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The impact of industry specifics on the effectiveness of high-tech mergers and acquisitions in developed capital markets

Introduction

merger acquisition high tech

Over the past few decades, the number of mergers and acquisitions has increased significantly (Benou and Madura, 2005). Experts report that in 2018 the volume of transactions grew so much that it broke the previous records set in the last pre-crisis year, 2007, and in 2016. M&A transactions are one of the basic concepts of modern business, which we have to reckon with and study. The high-tech industries today constituted up to a half of the GDP in developed economies. In the United States, it has wide influence, for example, due to high-tech sector cost savings and an increase in the productivity, the inflation rate on the country-wide level is decreasing by half of the percent every year (Davis and Madura, 2017). Due to the increasing importance of this phenomenon, the number of scientific studies on this issue has increased.

The relevance of the research can be explained by the fact that the share of high-tech transactions in the total pool of transactions in recent years has gradually increased and today such transactions constituting more than a half of the M&A value at the developed capital markets. The study becomes even more relevant every year.

Another issue contributing to the topicality of the paper is that despite the increasing amount of the researches dedicated to the M&A performance, high-tech deals do not obtain the sufficient deal of scientist's interest. Authors (Trigeorgis, 1993; Puranam, 2001; Alexandris, 2013; Roller, Stennek and Verboven, 2006; Ornaghi, 2009) highlight the distinct features of such deals, most of which are directly connected to the R&D role in the high-tech company's activity, the issues connected with valuation of such companies, growth options and higher level of risk associated with them.

There are several studies dedicated to the high-tech companies' M&A performance. Rheґaume and Bhabra (2008) considered the different outcome of the deals across the industries and found significant differences in the M&A performance. Kim (2018) indicates the industrial difference of the M&A deals outcome, but the conducted analysis was mostly focusing on the assets specificity of the companies. Authors made an attempt to include the industry's specificity into consideration by the control of the company affiliation with high-tech (Davis and Madura, 2015; Alexandridis, Mavrovitis, and Travlos, 2011) or particular industry (Rheґaume and Bhabra, 2008). The most commonly used approach of the dummy control variable indicates the ceteris paribus change in M&A deals from one industry to another. However, this approach does not allow to investigate the different influence of the determinants on M&A performance in the specific high-tech industry. Thus, despite the great current interest of the authors to high-tech mergers and acquisitions, it cannot be said that the issue has been fully investigated.

Some researches were dedicated to the M&A performance of the companies in particular high-tech industries. The following authors studied the particular high-tech industries: medical technology and biotech industry - Ravenscraft and Long (2000), Ornaghi (2009), Danzon, Epstein, and Nicholson (2007); software industry - Morton and Shapiro (2014), Goedhart, Koller, and Wessels (2010); communication industry - Spector (2007), Cloodt, Hagedoorn and Kranenburg (2006); Li (2005); computer and electrical equipment industry - Blonigen and Taylor (2003); automotive and aerospace industry - Laabs and Schiereck (2010). These authors presented the significant features of the industries, however, previously the comparative analysis was not conducted and the motives as the industry specificity factors were not tested.

The main aim of this paper is to investigate the influence of industry specificity on the high-tech M&A deal performance. To fulfill this goal, the following tasks will be solved:

· Conduct a literature analysis to determine the scientific society's opinion on high-tech M&A deals entity and features;

· Identify the difference between high-tech industries in the context of M&A motives;

· Create a hypotheses concerning the M&A performance in different industries based on the literature review;

· Collect and describe the empirical data;

· Conduct a regression analysis and check hypothesis on the empirical data.

The object of the research is high-tech M&A deals in the developed capital markets. The subject of the research - the influence of the acquirer's industry specificity on the high-tech M&A performance.

The scientific novelty of the paper consists of the following aspects:

· Was conducted the comparative analysis of the literature describing the distinctive features of the high-tech M&A deals;

· Was determined the significant features of the high-tech industries and motives that induce acquirers to conduct the deal in the particular industries;

· Was presented empirical evidence of the specific motives' influence;

· Was created a new approach to the M&A performance determinants as the motives for the deal;

· Was introduced the new classification of the M&A performance determinants and method of its selection;

· For the first time was analyzed the high-tech M&A performance comparing the high-tech and non-high-tech acquirers.

The theoretical significance of the paper is that it offers new approaches to the high-tech industries specificity determination and its expression in the high-tech M&A performance determinants. Combined with the new determinants classification, the findings of the paper could be used by the scientific society in the future researches. Also, paper stands in line with other researches and provides actual additional confirmation of the previously obtained results.

Despite the drawbacks of the paper caused by imperfection of the sample, the theoretical conclusions and hypotheses made for the computer/electrical equipment and automotive/aerospace industries might be valuable for the prospects researches. Authors might prove or reject these theoretical findings in the following researches.

