1 Strategies for Supply Chain Sustainability: Low Cost Country Sourcing Perspective Abstract Purpose - There is a paucity of studies pertaining to supply chain sustainability (SCS) in the case of sourcing from low-cost countries. Therefore, grounded on stakeholder theory and dynamic capability view (DCV), this study develops a model for SCS that identifies and prioritizes optimal strategies to address the supply chain sustainability (economic, social and environmental) requirements of the stakeholders in the context of apparel industry in Bangladesh. Methodology - This study adopts a mixed method approach: a combination of both qualitative and quantitative research methods. The qualitative approach is comprised of identifying the sustainability requirements of the stakeholders and strategies to support the SCS requirements. On the other hand, the quantitative approach applies fuzzy Quality Function Deployment (QFD) integrated 0-1 non-linear optimization technique to identify optimal strategies for addressing the stakeholders’ sustainability requirements. Findings - The results show that ensuring a work environment with hazard free ingredients and no child labour, incorporates health and safety of employees, and provisions fair wages as high priority SCS requirements. The research findings also show that formulating a human resource policy regarding workers’ benefits, undertaking sustainability awareness programs, and developing health and safety issues, are the most important strategies for complying with the SCS requirements of the stakeholders. Practical implications - The findings of our study will assist the supply chain managers in prioritizing the SCS requirements of the stakeholders, as well as selecting and implementing optimal strategies in alignment with business needs to meet the SCS requirements. Originality/value- Drawing on stakeholder theory and dynamic capability view this study develops a theoretical model for SCS in the context of sourcing from a low-cost country Bangladesh, which is a novel attempt in SCS literature. Key words: Supply chain sustainability, Stakeholders’ requirements, stakeholder theory, dynamic capability view, optimal strategy, QFD. 1. Introduction The global textile and garment industry is at a crossroads. It is a three trillion dollar industry … The flipside of this growth and the accelerating production of fashion has been a broadening and deepening track record of poor working conditions and heavy pollution. The collapse of the Rana Plaza factory in April 2013 in Dhaka, Bangladesh jolted to life widespread and increasingly prolonged scrutiny of the industry. This incident has brought longstanding questions to the forefront over how to bridge the gap between economic viability and social and environmental performance. (Martin 2013). Clearly the economic, social and environmental issues are predominant in the corporations of many developing countries such as Bangladesh, Pakistan, and India (Naeem and Welford 2009). More specifically, these issues also prevail in human intensive organisations, such as, Apparel industry (Islam2 and Deegan 2008, Ahmed and Peerlings 2009). The Apparel manufacturing industry productivity and competitive advantage is susceptible to changing global competitive pressures in both developed and developing nations. Operating in a high vs low labour cost environment presents different practical challenges for manufacturing firms operating in different economic conditions. Roos (2012) defines high and low cost economies as follows: “In a low-cost operating environment the primary basis for competitive success is low cost and the key basis for competitive advantage is efficiency and access to inputs for which there exist a comparative advantage. In a high-cost environment the primary basis for competitive success is value for money arrived at through competitive advantages grounded in constant innovation approached in an integrated way” (p.9). These differences vary across countries and are predisposed by the labour-capital intensity of production, which in turn is shaped by the economic condition of a particular nation, These structural differences in the economy and society are due to legislative and institutional factors such as the cost of labour, private and public investments in education, R&D capital investments, capacity for technology and labour diffusion, access to market information, ability to efficiently manage risk and uncertainty and a myriad of other factors. Clearly, Bangladesh is a low-cost developing country (Gereffi, Gary and Stacey Frederick 2010)., yet one of the leading exporters of Apparels in the world. Apparel industry is an economic propeller of Bangladesh and accounts for 78.6% of total export earnings and over 4 million direct employments of which 80% are women. The export of Apparel has grown exponentially from US$5.99 billion in 2001 to US $24.3 billion in 2012 (Ivanou 2013) making Bangladesh as the second largest Apparel exporter in the world. But the Apparel supply chain members are accused of poor working conditions, inadequate health and safety measures of the factory, violation of human rights, environmental pollution and the use of child labour (Belal and Owen 2007; Islam and Deegan 2008; Naeem and Welford 2009), which threaten the sustainability of Apparel supply chain. These issues are often highlighted in western media (Butler 2013; Ivanou 2013) and as a result the buyers and other stakeholders impose social and environmental compliances on low cost country Apparel manufacturers. However, to comply with stakeholder requirements, balancing the act of economic, social and environmental issues is an extremely difficult task (Pagell and Wu 2009); it is even more difficult in the case of sourcing from low-cost country manufacturers while resource shortage is one of the prime constraints in implementing sustainability strategies (Ageron et al. 2012; Muduli and Barve 2012; Arevalo and Aravind 2011; Welford and Frost 2006). Hence, organizations in such low-cost countries need to set contextualised strategies to enhance supply chain sustainability performance (Plambeck and Taylor 2015). This study thus develops a model for supply chain sustainability that identifies, prioritizes and finds the optimal strategies to address the sustainability (economic, social and environmental) requirements of the stakeholders in the context of the Apparel Industry of Bangladesh by using fuzzy QFD approach. The motivation of this study is influenced by the challenge of translating stakeholders’ sustainability requirements into meaningful and practicable strategies. Literature suggest that it is extremely difficult, if not impossible, to reconcile stakeholders’ concerns. This is more so when an industry has myriad of secondary stakeholders (e.g., various lobby groups, environmental activists, media etc.). Hall and Vrendenburg (2005, p.11) call it “stakeholder ambiguity”. The authors report that stakeholder ambiguity is difficult to manage as “it is idiosyncratic and context-specific”. Fassin (2009) in an attempt to reconceptualise stakeholder model identifies various ambiguity, vagueness and3 pressure groups in a stakeholder model. Organizations will thus face extreme difficulty in addressing the requirements of these varied stakeholders. In a recent paper Hall et al. (2014) identify stakeholders’ differences in risk perceptions of new technology development and assert that soft factors are playing increasing roles in management decision making. Recent studies also suggest that