The configuration of inter-organizational relationship features in the life cycle perspective

Abstract

Purpose

This study examines what is the significance of the features of inter-organizational relationships in consecutive phases of the relationship life cycle.

Design/methodology/approach

Qu antitative, large-scale surveying was run on 786 software developers operating in Poland. The research hypothesis regarding the systematic increase of relational features (i.e. commitment, communication, (lack of) conflict, cooperation, intensity, investments, longevity, multidimensionality of bonds, trust, and velocity) across the particular relationship life cycle phase le (i.e. initial, development, maintenance, dormant/end, and reactivation) was verified using ANOVA and post-hoc tests.

Findings

The results show that the majority of considered features of inter-organizational relationships non-significantly but progressively strengthen from the initial phase, through the development phase, to the maintenance phase, then significantly weaken in the dormant/end phase and strengthen again in the reactivation phase. Interestingly, velocity–as the only examined feature–significantly increases in dormant/end and then decreases if the relationship is reactivated.

Originality/value

Prior studies were focusing on single feature, this one offers a holistic view considering ten relational facets. Moreover, this is one of the few research studies exploring the changes of relational features adopting the life cycle perspective.

Citation

Klimas, P., Sachpazidu, K., Stańczyk, S., Nadolny, M., Grześkowiak, A. and Stanimir, A. (2022), "The configuration of inter-organizational relationship features in the life cycle perspective", Journal of Organizational Change Management, Vol. 35 No. 6, pp. 846-867. https://doi.org/10.1108/JOCM-04-2022-0118

Introduction

Modern organizations are more prone to gain from a relational advantage (Dyer and Singh, 1998) based on cooperation (Baraldi and Ratajczak-Mrozek, 2019) and/or coopetition (Jakobsen, 2020; Ricciardi et al., 2022) being recently seen as essential, “to thrive and generate desired outcomes” in relationships (Czakon et al., 2020, p. 6). Indeed, the turn into intensive exploitation of inter-organizational relationships (IOR) - through which cooperation/coopetition is utilized - “can be one of the fundamental changes in the modern business management” (Ardakani et al., 2018, p. 852).

Inter-organizational relationships are dynamic (Ford, 1980; Hansen et al., 2013) and their dynamics still is one of the most important areas in management studies (Yaqub, 2017; Ardakani et al., 2018). The dynamic view on IOR can be thought of in two ways.

First, the changes of IOR life cycle phases through which IOR develop over time (Kusari et al., 2013; Hastings et al., 2016). Second, the changes in IOR features over time (Lee and Johnsen, 2012; Ryan et al., 2012; Lunardo et al., 2018).

The recognition of changes in both IOR development path and IOR features seems to be important as those evolutions influence relational outcomes (Palmatier et al., 2013).

IOR are characterized by specific features (Jap and Anderson, 2007; Ming-Huei and Wen-Chiung, 2011; Gelei and Dobos, 2014). The consideration of relational attributes is claimed as relevant due to their role for cooperating partners. Some of the relationship attributes (e.g. commitment, cooperation, trust) are seen as contributing to effective relational exchange (Kusari et al., 2013). In the same vein, some of IOR features (i.e. trust, commitment, and proximity) underlaying inter-organizational networks leverage organizational learning and thus, firm performance as well (Klein et al., 2020). Moreover, as suggested by Holm et al. (1999) those changes in the features of IOR impact the relationship performance - “the empirical and valid findings show that through development of relationship (through increasing connectiveness, commitment, dependence) the new value, namely the value of relationships is created” (Holm et al., 1999, p. 479). Indeed, it has been shown that different features of IOR in different phases of relation life-cycle can impact firm performance (Fynes et al., 2005; Esposito and Passaro, 2009).

In this regard, further exploration of IOR features is needed (Jap and Anderson, 2007; Lussier and Hall, 2018; Fayezi and Ghaderi, 2022; Sachpazidu et al., 2022). In particular, it is important to identify how IOR features' significance changes as little research so far have examined their dynamics by linking them to the phases of relationship development (Lee and Johnsen, 2012). Next to the changes in IOR features, the literature points at the need for a better understanding of the specificity of phases of IOR development (Holmlund, 2004; Jap and Ganesan, 2000). Pragmatically, exploration of IOR features seems to be relevant as besides their positive effects on firm performance (Fynes et al., 2005), some of them can be seen as essential for cooperation establishment and its long-term maintenance (Zineldin, 2002).

So far only few features have been investigated in the context of the changes across the phases of the IOR life cycle. For instance, Gelei and Dobos (2014) explored investments, Kursari et al. (2013) investigated trust, whereas Lee and Johnsen (2012) recognized eight attributes of relationships asymmetry. Interestingly not only the phases of IOR life cycle may differentiate the levels of IOR features. For instance, the differences in relationship attributes (e.g. trust, investments, relational norms, interdependence) may result from the type of relationship as claimed by Lambe et al. (2000).

Although IOR features are suggested to be changeable along the IOR development path (Palmatier et al., 2013) a lot of features have not been empirically investigated from this specific perspective. Thereby, in this paper, we explored the significance of changes of IOR features in the subsequent phases of IOR life cycle. In our quantitative, large-sample study (n = 786) we investigate ten IOR features (i.e. commitment, communication, (lack of) conflict, cooperation, intensity, investments, longevity, multidimensionality of bonds, trust, and velocity), their levels in five typical phases of IOR life cycle (i.e. initial, development, maintenance, dormant/end, and reactivation), as well as the significance of changes in features' levels between the successive phases.

