Socially responsible supplier development: Construct development and measurement validation

Int. J. Production Economics 140 (2012) 160–167

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Socially responsible supplier development: Construct development and measurement validation Rainy X.A. Lu 1, Peter K.C. Lee n, T.C.E. Cheng 2 Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hong Kong, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 29 October 2010 Accepted 27 January 2012 Available online 2 February 2012

Chinese manufacturing has recently been plagued by a raft of product safety problems such as melamine-tainted milk, lead-tainted toys, toxic toothpaste, defective tyres, and fake medicines. A probable cause of these incidents is a lack of business ethics in the suppliers concerned. In the literature much has been suggested on the use of corporate social responsibility (CSR) to improve firms’ ethical behaviors and on the use of supplier development (SD) to improve suppliers’ capabilities. This research integrates the literature on CSR and SD to develop a new approach, called socially responsible supplier development (SRSD), to address suppliers’ ethical problems. SRSD suggests leveraging a buying firm’s concerted supplier development efforts to improve its important suppliers’ capabilities in CSR implementation. We develop and validate scales for measuring SRSD practices. In addition, we provide empirical evidence on the validity of existing CSR scales for Chinese manufacturing firms. Our results are based on analysis of the data of 160 pairs of buyer–supplier relationships in four manufacturing industries in China. The results indicate that all the scale items possess adequate reliability and validity to reflect SRSD and CSR. We also discuss the implications of our findings for research and practice. & 2012 Elsevier B.V. All rights reserved.

Keywords: Corporate social responsibility Supplier development Survey Scale development and validation

1. Introduction Although many researchers have strongly advocated that any manufacturing organization should develop in sustainable ways that satisfy the needs of multiple stakeholders and create values through environmental and social performance (Ciliberti et al., 2008; Vachona and Klassen, 2008; Pagell and Gobeli, 2009), many manufacturers are still severely affected by unethical behaviors that occur in their manufacturing processes and supply chains. For instance, a pet food manufacturer, Menu Foods, paid a $24 million settlement to customers in 2008 because its Chinese suppliers intentionally spiked the gluten with melamine to pass chemical inspection (Tybout and Roehm, 2009). Unfortunately, melamine was used not only in pet food, But also in milk products for humans. The melamine-tainted milk manufactured in China caused nearly 300,000 people to fall sick and several deaths of infants (DeLaurentis, 2009). The dairy products of 21 manufacturers including such major players as Mengniu, Yili, and Sanlu were also found contaminated. The scandal spread into a global concern with recalls, bans, or warnings of contaminated food

n

Corresponding author. Tel.: þ852 2766 7415; fax: þ852 2330 2704. E-mail addresses: [email protected] (R.X.A. Lu), [email protected] (P.K.C. Lee), [email protected] (T.C.E. Cheng). 1 Tel.: þ852 6200 8760; fax: þ 852 2330 2704. 2 Tel.: þ852 2766 5216; fax: þ852 2330 2704. 0925-5273/$ - see front matter & 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.ijpe.2012.01.032

being reported in Europe, the USA, and Asia (BBC, 2010; DeLaurentis, 2009). Investigations revealed that the problems were caused by suppliers. They are farms or similar businesses, which added melamine to diluted milk to boost the apparent presence of protein in the milk (Ma, 2009; Fairclough, 2008). In addition to food-related organizations, Mattel, a toy company, recalled approximately 14 million toys because of their excessive levels of lead or the presence of small detachable magnets that can be swallowed. This scandal resulted in Mattel facing numerous lawsuits and suffering severe reputation damage (Gilbert and Wisner, 2010). Similarly, it is not Mattel but its suppliers that produce the defective toys. There are other similar supplierrelated ethical problems such as toxic toothpaste, defective tyres, and fake medicines (Ip, 2009; Lu, 2009) and strong public criticisms of Nike, Adidas, and Sainsbury for their failure in controlling labor abuses in their suppliers (Barton, 2007; Yu, 2008; Emmelhainz and Adams, 1999). These supplier-related ethical problems and their consequences imply that buying firms need to recognize suppliers’ ethical problems as a strategically important concern. In the management literature, concerns for managing ethics in organizations typically refer to the approach of corporate social responsibility (CSR). One common perspective to understand CSR is to use stakeholder theory to conceptualize CSR as the extent to which businesses assume the economic, legal, ethical, and discretionary responsibilities imposed on them by their various stakeholders (Maignan et al., 1999). The

