THE ROLE OF THE PRESENCE OF CHIEF OPERATING OFFICER

THE SHAREHOLDER BENEFITS OF VERTICAL MERGER AND ACQUISITION:

THE ROLE OF THE PRESENCE OF CHIEF OPERATING OFFICER

Master’s Thesis, MSc Supply Chain Management University of Groningen, Faculty of Economics and Business

January 25, 2021

FILIP FILIPOV Student number: S3152537 e-mail: f.v.filipov@student.rug.nl

Supervisor dr. X. (Bruce) Tong

Co-assessor

dr. J.A.C. (Jos) Bokhorst

Abstract

Recent academic literature views supply chain integration as value creating and a way to achieve it is by consolidating parts of the supply chain. This paper investigates the shareholder benefits of vertical mergers & acquisitions and the moderating effect of a dedicated COO. The shareholder value effects are calculated based on the market reaction of the M&A announcement using event study methodology to estimate the abnormal returns for samples of upstream and downstream vertical M&As during 2003-2017. There are significant abnormal returns of 0.90%

in the case of upstream vertical mergers & acquisitions and small or insignificant ones in the case

of downstream ones. Having a dedicated COO is found to positively moderate the shareholder

effect of the vertical M&As only in the case of upstream M&As. I also find that firms with

higher operational efficiency and leverage benefit more from vertical M&As.

Table of Contents:

1. Introduction ……….4

2. Theoretical background………...………...7

2.1 Vertical mergers & acquisitions………....………...7

2.2 Chief Operating Officer………...………....8

2.3 Vertical mergers & acquisitions with Chief Operating Officer…..………10

3. Hypotheses………...………..10

3.1 Impact of vertical mergers & acquisitions on shareholder value……….…..…………...10

3.2 Chief Operating Officer and vertical mergers & acquisitions………....…………...11

4. Methodology………….……….………..………..12

4.1 Data Collection……… …….12

4.2 Research Design………13

4.3 Control variables………..…….15

5. Results……….……….……….……….17

6. Discussion…..………….……….……….……….22

6.1 Summary of results…..………….……...……….……….22

6.2 Discussion of results and implications……….……….……….22

6.3 Managerial implications………..………….……….……….24

7. Limitations and future research…………..….……….……….24

8. References………..………25

9. Appendix………..…………..………31

1. Introduction

Since globalization started in the 1980s, companies have outsourced a large part of their operations overseas, creating long and complex supply chains in search of lower production costs (Baldwin, 2012). However, supply chain (vertical) integration, which integrates different stages of the value-chain, is also argued to be beneficial and it can be achieved by close collaboration with the buyer/supplier (Mitra and Singhal, 2008). One way of doing this is by vertically integrating the buyer/supplier of the firm via vertical merger or acquisition (V-M&A). The basic rationale behind all types of M&As (conglomerate, horizontal and vertical) is to create shareholder value via synergies, improved bargaining power and risk diversification (Tuch and O’Sullivan, 2007). However, M&As usually fail to bring wealth to the shareholders, with the failure rate being somewhere between 30% (Bruner, 2002) and 70-90% (Christensen et al., 2011). According to Tuch and O’Sullivan (2007), most studies conclude that M&As result in either significant negative abnormal returns or insignificant ones. However, when distinguishing between the types of M&As, V-M&As seem to be positively related with shareholder value (Maquieira et al., 1998; Walker, 2000; Healy et al., 1992). A possible explanation for this phenomenon is that investors expect vertical M&As to benefit more from economies of scale and scope compared to diversifying ones (Singh and Montgomery, 1987).

This study focuses on vertical M&As, which are a specific type of investment where two companies merge or an acquirer (buyer/supplier) buys the target firm (supplier/buyer). Unlike horizontal M&As where firm acquires a competitor operating in the same market or conglomerate ones where a firm from unrelated industry is acquired, V-M&As are used to consolidate the firms’ supply chain by acquiring a buyer or supplier of the focal firm. The rationale behind V-M&As is gaining efficiencies such as economies of scale and eliminating redundant facilities, resulting in competitive advantage (Maksimovic and Phillips, 2001).

Nowadays supply chains are long and complex, thus vertical M&A may reduce information

asymmetry and help communicate customers’ demands upstream, both of which are becoming

increasingly important in recent years (Guan and Rehme, 2012). Therefore, V-M&As are

becoming more important and beneficial to investors as they are likely to generate shareholder

value. However, the downside of vertical M&As is that the operations of the target company

needs to be consolidated, resulting in even longer and more complex internal supply chains,

which in turn requires additional managerial resources. For example, if a supplier that produces steel is acquired, the acquirer will have to manage the supplier’s operations as well as their suppliers of ore, effectively controlling another tier of the supply chain. Moreover, some processes need to be tailored to better fit the needs and strategy of the acquirer in order to benefit from the generated synergies.

The majority of literature focuses on the horizontal M&As and not many investigate how vertical M&As influence shareholder value. Most studies agree that M&As between companies operating in the same or related industries are more beneficial than M&As unrelated ones, but more should be done specifically for vertical M&As, using more recent dataset. Therefore, the first aim of this study is to investigate the effect of vertical M&A on shareholder value by answering the following research question:

Q1: Do vertical mergers & acquisitions increase shareholder value?

Considering the high failure rate of mergers and the complexity of running a vertically integrated firm, it might be beneficial to have a top-tier manager with experience and knowledge of operations and supply chain management (SCM), such as the Chief Operating Officer (COO).

