An integrative approach to assessing buyer-supplier relationships: scale development and validation Open Access

Over the past few decades, a growing trend to foster long-term relationships between buyers and suppliers (buyer-supplier relations, BSRs) has emerged (Negri, Cagno, Colicchia, & Sarkis, 2021; Negri et al., 2021; Jia, Stevenson, & Hendry, 2023). Scholars have identified interdependent partnerships between buyers and suppliers as the primary means of establishing core competencies to build capabilities over competitors (Mungra & Yadav, 2019). This shift in business practice came with a change in research focus within the domain of supply chain and alliance management, which has transitioned from themes of power dynamics, dependence, and conflicts to an emphasis on relationship quality (Dyer & Singh, 1998; Nyaga & Whipple, 2011), trust, commitment, and other foundational values that characterize enduring relationships (Ryssel, Ritter, & Gemünden, 2004; Gil-saura, Frasquet-deltoro, & Cervera-taulet, 2009; Alghababsheh & Gallear, 2020; Ye, Yang, Huo, & Zhao, 2023). Enterprises are increasingly engaging in long-term collaborative endeavors with key partners to create value and forge a competitive edge (Anand & Khanna, 2000; Mungra & Yadav, 2019; Sjoerdsma & van Weele, 2015; Zhao, Huang, & Su, 2019), enhance their innovation capacity (Inemek & Matthyssens, 2013), reduce costs (Dagger and O'Brien, 2010; Yang, 2013), diminish risks inherent in exchange relations (Segarra-Moliner, Moliner-Tena, & Sánchez-Garcia, 2013), and bolster overall performance (Clauss & Tangpong, 2018).

However, despite their largely recognized benefits, lasting partnerships between suppliers and buyers have some disadvantages (Oliveira & Lumineau, 2019; Möllering & Sydow, 2019). Partners need to adapt to changing circumstances (Clauss & Tangpong, 2018), because otherwise the dangers of overembeddedness (Uzzi, 1996), path-dependency (Sedgwick & Jensen, 2021), and risks of opportunism (Lumineau & Oliveira, 2020) loom large. Therefore, collaborating organizations are recommended to carefully select their partners and regularly appraise their partnerships to make sure these collaborations are still beneficial for them (Stevens, MacDuffie, & Helper, 2015). Regular checks and reviews of partnerships are important, because organizations tend to favor continuity of partnerships over changing partners even in the face of challenges (Anderson, 1995; Gounaris, 2005). Specifically, the outcomes of supplier evaluations can yield insightful data on elements of supplier performance that necessitate enhancement (Noshad & Awasthi, 2018), and enable the measurement of a supplier’s adherence to a company’s performance benchmarks (Simpson, Siguaw, & White, 2002), thus safeguarding the buyer from incurring excessive costs.

The literature on the comprehensive evaluation of BSRs has identified critical factors in assessing the quality of ongoing BSRs: perceived performance of the supplier, satisfaction with the supplier, and trust in the supplier (Holtgrave, Nienaber, Tzafrir, & Schewe, 2020; Poppo, Zhou, & Zenger, 2008; Prahinski & Benton, 2004; Zhong, Su, Peng, & Yang, 2017). These three factors are key determinants of relationship quality (Svensson, Mysen, & Payan, 2010; Ferro, Padin, Svensson, & Payan, 2016). However, while studies to date have propelled the discourse forward by identifying the factors integral to assessing BSRs and offering some tools to monitor BSRs, there remains a notable gap in understanding the interrelation among factors that are key for assessing BSRs. Hence, there is a need to develop an evaluative framework that both encompasses these factors and clarifies their interplay, thereby enabling enable comprehensive BSR evaluation.

We fill this gap by achieving these two research objectives:

• (1)

  Investigating relations between factors integral to comprehensive evaluation of BSRs: perceived performance of the supplier, satisfaction with the supplier, goodwill-based trust, and competence-based trust in the supplier.

• (2)

  Developing a framework to showcase these factors in a form of a multi-item scale that can evaluate BSRs (BSR evaluation scale).

