Extending social sustainability to suppliers: a supplier perspective study on the role of supplier development practices and buyer-supplier trust

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Extending social sustainability to suppliers: a supplier

perspective study on the role of supplier development

practices and buyer-supplier trust

Master thesis, MSc, Supply Chain Management

University of Groningen, Faculty of Economics and Business

August 21, 2016

Miao Hu

Student Number: s2451808

Email Address: m.hu.14@student.rug.nl

Supervisor

Dr. Marije Bosch

Dr. C. Sancha Fernandez

Co-assessor

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ACKNOWLEDGEMENTS

I would like to thank Dr. Marije Bosch, Dr. C. Sancha- Fernandez, and Dr. Ing. Justin Drupsteen of the Rijksuniversiteit Groningen for their contributions regarding the research project. Their feedback was very helpful and guided me throughout the whole research process. Furthermore, I would like to thank Dr. Manda Broekhuis and Prof. Dr. Kees Ahaus for their assistance during the absence of Dr. C. Sancha- Fernandez, which guaranteed the smooth proceeding of my research in the final stage.

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ABSTRACT

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1. Introduction

Currently, the rising of globalization compels firms to adopt sustainability as an important part of their business (Crane & Matten, 2004). In order to achieve sustainability, one key challenge that firms encounter is the extension of sustainability to other supply chain partners such as suppliers (Sancha et al., 2015). Buying firms usually take the responsibility for their suppliers in the frontline (Hartmann and Moeller, 2014), since customers and other stakeholders do not distinguish all the different roles in a supply chain (Seuring & Gold, 2013). Krause et al. (2009) emphasized that firms’ sustainability is restricted by their suppliers (Krause et al., 2009). In fact, suppliers’ unethical behaviors can damage the buying firms’ sustainability performance (Faruk et al., 2001). For instance, Apple had been vilified after the Foxconn suicides scandal and Nike had been criticized for its suppliers’ poor working conditions in Vietnam (Chan & Pun, 2010; Kahle, et al., 2000). Such issues occur on the social dimension of sustainability and receive more and more attention of regulators, investors, customers, and non-governmental organizations (Gualandris et al., 2015). As such, buying firms need to implement practices that integrate and synchronize suppliers’ performance to be socially sustainable.

When buying firms face deficiencies in their suppliers’ sustainability performance, these firms can either develop their suppliers’ performance by investing personnel, time, and resources, or seek alternative suppliers (Krause et al., 2000). This thesis is based on the premise that the buying firms have to decide to adopt the former option, and implement practices, such as supplier assessment and incentives, to improve their suppliers’ sustainability performance. Supplier assessment comprises evaluating, comparing, and directing suppliers’ sustainability performance. To motivate the suppliers, buying firms initiate supplier incentives such as increased volumes of present business and priority consideration for future business based on their performances (Krause et al., 2000). Furthermore, many researchers have investigated supplier assessment (e.g. Klassen & Vereecke, 2012; Gavronski et al., 2011; Lee & Klassen, 2008; Vachon & Klassen, 2006) and supplier incentives (e.g. Porteous et al., 2015; Krause et al., 2009) as supplier development (SD) practices to extend environmental or economic sustainability to suppliers. However, in the social sustainability context, the impact of supplier assessment and supplier incentives has been rarely studied compared to other SD practices (e.g. collaboration with suppliers; competitive pressure) (Sancha et al., 2015; Terpend & Krause, 2015; Porteous et al., 2015). Therefore, this thesis focuses exclusively on supplier assessment and supplier incentives and investigates the relationship between these SD practices and suppliers’ social performance.

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economic sustainability performance only when buyers and suppliers are in condition of mutual dependence. A number of studies regard buyer-supplier trust (TR) as a paramount contextual variable in successful supply chain management (SCM) (e.g. Ireland & Webb, 2007; Benton & Maloni, 2005), as TR stands for a significant inter-organizational resource that stimulates sustainability (Gold et al., 2010), builds committed relationships, facilitates investment (Font et al., 2008), and collaboration (Simpson & Power, 2005). Nevertheless, the impact of TR on SD practices is scarce ever studying in sustainable supply chain management (SSCM) articles (Gualandris & Kalchschmidt, 2015).

In the literature review, three research gaps are identified. First of all, most of the existing SCM papers have investigated the effectiveness of supplier assessment and supplier incentives in either environmental (e.g. Porteous et al., 2015; Zhu et al., 2013; Zhu & Sarkis, 2007) or economic dimensions of sustainability (e.g. Rao & Holt, 2005; Zhu & Sarkis, 2004), while the social dimension has been neglected (e.g. Terpend & Krause, 2015; Klassen & Vereecke, 2012). Secondly, although TR is a paramount contextual variable in successful SCM, its impact on SD practices has seldom been investigated in SSCM research (Gualandris & Kalchschmidt, 2015). Moreover, a large number of studies have measured and analyzed the performance implications of SD practices from a buying firm’s perspective and perceptions data (e.g. Gimenez et al., 2012; Rao & Holt, 2005), while few papers have considered the impact of SD practices from a supplier’s perspective (e.g. Akamp & Muller, 2013; Carter, 2005). As a result, the current research could not provide a comprehensive illumination of SD practices regarding sustainability performance, yet offers only a partial view from a buying firm’s perspective.

