The moderating effect of CSR on the relation between an M&A announcement and the firm’s customer base.
Thesis
Research Seminar SIM
Author: R.B.T. van Looijengoed
Student number: S3531600
Email: r.b.t.van.looijengoed@student.rug.nl
Professor: Dr. J. Surroca
Faculty of Economics and Business
University of Groningen
Duisenberg Building, Nettelbosje 2, 9747 AE Groningen, The Netherlands
P.O. Box 800, 9700 AV Groningen, The Netherlands
http://www.rug.nl/feb
ABSTRACT
We argue that previous literature fails to recognize the impact on the external stakeholders in organizational changes like M&A’s. It is important to take external stakeholders, like customer relationships, into account as the customers are often the main objective for the organizational changes. This study addresses the question of whether or not an M&A announcement has a negative effect on the total amount of costumers because an M&A announcement may drive customers to find alternative options due to the uncertainty and risk involved, which will reduce the total amount of costumers after an M&A announcement. We extend the literature and conclude that an M&A announcement on its own have an negative relationship and a part of the customer base switched to another supplier, not only after the M&A deal but also after an M&A announcement. Secondly, we tested if Corporate Social Responsibility reduces uncertainty and risk and lower the negative effects on the customer base. We argue that the higher the level of CSR, the less negative the impact of an M&A announcement on the customer base because CSR limit the risk of organizational changes for customer relationships and thereby improve customer retention. This study contributes to the literature by stretching on the importance of the effect of an M&A announcement on the stakeholders and the role of CSR in organizational changes and provides several managerial implications.
Acknowledgment
TITLE
TABLE OF CONTENTS
INTRODUCTION ... 5
LITERATURE REVIEW ... 8
Mergers and Acquisitions... 8
Corporate Social Responsibility ... 10
METHODOLOGY ... 13
Measurements and Measures ... 16
Dependent Variable ... 16 Independent Variable ... 16 Moderator ... 17 Control variables... 17 EMPIRICAL ANALYSES ... 20 EMPIRICAL RESULTS ... 21 Main Analyses ... 21
Two Sample T-Test ... 21
Correlation Matrix ... 22
Regression Model ... 23
Robustness Check ... 25
Two Sample T-Test ... 25
Correlation Matrix ... 26 Regression Model ... 28 DISCUSSION ... 29 Summary Results... 29 Theoretical Implications ... 31 Practical Implications ... 32
Limitations and Future research ... 33
CONCLUSION ... 34
INTRODUCTION
Mergers and acquisitions (M&A’s) have become a popular strategy for firms to expand the organizational capabilities and improve the competitive market positions. M&A’s are generally used as a strategy to achieve growth, increasing the value creation for the stakeholders. M&A's as a strategy create synergy through economies of scales, applying knowledge and skills from one organization to another, and it helps to control a target firm's management to affect future performance (Halpern, 1983; Jensen & Ruback, 1983; Salter & Weinhold, 1979). Other motives to engage in M&A’s are sales or assets growth (Halpern, 1983), increasing the management’s prestige or power (Rhoades, 1983), and reduction of uncertainty in the external environment (Pfeffer, 1972). Despite all the advantages the M&A strategy provides, it also has critical challenges.
This paper addresses the question of whether or not an M&A announcement has a negative effect on the total amount of costumers. It is important to know the effect of an M&A announcement on the number of costumers because “the aim of the acquisition may be to get control of the exchange relationships, to change their character or to change the connections between the relationships” (Johanson & Matsson, 1992, p.217). On the other hand, argue that “the control of the relationships by an M&A is never certain because there are always two actors involved," and an M&A not only affects the business relationship between the two firms but also influences the relationship with customers and suppliers of the two firms (Anderson et al., 2001). Despite the arguments that relationships cannot fully be controlled, firms often engage in M&A’s to acquire exchange relationships based on the assumption that the business relations are automatically required when a firm merges with or acquire another firm (Anderson et al., 2001). However, previous literature shows that in the majority of mergers and acquisitions, the combination of both a firm's exchange relationship is less than two (Mark & Mirvis, 1998), which indicates that some of the customers switch to another firm during the M&A process. Anderson et al. (2001) conducted a case study on the effect of an M&A on the costumers and found evidence that after the acquisition, several costumers started to buy from other companies. The reason for switching suppliers was that "they did not feel confident that the supplier would give the same priority to their orders as the focal firm had done previously" (Anderson et al., 2001, p 581). This shows that an M&A announcement might raise concerns by the customers regarding the consequences of the M&A for their relationship with the firm. The costumers may lack the confidence that the firm will fulfill its obligations and respect the previous agreements and commitment in terms of quality and product availability. The lack of confidence may result in the fact that customers will choose partners with lower risk and uncertainty levels, which eventually result in higher customer defection.
expectation that the firm will honor its commitment (Jensen, 2001) and respect previous agreements.
