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Article

Modeling Partners’ Behavior in Long-Lasting B2B Supply Chain Relationships

1
Faculty of Economics and Business, ECOBAS Research Center, Department of Business Organization and Marketing, Campus Vigo, University of Vigo, 36310 Vigo, Pontevedra, Spain
2
Faculty of Economics and Business, Department of Applied Economics, Campus Vigo, University of Vigo, 36310 Vigo, Pontevedra, Spain
3
School of Communication, Leadership and Marketing, Departement of Marketing, Kristiania University College, Postboks 1190 Sentrum, 0107 Oslo, Norway
*
Author to whom correspondence should be addressed.
Mathematics 2024, 12(3), 399; https://doi.org/10.3390/math12030399
Submission received: 19 December 2023 / Revised: 15 January 2024 / Accepted: 24 January 2024 / Published: 26 January 2024
(This article belongs to the Special Issue Mathematical and Statistical Modeling of Socio-Economic Behavior)

Abstract

:
Companies have strengthened their long-term inter-organizational partnerships throughout the supply chain to neutralize competitive pressures and risks in uncertain environments. On this basis, this research aims to propose and test a model of partners’ behavior aimed at the maintenance of long-term collaboration. By using confirmatory factor analysis, structural equation modeling, and rival model testing, the theoretical model proposed attempts to identify, from a seller’s perspective, the critical variables of partners’ behavior. It also seeks to understand the effect of satisfaction between trust and commitment (as antecedents associated with relationship quality) and sales formalization, sales opportunism, and sales-specific assets (as postcendents linked to relationship efficiency). Our findings verify the nomological framework and demonstrate that the partnership quality variables affect relationship efficiency, through sales satisfaction. However, the results of our research cannot confirm the relationship between satisfaction and specific assets. This research is relevant as it deals with inter-organizational partnerships from a seller-oriented approach, and it is based on a combination of Relationship Marketing Theory and Transaction Cost Theory to demonstrate that the inter-organizational partnership quality variables exert a direct effect on the partnership efficiency variables.

1. Introduction

Contemporary business in industrial markets implies the management of close collaborations and partnerships of complex networks of supply chain partners [1] functioning as single units and handling long-lasting business relationships with partners [2,3]. Accordingly, research in the supply chain management arena has increased consideration of business relationships as they are regarded as “one of the prominent research streams” [4] (p. 252) because, indeed, collaboration allows business partners to achieve competitive advantages and improve their performance [2,3]. Moreover, as [5] recently affirmed, the majority of the research relates to how to develop collaboration whereas the complexity and the management of such collaborations and partnerships seem not “to have been sufficiently revealed in the literature” [5] (p. 393).
Supply chain and B2B relationships can be considered the foundation of supply chain management in any organization [6], but long-term collaborations, based on trust and commitment among partners, need to be understood as they determine the efficiency of the inter-organizational partnership, which will eventually give partners competitive advantages. As a matter of fact, companies currently operating in supply chains strengthen their inter-organizational partnerships in the supply chain by maintaining them over the long term to neutralize the dynamic nature of the environment [2,3] and strengthen their competitive position and performance in the marketplace. Compared to commercially isolated inter-organizational relations, long-lasting inter-organizational partnerships significantly reduce transaction costs, substantially increase sales, and ensure long-term profits [7].
The quality of inter-organizational partnerships is conditioned by the ability of the parties to maintain a successful, stable collaboration over time [8,9]. The effective management of these inter-organizational collaborations will depend on the balance between the trust, commitment, and satisfaction of the partners [10,11,12]. In turn, the quality of an inter-organizational partnership has effects on variables related to the efficiency of any relational transaction [13,14]. According to Transaction Cost Theory (TCT) [15,16,17,18], the most critical determinants of efficiency in enduring inter-organizational collaborations may be opportunistic behaviors, the degree of formalization of partnerships, and investments in specific assets.
Given the above, two important questions arise: first, what reasons can lead partners involved in a B2B relationship along the supply chain to change their attitudes from collaboration to animadversion? Second, what reasons can justify these partners to eventually abandon (unilaterally or bilaterally) a long-lasting and mutually beneficial business relationship? Therefore, given the importance of these long-term alliances for preserving and improving the competitiveness of companies operating along the supply chain, it becomes mandatory to analyze in depth those variables representing the behavior of the partners in a B2B relationship that can curb these changes, strengthening the efficiency of these relationships.
Based on Relationship Marketing Theory (RMT) and Transaction Cost Theory (TCT), this research analyzes the effect of the critical variables of quality in inter-organizational partnerships on the determinants of their efficiency, following a seller-oriented approach. In an inter-organizational partnership context, the theoretical model proposes structural relations in which both sales trust and sales commitment affect sales satisfaction, and in turn, sales trust also directly affects sales commitment. The model also includes direct relations between sales satisfaction and the variables that determine the efficiency of the inter-organizational partnership, namely sales opportunism, sales formalization, and specific sales assets.
Although there is a broad consensus in the literature focusing on inter-organizational alliances that trust, commitment, and satisfaction are critical constructs that determine partnership quality [7,19,20], not all research has coincided with their nomological position [8]. However, the current dominant trend [2,3,13,14,21] finds that satisfaction is the variable explained by both commitment and trust. Some studies also find that sales trust exerts a positive, direct effect on commitment [21]. Likewise, these key variables—of the partners’ behavior involved in inter-organizational partnership related to relationship quality—affect the efficiency of inter-organizational partnerships, influencing the risk of opportunistic behavior, the level of formalization of the partnership, and the volume of investments made in specific assets through sales satisfaction [22,23,24].
The research results make several valuable contributions to the literature on the analysis of the behavior of partners involved in inter-organizational partnerships along the supply chain, following a seller’s perspective. The main contribution lies in the seller-oriented approach, which complements the theoretical stream that analyzes inter-organizational partnerships from the buyer’s perspective. Likewise, most of the research analyzing inter-organizational partnerships along the supply chain has been conducted from the buyer’s perspective [25], because these investigations were developed within a marketing approach, which is fundamentally a customer-oriented focus [9,26]. However, the success of any inter-organizational collaboration always depends on all parties involved in the partnership, and not just the buyers [27]. Only a small amount of recent research [2,28] has developed studies on inter-organizational partnerships based on the seller’s perspective.
Another second contribution is demonstrating that the variables that determine the quality of inter-organizational partnerships have a direct effect on the variables that measure the efficiency of the partnership. The theoretical model relates variables of different natures, whose combined inclusion in the same model has only been developed by [13] in Taiwan; [14] in Norway; [29] in Canadal and [26] based on a sample that encompasses Finnish, Norwegian, and Swedish companies. All of these studies share the fact of being developed from a buyer-oriented perspective, and the models differ from ours in that they do not include a direct causal relation between trust and commitment. Only a recent investigation conducted on a sample of Norwegian companies by [2] was developed under the seller’s perspective. In this context, our research contributes to the validity over time, place, and duality of perspectives (buyer- and seller-oriented) of the results of previous research.
A third contribution Is the combined theoretical framework for determining the structural relations included in the theoretical model. Indeed, there are few studies on inter-organizational partnerships that are based simultaneously on Relationship Marketing Theory and Transaction Cost Theory.
Finally, the research findings demonstrate that the variables that measure inter-organizational partnership quality affect the variables measuring the efficiency of the partnership through sales satisfaction.

