Introduction

Corporate social responsibility (CSR) concepts are becoming more and more important in the supply chain. CSR compliances in channel relationships are increasingly recognized in practice (Bask and Kuula 2011; Murphy and Poist 2002; Vurro et al. 2010). Responding to customer and shareholder concerns for CSR, many seller firms have implemented CSR programs in their supply chains, which require suppliers to act in a socially responsible way regarding labor practices, product safety, local community, employee working conditions, and environmental issues (Carter and Jennings 2004; Mefford 2011; Salam 2009).

IKEA is a case in point. It is noted that suppliers can expect from IKEA with regard to working conditions, child labor, environment, and forestry management. IKEA explicitly requires its suppliers to comply with national laws and international conventions on the protection of the environment.

Indeed, there are many case studies and anecdotal evidence pointing out the importance of CSR for supply chain relationships and market performance. (For example, Seuring and Muller (2008, p. 455) note that a socially “sustainable supply chain has emerged as a growing topic” for managers because of the pressures and incentives for doing good at the supplier–buyer interface.) Christopher et al. (2011) propose that CSR initiatives of buyer and seller firms may hedge supply chain process risks, control risks, demand risks, supply risks, and environment risks in global product purchasing, likely enhancing channel performance.

In a comprehensive thematic content analysis, Tate et al. (2010, p. 23) reveal that the top 100 socially and environmentally responsible companies (e.g., 3M, Abbott, IBM, IKEA, and Xerox) all integrate CSR in their buyer–seller relationships.

However, beyond the case studies and anecdotal evidences, there is a lack of research that employs a large sample of real-world companies to comprehensively examine the role of CSR in channel relationships and sales performance. Thus, this article seeks to fill in this literature gap.

Specifically, the goal of this research is to develop and test a theoretical framework on the effects of CSR reciprocity on channel performance. Formally, we define CSR reciprocity as the joint occurrence of CSR strength of buyers and CSR strength of sellers. This framework suggests a set of “CSR reciprocity” hypotheses, i.e., (a) when the suppliers and the customers both exhibit high CSR strength simultaneously, CSR reciprocity influences channel tie intensity and channel sales performance and (b) the effects of CSR reciprocity are amplified (reduced) when the market is more (less) competitive. On the basis of a total of 3,518 buyer–seller channel relational ties collected from multiple secondary sources over 1998–2008, we find support for the framework.

The contribution of this research is three-fold. First, theoretically, we take an initial step to support the notion of CSR reciprocity in buyer–seller relationships. It is the matched CSR strength between buyers and sellers that fosters channel bonding and sales growth, i.e., birds of a feather flock together. However, when CSR strength is mismatched between buyers and sellers, it is not effective any longer.

Second, managerially speaking, we also investigate CSR from the market competition setting. To secure competitive advantages, it is important for managers to pay attention to the competitive environment when integrating CSR programs into the supply chain.

Finally, from a methodological perspective, our study contributes to the CSR literature by leveraging a unique dataset that is secondary and comprehensive. In doing so, we reveal more reliable and robust findings that support the relevance of CSR in the supply chain, over and beyond anecdotal evidence.

In a nutshell, this article crosses strategy, management, and marketing disciplines to examine whether CSR reciprocity affects the supply channel’s tie intensity and sales performance (main effects) and how market competition may amplify or hamper these influences of CSR reciprocity (moderated effects). Next, we present the theory background and hypotheses, followed by data and results.

Theory Background and Hypotheses

CSR Background

Corporations are increasingly adopting socially responsible actions, activities, policies, and processes (Kanji and Chopra 2010; Sen and Bhattacharya 2001). Echoing this rising importance, CSR is defined as a company’s activities and status related to its perceived societal or stakeholder obligations (e.g., Luo and Bhattacharya 2006). CSR can be measured along multiple social dimensions, ranging from product quality, corporate governance, diversity, employee relations, environmental stewardship, and human rights, to community involvement (Choi and Wang 2009; Hull and Rothenberg 2008; Surroca et al. 2010).

