June 25th, 2018
MASTER THESIS
The anxiety-reducing properties of corporate social
responsibility in the context of M&As
Nicolas Rittmeyer Student number: 2348241 N.rittmeyer@student.rug.nl
Word count: 13.428
Supervisor: prof. dr. J. Surroca Co-assessor: dr. H.C. Bruns
MSc. Business Administration – Change Management Faculty of Economics and Business
2
Abstract
This study examines the effect of corporate social responsibility (CSR) on the level of anxiety employees experience in the context of merger and acquisition (M&A). Using data from Thomson Reuters’ Datastream, ASSET4, and Zephyr database, the present study empirically tests if CSR performance affects the level of anxiety employees experience in the context of an M&A. In this respect, this study uses a sample of 118 internationally operating firms and applies a hierarchical regression analysis to determine if and to what degree the level of anxiety experienced by employees is influenced by both social and historical CSR aspirations, and a discrepancy between organization’s internal and external CSR activities. By doing so, the paper aims to contribute to both strategic CSR and M&A literature by enhancing our understanding as to why still so many M&As fail to live up to their expectations. The results indicate that CSR, in fact, may have anxiety reducing properties in extremely ambiguous situations such as an M&A. Moreover, this relationship is positively moderated by the level of CSR engagement within the same industry.
Keywords: Corporate Social Responsibility, Merger and Acquisition, Employee anxiety,
3
1. Introduction
Mergers and acquisitions (M&As) have become an increasingly popular means in recent decades for companies to acquire knowledge and to leverage complementary resources. Nevertheless, Seo and Hill (2005) point out that “in the majority of mergers and acquisitions (M&As), the combination of one plus one yields less than two” (p.422). Accordingly, studies show that more than half of M&As do not accomplish the outlined objectives (e.g., Deller & Klendauer, 2008)
4
do not possess sufficient information to make valid justice judgments regarding their future treatment. Aguilera et al. (2007) argue that in these situations employees may use CSR as an intermediary variable for fairness. Although there is a multitude of conflicting definitions for CSR, the following definition appears to incorporate most elements: CSR is defined as “situations where the firm goes beyond compliance and engages in actions that appear to further some social good, beyond the interests of the firm and that which is required by law” (McWilliams, Siegel, & Wright, 2006, p.1). Following Aguilera et al. (2007) line of reasoning, Bauman and Skita (2012) state that “CSR indicates to employees that their organization is generally committed to social justice across stakeholder relationships and can be trusted to provide them with the outcomes they deserve” (p.70).
5
M&A. At the same time, this study provides practical insights into how managers can diminish the degree of anxiety suffered by their employees and how to mitigate the potentially harmful ramifications of individuals experiencing high levels of anxiety.
Based on the identified literature gap and the goals of this research, the following research question emerges: “What is the relationship between an organization’s corporate
social responsibility activities and the level of employee anxiety in the context of an upcoming M&A?”
The contribution of this study is threefold. Firstly, this study sets out to enhance our understanding related to the role of CSR in the context of M&As. More specifically, the study investigates if and to what degree CSR might provide employees critical indications as to how they can expect to be treated in the future and the subsequent influence this inference might have on their level of anxiety. Secondly, by doing so, this study sets out to further examine if CSR is eligible to function as a temporal heuristic in particularly ambiguous situations such as an M&A. Thirdly, the present study follows the popular request by various scholars to investigate further the ethical implications of M&As on to the people affected by it.
2. Theoretical foundation and hypotheses
This section outlines the theoretical foundation from which the hypotheses are
6 2.1 Anxiety theory
Levinson (1976) reminds us, “all change is a loss experience.” Therefore, it is reasonable to assume that M&As - which often involve large-scale organizational change and a considerable degree of uncertainty - frequently prompt employees to contemplate the potential negative repercussions the M&A may have on their future jobs and standing within the firm (Nahavandi & Malekzadeh, 1988). Ergo, employees often react to M&As with increased dissatisfaction, lower levels of commitment and productivity, disloyalty, and occasionally active resistance (Appelbaum et al., 2000). Ivancevich, Schweiger, and Power (1987) posit that during an M&A, individuals go through the five stages of the Kubler-Ross grief model (denial,
anger, bargaining, depression, and acceptance) as the consequence of a perceived loss with the
first stage (i.e., denial) typically starting in the pre-merger phase.
The felt degree of anxiety may differ significantly among individuals based on the characteristics of the M&A (Rentsch & Schneider, 1991) and an individual’s psychological predisposition to feel stressed and anxious (Buono & Bowditch, 1990). Nevertheless, scholars and practitioners agree on the fact that employees - when faced with a possible M&A - generally experience high levels of anxiety (Ivancevich, Schweiger, & Power, 1987). These feelings occur when employees fear the potential loss of their occupation, as such anxiety can trigger self-survival instincts within the individual (Seo & Hill, 2005). Thus, to protect their status and power, individuals often engage in political activities which consequently can lead to internal conflicts and destructive competition among colleagues (Ivancevich, Schweiger, & Power, 1987).