2. Theoretical Framework

This research analyzes the causal relationship between partnership quality determinant constructs and variables that measure the efficiency of collaboration, for seller–buyer partnerships along the supply chain, from a seller-oriented perspective. The research hypotheses are underpinned by the foundations of Relationship Marketing Theory (RMT) and Transaction Cost Theory (TCT).
According to RMT [7], the quality of an inter-organizational partnership refers to the ability of the parties to make the relationship long-lasting and mutually beneficial [30,31,32]. The variables which contribute to the success of the partnership are trust, commitment, and satisfaction [11,12,33,34].
There is broad consensus in the literature framed within the RMT regarding trust, commitment, and satisfaction being the key dimensions of inter-organizational partnership quality [8,19,33]. Although there has been less consensus on the nomological position of these constructs, the most recent dominant tendency confirms that both trust and commitment are antecedent factors of satisfaction [2,3,13,14,21]. Furthermore, [2,10,21,25,33] found a positive causal relationship between trust and commitment.
From a psychological perspective [35,36], in an inter-organizational partnership, trust is understood as the belief that other parties involved in the partnership will behave with integrity [37], reliability [7,38,39], and a sense of honor. Trust is manifested through both a cognitive and an affective dimension. Cognitive trust arises from the experience of recurrent joint actions confirming that the other parties involved in the commercial exchange have kept their promises and acted in the partners’ best interests [40]. On the other hand, affective trust is a psychological state related to feelings of security and attachment, which build socio-emotional bonds [40,41,42,43]. Thus, in inter-organizational partnerships based on the seller’s perspective, trust refers to the expectation that exchange partners will keep their promises, meeting each other’s expectations [36]. Therefore, trust is related to the belief that parties will orient their actions towards the interests of the other parties and their actions will actively contribute to achieving the objectives of the collaboration [8,19,20,44] and, ultimately, the mutual benefits [7,36,45].
In the context of an inter-organizational seller partnership, commitment refers to the willingness of the parties to maintain the continuity of the long-term partnership [38,45,46], since they consider it important and valuable [38,47,48]. Such motivation encourages both buyers and sellers to dedicate resources and capabilities to the partnership. These short-term efforts will be continued over time if neither party perceives imbalances between the investments made by the other parties, and the expectations of long-term benefits remain [3,7,10,33].
Likewise, the parties’ satisfaction in an inter-organizational collaboration is an emotional state generated by the degree of compliance with expectations created about the partnership [49,50]. Satisfaction generally refers to a positive perception [47] resulting from a cognitive and emotional process. The cognitive process refers to the comparison of expectations and current tangible results, such as profits, growth, or sales. The emotional process is related to intangible issues, such as feelings of happiness, joy, or contentment arising from experiences within the inter-organizational partnership [43]. The sellers’ standards of comparison can be either the expectations that motivated them to engage in the inter-organizational partnership [39] or other previous experiences [44,51,52].
On the other hand, TCT [15,16,17,18,24] contributes to our understanding of the factors that determine the efficiency of inter-organizational partnerships. TCT focuses on the key factors for decisions on externalization (market), internalization (hierarchy), or joint inter-organizational action (hybrid) for the performance of a transaction, assuming that the decision-making agent is opportunist, rationally limited, and risk-neutral [52,53]. The variables that better explain this sort of decision are the degree of asset specificity, uncertainty, and frequency [53]. Therefore, a transaction will be conducted using a method of development (market, hybrid, or hierarchy) that minimizes production costs plus transaction costs [53].
Assets specific to an inter-organizational seller partnership are those created ad hoc for the performance of the collaborative activity, the value of which is significantly diminished if they are used for any other purpose [23,24]. Ref. [18] distinguishes between six specific types of assets: goodwill, client portfolios, physical assets, human resources, location, planning, and brand and other ad hoc assets. Investment in inter-organizational partnership-specific assets by the buyer and/or the seller generates risks for the party that makes a greater investment effort, who may lose bargaining power and may become hostage to the other party if the latter behaves opportunistically [24,54].
TCT assumes that parties in an inter-organizational partnership behave opportunistically when they seek with guile to satisfy their own self-interest [17,23]. Opportunistic individuals will go back on their word or mislead others if the circumstances are appropriate and will not disclose information they possess even if the party requests it. Thus, opportunism can show itself in the form of distortion, concealment of information, or lying [55].
Parties involved in an inter-organizational partnership mitigate the opportunism risks through contractual arrangements that contain all potential contingencies that may arise during the collaboration [22,54,56]. The degree of formalization of the inter-organizational seller partnership will depend on the level at which the rules established in the contracts determine behaviors and responsibilities within the partnership [57]. Thus, the higher the level of formalization of the partnership, the greater the legal implications in the event of non-compliance with the terms of the agreement. Moreover, these inter-organizational alliances generate interdependence and control between the seller and buyer. The extent of control is directly related to the level of structuring of the agreement.