requirements of sustainability follow a logic of ‘materiality’ and ‘adaptability’ (Lyndenberg 2012; Hsu et al. 2013; Reeves et al. 2012). Lyndenberg (2012) summarises that sustainability norms and standards are industry specific in which relevant stakeholders play a significant role in shaping the material requirements of sustainability. Hsu et al. (2013) showed how materiality analysis was carried out in an organization. In the same vein Reeves et al. (2012) argue that sustainability should be regarded as an ‘adaptive advantage’. In this research we also address the stakeholder ambiguity and materiality/adaptability concept of sustainability requirements by taking an “industry specific” fuzzy QFD modelling approach. It is envisaged that fuzzy Quality Function Deployment (QFD) approach, which is popular in translating customer/stakeholder requirements to appropriate design functions (Bottani and Rizzi 2006; Delice and Gungor 2010) will be the appropriate method in our case. Translating stakeholders’ sustainability requirements to appropriate strategies is very critical because of the influence of diversified stakeholders and the dynamic nature of their sustainability requirements. Beske (2012) identify that implementing supply chain sustainability strategies to satisfy the stakeholders is a dynamic capability. In line with Beske (2012) we argue that translating the dynamic nature of the stakeholders’ sustainability requirements to appropriate strategies is a dynamic capability for the organizations. We also propound that selecting optimal strategies to meet the sustainability requirements of the stakeholders with in the constrained resource is also a unique capability for the firms and their supply chains. Therefore, along with stakeholder theory we use dynamic capability view (Teece et al. 1997) to justify the supply chain sustainability model developed in this study. The paper is organised as follows. The next section presents the literature review to put our paper in the context of extant literature. This is followed by the research methodology section. The results are then presented followed by discussions where theoretical and managerial implications are presented. Finally, conclusions are presented. 2. Literature review 2.1 Supply chain sustainability and stakeholders’ requirements Issues pertaining to sustainability in supply chain have been researched in recent years from various perspectives. On one hand supply chain sustainability has been characterized as a mechanism for continuous improvements within organizations (UN Global Compact 2010) on the other attempts have been made to develop a theory of sustainable supply chain management (e.g. Carter and Rogers 2008). Seuring and Muller (2008, p. 1700) define sustainable supply chain (SSC) “as the management of material, information and capital flows as well as cooperation among companies along the supply chain while taking goals from all three dimensions of sustainable development, i.e., economic, environmental and social, into account which are derived from customer and stakeholder requirements”. Seuring and Muller’s (2008) definition highlights that SSC needs to deal with various sustainability requirements of the stakeholders to sustain in the long run. Therefore, focal firms of supply chains shall be held accountable for the environmental and social performance of supply chain members. Stakeholder theory offers a platform for ascertaining key groups to whom firms should direct their sustainability efforts (Shafiq et al. 2014). Freeman (1984) defines stakeholders as the individuals and groups that influence or can be influenced by the activities of the firm or their stakeholders. Stakeholder theory calls for managing the requirements of diversified stakeholders to4 sustain in the long run which utter the essence of identifying the sustainability requirements of the stakeholders and addressing those in due course. Supply chain sustainability has been recognized as a strategic weapon for organizations and their supply chain members as it has a pulling effect in the market deriving from customers demand (von Geibler et al. 2006). For achieving sustainability in supply chain a balance needs to be maintained among social, environmental and economic goals and corresponding stakeholders’ requirements (Carter and Rogers 2008; Carter and Easton 2011) which is also an important agenda of stakeholder theory (Freeman 1984). Balancing the priorities is also highlighted by Wu and Pagell (2011). The authors report that companies need to balance the short term economic gains and long term environmental goals in order to manage supply chain sustainability. In a related study Pagell and Gobeli (2009, p. 278) have shown that social performance (measured as employee wellbeing), environmental performance and operational performance “do interact in a significant way”. Hence operational managers should take advantage of this interrelationship to achieve supply chain sustainability. Parmigiani et al. (2011) study the dilemma of efficiency and accountability in supply chain sustainability. The authors propose that stakeholders’ exposure plays significant role in supply chain sustainability outcomes. To Perrini and Tencati (2006) a sustainable organization tries to maximize social and environmental performance along with economic performance for a sustainable and value based stakeholder relation. Above and many other related literature suggest that supply chain sustainability is now a salient requirement of customers, government and stakeholders (Seuring and Muller 2008). As a result organizations as well as their supply chains try to integrate sustainability in their strategic plans. Previous studies identified a number of sustainability issues to meet the buyers’ and other stakeholders’ requirements such as fair wages, good working environment and safety, restricting child labour and force labour, health hazard free product, controlling pollution and others. Table 1 presents a succinct view of the sustainability requirements of the stakeholders. (Insert Table 1 about here) Table 1 shows that sustainability requirements (as revealed by the literature review) are multidimensional in nature. This justifies our earlier discussions on the stakeholder ambiguity and materiality/adaptability concept of sustainability requirements. In such a context this study attempts to identify the sustainability requirements of Apparel supply chain taking an “industry specific” approach and to find out the effective ways to fulfil the requirements. 