As a research context, we have chosen Polish software developers as operating in an environment enabling the exploitation of dynamic relationships. The research focuses on software developers as firms operating inside are characterized as highly technological knowledge-based, and service-intensive (Coviello and Munro, 1997). The firms with such technological souls face many transactional choices along various value chain stages (Jacobides and Billinger, 2006) and have to immediately adjust to the hyper-competitive challenges (Le Roy et al., 2022). All of the above makes software developers willing (or even pushed) to exploit external relationships intensively (Coviello and Munro, 1997; Le Roy et al., 2022). Indeed, a highly competitive industry (Pellegrin-Boucher et al., 2013; Klimas and Czakon, 2022; Le Roy et al., 2022) with a high-efficiency level (Guzmán et al., 2010), software represents a fertile ground for the research focused on dynamics of relationship development.

Supportively to prior conceptual assumptions (Fynes et al., 2005; Ferreira et al., 2017) as the main contribution our study provides evidence for changeable (e.g. fluctuating velocity; parabolic investments; temporary linear longevity) and non-linear (e.g. shape of the inverted “U” identified for investments or continuously fluctuations of velocity) configuration of IOR features across the phases of the relationship life cycle. Our study shows that there is a quite typical path for developing IOR in terms of the configuration of their features (8 out of 10 features gains in significance from initial, through development and maintenance phases, then decrease in dormancy/end and increase again if IOR is reactivated – not applicable for investments and velocity). In this view, we fit into the stream of configurational approaches in the study of inter-organizational relationships (e.g. Ricciardi et al., 2022).

Theoretical background

Phases of IOR development

The foundation of our considerations is the life-cycle theory, one of the strong theories explaining the process of organizational change and development from its initiation to its termination (Van de Ven and Poole, 1995). By pointing to the sequences of events that unfold in these changes, the life cycle becomes helpful in mapping the changes appearing on the organization's development path. In a broader context, it refers to the changes faced by organizations, products, ventures, and also relationships (Ring and Van de Ven, 1994).

The relationship life-cycle (RLC) examines relationships changes over time (Jap and Anderson, 2007; Palmatier et al., 2013; Yaqub, 2017). The phases of RLC are used to describe a relationship's evolution through differences in behaviors, orientations, and inter-organizational processes (Dwyer et al., 1987).

RLC is acknowledged as a process (Ring and Van de Ven, 1994) but in the literature this process of IOR development is explained using “states”, “stages” or “mixed” approaches (Batonda and Perry, 2003). In general, while some authors suggest a sequential process of IOR development (Dwyer et al., 1987; Holm et al., 1999; Fynes et al., 2005; Goldring, 2010; Mangus and Ruvio, 2019), others claim their nonlinear and situational development (e.g. Palmatier et al., 2013; Yaqub, 2017; Ferreira et al., 2017; Kam and Lai, 2018) suggesting even a cyclical trajectory of relationship development (Ring and Van de Ven, 1994). Regardless of the approach, the development path is considered as differentiated in terms of the intensity of IOR features (Jap and Ganesan, 2000; Jap and Anderson, 2007; Kusari et al., 2013; Palmatier et al., 2013; Plewa et al., 2013; Gelei and Dobos, 2014; Kam and Lai, 2018).

In the literature, there is no commonly adopted model of the IOR life cycle. Nonetheless, as shown in Table 1, most of the applied models are built on seminal studies (e.g. Ford, 1980; Dwyer et al., 1987; Ring and Van de Ven, 1994) and can be summed up in a five-phase approach covering the following phases (Klimas et al., in press): initial, development, maintenance, dormant/end, and reactivation.

First, there is an initial phase. At this phase, mutual goals and objectives are determined (Hastings et al., 2016). However, as Meng (2010) highlights, in the initial phase partners are focused only on pursuing their objectives, thus trust and commitment are very low (Lau and Goh, 2005). In the literature initial phase is also labelled as initiating (Duanmu and Fai, 2007), matching (Ferreira et al., 2017), assessment (Davis and Love, 2011), exploratory (Lee and Johnsen, 2012), or early development (Lau and Goh, 2005).

The next phase is relationship development (Batonda and Perry, 2003; Lee and Johnsen, 2012) or growth (Abosag and Lee, 2013). This phase refers to intensive cooperation, communication, information sharing, mutual commitment and investments (Ferreira et al., 2017). During this phase, the partners still focus on their objectives, but they understand that a partial win is vital for all sides of cooperation (Meng, 2010).

After the development, there is the maintenance phase (Batonda and Perry, 2003). The maintenance phase reflects a strong relationship (Abosag and Lee, 2013) with ongoing adjustments and integrations resulting in increasing mutual commitment (Batonda and Perry, 2003). For some scholars, this is the last phase of RLC (e.g. Plewa et al., 2013) reflecting stable cooperation (Lau and Goh, 2005) and providing partners with the highest co-created value (Meng, 2010; Lee and Johnsen, 2012). Given the specificity of actors' behaviours this phase is labelled also as enduring (Davis and Love, 2011), stable (Lee and Johnsen, 2012), maturity (Meng, 2010; Restuccia and Legoux, 2019), or long-term phase (Lau and Goh, 2005; Abosag and Lee, 2013).

