Sustainable supply chain and company performance A global examination Eduardo Ortas and José M. Moneva Department of Accounting and Finance, University of Zaragoza, Huesca, Spain, and Igor Álvarez Department of Accounting and Finance, Basque Country University, San Sebastian, Spain Abstract Purpose – This paper aims to investigate the link between a sustainable supply chain and companies’ financial performance (FP) and provide empirical evidence about the relationship between these two constructs. This link is an important, but still unclear, subject. Design/methodology/approach – Multivariate measures of sustainable supply chain performance and companies’ FP are used for Granger causality tests on a large, diverse sample of 3,900 companies in a time frame of eight years (2004-2011). Findings – Results indicate general bidirectional causality between sustainable supply chain performance and companies’ margins and revenue. However, the link between firms’ profitability and sustainable supply chain performance is unidirectional. In addition, the recent financial crisis altered this link between the studied constructs. Finally, a wide diversity in relationship patterns between sustainable supply chain performance and companies’ FP emerges when the full sample is divided into different geographical regions and economic sectors as specified by the Global Industry Classification Standard system. Practical implications – This research makes recommendations for improving several processes, such as stakeholder evaluation of the sustainable supply chain performance of companies worldwide and manager testing of environmental policy outcomes. Originality/value – Building on the mostly qualitative literature on sustainable supply chain performance and companies’ FP, this research provides quantitative evidence of the gaps between these constructs. This research contributes to the discussions of supply chain management, environmental practices and the drivers of companies’ environmental and financial success. Keywords Corporate responsibility, Sustainability, Corporate social responsibility, Business administration, Environmental management, Environmental performance, Company performance, Sustainable supply chain management, Green supply chains, Sustainable supply chain performance, Granger causation Paper type Research paper 1. Introduction a reductionist corporate management model focused only on shareholders’ interests (Wood, 2008). Under this scenario, sustainable management of supply chains has become a core strategic factor for companies worldwide (Seuring, 2012). Companies have progressively broadened their approach to SCM by embracing social and environmental concerns (Svensson, 2007; Gimenez and Tachizawa, 2012), giving rise to a new concept: sustainable supply chain management[1] (SSCM) (Carter and Easton, 2011; Ashby et al., 2012). SSCM is defined as reformist SCM “which manages the material, information and capital flows as well as cooperation among companies along the supply chain Supply chain management (SCM) is an important environmental and social subject relating to corporate sustainability (Ashby et al., 2012). Companies’ interest in SCM has increased in recent decades because of growing global competition, outsourcing of companies’ non-core activities and the shortening of product life cycles (Skjøtt-Larsen et al., 2007). More importantly, companies’ close, long-term relationships with suppliers and other strategic partners have become a key factor in competitiveness (Christopher, 2005; Andersen and SkjOEtt-Larsen, 2009). At the same time, companies have become more deeply committed to corporate social responsibility (CSR) and sustainability (Freeman et al., 2010) by refusing to implement The authors would like to thank the anonymous reviewers for their insightful comments and feedback on the earlier versions of this paper. The authors also are grateful for financial help from the Spanish Education Ministry (research projects SIRCARSO SEJ2006-08317, SEJ2006-0395, MTM 2008-00625 and ECO2011-26171) and from the Zaragoza University (research projects UZ2009-SOC-08 and UZ2010-SOC-04). The usual disclaimer applies. The current issue and full text archive of this journal is available at www.emeraldinsight.com/1359-8546.htm Received 8 December 2013 Revised 8 February 2014 28 February 2014 Accepted 8 March 2014 Supply Chain Management: An International Journal 19/3 (2014) 332–350 © Emerald Group Publishing Limited [ISSN 1359-8546] [DOI 10.1108/SCM-12-2013-0444] 332 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 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 Müller, 2008, p. 1,700). In recent years, SSCM has driven the development of innovative tools which allow measuring companies’ sustainability performance, being this fact essential to improve companies’ social and environmental performance, including sustainable suppliers, modal and carrier selection, environmentally friendly vehicle routing and location decision and packaging choices (Carter and Easton, 2011). Increasingly, managers consider SSCM issues for not only their company but also their supply chain partners (Vachon and Klassen, 2006). This process is a logical result of the perception by academics and practitioners that SSCM is a critical corporate competitive factor that improves corporate social and environmental performance, minimizes spending on waste and improves the corporate image (Seuring et al., 2008; Rao and Holt, 2005). The literature also suggests that companies’ improvements of sustainable supply chain performance (SSCP) can sharpen their competitiveness and financial and operational performance (Keating et al., 2008). SSCP is “a company’s capacity to reduce the use of materials, energy, or water and to find more eco-efficient solutions by improving supply chain management”. Although the literature contains many studies on SSCP, these hypothesized relationships are still underdeveloped (Ashby et al., 2012), partly because theory in SSCM is still under development and inductive research methods such as case studies dominate the SSCM field (Ashby et al., 2012; Seuring and Müller, 2008). Although case studies represent a good path to insight into complex, contemporary phenomena (Yin, 2009), and have revealed very relevant findings in SSCM and SSCP, they often lack generalizability to other contexts and overall conclusions (Eisenhardt, 1989). For theories, SSCM and SSCP have generally relied on adjacent fields (Carter and Easton, 2011). Moreover, sustainability performance literature lacks global studies that assess the potential relationship between SSCP and company performance. This paper is placed in the field of sustainability performance management and measurement (Figge et al., 2002; Schaltegger et al., 2006), which represents an emerging field that addresses the social, environmental and economic performance issues of corporate management in general and of corporate sustainability management in particular (Schaltegger and Wagner, 2006). In particular, sustainability performance measurement is implemented to companies’ SSCP to show managers and stakeholders the possible dependence patterns between corporate financial performance (FP) and SSCP due to two factors: 1 a diverse sample of 3,900 companies from multiple economic sectors in most of the world’s developed and emerging markets; and 2 coverage of a period of economic growth and financial crisis to analyze whether market conditions influence the relationship of SSCP and FP. flexible to capture the complete dependence structure between these constructs. The work uses multivariate measures for SSCP and FP. Carroll (1979) and Moneva and Ortas (2010) argue that multivariate measures are necessary to handle the complex taxonomy of proxies related to FP and companies’ social and environmental performance. It will provide relevant implications for improving several processes, such as stakeholders’ evaluation of the SSCP of companies worldwide and managers’ testing of the results of incorporating SSCP processes into company policy. The rest of the paper is organized as follows. The next section analyses the previous literature on this topic and introduces research hypotheses. The third section focuses on sample selection, data description and applied methods. The fourth describes the results obtained. The last covers conclusions, implications of the work and further research opportunities in this field. 