COOs are often referred to as the number two in the organization and are usually taking care of

operations on behalf of the CEO (Bennett and Miles, 2006; Vancil, 1987), so that he/she can

focus more on strategy and the direction of the company. Nevertheless, the COO role is different

than that of an Operations Manager since the latter is not necessarily part of the Top

Management Team (TMT) and usually not as close to the CEO. Moreover, the C-suite position

of the COO can ensure that the operations of the post-merger company are considered when

formulating the strategy for the M&A and help identify candidates for which vertical integration

is easier to achieve. Although some COOs are appointed only to inherit the role of the CEO (heir

apparent), the position is primarily responsible for the internal operations of the company

(Bennett and Miles, 2006; Hambrick and Cannella, 2004). Considering the operational nature of

the role and its proximity to the CEO as a top-tier executive, it is likely that having a COO will

be beneficial when vertically integrating parts of the company’s supply chain. Moreover, as

firms grow and their operations become more complex, the workload of the CEO increases

which is why many big companies have a COO to run the day-to-day operations (Crainer and Dearlove, 2003).

Companies with a specific TMT member (different than the CEO) responsible for operations such as the COO should be better able to tap into the expected synergies and create more value out of a vertical M&A. However, Hambrick and Cannella (2004) argue that having both a CEO and a COO usually results in lower firm performance. Nevertheless, most studies focus on the effect on shareholders’ value when appointing a COO and it is unknown if there are shareholder benefits of having a COO in the case of vertical M&As. Therefore, in order to bring clarity, the second aim of this paper is to investigate if there are benefits of having a COO when vertically integrating the firm’s supply chain. This will be done by investigating vertical integration by means of a vertical M&A as COOs can bring value by providing guidance based on their operational expertise, as well as implementing the necessary changes. Therefore, the second research question that this paper answers is:

Q2: Does a Chief Operating Officer help increase firm performance after a vertical merger

& acquisition within a supply chain?

The outcome of this study brings more insights into the benefits of vertical M&As, as well as the

COO, by showing whether he or she can bring more value out of vertical integration. Moreover,

it is beneficial for practitioners as it may show the importance of having a specialist in the area of

operations and SCM to assist CEO’s with the task of running a vertically integrated firm. The

results also provide insights of the benefits of having a COO in a setting previously unexplored

by researchers such as the V-M&As. By controlling for several factors such as firm size,

competition and operations complexity, the outcome of this study will be able to show in which

cases COOs are more (less) beneficial. It will also show quantitative evidence of the value that

COOs can bring in such cases, which can help investors’ evaluation of such events. The

organization of this paper is as follows. The next section discusses the current literature on

M&As and V-M&As as well as the roles of the COO, followed by the Hypotheses section where

the underlying hypotheses are developed and the Methodology section where I explain how I

tested them. After that, the results of the research are be presented and discussed. The last section

draws conclusions based on the results along with discussion about the limitations of this study

and future research directions.

2. Theoretical background

2.1 Vertical mergers & acquisitions

The main rationale for M&As is the creation of shareholder value. It can be achieved by greater synergies or replacement of underperforming managers (Tuch and O’Sullivan, 2007). However, the research of past decades mostly argues the opposite. Smith and Kim (1994) and Dodd (1980) conclude that firms experience negative short-term abnormal returns of -0.23%, while Sudarsanam and Mahate (2003) argue that the bidder losses are between -1.39% and -1.47%, respectively. However, Franks and Harris (1989) find positive results from M&As but their sample dates back to the 1950s when acquirers’ shareholders benefited more (Bradley et al.

1988; Bruner 2002). Long-term results also tend to be negative or insignificant for the acquirers with the values ranging from -8.15% (Gregory, 1997) and -14.96% (Limmack, 1991) 24 months after the announcement day. According to Christensen et al. (2011), the two primary reasons why 70%-90% of mergers fail are because of improper evaluation and/or failure to integrate the two companies. Nevertheless, M&As between companies that are industrially related (V-M&As) experience positive abnormal returns (Walker, 2000; Sudarsanam et al., 1996) and improved cash flows (Healy et al., 1992).

Vertical (supply chain) M&As are present when a buyer acquires a supplier or vice versa, which can be treated as a supply chain phenomenon of vertical integration, defined as “vertical financial ownership” by Guan and Rehme (2012). Therefore, the formal definition for vertical integration used in this paper is “the overall scope of different business activities in a supply chain brought under the management of a single company”, as suggested by Majumdar and Ramaswamy (1994). Vertical integration can be viewed as a step towards supply chain integration (Stonebraker and Liao, 2006), where vertical integration relates to integrating at least two parts of the supply chain and supply chain integration involves the entire value chain. It can also be viewed as an extreme form of vertical supply chain collaboration (Hobbs and Young, 2000), but this view omits the fact that the business units operate under the same company. The basic rationale for vertical integration via M&As is removing the double marginalization by not paying mark-up that is due if the merged companies were operating as separate entities.

However, Guan and Rehme (2012) argue that there are other reasons which are not related to

Transaction Cost Economics (TCE), such as benefits from differentiation, information about customers and supply chain visibility. Other rationale for such supply chain integration includes the reduced inventory cost, higher capacity utilization and faster product development due to the improved flow of goods and services between the two companies (Goold & Campbell, 1998).

While there are many reasons why a company should vertically integrate its supply chain, the extent to which the firm will be able to extract those benefits depends on its ability to implement supply chain practices (Richey et al., 2009; Bai et al., 2020).

