Cultural Distance in Mergers and Acquisitions: The
Influence of Organizational Cultural Distance on Layoffs
After Mergers and Acquisitions
Master thesis
by
Marleen Merkus - S2757605
m.merkus@student.rug.nl
Supervisor: asst. prof. Marvin Hanisch
Co-assessor: prof. dr. Jordi Surroca
Faculty of Economics and Business
22 June 2020
Abstract
Mergers and Acquisitions (M&A’s) have increasingly been the topic of research the last few years. Several studies underline the fact that layoffs often seem to happen after M&A’s. Factors that have been that have been related to these layoffs are the relatedness of firms, the type of industry and whether the M&A is domestic or cross-border. While culture is seen as a factor that can cause M&A’s to succeed or fail, it has not been linked yet to the layoffs that occur after M&A’s. This study aims to ascertain how organizational cultural distance influences the number of layoffs after an M&A, by explaining it with the concept of the social identity theory. I propose that the hostility of the takeover moderates the relationship between organizational cultural distance and the number of layoff after M&A’s. The sample consists of 872 observations over time from 161 M&A deals of the biopharmaceutical industry. The study displays insignificant results for the relationship between organizational cultural distance and layoffs after M&A’s and also shows that hostility does not moderate this relationship. By conducting this research, I aim to contribute to the existing theory by providing new insights on the implications of cultural distance on the number of layoffs after M&A’s.
Table of content
1. Introduction 4
2. Theory and hypotheses 7
2.1 Layoffs and M&A’s 7
2.2 Organizational cultural distance 8
2.3 Social identity 10
2.4 Hostility of takeover 12
2.5 Conceptual model 13
3. Methodology 14
3.1 Data collection and sample 14
3.2 Measurements 15
3.2.1 Primary variables 15
3.2.2 Control variables 16
3.3 Data analysis 17
4. Results 18
4.1 Descriptive statistics and correlations 18
4.2 Regression and hypothesis testing 21
5. Discussion 24 5.1 Theoretical contribution 25 5.2 Managerial implications 26 5.3 Limitations 26 5.4 Further research 27 6. References 29 7. Appendices 33
Appendix A: Distribution of Missing Values 33
Appendix B: Dictionary to measure Cultural Fit 34
1. Introduction
Mergers and Acquisitions (M&A’s) have been researched increasingly during the last years (e.g. Cartwright & Cooper, 2014; Meglio & Risberg, 2011; Zollo & Meier, 2008; Rossi & Volpin, 2004). It has often been said that M&A’s will also result in workforce reductions and multiple studies have tried to examine this relationship (e.g. Conyon, Girma, Thompson & Wright, 2002; Krishnan & Park, 2002; O’Shaugnessy & Flanagan, 1998). In these studies it has become clear that there are multiple factors that play a role in why M&A’s often lead to layoffs. Some of these factors are relatedness between firms (Krishnan & Park, 2002; O’Shaugnessy & Flanagan, 1998), the type of industry and whether it is a cross-border or domestic M&A (Lehto & Böckerman, 2008) and paying acquisition premiums (Krishnan, Hitt & Park, 2007). One factor that has not been getting a lot of attention yet, is the relationship between cultural distance and layoffs after an M&A. However, there are reasons to expect that cultural differences might affect the number of layoffs after an M&A.
Social identification enables individuals to feel loyal to an organizational culture (Ashforth & Mael, 1989). Because two social groups are combined in an M&A, employees of one firm might perceive an M&A as a threat to their intra-group culture and can therefore develop negative responses and feelings towards the employees of the other firm (Bartels, Douwes, De Jong & Pruyn, 2006; Hogg & Terry, 2000). When groups or persons are more culturally or ethnically similar, they will most likely perceive a higher level of trust (McAllister, 1995), which may lead to less resistance. It is implied in the social identity theory that groups will show less resistance to identities that are similar to their own, while they are more resistant towards other identities (Bartels et al., 2006). Higher differences between two groups may create an “us-versus-them” thinking in situations such as M&A’s (Stahl & Voigt, 2008) and can also lead to the in-group bias (Stahl & Voigt, 2008; Björkman, Stahl & Vaara, 2007).
The effect of the social identity theory is predicted to be stronger in the case of hostile takeovers, as hostile takeovers can create hostility between the two firms which can create feelings of bitterness and can increase resistance (Hitt, Harrison, Ireland, 2001; Hambrick & Cannella, 1993). This is opposed to the more friendly mergers that are expected to be more cooperative and have better integration outcomes (Hambrick & Cannella, 1993). Considering that the hostility of a takeover might increase the negative feelings between the employees of both firms, it is expected that this would also lead to a stronger in-group bias.
