How Risks and Innovativeness Influence the Selection of Partner in NPD Alliances

Abstract

Most often, if a new product is complex, a unique company doesn't have all the competences or means to achieve alone its development. In this case alliances must be formed to carry on the development project. However, alliances often meet difficulties in achieving their objectives. That is mainly due to difficulties of communication between partners, or to missing skills or means required to go further in the innovative development. To successfully overcome risks of collaboration dysfunction, an alliance must be created between partners able to communicate, presenting a complementarity in the project and being presenting a maximum of characteristics useful for the new project. This paper aims to increase our understanding of how to make alliance with the purpose of exploring the opportunities emerging from a partner innovativeness and risks management. We present an original model of alliance assessment composed by two partners intending to develop a particular innovative project. Based on this model, we propose a decision support system helping choosing firms for an alliance. A case study from the aeronautical industry is presented and results are analysed.

A partner selection framework for strategic alliances based on project complexity and partner’s past experience

“…They also noted that not just knowledge stocks but also tasks should be considered in evaluating resource complementarity. Mostly it is indicated in the literature that sharing knowledge and learning between partners has a direct influence on enhancing new product performance (Deniaud et al (2017); Relich and Pawlewski (2018)). Uwizeyemungu et al (2018) studied the importance of complementarities between information technology and noninformation technology capabilities.…”

“…A mathematical model to calculate partnership score for each set of partners is proposed based on their knowledge criteria, and shown in Equation ( 2) (Deniaud et al (2017)). Where α, β and γ are three coefficients that weight knowledge criteria (3).…”

“…Mudambi and Tallman (2010) argue that basing alliance partner selection on knowledge similarity and close geographic distance has positive effects on innovation performance. Deniaud et al (2017) argue that evaluating projects to rank them as technologically simple or challenging plays an effective role in the partner selection phase.…”

A decision-making framework based on knowledge criteria for network partner selection

“…They also noted that tasks should be considered in evaluating resource complementarity. Mostly it is indicated in the literature that sharing knowledge and learning between partners, has a direct influence on enhancing new product performance [11], [21]. A previous study, which used data from international mutual investment in China, suggested that knowledge absorption of partners plays a critical role in learning and innovation [27].…”

“…Regarding innovation, Mudambi et al [10] argue that in alliance partner selection, knowledge similarity and close geographic distance have positive influences on final performance. Deniaud et al [11] indicated that higher knowledge sharing among partners in a network increases the degree of innovation of a project. It is also discussed that evaluating projects to rank them as a technologically simple or challenging projects plays effective role in partner selection phase.…”