2.2 Chief Operating Officer

The Chief Operating Officer is usually a member of the Top Management Team (TMT) that may have many roles in the organization as the firm’s motive for appointing one varies (Bennett and Miles, 2016; Crainer and Dearlove, 2003). They argue that the role of the modern day COO requires both operational and supply chain knowledge and that it is “nearly ubiquitous in operationally intensive businesses” (Bennett and Miles, 2016; p.7). For a vertically integrated manufacturer such as Seagate Technologies, the “complexity of managing a vertically integrated global manufacturing enterprise while simultaneously satisfying numerous external commitments placed on a CEO sometimes takes two sets of hands” (Bennett and Miles, 2016;

p.7), suggesting that the COO is essential for firm’s performance for large companies with complex supply chain and operations. The responsibilities of the COO are strategy implementation, resource allocation, monitoring and motivation of employees, as well as handling disruptions and solving problems within the organization (Hambrick and Cannella, 2004). Hambrick and Cannella (2004) found that very large companies have higher Return on Assets (ROA) when there is a COO, but also that CEOs that have a COO underperform compared to CEOs who don’t. Therefore, COOs should be more beneficial in cases such as vertical M&As where the company expands and operational complexity increases since the COO responsibilities are tightly related to the challenges that come with it.

Companies usually appoint COOs from within the company to run operations for which

operational expertise is required, but for some the reason is a need for radical change, thus

external COOs are hired since they can bring new ideas and practices. Bob Herbold’s

appointment at Microsoft in 1994 is probably the best example of such an external COO as he

managed to bring structure to the company and operational discipline (Crainer and Dearlove,

2003; Herbold, 2002), as a result contributing significantly during his 7 years of service as a COO. Bennett and Miles (2016) describe such COO as a change agent, hired to take care of operations and provide structure to the organization. Companies can have different needs from their COOs and that is why it is hard to precisely define the role. For example, Microsoft needed operational discipline, Intel used the COO to train a new CEO and Seagate Technologies simply needed another pair of hands to run operations. Apart from the value that COOs can bring due to their operational knowledge, they can also facilitate TMT-level information processing benefits which in turn increase operational performance (Marcel, 2009). All in all, the reason for which the role exists is because they bring value to the company and not due to corporate fashion (Crainer and Dearlove, 2003).

Nevertheless, the CEO/COO setup separates strategy formulation and implementation which might result in lower performance (Abelson, 1999), increasing cost and bureaucracy (Murray, 2000) and reduce the effectiveness of the CEO as an organization leader (Mintzberg, 1973;

Charan and Colvin, 1999). All in all, one cannot pinpoint the exact role of the COO as they are many, all of which are related to operations management. Considering that operational knowledge is the core that every COO needs, it is likely that the role can generate value in events such as vertical M&As.

2.3 Vertically integrating the firm’s supply chain with an appointed COO

Given that the source of benefits from vertical integration are largely related to operations and SCM, it is likely that managers with experience in operations and SCM such as the COO bring more value to the more complex, vertically integrated firm. Bai et al. (2020) argue that management practices can increase post-merger value and the effect is larger when the acquirer has more incentives and ability to implement structured management practices. Moreover, it was recently found that acquirers’ CEO with an experience in the target’s industry supply chain earn 1,5% more merger announcement returns (Fich & Nguyen, 2020), meaning that supply chain knowledge is found to be positively related to operational performance and profitability.

Nevertheless, organizations differ in many aspects which have to be considered when looking at

the value of the COO. For example, firms operating in more challenging environments have

stronger incentives to “achieve organizational rather than functional goals as well as establishing

supply chain-wide objectives, rather than narrow, single firm-focused goals” (Richey et al., 2009:836,837) since it is crucial for the firm's performance. Therefore, firms under pressure will have the incentive and need to create more shareholder value (by means of a vertical M&A) and such firms are likely to benefit more from having a COO. After a vertical M&A, firms grow in size and the complexity of in-house operations increases as well, putting pressure on the CEO if the company has no COO to help. As previously found, very large companies benefit from having a CEO/COO duo at the top (Hambrick and Cannella, 2004), which is mainly due to the complexity of operations (Bennett and Miles, 2016).

Figure 1 below presents the conceptual framework of this study. As discussed above, vertical M&As are expected to generate value so in the model this variable is positively related to shareholder value. The COO is expected to positively moderate the relationship between vertical M&As and shareholder value due to their operational expertise.

Figure 1 - Conceptual framework

3. Hypotheses

3.1 Impact of vertical mergers & acquisitions on shareholders’ value

The main reason why companies engage in vertical M&As is to improve performance by gaining

competitive advantage, resulting in increased shareholder value. There are many ways to benefit

from vertical integration such as securing key resources as well as deterring competitors’ access

to those (Hastings & Gilbert, 2005). A similar motive to acquire a supplier is the development of

specific products only for the company and not for competitors (Kedia et al., 2011). Another

reason that also relates to the external environment of the company is customer satisfaction (Guan & Rehme, 2012), as it is important to satisfy different customer demands in terms of product quality and waiting time. Vertical integration can also help increase the efficiency of internal operations by information sharing which in turn increases supply chain visibility (Guan

& Rehme, 2012). For example, production facilities can optimize the production plan after receiving more information about customer demands and/or warehouse capacities. Management will also be able to better understand the firm’s supply chain and optimize it by gaining data of the target company’s operations and costs. Last but not least, the elimination of mark-up from transactions between the two companies can improve the financial performance of the vertically integrated company. Therefore, I expect that vertical M&As have a positive relationship with shareholder value as indicated in hypothesis 1:

Hypothesis 1: Vertical merger & acquisition within the firm’s supply chain is positively related to shareholder value.

