iamot2018 effects of competitors' state on mergers and ... · (m&a). investigating 46,541...

International Association for Management of Technology IAMOT 2018 Conference Proceedings

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EFFECTS OF COMPETITORS’ STATE ON MERGERS AND ACQUISITIONS IN JAPAN

HIROKO YAMANO* Policy Alternatives Research Institute, The University of Tokyo, JAPAN

[email protected] MASANAO OCHI

Department of Technology Management for Innovation, School of Engineering, The University of Tokyo, JAPAN [email protected]

ICHIRO SAKATA The University of Tokyo, Innovation Policy Research Center, JAPAN

[email protected]

ABSTRACT

Industrial diversity, as characterized by the variety of companies in regional clusters, raises the question of whether general patterns determine the combinations of firms in mergers and acquisitions (M&A). Investigating 46,541 data on M&As in Japan from 2003 to 2016 provided by UZABASE, Inc., we found features that characterize M&As; the degrees of oligopoly by industrial classification. We focused on the effects of the competitors’ state on M&As and analyzed data in the following three steps. First, we computed the basic distribution of Japanese M&As characterized by the deals and companies. Second, we compared the correlation of features of M&As by industry. Third, we estimated the transition and correlation of the degree of industrial oligopoly with the number of acquisitions. The data confirm that industry concentration did not always intensify as the number of M&As increases. The degree of oligopoly was different among industries, suggesting a different impact of M&As according to the industry’s growth stage. Since the analysis of M&As from the viewpoint of industrial diversity in this study appears to show environmental stability caused by competitors’ states, corporate strategy managers will benefit from our findings.

Key words: merger and acquisition; industrial concentration; industrial diversity; oligopoly; network evolution

INTRODUCTION

Business activity is an optimization problem under environmental constraints influenced by changes in regulations, new technologies, competitors, and the economic/financial conditions. In this study, we focused on the effects of competitors’ state on mergers and acquisitions (M&A) in Japan.

From the period of high economic growth through the 1960s and the consecutive years to the 1990s, the number of Japanese M&As was comparatively modest due to corporate conditions such as long-term employment, the main-bank system and mutual mergers (Kester 2003). However, M&As acutely increased since the late 1990s in Japan. Arikawa and Miyajima (2007) suggest that the factors behind the Japanese M&A boom starting from the late 1990s included the effects of business restructuring, technological innovations, regulatory reforms and economic shocks, revealing the characteristics of cooperative M&As specific to Japan. Jensen (1993) claims that M&As were a positive factor as the


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main method of eliminating excess production capacity, and M&As played important roles in business restructuring, on behalf of the restructuring by the main banks in Japan (Jacson and Miyajima 2007).

Unlike a trade network, a M&A network is a low density network characterized by a persistent giant company governed by an intensive margin rather than an extensive margin, suggesting its stability over time (Dueñas et al. 2017). However, from the viewpoint of network evolution, M&As in Japan are in a state of unstable monopoly due to the preferential selection and concentration of M&A networks (Goto et al. 2017).

Porter (2003) claims that firms within the same industry are often clustered in groups with distinct business models and operations. In addition to the economic influence of geographical proximity among companies, several researches have revealed the relations between industrial concentration and M&As. Kamien and Zang (1989) suggested the possibility of partial monopolization, resulting in a product price increase and a decline in industry surplus. Brown and Greenbaum (2016) investigated the relationship between industrial diversity and economic resilience over the previous 35 years in Ohio, and revealed that counties with higher industrial concentrations had higher unemployment rates during years of national economic instability.

Industrial concentration and diversity is one of the potent conditions that affects M&A. Kamien and Zang (1993) characterized the conditions under which monopolization can occur, in regard to the number of buyers and firms in an industry. Hagedoorn and Duysters (2002) demonstrated that M&As are influenced by different environmental conditions and firm specific circumstances, revealing that the high-tech industry favors M&As rather than alliances.

The main purpose of this study was to analyze M&A networks in order to clarify the different environment constraints under conditions of industrial oligopoly and diversity.

METHODOLOGY

We investigated M&A data in Japan from 2003 to 2016 in the following three steps. First, we computed the basic distribution of industrial classification, deal types or years in which companies were founded or became listed. Second, we cross-tabulated deal types, entity roles and the number of acquisitions and the target companies by industry. Third, by analyzing the correlation in the number of acquisitions and the industry concentration estimated by the degree of oligopoly of the industry, we examined the characteristics of Japanese M&As from the viewpoint of industrial growth and diversity.