7
identity and purpose, which substantiate itself in the disenchantment with the firm and a shattered self-image (Ivancevich, Schweiger, & Power, 1987). M&As are a messy process wherewith a considerable number of outcomes and variables are not clearly defined before the M&A. The resulting ambiguity, and the mere workload associated with the M&A, regularly impedes managers to effectively communicate to their employees the repercussions the M&A will have on them. Consequently, anxiety spikes as uncertainty grow. This effect only fortifies by the flow of conflicting information and rumors that accompany these impactful events (Ivancevich, Schweiger, & Power, 1987). Moreover, the potential loss of one’s job does not only directly affect the person concerned but also one’s family as they have to deal with the potential loss of income and the emotional and psychological baggage that accompanies such an event. Lastly, individuals experience separation anxiety when they see or imagine another colleague is being laid off. Seo and Hill (2005) define separation anxiety as “a distinctive anxiety associated with the frightening situation of having a relationship change or drastically end” (p.426). As a matter of fact, an individual does not need to be laid off to feel separation anxiety, the mere presence of rumors may suffice to induce a strong emotional response (Seo & Hill, 2005).
8
situations such as M&As - which are typically accompanied by a significant amount of stress, anxiety, and increased workload - absenteeism reflects a severe issue to both the employer and colleagues. Absenteeism does not only present a financial burden to the focal company, due to the loss of productivity but with the same token, it further increases the level of stress employees experience as other employees must make up for the loss in the workforce.
2.2 Fairness heuristic theory
9
company. Research has shown that when employees perceive that they are being treated fairly, they are more likely to develop a perspective that is in favor of the change initiative even in circumstances of potential loss and calamity (e.g., Cobb, Folger, & Wooten, 1995; Neves & Caetano, 2006).
According to Seo and Hill (2005), “employee reactions to an organizational change such as M&A can be influenced by the following three types of fairness perceptions: (a) distributive justice, which is the fairness of outcomes received compared to an individual’s standard of fairness; (b) procedural justice, which is the fairness of procedures used to determine the outcomes; and (c) interactional justice, which is how the organizational members are treated by those responsible for determining outcomes and procedures” (p.431-432).
On a similar note, employees can utilize the same typology (i.e., procedural CSR, distributive CSR and interactional CSR) to not only evaluate how the focal company is treating its employees but also how it is impacting its broader social milieu (Aguilera et al., 2007). More specifically, procedural CSR looks at how employees judge the social engagement embedded in the organization’s activities. Distributive CSR examines the subsequent outcome of that action, whereas interactional CSR analyses how individuals within and outside the organization are treated as these actions are being executed. Aguilera et al. (2007) argue that “just as fairness heuristic theory predicts that fairness is used as a heuristic for trust, so do we propose that CSR is a heuristic for fairness” (p.840). Hence, employees may use CSR perceptions as a proxy to infer how justly they will be treated by the organization (Rupp, Shao, Thornton, & Skarlicki, 2013). In fact, in a study conducted by Jones, Willness, and Macneil (2009), the authors provide empirical evidence that a firm’s CSR positively influences applicants expected treatment and their subsequent intent to work for that firm.
10
Cropananzo, & Goldman, 2005). Prior research shows the positive influence of perceived justice on job satisfaction, turnover rate, absenteeism, organizational citizenship behavior, organizational commitment, and overall job performance (Colquitt, Conlon, Wesson, Porter, & Ng,2001; Aguilera et al., 2007). In contrast, perceived injustice can therefore lead to lowered job performance and at times even hostile behavior (Aguilera et al., 2007). As previously argued, individuals make use of fairness judgments in particularly ambiguous situations, where available relevant information is rare because it provides them with a sense of control and security (Rupp et al., 2006). Therefore, it follows that “an organization's CSR actions may indicate to employees that their organization also has concern for them” (p.540) which subsequently may have a positive effect on an individual's ability to cope with the uncertainty that surrounds M&A or in particular the pre-merger stage.
Hence, based on the previously elaborated inferences, the following hypothesis derives:
Hypothesis 1: CSR has a negative influence on the level of employee anxiety prior to
an M&A.