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success of employing CSR to address issues of ethics and enhance organizational performance has been well documented in the literature (e.g., Luo and Bhattacharya, 2006; McWilliams and Siegel, 2000). On the other hand, the operations and supply management literature has widely reported that supplier development (SD) is a viable approach for buying firms to improve the capabilities of their suppliers. Similarly, SD’s effectiveness in improving the operational performance of both the supplier and the buying firm is supported empirically by a number of studies (e.g., Krause et al., 2000, 2007). However, the current understanding of CSR and SD offers very few guidelines on how a buying firm can enhance its suppliers’ CSR capabilities. To fill this void, we introduce a novel approach in this research – socially responsibly supplier development (SRSD) – to address suppliers’ ethical problems. SRSD refers to the concerted supplier development efforts made by a buying firm to improve its important suppliers’ capabilities to CSR implementation. We expect that by implementing SRSD, important suppliers will be induced to implement CSR and the ethical performance of both suppliers and the buying firms will be improved. In order to advance the understanding of SRSD, we develop and test the measurement scales for SRSD in this research. Using qualitative methods including literature review, expert panel discussion involving six professionals, and a pilot test involving managers of 20 manufacturers, we identify three dimensions and the corresponding scale items of SRSD. Based on the data of 160 paired buyer–supplier manufacturers in China, we quantitatively validate the scales through various statistical tests. In addition, we also validate the scale items of seven selected dimensions of CSR. The contributions of this research to theory and practice are four-fold. First, we address the recent supplier-related ethical problems by introducing the SRSD concept that offers practical insights to manufacturers on how to take a proactive role in enhancing the ethical practices and performance of their suppliers. Second, we extend both the operations and supply management literature and the business ethics literature by introducing and developing the SRSD concept. Indeed, the development of the SRSD concept sheds light on how to integrate concepts from differing academic disciplines to generate a solution for a practical problem. Third, researchers can use the SRSD scales developed in this research to further test and refine the concept empirically. Practitioners can also use the scales as an assessment tool to evaluate their SRSD implementation status. Finally, in addition to developing the new SRSD scales, we also examine and validate seven relevant dimensions of CSR and their scale items in this research. Given the lack of validation studies on the use of CSR scales in Chinese organizations, our validation results contribute to improving the generalizability of the current CSR scales. The remainder of this paper is divided into three parts. In the second part we provide a literature review of related works on sustainability, ethics, operations management (OM), SD, and CSR, and discuss the theoretical background underpinning the development of the SRSD concept and its three underlying dimensions. In the third section we present and elaborate on the results of using qualitative and quantitative methods to develop and validate the SRSD and CSR scales. Finally, in the last section we discuss the theoretical and managerial implications of the research findings, and suggest topics for future research.

2. Conceptual background 2.1. Sustainability, ethics, and corporate social responsibility in operations management The importance of sustainability, ethics, and CSR has attracted increasing attention of operations and supply management

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researchers. For instance, Ciliberti et al. (2008) link the adoption of CSR practices to logistics management by developing a framework of ‘‘Logistics Social Responsibility’’ to address various sustainable supply chain management issues. Kleindorfer et al. (2005) conduct a review of the OM literature and offer insights on future sustainability challenges facing OM researchers and practitioners. Other researchers have pointed out that the sustainable development of organizations can be influenced by OM concepts such as product design, by-product management, product life extension, recovery processes, reverse logistics, and logistics network design (e.g., Matos and Hall, 2007; Kocabasoglu et al., 2007; Zhu et al., 2008). In addition, some traditional OM quantitative methods have been employed to examine sustainability problems such as determining the optimal CSR resource allocation for achieving maximum net returns and minimum emissions (Cruz and Wakolbinger, 2008). Nonetheless, because of increasing interdependence between buyers and suppliers in supply chains, many supply management researchers propose to extend the scope of concern to include upstream suppliers when formulating approaches to enhance sustainability or ethical performance. For instance, Vachona and Klassen (2008) assert the importance of supplier collaboration on environmental practices and empirically test the impact of joint actions in environmental planning, pollution reduction activities, and environmental goal setting on process-based performance. Carter and Jennings (2004) investigate the potential contributions of purchasing to CSR adoption with respect to such dimensions as community, workplace, safety, and human right, etc. Researchers have also considered other issues such as purchasing from minority business enterprises (e.g., Carter et al., 1999), and having a concern for the environment (e.g., Carter and Carter, 1998) and human rights (e.g., Emmelhainz and Adams, 1999). While organizations are well aware that they will be adversely affected by the unethical behaviors of their suppliers, managerial guidelines on how a buying firm may proactively enhance its suppliers’ capabilities in implementing ethics-related practices are virtually unavailable in the literature. A link between the concepts of CSR, sustainable development, and business ethics has been established since the late 1990s and many scholars even consider them as synonyms (Ciliberti et al., 2008). Of these three concepts, CSR is widely considered as a management approach for achieving sustainable development and ethics, and it is closely associated with the recent triple bottom line (3BL) framework (i.e., people, profit, and the planet) (Elkington, 1998). Broadly speaking, CSR refers to ‘‘actions that appear to further some social good, beyond the interest of the firm and that which is required by law’’ (McWilliams and Siegel, 2001). This understanding of CSR has been expanded from the perspective of stakeholder theory, which emphasizes corporate responsibilities towards multiple stakeholders that affect and are affected by organization’s actions (Freeman, 1984). Several empirical studies have provided evidence that CSR adoption can effectively reduce unethical practices and agency problems, strengthen relationships with primary stakeholders (e.g., increased employee commitment and customer satisfaction), and establish organization’s trustworthiness (Clarkson, 1995; Jones, 1995; Maignan and Ferrell, 2004). Moreover, the engagement of CSR is strongly linked to the creation of corporate reputation, which is considered to be an intangible resource for corporate sustainable development (Russo and Fouts, 1997). Obviously, if a buying firm intends to influence a supplier’s ethics management practices and performance, it could focus on influencing the supplier to implement CSR. However, although the OM and supply management literature has been replete with ideas on supplier management, suggestions on how a buying firm can influence its suppliers to implement CSR have been lacking.