The next phase is a decline (Meng, 2010; Restuccia and Legoux, 2019), dissolution (Abosag and Lee, 2013; Ring and Van de Ven, 1994) or in other words termination phase (Batonda and Perry, 2003). In this phase the exchange between partners may be minimized or even ended due to, e.g. contract termination (Batonda and Perry, 2003), change of key people who care about the relationship (insufficient level of trust) (Polonsky et al., 2010), or appearance of dissatisfaction with the relationship (Duanmu and Fai, 2007). Following Ford (1980), IOR can be broken or regressed at any point of the development path, however, usually it happens after the maturity phase (Dwyer et al., 1987) or as claimed by Plewa et al. (2013) it never happens as the relationship goes into the dormancy phase. Therefore, depending on the situation the fourth phase can take the form of dormancy or ending. Interestingly, the newer models (e.g. Duanmu and Fai, 2007; Meng, 2010; Davis and Love, 2011; De Almeida Moraes et al., 2017) do not assume the total ending of the relationships.

Before the final termination when cooperation truly breaks down, the relationship may enter the reactivation phase (Batonda and Perry, 2003). The relationship re-born refers to the renewal of its exploitation under the same or new contract, agreement, or project. It depends on the relationship's experience and history (Sivadas et al., 2012; Akrout, 2014; Mandják et al., 2015; Gaczek et al., 2018). Nonetheless, even though reactivation is typical for IOR which are already in a dormancy phase, there is evidence that the relationship cycle may be renewed at any stage of the RLC (Yaqub, 2017).

Features of IOR

Existing literature provides varied frameworks of IOR features (e.g. Dwyer et al., 1987; Young and Wilkinson, 1998; Jap and Anderson, 2007; Johnsen and Ford, 2008; Polonsky et al., 2010; Lee and Johnsen, 2012; Palmatier et al., 2013; Johnsen and Lacoste, 2016; Hastings et al., 2016; Zaefarian et al., 2017). Nonetheless, so far most of the authors have focused only on two attributes, trust and commitment (Dwyer et al., 1987; Palmatier et al., 2006; Standifer et al., 2010; Wang, 2012; Zaefarian et al., 2017) while leaving other features behind even though the holistic approach is needed (Johnsen and Ford, 2008).

In the literature, IOR features can be divided into two types - first- and second-order features (Holm et al., 1999; Jap and Ganesan, 2000; Palmatier et al., 2013). The first-order ones are understood as a higher-order constructs (e.g. Kumar et al., 1995; Henning-Thurau, 2000; Lang and Colgate, 2003) reflecting a combination of multiple lower-order (i.e. second-order) features (Dwyer et al., 1987; Crosby et al., 1990; Dorsch et al., 1998; Hennig-Thurau, 2001; Kumar et al., 1995; Palmatier, 2008). At the same time, the second-order ones are acknowledged as directly depending on the partner's behaviours and actions undertaken under the relationship. This paper focuses on the following second-order features: commitment, communication, (lack of) conflict, cooperation, intensity, investments, longevity, multidimensionality of bonds, trust, and velocity. The reasoning behind such focus is twofold.

First, so far the first-order features have attracted greater attention in empirical investigations (e.g. quality–Athanasopoulou, 2009 Akrout, 2014; Varotto and Parente, 2016; dynamics – Alajoutsijärvi et al., 1999; Palmatier et al., 2013; Mathur and Kumar, 2013; Johnsen and Ford, 2008; Lee and Johnsen, 2012; strength – Hausman, 2001; Åkerlund, 2005; Drogendijk and Andersson, 2013) thus we the focus on the second-order ones as much more needed.

Second, in contrast to the first-order features, although the second-order ones are frequently mentioned in the literature, they have not been analyzed in detail in terms of their changes across IOR life cycle (Holmlund, 2004; Johnsen and Ford, 2008; Gelei and Dobos, 2014; besides trust and investments–Jap and Anderson, 2007; Kusari et al., 2013).

The first feature – commitment–manifests in the active participation of IOR partners in sustaining the relationship, who are willing to make short-term sacrifices to achieve shared goals and long-term outcomes, with a commitment to maintain a valuable relationship (Wilson, 1995; Jap and Ganesan, 2000; Wang, 2012; Zaefarian et al., 2017; Klein et al., 2020). There are claims that commitment appears in the later phases of the IOR life cycle (Fynes et al., 2005) but others assume it is necessary across the entire IOR development (Wang, 2012; Palmatier et al., 2013). Commitment can change during the relationship (Baraldi and Ratajczak-Mrozek, 2019), that is, it can increase or decrease (Havila and Wilkinson, 2002) and is usually growing over the evolution of the relationship (Hastings et al., 2016).

The next feature is communication, which in the context of IOR is the formal or informal information exchange between partners (Harwood, 2006). It is shown as relevant for the establishment and has high credibility in building and maintaining the relationship (Fynes et al., 2005; Standifer et al., 2010). Communication within a relationship is determined by the quality of communication, the form in which information is shared, the extent to which partners are committed to the goals of the relationship, the existence of many different forms of communication, both direct and indirect and involvement of relationship partners in communication processes (Palmatier et al., 2006; Kam and Lai, 2018). Communication is shown as critical for relationship formation (Harwood, 2006) and crucial in the search and trial phase of IOR (Fynes et al., 2005).

