The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/0957-4093.htm Green warehousing, logistics optimization, social values and ethics and economic performance: the role of supply chain sustainability Yaw Agyabeng-Mensah Transportation Engineering College, Dalian Maritime University, Dalian, China Esther Ahenkorah The role of supply chain sustainability Received 19 October 2019 Revised 25 January 2020 14 March 2020 21 April 2020 14 June 2020 Accepted 30 June 2020 Regent University College of Science and Technology, Accra, Ghana Ebenezer Afum Transportation Engineering College, Dalian Maritime University, Dalian, China Essel Dacosta Dalian Maritime University, Dalian, China, and Zhongxing Tian Transportation Engineering College, Dalian Maritime University, Dalian, China Abstract Purpose – This study primarily explores the influence of green warehousing, logistics optimization and social values and ethics on supply chain sustainability and economic performance. The study further examines the mediating role of supply chain sustainability between economic performance and green warehousing, logistics optimization and social values and ethics. Design/methodology/approach – The study employs a quantitative research approach where survey data are collected from 200 managers of manufacturing companies in Ghana. The dataset is analyzed using partial least square structural equation modeling software (PLS-SEM) SmartPLS 3. Findings – The results show that green warehousing and logistics optimization negatively influence economic performance but improves economic performance through supply chain sustainability. It is further discovered that social values and ethics have a positive influence on supply chain sustainability and economic performance. Originality/value – This paper proposes and tests a theoretical model that explores the relationships between green warehousing, supply chain sustainability, economic performance, logistics optimization and social values and ethics through the resource dependency theory (RDT) in the manufacturing firms in Ghana. Keywords Supply chain sustainability, Green warehousing, Logistics optimization, Social values and ethics, Performance, Resource dependency theory Paper type Research paper 1. Introduction Supply chain activities of firms have led to environmental pollution, global warming and climate change and termination of human lives through the emission of greenhouse gases, improper waste management, production of non-biodegradable products, the inappropriate keeping of hazardous and explosive substances and excessive use of resources (Khan, 2019; Dekker, 2012; Feng et al., 2018; Khan et al., 2018). Firms are adopting green and social practices into their supply chain to reduce the impact of their activities on the environment, ensure societal safety, improve efficiency, gain competitive advantage, meet stakeholders’ demand and access new markets (Agyabeng-Mensah et al., 2020a, b, c, d). These socially and The International Journal of Logistics Management © Emerald Publishing Limited 0957-4093 DOI 10.1108/IJLM-10-2019-0275 IJLM environmentally inclined practices are adopted to ensure the safety and welfare of employees and other needs of stakeholders through less emission of greenhouses gases, waste reduction and resource and energy consumption (Longoni et al., 2018; Khan et al., 2018; Zaid et al., 2018). Nonetheless, the implementation of these socially and environmentally friendly practices face challenges due to their confusing and inconsistent influence on sustainability performance (Zaid et al., 2018; Adomako et al., 2019; Green et al., 2019a, b; AgyabengMensah et al., 2020a, b, c, d). Many studies have been conducted into the relationship between green practices and environmental conservation (Nilsson, 2013; Gotschol et al., 2014), continuous improvement (Carrizo-Moreira, 2014), financial performance (Liu et al., 2012; Sarkis et al., 2011) and social performance (Zaid et al., 2018; Agyabeng-Mensah et al., 2020a, b, c, d). Agyabeng-Mensah et al. (2020a, b, c, d) and Baah et al. (2020) found a positive relationship between green logistics practices and financial performance. Green et al. (2019a, b) suggest that green and lean practices combine to advance environmental sustainability among manufacturing firms in the US. Zaid et al. (2018) established a positive relationship between green practices and sustainability performance among Palestinian manufacturing firms. Longoni et al. (2018) discovered that green practices improve financial performance among firms in Italy, while Feng et al. (2018), which was conducted in the Chinese automobile manufacturing companies, found that green supply chain practices harm sales, profit margin and return on assets. Despite the extensive studies into green practices, scholars continue to root for more studies into the potency of green practices in the achievement of supply chain sustainability. Dubey et al. (2017a, b) and Tseng et al. (2019) further established that there is relatively less sustainability literature from the emerging economy perspective especially, in Africa. Besides, Eriksson et al. (2015) urge future studies to look into the role of social values and ethics and moral responsibility in supply chain sustainability. Moreover, Bartolini et al. (2019) suggest that there is inadequate literature, which considers green warehousing as a standalone variable. The aforementioned gaps have motivated us to conduct this study to advance the course of sustainability literature and practice. The study uses the resource dependency theory (RDT) to explore the influence of logistics optimization, green warehousing, social values and ethics on supply chain sustainability and economic performance. Further, the paper explores the indirect influence of logistics optimization, social values and ethics and green warehousing on economic performance through supply chain sustainability. This leads us to answer the research questions; (1) Do logistics optimization, green warehousing and social values and ethics directly influence supply chain sustainability and economic performance? (2) Does supply chain sustainability mediate the relationship between logistics optimization, social values and ethics, green warehousing and economic performance? The study will deepen the understanding of green supply chain practices from the developing economy’s perspective to strike a balance between literature since this study responds to the call from the social and green supply chain management literature (Eriksson et al., 2015; Dubey et al., 2017a, b; Tseng et al., 2019) to conduct empirical studies into the constructs used in this research. The study’s empirical model will serve as a blueprint for future study since it is among the few, if not the first empirical study that tests the link between green warehousing, social values and ethics, logistics optimization, supply chain sustainability and economic performance. Besides, it will provide evidence for practitioners to push for green supply chain practices as a strategy for achieving sustainability objectives. The first part of the study contains the introduction. The literature review forms the second part while research design, data analysis, results and discussion and conclusion form the third, fourth and fifth sections, respectively. 