Prior research suggests that the potential of CSR to create firm value lies in its ability to create favorable relationships with primary stakeholder groups such as customers, employees, investors, and suppliers (Barnett 2007; Peloza and Shang 2010). Positive relationships with primary stakeholder groups are of particular importance for firms because these groups directly provide crucial resources to the organization and have the ability to influence the firm’s bottom line (Berman et al. 1999; Clarkson 1995). Empirical research in management has investigated the role of organizational stakeholders such as employees (e.g., Turban and Greening 1996) and investors (e.g., Mackey et al. 2007). Marketing studies have focused on mediators in the customer domain. For instance, CSR has been shown to positively influence customer satisfaction (Luo and Bhattacharya 2006), customer loyalty (Du et al. 2007; Klein and Dawar 2004), willingness to pay a price premium (Creyer and Ross 1996), and share-of-wallet (Lichtenstein et al. 2004).

CSR can be embedded in the stakeholder theory as CSR is directed to a firm’s stakeholders’ interests (Maignan and Ferrell 2004; Mcwilliams and Siegel 2001). Following this perspective, CSR can be conceived as a strategic management process designed to establish cooperative firm–stakeholder relationships, which, in turn, positively influence performance (Barnett 2007; Berman et al. 1999; Jones 1995). The CSR literature also converges on moral capital (Godfrey 2005) as a key factor through which CSR can form stronger company–stakeholder relationships and higher channel performance. CSR creates moral capital, which leads to efficient contracting and ultimately increases channel performance (Barnett 2007). Hence, moral capital built through CSR of a customer firm can influence stakeholders’ behaviors toward the firm (Luo and Bhattacharya 2009) and provide insurance-like protection against risk in the channel relationships, thus likely boosting channel partner performance (Boyd et al. 2007; Sharma et al. 2010).

Extending this stream of research, we address whether and how reciprocity in CSR strength between buyers and sellers affect channel relational ties and sales performance. Next, we present the hypothesis logic.

Hypothesis on the Reciprocity in CSR Between Buyers and Sellers

We posit that it is the reciprocity in CSR strength between buyers and sellers that may affect channel tie intensity and channel sales performance. More specifically, reciprocity is a social norm which dictates that an action by one party (buyers) requires a corresponding movement by the other (suppliers). In this study, CSR reciprocity is the joint CSR strength of channel partners (both buyers and suppliers). It represents a cornerstone of channel relationships because only reciprocated actions can motivate exchange partners to continue the cooperation and benefit from the ongoing relationship (Hoppner and Griffith 2011; Houston and Gassenheimer 1987). In our setting, the CSR reciprocity view suggests that when the customer firms and supplier firms are reciprocal in CSR strength, the benefits of CSR in enhancing channel relationship ties and performance are more likely to be realized (i.e., birds of a feather flock together). Indeed, prior studies have shown that reciprocating leads to higher desires to resolve mutual concerns (Dwyer et al. 1987), enables the channel partners to be adjusted to the mutual needs (Lusch and Brown 1996), and improves channel communication effectiveness (Jap and Anderson 2007). Hoppner and Griffith (2011, p. 921) hold that reciprocity is so important that it determines how and when the channel relationships may “operate effectively and efficiently and to adapt to ever-changing environmental conditions.”

Echoing this, Boyd et al. (2007, p. 341) argue that mutual, reciprocal CSR strength of both buyers and sellers can improve procedural justice for exchange relationships, thus positively influencing channel sales performance. Importantly, Luo and Bhattacharya (2009) explicitly point out that moral capital can render companies as trustworthy partners for their suppliers. In fact, there is meta-analytic evidence that a relationship partner’s trustworthiness can strengthen successful B2B relationships and channel performance (Palmatier et al. 2006). This stream of research suggests that when both buyers and sellers are committed in CSR simultaneously (reciprocal condition), joint CSR strength may translate into trusted channel relationships with more social moral capital (Godfrey 2005; Luo and Bhattacharya 2009), which can positively affect channel communication, resolve channel conflict and, therefore, positively affect channel tie intensity and channel sales performance.

