Does Integrative Approach to Green Supply Chain Management Matter? An Empirical Study

Does Integrative Approach to Green Supply Chain Management Matter? An Empirical Study Sakun Boon-itt (sakun_boon@yahoo.com) Department of Operations Management, Thammasat University, Bangkok, Thailand Christina W.Y. Wong Institute of Textile and Clothing, The Hong Kong Polytechnic University, Hong Kong, China Chee Yew Wong Business School, University of Leeds, Leeds, UK Abstract The OM literature has recently recognized the needs to integrate environmental practices into the supply chains. There are recent attempts to develop constructs and measurement scales for integrative approaches to green supply chain management based on case studies and systematic literature review. Yet, there is a lack of large-scale empirical studies to investigate if such integrative approaches to green supply chain management really matter, and if so, how. The objective of this paper is to empirically verify the conceptualisations and measurements of the constructs called green supply chain integration (GSCI) and examine if each of the GSCI dimensions has positive impacts on environmental, cost reduction and business performance. Keywords: Supply chain integration, Green supply chain management, Sustainability Introduction The OM literature argues that there is a need to integrate environmental practices into the supply chains (Molina-Azorin et al., 2009; Gimenez & Tachizawa, 2012; Shi et al., 2012; Wong et al., 2015). Some constructs and measurement scales for integrative approaches to green supply chain management have recently been developed by using case studies (Wolf, 2011), survey (Yu et al., 2014) and systematic literature review (Wong et al., 2015). Wolf (2011) establishes a concept called sustainable supply chain integration as a way to integrate sustainability into supply chain management; it consists of internal integration, external downstream and upstream supply chain integration, as well as external stakeholder integration. Similarly, Wong et al. (2015) establish three green supply chain integration (GSCI) practices including internal, supplier, and customer green supply chain integration. Based on stakeholder theory, resource orchestration theory, and the notions of collaborative and integrative advantage, Wong et al. (2015) hypothesize that the three GSCI practices help acquiring, bundling, and leveraging resources and capabilities internally and externally, and subsequently increase the success of environmental management. 1

Yet, there is a lack of empirical studies to investigate if such integrative approaches to green supply chain management really matter, and if so, how. It is still unclear if such integrative approaches to green supply chain management can lead to better cost and financial performance in addition to environmental performance. The objective of this paper is to empirically verify the conceptualisations and measurements of the constructs called (GSCI) green supply chain integration and examine if each of the GSCI dimensions has positive impacts on environmental, cost reduction and finance performance. This paper extends the ground work built by Wolf (2011) and Wong et al. (2015) by formally verifying the conceptualizations of the three GSCI practices (Supplier, customer and internal integration) using Q-sort method and confirmatory factor analysis (CFA). The paper further refines Wong et al. (2015) hypothesis by adding cost and financial performance into the theory and tests these new hypotheses based on a survey of Thai manufacturing companies. Theoretical framework and hypotheses The concept of supply chain integration has been generally grounded in the theory of relational (collaborative) advantage (Dyer & Singh, 1998) or information processing (integrative) advantage (Schoenherr & Swink, 2012; Wong et al., 2011). Accordingly, collaborative and integrative advantages are generated by better information sharing and relationships across different functions, suppliers, customers, and stakeholders (Wong et al., 2015). Most of the sustainable or green supply chain management studies are grounded in these collaboration and integration arguments (e.g., Zhu et al., 2008a; Wolf, 201l; Vachon & Klassen, 2008). In reality, green supply chain efforts can start to generate benefits only if members of the supply chain can start mobilizing and integrating various resources in a coordinated manner. Such orchestrations of supply chain resources are triggered and supported by efforts to share information and initiate collaborate. Thus, this paper applies the resource orchestration theory as the theoretical foundation for green supply chain integration (GSCI). Resource orchestration theory explicitly concerns actions that effectively structure, bundle, and leverage firm resources, leading to an appropriate resource accumulation (Sirmon et al., 2011). Firm resources include internal resources owned by the firm as well as external resources owned by suppliers, customers and stakeholders accessible by the firms. Resource orchestration is very important for managing environment al issues in supply chains because there is a need to address disparate views about environmental responsibilities and approaches to achieve better environmental performance across the supply chains. Then only collaboration and exchange of information leads to the bundling and leverage of resources and competences across the supply chain to collectively reduce environmental impacts while meeting commercial imperatives, i.e., achieving cost advantage and financial performance throughout the supply chain. By combining the essence of collaborative and integrative advantage with resource orchestration theory, green supply chain integration (GSCI) is defined as the strategic collaboration and integration across functions, suppliers, customers and other external stakeholders in a supply chain to manage the environmental impact of supply chain activities through orchestration of resources and competencies across the entire supply chain (Wong et al., 2015). Based on the definition of GSCI, this paper establishes a theoretical framework, which includes green internal integration (GII), green supplier integration (GSI), and green customer integration (GCI) and three major performance outcomes - environmental, cost and financial performance as illustrated in Figure 1. We divide GSCI into GII, GSI and 2