2. Background 2.1 Theoretical framework In recent decades, SSCM has received attention from both academics and practitioners because of its potential to make corporate behavior more sustainable (Seuring et al., 2008; Sarkis et al., 2011). Moreover, the potential link between SSCP and companies’ FP has become a popular research topic because of its implications for corporate strategy, policy and economic sustainability (Fawcett et al., 2008). This context brings up the role of CSR and sustainable development (Figge and Hahn, 2001). CSR in the 1960s and 1970s was mainly motivated by social considerations. Its current performance orientation supposes a change from a macro to an organizational level (Carroll and Shabana, 2010). Given this inherent instrumentality (Hahn and Figge, 2001), many argue that companies will only contribute to sustainable development if they perceive an incentive to do so (Epstein and Roy, 2003; Husted and de Jesus Salazar, 2006; Rowley and Berman, 2000). Schaltegger and Synnestvedt (2002) note that an environmentally friendly company that is not economically friendly will sooner or later disappear from the market along with its environmentally beneficial activities. This consideration is similar to the business-case model of CSR defined by Berger et al. (2007) that considers CSR initiatives as adopted for pure rational and economic reasons. Thus, the link between a good environmental performer and a good financial performer has been a core topic in the corporate environmental management literature for years (Schaltegger and Synnestvedt, 2002). Despite the great number of academic contributions, links between corporate social and environmental performance (CSP) and companies’ FP are still not clear (Brammer and Millington, 2008; Hahn and Figge, 2011; Lockett, et al., 2006; Orlitzky et al., 2003; Ullman, 1985; Waddock and Graves, 1997; Wu, 2006). On one hand, several empirical papers assume environmental performance improvements generate new costs, while on the other, many papers have confirmed empirically that environmentally friendly activities generally payoff and improve companies’ FP (Porter and van der Linde, 1995). The direction of this relationship is still unclear. Do improvements in CSP generate better levels of companies’ FP? Or do improvements in This work aims to explore the broad relationships between these constructs, taking into account companies worldwide from many industries. It does not impose ex-ante causal relationships between SSCP and companies’ FP and remains 333 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 companies’ FP generate better levels of CSP? (Brammer and Millington, 2008; Scholtens, 2008; Waddock and Graves, 1997). To explain the potential relationship between CSP and companies’ FP, we will address the theories that explain the two directions of this relationship. Stakeholder theory proposes that satisfying stakeholders’ interest will improve companies’ FP (Freeman, 1984; Porter and van der Linde, 1995; Waddock and Graves, 1997). It also argues that bilateral stakeholder management relationships monitor managers and keep their attention on broad organizational financial goals (Hill and Jones, 1992; Jones, 1995). Managing the claims of stakeholders could increase efficiency by speeding up adaptation to changes in external demands (Freeman and Evan, 1990), such as new technologies or product developments. The instrumental dimension of stakeholder theory (Clarkson, 1995; Cornell and Shapiro, 1987; Donaldson and Preston, 1995; Freeman, 1984; Jones, 1995; Mitchell et al., 1997) suggests a positive relationship between CSP and companies’ FP (Preston, 1978; Anderson and Frankle, 1980; Freedman and Stagliano, 1991; Graves and Waddock, 2000; Griffin and Mahon, 1997; Berman et al., 1999; Van de Velde et al., 2005; Wu, 2006). To analyze the direction of the causality, two views are examined: 1 Slack resources theory: This theory argues that better FP can make slack financial and other resources available to invest in CSP, making companies’ FP a predictor of CSP (McGuire et al., 1990; Waddock and Graves (1997). This view is often based on the belief that good environmental performance is a kind of Giffin good for a company after it has reached high economic success (Schaltegger and Synnestvedt, 2002). The most successful companies have the most financial resources and can spend the most on CSR activities (Brammer and Millington, 2008; Waddock and Graves, 1997). This view is supported by Margolis et al. (2007), indicating that companies with superior FP are more likely to engage in CSR-related activities (Allouche and Laroche, 2005). However, if companies have fewer financial resources and consider social and environmental issues unnecessary, they would of course reduce the funding for CSR activities. 2 Good management theory: This theory proposes a high correlation between good management practices and CSP because attention to CSP improves relationships with key stakeholders (Freeman, 1984), thereby improving firms’ FP (McGuire et al., 1990; Waddock and Graves (1997). Kurucz et al. (2008) also support this effect based on the following arguments: ● CSR lowers cost and risk; ● CSR creates competitive advantage; ● CSR boosts legitimacy and reputation; and ● CSR creates win – win situations for the company and society. reputational (Peloza, 2006) or related to environmental management developed to reduce environmental risks. Second, CSP could generate benefits or reduce costs, both of which improve companies’ FP (Margolis et al., 2007). For example, it could mitigate the effects of negative regulatory or legislative actions (Freeman, 1984; Berman et al., 1999). Furthermore, positive community relationships may lead to company tax advantages. Third, if companies reach successful levels of FP, they could then be asked for social and environmental investments (Campbell, 2006). Generalized reciprocity may also motivate companies that do well to do good (Margolis et al., 2007). Kurucz et al. (2008) consider the reduction of cost and risk key to the positive relationship between CSP and companies’ FP. 2.2 Literature review: interactions between CSP, SSCP and firms’ FP Previous research comprises an important number of studies that confirm environmental proactivity reduces costs and risks (Berman et al., 1999; Dechant et al., 1994). Similarly, several works support that the costs of social responsibility are minimal, and potential benefits include employee satisfaction and productivity (Moskowitz, 1972; Parket and Eilbirt, 1975; Solomon and Hanson, 1985; McGuire et al., 1988; Wu, 2006). Another set of papers suggests that the appeal of CSP, rather than its substantive impact, generates financial returns. In this view, not the actual effect of doing good but the appearance of it, especially to shareholders, raises stock price, raises demand for products and makes workers more committed (Margolis et al., 2007). Pivato et al. (2008) claim that social performance benefits brand loyalty by building trust in customers. Similarly, Ribstein (2005) considers that CSR benefits companies’ FP by improving strategy processes and raising employee, customer and society loyalty. Furthermore, managing the claims of companies’ stakeholders could cause adaptation to external demands that increases efficiency (Freeman and Evan, 1990). Companies can be more successful by developing (up to some margin) relationships with customers, employees, communities and governments (Harrison and St. John, 1994; Kotter and Heskett, 