In contrast, when CSR reciprocity is not present between buyers and sellers, channel partners have little motivation to engage in pro-social behaviors that benefit the supply channel. Actually, when CSR strength is not reciprocal, channel partners may perceive an unfair, unbalanced relationship (Boyd et al. 2007; Luo et al. 2007), which may lead to channel shirking, opportunism, and other dark effects cancelling the potential benefits of CSR. Samaha et al. (2011) show that the negative effect of channel conflict, opportunism, and perceived unfairness in channel relationships overshadows the benefits associated with all other activities. The long-term success of channel relationships often depends more on preventing or mitigating the “bad” than on accumulating the “good” (p. 99). Thus, when CSR is not reciprocal in the channel, it is challenging to reap the benefits of CSR for channel relational ties and performance.

The upshot is that the joint occurrence of CSR strength more likely enhances channel tie intensity and channel sales performance when the suppliers and sellers both exhibit high CSR strength simultaneously, compared to when either suppliers or customers exhibit high CSR alone, but not both.

H 1

CSR reciprocity, joint CSR strength of buyers and sellers, positively influences channel performance as indicated by channel tie intensity and channel sales performance.

Hypothesis on the Moderating Role of Market Competition

Market competition is always regarded as an important context for the success of CSR strength (Du et al. 2007; Luo and Bhattacharya 2006). Competition intensity refers to a situation of severe price wars, diverse product alternatives, and added services (Zhou et al. 2005). According to Du et al. (2007), buyers can rely on multiple sellers to serve their needs and can more easily switch to competitors. Under such competitive threat, firms’ CSR investment will generate greater influence on channel relationship so as to create market entry barriers for rival firms (Godfrey 2005; Luo and Bhattacharya 2009).

We propose that market competition is an important context moderating the link between CSR reciprocity and channel performance. In other words, the influence of CSR reciprocity on channel performance varies under different competition environments. CSR reciprocity matters more for channel relationship and performance when the industry environment is more competitive as opposed to less competitive. More specifically, the positive effect of CSR on channel tie intensity and sales performance for the reciprocal buyers and sellers is enhanced (reduced) when the market competition intensity is high (low).

In highly competitive markets, CSR reciprocity can induce greater positive effects on channel performance. This is because CSR programs are of particular importance for firms to differentiate themselves from their competitors. For instance, under severe competition, CSR strength facilitates firms to introduce market-based innovations that target new markets (Porter 1985) and attract new customers with different value systems (Frazier et al. 2009; Zhou et al. 2005) so as to gain competitive advantages and improve organizational performance. CSR reciprocity, joint CSR strength of buyers and sellers, will thus better improve channel performance in a highly competitive market.

In contrast, when market competition is low, the influence of CSR reciprocity on channel performance will be reduced considerably. This is because both buyers and sellers may face little pressure of new market entrants and are less motivated to adopt reciprocal CSR strength to achieve and sustain competitive advantages. In other words, the benefits of the reciprocity in CSR between buyers and sellers on improving channel cooperation and reducing channel opportunistic behaviors are likely to be reduced when the market competition is low (Palmatier et al. 2006; Samaha et al. 2011).

Therefore, we hypothesize that market competition may moderate the effects of CSR reciprocity between buyers and sellers on channel tie intensity and channel sales performance in such a way that these effects are amplified when the market is more competitive and reduced when the market is less competitive.

H 2

Market competition moderates the effects of CSR reciprocity between buyers and sellers on channel tie intensity and channel sales performance in such a way that these effects are amplified (reduced) when the market is more (less) competitive.