The practical significance of the paper consists of the widening the high-tech M&A market understanding, reasoning of separate high-tech and non-high-tech deals consideration and determination of the motives to conduct the deal in high-tech sector. Conducted analysis allows investors to correct the expectation about the high-tech M&A performance and improves the comprehension of such a complex phenomenon as high-tech M&A deal.

In the first chapter of the paper there is conducted the literature analysis. The first part of it is dedicated to the determination of the high-tech M&A deals distinct features and substantiation of the necessity of such deals separate investigation. The second part includes consideration of the high-tech industries specificity, that is described by the motives actuating the acquirers to participate in the deal and its influence on the M&A performance.

The second chapter describes the methodology of the research. In the first half there are considered the issues of event study method for M&A performance calculation. The second half is dedicated to the determinants description that will be used as proxies for hypotheses testing in the regression analysis. Hypotheses determination is also presented in the second chapter. The hypotheses describe the potential influence of the motives on the M&A performance according to the industry specificity.

The last chapter of the paper consists of empirical analysis. The first section is dedicated to the sample description and the practical aspects of the following research. In the second part, regression analysis results is presented. Based on the results there will be given the confirmation or rejection of the hypotheses.

Chapter 1. Literature review

1.1 The differences of high-tech companies' M&A

A “high-tech” M&A deal for the purposes of this research is a merger or acquisition transaction, the target of which is a company whose main activity sphere is a high-tech industry. Notwithstanding the fact that the definition of high-tech industry suffers from a lack of a unified approach, the approaches used are relatively similar. Main SIC code (Standard Industrial Classification created in the UK in 1937 and used worldwide up to date) of the company is used by a multitude of authors (Kwon and Yin, 2006; Mohd, 2005; Katinen, 2002; Davis and Madura, 2017) as a determinant whether the company is related to the high-tech industry or not. Scientists divide the high-tech industries in 5 main groups: computer and electrical equipment, software, medical technology and biotech, communication and electrical equipment. Aforementioned classification is predominantly applied, but some authors eventually use other patterns and add alternative industries to this classification.

Authors compared the high-tech and non-high-tech M&A performance (Davis and Madura, 2017; Rheґaume and Bhabra, 2008; Aybar and Ficici, 2009) and parameters affecting it (Davis and Madura, 2015; Alexandridis, Mavrovitis, and Travlos, 2011; Eliasson, Hansson, and Lindvert, 2017). Davis and Madura (2015) determine that the affiliation of the target with high-tech industry constitutes the significant factor influencing the M&A outcome. This conclusion was confirmed by Alexandridis, Mavrovitis, and Travlos (2011) who studied 3206 deals in the US over the 1993 - 2006 period and found the significant negative influence of high-tech affiliation of the target to the high-tech industry in the deals before the 2000. Aybar and Ficici (2009) who investigated 433 deals happened during the period 1991 - 2004 had been driven to the similar conclusion.

In other researches authors made the attempts to explain the presence of this correlation. Benou and Madura (2005) assumed that the reason of correlation is that the high-tech sector is fraught with an increased level of risk, so the result of the transaction, the further synergy of companies entering the transaction, is less predictable.

The value of the company in high-tech industry relies more on the future than on the present days (Kohers and Kohers, 2000). This fact complexifies the determination of the true company value. Due to the high-tech industrial complexity for the investors, technology companies more frequently face the problem of underfinancing and have limited prospects to realize its potential in the generating of the cash flow (Benou and Madura, 2005). Kohers and Kohers (2000) showed that the high expectation about the advantages of high-tech company acquisition did not justify in the long-term period, and during the three years following the deal, acquirers underperform comparing to the industry. Thus authors conclude that the market perception of high-tech deals is exceedingly optimistic which is directly connected with the growth options possessed by the high-tech company and higher level of uncertainty associated with it prospects.

Puranam (2001) expound the negative performance differently: information asymmetry leads to the higher volatility of the stocks. In this context the shares of the high-tech companies are trading with higher premiums pending to the higher prospects in cash flow creation and synergy. The higher premiums negatively influence the performance of the deals (Alexandris, 2013).

The large role of R&D for high-tech companies also increases the uncertainty associated with their future, because not every R&D result could be commercialized in the foreseeable future. Trigeorgis (2014) claims that high-tech companies have especially uncommonly high level of R&D expenditures and possess unique operational characteristics because of it. The other activities of the company might be tuned in order to support the R&D processes that might influence the current performance of the company and in the long-term period might determine the prospects of the company (Davis and Madura, 2015). Thus, the results obtained by other studies not focusing on high-tech M&A could not be used and this type of deals should be considered separately.