No empirical research has been done on the effect of an M&A announcement on the total amount of costumers. This is important because customers are part of the stakeholders that are influenced by the M&A, and the stakeholders have a great influence on the M&A process in terms of M&A success or failure (Hunt, 1990). It is important to take the impact of customer relationships into account when analyzing the impact of M&As because relationships can be seen as market assets for future use (Johnson & Matson, 1985). The external relationships give the firm access to resources of other business actors, and these market-based assets must be cultivated and leveraged to increase shareholder value (Srivastava & Shervani; Fahey, 1998) and form the basis for future innovation. The evaluation of market-based assets like customer relationships is difficult because of their largely intangible nature. But this complexity is creating value for the organization because a significant proportion of the market value lies in the intangible, off-balance sheets assets, and the tacit and subjective nature of customer relationships creates shareholder value. Secondly, the relationships with the costumers form a basis for future innovation because they provide access to other sources and provide the firm with opportunities to enter and act within other relationships (Anderson et al., 2001). Secondly, there is no specific literature about the moderating effect of CSR in organizational changes and in particular in the relationship between an M&A announcement and the total amount of customers. It is important to know the effect of CSR since Benttinazzi & Zollo (2017) have found that customer orientation in the pre-acquisition phase increases the quality in the understanding and evaluation of the customer's relationship and the ability to assess the target value more precisely. They show that the customer orientation results in a higher level of customer retention, cross-selling of products across customer bases, and new customer acquisitions.
customer relationships on the M&A process and future firm performance. We extend and contribute to the CSR literature by filling in the gap in the literature about the role of CSR in organizational changes like mergers and acquisitions, by empirically testing whether or not CSR will positively moderate the relationship between the M&A effects on the customer base so that the higher the level of CSR, the less negative the impact of the announcement on the customer base.
LITERATURE REVIEW Mergers and Acquisitions
The announcement of an M&A can be seen as a disruptive change in the relationship with the customers. It might increase the uncertainty and risk level of the costumers towards the firm, in terms of quality of the firm's activities and the outputs. An M&A not only affects the two organizations but affects others (in)directly connected parties in their M&A process (Johanson & Matsson, 1992). The reaction of those parties is bound to affect the business relationship and the changes in the initiated interaction between the two merging or acquired firms and cause multiple actions and counteractions in the network of relationships (Halinen, Aino, Salmi, Asta, Havila & Virpi, 1999).
A relationship takes time to develop and evolves over time, and the developed history of interaction between the partners creates a social memory. A business relationship is path-dependent, and the connectedness of the relationship indicates that both parties need to invest in the relationship. The social interaction between the partners will create trust or distrust based on the history in the relationship (Anderson, Hakansson & Johanson, 1994). Trust is an important element in a relationship because it creates confidence, decreases the uncertainty, fosters openness, supports psychological safety, encourages knowledge sharing and joint problem solving, and reduces monitoring cost (Lumineau, 2017). While on the other hand, distrust supports monitoring vulnerability, encourages constructive skepticism, supports vigilance, and enables healthy suspicion. It develops fear, paranoia, and increases monitoring costs (Lumineau, 2017).
ways perceived as fair by the exchange partner, and does not take excessive advantage of an exchange partner when the opportunity is available (Dyer & Chu, 2000).
If there is a long history between the partners, the partners can better predict the trustworthy behavior of the partner, which also complies with a supplier-buyer relationship. Dyer and Chu (2000)found evidence from the social/embeddedness perspective that the longer the duration of the relationship since the first supplier-buyer transaction, the higher the trust of the buyer in the supplier. Interaction based trust is an essential factor for the judgment of suppliers and buyers make an effort to establish close relationships with their supplier in order to trust the supplier. The process-based perspective argues that a set of institutionalized processes and routines employed at the supplier, which are not attached to individuals but are impersonal processes and routines, create a stable context for exchange. Dyer and Chu (2000)argue that a supplier selection process, which is based on a track record of the continuous repeated exchange, increases higher trust in the supplier because both parties have invested in the relationship through continuous, predictable, and consistent purchasing routines. Further, when there is assistance provided by the supplier to the buyer, it increases the trust in the supplier due to the reciprocity, which creates goodwill and commitment.
continuity of employment. The risk of default on the implicit contracts is high because the new partner can default the contract without legal recourse. Renegotiating the contracts might indicate worse conditions for the employees and suppliers but also for costumers because the firm might change the quality levels, prices, and product assortment. For example, when the company changes the contracts with its employees, the customers may expect the fact that in time, their contracts with the M&A also need to be renegotiated.