The manuscript is organized as follows. The first section discusses the theoretical background that underpins this empirical study. The next section presents the methodology. It is followed by validation of the BSRs evaluation scale. Finally, we offer a discussion, conclusion, and recommendations for future research.

In building our research model and developing our hypotheses, we relied on social exchange theory (SET) as a primary theoretical framework. Researchers use SET to analyze business-to-business (B2B) relationships (Narasimhan, Nair, Griffith, Arlbjørn, & Bendoly, 2009; Shanka & Buvik, 2019; Zhang & Epley, 2009). This framework posits that entities, whether individuals or organizations, engage in social exchanges due to resource scarcity, compelling them to obtain these necessary assets from others (Contractor & Lorange, 2002). Cropanzano and Mitchell (2005, p. 890) define SET as a theory that involves “actions contingent on the rewarding actions of others, which, over time, facilitate mutually beneficial transactions and relationships.” These exchanges occur within an interdependence framework, in which actors rely on one another for desired outcomes (Molm, 1997), with the primary goals being rewards acquisition and detriments avoidance (Emerson, 1976).

Moreover, SET suggests that social interactions play an important role in value creation, influencing trust and commitment between partners (Kelley & Thibaut, 1978; Zaheer, McEvily, & Perrone, 1998). These voluntary exchanges are assessed based on their economic and social returns. According to Cassia, Haugland and Magno (2021), positive outcomes at the initial stages of interaction markedly increase the likelihood of sustained exchanges and the development of relationships, whereas negative outcomes may cause premature termination. By facilitating a deeper understanding of the initiation and evolution of business supplier relationships, SET has been instrumental in exploring the nuances of B2B interactions through lenses such as satisfaction, trust, commitment, and the duration of relationships (Lambe, Wittmann, & Spekman, 2001; Mohd Noor, Perumal, & Goaill, 2015).

Perceived performance of a supplier in the relationship refers to the extent to which a buyer’s relationship with supplier aids in achieving the buyer’s goals (Gaski & Nevin, 1985). A high level of performance is crucial for optimizing the benefits of a BSR. Viewed as an output, performance in an interorganizational relationship embodies the goal of a partnership (Perry, 1991). The literature on interorganizational relationships often uses the terms “success,” “effectiveness,” and “efficiency” interchangeably with “performance” (for a review see Mungra & Yadav, 2019).

Perceived performance of a supplier is the effectiveness with which a supplier fulfills the buyer’s requirements, according to the buyer. According to SET, when a supplier receives incentives or benefits, such as more business from the buyer, they feel obligated to meet the buyer’s expectations (Nyaga, Lynch, Marshall, & Ambrose, 2013). The BSRs literature has discussed in detail how buyers and suppliers collaborate to achieve operational outputs, focusing on quality, lead time, productivity, delivery, responsiveness, cost, and technical support, among others (Terpend, Tyler, Krause, & Handfield, 2008; Wu, Choi, & Rungtusanatham, 2010; Villena, Revilla, & Choi, 2011). Prahinski and Benton (2004) emphasize the critical importance of supplier performance within the buyer-supplier dynamic, pinpointing key elements that drive performance, including product quality, delivery efficiency, competitive pricing, flexibility in responding to change requests, service support, and overall excellence.

In our study, we adopted a definition of performance that includes tangible benefits. Specifically, these performance benefits encompass financial gains such as profitability and cost savings, alongside operational non-financial performance metrics like delivery time, lead time, and product quality. While some studies incorporate relationship satisfaction within the scope of performance (for review, see Krathu, Pichler, & Xiao, 2015), we differentiate satisfaction as a distinct factor in evaluating BSRs due to its focus on the intangible facets of relationships. This distinction allows for a more nuanced understanding of the dynamics at play, ensuring that the assessment of performance is not conflated with the experience of satisfaction, thereby providing a clearer framework for the study.

Relationship satisfaction is an affirmative emotional state emanating from a comprehensive evaluation of the working relationship between parties (Kundu & Datta, 2015). Scholars identify satisfaction within partnerships as a fundamental element in the cultivation of superior BSRs (Ganguly & Roy, 2021). Satisfaction is a focal construct of interorganizational relationship quality (Ping, 2003), pronounced in SET (Homans, 1958; Blau, 1964).

