. In the fourth section, we present our data analyses and conclusive TISM model. In the fifth section, we present our discussions based on the results and highlight our specific contributions to the theory and practice. Finally, we have concluded our study with limitations and future research directions. 2. Literature review Ahi and Searcy (2013) define the SSCM concept as the voluntary integration of social, economic, and environmental considerations with key inter-organizational business systems to create a coordinated supply chain to effectively manage the material, information, and capital flows associated with the procurement, production, and distribution of products or services to fulfill short-term and long-term profitability, stakeholder requirements, competitiveness, and the resilience of the organization. Hence, SSCM can be simply interpreted as the process of managing a supply chain with equal importance on the social, environmental, and economic
5
dimensions of its operations, with the long-term consistent performance of its business in mind. Combining the sustainability concept with supply chain management philosophy helps managers solve social, environmental, and economic issues related to day-to-day purchasing logistics and operations activities (see Brandenburg and Rebs, 2015; Seuring and Muller, 2008; Carter and Easton, 2011; Ashby et al, 2012; Touboulic and Walker, 2015; Stephens et al., 2017). Hence, we may argue that supply chain is not a single destination but is actually a continuous journey of improvement with a long trajectory (Silvestre, 2015a). Silvestre (2015b) developed a theoretical framework for sustainable supply chain based on stakeholder theory and contingency theory, with reference to emerging economies. Further, Reefke and Sundaram (2017) argue that three dimensions—social, environmental, and economic performance measures—are equally important. Next, we have outlined the need for organizational theories and how we have used organizational theories to identify the enablers of SSCP in our study. 2.1. How may the use of organizational theories help explain the complexities in sustainable supply chains? Organizational theories are mixes of more than one theory that deal with the formal organization and basic scientific fundamentals to increase management efficiency (Taylor, 1947; Weber, 2009; Fayol, 1949). Efficient, intelligent use of overlapping and complementary organizational theories provides support for the development of multidimensional and strategic frameworks for sustainable supply chain management (Varsei et al., 2014). Many authors like (see Halldorsson et al. 2003; Ketchen and Hult, 2007; Miri-Lavassani et al., 2009) have used organizational theories to give fundamental support for various concepts related to supply chain management. Despite the popularity of theory-focused research among O&SCM scholars, the use of organizational theories in sustainable supply chain management is still scant (Halldorsson et al., 2003). Organizational theories help to explain the dynamics that affect decisions regarding sustainability activities in the supply chain (Glover et al., 2014; Ball and Craig, 2010). Ketchen and Hult (2007) argue that organizational theories help distinguish the best value supply chain from traditional supply chains by helping us know more than what we already know. Halldorsson et al. (2003) further argue that incorporating organizational theory concepts into a supply chain helps companies ensure better coordination and efficient partnering within the supply chain. Hence, by following these points, we are attempting to integrate the concepts of RBV and IT to build the multidimensional strategic theoretical framework for sustainable supply
6
chain performance. A list of articles that used various organizational theories for theory development are listed in Table 1. Table 1. Use of organizational theories in supply chain Theory
Articles Beske (2012); Heikkurinen and Forsman-Hugg (2011);
Resource-based view theory (Barney, 1991)
Klassen and Vereecke (2012); Markley and Davis (2007); Morali and Searcy (2013); Reuter et al. (2010); Guang Shi et al. (2012)
Institutional theory (DiMaggio and Powell, 1983)
Ketokivi and Schroeder (2004); Law and Gunasekaran (2012); Meixell and Luoma (2015); Snider et al. (2013); Zhu and Geng (2013); Zhu et al. (2013) Carter and Rogers (2008); Craighead et al. (2016);
Transaction cost theory (Williamson, 1981)
Jiang (2009); Pagell et al., (2010); Stonebraker and Liao (2006); Yigitbasioglu (2010) Carter and Jennings (2002); Gold et al. (2010);
Stakeholder theory (Freeman, 1984)
Kirchoff et al. (2011); Matos and Hall (2007); Walker and Brammer (2009); Park-Poaps and Rees (2010)
2.2. How integration of resource-based view and institutional theory can explain SSCP The extensive review of literature suggests that resource-based view theory (RBV) is one of the most popular organizational theories that have been used to explain complex operations and supply chain management phenomena (Bowen et al., 2001; Rungtusanatham et al., 2003; Wu et al., 2006; Hunt and Davis, 2012; Gligor and Holcomb, 2014; Brandon-Jones et al., 2014). Making the resources of an organization very distinctive or superior compared to the resources of its rivals may become a competitive advantage to the firm, provided that the resource requirements match exactly with the environmental opportunities and business requirements (Andrews, 1971; Thompson and Strickland, 1990). This is the base of classical resource-based view in simple words (Wernerfelt, 1984; Peteraf, 1993; Wernerfelt, 1995). Resource-based view theory helps overcome the challenges in SSCM by recognizing and developing key resources that contribute directly or indirectly toward the attainment of economic performance through capability-building in the supply chain. Resource-based view theory is derived from strategic
7
management and the theory of competitive advantage (Carter and Rogers, 2008), whereas institutional theory is derived from institutional economics, evolutionary economics, and actornetwork theory (Wickramasinghe and Alawattage, 2007). Hence, we may argue that RBV focuses mainly on resources and economic rationale, completely ignoring the societal expectations and institutional forces affecting the competitive advantage of the firm. Institutional theory is another popular organizational theory that has been used extensively in operations and supply chain management research (Ketokivi and Schroeder, 2004; Liu et al., 2010). Environment-related practices in SCM (Sarkis et al., 2011) and the implementation of quality programs and technology applications (Barratt and Choi, 2007; Nair and Prajogo, 2009; Liu et al., 2010; Heras-Saizarbitoria et al., 2011) are some of the specific operations management issues explained using institutional theory. Institutional theory provides a clear answer to the question of why organizations become similar in nature by implementing the same kind of business practices (DiMaggio and Powell, 1983). Thus, institutional theory explains the causes of isomorphism among organizational behaviors (Deephouse, 1996). There are many recent research outcomes with a focus on the development of theoretical framework on sustainable supply chain management (see Ahmadet al., 2017; Dubey et al., 2015; Glover et al., 2014; Grob and Benn, 2014; Zhu et al., 2013; Schaltegger and Burritt, 2014). According to DiMaggio and Powell (1983), there are three types of institutional pressures: coercive, mimetic, and normative pressures, which together become the force behind institutional isomorphism. Institutional theory helps point out the factors that may help organizations improve the legitimacy, societal expectations, and capabilities required for survival. Improving legitimacy helps the organization ensure safe access to better resources, minimize risks, and improve its reputation and stakeholder relationships (Sherer and Lee, 2002; Staw and Epstein, 2000). Following Oliver’s (1997) arguments, we can argue that the integration of these two theories are unique in their nature and as natural allies to best align all three pillars of sustainability: social, environmental, and economic factors. In contrast, resource selection and sustainable competitive advantages are highly influenced by institutional factors (Oliver, 1997). Development of resources and competitive advantages are also more likely to be affected by institutional forces beyond economic factors (Barney et al., 2001). Varsei et al. (2014) have used the combination of three organizational theories, RBV, IT, and stakeholder theory, to develop a sustainable supply chain performance framework. Sarkis et al. (2010) and Varsei et al. (2014) also argue that RBV
8
and IT complement each other. Thus, these two theories were selected because they are distinct from each other and contribute unique viewpoints, but are complementary in deriving meaningful insights in SSCM (Fang et al., 2012; Hansjürgensand Antes, 2008; Berrone et al., 2008). 2.3. Sustainable supply chain performance (SSCP) There is a rich body of literature that explicitly suggests a positive relationship between sustainable supply chain management practices and organizational performance (Golicic and Smith, 2013; Grekova et al., 2016). The same is the case with similar studies in the past that have noted a positive relationship between sustainable supply chain performance and organizational performance (De Brito et al., 2008; Esfahbodi et al., 2016; Wang and Sarkis, 2013). However, the studies utilizing all three dimensions are limited. Ageron et al. (2012) argue that external pressures, financial barriers, supplier selection, and waste reduction efforts have a high impact on SSCP. Taticchi et al. (2013) argue, based on extensive literature review, that only thirty papers were published until 2013 on the sustainability performance measures of supply chains considering all three dimensions, whereas there are only 205 relevant research papers in sustainable supply chain performance measurement. Hence, we strongly argue that research attempts considering all three basic dimensions deciding the SSCM performance are still very limited. The performances of triple bottom line pillars of sustainability are narrated below: 2.3.1. Economic performance (ECOP) Economic performance is an integral component of the sustainability performance of supply chains. There is a positive link between corporate social performance and financial outcomes (Orlitzky et al., 2003) and financial and environmental performance (Horvathova, 2010). Organizations must successfully align their financial goals with environmental and social goals to have a sustainable supply chain strategy (Pagell and Wu, 2009). Greening the supply chain operations and processes is another way to improve the economic performance (Rao and Holt, 2005). According to Krause et al. (2009), if cost is measured over the whole product life cycle, sustainability efforts are cost-effective in both the short- and long-term point of view. 2.3.2. Environmental performance (EP) There is consensus among scholars to conserve the environment for sustainable development. Most of the prior studies have considered carbon emissions as the main performance measurement parameter for environmental sustainability (Boukherroub et al., 2017; Ji et al.,
9
2014; Tseng and Hung, 2014). Rokka and Uusitalo (2008) argue that customers increasingly prefer green products due to increased environmental awareness and ethics. Green products help organizations improve green brand equity through green marketing and by targeting green customers, which in turn helps organizations achieve competitive advantage (Liu et al., 2012). The positive impact of environmental performance on green manufacturing and green supply chain are well established (e.g., Ahi and Searcy, 2013; Wagner and Schaltegger, 2004; Schoenherr, 2012; Lo et al., 2012). Ho and Choi (2012) argue that strategic management of environmental challenges helps organizations get competitive advantage and have better sustainability performance. 2.3.3. Social performance (SP) Social performance is one of the three dimensions of sustainability that can never be ignored. Social values and ethics is one of the unavoidable dimensions of sustainable supply chain management organization (Gunasekaran and Spalanzani, 2012; Drake and Schlachter, 2008; Roberts, 2003; Beamon, 2005; Mont and Leire, 2009). Lobel (2006) further argues that human rights violations are another major concern in social sustainability. Lack of corporate strategy and lack of management involvement may hamper an organization’s sustainability achievement efforts (Griffiths and Petrick, 2001; Carter and Dresner, 2001). According to Hutchins and Sutherland (2008), the social dimension pillar of sustainability was not well defined until recently. There are many articles acknowledging the importance and role of corporate social responsibility in supply chain (see Anderse and Skjoett-Larsen, 2009; Hutchins and Sutherland, 2008; Maloni and Brown, 2006; Tate et al., 2010; Spence and Bourlakis, 2009; Seuring et al., 2008). Provision for better working conditions, fair compensation, equal human rights, and cultural diversity are some of the social factors that will affect the social sustainability performance (Rajak and Vinodh, 2015). So, sustainable supply chain performance is considered as the focus of this research. 2.4. Enablers of sustainable supply chain performance Based on RBV and institutional theory logic, we have identified ten enablers of SSCP. 2.4.1. Coercive pressure (CP) Coercive isomorphism results from external formal and informal pressures from the external organizations or competitors of the firm or from the cultural expectations of the society in which it operates (DiMaggio and Powell, 1983; Kauppi, 2013). One of the crucial pressures driving
10
environmental management is coercive pressure (Kilbourne et al., 2002). This includes any pressure created by government or external bodies. According to Liu et al. (2010), powerful organizations put forth coercive force on their suppliers to maintain favorable operational practices that will serve their interests. Consumer preferences decide the features and price of the product (Bask et al., 2013; Orsato, 2006; Trowbridge, 2001). Thus, we may argue that coercive pressure has a major role in shaping the environmental and social performance-related factors of sustainable supply chain performance and must be considered among the important elements. 2.4.2. Mimetic pressure (MP) Mimetic pressure is created when an organization mimics some other one. Competition is identified as one of the mimetic pressures, based on institutional theory, because an organization will try to capture the best sustainability and other innovative practices already successfully adopted by its competitors (Liang et al., 2007; Dubey et al., 2015). Mimetic isomorphism arises when firms attempt to imitate each other because of rising uncertainties (Zsidisin et al., 2005; Kauppi, 2013). Mimetic isomorphism arises when firms try to avoid risk by becoming followers rather than first movers by imitating most successful practices of the first movers (Kauppi, 2013). So, we can understand that these imitating attempts will have a strong impact on the sustainability performance of a supply chain and must be considered one of the important elements. 2.4.3. Normative pressure (NP) Normative pressure evolves from the isomorphism that results when members of professional bodies define the conditions and methods of their work to enforce the legitimacy of their occupation (DiMaggio and Powell, 1983). If there are many individuals with similar qualifications and experience in an organization or a professional body, they may tend to define problems in a similar way and may filter out the common information, which ultimately will lead to homogeneity over some period (St John et al., 2001; Gopal and Gao, 2009). It was found that around 75% of U.S. customers finalized their purchasing decisions keeping the enterprise’s environmental reputation in mind, and around 80% of customers were willing to pay more for environmentally friendly products (Carter et al., 2000). Thus, normative pressures in a developed market arise mainly from environmental awareness and ethical values (Ball and Craig, 2010) and must be considered one of the important factors having a positive influence on the sustainability performance of the supply chain.