Andres-Alonso et al. (2006) highlights the importance of the knowledge base transfer in high-tech M&A deals. The acquisition of the firm possessing knowledge base is considered to be a useful aid for possible technological progress. Acquirer firm obtains a capability to introduce products with higher quality to the market, or make the processes faster, bring radically new technology to the consumer, eliminate competitive technology or change business process for the purpose of performance increase. (Roller, Stennek & Verboven, 2006; Ornaghi, 2009). Ornaghi (2009) assumes that the R&D acquisition in high-tech M&A deals has positive influence on the long-term firm performance, but acquisition with aim to eliminate competing technology or company from the market does not have prominent impact.

During the last decades the M&A market has changed drastically. Shleifer and Vishny (2003) mention that the prices before 2000 were based on the fundamentals of the firms, and on the value of physical assets, as opposed to the expectations concerning the company's prospects. The behavioral theory that makes acquirers to obtain the less overvalued assets in previous periods is no longer applicable to the modern M&A market of the sixth M&A wave. (Alexandridis, Mavis and Travlos, 2011)

The increased amount of the high-tech M&A deals contributed to this significant change on the market. Alexandridis, Mavis and Travlos (2011) indicate that the affiliation of the target with the high-tech industry has a significant negative effect on the M&A performance of the acquirer.

The reason is that the market valuation of high-tech firms includes the prospects for the intangible assets of the firm and the results of research and development, which the market as a whole tends to overestimate the price of these firms. Authors indicate that high-tech companies which are now in the sixth wave of M&A are overvalued to a greater degree, despite the fact that the authors rely on the concept of market efficiency. The research shows the negative performance of the high-tech M&A deals, because the acquirers are obliged to pay excessively high price to obtain the target.

Previously we have considered the special features of the target company. However, the acquirer characteristics influence the M&A performance as well. M&A deals in high-tech industries are sensitive type of deals due to the extensive influence on the acquirer (Jamison and Sitkin, 1986). Haspeslag and Jamison (1991) claim that such deals violate the acquirer's routine, and lead to the technological delays and failures. Since this types of failures are especially problematic to the firm, the performance of the deal becomes negative (Ahuja and Katila, 2001).

The overwhelming majority of the modern researches are devoted to the M&A performance and determinants that influence the outcome of the deal include acquirer's indicators. (Alexandridis, Mavrovitis, and Travlos, 2011; Davis and Madura, 2015, 2017)

Authors predominantly study the variables showing the financial state of the acquirer, liquidity, amount of assets, R&D expenditures and performance, and array of other factors by which the firm could be described shortly and universally. Consequently, the acquirer characteristics also influence the M&A performance. Davis and Madura (2017) studied 749 M&A deals at the developed capital market during 1986 - 2014 and included the equal amount of target's and acquirer's characteristics into consideration. Mentioned authors also noted the significant influence of acquirer's leverage, cash flow, R&D and growth options on the M&A performance.

Ferreira, Miguel & Massa (2019) concluded that the type of the acquirer (institutional investor or not) influences the performance of the M&A deal through the financial state of the firm and through the premiums paid to the target's price. Other authors such as Park and Ghauri (2011), and Schiffbauera, Siedschlagb and Ruaneb (2017) claim that the foreign origin of the acquirer impacts the possibility and prospects of the deal, because the foreign companies use “cherry picking” strategy and obtain the most effective and prospective firms, thus these deals create value for the acquirer. The size of the company and management style are also the factors that might influence the M&A performance. Moskowitz (2017) confirms that in case when the high-tech companies are operating in the same industry with significantly different management style, the united company might underperform after the deal. Therefore, the type of the acquirer precisely matters for the deal performance.

In the studies dedicated to the high-tech M&A deals the type of the acquirer is usually omitted. The only determinant expanded to the several researches is the relatedness of the acquirer and target. This factor usually describes the situation when the acquirer and the target operate in the same industry. In this situation the high-tech affiliation of the acquirer might be included into consideration only if the acquirer operates in high-tech industry and acquires the company in the same industry. Although, there is an array of the deals that is cross-industrial and where the acquirer is high-tech company. Unfortunately, the amount of researches dedicated to this issue is close to none.

Therefore, the type of the acquirer, its industrial specificity and characteristics influence the M&A performance along with the target's properties. Indication of the deal participant's industry relatedness does not allow sufficiently to take into account the features of the buyer. Also the high-tech deals are different from the non-high-tech M&A deals, that constituted complicated phenomenon that should be considered in more details. This analysis will be conducted in the further section.