3. Hypothetical Framework

3.1. Determinants of Partners’ Behavior Based on Inter-Organizational Relationship Quality

Ref. [58] pointed out that the parties’ commitment to an inter-organizational partnership would be impossible without generating a mutual emotion of psychological bonding. The affective dimension of trust generates socio-emotional feelings of security and attachment that strengthen the affective bond needed for fostering the partners’ commitment involved in the B2B relationship [33,40,41,42,43]. Likewise, the partners will perceive that the collaboration is taking place in an atmosphere of trust when the parties fulfill all of their promises, act in the best interest of all partners, and are not only guided by self-interest, strengthening the willingness to maintain the inter-organizational partnership in the long term and thus encouraging partners’ commitment [10,38,40,45,46]. Consequently, it is to be expected that the more confidence the buyer inspires in the seller, the more commitment the seller will demonstrate to the inter-organizational partnership. Thus, the following hypothesis can be formulated:
Hypothesis 1:
Sales trust affects sales commitment positively in inter-organizational partnerships.
In the literature on inter-organizational partnerships, there is broad consensus that trust between parties improves their experiences within the partnership, enhances performance, and improves satisfaction [59]. Trust is considered a fundamental factor in establishing successful and long-lasting partnerships. It allows parties to have confidence in each other’s intentions, reliability, and competence, fostering effective communication and collaboration. Additionally, trust mitigates uncertainties and risks associated with inter-organizational partnerships, creating a conducive environment for mutual growth and the achievement of shared goals [33]. If this occurs, the sellers’ satisfaction will be enhanced because they have behaved in a trustworthy manner, contributing to the accomplishment of commitments established in the collaboration [33]. Therefore, in an inter-organizational seller partnership, trust is considered as an antecedent to satisfaction [2,7,60]. Consequently, the following hypothesis can be formulated:
Hypothesis 2:
Sales trust affects sales satisfaction positively in inter-organizational partnerships.
Because seller satisfaction in an inter-organizational partnership is related to a positive emotional state generated from parties’ behavior oriented to achieving the objectives stipulated in the collaboration agreement [47,49] and because the parties’ commitment to maintaining an ongoing inter-organizational partnership is manifested in their willingness to invest resources and capabilities to maintain it in the long-term [38,45,46], then, consequently, the greater the willingness of the parties to maintain the partnership, investing in it to achieve the established objectives, the greater the satisfaction of the seller in this inter-organizational partnership [19]. In fact, when partners are committed to each other, they are more likely to invest time, resources, and effort in building and maintaining the relationship over an extended period. This long-term perspective contributes to overall satisfaction, as both parties can anticipate stable and reliable collaborations [7,33]. Likewise, committed partners in a B2B collaboration are aligned in terms of objectives and values, which creates a stronger sense of cohesion and unity and contributes to satisfaction, as parties feel that they are working towards common objectives that benefit each other. Thus, research focused on inter-organizational seller partnerships along the supply chain has demonstrated that commitment directly and positively affects satisfaction [2,21,25]. Consequently, the following hypothesis can be formulated:
Hypothesis 3:
Sales commitment affects sales satisfaction positively in inter-organizational partnerships.

3.2. Determinants of Partners’ Behavior Based on the Efficiency of the Seller–Buyer Relationships

Most results of research [2,13,14,26,29] have shown that there is a direct and positive effect of satisfaction on the assets specific to the inter-organizational partnership. These assets include knowledge sharing, resource pooling, and collaborative decision-making. If the partners are satisfied with their B2B relationship, they are more likely to engage in these cooperative behaviors and invest in and allocate resources toward the success of the partnership [24]. We postulate that if a seller is satisfied with the buyer in the inter-organizational partnership, the seller will be more prone to invest in specific assets for the collaboration. Consequently, we propose the following hypothesis:
Hypothesis 4:
Sales satisfaction affects partnership-specific sales assets positively in inter-organizational partnerships.
In an opportunistic inter-organizational partnership context, parties behave in an insincere or dishonest way in transactions, so it can be expected that promises are not always kept and contracts are not always honored [61]. Previous research has found that parties satisfied with an inter-organizational partnership are less inclined to manifest opportunistic behaviors since such behaviors can lead to defection from the partnership [26,29]. Parties in a successful inter-organizational partnership are more likely to prioritize the mutual long-term benefits that come from cooperation and collaboration. This creates a sense of mutual understanding, reducing the desire to engage in opportunistic actions that could harm the partnership and also reducing the propensity of the parties to withhold information or resources, seek alternative partnerships, or even sabotage the partnership altogether. In contrast, satisfied parties in a B2B partnership are more likely to engage in reciprocal behaviors or adhere to norms of fairness and tend to engage in open communication and transparency which reduces information asymmetry. Therefore, the higher the level of satisfaction perceived by the parties, the lower the probability of opportunistic behavior between the seller and buyer within the inter-organizational partnership [23]. Consequently, we propose the following hypothesis:
Hypothesis 5:
Sales satisfaction affects sales opportunistic behavior negatively in inter-organizational partnerships.
A satisfied party will be less reluctant to take on more formalized contractual structures to regulate their behavior and responsibilities in the collaboration. This is because the seller’s feeling of satisfaction is induced by the high levels of trust and commitment of the parties involved in the inter-organizational partnership, which reduce the potential risks that may be generated by opportunistic behaviors or the existence of specific assets [24,56]. In fact, when parties involved in a B2B relationship have experienced favorable outcomes from the collaboration, these satisfied partners will feel more confident in committing to formal agreements that clearly outline expectations and obligations [22]. This increased belief in the relationship encourages the party to accept more structured contractual frameworks, ensuring smooth coordination and minimizing potential conflicts. In this sense, [13,14] demonstrated the existence of a direct and positive relation between satisfaction levels and the level of transaction formalization. Consequently, we propose the following hypothesis:
Hypothesis 6:
Sales satisfaction affects sales formalization positively in inter-organizational partnerships.

4. Methodology

4.1. Study Design

Our partners’ behavior model in inter-organizational seller–buyer partnerships (Figure 1) consists of six hypothesized relations in seller settings and posits that sales satisfaction is positioned between trust and commitment as antecedents and formalization, opportunism, and specific assets as postcedents. It also postulates that trust affects commitment.
Therefore, our aim is to verify the nomological framework and demonstrate that the partnership quality variables affect relationship efficiency though sales satisfaction. This nomological framework provides a theoretical structure that describes the network of cause–effect connections among variables, contributing to a more comprehensive understanding of the particular phenomenon related to the long-lasting B2B relationships established throughout the supply chain.

4.2. Participants

The corporate sample consists of a broad spectrum of Spanish businesses across different industries and of different sizes in terms of full-time staff and annual sales (Table 1). The sample was gathered from LinkedIn with specified search criteria, which state that the respondents should be sales or marketing managers/directors at a Spanish small- or medium-sized company, whose products and/or services should be sold exclusively to other business customers, as our study focuses on inter-organizational relations under a seller’s perspective. Therefore, a random sample encompassing 1240 possible participating businesses was generated from a total study population of 2576 Spanish small- and medium-sized enterprises (SMEs) (48.1% of the total).

4.3. Data Collection

Potential respondents were contacted using LinkedIn to request their consent to participate in the study prior to sending them the link to the survey. Only those who indicated their willingness to participate in the study were included in the study. A letter of introduction was emailed to each sales or marketing executive, asking them to complete the questionnaire online truthfully using a Qualtrics link. The respondents were requested to think of one current B2B customer with whom the company had interacted over the last twelve months when answering each item in the questionnaire.

4.4. Data Quality Check Procedure

To ensure data quality, the letter sent to potential respondents also contained a statement of strict confidentiality with respect to data treatment. Furthermore, to enhance the data quality, the respondents were asked to respond from their own perspectives, and two control questions on the sales executives’ competence permitted verification of their knowledge and experience as sellers [62], asking them to “Please consider how knowledgeable and experienced you are concerning your business and your business dealings with this customer.” Two items were provided as follows: (a) “I have a lot of knowledge about this customer” and (b) “I have a lot of experience with this customer”. Finally, 312 completed questionnaires were returned (25.16%), of which 75 were found to be unusable due to non-response bias. The number of usable responses from the respondents was 237, on the basis of which the model was estimated.