The literature distinguishes result from relationship satisfaction (Whipple, Lynch, & Nyaga, 2010). Result satisfaction has an economic character, and it refers to a buyer’s appraisal of the financial benefits derived from the relationship, such as sales volume, profit margins, and discounts (Geyskens & Steenkamp, 2000). Therefore, while result satisfaction concentrates on performance issues, relationship satisfaction focuses on relationship activities, such as decision-making participation, information sharing, and coordination. This type of satisfaction pertains to the relationship’s psychological dimensions (Geyskens & Steenkamp, 2000), focusing on the evaluation of interaction experiences – how rewarding social interactions are (Crosby, Evans, & Cowles, 1990; Scheer & Stern, 1992; Gassenheimer & Ramsey, 1994). In this study, we conceptualized satisfaction as intangible relationship satisfaction, while tangible results appraisals fall under the rubric of perceived performance (Krathu, Pichler, & Xiao, 2015).

Trust is recognized as a fundamental element in interorganizational relationships, embodying the readiness to embrace vulnerability based on the positive expectation of another organization’s intentions or behaviors. The main driver of positive expectations is the trustworthiness of the other party (Mayer, Davis, & Schoorman, 1995; Rousseau, Sitkin, Burt, & Camerer, 1998; Colquitt, Scott, & LePine, 2007). At the interorganizational level, trustworthiness relates to whether one firm is reliable and would act in the other firm’s best interest (Sako, 1992; Hunt & Morgan, 1994; Baker, 1999). Consequently, applying these studies to our research context, we conceptualized trust as a buyer’s conviction about a supplier’s trustworthiness. Such conviction results from the buyer’s belief that the supplier is trustworthy, meaning competent, responsible, honest, and fair (Hunt & Morgan, 1994; Mayer et al., 1995). Our conceptualization also captures the affective side of trust (Ring & Van de Ven, 1992; Barney & Hansen, 1994; Dyer & Chu, 2003), which is the most common dimension of trust used in BSRs studies (e.g. Hunt & Morgan, 1994).

Within BSRs, trust is paramount, significantly enhancing the effectiveness of the partnership (Brattström & Bachmann, 2018; Schilke & Lumineau, 2023). It serves as a safeguard against opportunistic behaviors, thereby exerting a beneficial impact on the performance of the involved entities (e Silva, Bradley, & Sousa, 2012). Trust among partners reduces risk (Ghosh & Fedorowicz, 2008; Huang & Chiu, 2018), fosters flexibility (Wathne & Heide, 2000) and innovativeness (Sako, 1992; Capaldo, 2007), improves knowledge transfer (Levin & Cross, 2004) and information sharing (Ebrahim-Khanjari, Hopp, & Iravani, 2012). Trust plays a key role in the building of a long-lasting relationship (Ganesan, 1994). Buyers and suppliers in a high-trust relationship communicate openly, solve problems together, and share goals (Fawcett, Fawcett, Watson, & Magnan, 2012). Within SET, trust is an inherent aspect of social exchange (Brattström & Bachmann, 2018).

Aligning with research on inter-firm relations, we adopted the classification of trustworthiness beliefs into two dimensions, distinguishing “competence” from “goodwill” (Sheppard & Sherman, 1998; Das & Teng, 2001). This division is prevalent throughout the literature, where competence is alternately termed as “ability” or “expertise,” and goodwill as “integrity.” Competence-based trust stems from the belief in a partner’s abilities, founded on optimistic expectations about a partner’s technical acumen, experience, and dependability in meeting objectives (Nooteboom, Berger, & Noorderhaven, 1997). It embodies the confidence that a partner will adhere to contractual obligations. Conversely, goodwill-based trust relates to responsibility (Nooteboom et al., 1997), integrity (Mayer et al., 1995), and the partner’s benign intentions (Möllering, 2006). It represents the hopeful expectation of a partner’s benevolence, equity, and mutual respect. Goodwill-based trust goes beyond mere formal agreements and enables the collaborative pursuit of new ventures between the parties. Within SET, goodwill-based trust accumulates with repeated exchange experiences. The buyer and supplier follow the reciprocity principle which leads to an increased flow of resources between them (Chen, Chen, Liu, & Yao, 2018).