2. Literature review 2.1 Resource dependency theory (RDT) RDT is one of the strategic theories that received attention through the work of Salancik and Pfeffer (1978). RDT was not originally developed as a profit seeking theory. However, the theory has been developed to include profit seeking objective which is congruent with organizational economics-based approaches and is capable of explicating the differences between performances (e.g. Pfeffer, 2005; Villalonga and McGahan, 2005). RDT posits that naturally, firms do not have adequate resource to implement their strategies and plans individually to achieve expected performance outcome. Hence it is imperative for them to partner with other supply chain members to obtain adequate and needed resource (Pfeffer and Salancik, 2003) for sustainable development (Ulrich and Barney, 1984). The RDT suggests that there is the need for interdependence among firms in order to obtain sufficient resource to sustain growth among themselves (Salancik and Pfeffer, 1978). This reflects the postion of the RDT, which indicates that firms cannot claim full self-sufficiency regarding critical resources. The RDT proposes a collaboration among firms in a supply chain in order to achieve higher performance gains. Green warehousing, logistics optimization and social values and ethics are typical resources needing the collective efforts of supply chain partners for effective implementation to improve performance benefits (Shang et al., 2010; Zhu et al., 2005). According to Sarkis et al. (2011), the role of the quality and effectiveness of supply chain collaboration in the implementation of sustainable/green supply chain management practices should not be undermined. Collaboration with supply chain partners can be properly managed and developed into relationship-specific assets to serve as sources of competitive advantage. The RDT calls for proper relationship between a focal firm and its suppliers and customers to reduce the environmental uncertainty around the operations of the firm (Carter and Rogers, 2008; Cao et al., 2010). Zhu et al. (2005) suggest that collaboration among supply chain partners is essential for internal and external coordinations for effective implementation of sustainable supply chain practices (green warehousing, social values and ethics and logistics optimization) to achieve expected performance results. The RDT posits that firms that have power within the supply can advance the course of spreading sustainable supply chain management practices among supply chain members. Gonzalez et al. (2008) established that larger firms with superior powers in the supply chain will expect their small supplier firms to adopt socially, ethically and environmentally sound practices to achieve sustainable development goals. This study adopts the RDT to explicate the role of adopting sustainable/green supply chain management practices such as green warehousing, logistics optimization and social values and ethics in performance improvement among manufacturing firms in Ghana. 2.2 Development of hypotheses 2.2.1 Green warehousing and supply chain sustainability. Warehousing is one of the critical activities of in-house and outbound logistics and distribution. According to McKinnon (2010), warehousing and goods handling contribute to 2–3 percent of energy-related CO2 emissions worldwide. Abushaikha (2018) and Gu et al. (2016) suggest that warehouses may serve as a source of non-value added activities due to the numerous activities associated with its operation. Warehousing activities produce enormous waste in the supply chain, which require the adoption of practices and policies that reduce waste to eliminate their adverse impact on the environment and human lives (Abushaikha, 2018). Again, warehousing activities especially, where hazardous substances are kept pose several risks to the safety of The role of supply chain sustainability IJLM the environment and health of the employees in situations where employees’ knowledge is limited and proper labeling practices are not adopted. Warehousing activities such as movement of vehicles from one warehouse to the other also increase the carbon dioxide emission in the environment. This shows that warehousing is an area of logistics that requires serious attention from firms undertaking supply chain sustainability projects to meet the requirements of stakeholders and gain competitive advantage (Abushaikha, 2018). Several scholars (Yildiz Çankaya and Sezen, 2019; Colicchia et al., 2011) have realized the importance of warehouse sustainability and suggested the usage of green energy sources and strategies as well as the adoption of energy-efficient handling technologies to manage the warehouse and its related issues. According to Tan et al. (2009), firms should adopt information technology such as iThink, which is useful for forming dynamic connections among social, environmental and economic issues. Green packaging which includes using green packaging materials, cooperating with sellers to ensure standardization of packaging, reducing material usage and unpacking time, adopting returnable packaging methods and promoting recycling and reuse programs (Ninlawan et al., 2010) improves sustainability in the warehouse. The use of recyclable and biodegradable materials for repackaging of products in the warehouses may ensure environmental sustainability. Besides, green packaging may reduce the use of materials and optimize the use of space within the warehouse to ensure efficiency. According to Harris et al. (2014), firms that aim at improving supply chain sustainability and economic performance may adopt proper warehouse management system. Space maximization and just-in-time (JIT) are essential to green warehousing (Tan et al., 2009). JIT aims at reducing inventory costs and waste using less storage and warehouse space (Green et al., 2019a, b). Moveover, according to Agyabeng-Mensah et al. (2020a, b, c, d), JIT reduces overhead cost and consumption of resources through proper inventory management. Wu and Dunn (1995) suggest that proper use of storage area, reduction of retrieval cost and energy usage are vital goals of green warehousing. Wang et al. (2015) highlight the relevance of recycling facilities in promoting green warehousing to advance supply chain sustainability. Green warehousing requires the collaborative effort of supply chain members in order to achieve the expected sustainability performance outcome. The effort of suppliers is required in ensuring that green materials are provided to promote green warehousing activities. Hence, from the RDT perspective, we hypothesize that; H1. Green warehousing has a significant positive influence on supply chain sustainability. 2.2.2 Logistics optimization and supply chain sustainability. Logistics activities form a significant part of supply chain activities. Generally, the nature of logistics activities makes them environmentally unfriendly. Logistics activities such as transportation contribute hugely to environmental pollution and the greenhouse effect (Khan, 2019). Khan et al. (2007) argued that freight transport contributes about 8% of the world’s energy-related CO2 emissions. In the road transport sector, the amount of energy used to move freight is increasing at a faster rate due to high demand for goods and services, which has resulted in the emission of greenhouse gases that are harmful to human health and pollute the environment (Hishan et al., 2019). This is an indication that logistics activities have undesirable effect on the environment and human lives. There is a need to optimize logistics activities to reduce adverse environmental impact and ensure environmental sustainability (Agyabeng-Mensah et al., 2020a, b, c, d). Logistics optimization involves the implementation of reverse logistics practice, collaboration and the use of clean fuel to considerably control environmental effect of the operations of an organization (Neto et al., 2008; Boix et al., 2015). In other words, logistics optimization involves the adoption of practices that green the supply chain operations to reduce externalities and enhance profitability. According to Halldorsson and Kovacs (2010), there is the need to develop and implement energy-efficient logistics practices and supply chain systems to reduce global carbon footprint through the adoption of clean fuel and proper routing systems. Firms have to optimize their routes and use clean fuels to ensure the reduction of pollution that harms human lives (Khan, 2019). Tang et al. (2016) argue that firms must locate their warehouses closer to consumers to reduce the long traveling distances, which leads to the reduction of carbon emissions. Further, Tang et al. (2016) suggest that companies may build their warehouses in places that ensure the use of alternative ecofriendly transportation modes to advance supply chain sustainability. According to Dowlatshahi (2000) and Gonzalez-Torre et al. (2004), the development of reverse logistics channels decreases the usage of resources, and improves recycling and reuse of products leading to improvement in the achievement of supply chain sustainability objectives. Reverse logistics is a concept that involves reclaiming, inspecting/ selecting/sorting, re-processing/direct recovering and redistributing products to retrieve value (Hansen et al., 2018). Firms, which employ reverse logistics, reduce the impact of their products on the environment while ensuring that several people are hired into the supply chain (Baah, 2019). Logistics collaboration involves bringing together supply chain partners to set congruent goals and map strategies to achieve the strategies through information and resource sharing. Agyabeng-Mensah et al.