1992) which differentiate their products/services (Kapstein, 2001). A perception as “ethical” improves a company’s reputation (Klein and Dawar, 2003; Fombrun and Shanley, 1990; Peloza, 2005; Turban and Greening, 1996) and attracts socially responsive investors (Kapstein, 2001). Porter and Kramer (2002) argue that philanthropy and competitive advantage become mutually reinforcing, a virtuous cycle. Specific SCM literature in this field usually hypothesizes that high levels of SSCP can reduce monetary risks and increase companies’ FP (Owens, 1972; Ashby et al., 2012). The main theoretical perspective testing the impact of supply chain environmental performance on FP is the natural resource-based view of companies (Vachon and Klassen, 2006). An environmental management strategy founded on resources can theoretically create sustained strategic advantages. Klassen and Whybark (1999) found evidence that the selection of pollution prevention technologies enabled manufacturers to do things competitors find difficult to replicate. Christmann (2000) argued that companies can Burritt and Schaltegger (2010) indicate that sustainability practices may improve the basis for companies’ decisions to improve performance, (eco-) efficiency or reputation or decide an improvement is not worth pursuing. Margolis et al. (2007) also support this view by suggesting three plausible motivations. First, risk mitigation could be 334 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 5 develop new capabilities that improve their competitive advantages from environmental management to other management areas and, therefore, improve their FP. Specifically, Zhu and Cote (2004) demonstrate that SSCM allows companies to concurrently improve their economic and environmental performance. This claim is in line with previous findings that SSCM can yield not only environmental but also financial benefits (Walton et al., 1998). Several case studies suggest that SSCM, including the use of standards (i.e. ISO 14000), improves efficiency and reduces costs (Handfield et al., 1997; Walton et al., 1998). Carter and Ellram (1998) found that SSCM that reduces resource consumption through recycling, reuse and appropriate waste management saves costs and increases FP. Carter et al. (1999, 2000) support this, noting that poor SSCM can cause costs, including fines and liabilities. Alvarez Gil et al. (2001) and Sroufe (2003) argue that environmental practices, such as SSCM, have a significant impact on companies’ competitiveness, risk exposure and FP. Similarly, Bowen et al. (2001) and Hall (2003) suggest that SSCM allows companies to reduce costs by including suppliers in a participative decision-making process that promotes environmental innovations. Zhu and Cote (2004) show how companies can improve their FP through SSCM that transforms waste into resources. Furthermore, Rao and Holt (2005) associated the results of SSCP, including cost and risk reductions and improved corporate image and environmental performance, with better FP. SCM literature has found some negative consequences from effective SSCM. Min and Galle (1997) identified different costs, including those stemming from environmental programs and uneconomical recycling and reuse, as the main barriers to SSCM’s implementation, which could reduce FP. This finding agrees with that of the study by Walley and Whitehead (1994), who argue that environmental challenges have always been costly and offered little financial payback. From a different perspective, Zhu and Sarkis (2007) found that when market pressures improve SSCP, companies’ FP tends to deteriorate. The following seven are among the principal reasons of why the link between FP and CSP remains unclear: 1 Schaltegger and Synnestvedt (2002) and Ullman (1985) have criticized empirical studies for lacking theoretical foundation. 2 Other authors have concluded that the positive relationship between CSP and FP resulted from poor event study methodology (Lockett et al., 2006; McWilliams and Siegel, 1998, 1998). 3 Brammer and Millington (2008) and Waddock and Graves (1997) indicate that the fundamental reason for the uncertainty about the relationship between CSP and FP refers to some methodological problems measuring CSP. 4 Aupperle et al. (1985), Brammer and Millington (2008), Carroll (1979), Waddock and Graves (1997) and Wood (1991) reveal that CSP is a multidimensional construct, with behaviors ranging across a huge variety of related inputs. 6 7 According to Barnett (2007), the impact of CSP on FP varies from one firm to the other, indicating inconclusive results attributable to situational factors. Pivato et al. (2008) drew attention to the importance of moderating variables such as industry- and country-specific factors. other authors have found the relationship between CSP and FP non-progressive (Barnett and Salomon, 2012; Schaltegger and Synnestvedt, 2002; Wagner and Blom, 2011; Wagner et al., 2002). For Barnett and Salomon (2012), the link between FP and CSP is U-shaped: companies with low CSP have higher FP than companies with moderate CSP, but companies with high CSP have the highest FP. Schaltegger and Synnestvedt (2002) found a curvilinear relationship between CSP and firms’ FP. 2.3 Hypotheses development Although claims of a positive relationship between SSCP and FP have gained relative strength in the field, the link between them is still ambiguous. Most of the research reviewed consisted of case studies of only one or two companies (Carter and Easton, 2011; Seuring, 2012), and thus provided limited support for global conclusions. Schaltegger and Synnestvedt (2002) argue that this relationship may differ depending on the regulatory regime, cultural setting, customer behavior, type of industry and size of company. Carroll and Shabana (2010), Barnett (2007) and Pivato et al. (2008) support this view, indicating that one depicts this relationship better by accounting for moderating variables and situational contingencies. Furthermore, some questions about this topic remain open, and answering them will yield a better understanding of this phenomenon: ● Is the relationship between SSCP and firms’ FP bidirectional? ● Has the financial crisis changed it? ● Does it vary among international markets? and ● Can it be influenced or moderated by the economic sector in which companies operate? Few studies have focused on testing the possible bidirectional relationship between CSP and firms’ FP. Orlitzky et al. (2003) noted that both instrumental stakeholder theory and slack resources descriptions were accurate, suggesting bidirectionality. Surroca et al. (2010) argue for giving it a bidirectional framework. Hart (1995), Shrivastava (1995a, 1995b) and Karagozoglu and Lindell (2000) provide a theoretical basis for the bidirectional win-win perspective, arguing that CSP improvements can improve firms’ FP, which then enhances CSP. Schreck (2011) theorized that improved CSP might improve profitability through increased operational efficiency and consumer or employee satisfaction, in line with slack resource theory. The studies that try to explain the influence of the financial crisis on this relationship are few (Theotokas and Giannarakis, 2011). Singh (2013) analyzed the FP of some socially responsible investments, compliant with CSR issues, before and after the financial crisis and concludes that companies who complied with environmental, social and governance (ESG) principles could mitigate the harm to FP in bear 335 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 3. Data, measures and method market periods. Karaibrahimoglu (2010) also considers the effects of the financial crisis on CSP and CSR, concluding that companies’ slack resources available to invest in CSP significantly decreased during the financial downturn, more so in the USA than in Europe and other countries. Other works also examined the impact of the crisis on CSR projects (Arevalo and Aravind, 2010; Yelkikalan and Köse, 2012). Njoroge (2009) claimed that in times of crisis, reduced investment in CSR and CSP is needed to reduce costs and, consequently, improve FP. Gallego et al. (2013) found that CSP has no influence on a company’s FP during the financial crisis period. Based on these findings, we propose to test the following hypothesis: H1. 