مدیریت زنجیره‌ تامین پایدار: یک رویکرد سلسله مراتبی شبکه‌ حلقه بسته Sustainable supply chain management: a closed-loop network hierarchical approach

Sustainable business development has received attention over the last few decades because of the significant focus in the electronic supply chain network on environmental, social and corporate responsibility (Ahi and Searcy, 2013). In addition, the markets and operations have prompted firms to revisit their corporate, business and functional operations and to aim for sustainable supply chain management (SSCM) (Ageron et al., 2012). Recognizing the importance of sustainability in supply chain management, there have been attempts made to develop an evaluation performance framework. An efficient and accurate performance measurement framework can serve as a useful tool that enables management to control, monitor and improve their firms’ processes and performance. Hence, Kaplan and Norton (1992; 1996) have proposed a balanced scorecard (BSC) to assess business performance using financial and non-financial indicators. The BSC enables the expression of business performance indicators and thus ensures the framework required for the performance measurement of management functions. Nevertheless, the framework is a multi-hierarchical structure of dependence relations with a close-loop structure for the aspects and criteria of an organization. The existing SSCM literature fails to address these issues for performance assessment (Carter and Rogers, 2008; Seuring et al., 2008; Ageron et al., 2012; Gopalakrishnan et al., 2012; Walker and Jones, 2012; Ahi and Searcy, 2013) . In the literature, sustainability has become a trend, and it enables firms to integrate environmental and social issues into their corporate strategies (Srivastava, 2007). Firms are increasingly aware of the importance of their responsibility toward their stakeholders to address sustainability in their strategic development, and this environmental sustainability is impossible without incorporating SSCM (Preuss, 2005; Bai and Sarkis, 2010). SSCM is characterized by the explicit integration of environmental and social objectives that extend the economic dimension to integrate environmental and social considerations (Tseng, 2013). Carter and Rogers (2008) defined SSCM as the strategic integration and achievement of an organization’s social, environmental and economic goals in the systemic coordination of key internal business processes for improving the long-term performance of the individual firm and its supply chains. Gupta and Palsule-Desai (2011) presented a set of SSCM managerial practices that consider environmental impact, value chain and multi-perspectives on the entire product life cycle. However, a comprehensive review of SSCM studies has been presented in several studies (Seuring et al., 2008; Seuring and Müller, 2008; Gupta and Palsule-Desai, 2011; Zailani et al., 2012; Liu et al., 2012; Ahi and Searcy, 2013). The SSCM on the performance measure is currently unavailable, and thus, a performance approach toward the examination of SSCM is needed. From a theoretical perspective, the concept of SSCM integrates the environmental, social, and economic aspects that allow an organization to achieve long-term economic viability in supply chain management (Tseng et al., 2008; Kuo et al., 2001; Tseng and Chiu, 2013). It is also a strategic factor for increasing a firm’s effectiveness and for better realizing sustainable organizational goals to enhance competitiveness, achieve better customer service and increase profitability. In particular, SSCM includes the movement and storage of sustainable raw materials and green products from the point of origin to a point of sustainable consumption (Brandenburg et al., 2014). The provision of sustainable products that are required by end customers in a supply chain involves the cooperation of interconnected networks, channels and node businesses. From a traditional firm’s point of view, the shareholders are the owners of a company, and the firm has a binding fiduciary duty to meet needs and increase value in a supply chain. Even competitors are counted as stakeholders, and their status is derived, in this view, from their capacity to affect the firm and its stakeholders (Donaldson and Preston, 1995; Friedman and Miles, 2002). In lieu of this, most of these firms realize that, in order to evolve, they must develop an efficient and effective sustainable supply chain, which needs to be assessed based on its performance (Tseng and Geng, 2012). Hence, the stakeholder theory and the BSC model are the basic theory and model for this performance evaluation. In the BSC model, there are four aspects that need to be balanced for SSCM performance measurement; these include sustainability, stakeholders, internal business process, and learning and development (Kaplan and Norton, 1996), and they integrate environmental and social aspects with economic performance. Wu et al. (2010) proposed a corresponding fuzzy scale to evaluate the linguistic preferences within close-loop hierarchical BSC structures that can clearly reflect performance and importance weights. Chen et al. (2011) asserted that the balanced scorecard approach is an effective technique for a hybrid multi-criteria decision making (MCDM) model performance evaluation in order to solve the dependence and feedback problems at a hot spring hotel. Lin et al. (2013) explored and built a BSC structure with fuzzy linguistic preferences for measuring and improving hospital services. The BSC quantitative models are often practically applied in an open-structure framework. In this context, the BSC framework ought to focus on close-loop evaluation in order to fulfill the existing gaps in the SSCM literature (Linton et al., 2007; Matos and Hall, 2007; Miemczyk et al., 2012; Zailani et al., 2012; Abbasi and Nilsson, 2012; Tseng and Chiu, 2013; Zhu et al., 2013; Tseng, 2013). A further understanding of the common and unique SSCM evaluation characteristics is necessary to help further catalyze this study, which offers numerous opportunities to improve firm performance. Existing studies have informed managers of the interdependence between environmental and economic systems, but they fall short in explaining how a firm handles the performance criteria of different BSC aspects from a typical case. Few SSCM existing studies have presented an evaluation of qualitative and quantitative information together. For instance, Wu and Pagell (2011) presented theory-building through case studies to balance profitability and environmental sustainability when making supply chain decisions under uncertainty. Lin and Tseng (2014) adapts a hierarchical structure and linguistic preferences to identify the competitive priorities under SSCM. However, the previous studies are ignored the qualitative and quantitative information together. The purpose of this study is to make sense of the complex SSCM environment to address information complexity and uncertainty, and to recommend actions that induce change. Hence, this study proposes a fuzzy set theory to transform linguistics preferences into crisp numbers, the fuzzy Delphi method (FDM), to eliminate the performance criteria under perceptions and the analytical network process (ANP) to resolve the interdependent relationships in a complex environment. Therefore, this study focuses on SSCM in both BSC aspects and practical criteria. The study questions are as follows: 1. What are these criteria? 2. What are the important aspects and criteria as they relate to current SSCM performance practice under uncertainty and interdependent relationships? SSCM leads to a reduction in resources, material and waste by enabling better resource utilization and plays a significant role in achieving social, environmental, and economic performance; thus, it contributes to the field of sustainable development. Its main contribution is to present and organize the key performance aspects for BSC and the criteria concerning the effects of SSCM on the sustainable supply chain performance of the focal firm. The paper is organized as follows. First, there is a BSC performance evaluation of the role of the BSC framework in SSCM and a review of the literature on the study criteria followed by the development of the SSCM-BSC framework in section 2. Section 3 presents the method and data analysis. Then, data from an expert linguistic preference questionnaire survey of professionals in a focal electronic manufacturing firm are used to examine the answers to the study questions. The data were then analyzed using the fuzzy Delphi method and the fuzzy analytical network process. The results are discussed in section 4. This discussion is a hierarchical model, for which the aspects and criteria are presented in hierarchical and interdependent relationships under the condition of uncertainty. The last section presents the discussion, implications, contributions and limitations, and conclusions.