As has been previously mentioned, the relationship between the cultural distance and layoffs after M&A’s has not been given a lot of attention, while several studies have proven that cultural differences affect M&A outcomes. In this paper I will try to address this gap by studying the relationship between cultural distance and layoffs after M&A’s. This paper is focused on the organizational level rather than the national level, which is why I will look at the organizational cultural distance. Therefore I have formulated the following research question:
How does the organizational cultural distance between two firms influence the number of layoffs after M&A’s and is this relation moderated by the hostility of takeovers?
increases, the number of layoffs will also increase after an M&A. This effect is expected to be magnified by the hostility of the takeover.
I will test these predictions by using a dataset of 1,454 M&A deal contracts from the biopharmaceutical industry from the years 1994 until 2019. A regression analysis has been performed to measure the effect of the cultural distance as well as the effect of the hostility on the change of the number of employees after an M&A. The outcome displays to be insignificant for both variables, which means that cultural distance does not seem to have an effect on the number of employees of a firm after an M&A and that hostility does not magnify this effect.
The theoretical contribution of this paper is the expansion of the M&A literature to a subject that has been getting less attention; the relationship between cultural distance and layoffs. With this paper, I have tried to link two important factors in M&A’s that have only limitedly been investigated together in the literature. In addition, by explaining the cultural distance with the social identity theory, this paper might provide a better understanding of cultural distance in M&A’s. This might help managers to get a deeper understanding of how cultural distance plays a role in M&A’s and how this can affect people in the firm, but also how it can affect themselves.
2. Theory and hypotheses
In this section I will firstly explain the relationship between layoffs and M&A’s with the use of prior literature. After that I will describe the effects of organizational cultural distance on M&A outcomes and will then relate this to the social identity theory, which leads to the formulation of Hypothesis 1. Finally I will describe the moderator hostility of takeover and its expected effect on the relationship between organizational cultural distance and the number of layoffs after M&A’s, followed by
Hypothesis 2 and a conceptual model that visualizes both hypotheses.
2.1 Layoffs and M&A’s
Different researches have discussed the influence of M&A’s on workforce reductions (e.g. Conyon et al., 2002; Krishnan & Park, 2002; O’Shaugnessy & Flanagan, 1998). M&A’s require changes and reorganization in the target firm and it is likely that these reorganizations include the restructuring and even disposal of assets; these disposals of assets may entail layoffs as well (Capron & Guillén, 2009). Whilst most research suggests or proves that there is a relationship between M&A’s and the number of layoffs after an M&A, reasons behind this relationship remain mostly unclear.
Another factor that has been suggested to be related with the number of layoffs in M&A’s is whether the M&A is domestic or cross-border. The study of Lehto and Böckerman (2008) displayed that cross-border M&A’s cause workforce reductions in the manufacturing industry. However, they found only little evidence that this is the case for non-manufacturing industries as well. For domestic M&A’s, where the acquirer is owned domestically and located in Finland, their results showed that there are negative employment effects for all sectors. The results of Gugler and Yurtoglu (2004) indicated that domestic mergers reduce employment more than cross-border mergers, however, these differences were not statistically significant. Krishnan et al. (2007) also suggest that the payment of acquisition premiums leads to workforce reductions in the merged firm. They argue that larger premiums will result in greater workforce reductions. This is due to the fact that managers are likely to overestimate the number of layoffs is needed when acquisition premiums have been paid. These studies show that there is a relationship between M&A’s and layoffs and that there are different factors that drive this relationship.
However, as been stated by Conyon et al. (2002), there is only limited evidence on the overall employment impact of mergers. One example that has not been described much in the literature yet, is the relationship between cultural distance and layoffs in M&A’s. In the M&A literature cultural distance has been identified as an important factor (Stahl & Voigt, 2008), however, there has been almost no evidence on the relationship between cultural distance and layoffs after M&A’s. There is one study of Hambrick and Cannella (1993) which suggests that the rate of executive departure is higher when there is a larger cultural distance between the two firms. While this does not prove a relationship between cultural distance and layoffs, one could argue that the effect of cultural distance might go much further than only the departure of executives, meaning that it could also explain other layoffs. Therefore, this study will focus on the relationship between cultural distance and layoffs after M&A’s. In the following paragraph I will elaborate on the relationship between cultural distance and M&A’s.
2.2 Organizational cultural distance
authors of literature on organizational culture (e.g. Bauer & Matzler, 2014; Gregory, Harris, Armenakis, & Shook, 2009): the shared set of beliefs, values and assumptions by the members of an organization. In order to understand and measure the differences between two different cultures, I will refer to the term cultural distance. Cultural distance has been defined as the extent to which different cultures are similar or dissimilar (Shenkar, 2001). Thus, organizational cultural distance in this paper will be referred to as the differences in the shared set of beliefs, values and assumptions by the members of the organization.