GCI because these three are distinct practices given the differences among integration across functions, suppliers and customers. Since these three GSCI practices are integrated into the existing management systems that take into account the alignment between economic, environmental and societal impacts as well as orchestration of resources across the supply chain, they are expected to generate cost, financial and environmental benefits. Green Internal Integration (GII) Environmental Performance Green Supplier Integration (GSI) Green Customer Integration (GCI) Cost Performance Financial Performance Figure 1 Theoretical Framework Green internal integration (GII) is defined as the strategic collaboration and integration across internal resources, such as top management, management systems, quality control, and functions via an integrated management system for managing the environmental impacts of the supply chain (Wong et al., 2015: 52). GII includes the integration of environmental goals and responsibilities into business strategies and top management reward, and the attempts to balance commercial, societal, and environmental goals for achieving sustainable growth (Montabon et al., 2007; Berrone & Gomez-Mejia, 2009; Carmody & Zeppel 2009; Pagell & Wu, 2009; Wagner, 2009; Jabbour, 2010; Carter & Easton, 2011; Gond et al., 2012; Hofer et al., 2012). GII is achieve through a single integrated management system that incorporates environmental goals, performance, and responsibilities into code of conducts, functional commercial decisions, and human resource decisions among different functions (Klassen, 1997; Margerum & Born, 2000; Schiefer, 2002; Montabon et al., 2007; Magrini & Lins, 2007; Nawrocka, 2008; Hu & Hsu, 2010; Tari & Molina-Azorin, 2010; Shi et al., 2012; Gond et al., 2012) as well as cross-functional communication, coordination and collaboration (Zhu & Sarkis, 2004; Russo & Harrison, 2005; Margerum & Born, 2008; Montabon et al., 2011; Zhu et al., 2012). As argued by the resource orchestration theory, we posit the following hypothesis: H1: Green internal integration (GII) is positively associated with (a) environmental performance, (b) cost performance, and (c) financial performance Green supplier integration (GSI) is defined as the strategic collaboration and integration with suppliers in a supply chain to manage the environmental impact of supply chain activities through orchestration of resources and competencies across the supply bases (Wong et al., 2015: 55). GSCI includes the exchange of information about goals, responsibilities, strategies, benefits, best-practices, performance standards related to environmental issues with suppliers using an integrated environmental information system (Rao, 2002; Hervani et al., 2005; Seuring & Muller, 2008; Hu & Hsu., 2010; Arimura et al., 2011; Zhu et al., 2012; Lai et al., 2012; Green et al., 2012; Kim & Rhee, 2012). GSCI also relies on providing assistance, resources, support and guidance to 3