3.2 Chief Operating Officer and vertical mergers & acquisitions

Most of the synergies that arise from vertical M&As depend on the ability of management to

realize them. In order to improve the operations of the vertically integrated company,

management needs to identify key processes of the target firm that have to be synced with

existing operations (Richey et al., 2009). The change requires extensive operational knowledge

as it is important to distinguish between value and non-value added activities, which is the key

for implementing a successful integration strategy along with efficient resource allocation

between the different business units, especially to the recently acquired ones. The operational

knowledge of the COO should help facilitate the integration of operations and the efficient

resource allocation needed for change. Moreover, some COOs are specifically hired for change

management (Bennett and Miles, 2016), meaning that they are likely to be able to come up with

strategies to integrate both the operations and the employees of the target company. Apart from

the personal capabilities of the COO, the role is found to be beneficial as it fosters TMT

information sharing and processing (Marcel, 2009). TMT members can feel free to oppose the

COO when discussing an important topic as he or she might not have the authority to dismiss

them. Moreover, the COO can be used as a deliverer of bad news to the CEO and start a

discussion with him/her about strategic choices. Therefore, COOs can also be beneficial in the selection of potential targets by promoting TMT discussion and by providing an opinion on the operational fit between the two companies. Nevertheless, I acknowledge that the benefits of the COO also depend on his/her relationship with the CEO as their functions must be coordinated and integrated (Andrews, 1980). Considering the responsibilities of the COO and the benefits of having one, I expect that the role can be beneficial in the case of vertical M&A:

Hypothesis 2: Chief Operating Officer significantly increases shareholder value after a vertical merger & acquisition within the firm’s supply chain.

4. Methodology

The event study method is used to calculate the abnormal returns stemming from V-M&As, as it is the most used method to estimate the change in shareholder’s value caused by M&As. Next, an OLS regression is used to test the effect of having a dedicated COO on the abnormal returns.

First, the data collection process is explained followed by the steps taken to carry out the event study and description of variables used for the regression.

4.1 Data collection

The dataset used in this event study consists of V-M&As in the period 2003-2017, where the acquirer is a member of S&P 1500 listed firms in the United States. It is required for both the acquirer and the target to have valid industry codes based on the NAICS (North American Industry Classification System), where the number of industries are 59 as classified by the U.S.

Bureau of Economic Analysis (BEA). This is necessary in order to classify the mergers as

vertical, which I do by looking into the industry input-output relationship to calculate the

industrial vertical relatedness (see Ahern, 2012; Fich and Nguyen, 2020), calculating and

differentiating between upstream and downstream reliance. Upstream (downstream) reliance

equals the monetary value of acquirer’s industry input (output) coming from the target’s industry

scaled by the monetary value of acquirer’s output consumed by other industries, measured in US

dollars. I identify an upstream (downstream) M&A when the merging companies’ industries

have an upstream (downstream) reliance of 10% and/or 20%. For example, an upstream M&A

(UMA) is present when the acquirer’s industry imports goods worth $0.1 or $0.2 (for 10% or

20% reliance) while it exports goods to other industries with a monetary value of $1. In the data sample there are both upstream and downstream V-M&As (UMA and DMA) with reliance threshold of 10% and 20%. It is important to mention that there are many events which can be categorized both UMA and DMA, as it is common for industries to have two-way relationship.

Events which were initially recognized as upstream are used only in the UMA samples, same as the downstream ones, which is done to produce results specifically related to each type of V- M&A. Therefore, the final sample consists of 1088 UMAs at 10% upstream reliance which goes down to 831 when the threshold is raised to 20%. The DMA sample is smaller with 292 events at 10% and 154 at 20% downstream reliance.

Three dummy variables are used to measure the effect of acquirer’s COO on the abnormal returns. The first one indicates whether there is a COO role in the TMT of the company and the second shows whether the CEO takes that role. The third variable is used to identify the presence of a dedicated COO in order to remove cases where the CEO serves as a COO. The variables are generated by extracting data from the S&P Capital IQ's Execucomp since companies are required to report the names and titles of TMT members to the Securities and Exchange Commission (SEC). In order to calculate control variables, data from the annual reports was extracted from the Compustat Annuals database and data for the market competition of the acquirer was obtained from the Compustat Historical Segments database.

4.2 Research design

In order to answer the underlying research question, an event study is conducted. It is the most

commonly used method to estimate abnormal returns caused by specific events such as M&A

(Tuch and O’Sullivan, 2007). The method adjusts for market-wide influences on the stock price,

providing a good estimation of the stock market’s reaction as it controls for the systematic risk of

the stock. The efficient market assumption is needed to conduct event study stating that the

market is in the semi-strong form, meaning that all historical price data and publicly available

information is incorporated in the stock price (Fama, 1970). Therefore, I assume that the market

reacts efficiently to new information in an unbiased manner and the expected shareholder gains

are incorporated in the stock price of the company right after the public announcement of the

M&A. Abnormal returns are the difference between estimated returns and actual returns.

Estimated returns calculated and used as an indicator of what the stock price of the company would be if the event (V-M&A) did not occur. By looking at the difference between the actual and estimated returns at the announcement date I can measure the effect of V-M&As on shareholder value on that day. The standard market model event study methodology is used to calculate the abnormal return caused by the event as described by MacKinlay (1997), where the day of the event is when the vertical merger is announced. I briefly describe the process of estimating abnormal returns using the market model below, similar to the one used in Hendricks and Singhal (2008).

First, I calculate the estimated return of stock i on day t using the following equation:

(1)

where

is the return on stock i on day t,

is the intercept of the relationship for stock i,

is the slope of the relationship for stock i with the market return, r

is the market return on day t and

is the error term for stock i on day t.

is an estimate of the constant daily return for stock i,

r

is the portion of the return for stock i that is due to market-wide movements and

is the part of the return of stock i that cannot be explained by market movements. Using equation (1) above, I calculate the estimates ̂ , ̂ and the variance of the error term S

for each firm from the sample using data of 210 trading days prior to the event window, leaving a 10 days gap to prevent possible influence on the estimated returns caused by spillage of information regarding the event. Therefore, the length of the estimation window consists of 200 days as it is long enough to accurately predict the stock’s normal movement while having low chance of incorporating other events that might significantly influence the produced estimates. The market return is derived from the S&P 1500 index since sample firms are part of it, providing the most accurate market returns for event studies related to those companies. After calculating the estimates ̂ and ̂ , I use them to calculate

which is the abnormal return for stock i on day t using the equation (2) below:

( ̂ ̂

)

̂ ̂

(2)

where

, the abnormal return for stock i on day t is the difference between

, the actual return

of stock i on day t, and ( ̂ ̂

) the expected return on stock i on day t.