(2020a, b, c, d) found that green logistics practices have positive influence on environmental and social performances. Firms may be required to share resources and skills with supply chain partners to implement green policies to achieve environmental and social sustainability goals. Based on the literature review, it could be established that collaborative efforts from suppliers and customers are essential for proper implementation of logistics optimization to significantly advance supply chain sustainability. Thus, through the RDT, we hypothesize that; H2. Logistics optimization has a significant positive influence on supply chain sustainability. 2.2.3 Social values and ethics and supply chain sustainability. Dubey et al. (2017a, b) posit that in recent times, scholars have given considerable attention to the role of social values and ethics in sustainable development and have hugely debated the topic. Ethical theories are founded on ideologies that demonstrate what is right or the need to build a good society” (Garriga and Mele, 2004, p. 60). Social values and ethics comprise the practice of engaging in morally and socially acceptable activities to enhance supply chain sustainability. According to Gunasekaran and Spalanzani (2012), the successful implementation of social value and ethics ensures the welfare and safety of community members and employees. Cantor et al. (2012) argue that corporate sustainability programs require the management of firms to motivate employees by getting them involved in the business processes to comprehend the prime matters of the firm and embrace the newly carved visions of the firm. Scholars such as Drake and Schlachter (2008) and Muller (2009) argue that ethical sourcing and purchasing lead to improved environmental performance. Ethical purchasing involves the buying of harmless goods and inputs from suppliers who are ethically sound. Ethical purchasing may ensure that the best practices in sourcing are obeyed to safeguard the environment and human lives through the selection and buying of new products and raw materials from suppliers whose activities are not detrimental to human lives and the environment. According to Beamon (2005), engineering ethics significantly contributes to the design and development of an ecofriendly supply chain. Chiou et al. (2011) argue that green purchasing and eco-innovation improve green competitiveness and performance. Studies indicate that firms can improve their environmental performance when they collaborate on adopting green practices that offer win-win opportunities with their stakeholders (customers) (Zhu et al., 2017). Thus, through the RDT, we hypothesize that; H3. Social values and ethics have a significant positive influence on supply chain sustainability. The role of supply chain sustainability IJLM 2.2.4 Logistics optimization and economic performance. Performance is the measure of the outcome of the combination of an organization’s process, strategies and resources to achieve organizational goals. Performance improvement is key to the survival of every firm (Agyabeng-Mensah et al., 2019a, b, c). Performances are measured to know how effectively they have employed shareholders’ funds entrusted into their care for the benefit of all stakeholders. Performance of a firm has been measured from several perspectives. According to Agyabeng-Mensah et al. (2019a, b, c) performance involves financial and non-financial outcomes of application of business processes, activities, policies, capabilities and resources. Several variables contribute to the performance of firms, especially economic performance (Baah and Jin, 2019), which is applied in this study. Economic performance is the outcome of the combination of resources, policies and capabilities of firms to achieve operational, marketing and financial performances through the fusion of social and green practices into the firms’ supply chain operations. Logistics activities contribute significantly to the cost of operation, which may negatively affect economic performance (Agyabeng-Mensah et al., 2020a, b, c, d). Fuel cost, transportation cost, legal fees relating to the violation of regulations, buying of carbon emission cards, waste of resources and excessive use of fuel contribute to the enormous logistics cost that has a massive impact on economic performance (Simper et al., 2019; Agyabeng-Mensah et al., 2020a, b, c, d). However, logistics activities could serve as economic performance booster when they are effectively managed (Agyabeng-Mensah et al., 2020a, b, c, d). There is a need for firms to ensure that logistics optimization enhances logistics efficiency and improves economic performance (Niknejad and Petrovic, 2014; Garetti and Taisch, 2012). Organizations may collaborate with supply chain members to undertake risky and costly green and social projects that may project the image of the firm to attract new customers to enhance economic performance (Agyabeng-Mensah et al., 2020a, b, c, d). Zaid et al. (2018) suggest that a firm’s collaboration with its supply chain partners may enhance economic performance. Besides, logistics optimization activities such as reverse logistics practices help firms to meet the environmental regulatory requirements and stakeholder pressures, demanding firms to save money through the elimination of costs associated with fines and legal battles (Agyabeng-Mensah et al., 2020a, b, c, d; Baah, 2019). Stakeholders are ready to pay more for the goods of companies that are ecofriendly, leading to improved profitability (Green et al., 2019a, b). Thus, we develop the hypothesis, H4. Logistics optimization has a significant positive influence on economic performance. 2.2.5 Green warehousing and economic performance. Several firms carry out green activities with the aim of improving the economic performance of firms and reducing environmental impact (Feng et al., 2018; Baah and Jin, 2019). According to Coyle et al. (2013) and Amemba et al. (2013), green warehousing involves using minimum energy and maximizing space usage to reduce cost and ensure efficiency to enhance economic performance. Besides, green warehousing involves the use of pollution-free energy, which may save firms the cost of environmental fines. Moreover, warehouses built with high-energy performance certificates consume less energy to reduce energy cost and advance profitability (Indrawati et al., 2018). Further, green warehousing may eliminate the cost of pollution control through zero production of waste and emission, which may translate into improved economic performance. Again, green activities that deal with lighting, air tightness and thermal insulation in the warehouses ensure a reduction in energy consumption. According to Cox and Graham (2010), green warehousing provides optimal use of capacity to increase profitability. Green warehousing activities like any other green supply chain practices are acknowledged as an efficient and broad approach to achieving higher operational performance (Wong et al., 2012; Zailani et al., 2012; Zhu et al., 2008). The use of green technologies in warehouses may result in less waste management and improve process quality, which creates ability for firms to respond to changes in customers’ demand leading to improved sales and profitability. Customers perceive greener products as goods of better quality, which leads to an increase in the market share of the firm through customer satisfaction and loyalty (Baah, 2019). Torabizadeh et al. (2020) suggest that the introduction of green practices into supply chain activities such as warehousing has a positive influence on economic performance. Ecologically responsible behavior mitigates risk and, subsequently, enhances economic performance (Zhang and Chen, 2017). We hypothesize that; H5. Green warehousing has a significant positive influence on economic performance. 