A prospective M&A announcement might raise concerns by the customers if the company will fulfill its obligations and respect the previous explicit and implicit contracts and commitment in terms of quality. The lack of confidence and fear eventually may result in the fact that customers will choose partners with lower risk and uncertainty levels. Mark and Mirvis (1998) stated that in the majority of mergers and acquisitions, the combination of one plus one yields less than two, which indicates that after the deal, some of the customers have left the firm. We expect that this is partly caused by the M&A announcement. We expect that after an M&A announcement, the total amount of consumers of the firm will decline because of the higher uncertainty and risk levels. We expect that in this case, it does not matter whether the M&A deal is completed of withdrawn because the announcement on its own will drive customers to find alternative options due to the uncertainty and risk involved, which will reduce the total amount of costumers after an M&A announcement. In other words, an announcement of engagement in M&A will decrease the total amount of costumers, which lead to the following hypothesis:
Hypothesis 1: The announcement of an M&A will have a negative impact on the total amount of the customer base.
Corporate Social Responsibility
practices of firms that address share- and stakeholders pressures associated with the embedding social norms and legalization into firms (Rathert & Rathert, 2015).
itself and its customers through CSR, which increased the likelihood that costumers will find out about the firm's CSR involvement and reward the firm for its CSR efforts. Schuler and Cording (2006) support the findings that the lack of customer awareness about the CSR initiatives is a major limiting factor in their ability to respond to these initiatives. McWilliams and Siegel (2001) stated that for CSR differentiation to be successful, the (potential) costumers must be fully aware of the CSR characteristics.
We expect that the CSR of a firm will positively moderate the relationship between the effects of an M&A announcement on the customer base, so that the higher the level of CSR the less negative the impact of the announcement of M&A on the customer base, because organizations with good CSR consider a wide range of stakeholders interest and safeguard their, transparency, trustworthiness, and accountability to all stakeholders (Jamali, Safieddine & Rabbath, 2008). Research shows that firms with high CSR engagement usually have more socially responsible agendas, and we expect that it reduces the uncertainty and risk levels of the customer towards the new M&A partner because the new partner has a stronger reputation for keeping their commitments. Skiftenis Flak, Rose, Skiftenes (2005) found evidence that firms with CSR engagement indeed consider stakeholder interest more profoundly in their decision making processes.
The stronger reputation enables the costumers to predict the trustworthy behavior of the partner better. CSR creates a perspective that the firm has a stronger incentive to contribute resources and effort to the firm to keep its commitments and obligations towards their customers. Secondly, CSR reduces the information gap between the firm and its customers, which makes it more likely that costumers will find out about the firm's CSR involvement and trust the new partner more quickly. CSR, in this case, will weaken the behavioral uncertainty and risk levels of the new partner and will lower the defection rate. Thirdly, CSR improves customer satisfaction, which results in increased customer retention and improves the profitability of the firm (Reichheld & Sasser, 1990). The U.S. Office of Costumer Affairs conducted research that shows that it can be five times as costly to attract a new customer than keep an old one (Fommel, 1987; Wemerfelt, 1988). CSR will lower the defection rate trough customer satisfaction and thus positively influence the negative effect of the CSR on the customer base.
the announcement of M&A on the customer base. Figure 1 depicts the basic relations of my conceptual model.
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Figure 1. Conceptual model research design.
METHODOLOGY
The sample of this research is the consultancy industry. The consulting industry has exploded and occupies a large and increasing number of people, and during the last two decades, organizations mainly relied on advice from lawyers and auditors. Statistics show that that there is an exceptional growth of services like I.T. consulting, management consulting, investment consulting, and temporary staffing consulting and auditing firms have added advisory services to their portfolio (Furusten & Werr, 2005). This growth is mainly driven by the strive for efficiency, flexibility, and to get access to the latest expertise. However, relying on external expertise for specialized knowledge is not unproblematic because organizations leave control of the content and quality of the needed services to the mechanisms of the external markets.
In the consulting industry, the buyer of expert services is vulnerable. The relationship between the buyer and the supplier is characterized by knowledge deficiencies and the fact that the buyer put himself into a dependent position regarding the supplier. This dependent position might be perceived as uncomfortable by the client and illegitimate by the environment (Maister, 1993 & Schein, 1988). This shows that trust and confidence in the partner is an important factor in the
M&A announcement Customer base
consulting industry because the buyer is vulnerable for exploitation but is assumed to be protected by the consultant's professional ethics and norms (Furusten & Werr, 2005). Trust based on close interaction is an essential mechanism because close interaction enables the customer to judge whether the supplier is trustworthy or not. The personal experience of the buyer towards a consultant and the experience with their colleagues are important criteria for choosing a consultant (Clark, 1995). Interaction based trust is an essential factor for the judgment of suppliers, and buyers make an effort to establish close relationships with their consultant in order to trust the consultant (Glucker & Armbruster, 2003).