suppliers (Rao, 2002; Hu & Hsu, 2010; Kim & Rhee, 2012; Wong et al., 2012; Gopalakrishnan et al., 2012) as well as coordination, standardization, and integration of closed-loop forward and reverse supply chain processes and related planning, performance measurement, and environmental management processes with suppliers (Bowen et al., 2001; Kleindorfer et al., 2005; Montabon et al., 2007; Zuo et al., 2009; Yen & Yen, 2012). As argued by the resource orchestration theory, we posit the following hypothesis: H2: Green supplier integration (GSI) is positively associated with (a) environmental performance, (b) cost performance, and (c) financial performance Green customer integration (GCI) is defined as the strategic collaboration and integration with customers in a supply chain to manage the operational and environmental impact of supply chain activities through orchestration of resources across customer bases (Wong et al., 2015: 55). GCI includes the exchange of information about environmental goals, practices and strategies as well as cleaner production technology, information about products and their life-cycle impacts with customers (Vachon & Klassen, 2006; Darnall et al., 2008; Gonzalez-Benito, 2008; Zhu et al., 2008b; Hazen et al., 2011) so that the supplier and customer begin to develop mutual environmental responsibilities and achieve environmental goals collective (Deans, 1999; Vachon & Klassen, 2006 & 2008; Zhu et al., 2008a; Lee et al., 2012; Beske 2012). These practices allow orchestration of the supplier and customer s resources by coordinating close-loop return processes, logistics planning and green supply chain activities, measure environmental impacts, solve environmental related problems and make decisions about reducing environmental impacts together (Wong et al., 2015). As argued by the resource orchestration theory, we posit the following hypothesis: H3: GCI is positively associated with (a) environmental performance, (b) cost performance, and (c) financial performance Research Methodology One of the aims of this paper is to test the conceptualization of green supply chain integration (GSCI) by Wong et al. (2015). We have adopted the definitions of GSCI and three practices (GII, GSI and GCI) from Wong et al., (2015) and further established the components of each practice (see above). We consider GII, GSI and GCI as second-order constructs. GII consists of three first-order constructs (i.e., integration of environmental goal into business strategy; integration of environmental strategy into management systems; cross-functional collaboration). GSI composes of four first-order constructs (i.e., exchange environmental information with suppliers; collaborate with suppliers; assisting suppliers; integrate process with suppliers). GCI contains three first-order constructs (i.e., exchange of environmental information with customers; collaborate with customers; integrate process with customers). After being examined by academic and practitioner experts in the field, altogether we established twelve GSCI first-order constructs with 51 measurement items as the survey instrument. A mail survey in Thailand is employed to validate the constructs and test the hypotheses. This study used five-point Likert scale to collect data for the constructs of GSCI adopted from Wong et al. (2015), and environmental, cost reduction and business performance outcomes from the existing operations management literature (Boyer & Lewis, 2002; Ward & Duray, 2000; Swink et al., 2007). The items were translated into 4

Thai by two bilingual Thai researchers. A back-translation process was applied to ensure conceptual equivalence. Three academics from the field of supply chain and operations management reviewed the initial measurement scales and provided feedback. Next, we invited six expert judges who have related industry experience to validate the scales using the Q-Sort method. The Q-Sort method required experts to the scales into groups, in which each group corresponded to a construct upon agreement (Moore and Benbasat, 1991). The Q-Sort suggested acceptable content validity because the scale achieved a placement score, which is greater than 70% (Moore and Benbasat, 1991). The hit ratio is 78%, indicates acceptable initial discriminant and convergent validity. To establish the extent to which each company practices GSCI practices, the respondents were asked to assess the extent of which their firms implement the green supply chain integration practices on a five-point Likert scale of 1 = almost never to 5 = almost always. The survey instrument asked respondent to assess cost, financial and environmental performance in terms of improvement achieved in the past-two years relative to the industry s average. That means we are interested in competitive performance and improvement in performance rather than performance in the eyes of each respondent. Thus, we have attempted to eliminate potential bias due to different views of actual performance. We selected manufacturing industry in Thailand as the sample of this study. By collecting sample from one industry can minimize confounding effects due to variations in organizational and supply chain practices across industries. We drew a sample of 1,325 manufacturers from electronic, automotive, and food industry for a mass survey. 203 usable responses were received with a response rate of 15%. The majority of the firms (88.2%) environmentally certified. Most of the responding firms (50.2%) have more than 500 employees, 42.9% have 101-500 employees, and the remaining responding firms (6.9%) have less than 100 employees. 31.8% of firms have more than US$50M annual sales, while 68.2% have less than US$50M annual sales. The survey was answered by a mixed of COO (25.6%), CEO (25.1%), functional managers related to operations and environment (25.6%) and others. Table 1 Construct CFA results Constructs Loadings Goodness of Fit indices.74-1.00 χ 2 = 507.18, df = 161; IFI =.91; CFI =.91; IFI =.91; RMR =.02; Cronbach s alpha =.95; AVE =.83 Green Supplier Integration (2 nd order construct) Green Customer Integration (2 nd order construct) Green Internal integration (2 nd order construct).84-1.00 χ 2 = 224.80, df = 71; IFI =.95; CFI =.95; IFI =.95; RMR =.06; Cronbach s alpha =.96; AVE =.89.80-1.05 χ 2 = 222.39, df = 86; IFI =.93; CFI =.93; IFI =.93; RMR =.06; Cronbach s alpha =.92; AVE =.79.74-.87 χ 2 = 32.65, df = 2; IFI =.93; CFI =.93; IFI =.93; Financial Performance RMR =.03; Cronbach s alpha =.89; AVE =.65 Environmental.75-.87 χ 2 = 92.65, df = 12; IFI =.92; CFI =.92; IFI =.92; Performance RMR =.04; Cronbach s alpha = 92; AVE =.59 Cost Performance.65-.88 Cronbach alpha =.83; AVE =.62 (Note: No fit index because there are only three items) Following Gerbing and Anderson (1988), we performed confirmatory factor analysis (CFA) using the maximum likelihood estimation of AMOS 20.0 to test the psychometric properties of the measurement scales. We assessed the unidimensionality of the constructs 5