Despite the fact, that authors do not resort to direct comparison of the high-tech and non-high-tech deals, there are differences between these types of M&A deals. Besides the previously discussed target specificity and acquirer influence on the M&A performance, researchers indicate different motives for these two groups of deals. Considering the non-high-tech firms, researchers are adducing the array of the motives and intentions motivating firms to enter to the deal: from the tax benefits to the acquisition of effective management board. The motives cover all possible aspects of the company activity.

In the literature dedicated to the high-tech M&A deals Tjahjapranata, and Yap (2006), Andres-Alonso et al. (2006), Davis and Madura (2015) focus on the specific features, most of them center around the possibility of acquiring the existing technology or prospect R&D results and prospective growth options.

Following the Alexandridis, Mavis and Travlos (2011), we assume the market efficiency and in general right perception of the deal and prospect synergy. The main object of the firm existence is to increase its market capitalization and the wealth of the investors. The market players take into consideration the main aim of the firm and the potential motive that the acquirer entering the deal is following by and correctly change the expectations concerning the company's future. Consequently, the share price is changing and the M&A performance could be calculated. The potential M&A outcome is determined by the characteristics of the both companies entering the deal. The importance of each criterion varies depending on the initial motive of the deal and on the industrial specificity.

1.2 Motives of M&A in high-tech industries

While entering into a merger and acquisition deal, companies are considering a number of opportunities - the motives they pursue in the framework of their operational and M&A activities. The main reason for the participation in these transactions is to obtain a positive synergetic effect of companies' cooperation (Porter, 1985). Under the synergy we understand the ability of two or more companies to generate higher value while working together than working separately (Carpenter and Sanders, 2007).

Based on the conducted literature review we have determined that high-tech companies and their mergers and acquisitions have sufficient specificity leading to the necessity to study them separately. This finding naturally pushes the following question: are there fundamental differences within high-tech companies.

Kim (2018) asserts that while considering the M&A performance the specificity level of the industry (author focuses on the industry assets specificity and industry shocks) is playing the significant role. The results of his research push the idea of separate consideration of the high-tech industries. Author contemplates not only high-tech and non-high-tech companies' difference, but also investigates dissimilarity of the industries inside the high-tech sector.

Alexandridis, Mavrovitis, and Travlos (2011), Kim (2018), Davis and Madura (2015) affirm the different performance of the M&A deals across the different industries. Yaghoubi, Locke and Gibb (2012) while studying more than 3000 M&A deals in developed capital market revealed the groundbreaking industry specificity in M&A performance.

Authors argue, that one of the most important distinction between the industries is the motive that drives firms to participate in M&A. The determination of motives allows us in the further analysis to select the determinants that will affect the M&A performance most appropriately.

Despite the fact, that the amount of deals in high-tech field have risen during the last two decades, the number of the researches dedicated to the M&A performance in the specific industry has not been rising accordingly. Previously, the researches focusing on the difference in the motives for high-tech M&A deals among the industries have not been made. However, while investigating the subject several researches dedicated to the particular industries as well as practical reports from consulting and research companies were found. In this paper, the comparative analysis of the high-tech M&A deals for particular industries would be conducted for the first time.

The motives for the M&A deal derived by the researchers could be combined in three groups: strategic, operational and organizational. The first group consists of the following motives: increase in the scale of operations (Berk DeMarco, 2013); obtaining the new R&D results and know-hows (Capron, 1999) and increase in R&D efficiency (Roller, Stennek & Verboven, 2006; Ornaghi, 2009); capture of the market share/new market (Rizvi, 2008; Gopinath, 2003) as well as entry to the new market or segment (Jost & Velden, 2008; Gopinath, 2003); diversification (Garrone and Veugelers, 2005) and growth (Grieco, Pinkse & Slade, 2018).

Operational motives are not as diverse as previous and include cost reduction (Stiebale, 2014), tax benefits (Liu, Mukherjee & Wang, 2015), increase in market capitalization (Ahuja & Katila, 2001) and acquisition for the following resale with increase in the value of the company (Rhodes-Kropf and Robinson, 2005).

The last group of motives are organizational. The influence of this type of motives is quite complex to measure and it is rather hard to predict its influence on the M&A performance. However, for some companies this might appear to be the substantial motive (Lendel, 2017). In this group the following motives might be included: acquisition of human resources (Owen & Yawson, 2010) and effective management board (Guo at all, 2018).

These motives are general and applicable to any company. However, while considering mergers and acquisitions in high-tech industries, researchers pay attention to particular strategic and operational motives. The most important motives are associated with conducted R&D and its results, the potential of their application results in growth options. Operational motives in high-tech M&A deals are represented by the cost reduction due to the increase of scale of operations and the application of new operating models.