Next, the daily mean abnormal return ̅ is calculated by averaging the abnormal returns for sample firms on day t, using equation (3):

̅ ∑

(3)

where N is the number of sample observations on day t. Afterwards, the cumulative abnormal returns (CAR) are calculated for a specific time period of the event window, which is derived by calculating the sum of the daily mean abnormal returns for the same time period:

(

) ∑

̅ (4)

Next, each daily mean abnormal return (Āt) is divided by its estimated standard deviation S

to compute a standardized abnormal return

:

(5)

Finally, the test statistics ( ) for day t is calculated by:

∑

√ (6)

I use a 3-day [-1;+1] event window which was specifically chosen to check for possible information leaks and earlier market reactions that might result from them (Mitra and Singhal, 2008). Moreover, including another day after the announcement date controls for late market reactions and/or release of additional information about the M&A deal. On days when the stock exchange is closed such as holidays, the stock price is equal to the previous day’s closing price.

4.3 Control variables

Several control variables are used to incorporate factors that might influence the results of the

study (see Table 1 below). First, the year of the event is taken into account in order to control for

time trends as M&As happen in waves (Ahern et al., 2014). Second, the firm size of the acquirer

is controlled for since bigger firms are harder to be managed and are likely to benefit more from

having a COO (Hambrick and Cannella, 2004). Thirdly, the operational efficiency of the

acquirer is used as it measures the ability of the firm’s assets to generate revenue (Roh et al.,

the acquirer is taken into account as it can act as stimuli for growth and puts pressure on operations to generate stronger cash flows in order to pay the higher interest payments (Baxter, 1967). Lastly, market concentration is used to control for the market concentration of the acquirer since V-M&As are found to be more beneficial in non-competitive markets (Kedia &

Ravid, 2011). A summary of the control variables and their measurement is present in Table 1 below.

Table 1

Control variables

Variable Measurement Importance (rationale)

Year Year in which the M&A occurred To control for time trends as mergers happen in waves (Ahern et al., 2014)

Firm size of acquirer Natural logarithm of total assets Bigger firms are harder to manage (Hambrick and Cannella, 2004)

Operational efficiency of acquirer using return on assets (ROA) in year (t-1) as proxy

Operating income after depreciation in year (t-1) divided by the book value of assets in year (t-1)

Measures the ability of assets to generate value (Roh et al., 2016; Hendricks et al., 2015; Swink and Schoenherr, 2015)

Financial leverage of acquirer

Book value of long-term debt in (t- 1) divided by the book value of assets in year (t-1)

Measures the pressure on operations to generate cash flows

(Roh et al., 2016; Graham et al., 2013)

Market Concentration Herfindahl Hirschman Index (HHI) Vertical mergers are likely to generate more value in non-competitive markets (Kedia & Ravid, 2011)

Descriptive statistics and correlation matrices for the sample of Upstream and Downstream V- M&As at 10% reliance are presented below (Table 2; Table 3). For the sub-samples of 20%

related upstream and downstream V-M&As please refer to the Appendix.

Table 2

Descriptive statistics and correlations of Upstream vertical M&As 10% related

Variables Mean SD 1 2 3 4 5 6 7 8

1 CAR (-1;+1) .01 .04

2 COO Presence .22 .41 0.10*

3 CEO as COO .22 .41 -0.10* 0.04*

4 Dedicated COO .17 .37 0.11* 0.84* -0.24*

5 Year 2010.28 4.33 0.00* 0.40* 0.04* 0.31*

6 Size 8.44 1.62 -0.15* -0.10* 0.15* -0.17* 0.05

7 Return on Assets .16 .07 0.03* 0.00* 0.05* -0.03* -0.06 0.25*

8 Leverage .52 .16 0.05* -0.02* 0.09* -0.01* 0.02 0.15* -0.04*

9 Market Concentration .56 .19 -0.04* 0.07* 0.08* 0.04* 0.03 -0.01* 0.16* -0.07 N = 585 Significance: *** p<0.01, ** p<0.05, * p<0.1

Table 3

Descriptive statistics and correlations of Downstream vertical M&As 10% related

Variables Mean SD 1 2 3 4 5 6 7 8

1 CAR (-1;+1) .00 .04

2 COO Presence .18 .39 -0.12

3 CEO as COO .19 .39 -0.03 0.04*

4 Dedicated COO .14 .35 -0.07 0.86* -0.20*

5 Year 2010.95 4.13 -0.11 0.27* 0.03* 0.18*

6 Size 9.33 1.90 -0.10 -0.29* -0.01* -0.30* 0.23*

7 Return on Assets .15 .09 -0.11 -0.24* -0.13* -0.31* -0.04* 0.25*

8 Leverage .60 .19 -0.01 -0.06* 0.18* -0.14* 0.19* 0.34* -0.20*

9 Market Concentration .61 .21 -0.18 -0.09* -0.22* -0.04* 0.02* 0.05* 0.08* 0.01 N = 121 Significance: *** p<0.01, ** p<0.05, * p<0.1

5. Results and analysis

The results of the event study indicate that vertical mergers are viewed positively by the market, shown by the significant increase in shareholder value. This specifically holds for upstream V- M&As while downstream V-M&As show less significant results and usually when implementing non-parametric tests such as the binomial sign test (Table 2). I present the results of a two-tailed t-tests which I used to test if the abnormal returns are significantly different than 0. Moreover, I use a binomial generalized sign test to show whether there are more events with positive or negative abnormal returns than predicted. The “%>0” (see Table 2) shows the percentage of events with positive abnormal returns and the Z-score above it shows the significance of the generalized sign test.