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2.2. Supplier development and socially responsible supplier development Lee and Kim (2009) examine CSR adoption in suppliers from the perspective of supply management and find that suppliers may not be able to implement CSR effectively because of their lack of social responsibility consciousness and resources such as time and money for the necessary operational changes and capacity building. In addition, some researchers have pointed out the importance of buyer’s influence and support to supplier’s CSR adoption through inter-organizational learning and collaboration (Maignan and Ferrell, 2004; Choi and Wang, 2009; Andersen and Skjoett-Larsen, 2009; Salam, 2009; Tate et al., 2010). In this research we argue that SD is a relevant management practice in that its elements and the related actions can be adapted by buying firms to influence their suppliers to implement CSR. The term supplier development was introduced by Leenders (1966) to represent the efforts made by manufacturers to improve their suppliers’ performance. More recently, SD has been widely considered as an effective approach for buyers to improve their suppliers’ capabilities and performance (Krause et al., 2007). A number of studies have offered empirical evidence that SD is effective in solving the buyer’s productivity and quality problems (Krause et al., 1998), and improving its operational performance (Humphreys et al., 2004; Krause et al., 2000). The elements of SD consist of operational knowledge transfer activities, such as shared vision, direct involvement, and supplier assessment (Krause et al., 2007). Furthermore, Modi and Mabert (2007) maintain that SD can facilitate the flow of tacit manufacturing and operations knowledge across organizational boundaries through diverse communication activities and resource allocation. In view of SD’s effectiveness in influencing suppliers and its elements that facilitate the transfer of tacit knowledge, we believe that it is an appropriate base to develop a new management approach—socially responsible supplier development. We define SRSD as a buyer firm’s concerted supplier development efforts to improve its important suppliers’ capabilities and commitment to CSR implementation. Consequently, through the implementation of SDSR, a buying firm can proactively influence its suppliers to implement CSR in order to enhance its own ethical performance. According to Krause et al. (2007), SD comprises seven dimensions, namely buyer commitment, shared values, information sharing, supplier evaluation, supplier development activities, supplier dependence, and buyer dependence. In order to identify which of these dimensions are particularly related to the actions of SRSD, we conducted an in-depth interview with a panel of experts. The interview results suggest that information sharing, supplier evaluation, and supplier development activities are the more relevant dimensions. The expert panel commented that the other four dimensions mainly pertain to the importance of supplier relationship rather than the actions for developing supplier capabilities. Based primarily on the suggestions of the panel, we identify and develop the definitions and scales for the three dimensions of SRSD. The first dimension of SRSD is socially responsible information sharing (SR-information sharing), which refers to the sharing and discussion of knowledge of CSR concepts and implementation between the buying firm and the supplier. Through SR-information sharing, suppliers can learn CSR knowledge such as the fundamental concepts, related practices, implementation guidelines, and outcome measurement, etc. The second dimension of SDSR is socially responsible supplier evaluation (SRsupplier evaluation), which refers to buyer’s efforts in regularly assessing suppliers’ CSR implementation processes, and relevant ethical behaviors, and outcomes. This dimension also involves providing feedback and rewards to suppliers on a regular basis. The third dimension of SRSD is socially responsible supplier