Investigating the importance of motives for high-tech M&A deals we appeal to the specificity of the companies in this sphere. The greater level of risk associated with industry is correlated with the higher level of acquirer cautiousness in target selection. Thus, the deal should fulfill the expectations and particular initial motives, that makes deal motives a touchstone of the high-tech M&A. The importance of each motive diverge from industry to industry and is determined by the needs of the acquirer and by the specificity of the industry itself.

Medical technology and biotech

Among the other high-tech industries this is the most investigated. The reason behind it is that the deals associated with medical technologies and biotech are characterized by the highest transaction values and by the immense number of M&A.

Authors mention that the R&D conducted by firms, created know-hows and technologies, plays the significant role in this type of M&A. Ornaghi (2009) indicates that the intensity of R&D is the main dimension in which companies compete in this industry and the main factor that contributes in the firm's success and the potential market position. The importance of the R&D factor for this industry is also confirmed by the fact that the R&D to revenue rate is one of the highest among the other industries in the developed capital markets (Haucap, Rasch and Stiebale, 2019).

Bena (2014) claims that the most significant for the acquirer in order to initiate the M&A in medical technologies and biotech industry is the scale of conducted by target R&D projects. Thus, author affirms that M&A is the instrument to obtain the critical mass of in-house clinical researches that allows to effectively create the new product and bring it to the market. This point of view is also supported by Higgins and Rodriguez (2005) and Haucap, Rasch and Stiebale (2019). Eisenman and Paruchuri (2019) assume that this motive is the most important in the mergers of pharmaceuticals market because it allows to transfer the knowledge base and partly substitute the acquirer R&D activity in order to achieve the similar results. The acquirer's resources in this case could be used more efficiently.

Besides the importance of the R&D scale, Eisenman and Paruchuri (2019) indicate the importance of the knowledge base transfer to the market in a form of a new product or improvements made to the existing ones. Davis and Madura (2017) measure this capability by the growth option index, that represents connection of the R&D expenses and the market value of the company minus the assets in place. This approach indicates the external valuation of conducted research and developments contribution to the company's activity, market position and prospects of the future growth representing by exceedance of market value of the company over assets. Based on the idea of the critical mass of R&D gain for the acquirer, the growth options of this deal side contribute to the M&A performance. The motive in this case represents the feature of the acquirer to transfer the value of R&D expenses to the market capitalization in the most efficient way.

Other motive designated by Ornaghi (2009) is the volume of operation of such companies translating into its access to the customers and distribution channels, operational efficiency. The economy of scale as the motive for pharmaceutical and biotech industries is also mentioned by Danzon, Epstein and Nicholson (2007).

In the conducted researches there was not found whether M&A deals created the value, because the results are controversial. Higgins and Rodriguez (2005) claim that the abnormal return for these deals was positive for both acquirer (3, 9%) and target (16%). This conclusion was made by investigating the 60 transactions from 1994 to 2001 in the US market. Ravenscraft and Long (2000) found out that despite the positive return for the target company (approximately 13,3%), the result for the acquirer was negative and constituted -2,1%, but was not significantly different from zero. In order to deduce this finding authors studied 65 mergers during 1985 - 1996 in the US. Danzon, Epstein and Nicholson (2007) investigated 165 deals over $500 mln in the developed capital markets from 1988 to 2000. They found no evidence of positive significant impact of conducted mergers on companies' performance.

To conclude, at the medical technology and biotech industry the most important motive for M&A is the potential economy of scale, amount of conducted R&D and capability of acquirer growth options employment. The consensus on the average result of the deal was not reached by the authors - while some of them determine the positive significant average return, others claim that the average result is negative and insignificant. The considered results possess two drawbacks. Firstly, Ravenscraft and Long (2000) draw a conclusion based on the small sample. Secondly, the deals investigated happened before 2000 and the results are not applicable to the current date due to the market transformation and M&A wave change.

Communications

Authors studying the communication sphere of M&A deals usually derive three main motives for the deal realization. The first one is strategic motive: increase the scale of operations and market presence expansion. This motive was marked as the dominant by Dehninga, Richardsonb, and Stratopoulosc (2005) and Akrofi (2014). Akrofi (2014) additionally detaches several aspects of the scale acquisition. Among the most important motives he highlights entering in the new geographic or product market and obtaining the economy of scale. Quite apart from the fact that these motives have different nature and serves various goals of the company, they could be generalized by the concept of scale acquisition. Hahn and Kim (2016) affirm that dominate motive for M&A deals in this industry is an increase in profitability, but in the way this reason is corresponding with previous cause of increase in the amount of operation scale and of the market share. Authors claim that the consolidation of the market power leads to the increase in prices and the increase in profitability. Spector (2007) mentions the impact of the governmental regulation of the industry which allows or prohibits the expansion of this type of company.