2.2 Supply chain sustainability and dynamic capability view Based on the extant literature, dynamic capability view (DCV) is defined as the organisational capability to successfully identify opportunities, followed by executing necessary actions to reconfigure organisational assets and operational capabilities to address the rapidly changing external environment (Teece, Pisano and Shuen 1997; Teece 2009). The term external environment refers to the business ecosystem comprising individuals, organisations or institutions that can have an impact on the focal organisation and its customers and suppliers (Teece 2009). Dynamic capability view (DCV) addresses the context insensitivity of traditional resource-based view by planning appropriate resources and capabilities to respond to situation specific changes (Teece et al. 1997; Eisenhardt and Martin 2000). In other words, it fits with the idiosyncrasy of market requirements and their changes. In addition, DCV emphasizes on clarifying the processes, resources and strategies through which companies can achieve competitive advantage in a dynamic market environment (Teece et al. 1997; Eisenhardt and Martin 2000). Additionally, standard-setting bodies, regulatory authorities, the judiciary system, education and research organisations are also included into the relevant community5 of organisation that may have a potential impact on the focal organisation’s strategic intent (Teece, 2009). We posit that the stakeholders’ sustainability requirements are changing in the phase of changing market environment. The dynamic nature of the market environment for example, intensive pressure of stakeholders along with the fierce competition of the competitors are compelling the managers to implement appropriate sustainability strategies through collaboration in supply chains. Therefore, marketers need to translate the sustainability requirements of the diversified stakeholders in devising appropriate strategies to co-exist in a dynamic market environment. In this context, Beske (2012) states that, to meet the changing market need, developing and implementing sustainability strategy in supply chain is a dynamic capability for the organizations. Agarwal and Selen (2009, 2011, and 2014) highlight how dynamic capability building in changing environments is enhanced through collaborative service value networks leading to innovation. Agarwal & Selen (2009) highlight organizations and their supply chains/networks manoeuvre., mobilise and develop ability to reconfigure, reuse and reutilise resources and enhance capabilities, which Teece et al. (1997) explained as dynamic capability for the firms. Commensurate with this we posit that organizations need to arrange and rearrange their resources and capabilities to implement sustainability strategies per the requirements of the stakeholders. However, implementing the sustainability strategies are influenced by multiple constraining factors such as resource, technology, expertise etc, and selecting the most suitable strategies is a key success factor to achieve sustainable competitive advantage (Chowdhury et al. 2015). Aligned with dynamic capability view (Teece et al. 1997) selecting such strategies can also be attributed to defining the path of competencies in the changing market scenario. Therefore, drawing on dynamic capability view we argue that organisations through collaboration can select optimal sustainability strategies to meet the sustainability requirements of diversified stakeholders; having to do arms them with the dynamic capability required for the organizations and their supply chains to work collaboratively. 2.3 Process of meeting sustainability requirements Compliance of sustainability requirements is very important to compete in the market. In the context of Bangladesh a study by Chowdhury et al. (2015) and Hossain et al. (2012) report that lack of regulatory framework, socio economic problems, lack of awareness and sustainable education, lack of initiative from government, resource constraints and tendency to disobey laws are the main barriers of sustainability. Mitigation of these problems is very important to fulfil the sustainability requirements of the buyers and the stakeholders. A number of researchers argued that a strategic sustainability policy can help an organisation move towards sustainable business practice (See for example, Aragón-Correa and Sharma 2003; Kuasirikun 2005; among others). Regulations in most countries require some social and environmental aspects of business activities and wider sustainability issues are frequently addressed by the regulations (Schaltegger and Burritt 2005). These regulations force managers to consider sustainability management. Plambeck and Taylor (2015) suggest that buying firms need to apply obvious approaches such as auditing and publicizing negative audit reports as well as less obvious approaches such as reducing the supplier's margin to motivate the supplier to comply with sustainability standard. To meet the sustainability expectation of the stakeholders, organisations now evaluate their social and environmental performance through achieving the certificates such as ISO 14001, United Nations global compact membership from different standard setting bodies and more (Adams and Narayanan 2007). In the global challenging and competitive business arena, organisations focus on social and environmental compliance; ensure sustainable working conditions including occupational health, safety and hygienic matters to meet the requirements of customers (Islam and Deegan 2008). Chowdhury et al. (2015) and Hossain et al.6 (2012) argued that awareness creation and continuous training of employees, management and other stakeholders can help the organisation to achieve their sustainability objectives. Internal stakeholder requires more training and education for supply chain sustainability which fulfil the management desire of increased environmental, social and sustainability standards (Seuring et al. 2008). To meet the sustainability standard, technological advancement particularly the efficiency of technology is important aspect. Awaysheh and Klassen (2010) reported that supply chain structure (in terms of dependency, transparency and distance) also plays and important role in ensuring supplier socially responsible practices. Considering the review of existing literature Table 2 summarizes the processes of meeting sustainability standard in concise way. (Insert Table 2 about here) Table 2 highlights that previous studies have undertaken several ways and means to meet the supply chain sustainability requirements of the stakeholders. These varied from the company level strategies to much higher level strategies beyond the companies (for example first two columns of Table 2). These will be the basis of our current study to investigate the optimal strategies to attain the supply chain sustainability requirements for Apparel industry stakeholders in Bangladesh. 2.4 Quality function deployment (QFD): As mentioned earlier, our study has used Quality Function Deployment (QFD) methodology to identify and prioritize the optimal strategies to meet the sustainability requirements of the apparel supply chain. QFD is frequently used in strategic management and operations management. It is considered to be one of the very effective methodologies to find organizational strategies to incorporate the customer needs and thus achieve organizational goals (Akao 1990; Chan and Wu 2002, 2003). Because of its widespread applicability to determine suitable operational strategies, QFD has been used by many scholars to manage sustainability strategies. For instance, Chowdhury and Quaddus (2016) used QFD to develop the sustainable service design and Vinod and Cintha (2011) employed QFD for enabling sustainability in the organisation. In a similar fashion, QFD is deployed to incorporate voice of customers and stakeholders for sustainable supplier selection (Dai and Blackhurst 2012), sustainable product design (Vinod and Rathod 2010), and other issues related to sustainability. However, to the best of our knowledge QFD has not been applied to address the sustainability requirements of stakeholders in the case of apparel supply chain which spans from low-cost producing countries to the developed countries. This gap in the literature motivated us to apply QFD in our research. 