In light of the above-mentioned gaps, two corresponding objectives are formed in this study. Firstly, this thesis aims to analyze the relationship between SD practices (i.e. supplier assessment and supplier incentives) and suppliers’ social performance in order to enrich the empirical evidence in the existing SCM papers. Secondly, this study investigates how TR influence the effectiveness of SD practices on suppliers’ social performance to identify the function of TR in the process of implementing SD practices. It is also noteworthy to mention that this study adopts a supplier’s perspective when measuring the implementation of SD practices, suppliers’ social performance, and TR. Therefore, this study aims to answer the following research questions:

RQ1: Do SD practices contribute to improving suppliers’ social performance?

RQ2: Does TR influence the effectiveness of SD practices on suppliers’ social performance?

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on the role of TR. In addition, these findings will direct buying firms to extend social sustainability to suppliers and as a result, to achieve a truly social sustainable supply chain by improving the suppliers’ social performance.

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2. Theoretical background

2.1 Supplier assessment and suppliers’ social performance

Supplier assessment implies a whole process that evaluates, compares, and directs suppliers’ outputs with respect to specific performance criteria (Sancha et al., 2015; Gualandris & Kalchschmidt, 2014; Klassen & Vereecke, 2012; Lee & Klassen, 2008; Gavronski et al., 2011; Vachon & Klassen, 2006). In the social dimension, the implementation of assessment practices implies the evaluation of suppliers (e.g. use of child labor, working conditions, and fair salary)(Gualandris & Kalchschmidt, 2014). Supplier assessment allows the buying firms to judge whether suppliers meet current and future business requirements. The evaluation result needs to be quantified and communicated with suppliers in order to notify them of the disparity between their current performance and the buying firm expectations (Prahinski & Benton, 2004) so that suppliers are aware of further improvement (Krause et al., 2000).

A number of researchers have investigated supplier assessment (e.g. Klassen & Vereecke, 2012; Gavronski et al., 2011; Lee & Klassen, 2008; Vachon & Klassen, 2006) as SD practices to extend environmental or economic sustainability to suppliers. However, on the social sustainability dimension, the impact of supplier assessment has been rarely studied before.

Hawkins et al. (2008) pointed out that there was always a risk that suppliers behaved as opportunism for self-interest especially regarding the social dimension. For instance, even though child labor is not allowed according to Nike’s regulations, its suppliers in Vietnam might still employ child labor under the table to reduce labor costs (Basu & Tzannatos, 2003). The cause of this opportunism behavior can be the buyers’ lack of direct control on suppliers, which will eventually result in poor suppliers’ social sustainability performance that devastates the buying firms’ reputation. In order to eliminate such occurrences, Carter and Rogers (2008) argued that buying firms could implement supplier assessment to strengthen buyers’ power of control by pressuring suppliers to evaluate and to reduce unethical behaviors. Lee and Klassen (2008) stated that suppliers’ environmental assessment exert coercive pressure on the suppliers and pushed them to comply with environmental issues. In this sense, supplier assessment also has a positive impact on suppliers’ social performance as well. By adopting supplier assessment, buying firms acquire a direct control to dispel supplier’s opportunism and force them to re-evaluate social concerned issues under explicit supervision. In addition, supplier assessment contributes to pushing suppliers to make adjustment based on assessment criteria and exclude negative social behaviors (e.g. unsafe working condition, employ of child labor, and long working hours) and to achieve improvement on social sustainability performance.

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social sustainability performance(i.e. compliance with child labor employment, safety production, etc.). As, the following hypothesis can be formulated:

Hypothesis 1: Supplier assessment is positively associated with suppliers’ social performance.

2.2 Supplier incentives and suppliers’ social performance

Incentives are external stimuluses that motivate future behavior in the field of behavior science (Berstein & Nash, 2008). The study of incentives in supply chain research mainly focused on the manufacturer–retailer and buyer-supplier links (Terpend & Krause, 2015). Previous studies (Krause et al., 2000; Monczka, Trent, & Callahan, 1993; Giunipero, 1990) defined supplier incentives as improvement practices provided by buying firms to their suppliers by giving rewards such as increased volumes of present business and priority consideration of future business for supplier with best performance.

Krause et al. (2000) stated that supplier incentives, such as promises of increased business in the present or future business, combined with SD practices, such as supplier training, contributed to significant buying firm performance improvement. Kumar et al. (2011) also studied the role of economic incentives with suppliers on the performance of buyers. In addition to these studies, supplier incentives are usually investigated with little focus on how it may be implemented to improve suppliers’ social performance or to integrate suppliers’ social performance with the goals of the buying firms (Terpend et al., 2015).

In order to interpret the relationship between supplier incentives and suppliers’ social performance, previous studies are followed and supplier incentives are divided into competitive incentives and cooperative incentives (Terpend et al., 2015). According to the definitions of Terpend et al. (2015), competitive incentives imply business awards based on suppliers’ performance compared to other suppliers. In this case, supplier incentives can be additional businesses or increased purchase volumes. In contrast, cooperative incentives refer to a sharing of the benefits of improved performance within a buyer-supplier relationship; these incentives are based on their mutual performance and are not influenced by the performance of other suppliers. Here, supplier incentives are generally in the form of increased business engagement and price premiums. For competitive incentives, extrinsic competition motivates suppliers to engage with buying firms in order to secure their business (Pulles et al., 2014; Terpend et al., 2011).