3.1 Measures of FP and SSCP Previous research addresses the complexity of measuring multidimensional constructs such as FP, CSP and SSCP (Waddock and Graves, 1997; Soana, 2011). Summarizing previous works mainly uses the following five methods: 1 content analysis (Abbott and Monsen, 1979; Gray et al., 1995; Patten and Crampton, 2004; Wolfe, 1991); 2 questionnaire surveys (Aupperle, 1991; Aupperle et al., 1985; Maignan and Ferrel, 2000); 3 reputational measures (Bowman and Haire, 1975; McGuire et al., 1988; 4 case studies (Clarkson, 1991; Patten, 1992; Cho, 2009); and 5 CSR ratings of social and environmental audits (Abbott and Monsen, 1979; Cho and Patten, 2007; Graves and Waddock, 2000; Greening and Turban, 2000; Griffin and Mahon, 1997; Gjølberg, 2009; Waddock and Graves, 1997). The possible bi-directional relationships between SSCP and corporate FP vary depending upon financial market growth patterns. There is general agreement that corporate culture influences firms’ FP (Deshpande et al., 1993; Denison and Mishra, 1995; Han et al., 1998). Thus, the link between CSP and firm’s FP should also be influenced by cultural aspects that vary between countries and geographical areas (Sugita and Takahashi, 2013). Branzei et al. (2001) found Chinese managers have different views on CSP than the Japanese. Similarly, Wagner (2009) found that CSP and FP are moderated by national culture. Ringov and Zollo (2007) concluded that national culture (power distance, individualism, masculinity and uncertainty avoidance) influenced CSP in different ways in North America, Europe and Asia. Therefore, national variations in the CSR concept influence expectations of CSR and CSP and their impact on FP (Scholtens and Kang, 2013). Miras et al. (2013) investigated the moderating role of national culture in CSP and FP, and conclude that the role exists. We extend this debate to the relationship between SSCP and firms’ FP, and propose to test the following hypothesis: H2. This research uses financial and supply chain performance indicators to evaluate the relationship between FP and SSCP. SSCP indicators came from the ASSET4® database of Datastream provided by Thomson Reuters Inc., which provides objective and systematic ESG data using ⬎280 key performance indicators and 750 individual data points and their original data sources from ⬎4,000 global companies, including MSCI World, MSCI Europe, STOXX 600, NASDAQ 100, ASX 300 and MSCI emerging markets. Among the many studies addressing some of the problems of selecting adequate measures of corporate CSP (Margolis and Walsh, 2001), the Kinder, Lydenberg and Domini[2] (KLD) and ASSET4 measures are recognized as the most complete ratings of CSP and social responsibility. They use a multidimensional variable that captures a wide range of stakeholder performance issues. Specifically, the key performance indicators are assessed by independent external social audits (Orlitzky et al., 2003) that apply social and environmental screens, thus reflecting companies’ social, environmental, economic and corporate governance strengths and weaknesses. SSCP was measured through a three-step procedure. First, an intensive search of the ASSET4 ESG database identified the key performance indicators of SSCP (see Table AI in the Appendix for a complete description of each). Next, a factor analysis led to a dimension reduction of all SSCP indicators. Because the key performance indicators are binary, we computed their matrix of tetrachoric correlations for factor analysis (Bock and Lieberman, 1970; Knol and Berger, 1991). The exploratory factor analysis of the SSCP construct was satisfactory. Table AII in the Appendix reveals that only one extracted factor had an eigenvalue higher than 1 that refers to the scree plots of SSCP and FP. We implemented the Kaiser-Guttman factor rotation method. However, the solution could not be rotated because only one component was extracted. All of these considerations indicate the unidimensionality of the SSCP factor. This agrees with the Kaiser-Guttman method’s tendency to overestimate the number of factors (Courtney, 2013). The variance explained by the SSCP factor achieves satisfactory values above 87 per cent. The The possible bidirectional relationships between SSCP and corporate FP varies in different countries’ financial markets depending upon financial market growth patterns. Several academics indicated exogenous factors, such as the growth of an industry, affect the relationship between CSP and FP (Russo and Fouts, 1997). Similarly, Freedman and Jaggi (2005) revealed the link between firms’ FP, and their CSP differed in chemical, energy, vehicle and insurance companies. Furthermore, Elsayed and Paton (2005) found CSP had a positive impact on FP in the chemical and telecommunication industries, but a negative impact on FP in textiles, clothing, metals and motor vehicles. We also contribute to this debate extending the possible industry effect on SSCP and firms’ FP, and thus propose the following hypothesis: H3. The possible bidirectional relationships between SSCP and corporate FP is modified by the industry sector in which companies operate and financial market growth patterns. 336 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 factorial loadings of each different indicator are significant. Similarly, the factor analyses are optimal. The Kaiser-Meyer-Olkin test value is above 0.85. The Bartlett’s sphericity tests indicate that the correlation matrix of the variables included in the analysis differs significantly from the identity matrix. Internal consistency is assured because the values provided by Cronbach’s alpha and Revelle’s beta (Revelle, 1979) are above 0.7 (Nunnally, 1978; Table AI in Appendix). Furthermore, composite reliability is above 0.9. Thus, although Cronbach’s alpha tends to underestimate true reliability (Peterson and Kim, 2013), the differences are non-significant. The measurement scales are highly reliable, indicating the SSCP theoretical concept seems properly defined by the measurement variables (see Table AII and Figure A1 in Appendix). Finally, in a third step, we obtained the SSCP for each company by normalizing factor scores. The SSCP factor varies from 0 to 1, reflecting companies’ lower or higher commitment to SSCP. Twenty-one FP indicators were obtained from the Datastream database (see Table AIII in Appendix for their definitions). All were classified into three different categories: 1 Margins/Performance (FP-MA), which measures a company’s commitment to, and effectiveness at, maintaining a stable cost base, reflecting its capacity to increase its margins by improving its performance, including production process innovations. 2 Profitability/Shareholder Loyalty (FP-PR), which measures a company’s commitment to, and effectiveness at, generating high return on investments and a loyal shareholder base. 3 Revenue/Customer Loyalty (FP-RE), which measures a company’s commitment to, and effectiveness at, generating long-term revenue growth, reflecting its capacity to grow while maintaining a loyal client base through satisfaction programs and avoiding anti-competitive behaviors and price fixing. Table I shows the main descriptive statistics of FP and SSCP. The maximum and minimum values of FP and SSCP dimensions are widely diverse, a promising sign for the investigating the dependence patterns between these constructs. The mean values of SSCP increased from 2004 to 2008, coinciding with large economic growth in major world economies. Furthermore, mean scores of SSCP decreased from 2009 to 2011, the time of the financial crisis. This suggests that SSCP increases while companies’ financial success increases and the two decrease together. However, these findings should be tested to support reliable conclusions. Finally, FP also seems to be influenced by market conditions, showing similar behavior to SSCP (except for the FP-PR dimension, which displays a positive general trend for the sample). 