Methodology

Data Collection and Sample

To test the hypotheses, we compile a large-scale secondary data set on the basis of multiple archival sources. Different from most prior studies with case studies or surveys, our use of different secondary data sources is desirable because doing so has a high level of external validity and can reduce the common method bias, a critical issue in research methodology (Rindfleisch et al. 2008). Table 1 reports the variables and data sources.

Table 1 Variables and data sources
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Our unit of data analysis is the supplier–customer dyad. For each dyad, we collected data for the buyer’s CSR and the supplier’s CSR. We then matched the buyer’s intensity of relational ties with the supplier (channel tie intensity), as well as the sales growth from the supplier (channel sales performance).

Overall, we have data on 386 supplier–customer dyads over 1998–2008, with a total of 3,518 buyer–seller channel relational ties. These 386 dyadic relationships are in a unbalanced panel format, because some of the buyer–seller relationships were established and others were dissolved dynamically (Tuli et al. 2010). The dyads involve 192 customer firms and 216 supplier firms. The sampled firms are from diverse industries such as high technology, services, and manufacturing industries, with standard industrial classification codes ranging from 35–38, 15–24, to 47–80, respectively. Table 2 reports the descriptive statistics and the correlation matrix.

Table 2 Descriptives and correlations
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Measures

CSR Strength of Buyers and Sellers

For both buyers and sellers, we measure CSR as strength of firm activities with a comprehensive set of 94 measurement items along seven social dimensions (product quality, corporate governance, diversity, employee relations, environmental stewardship, human rights, and community involvement). The data source is from the Kinder, Lydenberg, Domini & Co. (KLD) Socrates dataset. The reliability and validity of KLD have been established in the strategic management literature (Choi and Wang 2009; Godfrey et al. 2009; Hull and Rothenberg 2008; Waddock and Graves 1997).

Essentially, KLD compiled the CSR data based on firm Securities and Exchange Commission (SEC) filings, annual reports, annual surveys sent to firms’ investor relations offices, government surveys, and general press releases. Each year, the KLD index covers over 650 publicly traded companies including S&P 500 firms and about 150 firms from the Domini Social Index. It is noted that “the KLD Socrates data provide critical input for individual stakeholder groups (investors and others) in their formulation of a firm’s reputation for social involvement and CSR” (Godfrey et al. 2009, p. 433). Thus, not surprisingly, the KLD dataset has been quite popular in strategy and management literature to measure CSR strength over the last two decades (e.g., Hull and Rothenberg 2008; Surroca et al. 2010; Waddock and Graves 1997). Indeed, Wang et al. (2009, p. 8) argue that “KLD is the best data available for a comprehensive measure” to gauge the strength of firm CSR actions toward various stakeholders.

CSR Reciprocity

In this study, CSR reciprocity is the joint CSR strength of buyers and sellers. We thus measured CSR reciprocity as the interaction between a seller and buyer’s CSR strength (see a similar study in Luo et al. 2007).

Channel Tie Intensity

For each buyer–seller dyad, we measure channel tie intensity as the buyer’s intensity of relational ties with the supplier. Specifically, following Tuli et al. (2010), we consult multiple sources to locate the number of different relational ties between the firm and its suppliers. Channel ties include selling alliances, R&D alliances, marketing alliances, equity ownerships, and board memberships (see Bucklin and Sengupta 1993; Luo et al. 2007; Rindfleisch and Moorman 2001). We collect these different relational ties from the data sources of Thomson Financial SDC Platinum.

To identify buyers and sellers in the channel, we follow the procedures reported in Tuli et al. (2010). Specifically, for public companies, the SEC requires them to identify and report the customer firms that contribute more than 10 % of the suppliers’ sales revenues. In addition, suppliers tend to disclose sales to their customer firms with <10 % of their sales revenues in media press and on the corporate websites, because the accounting literature suggests that firms gain favorable investor responses by engaging in more information disclosure (Bushee and Noe 2000; Gu and Li 2007). In line with Tuli et al. (2010, p. 40), we use SEC Filings 10-K, 10-Q, COMPUSTAT, Securities Data Company database, EBSCO, FACTIVA, and supplier websites to track the various customers to sellers.