by using Cronbach s alpha and composite reliability. The results in Table 1 indicate that all constructs have Cronbach s alpha and composite reliability higher than the 0.70 threshold, suggesting that the measurement scales have adequate reliability. We evaluated the convergent validity of the measurement scales by assessing the loadings and significant level of each measurement item on their respective construct. We also tested the discriminant validity of the constructs by conducting a series of chi-square difference tests to assess the differences between each pair of constructs. The chi-square difference of each pair of construct is statistically significant, suggesting discriminant validity of constructs. Results and analyses We then model the structural model following the theoretical framework in Figure 1. The results of the structural analysis found that the model was a good fit to the data (χ2 = 3182.24, df = 1839, IFI = 0.91, TLI = 0.90; CFI = 0.91, RMR = 0.06). After establishing model fit, the hypothesized relationships were analysed. As summarized in Table 2, the overall pattern of the structural model results in this study provides partial support for the positive relationships between GSCI and performance outcomes. Based on the findings, only GSI and GII have positive and significant impact on environmental performance, β = 0.25 (p < 0.05) and β = 0.23 (p < 0.01), respectively. GCI, on the other hand, has positive and significant impact on both cost reduction β = 0.26 (p < 0.05) and financial performance β = 0.22 (p < 0.05). GSI also has a positive and significant impact on financial performance β = 0.20 (p < 0.05). In addition, the variance explained by GSI, GII and GCI on environmental performance is 18.2%, cost reduction is 15.5%, and financial performance is 15.7%. Even though GSI, GII and GCI cannot explain the majority of the environmental, cost and financial performance, they represent significant contributions to the bottom lines and environment. Table 2 Structural model testing Standardized Estimates Interpretation GII and performance H1(a) GII Environmental performance.25* H1(a) accepted H1(b) GII Cost performance.07 H1(b) rejected H1(c) GII Financial performance.04 H1(c) rejected GSI and performance H2(a) GSI Environmental performance.23** H2(a) accepted H2(b) GSI Cost performance.12 H2(b) rejected H2(c) GSI Financial performance.20* H2(c) accepted GCI and performance H3(c) GCI Environmental performance.01 H3(a) rejected H3(c) GCI Cost performance.26* H3(b) accepted H3(c) GCI Financial performance.22* H3(c) accepted **P<0.01; *P<0.05 Discussion The results of this study provide some interesting implications. Firstly, the results suggest that manufacturers in Thailand have implemented integrative approaches to green supply chain management (GSCI) at different extents. We observe some manufacturers with consistently high levels of GSI, GII and GCI, which indicate such integrative approaches to green supply chain management are aspirational and yet achievable. Taking the work 6

of Wolf (2011), Yu et al. (2014) and Wong et al. (2015) a step further, this study verifies and validates the measurement scales for GSCI as a new concept and its sub-components (i.e., green internal, supplier and customer integration) for facilitating future empirical green supply chain management research. Compared to previous studies that reported mixed findings in the performance implications of various green supply chain management practices (e.g., Zhu & Sarkis, 2004; Vachon & Klassen, 2008), our results suggest that an integrative approaches to green supply chain management ground on resource orchestration theory can lead to significant contributions in environmental, cost and financial performance. The next interesting finding is this study not only shows that the three GSCI practices can collectively improve cost, financial and environmental performance, it provides early indicates which GSCI practices are more effective in affecting which performance outcomes. That means the results encourage manufacturers to develop an integrated managed system that ties all internal functions and top management with external suppliers and customers at strategic and process levels to enable effective collaboration and orchestration of resources, instead of debating on the best ways to achieve win-win situation. Managers need to understand where performance comes about. Our results suggest that the improvement of manufacturers environmental performance originated mostly from green internal and supplier integration, but not green customer integration. These results echo Vachon and Klassen s (2008) study about supplier environmental collaboration. This is probably because the manufacturers have more opportunity and influence over the environmental issues related to manufacturing and logistics processes of their own and suppliers operations, making the integrative approaches more effective in reducing environmental damages. Integration with customers, even though it is for environmental management, often prioritizes cost and financial performance. Somehow we argue that green customer integration drives upstream members to look into cost saving activities that benefit the customers. It may also help to create greener products that actually add margins or create new markets and hence contribute to financial performance. Our results also indicate that green internal and supplier could not lead to cost benefit. As proved earlier (Zhu & Sarkis, 2004) that there is a cost to implement internal and supplier green supply chain practices. Thus, the efforts to integrate internally and with suppliers in greening the supply chains do not necessary improve cost. Furthermore, these efforts also do not improve financial performance because better environmental performance owing to upstream and internal initiatives does not focus on making products and services more competitive. This shortcoming is overcome by green customer integration because collaborating with customers help to reduce cost of transaction while manufacturers attempting to reduce the cost of materials, waste and energy. Green customer integration can be a good investment because such a collaborative orientation builds up relational rents and increase customer satisfaction. Contrary to previous evidence based on the concepts of external green supply chain management (Zhu & Sarkis, 2004) and customer environmental collaboration, our results show that green customer integration would not necessary improve manufacturers environmental performance. This is partly due to the emphasis on purely documentary compliance and the pressures from the customers to improve environmental performance of the customer operations. Yet, green customer integration improves business performance by allowing manufacturers to better understand and produce products that market needs. Conclusion 7