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In this case, suppliers will not only benefit from positive economic outcomes but also from integrated and synchronized social outcomes (Lambeet et al., 2001). Therefore, suppliers would strive to improve their social performance in compliance with buying firms. Moreover, cooperative incentives transfer accountability of being social sustainable to the suppliers, motivating them to manage social issues and behave in accordance with buying firms. Hence, it is likely that both cooperative and competitive incentives contribute to improving suppliers’ social performance. Accordingly, the following hypothesis is anticipated:

Hypothesis 2: Supplier incentives are positively associated with suppliers’ social performance.

2.3 TR and the effectiveness of SD practices

When describing TR, researchers provide several definitions. For example, Doney and Cannon (1997, p. 36) defined TR as “the perceived credibility and benevolence of a target of trust”; Dyer and Chu (2003, p. 58) described TR as “…one party’s confidence that the other party in the exchange relationship will not exploit its vulnerabilities…”. Accordingly, in a supplier’s perspective, TR can be defined and measured as suppliers’ perceived trustworthiness of buying firms.

Many studies regard TR as a paramount contextual factor in successful SSCM (e.g. Gold et al., 2010). In sum, TR stands for an essential inter-organizational resource which stimulates sustainability (Gold et al., 2010), builds committed relationships, and facilitates investment (Font et al., 2008), and collaboration (Simpson & Power, 2005). Aiming to improve suppliers’ sustainability performance through SD practices, previous researchers strongly suggested that the bias caused by contextual factors should be taken into consideration (Tachizawa & Wong, 2014). Thus, it needs to be examined how TR could impact the effectiveness of SD practices as an essential contextual variable.

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following hypothesis is proposed:

Hypothesis 3: TR positively moderates the positive effect supplier assessment has on suppliers’ social performance.

When buying firms implement competitive incentives to motivate suppliers for social sustainability performance improvement, these firms usually promise suppliers future business awards based on suppliers’ performance (Terpend et al., 2015). Here, TR represents a safeguard that guarantees the credibility of buying firms and the fulfillment of promised awards or contracts (Gualandris & Kalchschmidt, 2015). From a supplier’s point of view, TR reduces the possibility that buying firms behave improperly and increases the reliability of buying firms’ commitments (Ireland & Webb, 2007; Benton & Maloni, 2005). As a result, suppliers become more willing to improve their social performance to win the business awards, as these awards are perceived as genuine. Hence, TR could positively moderate the positive effect competitive incentives have on suppliers’ social performance. Comparatively, cooperative incentives highlight social performance consistency between buyer and supplier (Terpend et al., 2015). In order to achieve performance consistency, information sharing process and partner-specific absorptive capacity are requisite (Gualandris & Kalchschmidt, 2015). Ireland and Webb (2007) claimed that TR contributes to fostering information sharing process and enables the development of partner-specific absorptive capacity, as TR facilitates information transmission between buyers and suppliers, promotes co-development, and accelerates the exploitation into social sustainability performance outcomes. Thus, TR positively moderates the positive effect cooperative incentives have on suppliers’ social performance. In summary, the following hypothesis is formulated:

Hypothesis 4: TR positively moderates the positive effect supplier incentives have on suppliers’ social performance.

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11 Figure 1 Conceptual model

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3. Methodology

3.1 Sample selection and data collection

This thesis focuses on Chinese manufacturing firms. The ideal set of manufacturing industries in this research possess the following features: own production chain, own upstream and downstream partners, completeness of supply chain, and relevant regulations and laws about developing sustainable supply chain practices in recent years (Awaysheh & Klassen, 2010). Accordingly, thirteen industries were selected: food industry and beverages (NACE codes 10-11), tobacco manufacturers (12), textile manufacturers (13-14), leather and shoes manufacturers (15), wood and cork manufacturers (16), paper manufacturers (17), chemical and pharmaceutical manufacturers (20-21), plastic and rubber manufacturers (22), metallurgy industry (23-25), electronics and optics manufacturers (26), electrical equipment manufacturers (27), machinery manufacturers (28), and car manufacturers (29-30). Each of these industries has its own production plants and requires sustainable supply chain practices throughout the whole supply chain. The corresponding regulations and laws about sustainability are extremely strict in these industries. Furthermore, in order to guarantee that the questionnaires were answered by qualified respondents, the ideal respondents are CEO, Plant Manager, Manager of Operations Department, Manager of Environmental Department, or other plant manager equivalent manager who are acquainted with supply chain practices and procedures and directly involved in managing internal operations, the supply chain, and, ideally, the surrounding community (Awaysheh & Klassen, 2010). Moreover, the respondents should be familiar with SD practices implemented in their organizations and the evaluation of social performance of their plants. This purposed sampling was aimed at achieving external validity and contributing to the generalization of the results (Cook et al., 1979). Data collection took place from April 2016 to May 2016. In order to collect nationwide data from Chinese plants, a third-party data collection service provider1_{was contacted}

for assisting the data collection process. Many academic institutions in China (e.g. The Chinese University of Hong Kong, University of Macau, City University of Hong Kong, and The Hong Kong Polytechnic University) have collaborated with the company for domestic data collection.2 Moreover, another researcher who participated in this project collected data from Chinese plants via social relations. An initial invitation survey link3 was sent to a total of 147 Chinese manufacture plants via email. After two weeks, a reminder was distributed to respondents who promised but had not completed the survey yet. While 54 plants declined to participate, the other plants all decided to answer the questionnaires. As a result, 93 responses were obtained. After checking the data completeness and effectiveness, seven responses were removed because of significant contradictory answers (e.g. unexpected values for reverse–coded items) or

