Alliances motive and the stock market response: A comparative analysis across industries

Abstract

We analyze the announcement-period returns of 4315 two-party, non-equity alliances undertaken by US-based firms between 1986 and 2015 in 11 industries and find positive returns for all of the 11 samples, with the Drug industry reporting the highest (2.69%) cumulative abnormal return (CARs) and Wholesale Trade for Non-Durable Goods industry the lowest (0.84%) around the five-day window surrounding the announcement of the alliances. Using proxy variables, we study whether the alliances in the specific industry are motivated by Exploration, Exploitation, or a combination of both Exploration and Exploitation motive. We find strong evidence that the alliances in the Business Services; Computer and Office Equipment; Electronic and Electrical Equipment; and Telecommunications industries are Exploration motivated. Alliances in the Investment & Commodity Firms, Dealers, and Exchanges; Measuring, Medical, Photo Equipment and Clocks; Prepackaged Software; and Wholesale Trade-Durable Goods industries are motivated by the Exploitation motive, whereas alliances in the Communications Equipment and Drugs industries are motivated by both Exploration and Exploitation (dual) motives. The average CAR (ACAR) for alliances in industries motivated by both Exploration and Exploitation motives is the highest at 2.2%—thereby, creating the most value—followed by Exploitation motivated at 1.58% and Exploration motivated at 1.23%.

Keywords:

• strategic alliance
• performance
• exploration
• exploitation
• inter-industry studies

JEL Classification:

• D34
• D74
• D78
• G34
• L22

PUBLIC INTEREST STATEMENT

We analyze the announcement-period returns of 4315 two-party, non-equity alliances undertaken by U.S. based firms between 1986 and 2015 in 11 industries and find positive returns for all of the 11 industry samples. In aggregate, the returns are higher than reported in prior studies pertaining to alliances. Using proxy variables, we stratify the industry samples whether the alliances in the specific industry are motivated by Exploration, Exploitation, or a combination of both Exploration and Exploitation motive. We find strong evidence that the alliances motivated by the dual motive of both Exploitation and Exploration yield the highest returns, followed in declining order by alliances motivated by the Exploitation motive and the Exploration motive. Results emanating from our cross-sectional regressions can be utilized to design industry studies on alliances and confirm structural parameters of individual industries, especially as it pertains to the cost of capital of the alliance firms. Also, potential future research can explore long-run performance of the alliances.

Notes

1. There have been several studies documenting the valuation effects of joint ventures between non-financial firms (McConnell and Nantell (1985); Crutchley, Gou, and Hansen (1991); and Chan et al. (1997)) and financial firms (Gleason, Mathur, and Wiggins (2003); Chiou and White (2005); Marciukaityte, Roskelley, and Wang (2009); and Amici, Fiordelisi, Masala, Ricci, and Sist (2013)). All report positive abnormal returns around the announcement of alliances and/or joint ventures.

2. The SDC database relies on information from US Securities and Exchange Commission, industry publications, and/or other news sources. The data have information on joint ventures and strategic alliances encompassing research and development agreements, marketing and manufacturing agreements, supply agreements and licensing and distribution arrangements (Schilling, 2009).

3. The first reported alliance in the SDC database is in the year 1986.

4. The data downloaded from SDC listed both strategic alliances and joint ventures. We have restricted our study to only strategic alliances.

5. The lowest number of alliances within any industry that was omitted was 1 and the highest 40.

6. We analyzed the whole sample over (−3, +3) and (−1, +1) windows to test the robustness of the analysis. The results are essentially the same.

7. The KZ index is defined in Appendix A, Variable definitions.

8. The funds flow deficit is equal to dividends paid in year t+ Investments in year t + Change in working capital in year t current portion of long-term debt in year t-cash flow after interest and taxes in year t.

9. The SDC database flags for the kind of alliance.

10. The Altman Z-score is defined in Appendix A, Variable definitions. A score below 1.8 means the company is probably headed for bankruptcy, while companies with scores above 3.0 are not likely to go bankrupt. The lower/higher the score, the higher/lower the likelihood of bankruptcy.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Manish Tewari

Manish Tewari has an undergraduate degree in engineering from the Indian Institute of Technology, New Delhi and a Ph.D. in finance from the University of Central Florida. Tewari’s major areas of research are in Corporate Bonds, Financial Derivatives, Corporate Social Responsibility, and Alliances & Joint Ventures. He has published papers on corporate bond provisions including publication in the top journal in finance, Journal of Financial Economics. His research in the field of corporate social responsibility has led to publication in the prestigious Journal of Business Ethics. Currently, he is pursuing studies exploring motivation for alliances and joint ventures at the industry level. This paper is a result of one such study which has opened other potential research avenues in the field.

Tewari has an extensive teaching experience in finance and has taught a wide variety of finance courses including Corporate Finance, Investments, Money and Banking. Financial modeling, and Student Investment Fund.