development (SR-supplier development), which refers to buyer’s efforts in identifying improvement areas in suppliers’ CSR implementation and in taking necessary actions to rectify problems. Example actions of this dimension include ethical performance record study, site visit, problem identification analysis, training, etc. In sum, in a SRSD program, SD-information sharing is about the transfer of CSR knowledge to suppliers, SR-supplier evaluation is about the use of an audit and feedback system to monitor suppliers’ CSR implementation and outcomes, and SR-supplier development is about making direct improvement efforts in suppliers’ CSR implementation. 2.3. CSR dimensions and scales If SRSD is an effective practice, its direct result should be the effective implementation of CSR in suppliers. Thus, to assess the validity of the SRSD scales developed in this research, we need to investigate how the buying firm’s SRSD adoption is associated with its suppliers’ CSR adoption. However, the measurement of CSR could be a problematic issue because of the diverse operationalization results available in the literature. For instance, CSR, as a political behavior, embodies government concerns, organization credibility, philanthropic contribution, and resource accommodation (Luo, 2006). From the perspective of stakeholder theory, CSR embraces the responsibilities towards five related parties, including the community, investors, employees, customers, and suppliers (Spiller, 2000). The environmental dimension is also considered a key dimension of an organization’s sustainable development (Lindgreen et al., 2009). A review of the CSR literature suggests that the CSR approach consists of multiple facets, including economic responsibility, legal responsibility, environmental protection, consumerism, shareholder interests, staff development, and equality (Xu and Yang, 2010). Furthermore, when there is a weak legal system in countries such as China, ethics code should be one of the important dimensions to represent CSR (Luo, 2006). Based on the information found from the literature review and the comments of the expert panel, we identify that CSR has seven dimensions, which are concerns for ethics codes, investors, employees, suppliers, customers, environmental protection, and the community. In fact, most of the existing CSR scales are validated by using service organization data collected in the USA. Using data from Chinese manufacturers to validate the identified CSR dimensions, we contribute to improving the generalizability of the CSR concept and scales.

3. Methodology 3.1. The scale development process 3.1.1. Scale generation—expert interview To identify, develop, and validate the scales for SRSD and CSR, we employ both qualitative and quantitative methods. Following Churchill’s (1979) paradigm and other scale development studies such as Linderbaum and Levy (2010), we identify and develop the constructs through qualitative efforts including conducting a review of the relevant literature, and discussion with subject matter experts. Specifically, we extensively reviewed the literature on OM, SD, and CSR to identify or develop the draft scales for these approaches. Next, we formed an expert panel in order to solicit experts’ insights to refine our draft scales (e.g., Yeung, 2008). We form the expert panel based on two criteria. First, the members must be knowledgeable in the practices of supply management or business ethics in organizations in China. Second, as we intend to collect exploratory insights, we identify members with diverse backgrounds to make sure that insights from

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differing perspectives are collected (Bryman, 2008). Consequently, our panel consisted of six professionals from different sectors in China, including two senior purchasing managers, one university professor, two government officials, and one publisher editor. The panel discussion results are as follows: First, Chinese organizations increasingly consider business ethics and the implementation of related management practices such as CSR as critical issues because the government has placed a strong emphasis on ethics and heightening expectations from customers in export markets. Second, all the CSR dimensions and scales proposed by Lindgreen et al. (2009) and one of the dimensions (i.e., ethics code) suggested by Luo (2006) are deemed appropriate to reflect CSR adoption in China. Third, the experts identified three of the scales by Krause et al. (2007), namely supplier evaluation, supplier development, and information sharing, are relevant constructs reflecting the actions taken a buyer to enhance its’ suppliers’ CSR implementation. Finally, the panel offered ideas on how to select and modify the items of these three scales to more accurately reflect a buyer’s actions when adopting SRSD. Consequently, the preliminary scales of this research comprise the CSR scales of Lindgreen et al. (2009) and Luo (2006), and the new SRSD scales that we develop by modifying the scale items concerning information sharing, supplier evaluation, and supplier development (Krause et al., 2007). 3.1.2. Scale purification—pilot test We translated the preliminary scales of this research from English to Chinese following the approach of Zhao et al. (2006). We pilot-tested the Chinese version of the preliminary scales by interviewing managers in ten buyer–supplier relationship pairs. These participating managers carry such titles as CEO, general manager, factory manager, or purchasing manager. In order to make sure that the revised scales are relevant to the target industries of this research, the buying firm informants of the pilot test were managers randomly selected from the same industries (i.e., clothing, pharmaceutical, automotive, or food industries). Based on the information provided by the buying firm informants, we contacted and interviewed the supplier informants. We provided all the informants of the pilot test with an USB memory stick and a supermarket coupon to reward their efforts. During the interviews, we provided the managers with details of the definitions and dimensions of SRSD and CSR. Based on the interview results, we made minor changes to a few items to improve their content validity and readability. In addition, we removed several CSR items for reasons such as the item is a broad ethical attitude instead of a specific CSR action (e.g., voluntarily exceed government-imposed environmental regulations), the item shares very similar concepts with another item (e.g., two items concerning community donation), or the item represents an advanced level of CSR adoption that Chinese organizations are unlikely to engage in at present (e.g., we have a dedicated supplier development team focusing on improving suppliers’ business ethics). Finally, on completing the pilot test, we came up with 40 scale items, each assessed by a seven-point Likert scale anchored at (1) strongly disagree to (7) strongly agree, to represent the three dimensions of SRSD and the seven dimension of CSR (see Table 1). 3.2. Scale validation 3.2.1. Domain specification China is the largest emerging economy in the world with exports of US$428.6 billion (Zhao et al., 2007). A primary location for international outsourcing, China accounts for over 50% of total