In the literature on interorganizational relationships, the constructs of trust, perceived performance, and satisfaction are pivotal in BSR quality (Svensson et al., 2010; Ferro et al., 2016). The literature recognizes the importance of relationship quality in forging sustainable competitive advantages in BSRs (Dyer & Singh, 1998; Nyaga & Whipple, 2011). A review of these dimensions, within the context of BSRs, reveals a lack of consensus on how the constructs of perceived performance of the supplier, satisfaction and trust interact.

Therefore, this study is dedicated to the empirical investigation of the research model illustrated in Figure 1.

This model explores relationships between perceived performance of the supplier, relationship satisfaction, goodwill-based trust, and competence-based trust.

By examining these relationships, the study fills the identified research gap by testing four hypotheses:

Performance concerns matter to trust both as evaluations of past performance and in form of anticipated future benefits (Parkhe & Miller, 2000; Poppo et al., 2008). A good record of past performance in lasting relationships provides knowledge about partner’s abilities, reinforcing competence-based trust. Through learning about the partner in collaboration, joint problem-solving, and regular communication including informal interactions, buyers can also learn about the supplier’s goodwill. Regarding the impact of specific aspects of performance on trust, research shows that the quality of products or services, on-time deliveries, competitive pricing, flexibility, and post-transaction support are linked to trust judgments. High performance in partnerships usually supports the development and long-term resilience of trust, while poor performance may undermine the foundations of trust, by lowering partners’ trustworthiness.

Perceived performance of the supplier encompasses quality, delivery timeliness, cost management, and responsiveness. It is instrumental in shaping buyer satisfaction (Anderson & Narus, 1990; Szymanski & Henard, 2001). Performance evaluations comprise tangible facets of the relationship. Therefore, positive perceptions of supplier’s performance in terms of financial and operational gains are likely to lead to increased relationship satisfaction.

Szymanski and Henard (2001) provide a meta-analytic review that underscores the positive correlation between performance and satisfaction across contexts (e.g. Churchill & Surprenant, 1982; Oliver & DeSarbo, 1988), including BSRs. Their findings suggest that the better the supplier meets or exceeds performance expectations, the more satisfied the buyer is. This relationship is reinforced by theories of expectancy and confirmation, where satisfaction is seen as a result of the supplier’s performance relative to the buyer’s expectations (Oliver, 1980). Given this body of evidence, it is reasonable to hypothesize that perceived performance of the supplier positively and significantly influences relationship satisfaction with that supplier.

While research is inconclusive about the association between relationship satisfaction and trust (Mysen, Svensson, & Payan, 2011), a firm’s satisfaction with the business partner has been found to affect outcomes of trust (Moliner, Sanchez, Rodrıguez, & Callerisa, 2007a; Mysen et al., 2011); other research identifies satisfaction as an antecedent of trust (Ganesan, 1994; Ha & Muthaly, 2008; Moliner et al., 2007a, Moliner, Sánchez, Rodríguez, & Callarisa, 2007b). While some research suggests that trust is a precursor to relationship satisfaction in interorganizational relationships (Anderson & Narus, 1990; Payan & Svensson, 2007; Skarmeas & Robson, 2008), we add our hypothesis to the first argument because of the stronger expected effects of satisfaction leading to trust. In other words, satisfaction with a supplier has been found to increase trust between collaborating firms to the point that may even elicit excessive trust (Lazzarini, Miller, & Zenger, 2008). Intangible benefits derived from the satisfaction of interacting with trusted partners often overshadow tangible gains and inhibit accurate assessment of trustworthiness (Inkpen & Ross, 2001). In fact, when relationship satisfaction is high, the chances of reassessing the partner’s trustworthiness is likely to decrease (Langfred, 2004), because actors tend to accept information from trusted partners at face value (Uzzi, 1997) and invest less effort in verifying the accuracy of information (Mizruchi & Stearns, 2001).

