Collaborative B2B sales partnerships in supply chains: An integrative framework of social and action alignment

Abstract

In business-to-business (B2B) contexts, sales organizations require both long-term and stable partnerships to accomplish their tasks effectively and enhance mutual value and satisfaction for the parties involved. Collaboration and satisfaction are two connected and central issues in the relational marketing (RM) literature. Considering the association viewpoint and membership domain (MD) theory, collaboration in B2B sales partnerships implies that parties should cooperate and align their interests and goals (social association), as well as coordinate their tasks and align their actions (action association). Nevertheless, this duality has been severely misunderstood in the literature, and it is therefore necessary to clarify and integrate this dichotomy within the same research framework. Accordingly, this research examines how to connect collaboration and satisfaction by decomposing and disaggregating them within the same alignment model.

1

Introduction

Sales organizations fundamentally require interorganizational collaboration and partnership to perform their tasks. In the context of business to business (B2B) it is generally agreed that collaborative alliances between buyers and sellers in supply chains require long-term and stable partnerships, which form the basis for value generation and satisfaction for the parties involved (Arli et al., 2018; Guan et al., 2022; Zacharia et al., 2011). Such partner collaboration implies the need for inter-firm cooperation and coordination (Payan, 2007; Gulati et al., 2012; Høgevold et al., 2019) which leads to relational exchanges and business success (Arli et al., 2018).

These issues of supply chain collaboration, partnership and relational exchanges have become of strategic concern for firms in B2B contexts, as well as of relevance in the literature and research on supply chain management (Berry, 1983; Corsten & Felde, 2005; Spekman & Davis, 2016; Zacharia et al., 2011). The reason is that firms collaborating and creating value together enhance mutual value and satisfaction along their value chains (Di Benedetto et al., 2019; Kanter, 1994; Palmatier, 2008). Specifically, collaboration and satisfaction are two related issues in industrial markets that are still focal points for research (Fill & Fill, 2005; Guan et al., 2022; Gligor et al., 2020).

In the literature on B2B and supply chain management, collaboration implies partners coordinating or aligning their actions to achieve common goals, as well as supply chain partners aligning their interests or cooperating with each other (Camerer & Knez, 1996, 1997; Foss, 2001; Høgevold et al., 2019). Indeed, Gulati et al. (2012) have confirmed that collaboration in B2B partnerships embraces two facets: cooperation and coordination; that is, firms which collaborate need to align their interests, decision-making and action implementation.

This study provides a deeper understanding of B2B sales partnerships along the supply chain by clarifying the essence of and connection between these two core elements (i.e., collaboration and satisfaction) considering an alignment viewpoint in line with recent works such as Guan et al. (2022), and the notion of closer domains proposed by Ting (2011). Building on recent calls (Høgevold et al., 2020a), we examine how to connect collaboration and satisfaction of B2B partnerships in supply chains by decomposing and disaggregating both issues within the same model (Gulati et al., 2012; Høgevold et al., 2019; Marqui et al., 2013; Mpinganjira et al., 2017; Ting, 2011). Specifically, satisfaction is important in collaborative alliances, as it is the consequence of relational exchanges (Ferro et al., 2016; Mpinganjira et al., 2017; Skarmeas et al., 2008). Furthermore, the literature has indicated two dimensions of this issue: social (or non-economic) satisfaction, and financial (or economic) satisfaction (Geyskens & Steenkamp, 2000; Høgevold et al., 2020a; Palmatier, 2008) and the need “to include these two poles separately” for “a global assessment of partnership fulfillment” (Høgevold et al. 2019). Therefore, considering this duality is highly relevant for research in this arena.

Undoubtly, collaboration fosters opportunities for firms to create value (Camarinha-Matos & Afsarmanesh, 2006; Zacharia et al., 2011), and in turn, superior performance (Martin & Grbac, 2003). According to the organizational dynamics school of thought, firms involved in collaborative alliances within their business processes have to cooperate (i.e., resolve to work together), and coordinate (i.e., share tasks and responsibilities), to carry out their joint activities (Gulati et al., 2012; Høgevold et al., 2020b; Sheth et al., 1988). Nevertheless this duality in B2B collaboration has been largely misunderstood in the literature (Spekman & Davis, 2016) and, indeed, there are recent research calls to clarify and integrate this dichotomy within the same research framework (Gulati et al., 2012; Kale & Singh, 2009; Høgevold et al., 2019).