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output value in the global manufacturing industry (Zhao et al., 2006; Liu et al., 2009). In addition, the gross industrial output value of food, pharmaceutical, and clothing industries were $771.654, $943.576, and $787.498 billion yuan (approximately US$114, 139, and 116 billion), respectively, in 2009 (China Statistics Yearbook, 2009), highlighting the sizable scales of these industries and their important roles in the international markets. However, several safety incidents (e.g., melamine-tainted milk and lead painted toy) have occurred in Chinese manufacturing industries partly because of weak ethical consciousness within companies and their supply chain partners, which results in an undesirable impression of Chinese-made products (Lu, 2009). Indeed, since safety incidents may cause health or safety problems to consumers, such dire consequences may prompt manufacturers to look for new management insights to guide them on their efforts to improve ethical performance. So in this research we collect data from the food (C14, C15), pharmaceutical (C27), automotive (C371, C372, C373), and clothing (C18, C19) industries of China to validate our scales (National Bureau of Statistics of China, 2011).

3.2.2. Data collection and the sample We create the company database for the buyer survey of this research by combining information from different authorized sources, including the State Administration for Industry and Commerce of the People’s Republic of China, the State Food and Drug Administration (SFDA), the China National Garment Association (CNGA), and the China Association of Automobile Manufacturers (CAAM). Since business ethics and CSR are more likely to be considered as important issues in larger organizations, we identify manufacturers that have 300 or more employees, or $30 million or more in annual sales volume (in yuan) as our target sample. The resultant database includes 1000 randomly selected manufacturers that are evenly distributed among the target industries. We primarily follow the procedures of Dillman (2007) for questionnaire distribution and collection in both the buyer and supplier surveys. In the buyer survey, the informants have to fill in the scale items for SRSD. In order to make sure that the informants are sufficiently knowledgeable to carry out the survey, we specify in the questionnaire instructions that the informant should be the functional manager who is responsible for supply management in the firm. In completing the questionnaire, we asked the informant of the buyer survey to focus on the supplier that is the most crucial to the performance of the buying firm and to provide information on that supplier at the end of the questionnaire. Based on the supplier information provided in the buyer survey, we subsequently conducted the supplier survey to collect data on the supplier’s CSR implementation. Similarly, we specify in the instructions of the supplier survey that the informant should be a senior manager at the corporate level, who is responsible for ethics management or CSR in the firm. We first contacted the target informants of both the buyer and supplier surveys through phone calls to explain the background and the importance of their participation in this research. After obtaining the agreement from the informants, we sent the relevant questionnaires to them by mail or through the Internet. We issued three rounds of remainders. We provide clear instructions in the questionnaires, which present the requirements on the background of the informant, the guidelines on how to fill in the items, and a statement to assure the confidentiality of the data. We offered informants who completed the questionnaire a gift (i.e., an USB memory stick or a supermarket coupon) to reward their efforts. In addition, we promised that we would provide the informants with an executive summary of our research findings.

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Table 1 SRSD and CSR scales and items: standardized CFA path loadings and descriptive statistics.

SRSD and CSR scale items SR-information sharing Provide this supplier with knowledge on CSR that can help it to improve ethical performance Keep each other informed about our CSR practices or changes that may affect this supplier Communicate the ethical behavior requirements clearly and accurately to the supplier Communicate CSR issues at different levels of management and cross-functional areas SR-supplier evaluation Assessment of supplier’s ethical performance through formal evaluation Provide the supplier with feedbacks about the results of such evaluation Use a certification program to recognize the supplier’s CSR capability Change the business order quantity according to the evaluation results SR-supplier development Allocation of our personnel to improve the supplier’s capabilities in CSR implementation Regular visits by our personnel to the supplier to help it improve ethical performance Training/education of the supplier’s personnel about CSR practices and the required skills Ethics codes Established a set of transparent, comprehensive, and stringent codes of conduct Every manager and employee has strictly implemented the above codes of conduct Established an ethics compliance team, department or division Environment Measure our organization’s environmental performance Incorporate environmental concerns in our business decisions Incorporate environmental performance objectives in our organizational plans Financially support environmental initiatives Minimize the environmental impact of all our organization’s activities Investors Provide our investors with full and accurate financial information about the organization Incorporate the interests of our investors in business decisions Inform our investors of changes in corporate policy Provide all investors with a competitive return on investment Seek the input of our major investors regarding strategic decisions Employees Provide our employees with salaries that properly and fairly reward them for their work Provide procedures that help to insure the health and safety of our employees Care the private and professional lives of employees Support our employees who want to pursue further education Customers Adapt products or services to enhance the level of customer satisfaction Provide all customers with the information needed to make sound purchasing decisions Satisfy the complaints of our customers about products or services Incorporate the interests of our customers in our business decisions Suppliers Incorporate the interests of our suppliers in our business decisions Inform our suppliers about organizational changes affecting our purchasing decisions Open the purchasing principles and sign the contract according to the law Pay attention to how suppliers manage the ethical performance of their upstream partners Community Financially support education and cultural activities in the communities where we operate Help improve the quality of life in the communities where we operate Incorporate the interests of the communities where we operate in our business decisions Stimulate the economic development in the communities where we operate

Standardized path loading

Critical ratiob

Mean S.D.