Trust is essential for achieving performance gains in BSRs (Dyer & Singh, 1998; Dyer & Chu, 2003). A buyer’s trust in the supplier can reduce transaction costs (Barney & Hansen, 1994) and facilitate efficient outcomes (Dyer & Chu, 2003). Moreover, trust reduces conflict and makes negotiations less costly (Dyer & Singh, 1998). Furthermore, trust acts as a mechanism through which committed parties expand the scale and scope of their exchanges and take greater risks within the relationship (Gulati, 1995). As trust in a supplier increases, a buyer can move beyond routine work with the supplier to riskier, higher-potential business interactions. These positive characteristics of trust explain how committed parties achieve performance gains.

Trust has significant positive effects on performance, especially in BSRs (Vlachos & Bourlakis, 2006). It promotes more flexible and responsive supply chain mechanisms, enhancing resilience through mutual support during disruptions (Manfredi & Capik, 2022). Trust is also a key factor in encouraging innovation and knowledge sharing between buyers and suppliers, which is essential for improving existing or developing new products, processes, or services. Moreover, it fosters commitment and the cultivation of long-term partnerships, contributing to stability and operational efficiency.

The study investigated relations between perceived performance of the supplier, satisfaction with the supplier, goodwill-based trust, and competence-based trust in the supplier in BSRs; and on this basis developed a multi-item BSR evaluation scale.

To realize these objectives, we used the buyer-supplier relationship at the firm-to-firm level as the analysis unit. To collect empirical data, we administered a Computer-Assisted Telephone Interview survey. We collected the data in May 2023.

Our initial survey instrument utilized the measurements from previously published studies (see Table 1). Working separately, we translated the English-language original items into Polish. We discussed and resolved any inconsistencies between the two translations.

We then employed six items from Prahinski and Benton (2004) to measure the perceived performance of the supplier. Moreover, we used four items as developed by Cassia et al. (2021) to measure satisfaction with the supplier. We measured goodwill-based trust toward a supplier using four items from Holtgrave et al. (2020). Finally, we employed four items to measure competence-based trust (Holtgrave et al., 2020). We used a 7-point Likert scale to operationalize the study’s measurements.

We pre-tested the survey instrument on the sample of 196 respondents. Based on the feedback, we modified the instrument to enhance its clarity (see Table 1 for final items).

The duration of the buyer-supplier relationship and declared trust in the supplier have a significant impact on the buyer-supplier relationship (Zhong et al., 2014; Zhou & Poppo, 2010). Therefore, we used them as control variables. We measured the duration variable of the buyer-supplier relationship using a single question: “How long has your company been working with this supplier?” We also used a single question when measuring declared trust variable: “How would you rate the level of trust your organization has in this key strategic supplier?”

Moreover, we controlled for firm size and industry type. We coded the first one for micro, small, medium, and large firms. We coded the industry type for manufacturing companies and service companies.

In this study, we collected data from the manufacturing and service industries. We selected these two sectors due to the inherent distinctions between them. The manufacturing sector focuses on product, while the service industry emphasizes process. Moreover, the manufacturing sector demonstrates high barriers to entry, unlike the service sector which tends to have lower barriers.

We employed non-probability purposive sampling approach to choose respondents from these two sectors. We limited ourselves to recruiting employees in managerial positions and who interacted with suppliers. To collect data, the contracted market research agency was instructed on the process and briefed on the research goals. The agency recorded interviews with respondents, which allowed us to control the data collection and ensure data quality.

We conducted the study using a structured questionnaire. Following Hair, Page and Brunsveld (2019), we standardized the questionnaire with predetermined response choices. We had 422 respondents in the study sample. The sample included respondents from firms of various sizes, with the majority (86%) being micro and small firms. Medium-sized companies comprised 9% of the sample, and large companies 5%. In terms of respondents, more than 62% were board members, more than 20% were managers, and the remainder were professionals. Furthermore, 80.3 % have worked in their companies for more than 10 years.