3.3 Econometric models Recent meta-analyses examining the relationship between companies’ financial success and sustainability practices mostly used linear regression (Roman et al., 1999; Margolis and Walsh, 2003; Orlitzky et al., 2003; Wu, 2006; Van Beurden and Gössling, 2008). However, with very few exceptions (Bird et al., 2006; Chatterji et al., 2007), the literature lacks studies of causation between SSCP and FP. Among the various methods available to analyze the causation of these constructs and its direction, the literature highlights the distributed-lag and Granger causality models. We found the latter more suitable for the purposes of this research. The distributed-lag model focuses only on timing and may require determining how far back in time to go to find any interaction between SSCP and FP. The Granger causality model is more concerned with precedence than the usual sense of causation (Scholtens, 2008). Thus, the Granger causality model should yield convincing evidence relevant to such questions as whether changes in SSCP cause changes in FP and vice versa. It allows capturing bidirectional causality between SSCP and FP (Brooks, 2002). The Granger causality test is quite simple (Cheng and Lai, 1997). It is a convenient approach for detecting causation between two variables (Yang, 2000): one called one called xt (Granger-cause), and one called yt, if the prediction of the current value of yt is improved by using several past values of the xt variable and its own past values. Granger’s causality test requires the series of variables to be stationary. In this research, the Augmented Dickey and Fuller (1979) unit root test (ADF) examines the unit roots and stationary property of the variables (see the last column of Table I). The values of the ADF tests for all variables indicate that all are stationary because the null hypothesis of the ADF test – i.e. presence of a unit root – is rejected for all variables at a 1 per cent confidence level. Therefore, the Granger causality test will provide robust estimates. The lag-length selection of the model in Table II is based on Akaike’s information criterion (AIC) and Schwarz’s information criterion (SIC). As shown here, the AIC and SIC favor a model with three lags. To test for Granger causation and following Scholtens (2008), we estimate the following equations: As with SSCP key performance indicators, we undertook three factor analyses. Their results were also satisfactory, showing high adequacy and reliability (see Table AIV and Figure A1 in Appendix). Then the factor-normalized scores were obtained to get the companies’ FP in three dimensions. As with the SSCP factor, the three FP constructs range from 0 to 1, reflecting companies’ levels of financial success. Although these measures of FP can be biased by accounting differences among companies, McWilliams et al. (2006) argued that other measures of FP, such as market-based proxies, only focus on shareholders, although sustainability and SSCP also affect non-financial stakeholders. 3.2 Descriptive analysis We monitored the selected companies from 2004 to 2011 using ASSET4 and DataStream databases. Instead of a regional or industry focus as in previous research, this paper analyzes an impressive 3,941 firms – 31,528 firm-years – grouped in ten primary economic sectors in the Global Industry Classification Standard system. However, there was no match between SSCP and FP for 41 companies, resulting in a final total of 3,900 firms and 31,200 firm-years (see Table AV and Table AVI in Appendix for the distribution of companies in each country and economic sector). 337 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Table I Descriptive statistics for SSCP and FP measures Total sample (n ⴝ 3,900) SSCP (2011) SSCP (2010) SSCP (2009) SSCP (2008) SSCP (2007) SSCP (2006) SSCP (2005) SSCP (2004) FP-MA (2011) FP-MA (2010) FP-MA (2009) FP-MA (2008) FP-MA (2007) FP-MA (2006) FP-MA (2005) FP-MA (2004) FP-PR (2011) FP-PR (2010) FP-PR (2009) FP-PR (2008) FP-PR (2007) FP-PR (2006) FP-PR (2005) FP-PR (2004) FP-RE (2011) FP-RE (2010) FP-RE (2009) FP-RE (2008) FP-RE (2007) FP-RE (2006) FP-RE (2005) FP-RE (2004) Minimum Maximum Mean SD Variance Skewness Kurtosis ADF 0.0667 0.0639 0.0675 0.0755 0.0763 0.1035 0.1021 0.1193 0.0312 0.0423 0.0414 0.0401 0.0404 0.0619 0.0513 0.0623 0.0109 0.0125 0.0154 0.0171 0.0243 0.0371 0.0491 0.0543 0.0111 0.0151 0.0154 0.0132 0.0159 0.0199 0.0232 0.0347 0.9381 0.9423 0.9417 0.9437 0.9496 0.9623 0.9682 0.9702 0.9723 0.9801 0.9812 0.9816 0.9823 0.9901 0.9934 0.9922 0.9709 0.9676 0.9688 0.9812 0.9823 0.9855 0.9834 0.9888 0.9712 0.9788 0.9832 0.9849 0.9810 0.9783 0.9823 0.9799 0.4982 0.4993 0.5005 0.5058 0.5053 0.5013 0.4937 0.4847 0.4931 0.4942 0.5004 0.5006 0.4951 0.4948 0.4957 0.4861 0.5100 0.5099 0.5098 0.5097 0.5050 0.5034 0.5004 0.5001 0.4944 0.4951 0.4953 0.4950 0.4994 0.5040 0.5007 0.4971 0.3204 0.3203 0.3216 0.3196 0.3186 0.3201 0.3178 0.3178 0.3037 0.3022 0.3029 0.3021 0.3020 0.2971 0.2929 0.2912 0.2999 0.2991 0.3004 0.2978 0.2990 0.2986 0.2972 0.2933 0.3011 0.2973 0.2952 0.2924 0.2965 0.3011 0.3012 0.3021 0.103 0.103 0.103 0.102 0.102 0.102 0.101 0.101 0.0922 0.0913 0.0917 0.0913 0.0912 0.0883 0.0858 0.0848 0.0899 0.0895 0.0902 0.0887 0.0894 0.0892 0.0883 0.0860 0.0907 0.0884 0.0871 0.0855 0.0879 0.0907 0.0907 0.0913 0.025 0.028 0.030 ⫺0.007 ⫺0.026 0.115 0.219 0.368 0.044 0.062 0.046 0.033 0.114 0.151 0.162 0.224 0.010 ⫺0.041 ⫺0.031 ⫺0.022 0.004 0.054 0.072 0.106 0.055 0.069 0.150 0.121 0.045 ⫺0.011 0.034 0.030 ⫺1.629 ⫺1.624 ⫺1.644 ⫺1.615 ⫺1.590 ⫺1.640 ⫺1.615 ⫺1.596 ⫺1.343 ⫺1.331 ⫺1.331 ⫺1.317 ⫺1.332 ⫺1.253 ⫺1.206 ⫺1.181 ⫺1.331 ⫺1.315 ⫺1.311 ⫺1.252 ⫺1.287 ⫺1.262 ⫺1.225 ⫺1.234 ⫺1.305 ⫺1.252 ⫺1.227 ⫺1.161 ⫺1.262 ⫺1.323 ⫺1.323 ⫺1.331 ⫺12.717a ⫺16.543a ⫺18.321a ⫺17.520a ⫺15.791a ⫺12.632a ⫺13.583a ⫺16.542a ⫺15.313a ⫺19.756a ⫺18.953a ⫺14.396a ⫺17.502a ⫺16.515a ⫺19.369a ⫺13.579a ⫺15.013a ⫺14.967a ⫺18.888a ⫺16.531a ⫺15.002a ⫺18.396a ⫺19.620a ⫺17.060a ⫺20.321a ⫺12.363a ⫺13.315a ⫺17.513a ⫺14.446a ⫺15.055a ⫺16.316a ⫺17.777a Notes: This table shows the main descriptive statistics of the SSCP measures and the three dimensions of the company’s FP for every period of the sample considered (2004-2011). The last column (ADF) refers to the Augmented Dickey Fuller unit root test values; a H0 of ADF test (presence of a unit root) rejected at a significance level of 1 per cent SSCPi,t ⫽ ␤0 ⫹ ␤1FPi,t-1 ⫹ ␤2FPi,t-2 ⫹ ␤3FPi,t-3 ⫹ ␤4SSCPi,t-1 ⫹ ␤5SSCPi,t-2 ⫹ ␤6SSCPi,t-3 ⫹ ␧i,t (1) FPt ⫽ ␤0 ⫹ ␤1SSCPt-1 ⫹ ␤2SSCPt-2 ⫹ ␤3SSCPt-3 ⫹ ␤4FPt-1 ⫹ ␤5FPt-2 ⫹ ␤6FPt-3 ⫹ ␯i,t (2) where, SSCPi,t refers to the level of SSCP of company i in period t; FPi,t is the level of FP of company i in period t; ␤i is the regression coefficient; and ␧i,t and ␯i,t are each equation’s residuals. Table II Symmetric lag-length selection of the econometric model Lag 1 2 3 4 5 6 7 AIC SIC 5.2345 5.3499 5.4333 5.2265 5.2202 5.2155 5.2012 5.2777 5.3512 5.4501 5.2300 5.2254 5.2189 5.2102 4. Results Tables III-V show parameter estimates for the Granger causality tests. Table III indicates bidirectional causality between margins (FP-MA) and revenue (FP-RE) and SSCP for two reasons. First, both margins and revenue influence companies’ SSCP during stability and crisis. This effect clearly supports the postulates of the slack resources theory, which argues that the availability of slack, financial and other resources provide the chance to invest in CSP, making FP a predictor of SSCP. Second, SSCP caused companies’ margins Notes: The table shows the values reached by Akaike’s information criterion (AIC) in the second column and Schwarz’s information criterion (SIC) in the third column for each lag of the econometric model (first column). The best lag-length selection is shown