0.836

9.25

4.79

1.284 1

7

0.756

8.527

5.18

1.125 1

7

0.847

9.321

4.93

1.244 1

7

0.696

–

4.72

1.156 1

7

0.892 0.905 0.745 0.698

10.272 10.359 8.761 –

5.04 4.89 5.08 4.79

1.057 1.322 1.147 1.284

1 1 1 1

7 7 7 7

0.812

11.855

3.99

1.519 1

7

0.826

12.085

4.61

1.463 1

7

0.88

–

4.58

1.623 1

7

0.854 0.877 0.865

13.269 13.687 –

5.08 5.26 5.13

1.272 1 1.236 2 1.260 2

7 7 7

0.853 0.854 0.886 0.526 0.685

14.031 14.039 – 7.001 9.925

5.57 5.56 5.61 5.37 5.93

1.102 1.180 1.224 1.252 1.091

3 2 2 1 3

7 7 7 7 7

0.877

16.387

5.57

1.102 3

7

0.91 0.902 0.896 0.83

17.866 17.464 – 14.564

5.56 5.61 5.37 5.93

1.180 1.224 1.252 1.091

2 2 1 3

7 7 7 7

0.971

5.246

5.97

1.000 3

7

0.768 0.764 0.405

5.102 5.096 –

6.19 6.06 5.94

0.908 4 0.943 3 1.001 3

7 7 7

0.774

6.112

6.09

0.896 4

7

0.885

6.388

5.80

1.057 3

7

0.847 0.498

6.323 –

5.96 5.69

0.990 4 1.172 3

7 7

0.845

8.137

5.41

1.118 3

7

0.826

8.113

5.49

1.213 1

7

Min. Max.

Cronbach’s alphaa 0.864

0.879

0.878

0.899

0.870

0.946

0.815

0.824

0.785

0.482

5.328

5.86

1.049 3

7

0.655

–

5.13

1.318 1

7

0.66

9.724

4.93

1.260 1

7

0.907

16.678

5.24

1.320 2

7

0.894

0.91

–

5.18

1.286 2

7

0.821

13.973

5.49

1.387 2

7

a

Cronbach’s alpha values exceed 0.70 exhibit reliability. The critical ratio (CR) and associated p-value for a one-tailed test of significance are as follows: CR¼ 1.28, p-value o0.10; CR ¼ 1.64, p-value o 0.05; CR ¼2.33, p-value o 0.01; CR ¼3.10, p-value o 0.001. b

Of the 750 buying firms that agreed to participate in the survey, 220 of them retuned the questionnaires, yielding a response rate of 29.3%. These 220 sample firms are fairly evenly distributed among the four target industries (food: 25%,

automotive: 28.1%, pharmaceutical: 19.4% and clothing: 27.5%). Based on the supplier information provided by 208 valid buying replies, we conducted the supplier survey and collected 160 usable questionnaires, yielding a response rate of 76.9 %.

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models exhibit fit indices with a score of 0.90 or greater, implying that all nine models have a satisfactory fit and that all of the items are valid in reflecting their corresponding constructs.

We reviewed all the returned questionnaires for errors such as missing data and miscoding. We found missing data in around 7% of the questionnaires. We made follow-up phone calls to the informants concerned to ask for the required information. The descriptive results show that the respondents averaged 6.25 years with their organization. In order to test the common method bias, we apply Harman’s one-factor method and the analysis results show that there is not any factor accounting for a majority of the variance within a total of 73.79% variances explained, further implying no single factor dominated the variance in the data (Podsakoff and Organ, 1986). We also test the non-response bias by comparing the responses of early and late waves through ttests (Armstrong and Overton, 1977) and find no statistically difference between the early and late respondents. Consequently, the final sample used in this research consists of 160 dyadic buyer–suppliers relationships in Chinese manufacturers.

3.2.3.3. Convergent validity analysis. Convergent validity assesses whether items underlying a specific construct are convergent or share a high proposition of variance in common (Hair et al., 2010). To establish convergent validity, we assess the significance of item factor loading, average variance extracted (AVE), and construct reliability (CR) (Hair et al., 2010). The standardized path loadings shown in Table 1 indicate that all the items are highly significantly (at p o0.001) related to their corresponding construct, each is significantly different from zero with the critical ratio greater than 3.09. Table 2 shows the results of AVE and CR. AVE is a summary indicator of convergence and if its value is less than 0.5, it indicates that more error remain in the model than the variance explained by the latent variable (Hair et al., 2010). As for CR, a value of 0.7 or above indicates sufficient internal consistency of the latent variable analyzed. The results in Table 2 suggest that all the constructs fulfill the threshold levels of both AVE and CR, thus establishing convergent validity for the scales of this research.