2.5 Fuzzy QFD approach: Zadeh (1965) was first to introduce the fuzzy set theory to deal with the issue of ill-defined problems that encountered a certain level of uncertainty and ambiguity. The prime advantage of using fuzzy logic is the conversion of ambiguous subjective judgement to precise objective expressions, such as the relationship between the sustainability requirements and the derived strategies to support the requirements. Further, the application of fuzzy numbers has become enormously important in the area of decision-making in which linguistic scales are adopted and especially in situations when a panel of decision makers (DMs) are involved in subjective decision making process (Bottani and Rizzi 2006). Literature reveals that fuzzy method has been used within QFD framework. Khoo and Ho (1996) proposed that the ambiguity in QFD operations can be resolved by the application of fuzzy numbers. Wang (2004) enumerated a fuzzy approach to prioritize the strategies in QFD environment. Researchers such as Bottani and Rizzi (2006) and Pujawan and Geraldin (2009) used fuzzy QFD to overcome the ambiguity in traditional QFD method by quantifying the subjective judgements7 regarding the relationships among the customer requirements and mitigation strategies. In line with the previous literature and to address the vagueness in various assessments Fuzzy-QFD methodology has been proposed in this paper to determine the objective sustainability requirements of the buyers and stakeholders (WHATs in QFD terminology), the strategies to address the sustainability requirements (HOWs in QFD terminology) and the relationship between the HOWs and WHATs. 3. Research methodology We use a mixed method research design, a combination of sequential process of qualitative and quantitative methods (Bryman 2006) as portrayed in Figure 1, because it assists in increasing the quality, accuracy, validity and reliability of data (Creswell 2003; Babbie 2004). As shown in Figure 1 our research design is split into three phases (see also Akao 1990; Chan and Wu 2002, 2003). QFD Phase 1 involves the qualitative data collection in terms of identifying apparel supply chain sustainability requirements and strategies to support the requirements (qualitative part of QFD). QFD Phases 2 and 3 subsequently apply QFD methodology (quantitative parts) to prioritize and identify the optimal strategies to address the apparel supply chain sustainability requirements. Table 3 provides a summary of the research design adopted underpinning the research model framework proposed herein in Figure1. Figure 1: Research Model (Insert table 3 about here) Figure 2 shows a generic QFD model wherein the WHATs in Figure 2 are the customer requirements that are stakeholders’ sustainability requirements of apparel supply chain in our case. The HOWs are the design requirements that are strategies to support the sustainability requirements in our case. The “importance” on the right-hand side of Figure 2 are the importance weights of the WHATs. The “absolute and relative values” underneath Figure 2 are the weighted importance weights of the HOWs (weighted by the WHATs). The relationship matrix shows the relation between the WHATs and the HOWs, i.e., to what extent the WHATs (the sustainability requirements/SRs) are realized by the HOWs (the strategies/STs). The roof of the QFD model (correlation matrix in Figure 2) shows the relation between the HOWs (strategies), i.e. the extent of overlaps in the strategies. We amend Figure 2 and display its context specific version (as shown in Figure 4) “Supply Chain Sustainability Model” discussed later. (Insert Figure 2 about here) (Insert Table 4 about here) It is noted from the steps (Table 4) that QFD methodology needs extensive interaction from the case companies for various data collection. Detail discussions of executing each of the QFD phases (Figure 1) along with the corresponding steps and the results obtained are presented below.8 4. Results 4.1 QFD Phase 1 Results In this phase, steps 1 and 2 are executed with the aim of identifying the sustainability requirements and strategies of meeting the sustainability requirements in the context of apparel supply chain of Bangladesh. First, extensive literature review is conducted with respect to supply chain sustainability, sustainability requirements and processes of meeting requirements in the context of Bangladesh and other developing countries to come up with a range of factors and variables. Tables 1 and 2 presented earlier showed the outcomes from the literature review. Then qualitative field study is conducted with seven companies consisting of apparel buying agents, apparel manufacturers and their suppliers in order to identify the sustainability requirements in the context of apparel supply chain of Bangladesh. The purpose of this field study phase was to refine and contextualize the list of sustainability requirements and the strategies found in the literature review as summarised earlier in Tables 1 and 2. The participant companies were selected spanning the Apparel supply chain and their willingness to participate in the field study. Considerations were also given to select the companies which directly export to the buyers rather than via third party. Literature (Meier and Jr. 2006) suggests that seven companies is an acceptable sample size for qualitative interviews. We also found that no new issues (requirements and strategies) were coming up during the last two interviews. Hence our selection of seven companies as a sample of interviewees is justified. The interview time was between 60 to 80 minutes. Table 5 shows the profile of the interview participants. Our interview protocol was simple. Our interview question was open ended. We first asked the interviewees their opinions “on the sustainability requirements”. We then followed it up by their opinions “on the strategies to meet the sustainability requirements”. The interviews were transcribed and analysed based on content analysis procedure (Berg 2004) in two stages. The first stage dealt with the single interview transcripts. The second stage dealt with the cross interview transcripts in order to obtain meaningful list of sustainability requirements and the corresponding strategies. This list was then compared with the literature for necessary amendments. Table 6 shows the sustainability requirements and the strategies as obtained from the interview process. Table 6 reveals that the sustainability requirements can be classified into four categories: social, environmental, operational and economic with ten sustainability requirements and nine strategies being identified. Most of the sustainability requirements are consistent with the factors and strategies identified from the literature review (Tables 1 and 2). (insert Tables 5 and 6 about here) 4.2 QFD Phase 2 Results In this phase the quantitative steps 3, 4 and 5 are executed with the aim of determining the weights of sustainability requirements and the weights of the strategies. In this phase, a single case company has been selected for quantitative data regarding the importance of the sustainability requirements and the corresponding strategies. We select single case because QFD approach becomes more complex by adding more cases. Out of the seven case companies the selected company supported all the sustainability requirements and the corresponding strategies explored in the field survey (phase 1). It is also one of the biggest garment manufacturing companies in Bangladesh and is a big player in garment policy making arena in Bangladesh. Three decision makers have been involved from the case company to avoid the biasness in decision making (Lee and Kim 2000). They are the supply chain manager, merchandising manager and the production manager. Fuzzy-QFD tool has been used in eliciting the data needed to execute steps 3, 4 and 5 discussed next.9 Execution of fuzzy logic requires fuzzy number groups or sets where the elements of a set are related to a value that indicates to what extent the element is a member of the set. This value may be within the range [0,1], where 0 represents minimum degree of membership and 1 represents the maximum degree of membership and intermediate values refer to partial membership (Zadeh 1965). Number of membership functions are available: triangular, trapezoidal, gaussian, generalized bell and others (Jang et al. 1997). We use triangular membership function in line with the previous literature (Bevilacqua et al. 2006; Karsak 2004; Chan and Wu 2005), which is called triplets. The triplets has the form of A=(𝘝, 𝞲, 𝐵) where 𝘝, 𝞲 and 𝐵 are in the membership group A. 