11
2.4.4. Top management belief (TMB) Organizations can gain competitive advantage by building capabilities, and top management belief and commitment have a major role in competency development within a firm (Sirmon et al., 2007; Augier and Teece, 2009; Hitt et al., 2015). The psychological state of the top management in embracing sustainability practices in a supply chain is referred to as top management belief (Dubey et al., 2016). Further, Chadwick et al. (2015) and Prajogo and Olhager (2012) argue strongly that top management belief is an important factor in nurturing organizational capabilities. According to Walsh (1988), top management beliefs are the main stimuli behind the decisions and strategy adopted by organizations and influence the decisionmaking process. Scholars in the past have noted the importance of top management belief in building strong information-sharing systems capability that will have a positive impact on the sustainability performance of the supply chain. To conclude, we argue strongly in favor of considering the role of top management belief as an important factor in the enhancement of sustainable supply chain performance. 2.4.5. Top management participation (TMP) The behavior and actions performed by the top management to encourage sustainability practices are referred to as top management participation (Dubey et al., 2016). In many empirical research works, researchers have considered top management participation as a measure of actions grounded in their beliefs (Dubey et al., 2016; Liang et al., 2007). It is a widely accepted fact that top management commitment is one of the critical driving forces of sustainable supply chain transformation and firm performance through the achievement of competitive advantage (Hitt et al., 2015; Prajogo and Olhager, 2012; Waller and Fawcett, 2013; Wu, et al., 2006). According to Liang et al. (2007), different measures of top management participation and commitment include supply chain partnering with vision for effective supply chain collaboration, formulation of strategy for organizational information-sharing, and the development of metrics to monitor supply chain success. Thus, we have considered top management participation as one of the few selected elements in our study. 2.4.6. Supply chain information-sharing (SCIS) Information-sharing (Premkumar and King, 1994) is considered one of the critical organizational resources in generating supply chain capabilities and collaboration (Barney, 1991; Grant, 1991). According to Closs et al. (1997), logistics information system capabilities have a positive impact
12
on the logistics competency of the firm. Improper communication or insufficient information sharing within the entities of a supply chain is considered one of the barriers of SSCM (Seuring and Muller, 2008). Information systems help ensure better collaboration and coordination and assist the entire chain in achieving the goal as a single unit (Dewett and Jones, 2001). According to Brandon-Jones et al. (2014), based on RBV theory, effective information-sharing and connectivity have a positive impact on improving supply chain visibility, which in turn improves supply chain performance. Hence, supply chain information-sharing is considered among the elements of the study. 2.4.7. Supply chain connectivity (SCC) Collaboration helps to commercialize and ensure easy access to innovative technologies for the local and lower-tier suppliers in the supply chain (Dam and Petkova, 2014; Glover et al., 2014). Barrat and Oke (2007) identify connectivity as an important organizational resource that is an outcome of better information-sharing. Lee (2010) shows the success story of interorganizational supply chain collaboration, which helped Hewlett-Packard, Electrolux, Sony, and Braun reduce their recycling and disposal cost by 35% by developing a common European recycling platform. Network-sharing and connectivity improve supply chain visibility, which in turn improves the resilience and robustness of the supply chain (Brandon-Jones et al., 2014; Crook and Esper, 2014). Some of the important measures of supply chain connectivity include the level of integration within the supply chain and firm, the level of information systems linkages existing with partners in the supply chain network, and the level of adequacy of the current information systems to satisfy the existing communication requirements (Fawcett et al., 2009; Brandon-Jones et al., 2014; Duan and Xiong, 2015). Hence, we may argue that SCC is one of the important enablers of sustainable supply chain performance. 2.4.8. Logistics capability (LC) Logistics capabilities can be defined as the specialized skills, attributes, and knowledge that a firm has to acquire to manage logistics activities, such as transportation of finished goods and raw materials, in the most efficient and effective way (Morash et al, 1996; Mentzer et al., 2004; Gligor and Holcomb, 2012). Logistics capability is difficult to imitate and duplicate (Olavarrieta and Ellinger, 1997), and is one of the important parameters in exceeding customer expectations and enhancing market and financial performance (Hayes and Pisano, 1994). There is a considerable amount of literature content that clearly acknowledges that logistics capability is
13
one of the key enablers of an organization’s performance (Fawcett et al., 1997; Daugherty et al., 1998; Bowersox et al., 1999; Lynch et al., 2000; Zhao et al, 2001; Mentzer et al., 2004; Esper et al, 2007; Sezhiyan et al., 2011; Gligor and Holcomb, 2014). According to Hsu et al. (2016) and Roehrich et al. (2014), despite the growing number of empirical research works in sustainable supply chain management, the benefits of SSCM and how it supports developing new capabilities and the creation of value to the business are rarely discussed. Despite this, there has been very little work done exploring the role of logistics capability in the journey of the implementation of sustainability concepts in supply chain management (Dey et al., 2011). A clear picture of the interconnection between logistics capabilities and sustainable supply chain management are also found to be a missing link in the literature (Esper et al, 2007; Sandberg and Abrahamsson, 2011). Logistics capability helps organizations use their assets effectively to create customer value (Bowersox et al., 1999). Gonzalez-Torre et al. (2004) and Dowlatshahi (2000) further emphasize the need to develop reverse logistics networks, to increase the utilization of resources and for the reuse and recycling of the product. Reverse logistics practices are critical for the sustainability performance of the supply chain because they help the organizations have substantial cost savings, profitability, improved customer satisfaction, and brand value, and they make its operations environmentally friendly (Hsu et al., 2013; Hsu et al., 2016). According to Jayaraman and Luo (2007), the aspects of the influence of SSCM in capability development or value creation are still missing. To bridge this gap, we are attempting to consider logistics capability development as one of the important elements based on resource-based view theory. And thus, we argue that logistics capability has a positive impact on the sustainability performance of supply chain management in multiple ways and must be considered in the study. 2.4.9. Supply chain talent (SCT) Dubey and Gunasekaran (2015) argue that talent is an important factor in getting better support for sustainable supply chains, and companies must be alerted to focus on developing talented supply chain professionals for the success of sustainability initiatives. Despite the increasing demand and salaries for supply chain professionals, there is a growing shortage of supply chain talent that is predicted to get worse (Cottrill, 2010; Bradley, 2013; Ellinger and Ellinger, 2014). Hammer (2004) argues that supply chain talent is critical, as all breakthrough innovations in supply chain processes are initiated by a few people who have the capability to destroy and shake
14
up entire industries. In achieving sustainable supply chain management excellence, developing a talent pool is the first component of supply chain transformational strategy implementation (Dittmann, 2012; Slone et al., 2010). Giunipero et al. (2006) further emphasize that ensuring smooth functioning, strong strategic collaboration, and strategic cost reductions are very difficult without talented supply chain professionals with strong technical, communication, and financial skills. Many researchers like Zhang and Lv (2015), Beth et al. (2003), Lambert et al. (1998), and Gammelgaard and Larson (2001) strongly argue that supply chain talent development needs further conscious, planned efforts from the organizations and is one of the areas that lacks attention. Touboulic and Walker (2015) also argue for multi-level theory development efforts in SSCM and identify a gap that considers human knowledge, talent, and other intangible benefits in the conceptual framework development of SSCM. Thus, we too have considered supply chain talent as one of the enablers of the sustainability performance of the supply chain. Symbolic Notation E1
Table 2. Enablers of sustainable supply chain performance Enablers of SSCP Authors (Year) Coercive pressure (CP)
E2
Normative pressure (NP)
E3
Mimetic pressure (MP)
E4
Top management belief (TMB)
E5
Top management participation (TMP)
E6
Supply chain connectivity (SCC)
E7
Supply chain information-sharing (SCIS)
E8
Supply chain talent (SCT)
Bask et al. (2013); DiMaggio and Powell (1983); Kauppi (2013); Kilbourne et al. (2002); Liu et al. (2010); Orsato (2006); Trowbridge (2001) Ball and Craig (2010); Carter et al. (2000); DiMaggio and Powell (1983); St John et al. (2001); Gopal and Gao (2009) Dubey et al. (2015); Kauppi (2013); Liang et al. (2007); Zsidisin et al. (2005) Augier and Teece (2009); Hitt et al. (2015); Sirmon et al. (2007) Dubey et al. (2016); Liang et al. (2007); Hitt et al. (2015); Prajogo and Olhager (2012); Waller and Fawcett (2013);Wu et al. (2006) Barrat and Oke (2007); Brandon-Jones et al. (2014); Crook and Esper (2014); Dam and Petkova (2014); Duan and Xiong (2015); Fawcett et al. (2009); Glover et al. (2014); Lee (2010) Barney (1991); Brandon-Jones et al. (2014); Closset al.(1997); Dewett and Jones (2001); Grant (1991); Premkumar and King (1994); Seuring and Muller (2008) Beth et al. (2003); Dubey and Gunasekaran (2015); Gammelgaard and Larson (2001); Giunipero et al. (2006); Lambert et al. (1998)
15
E9
Logistics capability (LC)
E10
Sustainable supply chain performance (SSCP)
Olavarrieta and Ellinger (1997); Hayes and Pisano (1994); Zhao et al. (2001); Aitken and Harrison (2013); Jayaraman and Luo (2007); Fawcett et al. (1997); Daugherty et al. (1998); Bowersox et al. (1999); Lynch et al. (2000); Zhao et al. (2001); Mentzer et al. (2004); Esper et al. (2007); Sezhiyan et al. (2011); Gligor and Holcomb (2012) Forman and Jrgensen (2004); Pagell and Wu (2009); Preuss (2007); Ortas et al. (2014); Wang and Sarkis (2013); Zailani et al. (2012)
3. Research methodology Enablers were selected based on the literature review and expert opinion. Expert opinion is used to understand and confirm the literature review findings and the interrelationships among the enablers considered in the study. Details of data collection procedure followed are explained below. We have adopted a survey-based approach based on the guidelines of Fawcett et al. (2014) for getting the expert opinion. Supply chain professionals from the automotive industry in India were targeted in the study. The reasons for this approach are twofold. The first is that focusing on the Indian context will help bridge the gap of having a shortage in the number of empirical research attempts on the sustainability performance of the supply chain with reference to emerging economies like India (Silvestre, 2015a, 2015b). Since our focus is on the automotive industry in India, this can be considered a response to the call for more research attempts with reference to the automotive industry in the sustainable supply chain domain (Brandenburg and Rebs, 2015). Moreover, data collection for this project was done as a part of another ongoing empirical research attempt with reference to the automotive industry in India from the various studies. In the second phase of the research, these enablers were verified and interlinks were drawn based on the opinion of experienced supply chain professionals working with automotive manufactures having fifteen-plus years of experience. An exclusive list of manufacturers from the automotive domain based in three major automotive hubs in India—Delhi-National Capital Region, Chennai, and Pune—are collected from various sources, like the Automotive Manufactures Association list, the Delhi Auto Expo, and different automotive manufacturers in Pune. A total of thirty-five randomly selected senior supply chain professionals from the exclusive available list were contacted, and the questionnaire was shared online. We received twenty-seven usable responses with all necessary details at the end of the data collection process, which took around forty to fifty days. After sharing the questionnaire, telephone conversations
16
were held to get their detailed opinions, and the process was done in a single stage. The step-bystep procedure to develop the TISM framework, as detailed by Warfield (1974) and Sushil (2009, 2012, and 2016), and its flow chart are briefed in the following section. 3.1. Identify and define elements In this paper, based on extensive literature review followed by brainstorming with experts, we have finally identified ten enablers of SSCP (see Table 2). The objective of the prospective TISM framework is to explore the relationships and the selection of these elements, which were supported by established theories such as institutional theory and resource-based view theory. Table 3. Structural self-interaction matrix of enablers (SSIM) E10
E9
E8
E7
E6
E5
E4
E3
E2
E1
E1
V
O
V
V
O
V
V
X
X
X
E2
V
O
O
V
V
V
V
X
X
E3
V
V
O
V
O
V
V
X
E4
O
V
V
X
V
X
X
E5
O
V
V
X
V
X
E6
V
X
X
A
X
E7
O
V
V
X
E8
V
A
X
E9
V
X
E10
X
3.2. Define and interpret contextual relationships among elements The contextual relationships between each pair of elements are to be defined based on expert opinion by explaining the guidelines of VAXO matrix formulation to them. In our study, we randomly approached thirty-five subject matter experts in sustainable supply chain management with the help of professional networking sites, and we received a response rate of around 78%. The experts were carefully chosen by ensuring a minimum of fifteen years of professional experience in supply chains, and the matrix was explained on the phone when and where required. The VAXO matrix has some set rules that the respondent had to follow: V: if i leads to j but j doesn’t lead to i; A: if i doesn’t lead to j and j leads to i; X: if i and j lead to each other; O: if i and j are not related each other. For each pair, the first check was to predict the relationship
17
based on “Yes (Y)” or “No (N).” If the response was “Yes,” then further explanation was requested and thus helped us get “Interpretive Logic - Knowledge Base,” shown in Table 7. 4. Data analyses and results Based on the expert opinion, paired comparisons of responses between the enablers are done and are used to build the reachability matrix. The final reachability matrix is derived from the initial reachability matrix by considering the transitivity property. Transitivity links help ensure the consistency of the links measured and ensure that all possible interpretive links are incorporated in the model (Farris and Sage 1975a; Sushil 2012). If a leads to b and b leads to c, then based on the transitivity principle, the assumption that a leads to c will be true. Consideration of transitivity links also helps ensure that there are no possible gaps in the listed interconnections among the variables. Once the final reachability matrix is ready, the next step is level partitioning. Level partitioning is the process of ranking different elements into different levels. The reachability set and antecedent set are found out from the final reachability matrix (Warfield, 1974). If the reachability set’s intersection with the antecedent set is the reachability set itself, then those variables occupy the top levels of the hierarchy. The final output of level partitioning is shown in Table 6. To get the subsequent level variables, the top-level element or elements should be removed and iterations performed repeatedly. The digraph or directed graph is made based on the levels of elements identified from the reachability matrix. Connections are to be made based on the level-wise element partition with the directed links in the reachability matrix. Information in the digraph and interpretive direct interaction matrix are used to make the TISM model. The full element names with the interpretation of elements are to be placed in boxes replacing the nodes in the digraph. The TISM model developed is shown in Figure 2. Interpretive logic between the elements is also to be shown as on the transitive links between the elements. The driving power and dependence of elements are used to plot the MICMAC analysis shown in Figure 1 to clearly bifurcate the elements into four quadrants. The transitivity links based on expert opinion are shown in Table 4. The final binary interaction matrix replacing all values with ‘1’ and ‘0’ is shown in Table 5. Table 4. Final reachability matrix E10 E9 E8 E7 E6 E5 E4 E3 E2 E1 Driving power E1
1
1*
1
1
1*
1
1
1
1
1
10
18
E2
1
1*
1*
1
1
1
1
1
1
1
10
E3
1
1
1*
1
1*
1
1
1
1
1
10
E4
1*
1
1
1
1
1
1
0
0
0
7
E5
1*
1
1
1
1
1
1
0
0
0
7
E6
1
1
1
0
1
0
0
0
0
0
4
E7
1
*
1
1
1
1
1
1
0
0
0
7
E8
1
0
1
0
1
0
0
0
0
0
3
E9
1
1
1
0
1
0
0
0
0
0
4
E10
1
0
0
0
0
0
0
0
0
0
1
Dependence
10
8
9
6
9
6
6
3
3
3
* Represents transitivity property checked. Table 5. Final binary direct interaction matrix E10 E9 E8 E7 E6 E5 E4 E3 E2 E1 Driving power E1
1
1
1
1
1
1
1
1
1
-
10
E2
1
1
1
1
1
1
1
1
-
1
10
E3
1
1
1
1
1
1
1
-
1
1
10
E4
1
1
1
1
1
1
-
0
0
0
7
E5
1
1
1
1
1
-
1
0
0
0
7
E6
1
1
1
0
-
0
0
0
0
0
4
E7
1
1
1
-
1
1
1
0
0
0
7
E8
1
0
-
0
1
0
0
0
0
0
3
E9
1
-
1
0
1
0
0
0
0
0
4
E10
-
0
0
0
0
0
0
0
0
0
1
Dependence
10
8
9
6
9
6
6
3
3
3
Table 6. Level matrix Element E10 E6, E8, E9 E4, E5, E7 E1, E2, E3
Level Level 1 Level 2 Level 3 Level 4
19
Figure 1. MICMAC C diagram
20 Table 7. Transitive links from experts for enablers of sustainable supply chain performance E1
E3
E3
E4
Sharing of resources and knowledge
Better awaren ess through associa tion
Recommend ations from industry associations and groups
Improved benchma rk and standards
Competiti on among the industry group members
Need for better monito ring and error proofing Need to gain compet itive advant age High enthusi asm and efforts
E4
E5
Interpretive Matrix E5 E6
Governm ent and legislative rules and regulations
E1
E2
E2
Knowledge on easy-toimplement and adoptable systems Improved investment in innovative technologies
E6
E7
E8
E9 E10
E8
Better information flow and control Better process and system design Synchronized material flow
E9
E10
Need for emission control and profit maximization
Knowled ge transfer and better exposure
Better understa nding and knowled ge
Better transpare ncy
E7 Better collabora tion among partners to come up with the new rules and standards
Interorganizatio nal interactions
Talent retention and manage ment Better Informati on sharing process
Improved culture, skill and talent develop ment Careful talent and capability develop ment Team work and connecti vity
Better investments
Efficient monitoring and corrections
High resource utilization
Better collaboration and unity
Increased visibility and coordination
Lean supply chain Highly efficient planning and execution High responsiveness and agility
21
5. Discu ussions The objective of ouur current study s was too understannd the sustaiinable suppply chain cooncept, the missing links in thhis researchh domain, and the keey elementss impactingg the perforrmance of
22
sustainable supply chain. We have used the TISM approach, which is regarded as one of the alternate methods for developing a theoretical framework in SSCM (Luo et al. 2017; Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012) as a response to the call for more research attempts by using alternate methodology in operations management (Barratt et al., 2011; Taylor and Taylor, 2009). Even though there are growing numbers of empirical research attempts in SSCM, theoretically grounded research bodies in SSCM are relatively rare (Carter and Easton, 2011; Craig and Rogers, 2008; Mollenkopf et al., 2010), and this research responds to this existing gap by providing a strong and comprehensive theoretical framework (Hermosa and Adrien-Kirby, 2012) and by also selecting a few constructs and their interrelationships by deeply analyzing the theory behind the selection of those particular constructs (Winter and Knemeyer, 2013). Thus, this study is a proper response to the call for more theoretically grounded research attempts by making comprehensive and clear conceptual frameworks of the sustainability performance of the supply chain (Winter and Knemeyer, 2013; Touboulic and Walker, 2015) based on institutional theory and resource-based view theory. Another important point is that this research has succeeded in considering a combination of well-established theories like Madhok (2002), which are very scant. But RBV focuses mainly on resources and their economic rationale. Thus, it can be understood that the focus of RBV is on the economic pillar of sustainability and institutional theory is on the environmental and social pillars of sustainability (Sherer and Lee, 2002; Staw and Epstein, 2000). Hence, we argue that the integration of these two theories is not only unique in its viewpoint in explaining the sustainability dimensions, but the theories are also complementary to each other (Fang et al., 2012; Hansjürgens and Antes, 2008; Berrone et al., 2008). However, based on our best knowledge, empirical research attempts using a combination of these two theories in line with the research attempts of Clemens and Douglas (2006) and Oliver (1997) are rare, and this can be considered one of the few among them. Jayaraman and Luo (2007) argue that the aspects of the influence of SSCM on capability development or value creation are still missing. To bridge this gap, we are attempting to consider logistics capability development as one of the important elements, based on resource-based view theory. Literature review helped us list a few important elements, such as D1 - Coercive pressure (CP), D2 Normative pressure (NP), D3 - Mimetic pressure (MP), D4 - Top management belief (TMB), D5 - Top management participation (TMP), D6 - Supply chain connectivity (SCC), D7 - Supply
23
chain information sharing (SCIS), D8 - Supply chain talent (SCT), D9 - Logistics Capability (LC), and D10 - Sustainable supply chain performance (SSCP). The results show that the supply chain information-sharing capability will be a real competitive advantage for the firm to go for supply chain connectivity, which is again crucial for building logistics capability. The framework clearly shows that supply chain connectivity, logistics capability, and supply chain talent are equally crucial in enhancing the sustainability performance of a supply chain. All the elements chosen in this analysis are relevant, as there are no autonomous variables found in the MICMAC analysis shown in Figure 1. From the MICMAC diagram, it can also be interpreted that top management participation (TMP), supply chain connectivity, and supply chain talent are linkage variables. These variables are characterized by their strong dependency and driving power and are very sensitive elements. Any minor changes in the system or to any other variables will affect these elements. Coercive pressure, mimetic pressure, and normative pressure are found to have high driving power that will determine the sustainability performance of the supply chain. Elements such as supply chain connectivity, supply chain talent, and logistics capability are at the same level in the framework, indicating the direct positive impact of these elements on the sustainability performance of supply chain, which in turn will help organizations achieve a competitive edge over rivals. Again, these capabilities will be achieved with the support of three of the other capabilities, which come in the next lower hierarchy level, such as supply chain information sharing, top management belief, and participation. 5.1. Theoretical contributions The current study attempt may be considered an extension of the literature on theoretical framework development based on a combination of well-established organizational theories (Clemens and Douglas, 2006; Madhok, 2002), sustainability (Bell and Morse, 2013; Dyllick and Hockerts, 2002), and supply chain performance (Taticchi et al., 2015; Tseng et al., 2015). This can also be considered a response to the call for more empirical research works on sustainable supply chain performance by considering the conditions of emerging economies (Silvestre, 2015). The conceptual framework is developed using the TISM approach, which is again based on systems theory and the one which is widely getting accepted as an effective alternate research methodology for theoretical framework development in SSCM (Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012). Hence, the study clearly explores the possibility of
24
building the framework based on a combination of well-established multiple theories with reference to an emerging nation by effectively using an alternative methodology. The study is unique in its kind as it figures out the top ten most relevant elements of the sustainability performance of the supply chain and classifies them based on their driving power and dependence into four categories, viz., autonomous, driving, linkage, and dependence variables, using MICMAC analysis. It also helps in clearly depicting the hierarchy and interlinks among the indicators, which play a crucial role in imparting sustainability performance to the supply chain of organizations. Thus, as a whole, it can be concluded that this study provides immense scope both on theoretical and managerial front for supply chain enthusiasts and researchers. 5.2. Managerial implications Senior supply chain managers can depend on this study to clearly understand the focus areas like supply chain talent, logistics capability, top management commitment, and supply chain integration based on institutional pressures to achieve better social, environmental, and economic performance. Clearly depicted interlinks among the elements from the framework can be considered to plan for focused actions to attain the desired level in the sustainable supply chain performance. Efforts of supply chain managers can be prioritized just on the few mentioned enablers to achieve better sustainability performance by clearly understanding the driving power and dependence of each variable. The study will also help managers to identify very sensitive variables having high dependence and driving power that need continuous monitoring for the effective implementation of sustainable supply chain practices. Sustainable supply chain policy makers can also depend upon this framework to take the business in the right direction and to the next global level. 6. Conclusions, limitations and future research directions This article is a unique attempt to generate a comprehensive theoretical framework using a multimethods approach. The article may be considered an extension of the previous work (see Sushil, 2012, 2016) to explain how TISM can be used as an effective alternate theoretical framework development methodology (see Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012). Enablers of sustainable supply chain performance are identified based on institutional theory and resource-based view theory as a response to have more theoretically grounded research articles in the SSCM domain (see Hoejmose and Adrien-Kirby, 2012; Touboulic and Walker, 2015). This research also answers the call for more research attempts
25
from emerging nations by limiting the scope of research to the Indian context (Avittathur and Jayaram, 2016; Esfahbodi et al., 2016; Silvestre, 2015a, b). By focusing on the automotive industry in India, we are also contributing to the existing very limited research content in the automotive sustainable supply chain domain (Brandenburg and Rebs, 2015). At the end of the article, it can be seen that we have answered all three research questions formulated at the beginning of the research. Because we have come up with i) all the important enablers of sustainable supply chain performance to answer to the first research question ii) by coming up with a theoretical framework showing the interrelationships and the levels of variables to answer the second and third research questions. Finally, to conclude with, this article is contributing immensely toward the existing managerial and theoretical sustainable supply chain knowledge body, i) by providing a comprehensive and clear list of enablers of sustainable supply chain performance, ii) by deriving the clear interlinks and the hierarchy of these enablers through a theoretical framework, iii) by classifying the enablers based on their driving power and dependence, and iv) by shaping out the research process as a response to multiple research gaps existing in the sustainable supply chain domain. Further, research is to be conducted to rectify any possible bias in the analysis that may arise, as the study uses expert surveys and semi-structured questionnaires. One limitation of the study is that it may not be able to portray the relative weightings of elements considered in this study using only TISM methodology. Thus, this work can be extended by using structured questionnaire surveys to explore the real relative weightings of the elements considered. Moreover, more accurate results can be achieved if we go for a higher sample size instead of the current relatively small sample size. Factor analysis using a structural equation modeling technique with a high sample size can be an alternative way to overcome the above-mentioned limitations of this study. Fuzzy MICMAC analysis is one of the alternate ways to further improve sensitivity and to understand the intensity of the relationship between elements. Fuzzy MICMAC will assume intermediate values between 0 and 1, which may enhance the accuracy instead of going with only 0 and 1 as used in the current research. Khatwani et al. (2015) also showed a better extension of the TISM framework, which also offers a comprehensive framework better than this research attempt.