Next, there is the lack of conflict, which in the case of coopetitive relationships (i.e. linking cooperating competitors) takes rather the form of conflict (Jakobsen, 2020). The inter-organizational relationships are established to reach shared goals, but it does not mean that not shared goals are abandoned. In practice, the extent of overlaps of the actors' – sometimes competing – interests results in tensions between the partners (Fernandez et al., 2014). Those tensions lead to conflicts (Rajala and Tidström, 2021), considered as the differences between partners' perceptions of the relationship, targeted and shared goals, but also real or perceived engagement in achieving them (Ratajczak-Mrozek et al., 2019). The conflict may arise over minor as well as major issues (Johnsen and Ford, 2008; Lee and Johnsen, 2012) and can be mitigated through partners' engagement in planning the relationship goals (Fynes et al., 2005). Interestingly, conflict increases together with the commitment to the relationship (Meng, 2010). Usually, conflict(s) occurs as the collaboration partners come closer and the relationship stabilizes in the development process (Johnsen and Lacoste, 2016). Especially, the conflict may grow in long-lasting relationships, where disagreements and expectations of relationship partners change over time. The emergence of conflict at this stage of the relationship most often results in the postponement of rethinking the terms of the relationship, renegotiating agreements, or signing new documents that resolve contentious issues (Ring and Van de Ven, 1994).

IOR are characterized also by cooperation, which consists of the joint partners' efforts aimed to achieve the common goals and obtain the expected results (Johnsen and Ford, 2008, p. 473; Palmatier et al., 2006). Indeed, cooperation as a facet of IOR means real implementations, actions, or behaviours of actors engaged in the relationship and focused on the transposition of the shared goals into business reality. Operationally, cooperation is understood as a level of those joint activities undertaken for achieving shared goals in terms of their intensity, value, and extent of working together. It is indicated that cooperation under a given IOR is changeable over time - “cooperation may evolve within a relationship over time” (Johnsen and Ford, 2008, p. 473; Lee and Johnsen, 2012, p. 694). Interestingly, the cooperation between partners may even occur in the dormancy phase, when the formal relationship is latent but the cooperation between partners, especially personal engagement in it exists as partners are willing to keep the relationship for future engagement (Plewa et al., 2013).

Then, relationship intensity refers to the level, density, and frequency of contact of the engaged individuals in the relationship but also the value of the resource flows between the organizational actors (Rosson and Ford, 1982; Johnsen and Ford, 2008; Lee and Johnsen, 2012). Intensity seems to be linked with other IOR features as it manifests itself in the commitment of the relationship partners' employees, extensive communication, and maintenance of collaborative efforts to develop the relationship (Denize and Young, 2007; Abosag and Lee, 2013). Intensity evolves over time in the relationship (Holm et al., 1999).

The next considered feature there is investments, which refers to the partners' (usually idiosyncratic, relation-specific) investments of physical, financial, and time resources directed at developing strong relations (Morgan and Hunt, 1994; Mathur and Kumar, 2013) considered as successful in reaching the goals of the relationship (Holm et al., 1999; Jap and Anderson, 2007; Kusari et al., 2013; Kam and Lai, 2018). Relationship investments are particularly important in the process of strengthening (Mathur and Kumar, 2013) and consolidating relationships and affect the coordination of relationships (Jap and Ganesan, 2000). Interestingly, under investments there are also covered the past flows, thus they are seen not only as a present but rather as all of the investments accumulated under the IOR from its early beginning (Gelei and Dobos, 2014).

Longevity, also labelled as temporality (Ming-Huei and Wen-Chiung, 2011) or duration (Lussier and Hall, 2018), is understood as the preservation, persistence of relationships, which to some extent reflects relationship stability (Wang, 2012). According to the relationship life cycle, the longer relationship is, the more profit to the relationship it gives (Woo and Leelapanyalert, 2014). Nonetheless, although time dependent length of the relationship positively influences relationship effectiveness (Mathur and Kumar, 2013) if the relationship is maintained too long it may result in the “locking in” effect (Yaqub, 2017).

Next, there is multidimensionality of bonds reflecting the very complex (Holmlund, 2004) and multidimensional (Mangus and Ruvio, 2019) nature of IOR determined by the number of different types of ties (bonds, interactions, exchanges) between partners. Those varied ties that can occur between relationship partners are usually economic, technical, legal, administrative, social, emotional, organizational, psychological, temporal, informational and others (Arantola, 2002; Wang et al., 2016; Kam and Lai, 2018). The multidimensionality of bonds can be seen as a manifestation of inter-organizational proximity (Klein et al., 2020). The multidimensionality of bonds evolves between relationship partners as they become more involved and committed to the relationship over time (Havila and Wilkinson, 2002).

Trust in a relationship refers to the partners' sense of belief and confidence in the honesty and intentions of the other partners in the relationship characterized by the relationship partners' perception of the partners' intentions and willingness to accept the partners' weaknesses and sincere belief in the success of the joint action (Jap and Anderson, 2007; Lee and Johnsen, 2012; Abosag and Lee, 2013; Kam and Lai, 2018; Klein et al., 2020; Lewicka and Zakrzewska-Bielawska, 2020). Trust changes over time (Baraldi and Ratajczak-Mrozek, 2019; Kostis and Näsholm, 2020), hence it is especially important in the establishing phase, when the relationship is starts but is not indispensable to develop a relationship (Gaczek et al., 2018).

Last but not least, velocity refers to the rate and directions of (planned and unplanned) changes of the relationships in time (Fynes et al., 2005; Denize and Young, 2007; Palmatier et al., 2013). Velocity allows to capture changes in the trajectory of the relationship, importantly it refers not only to the changes per se (as it is in the case of relationship stability – Palmatier et al., 2013; Forkmann et al., 2016) but also to their level and direction – the magnitude of changes is important – Harmeling et al. (2015). A high velocity may result in a transition from one relationship phase to another and also in a change of phase over time (Palmer, 2007; Harmeling et al., 2015) as relationships trust sometimes fails and sometimes is regained (Zerbini and Castaldo, 2007).