2.2.6 Green warehousing, logistics optimization, social values and ethics, supply chain sustainability and economic performance. Sustainability is a ubiquitous word used across all the critical functions of firms (Zaid et al., 2018) and among scholars in supply chain. Soytas et al. (2019) indicate that the adoption of sustainable development principles may necessitate changes in operations and policies of firms to be able to remove adverse social and environmental effects. The study defines supply chain sustainability as the measurement of positive influence of social policies and green practices on energy and resource conservation and protection of the environment. This means that supply chain sustainability covers environmental and social performances in this study. According to Feng et al. (2018), green practices positively influence environmental performance leading to low cost of operation, low price of goods and increased market size, sales, net profit margin and return on investment among Chinese automobile manufacturing firms. Longoni et al. (2018) suggest that green practices improve financial performance through environmental performance. Makov and Newman (2016) argue that green practices which advance the welfare of employees and the members of the society enhance the reputation of the firms. This may attract potential customers and retain existing ones leading to improved economic performance. Employee safety and welfare could be improved through the adoption of green logistics practices that reduce greenhouse gas emission and proper management of waste (Baah, 2019) to reduce health problems (Khan, 2019). Dubey et al. (2017a, b) suggest that green practices in supply chain enhance green brand image and ensure brand equity resulting in cost savings and improved customer satisfaction. Logistics optimization, social values and ethics and green warehousing activities improve financial performance through cost savings while producing and providing ecofriendly products to satisfy the varying needs of customers. Torabizadeh et al. (2020) suggest that green warehousing has a positive influence on firm performance. Again, ensuring the safety and welfare of employees and external stakeholders through social values and ethics improve social sustainability of firms which reduces labor turnover and recruitment cost (Longoni et al., 2018). Green supply chain practices retain competently and attract talented employees that have the requisite skills to implement environmental practices and social policies to reduce waste, conserve energy and resources, ensure employee and societal safety and welfare and improve economic performance (Zaid et al., 2018; Agyabeng-Mensah et al., 2020a, b, c, d). Prior studies suggest that green practices in the supply chain lead to leanness and efficiency, which increase market shares and create profitability (Feng et al., 2018; Baah, 2019). Soytas et al. (2019) provide empirical evidence to confirm the positive relationship (possibly causally) between corporate social sustainability and financial performance. Besides, AgyabengMensah et al. (2020a, b, c, d) suggest that social and environmental performances influence financial performance positively. Allouche and Laroche (2005) and Gonenc and Scholtens (2017) posit that social performance is positively related with financial performance through the satisfaction of customers’ utility. However, Lu and Abeysekera (2014) suggest that there are inconclusive findings between financial performance and corporate social performance. Thus, we examine the relationship between green warehousing, social values and ethics, supply chain sustainability and economic performance through RDT. Therefore, we hypothesize that; The role of supply chain sustainability IJLM H6. Social values and ethics has a significant positive influence on economic performance H7. Supply chain sustainability has a significant positive influence on economic performance. H8. Supply chain sustainability mediates the relationship between green warehousing and economic performance. H9. Supply chain sustainability plays a mediating role between logistics optimization and economic performance. H10. Supply chain sustainability plays a mediating role between social values and ethics and economic performance. 3. Research design 3.1 Data collection The respondents of this study were selected from the manufacturing industry in Ghana. The context of this study is Ghana because of the inadequate literature addressing supply chain sustainability issues in emerging economies and Africa (Baah, 2019; Zaid et al., 2018; Bastas and Liyanage, 2019). Four hundred and twenty-three (423) firms were sampled from the five hundred and seventy (570) manufacturing firms in Ghana from the database of Manufacturers Association. The firms were contacted through phone calls to assess their willingness and eligibility to participate in the study. Two hundred and sixty-one (261) firms were eligible and agreed to participate in the study. Two hundred and sixty-one (261) questionnaires and confidentiality and assurance letters seeking permission, explaining the academic purpose of the study and assuring them of our duty to hide their identities were sent to the respondents through the mail. The respondents were given one month (from June 1 to 30, 2019) to complete the questionnaires. We sent a two-day interval message to remind the respondents to fill the questionnaires after the first 18 days to increase participation. We received two hundred and ten (210) questionnaires at the end of June 2019, where ten (10) were invalid due to missing data. The two hundred (200) valid responses represented 35.08% (200/ 570) of the population. The questionnaires were collected in two waves, where the early wave of response (within the first 18 days) was one hundred and eight (108), and the late wave of response (within the last 12 days) was ninety-two (92). The respondents included managing directors, procurement managers, supply chain managers, warehouse managers, logistics managers who have not less than five years of work experience and have occupied their current positions for not less than eight years. The profiles of the respondents place them in a suitable position to provide the necessary and relevant data for this study. The soft drink manufacturers (44%), textile manufacturers (16.5%), shoe manufacturers (16%) and furniture manufacturers (12%) were the contributions of each of the industries toward the data used for this study. The details of the companies and the respondents are contained in Tables 1 and 2. 3.2 Conceptual model The conceptual model shows the relationship between the dependent variables (economic performance), mediating variable (supply chain sustainability) and the independent variables (green warehousing, logistics optimization and social values and ethics). The directions of the arrows suggest the flow of influence from logistics optimization, social values and ethics and green warehousing to supply chain sustainability and economic performance. The first model looks at the direct effects between green warehousing, logistics optimization and social Companies Textiles factory Soft drinks Shoe manufacturers Stationary Furniture Totals Number of firms Percentage (%) 33 88 32 23 24 200 16.5 44 16 11.5 12 100 1–5 6–10 11–15 16–20 Above 20 Total Age (Years) 21 32 43 65 37 200 10.50 16 21.50 32.5 18.5 100 Below 10 10–40 40–80 80–120 120–600 Above 600 Total Annual sales (million Cedis) 29 63 42 27 22 17 200 14.50 31.50 21 13.50 11 8.50 100 Number of employees 42 79 33 18 12 16 200 20 39.5 16.5 9 6 8 100 1–99 100–199 200–299 300–399 400–499 500 and above Total Position Number Percentage (%) of respondents Managing directors Procurement manager Supply chain manager Warehouse managers Logistics managers Total Work experience (Years) Below 5 5–10 10–15 16–20 Above 20 Total 50 15 42 48 45 200 Number 16 73 23 39 49 200 25 7.5 21 24 22.50 100 Percentage 8.00 36.50 11.50 19.50 24.50 100 values and supply chain sustainability. Moreover, the model B shows the direct effect between green warehousing, logistics optimization, social values and ethics, supply chain sustainability and economic performance. Further, the model C shows the indirect influence of green warehousing, logistics optimization and social values and ethics on economic The role of supply chain sustainability Table 1. Profile of responding companies Table 2. Profile of respondents IJLM performance through supply chain sustainability. Based on RDT, we propose and test a model to ascertain how social values and ethics, logistics optimization and green warehousing could be employed by firms to achieve improved performance (supply chain sustainability and economic performance) as shown in Figure 1. 