The consultancy sector is used as the population of interest in this study because they are sophisticated clients of the merging or acquired firm, which enhances the probability that there will be changes in the amount of customer base of the firm. The data that we will use can be classified as secondary data because a third party has collected and stored the data in an accessible database (Blumberg, Cooper & Schindler, 2014). The sample consists of 661 organizations from 57 different countries in the consultancy-sector, from which 336 firms made an M&A announcement on 01-01-2015 until 01-01-2018. The other 315 consultancy firms were added as a control group and which were controlled by year, to exclude other external factors, so that the dataset, results, and conclusions become more representative.
which is in this case, the effect of an M&A announcement on the efficiency ratio, is right, we support the main analyses with a robustness check. We conducted a robustness check with a reduced sample of 84 firms and tested whether the total amount of customers after the announcement but before the completion of the deal was lower than before the deal. When the results of the robustness check support the hypothesis, then the results of the main analyses are stronger. As stated before, we conducted a robustness check with a reduced sample, 42 consultancy firms with an M&A announcement between 01-01-2015 until 01-01-2018, and 42 consultancy firms without an M&A announcement but were active in the same year. The robustness check is based on the absolute numbers of costumers before and after the announcement. The condition to measure the number of customers in the customer base is to measure the number of costumers before the announcement and after the announcement but before the deal is completed. The condition tackles many confounding factors that may provide another explanation of the results that makes it very difficult to disentangle. It could be that when organizations merge, the buyer divides the target into different pieces, and some are incorporated, and others are sold, which will result in a reduction of customers before and after the deal. Overall, when taking the results of the comparison the number of customers before and after the M&A deal, the results are biased by confounding factors.
Measurements and Measures Dependent Variable
The dependent variable, "Costumer base," is measured with the efficiency ratio; total sales/total assets. This measure is based on the assumption that when customers leave the firm, the efficiency rate will be lower. This ratio is important because various researchers have shown that the higher the customer defection rate of the firm, the lower the efficiency and the profitability performance (Reichheld & Sasser, 1990). Fommel (1987) and Wemerfelt (1988), showed that customer satisfaction influences profitability through customer retention. The U.S. Office of Costumer Affairs conducted research that shows that it can be five times as costly to attract a new customer than keep an old one. In other words, when the firm switches to another supplier, the efficiency rate will be lower. We measure the average efficiency rate of the three quarters before the announcement of the deal and compare it with the efficiency between the completion and announcement and check whether there is a change in the efficiency which is caused by customer defection as a result of the M&A announcement.
Secondly, in the robustness check, the dependent variable “Costumer base” will be measured with absolute numbers of costumers. The independent variable will be measured by the total number of customers before the M&A announcement and after an M&A announcement but before completion of the deal.
Independent Variable
Moderator
The moderator is CSR performance, and to find information about the CSR performance; the Eikon database is used. The CSR performance will be measured through the Thomas Reuters ESG Combined Score, which is based on the reported information in the environmental, social, and corporate governance pillars (ESG Score) with an ESG Controversies overlay. The ESG are defined in the Eikon database as follows;
Social pillar: This pillar measures the “capacity to generate trust and loyalty with the workforce of the organization, their customers, and the relationship with the society, through its use of best management practices” (Eweje & Bathurst, 2017). The score reflects the reputation and the health of the license to operate. All these factors are key factors and form the base for shareholder value in the long term (Eweje & Bathurst, 2017).
Environmental pillar: this pillar measures the impact of organization on “the living and non-living natural systems” (Eweje & Bathurst, 2017). The score shows how the management practices are successfully used “to avoid environmental risks and capitalize environmental opportunities in order to generate long term shareholder value” (Eweje & Bathurst, 2017).
Corporate Governance pillar: This scale measures the systems and processes of the organizations that ensure that the board members of the organization and the executives will act in a way that it benefits the long-term shareholders. The Corporate Governance score is a “reflection of the capacity of the organization to control the responsibilities and rights through incentives to generate long term shareholder value” (Eweje & Bathurst, 2017).
In the calculation of the ESG Combined Score, a percentile rank scoring methodology is used to eliminate hidden layers of calculations. In Eikon, the CSR performance score from 0 (low) until 1 (high).
Control variables
This study added nine control variables that are held constant in order to assess the relationship between multiple variables. In order to allow us to better understand the relationship between the customer base (Efficiency Ratio) and M&A announcement, we added eight control variables that are divided into two groups, namely firms' characteristics and country characteristics.
often assumes that larger firms are better positions to engage in CSR (Husted & Salazar, 2006) Smaller firms have in general lower intertie forces and possess structures that are more flexible, which strengthens the effect on the customer defection and CSR, but on other hand often have a lack of resources such as human or financial capital (Jenkins, 2004). The size of the firm will be determined by the total amount of employees (Boone, Field, Karpoff & Raheja, 2006).
Industry. The second control variable is an industry, which is an important control variable because not all the acquiring firms are located in the same consultancy industry. We need to control for industry because the industry has a significant impact on firm socially responsible behavior because of the differences in resources and stakeholder management (Post, Rahman & Rubow, 2011). We measure the industry through the Thomas Reuters Combined Industry Score that estimates the available resources and stakeholder management per industry in which the firm is operating. It provides a score for every industry per firm, from low (0) until high (50), based on a combined model of structural, smart ratio, and text mining credit risk models.