1_{Shanghai Information Recycle Limited Company. http://www.sojump.com/html/loopinfo.aspx} 2_{Source from: http://www.sojump.com/html/promote/morecasesnew.aspx}

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deficient answers (e.g. items or respondents with too many missing data). Thus, a total of 86 respondents provided useful and valid responses for subsequent analysis, resulting in an effective response rate of 58%. According to Mitchell (1993), there should be at least 10 observations for each variable. In this study, there are four variables of the constructs; therefore, the least requirement for the sample size (40) was satisfied. Finally, the 28 missing answers were replaced with the corresponding average values for each question.

On the basis of data completeness, the logic of the data is verified. Given the fact that in this research, data was collected separately by two individual researchers, which may introduce a bias that influences the correctness of data analysis. Therefore, an independent sample t-test analysis was adopted for measuring the difference of two sets of data that was collected separately. According to the results of Levene’s test for equality of variance and t-test for equality of means, a comparison of the mean values of turnover and number of employees exists (Turnover: F= 2.231, p= 0.139 > 0.05, t (84) = 0.438, p= n.s.4; Number of employees: F=0.175, p= 0.677 >0.05, t (84) = 0.213, p= n.s.). The results demonstrate that no bias was introduced by the different researchers. Consequently, it was decided to combine the two samples together as one integrated sample for subsequent analysis. Furthermore, considering that the early and late respondents may pose a threat to the validity of results, a total of 40 early and 40 late respondents were grouped to conduct comparisons (Lindner et al., 2001). Subsequently, a one-way ANOVA analysis was performed on the control variables firm turnover and number of employees. The results were as follows: (1) turnover: F=0.969, p=0.418>0.05 (2) number of employees: F=0.713, p=0.588>0.05. Based on the p-value, it can be concluded that during the data collection process, no bias is introduced by the early and late response. For this reason, non-response bias is not considered a problem in this research.

Table 1 provides a comprehensive sample description. As the firms did not have a common position that dealt with these issues, there is high diversity in terms of positions held by respondents. Approximately 83.8% of the respondents held the title of plant or operations manager or CEO. Roughly 5.9% held a title such as environmental department manager or quality manager, and 10.5% of the respondents did not provide information about their position. Furthermore, the firm’s size was measured in terms of total annual sales and number of employees. As such, firms with an annual turnover lower than 10 million euros amounted to 16.3%, 14% have an annual turnover between 10 million and 20 million, 36% of firms had between 20 million and 50 million, and the remaining 33.8% had an annual turnover higher than 50 million euros. In the context of number of employees, 43% of the firms employ between 101 and 500 employees, followed by 36% with more than 500 employees, 15.1% of firms have 51 to 100 employees, and only 5.8% of firms with fewer than 50 employees. Finally, the sample covers a variety of industries. Regarding distribution of these industries, more than 85% of the respondents are employed in the chemicals and allied

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products industry (30.2%), electronic and electrical equipment (31.4%), food industry (9.3%), and textile manufacturing (5.9%). The vast majority of the companies belong to the manufacturing sector.

Table 1 Sample description

Position n % Manager of Operations Department 35 40.7% CEO 17 19.8% Manager of Environmental Department 4 4.7% Plant Manager 20 23.3% Quality Manager 1 1.2% Others 9 10.5% Total 86 100%

Industry n % Chemical and allied products 26 30.2%

Electronic and electronical equipment and

Components 27 31.4% Textile Mill products 5 5.9% Leather and leather products 1 1.2% Apparel and other finished products made from

Fabrics and similar materials 1 1.2% Food industry 8 9.3% Car Manufacture 3 3.5% Machinery Manufacture 2 2.3% Pharmaceutic Industry 2 2.3% Electronic Equipment Manufacture 2 2.3% Plastic and Rubber Manufacture 2 2.3% O t h e r s 7 8 . 1 % Total 86 100% Number of Employees n % Between 1 and 10 0 0% Between 11 and 50 5 5.8% Between 51 and 100 13 15.1% Between 101 and 500 37 43% More than 500 31 36% Tot al 86 100% Turnover (€) n % Less than 10 million 14 16.3% Between 10 million and 20 million 12 14% Between 20 million and 50 million 31 36% Between 50 million and 100 million 12 14% More than 100 million 17 19.8%

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15 3.2 Measures development

Based on a literature review, the survey instrument was designed and developed in this research. Moreover, to establish content validity, multiple items for each construct was employed, which is in accordance with prior literature. In this study, all the constructs have been adopted in previous research. When necessary, these constructs were re-formulated to reflect measurements from a supplier’s perspective (See Appendix A for a detailed questionnaire).