26
References Ahmad, N. K. W., de Brito, M. P., Rezaei, J., and Tavasszy, L. A. (2017). An integrative framework for sustainable supply chain management practices in the oil and gas industry. Journal of Environmental Planning and Management, 60(4), 577-601. Andrews, K. R. (1971). The Concept of Corporate Strategy, Irwin, Homewood, IL. Augier, M., and Teece, D. J. (2009). Dynamic capabilities and the role of managers in business strategy and economic performance. Organization Science, 20(2), 410-421. Bag, S. (2016). Flexible Procurement Systems is Key to Supply Chain Sustainability. Journal of Transport and Supply Chain Management, 10(1). doi:10.4102/jtscm.v10i1.213. Ball, A., and Craig, R. (2010). Using neo-institutionalism to advance social and environmental accounting. Critical Perspectives on Accounting, 21(4), 283-293. Ball, A., and Craig, R. (2010). Using neo-institutionalism to advance social and environmental accounting. Critical Perspectives on Accounting, 21(4), 283-293. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Barney, J. B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view. Journal of Management, 27(6), 643-650. Barratt, M., and Choi, T. (2007). Mandated RFID and institutional responses: Cases of decentralized business units. Production and Operations Management, 16(5), 569-585. Barratt, M., and Oke, A. (2007). Antecedents of supply chain visibility in retail supply chains: a resource-based theory perspective. Journal of Operations Management, 25(6), 1217-1233. Bask, A., Halme, M., Kallio, M., and Kuula, M. (2013). Consumer preferences for sustainability and their impact on supply chain management: The case of mobile phones. International Journal of Physical Distribution and Logistics Management, 43(5/6), 380-406. Bell, S., and Morse, S. (2013). Measuring sustainability: Learning from doing. Routledge. Berrone, P., Gelabert, L., Fosfuri, A., and Gómez-Mejía, L. R. (2008). Can Institutional Forces Create Competitive Advantage? An Empirical Examination of Environmental Innovation. Academy of Management Proceedings, 2008(1), 1-6. Academy of Management. Beske, P. (2012). Dynamic capabilities and sustainable supply chain management. International Journal of Physical Distribution and Logistics Management, 42(4), 372-387. Beth, S., Burt, D. N., Copacino, W., Gopal, C., Lee, H. L., Lynch, R. P., and Morris, S. (2003). Supply chain challenges. Building relationships. Harvard Business Review, 81(7), 64-73. Birchall, J. (February 25, 2010). Walmart to Set Emissions Goals for Suppliers. Financial Times.
27
Bowen, F. E., Cousins, P. D., Lamming, R. C., and Farukt, A. C. (2001). The role of supply management capabilities in green supply. Production and Operations Management, 10(2), 174-189. Bowersox, D. J., Closs, D. J., and Stank, T. P. (1999). 21st century logistics: making supply chain integration a reality. Bowersox, D. J., Stank, T. P., and Daugherty, P. J. (1999). Lean launch: managing product introduction risk through response‐based logistics. Journal of Product Innovation Management, 16(6), 557-568. Boyer, K. K., Frohlich, M., and Hult, G. T. M. (2005). Extending the Supply Chain. AMACOM, New York, NY. Bradley, P. (2013). Industry wants you. DC Velocity, April, 34-36. Brandon‐Jones, E., Squire, B., Autry, C. W., and Petersen, K. J. (2014). A Contingent Resource‐ Based Perspective of Supply Chain Resilience and Robustness. Journal of Supply Chain Management, 50(3), 55-73. Carter, C. R., and Jennings, M. (2000). Purchasing's Contribution to the Socially Responsible Management of the Supply Chain. Tempe, AZ: Center for Advanced Purchasing Studies. Carter, C. R., and Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution and Logistics Management, 38(5), 360-387. Carter, C. R., and Easton, P. L. (2011). Sustainable supply chain management: evolution and future directions. International Journal of Physical Distribution and Logistics Management, 41(1), 46-62. Carter, C. R., Kale, R., and Grimm, C. M. (2000). Environmental purchasing and firm performance: an empirical investigation. Transportation Research Part E: Logistics and Transportation Review 36(3), 219-228. Chadwick, C., Super, J. F., and Kwon, K. (2015). Resource orchestration in practice: CEO emphasis on SHRM, commitment-based HR systems, and firm performance. Strategic Management Journal, 36(3), 360-376. Clemens, B., and Douglas, T. J. (2006). Does coercion drive firms to adopt ‘voluntary’ green initiatives? Relationships among coercion, superior firm resources, and voluntary green initiatives. Journal of Business Research, 59(4), 483-491. Closs, D. J., Goldsby, T. J., and Clinton, S. R. (1997). Information technology influences on world class logistics capability. International Journal of Physical Distribution and Logistics Management, 27(1), 4-17.
28
Cottrill, K. (2010). Are you prepared for the supply chain talent crisis?. MIT Center for Transportation and Logistics White Paper, 1-11. Craighead, C. W., Ketchen Jr, D. J., and Cheng, L. (2016). “Goldilocks” Theorizing in Supply Chain Research: Balancing Scientific and Practical Utility via Middle-Range Theory. Transportation Journal, 55(3), 241-257. Crook, T. R., and Esper, T. L. (2014). Do resources aid in supply chain functioning and management? Yes, but more (and more precise) research is needed. Journal of Supply Chain Management, 50(3), 94-97. Dam, L., and Petkova, B. N. (2014). The impact of environmental supply chain sustainability programs on shareholder wealth. International Journal of Operations and Production Management, 34(5), 586-609. Daugherty, P. J., Stank, T. P., and Ellinger, A. E. (1998). Leveraging logistics/distribution capabilities: the effect of logistics service on market share. Journal of Business Logistics, 19(2), 35. Deephouse, D. (1996). Does isomorphism legitimate? Academy of Management Journal, 39(4), 1024-1039. Dewett, T., and Jones, G. R. (2001). The role of information technology in the organization: a review, model, and assessment. Journal of Management, 27(3), 313-346. Dey, A., LaGuardia, P., and Srinivasan, M. (2011). Building sustainability in logistics operations: a research agenda. Management Research Review, 34(11), 1237-1259. DiMaggio, P. J., and Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147160. Dittmann, J. P. (2012), Supply Chain Transformation: Building and Executing an Integrated Supply Chain Strategy, McGraw-Hill, New York, NY. Dowlatshahi, S. (2000). Developing a theory of reverse logistics. Interfaces, 30(3), 143-155. Duan, L., and Xiong, Y. (2015). Big data analytics and business analytics. Journal of Management Analytics, 2(1), 1-21. Dubey, R., and Gunasekaran, A. (2015). Shortage of sustainable supply chain talent: An industrial training framework. Industrial and Commercial Training, 47(2), 86-94. Dubey, R., Gunasekaran, A., and Ali, S. S. (2015). Exploring the relationship between leadership, operational practices, institutional pressures and environmental performance: A framework for green supply chain. International Journal of Production Economics, 160, 120132.
29
Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Wamba, S. F., and Song, M. (2016). Towards a theory of sustainable consumption and production: Constructs and measurement. Resources, Conservation and Recycling, 106, 78-89. Dubey, R., Gunasekaran, A., Papadopoulos, T., Childe, S. J., Shibin, K. T., and Wamba, S. F. (2017). Sustainable supply chain management: Framework and further research directions. Journal of Cleaner Production. doi:10.1016/j.jclepro.2016.03.117. Dubey, R., Gunasekaran, A., Wamba, S. F., and Bag, S. (2015b). Building theory of green supply chain management using total interpretive structural modeling (TISM). IFACPapersOnLine, 48(3), 1688-1694. Dyllick, T., and Hockerts, K. (2002). Beyond the business case sustainability. Business Strategy and the Environment, 11(2), 130-141.
for corporate
Ellinger, A., and Ellinger, D. (2014). Leveraging human resource development expertise to improve supply chain managers' skills and competencies. European Journal of Training and Development, 38(1/2), 118-135. Esper, T. L., Clifford Defee, C., and Mentzer, J. T. (2010). A framework of supply chain orientation. The International Journal of Logistics Management, 21(2), 161-179. Esper, T. L., Fugate, B. S., and Davis‐Sramek, B. (2007). Logistics learning capability: sustaining the competitive advantage gained through logistics leverage. Journal of Business Logistics, 28(2), 57-82. Fang, H., Memili, E., Chrisman, J. J., and Welsh, D. H. (2012). Family Firms’ Professionalization: Institutional Theory and Resource-Based View Perspectives. Small Business Institute Journal, 8(2), 12-34. Farris, D. R., and Sage, A. P. (1975a). On the use of interpretive structural modeling for worth assessment. Computers and Electrical Engineering, 2(2-3), 149-174. Farris, D. R., and Sage, A. P. (1975). On the use of interpretive structural modeling for worth assessment. Computers and Electrical Engineering, 2(2), 149-174. Fawcett, S. E., Stanley, L. L., and Smith, S. R. (1997). Developing a logistics capability to improve the performance of international operations. Journal of Business Logistics, 18(2), 101. Fayol, H. (1949). General and industrial administration. NY: Pitman. Forman, M., and Jrgensen, M.S. (2004). Organising environmental supply chain management. Greener Management International, 2004(45), 43-62. Formentini, M., and Taticchi, P. (2016). Corporate sustainability approaches and governance mechanisms in sustainable supply chain management. Journal of Cleaner Production, 112, 1920-1933.
30
Gammelgaard, B., and Larson, P. D. (2001). Logistics skills and competencies for supply chain management. Journal of Business Logistics, 22(2), 27-50. Garbie, I. H. (2014). An analytical technique to model and assess sustainable development index in manufacturing enterprises. International Journal of Production Research, (ahead-of-print), 1-40. Giunipero, L., Handfield, R. B., and Eltantawy, R. (2006). Supply management's evolution: key skill sets for the supply manager of the future. International Journal of Operations and Production Management, 26(7), 822-844. Gligor, D. M., and Holcomb, M. (2014). The road to supply chain agility: an RBV perspective on the role of logistics capabilities. The International Journal of Logistics Management, 25(1), 160-179. Glover, J. L., Champion, D., Daniels, K. J., and Dainty, A. J. D. (2014). An Institutional Theory perspective on sustainable practices across the dairy supply chain. International Journal of Production Economics, 152, 102-111. Gold, S., Seuring, S., and Beske, P. (2010). Sustainable supply chain management and inter‐ organizational resources: a literature review. Corporate Social Responsibility and Environmental Management, 17(4), 230-245. Gonzalez-Torre, P. L., Adenso-Diaz, B., and Artiba, H. (2004). Environmental and reverse logistics policies in European bottling and packaging firms. International Journal of Production Economics, 88(1), 95-104. Gopal, A., and Gao, G. (2009). Certification in the Indian offshore IT services industry. Manufacturing and Service Operations Management, 11(3), 471-492. Grant, R. M. (1991). The resource-based theory of competitive advantage: implications for strategy formulation. California Management Review, 33(3), 114-135. Grob, S., and Benn, S. (2014). Conceptualising the adoption of sustainable procurement: an institutional theory perspective. Australasian Journal of Environmental Management, 21(1), 11-21. Guang Shi, V., Lenny Koh, S. C., Baldwin, J., and Cucchiella, F. (2012). Natural resource based green supply chain management. Supply Chain Management: An International Journal, 17(1), 54-67. Halldorsson, A., Kotzab, H., and Skøtt-Larsen, T. (2003). Interorganizational theories behind supply chain management-discussion and applications. Hammer, M. (2004). Deep Change: How Operational Innovation Can Transform Your Company. Harvard Business Review, 82(9), 133.
31
Hansjürgens, B., and Antes, R. (Eds.) (2008). Economics and management of climate change: risks, mitigation and adaptation. Springer Science and Business Media. Hayes, R.H., and Pisano, G.P. (1994). Beyond world-class: the new manufacturing strategy. Harvard Business Review, 72(1), 77-86. Heikkurinen, P., and Forsman‐Hugg, S. (2011). Strategic corporate responsibility in the food chain. Corporate Social Responsibility and Environmental Management, 18(5), 306-316. Heras-Saizarbitoria, I., Landín, G. and Molina-Azorín, J. (2011). Do drivers matter for the benefits of ISO 14001?. International Journal of Operations and Production Management, 31(2) 192-216. Hitt, M. A., Xu, K., and Carnes, C. M. (2015). Resource based theory in operations management research. Journal of Operations Management, 41, 77-94. Hoejmose, S. U., and Adrien-Kirby, A. J. (2012). Socially and environmentally responsible procurement: A literature review and future research agenda of a managerial issue in the 21st century. Journal of Purchasing and Supply Management, 18(4), 232-242. Hsu, C. C., Tan, K. C., and Mohamad Zailani, S. H. (2016). Strategic orientations, sustainable supply chain initiatives, and reverse logistics: Empirical evidence from an emerging market. International Journal of Operations and Production Management, 36(1), 86-110. Hsu, C. C., Tan, K. C., Suhaiza H. M. Z., and Jayaraman, V. (2013). Supply chain drivers that foster the development of green initiatives in an emerging economy. International Journal of Operations and Production Management, 33(6), 656-688. Hunt, S. D., and Davis, D. F. (2012). Grounding supply chain management in resource‐ advantage theory: in defense of a resource‐based view of the firm. Journal of Supply Chain Management, 48(2), 14-20. Jayaraman, V., Klassen, R., and Linton, J.D. (2007). Supply chain management in a sustainable environment. Journal of Operations Management, 25(6), 1071-1074. Jiang, B. (2009). Implementing supplier codes of conduct in global supply chains: Process explanations from theoretic and empirical perspectives. Journal of Business Ethics, 85(1), 77-92. John, C. H. S., Cannon, A. R., and Pouder, R. W. (2001). Change drivers in the new millennium: implications for manufacturing strategy research. Journal of Operations Management, 19(2), 143-160. Kauppi, K. (2013). Extending the use of institutional theory in operations and supply chain management research: Review and research suggestions. International Journal of Operations and Production Management, 33(10), 1318-1345.
32
Ketchen, D. J., and Hult, G. T. M. (2007). Bridging organization theory and supply chain management: The case of best value supply chains. Journal of Operations Management, 25(2), 573-580. Ketchen, D. J., and Guinipero, L. (2004). The intersection of strategic management and supply chain management. Industrial Marketing Management, 33(1), 51-56. Ketokivi, M. A., and Schroeder, R. G. (2004). Strategic, structural contingency and institutional explanations in the adoption of innovative manufacturing practices. Journal of Operations Management, 22(1), 63-89. Khatwani, G., Singh, S. P., Trivedi, A., and Chauhan, A. (2015). Fuzzy-TISM: A fuzzy extension of TISM for group decision making. Global Journal of Flexible Systems Management, 16(1), 97-112. Kilbourne, W. E., Beckmann, S. C., and Thelen, E. (2002). The role of the dominant social paradigm in environmental attitudes: a multinational examination. Journal of Business Research, 55(3), 193-204. Kirchoff, J. F., Koch, C., and Satinover Nichols, B. (2011). Stakeholder perceptions of green marketing: the effect of demand and supply integration. International Journal of Physical Distribution & Logistics Management, 41(7), 684-696. Klassen, R. D., and Vereecke, A. (2012). Social issues in supply chains: Capabilities link responsibility, risk (opportunity), and performance. International Journal of Production Economics, 140(1), 103-115. Lambert, D. M., Cooper, M. C., and Pagh, J. D. (1998). Supply chain management: implementation issues and research opportunities. The International Journal of Logistics Management, 9(2), 1-20. Law, K. M., and Gunasekaran, A. (2012). Sustainability development in high-tech manufacturing firms in Hong Kong: Motivators and readiness. International Journal of Production Economics, 137(1), 116-125. Lee, H. L. (2010). Don't tweak your supply chain–rethink it end to end. Harvard Business Review, 88(10), 62-69. Liang, H., Saraf, N., Hu, Q., and Xue, Y. (2007). Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Quart. 31(1), 59-87. Lin, Y. H., and Tseng, M. L. (2016). Assessing the competitive priorities within sustainable supply chain management under uncertainty. Journal of Cleaner Production, 112, 21332144.