Therefore, in order to clarify what leads to successful B2B sales partnerships and collaboration in supply chains, in line with the work of Payan et al. (2019), and building on open research and the gap identified by Høgevold et al. (2019, 2020a), in this work we offer an integrative framework by merging the duality of those two relevant issues, satisfaction (i.e. economic and non-economic) and collaboration (i.e. cooperation and coordination), into one model by considering the dual domain reasoning proposed by Ting (2011), in which those concepts or variables of the same domain are more closely related than those from different ones, and for the specific case of B2B sales partnerships. Under this closer domain view (Ting, 2011), coordination and economic satisfaction can be related to the economic chain and can thus be seen as both outcome-related variables belonging to this outcome domain, while cooperation and non-economic or social satisfaction relate more to attitudes and the social chain and, hence, are best considered as variables belonging to the process domain.

In all, the study presented here applies the following structure: first, we present an alignment vision of B2B collaboration and, accordingly, we next introduce our research model and develop the assumptions. Afterwards, we explain our research methodology and present the empirical findings and analysis, concluding with some research and practical implications.

2

Theoretical background, research model and hypotheses

2.1

Alignments in B2B collaboration

Implicit to the creation of B2B collaboration alliances and partnerships is the notion of alignment. In business, this concept helps to frame the integration of key processes and systems in a firm (Labovitz & Rosansky, 1997) and refers to a match, strategic fit or the interface between the two, toward a common set of objectives and in search of the best possible solution (for a review, see Scherpereel, 2006). In this regard, alignment has to do with a B2B partnerships orientation, and refers to the agreement or alliance between two firms to achieve goals collaboratively and increase value (Arli et al., 2018).

Certainly, this issue of alignment allows B2B-oriented firms to create satisfactory and long-term partnerships by collaborating with their partners. That is, by collaborating within the supply chain, partners will do better than working alone (Camarinha-Matos & Afsarmanesh, 2006; Corsten & Felde, 2005; Day, 2000; Di Benedetto et al., 2019; Viio & Gronroos, 2014). Consequently, this idea of alignment is inherent to B2B sales partnerships in the supply chain and collaboration within the relational view of the firm, as firms intentionally strive to align their goals and actions with one another in sustaining a partnership aimed at achieving better gains conjointly.

Applying a partnership-marketing mind-set, aligning in B2B implies firms first recognizing the interest in and benefits of working together and cooperating and, next, the development and coordination of joint actions in a serious effort for partner firms to interact, that is, B2B collaboration. Specifically, the former refers to the partners’ predisposition to work together (Payan & Svensson, 2007) whereas the latter reflects the specific actions that parties undertake together in the supply chain (Svensson & Mysen, 2011).

Thus, long-term collaboration and partnerships between organizations can be visualized in terms of a metaphor of alignment. Indeed, cooperation is connected to the attitudes of firms which are aligning their interests, while coordination refers to the specific actions (i.e., firms aligning actions). Moreover, for a good understanding of collaboration in B2B partnerships, the literature has stressed the need to consider these two related aspects separately (Kale & Singh, 2009; Payan et al., 2019), to avoid the kind of failure reports connected to this issue (Gulati et al., 2012).

Therefore, firms have to identify and perform those required actions together (i.e., action alignment), as well as consciously desire to become involved in such aligned actions (i.e., interest or social alignment) in order to achieve mutual collaboration. This alignment vision creates the routes by which collaboration and a B2B relational orientation generate value for the parties involved in supply chain partnerships.

2.2

Research model

If parties collaborate, satisfaction should emerge (Homburg et al., 2012; Roberts-Lombard et al., 2019). Accordingly, satisfactory B2B partnerships imply firms achieving better sales, margins, or revenue, or lowering their costs and increasing profitability (Geyskens & Steenkamp, 2000; Walz, 2009). Also, there should be emotional rewards from the relational interaction, such us an exchange of ideas, loyalty, or personal gratification (Chen et al., 2011; Gassenheimer & Ramsey, 1994; Rodríguez del Bosque et al., 2006).

In addition, the above-mentioned alignment vision implicit in B2B sales partnerships can be applied to both the concepts of collaboration as well as to satisfaction, as the alignment can be referred to action alignment for one side, and interest or social alignment for the other (Colvin & Boswell, 2007). Specifically, action alignment is more objective and relates to the integration of firms’ actions and strategic goals to maximize value creation. By contrast, interest or social alignment is subjective and relates to those behavioral or social outputs derived from the realization of the organizational strategy that go beyond traditional monetary compensation.