Supplier assessment – this construct consists of assessment of suppliers on the aspect of social performance perceived by suppliers. Three questions were adapted from Min and Galle (1997), Large and Thomsen (2011), and Krause et al. (2000). A sample item is “Our key customer assesses our social performance through formal evaluation, using established guidelines and procedures.” Responses were provided on a five-point scale ranging from 1 (none) to 5 (high).

Supplier incentives – five questions derived from Porteous et al. (2015) were adopted for measuring suppliers’ perceived incentives offered by buying firms. These questions contained measurements for both competitive incentives (e.g. “Preferred supplier status such as priority for future business”) and cooperative incentives (e.g. “Price premiums”). Responses were given on a five-point scale ranging from 1 (none) to 5 (high). One item (i.e. Public recognition) was dropped because of cross loading of components. However, it should be noted that incentives included in these questions were general incentives that had no specific focus on the social dimension. As the supplier incentives have been rarely studied before in this field (e.g. Terpend and Krause, 2015; Porteous et al., 2015), there was limited literature available concerning social-focused incentives.

TR – this construct includes seven questions used for evaluating the TR from a supplier’s perspective. Accordingly, TR was measured as buying firms’ trustworthiness perceived by the suppliers in this study (Gualandris & Kalchschmidt, 2015). This construct and items were adapted from Doney and Cannon (1997) and Gorton et al. (2015). A sample item is “Our key customers keep the promises they make.” Responses were given on a five-point scale ranging from 1 (strongly agree) to 5 (strongly disagree). Suppliers’ social performance – in order to measure how suppliers perceive their social performance, five questions, adapted from Awaysheh and Klassen (2010), were implemented in this construct. A sample item is “Safety and labor conditions are present in our facilities”. Responses were provided on a five-point scale ranging from 1 (far worse) to 5 (far better). Yet, one item (i.e. Compliance with child labor employment) was dropped because of cross loading of components.

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were translated by consulting with literature or a professional database. Additionally, a professional Chinese teacher checked the translated version to guarantee the questionnaire was accurate and understandable.

In addition, exploratory factor analysis (EFA) was performed to explore the number of latent constructs underlying a set of items (using varimax rotation) and to provide evidence of construct validity. Before EFA, two steps were taken to ensure the quality of data analysis. Firstly, six items used for measuring TR from a supplier’s perspective were re-coded to ensure that all items were coded in the same direction; secondly, Kaiser-Meyer-Olkin (KMO) and Bartlett’s Test were conducted to assess whether the sample size was adequate for factor analysis. The value of the KMO test is 0.884> 0.6, which indicates adequate sampling. The p-value of Bartlett’s test is 0.000< 0.001, which signifies correlated items for each factor. Therefore, the sample of all four factors of this research is adequate, and selected items are mutually correlated. Following a principal component analysis was conducted on 18 items to test the retention of factors. An orthogonal rotation (varimax) was used, and this revealed that four components were distinguished without cross loading. Moreover, the combination of 18 items retains 76.5% of the constructs indicators’ total variance, which is greater than the benchmark of 50% and proved to be construct validity. The Rotated Component Matrix demonstrated that each variable had at least three items, with each item loading onto only one specific factor (no cross-loadings). Therefore, the samples of this research are adequate, and selected items are mutually correlated. Furthermore, the Cronbach’s alpha values per each construct were tested to verify the reliability. Reliability concerns the extent to which the observed items that measure a latent variable relate to one another in a consistent manner (Karlsson, 2010). Finally, all the Cronbach’s alpha values were larger than 0.8, which indicated a good internal consistency of items per each construct. Below, Table 2 provides an overview of the descriptive and measurement assessment (factor loadings).

3.3 Data analysis

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In order to conduct the moderator analysis in this study, the relevant data needed to be transformed into standardized values. To be specific, two independent variables (i.e. supplier assessment and supplier incentives) and the moderator (i.e. TR) were standardized to process the moderator analysis, as is discussed in the succeeding chapter.

Table 2 Descriptive and measurement assessment

Construct name Items Mean StDev Loadings α

Supplier assessment Our key customer assesses our social 3.97 0.93 0.829 0.808 performance through formal evaluation,

using established guidelines and procedures

Our key customer performs social audits 3.80 0.98 0.814 for our internal management systems

Our key customer provides us with feedback 3.77 1.00 0.783 about the results of the social evaluation

Supplier incentives Increased business engagements 4.14 0.84 0.842 0.838 Preferred supplier status such as priority 4.14 0.95 0.821

for future business

Better terms and conditions 3.89 0.85 0.703 Price premiums 3.98 0.88 0.758

TR Our key customer keeps the promises it makes 3.22 1.58 0.958 0.971 (Suppliers' percievd

buying frims' Our key customer is always honest with us 3.09 1.45 0.904 trustworthiness)

Our key customer is genuinely concerned that 3.07 1.57 0.928 our business succeeds

When making important decisions, our key customer 3.05 1.43 0.904 considers our welfare as well as its own

We trust our key customer keeps our best interests 3.14 1.26 0.875 in mind

We find it necessary to be cautious with our key 3.20 1.65 0.926 Customer

Our key customer is trustworthy 3.19 1.62 0.956

Supplier's social Safety and labor conditions in our facilities 4.21 0.77 0.877 0.83 performance

Compliance with human rights 4.07 0.82 0.736

Social reputation 4.12 0.79 0.754

Decrease in the number of industrial accidents 4.35 0.79 0.826

EFA Analysis Adequacy.