33
Liu, H., Ke, W., Wei, K.K., Gu, J., and Chen, H. (2010). The role of institutional pressures and organizational culture in the firm's intention to adopt internet-enabled supply chain management systems. Journal of Operations Management, 28(5), 372-384. Luo, Z., Dubey, R., Papadopoulos, T., Hazen, B., and Roubaud, D. (2017). Explaining Environmental Sustainability in Supply Chains Using Graph Theory. Computational Economics, 1-19. doi:10.1007/s10614-017-9688-2. Lynch, D. F., Keller, S. B., and Ozment, J. (2000). The effects of logistics capabilities and strategy on firm performance. Journal of Business Logistics, 21(2), 47. Madaan, J.K., and Choudhary, D. (2015). A flexible decision model for risk analysis in product recovery systems. Global Journal of Flexible Systems Management, 16(4), 313-329. Madhok, A. (2002). Reassessing the fundamentals and beyond: Ronald Coase, the transaction cost and resource‐based theories of the firm and the institutional structure of production. Strategic Management Journal, 23(6), 535-550. Mangla, S. K., Kumar, P., and Barua, M. K. (2014). Flexible decision approach for analysing performance of sustainable supply chains under risks/uncertainty. Global Journal of Flexible Systems Management, 15(2), 113-130. Markley, M. J., and Davis, L. (2007). Exploring future competitive advantage through sustainable supply chains. International Journal of Physical Distribution and Logistics Management, 37(9), 763-774. Matos, S., and Hall, J. (2007). Integrating sustainable development in the supply chain: the case of life cycle assessment in oil and gas and agricultural biotechnology. Journal of Operations Management, 25(6), 1083-1102. Meixell, M. J., and Luoma, P. (2015). Stakeholder pressure in sustainable supply chain management. International Journal of Physical Distribution & Logistics Management, 45(1/2), 69. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., and Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1-25. Min, H., and Galle, W.P. (1997). Green purchasing strategies: trends and implications. International Journal of Purchasing and Materials Management, 33(2), 10-17. Min, H., and Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations and Production Management, 21(9), 1222-1238. Miri-Lavassani, K., Movahedi, B., and Kumar, V. (2009). Developments in theories of supply chain management: The case of B2B electronic marketplace adoption. International Journal of Knowledge, Culture and Change Management, 9(6), 85-98.
34
Mollenkopf, D., Stolze, H., Tate, W.L., and Ueltschy, M. (2010). Green, lean and global supply chains. International Journal of Physical Distribution and Logistics Management, 40(1/2), 14-41. Morali, O., and Searcy, C. (2010). Building sustainability into supply chain management: A research agenda. In Proceedings of the 1st annual international symposium on green supply chains, Akron-Canton, OH, USA. Morash, E. A., Droge, C. L., and Vickery, S. K. (1996). Strategic logistics capabilities for competitive advantage and firm success. Journal of Business Logistics, 17(1), 1. Nair, A. and Prajogo, D. (2009). Internalisation of ISO 9000 standards: the antecedent role of functionalist and institutionalist drivers and performance implications. International Journal of Production Research, 47(16), 4545-4568. Olavarrieta, S., and Ellinger, A. E. (1997). Resource-based theory and strategic logistics research. International Journal of Physical Distribution and Logistics Management, 27(9/10), 559-587. Oliver, C. (1997). Sustainable competitive advantage: Combining institutional and resourcebased views. Strategic Management Journal, 18(9), 697-713. Orsato, R.J. (2006). When does it pay to be green?. California Management Review, 48(2), 128. Ortas, E., Moneva, J. M., and Alvarez, I. (2014). Sustainable Supply Chain and Company Performance: A Global Examination. Supply Chain Management: An International Journal, 19(3), 9-9. Pagell, M., and Wu, Z. (2009). Building a more complete theory of sustainable supply chain management using case studies of exemplars. Journal of Supply Chain Management, 45(2), 37-56. Pagell, M., Wu, Z., and Wasserman, M. E. (2010). Thinking differently about purchasing portfolios: an assessment of sustainable sourcing. Journal of Supply Chain Management, 46(1), 57-73. Park-Poaps, H., and Rees, K. (2010). Stakeholder forces of socially responsible supply chain management orientation. Journal of Business Ethics, 92(2), 305-322. Peteraf, M. A. (1993). The cornerstones of competitive advantage: A resource‐based view. Strategic Management Journal, 14(3), 179-191. Prajogo, D., and Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514-522.
35
Premkumar, G., and King, W. R. (1994). Organizational characteristics and information systems planning: an empirical study. Information Systems Research, 5(2), 75-109. Preuss, L. (2007). Buying into our future: sustainability initiatives in local government procurement. Business Strategy and the Environment, 16(5), 354-365. Reefke, H., and Sundaram, D. (2017). Key themes and research opportunities in sustainable supply chain management–identification and evaluation. Omega, 66, 195-211. Reuter, C., Foerstl, K. A. I., Hartmann, E. V. I., and Blome, C. (2010). Sustainable global supplier management: the role of dynamic capabilities in achieving competitive advantage. Journal of Supply Chain Management, 46(2), 45-63. Roehrich, J. K., Grosvold, J., and Hoejmose, S. U. (2014). Reputational risks and sustainable supply chain management: Decision making under bounded rationality. International Journal of Operations and Production Management, 34(5), 695-719. Rungtusanatham, M., Salvador, F., Forza, C., and Choi, T. Y. (2003). Supply-chain linkages and operational performance: a resource-based-view perspective. International Journal of Operations and Production Management, 23(9), 1084-1099. Sandberg, E., and Abrahamsson, M. (2011). Logistics capabilities for sustainable competitive advantage. International Journal of Logistics Research and Applications, 14(1), 61-75. Sarkis, J., Gonzalez-Torre, P., and Adenso-Diaz, B. (2010). Stakeholder pressure and the adoption of environmental practices: The mediating effect of training. Journal of Operations Management, 28(2), 163-176. Sarkis, J., Zhu, Q., and Lai, K. H. (2011). An organizational theoretic review of green supply chain management literature. International Journal of Production Economics, 130(1), 1-15. Sarma, P. R. S., and Pramod, V. R. (2015). Structural flexibility in supply chains: TISM and FISM approach. In Sushil, and G. Chroust (Eds.), Systemic flexibility and business agility, Flexible Systems Management (305-321). New Delhi: Springer. Schaltegger, S., and Burritt, R. (2014). Measuring and managing sustainability performance of supply chains: Review and sustainability supply chain management framework. Supply Chain Management: An International Journal, 19(3), 232-241. Seuring, S.; Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16, 1699-1710. Sezhiyan, D. M., Page, T., and Iskanius, P. (2011). The impact of supply effort management, logistics capability, and supply chain management strategies on firm performance. International Journal of Electronic Transport, 1(1), 26-44. Sherer, P. D., and Lee, K. (2002). Institutional change in large law firms: A resource dependency and institutional perspective. Academy of Management Journal, 45(1), 102-119.
36
Shibin, K. T., Gunasekaran, A., Papadopoulos, T., Dubey, R., Singh, M., and Wamba, S. F. (2016). Enablers and barriers of flexible green supply chain management: A total interpretive structural modeling approach. Global Journal of Flexible Systems Management, 17(2), 171188. Silvestre, B. S. (2015). A hard nut to crack! Implementing supply chain sustainability in an emerging economy. Journal of Cleaner Production, 96, 171-181. Silvestre, B. S. (2015). Sustainable supply chain management in emerging economies: Environmental turbulence, institutional voids and sustainability trajectories. International Journal of Production Economics, 167, 156-169. Singh, R.K., and Sharma, P.B. (2015). TISM-based model to evaluate the flexibility index of a supply chain. In Sushil, and G. Chroust (Eds.), Systemic flexibility and business agility, Flexible Systems Management (323–342). New Delhi: Springer. Sirmon, D.G., Gove, S., and Hitt, M.A. (2008). Resource management in dyadic competitive rivalry: The effects of resource bundling and deployment. Academy of Management Journal, 51(5), 919-935. Slone, R. E., Dittmann, J. P. and Mentzer, J. T. (2010), New Supply Chain Agenda: The 5 Steps That Drive Real Value, Harvard Business Press, Boston, MA. Snider, K. F., Halpern, B. H., Rendon, R. G., and Kidalov, M. V. (2013). Corporate social responsibility and public procurement: How supplying government affects managerial orientations. Journal of Purchasing and Supply Management, 19(2), 63-72. Staw, B. M., and Epstein, L. D. (2000). What bandwagons bring: Effects of popular management techniques on corporate performance, reputation, and CEO pay. Administrative Science Quarterly, 45(3), 523-556. Stonebraker, P. W., and Liao, J. (2006). Supply chain integration: exploring product and environmental contingencies. Supply Chain Management: An International Journal, 11(1), 3443. Sushil (2005a). Interpretive matrix: a tool to aid interpretation of management and social research. Global Journal of Flexible Systems Management, 6(2), 27-30. Sushil (2005b). A flexible strategy framework for managing continuity and change. International Journal of Global Business and Competitiveness, 1(1), 22-32. Sushil (2009). Interpreting the interpretive structural model. Working paper, IIT Delhi. Sushil (2012). Interpreting the interpretive structural model. Global Journal of Flexible Systems Management, 13(2), 87-106.
37
Sushil (2016). How to check correctness of total interpretive structural models?. Annals of Operations Research, 1-15 (DOI: 10.1007/s10479-016-2312-3). Taticchi, P., Garengo, P., Nudurupati, S. S., Tonelli, F., and Pasqualino, R. (2015). A review of decision-support tools and performance measurement and sustainable supply chain management. International Journal of Production Research, 53(21), 6473-6494. Taylor, F. W. (1947). Scientific management. New York and London: Harper and Row. Thompson, A. A. and Strickland, A. J. (1990). Strategic Management: Concepts and Cases, Irwin, Homewood, IL. Touboulic, A., and Walker, H. (2015). Theories in sustainable supply chain management: a structured literature review. International Journal of Physical Distribution and Logistics Management, 45(1/2), 16-42. Trowbridge, P. (2001). A case study of green supply-chain management at advanced micro devices. Greener Management International, 35, 121-135. Tseng, M., Lim, M., and Wong, W.P. (2015). Sustainable supply chain management: A closedloop network hierarchical approach. Industrial Management and Data Systems, 115(3), 436461. Varsei, M., Soosay, C., Fahimnia, B., and Sarkis, J. (2014). Framing sustainability performance of supply chains with multidimensional indicators. Supply Chain Management: An International Journal, 19(3), 242-257. Walker, H., and Brammer, S. (2009). Sustainable procurement in the United Kingdom public sector. Supply Chain Management: An International Journal, 14(2), 128-137. Walley, N., and Whitehead, B. (1994). It's not easy being green. The Earth scan reader in business and the environment, 36-44. Walsh, J. P. (1988). Selectivity and selective perception: an investigation of managers’ belief structures and information processing. Academy of Management Journal, 31(4), 873-896. Wang, Z., and Sarkis, J. (2013). Investigating the relationship of sustainable supply chain management with corporate financial performance. International Journal of Productivity and Performance Management, 62(8), 871-888. Warfield, J. N. (1974). Toward interpretation of complex structural models. IEEE Transactions on Systems, Man and Cybernetics, 5, 405-417. Weber, M. (2009). The theory of social and economic organization. Simon and Schuster. Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171-180.
38
Wernerfelt, B. (1995). The resource‐based view of the firm: Ten years after. Strategic Management Journal, 16(3), 171-174. Wickramasinghe, D., and Alawattage, C. (2007). Management accounting change: approaches and perspectives. Routledge. Winter, M., and Knemeyer, A. M. (2013). Exploring the integration of sustainability and supply chain management: Current state and opportunities for future inquiry. International Journal of Physical Distribution and Logistics Management, 43(1), 18-38. Wu, F., Yeniyurt, S., Kim, D., and Cavusgil, S. T. (2006). The impact of information technology on supply chain capabilities and firm performance: A resource-based view. Industrial Marketing Management, 35(4), 493-504. Yadav, D. K., and Barve, A. (2016). Modeling post-disaster challenges of humanitarian supply chains: A TISM approach. Global Journal of Flexible Systems Management, 17(3), 321-340. Yigitbasioglu, O. M. (2010). Information sharing with key suppliers: a transaction cost theory perspective. International Journal of Physical Distribution & Logistics Management, 40(7), 550578. Zailani, S., Jeyaraman, K., Vengadasan, G., and Premkumar, R. (2012). Sustainable supply chain management (SSCM) in Malaysia: A survey. International Journal of Production Economics, 140(1), 330-340. Zhang, H.Y., and Lv, S. (2015). Intellectual Capital and Technological Innovation: The Mediating Role of Supply Chain Learning. International Journal of Innovation Science, 7(3), 199-210. Zhao, M., Dröge, C., and Stank, T. P. (2001). The effects of logistics capabilities on firm performance: customer‐focused versus information‐focused capabilities. Journal of Business Logistics, 22(2), 91-107. Zhu, Q., and Geng, Y. (2013). Drivers and barriers of extended supply chain practices for energy saving and emission reduction among Chinese manufacturers. Journal of Cleaner Production, 40, 6-12. Zhu, Q., Sarkis, J., and Lai, K. H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106-117. Zhu, Q., Sarkis, J., and Lai, K. H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106-117.
39
Zsidisin, G.A., Melnyk, S.A., and Ragatz, G.L. (2005). An institutional theory perspective of business continuity planning for purchasing and supply management. International Journal of Production Research, 43(16), 3401-3420.
K.T. Shibin, Angappa Gunasekaran, Rameshwar Dubey
PII: DOI: Reference:
S2352-5509(17)30021-0 http://dx.doi.org/10.1016/j.spc.2017.06.003 SPC 97
To appear in:
Sustainable Production and Consumption
Received date : 20 January 2017 Revised date : 10 June 2017 Accepted date : 21 June 2017 Please cite this article as: Shibin, K.T., Gunasekaran, A., Dubey, R., Explaining sustainable supply chain performance using a total interpretive structural modeling approach. Sustainable Production and Consumption (2017), http://dx.doi.org/10.1016/j.spc.2017.06.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Explaining Sustainable Supply Chain Performance Using a Total Interpretive Structural Modeling Approach
Highlights 1. The antecedents of the sustainable supply chain performance have been proposed. 2. The Graph Theory Approach has been proposed to develop a theoretical framework. 3. The TISM model and MICMAC output should be integrated to develop a testable framework. K.T. Shibin Symbiosis International University, Lavale, Pune-412115, Maharashtra, India Email: [email protected]
Angappa Gunasekaran (Corresponding author) School of Business and Public Administration California State University, Bakersfield 9001 Stockdale Highway Bakersfield, CA 93311-1022 USA Tel: (661) 654-2184 Fax: (661) 654-2207 E-mail: [email protected]
Rameshwar Dubey Montpellier Business School Montpellier Research in Management 2300 Avenue des Moulins 34000 Montpellier France E-mail: [email protected]/[email protected]
2
Explaining Sustainable Supply Chain Performance Using a Total Interpretive Structural Modeling Approach Abstract: In this paper, we have attempted to develop a theoretical framework to explain sustainable supply chain performance (SSCP) using a total interpretive structural modeling (TISM) technique, an alternative method for generating theories. We have identified the enablers of SSCP using two organizational theories: resource-based view (RBV) and institutional theory (IT). Next, we have developed an instrument (structural self-interaction matrix) to capture the inputs of the respondents. Following graph theory logic, the directed graphs used for joining two nodes were converted into binary digit matrix (reachability matrix). Finally, the reachability matrix has been used to develop a total interpretive structural model (TISM) following Sushil’s (2012) guidelines, and further corrected existing inconsistencies in the previous TISM works using Sushil’s (2016) correction suggested for TISM-based models. The current study contributes to our understanding of SSCP and the enablers of SSCP. This study also contributes to the body of alternative research methods that have been used for generating management theories. Our study also provides guidance to the practitioners who are engaged in management of the sustainable supply chain performance in their organizations. Finally, our study also outlines the limitations of the current study and future research directions to expand the current study to a next level. Key words: Sustainable supply chain management (SSCM), TISM, institutional theory, resource-based view theory, sustainability measurements, sustainability operations 1. Introduction In this highly competitive era, the competition is “supply chain versus supply chain” rather than “company versus company” (Boyer et al., 2005; Ketchen and Guinipero, 2004; Ketchen and Hult, 2007). The one nation, one world concept of globalization makes today’s supply chain far more complex (Reuter et al., 2010). Greenhouse gas emissions (Birchall, 2010), inequality (Easterly, 2007), and social injustice (Stiglitz, 2013) are a few of the issues that have affected the global supply chains. Empirical evidence from academic literature is significant to demolish the traditional thought process that the organizational actions and policies of successful enterprises are only guided by economic efficiency considerations (Kauppi, 2013; Min and Galle, 1997, 2001). Environment, society, and economy are the three widely accepted components of
3
sustainability (Garbie, 2014; Carter and Easton, 2011; Dyllick and Hockerts, 2002). Improved sustainable supply chain performance adds long-term corporate financial benefits (Ortas et al., 2014; Wang and Sarkis, 2013; Zailani et al., 2012) and competitive advantage (Forman and Jrgensen, 2004; Preuss, 2007) to the organization. Development of a strategic framework for sustainable supply chain performance by successfully aligning economic goals with environmental and social goals is critical for organizations (Pagell and Wu, 2009). Thus, it is crystal clear that more attention needs to be paid to the sustainability aspect of supply chain and on enhancing the SSCP of supply chains. The literature focusing on sustainable supply chain management (SSCM) has attracted enormous interest among academics (e.g., Winter and Knemeyer, 2013; Touboulic and Walker, 2015; Dubey et al., 2016; Silvestre, 2015a, b). The prior studies have found a significant relationship between sustainability practices and SSCP (Golicic and Smith, 2013; Grekova et al., 2016) and between SSCP and organizational performance (De Brito et al., 2008; Esfahbodi et al., 2016; Wang and Sarkis, 2013). However, little research has been carried out to measure and manage the sustainable supply chain performance (Schaltegger and Burritt, 2014). Despite increasing contributions from academics, theory-focused research in SSCM is relatively rare (Carter and Easton, 2011; Carter and Rogers, 2008; Mollenkopf et al., 2010; Hoejmose and Adrien-Kirby, 2012; Touboulic and Walker, 2015). Winter and Knemeyer (2013) argue that the researchers must go in deep to analyze the theory behind the selection of the constructs used for building a theoretical model. Identifying the critical contextual factors of SSCP is very important, and there is a pressing need to have further research on this front (Halldorsson et al., 2009; Hervani et al., 2005; Forman and Jrgensen, 2004; Preuss, 2007). Use of alternate methods for theory development has received much endorsement among operations management research community in the very recent past (Barratt et al., 2011; Taylor and Taylor, 2009). Moreover, in many cases, a theoretical framework using inductive approaches may remain untested (Hyde, 2000), and deductive approaches may fail to generate new theories (Markman and Krause, 2014). Thus, we draw guiding research questions to address these research gaps: RQ1: What are the most important enablers of sustainable supply chain performance based on the resource-based view theory and institutional theory? RQ2: How they are interlinked to each other?