4.5. Study Measures

The partners’ behavior research model in inter-organizational seller–buyer partnerships displayed in Figure 1 is based on several constructs, all of which are defined in Table 2.
Table 3 shows the multi-item measures of each construct used in the questionnaire, applying a five-point Likert scale, where (5) is strongly agree and (1) strongly disagree.

5. Results

5.1. Univariate Statistics

The estimations of each construct item resulting from the univariate statistics are displayed in Table 4. The average variance explained per construct exceeds the recommended threshold of 0.5, and the average factor loading per construct exceeds the recommended threshold of 0.7 [68].

5.2. Measurement Model

5.2.1. Confirmatory Factor Analysis

The confirmatory factor analysis [69], including six constructs and eighteen reflective items and using SPSS/AMOS 27.0 software, shows that the goodness-of-fit measures of the measurement model meet the established thresholds [68] (pp. 745–749). The chi-square is 180,307 with 120 degrees of freedom. This chi-square is statistically significant at p = 0.000, based on a sample size of N = 237. The normed chi-square (X2/df) is 1.503, with an NFI of 0.931, an RFI of 0.901, an IFI of 0.976, a TLI of 0.965, and a CFI of 0.975. The RMSEA is 0.046 with a confidence interval of 90%: 0.031–0.059. Figure 2 shows the confirmatory factor analysis.

5.2.2. Construct Reliability and Validity

We followed [70] instructions for social sciences to minimize common method bias and to avoid obstructing the validity of the empirical findings in relation to the measurement properties of constructs. Procedural statistical remedies were applied in this study, such as knowledgeable sales executives who are professionally interested in the subject area of this study. Furthermore, the questionnaire design strove to reduce the time and effort in filling out the questionnaire. Moreover, the Harman single-factor test shows that if the number of factors is set to one and the explained variance is 36.15%, then common method bias is not a concern in this study.
Convergent validity was estimated based on the variance extracted from each construct [68] (Table 5), which exceeds the established threshold of 50%, ranging from 65% to 77%, except for sales formalization which explained 47% of the variance because item ‘a’ has low explained variance as well as low factor loading (Table 4). Moreover, the variance extracted is larger than the corresponding squared inter-construct correlations for each construct (Table 5), indicating that the inter-organizational seller partnership model displays discriminant validity [68]. Furthermore, the composite trait reliability levels of constructs in the research model exceed 0.7 [68], ranging from 0.81–0.91.

5.3. Structural Model

The structural model demonstrates that the goodness-of-fit measures meet the established thresholds. The chi-square is 212.908 with 129 degrees of freedom. It is statistically significant at p = 0.000. The normed chi-square (X2/df) is 1.650 with an NFI of 0.918, an RFI of 0.892, an IFI of 0.966, a TLI of 0.954, and a CFI of 0.966. The RMSEA is 0.052 with a confidence interval of 90%: 0.040–0.065.
The hypothesized relations between the constructs in the research model are all significant at p = 0.000, except that sales satisfaction does not relate to sales-specific assets (p = 0.751). The regression coefficients range from 0.342–0.599. Consequently, the empirical findings (Table 6) support five of the six hypotheses between the constructs of the antecedents and postcedents in the sales satisfaction research model.
The hypothesized relations in the model (Figure 3) are all significant and consistent with previous studies on satisfaction with antecedents of trust and commitment on the one hand and the postcedents of formalization and opportunism on the other, across contexts and through time, based on purchase business partnerships [25] and the same research model. However, the hypothesized relationship between sales satisfaction and sales-specific assets is not supported. Thus, the empirical findings confirm the nomological validity based on a sales perspective instead of a purchase one.
The guidelines of convergent, discriminant, and nomological validity, as well as construct reliability, are satisfactorily accomplished in this study. We therefore conclude that the measurement and structural properties of the inter-organizational seller partnership model in Spanish businesses indicate validity and reliability.

5.4. Refined Model

The goodness-of-fit measures of the structural model previously verified are all satisfactory, but the factor loading of one item (i.e., sales formalization ‘a’) is much lower than all of the others included in the research model. A refined model is therefore verified, excluding this item from the structural model.
The goodness-of-fit measures of the refined model are enhanced in line with the established thresholds. The chi-square is 177.401 with 113 degrees of freedom, all of which are statistically significant at p = 0.000. The normed chi-square (X2/df) is 1.570 with an NFI of 0.930, an RFI of 0.906, an IFI of 0.974, a TLI of 0.964, and a CFI of 0.973. The RMSEA is 0.049 with a confidence interval of 90%: 0.035–0.062. Accordingly, the outcome of the refined research model is satisfactory, with it being valid and reliable based on a sample of sales executives in Spanish inter-organizational partnerships.

6. Discussion

6.1. Research Implications

The findings reported provide relevant and valuable support for a generalizable nomological framework across contexts and through time, in relation to antecedents and postcedents of satisfaction in inter-organizational partnership settings, in accordance with models tested in previous studies based on inter-organizational purchase and sales partnerships. Consequently, this investigation expands the findings reported in previous studies based on a purchase perspective in inter-organizational partnerships [13,14,26,29].
In particular, the findings of this study suggest that the conceptual model linking trust, commitment, and satisfaction is valid considering the point of view of sellers in B2B relationships. Indeed, the model verifies the role of sales trust relating positively to sales commitment in inter-organizational seller partnerships. The model also verifies the role of sales trust and sales commitment as dual precursors to sales satisfaction, as reported in previous studies based on a purchase perspective [3,13,14]. Moreover, the model verifies the role of sales trust relating positively to sales commitment in inter-organizational seller partnerships. Specifically, our results show that both trust and commitment directly and positively influence satisfaction. Also, trust affects commitment in congruence with the key variable model of Morgan and Hunt [7] but, in our case, considering and changing the perspective to the seller´s view instead of the buyer´s one. To be precise, as Relationship Marketing Theory and research affirms, trust and commitment are relevant variables for achieving B2B collaborative relationships [8,19,20]. In addition, as trust or confidence in the partner emerges, the perception that partners will rely on each other will also increase their motivation to commit to each other [7,10,33], in line with [34] (p. 1177) who posit that commitment appears to be “a necessary complement of trust”.
Moreover, satisfaction is considered a driver of business based on a relationship perspective [50]. Thus, and in line with [14,29], the model confirms that sales satisfaction bridges between sales trust and sales commitment on the one hand, and sales formalization and sales opportunism on the other, but not on specific sales assets. These results are in concordance with TCT, when partners are satisfied, they will be more prompt to formalize their collaboration and develop contractual rules and norms for the relationship [22,24] as a way to reduce the risk of partners’ opportunism [23]. Specific sales assets are most likely dependent on the extent of sales formalization in an inter-organizational seller partnership, as reported recently by [28,54].
As a whole, the results provided in the proposed model provide insights into both Transaction Cost Theory (TCT) and Relationship Marketing Theory (RMT) for research in business collaboration and supply chain management. We offer relevance on the particular role of satisfaction in B2B relationships as, initially, it forces and manages partners’ collaboration and then supports expansion, formalizes partnerships, and reduces opportunism.