KMO= 0.884 (threshold value is 0.600).

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4. Results

4.1 Descriptive statistics

Table 3 Means, Standard Deviations, and Correlations

Variables Mean S.D. 1 2 3 4

1.Supplier assessment 3.84 0.82

2.Supplier incentives 4.04 0.72 0.51**

3.TR(Buying firm's trustworthiness) 3.14 1.4 -0.11 -0.04

4.Supplier's social perfromance 4.19 0.65 0.08 0.35** 0.11

** Correlation is significant at the 0.01 level (2–tailed).

The descriptive statistics results of the four variables are illustrated in Table 3. In this research, the mean and standard deviation of each variable was measured, and it was established how random paired variables correlate with each other. The research findings indicate that there is a significant positive relationship between supplier assessment and supplier incentives, r = .51, p < .01. The correlation table also reveals that an increase in supplier incentives is significantly related with an increase in suppliers’ social performance (r =.35, p <.01). However, the hypothesis that an increase in supplier assessment is significantly associated with an increase in supplier’s social performance was not significant according to the correlation between these two variables (r =.08, p = n.s.).

4.2 Supplier assessment and suppliers’ social performance

Table 4 LR analysis of supplier assessment and suppliers’ social performance (H1)

Model 1 Model 2

Step and variables B SE B SE Intercept 4.51*** (0.35) 4.22*** (0.50) Control Number of Employees - 0.24* (0.12) - 0.23* (0.12) Turnover 0.21** (0.08) 0.22** (0.08) Main effects Supplier assessment 0.07 (0.08) R square 0.09 0.09 △ R square 0.01 *** P < .001 ** P < .01 * P < .05

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results of the regression analysis for hypothesis 1. Model 1 indicates that the number of employees has a significant and negative effect on suppliers’ social performance (p<0.05, R2 = 0.09), and the turnover has a significant and positive effect on suppliers’ social performance (p<0.01, R2 = 0.09). These two variables account for 9% of the variation in suppliers’ social performance. Model 2 illustrates that supplier assessment has no significant effect on suppliers’ social performance (B =0.07, p = n.s., R2 =0.09). This means that an increase of supplier assessment leads to no significant increase in suppliers’ social performance. Since R-squared represents the explained variance, the combination of number of employees and turnover accounts for 9% of the variation in suppliers’ social performance, while supplier assessment has no influence on the variation in suppliers’ social performance. Consequently, the results provide no support for hypothesis 1 since no significant positive relationship can be established between supplier assessment and suppliers’ social performance.

4.3 Supplier incentives and suppliers’ social performance

Table 5 LR analysis of Supplier incentives and suppliers’ social performance (H2)

Model 1 Model 2

Step and variables B SE B SE Intercept 4.51*** (0.35) 3.12*** (0.50) Control Number of Employees - 0.24* (0.12) - 0.22* (0.11) Turnover 0.21** (0.08) 0.22** (0.07) Main effects Supplier incentives 0.32*** (0.09) R square 0.09 0.22 △ R square 0.13*** *** P < .001 ** P < .01 * P < .05

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the results confirm hypothesis 2: Supplier incentives is positively associate with

suppliers’ social performance.

4.4 Impact of TR on the effectiveness of supplier assessment Table 6 LR analysis of moderating effect of TR (H3)

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE Intercept 4.51*** (0.35) 4.47*** (0.35) 4.47*** (0.35) Control Number of Employees - 0.24* (0.12) - 0.23 (0.12) - 0.23 (0.12) Turnover 0.21** (0.08) 0.21** (0.08) 0.21** (0.08) Main effects Supplier assessment 0.06 (0.07) 0.07 (0.10)

TR (Buying firms’ trustworthiness) 0.07 (0.07) 0.07 (0.07)

Two-way interaction Supplier assessment*TR - 0.01 (0.09) R square 0.09 0.11 0.11 △ R square 0.02 0.00 *** P < .001 ** P < .01 * P < .05

Linear regression analysis was adopted to assess the influence of TR on the effectiveness of supplier assessment. Table 6 provides the results of the regression analysis for hypothesis 3. Model 1 indicates that the number of employees has a significant negative effect on suppliers’ social performance (p<0.05, R2_{= 0.09), and}

the turnover has a significant positive effect on suppliers’ social performance (p<0.01, R2_{= 0.09). These two variables account for 9% of the variation in suppliers’ social}

performance. Model 2 reveals that supplier assessment has no significant effect on suppliers’ social performance (B =0.06, p = n.s., R2_{=0.11); moreover, TR also has no}

significant effect on suppliers’ social performance (B =0.07, p =n.s., R2 _=0.11).