Summing up, IOR exhibit a wide range of features. Those features change over time (Palmatier et al., 2013; Gelei and Dobos, 2014; Hastings et al., 2016; Lunardo et al., 2018) and thus reach different levels in particular phases of IOR development (Lee and Johnsen, 2012; Kusari et al., 2013; Plewa et al., 2013; Kam and Lai, 2018). Nonetheless, the existing literature is not consistent regarding the trajectory of the changes of particular relational attributes – Table 2.

Methodological design

This study aims to examine what is the significance of the features of inter-organizational relationships in consecutive phases of the relationship life cycle.

It should be added that the changes are considered in terms of the levels of significance of particular features for IOR exploitation (e.g. Jap and Anderson, 2007; Johnsen and Ford, 2008). Given that the hypothesis is: IOR features increase in the subsequent phases of IOR life cycle.

Given IOR are acknowledged as context-dependent (Kursari et al., 2013) our large-scale surveying was run in one specific national and industry context, namely software developers in Poland. The study was carried out in February 2020 and was based on mixed data collection techniques (i.e. CATI, CAWI, and CATI). As the study focused on IOR, managers responsible for establishment, development, maintenance, and termination of IOR were targeted as key informants.

We selected the representative sample of 800 companies (sample frame ≈ 124,000 according to the Central Statistical Office) using a stratified – based on firm size criterion – sampling technique. In the analytical process 786 valid questionnaires were used and 14 questionnaires were excluded due to the identified tendency bias.

Operationally the data collection was divided into three steps. First, as in prior studies on IOR (e.g. Dwyer et al., 1987; Jap and Ganesan, 2000; Jap and Anderson, 2007; Kusari et al., 2013; Mathur and Kumar, 2013; Palmatier et al., 2013) at the beginning of the survey we asked our respondents to think about the most important IOR in their company's experience and then answer all of the further questions in the context of this particular inter-organizational relationship.

Second, we asked the respondents to identify in what phase of the life cycle is currently the chosen IOR. Particular phases of the IOR life cycle: Initial (I), Development (D), Maintenance (M), Dormant/End (D/E), and Reactivation (R) were described following Klimas et al. (in press).

Third, using a 7-point Likert scale we asked our respondents to assess the chosen IOR in terms of its particular features. The measurement of particular features was made using indicators and scales already available in the literature: commitment (Jap and Ganesan, 2000; Zaefarian et al., 2017) – 6 items, communication (Palmatier et al., 2006; Claycomb and Frankwick, 2010; Zaefarian et al., 2017) – 5 items, (lack of) conflict (Sharma et al., 2015) – 5 items; cooperation (Lussier and Hall, 2018) – 6 items, intensity (Palmatier et al., 2006; Jap and Anderson, 2007; Lee and Johnsen, 2012; Mathur and Kumar, 2013) – 5 items, investments (Jap and Anderson, 2007; Claycomb and Frankwick, 2010; Kusari et al., 2013; Kam and Lai, 2018) – 5 items, longevity (Lee and Dawes, 2005; Kam and Lai, 2018; Lussier and Hall, 2018) – 6 items, multidimensionality of bonds (Arantola, 2002) – 9 items, trust (Jap et al., 1999; Jap and Anderson, 2007; Palmatier et al., 2013; Kam and Lai, 2018; Ndubisi and Nataraajan, 2018) – 6 items, and velocity (Denize and Young, 2007) – 7 items. All of the scales were positively validated (i.e. α ∈ <0.7; 0.9>; CR > 0.7; AVE > 0.5 or AVE > 0.4 with concurrent CR > 0.8) in the chosen research context [1] (Klimas et al., 2022).

Data analysis was carried out in two stages. First, a one-way analysis of variance ANOVA (Sahai and Ageel, 2000) was used to compare average features values across the distinguished five life cycle phases (I, D, M, D/E, R).Conducting the ANOVA was preceded by checking the assumption of equality of variance (homogeneity of variance) using Levene's test. When there was no basis for rejecting the hypothesis of equality of variances, classical ANOVA was used, while when inequality of variances was found, Welch's ANOVA (robust test of equality of means) was applied. However, as the ANOVA result does not identify which pairs of means are statistically different, the post hoc tests were performed as well.

Second, to compare the average level of IOR features in relation to responses concerning the chronological phases of the cycle and to directly test our research hypothesis, the t-test for equality of means was applied for independent samples for each variable separately. Due to the formulation of the research hypothesis defining the direction of the examined changes (higher values of IOR features in the later phase of the life cycle) a one-sided test (1-tailed) was applied. The hypothesis of equality of average values μt = μt + 1 was tested against the alternative hypothesis formulated in the form of inequality: μt < μt + 1. The comparisons were made between chronologically consecutive phases, namely I–D, D-M, M-D/E, and D/E-R. The testing process was preceded by checking the assumption of homogeneity of using Levene's test. Depending on the result, the conclusion was based on the version of t test appropriate for the assumption of equal variances or applied in the case of no assumption of equal variances.

Data was analyzed using Statistic ver. 13.

Results

Results of Levene's test shows that three relationship features are characterized by heterogeneity of variance (p < 0.05): Conflict, Communication, Longevity. Therefore, Welch's ANOVA was used for these features. For the remaining variables, classical ANOVA was used to analyze the potential differences. The results of the one-way analysis of variance are presented in Table 3.