6.2. Managerial Implications

The empirical findings yield several managerial implications regarding the role that sales satisfaction plays in inter-organizational seller partnerships.
A lesson for business practice is that sales trust and sales commitment play a role in the seller’s contentment and positive perception of the customer. Sales trust rests on fair negotiations, reliance, and a trustworthy partnership with the customer, while sales commitment rests on the willingness and dedication to continue the partnership with the customer. Sales trust is also an antecedent to sales commitment. Consequently, managing inter-organizational seller partnerships in business practices requires the development and maintenance of the triangular interrelation between trust, commitment, and satisfaction.
Since both satisfaction and commitment depend on levels of trust, managers should convey signals that they will behave in a confidence-generating manner. To this end, it is necessary that the parties dedicate their efforts to meeting the obligations acquired in order to remain credible for the other parties. This credibility will be reinforced by building socio-emotional bonds and strengthening mutual knowledge. In short, it is a matter of strengthening the feeling of security [43] and attachment that facilitates the exchange of confidential information and the implementation of investments in the partnership without risk of imbalances between the parties [41]. Managers should strive to maintain a principle of reciprocity in all of their actions [40,42]. Furthermore, to enhance commitment, and in turn, satisfaction, practitioners should encourage transparent and open management, generate feelings of happiness, and strive to achieve mutual understanding [7,39].
Another lesson for business practice is that the formalization of inter-organizational seller partnerships with the customer requires that the seller be satisfied with it. Sales satisfaction is not accomplished if opportunistic actions are undertaken by the customer, such as not keeping promises, altering facts, and being dishonest. Nevertheless, sales-specific assets do not rely on sales satisfaction but appear to be dependent on the extent to which the formalization of the partnership has progressed. Subsequently, the seller is reluctant to make specific investments in the inter-organizational seller partnership with the customer, although the seller is satisfied with it. The seller requires the inter-organizational partnership to be formalized with a clear distribution of tasks and well-established information routines with the customer.

7. Conclusions

The research findings derived from the hypothesis testing confirm that sales trust relates positively to sales commitment in inter-organizational seller partnerships. The results also confirm that sales trust and sales commitment are dual precursors to sales satisfaction. Likewise, the findings also confirm that sales satisfaction bridges the relationship between sales trust and sales commitment on the one hand, and sales formalization and sales opportunism on the other, but not specific sales assets.
Therefore, these research results generalize the nomological framework and establish the structural properties between sales antecedents, sales satisfaction, and sales postcedents. From a seller’s perspective, the research results show that sales satisfaction bridges the relationship between variables measuring quality (sales confidence and sales commitment) and variables measuring collaboration efficiency (sales opportunism and formalization) in an inter-organizational partnership. However, it was found that there is no direct influence between sales satisfaction and investment in partnership-specific assets.
Concerning previous research, the research results of the hypothetical testing in this study verify the validity and reliability of an inter-organizational seller partnership purchase framework in sales settings, broadening the applicability to both perspectives in inter-organizational partnerships. Indeed, in accordance with models tested in earlier studies based on inter-organizational purchase and sales partnerships, the reported findings offer pertinent and valuable support for a generalizable nomological framework across contexts and over time, regarding antecedents and postcedents of satisfaction in inter-organizational partnership settings. As a result, this study broadens the conclusions of prior research that were focused on a buyer viewpoint in inter-organizational partnerships.
The managerial implications of the findings suggest that practitioners should devote efforts to maintaining parties’ trust, commitment, and satisfaction through transparent and open management. They should also generate feelings of happiness and strive to achieve mutual understanding in order to meet the obligations acquired. These managerial behaviors reinforce the socio-emotional bonds, strengthening the feeling of security, which fosters the partners to invest in specific assets and inclines them to avoid opportunistic behaviors.
Regarding the future scope of this study, although the generalizable characteristics of a nomological framework have been fortified in this study, further research is needed beyond Western business settings, such as Eastern ones in Asia (e.g., China, South Korea, China, and India), to determine the extent to which these characteristics hold in different cultural contexts. This is important because cultural differences can significantly influence the applicability of a nomological framework. For example, collectivist cultures in Asia may prioritize group harmony and conformity, which could impact the relationships between the variables included in the theoretical model. Additionally, the values and norms of these oriental business settings may influence the way individuals perceive and respond to the same circumstances. Therefore, investigating the generalizability of a nomological framework in different cultural contexts is crucial for its practical application and theoretical development.