Certainly, the formation of collaborative alliances involves the firms’ interest in working together along the supply chain (i.e., cooperation or social alignment), and the joint activities undertaken (i.e., coordination or action alignment). Similarly, a global assessment of satisfaction refers to emotional compensation or subjective outcomes (NES or social alignment), and functional or economic benefits (ES or action alignment) (Payan et al., 2019; Guan et al., 2022). Furthermore, “there is a fit between the two components of collaboration with the two dimensions of satisfaction” (Høgevold et al., 2019).

In addition, and according to Ting's (2011) domain vision, the interaction of variables of the same domain is greater than those of different ones. Therefore, considering this vision, both variables related to action alignment (i.e., coordination and ES) fit together within the outcome domain, as both are related to the economic resources and transaction outcomes in the chain. Equally, the two social variables (i.e., cooperation and NES) fit within the process domain of the social chain, as they are considered attitudinal, emotional and social aspects related to the interaction (Ferro et al., 2016; Payan et al., 2019; Mpinganjira et al., 2017; Ting, 2011).

Based on this logic, we present a research model in which the concepts fitting in to each domain. That is, coordination and ES into the action alignment or outcome domain of the supply chain, and cooperation and NES into the social alignment or process domain of the supply chain, have a positive effect on each other (see Fig. 1).

Fig. 1.

Research model.

2.3

Hypotheses

Fig. 1 outlines the research model considered in this study, which is based on the one from Payan et al. (2019) in B2B purchase partnerships. Fig. 1 posits that coordination influences economic satisfaction (ES), based on the assumption that both concepts belong to the same outcome domain. Fig. 1 also posits that cooperation influences non-economic satisfaction (NES), based on the assumption that both concepts belong to the process domain. We now develop the research hypotheses for our model:

2.3.1

Coordination and ES

In line with the literature, we first suggest a link between satisfaction and coordination, as coordination may improve outcomes (Field & Meile, 2008; Payan & Svensson, 2007; Prahinski & Benton, 2004). More precisely and considering the duality of satisfaction (i.e., ES and NES), and consistent with such work as Høgevold et al. (2019) or Payan et al. (2019), we argue that coordination increases ES, as coordinating strategies enhances the various components of ES, such as improving response and supply time, reducing costs, and enhancing customer service (Sarmah et al., 2006). Therefore, we formulate the first assumption in our research model as follows:

H₁:Coordination has a positive effect on ES in B2B sales partnerships.

2.3.2

Coordination and cooperation

Furthermore, collaboration requires coordination as well as cooperation, given that they are two necessary parts of organizational collaboration (Nurdin et al., 2014), and organizations need to handle both simultaneously (Marqui et al., 2013). Cooperation reflects the attitude and intention to work together whereas coordination implies joint actions by parties in the supply chain (Høgevold et al., 2019; Payan, 2007).

It is also generally agreed that firms in the supply chain start coordinating their activities for aspects that might not be related to cooperation (Payan & Svensson, 2007). Indeed, before a cooperative alliance begins, firms have already worked together in a coordinated manner (Knez & Camerer, 2000; Gulati et al., 2005). More precisely, when firms engage in coordinating activities, a cooperative mindset emerges (Guan et al., 2022; Gulati et al., 2005). Hence, we formulate the second assumption in the research model as follows:

H₂:Coordination has a positive effect on cooperation in B2B sales partnerships.

2.3.3

ES and cooperation

Moreover, on the foundation of cooperative alliances, and as the first steps of relational interactions, firms work together on minor issues (Payan & Svensson, 2007; Gulati et al., 2005). In doing so, while deciding on the continuity of the partnership and future cooperation, firms in the supply chain have to evaluate the alliance, considering the probability of attaining the necessary benefits (Rodríguez del Bosque et al., 2006; Lambert, 2009).

Accordingly, if cooperation offers the firms greater gains than without an alliance, it is likely that firms will continue with the partnership and that there will be continuity in the inter-firm cooperation (Guan et al., 2022; Høgevold et al., 2019; Baker et al., 2002; Morgan, 2000; Das & Teng,1998). At the early stages of a partnership and while deciding on future cooperation in the supply chain, firms consider the rewards and economic benefit they are having. Consequently, we formulate the third assumption p in the research model as follows:

H₃:ES has a positive effect on cooperation in B2B sales partnerships.