4
RQ3: What are the levels of these enablers in the conceptual framework of sustainable supply chain performance? Hence, in this context, a total interpretive structural modeling (TISM) approach may be considered as an alternative method for addressing our three research questions (Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012). Hence, our study attempts to develop an SSCP framework by using a multi-methods approach that includes qualitative interpretive logic and graph theory approach (Luo et al., 2017). TISM is one of the methods, which attempts to answer three basic questions of theory development: “what,” by showing the nods as variables, and “why” and “how,” by showing interlinks (Sushil, 2012, 2016; Dubey et al., 2017; Luo et al., 2017). Following Sushil’s (2012) contribution, the TISM method has achieved significant popularity as an effective alternate method for building models (Mangla et al., 2014; Sarma and Pramod, 2015; Dubey et al., 2015b; Singh and Sharma, 2015; Madaan and Choudhary, 2015; Shibin et al., 2016; Yadav and Barve, 2016; Bag, 2016; Dubey et al., 2017). Although there are efforts from emerging economies researchers to build an SSCP framework (see Avittathur and Jayaram, 2016; Esfahbodi et al., 2016; Silvestre, 2015a, b), the contribution is scant. Hence, we have noted this as another important research gap that we try to address through this study in the context of the automotive industry in India. The remaining portion of this paper is as follows. In the next section, we present an extensive literature review. In the third section, we outline the research methodology adopted in our study. In the fourth section, we present our data analyses and conclusive TISM model. In the fifth section, we present our discussions based on the results and highlight our specific contributions to the theory and practice. Finally, we have concluded our study with limitations and future research directions. 2. Literature review Ahi and Searcy (2013) define the SSCM concept as the voluntary integration of social, economic, and environmental considerations with key inter-organizational business systems to create a coordinated supply chain to effectively manage the material, information, and capital flows associated with the procurement, production, and distribution of products or services to fulfill short-term and long-term profitability, stakeholder requirements, competitiveness, and the resilience of the organization. Hence, SSCM can be simply interpreted as the process of managing a supply chain with equal importance on the social, environmental, and economic
5
dimensions of its operations, with the long-term consistent performance of its business in mind. Combining the sustainability concept with supply chain management philosophy helps managers solve social, environmental, and economic issues related to day-to-day purchasing logistics and operations activities (see Brandenburg and Rebs, 2015; Seuring and Muller, 2008; Carter and Easton, 2011; Ashby et al, 2012; Touboulic and Walker, 2015; Stephens et al., 2017). Hence, we may argue that supply chain is not a single destination but is actually a continuous journey of improvement with a long trajectory (Silvestre, 2015a). Silvestre (2015b) developed a theoretical framework for sustainable supply chain based on stakeholder theory and contingency theory, with reference to emerging economies. Further, Reefke and Sundaram (2017) argue that three dimensions—social, environmental, and economic performance measures—are equally important. Next, we have outlined the need for organizational theories and how we have used organizational theories to identify the enablers of SSCP in our study. 2.1. How may the use of organizational theories help explain the complexities in sustainable supply chains? Organizational theories are mixes of more than one theory that deal with the formal organization and basic scientific fundamentals to increase management efficiency (Taylor, 1947; Weber, 2009; Fayol, 1949). Efficient, intelligent use of overlapping and complementary organizational theories provides support for the development of multidimensional and strategic frameworks for sustainable supply chain management (Varsei et al., 2014). Many authors like (see Halldorsson et al. 2003; Ketchen and Hult, 2007; Miri-Lavassani et al., 2009) have used organizational theories to give fundamental support for various concepts related to supply chain management. Despite the popularity of theory-focused research among O&SCM scholars, the use of organizational theories in sustainable supply chain management is still scant (Halldorsson et al., 2003). Organizational theories help to explain the dynamics that affect decisions regarding sustainability activities in the supply chain (Glover et al., 2014; Ball and Craig, 2010). Ketchen and Hult (2007) argue that organizational theories help distinguish the best value supply chain from traditional supply chains by helping us know more than what we already know. Halldorsson et al. (2003) further argue that incorporating organizational theory concepts into a supply chain helps companies ensure better coordination and efficient partnering within the supply chain. Hence, by following these points, we are attempting to integrate the concepts of RBV and IT to build the multidimensional strategic theoretical framework for sustainable supply
6
chain performance. A list of articles that used various organizational theories for theory development are listed in Table 1. Table 1. Use of organizational theories in supply chain Theory
Articles Beske (2012); Heikkurinen and Forsman-Hugg (2011);
Resource-based view theory (Barney, 1991)
Klassen and Vereecke (2012); Markley and Davis (2007); Morali and Searcy (2013); Reuter et al. (2010); Guang Shi et al. (2012)
Institutional theory (DiMaggio and Powell, 1983)
Ketokivi and Schroeder (2004); Law and Gunasekaran (2012); Meixell and Luoma (2015); Snider et al. (2013); Zhu and Geng (2013); Zhu et al. (2013) Carter and Rogers (2008); Craighead et al. (2016);
Transaction cost theory (Williamson, 1981)
Jiang (2009); Pagell et al., (2010); Stonebraker and Liao (2006); Yigitbasioglu (2010) Carter and Jennings (2002); Gold et al. (2010);
Stakeholder theory (Freeman, 1984)
Kirchoff et al. (2011); Matos and Hall (2007); Walker and Brammer (2009); Park-Poaps and Rees (2010)
2.2. How integration of resource-based view and institutional theory can explain SSCP The extensive review of literature suggests that resource-based view theory (RBV) is one of the most popular organizational theories that have been used to explain complex operations and supply chain management phenomena (Bowen et al., 2001; Rungtusanatham et al., 2003; Wu et al., 2006; Hunt and Davis, 2012; Gligor and Holcomb, 2014; Brandon-Jones et al., 2014). Making the resources of an organization very distinctive or superior compared to the resources of its rivals may become a competitive advantage to the firm, provided that the resource requirements match exactly with the environmental opportunities and business requirements (Andrews, 1971; Thompson and Strickland, 1990). This is the base of classical resource-based view in simple words (Wernerfelt, 1984; Peteraf, 1993; Wernerfelt, 1995). Resource-based view theory helps overcome the challenges in SSCM by recognizing and developing key resources that contribute directly or indirectly toward the attainment of economic performance through capability-building in the supply chain. Resource-based view theory is derived from strategic
7
management and the theory of competitive advantage (Carter and Rogers, 2008), whereas institutional theory is derived from institutional economics, evolutionary economics, and actornetwork theory (Wickramasinghe and Alawattage, 2007). Hence, we may argue that RBV focuses mainly on resources and economic rationale, completely ignoring the societal expectations and institutional forces affecting the competitive advantage of the firm. Institutional theory is another popular organizational theory that has been used extensively in operations and supply chain management research (Ketokivi and Schroeder, 2004; Liu et al., 2010). Environment-related practices in SCM (Sarkis et al., 2011) and the implementation of quality programs and technology applications (Barratt and Choi, 2007; Nair and Prajogo, 2009; Liu et al., 2010; Heras-Saizarbitoria et al., 2011) are some of the specific operations management issues explained using institutional theory. Institutional theory provides a clear answer to the question of why organizations become similar in nature by implementing the same kind of business practices (DiMaggio and Powell, 1983). Thus, institutional theory explains the causes of isomorphism among organizational behaviors (Deephouse, 1996). There are many recent research outcomes with a focus on the development of theoretical framework on sustainable supply chain management (see Ahmadet al., 2017; Dubey et al., 2015; Glover et al., 2014; Grob and Benn, 2014; Zhu et al., 2013; Schaltegger and Burritt, 2014). According to DiMaggio and Powell (1983), there are three types of institutional pressures: coercive, mimetic, and normative pressures, which together become the force behind institutional isomorphism. Institutional theory helps point out the factors that may help organizations improve the legitimacy, societal expectations, and capabilities required for survival. Improving legitimacy helps the organization ensure safe access to better resources, minimize risks, and improve its reputation and stakeholder relationships (Sherer and Lee, 2002; Staw and Epstein, 2000). Following Oliver’s (1997) arguments, we can argue that the integration of these two theories are unique in their nature and as natural allies to best align all three pillars of sustainability: social, environmental, and economic factors. In contrast, resource selection and sustainable competitive advantages are highly influenced by institutional factors (Oliver, 1997). Development of resources and competitive advantages are also more likely to be affected by institutional forces beyond economic factors (Barney et al., 2001). Varsei et al. (2014) have used the combination of three organizational theories, RBV, IT, and stakeholder theory, to develop a sustainable supply chain performance framework. Sarkis et al. (2010) and Varsei et al. (2014) also argue that RBV
8
and IT complement each other. Thus, these two theories were selected because they are distinct from each other and contribute unique viewpoints, but are complementary in deriving meaningful insights in SSCM (Fang et al., 2012; Hansjürgensand Antes, 2008; Berrone et al., 2008). 2.3. Sustainable supply chain performance (SSCP) There is a rich body of literature that explicitly suggests a positive relationship between sustainable supply chain management practices and organizational performance (Golicic and Smith, 2013; Grekova et al., 2016). The same is the case with similar studies in the past that have noted a positive relationship between sustainable supply chain performance and organizational performance (De Brito et al., 2008; Esfahbodi et al., 2016; Wang and Sarkis, 2013). However, the studies utilizing all three dimensions are limited. Ageron et al. (2012) argue that external pressures, financial barriers, supplier selection, and waste reduction efforts have a high impact on SSCP. Taticchi et al. (2013) argue, based on extensive literature review, that only thirty papers were published until 2013 on the sustainability performance measures of supply chains considering all three dimensions, whereas there are only 205 relevant research papers in sustainable supply chain performance measurement. Hence, we strongly argue that research attempts considering all three basic dimensions deciding the SSCM performance are still very limited. The performances of triple bottom line pillars of sustainability are narrated below: 2.3.1. Economic performance (ECOP) Economic performance is an integral component of the sustainability performance of supply chains. There is a positive link between corporate social performance and financial outcomes (Orlitzky et al., 2003) and financial and environmental performance (Horvathova, 2010). Organizations must successfully align their financial goals with environmental and social goals to have a sustainable supply chain strategy (Pagell and Wu, 2009). Greening the supply chain operations and processes is another way to improve the economic performance (Rao and Holt, 2005). According to Krause et al. (2009), if cost is measured over the whole product life cycle, sustainability efforts are cost-effective in both the short- and long-term point of view. 2.3.2. Environmental performance (EP) There is consensus among scholars to conserve the environment for sustainable development. Most of the prior studies have considered carbon emissions as the main performance measurement parameter for environmental sustainability (Boukherroub et al., 2017; Ji et al.,
9
2014; Tseng and Hung, 2014). Rokka and Uusitalo (2008) argue that customers increasingly prefer green products due to increased environmental awareness and ethics. Green products help organizations improve green brand equity through green marketing and by targeting green customers, which in turn helps organizations achieve competitive advantage (Liu et al., 2012). The positive impact of environmental performance on green manufacturing and green supply chain are well established (e.g., Ahi and Searcy, 2013; Wagner and Schaltegger, 2004; Schoenherr, 2012; Lo et al., 2012). Ho and Choi (2012) argue that strategic management of environmental challenges helps organizations get competitive advantage and have better sustainability performance. 2.3.3. Social performance (SP) Social performance is one of the three dimensions of sustainability that can never be ignored. Social values and ethics is one of the unavoidable dimensions of sustainable supply chain management organization (Gunasekaran and Spalanzani, 2012; Drake and Schlachter, 2008; Roberts, 2003; Beamon, 2005; Mont and Leire, 2009). Lobel (2006) further argues that human rights violations are another major concern in social sustainability. Lack of corporate strategy and lack of management involvement may hamper an organization’s sustainability achievement efforts (Griffiths and Petrick, 2001; Carter and Dresner, 2001). According to Hutchins and Sutherland (2008), the social dimension pillar of sustainability was not well defined until recently. There are many articles acknowledging the importance and role of corporate social responsibility in supply chain (see Anderse and Skjoett-Larsen, 2009; Hutchins and Sutherland, 2008; Maloni and Brown, 2006; Tate et al., 2010; Spence and Bourlakis, 2009; Seuring et al., 2008). Provision for better working conditions, fair compensation, equal human rights, and cultural diversity are some of the social factors that will affect the social sustainability performance (Rajak and Vinodh, 2015). So, sustainable supply chain performance is considered as the focus of this research. 2.4. Enablers of sustainable supply chain performance Based on RBV and institutional theory logic, we have identified ten enablers of SSCP. 2.4.1. Coercive pressure (CP) Coercive isomorphism results from external formal and informal pressures from the external organizations or competitors of the firm or from the cultural expectations of the society in which it operates (DiMaggio and Powell, 1983; Kauppi, 2013). One of the crucial pressures driving
10
environmental management is coercive pressure (Kilbourne et al., 2002). This includes any pressure created by government or external bodies. According to Liu et al. (2010), powerful organizations put forth coercive force on their suppliers to maintain favorable operational practices that will serve their interests. Consumer preferences decide the features and price of the product (Bask et al., 2013; Orsato, 2006; Trowbridge, 2001). Thus, we may argue that coercive pressure has a major role in shaping the environmental and social performance-related factors of sustainable supply chain performance and must be considered among the important elements. 2.4.2. Mimetic pressure (MP) Mimetic pressure is created when an organization mimics some other one. Competition is identified as one of the mimetic pressures, based on institutional theory, because an organization will try to capture the best sustainability and other innovative practices already successfully adopted by its competitors (Liang et al., 2007; Dubey et al., 2015). Mimetic isomorphism arises when firms attempt to imitate each other because of rising uncertainties (Zsidisin et al., 2005; Kauppi, 2013). Mimetic isomorphism arises when firms try to avoid risk by becoming followers rather than first movers by imitating most successful practices of the first movers (Kauppi, 2013). So, we can understand that these imitating attempts will have a strong impact on the sustainability performance of a supply chain and must be considered one of the important elements. 2.4.3. Normative pressure (NP) Normative pressure evolves from the isomorphism that results when members of professional bodies define the conditions and methods of their work to enforce the legitimacy of their occupation (DiMaggio and Powell, 1983). If there are many individuals with similar qualifications and experience in an organization or a professional body, they may tend to define problems in a similar way and may filter out the common information, which ultimately will lead to homogeneity over some period (St John et al., 2001; Gopal and Gao, 2009). It was found that around 75% of U.S. customers finalized their purchasing decisions keeping the enterprise’s environmental reputation in mind, and around 80% of customers were willing to pay more for environmentally friendly products (Carter et al., 2000). Thus, normative pressures in a developed market arise mainly from environmental awareness and ethical values (Ball and Craig, 2010) and must be considered one of the important factors having a positive influence on the sustainability performance of the supply chain.