To measure industrial concentration and diversity, we investigated four types of values that represent company scale and market share, i.e., total sales, market capitalization, employee number, and total assets. By examining the time transition of each value, we decided to use total sales for the oligopoly calculation because total sales represent clear and consecutive differences among industries. We calculated each industry’s degree of oligopoly by the Herfindahl Hirschman index (HHI), given by the following equation:

HHI =$ (𝑀'/𝑀)*+

',-

where M is the total amount of sales of all companies in Industry S, Ms is the total sales of a company in Industry S and N is the number of companies in Industry S. In short, the HHI index is the square-sum


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of the market share represented by 𝑀'/𝑀. To examine the correlation of acquisition and oligopoly directly, we calculated and plotted the standardized number of acquisitions and the standardized degree of oligopoly.

Data

Analysis was performed on deal data from Japanese companies with corporate information and financial statements between 2003 and 2016. The data was obtained by company database information platform SPEEDA, provided by UZABASE, Inc. In this study, we mainly used deal type, deal execution period, entity role with company information such as industrial classification, founding year, listing year, annual sales and accounting dates. In this database, companies participating in M&A are divided into four roles, i.e., acquirer, ultimate acquirer, target and seller. Deal data consisted of seven deal types, i.e., minority stake, acquisition, joint venture, fund by-out, MBO, demerger, and merger of equals. Among these seven deal types and four roles, the main focus of this study was the acquisition between acquirer and target, because these selections are the general understanding of M&As. Tables 1 and 2 present a basic description of the data. The data had information of 2,986 listed companies with 21,807 entries and a total of 10,445 companies with 46,541 entries, related to M&A in Japan.

Table 1: Number of Companies and M&As by Industry

Listed Total Industry Company M&A Company M&A Intermediate distribution 186 982 517 976 Public service 24 119 126 133 Medicine - Bio 125 695 330 694 Dining Out 87 356 254 423 Retail 234 1482 748 1553 Advertisement - IC service 424 2731 1821 3243 Construction - Real estate 322 1768 1194 2038 Machinery - Electrical products 410 3046 1003 2908 Corporate service 156 916 628 774 Consumer service 85 428 411 477 Material - Processed material 319 2077 712 1833 Resources - Energy 25 128 90 185 Transport machine 126 759 206 486 Transportation service 96 505 281 483 Finance 157 1200 1460 4966 Food - Commodities 210 985 664 1115 Sum 2986 18177 10445 22287

Table 2: Number of M&As and Entries by Deal Type

Listed Total Deal Type M&A Entry Avg. M&A Entry Avg. Acquisition 4496 5407 1.20 6045 13887 2.30 Demerger 3 4 1.33 5 10 2.00


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Fund Buy-out 99 122 1.23 216 492 2.28 Joint Venture 839 1234 1.47 1037 2770 2.67 MBO 79 84 1.06 164 335 2.04 Merger of Equals 2 3 1.50 3 5 1.67 Minority Stake 12659 14233 1.12 14817 29042 1.96 Sum 18177 21087 1.16 22287 46541 2.09

RESULTS

Time series transition of M&A by deal type

Figure 1 represents the time series transition of the number of M&A entries in Japan by three major deal types. Minority stake was the largest component of M&A and acquisition was the second largest. Overall, the number of M&As tended to increase during the setting period, except for the decrease after 2009, which might reflect the effect of the Lehman shock in 2008.

Figure 1: Time series transition of M&As by deal type

Deal type, entity role and industry distribution

Figure 2 represents the number of companies involved in M&As compared by two entity roles, two deal types and 16 industries. We investigated the distribution of companies in three axes; entity role: acquirer / target, deal type: acquisition / minority stake, and industrial category. Overall, there were fewer acquirers than target companies except for minority stake in finance. The number of target companies was the highest in the advertisement and information communication service (AICS) industry in both acquisition and minority stake. Machinery - Electrical products industry is the second highest target in minority stake, although there are few acquirers in minority stake.

Figure 2: Deal type, entity role and industry distribution of involved companies


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Deals by acquirer and target in 16 industries

Figure 3 represents the number of deals of acquirer and target companies in 16 industries. There were clear differences between acquisition and minority stake in the deal distribution by industry. In acquisition, most deals occurred in the same industry, i.e., the industry of the acquirer and the target was the same in the majority of deals. However, in minority stake, most deals were made by acquirers in the finance industry, and their main targets were not in finance but in other industries. Among minority stakes by finance companies, Machinery - Electrical products industry had the highest number of deals, followed by AICS, Material - Processed material and Construction - Real estate industry, showing an almost similar tendency to that occurring in acquisitions in the same industry.