This paper empirically verifies that integrated approaches to green supply chain management called green supply chain integration (GSCI) can be divided into green internal, supplier and customer integration. The main contribution of this paper lies on our approach in dividing GSCI into three dimensions and differentiate their influences environmental, cost reduction and business performance. Green internal integration (GII) involves the strategic collaboration and integration across internal resources via an integrated management linking top management with management systems, quality control, and different functions together. Green supplier integration (GSI) extends GII to upstream suppliers with a focus on exchange information, supplier assistance, collaboration and process coordination. We demonstrate that both GII and GSI are critical for improving environmental performance. Green customer integration (GCI) extends GII to downstream customers with an emphasis in information exchange, collaboration and process coordination. We show that GCI and GSI are keys to financial performance and only GCI helps to reduce cost. Our empirical analyses show that only when all the three dimensions of GSCI are successfully orchestrated companies are able to improve environmental performance while reducing cost and improving financial performance. Specifically, the paper suggests managers to put efforts in integrate environmental management internally and with supplier for improving environmental performance and with customer for reduce cost and improve business performance. Further empirical investigation is needed to generalize the findings. Acknowledgments This research is supported in part by the Research Grants Council of the Hong Kong Special Administration Region and the Economic & Social Research Council (ES/J016799/1). References Arimura, T.H., Darnall, N. & Katayama, H., (2011), Is ISO 14001 a gateway to more advanced voluntary action? The case of green supply chain management, Journal of Environmental Economics and Management, 61(2), 170-182. Berrone, P. & Gomez-Meija L.R., (2009), Environmental performance and executive compensation: an integrated agency-institutional perspective, Academy of Management Journal, 52(1), 103-126. Beske, P., (2012), Dynamic capabilities and sustainable supply chain management, International Journal of Physical Distribution & Logistics Management, 42(4), 372-387. Bowen, F.E., Cousins, P.D., Lamming, R.C. & Faruk, A.C. (2001), The role of supply management capabilities in green supply', Production & Operations Management, 10(2), 174-189. Boyer, K.K., & Lewis, M.W., (2002), Competitive priorities: investigating the need for trade-offs in operations strategy, Production and Operations Management, 11(1), 9-19. Carmody, J. & Zeppel, H., (2009), Specialist accommodation operations in North Queensland: barriers to the implementation of environmental management practices, International Journal of Management & Decision Making, 10(3-4), 201-213. Carter, C.R. & Easton, P.L., (2011), Sustainable supply chain management: evolution and future directions, International Journal of Physical Distribution & Logistics Management, 41(1), 46-62. Darnall, N., Jolley, G.J. & Handfield, R., (2008), Environmental management systems and green supply chain management: complements for sustainability? Business Strategy and the Environment, 17(1), 30-45. Deans, I., (1999), An approach to the environmental management of purchasing in the utilities sector, Eco - Management and Auditing, 6(1), 11-17. Dyer, J.H. & Singh, H. (1998), The relational view: cooperative strategy and sources of interorganizational competitive advantage, Academy of Management Review, 23(4), 660-679. Gerbing, D.W. & Anderson, J.C., 1988. An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186 192. 8

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