Furthermore, Model 3 demonstrates that the interactive of supplier assessment and TR on suppliers’ social performance is not significant (B = -0.01, p =n.s., R2 _{=0.11). Since}

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21 4.5 Impact of TR on the effectiveness of supplier incentives

Table 7 LR analysis of moderating effect of TR (H4)

Model 1 Model 2 Model 3

Step and variables B SE B SE B SE Intercept 4.51*** (0.35) 4.41*** (0.33) 4.41*** (0.33) Control Number of Employees - 0.24* (0.12) - 0.21 (0.11) - 0.21 (0.11) Turnover 0.21** (0.08) 0.21** (0.07) 0.21** (0.07) Main effects Supplier incentives 0.24*** (0.06) 0.29** (0.08)

TR (Buying firms’ trustworthiness) 0.07 (0.06) 0.09 (0.07)

Two-way interaction Supplier incentives*TR - 0.09 (0.09) R square 0.09 0.23 0.24 △ R square 0.14** 0.01 *** P < .001 ** P < .01 * P < .05

Linear regression analysis was adopted to evaluate the impact of TR on the effectiveness of supplier incentives. Table 7 presents the results of the regression analysis for hypothesis 4. Model 1 indicates that the number of employees has a significant and negative effect on suppliers’ social performance (p<0.05, R2_{= 0.09),}

and the turnover has a significant and positive effect on suppliers’ social performance (p<0.01, R2 = 0.09). These two variables account for 9% of the variation in suppliers’ social performance. Model 2 demonstrates that supplier incentives has a significant positive effect on suppliers’ social performance (B =0.24, p<0.001, R2 =0.23), while TR has no significant effect on suppliers’ social performance (B =0.07, p =n.s., R2

=0.23). Additionally, Model 3 demonstrates that the interactive of supplier incentives and TR on suppliers’ social performance is not significant (B = -0.09, p =n.s., R2 _=0.24).

As R-squared represents the explained variance, the combination of number of employees, turnover, supplier incentives, TR, and the interactive of supplier incentives and TR accounted for 24% of the variation in suppliers’ social performance. In sum, it can be concluded that the results offer no support for hypothesis 4.

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5. Discussion

Most of the literature on SD practices has a confining focus on environmental or economic dimensions of sustainability, while the social dimension has been neglected (Sancha et al., 2016; Klassen & Vereecke, 2012). In addition, many studies have measured and analyzed the performance implications of SD practices from a buying firm’s perspective (e.g. Gimenez et al., 2012; Rao & Holt, 2005), whereas only a few papers have considered the impact of SD practices from a supplier’s perspective (e.g. Akamp & Muller, 2013; Carter, 2005). As a result, the current research only provides a partial view from a buying firm’s perspective. As such, this master thesis focuses on suppliers, adopts a supplier’s perspective, and investigates the relationship between two identified SD practices (i.e. supplier assessment and supplier incentives) and suppliers’ social performance in the context of China. Moreover, TR as a paramount contextual variable which may influence the function of SD practices and its impact on the effectiveness of SD practices were also taken into consideration in this master thesis. The discussion involves the following three points:

1. Theoretical implications 2. Methodological implications 3. Managerial implications

5.1 Theoretical implications

Impact of supplier assessment on suppliers’ social performance

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requirements, these suppliers will not achieve social performance improvement. For this reason, the research findings are in line with Lim and Phillips (2008), Strand (2009) and Carsten et al. (2010)’s findings and indicate that relying unitarily on assessment does not achieve sustainability.

Impact of supplier incentives on suppliers’ social performance

The result in this master thesis provides support to the hypothesis that supplier incentives are positively associated with suppliers’ social performance. Moreover, the previous studies also indicate positive results regarding the impact of supplier incentives on performance improvement. Krause et al. (2000) stated that supplier incentives have both direct and indirect positive impacts on buying firms’ product performance. Porteous et al. (2015) established that offering suppliers incentives of increased business is strongly associated with a reduction in suppliers’ social performance violations. This master thesis examined the competitive incentives (e.g. increased business) and cooperative incentives (e.g. price premiums) jointly and ascertained that by implementing these incentives on suppliers, the buying firms are able to extend the social sustainability to suppliers and help them to achieve a significant social performance improvement. This research result is in line with Terpend and Krause’s study on US industrial firms (Terpend &Krause, 2015), in which they found that supplier incentives had a significant and positive effect on supplier performance for meeting buying firms’ expectations. In addition, this study provides empirical evidence on the effectiveness of supplier incentives and extended the research of supplier incentives to the suppliers’ social performance dimension. However, it is noteworthy that comparing with the construct of supplier assessment, the adopted items for measuring supplier incentives were not specific on social dimension but general incentives derived from the research of Porteous et al. (2015). Therefore, the construct of supplier incentives may slightly degrade the reliability of the research findings.

The impact of TR on the relationship between SD practices and suppliers’ social performance

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highlighted that dependency decides the degree of how a supplier relies on buying firms for critical resources, and the dependency could directly affect the suppliers’ adoption of social responsible practices. In comparison with dependence, as TR is more related to spontaneous collaboration(Handfield & Nichols, 1999), its influence on the suppliers may not be as coercive as dependency. This could be the reason why the hypothesis could not be proved.

5.2 Methodological implications

In addition to the above-mentioned theoretical implications, it is noteworthy that there are some methodological differences between this research and previous studies (e.g. Sancha et al., 2015; Gualandris & Kalchschmidt, 2014). These distinctions are elaborated as follow.