Another motive, commonly derived by authors, is the desire of the companies in communication industry to diversify (Cloodt, Hagedoorn and Kranenburg (2006); Li (2005); Kohers and Kohers (2001)). Kohers and Kohers (2001) found that acquirer in the communication industry that conducted the deal with target in the similar industry performs less well than comparable firm.

Rheґaume and Bhabra (2008) dedicated to the theme of M&A performance of communication industry and obtained the opposite results. For their research they chosen the several narrow event windows from 1 to 3 days wide and cumulative abnormal return approach. Authors studied the 3 groups of companies in information-based industries, while only two of which were high-tech, according to the SIC codes description of the groups. Researchers found that related acquisitions create value and gain significant positive cumulative abnormal return.

Rheґaume and Bhabra (2008) indicate the positive average significant abnormal return of the deals. Researchers investigated 2421 deals during 1993 - 2005 in the developed capital markets as exemplified by the US and noticed a positive and significant return in communication (0.92%) and communication equipment (0.72%) on the 3 days (-1;+1) event window.

Comparable results were obtained by Okoeguale and Loveland (2017) who researched 126 mergers in the US from 1980 to 2009. Authors found positive and significant acquirer abnormal return for the deals (1.47%).

Finally, the acquisition of scale and aspiration of the companies to diversified the cash flow are the most important reasons that motivate companies in communication industry to conduct the M&A deals. In general, these transactions have positive impact on the company's perception on the market that expressed in the positive abnormal returns for the deals.

Software

In contrast with the two previous industries the number of researches dedicated to the software industry is quite low. Authors usually emphasize the two main factors for the M&A deals in software industry. The first one is knowledge acquisition (Davis and Madura, 2015). Morton and Shapiro (2014) notice that in the last decades the intellectual property not only separated from the other assets, but also became the crucial possession for the software company to succeed, that appears as important motive in M&A activity for this industry.

The acquirer company's aim in such deal is to obtain the new technology. In this framework companies try to develop a digital strategy. In order to fulfil it, the obtained company's technology can be used to develop the acquirer's product or to create a new offer to the market; can be applied to improve buyer's operations or business processes; or can be eliminated from the market in order to exclude cannibalization of the existing products (Goedhart, Koller, and Wessels, 2010).

There is a difference in the role of R&D as a motive for M&A deals in the medical technology/biotech and software industries. In the medical technology industry the most important factor is R&D scale, thus the R&D expenses of the target and the acquirer are contributing. In the software industry the R&D acquisition becomes the motive and the dependence of potential synergy from the buyers R&D was not considered.

The commercialization of the R&D results which ensure the increase in market capitalization is vital for the software industry. Firstly, the companies are rarely focus on the fundamental researches, initially intending to commercialized expenses. Secondly, the success of the implementation of the created technology depends on the company's unique features, management capabilities, because the development is based frequently on the incremental innovation and can be copied by the competitors. Target's capability to implicate the obtained R&D results into the market activity is crucial in the software industry, so the companies with this feature consider to be an amiable target (Moskowitz, 2017).

Due to the high growth rate of the software industry in the last decade market players demonstrate particular interest for this sector that leads to the higher demand (Gartner, 2019). It has an impact on the prices of software companies shares that trade with higher premiums. In this situation, the market value of the firms rising that contributes to the higher growth options measured by the technique of Davis and Maduro (2017). According to Alexandridis, Mavrovitis, and Travlos (2011), it leads to lower M&A performance. Thus, the software industry acquirers attempt to obtain the company with a lower level of growth options in order not to pay overstated price.

Other motive that stimulates companies in the software industry to conduct M&A is the acquisition of scale of operations. There are two main aspects in this point: to widen the number of clients and to add realization channels and an attempt to eliminate the competing technology from the market (Goedhart, Koller, and Wessels, 2010).

Akhigbe and Martin (2002) investigating the M&A performance in software industry indicate that the deals in general leads to the negative CARs, but the result is insignificant. However, due to the fact that research was conducted based on the data before 2000 and software industry has undergone significant changes after the date, we cannot rely entirely on these findings and anticipate negative M&A performance.

At the conclusion, the main motives for the firm in the software industry to became the acquirer are to obtain the conducted R&D and its results, not to overpay for the growth options of the target, and increase the scale of operation.

Computer and electrical equipment

These two industries are considered as distinct by the classification, but their common features allow us to unite them in one group. Studying research by Stennek and Verboven (2000) and presented cases showed that companies in computer and electrical equipment industries have similar motives to be engaged in M&A as an acquirer.

In M&A deals companies in computer and electrical equipment industries pursue the goal to acquire R&D results. Firms pursue this goal in order to implement R&D into the operational activity to create new or improve the existing product or update the business processes.