M&A literature has identified culture as an important factor that influences the outcomes of an M&A (Stahl & Voigt, 2008; Buono et al., 1985) and is seen at its full strength when two dissimilar cultures are forced to merge into one culture (Lodorfos & Boateng, 2006). The greater the distance between two cultures, the more both firms have to change in order to achieve a combined culture (Cartwright & Cooper, 1993). There has been a focus on national culture (Stahl & Voigt, 2008), organizational culture (Weber, 1996; Cartwright & Cooper, 1993; Buono et al., 1985) or even both types of culture (Teerikangas & Very, 2006; Weber et al.,1996) in the context of M&A’s. People might be lured into thinking that cross-border M&A’s cause more difficulties due to differences in national culture, however, differences in organizational cultures can prove to be even more difficult (Teerikangas & Very, 2006). Although most scholars intuitively would say that cultural differences matter in M&A’s and several studies have proven this as well, there are still questions remaining how the cultural differences affect M&A’s and what can be done to manage these differences more effectively (Stahl & Voigt, 2008). Research has revealed that organizational cultural differences between firms affects several processes after M&A’s, including: the degree of change needed after M&A’s (Cartwright & Cooper, 1993), the integration process after an M&A (Jemison & Sitkin, 1986) and performance after M&A’s (Weber, 1996). That being so, it is out of the question that cultural distance is an important factor in M&A’s.
between the culture and structure which will foster certain behavioural responses of individuals and groups in the organization (Bijlsma-Frankema, 2001). Therefore it will probably not come as a surprise that in the case of an M&A, where two organizational cultures come together, the changes that follow can be a very difficult experience for the individuals in both firms. On top of the fact that M&A’s naturally create an “us-versus-them” relationship, combining two firms may result in a clash between the two cultures of the firms, which leads to the attacking of the other side and the defending of their own (Seo & Hill, 2005; Bijlsma-Frankema, 2001; Marks & Mirvis, 1992). Even when there is no clash, cultures between the two firms will most likely be different from each other (Bijlsma-Frankema, 2001). Both firms have their own beliefs, values and assumptions (Schein, 2010) and combining two cultures, requires employees to change their values, beliefs and attitudes, but also their social identity (Steigenberger, 2017). In an M&A, these differences between the two cultures may give a feeling of “them-and-us” between the employees of both firms (Bijlsma-Frankema, 2001). These feelings of “them-and-us” can be explained by the social identity theory of Tajfel and Turner (1979) on which I will elaborate on in the next paragraph.
2.3 Social identity
Seo and Hill (2005) have identified six theoretical themes that have implicitly or explicitly formed the basis for explaining employees’ psychological and behavioural responses to M&A-related organizational change. One of these theories is the social identity theory, which originates from Tajfel and Turner (1979). Tajfel (as cited in Hogg & Terry, 2000, p. 122) defines the social identity theory as “the individual's knowledge that he belongs to certain social groups together with some emotional and value significance to him of this group membership". Since work is often a prominent part of an individual’s life, one could assume that the workplace, being the company, department or even a workgroup, is a social group that individuals identify with (Bartels et al., 2006).
continuation of their current identity, which could lead them to resisting an M&A. This would especially be the case when employees feel it is a serious threat to the intra-group culture (Bartels et al., 2006). In addition, these feelings may not only be triggered by the probability of losing their current identity, but also by the prospect of having to unite with a distinct group (Van Leeuwen, Van Knippenberg & Ellemers, 2003). When engaging in an M&A, the in-group bias and “us-versus-them” thinking are likely to occur (Björkman et al., 2007; Stahl & Voigt, 2008). The in-group bias has been explained in the social identity theory and is defined as “those instances of favouritism which are unfair or unjustifiable in the sense that they go beyond the objective requirements or evidence of the situation” (Turner, Brown & Tajfel, 1979, p. 187). This in-group bias can work in two ways: one being that the members in the acquired firm may resist against the people from the acquiring firm (Stahl & Voigt, 2008) and one being that the managers of the acquiring firm might feel superior and treat the members of the target firm as inferior (Hambrick & Cannella, 1993). The feeling of superiority might also lead to parent firm arrogance, which happens when the parent firm believes that their style, values, beliefs and practices are superior (Jemison & Sitkin, 1986).