2.3.4

Cooperation and NES

Finally, if the firm achieve cooperation, these increases the potential for mutual gains and satisfaction (Skinner et al., 1992; Geyskens et al., 1999). Indeed, firms’ cooperation relates to objectives, rules and attitudes associated with the partner's orientation to work together (Høgevold et al., 2019; Payan, 2007) implying relational experiences (Rodríguez del Bosque et al., 2006; Guan et al., 2022) which are considered social aspects of satisfaction (Ha et al., 2004; Høgevold et al., 2020a; Palmatier, 2008).

Clearly, cooperation implies that the parties to adopt a relational approach that offers them emotional rewards and psychosocial benefits (Guan et al., 2022; Høgevold et al., 2019; Payan et al., 2019). Accordingly, we formulate the fourth assumption in the research model as follows:

H₄:Cooperation has a positive effect on NES in B2B sales partnerships.

3

Methodology

3.1

Research and sample setting

The study sample was obtained from LinkedIn, and data collection was conducted through an online self-administered questionnaire distributed among sales or marketing managers/directors in small- and medium-sized firms across industries in Spain.

The questionnaire was distributed to 1240 managers/directors in small- and medium-sized firms across industries in Spain, providing a Qualtrics link for completing the survey online. 312 usable responses were obtained (response rate of 25.16 %), although 70 responses had to be excluded because of non-response bias. Therefore, this study was finally based on 242 usable responses.

The Qualtrix link included a letter requesting the collaboration of managers/directors in this study. The letter included the purpose and justification for the investigation, a commitment to confidentiality in data processing, instructions on completing the questionnaire, and the questionnaire to be completed online by the informants. According to the instructions, respondents were asked to consider each item in the survey, bearing in mind only one relevant B2B-customer during the last twelve months.

Respondents were assured that their responses would be treated anonymously, to encourage them to comply our request that they answer all survey items honestly. To reinforce this confidentiality, respondents were not asked to disclose any information about the customer firm based on which they were responding to the questionnaire. In this way, we tried to avoid potential common method bias in the data-collection process.

To further reinforce the absence of this bias, the survey included two questions to check the respondent's suitability for participation in the study. These questions were intended to inquire about, on the one hand, whether the respondent had sufficient knowledge about the client on which he/she was completing the survey, and, on the other hand, whether he/she had extensive experience with this client. The responses obtained to these two questions revealed that 97.1 % of the respondents had extensive knowledge of that customer and 96.2 % had a positive experience with that customer. These data showed that five respondents did not adequately meet these requirements to participate in the study, so it was decided to eliminate their questionnaires from the sample. Thus, the final study sample consisted of a total of 237 usable questionnaires.

Table 1 shows the distribution of the firms participating in the study by sector and firm size, the latter based on the number of full-time employees and annual revenue.

Table 1.

Sample characteristics.

Industry	Count	Full-Time Employee Equivalent	Count	Annual Turnover (Euro)	Count
Accomodation, Cafe or Restaurant	12	1–4	44	0 – 4.9 Millions	125
Agriculture, Forest or Fishing	9	5–9	23	5.0 – 9.9 Millions	31
Communication Services	20	10–19	38	10.0 – 24.9 Millions	25
Construction	21	20–49	39	25.0 – 99.9 Millions	32
Cultural or Recreational Services	3	50–99	34	100 + Millions	16
Education	7	100 - 249	28	Non-response	8
Electricity, Gas or Water	11	250 +	24	Total	237
Finance and/or Insurance	6	Non-response	7
Govt Admin or defence	2	Total	237
Health & Community Services	3
Mining	17
Manufacturing	7
Personal and Other Services	14
Property and Business Services	21
Retail Trade	13
Transport and Storage	43
Wholesale Trade	23
Non-response	5
Total	237

3.2

Concept items and measurement

The original sources of multi-item measures used in the questionnaire to test the assumptions in the research model are the following: ES was measured using the scale provided by Sanzo et al. (2003), while NES uses Geyskens et al.’s (1999) original scale. Also, the scales provided by Guiltinan et al. (1980) and Heide and John (1988) were considered in measuring coordination, and finally the cooperation measure is based on the scale from Skinner et al. (1992).