in bold 338 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Table III Granger causality tests of SSCP and FP FP (dimensions) SSCP does not Granger cause FP dimension Pre-crisis period Crisis period F-value Significance F-value Significance FP dimension does not Granger cause SSCP Pre-crisis period Crisis period F-value Significance F-value Significance FP-MA (margins) FP-PR (profitability) FP-RE (revenue) (94.41) (3.04) (67.21) (123.22) (2.64) (91.21) 0.000 0.170 0.000 (243.05) (8.41) (33.65) 0.000 0.000 0.000 0.000 0.032 0.000 (101.11) (2.25) (77.21) 0.000 0.061 0.000 Notes: This table shows the p-values of the Granger causality tests between SSCP and firms’ FP for the full sample and for both the pre-crisis and of financial crisis periods. Parameters are shown in bold and italics when the null of no causation can or cannot be rejected. Parameters inside parentheses refer to the F-values of the Granger causality tests Summarizing and comparing causation patterns between SSCP and FP across different geographical areas, it appears that these linkages are relatively complex, presenting bidirectional, unidirectional and missing relationships. This suggests that SSCP – FP relationships vary among financial markets around the world, supporting H2. The estimates in Table V reveal the wide diversity in the SSCP – FP relationship patterns in different economic sectors. In general, there appears to be bidirectional causation between companies’ margins and levels of SSCP, with the sole exception of the telecommunications sector, where SSCP did not cause margins during the bullish market from 2004 to 2008. This can be explained: telcos during the pre-crisis period were dealing with the dot-com collapse beginning around 2001. This effect also appears in this sector when relations between SSCP and profitability and revenue are examined to add robustness to the effects observed on those companies’ margins. SSCP and all other companies’ revenue seem bidirectionally related. The results generated by the causality tests of SSCP and companies’ profitability demonstrate a wide range of relationship patterns between those constructs in different economic sectors. First, companies’ profitability did not cause SSCP during the pre-crisis period (2004-2008), with the exceptions of the healthcare, non-cyclical consumer goods and services, technology and utilities sectors. Moreover, companies’ profitability did not precede the SSCP attained by companies during the financial crisis, except for the non-cyclical consumer goods and services and utilities sectors. These findings may indicate that companies in non-cyclical economic sectors were less harmed by the financial crisis. On the other hand, companies that showed a significant link between profitability and SSCP during the pre-crisis period and in cyclical sectors, such as healthcare and technology, were more market-sensitive and more likely to put economic and financial issues ahead of social and environmental ones during the financial crisis. Exploring the opposite relationship reveals that SSCP causes profitability of companies operating in the financial, non-cyclical consumer goods and services and utilities sectors. Thus, utilities and non-cyclical consumer goods and services companies showed a bidirectional link between SSCP and FP during the sample period. However, the precedence link between SSCP and financial companies’ profitability disappeared during the bear market, when their profitability was strongly harmed by toxic assets such as sovereign debt of questionable liquidity and negative return, collateralized debt obligations and subprime mortgages. On the contrary, SSCP caused the FP-PR of basic materials, and revenue, in line with good management theory, indicating SSCP causes companies’ financial and economic performance. Examining the interactions between SSCP and the last dimension of companies’ FP (i.e. companies’ profitability [FP-PR]), slightly different behavior is appreciated than that observed for companies’ margins and revenues because of two observed effects. First, companies’ profitability caused SSCP only during the pre-crisis period (2004-2008). This result can be explained by the slack resources to theory. Second, the results indicate that SSCP did not cause profitability in a pre-crisis period, but preceded profitability during the crisis. These results indicate companies’ managers should take care of SSCM in down markets because of its influence on profitability levels. All of these considerations indicate that the emergence and consolidation of the financial crisis did change the precedence link between SSCP and companies’ FP, supporting H1. Table IV presents the estimates of the Granger causality tests between SSCP and FP when the selected companies are grouped by geographical areas. It appears that SSCP and the three FP dimensions of African companies are not related. This indicates the absence of precedence patterns between companies’ FP (i.e. margins, revenue, and profitability) and SSCP. This is not in line with the premises of the slack resources or good management theories. There was bidirectional causality between the SSCP and FP of American companies during the two periods of the full sample. In addition, during market stability, there was bidirectional causality from SSCP to the three dimensions of FP in European companies. However, the SSCP and FP of European companies are not associated during the financial crisis, a result that may indicate influence on the FP of European companies from other financial factors. Results reveal bidirectional causation between Asian companies’ FP and SSCP, supporting slack resources and good management theories. The only exception is that SSCP did not cause the profitability (FP-PR) of Asian companies during the pre-financial crisis period. Finally, results in Table IV suggest some interactions between the SSCP and FP of Oceanian enterprises, namely, SSCP precedes companies’ margins and revenues. Furthermore, Oceanian companies’ profitability precedes their SSCP during the financial crisis. However, the profitability of these companies did not predict their SSCP during the market downturn. Yet, during the financial crisis, the Oceanian companies’ SSCP preceded their profitability. Finally, the results show that, during market stability (2004-2008), SSCP and revenue were not related. 339 340 0.892 0.310 0.821 FP-MA (Margins) FP-PR (Profitability) FP-RE (Revenue) 0.761 0.534 0.832 0.899 0.391 0.701 Crisis period 0.000 0.003 0.000 0.000 0.061 0.000 Pre-crisis period Asia Europe Pre-crisis Crisis period period 0.000 0.000 0.000 SSCP does not Granger cause FP dimension 0.000 0.551 0.000 0.821 0.000 0.449 FP dimension does not Granger cause SSCP 0.000 0.000 0.743 0.009 0.000 0.799 0.000 0.000 0.501 Crisis period 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 America Pre-crisis Crisis period period 0.000 0.069 0.003 0.000 0.569 0.000 0.000 0.221 0.000 0.000 0.042 0.000 Oceania Pre-crisis Crisis period period Notes: This table shows the p-values of the Granger causality tests between SSCP and firms’ FP when the full sample is divided by geographical area, both before and during the financial crisis. Parameters are shown in bold and italics when the null of no causation can or cannot be rejected 0.712 0.512 0.654 FP-MA (Margins) FP-PR (Profitability) FP-RE (Revenue) FP dimensions Africa Pre-crisis period Table IV Granger causality tests of SSCP and FP by geographical area Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Table V Granger causality tests of SSCP and FP by economic sector FP-MA (Margins) Pre-crisis Crisis period period Basic materials Cyclical consumer goods and services Energy Financial Healthcare Industrials Non-cyclical consumer goods and services Technology Telecommunications services Utilities 0.000 0.000 0.000 0.000 0.023 0.000 0.000 0.000 0.059 0.010 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Basic materials Cyclical consumer goods and services Energy