Channel Sales Performance

For each buyer–seller dyad, we measure channel sales performance as the buyer’s sales growth from the supplier. We use the log of sales revenue and calculate the changes in channel sales performance as the difference between the log of sales at time t and the time t − 1. That is, log(sales t ) − log(sales t−1) = log(sales t /sales t−1) = sales growth rate. The data for sales revenue are provided by COMPUSTAT (Matsuno and Mentzer 2000).

Market Competition

We measure marketing competition intensity as the Herfindahl industry concentration index (Anderson et al. 2004; Luo et al. 2010). This index is the sum of squared market shares of the firms in the industry derived from sales revenue as reported in COMPUSTAT. That is, \( {\text{Herfindahl}}_{j} = \sum_{i}^{I} {s_{ij}^{2} } , \) where s ij is the ratio of firm i’s sales to the total sales of industry j to which firm i belongs (Hou and Robinson 2006, p. 1933).

Control Variables

We control for multiple factors to rule out alternative explanations to the findings and because the differences of both buyer and seller firms in innovation efforts, product offerings, resources, and capital financing structure can affect firm financial support for CSR actions (Gruca and Rego 2005; Luo and Bhattacharya 2006).

Firm size is the natural log of firms’ number of employees. Bigger firms may drive stronger CSR benefits than smaller firms because of economies of scale.

R&D is measured by the ratio of research and development expenses to total assets, supplied by COMPUSTAT.

Product quality is a firm’s relative ability to meet the minimum condition or the threshold of product attributes when offering its products or service in competitive markets, supplied by the Fortune magazine.

Firm leverage refers to the ratio of book debt to total assets (Luo and Donthu 2006).

We control for market power of suppliers, because the marketing literature suggests that channel power structure affects the nature of the buyer–seller relationship (Anderson and Weitz 1992; Palmatier et al. 2006). This measure is the relative power of a supplier over a customer firm, measured as the ratio of supplier market share to the customer market share (Tuli et al. 2010, p. 42).

Finally, industry uncertainty is controlled for, because demand fluctuations and different types of industry environments can affect the outcomes of CSR actions (Luo and Bhattacharya 2009). It is measured as the standard deviation of 5-year sales growth rates across firms in a given industry (Gruca and Rego 2005).

Analyses

For the analyses, we introduce a changes–changes model to minimize unobserved heterogeneity due to any unobserved firm or time effects (Tuli et al. 2010). The dependent variables are the 1-year change of channel sales performance and channel tie intensity (i.e., ∆channel sales performance and ∆channel tie intensity). The independent variables include the one-year change of CSR Reciprocity (i.e., ∆CSR reciprocity) and the control variables from both seller and buyer firms:

