This paper examines drivers of merger partner selection and impacts of those factors on post-merger innovation outcomes analyzing 1,432 merger transactions in U.S. ICT industries. Throughout the paper, technological similarity between merging firms and technological diversity of an individual firm are important factors affecting firms' merger partner choice. In order to show their impacts on merger partner selection, we use a two-sided matching model as a theoretical framework and employ a maximum score estimation as an empirical methodology. With these empirical strategies, our findings are summarized as follows. First, technological similarity between merging firms has positive effects on merger value creation. This implies that similar technologies between merging firms plays an important role in choosing their merger partners. Second, technological diversity of an individual firm increases expected merger values. This means that firms tend to choose their deal partners with diverse technologies for the purpose of maximizing their expected merger values. Lastly, we estimate post-merger innovation impacts for actual merger transactions. As a result, estimated merger values created by technological similarity and diversity increase the number of merged firms' patents after merger. This implies that expected merger values are realized through the channel of post-merger innovation outputs.

Executive Summary

I. Introduction

II. Two-Sided Matching Model

III. Empirical Strategy

1. Data Description

2. Estimation Methodology

IV. Empirical Results

1. Determinants of Merger Partner Selection

2. Model Goodness-of-Fit

3. The Impacts of Technology Similarity and Diversity on Post-Merger Innovation

V. Conclusion and Discussion

References

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