We began by verifying the factorability of the data. We performed the analysis in R studio software using Lavaan (Rosseel, 2012) and psych (Revelle, 2017) libraries. We used Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity as they provide information on whether or not factor analysis can be applied. The KMO coefficient assesses the suitability of a data matrix for factor analysis and if the data structure is appropriate for extracting factors. The recommended KMO value for factor analysis is 0.60 or higher (McCroskey & Young, 1979; Pett, Lackey, & Sullivan, 2003; Tabachnick & Fidell, 2007). Bartlett’s test of sphericity compares the correlation matrix with the identity matrix which is filled with 0. It measures null hypothesis that the variables are not correlated. Bartlett’s test is significant at value of <0.05 or less indicating that the variables are correlated, and factor analysis is appropriate. As presented in Table 2, KMO test and Bartlett’s test of sphericity indicate that factor analysis was suitable. In the next step, we performed exploratory factor analysis (EFA) to determine the number of factors underlying the data.

We performed EFA with maximum likelihood as the extraction method and with direct oblimin as the rotation method. Consequently, EFA provided evidence of a three-factor model: perceived performance of the supplier (PP), satisfaction with the supplier (STS), and goodwill-based trust with competence-based trust together on one latent factor from now on labeled Trust in the supplier (TS) accounting for 62% of the total variance. Once the factors were extracted, we used factor loading to determine the degree to which items load onto particular factors. Following the recommendations of Hair, Black, Babin and Anderson (2010), we considered factor loadings greater than 0.50. Therefore, we dropped two items (S2 and C4). All remaining items had strong loadings on the specific factors (see Table 3).

We tested the three-factor model resulting from EFA through maximum-likelihood confirmatory factor analysis (CFA) to validate the measure’s dimensionality, reliability, and validity (Carpenter, 2018). We tested the fitness of model with three-factors: perceived performance of the supplier (PP), satisfaction with the supplier (STS), trust in the supplier (TS). According to Hu and Bentler’s recommendations (1999), models with TLI and CFI close to 0.95 or higher, RMSEA close to 0.06 or lower and SRMR close to 0.08 or lower are representative of good-fitting models. We also followed Browne and Cudeck (1993) who suggested borderline of RMSEA at the level of 0.08.

The results of CFA indicated a good model fit (χ² = 300.71, df = 101, CFI = 0.97; TLI = 0.965; SRMR = 0.035; RMSEA = 0.068).

We evaluated convergent validity based on the average variance extracted (AVE) Therefore, in the following step, we examined the scale’s convergent validity (see Table 2). It indicates for convergent validity, as it is greater than 0.5 (Fornell & Larcker, 1981). In our study, AVE from each factor ranged from 0.66 to 0.78 providing evidence for convergent variables.

To establish discriminant validity between the factors, we compared AVE with the squared interconstruct correlations (Fornell & Larcker, 1981; Hair et al., 2010). Discriminant validity exists when the AVE of each construct is larger than the squared correlation coefficients between any two constructs. As the AVE was higher than the squared correlation coefficients, discriminant validity is achieved (see Table 4).

In summary, results obtained from the process of scale development and validation provide evidence of the soundness of three-factor BSR scale with Factor 1 being labeled “perceived performance of the supplier,” Factor 2 “satisfaction with the supplier” and Factor 3 “trust in the supplier.”

In the next step, we applied SEM to test the relationships between perceived performance of the supplier, satisfaction with the supplier, goodwill-based and competence-based trust. Following Wu, West and Taylor (2009), the results of SEM indicated a good model fit (RMSEA = 0.069, CFI = 0.97, TLI = 0.96, SRMR = 0.035, χ² = 300.707, df = 100).

Subsequently, we examined the statistical significance of the path coefficients among the variables. All the paths were statistically significant. The paths were: from satisfaction with the supplier (STS) to trust in the supplier (TS); from perceived performance of the supplier (PP) to satisfaction with supplier (STS) and to trust in the supplier (TS); from trust in the supplier (TS) to perceived performance of the supplier (PP). Therefore, all the four hypotheses are supported. Figure 2 shows the models’ SEM results.

This study contributes to the academic discourse by investigating relations between factors used to assess relationship quality in BSRs and, consequently, by proposing an integrative measurement instrument that serves to assess ongoing BSRs. This approach responds to the call for a more comprehensive evaluation framework that reflects the complex interplay of factors influencing relationship quality in BSRs (O’Connor, Lowry, & Treiblmaier, 2020). Our empirical analysis leveraging SEM validated the proposed instrument and elucidated the significant roles of satisfaction, trust, and performance in shaping the BSRs’ quality.