The results of the tests show that there are statistically significant abnormal returns (AR) of

0.45% (p<0.01) on the announcement date of a UMA (10% related) and 0.40% AR (p<0.01) a

day after. There are significant positive cumulative abnormal returns (CAR) of 0.90% (p<0.01) for the 3-day event window. The results of the non-parametric test are significant as well (p<0.01).UMA (20% related) announcements show statistically significant positive AR of 0.21%

(p<0.05) on Day 0 and 0.16% (p<0.10) on day 1 with CAR of 0.37% (p<0.01). There are no significant returns on Day -1 for both types of UMA.

Downstream V-M&As at both 10% and 20% relatedness are associated with positive abnormal returns. DMAs (10% related) experience significant AR of 0.30% (p<0.10) on day 0 and CAR of 0.15% (p<0.10). When raising the relatedness to 20%, DMAs show no significant abnormal returns based on the t-test and significant AR of 0.29% (p<0.01) and CAR of 0.12% (p<0.05), based on the results of the non-parametric test.

For both UMAs and DMAs there are mostly positive CAR (53.36% and 53.42%, respectively) at the 10% relatedness threshold. The number of positive CAR increase to 58.60% and 58.44%

when increasing the threshold to 20% relatedness. Considering the results of both types of tests, it is reasonable to conclude that Upstream V-M&As are positively related to shareholder value, supporting H1. However, the results show less convincing evidence for the positive relationship between Downstream V-M&As and shareholder value. Nevertheless, when taking into account the results of the non-parametric test and the high number of positive abnormal returns, I conclude that the effect of DMAs is positive but not as strong as it is with UMAs. All in all, there are significant benefits from V-M&As and H1 is supported.

Table 4

Average abnormal returns of the event window for the four types of M&As Type of merger (N of events)

Day -1 Day 0 Day 1

CAR(- 1;1)

Upstream M&A 10% related (N=1088)

AR 0.05% 0.45% 0.40% 0.90%

T-test 0.91 4.70*** 4.46*** 6.59***

Z-test 0.78 4.23*** 3.15*** 7.63***

%>0 50.18% 55.42% 53.77% 53.36%

Upstream M&A 20% related (N=830)

AR 0.01% 0.21% 0.16% 0.37%

T-test 0.15 2.19** 1.72* 2.64***

Z-test -0.46 1.62* 0.44 6.87***

%>0 48.19% 51.81% 49.76% 58.60%

Type of merger (N of events) Day -1 Day 0 Day 1 CAR(-1;1)

Downstream M&A 10% related (N=295)

AR -0.15% 0.30% 0.05% 0.15%

T-test -1.16 1.90* 0.23 1.90*

Z-test -1.00 2.96*** 0.75 1.80*

%>0 45.08% 56.61% 50.17% 53.42%

Downstream M&A 20% related (N=153)

AR -0.17% 0.29% 0.18% 0.12%

T-test -0.78 1.47 0.50 1.47 Z-test -0.39 3.00*** 1.06 2.10**

%>0 46.41% 60.13% 52.29% 58.44%

Note: T-test results are from two-tailed t-test and Z-tests are based on Binomial sign test. Significance is reported as follows: *p <0.10; **p < 0.05; ***p< 0.01.

The results of the OLS multiple regressions are divided into two models and in both of them the dependent variable is the cumulative abnormal return (CAR). Other studies (see Mitra and Singhal, 2008) use the mean AR of day 0, but since there are significant AR on day 1 it is better to use the CAR returns. Model 1 has two independent dummy variables related to the COO role – COOANN which takes value of 1 if there is a COO present in the TMT and CEOCOO which takes value of 1 if the CEO is serving as a COO and 0 otherwise. Model 2 uses one dummy variable DEDCOO which takes value of 1 if there is a dedicated COO, different from the CEO.

The analysis is divided into two models in order to check the effect of having a dedicated COO compared to situations where the CEO takes the role of COO. The results for Model 1 are presented in Table 5 and those of Model 2 in Table 6.

For DMAs (both 10% and 20%), the regression F-values are not significant, indicating that the used models are unable to explain much of the variance of the variables. The R

values of those regressions are between 6.74% and 17.27%, but the Adjusted R

values are low or negative.

On the contrary, UMA regressions have highly significant F-values for both models at 10% and 20% (p<0.01). R

and Adjusted R

values are about 5% and 4%, respectively, which is below the values of comparable studies that try to explain the behavior of abnormal returns (Mitra and Singhal, 2008). Results indicate that the presence of COO is positively related to abnormal returns for 10% related UMAs and insignificant when the threshold goes up to 20%. Moreover, UMAs where the CEO serves as COO experience lower returns (p<0.05) at both 10% and 20%

relatedness. Company size is found to be negatively related to abnormal returns (p<0.01), while

operational efficiency is positively related (p<0.10). Highly leveraged companies experience significantly higher abnormal returns (p<0.05) and market concentration does not affect returns from V-M&As. For the exact values see Table 5 below.