𝘝, and 𝐵 are the lower and upper limits of the fuzzy number, while 𝞲 is the most likely element (closest fit). The fuzzy membership function is as follows 𝐍 𝞲−𝘝 − 𝐵 𝞲−𝘝 , 𝐵 (𝘝, 𝞲) µx(𝐩 = 𝐍 𝞲−𝐵 − 𝐵 𝞲−𝐵 , 𝐵 (𝐵, 𝞲) 0, otherwise. It is noted that we use the triplet membership function to quantify the linguistic data in our application. To assess a group of attributes we used the linguistic set U= (VL, L, M, H, VH), where, VL = very low, L = low, M = medium, H = high, VH = very high (Bevilacqua et al. 2006). The corresponding triangular fuzzy membership function is shown in Figure 3. In Figure 3, VL= (0,1,2); L= (2,3,4); M= (4,5,6); H= (6,7,8) and VH= (8,9,10) (Bevilacqua et al. 2006). As an example, the linguistic variable H varies from 6 to 8, 7 being most likely with the maximum degree of membership of 1. (Insert Figure 3 about here) To assess the importance ratings (step 3) of the sustainability requirements (WHATs) we asked each decision maker (DM) of the case company to provide verbal (linguistic) responses using the linguistic set U= (VL, L, M, H, VH). Table 7 shows the results of this assessment. It is noted that the perceptions of the DMs are not markedly different. The linguistic variables were then defuzzied using the triangular membership function (Figure 3). The responses from three DMs were aggregated using the average operator. It is noted that numerous aggregation methods (for example, max min, arithmetic average, weighted arithmetic average, geometric average, and ordered weighted average operator) can be used to calculate fuzzy weights. In this paper, we used the average operator because of its simplicity and wide scale use in similar applications (Bevilacqua et al. 2006; Karsak 2004; Yager 1988). Table 8 shows the aggregated importance ratings (Wi, i = 1 to 10) in fuzzy triplets in terms of 𝘝 (lower value), 𝞲 (most likely value) and 𝐵 (upper value). Looking at the column of 𝞲 (most likely) it is observed that SR4 (Restricting child labour in organizations) and SR8 (Quality) has the highest important rating of 9. (Insert Tables 7 and 8 about here) We next executed step 4 (relationship between the sustainability requirements (WHATs) and the strategies (HOWs). This step required extensive interactions with the three decision makers (DMs) of the company. We asked each DM: ‘to what extent the strategies (HOWs) support the sustainability requirements (WHATs)”, i.e., the relationship between the WHATs and the HOWs using the above linguistic variables. The results (after few rounds of deliberations) are shown in Table 9 in the form of10 a correlation matrix. It is noted that Table 9 shows the assessments of three DMs under each ST (strategies). Following the defuzzification procedure and the process of aggregation of three DM’s responses as applied above we resulted in the main WHAT-HOW correlation matrix as shown in Figure 4. The main body of Figure 4 shows the correlation between WHATs and HOWs: Rij in fuzzy triplets in terms of 𝘝 (lower value), 𝞲 (most likely value) and 𝐵 (upper value), where i = 1 to 10 are the WHATs and j = 1 to 9 are the HOWs. (insert Table 9 and Figure 4 about here) Step 5 is now executed to find the absolute importance (AI) and relative importance (RI) of the strategies/design requirements (HOWs). The AI is found by using the following equation. 𝐵 𝐠= ∑𝐠𝐽1 𝐵 𝐵𝐠∀𝐠, 𝐠= 1, … … , 𝐠.... ........ (1) Where, AIj = Absolute importance of the jth strategy (ST or HOWs), (j = 1 to 9 in our case) 𝐵 = Weight of the ith sustainability requirements (SR or WHATs), (i = 1 to 10 in our case, obtained from Table 8). 𝐵𝐠= Correlation value between the ith WHATs and jth HOWs. (obtained from Figure 4). The fuzzy triplets of AI values of the strategies (in terms of 𝘝 (lower value), 𝞲 (most likely value) and 𝐵 (upper value) are shown in the row of “AI of HOWs” in Figure 4. Before finding the relative importance (RI) of the strategies the ‘crisp’ values of AI’s need to be found. Following the suggestion of Bevilacqua et al. (2006) and Facchinetti et al. (1998) we find the ‘crisp’ value by using the following equation: AIcrisp = (AIlower value + 2AImost likely +AIupper value)/4 Facchinetti et al. (1998) suggest that above formula provides a compromise crisp value which is a special linear combination of the optimistic, pessimistic and most likely values. Figure 4 shows the crisp values of the absolute importance of the strategies. It is noted that these crisp values of AIs are the benefits of implementing the corresponding strategies. It is observed from Figure 4 that the AI crisp values range from a low of 24.5 (for SR9: recycling, reusing and treatment of wastes) to a maximum of 55.41 (for SR1: improving HR policy regarding worker’s benefits). The relative importance (RI) of the strategy (SRs) j is found by: 𝐵 𝐠= 𝐵𝐍 ∑𝐠𝐽1 𝐵𝐠....................... (2) Figure 4 shows the relative importance of the strategies. 4.3 QFD Phase 3 Results In this QFD phase steps 6, 7 and 8 are executed with a view to eventually finding the optimal strategies (HOWs) by non-linear optimization problem. In step 6 we found the interrelationships among the HOWs by interacting with the DMs of the case company in a group environment. Results of this group deliberation are shown in the roof of Figure 4. For example, SR2 and SR3 has a very strong relationship. Thus, substantial savings can be achieved if they are implemented together. On the other hand, SR1 and SR2 has weak relationship. We also obtained the estimated cost savings, Sij of implementing strategy i and j together, from the DMs in Bangladeshi Taka (BDT). These are as follows: S16 = 4 million BDT, S17 = 2 million BDT, S23 = 2.5 million BDT, S67 = 3.5 million BDT, S68 = 4 million BDT and S89 = 3 million BDT.11 In step 7 we first obtained the fuzzy triplets of cost of implementing each strategy in terms of pessimistic, optimistic and most likely values by interacting with the DMs (in a group environment). Figure 4 shows these values in terms of millions of BDT. Expected cost of implementing the HOWs are derived by using the formula: Expected Cost = (Optimistic Cost + 4Most likely Cost + Pessimistic Cost)/6 Above estimate of expected cost is widely used in project management and PERT applications (IEEE Computer Society 2011, pp. 172-173) where activity costs are found by the above formula. These expected costs are also shown in Figure 4. Finally, the benefit-cost-ratio (BCR) of each strategy type (ST) is found by taking the ratio of AI (benefit) and the corresponding expected cost. Table 6 shows the Strategies (STs) to support the SRs. For example, the BCR for ST2 is 13.335 (see Figure 4). It is