Author Contributions

Conceptualization, G.S. and C.F.-S.; methodology, G.S. and C.F.-S.; validation, G.S. and C.F.-S.; formal analysis, G.S.; investigation, G.S. and C.F.-S.; resources, C.F.-S., C.P. and C.O.-N.; data curation, C.F.-S., C.P. and C.O.-N.; writing—original draft preparation, G.S., C.F.-S., C.P. and C.O.-N.; writing—review and editing, G.S., C.F.-S., C.P. and C.O.-N.; visualization, G.S., C.F.-S., C.P. and C.O.-N.; supervision, G.S. and C.F.-S.; project administration, G.S. and C.F.-S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Sutton-Brady, C. As time goes by: Examining the paradox of stability and change in business networks. J. Bus. Res. 2008, 61, 968–973. [Google Scholar] [CrossRef]
  2. Høgevold, N.; Svensson, G.; Mpinganjira, M. Precursors and outcomes of satisfaction in seller-customer business relationships: A sales perspective. Int. J. Procure. Manag. 2020, 13, 531–552. [Google Scholar] [CrossRef]
  3. Payan, J.M.; Hair, J.; Svensson, G.; Andersson, S.; Awuah, G. The precursor role of cooperation, coordination, and relationship assets in a relationship model. J. Bus. Bus. Mark. 2016, 23, 63–79. [Google Scholar] [CrossRef]
  4. Ataseven, C.; Nair, A. Assessment of supply chain integration and performance relationships: A meta-analytic investigation of the literature. Int. J. Prod. Econ. 2017, 185, 252–265. [Google Scholar] [CrossRef]
  5. Huang, Y.; Han, W.; Macbeth, D.K. The complexity of collaboration in supply chain networks. Supply Chain. Manag. Int. J. 2020, 25, 393–410. [Google Scholar] [CrossRef]
  6. Jamaluddin, F.; Saibani, N. Systematic literature review of supply chain relationship approaches amongst business-to-business partners. Sustainability 2021, 13, 11935. [Google Scholar] [CrossRef]
  7. Morgan, R.M.; Hunt, S.D. The commitment-trust theory of relationship marketing. J. Mark. 1994, 58, 20–38. [Google Scholar] [CrossRef]
  8. Gil-Saura, I.; Frasquet-Deltoro, M.; Cervera-Taulet, A. The value of B2B relationships. Ind. Manag. Data Syst. 2009, 109, 593–609. [Google Scholar] [CrossRef]
  9. Hütten, A.S.; Salge, T.O.; Niemand, T.; Siems, F.U. Advancing relationship marketing theory: Exploring customer relationships through a process-centric framework. AMS Rev. 2018, 8, 39–57. [Google Scholar] [CrossRef]
  10. Čater, T.; Čater, B. Product and relationship quality influence on customer commitment and loyalty in B2B manufacturing relationships. Ind. Mark. Manag. 2010, 39, 1321–1333. [Google Scholar] [CrossRef]
  11. Roberts-Lombard, M.; Reynolds-de Bruin, L. Strengthening graduate employee commitment through internal marketing in the South African retail banking industry. S. Afr. J. Bus. Manag. 2017, 48, 91–105. [Google Scholar] [CrossRef]
  12. Sales-Vivó, V.; Gil-Saura, I.; Gallarza, M.G. Comparing relationship of quality satisfaction models: Effects of B2B value co-creation. Int. J. Retail. Distrib. Manag. 2021, 49, 941–957. [Google Scholar] [CrossRef]
  13. Mysen, T.; Svensson, G.; Lee, T.R. Trust and commitment-based satisfaction and the impact on specific investments, formalisation and opportunism. Int. J. Bus. Excell. 2011, 4, 696–714. [Google Scholar] [CrossRef]
  14. Mysen, T.; Svensson, G.; Payan, J.M. Causes and outcomes of satisfaction in business relationships. Mark. Intell. Plan. 2011, 29, 123–140. [Google Scholar] [CrossRef]
  15. Coase, R.H. The nature of the firm. Economica 1937, 4, 386–405. [Google Scholar] [CrossRef]
  16. Coase, R. The problem of social cost. J. Law Econ. 1960, 3, 1–44. [Google Scholar] [CrossRef]
  17. Williamson, O.E. Markets and Hierarchies: Analysis and Antitrust Implications; The Free Press: New York, NY, USA, 1975. [Google Scholar]
  18. Williamson, O.E. Comparative economic organization: The analysis of discrete structural alternatives. Adm. Sci. Q. 1991, 36, 269–296. [Google Scholar] [CrossRef]
  19. Viio, P.; Grönroos, C. Value-based sales process adaptation in business relationships. Ind. Mark. Manag. 2014, 43, 1085–1095. [Google Scholar] [CrossRef]
  20. Walz, A.M. The Definition, Creation, and Evolution of Buyer-Seller Relationships. Ph.D. Thesis, Louisiana State University, Baton Rouge, LO, USA, 2009. No. 3751. Available online: https://digitalcommons.lsu.edu/gradschool_dissertations/3751 (accessed on 4 July 2022).
  21. Høgevold, N.; Rodriguez, R.; Svensson, G.; Roberts-Lombard, M. Validating the sequential logic of quality constructs in seller-customer business relationships—Antecedents, mediator and outcomes. J. Bus. Bus. Mark. 2022, 29, 43–67. [Google Scholar] [CrossRef]
  22. Cisi, M.; Sansalvadore, F. Formalized business networks in SMEs and structural relations for their governance. J. Small Bus. Entrep. 2022, 34, 295–312. [Google Scholar] [CrossRef]
  23. Lai, F.; Tian, Y.; Huo, B. Relational governance and opportunism in logistics outsourcing relationships: Empirical evidence from China. Int. J. Prod. Res. 2012, 50, 2501–2514. [Google Scholar] [CrossRef]
  24. Rindfleisch, A. Transaction cost theory: Past, present, and future. AMS Rev. 2020, 10, 85–97. [Google Scholar] [CrossRef]
  25. Roberts-Lombard, M.; Mpinganjira, M.; Svensson, G. Antecedents and outcomes of satisfaction in buyer–supplier relationships in South Africa: A replication study. S. Afr. J. Econ. Manag. Sci. 2017, 20, a1497. [Google Scholar] [CrossRef]
  26. Rindell, A.; Mysen, T.; Svensson, G.; Billström, A. A validation of inputs and outputs of satisfaction in business-to-business relationships through a Nordic comparison. Int. J. Procure. Manag. 2013, 6, 424–443. [Google Scholar] [CrossRef]
  27. Campbell, A. Buyer-supplier partnerships: Flip sides of the same coin? J. Bus. Ind. Mark. 1997, 12, 417–434. [Google Scholar] [CrossRef]
  28. Høgevold, N.; Svensson, G.; Mpinganjira, M. A seller perspective on economic and non-economic satisfaction as precursors to formalisation, specific investments, and dependence in business relationships. Int. J. Phys. Distrib. Logist. Manag. 2021, 51, 281–304. [Google Scholar] [CrossRef]
  29. Hutchinson, D.; Singh, J.; Svensson, G.; Mysen, T. Antecedents and postcedents of satisfaction in business relationships in Canada. Int. J. Logist. Econ. Glob. 2011, 3, 189–206. [Google Scholar] [CrossRef]
  30. Ahearne, M.; Atefi, Y.; Lam, S.K.; Pourmasoudi, M. The future of buyer–seller interactions: A conceptual framework and research agenda. J. Acad. Mark. Sci. 2022, 50, 22–45. [Google Scholar] [CrossRef]
  31. Barari, M.; Ross, M.; Thaichon, S.; Surachartkumtonkun, J. A meta-analysis of customer engagement behaviour. Int. J. Consum. Stud. 2021, 45, 457–477. [Google Scholar] [CrossRef]
  32. Wei, C.-L. How relationship quality, service quality, and value affect the intention to purchase IT/IS outsourcing services. Inf. Syst. Manag. 2021, 39, 202–219. [Google Scholar] [CrossRef]