The social identity theory implies that group members show more resistance towards new identities that are more different from their own than towards identities that are more similar to their own (Bartels et al., 2006). In the case of cultural distance, this would mean that resistance is likely to be higher when the perceived cultural distance is higher. It can create a feeling of “us-versus-them” between the employees of both firms, which might cause the in-group bias and the situation that employees feel superior towards the other firm (Bijlsma-Frankema, 2001; Hambrick & Cannella, 1993). In M&A’s, where it is likely that layoffs occur, I expect that a the increase in cultural distance will also lead to more layoffs, following the line of thinking of the social identity theory where feelings of resistance and superiority may emerge. This leads to the following hypothesis:
2.4 Hostility of takeover
According to Morck, Shleifer & Vishny (1988), there are two broad classes of takeovers, one being the more disciplinary takeover and the other being the more synergistic takeover. The motive of the acquisition takeover does not necessarily determine whether the takeover is friendly or hostile, as in both cases the managers of the target firm can show resistance or cooperativeness (Morck et al., 1988). Hostile takeovers are defined as acquisitions that did not have negotiations before the initial bid or that are actively opposed by that target firm’s management or board of directors (Schneper & Guillén, 2004; Conyon et al., 2002; Morck et al., 1988). This type of takeover may be seen as a “wake-up call” for the management of the target firm that they have been managing the firm inefficiently (Chatterjee, Harrison & Bergh, 2003). Bidders claim that they offer a fair price for the shares of the firm that would reflect the value of the firm under their management. On the other hand, the management accuses the bidders of trying to buy shares for a lower price that does not reflect the real value of the shares (Hirshleifer & Titman, 1990). Additionally, Conyon, Girma, Thompson & Wright (2001) state that the acquirers in hostile takeovers are interpreted to have the objection to substitute the managers and to raise the return on the corporate assets. Transactions like these are likely to be associated with the increased productivity and workforce reductions.
moderates the relationship of organizational cultural distance and layoffs after M&A’s. This leads to the following hypothesis:
Hypothesis 2: The hostility of the takeover has a moderating effect on the relationship of organizational cultural distance on layoffs after M&A’s.
2.5 Conceptual model
Based on the formulation of the hypotheses in the previous paragraphs, the conceptual model is visualized as follows:
Figure 1: conceptual model
Organizational
cultural distance
Layoffs after M&A’s
Hostility of takeover
3. Methodology
This section contains descriptions on how the data has been collected, the variables and the measurements that have been used and, finally, the used methods to analyse the data.
3.1 Data collection and sample
For this study we used a database which consists of 1,454 M&A deal contracts from the biopharmaceutical industry from the years 1994 until 2019. These contracts originate from the U.S. Security and Exchange Commission (SEC). This database has been provided by the Faculty of Economics and Business from the University of Groningen. Duplicate contracts, terminations, contracts for which no information could be found and contracts that contained more than one acquirer were dropped before the analysis, which led to a total of 1,094 contracts. The observations with missing values have been dropped during the analysis as well, which is why the final sample has been reduced to 872 observations of in total 161 separate contracts. A distribution of the missing values per variable and the number of values missing per observation can be found in Appendix A. Here can be seen that the variables cultural distance, total employees, ROA target and relative size had the most missing variables, which explains the substantial smaller amount of observations in the final sample compared to the complete dataset.
we have used the website archive.org in order to find archived websites of the firms at a specific moment in time. The data for the hostility variable comes from press releases. We have looked up press releases concerning each M&A deal and whenever in these press releases the M&A was identified as hostile, we marked this particular M&A deal as hostile in the dataset.
3.2 Measurements
3.2.1 Primary variables
Organizational cultural distance: the independent variable organizational cultural distance will be
measured in terms of differences in mission statements between the two firms. Culture as defined by Schein (2010), should be reflected in mission statements of an organization, as mission statements should be developed from core values and beliefs (Irani, Beskese & Love, 2004). Additionally, Babnik, Breznik, Dermol and Trunk Širca (2014) mention that mission statements contain values and cultural dimensions. Therefore, in this study I will use the mission statement as a predictor of culture and compare mission statements between the two firms by doing a text analysis. This is in line with the methodology used by Hanisch, König, Haeussler, Graf-Vlachy & Cho (2018). They measure cognitive frame similarity by using the organization’s mission statement. The mission statements of the year before the M&A will be collected for both acquirer and target. To measure the cultural distance, a computer-aided text analysis will be conducted on the mission statements. This measures the similarity between those statements based on dictionary that has been developed by Hanisch et al., (2018), which can be found in Appendix B. In order to measure the distance instead of similarity, I will subtract the outcome of the computer-aided text analysis with 1.
Layoffs after M&A’s: the dependent variable layoffs after M&A’s will be measured by looking
the target company to the acquiring company so it would give a more accurate number to compare with after M&A’s.