noted that strategies ST2 (awareness programs) and ST5 (supplier evaluation) has the highest BCR. In step 8 we develop the optimization model to find the optimal strategies (HOWs) to meet the sustainability requirements (WHATs) by maximizing the total BCR under a budget constraint. In line with Park and Kim (1998) we develop the 0-1 non-linear optimization problem as follows: However, we use the total benefit-cost-ratio (BCR) in our model. Max f(x) = ∑𝐠𝐽1 𝐵𝐵𝐵 s.t . ∑𝐠𝐽1 𝐵𝐵 − ∑𝐠𝐽1 ∑𝐠𝐾𝐠𝐵𝐵𝐵𝐠≤ B (3) 𝐠∈ 𝐠and 0, 1. Where BCRj is the benefit-cost-ratio of strategy j, 𝐵 is the cost of strategy j and 𝐵𝐠is the saving (in million BDT) in implementing strategies i and j together. B is the available budget. It is noted that the optimization problem (3) above is a non-linear bi-criteria problem. Maximizing BCR is equivalent to maximizing the absolute importance (AI) and minimizing the expected cost. Hence our optimization problem is an extension of Park and Kim (1998). In our application the specific version of problem (3) is as follows: Max f(x) = ∑𝐠𝐽1 𝐵𝐵𝐵 Subject to: 𝐱𝐱+𝐲𝐲+𝐳𝐳+𝐴𝐴+𝐵𝐵+𝐶𝐶+𝐷𝐷+𝐸𝐸+𝐹𝐹 - 𝐱,6𝐱𝐶− 𝐱,7𝐱𝐷−𝐲,3𝐲𝐳−𝐶,7𝐶𝐷−𝐶,8𝐶𝐸−𝐸,9𝐸𝐹 ≤ 20 xj = 0, 1 The BCRj, and 𝐵 are available from Figure 4. 𝔎𝐠𝐵𝐵𝐠𝐵𝐠𝐵𝐠has been found earlier in the section (where?) refer to equation or parameter. The available budget B is 20 million BDT (obtained from the case company). The results of the optimization problem are shown in Table 10 along with the sensitivity analyses on the available budget. With the available budget of 20 million BDT it is observed that Strategies ST1, ST2, ST4, ST5, ST6, and ST7 are selected with a total BCR of 65.67. The sensitive analyses show that when the budget is increased to 30 million BDT all strategies are selected. (insert Table 10 about here) The management of the case company wanted to implement strategies ST1, ST2 and ST3 (see Table 6) as a matter of policy. We therefore added extra constraints to the above model and ran the optimization model again. Table 11 shows the results. For the 20 million BDT budget strategies ST8 and ST9 still remain unselected. Strategy ST4 is also not selected. Again the sensitivity analyses show12 that all the strategies are selected when the budget is increased to 30 million BDT. Implications of these results will be discussed next. (insert Table 11 about here) 5. Discussions and Implications Consistent with the motivation for this research, ten sustainability requirements (WHATs) have been identified (Table 6) which are also consistent with previous literature as shown in Table 1. Corresponding to the ten sustainability requirements nine Strategies (HOWs) have been identified from the case company. These strategies have been prioritized and optimized under a budget constraint using the Fuzzy QFD methodology. We split the Fuzzy QFD methodology into three phases. The results in the previous sections show outcomes of the three QFD phases. We now deliberate on the outcomes to show the implications of the results. The outcome of phase 1 produced Table 6 which shows the sustainability requirements (SRs or WHATs in QFD terminology) and corresponding Strategies (STs or HOWs in QFD terminology) to support the sustainability requirements. It is observed that there are five sustainability requirements under ‘social’, two requirements under ‘environmental’ two under ‘operational’ and one under ‘economic’ sustainability requirement. This shows that apparel manufacturers in Bangladesh are mostly concerned with the social aspects of the sustainability requirements. This is in line with the existing literature (Martin 2013; Naeem and Welford 2009; Islam and Deegan 2008 and Ahmed and Peerlings 2009). It is observed that four strategies (ST1, ST2, ST3, and ST7) have been identified to deal with the employees, while the remaining five strategies (ST4, ST5, ST6, and ST8, and ST9) address the operational aspects of the companies. This is an interesting finding as it shows that the companies are taking a balanced approach in strategies to support the sustainability requirements despite the fact that most of their concerns are ‘social’ type. The outcome of Phase 2 of our analysis produced the importance ratings (weights) of the sustainability requirements (WHATs) and the absolute (and relative) importance of the strategies (HOWs) by using fuzzy set theory. All these results are summarized in Figure 4 which we call supply chain sustainability model. As par the crisp values of the absolute importance (AI) it is observed that all the strategies related to employees are highly ranked (ST1, ST2, ST3 and ST7) compared to the company related strategies (ST4, ST5, ST6, and ST8, and ST9). In fact, ST8 (efficient machinery) and ST9 (recycling etc.) are ranked very low. This highlights that the case company is dedicated to resolve the employee related (social) concerns with high priorities. However, taking the cost of implementation into consideration the ranks change dramatically. Thus, looking into the benefit-costratio (BCR) the top four strategies are ST2 (sustainability awareness program: employee related) (Belal and Cooper, 2011; Hossain, Rowe and Quaddus, 2012), ST5 (supplier evaluation: company related) (Caniato et al., 2012; Bai and Sarkis, 2010), ST7 (training and development: employee related) (Hossan, Sarker and Afroze, 2012; Abdullah, 2005) and ST4 (social & environmental audit report: company related) (Belal and Cooper, 2011; Hossain, Rowe and Quaddus, 2012). It is also observed that the lowest two strategies in terms of BCR are company related (ST6 and ST9). From the BCRs it is also revealed that sustainability awareness program, training and development of employees as well as supplier evaluation (ST5) (Caniato et al., 2012; Bai and Sarkis, 2010), training and monitoring (ST5) (Hossan, Sarker and Afroze, 2012; Abdullah, 2005) involve low cost in comparison to the benefits derived thus they have a higher BCR. Though HR policy regarding payments and benefits of the workers as well as hazard and safety factors have high cost of implementation they have high contribution to sustainability requirements. Therefore, these factors should be implemented by the company gradually because buyers will not buy products from the companies without ensuring these factors. These results should be an eye opener for the company in terms of their priorities of actions.13 Phase 3 of our analyses produced the relationship between the strategies (STs) and eventually optimal strategies to be implemented in order to maximize the total BCR under a budget constraint. It is noted that relationships between the STs were evaluated in terms of overlaps between the strategies and they all came out to be positively overlapped. Roof of Figure 4 shows the positive relationship among the strategies. However, in theory it is possible to have negatively overlapped strategies, i.e., implementation of a strategy can diminish the effect of another strategy (Pagell and Gobeli 2009; Wu and Pagell 2011). This area needs further quantitative research and evidence. The optimization results are shown in Tables 10 and 11. Table 10 shows that with the budget of 20 million BDT the strategies ST1, ST2, ST4, ST5, ST6, and ST7 are selected with a total BCR of 65.67. This is a balanced result with three employee related (ST1, ST2, ST7) and three company related (ST4, ST5, ST6) strategies being selected. Result changes slightly with a tighter budget of 15 million BDT. However, total BCR reduces drastically to 54.57. On the other hand, when the budget increases to at least 30 million BDT all the strategies are selected with an optimized total BCR of 84.39. Table 11 shows the results of optimization when the management decided to implement ST1, ST2 and ST3 (all employees related) as a matter of policy. Comparing the results of Table 10 and 11 it is evident that the total BCRs are very similar for all the budget limits. Hence, it is revealed that for this case company the management leadership is able to implement their specific policy of implementing some chosen strategies without much sacrificing the total BCR. This is an interesting finding with respect to this case company. From the above discussions it can be summarized that by following our approach organizations are able to prioritize and implement optimal strategies to ensure supply chain sustainability by meeting the stakeholders’ sustainability requirements effectively and efficiently. Organizations and their supply chains can also implement some specific strategies/policies and they should try to increase their budgets to improve the overall sustainability performance. 