  33. Gounaris, S.P. Trust and commitment influences on customer retention: Insights from business-to-business services. J. Bus. Res. 2005, 58, 126–140. [Google Scholar] [CrossRef]
  34. Mukherjee, A.; Nath, P. Role of electronic trust in online retailing: A re-examination of the commitment-trust theory. Eur. J. Mark. 2007, 41, 1173–1202. [Google Scholar] [CrossRef]
  35. Schoorman, F.D.; Mayer, R.C.; Davis, J.H. An integrative model of organizational thrust: Past, present, and future. Acad. Manag. Rev. 2007, 32, 344–354. [Google Scholar] [CrossRef]
  36. Zaheer, A.; McEvily, B.; Perrone, V. Does trust matter? Exploring the effects of inter-organisational and interpersonal trust on performance. Organ. Sci. 1998, 9, 141–159. [Google Scholar] [CrossRef]
  37. Kumar, N.; Scheer, L.K.; Steenkamp, J.B.E. The effects of perceived interdependence on dealer attitudes. J. Mark. Res. 1995, 32, 348–356. [Google Scholar] [CrossRef]
  38. Moorman, C.; Zaltman, G.; Deshpande, R. Relationships between providers and users of market research: The dynamics of trust within and between organizations. J. Mark. Res. 1992, 29, 314–329. [Google Scholar] [CrossRef]
  39. Sarmento, M.; Simões, C.; Farhangmehr, M. Applying a relationship marketing perspective to B2B trade fairs: The role of socialization episodes. Ind. Mark. Manag. 2015, 44, 131–141. [Google Scholar] [CrossRef]
  40. Nyamrunda, F.C.; Freeman, S. Strategic agility, dynamic relational capability, and trust among SMEs in transitional economies. J. World Bus. 2021, 56, 101–175. [Google Scholar] [CrossRef]
  41. Akrout, H.; Diallo, M.F. Fundamental transformations of trust and its drivers: A multi-stage approach of business-to-business relationships. Ind. Mark. Manag. 2017, 66, 159–171. [Google Scholar] [CrossRef]
  42. Allen, M.; George, B.; Davis, J. A model for the role of trust in firm level performance: The case of family businesses. J. Bus. Res. 2018, 84, 34–45. [Google Scholar] [CrossRef]
  43. Johnson, D.; Greyson, K. Cognitive and affective trust in service relationships. J. Bus. Res. 2005, 58, 500–507. [Google Scholar] [CrossRef]
  44. Anderson, J.C.; Narus, J.A. A model of distributor firm and manufacturer firm working relationships. J. Mark. 1990, 54, 42–58. [Google Scholar] [CrossRef]
  45. Ghanadiof, O.; Sanayei, A.; Emami, M. Effect of customer perception on salesperson owned commitment in customer-salesperson relationship. Eur. J. Bus. Manag. Res. 2021, 6, 137–142. [Google Scholar] [CrossRef]
  46. Yoon, Y.L.; Yoon, Y.; Nam, H.; Choi, J. Buyer-supplier matching in online B2B marketplace: An empirical study of small- and medium-sized enterprises (SMEs). Ind. Mark. Manag. 2021, 93, 90–100. [Google Scholar] [CrossRef]
  47. Dwyer, F.R.; Schurr, P.H.; Oh, S. Developing buyer-seller relationships. J. Mark. 1987, 51, 11–27. [Google Scholar] [CrossRef]
  48. Pansari, A.; Kumar, V. Customer engagement: The construct, antecedents, and consequences. J. Acad. Mark. Sci. 2017, 45, 294–311. [Google Scholar] [CrossRef]
  49. Anderson, J.C.; Narus, J.A. A model of the distributor’s perspective of distributor-manufacturer working relationships. J. Mark. 1984, 48, 62–74. [Google Scholar] [CrossRef]
  50. Yeung, M.C.; Ramasamy, B.; Chen, J.; Paliwoda, S. Customer satisfaction and consumer expenditure in selected European countries. Int. J. Res. Mark. 2013, 30, 406–416. [Google Scholar] [CrossRef]
  51. Andaleeb, S. An experimental investigation of satisfaction and commitment in marketing channels: The role of trust and dependence. J. Retail. 1996, 72, 77–93. [Google Scholar] [CrossRef]
  52. Pathak, B.; Ashok, M.; Tan, Y.L. Value co-destruction: Exploring the role of actors’ opportunism in the B2B context. Int. J. Inf. Manag. 2020, 52, 102093. [Google Scholar] [CrossRef]
  53. Williamson, O.E. Transaction-cost economics: The governance of contractual relations. J. Law Econ. 1979, 22, 233–261. [Google Scholar] [CrossRef]
  54. Zhang, Q.; Wang, M.; Zhao, Z. Does asset specificity lead to value expropriation or value creation? An Institutional View. Int. J. Phys. Distrib. Logist. Manag. 2022, 52, 813–833. [Google Scholar] [CrossRef]
  55. Kang, B.; Jindal, R.P. Opportunism in buyer–seller relationships: Some unexplored antecedents. J. Bus. Res. 2015, 68, 735–742. [Google Scholar] [CrossRef]
  56. Guercini, S.; Tunisini, A. Formalizing in business networks as a tool for industrial policy. IMP J. 2017, 11, 91–108. [Google Scholar] [CrossRef]
  57. Gimeno-Arias, F.; Santos-Jaén, J.M. Using PLS-SEM for assessing negative impact and cooperation as antecedents of gray market in FMCG supply chains: An analysis on Spanish wholesale distributors. Int. J. Phys. Distrib. Logist. Manag. 2023, 53, 718–742. [Google Scholar] [CrossRef]
  58. Sung, Y.; Choi, S.M. I won’t leave you although you disappoint me: The interplay between satisfaction, investment, and alternatives in determining consumer–brand relationship commitment. Psychol. Mark. 2010, 27, 1050–1074. [Google Scholar] [CrossRef]
  59. Geyskens, I.; Steenkamp, J.B.E.; Kumar, N. A meta-analysis of satisfaction in marketing channel relationships. J. Mark. Res. 1999, 36, 223–238. [Google Scholar] [CrossRef]
  60. Yang, S. Understanding B2B customer loyalty in the mobile telecommunication industry: A look at dedication and constraint. J. Bus. Ind. Mark. 2015, 30, 117–128. [Google Scholar] [CrossRef]
  61. Reich, R.B.; Mankin, E.D. Joint ventures with Japan give away our future. Harv. Bus. Rev. 1986, 64, 78–86. [Google Scholar]
  62. Campbell, D.T. The informant in quantitative research. Am. J. Sociol. 1955, 60, 339–342. [Google Scholar] [CrossRef]
  63. Anderson, E.; Weitz, B. The use of pledges to build and sustain commitment in distribution channels. J. Mark. Res. 1992, 29, 18–34. [Google Scholar] [CrossRef]
  64. Heide, J.B.; John, G. The role of dependence balancing in safeguarding transaction-specific assets in conventional channels. J. Mark. 1988, 52, 20–35. [Google Scholar] [CrossRef]
  65. Dahlstrom, R.; Nygaard, A. An empirical investigation of ex post transaction costs in franchised distribution channels. J. Mark. Res. 1999, 36, 160–170. [Google Scholar] [CrossRef]
  66. John, G. An empirical investigation of some antecedents of opportunism in a marketing channel. J. Mark. Res. 1984, 21, 278–289. [Google Scholar] [CrossRef]
  67. Provan, K.G.; Skinner, S.J. Interorganizational dependence and control as predictors of opportunism in dealer-supplier relations. Acad. Manag. J. 1989, 32, 202–212. [Google Scholar] [CrossRef]
  68. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tatham, R.L. Multivariate Data Analysis, 6th ed.; Prentice Hall: New Jersey, NJ, USA, 2006. [Google Scholar]
  69. Jöreskog, K.G.; Sörbom, D. LISREL III: Estimation of Linear Structural Equations Systems by Maximum Likelihood Methods; National Educational Resources, Inc.: Chicago, IL, USA, 1976. [Google Scholar]