The multi-item measures from the above-mentioned sources were modified by Payan et al. (2019) who tested a similar model based on buyer partnerships in B2B settings. Høgevold et al. (2019) adapted the multi-item measures to seller partnerships in B2B settings. Recently, Guan et al. (2022) applied both buyer and seller multi-item measures in their dual study of purchase and sales partnerships in B2B settings. This study applied the multi-item measures by Høgevold et al. (2019).

The multi-item measures displayed in Table 2 were measured on Likert-scales with the anchor points of (5) strongly agree and (1) strongly disagree.

Table 2.

Multi-item measures used in B2B sales partnerships.

Economic Satisfaction (ES)

a) We benefit economically from the relationship with this customer.

b) This customer contributes to our financial performance.

c) This customer generates economic growth for us.

Non-Economic Satisfaction (NES)

a) The relationship between us and this customer is positive.

b) Our firm is content about its relationship with this customer.

c) The relationship between us and this customer is satisfying.

Cooperation

a) Our relationship with this customer is cooperative.

b) There is a cooperative attitude between us and this customer.

c) My firm prefers to cooperate with this customer.

Coordination

a) We work jointly with this customer on issues that affect both firms.

b) Our processes are coordinated with those of this customer.

c) Our activities are coordinated with the activities of this customer.

4

Empirical findings and analysis

The multivariate process analysis was divided into three phases: (i) a measurement model is tested based on confirmatory factor analysis (Jöreskog & Sörbom, 1976); (ii) a structural model was tested based on structural equation modeling (Hair et al., 2006); and (iii) ultimately, a rival model was tested.

Consequently, the confirmatory factor analysis verified the measurement properties of each multi-item measure in the research model. The structural equation modeling verified the assumptions in the research model displayed in Fig. 2 and verified the rival model. The first, second and third phases of the multivariate analyses were based on four multi-item measures consisting of three items each. The SPSS/AMOS 27.0 software was applied.

Fig. 2.

Hypothesized relationships in the research model.

The assumptions in the research model are displayed in Fig. 2, and as previously reported, were as follows:

• ✓

  H₁: Coordination has a positive effect on ES in B2B sales partnerships.

• ✓

  H₂: Coordination has a positive effect on cooperation in B2B sales partnerships.

• ✓

  H₃: ES has a positive effect on cooperation in B2B sales partnerships.

• ✓

  H₄: Cooperation has a positive effect on NES in B2B sales partnerships.

4.1

Univariate statistics of items and multi-item measures

The univariate statistics of each multi-item measure displayed in Table 3 are as follows: (i) number of respondents, (ii) mean value per item and average per multi-item measure, (iii) standard deviation per item and average per multi-item measure, (iv) variance explained per item and average per multi-item measure, and (v) factor loading per item and average per multi-item measure. Table 3 displays satisfactory univariate statistics across multi-item-measures, in line with recommended thresholds (Hair et al., 2006).

Table 3.

Univariate statistics of multi-item measures.

Multi-item measure	N	Mean		Std deviation		Variance explained		Factor loading
		Item	Average	Item	Average	Item	Average	Item	Average
Coordination
a)	237	3.78	3.72	1.06	0.99	0.43	0.65	0.65	0.80
b)	237	3.68		0.98		0.74		0.86
c)	236	3.71		0.94		0.78		0.88
Cooperation
a)	237	3.83	3.88	1.02	0.97	0.84	0.66	0.92	0.80
b)	236	3.90		0.98		0.81		0.90
c)	237	3.90		0.91		0.33		0.57
Economic Satisfaction (ES)
a)	236	4.12	4.08	0.75	0.72	0.57	0.54	0.75	0.73
b)	236	4.08		0.67		0.49		0.70
c)	237	4.05		0.74		0.55		0.74
Non-Economic Satisfaction (NES)
a)	236	4.26	4.22	0.77	0.77	0.71	0.77	0.84	0.88
b)	236	4.18		0.79		0.83		0.91
c)	237	4.23		0.75		0.78		0.88

Table 3 displays a very low non-response bias consisting of 236–237 valid responses out of 237 on each item, with mean values per multi-item measure ranging from 3.72 to 4.22, and standard deviation ranging from 0.72 to 0.99. Table 3 also shows that the variance explained across multi-item measures ranged from 0.54 to 0.77, and that the factor loadings per multi-item measure ranged from 0.73 to 0.88. Accordingly, the multi-item measures exceed the proposed thresholds (Hair et al., 2006) of 0.5 for average variance explained, and 0.7 for average factor loading, per multi-item measure. Consequently, the univariate statistics demonstrated satisfactory levels for findings.

