Value-creation-capture-equilibrium in new product development alliances: A matter of coopetition, expert power, and alliance importance
Introduction
Firms form alliances to access external resources for their new product development (NPD) (Das, 2014; Lee, Park, Yoon, & Park, 2010; Santamaría, Nieto, & Barge-Gil, 2009; Schleimer & Faems, 2016). However, many NPD alliances experience imbalances between firms' inputs to value creation and abilities to capture value (Das & Rahman, 2010; Fonti, Maoret, & Whitbred, 2017; Ritala & Hurmelinna-Laukkanen, 2009), which might exist due to differences in the firms' abilities and motivation (Chen, Kuo-Hsien, & Tsai, 2007; Kalaignanam, Shankar, & Varadarajan, 2007). For instance, alliance partners are sometimes tempted to behave opportunistically, such as by reducing their inputs into value creation or by maximizing their value capture (Das & Teng, 2000; Fredrich, Bouncken, & Kraus, 2019; Hamel, 1991). Furthermore, while alliance partners might equally contribute to value creation, some partners might be more proficient and motivated in capturing the added innovation value (Clauss & Bouncken, 2019; Hoffmann, Lavie, Reuer, & Shipilov, 2018). Especially from a dynamic relational view (Das & Teng, 2000; Dyer & Singh, 1998; Dyer, Singh, & Hesterly, 2018), alliances with a sufficient symmetry in value creation and capture are more likely to reach their long-term goals, while asymmetry could lead to potential opportunism and relationship failure (Das & Rahman, 2010). The concept of the value-creation-capture-equilibrium (VCCE) between firms in alliances describes firms' relative inputs and efforts to the value creation in dyadic NPD alliances, as well as the alliance partners' relative abilities in capturing a portion of that value in the pursuit of private and common benefits (Bouncken, Fredrich, Kraus, & Ritala, 2019; Khanna, Gulati, & Nohria, 1998). The high uncertainties of inputs and outputs of NPD alliances bring challenges to the VCCE (Hoffmann et al., 2018; Jacobides, Knudsen, & Augier, 2006; Lavie & Rosenkopf, 2006). This VCCE exists when firms have equally (i.e. to the same extent) contributed to value creation and involve equal abilities to capture the value created from a particular NPD alliance (Bouncken, Fredrich, Kraus, & Ritala, 2019). Yet, little is known on when firms pursue balance of value creation and capture in alliances (Lavie & Rosenkopf, 2006; Ozmel, Yavuz, Reuer, & Zenger, 2017).
Our paper aims to explain how and why firms can achieve an equilibrium in the relative value creation and value capture in their NPD alliances. Inter-firm relationships experience a variance of inputs, outputs, and learning over the course of the alliance (Das & Kumar, 2007; Das & Teng, 2002; Dyer et al., 2018). Combining the relational view with the literature on innovation alliances (Clauss & Bouncken, 2019; Rai, 2016; Tyler & Caner, 2016; Wagner & Goossen, 2018; Wu, Luo, Slotegraaf, & Aspara, 2015), we model three important determinants that might influence the VCCE. The first is the coopetition intensity between the alliance partners (i.e. simultaneous competition and collaboration), the second is the expert power of the alliance partner, and the third is the focal firm's relative importance of the particular NPD alliance. All three conditions can facilitate imbalances and learning opportunities related to a dynamic relational view of dyadic alliances (Das & Teng, 2000; Dyer et al., 2018; Dyer & Singh, 1998).
Our model thus considers three conditions to VCCE. The first considers competitive and collaborative dynamics (i.e. coopetition) that have to be balanced in alliances (Cassiman, Di Guardo, & Valentini, 2009; Gnyawali & Park, 2011). Coopetition involves potential for bargaining and tensions (Bengtsson & Kock, 2000; Brandenburger & Nalebuff, 1996) that need to be considered as drivers and barriers to VCCE (Tidström, 2014). On the upside, coopetition tensions drive the search for new solutions using the strength of partners (Tidström, 2014), while on the downside, coopetition tensions go along with opportunism risks and protection (Gnyawali & Ryan Charleton, 2018). Considering the two effects, we expect that greater levels of coopetition intensity will promote a more balanced VCCE in NPD alliances. Second, the expert power of the focal firm's NPD partner brings expertise and power that might improve value creation processes, but also comes with dangers of power asymmetries (Clauss & Bouncken, 2019; Sahadev, 2005). Expert power refers to the power source's access to knowledge and skills desired by the power target (French Jr. & Raven, 1959). When the other firm has high expertise, it might contribute valuable external resources to the alliance. Expert power partners can kick-off a huge array of learning dynamics that might bind partners but also provide opportunities for imbalances (Dyer et al., 2018; Dyer, Singh, & Kale, 2008). Still, an expert partner might also have improved abilities to “outsmart” the other actors. In NPD alliances, expert power partners have high levels of knowledge about the problem space under consideration, e.g. market or technological expertise that may provide further information advantages and benefits (Maloni & Benton, 2000; Stern, Dukerich, & Zajac, 2014). On the one hand, we expect that focal firms are likely to seek balanced VCCE in their NPD alliances with partners possessing high levels of expert power given these high stakes. On the other hand, we also expect that partners with high expert power might intensify coopetition tensions and lead to alliance instability (Das & Teng, 2000; Dyer et al., 2008; Dyer et al., 2018), resulting in less balanced NPD alliances. In our study, we thus anticipate that expert power will exhibit a positive direct effect and a negative moderating effect on the relationship between coopetition intensity and VCCE. Third, investments in relation-specific assets contribute towards relational rents (Dyer et al., 2008; Dyer et al., 2018), and gradually affect the relative importance of the focal NPD alliance (i.e. the relative financial importance of the alliance within overall sales of the focal firm). The relative importance triggers further attention to the alliance and also motivates the focal firm to establish a long-term relationship. Thus, we expect that the importance of the NPD alliance will increase the focal firm's efforts to balance its VCCE. Again, we expect that this balance-seeking is disrupted when coopetition intensity increases and the focal firm attributes more relative importance to the NPD alliance. Here, either of the firms might become more interested in individual gains or restrict their value creation inputs, thereby negatively influencing the VCCE.