In our study only for the Investments, there were no differences in the mean level across life cycle phases (p = 0.102). In other words, the remaining nine IOR features show significant differences in their level across different phases of RLC. As shown in Figure 1, in general, the considered features systematically increase in the first three phases (i.e. I, D, M), then decrease in the D/E phase, and finally increase again if the relationship is reactivated.

Post hoc tests were used to determine which phases were affected by the differences. The results are shown in Table 4. ANOVA analysis confirms the significance of the value differences and post-hoc tests indicate the relationship phases are varied in terms of the levels of IOR features.

Interestingly, the significant differences were not identified for all of the IOR features between all of the subsequent phases of RLC. First, Velocity is the only feature with a significant difference between the D and M phases. Second, Commitment, Communication, and Longevity are those features with a significant difference between D/E and R phases. All in all, multiple comparisons show that the majority of significant differences are between two pairs of phases namely D-D/E and M-D/E phases.

The process of testing of research hypothesis assuming that the higher values of IOR features are reached in the later phase of the life cycle was preceded by verification of variance equality. Inequality of variance (p < 0.05) was found when comparing the following IOR features: (1) Velocity between M and D phases; (2) Communication, (lack of) Conflict, Longevity, and Trust between D/E and M phases; (3) Communication, Cooperation, and Longevity between R and D/E phases. For the rest, Levene's test indicates that there is no basis for rejecting the hypothesis of equality of variance. The results of the comparisons between phases of RLC for IOR features are presented in Table 5.

Our analysis shows that all differences in means for I-D phases are positive. Statistically significant differences in the one-sided test (p < 0.05) were found for the features: (lack of) Conflict, Investments. It can be concluded that the average level of these features in D (later) phase is significantly higher than in I (earlier) phase. For the remaining features no statistically significant differences were found.

Differences of means for phases D-M are positive except for Investment and Velocity. Statistically significant differences in the one-sided test (p < 0.05) allowing to check whether in the M (later) phase the mean scores are higher than in the D (earlier) phase were obtained for IOR Longevity. It can be concluded that its average level in the M phase is significantly higher than in the D phase. Whereas, for Velocity it can be concluded that values in D phase are significantly higher than in M phase (i.e. Velocity decreases starting from M phase). For the other characteristics, no statistically significant differences were found, which means that the phase of the life cycle does not affect the levels of IOR features.

Differences in means for M-D/E phases are negative except for Velocity. Indeed, as statistically significant differences in a one-sided test (p < 0.05) were obtained for the Velocity, it can be concluded that its average level in D/E phase is significantly higher than in M phase. No significant difference was found for the Investments. The remaining results (i.e. for the remaining 9 IOR features) lead to the conclusion that there are statistically significant differences between the means for the phases, but of opposite nature. It is in D/E phase that values are lower than in M phase.

Finally, the differences in means for phases D/E-R are positive except for Investments and Velocity. Statistically significant differences were obtained for traits: Commitment, (lack of) Conflict, Communication, Cooperation, Intensity, Longevity, and Multidimensionality of bonds. It can be concluded that their average level in R phase is significantly higher than in D/E phase. No significant difference was found for the characteristics Investments and Trust. For the variable Velocity there is a statistically significant difference between the means for the phases, but in the DE/phase there are higher values than in the R phase.

Discussion and conclusions

This study supports prior claims that IORs are rich in changes (Harmeling et al., 2015). Recognition of those changes we see as relevant for strategic management as the changes are claimed as impacting effectiveness (Mathur and Kumar, 2013), economic and business performance (Varotto and Parente, 2016) as well as time performance (Esposito and Passaro, 2009). Particularly, our study provides several contributions to literature on inter-organizational relationships thus strengthen the relational view in strategic management.

First, it sheds new and desired (Jap and Ganesan, 2000; Holmlund, 2004; Jap and Anderson, 2007; Lussier and Hall, 2018) light on the specificity of IOR features. Here we offer a 10-puzzle picture revealing different configurations of IOR features over the subsequent phases of the relationship life cycle. On the one hand, this research not only supplements prior studies focused on single characteristics but also supports another research stream providing evidence for changeable configurations of relational facets of relationships over time (Ricciardi et al., 2022). On the other hand, our study shows these different configurations using the concept of the life cycle which is original in the context of those ten specific attributes (except trust and investments – Jap and Anderson, 2007; Kusari et al., 2013).

In the view of past studies, we empirically confirmed that all of the IOR features can decrease or increase (Havila and Wilkinson, 2002), but never remain static throughout the relationship as emphasized Ford (1980). Supportively to the prior empirical evidence, we found out that velocity changes in a non-linear way (Harmeling et al., 2015) while cooperation – as suggested by Johnsen and Ford (2008) and by Lee and Johnsen (2012) – positively and gradually evolve over time however this evolution seems to be just slightly increasing. Next, as in the literature, we found out that intensity of the relationship evolves over the age of the relationship (Holm et al., 1999) and first it grows then rapidly decreases (Palmatier et al., 2013). Furthermore, investments seem to grow incrementally in a successive manner what remains in line with an assumption that they depend on accumulated resource flows (Gelei and Dobos, 2014). Last but not least, given an evolutionary and dynamic perspective, our study supports and broadens prior qualitative evidence for the successive increase of cooperation, intensity, coping with conflict, and trust across the phases of Building, Establishing, and Maintaining (Lee and Johnsen, 2012).

At the same time, our study has not confirmed that commitment appears in the later phases of IOR life cycle (Fynes et al., 2005) and communication is crucial in IOR forming (initial) phase (Fynes et al., 2005; Harwood, 2006) - at least not as significant as other features. Our results also differ for the lack of conflict which in the literature appears when the relationship stabilizes (Johnsen and Lacoste, 2016) and usually grows in long-lasting relationships (Ring and Van de Ven, 1994). Moreover, we have not found support that trust reaches high level at the beginning of relationship, and then goes low as Panda and Dash (2016) claimed.