Hostility of takeover: the moderating variable the hostility of the takeover will be measured by
looking at press releases about the M&A. If these press releases state that the takeover is hostile, the M&A will also be defined as hostile. Hostile cases are marked with a “1” in the dataset, whereas friendly cases are marked with a “0” in the dataset.
3.2.2 Control variables
It is likely that layoffs after M&A’s will be affected by other variables than the ones proposed in this paper. Therefore the following control variables will be used:
Prior performance of acquiring firm: acquiring firms that were performing poorly before
the M&A are more likely to reduce their workforce in order to reduce costs (Krishnan et al., 2007). The performance will be measured by using the Return on Assets (ROA), which I will calculate by taking the total assets and net income of the acquiring firm one year prior to the M&A.
Prior performance of target firm: when a target firm has been performing poorly before the
M&A, it is more likely that layoffs will follow (Krishnan et al., 2007). I will measure the performance by using the Return on Assets (ROA) of one year prior to the M&A, which I will calculate by taking the total assets and net income of the target firm one year prior to the M&A.
Relatedness: as shown in the study of Krishnan and Park (2002), firms that acquire related
firms, are likely to lay off employees. Firms that have a high relatedness would likely have more redundancies in their activities. In order to eliminate the redundancies, it is expected that firms might choose to reduce their workforce. Relatedness will be measured by comparing the firm types of both firms and when they are similar, they will be marked as “1” in the dataset, otherwise they will be marked as “0”.
Geographical distance: as been mentioned by Lehto and Böckerman (2008), geographical
M&A’s. Therefore I expect that geographical distance might affect the outcomes of my hypothesis, thus I include this as a control variable. I calculate the geographical distance by calculating the distance in kilometres between the headquarters of both firms.
Relative firm size: the relative firm size is expected to affect the number of employees after an
M&A (Krishnan et al., 2007; Hambrick & Cannella, 1993). When the acquiring and target firm are of similar sizes, it is likely that redundancies are perceived to be higher. As has been said before, in order to eliminate redundancies, one may choose to lay off employees (Krishnan and Park, 2002). I calculate the relative firm size as a ratio of the revenues of both the target and acquiring firm in the year before the M&A.
Deal type: in order to control for the possible effects that the different deal types have on layoff
outcomes, I include a control variable for each deal type.
Deal size: to control for the effects of the deal size, the logarithm of deal value will be added
as a control variable.
Year dummies: to control for every year I made a variable for all of the possible contract years
and marked the year variables that corresponded with the contract with a “1”, otherwise I marked them with a 0.
3.3 Data analysis
4. Results
In this section I will present the results of this study and reject or accept my hypotheses. Firstly, I will show and describe the descriptive statistics and correlations. Secondly, the results of the regression analysis to test the hypotheses will be described leading to the rejection or acceptance of the hypotheses.
4.1 Descriptive statistics and correlations
Table 1: Descriptive statistics and correlations
Variable Mean S.D. Min Max (1) (2) (3) (4) (5) (6) (7) (8) (9)
Table 2: Variance Inflection Factors test Variable VIF 1/VIF
Cultural distance 1.21 0.826920 Hostility 1.04 0.962612 ROA acquirer 1.08 0.927919 ROA target 1.07 0.935699 Type relatedness 1.04 0.964000 Geographical distance 1.05 0.949515 Relative size 1.05 0.950856 Deal size 1.26 0.795292 Mean VIF 1.10
Within the sample 77.06% of the entries are acquisitions, the other 22.94% of the entries are different deal types; the complete distribution can be found in Appendix C. It should be noted that in the final sample there are 0 observations of the deal type minority stock purchase. The observations in the sample are almost equally divided between related firms (50.11%) and non-related firms (49.89%), while the distribution between hostile M&A’s (1.83%) and non-hostile M&A’s (98.17%) is very unequal.
Figure 2: graph of yearly average of total employees
4.2 Regression and hypothesis testing
Table 3 displays the results of the Fixed Effects GLS regression. All three models have a very weak R²
and explain about 8% to 9% of the variance. The overall model is statistically significant (p < 0.01). For all of the models I standardized the non-binary independent variables in order to address differential scaling issues for the independent variables (Cohen et al., 2003). It should be noted that the control variable for the deal type of minority stock purchase has been omitted from the regression as there was no variation in the observations.
to the expectation that higher relatedness will lead to more redundancies and therefore a higher workforce reduction. The results also display a positive statistically significant effect for geographical
distance (b = 1,861, p < 0.01), which means that when the geographical distance increases, the total
number of employees increases as well. The other control variables all show no significant effects on the independent variable total employees.