3.2.3. Validation test 3.2.3.1. Reliability analysis. Reliability is the accuracy or precision of a measuring instrument, which refers to the degree of consistency between multiple measures of a variable (Hair et al., 2010). We examine our scales’ Cronbach’s alphas for reliability. As shown in Table 1, all the scales’ Cronbach’s alphas are greater than 0.7, which exhibit excellent reliability (Kline, 1998).

3.2.3.4. Discriminant validity analysis. Discriminant validity refers to the extent to which two conceptually similar concepts are distinct (Hair et al., 2010). We employ a chi-square difference test to check the discriminant validity of the scales of this research. We conduct the test by fixing the correlation between various constructs to 1.0 and re-running the analysis on the constrained model (Fornell and Larcker, 1981). By constraining the correlations between the constructs of the final structural model to 1, the chi-square value increases by 295.537, with an increase of 45 degrees of freedom. The difference in the chi-square statistics is highly significant at p¼ 0.001 level (w2 480.08), implying that discriminant validity of all the constructs analyzed is satisfactory.

3.2.3.2. Unidimensionality analysis. We perform confirmatory factor analysis (CFA) to test the unidimensionality of the scales. We construct a total of nine measurement models to analyze the three dimensions of SRSD and the seven dimensions of CSR. Note that we combine SR-supplier development of SRSD and ethics code of CSR into one measurement model in the analysis in order to achieve overidentification, as required by the analysis method (Hair et al, 2010). Table 2 lists the results of each measurement model with respect to adjusted goodness-of-fit index (AGFI), goodness-of-fit index (GFI), comparative fit index (CFI), Bentler-Bonett normed fit index (NFI), and non-normed fit index (NNFI). The results indicate that all the Table 2 Unidimensionality and reliability analyses of SRSD and CSR scales. SRSD and CSR construct dimension

AGFIa

GFIa

CFIa

NFIa

NNFIa

Construct reliabilityb

Average variance extractedc

1. SR-information sharing 2. SR-supplier evaluation

0.99 0.96

1.00 0.99

1.00 1.00

1.00 0.99

1.01 1.00

0.87 0.89

0.62 0.66

3. SR-supplier development 4. Ethics code 5. Environment 6. Investors 7. Employees 8. Customers 9. Suppliers 10. Community

0.90

0.96

0.98

0.97

0.96

0.90 & 0.88

0.75 & 0.71

0.96 0.94 0.92 1.00 0.90 0.95

0.99 0.98 0.98 1.00 0.98 0.99

1.00 1.00 0.99 1.00 0.98 1.00

0.99 0.99 0.98 1.00 0.97 0.99

1.00 0.99 0.96 1.02 0.94 0.99

0.88 0.95 0.83 0.85 0.80 0.90

0.60 0.78 0.57 0.59 0.51 0.69

a Goodness-of-fit index (AGFI), goodness-of-fit index (GFI), comparative fit index (CFI), the Bentler-Bonett normed fit index (NFI) and non-normed fit index (NNFI) value equals or exceeds 0.90 indicate strong scale unidimensionality. b Construct reliability values equal or exceeds 0.70 indicate strong convergent validity. c Average variance extracted values equal or exceeds 0.50 indicate strong convergent validity.

Table 3 Predictive validity test results: correlation between SRSD scales and CSR scales. CSR scales

Ethics codes

Environment

Investors

Employees

Customers

Suppliers

Community

SRSD scales SR-information sharing SR-supplier evaluation SR-supplier development

0.588a 0.577a 0.463a

0.522a 0.434a 0.317a

0.522a 0.434a 0.317a

0.417a 0.385a 0.221b

0.323a 0.212 0.133

0.623a 0.548a 0.402a

0.432a 0.354a 0.273a

a b

Spearman correlations with associated p-value r 0.001. Spearman correlations with associated p-value r 0.005.

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3.2.3.5. Predictive validity analysis. Predictive validity refers to ‘‘a measure of how well antecedent constructs predict the hypothesized dependent variable’’ (Stratman and Roth, 2002). Since the practice of SRSD is employed to improve the supplier’s capabilities in implementing CSR practices, we use the data on supplier’s CSR to assess the predictive validity of the SRSD scales. The Spearman correlations shown in Table 3 indicate that, of the 21 associations examined, 19 of them are statistically significant (po0.005). Note that the majority of the associations are significant to the level at p o0.001, indicating that the scales for SRSD exhibit strong predictive validity.