5.1 Theoretical implications Theoretical implications of this study lies in four aspects: (i) Relying on stakeholder theory and dynamic capability view this paper is instrumental in presenting a model of supply chain sustainability in the context of low cost country sourcing which is a unique contribution in supply chain sustainability literature; (ii) it shows that fuzzy QFD approach can be used effectively to meet the supply chain sustainability requirements of the stakeholders in the context of low cost country sourcing; (iii) it is possible to elicit various sustainability requirements and prioritize them thus educating the management in terms of what is feasible and optimal to implement; and (iii) it is also possible to expound the complementariness in strategies so as to enable the management to leverage them and implement different kind of strategies simultaneously within limits. Our study also shows how stakeholder theory (Freeman 1984) is significant in dealing with the sustainability requirements of the diversified stakeholders. Our various sustainability requirements (Table 6) support the conflicting nature of the stakeholders’ demands. The strategies in Table 6 (and their implementation) also confirm the need for organizations’ dynamic capability to meet the changing requirements of the stakeholders. Further, the optimization of strategies shows that organizations need to select the best strategies to implement the sustainability strategies with in the resource constraint as resource shortage is one of the major barriers to implement sustainability strategies (Ageron et al. 2012; Muduli and Barve 2012; Arevalo and Aravind 2011; Welford and Frost 2006).14 5.2 Managerial implications In terms of the managerial implications, the supply chain sustainability model shows the various important sustainability requirements of the stakeholders and the corresponding strategies for ensuring sustainability in the apparel industry of Bangladesh. It will help the apparel managers, government and other stakeholders to identify the prioritized sustainability requirements of the stakeholders, identifying, prioritising and implementing the relevant strategies and processes to meet the requirements in apparel industry. It is critical for the decision makers to take optimal decision in the situation of scarce resources and consider various scenarios. This model will therefore help them to decide and implement the best strategies within the limited budgets and resources. 6. Conclusions This research has several important contributions. Firstly, it identifies the sustainability requirements of the apparel industry stakeholders and the corresponding strategies to support the requirements. Secondly, it helps to identify the prioritised sustainability requirements and prioritised strategies. Thirdly, it identifies the optimal strategies under a budget constraint. Fourthly, it conducts a sensitivity analysis to understand what happens if the budget is changed. Finally, drawing on stakeholder theory and dynamic capability view the supply chain sustainability model developed in this study is unique in its application in the context of low cost country sourcing. This model is of tremendous value for the supply chain managers in identifying the sustainability requirements of the stakeholders and arms these managers with a model that is instrumental in designing optimal strategies to meet the requirements in the context of sourcing from low cost countries. It offers some food for thought for the management of the case company in terms of improving their supply chain sustainability performance. This study has some limitations which open ups opportunities for further research. The quantitative case study is conducted with a single company (albeit being a very large company) as the detailed data for QFD methodology are extremely demanding to collect. A replication of the study in another contrasting company will be ideal. Further research can also be done in terms of identifying the conflicting strategies to support the sustainability requirements which will result in negative complementariness in strategy implementation. 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Human rights Islam and Deegan 2008; Knutsen 2004. Restricting child labour and force labour Islam and Deegan, 2008; Emmelhainz, 1999. Water pollution Knutsen 2004; Gripsrud, et al. 2006; Epstein and Wisner, 2001 Air pollution GRI; Epstein and Wisner, 2001 Soil pollution GRI Recycling wastes Epstein and Wisner, 2001 Product safety and restricting the use of Hazardous material Islam and Deegan, 2008; Gripsrud, Jahre et al. 2006; Epstein and Wisner, 2001. Complying environmental legislation GRI; Cooper and Ellram, 1993. Sales and business volume GRI; Cooper and Ellram, 1993. Cost GRI Profit/net income GRI Sales growth Epstein and Wisner, 2001 Delivery lead time Bateman and David, 2002; Hadjikhani, 2005. Quality Bateman and David, 2002; Epstein and Wisner, 2001 Meeting quality, cost and other specification Lummus et al. 2005 Efficient and Updated Machinery and technology Drake and Spinler, 2013; Aragón-Correa and Sharma, 2003 Monitoring the social Performance of suppliers Knutsen, 2004; Epstein and Wisner, 2001 Social and Environmental certification and audit Emmelhainz, 1999; Giunipero et al. 2008. Table 2: Processes of meeting sustainability compliance Processes of meeting sustainability Literature Enhancing regulatory framework Belal and Cooper, 2011; Hossain, Rowe et al. 2012; Rowe and Guthrie, 2010; Imam, 2000; Lodhia, 2003. Creating awareness and knowledge regarding sustainability Belal and Cooper, 2011; Hossain, Rowe and Quaddus, 2012; Cooper and Ellram, 1993. Developing written policy Nayeem and Welford, 2008; Lo and Sheu, 2007. Setting sustainability strategy Nayeem and Welford, 2008; Brito et al., 2008; Lo and Sheu, 2007. Need for investment and resources Hahn and Scheermesser, 2006; Maximiano, 2005. Training and development Hossan, Sarker and Afroze, 2012; Abdullah, 2005. Participative management system Hossan, Sarker and Afroze, 2012 Monitoring and auditing Emmelhainz, 1999; Chowdhury et al., 2012. Social and environmental reporting Belal and Cooper, 2011; Hossain, Rowe and Quaddus, 2012 Environmental certification of suppliers Caniato et al., 2012; Chowdhury et al., 2012. Supplier evaluation and selection Caniato et al., 2012; Bai and Sarkis, 2010 Table 3: Overall research design Phases Research Objectives Data collection Data analysis Phase 1 Identifying the