Firm age. The third control variable is the firm age. Firm age influences the dependent variable because young firms might have a greater failure risk because they might have a lack of valuable resources (Thornhill & Amit, 2003). We expect that firms that have experience regarding mergers or acquisitions may influence the dependent variable. For example, firms that have experience with M&A may value customer relationships more accurately. Older firms are expected to have more experience and have larger earning in comparison with the younger ones, and CSR consists of complex decision making and requires a large capital injection, so it is assumed that the age of the firm has an impact in the CSR performance of an organization (Rao & Tilt, 2016). The firm age will be determined by the number of years that the firm exists.
Reputation. Reputation is a determinant of customer retention (Milan, Eberle & Bebber, 2015). The reputation is measured Thomas Reuters Retailing Responsibility Score, which measures the extent to which the company promotes and supports public health and the Product Responsibility Score, which measures the impact of the firm's products or services on customers and community, customer health and safety, fair trade, privacy, etc. It provides a score for every industry per firm, from low (0) till high (100), based on a combined model of the Thomas Reuters Retailing Responsibility Score and Product Responsibility Score.
by the Thomas Reuters Controversy Score which is a combination of the Environmental Controversy Score which includes the environmental impact of the company's operations on the natural resources, Product Access Controversy Score which considers information if the company's product were accessible for everyone, Controversies Responsible Marketing Score include the controversies that are published in the media linked to the company's marketing practices like misleading marketing, and Controversies Privacy Score which includes the controversies linked to employee or customer privacy and integrity, Controversies Customer Health & Safety and Controversies Responsibility R&D. The Thomas Reuters Controversy Score is measured from low (0) until high (100).
Change in price. An increase in the prices may have a negative impact on customer retention (Homburg, Hoyer & Koschate, 2005). We measure the net price difference between the latest completed day and the closing price from a calendar year ago.
GDP growth. The seventh control variable will be the GDP growth because wealthier countries may have higher restrictions regarding CSR (Chen, Hung & Wang, 2018). GDP growth for every country will be included as a measure to control for GDP (Cox, Strudwick, Paton & Schroder, 2011) because firms from wealthier countries may score higher in terms of CSR. GDP growth also influences M&A like, for example, that countries with GDP growth reduce the overall portfolio risks (Boateng, Hua, Udin & Du, 2014).
EMPIRICAL ANALYSES
This study used Ordinary Leas Squares (OLS) regression to test the relationship between an M&A announcement and the customer base, measured by the efficiency ratio, total sales divided by the total assets. It measures the difference in the average efficiency ratio of the three quarters before the announcement with the efficiency after the announcement but before the deal, compared with the control group. The OLS regression estimates the relationship minimizing the sum of the squared in the difference between the observed and predicted values of the efficiency ratio. The dependent variable is the Efficiency ratio, and the independent variable is the M&A announcement, The control variables in this regression are Firm Size, Industry, Firm Age, Reputation, Controversy, Change in price, GDP growth, Overall Country Risk. The OLS regression is a statistical method that produces the one straight line that minimizes the total squared error.
The first issue this study addresses is heteroscedasticity, which occurs when the residuals at every level if the predictor variables are not constant (Lewis & Linzer, 2005). Heteroscedasticity is present when the size of the error term differs across the values of an independent variable. Heteroscedasticity could result in biased test statistics due to the biased estimates of standard errors, which may result in hypothesis testing, which can be considered abnormal. When there is heteroscedasticity, the standard error must be corrected through the White Heteroscedasticity Consistent standard errors in the regression model. To test the data, whether there is heteroscedasticity, a Breach-Pagan /Cook-Weisberg test is used, which fails to accept the null hypothesis with a p-value of 0.000. The results of the Breach-Pagan /Cook-Weisberg test show a large chi-square value of 49.71 and a Prob > chi of 0.0000, so the null hypothesis is rejected, which indicates that there is heteroscedasticity. As heteroscedasticity is present in this study, the standard error must be corrected for heteroscedasticity (Lewis & Linzer, 2005). We accounted for heteroscedasticity by using the With Heteroscedasticity Consistent (robust) standard errors throughout the regression model.
the announcement but before the deal, compared with the control group. The OLS regression estimates the relationship minimizing the sum of the squared in the difference between the observed and predicted values of the efficiency ratio. The dependent variable is the total amount of customers, and the independent variable is the M&A announcement, The control variables in this regression are Firm Size, Industry, Firm Age, Reputation, Controversy, Change in price, GDP growth, Overall Country Risk. We tested the data for heteroscedasticity by using a Breach-Pagan /Cook-Weisberg test. The results of the test indicate again that there is heteroscedasticity. We accounted for heteroscedasticity by using the With Heteroscedasticity Consistent (robust) standard errors throughout the regression model.