This idea was approved by the Blonigen and Taylor (2003). Authors found out that companies in computer and electrical equipment industries are striving to obtain targets with the higher level of R&D. This motive authors marked as the most important and significant. Ceteris paribus company are more likely to conduct M&A as an acquirer if it has lower level of R&D. Thus, the companies are obtaining the R&D scale in order to decrease the necessity of its own current R&D and to increase the efficiency of this activity. This conclusion was made by the investigating 217 deals of electronic and electrical equipment production companies in the US in 1985 - 1993.

From the other perspective, companies in computer and electrical equipment industries are motivated by the possible increase in the efficiency of operation. This goal might be achieved by the adopting of the existing efficient operations patterns and by the inclusion of the other more profitable company in the current business.

Yaghoubi, Locke and Gibb (2012) in their research dedicated to the connection of industry and M&A performance studied 3101 deals during the 1981 - 2007 in the US and emphasize the relatively small amount of the deals in this industry. Authors found that M&A has insignificant negative effect on the acquirer's performance. The findings demonstrate that these industries claim for the additional investigation, however, there are not many papers dedicated to the subject.

Automotive and aerospace

As for the companies discussed above in the previous groups the number of researches for automotive and aerospace is exceedingly low. It is also accompanied by the small samples in the researches for these industries (Yaghoubi, Locke and Gibb, 2012). The authors who have investigated the M&A motives for this companies (Mergers & Acquisitions Review 2018, 2019) highlighted the importance of the empire building issue. Laabs and Schiereck (2010) conducted the research in this field by studying the 230 deals from 1981 to 2007 in developed capital market considering the Germany as an example. Authors found that in general acquirers in automotive industry in the short event window (authors investigated 11 different windows from 1 to 41 days long) obtain the significant and positive abnormal return.

The motives determined for each industry have significant limitations. Firstly, the authors derive it by overlooking the industry in general, thus it might not be suitable for the particular M&A deal or the motives determined as the most important might not be as crucial for the specific deal. Secondly, the M&A deal is a complex procedure, influenced by the array of factors from the micro level of the firms to macro conditions. Consequently, the motives determined for particular industry are not exhaustive, but only the ones' authors pointed as the most important, and that subsequently would be the base for the hypothesis formation for the specific industries and would be tested further in the paper by regression analysis.

To sum up, the high-tech M&A deals have several features that detach them from the other deals. These differences include consequences of the high-tech companies' specificity. Firstly, future based valuation of the high-tech firms leads to the deviation of the true value of the company. Secondly, there is a specific role of the R&D process and its results on the company's performance. Also, the prospects of this R&D results implementation are not predetermined, thus, they increase the uncertainty level of firms' prospects. Thirdly, high-tech firms more often face the problem of underfinancing that reduces the opportunities for the full realization of their potential. These factors together stipulate the influence of target's high-tech affiliation on acquirer M&A performance.

The acquirer's type also has an impact on the M&A performance. Many authors recognize this influence, although the issue is generally under-researched. In general, high-tech transactions is a specific and complex concept. Therefore, this point should be studied separately in more detail with consideration for the acquirer's specificity.

In the second part of this chapter we identified the differences between the M&A deals in high-tech industries by the main motives of transaction conduction. For the medical technology and biotech industries the main motives are: the synergy of R&D, acquisition of scale of operations and acquirer's growth options employment, for communication industry - acquisition of scale of operations, for software industry - R&D, scale of operations and relatively low rated by the market at the time of the deal target's growth options, computer and electrical equipment industries acquire the R&D and efficiency in operations and for automotive and aerospace industries the main motive is the empire building.

Chapter 2. Methodology and hypotheses

2.1 Analysis of the change in abnormal returns

In the literature, the most commonly used method of M&A performance evaluation is the determination of the change in abnormal returns. First of all, it is necessary to define the concept of abnormal return. The abnormal return is the difference between the actual and normal return of security over the event window (Mackinlay, 1997). The values of abnormal return are calculated for the defined event window and after summed to obtain the value of Cumulative abnormal return (CAR) that is used for the determination of the M&A performance. (Fama & French, 1993)

AR_it = R_it - E(R_it)

AR_it - abnormal return for firm i on day t

R_it - actual return for firm i on day t

E(R_it) - expected return for firm i on day t

CAr_it = ,

where

the N - the number of days in the event window

During the calculation, two factors might have an impact on the final result: event-window length and the basis chosen as an expected return for the day.

Event window

The Analysis of the change in abnormal returns on a short-term time interval al is the most common method used in the empirical researches. Authors have different approaches to event window length determination. In the researches was used the periods consist of 1-2 days (Laabs and Schiereck, 2010), 3 days (Shah & Parvinder, 2014), 9 days (Nagano & Yuan, 2013), 11 days (Gubbi, 2010), 21 days (Aybar & Ficici, 2009).