4.2

Multivariate statistics of measurement and structural models

The goodness-of-fit measures and other statistics from the multivariate analyses in relation to the measurement and structural models are reported in this section.

The measurement model demonstrated satisfactory goodness-of-fit estimates (Hair et al., 2006), with a Chi-square of 113.80 and 48 degrees of freedom, being statistically significant at p = 0.000 based on a sample of 237. The fit estimates were also satisfactory with a normed Chi-square (X²/df) of 2.371, a NFI of 0.931, a CFI of 0.958 and a RMSEA of 0.076. Consequently, the measurement model based on the research model demonstrated satisfactory fit, and the structural model has therefore been tested as displayed in Fig. 2.

The structural model of the research model also demonstrated satisfactory goodness-of-fit estimates (Hair et al., 2006) with a Chi-square of 184.682 and 50 degrees of freedom, being statistically significant at p = 0.000, based on a sample of 237. In addition, the fit estimates were satisfactory, with a normed Chi-square (X²/df) of 3.694, a NFI of 0.888, a CFI of 0.915 and a RMSEA of 0.107.

4.3

Regression statistics of research model

The assumptions in the research model, as displayed in Fig. 2, were significant at p-values between 0.000 and 0.012, with regression coefficients between 0.190 and 0.497, as displayed in Table 4. The empirical findings confirmed the assumptions tested, based on B2B sales partnerships.

Table 4.

Regression statistics of research model.

Hypothesis	ExogenousConstruct	EndogenousConstruct	Regression Coefficients	Significance	Results
1	Coordination	Economic Satisfaction (ES)	0.312	0.000	Supported
2	Coordination	Cooperation	0.454	0.000	Supported
3	Economic Satisfaction	Cooperation	0.190	0.012	Supported
4	Cooperation	Non-Economic Satisfaction (NES)	0.497	0.000	Supported

4.4

Reliability and validity of multi-item measures

The discriminant validity of the multi-item measures of the research model is assessed by comparing the average variance extracted and the squared inter-concept correlations (Hair et al. 2006).

Table 5 shows that the average variance extracted for all multi-item measures were higher than the corresponding squared inter-concept correlations. This demonstrated that the research model met the criteria for satisfactory discriminant validity. The assumptions in the research model (H₁, H₂, H₃ and H₄₎ displayed in Fig. 2 were significant as displayed in Table 4, subsequently demonstrating nomological validity. The average variances extracted from each multi-item measure were all higher than 50 % (54.0–77.3 %) and demonstrated satisfactory convergent validity. Finally, the composite trait reliability of the multi-item measures displayed in Table 5 also demonstrated satisfactory reliability (0.835–0.918). In conclusion, the research model demonstrated validity and reliability in B2B sales partnerships.

Table 5.

Squared inter-concept correlations, variance extracted and composite trait reliability of multi-item measures.

Variable	(1)	(2)	(3)	(4)
(1) Economic Satisfaction (ES)	1000
(2) Non-Economic Satisfaction (NES)	0.432	1000
(3) Cooperation	0.093	0.226	1000
(4) Coordination	0.099	0.176	0.252	1000
Variance Extracted	54.0 %	77.3 %	65.7 %	64.7 %
Composite Trait Reliability	0.835	0.918	0.875	0.873

4.5

Rival model

A rival model was assessed in relation to the research model, as displayed in Fig. 2, to check the relevance of cooperation and coordination in relation to the other multi-item measures. The rival model assessed the untested direct partnerships between the multi-item measures of ES and NES, as well as coordination and NES in the research model. The rival model demonstrated that only the assumptions between ES and NES were significant at a p-value of 0.000 with a regression coefficient of 0.543, while the one between coordination and NES is non-significant at a p-value of 0.078 with a regression coefficient of 0.124.

Furthermore, the Parsimony-Adjusted Fit estimates demonstrated that the research model (with PRATIO: 0.641; PNFI: 0.569; PCFI: 0.586) displayed in Fig. 2 had a comparatively better fit than the rival model: (PRATIO: 0.615; PNFI: 0.563; PCFI: 0.580). However, the rival model demonstrated slightly improved goodness-of-fit estimates (NFI: 0.931; CFI: 0.958; RMSEA: 0.076) in relation to the research model (NFI: 0.888; CFI: 0.915; RMSEA: 0.107).