The normality of both datasets is tested by the Shapiro-Wilk test. It is important that the variables seem to be normality distributed because a violation of normality can lead to a biased p-value and hence affect the significance of the test results. The results of the Shapiro-Wilk test is conducted on both datasets, and the null hypothesis is rejected when the p-value is exceeding 0.05; thus, all variables of both datasets seem to be normally distributed.
EMPIRICAL RESULTS Main Analyses
Two Sample T-Test
made no M&A announcement have a significantly higher mean of efficiency ratio than the group of firms that have made an M&A announcement.
Table 1 Two-sample T-test
Group Obs Mean Std. Err. Std. Dev. [95%Conf. Interval]
0 315 87.16851 3.803632 82.81092 79.6944 94.64261
1 336 24.20986 5.146689 76.68394 14.06699 34.35273
combined 661 67.08687 3.260553 86.01929 60.68516 73.48859
diff 62.95864 6.399689 50.38266 75.53463
diff = mean(0) - mean(1) t = 9.8378 Ho: diff = 0 Satterthwaite's degrees of freedom = 653.709
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 1.0000 Pr(T > t) = 0.0000 Pr(T > t) = 0.0000
Correlation Matrix
3 shows that the variable controversies have a VIF of 3.68, and the model has an overall VIF of 2.47, which is under the threshold of 10 (Alauddin & Nghiemb, 2010), and suggest that in this research multicollinearity is not a problem.
Table 3
Variance Inflation Factors
Variable VIF 1/VIF
M&A Announcement 1.50 0.665478 M&A Announcement *CSR performance 2.15 0.465756 Country Risk 1.03 0.972654 GDP_Growt 1.00 0.995844 Industry 1.02 0.984966 Firm Size 1.22 0.816744 CSR Performance 8.77 0.113973 Firm Age 1.01 0.991096 Price Change 1.01 0.986690 Controversies 3.68 0.271671 Reputation 4.82 0.207637 Mean VIF 2.47 Regression Model
level of 0.05 with a coefficient of .1380601. The results in Table 4 show significant support for the second hypothesis; The CSR of a firm will positively moderate the relationship between the M&A effects on the customer base so that the higher the level of CSR, the less negative the impact of the announcement of M&A on the customer base. CSR performance as a control variable also has a significant positive effect on the relationship between the M&A announcement and the efficiency rate. The overall significant test of the model is 0.000, which is under the required alpha level (0.05). The R-squared of 0.2140 indicates that 21.40 percent of the Efficiency Ratio can be predicted from the variables 1-9. In other words, 21.40 percent of the variance in the efficiency ratio trough the M&A announcement can be predicted from the nine control variables. The last variable _cons represent the constant or Y-intercept, which refers to the height of the regression line when it crosses the Y-axis, the predicted value of the Efficiency Ratio when all other variables are 0. Table 4 Regression Analyses Number of obs = 661 F(10, 65) = 19.24 Prob > F = 0.0000 R-squared = 0.2140 Root MSE = 76.047 Robust
Robustness Check Two Sample T-Test
To test the hypothesis, we conducted a two samples independent T-test to test whether or not there is a significant difference between the means of the two groups and whether or not the difference is significantly higher or lower than the control group. Table 5 provides the results of the independent sample T-test, based on the reduced sample of 84 firms that contains information on the total number of customers. The independent T-test compares the means of the two groups, in this case, the group of firms that make an M&A announcement (0) and the control group (1). The t-statistic is 2.0263 with 41.2079 Satterthwaite's degrees of freedom, and the corresponding two-tailed p-value Pr (|T| >|t|) is 0.0492, which is less than 0.05. We can conclude that the difference in means of the total amount of customers between the group of firms that made an M&A announcement and the control group is different from 0, allowing for the difference in variances across groups. Secondly, the corresponding p-value of the one-tailed p-value Pr (T > t) is 0.0246, which is less than the pre-specified alpha level 0.05, indicating that the difference in means of the control group is significantly higher than zero. The results confirm the expectation that the group of firms that made no M&A announcement have a significantly higher mean of the total amount of customers than the group of firms that made an M&A announcement
Table 5 Two-sample T-test
Group Obs Mean Std. Err. Std. Dev. [95%Conf. Interval]
0 42 582.8571 153.1199 992.3302 273.6253 892.089
1 42 -5586.57 3040.85 19706.96 -11727.69 554.549
combined 84 -2501.85 1550.572 14211.23 -5585.883 582.169
diff 6169.429 3044.702 21.46958 12317.39
diff = mean(0) - mean(1) t = 2.0263 Ho: diff = 0 Satterthwaite's degrees of freedom = 41.2079
Correlation Matrix
A Pearson correlation coefficient test is conducted on the reduced sample to measure the statistical relationship of the variables. In Table 7, the Pearson correlation matrix between the dependent variable Total amount of Customers, independent variable M&A announcement and the control variables CSR performance, Firm Size, Industry, Firm Age, Reputation, Controversies, Change in price, GDP growth, Overall Country Risk are presented. The correlation matrix shows that an M&A announcement has a significant correlation coefficient of -0.2148 with a significance level of 0.05, which confirms our expectations there is a negative correlation between the total amount of customers and the M&A announcement. One unexpected correlation is CSR performance, which is negatively correlated with the total amount of customers, while we expected that CSR would have a positive correlation.