3.3 Operationalization of the constructs In order to test the hypotheses in this study, we use a quantitative research approach where questionnaires are utilized to gather data. Developing the right measures for constructs is one of the challenges facing today’s scholars (Agyabeng-Mensah et al., 2020a, b, c, d; Nawanir et al., 2013; Abushaikha, 2018), which requires a lot of work. We developed the items used to measure the theoretical constructs through extensive literature review. The data is gathered from the databases of Web of Science, Scopus and EBSCO. Because our study focuses on firms that have adopted relevant sustainable supply chain initiatives, we used highly experienced experts in sustainable supply chain practices from the academia and industry to develop clear, accurate and reliable scales and for pretesting of our questionnaires. Six questionnaires were emailed to six experienced supply chain academics and managers to express their opinions on the reliability, accuracy, validity and clarity of the instrument. The comments received from the experts caused us to drop and add some measures relevant to and representative of the study context. In order to achieve high statistical variability among the responses, the measurement items were measured using five-point Likert scale anchored from (1) strongly disagree to strongly agree (Chen and Paulraj, 2004; Dubey et al., 2017a, b). Existing scales were adapted to suit logistics optimization, green warehousing, social values and ethics, supply chain sustainability and economic performance after a consultation with experienced academics in sustainable supply chain management. The respondents were asked to select one of the anchors to rate the items from 1 5 strongly disagree, 2 5 disagree, Green warehousing Supply chain sustainability Social values and ethics Logistics optimization Control variables Nature of industry Firm size Independent effects (a) Green warehousing Green warehousing H5 H1 Social values and ethics Economic performance Logistics optimization Supply chain sustainability Independent effects Social values and ethics (b) Figure 1. Proposed conceptual model Logistics optimization Supply chain sustainability H7 H6 Green warehousing Social values and ethics H3 H2 H4 Supply chain sustainability Economic performance Supply chain sustainability as a mediator (c) Logistics optimization Full model (d) Economic performance 3 5 neutral, 4 5 agree and 5 5 strongly agree to show the degree of their disagreement or agreement. The study used reflective first-order level models to measure green warehousing, logistics optimization, social values and ethics, supply chain sustainability and economic performance. Logistics optimization was measured using six items. The items were adapted from Nikolaou et al. (2013), Vijayan (2014) and Boix et al. (2015). Also, green warehousing was measured using seven items. The items were adopted from Coyle et al. (2013) and Amemba et al. (2013). The study employed eight items to measure social values and ethics, which were adopted from Sarkis et al. (2011), Hoejmose et al. (2013), Gunasekaran and Spalanzani (2012) and Eriksson et al. (2015). Supply chain sustainability was measured using eight items adopted from and Green et al. (2019a, b), Zaid et al. (2018) and Longoni et al. (2018). Economic performance was also measured using seven items adapted from Agyabeng-Mensah et al., 2020a, b, c, d and Abushaikha (2018). The constructs and their respective measures are shown in appendix and Figures 1 and 2. Nature of industry and firm size is are likely to have influence the adoption of green practices (Agyabeng-Mensah et al. (2020a, b, c, d)) and social values and ethics that may affect supply chain sustainability and economic performance. Also, certain industries command extensive sustainable practices to regulate the adverse impact of their operations on the environment and society. On the other hand, large firms have adequate resource capacity to implement sustainable supply chain practices as compared to small firms (Liang and Yuyan, 2007). This study employs sales and number of employees to connote firm size. This study employs firm size and nature of industry as control variables to curtail the confounding effect of the exogenous constructs on the endogenous constructs (Chen and Paulraj, 2004). The role of supply chain sustainability 3.4 Nonresponse, common method bias and endogeneity tests The results of the paper could be affected by nonresponse bias since the data were collected in two waves using mails and questionnaires. We followed the suggestion of Armstrong and Overton (1977) to test the nonresponse bias of the early and late responses. The results of our test for nonresponse bias between the early 108 response and the late 92 response using the t-test show that nonresponse bias is not a problem in this study since the early and late waves of responses are not substantially different at the 5% significance level. This is one of the commonly used methods in the supply chain management literature (Green et al., 2019a, b; Inman and Green, 2018). Moreover, a t-test conducted to examine the difference in perceptions of the respondents about the implementation and the influence of green warehousing, logistics optimization and social values and ethics on supply chain sustainability and Control variables Nature of industry Firm size Green warehousing Social values and ethics –0.408** 0.371** 0.358** 0.245** Economic performance 0.173* 0.344** Logistics optimization Supply chain sustainability –0.213** Note(s): ** = significance, * = significance. All the paths are significant at 5% confidence interval Figure 2. Measurement model IJLM economic performance suggest that there is no significant difference in perception among managing directors, procurement managers, supply chain managers, warehouse managers and logistics managers. Podsakoff et al. (2003) posits that standard method bias test deals with an exploratory factor analysis (EFA) considers all observed variables and when a single factor explains a value ≥ 0.50 (i.e., ≥50%), which is a majority of the cumulative variance among measures, then, there is common method bias. The EFA performed on the variables in this study suggests 0.2722 (27.22%) as the first extracted factor explicated of the variance, which is below the 50% threshold. Hence, it could be reasonably and sufficiently confirmed that our study is without common method bias. As suggested by Guide and Ketokivi (2015), we conducted an endogeneity test of the exogenous constructs in our proposed model. Green warehousing, logistics optimization and social values and ethics are conceptualized as constructs antecedent to supply chain sustainability an economic performance. This was done with the consideration that green warehousing, logistics optimization and social values and ethics have the tendency to influence supply chain sustainability and economic performance and not vice versa (Guide and Ketokivi, 2015; Dong et al., 2016; Dubey et al., 2017a, b). Hence, we postulate that there is nonexistence of endogeneity in this context. Moreover, considering the non-normally distributed nature of our exogenous constructs, we employed the Gaussian copula approach to test endogeneity in the endogenous constructs. We assessed the copula coefficient significance to determine existence of endogeneity using bootstrapping (Ebbes et al., 2016). The copula coefficients obtained for the constructs is insignificant, which suggests that the study is free from a possible endogeneity (Hausman, 1978; Park and Gupta, 2012). 