Nevertheless, the Parsimony-Adjusted Fit estimates were consistently higher, based on the research model in relation to the rival model. It can therefore be concluded that the measurement and structural properties of the research model displayed in Fig. 2 demonstrated satisfactory convergent, discriminant and nomological validity, as well as multi-item measure reliability.

5

Research implications

The empirical findings reported in this study on Spanish B2B sales partnerships in supply chains demonstrated consistency with the findings reported in the original study by Payan et al. (2019) on Spanish B2B purchase partnerships, and the original study by Høgevold et al. (2019) on Norwegian B2B sales partnerships, as well as the dual study by Guan et al. (2022) on Taiwanese purchase and sales partnerships in B2B settings. Consequently, this study demonstrated satisfactory validity and reliability of the research model in B2B sales partnerships.

In B2B sales contexts, the estimated theoretical model enabled us to confirm the relevance of considering both the objective and subjective aspects of satisfaction separately (Høgevold et al., 2019; Rodríguez del Bosque et al., 2006), instead of using a single concept of overall partnership satisfaction. The empirical findings demonstrated that multi-item measures within the same domain, coordination/ES or cooperation/NES (i.e., either action/outcome domain or social/process domain) have stronger partnerships than those between multi-item measures pertaining to different domains. The separate use of the dimensions related to satisfaction, referring to economic and non-economic satisfaction, implies an enrichment of the models on collaboration in the supply chain management literature.

It has been demonstrated that coordination relates positively to ES in B2B sales collaborations. This result is, according to previous studies by Sarmah et al. (2006), who state that coordination improves elements of ES such as a reduction of response and delivery times, cost reductions, and improvement of services provided to the customer. Therefore, the better the coordination of the specific actions that parties undertake together (Svensson & Mysen, 2011), the greater the sales, margins, or revenue and the lower the costs. Consequently, profitability is improved (Geyskens & Steenkamp, 2000; Walz, 2009) and, ultimately, ES within the B2B partnership is greater.

The empirical findings have also confirmed that coordination relates positively to cooperation in B2B sales partnerships. This finding had been previously supported by several previous studies, such as Guan et al. (2022) or Gulati et al. (2005), which claimed that willingness to cooperate is greater when partners were involved in jointly coordinating activities. This causal relationship between coordination and cooperation is explained by the logical sequence of collaboration (Knez & Camerer, 2000; Gulati et al., 2005; Payan & Svensson, 2007), i.e., first the firms coordinate the specific actions which will be performed together in the supply chain (Svensson & Mysen, 2011) and then the partners will be more prone to work together and cooperate (Payan & Svensson, 2007).

The present study's empirical results further validate the positive impact of ES on cooperation within B2B sales partnerships. This finding aligns with prior research conducted by Baker et al. (2002); Das & Teng (1998); Guan et al. (2022); Høgevold et al. (2019), and Morgan (2000), which demonstrated that when partners perceive tangible rewards and economic advantages from their involvement in the collaboration, their inclination to cooperate and maintain the B2B partnership is enhanced.

Finally, the empirical results revealed a positive association between cooperation and NES in B2B sales partnerships. Prior studies conducted by Guan et al. (2022), Høgevold et al. (2019), Payan et al. (2019), and Rodríguez del Bosque et al. (2006) have consistently demonstrated that cooperation entails the adoption of a relational approach that provides emotional rewards and psychosocial benefits to the parties involved. Accordingly, when partners are more prone to collaborate (Payan & Svensson, 2007), they experience an increase in emotional rewards from the collaborative efforts within the supply chain.

6

Managerial implications

Creating B2B collaborative agreements is necessary for developing stable partnerships between sellers and buyers involved in a sectorial supply channel (Fill & Fill, 2005; Guan et al., 2022). Satisfactory long-term partnerships in supply chains offer superior gains to partners in collaborative alliances.

Consequently, according to the tested theoretical model, the ultimate objective of the industrial sales partnership is ensuring the continuity and quality of the partnership by means of achieving satisfactory levels of NES, understood as an emotional outcome from the partnership (Ha et al., 2004; Palmatier, 2008). Along these lines, cooperation is an antecedent of the NES. In turn, the partners’ predisposition to work together (Payan & Svensson, 2007) is fostered by good coordination of the B2B sales partnership and that the partners achieving adequate levels of ES from their participation in the collaboration. At the same time, adequate coordination within the inter-organizational partnership reinforces the ES derived from the alliance.