Figure 3: Deals by acquirer and target in 16 industries

1: Intermediate distribution, 2: Public service, 3: Medicine - Bio, 4: Dining Out, 5: Retail, 6: Advertisement - IC service, 7: Construction - Real estate, 8: Machinery - Electrical products, 9: Corporate service, 10: Consumer service, 11: Material - Processed material, 12: Resources - Energy, 13: Transport machine, 14: Transportation service, 15: Finance, 16: Food – Commodities

Years of foundation and listing

Figure 4 shows the years of foundation of listed companies in five major industries for more than 270 listed companies. The AICS industry was the youngest industry comprised of a large proportion of companies founded after the late 1990s with its peak around 2000. On the other hand, Construction - Real estate, Machinery - Electrical products and Material - Processed material industry had their founding peak after 1945, the year that World War II ended.

1 2 3 4 5 6 7 8 9

10 11 12 13 14 15 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Acqu

irer

Target / Acquisition Target / Minority stake


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Figure 4: Year of foundation and number of listed companies by industry

Figure 5 represents the year of the listing of companies in five major industries. The overall tendency was similar to that detected in the founding years, showing a large portion of listings after the 1990s in the AICS industry, in contrast to those in the Construction - Real estate, Machinery - Electrical products and Material - Processed material industry after World War II. The AICS industry had two large falls in listings in 2003 and 2009.

Figure 5: Year of listing and number of listed companies by industry

Num

ber o

f com

pani

es

Num

ber o

f com

pani

es


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Acquisitions by companies listed before and after 2000

Considering the fact that most companies of the AICS industry were listed after 2000, we divided the data into two parts, i.e., companies listed before and after 2000. Figure 6 represents the number of acquisitions by the two types of companies in five major industries. Among the companies listed before 2000, the Machinery - Electrical products industry had the highest acquisition number. However, among companies listed after 2000, the AICS industry was the highest. In both types of companies, we detected a similar tendency of up and down, showing two valleys in 2009 after the Lehman shock and in 2012 after the Great East Japan Earthquake. The Construction - Real estate industry showed the opposite direction to that of other industries, especially in 2012 after the

earthquake.

Figure 6: Transition of the number of acquisitions by companies listed before and after 2000

Degree of oligopoly in major industries

Figure 7 represents the time series transitions of the degree of industrial oligopoly HHI, calculated by the total sales of two types of companies listed before 2000 and all listed companies. In both types of companies, the AICS industry had the highest degree of oligopoly with a declining slope. Although the Machinery - Electrical products industry also showed a declining tendency, the degree of oligopoly was much lower than that of the AICS industry. Retail industry’s degree of oligopoly distinctively increased within the companies listed before 2000.

Companies listed before 2000 All listed companies


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Figure 7: Transition of degree of oligopoly in major industries

Figure 8 represents the correlation between the standardized degree of oligopoly and the number of acquisitions in five major industries. We detected two opposite correlations among the industries of companies listed before 2000. The AICS industry and Machinery - Electrical products industry showed a negative correlation, whereas the Retail, Construction - Real estate, and Material - Processed material industry showed a positive correlation.

Figure 8-1: Correlation of oligopoly and acquisition

Companies listed before 2000 All listed companies


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Figure 8-2: Correlation of oligopoly and acquisition

DISCUSSION

Competitors’ state on M&A in Japan

Due to the business restructuring, technological innovations, regulatory reforms in the late 1990s, and the following burst of M&As along with increasing company listings, M&A research in Japan had difficulty in investigating objective analysis with a sufficient amount of long-term data until recently. In this study, we obtained and analyzed M&A data for 13 consecutive years from 2003 to 2016.

By analyzing the M&A data from multiple aspects such as deal types, entity roles, and industries, we detected significant characteristics of Japanese M&As related to the competitors’ state, as listed below with detailed descriptions. These characteristics will be useful not only for designing models and features to predict or optimize M&As, which we will study in future, but also for planning M&A strategies in real business.

i. Deviations of acquirer and target

ii. Effects of economic climate on founding and listing year

iii. Differences in degree of oligopoly by industry

iv. Positive and negative correlations between oligopoly and acquisition

Deviations of acquirer and target

The deviation in the number of acquirers and target companies revealed that Japanese M&As were dominated by fewer acquirers with various target companies (Fig. 2). The average entry rate of total companies related to acquisition was 2.34, indicating that there were two or more companies in each


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acquisition. However, the average decreased in listed companies, indicating that one of the related companies was not a listed company in most acquisitions (Table 2). We found most target companies were not listed, therefore, there were more acquirers than targets in listed companies.