Model 2 includes the independent variables cultural distance and hostility as well as the control
variables. Both cultural distance (b = -2,021, p > 0.1) and hostility (b = -1,470, p > 0.1) appear to be statistically insignificant. Again, the control variables type relatedness (b = 2,484, p < 0.01) and
geographical distance (b = 1,890, p < 0.01) display a positive significant effect on the total number of
employees. The control variable ROA acquirer (b = -29,474, p < 0.01) continues to display a statistically significant negative effect on the total number of employees..
In Model 3 the complete model including the interaction term of the moderator hostility is displayed. The independent variables cultural distance (b = -2,095, p > 0.1) and hostility (b = -13,371, p > 0.1) again display to be insignificant, thus there is no support for Hypothesis 1 and therefore
Hypothesis 1 is rejected. The interaction term of the moderator hostility also demonstrates to be
Table 3: Results of the Fixed Effects GLS regression
Variables Model 1 Model 2 Model 3
Independent variable Cultural Distance -2,021 -2,095 (1,367) (1,378) Moderator variable Hostility -1,470 -13,371 (3,058) (27,021)
Hostility x Cultural Distance 814.2
(1,837) Control variables ROA Acquirer -28,867** -29,474*** -29,189** (11,293) (11,297) (11,322) ROA Target -18,170 -18,123 -18,248 (15,777) (15,784) (15,796) Type Relatedness 2,562*** 2,484*** 2,529*** (865.0) (866.2) (872.5) Geographical Distance 1,861*** 1,890*** 1,847*** (493.2) (493.4) (502.9) Relative Size -348.6 -360.0 -353.6 (607.4) (607.3) (607.8)
Deal Type: Acquisition 1,249 7,390 7,840
(5,084) (6,841) (6,920)
Deal Type: All Stock Transaction 196.4 7,039 7,454
(6,564) (8,228) (8,286)
Deal Type: Majority Stock Purchase 8,506 14,685 15,156
(10,582) (11,467) (11,523)
Deal Type: Merger -195.3 6,025 6,451
(5,068) (6,860) (6,931)
Deal Type: Stock for Stock -336.1 6,718 7,216
(7,545) (9,180) (9,254)
Deal Type: Stock for Stock Merger -2,144 4,587 4,907
(7,482) (9,084) (9,118)
Deal Size -1,889 -3,139 -3,273
(2,130) (2,389) (2,410)
Yearly Effects Yes Yes Yes
Constant 25,394*** 21,797*** 21,604*** (2,932) (3,964) (3,991) N 872 872 872 Number of deals 161 161 161 F-statistic 2.24*** 2.17*** 2,10*** R-squared 0.084 0.087 0.088
Standard errors in parentheses. Significance levels at: *** p<0.01, ** p<0.05, * p<0.1
5. Discussion
M&A’s and layoffs after said M&A’s often go hand in hand (Conyon et al., 2002). There are many factors that can trigger this, and as can be seen in different studies, it is most likely that in a majority of the cases more than one factor is the cause behind the layoffs that follow an M&A. However, not all research is consistent in showing that M&A’s cause layoffs and it seems that different characteristics of the acquirer, target and M&A deals are the source of this (e.g. Lehto & Böckerman, 2008). In this paper I tried to find out whether cultural distance between the two firms affects the number of layoffs after an M&A. I used the variables total employees and cultural distance and incorporated the ‘M&A-effect’ in order to investigate the relationship between cultural distance and the number of total employees after M&A’s. My expectation was that a greater cultural distance would also lead to more layoffs, due to the in-group bias which is likely to occur in M&A’s (Stahl & Voigt, 2008; Björkman et al., 2007). Additionally, my expectation was that hostile takeovers would magnify this effect and therefore lead to an higher number of layoffs. The results of my research showed that both hypotheses were insignificant, meaning that in this study cultural distance has not shown to have an effect on the number of layoffs after an M&A, nor hostility does affect the relationship between cultural distance and number of layoffs after an M&A. As has been said, there are many factors that can be of influence on layoffs after M&A’s and therefore one must be careful about drawing the conclusion that cultural distance is does not affect layoffs after M&A’s. This study only focused on companies in the biopharmaceutical industry, and as also became clear in the study of Lehto and Böckerman (2008), some effects are only visible in specific industries. Thus, it could very well be that studies on the relationship between cultural distance and layoffs after M&A’s in other industries also give different results.
