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Cohabitation before marriage: do prior alliances enhance post-merger performance?

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Abstract

We investigate the impact of prior alliance relationships on subsequent mergers between partner firms. We argue that an acquirer’s prior alliance experience with the target reduces information asymmetry, which helps improve acquisition performance. Alternatively, agency problems arising from familiarity may lead to inefficient decision making. Examining mergers between 1986 and 2014, we find evidence that prior alliance collaboration is positively associated with the acquirer’s long-term profitability and growth. This positive effect is more pronounced when target-specific learning and experience are more crucial to merger success, such as targets in knowledge-intensive or organizational-capital-intensive industries as well as cross-industry mergers. However, we cannot formally rule out the possibility that our results are partly driven by the small size of our sample.

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Notes

  1. Our paper is also motivated by the following anecdotal evidence. Starting from early 1990s, Moet Hennessy Louis Vuitton (LVMH), a French multinational luxury company, began forming alliances with distributors and manufactures in almost all geographies. Later, LVMH decided to integrate these activities under one roof and bought out all its partners except for Chalhoub Group in United Arab. This strategy has transformed LVMH from an old trunk maker into a luxury powerhouse. According to Yves Carcelle, former CEO of LVMH, the success comes from “understanding and controlling the know-how and having your experts in-house.” See “When to Partner and When to Acquire, Louis Vuitton Style” with Dr. Andrew Shipilov at INSTEAD Business School.

  2. We initially identified 442 alliance-based mergers. As we discuss in Sect. 3.1, additional screening procedures have substantially reduced our sample size. Nevertheless, this sample size is consistent with the prior literature such as Zaheer et al. (2010). It is also worth noting that the total transaction value of the 442 mergers reaches $1.38 trillion (in 2014 dollars), which is economically significant given the aggregate spending of more than $3.4 trillion over 12,000 deals from 1988 to 2008 (Custódio and Metzger 2013).

  3. We also conduct several robustness tests to alleviate potential selection biases. First, we estimate a firm fixed effects model to make sure that our results are not driven by time-invariant unobserved acquirer characteristics. Second, we rerun our analyses with a sample of acquisitions in which acquirers have purchased both allied targets and non-allied targets. Using this sample helps to account for time-varying unobserved acquirer characteristics. Finally, we construct a propensity score matched sample, where each alliance-based acquisition is matched to similar non-alliance-based acquisitions by the likelihood of having prior alliance experience with the target. This test is to mitigate the concern that acquirers that have prior alliances with the targets might be different from those who don’t. Our results are robust to all of these methods.

  4. Our paper extends Porrini (2004) who finds a positive correlation between previous alliance tie on ROA growth of acquirers in manufacturing sector. Our paper differs in several ways. First, while Porrini (2004) remains silent on the potential selection issues, we address these concerns by taking several approaches. Second, we show that the effect of alliance is concentrated in settings with a higher degree of information asymmetries. Finally, we investigate the determinants of having prior alliances with the target and provide additional insights to the extant literature.

  5. For example, Zaheer et al. (2010) find no significant short-term stock market reactions for acquisitions with prior alliances, except for international mergers.

  6. We provide more detailed discussion on this issue in Sect. 3.3.

  7. Qi et al. (2015) study a more general angle of alliance experience and find that targets with alliance experience receive higher premiums. However, the study does not focus on the sequential alliance-acquisition choice. Rather, it argues that alliance experience of a target can have a signaling effect.

  8. Similar approaches have been used in Healy et al. (1992), Houston et al. (2001), and Porrini (2004).

  9. This is because minority stake acquisitions do not involve major change of ownership or control of the target firm.

  10. Although small, this sample size is consistent with other related studies. For example, Porrini (2004) examines 30 mergers preceded by alliances in a sample of 437 mergers. Zaheer et al. (2010) analyze 204 such mergers in their regression analysis based on a matched sample. Chang and Tsai (2013) rely on 95 mergers with prior alliances to compare with 4198 mergers without. We note that the biggest factor that reduces our sample size is the requirement on non-missing deal transaction value. In unreported analysis, we compare all deal characteristics and financial variables before and after implementing this restriction and find no significant differences between the two samples.

  11. For example, Bodnaruk et al. (2013) find a positive association between a firm’s quality of governance and its alliance activity. If firms without alliances tend to be poorly governed, leading to worse post-merger performance, then including these firms introduce an upward bias on our coefficient estimates.

  12. In unreported tests, we also examine the short-term market reactions to the alliance-based acquisitions. We do not find any strong evidence for the wealth effects of these mergers. This result, combined with better long term stock performance of alliance-based mergers (see Chang and Tsai 2013) suggests that investors underreact to mergers with prior alliances.

  13. To further mitigate the concern that prior alliances might capture merger relatedness, in our robustness checks, we follow Alhenawi and Stilwell (2018) to include dummies for in-state mergers or high-tech mergers. Our results continue to hold. These results are reported in Appendix Table 13.

  14. We note that the reported R2 is small in these regressions. The reason may be that our dependent variables are measured in changes, which are relatively noisier than those measured in levels.

  15. We calculate the industry yearly averages of total R&D and advertising expenditures scaled by assets using all firms in the Compustat. Our results are robust if we use median values of knowledge intensity to split the sample.

  16. Accordingly, these industries have the following SIC codes: 2833–2836, 3571–3579, 3612–3652, 3661–3699, 3721, 3724, 3728, 3761, 3764, 3769, 3821–3899, 737X, 8711, and 873X.

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Acknowledgements

We thank Ferhat Akbas, Christopher Anderson, George Bittlingmayer, Robert DeYoung, Phyllis Keys, Paul Koch, Lei Li, Felix Meschke, William O’Brien, Kelly Welch, Babajide (Jide) Wintoki, Steven Zheng, and seminar and conference participants at the University of Kansas, Southern Connecticut State University, the Financial Management Association (FMA) Annual Meetings, the Midwest Finance Association (MFA) Annual Meetings and the Southwestern Finance Association (SWFA) Annual Meetings for their insightful suggestions and helpful comments. We gratefully acknowledge the financial support from the Southwestern Finance Association that awarded this paper as the McGraw-Hill/Irwin Distinguished Paper and Outstanding Doctoral Student Paper at the 2014 Annual meetings.

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Authors and Affiliations

  1. Paul College of Business and Economics, University of New Hampshire, 10 Garrison Ave, Durham, NH, 03824, USA

    Zhaozhao He

  2. School of Business, Southern Connecticut State University, 501 Crescent Street, New Haven, CT, 06515, USA

    Han Yu

  3. College of Business and Economics, Towson University, Towson, MD, 21252, USA

    Lijing Du

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  1. Zhaozhao He
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Correspondence to Zhaozhao He.

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Appendix

Appendix

See Tables 11, 12 and 13.

Table 11 Variable definition
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Table 12 Determinants of having prior alliances with the target
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Table 13 Additional controls for merger relatedness
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He, Z., Yu, H. & Du, L. Cohabitation before marriage: do prior alliances enhance post-merger performance?. Rev Quant Finan Acc 54, 1315–1349 (2020). https://doi.org/10.1007/s11156-019-00826-3

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