4. Data analysis, results and discussions 4.1 Data analysis The study used the partial least square structural equation modeling (PLS-SEM) technique (SmartPLS software 3.2.8) to analyze the data. Peng and Lai (2012) claim that the application of PLS-SEM in management research has seen an increment in recent times. According to Hair et al. (2012) and Hair et al. (2017), PLS-SEM is appropriate for an explorative study. Consequently, Hair et al. (2012) suggest that PLS-SEM is mainly used for predicting main target variables or ascertaining primary drivers of constructs. However, Hair et al. (2017) argue that covariance based structural equation modeling (CB-SEM) is more suitable for “theory testing and confirmation.” Since this study is explorative in nature and seeks to predict the influence of green warehousing, logistics optimization and social values and ethics on supply chain sustainability and economic performance, PLS-SEM is suitable (Hair et al., 2012; Green et al., 2019a, b; Hair et al., 2017; Baah, 2019). The analysis involves the evaluation of the measurement model and structural model, where the measurement model assessment involves finding the validity and reliability of the constructs in the model. The reliability and validity of the model are examined through convergent validity, internal consistency reliability and discriminant validity reliability. The structural model evaluation consists of the assessment of the predictive relevance (Q2), variance explained (R2) and effect size (F2) of green warehousing, social values and ethics and logistics optimization on supply chain sustainability and economic performance. The global model fit was tested using the goodness of fit (GoF). The analysis was done through calculating a Pls algorithm with 300 iterations, blindfolding with a D value of 6 and bootstrapping with a subsample size of 5,000 (see Table 3). 4.1.1 Measurement model assessment. The model was assessed to determine the validity and reliability of the constructs using convergent validity, discriminant validity, internal consistency reliability and indicator reliability. The convergent validity of the model was Construct Green warehousing Green warehousing Logistics optimization Economic performance Social values and ethics Supply chain sustainability Logistics optimization Economic performance Social values and ethics 1.879 1.525 1.731 1.564 1.975 1.916 1.661 1.847 1.871 1.957 1.768 1.937 1.865 1.607 1.652 2.631 2.613 2.656 Supply chain sustainability The role of supply chain sustainability 1.548 2.628 Table 3. Inner VIF values examined using the average variance extracted (AVE) whiles the indicator reliability was determined using the factor loadings (Henseler et al., 2015). Internal consistency was assessed using composite reliability and Cronbach’s alpha (Henseler, 2017). The thresholds used for measuring the factor loadings, Cronbach’s alpha, composite reliability and AVE were >0.70, >0.70, >0.70 and >0.50, respectively (Henseler et al., 2015). The least values for composite reliability (0.860), Cronbach’s alpha (0.802), factor loadings (0.641) and AVE (0.550) indicate that the scales used to measure the model in this study are reliable. The threshold of <0.85 was used to confirm the discriminant validity of each of the constructs (Henseler, 2017). The results of the analysis suggested that the maximum HTMT ratio (0.733) show that the model had achieved good discriminant validity. The values for the measurement variables are shown in Table 4 and 5. Construct Green warehousing Logistics optimization Economic performance Social values and ethics Supply chain sustainability Construct Logistics optimization Economic performance Social values and ethics Supply chain sustainability Cronbach’s alpha Rho A Composite reliability Average variance extracted (AVE) 0.802 0.827 0.877 0.802 0.868 0.809 0.843 0.887 0.933 0.930 0.870 0.878 0.907 0.860 0.908 0.626 0.557 0.620 0.672 0.713 Green warehousing Logistics optimization Economic performance 0.436 0.723 0.608 0.340 0.668 0.470 0.685 0.733 0.682 Table 4. Construct reliability and validity Social values and ethics 0.644 Table 5. Heterotrait-monotrait ratio (HTMT) IJLM 4.1.2 Assessment of structural model. The structural model assessment comprised the evaluation of the effect size, variance explained and the predictive relevance of the exogenous variables (logistics optimization, green warehousing and social values and ethics) on the endogenous variables (supply chain sustainability and economic performance) and the model fit. The variance explained values (R2) were evaluated using the threshold of 0.25, 0.50 and 0.75, which means small, moderate and substantial, respectively (Hair et al., 2013). The R2 figures for supply chain sustainability (32.10%) and economic performance (52.10%) showed that the model explained moderately of supply chain sustainability and moderate economic performance. Besides, the f2 values of 0.212, 0.027 and 0.082 and 0.218, 0.049 and 0.051 show the effect sizes of green warehousing, logistics optimization and social values and ethics on the supply chain sustainability and economic performance, respectively. Finally, the predictive relevance suggested by Stone-Geisser’s Q2 value (Stone, 1974; Geisser, 1974) was evaluated using an omission distance (D) value of 6, which falls within the range 5–12 suggested by the study (Hair et al., 2017). The Q2 values of 0.300 and 0.332 for both economic performance and supply chain sustainability showed that the model has excellent predictive relevance. Further, the analysis suggests a global model fit value of 41.37%. The multicollinearity test was conducted using the variance-inflated factor. The highest inner VIF value is 2.656, which is far below the threshold of 3.3 suggested by Kock (2015). This suggests that multicollinearity is not a problem in this study. 5. Results The results of the analysis indicate that the hypotheses H1, H2, H3, H4, H5, H7, H8, H9 and H10 are statistically significant at 5%. However, hypothesis H6 is not statistically supported. Moreover, H4 and H5 are rejected because the direct relationships between green warehousing, logistics optimization and economic performance are negative. These results are contradictory to our hypotheses. The analysis reveals that the hypothesis, which states that green warehousing significantly and positively influences supply chain sustainability (H1, β 5 0.371, t 5 7.836, p 5 0.000) is statistically supported. Besides, it is found that logistics optimization positively and significantly influences supply chain sustainability (H2, β 5 0.344, t 5 6.743, p 5 0.000). Hence, hypothesis H2 is supported. Similarly, the hypothesis stating that social values and ethics has a positive and significant influence on supply chain sustainability is statistically supported (H3, β 5 0.358, t 5 9.197, p 5 0.000). Again, the result reveals that social values and ethics has insignificant positive influence on economic performance (H6, β 5 0.173, t 5 1.853, p 5 0.2710), which does not support hypothesis 6. In addition, the hypothesis which states that supply chain sustainability has a significant and positive influence on economic performance is statistically supported (H7, β 5 0.254, t 5 9.197, p 5 0.000). Moreover, the results suggest that logistics optimization significantly and negatively influences economic performance (H4, β 5
0.213, t 5 2.730, p 5 0.000), which does not support H4. Similarly, the hypothesis, which states that green warehousing has a significant and positive influence on economic performance (H5, β 5
0.408, t 5 5.690, p 5 0.000), is not supported since the result suggests a negative relationship between the constructs. The study further evaluates the indirect influence of green warehousing, social values and ethics and logistics optimization on economic performance through supply chain sustainability. The outcome of the analysis shows that supply chain sustainability plays partial competitive mediating roles between green warehousing and economic performance (H8; t 5 2.691, p 5 0.007) and logistics optimization and economic performance (H9; t 5 2.596, p 5 0.010). Hence, the results support the hypotheses H8 and H9. Besides, the findings indicate that supply chain sustainability plays a partial complementary mediating role between social values and ethics and economic performance (H10, t 5 2.550, p 5 0.011). Hence, hypothesis H10 is statistically supported (see Table 6 and 7). Direct path Hypothesis Beta (β) T statistics (jO/ STDEVj) P-values Green warehousing - > Supply chain sustainability Logistics optimization - > Supply chain sustainability Social values and ethics - > Supply chain sustainability Logistics optimization - > Economic performance Green warehousing - > Economic performance Social values and ethics- > Economic performance Supply chain sustainability - > Economic performance H1 0.371 7.836 0.000 Supported H2 0.344 6.743 0.000 Supported H3 0.358 6.197 0.000 Supported H4