Financial Healthcare Industrials Non-cyclical consumer goods and services Technology Telecommunications services Utilities 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.012 0.000 0.000 0.000 0.000 0.005 0.000 0.000 0.000 0.005 0.000 FP-PR (Profitability) Pre-crisis Crisis period period SSCP does not Granger cause FP dimension 0.251 0.011 0.899 0.445 0.201 0.119 0.041 0.404 0.788 0.011 0.506 0.401 0.002 0.019 0.149 0.772 0.455 0.401 0.034 0.018 FP dimension does not Granger cause SSCP 0.432 0.591 0.531 0.602 0.589 0.291 0.201 0.243 0.021 0.242 0.897 0.145 0.019 0.004 0.001 0.306 0.632 0.159 0.029 0.023 FP-RE (Revenue) Pre-crisis Crisis period period 0.000 0.000 0.021 0.000 0.000 0.000 0.000 0.000 0.059 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.011 0.000 0.000 0.000 0.000 0.002 0.225 0.012 0.000 0.011 0.009 Notes: This table shows the p-values of the Granger causality tests of SSCP and firms’ FP when the full sample is divided by the economic sector before and during the financial crisis. Parameters are shown in bold and italics when the null of no causation can or cannot be rejected One of the most important findings is the support for a significant, bidirectional causation between SSCP and companies’ margins and revenue. This remained true for companies’ profitability and SSCP during bull markets but not during the financial crisis. These findings show that managers mostly serve shareholders’ interests during bear markets, prioritizing financial and economic issues over environmental concerns. Furthermore, this research reveals that the relationship between SSCP and FP is not static but changes with macroeconomic conditions. It also varies with geography. Regions showed bidirectional relationships except in Africa and in Europe specifically during the financial crisis. These exceptions need further analysis. Another relevant finding of this paper is that for all other companies analyzed, SSCP acts as a driver with a significant impact on FP. Furthermore, this relationship is even more significant when FP is measured through margins. Because operational costs are a key factor in margins, this research emphasizes that SSCP lets companies reduce costs (specifically related to environmental expenditures) by developing new technologies that mitigate their activities’ environmental impact. This is particularly relevant because increasing SSCP benefits companies in other ways: ● improved efficiency; ● higher product quality; ● a lead on competitors and legislation; ● access to new markets; ● increased employee motivation and satisfaction; ● improved public relations; healthcare and non-cyclical companies during the financial crisis. These considerations suggest that the economic sector in which companies operate can modify the relationship between SSCP and FP, supporting H3. 5. Conclusions Sustainability performance measurement is one of the key issues comprising the broad concept of CSR. The possibility of measuring the companies’ social and environmental performance brings up the opportunity to analyze the instrumentality of CSR. Considering the usefulness, in financial terms, of CSR activities in SCM, may promote the implementation of sustainability practices in companies’ supply chains. Sustainability performance measurement literature provides conflicting views about the relationship between SSCP and companies’ FP. One view is that the best financial performers have slack resources available to invest in improving their SSCP. An opposite view is that companies that increase their SSCP through their commitment to environmental concerns, consequently, improve their FP. This view holds that addressing environmental issues as part of corporate strategy can create new opportunities for competition, as well as new ways to add value to core business programs, improving long-term FP. This paper investigated empirical evidence about the possibly bidirectional relationship patterns between SSCP and FP. Multivariate measures of SSCP and FP supplied Granger causality tests of these constructs with a large, diverse sample of 3,900 firms over eight years (2004-2011). 341 ● ● Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 References financial aid; and better organizational reputation. Abbott, W.F. and Monsen, R.J. (1979), “On the measurement of corporate social responsibility: self-reported disclosures and a method of measuring corporate social involvement”, Academy of Management Journal, Vol. 22 No. 3, pp. 501-515. Allouche, J. and Laroche, P. (2005), “A meta-analytical investigation of the relationship between corporate social and financial performance”, Revue de Gestion des Resources Humaines, Vol. 57, pp. 18-41. 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The following three are among the main limitations of this research: 1 We used a huge sample of companies and years of data that generated statistical robustness; yet, to refine the link between SSCP and FP, one must analyze the quality of SSCP management with respect to the range of possibilities for improving SSCP efficiently (Schaltegger and Synnestvedt, 2002). 2 We used environmental indicators to measure SSCP, but characterized this unobservable factor by explicit integration of environmental or social objectives which extend the economic dimension to the triple bottom line (Seuring and Müller, 2008), thus comprising social issues such as occupational health and safety and child labor. 3 Granger causality tests in this research only capture a correlation between the current value of one variable and the past values of others (Scholtens, 2008). Thus, it does not mean that changes in one variable cause changes in another variable (Brooks, 2002). 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Does the company use environmental criteria (e.g., ISO 14000, energy consumption) in the selection process for its suppliers or sourcing partners? Does the company report or end a partnership with a sourcing partner if environmental criteria are not met? Does the company survey its suppliers’ environmental performance? Does the company describe, claim to have or mention processes to include its supply chain in its efforts to lessen its overall environmental impact? Does the company claim to use key performance indicators or a balanced scorecard to monitor the environmental impact of its supply chain? Has the company set targets or objectives to be achieved for the environmental impact of its supply chain? Is the company making progress toward or achieving its objectives for the environmental impact of its supply chain? 0.823ⴱⴱⴱ Number of eigenvalues above one: 1 0.889ⴱⴱⴱ Variance explained: 87.15 per cent 0.799ⴱⴱⴱ Kaiser–Meyer–Olkin test: 0.859 0.845ⴱⴱⴱ Barlett’s sphericity test: 0.865ⴱⴱⴱ ␹2 ⫽ 325.834ⴱⴱⴱ (28 df) 0.891ⴱⴱⴱ Cronbach’s alpha ⫽ 0.901 0.834ⴱⴱⴱ Revelle’s beta ⫽ 0.873 0.871ⴱⴱⴱ Composite Reliability ⫽ 0.904 SSCP KI 2 SSCP KI 3 SSCP KI 4 SSCP KI 5 SSCP KI 6 SSCP KI 7 SSCP KI 8 Note: *** Significant at 1% 347 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Table AII SSCP construct factor information Initial eigenvalues Variance Cumulative variance (per cent) (per cent) Total 1 2 3 4 5 6 7 8 4.052 0.790 0.710 0.650 0.550 0.470 0.401 0.377 87.15 4.00 3.23 2.10 1.30 0.80 0.75 0.67 87.15 91.15 94.38 96.48 97.78 98.58 99.33 100.00 Total Extraction sums of squared loadings Variance Cumulative variance (per cent) (per cent) 4.052 87.15 87.15 Table AIII FP construct’s key indicators (KI) Factor Indicator FP-MA FP FP FP FP FP FP FP FPⴚPR FP KI 8 FP KI 9 FP KI 10 FPⴚRE FP FP FP FP FP FP FP FP FP KI KI KI KI KI KI KI KI KI KI KI KI KI KI KI KI 1 2 3 4 5 6 7 11 12 13 14 15 16 17 18 19 FP KI 20 FP KI 21 Note: *** Description Loading Percentage change of operating income in the past three years Net income growth (three-year annual growth) Operating profit margin Net margin Return on assets (ROA) Sales in USD per employee Total salaries and benefit expenses (staff costs) divided by net sales or revenue Return on equity (ROE) Return on invested capital (ROIC) Operating cash flow (or unlevered free cash flow [UFCF]) growth (three-year annual growth) Current ratio (total current assets/total current liabilities) Net debt to equity Long-term debt to equity Retained earnings divided by equity Dividend payout ratio Net sales or revenue growth (three year annual growth) Net sales or revenue in USD Research and development costs divided by net sales or revenue Total US patents owned in the current year divided by net sales or revenue in USD Variability of quarterly sales over the past three years Total value of the company’s brands in USD Significant at 1% 348 Construct information ⴱⴱⴱ 0.801 0.934ⴱⴱⴱ 0.971ⴱⴱⴱ 0.911ⴱⴱⴱ 0.952ⴱⴱⴱ 0.949ⴱⴱⴱ 0.812ⴱⴱⴱ Number of eigenvalues above one: 1 Variance explained: 92.77 per cent Kaiser–Meyer–Olkin test: 0.904 Barlett’s sphericity test: ␹2 ⫽ 343.001ⴱⴱⴱ (21 df) Cronbach’s alpha ⫽ 0.924 Revelle’s beta ⫽ 0.889 Composite reliability ⫽ 0.926 0.923ⴱⴱⴱ 0.917ⴱⴱⴱ 0.895ⴱⴱⴱ Number of eigenvalues above one: 1 Variance explained: 91.54 per cent Kaiser–Meyer–Olkin test: 0.899 Barlett’s sphericity test: ␹2 ⫽ 395.845ⴱⴱⴱ (28 df) Cronbach’s alpha ⫽ 0.913 Revelle’s beta ⫽ 0.854 Composite reliability ⫽ 0.916 0.873ⴱⴱⴱ 0.894ⴱⴱⴱ 0.900ⴱⴱⴱ 0.912ⴱⴱⴱ 0.888ⴱⴱⴱ 0.941ⴱⴱⴱ 0.937ⴱⴱⴱ 0.931ⴱⴱⴱ 0.891ⴱⴱⴱ 0.915ⴱⴱⴱ 0.924ⴱⴱⴱ Number of eigenvalues above one: 1 Variance explained: 83.21 per cent Kaiser–Meyer–Olkin test: 0.801 Barlett’s sphericity test: ␹2 ⫽ 300.834ⴱⴱⴱ (15 df) Cronbach’s alpha ⫽ 0.851 Revelle’s beta ⫽ 0.802 Composite reliability ⫽ 0.856 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Table AIV FP construct’s factor information Initial eigenvalues Variance Cumulative variance (per cent) (per cent) Total FP-MA 1 2 3 4 5 6 7 FP-PR 1 2 3 4 5 6 7 8 FPⴚRE 1 2 3 4 5 6 Total Extraction sums of squared loadings Variance Cumulative variance (per cent) (per cent) 3.405 0.832 0.783 0.642 0.500 0.432 0.406 92.77 2.45 1.99 1.01 0.90 0.79 0.09 92.77 95.22 97.21 98.23 99.12 99.91 100 3.405 92.77 92.77 6.075 0.603 0.522 0.301 0.204 0.150 0.094 0.051 91.54 3.770 2.033 0.904 0.521 0.476 0.401 0.355 91.54 95.31 97.34 98.25 98.77 99.24 99.65 100 6.075 91.54 91.54 3.753 0.779 0.745 0.303 0.256 0.164 83.21 5.888 4.824 3.009 2.155 0.914 83.21 89.10 93.92 96.93 99.09 100.00 3.753 83.21 83.21 Table AV Companies in the sample classified by country Country Abu Dhabi Australia Austria Belgium Brazil Canada Channel Islands Chile China Colombia Cyprus Czech Republic Denmark Dubai Egypt Finland France Germany Greece Hong Kong Number of companies Percentage 1 298 20 27 68 297 1 18 73 4 1 4 25 1 4 27 94 82 22 128 0.03 7.64 0.51 0.69 1.74 7.62 0.03 0.46 1.87 0.10 0.03 0.10 0.64 0.03 0.10 0.69 2.41 2.10 0.56 3.28 Country Number of companies Percentage 4 59 23 16 14 51 424 1 1 4 6 40 21 2 34 11 1 23 1 1 0.10 1.51 0.59 0.41 0.36 1.31 10.87 0.03 0.03 0.10 0.15 1.03 0.54 0.05 0.87 0.28 0.03 0.59 0.03 0.03 Hungary India Indonesia Ireland Israel Italy Japan Jordan Kazakhstan Kuwait Luxembourg Malaysia Mexico Morocco The Netherlands New Zealand Nigeria Norway Oman Peru Notes: This table shows the companies analyzed in the empirical work and classified by country 349 Country Philippines Poland Portugal Qatar Russia Saudi Arabia Singapore South Africa South Korea Spain Sri Lanka Sweden Switzerland Taiwan Thailand Turkey UK US Zimbabwe Total Number of companies Percentage 11 21 12 2 34 6 52 50 90 49 1 50 65 96 21 20 333 1,054 1 3,900 0.28 0.54 0.31 0.05 0.87 0.15 1.33 1.28 2.31 1.26 0.03 1.28 1.67 2.46 0.54 0.51 8.54 27.03 0.03 100 Sustainable supply chain and company performance Supply Chain Management: An International Journal Eduardo Ortas, José M. Moneva and Igor Álvarez Volume 19 · Number 3 · 2014 · 332–350 Table AVI Companies in the sample classified by economic sector About the authors Number of companies Percentage Economic sector Basic materials Cyclical consumer goods and services Energy Financial Healthcare Industrials Non-cyclical consumer goods and services Technology Telecommunications services Utilities Total 481 592 347 791 222 609 263 285 123 187 3,900 Eduardo Ortas is an Assistant Professor of Finance at the Faculty of Business Administration of the University of Zaragoza. He holds a PhD in Accounting and Finance from the University of Zaragoza. He has participated in many national and international research projects related with sustainability, corporate social responsibility and ethical investment. His research focuses on corporate social, environmental and financial performance, sustainable supply chain management, socially responsible investment and other topics related with corporate sustainability. His publications include textbooks and research papers in relevant international journals. Eduardo Ortas is the corresponding author and can be contacted at: edortas@unizar.es 12.33 15.18 8.90 20.28 5.69 15.62 6.74 7.31 3.15 4.79 100 Notes: This table shows the companies analyzed in the empirical work and classified by economic sector as indicated by the Global Standard Classification Standard (GICS) José M. Moneva is a Professor of Accounting and Finance at the Faculty of Business Administration of the University of Zaragoza. He has directed and participated in different national and international research projects related with sustainability, corporate social responsibility and ethical investment. His research focuses on corporate social, environmental and financial performance; sustainable supply chain management; socially responsible investment; and other topics related with corporate sustainability. His publications include textbooks and research papers in relevant international journals (www.catedrabsh-uz.es/ pdf/CVen-jmmoneva.pdf). Figure A1 Sustainable supply chain performance and financial performance constructs’ scree plots 7 SSCP FP-MA FP-PR FP-RE 6 5 4 Igor Álvarez is an Assistant Professor of Accounting at the Faculty of Business Administration of the University of Basque Country. He holds a PhD in Accounting and Finance from University of Basque Country. He has participated in many national and international research projects related with sustainability, corporate social responsibility and social and environmental disclosure. His research focuses on corporate social, environmental and financial performance; sustainable supply chain management; social and environmental disclosure; and other topics related with corporate sustainability. His publications include textbooks and research papers in international journals. 3 2 1 0 1 2 3 4 5 6 7 8 Notes: This figure shows the scree plots for the SSCP and the three unobservable constructs of financial performance. The x-axis represents the component number and the y-axis represents the eigenvalues To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints 350 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. www.ccsenet.org/ijbm International Journal of Business and Management Vol. 7, No. 4; February 2012 What is a Responsible Supply Chain? Terje I.Vaaland (Corresponding author) UiS Business School, University of Stavanger NO-4035 Stavanger, Norway Tel: 47-9098-1256 E-mail: terje.vaaland@uis.no Richard Afriyie Owusu Faculty of Business Studies, University of Vaasa FI-65101 Vaasa, Finland E-mail: kwakus2403@hotmail.com Received: October 24, 2011 Accepted: November 9, 2011 Published: February 16, 2012 doi:10.5539/ijbm.v7n4p154 URL: http://dx.doi.org/10.5539/ijbm.v7n4p154 The research is financed by A/S Norske Shell and the EPCI Foundation Abstract The paper introduces the concept of responsible supply chain based on two dimensions, the core processes of a supply chain and the concept of corporate social responsibility (CSR). It is suggested that a responsible supply chain is achieved through manifested core values of the supply chain actors, strategies, and tactics. The paper further discusses the individual supply chain actors’ responsibility in securing a responsible supply chain beyond the actors’ direct contr...
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