11
2.4.4. Top management belief (TMB) Organizations can gain competitive advantage by building capabilities, and top management belief and commitment have a major role in competency development within a firm (Sirmon et al., 2007; Augier and Teece, 2009; Hitt et al., 2015). The psychological state of the top management in embracing sustainability practices in a supply chain is referred to as top management belief (Dubey et al., 2016). Further, Chadwick et al. (2015) and Prajogo and Olhager (2012) argue strongly that top management belief is an important factor in nurturing organizational capabilities. According to Walsh (1988), top management beliefs are the main stimuli behind the decisions and strategy adopted by organizations and influence the decisionmaking process. Scholars in the past have noted the importance of top management belief in building strong information-sharing systems capability that will have a positive impact on the sustainability performance of the supply chain. To conclude, we argue strongly in favor of considering the role of top management belief as an important factor in the enhancement of sustainable supply chain performance. 2.4.5. Top management participation (TMP) The behavior and actions performed by the top management to encourage sustainability practices are referred to as top management participation (Dubey et al., 2016). In many empirical research works, researchers have considered top management participation as a measure of actions grounded in their beliefs (Dubey et al., 2016; Liang et al., 2007). It is a widely accepted fact that top management commitment is one of the critical driving forces of sustainable supply chain transformation and firm performance through the achievement of competitive advantage (Hitt et al., 2015; Prajogo and Olhager, 2012; Waller and Fawcett, 2013; Wu, et al., 2006). According to Liang et al. (2007), different measures of top management participation and commitment include supply chain partnering with vision for effective supply chain collaboration, formulation of strategy for organizational information-sharing, and the development of metrics to monitor supply chain success. Thus, we have considered top management participation as one of the few selected elements in our study. 2.4.6. Supply chain information-sharing (SCIS) Information-sharing (Premkumar and King, 1994) is considered one of the critical organizational resources in generating supply chain capabilities and collaboration (Barney, 1991; Grant, 1991). According to Closs et al. (1997), logistics information system capabilities have a positive impact
12
on the logistics competency of the firm. Improper communication or insufficient information sharing within the entities of a supply chain is considered one of the barriers of SSCM (Seuring and Muller, 2008). Information systems help ensure better collaboration and coordination and assist the entire chain in achieving the goal as a single unit (Dewett and Jones, 2001). According to Brandon-Jones et al. (2014), based on RBV theory, effective information-sharing and connectivity have a positive impact on improving supply chain visibility, which in turn improves supply chain performance. Hence, supply chain information-sharing is considered among the elements of the study. 2.4.7. Supply chain connectivity (SCC) Collaboration helps to commercialize and ensure easy access to innovative technologies for the local and lower-tier suppliers in the supply chain (Dam and Petkova, 2014; Glover et al., 2014). Barrat and Oke (2007) identify connectivity as an important organizational resource that is an outcome of better information-sharing. Lee (2010) shows the success story of interorganizational supply chain collaboration, which helped Hewlett-Packard, Electrolux, Sony, and Braun reduce their recycling and disposal cost by 35% by developing a common European recycling platform. Network-sharing and connectivity improve supply chain visibility, which in turn improves the resilience and robustness of the supply chain (Brandon-Jones et al., 2014; Crook and Esper, 2014). Some of the important measures of supply chain connectivity include the level of integration within the supply chain and firm, the level of information systems linkages existing with partners in the supply chain network, and the level of adequacy of the current information systems to satisfy the existing communication requirements (Fawcett et al., 2009; Brandon-Jones et al., 2014; Duan and Xiong, 2015). Hence, we may argue that SCC is one of the important enablers of sustainable supply chain performance. 2.4.8. Logistics capability (LC) Logistics capabilities can be defined as the specialized skills, attributes, and knowledge that a firm has to acquire to manage logistics activities, such as transportation of finished goods and raw materials, in the most efficient and effective way (Morash et al, 1996; Mentzer et al., 2004; Gligor and Holcomb, 2012). Logistics capability is difficult to imitate and duplicate (Olavarrieta and Ellinger, 1997), and is one of the important parameters in exceeding customer expectations and enhancing market and financial performance (Hayes and Pisano, 1994). There is a considerable amount of literature content that clearly acknowledges that logistics capability is
13
one of the key enablers of an organization’s performance (Fawcett et al., 1997; Daugherty et al., 1998; Bowersox et al., 1999; Lynch et al., 2000; Zhao et al, 2001; Mentzer et al., 2004; Esper et al, 2007; Sezhiyan et al., 2011; Gligor and Holcomb, 2014). According to Hsu et al. (2016) and Roehrich et al. (2014), despite the growing number of empirical research works in sustainable supply chain management, the benefits of SSCM and how it supports developing new capabilities and the creation of value to the business are rarely discussed. Despite this, there has been very little work done exploring the role of logistics capability in the journey of the implementation of sustainability concepts in supply chain management (Dey et al., 2011). A clear picture of the interconnection between logistics capabilities and sustainable supply chain management are also found to be a missing link in the literature (Esper et al, 2007; Sandberg and Abrahamsson, 2011). Logistics capability helps organizations use their assets effectively to create customer value (Bowersox et al., 1999). Gonzalez-Torre et al. (2004) and Dowlatshahi (2000) further emphasize the need to develop reverse logistics networks, to increase the utilization of resources and for the reuse and recycling of the product. Reverse logistics practices are critical for the sustainability performance of the supply chain because they help the organizations have substantial cost savings, profitability, improved customer satisfaction, and brand value, and they make its operations environmentally friendly (Hsu et al., 2013; Hsu et al., 2016). According to Jayaraman and Luo (2007), the aspects of the influence of SSCM in capability development or value creation are still missing. To bridge this gap, we are attempting to consider logistics capability development as one of the important elements based on resource-based view theory. And thus, we argue that logistics capability has a positive impact on the sustainability performance of supply chain management in multiple ways and must be considered in the study. 2.4.9. Supply chain talent (SCT) Dubey and Gunasekaran (2015) argue that talent is an important factor in getting better support for sustainable supply chains, and companies must be alerted to focus on developing talented supply chain professionals for the success of sustainability initiatives. Despite the increasing demand and salaries for supply chain professionals, there is a growing shortage of supply chain talent that is predicted to get worse (Cottrill, 2010; Bradley, 2013; Ellinger and Ellinger, 2014). Hammer (2004) argues that supply chain talent is critical, as all breakthrough innovations in supply chain processes are initiated by a few people who have the capability to destroy and shake
14
up entire industries. In achieving sustainable supply chain management excellence, developing a talent pool is the first component of supply chain transformational strategy implementation (Dittmann, 2012; Slone et al., 2010). Giunipero et al. (2006) further emphasize that ensuring smooth functioning, strong strategic collaboration, and strategic cost reductions are very difficult without talented supply chain professionals with strong technical, communication, and financial skills. Many researchers like Zhang and Lv (2015), Beth et al. (2003), Lambert et al. (1998), and Gammelgaard and Larson (2001) strongly argue that supply chain talent development needs further conscious, planned efforts from the organizations and is one of the areas that lacks attention. Touboulic and Walker (2015) also argue for multi-level theory development efforts in SSCM and identify a gap that considers human knowledge, talent, and other intangible benefits in the conceptual framework development of SSCM. Thus, we too have considered supply chain talent as one of the enablers of the sustainability performance of the supply chain. Symbolic Notation E1
Table 2. Enablers of sustainable supply chain performance Enablers of SSCP Authors (Year) Coercive pressure (CP)
E2
Normative pressure (NP)
E3
Mimetic pressure (MP)
E4
Top management belief (TMB)
E5
Top management participation (TMP)
E6
Supply chain connectivity (SCC)
E7
Supply chain information-sharing (SCIS)
E8
Supply chain talent (SCT)
Bask et al. (2013); DiMaggio and Powell (1983); Kauppi (2013); Kilbourne et al. (2002); Liu et al. (2010); Orsato (2006); Trowbridge (2001) Ball and Craig (2010); Carter et al. (2000); DiMaggio and Powell (1983); St John et al. (2001); Gopal and Gao (2009) Dubey et al. (2015); Kauppi (2013); Liang et al. (2007); Zsidisin et al. (2005) Augier and Teece (2009); Hitt et al. (2015); Sirmon et al. (2007) Dubey et al. (2016); Liang et al. (2007); Hitt et al. (2015); Prajogo and Olhager (2012); Waller and Fawcett (2013);Wu et al. (2006) Barrat and Oke (2007); Brandon-Jones et al. (2014); Crook and Esper (2014); Dam and Petkova (2014); Duan and Xiong (2015); Fawcett et al. (2009); Glover et al. (2014); Lee (2010) Barney (1991); Brandon-Jones et al. (2014); Closset al.(1997); Dewett and Jones (2001); Grant (1991); Premkumar and King (1994); Seuring and Muller (2008) Beth et al. (2003); Dubey and Gunasekaran (2015); Gammelgaard and Larson (2001); Giunipero et al. (2006); Lambert et al. (1998)
15
E9
Logistics capability (LC)
E10
Sustainable supply chain performance (SSCP)
Olavarrieta and Ellinger (1997); Hayes and Pisano (1994); Zhao et al. (2001); Aitken and Harrison (2013); Jayaraman and Luo (2007); Fawcett et al. (1997); Daugherty et al. (1998); Bowersox et al. (1999); Lynch et al. (2000); Zhao et al. (2001); Mentzer et al. (2004); Esper et al. (2007); Sezhiyan et al. (2011); Gligor and Holcomb (2012) Forman and Jrgensen (2004); Pagell and Wu (2009); Preuss (2007); Ortas et al. (2014); Wang and Sarkis (2013); Zailani et al. (2012)
3. Research methodology Enablers were selected based on the literature review and expert opinion. Expert opinion is used to understand and confirm the literature review findings and the interrelationships among the enablers considered in the study. Details of data collection procedure followed are explained below. We have adopted a survey-based approach based on the guidelines of Fawcett et al. (2014) for getting the expert opinion. Supply chain professionals from the automotive industry in India were targeted in the study. The reasons for this approach are twofold. The first is that focusing on the Indian context will help bridge the gap of having a shortage in the number of empirical research attempts on the sustainability performance of the supply chain with reference to emerging economies like India (Silvestre, 2015a, 2015b). Since our focus is on the automotive industry in India, this can be considered a response to the call for more research attempts with reference to the automotive industry in the sustainable supply chain domain (Brandenburg and Rebs, 2015). Moreover, data collection for this project was done as a part of another ongoing empirical research attempt with reference to the automotive industry in India from the various studies. In the second phase of the research, these enablers were verified and interlinks were drawn based on the opinion of experienced supply chain professionals working with automotive manufactures having fifteen-plus years of experience. An exclusive list of manufacturers from the automotive domain based in three major automotive hubs in India—Delhi-National Capital Region, Chennai, and Pune—are collected from various sources, like the Automotive Manufactures Association list, the Delhi Auto Expo, and different automotive manufacturers in Pune. A total of thirty-five randomly selected senior supply chain professionals from the exclusive available list were contacted, and the questionnaire was shared online. We received twenty-seven usable responses with all necessary details at the end of the data collection process, which took around forty to fifty days. After sharing the questionnaire, telephone conversations
16
were held to get their detailed opinions, and the process was done in a single stage. The step-bystep procedure to develop the TISM framework, as detailed by Warfield (1974) and Sushil (2009, 2012, and 2016), and its flow chart are briefed in the following section. 3.1. Identify and define elements In this paper, based on extensive literature review followed by brainstorming with experts, we have finally identified ten enablers of SSCP (see Table 2). The objective of the prospective TISM framework is to explore the relationships and the selection of these elements, which were supported by established theories such as institutional theory and resource-based view theory. Table 3. Structural self-interaction matrix of enablers (SSIM) E10
E9
E8
E7
E6
E5
E4
E3
E2
E1
E1
V
O
V
V
O
V
V
X
X
X
E2
V
O
O
V
V
V
V
X
X
E3
V
V
O
V
O
V
V
X
E4
O
V
V
X
V
X
X
E5
O
V
V
X
V
X
E6
V
X
X
A
X
E7
O
V
V
X
E8
V
A
X
E9
V
X
E10
X
3.2. Define and interpret contextual relationships among elements The contextual relationships between each pair of elements are to be defined based on expert opinion by explaining the guidelines of VAXO matrix formulation to them. In our study, we randomly approached thirty-five subject matter experts in sustainable supply chain management with the help of professional networking sites, and we received a response rate of around 78%. The experts were carefully chosen by ensuring a minimum of fifteen years of professional experience in supply chains, and the matrix was explained on the phone when and where required. The VAXO matrix has some set rules that the respondent had to follow: V: if i leads to j but j doesn’t lead to i; A: if i doesn’t lead to j and j leads to i; X: if i and j lead to each other; O: if i and j are not related each other. For each pair, the first check was to predict the relationship
17
based on “Yes (Y)” or “No (N).” If the response was “Yes,” then further explanation was requested and thus helped us get “Interpretive Logic - Knowledge Base,” shown in Table 7. 4. Data analyses and results Based on the expert opinion, paired comparisons of responses between the enablers are done and are used to build the reachability matrix. The final reachability matrix is derived from the initial reachability matrix by considering the transitivity property. Transitivity links help ensure the consistency of the links measured and ensure that all possible interpretive links are incorporated in the model (Farris and Sage 1975a; Sushil 2012). If a leads to b and b leads to c, then based on the transitivity principle, the assumption that a leads to c will be true. Consideration of transitivity links also helps ensure that there are no possible gaps in the listed interconnections among the variables. Once the final reachability matrix is ready, the next step is level partitioning. Level partitioning is the process of ranking different elements into different levels. The reachability set and antecedent set are found out from the final reachability matrix (Warfield, 1974). If the reachability set’s intersection with the antecedent set is the reachability set itself, then those variables occupy the top levels of the hierarchy. The final output of level partitioning is shown in Table 6. To get the subsequent level variables, the top-level element or elements should be removed and iterations performed repeatedly. The digraph or directed graph is made based on the levels of elements identified from the reachability matrix. Connections are to be made based on the level-wise element partition with the directed links in the reachability matrix. Information in the digraph and interpretive direct interaction matrix are used to make the TISM model. The full element names with the interpretation of elements are to be placed in boxes replacing the nodes in the digraph. The TISM model developed is shown in Figure 2. Interpretive logic between the elements is also to be shown as on the transitive links between the elements. The driving power and dependence of elements are used to plot the MICMAC analysis shown in Figure 1 to clearly bifurcate the elements into four quadrants. The transitivity links based on expert opinion are shown in Table 4. The final binary interaction matrix replacing all values with ‘1’ and ‘0’ is shown in Table 5. Table 4. Final reachability matrix E10 E9 E8 E7 E6 E5 E4 E3 E2 E1 Driving power E1
1
1*
1
1
1*
1
1
1
1
1
10
18
E2
1
1*
1*
1
1
1
1
1
1
1
10
E3
1
1
1*
1
1*
1
1
1
1
1
10
E4
1*
1
1
1
1
1
1
0
0
0
7
E5
1*
1
1
1
1
1
1
0
0
0
7
E6
1
1
1
0
1
0
0
0
0
0
4
E7
1
*
1
1
1
1
1
1
0
0
0
7
E8
1
0
1
0
1
0
0
0
0
0
3
E9
1
1
1
0
1
0
0
0
0
0
4
E10
1
0
0
0
0
0
0
0
0
0
1
Dependence
10
8
9
6
9
6
6
3
3
3
* Represents transitivity property checked. Table 5. Final binary direct interaction matrix E10 E9 E8 E7 E6 E5 E4 E3 E2 E1 Driving power E1
1
1
1
1
1
1
1
1
1
-
10
E2
1
1
1
1
1
1
1
1
-
1
10
E3
1
1
1
1
1
1
1
-
1
1
10
E4
1
1
1
1
1
1
-
0
0
0
7
E5
1
1
1
1
1
-
1
0
0
0
7
E6
1
1
1
0
-
0
0
0
0
0
4
E7
1
1
1
-
1
1
1
0
0
0
7
E8
1
0
-
0
1
0
0
0
0
0
3
E9
1
-
1
0
1
0
0
0
0
0
4
E10
-
0
0
0
0
0
0
0
0
0
1
Dependence
10
8
9
6
9
6
6
3
3
3
Table 6. Level matrix Element E10 E6, E8, E9 E4, E5, E7 E1, E2, E3
Level Level 1 Level 2 Level 3 Level 4
19
Figure 1. MICMAC C diagram
20 Table 7. Transitive links from experts for enablers of sustainable supply chain performance E1
E3
E3
E4
Sharing of resources and knowledge
Better awaren ess through associa tion
Recommend ations from industry associations and groups
Improved benchma rk and standards
Competiti on among the industry group members
Need for better monito ring and error proofing Need to gain compet itive advant age High enthusi asm and efforts
E4
E5
Interpretive Matrix E5 E6
Governm ent and legislative rules and regulations
E1
E2
E2
Knowledge on easy-toimplement and adoptable systems Improved investment in innovative technologies
E6
E7
E8
E9 E10
E8
Better information flow and control Better process and system design Synchronized material flow
E9
E10
Need for emission control and profit maximization
Knowled ge transfer and better exposure
Better understa nding and knowled ge
Better transpare ncy
E7 Better collabora tion among partners to come up with the new rules and standards
Interorganizatio nal interactions
Talent retention and manage ment Better Informati on sharing process
Improved culture, skill and talent develop ment Careful talent and capability develop ment Team work and connecti vity
Better investments
Efficient monitoring and corrections
High resource utilization
Better collaboration and unity
Increased visibility and coordination
Lean supply chain Highly efficient planning and execution High responsiveness and agility
21
5. Discu ussions The objective of ouur current study s was too understannd the sustaiinable suppply chain cooncept, the missing links in thhis researchh domain, and the keey elementss impactingg the perforrmance of
22