0.213 4.630 0.000 H5
0.408 8.690 0.000 H6 0.173 1.853 0.271 H7 0.245 4.730 0.006 Not supported Not supported Not supported Supported F2 0.001 T statistics 1.533 P-values 0.387 0.000 1.101 0.913 0.001 1.430 0.322 0.000 1.665 0.221 Results The role of supply chain sustainability Control variables Nature of industry- > Supply chain sustainability Firm size - > Supply chain sustainability Nature of industry- > Economic performance Firm size - > Economic performance Table 6. Direct effect T statistics (jO/ STDEVj) P-values H8 2.691 0.007 Supported H9 2.569 0.010 Supported H10 2.550 0.011 Supported Indirect path Hypothesis Green warehousing - > Supply chain sustainability - > Economic performance Logistics optimization - > Supply chain sustainability - > Economic performance Social values and ethics - > Supply chain sustainability - > Economic performance Results 6. Discussions The study uses the RDT as the theoretical lens of this study to explore the direct influence of green warehousing, logistics optimization and social values and ethics on supply chain sustainability as well as the direct and indirect influence of green warehousing, logistic optimization and social values and ethics on economic performance. The findings reveal that green warehousing, logistics optimization and social values and ethics significantly improve supply chain sustainability (H1, H2, H3). This suggests that the implementation of sustainable supply chain practices such as logistics optimization, green warehousing and social values and ethics require the collaborative efforts of supply chain partners achieve supply chain sustainability results. This advances the position of the RDT that relationship between supply chain partners is essential for sustainability development (Ulrich and Barney, 1984). Hence, the manufacturing firms in Ghana collaborate with suppliers and customers to implement green warehousing, social values and ethics and logistics optimization to reduce waste, minimize greenhouse gas emissions, ensure energy and Table 7. Mediation IJLM resource conservation and improve societal and employee safety and wellbeing. Ries et al. (2018) suggests that logistics activities contribute to about 5.5% to 13% of the entire global supply chain emissions. The implementation of green warehousing may serve as a solution to logistics emission through reduced gas emission, air pollution, which improves supply chain sustainability. This finding is consistent with extant literature (Agyabeng-Mensah et al., 2020a, b, c, d; Zaid et al., 2018), which establish that green practices substantially improve supply chain sustainability. Again, the findings indicate that the effective implementation of logistics optimization as a green practice requires collaboration along the supply chain to achieve desired sustainability results. Hence, logistics optimization implemented with the collaborative efforts of supply chain members leads to significant reduction in greenhouse gas emission and adverse impact of firms’ operation on the environment and the health and wellbeing of members of the society. This indicates that collaboration with customers and suppliers in the implementation of logistics optimization improve performance as posited by RDT. Also, social values and ethics are usually adopted to ensure the welfare and safety of employees and society (Croom et al., 2018). For a firm to develop and implement effective social value and ethics along the supply chain to achieve excellent results, the role of customers and suppliers are required. This reveals that an increase in sharing of social values and ethics among supply chain partners facilitate the achievement of expected supply chain sustainability goals, which represents the position of RDT. Besides, our result reveals that social values and ethics contribute to the advancement of economic performance (H6). However, the influence of social values and ethics on economic performance is insignificant. This may be due to the fact that social values and ethics takes longtime to reflect in the economic performance. On the contrary, the results reveal that green warehousing and logistics optimization have significant negative influence on economic performance (H4-H5). This indicates that green practices that are implemented solely to gain economic benefits may adversely affect the economic performance. The above findings answer the first question of our study, which forms a key contribution of this study. Consequently, the second question of this study is answered in this section. The study’s findings reveal that supply chain sustainability significantly improves economic performance while it mediates the influence of green warehousing, logistics optimization and social values and ethics on economic performance (H7, H8, H9, H10). These findings are consistent with extant literature (Afum et al., 2020; Feng et al., 2018; Agyabeng-Mensah et al., 2020a, b, c, d; Yu et al., 2020). This confirms that the implementation of green warehousing and logistics optimization ensure societal and employee safety as well as protect the environment from destruction and ensure growth in market size, sales, profitability and return on investment. This may lead to improvement in societal acceptance (Kumar and Shekhar, 2015) and result in the retention of customers and the attraction of new customers relative to competitors leading to improved economic performance. Social values and ethics improves the welfare of employees and society members, which protects the image of a firm and attracts loyal customers and employees. This may lead to savings in the cost of recruitment due to reduced labor turnover rate and improve sales and profit margins (Agyabeng-Mensah et al., 2020a, b, c, d). The findings of the study has establish that the concerted effort from suppliers and customers of a firm toward the implementation of green warehousing, logistics optimization and social values and ethics is required to achieve substantial improvement in supply chain sustainability goals as posited by the RDT. Besides, the findings indicate that despite the level of collaboration among supply chain partners toward the implementation of green warehousing and logistics optimization the firm’s economic performance may be adversely affected. Moreover, social values and ethics have insignificant influence on economic performance. These results defeat the position of RDT in situations where the adoption of green practices do not address significant environmental and social problems which may translate into improved economic performance. Hence, we establish that based on the RDT, the effort of supply chain partners are required for effective implementation of green warehousing, logistics optimization and social values and ethics that advances supply chain sustainability in order to achieve significant economic performance goals. 