  70. Podsakoff, P.; MacKenzie, S.; Podsakoff, N. Sources of method bias in social science research and recommendations on how to control it. Annu. Rev. Psychol. 2012, 63, 539–569. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Inter-organizational seller partnership model.
Figure 1. Inter-organizational seller partnership model.
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Figure 2. Confirmatory factor analysis.
Figure 2. Confirmatory factor analysis.
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Figure 3. Estimated structural model.
Figure 3. Estimated structural model.
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Table 1. Industry, full-time staff equivalent, and annual sales.
Table 1. Industry, full-time staff equivalent, and annual sales.
IndustryCountFull-Time Staff EquivalentCountAnnual Sales (Million Euro)Count
Accommodation, Cafe, or Restaurant121–4440–4.9125
Agriculture, Forestry, or Fishing95–9235.0–9.931
Communication Services2010–193810.0–24.925
Construction2120–493925.0–99.932
Cultural or Recreational Services450–9934100+16
Education7100–24928n.a.8
Electricity, Gas, or Water12250+24Total237
Finance and/or Insurance6n.a.7
Govt. Admin or Defense2Total237
Health and Community Services3
Mining3
Manufacturing17
Personal and Other Services7
Property and Business Services29
Retail Trade23
Transport and Storage15
Wholesale Trade43
No response provided4
Total 237
Table 2. Constructs of partners’ behavior model in inter-organizational seller–buyer partnerships.
Table 2. Constructs of partners’ behavior model in inter-organizational seller–buyer partnerships.
SourceDefinition
[51,59]Satisfaction refers to the positive affective state resulting from the appraisal of all aspects of an organization’s working together with another organization.
[36]Trust refers to the expectation that another business can be relied upon to fulfill its obligations and that it will act and negotiate fairly, even where the possibility of opportunism is present.
[7,63]Commitment refers to an enduring desire to maintain a partnership.
[64]Specific assets refers to those human and physical assets (tangible and intangible) required to support exchange, and which are specialized to the specific exchange partnership. If the partnership were to be terminated, the value of these assets would be largely lost, because their salvage value outside the partnership is very low
[65]Formalization refers to the extent to which rules and procedures govern the partnership between inter-organizational parties.
[65,66,67]Opportunism refers to self-interest-seeking behavior embodied in calculated efforts to mislead and confuse trading parties.
Table 3. Questionnaire items.
Table 3. Questionnaire items.
VariableItemsSource
Sales Satisfaction(a) The partnership between us and this customer is positive.
(b) Our firm is content about its partnership with this customer.
(c) The partnership between us and this customer is satisfying.
[51,59]
Sales Trust(a) This customer is fair in its negotiations with us.
(b) We can rely on this customer.[36]
(c) This customer is trustworthy.
Sales Commitment(a) We would like to continue our partnership with this customer.
(b) We intend to do business with this customer well into the future.
(c) We are dedicated to continuing doing business with this customer.
[7,63]
Sales Specific Assets(a) We have made investments in resources that are of most use only to this customer.
(b) We have customized an essential share of our business in dealing with this customer.
(c) We have tailored our business to accommodate the needs of this customer.
[64]
Sales Formalization(a) Our partnership with this customer is regulated by written contracts.
(b) There is a clear distribution of tasks with this customer.
(c) There are well-established information routines with this customer.
[65]
Sales Opportunism(a) This customer does not always do what they promise.
(b) This customer alters the facts slightly in order to get what they need.
(c) This customer is not always honest with us.
[65,66,67]
Table 4. Univariate statistics of items.
Table 4. Univariate statistics of items.
ItemNMeanStd. DevVariance ExplainedFactor
Loading
Sales Satisfaction
(a)2364.260.770.710.84
(b)2364.180.770.840.91
(c)2374.230.750.770.89
Sales Trust
(a)2333.541.000.640.80
(b)2343.930.800.640.80
(c)2343.960.920.720.85
Sales Commitment
(a)2374.610.590.850.92
(b)2374.590.590.870.93
(c)2374.430.680.450.67
Sales Specific Assets
(a)2362.921.170.530.73
(b)2362.901.140.880.94
(c)2362.941.120.530.73
Sales Formalization
(a)2333.601.250.140.37
(b)2343.790.910.490.70
(c)2343.910.940.780.88
Sales Opportunism
(a)2332.481.160.470.69
(b)2332.501.160.690.83
(c)2332.341.170.910.95
Table 5. Squared inter-construct correlations and summary statistics.
Table 5. Squared inter-construct correlations and summary statistics.
Variable(1)(2)(3)(4)(5)(6)
(1) Sales Satisfaction1000
(2) Sales Trust0.501000
(3) Sales Commitment0.370.271000
(4) Sales Specific Assets0.000.000.021000
(5) Sales Formalization0.200.130.160.031000
(6) Sales Opportunism0.330.340.190.010.091000
Variance Extracted77.3%66.7%72.3%64.7%47.0%69.0%
Composite Trait Reliability0.910.880.900.880.810.89
Table 6. Verification of hypothesized relationships.
Table 6. Verification of hypothesized relationships.
HypothesisExogenous
Construct
Endogenous
Construct
Regression WeightSignificanceFinding
1Sales TrustSales Commitment0.5190.000Supported
2Sales TrustSales Satisfaction0.5420.000Supported
3Sales Commitment Sales Satisfaction0.3420.000Supported
4Sales Satisfaction Sales Specific Assets0.0220.571Not Supported
5Sales SatisfactionSales Opportunism−0.5990.000Supported
6Sales SatisfactionSales Formalization0.4390.000Supported
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Ferro-Soto, C.; Padín, C.; Otero-Neira, C.; Svensson, G. Modeling Partners’ Behavior in Long-Lasting B2B Supply Chain Relationships. Mathematics 2024, 12, 399. https://doi.org/10.3390/math12030399

AMA Style

Ferro-Soto C, Padín C, Otero-Neira C, Svensson G. Modeling Partners’ Behavior in Long-Lasting B2B Supply Chain Relationships. Mathematics. 2024; 12(3):399. https://doi.org/10.3390/math12030399

Chicago/Turabian Style

Ferro-Soto, Carlos, Carmen Padín, Carmen Otero-Neira, and Göran Svensson. 2024. "Modeling Partners’ Behavior in Long-Lasting B2B Supply Chain Relationships" Mathematics 12, no. 3: 399. https://doi.org/10.3390/math12030399

APA Style

Ferro-Soto, C., Padín, C., Otero-Neira, C., & Svensson, G. (2024). Modeling Partners’ Behavior in Long-Lasting B2B Supply Chain Relationships. Mathematics, 12(3), 399. https://doi.org/10.3390/math12030399

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