The time spans that authors use while applying the long event window usually varies from 1 year to 3 years (Yaghoubi, Locke and Gibb, 2012), some researches applied 9 years event window (Fowler & Schmidt, 1989). Yaghoubi, Locke, and Gibb (2012) investigated the CAR for different industries, including high-tech, and found that for some of them CARs were significant: positive for pharmaceuticals and negative for telecommunications.

Change in abnormal returns on the short event window is the most frequently used method for measurement of M&A performance (Rani and Yadav, 2012). Authors resort to the CAR calculation for the short term event window due to several positive aspects of the method. The first one is the simplicity of the methodology. The data is available for all publicly traded companies. Furthermore, this method allows determining the change in the shareholders' wealth as a result of an M&A deal. (Cannella & Hambrick, 1993). Secondly, the amount of data needed is relatively low comparing to the long event window. Significant impact on the deal results has the possible opportunities for technology development and its marketization prospects. Unfortunately, no method allows certainly to calculate the future results, thus the market valuation is the most objective available information for the researcher. This expectation is the representation of the company's prospects through the spectacle of the market participants experience.

Researches proceed from the premise that the market is efficient, thus the potential synergy of the companies engaging in the deal would be evaluated to the fullest extent possible. The M&A is not the only event that might influence the company's value, thus while considering the short period for CAR calculation the influence of other issues is descent because they are not included in the considered time slot.

Despite the positive aspects of the method mentioned above, it receives criticism. Montgomery and Wilson (1986) emphasize that the method measures the anticipation of the market players concerning the deal, not the actual performance. Not every significant factor that could influence the effectiveness of the deal is taken into account (Hatem, 2015). The quality information is available only for public companies (Sachin, Wiles, and Mishra, 2015).

Normal return

In choosing the base for expected returns, authors usually apply one of the following approaches. The methods implicate appliance of the index return in the match jurisdiction. For developed capital markets and the USA in particular usually applied the NYSE, Nasdaq, or S&P 500 indexes. The selection based on the author's judgment and assumptions, the sample specificity or by the fact in which of the indexes the firm is represented. Authors evaluate the regression model:

E(R_it) = б + в_i*r_m,t,

Where

r_m,t, - is the market return.

Another form of this approach consists in index model regression analysis.

E(R_it) = б + в₁*I_1,t + … + в_n*I_n,t

Where

I - is index return.

For the regression analysis typically chosen the 120 trading days' prior to the deal event window. Davis and Madura (2015) and Rheґaume and Bhabra (2008) applied the modification of this method. Authors obtain the beta for each company that had already calculated by the market information system and multiply it by the chosen index return. Thus they found the base for the M&A CAR comparison - normal return.

The subject of M&A performance

The M&A deal implies the participation of at least 2 sides, thus the performance could be measured for both of them. Shah and Arora (2014) highlight that for target company CAR are usually positive, that connected with higher premiums paid for control acquisition during the M&A that consequently increase the price of the shares and eventually leads to positive CAR in the researches.

For the acquirer company, the question of the value creation through M&A is controversial. Many authors find evidence that M&A deals destroy the value and as a result, the CAR is negative. For example, this result was obtained by Schoenberg (2006). Sudarsanam and Mahate (2006) indicates that the CAR for the acquirer company was not only negative but also insignificant, thus the M&A performance, in general, is not determined. The rationale behind this is that the deals on the whole market are protuberantly different from one another, so there is no basis for anticipating that the expectations of the market players would be similar. The possible solution to this problem is to investigate the deals divided into the specific groups and study the outcome of the more homogeneous groups of M&A. The acquirer's M&A performance to a greater extent is determined by the expectation of the market concerning the synergy of the combined firm and its prospects in the future. Therefore, this measure, in an ultimate way, serves the purpose of the study - to investigate the M&A performance.

Empirical researches indicate that high-tech M&A deal has more determined performance. It is true at least for the researchers conducted for medical equipment/biotech and communication industries, partly investigated spheres of high-tech M&A. In the medical equipment/biotech industry Higgins and Rodriguez (2005) found the significant positive performance of the deals for the acquirer. Ravenscraft and Long (2000) investigated the same sphere to discover the significant negative performance of M&A. The difference in findings might be explained by the distinct time spans considered by the authors and natural changes in the M&A market and developed markets' economy (Alexandridis, Mavrovitis, and Travlos, 2011). Rheґaume and Bhabra (2008) studied communication industry also found the significant positive CAR values for the deal. Thus, based on the previous researches we might conclude that the deals in particular high-tech industry possess the higher level of homogeneity to compare to the pool of all deals, that leads to the more significant results and further practical usefulness.