In Table 7, the correlation matrix shows a highly significant correlation of 0.9543 between firm size and the number of customers, which could indicate that there is multicollinearity. An additional test for multicollinearity, the Variance Inflation Factors, is conducted. Table 6 shows the results of the test and reveals that the Firm size has a VIF of 1.31. When the VIF is under the threshold of 10 (Alauddin & Nghiemb, 2010), multicollinearity is not a problem. The overall VIF is 2.62, and the highest VIF is 7.30 for CSR performance and a VIF of 5.34 for reputation, which shows that there is no multicollinearity.
Table 6
Variance Inflation Factors
Variable VIF 1/VIF
between and announcement of an M&A, and the customer base measured the total amount of customers. The regression model presented in Table 8 shows support for a negative relationship between the M&A announcement and the total amount of customers. We found support for the first hypothesis that the M&A announcement has a negative effect on the total amount of customers with a coefficient of -2.867308 and a p-value less than 0.05. The results of the regression confirm the first hypothesis and support that an M&A announcement will have a negative impact on the total amount of customers. Secondly, the results show that the coefficient of the interaction of CSR performance is in the expected direction; however, it is not significant. This may be caused by a reduced number of observations for these analyses, and it may be that when the analyses are done with more observation, the results will probably support the second hypotheses as well.
Table 8 Regression Analyses Number of obs = 84 F(10, 65) = 23.22 Prob > F = 0.0000 R-squared = 0.9385 Root MSE = 4007.2 Robust
Number of Customers Coef. Std. Err. t P>t [95% Conf. Interval] M&A Announcement -2.867308 1.250.272 -2.29 0.025 -5365.014 -369.603 M&A Announcement*CSR .0043834 .0056344 0.78 0.439 -.0068725 .0156393 Industry 2.847693 5.677.226 0.50 0.618 -8493.871 14189.26 Firm Size -.0905516 .0068867 -13.15 0.000 -.1043093 -.0767939 Firm Age -.0516694 .5966529 -0.09 0.931 -1.243621 1.140282 CSR performance .0121912 .0044704 2.73 0.008 .0032605 .0211219 GDP Growth -.8851538 413.009 -0.21 0.831 -9.135956 7.365649 Controversies 2.214298 3.228.131 0.07 0.946 -62.27503 66.70362 Reputation -1.049805 6.372.712 -1.65 0.104 -232.29 22.32909 Price Change 6.638588 8.499.705 0.78 0.438 -10.34152 23.6187 Country Risk -1.586801 8.430.374 -1.88 0.064 -327.0962 9.735931 _cons 2.628645 1.245.409 2.11 0.039 140.6548 5116.636 DISCUSSION Summary Results
(2002) that found evidence that after the acquisition, several costumers started to buy from other companies because they were not confident that the supplier took their relationship as important as before. We expected that the lack of confidence and fear eventually might result in the fact that customers will choose other partners with lower risk and uncertainty levels. In line with the research of Mark & Mirvis (1998) who stated that in the majority of mergers and acquisitions, the combination of one plus one yields less than two regarding the customer relations after the deal, we expected that after an M&A announcement, the total amount of consumers of the firm will decline because of the higher uncertainty and risk levels for the customers. In other words, we expected that costumers would switch to partners with lower uncertainty and risk level, which reduce the total amount of costumers after an M&A announcement. The results of the T-test confirm that the group of firms that made an announcement have a significantly lower efficiency rate and lower amount of customers after an M&A announcement than a firm that made no M&A announcement. This is confirmed by the results of the regression analyses, which found significant support for hypothesis 1; "The announcement of an M&A will have a negative impact on the total amount of the customer base."
coefficient of the interaction of CSR performance is in the same direction, however it is not significant on conventional levels, which is caused by the reduced number of observations. Based on both analyses, we can conclude that CSR will positively moderate the relationship between the M&A effects on the customer base, that the higher the level of CSR, the less negative the impact of the announcement on the customer base.
Theoretical Implications
The M&A literature mainly concentrates on the organizational fit, integration process, and the causes of failure of M&AS's but fails to recognize the company's external business relationships in the M&A process. We argue that it is important to take the external business relationship into account because customers are part of the stakeholders that are influenced by the M&A, and the stakeholders have a great influence on the M&A process in terms of M&A success or failure (Hunt, 1990). It is important to take the impact of customer relationships into account when analyzing the impact of M&As because relationships can be seen as market assets for future use (Johnson & Matson,1985). Secondly, M&As are mostly based on the assumption that business relations are automatically required when a firm merges with or acquires another firm (Anderson et al., 2001), while previous literature show that in the majority of mergers and acquisitions the combination of both firm’s customer relationship is less than two (Mark & Mirvis, 1998).