Table 5

Cross sectional regression analysis using two COO dummy variables

Variable Model 1

UMA10% UMA20% DMA10% DMA20%

Intercept ( ) ^{2.858 2.619 4.685 7.682}

(6.382) (7.209) (15.329) (27.914)

COOANN (

) ^{.01** .006 -.021* -.015}

(.004) (.005) (.011) (.016)

CEOCOO (

) ^-.008** _(.004) ^-.009** _(.005) ^-.009 _(.01) ^-.008 _(.016)

YEAR ( ) ^{-.372 -.341 -.608 -.999}

(.839) (.948) (2.016) (3.67)

SIZE ( ) ^{-.004*** -.004*** -.002 -.002}

(.001) (.001) (.002) (.004)

ROA (

) ^.047* _(.025) ^.051* _(.029) ^-.058 _(.045) ^-.12 _(.127)

LEV ( ) ^{.021** .027** .002 -.026}

(.01) (.012) (.022) (.038)

MCONC (

) ^{-.01 -.01 -.04** -.044}

(.009) (.01) (.018) (.038)

Sample Size 585 464 121 43

F 4.51*** 3.72*** 1.60 0.80

R

5.19% 5.40% 9.02% 13.79%

Adjusted R

4.04% 3.95% 3.38% -3.45%

Note: Results are based on a two-tailed t-test and standard errors are reported in parentheses. *** p<.01,

** p<.05, * p<.10 are used to denote significance at the 1%, 5% and 10% level, respectively. The maximum VIF value of all regressions is 1.65 (below the widely accepted threshold of 10), showing no concern of serious multicollinearity issue.

Model 2 uses only one COO dummy variable that checks for the presence of a dedicated COO,

the results of which are reported in Table 6. The regression F-values for both types of UMAs are

significant at the 1% level. For UMAs, R

values are about 4.5% and Adjusted R

values are

about 3.5%, lower than comparable studies. The presence of a dedicated COO is beneficial in the

case of 10% related UMAs (p<0.05) and insignificant at 20% relatedness. Similar to Model 1,

the results of Model 2 indicate that firm size is negatively related to abnormal returns (p<0.01)

and higher operation efficiency is associated with higher abnormal returns (p<0.05), for both 10% and 20% industrial relatedness. High leverage is associated with higher abnormal returns at both levels of relatedness, the results of 10% related UMAs are significant at the 10% level and at 5% when the reliance threshold increases to 20%.

The results of both models indicate that the COO role is beneficial in the case of slightly related Upstream V-M&As. The low F-values of the regressions done for the DMA samples show that the abnormal returns are influenced by variables which are not considered in the model.

Moreover, the significant negative relationship between the CEOCOO variable and abnormal returns indicates that having a CEO with the role of COO is detrimental in the case of V-M&As.

Therefore, H2 is supported in the case of UMAs and rejected in the case of DMAs.

Table 6

Cross sectional regression analysis using one dedicated COO variable

Variable Model2

UMA10 UMA20 DMA10 DMA20

Intercept ( ) ^1.646 _(6.175) ^3.152 _(6.911) ^10.063 _(15.001) ^13.9 _(27.497)

DEDCOO (

) .01** .007 -.015 -.003

(.005) (.005) (.012) (.018)

YEAR ( ) ^{-.212 -.41 -1.317 -1.818}

(.812) (.909) (1.973) (3.616)

SIZE ( ) ^-.004*** _(.001) ^-.005*** _(.001) ^-.002 _(.002) ^-.002 _(.004)

ROA (

) ^{.048* .052* -.058 -.107}

(.025) (.029) (.046) (.131)

LEV ( ) ^{.019* .025** -.004 -.033}

(.01) (.012) (.022) (.037)

MCONC (

) ^-.011 _(.009) ^-.011 _(.01) ^-.033* _(.018) ^-.034 _(.033)

Sample Size 585 464 121 43

F 4.56** 3.65*** 1.37 1.04

R

4.52% 4.58% 6.74% 17.27%

Adjusted R

3.52% 3.33% 1.83% 0.07%

Note: Results are based on a two-tailed t-test and standard errors are reported in parentheses. *** p<.01,

** p<.05, * p<.10 are used to denote significance at the 1%, 5% and 10% level, respectively. The

maximum VIF value of all regressions is 1.33 (below the widely accepted threshold of 10), showing no

concern of serious multicollinearity issue.

6. Discussion

6.1. Summary of results

This study analyzes the impact of vertical M&As on shareholder value by measuring the abnormal returns around the announcement date, as well as the moderating effect of having a COO. Industrial relatedness is used to classify M&As as vertical and event study methodology (market model) is applied to measure the stock market reaction (abnormal returns). For the sample of 1088 upstream M&As (10% related) I find that there are significant abnormal returns of 0.90%, which go down to 0.37% when the reliance threshold is raised to 20% (n=830).

Downstream M&As have positive abnormal returns of 0.15% and 0.12% for 10% and 20%

relatedness, respectively, which are slightly significant. The cross-sectional regression analysis shows that companies with COO different than the CEO benefit more only from upstream M&As which are slightly related, as those benefits are not present when the relatedness threshold increases. Moreover, companies that have their CEO serving as a COO experience lower abnormal returns. Operational efficiency, measured as return on assets, is found to be positively related to shareholder value in the case of upstream V-M&As. Bigger companies experienced lower abnormal returns and those with higher financial leverage benefitted more from upstream M&As. The regression results for downstream M&As are insignificant.

6.2. Discussion of results and implications

There are several takeaways of the results described above. First, upstream vertical M&As, are

found to be beneficial for shareholders, similar to results of the existing literature for supply

chain integration activities (Narasimhan and Kim, 2002; Mitra and Singhal, 2008). Moreover, the

findings contribute to the existing literature by showing that extreme forms supply chain

integration such as vertical integration of a company are also beneficial. Second, downstream

M&As are less beneficial for shareholders compared to upstream ones, indicating that more is to

be gained by integrating suppliers rather than buyers. Kumar (2009) argues that companies that

undergo downstream integration are usually in pursuit of steady profit streams by producing

more value-added products or to gain new competencies. Therefore, a downstream V-M&A is

likely to be used by companies that want to grow and enter new markets, something which is

hard to evaluate in the short-run. Another explanation for this might be the skepticism of

investors that the acquirer can manage with the higher complexity of downstream operations.