We test our model using a survey study of N = 471 high-tech firms pursuing dyadic NPD alliances. NPD alliances rely on the partnering firms' R&D capacities, but also complementarities in the areas of intellectual property, technology, sourcing, and marketing (Pullen, Weerd-Nederhof, Groen, & Fisscher, 2012). Thus, NPD alliances in our study potentially involve collaboration at multiple stages of the product innovation process (Ahmed & Shepherd, 2010).
Our results show that increasing intensities of coopetition relate to greater VCCE. We find that expert power has a positive moderating effect on the coopetition-VCCE relationship which is in contrast to our hypothesized negative moderation. Aligned with our theorizing, greater relative importance of the NPD alliance to the focal firm has a positive direct effect on the VCCE. This relative importance also exhibits a negative moderating effect on the coopetition-VCCE relationship.
Overall, our study brings the concept and conditions of VCCE to the dynamic relational view of alliances (Das and Teng, 2000, Dyer et al., 2018, Dyer et al., 2008). Focusing on relative value creation and relative value capture separately, we were able to further disentangle the underlying mechanisms and reveal nuanced, yet important differences that inform research on value creation and capture in alliances (Lavie, 2006a; Ozmel et al., 2017), and particularly under coopetition (Arslan, 2018; Bouncken, Fredrich, & Kraus, 2020; Fonti et al., 2017; Hoffmann et al., 2018; Ritala & Hurmelinna-Laukkanen, 2009). We show that coopetition – itself a balance between collaboration and competition – is a convergence force to value creation and capture, highlighting the specificity of coopetition as argued by coopetition scholars (Czakon & Rogalski, 2014; Granata, Lasch, Le Roy, & Dana, 2017; Le Roy & Czakon, 2015). Furthermore, reflecting the high stakes and related mutual monitoring, we support that positive tensions of expert power facilitate the balanced value creation and capture in highly coopetitive NPD alliances (Czakon, 2009; Fernandez, Le Roy, & Gnyawali, 2014; Gnyawali & Park, 2011). We also clarify negative tensions related to the competition-dominated behavior in coopetition (Arslan, 2018; Asgari, Tandon, Singh, & Mitchell, 2018; Cui, Yang, & Vertinsky, 2018; Tidström, 2014) by demonstrating how high alliance importance (as perceived by the focal firm), coupled with high coopetition intensity, will result in unbalanced value creation and capture in dyadic NPD alliances.
Section snippets
New product development alliances
Alliances refer to a wide range of interfirm relationships, most of them including strategic purposes (Osborn & Hagedoorn, 1997). According to Kale and Singh (2009), a strategic alliance is “a purposive relationship between two or more independent firms that involves the exchange, sharing, or co-development of resources or capabilities to achieve mutually relevant benefits” (p. 46). The relational view of alliances and its revisited dynamic relational view delivers a fundamental theoretical
Hypotheses
The dynamic relational view that considers inter-partner dynamics and stabilization in alliances guides our theorizing (Dyer et al., 2018). Alliances undergo social processes that include learning and that determine the creation of value in alliances (Dyer & Hatch, 2006; Dyer & Singh, 1998). Knowledge exchange and learning processes create relational rents and can breed further complementarities (Weber et al., 2016). On the one hand, high stability in repeated ties can reduce performance (
Sample
We focus on a broad range of highly innovative industries represented by firms at any of eight independent, international trade fairs hosted in Germany during 2014–2017. Overall 53,305 international exhibitors classified as service providers (e.g. SIC code 7371) and manufacturers of electronics (e.g. SIC code 3679) and medical devices (e.g. SIC code 3841) participated in these trade fairs. We reduced common method variance (CMV) by following recommendations of Podsakoff, MacKenzie, Lee, and
Hypothesis testing
Table 2 provides results based on MLR estimations for nested models starting with control variables and the main hypothesis 1 (Model A). We find support for coopetition intensity leading to a greater VCCE (H1: β = 0.15, p = .002). Model B and Model C introduce expert power and relative alliance importance as additional contingencies separately, with Model D testing both contingencies simultaneously. We find no evidence of the partner's expert power affecting the VCCE directly, rejecting
Theoretical implications
Our study is embedded in the dynamic relational view (Dyer et al., 2008; Dyer et al., 2018; Dyer & Singh, 1998). We consider the dynamic relational view in the context of NPD alliances where complementarities and positive externalities between partnering firms are key (Cui et al., 2018; Schleimer & Faems, 2016; Wagner & Goossen, 2018). To increase complementarities, firms need to be motivated to learn and to integrate their unequal capabilities to value creation. Furthermore, to achieve
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