Second, our study shows that–in terms of relational features–there is a typical, successively increasing development path of IOR. Indeed, in contrast to prior suggestions that relational constructs, including the features of IOR, “follow unique path-dependent growth trajectories, according to the relative contribution of a construct-specific set of underlying time-varying processes” (Palmatier et al., 2013, p. 27) our study suggests that although the levels reached by particular features are slightly (mainly insignificantly) different among considered phases of IOR (c.f. Figure 1), there can be sketched their general development path. All in all, as the IOR features take different configurations across the phases of the relationship life cycle, the path of the relationship development appears to be indeed time-dependent (Goldring, 2010; Mathur and Kumar, 2013; Gelei and Dobos, 2014). Nonetheless, the dynamic perception of the life cycle should not assume it is just a trajectory of continuous growth (Palmatier et al., 2013). As we take the perspective of time we shed light on the temporal dynamics of IOR deemed desired and essential for further development of IOR theory (Castañer and Oliveira, 2020).

Third, given our results, our research hypothesis can be partially supported while the IOR features do not develop in a linear fashion. Indeed, the vast majority of IOR features increase starting from Initial phase, through Development and Maintenance phases, then decrease in Dormant/End phase and increase again if the relationship goes to the Reactivation phase. Indeed, considering the significant differences between the consecutive phases (Table 4), our results show that the levels of the IOR features are not statistically different, although they do increase gradually from the Initial phase, through Development to Maintenance. The revealed exception there is Velocity varying significantly in the M phase. For almost all of the considered IOR features, a clear and statistically significant difference emerges between the M and D/E phases, when levels of features decrease significantly. Interestingly, Velocity–unlike the other IOR features – significantly increases in D/E phase. Given, that it increases further if the relationship is reactivated, it shows Velocity as the only one attribute characterized by a linear dynamics.

Fourth, this study provides awaited empirical evidence (Batonda and Perry, 2003; Sivadas et al., 2012; Akrout, 2014; Mandják et al., 2015; Yaqub, 2017; Gaczek et al., 2018) that the life cycle of IOR do not have to end with the complete breaking of the relationship, but the relationship can be reactivated and if IOR is reactivated the relational features are significantly developed. This is a general conclusion, however no significant differences were found for Investments and Trust. Moreover, Investments–unlike the other IOR features – decrease in Reactivation phase. It may suggest that if IOR is reactivated, its exploitation builds on past mutual investments and there is no new investment of resources in the inter-organizational relationship. All in all, as the considered IOR features are identifiable in the reactivation phase, the life cycle of IOR seems to be cyclical, instead of just non-linear and consists of unrepeatable phases, as suggested by Ring and Van de Ven (1994).

There are some limitations that should be considered. First, our study although based on a large and randomly selected sample was limited to one country and one industry. Even though IOR are seen as highly context-dependent (Kursari et al., 2013) thus intentional focus on a given national and industry context is methodologically reasoned the above conclusions should be seen as non-fully generalizable (Czakon et al., 2014). We chose Polish software developers industry rather for appropriateness than for the representativeness and possibility for generalization. That means that although the presented results are novel they refer to exploration of inter-organizational features only in specific industry context – software developers. Thus, the obtained results also provide a basis for their verification in other industries. Also, there are limitations due to the geographical context. Therefore, replicating the study in other countries would allow a cross-board validation of our results. Second, as in other studies (e.g. Jap and Ganesan, 2000) we relied on responses about dyadic relationships collected from one actor only while every IOR links at least two actors. Thus to provide a better understanding of the relational issues, the adoption of a dyadic, triadic, or network perspective to every single considered IOR would be more cognitively reasoned (Ferreira et al., 2017; Lussier and Hall, 2018).

To push our research further we suggest exploring the relational features and their changes over time in the context of social relationships. On the one hand some features have been proven relevant for interpersonal relationships (Valitova and Besson, 2021) also relationships maintained by network leaders (Soares et al., 2020) but a comprehensive list of relational attributes is missing. On the other hand, interpersonal relationships are also acknowledged as underlying IOR (BarNir and Smith, 2002; Wang et al., 2016), thus the features identified for IOR may be linked or even impacted by the features of social relationships but there is no empirical evidence supporting such transposition. Last but not least, IOR are attributed to formality versus social control (Larson, 1992) therefore it would be interesting to find out if (and to what extent if any) formality/informality level matters for the configuration of IOR features. In the same vein, the possible dependence of the configuration of IOR features can be explored in the context of other bipolar attributes like trust-distrust (Kostis and Näsholm, 2020), conflict-lack of conflict (Lee and Johnsen, 2012), or asymmetry-symmetry (Salonen and Gabrielsson, 2012).