sustainable supply chain. We have used the TISM approach, which is regarded as one of the alternate methods for developing a theoretical framework in SSCM (Luo et al. 2017; Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012) as a response to the call for more research attempts by using alternate methodology in operations management (Barratt et al., 2011; Taylor and Taylor, 2009). Even though there are growing numbers of empirical research attempts in SSCM, theoretically grounded research bodies in SSCM are relatively rare (Carter and Easton, 2011; Craig and Rogers, 2008; Mollenkopf et al., 2010), and this research responds to this existing gap by providing a strong and comprehensive theoretical framework (Hermosa and Adrien-Kirby, 2012) and by also selecting a few constructs and their interrelationships by deeply analyzing the theory behind the selection of those particular constructs (Winter and Knemeyer, 2013). Thus, this study is a proper response to the call for more theoretically grounded research attempts by making comprehensive and clear conceptual frameworks of the sustainability performance of the supply chain (Winter and Knemeyer, 2013; Touboulic and Walker, 2015) based on institutional theory and resource-based view theory. Another important point is that this research has succeeded in considering a combination of well-established theories like Madhok (2002), which are very scant. But RBV focuses mainly on resources and their economic rationale. Thus, it can be understood that the focus of RBV is on the economic pillar of sustainability and institutional theory is on the environmental and social pillars of sustainability (Sherer and Lee, 2002; Staw and Epstein, 2000). Hence, we argue that the integration of these two theories is not only unique in its viewpoint in explaining the sustainability dimensions, but the theories are also complementary to each other (Fang et al., 2012; Hansjürgens and Antes, 2008; Berrone et al., 2008). However, based on our best knowledge, empirical research attempts using a combination of these two theories in line with the research attempts of Clemens and Douglas (2006) and Oliver (1997) are rare, and this can be considered one of the few among them. Jayaraman and Luo (2007) argue that the aspects of the influence of SSCM on capability development or value creation are still missing. To bridge this gap, we are attempting to consider logistics capability development as one of the important elements, based on resource-based view theory. Literature review helped us list a few important elements, such as D1 - Coercive pressure (CP), D2 Normative pressure (NP), D3 - Mimetic pressure (MP), D4 - Top management belief (TMB), D5 - Top management participation (TMP), D6 - Supply chain connectivity (SCC), D7 - Supply
23
chain information sharing (SCIS), D8 - Supply chain talent (SCT), D9 - Logistics Capability (LC), and D10 - Sustainable supply chain performance (SSCP). The results show that the supply chain information-sharing capability will be a real competitive advantage for the firm to go for supply chain connectivity, which is again crucial for building logistics capability. The framework clearly shows that supply chain connectivity, logistics capability, and supply chain talent are equally crucial in enhancing the sustainability performance of a supply chain. All the elements chosen in this analysis are relevant, as there are no autonomous variables found in the MICMAC analysis shown in Figure 1. From the MICMAC diagram, it can also be interpreted that top management participation (TMP), supply chain connectivity, and supply chain talent are linkage variables. These variables are characterized by their strong dependency and driving power and are very sensitive elements. Any minor changes in the system or to any other variables will affect these elements. Coercive pressure, mimetic pressure, and normative pressure are found to have high driving power that will determine the sustainability performance of the supply chain. Elements such as supply chain connectivity, supply chain talent, and logistics capability are at the same level in the framework, indicating the direct positive impact of these elements on the sustainability performance of supply chain, which in turn will help organizations achieve a competitive edge over rivals. Again, these capabilities will be achieved with the support of three of the other capabilities, which come in the next lower hierarchy level, such as supply chain information sharing, top management belief, and participation. 5.1. Theoretical contributions The current study attempt may be considered an extension of the literature on theoretical framework development based on a combination of well-established organizational theories (Clemens and Douglas, 2006; Madhok, 2002), sustainability (Bell and Morse, 2013; Dyllick and Hockerts, 2002), and supply chain performance (Taticchi et al., 2015; Tseng et al., 2015). This can also be considered a response to the call for more empirical research works on sustainable supply chain performance by considering the conditions of emerging economies (Silvestre, 2015). The conceptual framework is developed using the TISM approach, which is again based on systems theory and the one which is widely getting accepted as an effective alternate research methodology for theoretical framework development in SSCM (Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012). Hence, the study clearly explores the possibility of
24
building the framework based on a combination of well-established multiple theories with reference to an emerging nation by effectively using an alternative methodology. The study is unique in its kind as it figures out the top ten most relevant elements of the sustainability performance of the supply chain and classifies them based on their driving power and dependence into four categories, viz., autonomous, driving, linkage, and dependence variables, using MICMAC analysis. It also helps in clearly depicting the hierarchy and interlinks among the indicators, which play a crucial role in imparting sustainability performance to the supply chain of organizations. Thus, as a whole, it can be concluded that this study provides immense scope both on theoretical and managerial front for supply chain enthusiasts and researchers. 5.2. Managerial implications Senior supply chain managers can depend on this study to clearly understand the focus areas like supply chain talent, logistics capability, top management commitment, and supply chain integration based on institutional pressures to achieve better social, environmental, and economic performance. Clearly depicted interlinks among the elements from the framework can be considered to plan for focused actions to attain the desired level in the sustainable supply chain performance. Efforts of supply chain managers can be prioritized just on the few mentioned enablers to achieve better sustainability performance by clearly understanding the driving power and dependence of each variable. The study will also help managers to identify very sensitive variables having high dependence and driving power that need continuous monitoring for the effective implementation of sustainable supply chain practices. Sustainable supply chain policy makers can also depend upon this framework to take the business in the right direction and to the next global level. 6. Conclusions, limitations and future research directions This article is a unique attempt to generate a comprehensive theoretical framework using a multimethods approach. The article may be considered an extension of the previous work (see Sushil, 2012, 2016) to explain how TISM can be used as an effective alternate theoretical framework development methodology (see Dubey et al., 2017; Dubey et al., 2015a, b; Jena et al., 2017; Sushil, 2012). Enablers of sustainable supply chain performance are identified based on institutional theory and resource-based view theory as a response to have more theoretically grounded research articles in the SSCM domain (see Hoejmose and Adrien-Kirby, 2012; Touboulic and Walker, 2015). This research also answers the call for more research attempts
25
from emerging nations by limiting the scope of research to the Indian context (Avittathur and Jayaram, 2016; Esfahbodi et al., 2016; Silvestre, 2015a, b). By focusing on the automotive industry in India, we are also contributing to the existing very limited research content in the automotive sustainable supply chain domain (Brandenburg and Rebs, 2015). At the end of the article, it can be seen that we have answered all three research questions formulated at the beginning of the research. Because we have come up with i) all the important enablers of sustainable supply chain performance to answer to the first research question ii) by coming up with a theoretical framework showing the interrelationships and the levels of variables to answer the second and third research questions. Finally, to conclude with, this article is contributing immensely toward the existing managerial and theoretical sustainable supply chain knowledge body, i) by providing a comprehensive and clear list of enablers of sustainable supply chain performance, ii) by deriving the clear interlinks and the hierarchy of these enablers through a theoretical framework, iii) by classifying the enablers based on their driving power and dependence, and iv) by shaping out the research process as a response to multiple research gaps existing in the sustainable supply chain domain. Further, research is to be conducted to rectify any possible bias in the analysis that may arise, as the study uses expert surveys and semi-structured questionnaires. One limitation of the study is that it may not be able to portray the relative weightings of elements considered in this study using only TISM methodology. Thus, this work can be extended by using structured questionnaire surveys to explore the real relative weightings of the elements considered. Moreover, more accurate results can be achieved if we go for a higher sample size instead of the current relatively small sample size. Factor analysis using a structural equation modeling technique with a high sample size can be an alternative way to overcome the above-mentioned limitations of this study. Fuzzy MICMAC analysis is one of the alternate ways to further improve sensitivity and to understand the intensity of the relationship between elements. Fuzzy MICMAC will assume intermediate values between 0 and 1, which may enhance the accuracy instead of going with only 0 and 1 as used in the current research. Khatwani et al. (2015) also showed a better extension of the TISM framework, which also offers a comprehensive framework better than this research attempt.
26
References Ahmad, N. K. W., de Brito, M. P., Rezaei, J., and Tavasszy, L. A. (2017). An integrative framework for sustainable supply chain management practices in the oil and gas industry. Journal of Environmental Planning and Management, 60(4), 577-601. Andrews, K. R. (1971). The Concept of Corporate Strategy, Irwin, Homewood, IL. Augier, M., and Teece, D. J. (2009). Dynamic capabilities and the role of managers in business strategy and economic performance. Organization Science, 20(2), 410-421. Bag, S. (2016). Flexible Procurement Systems is Key to Supply Chain Sustainability. Journal of Transport and Supply Chain Management, 10(1). doi:10.4102/jtscm.v10i1.213. Ball, A., and Craig, R. (2010). Using neo-institutionalism to advance social and environmental accounting. Critical Perspectives on Accounting, 21(4), 283-293. Ball, A., and Craig, R. (2010). Using neo-institutionalism to advance social and environmental accounting. Critical Perspectives on Accounting, 21(4), 283-293. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Barney, J. B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view. Journal of Management, 27(6), 643-650. Barratt, M., and Choi, T. (2007). Mandated RFID and institutional responses: Cases of decentralized business units. Production and Operations Management, 16(5), 569-585. Barratt, M., and Oke, A. (2007). Antecedents of supply chain visibility in retail supply chains: a resource-based theory perspective. Journal of Operations Management, 25(6), 1217-1233. Bask, A., Halme, M., Kallio, M., and Kuula, M. (2013). Consumer preferences for sustainability and their impact on supply chain management: The case of mobile phones. International Journal of Physical Distribution and Logistics Management, 43(5/6), 380-406. Bell, S., and Morse, S. (2013). Measuring sustainability: Learning from doing. Routledge. Berrone, P., Gelabert, L., Fosfuri, A., and Gómez-Mejía, L. R. (2008). Can Institutional Forces Create Competitive Advantage? An Empirical Examination of Environmental Innovation. Academy of Management Proceedings, 2008(1), 1-6. Academy of Management. Beske, P. (2012). Dynamic capabilities and sustainable supply chain management. International Journal of Physical Distribution and Logistics Management, 42(4), 372-387. Beth, S., Burt, D. N., Copacino, W., Gopal, C., Lee, H. L., Lynch, R. P., and Morris, S. (2003). Supply chain challenges. Building relationships. Harvard Business Review, 81(7), 64-73. Birchall, J. (February 25, 2010). Walmart to Set Emissions Goals for Suppliers. Financial Times.
27
Bowen, F. E., Cousins, P. D., Lamming, R. C., and Farukt, A. C. (2001). The role of supply management capabilities in green supply. Production and Operations Management, 10(2), 174-189. Bowersox, D. J., Closs, D. J., and Stank, T. P. (1999). 21st century logistics: making supply chain integration a reality. Bowersox, D. J., Stank, T. P., and Daugherty, P. J. (1999). Lean launch: managing product introduction risk through response‐based logistics. Journal of Product Innovation Management, 16(6), 557-568. Boyer, K. K., Frohlich, M., and Hult, G. T. M. (2005). Extending the Supply Chain. AMACOM, New York, NY. Bradley, P. (2013). Industry wants you. DC Velocity, April, 34-36. Brandon‐Jones, E., Squire, B., Autry, C. W., and Petersen, K. J. (2014). A Contingent Resource‐ Based Perspective of Supply Chain Resilience and Robustness. Journal of Supply Chain Management, 50(3), 55-73. Carter, C. R., and Jennings, M. (2000). Purchasing's Contribution to the Socially Responsible Management of the Supply Chain. Tempe, AZ: Center for Advanced Purchasing Studies. Carter, C. R., and Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution and Logistics Management, 38(5), 360-387. Carter, C. R., and Easton, P. L. (2011). Sustainable supply chain management: evolution and future directions. International Journal of Physical Distribution and Logistics Management, 41(1), 46-62. Carter, C. R., Kale, R., and Grimm, C. M. (2000). Environmental purchasing and firm performance: an empirical investigation. Transportation Research Part E: Logistics and Transportation Review 36(3), 219-228. Chadwick, C., Super, J. F., and Kwon, K. (2015). Resource orchestration in practice: CEO emphasis on SHRM, commitment-based HR systems, and firm performance. Strategic Management Journal, 36(3), 360-376. Clemens, B., and Douglas, T. J. (2006). Does coercion drive firms to adopt ‘voluntary’ green initiatives? Relationships among coercion, superior firm resources, and voluntary green initiatives. Journal of Business Research, 59(4), 483-491. Closs, D. J., Goldsby, T. J., and Clinton, S. R. (1997). Information technology influences on world class logistics capability. International Journal of Physical Distribution and Logistics Management, 27(1), 4-17.
28
Cottrill, K. (2010). Are you prepared for the supply chain talent crisis?. MIT Center for Transportation and Logistics White Paper, 1-11. Craighead, C. W., Ketchen Jr, D. J., and Cheng, L. (2016). “Goldilocks” Theorizing in Supply Chain Research: Balancing Scientific and Practical Utility via Middle-Range Theory. Transportation Journal, 55(3), 241-257. Crook, T. R., and Esper, T. L. (2014). Do resources aid in supply chain functioning and management? Yes, but more (and more precise) research is needed. Journal of Supply Chain Management, 50(3), 94-97. Dam, L., and Petkova, B. N. (2014). The impact of environmental supply chain sustainability programs on shareholder wealth. International Journal of Operations and Production Management, 34(5), 586-609. Daugherty, P. J., Stank, T. P., and Ellinger, A. E. (1998). Leveraging logistics/distribution capabilities: the effect of logistics service on market share. Journal of Business Logistics, 19(2), 35. Deephouse, D. (1996). Does isomorphism legitimate? Academy of Management Journal, 39(4), 1024-1039. Dewett, T., and Jones, G. R. (2001). The role of information technology in the organization: a review, model, and assessment. Journal of Management, 27(3), 313-346. Dey, A., LaGuardia, P., and Srinivasan, M. (2011). Building sustainability in logistics operations: a research agenda. Management Research Review, 34(11), 1237-1259. DiMaggio, P. J., and Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147160. Dittmann, J. P. (2012), Supply Chain Transformation: Building and Executing an Integrated Supply Chain Strategy, McGraw-Hill, New York, NY. Dowlatshahi, S. (2000). Developing a theory of reverse logistics. Interfaces, 30(3), 143-155. Duan, L., and Xiong, Y. (2015). Big data analytics and business analytics. Journal of Management Analytics, 2(1), 1-21. Dubey, R., and Gunasekaran, A. (2015). Shortage of sustainable supply chain talent: An industrial training framework. Industrial and Commercial Training, 47(2), 86-94. Dubey, R., Gunasekaran, A., and Ali, S. S. (2015). Exploring the relationship between leadership, operational practices, institutional pressures and environmental performance: A framework for green supply chain. International Journal of Production Economics, 160, 120132.
29
Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Wamba, S. F., and Song, M. (2016). Towards a theory of sustainable consumption and production: Constructs and measurement. Resources, Conservation and Recycling, 106, 78-89. Dubey, R., Gunasekaran, A., Papadopoulos, T., Childe, S. J., Shibin, K. T., and Wamba, S. F. (2017). Sustainable supply chain management: Framework and further research directions. Journal of Cleaner Production. doi:10.1016/j.jclepro.2016.03.117. Dubey, R., Gunasekaran, A., Wamba, S. F., and Bag, S. (2015b). Building theory of green supply chain management using total interpretive structural modeling (TISM). IFACPapersOnLine, 48(3), 1688-1694. Dyllick, T., and Hockerts, K. (2002). Beyond the business case sustainability. Business Strategy and the Environment, 11(2), 130-141.
for corporate
Ellinger, A., and Ellinger, D. (2014). Leveraging human resource development expertise to improve supply chain managers' skills and competencies. European Journal of Training and Development, 38(1/2), 118-135. Esper, T. L., Clifford Defee, C., and Mentzer, J. T. (2010). A framework of supply chain orientation. The International Journal of Logistics Management, 21(2), 161-179. Esper, T. L., Fugate, B. S., and Davis‐Sramek, B. (2007). Logistics learning capability: sustaining the competitive advantage gained through logistics leverage. Journal of Business Logistics, 28(2), 57-82. Fang, H., Memili, E., Chrisman, J. J., and Welsh, D. H. (2012). Family Firms’ Professionalization: Institutional Theory and Resource-Based View Perspectives. Small Business Institute Journal, 8(2), 12-34. Farris, D. R., and Sage, A. P. (1975a). On the use of interpretive structural modeling for worth assessment. Computers and Electrical Engineering, 2(2-3), 149-174. Farris, D. R., and Sage, A. P. (1975). On the use of interpretive structural modeling for worth assessment. Computers and Electrical Engineering, 2(2), 149-174. Fawcett, S. E., Stanley, L. L., and Smith, S. R. (1997). Developing a logistics capability to improve the performance of international operations. Journal of Business Logistics, 18(2), 101. Fayol, H. (1949). General and industrial administration. NY: Pitman. Forman, M., and Jrgensen, M.S. (2004). Organising environmental supply chain management. Greener Management International, 2004(45), 43-62. Formentini, M., and Taticchi, P. (2016). Corporate sustainability approaches and governance mechanisms in sustainable supply chain management. Journal of Cleaner Production, 112, 1920-1933.
30
Gammelgaard, B., and Larson, P. D. (2001). Logistics skills and competencies for supply chain management. Journal of Business Logistics, 22(2), 27-50. Garbie, I. H. (2014). An analytical technique to model and assess sustainable development index in manufacturing enterprises. International Journal of Production Research, (ahead-of-print), 1-40. Giunipero, L., Handfield, R. B., and Eltantawy, R. (2006). Supply management's evolution: key skill sets for the supply manager of the future. International Journal of Operations and Production Management, 26(7), 822-844. Gligor, D. M., and Holcomb, M. (2014). The road to supply chain agility: an RBV perspective on the role of logistics capabilities. The International Journal of Logistics Management, 25(1), 160-179. Glover, J. L., Champion, D., Daniels, K. J., and Dainty, A. J. D. (2014). An Institutional Theory perspective on sustainable practices across the dairy supply chain. International Journal of Production Economics, 152, 102-111. Gold, S., Seuring, S., and Beske, P. (2010). Sustainable supply chain management and inter‐ organizational resources: a literature review. Corporate Social Responsibility and Environmental Management, 17(4), 230-245. Gonzalez-Torre, P. L., Adenso-Diaz, B., and Artiba, H. (2004). Environmental and reverse logistics policies in European bottling and packaging firms. International Journal of Production Economics, 88(1), 95-104. Gopal, A., and Gao, G. (2009). Certification in the Indian offshore IT services industry. Manufacturing and Service Operations Management, 11(3), 471-492. Grant, R. M. (1991). The resource-based theory of competitive advantage: implications for strategy formulation. California Management Review, 33(3), 114-135. Grob, S., and Benn, S. (2014). Conceptualising the adoption of sustainable procurement: an institutional theory perspective. Australasian Journal of Environmental Management, 21(1), 11-21. Guang Shi, V., Lenny Koh, S. C., Baldwin, J., and Cucchiella, F. (2012). Natural resource based green supply chain management. Supply Chain Management: An International Journal, 17(1), 54-67. Halldorsson, A., Kotzab, H., and Skøtt-Larsen, T. (2003). Interorganizational theories behind supply chain management-discussion and applications. Hammer, M. (2004). Deep Change: How Operational Innovation Can Transform Your Company. Harvard Business Review, 82(9), 133.
