General Discussion

This discussion examines the extent to which findings in the case study (Section 5-Paper

#3) support the research propositions drawn from the theoretical framework (Section 4-Paper #2).

The scope of the empirical investigation needed to be narrowed from the initial theoretical propositions in order to reduce complexity and to prioritize propositions. To this end, the case study solely addresses the dimension of ‘value creation’ in relationships and leaves for future research to investigate the dimension of ‘value destruction’. In addition, the case study targets the proposition with the highest potential for managerial implications, i.e., Proposition 5 (Section 4.3.4), reformulated as follows for the purpose of the case study:

P.5: The more relational the exchange orientation, the higher the relationship value

The findings from the case study support this proposition. Specifically, results show that a higher relationship value is associated with a relational exchange orientation while a lower relationship value is associated with a transactional exchange orientation. In addition, findings indicate that EO impacts the components of suppliers’ value offerings. For instance, two categories of customer relationships – the relational/low value category (R/L relationships) and the transactional/high value category (T/H relationships) – which yield similar overall RV differ on cost reductions with the first category (in a relational EO) scoring higher on cost reductions than the second (Figure 13). This corresponds to the typical ‘sacrifice’ on price made by a supplier to maintain a long-term customer relationship (e.g., Payne and Holt 2001; Ravald and Grönroos 1996).

In addition, the case study shows that exchange in the industry is not always distinctively perceived to be in one orientation or another. Findings reveal that two categories of customer relationships initially distinct in the orientation/value matrix (R/L and T/H relationships) (Figure 11) tend to merge in only one group. This group is characterized by a somewhat equivalent RV (Figure 13) and by an intermediate EO between transactional and relational (Figure 15). This way, it can be argued that customer relationships should be segmented into three categories: one category includes relationships in a clear transactional EO (and is estimated providing lower value to customers than the competition); a second category includes relationships positioned in an intermediate EO (and rates either similarly or higher in terms of value delivered to customers compared to the competition); and a third category includes relationships in a clear relational EO (that generates higher value for customers than the competition). Future research needs to further investigate the existence of this ‘intermediate EO’ and its implications for customer relationship management and relationship portfolio management.

The results of the empirical investigation also suggest that the influence between EO and RV is not unidirectional but mutual. Relationships initially selected by the study participants in the transactional/high value category (T/H relationships) appear more

‘relationally oriented’ than those in the relational/low relationships (R/L relationships) on several dimensions of EO (e.g., interdependence, communication, trust, and commitment) (Figure 15). On the one hand, this paradox may be explained by acknowledging that T/H relationships are developed in a more relational orientation than intuitively thought by study participants. This interpretation then reinforces the argument made in the case study in favor of a relational EO for generating superior RV. On the other hand, this paradox may reveal that perceived RV influences EO by determining, for instance, the time orientation of relationships, and levels of communication, commitment, coordination, and regulation between organizations. Likewise, Simpson et al. (2001) observe how purchasing firms increase their commitment and cooperation with suppliers because of positive relationship outcomes. Ulaga and Eggert’s (2006a) demonstrate the positive impacts of RV on

satisfaction, trust and commitment. What the present research also indicates is that RV has additional impacts on other elements of EO. It further suggests that feedback effects exist between RV and EO (e.g., increases in relational EO lead to increases in RV which in turn lead to further increases in relational EO). These feedback mechanisms should be further investigated since managers need to find an accurate balance between influencing EO for increasing RV and adapting EO to the actual and potential RV with trade partners.

By investigating Proposition 5, the case study also provides indirect insights on propositions elaborated on links ‘within’ and ‘between’ key elements of the theoretical model (Sections 4.3.1.-4.3.3). These propositions are stated as follows:

P.1: The more the situation of exchange is characterized by a long-term orientation, a high frequency of exchange, and high degrees of proximity and interdependence between firms, the more exchange behaviors are characterized by high levels of commitment, cooperation, communication, and trust.

P.2: The more the exchange regulation is decentralized, normative, and

characterized by noncoercive influences, the more the structure is networked, and the more coordination is integrated, flexible, reactive, and characterized by extended use of IT and IOSs.

P.3: The more the nature of IRs is collaborative, the more the governance is relational. The corollary holds that the more adverse IRs are, the more their governance is transactional.

Although the findings appear to support the linkages between most variables included in Proposition 1, proximity between firms is not found to have a significant impact in EO (Figure 15). This contradicts previous research on the positive effects of spatial and cultural proximity on relationships (Oerlemans and Meeus 2005; Porter 1998). One explanation for this contradiction is that distance between suppliers and customers has historically been a characteristic of the supply chain for structural wood products. Business actors have adapted to this situation by developing a ‘phone business’ culture which renders the issue of distance irrelevant. This adaptation was often noted by case study participants.

Nonetheless, future research could elucidate the role of proximity in EO and its impacts on

RV by methodically investigating the impact of relocating plants, distribution centers, and sales offices closer to customers.

The findings provide limited support for linkages stated in Proposition 2. This is explained by the restricted variation observed for variables characterizing the governance of exchange (Figure 15). Only strategic relationships (i.e., Relational/High value relationships) are described by study participants as being slightly more coordinated, regulated and embedded in an exchange network than other categories of relationships. This may suggest that the relational EO observed in the supply chain of wood products relies on behaviors and does not translate or has not yet translated into governance mechanisms. Another interpretation is that value-creating networks are emerging in the supply chain of wood products industry on the basis of strategic relationships between fewer and more powerful trade actors, including competitors (Sections 2.5. and 5.6.). The following quotation from one of the primary informants in the case study illustrates this point:

Jim: ‘A large part of my time is dedicated to procuring missing volumes in our programs with our biggest customers, so I call [Competitor #1] or [Competitor #2]

and ask them if they have this or that item, if they have it and want to sell it, and if I want to pay the price they ask for, we’ll go for it. They do exactly the same, this way we help each other with our surplus production. […] We still consider each other as competitors but somehow [Competitor #1] has become more of a client because they purchase our lumber. […] It started about 10-15 years ago with the

development of big boxes, the demand grew faster than production capacities and that’s when manufacturers started exchanging among each other.’

The findings from the case study tend to support the linkages stated in Proposition 3. A longer term orientation and higher levels of interdependence, commitment, cooperation, trust, and communication were associated with higher levels of regulation, coordination and network structure.

The case study focused on examining the impact of RV on EO and for this reason, findings do not inform Propositions 4 and 6 (Sections 4.3.4 and 4.3.5, respectively):

P.4: The more IR nature and governance are coherent, the more positive the outcome; that is, the more the outcome is characterized by superior value creation P.6: The more managers perceive uncertainty in the business environment, the more they rely on relational marketing orientation

A methodological approach was needed to develop a measure for EO, i.e., to evaluate characteristics of the nature and the governance of relationships, before addressing the issue of ‘coherence’ between these key elements. The case study proposes this methodology, and thus constitutes a building block for future research to address the issue of EO coherence (P.4) and the linkages between EO and environmental uncertainty (P.6).

In summary, the findings empirically support the initial theoretical proposition that superior relationship value is associated with a relational exchange orientation. Further, they deepen knowledge on value creation and on interfirm relationships in addition to consolidating a much needed bridge between these two research areas. Contributions and limitations of the research are specifically outlined in the next section.