Figures

Figure 1

The levels of IOR features across relationship life cycle

Table 1

Changes of IOR from the perspective of their life cycle

RLC origin	Ford (1980)	Dwyer et al. (1987)	Ring and Van de Ven (1994)
Field	Marketing, B2B (institutional buyer-seller)	Relational marketing, B2C (buyer-seller)	Management, IOR (wide scope of organizations)
Phases	Pre-relationship stage	Awareness	Emergence
	Early stage	Exploration	Evolution
	Development stage	Expansion	Dissolution
	Long term stage	Commitment	Renewal
	Final/rupture stage	Dissolution
Adoption	Heffernan and Poole (2004), Hastings et al. (2016)	Mangus and Ruvio (2019), Restuccia and Legoux (2019) (lack of awareness)	Batonda and Perry (2003), Baptista (2013), Kam, Lai (2018) Panda and Dash (2016) (only emergence and evolution phases)
	Theng Lau and Goh (2005), Woo and Leelapanyalert (2014) (lack of final phase) Ming-Huei and Wen-Chiung (2011) (lack of pre-relationship and final stage)	Fynes et al., (2005) (lack of dissolution) Sweeney and Webb (2007), Hansen et al., (2013), Akrout (2014) (lack of awareness and dissolution) Plewa et al. (2013) (dissolution changed into latent phase)
	Goldring (2010), Abosag, Lee (2013), Mandják et al. (2015) Lee and Johnsen, 2012 (lack of pre-relationship stage/awareness and final/dissolution phases); Ferreira et al. (2017) (lack of final/dissolution phase)

Note(s): Italics: Some scholars consider a pre-relationship phase (e.g. Abosag and Lee, 2013; Plewa et al., 2013) as an inherent RLC phase but in this phase IOR formally do not exist. Given the perspective of IOR features, even though before IOR is established there can be exchanged some social (Hasting et al., 2016) or even economic factors (Batonda and Perry, 2003), there is no commitment (Batonda and Perry, 2003) or trustworthiness (Abosag and Lee, 2013) and relationship formally does not exist

Table 2

Changeability of IOR features in the literature

IOR feature	Understated changeability	Linear changes	Nonlinear changes
Commitment	Ferreira et al. (2017)	Lau and Goh (2005), Hastings et al. (2016)	Havila and Wilkinson (2002), Heffernan and Poole (2004), Goldring (2010)
Communication	Ferreira et al. (2017)	Fynes et al. (2005)	Heffernan and Poole (2004), Plewa et al. (2013)
Conflict (lack of)	Ring and Van de Ven (1994), Ratajczak-Mrozek et al. (2019)	- not identified -	- not identified -
Cooperation	Ferreira et al. (2017)	Fynes et al. (2005), Hastings et al. (2016)	- not identified -
Intensity	Holm et al. (1999)	- not identified -	- not identified -
Investments	Ferreira et al. (2017)	Hastings et al. (2016)	Gelei and Dobos (2014)
Longevity	Mathur and Kumar (2013)	- not identified -	- not identified -
Multidimensionality of bonds	Arantola (2002), Havila and Wilkinson (2002)	- not identified -	- not identified -
Trust	Lewicka and Zakrzewska-Bielawska (2020), Batonda and Perry (2003)	Fynes et al. (2005), Lau and Goh (2005), Abosag and Lee (2013), Baraldi and Ratajczak-Mrozek (2019)	Havila and Wilkinson (2002), Heffernan and Poole (2004), Kursari et al. (2013), Plewa et al. (2013)
Velocity	Denize and Young (2007)	Palmatier et al. (2013), Harmeling et al. (2015)	Yaqub (2017)

Table 3

Results of analysis of variance

IOR feature	F Statistic	p-value
Commitment	9.244	0.000
Communication	6.556	0.000
Conflict (lack of)	5.194	0.000
Cooperation	6.926	0.000
Intensity	4.703	0.001
Investments	1.939	0.102
Longevity	10.744	0.000
Multidimensionality of bonds	4.321	0.002
Trust	4.018	0.003
Velocity	7.571	0.000

Table 4

Results of multiple comparisons (between all pairs of phases) for the levels of IOR features

Table 5

Results of comparisons of means values for IOR features in chronologically subsequent life cycle phases

IOR feature	Initial–development			Development–maintanance			Maintanance–dormant/End			Dormant/End–reactivation
	Mean difference	t stat	p-value	Mean difference	t statistic	p-value	Mean difference	t statistic	p-value	Mean difference	t statistic	p-value
Commitment	0.627	1.256	0.105	0.404	1.118	0.132	−2.305	−5.772	0.000	1.825	3.179	0.001
Communication	0.878	1.494	0.068	0.677	1.595	0.056	−2.544	−4.808	0.000	2.065	3.035	0.001
(lack of) Conflict	1.449	2.587	0.005	0.158	0.378	0.353	−2.042	−3.841	0.000	1.478	1.999	0.023
Cooperation	0.959	1.387	0.083	0.252	0.507	0.306	−2.708	−4.866	0.000	1.671	2.269	0.012
Intensity	0.604	1.539	0.062	0.274	0.967	0.167	−1.275	−3.968	0.000	0.899	1.947	0.026
Investments	1.996	2.475	0.007	−0.181	−0.295	0.384	−0.058	−0.091	0.464	−0.770	−0.886	0.188
Longevity	0.647	1.203	0.115	0.842	2.271	0.012	−3.065	−6.367	0.000	2.053	3.537	0.000
Multidimensionality of bonds	1.493	1.498	0.068	0.254	0.354	0.362	−3.021	−3.769	0.000	2.292	1.930	0.027
Trust	0.851	1.107	0.135	0.181	0.333	0.370	−2.279	−3.537	0.000	1.379	1.511	0.066
Velocity	0.390	1.091	0.138	−0.940	−3.329	0.000	1.565	5.042	0.000	−1.117	−2.814	0.003

Note(s): The p-value is shown for a one-sided tests

Note

1. The process of scale development, purification, and validation–run as an integrated result of systematic literature review, in-depth interviews, and large-scale surveying–is presented in Klimas et al. (2022).