This research advances previous literature and is built upon the study of Anderson et al., (2001), who conducted a case study on the effect of an M&A on the costumers and found evidence that after the acquisition, several costumers started to buy from other companies. They found that the main reason for switching suppliers was that "they did not feel confident that the supplier would give the same priority to their orders as the focal firm had done previously" (Anderson et al., 2001, p 581). This study showed that an M&A announcement might raise concerns by the customers and suppliers regarding the consequences of the M&A for their relationship with the firm. We extend the literature and conclude that an M&A announcement on its own have an negative relationship and a part of the customer base switched to another supplier, not only after the M&A deal but also after an M&A announcement.
customer bases was less than two, and we found that the M&A announcement, on its own, will lower the total amount of costumers in the customer base. This research creates theoretical awareness to take the customer into account when considering an M&A and incorporate the effect of an M&A announcement in the M&A processes.
We argue that little research has shown the role of CSR performance in organizational change of M&A for the customers. We filled in this gap, and our and we conclude that the CSR performance of a firm will positively moderate the relationship between the M&A effects on the customer base. We extend and contribute to the CSR literature by showing that CSR is beneficial because it positively moderate the relationship between the M&A effects on the customer base, so that the higher the level of CSR, the less negative the impact of the announcement on the customer base. This study extends the research of Benttinazzi & Zollo (2017), who suggest that CSR performance increases the quality in the understanding and evaluation of the customers' relationship and the ability to assess the target value more precisely. They show that CSR performance results in a higher level of customer retention, cross-selling of products across customer bases, and new customer acquisitions. We extend the literature by showing that CSR performance indeed lowers the negative effect of an M&A announcement and improve customer retention. It shows that firms with a higher CSR performance have lower negative effects from an M&A announcement on their customers and lower risk of negative effects on the customer base and future performance when the deal in not completed or fails. We argue that the higher the level of CSR, the less negative the impact of an M&A announcement on the customer base because CSR limit the risk of organizational changes for customer relationships and thereby improve customer retention.
Practical Implications
and fewer sales of the remaining customers and loss in efficiency may have a large impact on future firm performance. The policymakers must take the negative effects of the M&A announcement on their customers into consideration because when the deal fails or is withdrawn, the total amount of customers will be lower.
Secondly, we showed that investments in CSR is beneficial for the firm. To lower the negative effects of an M&A announcement, the firm must invest CSR when considering an M&A because it gives a clear signal to the stakeholders that the firm will respect the explicit and implicit contracts. The firm must invest in CSR performance because it lowers the negative effects of an M&A announcement on their customers and lower risk of negative effects on the customer base and future performance. We found that the higher the CSR performance the more beneficial CSR will be for the firm.
Limitations and Future research
Despite the contributions, several limitations must be taken into account. In the calculation of the total amount of customers, we make use of the efficiency ratio instead of the absolute number of customers since the absolute numbers of costumers in the period before and after the M&A announcement was not available in the databases. Instead of absolute numbers, we use the efficiency ratio based on the results of the previous literature, which stated that the efficiency and the profitability performance of the firm would be lower (Reichheld & Sasser, 1990). This is a limitation because it is not built on absolute numbers of customers but on the efficiency ratio, which increases the risk that unobserved factors influence the results. We conducted a robustness test of a reduced sample, which included the absolute number of firms instead of the efficiency ratio, to make the results stronger. The problem is that it was a reduced sample of 41 firms, which lowers the validity of the results. Future research may use absolute numbers of customers and use surveys or interviews to investigate more deeply the reasons for leaving to another supplier after an M&A announcement.
condition is not met, the customers will not respond positively to CSR, and there will be no moderation. We have incorporated CSR data of three quarters before the deal, which may be too little to deal with the congruency condition. Future research in the moderating effect of CSR in the relationship between M&A announcement and the customer base may incorporate a more extended dataset of CSR to deal better with the congruency condition.
Thirdly, we investigated firms that made M&A deals in the consultancy sector spread in 57 countries over the world. This brings limitations to this research because there might be various in industry and across countries in the relationship between the buyer and supplier and in CSR restrictions. It may be that the results are industry-specific because we expected that the consultancy sector is a sector whereby trust is an important factor in the buyer-supplier relationship. We based our research on the assumption that the buyer-supplier relationship is homogeneous across countries, but the buyer-supplier relationship may have different characteristics across countries and industries (Martinsuo & Ahola, 2010). Future research may investigate the results over different industries and investigate the buyer-supplier relationship differences across more deeply.
CONCLUSION
performance. Secondly, the firm must invest in CSR performance because it lowers the negative effects of an M&A announcement on their customers and lower risk of negative effects on the customer base and future performance.
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