31
Hansjürgens, B., and Antes, R. (Eds.) (2008). Economics and management of climate change: risks, mitigation and adaptation. Springer Science and Business Media. Hayes, R.H., and Pisano, G.P. (1994). Beyond world-class: the new manufacturing strategy. Harvard Business Review, 72(1), 77-86. Heikkurinen, P., and Forsman‐Hugg, S. (2011). Strategic corporate responsibility in the food chain. Corporate Social Responsibility and Environmental Management, 18(5), 306-316. Heras-Saizarbitoria, I., Landín, G. and Molina-Azorín, J. (2011). Do drivers matter for the benefits of ISO 14001?. International Journal of Operations and Production Management, 31(2) 192-216. Hitt, M. A., Xu, K., and Carnes, C. M. (2015). Resource based theory in operations management research. Journal of Operations Management, 41, 77-94. Hoejmose, S. U., and Adrien-Kirby, A. J. (2012). Socially and environmentally responsible procurement: A literature review and future research agenda of a managerial issue in the 21st century. Journal of Purchasing and Supply Management, 18(4), 232-242. Hsu, C. C., Tan, K. C., and Mohamad Zailani, S. H. (2016). Strategic orientations, sustainable supply chain initiatives, and reverse logistics: Empirical evidence from an emerging market. International Journal of Operations and Production Management, 36(1), 86-110. Hsu, C. C., Tan, K. C., Suhaiza H. M. Z., and Jayaraman, V. (2013). Supply chain drivers that foster the development of green initiatives in an emerging economy. International Journal of Operations and Production Management, 33(6), 656-688. Hunt, S. D., and Davis, D. F. (2012). Grounding supply chain management in resource‐ advantage theory: in defense of a resource‐based view of the firm. Journal of Supply Chain Management, 48(2), 14-20. Jayaraman, V., Klassen, R., and Linton, J.D. (2007). Supply chain management in a sustainable environment. Journal of Operations Management, 25(6), 1071-1074. Jiang, B. (2009). Implementing supplier codes of conduct in global supply chains: Process explanations from theoretic and empirical perspectives. Journal of Business Ethics, 85(1), 77-92. John, C. H. S., Cannon, A. R., and Pouder, R. W. (2001). Change drivers in the new millennium: implications for manufacturing strategy research. Journal of Operations Management, 19(2), 143-160. Kauppi, K. (2013). Extending the use of institutional theory in operations and supply chain management research: Review and research suggestions. International Journal of Operations and Production Management, 33(10), 1318-1345.
32
Ketchen, D. J., and Hult, G. T. M. (2007). Bridging organization theory and supply chain management: The case of best value supply chains. Journal of Operations Management, 25(2), 573-580. Ketchen, D. J., and Guinipero, L. (2004). The intersection of strategic management and supply chain management. Industrial Marketing Management, 33(1), 51-56. Ketokivi, M. A., and Schroeder, R. G. (2004). Strategic, structural contingency and institutional explanations in the adoption of innovative manufacturing practices. Journal of Operations Management, 22(1), 63-89. Khatwani, G., Singh, S. P., Trivedi, A., and Chauhan, A. (2015). Fuzzy-TISM: A fuzzy extension of TISM for group decision making. Global Journal of Flexible Systems Management, 16(1), 97-112. Kilbourne, W. E., Beckmann, S. C., and Thelen, E. (2002). The role of the dominant social paradigm in environmental attitudes: a multinational examination. Journal of Business Research, 55(3), 193-204. Kirchoff, J. F., Koch, C., and Satinover Nichols, B. (2011). Stakeholder perceptions of green marketing: the effect of demand and supply integration. International Journal of Physical Distribution & Logistics Management, 41(7), 684-696. Klassen, R. D., and Vereecke, A. (2012). Social issues in supply chains: Capabilities link responsibility, risk (opportunity), and performance. International Journal of Production Economics, 140(1), 103-115. Lambert, D. M., Cooper, M. C., and Pagh, J. D. (1998). Supply chain management: implementation issues and research opportunities. The International Journal of Logistics Management, 9(2), 1-20. Law, K. M., and Gunasekaran, A. (2012). Sustainability development in high-tech manufacturing firms in Hong Kong: Motivators and readiness. International Journal of Production Economics, 137(1), 116-125. Lee, H. L. (2010). Don't tweak your supply chain–rethink it end to end. Harvard Business Review, 88(10), 62-69. Liang, H., Saraf, N., Hu, Q., and Xue, Y. (2007). Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Quart. 31(1), 59-87. Lin, Y. H., and Tseng, M. L. (2016). Assessing the competitive priorities within sustainable supply chain management under uncertainty. Journal of Cleaner Production, 112, 21332144.
33
Liu, H., Ke, W., Wei, K.K., Gu, J., and Chen, H. (2010). The role of institutional pressures and organizational culture in the firm's intention to adopt internet-enabled supply chain management systems. Journal of Operations Management, 28(5), 372-384. Luo, Z., Dubey, R., Papadopoulos, T., Hazen, B., and Roubaud, D. (2017). Explaining Environmental Sustainability in Supply Chains Using Graph Theory. Computational Economics, 1-19. doi:10.1007/s10614-017-9688-2. Lynch, D. F., Keller, S. B., and Ozment, J. (2000). The effects of logistics capabilities and strategy on firm performance. Journal of Business Logistics, 21(2), 47. Madaan, J.K., and Choudhary, D. (2015). A flexible decision model for risk analysis in product recovery systems. Global Journal of Flexible Systems Management, 16(4), 313-329. Madhok, A. (2002). Reassessing the fundamentals and beyond: Ronald Coase, the transaction cost and resource‐based theories of the firm and the institutional structure of production. Strategic Management Journal, 23(6), 535-550. Mangla, S. K., Kumar, P., and Barua, M. K. (2014). Flexible decision approach for analysing performance of sustainable supply chains under risks/uncertainty. Global Journal of Flexible Systems Management, 15(2), 113-130. Markley, M. J., and Davis, L. (2007). Exploring future competitive advantage through sustainable supply chains. International Journal of Physical Distribution and Logistics Management, 37(9), 763-774. Matos, S., and Hall, J. (2007). Integrating sustainable development in the supply chain: the case of life cycle assessment in oil and gas and agricultural biotechnology. Journal of Operations Management, 25(6), 1083-1102. Meixell, M. J., and Luoma, P. (2015). Stakeholder pressure in sustainable supply chain management. International Journal of Physical Distribution & Logistics Management, 45(1/2), 69. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., and Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1-25. Min, H., and Galle, W.P. (1997). Green purchasing strategies: trends and implications. International Journal of Purchasing and Materials Management, 33(2), 10-17. Min, H., and Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations and Production Management, 21(9), 1222-1238. Miri-Lavassani, K., Movahedi, B., and Kumar, V. (2009). Developments in theories of supply chain management: The case of B2B electronic marketplace adoption. International Journal of Knowledge, Culture and Change Management, 9(6), 85-98.
34
Mollenkopf, D., Stolze, H., Tate, W.L., and Ueltschy, M. (2010). Green, lean and global supply chains. International Journal of Physical Distribution and Logistics Management, 40(1/2), 14-41. Morali, O., and Searcy, C. (2010). Building sustainability into supply chain management: A research agenda. In Proceedings of the 1st annual international symposium on green supply chains, Akron-Canton, OH, USA. Morash, E. A., Droge, C. L., and Vickery, S. K. (1996). Strategic logistics capabilities for competitive advantage and firm success. Journal of Business Logistics, 17(1), 1. Nair, A. and Prajogo, D. (2009). Internalisation of ISO 9000 standards: the antecedent role of functionalist and institutionalist drivers and performance implications. International Journal of Production Research, 47(16), 4545-4568. Olavarrieta, S., and Ellinger, A. E. (1997). Resource-based theory and strategic logistics research. International Journal of Physical Distribution and Logistics Management, 27(9/10), 559-587. Oliver, C. (1997). Sustainable competitive advantage: Combining institutional and resourcebased views. Strategic Management Journal, 18(9), 697-713. Orsato, R.J. (2006). When does it pay to be green?. California Management Review, 48(2), 128. Ortas, E., Moneva, J. M., and Alvarez, I. (2014). Sustainable Supply Chain and Company Performance: A Global Examination. Supply Chain Management: An International Journal, 19(3), 9-9. Pagell, M., and Wu, Z. (2009). Building a more complete theory of sustainable supply chain management using case studies of exemplars. Journal of Supply Chain Management, 45(2), 37-56. Pagell, M., Wu, Z., and Wasserman, M. E. (2010). Thinking differently about purchasing portfolios: an assessment of sustainable sourcing. Journal of Supply Chain Management, 46(1), 57-73. Park-Poaps, H., and Rees, K. (2010). Stakeholder forces of socially responsible supply chain management orientation. Journal of Business Ethics, 92(2), 305-322. Peteraf, M. A. (1993). The cornerstones of competitive advantage: A resource‐based view. Strategic Management Journal, 14(3), 179-191. Prajogo, D., and Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration. International Journal of Production Economics, 135(1), 514-522.
35
Premkumar, G., and King, W. R. (1994). Organizational characteristics and information systems planning: an empirical study. Information Systems Research, 5(2), 75-109. Preuss, L. (2007). Buying into our future: sustainability initiatives in local government procurement. Business Strategy and the Environment, 16(5), 354-365. Reefke, H., and Sundaram, D. (2017). Key themes and research opportunities in sustainable supply chain management–identification and evaluation. Omega, 66, 195-211. Reuter, C., Foerstl, K. A. I., Hartmann, E. V. I., and Blome, C. (2010). Sustainable global supplier management: the role of dynamic capabilities in achieving competitive advantage. Journal of Supply Chain Management, 46(2), 45-63. Roehrich, J. K., Grosvold, J., and Hoejmose, S. U. (2014). Reputational risks and sustainable supply chain management: Decision making under bounded rationality. International Journal of Operations and Production Management, 34(5), 695-719. Rungtusanatham, M., Salvador, F., Forza, C., and Choi, T. Y. (2003). Supply-chain linkages and operational performance: a resource-based-view perspective. International Journal of Operations and Production Management, 23(9), 1084-1099. Sandberg, E., and Abrahamsson, M. (2011). Logistics capabilities for sustainable competitive advantage. International Journal of Logistics Research and Applications, 14(1), 61-75. Sarkis, J., Gonzalez-Torre, P., and Adenso-Diaz, B. (2010). Stakeholder pressure and the adoption of environmental practices: The mediating effect of training. Journal of Operations Management, 28(2), 163-176. Sarkis, J., Zhu, Q., and Lai, K. H. (2011). An organizational theoretic review of green supply chain management literature. International Journal of Production Economics, 130(1), 1-15. Sarma, P. R. S., and Pramod, V. R. (2015). Structural flexibility in supply chains: TISM and FISM approach. In Sushil, and G. Chroust (Eds.), Systemic flexibility and business agility, Flexible Systems Management (305-321). New Delhi: Springer. Schaltegger, S., and Burritt, R. (2014). Measuring and managing sustainability performance of supply chains: Review and sustainability supply chain management framework. Supply Chain Management: An International Journal, 19(3), 232-241. Seuring, S.; Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16, 1699-1710. Sezhiyan, D. M., Page, T., and Iskanius, P. (2011). The impact of supply effort management, logistics capability, and supply chain management strategies on firm performance. International Journal of Electronic Transport, 1(1), 26-44. Sherer, P. D., and Lee, K. (2002). Institutional change in large law firms: A resource dependency and institutional perspective. Academy of Management Journal, 45(1), 102-119.
36
Shibin, K. T., Gunasekaran, A., Papadopoulos, T., Dubey, R., Singh, M., and Wamba, S. F. (2016). Enablers and barriers of flexible green supply chain management: A total interpretive structural modeling approach. Global Journal of Flexible Systems Management, 17(2), 171188. Silvestre, B. S. (2015). A hard nut to crack! Implementing supply chain sustainability in an emerging economy. Journal of Cleaner Production, 96, 171-181. Silvestre, B. S. (2015). Sustainable supply chain management in emerging economies: Environmental turbulence, institutional voids and sustainability trajectories. International Journal of Production Economics, 167, 156-169. Singh, R.K., and Sharma, P.B. (2015). TISM-based model to evaluate the flexibility index of a supply chain. In Sushil, and G. Chroust (Eds.), Systemic flexibility and business agility, Flexible Systems Management (323–342). New Delhi: Springer. Sirmon, D.G., Gove, S., and Hitt, M.A. (2008). Resource management in dyadic competitive rivalry: The effects of resource bundling and deployment. Academy of Management Journal, 51(5), 919-935. Slone, R. E., Dittmann, J. P. and Mentzer, J. T. (2010), New Supply Chain Agenda: The 5 Steps That Drive Real Value, Harvard Business Press, Boston, MA. Snider, K. F., Halpern, B. H., Rendon, R. G., and Kidalov, M. V. (2013). Corporate social responsibility and public procurement: How supplying government affects managerial orientations. Journal of Purchasing and Supply Management, 19(2), 63-72. Staw, B. M., and Epstein, L. D. (2000). What bandwagons bring: Effects of popular management techniques on corporate performance, reputation, and CEO pay. Administrative Science Quarterly, 45(3), 523-556. Stonebraker, P. W., and Liao, J. (2006). Supply chain integration: exploring product and environmental contingencies. Supply Chain Management: An International Journal, 11(1), 3443. Sushil (2005a). Interpretive matrix: a tool to aid interpretation of management and social research. Global Journal of Flexible Systems Management, 6(2), 27-30. Sushil (2005b). A flexible strategy framework for managing continuity and change. International Journal of Global Business and Competitiveness, 1(1), 22-32. Sushil (2009). Interpreting the interpretive structural model. Working paper, IIT Delhi. Sushil (2012). Interpreting the interpretive structural model. Global Journal of Flexible Systems Management, 13(2), 87-106.
37
Sushil (2016). How to check correctness of total interpretive structural models?. Annals of Operations Research, 1-15 (DOI: 10.1007/s10479-016-2312-3). Taticchi, P., Garengo, P., Nudurupati, S. S., Tonelli, F., and Pasqualino, R. (2015). A review of decision-support tools and performance measurement and sustainable supply chain management. International Journal of Production Research, 53(21), 6473-6494. Taylor, F. W. (1947). Scientific management. New York and London: Harper and Row. Thompson, A. A. and Strickland, A. J. (1990). Strategic Management: Concepts and Cases, Irwin, Homewood, IL. Touboulic, A., and Walker, H. (2015). Theories in sustainable supply chain management: a structured literature review. International Journal of Physical Distribution and Logistics Management, 45(1/2), 16-42. Trowbridge, P. (2001). A case study of green supply-chain management at advanced micro devices. Greener Management International, 35, 121-135. Tseng, M., Lim, M., and Wong, W.P. (2015). Sustainable supply chain management: A closedloop network hierarchical approach. Industrial Management and Data Systems, 115(3), 436461. Varsei, M., Soosay, C., Fahimnia, B., and Sarkis, J. (2014). Framing sustainability performance of supply chains with multidimensional indicators. Supply Chain Management: An International Journal, 19(3), 242-257. Walker, H., and Brammer, S. (2009). Sustainable procurement in the United Kingdom public sector. Supply Chain Management: An International Journal, 14(2), 128-137. Walley, N., and Whitehead, B. (1994). It's not easy being green. The Earth scan reader in business and the environment, 36-44. Walsh, J. P. (1988). Selectivity and selective perception: an investigation of managers’ belief structures and information processing. Academy of Management Journal, 31(4), 873-896. Wang, Z., and Sarkis, J. (2013). Investigating the relationship of sustainable supply chain management with corporate financial performance. International Journal of Productivity and Performance Management, 62(8), 871-888. Warfield, J. N. (1974). Toward interpretation of complex structural models. IEEE Transactions on Systems, Man and Cybernetics, 5, 405-417. Weber, M. (2009). The theory of social and economic organization. Simon and Schuster. Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171-180.
38
Wernerfelt, B. (1995). The resource‐based view of the firm: Ten years after. Strategic Management Journal, 16(3), 171-174. Wickramasinghe, D., and Alawattage, C. (2007). Management accounting change: approaches and perspectives. Routledge. Winter, M., and Knemeyer, A. M. (2013). Exploring the integration of sustainability and supply chain management: Current state and opportunities for future inquiry. International Journal of Physical Distribution and Logistics Management, 43(1), 18-38. Wu, F., Yeniyurt, S., Kim, D., and Cavusgil, S. T. (2006). The impact of information technology on supply chain capabilities and firm performance: A resource-based view. Industrial Marketing Management, 35(4), 493-504. Yadav, D. K., and Barve, A. (2016). Modeling post-disaster challenges of humanitarian supply chains: A TISM approach. Global Journal of Flexible Systems Management, 17(3), 321-340. Yigitbasioglu, O. M. (2010). Information sharing with key suppliers: a transaction cost theory perspective. International Journal of Physical Distribution & Logistics Management, 40(7), 550578. Zailani, S., Jeyaraman, K., Vengadasan, G., and Premkumar, R. (2012). Sustainable supply chain management (SSCM) in Malaysia: A survey. International Journal of Production Economics, 140(1), 330-340. Zhang, H.Y., and Lv, S. (2015). Intellectual Capital and Technological Innovation: The Mediating Role of Supply Chain Learning. International Journal of Innovation Science, 7(3), 199-210. Zhao, M., Dröge, C., and Stank, T. P. (2001). The effects of logistics capabilities on firm performance: customer‐focused versus information‐focused capabilities. Journal of Business Logistics, 22(2), 91-107. Zhu, Q., and Geng, Y. (2013). Drivers and barriers of extended supply chain practices for energy saving and emission reduction among Chinese manufacturers. Journal of Cleaner Production, 40, 6-12. Zhu, Q., Sarkis, J., and Lai, K. H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106-117. Zhu, Q., Sarkis, J., and Lai, K. H. (2013). Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 19(2), 106-117.
39
Zsidisin, G.A., Melnyk, S.A., and Ragatz, G.L. (2005). An institutional theory perspective of business continuity planning for purchasing and supply management. International Journal of Production Research, 43(16), 3401-3420.