7. Conclusion 7.1 Theoretical implications The study advances the literature in green supply chain management by developing and testing a model that explores the relationships between green warehousing, logistics optimization social values and ethics, supply chain sustainability and economic performance from the developing country’s perspective. Hence, this study serves as a response to researches requesting studies in sustainability from emerging economies, especially, Africa (Tseng et al., 2019; Bartolini et al., 2019; Dubey et al., 2017a, b). To the best of our knowledge, this is the first study that empirically tests the influence of green warehousing, social values and ethics and logistics optimization on both supply chain sustainability and economic performance through the RDT lens. Particularly, this study has revealed that RDT is an important theory that brings understanding to the collaboration between a focal firm and its supply chain partners. Essentially, RDT suggests that firms should work with their supply chain members in a way that facilitates resource sharing among them to achieve improved firm performance. Based on our findings, we posit that green warehousing, logistics optimization and social values and ethics are sustainable supply chain management practices that advance firm performance (supply chain sustainability and economic performance). In applying RDT to green warehousing, logistics optimization and social values and ethics context, we reveal that RDT can be effectively employed in a new context, which shows a new area of application. This addresses the recommendation by Pfeffer (2005) to invoke RDT to ensure its continuous relevance in literature. Moreover, this study advances the scope of the applicability of RDT (Singh et al., 2011). It has been shown in this study that RDT is applicable in explaining management tool at the operational and strategic levels which is different from extant empirical studies focusing on only strategic level actions such as strategic alliances (Gulati and Gargiulo, 1999) and mergers and acquisitions (Finkelstein, 1997). 7.2 Managerial implications The study may also contributes to the work of managers. The findings offer a logical basis for the adoption of green warehousing, logistics optimization and social values and ethics as supply chain sustainability strategies. Besides, this study serves as a blueprint and persuasive justification for managers to push for the adoption of social and ethical policies and practices in supply chain. Moreover, the study encourages managers to adopt logistics optimization, green warehousing and social values and ethics to improve supply chain sustainability. Besides, the study encourages firms to collaborate with their suppliers and customers to share resources in the implementation of green warehousing, logistics optimization and social values and ethics to achieve significant waste and gas emission reduction, improved welfare of employee and community members and increased sales, market share, profitability and return on investment. In addition, firms can effectively manage their relationships with supply chain members to convert them into sources of competitive advantage to advance economic performance. Further, while working with supply chain members (customers and suppliers) during the implementation of green warehousing, logistics optimization, and social values and ethics, firm’s employees are likely to develop skills and green capabilities to create competitive advantage and improve economic performance. This suggests that firms should not undermine the role of collaboration with suppliers and customers in the effective implementation of green warehousing, logistics optimization and social values and ethics. The findings indicate that The role of supply chain sustainability IJLM green warehousing and logistics optimization have adverse influence on economic performance. However, supply chain sustainability provides competitive mediation role between both logistics optimization and green warehousing and economic performance. This suggests that firms should adopt sustainable practices that have both social and environmental bearing to be able to advance economic performance. 7.3 Implication for society The researchers hold the belief that this study makes significant contributions to the entire society. Logistics activities of firms significantly contribute to greenhouse emissions and black air that are harmful to the health of people. This study suggests that green warehousing and logistics optimization reduce environmental pollution, waste and emission of harmful gases. This leads to improved health of the members of the society. Besides, the use of green energy and the reduction of waste and energy consumption help firms to meet the needs of final customers and other stakeholders in a way that conserve resources for the unborn generation and advance the ecology of our planet. Moreover, social values and ethics have a positive influence on supply chain sustainability, which suggests that this study unveils practices that seek the welfare and safety of employees and community members. 7.4 Limitation of the study and future direction This study has several limitations, which need to be addressed in future studies. The findings of the study suffer from limited generalizability. This is because the study was conducted in only manufacturing firms in Ghana. Future research could extend the study to other industries like the logistics industry. Again, though the sample size was adequate for the PLSSEM and adequately represented the manufacturing industry in Ghana, the response rate was relatively low. Future study may try to increase the response rate to add more credence to the findings. Though the results for common method bias and multicollinearity analysis showed that the model had good collinearity and suffered no common method bias, however, there may be the existence of a problem of multicollinearity due to the similarities in some of the measuring variables. The framework could also be tested in other industries and geographical areas. Researchers could test the framework by finding the impact of the antecedent variables on other measures of economic performance in future research. References Abushaikha, I. 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Corresponding author Yaw Agyabeng-Mensah can be contacted at: yawagyabeng830@gmail.com Appendix The role of supply chain sustainability Variables Measurement items Items Factor loadings Economic performance Reduced energy consumption cost Reduced inventory management cost Increased market share Increased sales growth Increased gross profit margin Increased net profit return Increased return on assets Our firm uses biodegradable packages in the warehouse We use plant-based products for packaging in our warehouse We have replaced plastics with paper packages in our warehouse We Use LED bulbs in the warehouse We use solar energy in the warehouse We use waste management systems in our warehouse We practice just-in-time concept in our warehouse We use inventory management system in our warehouse We reclaim products from customers for remanufacturing We collect used products for recycling We recall used products for proper disposal We work with distributors to build a optimized transportation network Our firm uses route optimization software to ensure efficiency We cooperate with suppliers and customers to develop route networks EP1 0.850 EP2 0.793 EP3 EP4 EP5 EP6 EP7 GW1 0.713 0.850 0.793 0.713 0.850 0.748 GW2 0.833 GW3 0.748 GW4 0.833 GW5 0.748 GW6 0.833 GW7 0.688 GW8 0.775 LO1 0.788 LO2 0.879 LO3 0.840 LO4 0.775 LO5 0.840 LO6 0.840 Green warehousing Logistics optimization Source of items Agyabeng-Mensah et al. (2020a, b, c, d), Nawanir et al. (2013), Abushaikha (2018) Coyle et al. (2013), Amemba et al. (2013) Nikolaou et al. (2013), Vijayan (2014), Boix et al. (2015) (continued ) Table A1. Questionnaire IJLM Variables Measurement items Items Factor loadings Supply chain sustainability Improvement in the firm’s environmental situation Reduction in energy usage Reduction in wastewater Improvement in the safety of workers and society Improvement the welfare of employees and society Improved equal job opportunities in our firm Reduction in carbon dioxide emission Our firm has developed internal ethical purchasing policies We purchase raw materials from only firms that do not engage in child labor There is job security policy for employees There is equal job opportunity policies for employees There is an internal ethical sourcing policies in our firm We cooperation with suppliers for environmental objectives We vet and audit suppliers based on their ethical policies Our firm organizes green training programs for employees There are environmental safety policies in our firm SCS1 0.921 SCS2 SCS3 SCS4 0.850 0.850 0.788 SCS5 0.791 SCS6 0.780 SCS7 0.850 SVE1 0.810 SVE2 0.839 SVE3 0.773 SVE4 0.764 SVE5 0.810 SVE6 0.852 SVE7 0.793 SVE8 0.885 SVE9 0.799 Social values and ethics Table A1. Source of items Green et al. (2019a, b), Zaid et al. (2018), Longoni et al. (2018) Sarkis et al. (2011), Hoejmose et al. (2013), Gunasekaran and Spalanzani (2012), Eriksson et al. (2015)