4. Discussion and conclusions Several recent ethical incidents reveal that a buying firm’s performance can be severely affected by its suppliers’ lack of concern for social responsibility. Nonetheless, the extant literature offers very limited suggestions on how a buying firm can proactively help its important suppliers implement CSR in order to improve the ethical performances of both the suppliers and the buying firm. In this research we integrate the literature on business ethics and supply management to come up with the SRSD concept, which is concerned with a buyer’s concerted efforts in developing its key suppliers’ CSR capabilities and implementation commitment. In order to further theory development and understanding of SRSD, reliable and valid measures of SRSD are required. Thus, we develop three multi-item scales reflecting the three dimensions of SRSD for researchers to examine buying firms’ efforts in influencing their suppliers’ CSR practices. Within the extant literature on supply management and business ethics, suggestions tend to concentrate on how to influence suppliers indirectly by paying attention to select ethical suppliers through diverse requirements and regulations in the tendering and assessment processes (e.g., Baden et al., 2009; Tsoi, 2010; Carter and Jennings, 2004; Carter et al., 1999; Carter and Carter, 1998). Obviously, SRSD represents a novel concept that extends the extant literature by suggesting that buying firms can take a proactive role in influencing the ethical practices and performance of their suppliers. Furthermore, SD researchers tend to consider SD as an approach for buying firms to improve operational performance through the transfer of OM knowledge or practices to suppliers (e.g., Krause et al, 2000; Krause, 2007). The SRSD concept extends the understanding of SD in that we propose that SD can be used for transferring corporate-level management practices, such as CSR, and its outcome can be ethical performance improvement in the supplier and the buying firm. In addition to the development of the SRSD concept, the multiitem SRSD scales we have developed and tested are another major contribution of this research. We employ qualitative methods to develop the scale items for the three dimensions of SRSD and validate them quantitatively based on the data of 160 pairs of buyer–supplier relationships. The analysis results indicate that our new scales exhibit adequate psychometric properties for theory building, testing, and refinement. Because of the increasing awareness of the importance of ethics and the trend towards developing closer and interdependent supplier relationships, we expect that many researchers will direct their attention towards exploring how organizations can work closely with suppliers in order to meet consumers’ heightening expectations on ethics. By using valid and reliable scales, such as the SRSD scales developed in this research, business ethics and supply management researchers will be able to move forward from conceptual discussions or anecdotal studies to testing specific hypotheses or conceptual models (Sethi and King, 1994).

The SRSD scales developed in this research contribute to practice by offering ideas to practitioners on what specific practices are needed when organizations intend to improve suppliers’ capabilities in CSR adoption. Specifically, the items of the first SRSD dimension (i.e., SR-information sharing) imply that the buying firm has to be willing to share its knowledge on CSR to suppliers. The items of the second SRSD dimension (i.e., SRsupplier evaluation) imply that the buying firm should put an audit and feedback system in place for monitoring suppliers’ CSR implementation and outcomes, and those of the third SRSD dimension (i.e., SR-supplier development) imply that the buying firm has to be ready to get directly involved in suppliers’ CSR implementation or ethics-related problem-solving efforts. In addition, the SRSD and CSR scale items can be used by organizations to monitor their SRSD and CSR implementation status and track changes over time. Furthermore, the scales could serve as a diagnostic tool that allows organizations to collect information to determine which particular SRSD or CSR dimensions are weak and in need of attention. In addition, within the framework of the recently developed ISO 26000 (i.e., an international standard on social responsibility), promoting social responsibility in the value chain is one of the values of the standard (ISO, 2010). Consequently, our developed SRSD scales will be particularly useful for organizations that intend to obtain ISO 26000 certification. Our research is not free of limitations, which introduce future research opportunities. First, we collect both interview data in the pilot test and survey data in the validation test from manufacturing organizations. Future research could collect data from service organizations for validation in order to improve the generalizability of the scales. Second, although the 160 pairs of buyer– supplier relationships in the data-set of this research can be deemed acceptable when compared with similar prior studies (e.g., Luo, 2006; Krause et al., 2007), a sample size of at least 200 is needed when there are 40 scale items in the CFA test (Hair et al., 2010). Future research could employ a bigger data-set in order to generate more accurate CFA results. Third, as an exploratory study, we use data from four industries for the validation test. However, organizations in different industries operate under different environments and face unique problems and constraints. Future research may replicate this research by focusing on a single industry in order to offer some industry-specific insights that may better meet the needs of organizations. Fourth, we conduct the validation test based on cross-sectional survey data, which makes the assumed cause–effect relationship in the examination of predictive validity questionable. Future research could use a longitudinal approach to collect data on SRSD and CSR at different times in order to obtain evidence to support the assumption in the predictive validity test. Finally, the results of the predictive validity test reveal an important research question that is not yet addressed by current research. The results indicate that the SRSD dimensions are significantly related to many of the dimensions of CSR. Future research could examine more rigorously how SRSD adoption in the buying firm is associated with CSR adoption in the supplier by using analysis methods such as structural equation modeling. In addition, when examining such associations, factors that may moderate or mediate the associations could be identified and tested empirically.

Acknowledgments We thank the Guest Editors and two anonymous referees for their helpful comments on an earlier version of our paper. This research was supported in part by the Research Grants Council of Hong Kong under Grant No. Poly U5198/08E.

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