Acquisitions tended to occur between acquirers and targets in the same industry, contrary to the distribution of targets in minority stakes acquired by finance companies. The deviation in the number of deals was similar between most acquisitions in the same industry and minority stakes in finance, indicating the possibility that minority stakes in finance predict or reflect the acquisitions in the other industries.

Effects of economic climate on founding and listing

Although recent entries and listings were dominant in the AICS industry, there were sharp declines in the years of listing in this industry (Fig. 4, Fig. 5). Those drops were detected after the IT bubble burst in 2002 and the Lehman shock in 2008, indicating the huge impact of changes in the economic climate on the listing. Although the AICS industry had the largest number of acquisitions recently, their deals were greatly affected by external economic conditions (Fig. 3 left, Fig. 6 right).

However, considering the fact that the AICS industry had a large number of unlisted companies (Table 1), this industry is likely to have many candidate companies for listing, in addition to the large portion of already listed new companies, and therefore, has the potential to continue growing.

The construction - real estate industry showed opposite directions in the acquisitions of companies listed before and after 2000, especially after the financial crisis in 2008 and the Great East Japan Earthquake in 2011 (Fig. 6). In the study of the Japanese inter-firm transaction network, large reconstruction demand after the earthquake in 2011 made the construction industry active and their transactions had a high replacement rate (Yamano et al. 2017). In addition to the effects on business transactions, this study showed that the construction industry acquisitions were also affected by external changes, such as reconstruction demand after a disaster.

Differences in the degree of oligopoly by industry

By examining individual industrial oligopolies, we found a decreasing tendency in two major industries, contrary to our knowledge of recent markets, becoming dominated by a few huge companies. The declining slope in the oligopoly of the AICS industry might be caused by the multitude of recent listed companies (Fig. 5). To remove the effect of those new listings, we recalculated the degree of oligopoly with limited companies listed before 2000, and found the declining tendency of the AICS industry slightly weakened, but was not changed significantly (Fig. 7). These analysis results suggest the competitive market of the AICS industry, turning into multi-polarization of established companies, beyond the simple influence of new listings.

On the other hand, the retail industry’s degree of oligopoly tended to increase and the tendency became stronger when we limited the calculation to the companies listed before 2000, indicating a growing gap in the sales of established companies in the retail industry.


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Positive and negative correlations between oligopoly and acquisition

The degree of industrial oligopoly is considered to increase with the activation of M&As, if the deals succeed and are completed within the industry. However, the correlations between oligopoly and acquisition in this study showed mixed results among industries. The detected positive correlation coincides with the basic understanding that the active acquisitions lead to giant companies with increasing disparity with other companies, and thus, oligopolistic control proceeds. However, the negative correlation in this study suggests that the more companies purchased other companies, the more the market diversified, resulting in high competitiveness of the industry. A negative correlation was seen in the top two industries of active acquisition and a large number of companies, i.e., AICS industry and the machinery - electrical products industry. M&As in these industries might induce merging companies to be uniformly competent or the dominant company to lose their share. In other words, M&As showed different impacts according to the industry’s growth stage.

Managerial implications

Since the analysis of M&A from the viewpoint of industrial and geographical diversity in this study appears to show environmental stability caused by competitors’ states, corporate strategy managers will benefit from our findings.

CONCLUSION

This study analyzed the M&A network by clarifying the differences in environmental constraints with industrial oligopoly and diversity. The retail industry, construction - real estate industry and material - processed material industry showed a tendency to concentrate with the acquisition, supporting the hypothesis of monopoly state or giant component caused by M&As. However, the AICS industry and machinery - electrical products industry tended to disperse, even if companies made new partners. The observed contrasting results in the relation of industry concentration and acquisition among industries suggests different impacts of M&A according to the industry’s growth stage.

Limitations and future research directions

In this study, we mainly focused on acquisition among 10 deal types such as minority stake, capital increase, IPO. Although we are interested in the evolutional transition of M&A, we did not examine the transitions of M&A deal type in the designated period. We focused on the environmental constraints that affect the acquisition of companies in Japan.

ACKNOWLEDGEMENTS

This work was supported by UZABASE, Inc.


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