Nevertheless, Rozen-Bakher (2018) find that V-M&As are more beneficial in the service sector rather than ones in manufacturing and explain this suggest this difference by the lack of power of labor unions in service industries. Those factors were not considered in the regression models and might better explain the variance of abnormal returns.

Companies with a dedicated COO are found to benefit more from upstream V-M&As but the benefits decrease when the industry reliance increases. This can be explained by the fact that the integration of highly related companies results in larger benefits from reduction in transaction costs. Those benefits are present regardless of the presence of a COO and the benefits of improved operations (for which the COO is beneficial) are relatively smaller. Nevertheless, companies where the CEO takes the role of COO experience lower abnormal returns, contrary to the findings of Hamrick and Cannella (2004). This can be explained by contingency theory, where the benefits from V-M&As are higher when a company is better structured to benefit from them. Therefore, when vertically integrating the firm’s supply chain, the organizational setup of having a dedicated COO is better than one where CEO takes the COO role. Moreover, Pagell (2004) propose that top management support is needed in order to internally integrate the firm’s supply chain, which an organization with a dedicated COO is more likely to achieve.

Larger firms are found to benefit less from upstream vertical M&As, similar to the findings of

other studies (Fich and Nguyen, 2020; Cai and Sevilir, 2012). This outcome may be due to the

fact that smaller firms have higher growth potential and investors reward them more in the case

of upstream vertical M&As. Another explanation is that the announcement of a V-M&A by a big

company is perceived by investors as lack of internal growth, regardless of the actual value from

the M&A. The results also show that firms with higher financial leverage receive higher

abnormal returns. High leverage means that the company is under pressure to generate stable

cash flows in order to meet interest obligations and dividend payments. This can motivate

managers to improve firm performance in order to keep their jobs and increase operational

efficiency. The findings also indicate that companies with a better ability to profit from their

assets experience higher abnormal returns. Firms with higher operational efficiency benefit more

from V-M&As which goes against the argument of Richey et al. (2009) that underperforming

companies are likely to profit more from M&As since they have higher incentive and need for

growth.

6.3 Managerial implications

The results of this study have a few managerial implications. First of all, firms should proactively inform the market of the potential benefits when acquiring upstream parts of the value-chain or when improving the relationships with them as investors perceive them as value- generating activities. Similarly, when integrating a company downstream in the supply chain, the management of the acquiring firm should focus more on the long-term benefits and market expansion rather than synergies from consolidated operations. Second, a dedicated COO is beneficial in the case of V-M&As and companies should delegate the responsibility of the CEO to run day-to-day operations to a COO. Last but not least, firms with high operational efficiency and leverage should considering V-M&As as growth opportunities.

7. Limitation and future research

The main limitations of this study relate to the event study methodology used to measure the short-term benefits of vertical M&As under the assumption of efficient market. Although it is common to assume market efficiency, the results of the study indicate there are significant returns a day after the announcement, indicating that the market may not react efficiently in the case of vertical M&As and/or there is more information that becomes publicly available after the M&A announcement. Moreover, this paper does not look into longitudinal accounting data that can reveal the long-term benefits of the M&A. It is possible that COOs help tap into the synergies from the V-M&A in the years after the event or the lack of dedicated COO detriments the company’s ability to benefit from the V-M&A. This study focuses solely on the short-term reaction of the market and uses only quantitative data and the analyses for the benefits of the COO have low R-squared, lower than the low R-squared values typical for event studies. This indicates that the regression models do not explain much of the variance of abnormal returns and it may be beneficial to measure the positives of having a COO using qualitative studies such as a case study. The COO’s responsibilities vary greatly and a multiple case study can show in which specific cases COOs are most important for the success of vertical M&As.

Finally, my research found little or no evidence of the benefits of downstream vertical M&As.

This topic can be further investigated in the future to find out why and when they can bring value

to shareholders.

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Appendix

Table. 7

Descriptive statistics and correlations of Upstream vertical M&As 20% related

Variables Mean SD 1 2 3 4 5 6 7 8

1 CAR (-1;+1) .01 .04

2 COO Presence .24 .43 0.07*

3 CEO as COO .22 .42 -0.12* 0.03*

4 Dedicated COO .18 .39 0.09* 0.83* -0.25*

5 Year 2010.33 4.34 -0.01* 0.43* 0.09* 0.33*

6 Size 8.39 1.57 -0.15* -0.07* 0.23* -0.15* 0.01

7 Return on Assets .16 .07 0.02* 0.05* 0.06* 0.00* -0.01 0.26*

8 Leverage .52 .16 0.08* 0.03* 0.10* 0.03* 0.00 0.14* -0.05*

9 Market Concentration .56 .19 -0.05* 0.09* 0.06* 0.04* 0.07 0.03* 0.22* -0.12*

N = 464 Significance: *** p<0.01, ** p<0.05, * p<0.1

Table. 7

Descriptive statistics and correlations of Downstream vertical M&As 20% related

Variables Mean SD 1 2 3 4 5 6 7 8

1 CAR (-1;+1) .00 .04

2 COO Presence .23 .43 -0.08

3 CEO as COO .37 .49 0.01 -0.20*

4 Dedicated COO .19 .39 0.04 0.87* -0.37*

5 Year 2010.28 3.75 -0.08 0.33* -0.04* 0.22

6 Size 8.84 1.67 -0.16 -0.27* 0.20* -0.22 -0.14

7 Return on Assets .14 .05 -0.18 -0.09* -0.22* -0.15 0.17 0.03

8 Leverage .60 .19 -0.16 -0.07* 0.32* -0.26 0.01 0.24 -0.20

9 Market Concentration .63 .21 -0.24 -0.14* -0.41* -0.03 -0.13 0.26 0.28 0.10

N = 43 Significance: *** p<0.01, ** p<0.05, * p<0.1