Our study reaffirms the critical role of supplier performance as a foundational pillar influencing both satisfaction and trust dimensions within BSRs. This underscores a fundamental premise in the management literature that operational excellence and the fulfillment of contractual obligations nurture trust and satisfaction among business partners (Ganesan, 1994). Notably, the positive correlation between perceived performance of the supplier and relationship satisfaction elucidates how tangible outcomes, such as quality, delivery timeliness, and cost management, are paramount in shaping buyer’s satisfaction (Geyskens & Steenkamp, 2000).

Moreover, the significant influence of satisfaction with the supplier on trust in the supplier highlights BSRs’ emotional and psychological underpinnings. This finding suggests that subjective experiences and the quality of interactions between buyers and suppliers are crucial in building a resilient and trusting partnership. It encourages firms to rethink their approach to relationship management, advocating for a balance between performance excellence and positive relational experiences. This is consistent with SET, which states that social norms are important in BSRs (Griffith, Harvey, & Lusch, 2006, p. 95).

The integration of goodwill-based trust and competence-based trust into a single factor of trust in the supplier supports the argument about the multifaceted nature of trust in BSRs. Our study indicates that there are not two separate types of trust, but only two distinct foundations within trustworthiness assessments (competence and goodwill) that comprise one component of trust.

Moreover, our findings underscore the critical impact of relationship satisfaction on enhancing both trust and foundations of trust, which positively influences the supplier’s performance. Additionally, the indirect positive effect of trust in the supplier on satisfaction with the supplier, mediated through the supplier’s performance, highlights the interconnectedness of these constructs (Holtgrave et al., 2020; Poppo et al., 2008; Prahinski & Benton, 2004; Zhong et al., 2017).

The study’s findings offer a nuanced perspective on the mechanisms that foster successful, long-term partnerships. They may be useful for managers aiming to build and sustain trusting interorganizational relationships, indicating that efforts should be directed not only to showcasing technical and operational competence, but also to demonstrating ethical conduct and a genuine commitment to the partner’s welfare. Furthermore, the BSR evaluation scale offers practitioners a robust tool for assessing the quality of supplier relationships. By incorporating the dimensions of supplier performance, satisfaction with the supplier, and trust in the supplier, managers can enhance supplier evaluation processes, make informed strategic decisions, and monitor relationship quality over time.

However, our research is not without limitations. As in most research of this type (Yawar & Kauppi, 2018), it focuses on the buyer’s perspective, which introduces a potential bias in capturing the entirety of BSRs dynamics. Future research should balance this perspective by incorporating insights from suppliers, thereby enriching our understanding of these complex relationships. Furthermore, the mechanisms through which buyer organizations can influence BSRs warrant further investigation. Exploring these mechanisms could reveal actionable strategies for both buyers and suppliers to enhance their collaborations and reap the mutual benefits.

Furthermore, our measure of trust, conceptualized as perceived trustworthiness, has been widely used in trust research, but it presents a reductionist view of the concept of trust. Future studies should explore other antecedent factors and account for the distinction between trustworthiness beliefs and actual trusting behavior. Next, the framework of our study requires further development including the literature on possible limitations of trust (Stevens et al., 2015; Six & Latusek, 2023). High relationship satisfaction and high perceived performance of the supplier can have a darker side that unfolds as the partnership progresses, leading to overembeddedness (Hagedoorn & Frankort, 2008), false sense of security for both firms (Forkmann, Webb, Henneberg, & Scheer, 2022), misallocating valuable resources (Molina-Morales, Martínez-Fernández, & Torlò, 2011), stifling innovation (Noordhoff, Kyriakopoulos, Moorman, Pauwels, & Dellaert, 2011), and missing business opportunities of potentially valuable new partnerships (Sorenson & Waguespack, 2006; Gu, Kineta, & Tse, 2008).

This research received support from the National Science Centre, Poland [Project Number 2020/37/B/HS4/02940].