What is noteworthy in this study, is that two of the control variables show a contrasting effect compared to prior literature. It was expected that the ROA acquirer would have a positive relationship with the total employees. However, the results show that in this case it is negatively related to the total
employees, meaning that when the financial performance of a firm before the M&A increases, it would
expectation that when a firm was performing poorly before the M&A, it would more likely lay off employees in order to reduce costs (Krishnan et al., 2007). Furthermore, results in prior literature have shown that higher relatedness between firms in M&A’s would also cause more layoffs, which is probably due to the redundancies in the workforce (Conyon et al., 2002; Krishnan & Park, 2002; O’Shaugnessy & Flanagan, 1998). This study displays an opposite effect with a strong statistical significance, namely that increases in type relatedness between firms also leads to an increase in total
employees.
5.1 Theoretical contribution
This paper contributes to the literature on layoffs in M&A’s, as there is still only limited evidence on the overall employment impact of mergers (Conyon et al., 2002). With this paper, I have tried to relate two important factors in M&A literature, namely cultural distance and layoffs. As prior literature has stated, layoffs often seem to happen in M&A’s (e.g. Conyon et al. 2002; Krishnan & Park, 2002; O’Shaugnessy & Flanagan, 1998) and culture is an important factor that could cause an M&A to fail (Chakrabarti et al., 2009). The results showed no relationship between the factors in the biopharmaceutical industry, which is not especially surprising as M&A’s are seen as complex, multifaceted phenomena that do not have one single success factor that makes them work (Bauer & Matzler, 2014; Cartwright, Teerikangas, Rouzies & Wilson-Evered, 2012). The complexity of the field has actually again been proven by this study, as the two control variables that have been discussed before, show opposite results to those of prior research such as Krishnan et al. (2007) and O’Shaugnessy and Flanagan (1998).
insignificant, this paper contributes to the existing literature by broadening the M&A theory on cultural distance and layoffs.
5.2 Managerial implications
This study provides several managerial implications. The first one being that managers should be aware of the fact that cultural distance between two firms can play a role in M&A’s and its performance. Managers should not think lightly about the implications a greater cultural distance between two firms can have and how this may cause the in-group bias. They should be aware about how the cultural differences affect themselves, but also how they affect others in both firms. One result of the in-group bias can be resistance towards the other firm and to the M&A as a whole, which can lead to difficulties in the integration. An M&A is complex and knows many factors that could cause it to fail. Therefore it is important for managers to understand that what might have worked before, will not guarantee the same outcomes now.
5.3 Limitations
One limitation to start with, is the data collection of this study. We worked together with a group of six students to collect the data and each did our own part, which does not completely rule out inconsistencies. The dataset has been checked thoroughly and decisions about how to collect data have been made on group level to ensure that all would follow the same procedure. However, you can never completely rule out human error and therefore is it likely that the dataset has some inconsistencies which may also distort the outcomes of my study.
Another limitation is the loss of data in this study. I started with a dataset consisting of a large number of M&A deals and the final sample has become substantially smaller due to missing variables. A lot of the missing variables come from specific firm information such as number of employees and financial information. It would be preferable to have a larger sample size in order to be more representative of the real world. The problem of data loss can probably be overcome in the future by trying to get the missing information from the firms themselves instead of only focusing on openly available information.
Furthermore, the measure for layoffs is not completely accurate. To measure layoffs in this study, I used the total number of employees and its changes over the years. It could very well be that a decrease in the number of employees were not all layoffs, but also voluntary resignations, for example. This has been a conscious choice, as it is more difficult to find the number of layoffs for a firm, while the number of employees is often information that is openly available. By focusing only on layoffs, the dataset for this study most likely would have been considerably smaller.
5.4 Further research
The first suggestion for future research is to further investigate what causes layoffs after an M&A. As has been suggested by O'Shaughnessy and Flanagan (1998), it could be that different types of M&A’s may also lead to different types of layoffs. Making a distinction between objectives of M&A’s and its layoffs could lead to different insights on why layoffs happen. In addition, it would be interesting to then find out whether cultural differences would affect the number of layoffs in some specific types of M&A’s.
In addition, I also suggest future research to investigate the relationship between cultural distance and layoffs in other industries. As other studies have also shown, different industries can also have different layoff outcomes in M&A’s (Lehto & Böckerman, 2008). Thus, it may be the case that cultural distance does influence the number of layoffs after M&A’s in specific industries.
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7. Appendices
Appendix A: Distribution of Missing Values
Table A.1: Number of missing values per variable
Variable Number of missing values
Total Employees 3,641 Cultural Distance 2,982 Hostility 49 ROA acquirer 672 ROA target 3,948 Type relatedness 567 Geographical distance 420 Relative size 4,144 Deal size 889
Table A.2: Number of missing values per observation
Missing values Number of observations
Appendix B: Dictionary to measure Cultural Fit by Hanisch et al. (2018)
Table B.1 Inductively Identified Dimensions and Associated Words in ‘About Us’ Sections
aDimensions Description Words and Lexemes in Dictionariesb
Time An organization’s temporal
orientation.