Subsequently, managers of the firms involved in the partnership should pay special attention to the design of vertical and horizontal coordination mechanisms, both informal and formal. The horizontal nature of coordination mechanisms facilitates the flow of information, while vertical coordination mechanisms are based on authority and hierarchy. In this sense, managers should build interpersonal networks oriented towards the exchange of information (Grandori & Soda, 1995). On the other hand, the creation of committees or working groups, facilitates direct and equal contact between the partners (Alexander, 1995; Grandori, 1997; Grandori & Soda, 1995). Further, managers of the firms involved in the stable business partnership should assume hierarchical responsibility (Kumar & Seth, 1998), based on direct supervision, through the design of a suitable hierarchical structure.

Likewise, to effectively manage the degree of ES within a partnership, it is important for practitioners to reduce the disparity between expected and achieved profits. To achieve this objective, the parties must collaborate and strive to fulfill the profitability, growth, and sales-evolution expectations associated with the B2B collaboration (Ting, 2011). Thus, managers should favor the sharing of financial, human, or technological resources. Accordingly, sales managers should provide their partners with access to knowledge, experience, and skills, both of a technological and market nature. These efforts of the parties foster joint technological innovation, both in terms of product and process, to facilitate greater success in the market by introducing innovative products and improving process efficiency.

Finally, since cooperation involves the collaborative actions undertaken by all parties involved (Svensson & Mysen, 2011) and enhances the perceived NES for parties engaged in the partnership, sales managers facilitate the joint planning of activities. This planning process should be flexible enough to adapt to unexpected changes in the business environment. Further, once the activity plan is agreed upon, practitioners should devote efforts to efficient resource allocation, aligned with the partnership's objectives.

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Conclusions, limitations and proposals for further studies

The results reported in this manuscript are an attempt to investigate issues related to buyers’ NES in a B2B partnership and the different factors that might impact on this collaboration from a seller point of view. It has been observed that the subject of buyer-seller partnerships has received due investigator attention from an industrial customer perspective, whereas this issue has received only limited attention in the literature from the seller's perspective.

Accordingly, in a new context focused on the seller, the empirical findings reported in this study on Spanish B2B sales partnerships verifies the findings of previous studies in B2B settings, such as Payan et al. (2019) based on purchase partnerships, and Høgevold et al. (2019) on sales partnerships, as well as the dual study by Guan et al. (2022) on both purchase and sales partnerships. Consequently, this study verifies and fortifies the supply management literature.

The most important contribution is that the estimated model includes separate dimensions of overall satisfaction, distinguishing between ES (belonging to the outcome domain) and NES (belonging to the process domain). In fact, our research findings have demonstrated that collaboration in B2B sales partnerships implies parties cooperating and aligning their interests and goals (process domain), as well as coordinating their tasks and aligning their actions (outcome domain). This means that coordination and ES relate to each other, and that cooperation and NES relate to each other. This distinction is an enrichment of studies focusing on B2B partnerships between industrial buyers and sellers in the supply chain.

In line with the findings of the study, it was concluded that efforts devoted to improving the coordination of the specific actions that parties undertake together in supply chains yield rewards in terms of improvements in sales, margins, income, and costs, which enhances the parties' ES with the B2B partnership. At the same time, coordination also fosters the partner's positive predisposition to cooperate. This greater propensity to work together within the partnership generates both emotional and psychosocial rewards, enhancing their NES.

Furthermore, the findings enable several relevant suggestions for practitioners. Managers should focus their efforts on the design of both formal and informal coordination mechanisms, both vertical and horizontal. These coordination mechanisms should facilitate both informal communications to foster mutual adaptation and the flow of information by means of formal channels. Furthermore, the design of a hierarchical and authoritarian structure will favor efficiency in joint decision-making.

Although our findings complement the results of other researchers of Norwegian firms, both from a buyer and seller perspective, further investigations should expand the context to the study of aspects of partnership quality in B2B settings, considering corporations of other non-European countries. There are therefore multiple opportunities for further research to explore the broader applicability of the proposed model and the closer domain viewpoint. Furthermore, our investigation tests a nomological relation among concepts belonging to the domain of both outcome and process in a B2B seller partnership context. However, this research stream would be usefully enlarged if further investigations attempt to estimate alternative nomological relations including other concepts of partnership quality in B2B, such as conflict, opportunism, or collaboration continuity.

Funding sources

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.