$$ \begin{aligned} \Updelta {\text{Channel}}\;{\text{performance}}_{\text{it}} & = \alpha + \beta \;\Updelta X_{\text{it}} + \varepsilon_{\text{it}} = \alpha + \beta_{1} \;\Updelta {\text{CSR}}\;{\text{reciprocity}}_{\text{it}} + \beta_{2} \;\Updelta {\text{R\&D}}\;{\text{intensity}}\;{\text{buyers}}_{\text{it}} \\ & \quad + \beta_{3} \;\Updelta {\text{R\&D}}\;{\text{intensity}}\;{\text{sellers}}_{\text{it}} + \beta_{4} \;\Updelta {\text{product}}\;{\text{quality}}\;{\text{buyers}}_{\text{it}} + \beta_{5} \;\Updelta {\text{product}}\;{\text{quality}}\;{\text{sellers}}_{\text{it}} \\ & \quad + \beta_{6} \;\Updelta {\text{firm}}\;{\text{size}}\;{\text{buyers}}_{\text{it}} + \beta_{7} \;\Updelta {\text{firm}}\;{\text{size}}\;{\text{sellers}}_{\text{it}} + \beta_{8} \;\Updelta {\text{firm}}\;{\text{leverage}}\;{\text{buyers}}_{\text{it}} \\ & \quad + \beta_{9} \;\Updelta {\text{firm}}\;{\text{leverage}}\;{\text{sellers}}_{\text{it}} + \beta_{10} \;\Updelta {\text{market}}\;{\text{power}}\;{\text{of}}\,{\text{sellers}}\;{\text{over}}\;{\text{buyers}}_{\text{it}} + \beta_{11} \;\Updelta {\text{industry}}\;{\text{uncertainty}}_{\text{it}} \\ & \quad + \beta_{12} \;\Updelta {\text{market}}\;{\text{competition}}_{\text{it}} + \beta_{13} \;\Updelta {\text{CSR}}\;{\text{strength}}\;{\text{buyers}}_{\text{it}} + \beta_{14} \;\Updelta {\text{CSR}}\;{\text{strength}}\;{\text{sellers}}_{\text{it}} + \varepsilon_{{\text{it}}} , \\ \end{aligned} $$

where i = 1, 2, …, 386 dyads, channel performance is the channel tie intensity or sales performance, and X it is the vector of independent variables.

Because our data is in a cross-sectional, time-series panel data structure, the model specifications should account for several features. First, to reduce the threats of serial correlation and heteroscedasticity, we employed the robust regression model with the Newey–West covariance matrix (see Appendix) and quadratic Hill climbing optimization method (Luo and Bhattacharya 2009).

In addition, the model should control for observed and unobserved heterogeneity. Observed heterogeneity is accommodated using the control variables. To account for unobserved heterogeneity due to time and industry effects, we use a changes–changes model in data analyses (Luo et al. 2010; Tuli et al. 2010).

Before reporting the results, we checked a variety of model assumptions with the RESET test, Durbin–Watson and White’s test, Jarque–Bera test, and Breusch–Pagan test. We find that none of the assumptions is violated (Gruca and Rego 2005). As our hypotheses involve moderated effects, we check for multicollinearity bias. Because the largest variance inflation factor is 3.028, less than the threshold level of 10.0, our results do not suffer from severe multicollinearity bias. Next, we report the hypotheses testing results as shown in Table 3.

Table 3 Results for the impact of reciprocal CSR on channel tie intensity and sales performance
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Results

Results for the Effects of CSR Reciprocity Between Buyers and Sellers

In H1, we expect that CSR reciprocity, joint CSR strength of buyers and suppliers, positively influences channel tie intensity and sales performance. The results in Table 3 suggest that there is a positive and significant impact of the joint effect of sellers’ CSR strength and buyers’ CSR strength on channel tie intensity and channel sales performance (β = 0.431, p < .01 and 0.207, p < .05, respectively), as expected. This indicates that CSR reciprocity imposes significant influence on channel performance. Thus, these findings provide evidence for H1.

In addition, there are four cases, depending on the high-low (2 × 2) situations of sellers and buyers’ CSR strength (on the basis of a median split). We then conducted parametric T tests and nonparametric Mann–Whitney tests comparing whether the channel performance is significantly different among the four cases. Both T tests and Mann–Whitney tests suggest that channel tie intensity and sales performance in the case of high–high sellers and buyers’ CSR simultaneously is significantly higher (p < .05) than that in all other cases (high–low, low–high, or low–low).

H2 expects that when the market is more (less) competitive, the effect of CSR reciprocity on channel tie intensity and sales performance is enhanced (reduced). Table 3 results suggest that the interaction between market competition and CSR reciprocity is significant for channel tie intensity (β = 0.239, p < .05), though only marginally significant for sales performance (p < .10).

