Document Type

Article

Publication Date

3-3-2021

Abstract

Research Summary

Network centrality is an important determinant of alliance performance. However, estimating how each alliance member's centrality affects alliance performance is challenging because the end market might value each partner's contribution differently. We solve this empirical question with a two‐sided matching model that accounts for the partners' endogenous selection and estimates the effect of each side's centrality and input quality on performance. We implement the method in the novel context of the Thoroughbred horse industry, in foal‐sharing alliances between buyers and suppliers. We find that buyer centrality has a larger marginal effect on the alliance performance than the supplier centrality because buyers, who on average are less central in our context, are more likely to diffuse valuable information to the end market.

Managerial Summary

Alliance partners often struggle with identifying what their contributions and their partner's contribution are to the alliance performance. We use a new method to identify each side's contribution to their alliance. Our findings offer a few recommendations to firms forming similar alliances. First, we find that the less central partner in the business network has greater impact on the alliance performance due to their ability to diffuse more valuable information to the market. Second, our results suggest that product input quality that is relatively unknown impacts alliance performance more than low and average quality. Alliance partners may benefit more from experimenting with unknown inputs. Third, more central actors may reduce spending on mass communications if valuable information comes to the market through their less central partners.

Comments

This article was originally published in Strategic Management Journal in 2021. https://doi.org/10.1002/smj.3275

Peer Reviewed

1

Copyright

The authors

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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