Past: ago, ancient, decade*, established, experience*, former*, heritage, histor*, last, legac*, old*, past,
previous*, tradition*; Present: agenda, availab*, contemporary*, current*, daily, day, exist*, now, ongoing, recent*, status, today; Future: ahead, become, expect*, future, later, next, plan, planning, plans, tomorrow, vision*; Long-term: always, constant*, continu*, era, long duration, long run, range, standing, long-term, long-time, maintain*, preserv*, stability, stable, sustain*, years; Short-term: accelerat*, agil*, dynamic*, fast*, flexib*, promptly, quick*, rapid*, short*, speed*, timely, urgent*
Responsibility An organization’s concern for its internal and external environments.
Society: accountable*, charit*, citizen*, community, compliance, complies, comply, donat*, ecolog*, ethic*,
footprint, honest*, integrity, justice, mankind*, moral*, neighbo*, philanthrop*, public*, responsib*, societ*, stakeholder*, transparen*, welfare; Organizational members: career*, colleague*, employ*, manage*, our*, personnel, staff, team*, training*, we, workplace
Motivation An organization’s motivations that guide its decision-making.
Prevention: *risk*, accura*, assur*, avoid*, careful*, conscientious*, control*, ensur*, mistake*, prevent*,
problem*, protect*, safe*, secur*, threat*, uncertain*, vigilan*; Promotion: *courag*, accomplish*, achiev*, advance*, aspira*, aspire*, attain*, augment*, chanc*, confidence, confident, desir*, empower*, enhanc*, expan*, foster*, goal*, grow*, imagin*, impact*, improve*, leverag*, opportunit*, possibilit*, potential*, progress*, promis*, promot*, pursu*, reach*, striv*, wish*; Rational: analy*, because, competen*, consequen*, data*, demonstrat*, evidenc*, expert*, know*, logic*, measur*, method*, mind*, proof*, proven, proving, rational*, reason*, result*, skill*, therefore, think*, thought*, thus, understand*, valid*, why; Emotional: belie*, compassionat*, dedicat*, devot*, emotion*, enthusias*, excit*, feel*, fun, inspir*, lov*, passion*, pride, proud, spirit
Innovation An organization’s approach to innovation and proclivity for change.
Closed: exclusiv*, independen*, in-house, internal*, own*, patent*, propert*, proprietary; Open: alliance*,
co-develop*, collaborat*, cooperat*, external*, franchis*, hand-in-hand, joint venture, licens*, partner*, sharing;
Explore: academic*, curios*, discover*, experiment*, invent*, investigat*, laborator*, learn*, research*,
scholar*, scien*, search*, studi*, study, test*, trial*, universit*; Exploit: cash*, commercial*, compete, competi*, distribute*, execute*, execution*, exploit*, financ*, manufactur*, market*, price*, pricing, produc*, profit*, revenue*, royalty, sale*, sell*, translation*, utiliz*; Technology: *therap*, antibod*, cell*, component*,
compound*, diagnos*, drug*, engineer*, enzyme*, feature*, gene*, high-tech*, intervention*, material*, medic*, molecul*, platform*, procedure*, prognos*, protein*, techn*, tissue*, vaccin*; Impact: alleviat*, betterment, care, caring, cur*, customer*, fight, heal*, help*, hope*, life, lives, patient*, suffer*, treat*, well-being
Strategy An organization’s positioning in the market.
Specialist: focus*, niche, segment*, speciali*, specialty; Generalist: array, beyond, breadth, broad*, diversif*,
entire, extensive, multifacet*, multiple, numerous, pipeline*, portfolio, range, several, spectrum, variety, various, wide; Pioneer: breakthrough, creat*, entrepreneur*, forefront, ground-breaking, novel*, pioneer*, revolution*, unmet, unprecedented, venture; Cost: *cost*, affordabl*, economical, generic*, inexpensive, over-the-counter;
Quality: best*, better, efficacy, excel*, leading, outstanding, profession*, quality, relia*, renowned, rigor*,
Appendix C: Distribution of Deal Types
Table C.1: Distribution of Deal Types in the used sample
Variable Frequency Percentage
Acquisition 672 77.06%
All Stock Transaction 5 0.57%
Majority Stock Purchase 11 1.26%
Merger 161 18.46%
Minority Stock Purchase 0 0%
Reverse Merger 2 0.23%
Stock for Stock 13 1.49%
Stock for Stock Merger 8 0.92%