The suppliers’ social performance construct

There is a lack of agreement on how to measure the social performance construct (de Giovanni, 2012). This thesis adopts five questions from Awaysheh and Klassen (2010) to measure the suppliers’ social performance construct. Furthermore, the measurement of this construct was based on comparisons with suppliers’ main competitors. Hence, the measurement only reflects a horizontal comparison of social performance with competitors and lacks a reflection on the vertical change of a supplier’s own social performance. Since this research targeted at measuring suppliers’ own social performance improvement after implementing SD practices, the construct of supplier’s social performance may not be appropriate in this master thesis. Therefore, the construct of supplier’s social performance may be a possible reason for the lack of significance regarding the hypothesis stated in this study.

A supplier’s perspective

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Cross-sectional survey

Limited by available research resources, this study adopted a cross-sectional survey for data collection. Considering that the cross-sectional survey does not allow the temporal sequence necessary to assess causality (Gualandris & Kalchschmidt, 2015), the collected data only reflects the cognition of respondents at a particular moment. Comparing with face-to-face interviews in a case study, cross-sectional survey with closed-ended questions may have limited validity. As the research objective is to investigate the impact of SD practices on suppliers’ social performance, the aim for the researcher is to collect data from the whole process and to establish a comprehensive understanding of the process and context from the perspective of suppliers. As such, a longitudinal study should be a better research method than a cross-sectional survey (Leonard-Barton, 1990). The choice of research deign in this study may lead to a distortion of research data and generate bias that resulted in the insignificance of our hypothesis.

The context of China

Data have only been collected from the Chinese manufacturing industry. Even though the procedures of data collection were proper and correct, a country caused deviation may still be possible. Moreover, particular attention should be paid to the Chinese unique national culture, as it could influence the research findings. According to the descriptive statistics results of the four variables in Table 3, it can be observed that the mean values of variables are very large. This could be due to the attribute of Chinese employees’ high degree of social desirability, as the respondents felt obligated to provide answers that would be viewed favorably by others (Cuixia et al., 2003). Another reason that may cause the high mean values is that TR plays a much more important role in emerging economies like China than in developed western countries (Gualandris & Kalchschmidt, 2015). In China, the manufacturing firms have more emphasis on guanxi, which refers to the interpersonal connections that applies to kinship, friendship, and social connections (Lee et al., 2005). Under such circumstances, the supplier-buyer relationship is usually based on guanxi and exhibits a high degree of TR, and the stress on guanxi could promote the exploitation of inter-organizational practices such as SD practices (Cai et al., 2010). Therefore, this study’s exclusive focus on the context of China can be a limitation. Consequently, the research results based on data collected from Chinese manufacturing firms may be exclusive and difficult to generalize in a universal level.

5.3 Managerial implications

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6. Conclusion

This paper has two objectives. First of all, this thesis investigates the relationships between two identified SD practices and suppliers’ social performance; secondly, it also examines whether TR could moderate the effectiveness of supplier assessment and supplier incentives on suppliers’ social performance. Regarding the first objective, it has been revealed that only supplier incentives were positively related to suppliers’ social performance. For the second objective, the research data indicates that TR does not moderate the impact of supplier assessment and supplier incentives.

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8. Appendix

Questions design for measuring variables

Supplier assessment: Adapted from Min and Glalle (1997), Krause et al., (2000), Large and Thomsen (2011).

Please indicate the current level of implementation of the following practices:

Social management (e.g., employee wellbeing, health and

safety management) None

High

Our key customer assesses our social performance through formal evaluation, using established guidelines and procedures

1 2 3 4 5 Our key customer performs social audits for our internal

management systems 1 2 3 4 5

Our key customer provides us with feedback about the results

of the social evaluation 1 2 3 4 5

Supplier incentives: Adapted from Krause et al., (2000), Porteous et al., (2015).

Please indicate the current level of implementation of the following incentives offered to you by your key customer to ensure sustainability:

Incentives None

High

Increased business engagements _{1 2 3} ₄ ₅ Preferred supplier status such as priority for future

business 1 2 3 4 5

Better terms and conditions _{1 2 3} ₄ ₅

Public recognition* _{1 2 3} ₄ ₅

Price premiums 1 2 3 4 5

*item dropped because of cross loading

Buying firms’ trustworthiness: Adapted from Doney and Cannon (1997), Gorton et al., (2015).

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Strongly agree Neutral

Strongly disagree

Our key customer keeps the promises it makes ® 1 2 3 4 5 Our key customer is always honest with us ® 1 2 3 4 5 Our key customer is genuinely concerned that our

business succeeds ® 1 2 3 4 5

When making important decisions, our key customer

considers our welfare as well as its own ® 1 2 3 4 5 We trust our key customer keeps our best interests in

mind ® 1 2 3 4 5

We find it necessary to be cautious with our key

customer 1 2 3 4 5

Our key customer is trustworthy ® 1 2 3 4 5 ®: Reverse item

Suppliers’ social performance: Adapted from Awaysheh and Klassen (2010)

Please indicate how your current plant´s performance compares with that of your main competitor(s) in the following areas:

Social Performance Far worse Similar

Far better

Safety and labor conditions in our

facilities 1 2 3 4 5

Compliance with human rights 1 2 3 4 5 Compliance with child labor

employment* 1 2 3 4 5

Social reputation 1 2 3 4 5

Decrease in the number of industrial

accidents 1 2 3 4 5

Extending social sustainability to suppliers: a supplier perspective study on the role of supplier development practices and buyer-supplier trust