supply chain sustainability (SCS) requirements of the stakeholders and the corresponding strategies to address the requirements. Literature regarding sustainability requirements, compliance and the process of meeting sustainability. Semi-structured questionnaire to collect data regarding sustainability requirements and mitigation approaches of seven case companies. Content analysis of literature search and analysis of data from field study Phase 2 Prioritizing the SCS requirements and the SSC strategies. Developing the priorities of each of the SCS requirements and SSC strategies based on the data of a single large case company (MN garments) Triangular Fuzzy set is used to determine the priority of each SCS requirement. Then FuzzyQFD is used to determine the priority of each SSC strategy. Phase 3 Determining the optimal SCS strategies under a budget constraint. Selecting the optimal SSC strategies based on the benefit and cost data of the single case company. QFD analysis and optimization of benefit-cost data by using nonlinear integer goal programming. Population for project Ready- made garments industry of Bangladesh Sample for qualitative study Seven companies consisting of garments manufacturers, supplier of accessories, Buying agents. Case Company A large Garment manufacturing company ‘A’ (for quantitative data and analysis)22 Table 4: The stepwise research process adopted in our study QFD Phase 1 Step 1 Identify the sustainability requirements (WHATs) of Apparel supply chain stakeholders. Step 2 Identify Strategies/design requirements (HOWs) to support the sustainability requirements. QFD Phase 2 Step 3 Determine the relative importance ratings (weights) of WHATs by using the Fuzzy set theory. Step 4 Determine the relationships between WHATs and HOWs using QFD methodology. Step 5 Determine the absolute importance and relative importance of HOWs weighted by the weights of the sustainability requirements (WHATs) found in step 3. QFD Phase 3 Step 6 Find the correlation between the strategies (HOWs) to determine the cost savings as a result of joint implementation of the correlated HOWs Step 7 Determine the Benefit-cost ratio of the strategies (HOWs). Step 8 Use non-linear optimization model to determine the optimal strategies (HOWs) within the limited budget. Table 5: Participants Description Participant Position Type of the company Company size (no of employees) Age of the company D1 General Manager Garment manufacturer 2000-3000 20-25 years D2 Manager Merchandising Buying agent 10-20 Less than 5 years D3 Supply chain manager Garment manufacturer More than 4000 5-10 years D4 Deputy General manager Accessory supplier Less than 1000 15-20 years D5 Deputy General manager Accessory supplier Less than 1000 10-15 years D6 Manager Merchandising Garment manufacturer 3000-4000 20-25 years D7 Supply chain manager Garment manufacturer More than 10000 20-25 years Table 6: Summary of Sustainability requirements and the Strategies Sustainability requirements (SR) Companies Social 1 2 3 4 5 6 7 Ensuring fair payments (SR1) y y y y y Ensuring benefits (SR2) y y y y y Ensuring health and Safety factors (SR3) y y y y y y Restricting child labour in organization (SR4) y y y y y y y Restricting force labour and harassment (SR5) y y y y Environmental Environment and health hazard free ingredient in product (SR6) y y y y y y y Reducing environmental impact and improving efficiency (SR7) y y y y y Operational Quality (SR8) y y y y y Lead time (SR9) y y y y y y y Economic Cost/competitive price (SR10) y y y y y y y Strategies (ST) Improving human resource (HR) policy regarding workers benefits (leave benefit, medical benefit, child care facility, transportation facility) (ST1) y y y y y Undertaking sustainability awareness programs (promoting and communicating sustainability to all employees, training, counsellingn and workshop on sustainability issues) (ST2) y y y y Developing health and safety by improving the existing condition of number of exit door, fire equipments, clean drinking water, adequate toilet. (ST3) y y y y y Preparing social and environmental audit report (conducting both internal and external audit) (ST4) y y y y y y Supplier evaluation, training and development (ST5) y y y y Reducing defection rate, quality control and lab testing during receiving material and shipment of products (ST6) y y y y y Training and development (skill development programs) (ST7) y y y y y Installing efficient machinery and technology (ST8) y y y Recycling, reusing and treatment of wastes (ST9) y y y y y y23 Table 7: Fuzzy importance ratings of sustainability requirements (WHATs) Sustainability Requirements (SR)/WHATs DM1 DM2 DM3 SR1 (Ensuring fair payments) VH VH H SR2 (Ensuring benefits) H VH H SR3 (Ensuring health and Safety factors) VH VH H SR4 (Restricting child labour in organization) VH VH VH SR5 (Restricting force labour and harassment) H H VH SR6 (Environment and health hazard free ingredient in product) VH VH VH SR7 (Reducing environmental impact and improving efficiency) H VH H SR8 (Quality) VH VH VH SR9 (Lead Time) VH VH H SR10 (Cost competitiveness) H H VH Table 8: Defuzzified and aggregate importance ratings of sustainability requirements (WHATs) WHATs xα xβ xϒ SR1 (Ensuring fair payments) 7.33 8.33 9.33 SR2 (Ensuring benefits) 6.67 7.67 8.67 SR3 (Ensuring health and Safety factors) 7.33 8.33 9.33 SR4 (Restricting child labour in organization) 8 9 10 SR5 (Restricting force labour and harassment) 6.67 7.67 8.67 SR6 (Environment and health hazard free ingredient in product) 8 9 10 SR7 (Reducing environmental impact and improving efficiency) 6.67 7.67 8.67 SR8 (Quality) 8 9 10 SR9 (Lead Time) 7.33 8.33 9.33 SR10 (Cost competitiveness) 6.67 7.67 8.67 Table 9: Correlation between the sustainability requirements (WHATs) and the strategies (HOWs) SR1 H H VH M M H H H VH M M H L L M VL VL L VL L L VL VL L VL VL L SR2 H VH VH M M H M M H M M H L L M VL VL L VL VL L VL VL L VL VL L SR3 M M H M H H H VH VH M M H M M H L L M H H VH L L M VL VL L SR4 H VH VH H H VH H VH VH H H VH M H H VL VL L VL VL L VL VL L VL VL L SR5 M H H M M H M H H L M M L L M VL VL L VL VL L VL VL L VL VL L SR6 L L M L M M M H H M M H M H H H VH VH M H H M M H VL VL L SR7 VL L L M M H M M H H H VH M M H VL L L M M H M H H H VH VH SR8 M M H L L M VL L L VL VL L M M H H VH VH H VH VH H VH VH L VL VL SR9 M H H VL L L VL VL L VL VL L L L M VL VL L M H H M H H L VL VL SR10 VL VL L L M M VL VL L VL VL L L L M L L M H VH VH M H H L L M ST1 ST2 ST3 ST4 ST5 ST6 ST7 ST8 ST9 Table 10: Optimization results with sensitivity analysis on Budget x1 x2 x3 x4 x5 x6 x7 x8 x9 BCR Budget 1 1 0 0 1 1 1 0 0 54.57 15 1 1 0 1 1 1 1 0 0 65.67 20 1 1 1 1 1 1 1 1 0 81.33 25 1 1 1 1 1 1 1 1 1 84.39 30 1 1 1 1 1 1 1 1 1 84.39 35 Table 11: Optimization results with sensitivity analysis on Budget when ST1, ST2, and ST3 are fixed x1 x2 x3 x4 x5 x6 x7 x8 x9 BCR Budget 1 1 1 0 0 1 1 0 0 51.01 15 1 1 1 0 1 1 1 0 0 64.09 20 1 1 1 1 1 1 1 1 0 81.33 25 1 1 1 1 1 1 1 1 1 84.39 30 1 1 1 1 1 1 1 1 1 84.39 3524 Figure 2. QFD model Note: 𝐵𝐠= Customer requirements; 𝐵 = Degree of importance of CRi’s; 𝐵𝐠= Design Requirements/strategies; 𝐵𝐠= Relationship Matrix (i.e. degree to which CRi is met by DRj) A.I.= Absolute importance of DRj’s ; R.I.= Relative importance of DRj’s/strategies. 𝐵(𝐩 0 1 2 3 4 5 6 7 8 9 10 VL L M H VH Degree of Membership Figure 3. Triangular fuzzy membership function of the importance rating (as par Bevilacqua et al. 2006)25  Legends = Strong = Medium ∆ = Weak ∆ ∆    ∆ ∆ ∆    Figure 4. Supply chain sustainability (SCS) model