In Fig. 1, we also show the moderating role of market competition for the cases of reciprocity in CSR strength (high–high) versus the cases of non-reciprocity (averages across the three cases of high–low, low–high, or low–low CSR strength). Again, as suggested by Fig. 1, the effects of CSR reciprocity on channel tie intensity are amplified when the market competition is high, whereas the effects are reduced when the market competition is low. Nevertheless, the effects of CSR reciprocity on channel sales performance are only slightly reduced when the market competition is low. However, the effects of CSR reciprocity on channel sales performance are indeed amplified when the market competition is high. Thus, overall, H2 is strongly supported for channel tie intensity, though less so for channel sales performance.

Fig. 1
figure 1

Plots for the moderating role of market competition. The moderating role of market competition for a channel tie intensity and b channel sales growth

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Additional Results

We also conducted the nonlinear test to examine the relationship between dependent and independent variables. Specifically, to examine the possible nonlinear relationship, we entered CSR reciprocity squared and cubic terms, and failed to find either of them significant (all p > .10). Thus, we did not support the possible nonlinear relationship in this dataset.

We performed additional analyses with bootstrapping (3,000 Monte Carlo simulation runs) and found consistent evidence for key coefficients related to the main and moderated effects of CSR reciprocity on channel tie and sales performance, further suggesting the results’ robustness. Moreover, to account for repeated observations for the same firms, we added one more control variable of repeated firm (1 = repeated firms, 0 = otherwise). The results suggested that with or without this control of a repeated firm variable, our findings on the main effects and moderated effects of CSR reciprocity on channel tie and sales performance are qualitatively the same, i.e., consistent findings.

Furthermore, as channel tie intensity is measured as the buyer’s intensity of relational ties with the supplier, it may be regarded as a count variable. Thus, we conducted additional estimations using a Poisson model. The results are presented in Table 4. The Poisson model results in Table 4 suggest that there is a positive and significant impact of the joint effect of sellers’ CSR strength and buyers’ CSR strength on channel tie intensity (β = 0.286, p < .01). Again, the interaction between market competition and CSR reciprocity is significant for channel tie intensity (β = 0.155, p < .05), as expected. Apparently, these results’ are consistent with those in Table 3, supporting our results’ robustness.

Table 4 Poisson model results for the impact of reciprocal CSR on channel tie intensity
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Implications and Conclusion

Drawing from the stakeholder theory (Freeman 1999; Donaldson and Preston 1995) and channel relational reciprocity literature (e.g., Hoppner and Griffith 2011), we develop a theoretical framework on the effects of CSR reciprocity on channel performance. On the basis of a total of 3,518 channel relational ties of large companies over 1998–2008, we find support for the framework predicting (1) CSR reciprocity, joint CSR strength of both buyers and sellers, positively influences channel relationship performance, (2) CSR has no significant influence on channel relationship performance when either buyers or sellers do not exhibit high CSR strength, and (3) the positive effect of CSR reciprocity on channel relationship performance is enhanced when the market competition is high rather than low. This framework offers important research and practice implications.

This study introduces the concept of CSR reciprocity to the supply chain literature. Vurro et al. (2010) suggest that sustainable value chains are shaped by network centrality. Hietbrink et al. (2010) highlight the role of CSR in business purchasing and strengthening buyer–seller relationships by sharing codes of conduct, social standards, eco-labeling, labor agreements, and social reporting. Primary supply chain integrating CSR categories of environment, diversity, human rights, philanthropy, and safety were established in the U.S. settings (Carter and Jennings 2004; Murphy and Poist 2002) and Asia settings (Salam 2009). Advancing this literature, we support the notion that it is the reciprocal match of CSR among buyers and sellers that bonds a successful buyer–seller relationship with higher channel performance. Conversely, when CSR is nonreciprocal or mismatched between buyers and sellers, it is not effective any longer in boosting channel performance.

We also contribute to the literature by expanding the customer domain outcomes of CSR (Luo and Bhattacharya 2006; Klein and Dawar 2004; Lichtenstein et al. 2004) with buyer–seller relationships in a B2B setting. The present results can be viewed as a promising starting point for scholars who may wish to further deepen the understanding of CSR and channels. We not only agree with Sharma et al. (2010, p. 334) that sustainability in the supply chain is a fertile field but also add that CSR reciprocity helps align the social interests of buyers and sellers for superior channel performance. Given that a socially sustainable supply chain is an emerging trend (Seuring and Muller 2008), we consider CSR-related channel relationships as a top research priority for future scholarly efforts.

Furthermore, our research has some implications for the conflicting findings with respect to the performance impact of CSR. In a comprehensive review, Margolis and Walsh (2003) conclude that the relationship between CSR and firm financial performance remains equivocal in the literature. Our study explains the mixed findings with a new insight. That is, empirical research should expand their research perspectives into the supply chain and examine CSR reciprocity from both buyers and sellers simultaneously.

For managers, integrating CSR into the supply chain is becoming very important as firms seek to create strategic advantages. Buying firms are implementing programs within their supply chains to make sure channel suppliers are acting in a socially responsible way. Many companies are now taking CSR into account in business purchasing from suppliers (Hietbrink et al. 2010).

It is noted that “buying firms are implementing programs within their supply chains aimed at ensuring suppliers act in a socially responsible way” (Boyd et al. 2007, p. 341). Moreover, Krause et al. (2009) point out that CSR and sustainability represents another important priority for supplier selection and retention (p. 20), besides product quality, cost, delivery, and flexibility (Rosenzweig and Roth 2004). Although Gravereau et al. (1978) stated that people in purchasing are perceived by many as “conservative, hard-nosed negotiators either unconcerned about CSR at best or denying such responsibility at worst” (Gravereau et al. 1978, p. 199), their survey analysis of industrial buyers already showed a significant concern for social issues more than 30 years ago. In the long run, managers should notice that socially responsible strategies in B2B settings can contribute to competitive advantage and performance superiority (Sharma et al. 2010).

However, our results suggest that channel performance is boosted only when CSR reciprocity is in place. It is a cornerstone of channel relationships because only reciprocated actions can motivate exchange partners to continue and benefit from the relationship (Hoppner and Griffith 2011; Houston and Gassenheimer 1987). Only when the customer firms and supplier firms are reciprocal in CSR strength, the benefits of CSR in enhancing channel relationship performance are realized. In contrast, when CSR is not reciprocal, supply chain partners may perceive an unfair relationship and, thus, fail to achieve higher channel relationship performance.

Furthermore, managers should be aware of the competitive setting. We do not claim a universal effectiveness of CSR reciprocity. For example, when the firms operate in more competitive markets, CSR reciprocity between buyers and sellers matters more in terms of enhancing channel relationship performance. Therefore, to secure competitive advantages, it is important for managers to pay attention to the competitive environments. The more competitive the market is, the more important it is for managers among buyers and sellers to integrate reciprocal CSR programs into the supply chain for mutual benefits.

Nevertheless, this study focuses on the reciprocity in terms of CSR strength rather than CSR weakness. We have conducted more analyses and considered CSR weakness for both buyers and sellers. We find that our hypothesis testing results are robust, after controlling for the effects of CSR weakness for both buyers and sellers. Thus, robustness analysis with CSR weaknesses as controls produces consistent results. Yet, we acknowledge that it can be a fruitful avenue for future research to address the mechanisms concerning how CSR weakness of buyers and sellers can harm channel performance in B2B settings.

In conclusion, this research addresses the role of CSR reciprocity between both buyers and sellers for channel performance. We hope it can motivate further research to investigate the importance of social responsibility and sustainability for channel relationship management.