2.3 CSR aspirations in the context of M&As
11 2.3.1 Social CSR aspirations
CSR has become an increasingly important means through which internal and external stakeholders evaluate the reputation and the legitimacy of a company to operate (Lewis, 2003; Zyglidopoulos, 2003). Nevertheless, a firm's reputation for CSR is not absolute; it is at its core a relative construct comprising of a company’s actions relative to the activities of companies operating in the same or similar industry (Bertels & Peloza, 2008). Hence, reputation functions on a continuum and is compared to other organizations (Bertels & Peloza, 2008). Companies that operate in an environment which is characterized by, for example, a high level of CSR activity often feel obliged to engage in similar levels of CSR as they do not want to lag behind their direct competitors. Similarly, industries that have a bad public reputation (e.g., tobacco or oil industry) - facing scrutiny by the public - are generally expected by society to engage in ‘extra’ CSR (Bertels & Peloza, 2008). In these industries, a company's reputation is frequently difficult to be distinguished from that of its industry associates which therefore necessitates these additional efforts. Subsequently, it is not the absolute rate of CSR that is important; instead, the actions relative to those of its industry peers. Vlachos, Panagopoulos, and Rapp (2013) argue that if employees discern that other firms engage in CSR to a similar degree, then employees will primarily associate the focal companies CSR actions as opportunistic and self-centered, mostly caused by outside forces. Therefore, the following hypothesis derives:
Hypothesis 2: Industry CSR positively moderates the relationship between CSR and the
level of employee anxiety prior to an M&A. So, the higher the industry CSR, the less negative the relationship between CSR and level of employee anxiety prior to an M&A.
2.3.2 Historical CSR aspirations
12
13
Hypothesis 3: CSR historical aspirations negatively moderates the relationship
between CSR and the level of employee anxiety prior to an M&A. Hence, the higher the CSR historical aspirations, the more negative the relationship between CSR and the level of employee anxiety prior to an M&A.
2.4 Internal and external CSR
14
On a similar token, in a study conducted by Donia et al. (2017), the authors argue that employees essentially characterize their organization’s CSR engagement as either substantive or symbolic (CSR-SS). Accordingly, employees consider their organization’s CSR as substantive if it perceived to serve others while genuinely supporting the public good. Contrastingly, an organization’s CSR engagement is viewed as symbolic when it is primarily performed with the purpose of profit and reputation enhancing motives. Other authors not only distinguish between substantive and symbolic CSR but instead also consider the audience or target of such activities, i.e., internal and external CSR (e.g., Donia et al., 2017; De Roeck, Marique, Stinglhamber, & Swaen, 2014). Internal and external CSR are defined as following: “Internal CSR refers to an organization’s policy and practices related to employee’s physical and psychological well-being, whereas external CSR is associated with an organization’s social and environmental practices aimed at enhancing its reputation and legitimacy among external stakeholders” (De Roeck et al., 2014, p.93).
15
Nevertheless, Sharma, Sharma, and Devi (2009) argue that there are still a number of organization that understand CSR as exclusively donating money to a social cause or engaging in philanthropic activities (i.e., external CSR), while neglecting to establish a strong internal culture that fosters these types of behavior in their employees (i.e., internal CSR). Companies that engage in primarily external CSR are often accused of “window dressing” or “green-washing” as these CSR activities are considered to be of symbolic nature (Brammer et al., 2007). In contrast, organizations that engage in external CSR foster employees’ ability to enhance their self-concept and self-worth as individuals derive a sense of identity-based on the company’s actions (Mael & Ashforth, 1992). However, if organization’s do not sufficiently engage in external CSR, they do not signal to its environment that it is participating in these types of activities, therefore failing to reap the full potential of engaging in CSR activities such as enhanced reputation, and better market evaluation (Hawn & Ioannou, 2016). Moreover, Hawn and Ioannou (2016) argue that a gap between internal and external CSR has negative implication as social actors outside the organization can challenge the firms for either a lack of credibility or transparency, which in turn may also influence how employees assess their organizations CSR engagement. To summarize:
Hypothesis 4: A discrepancy between internal and external CSR positively moderates
the relationship between CSR and the level of employee anxiety prior to an M&A. Hence, the higher the discrepancy between internal and external CSR, the less negative the relationship between CSR and the level of employee anxiety prior to an M&A.
3. Methodology
16
that build the foundation for this dataset - i.e., ASSET4, Datastream and Zephyr - and its characteristics are presented. Subsequently, the data measures are operationalized and discussed. Lastly, this section concludes with the data analysis method, whereby the utilized (moderated) hierarchical regression model is explained.
3.1 Study context
This study aims to shed light on employee’s response towards CSR in the context of major organizational changes involving the M&A of two companies. More specifically, this study investigates employee’s response during the pre-merger stage, amid the moment when individuals first heard rumors about a potential M&A. According to Appelbaum et al. (2000), “the pre-merger stage begins once the decision to merge has been made, but the public announcement and all legal issues have not yet taken place” (p.651). During the pre-merger stage, top-management discusses the further course of action, and it is during that phase that sensitive information is often leaked (Appelbaum et al., 2000). This leakage often results in the emergence of rumors among employees about the potential merger scenario (Ivancevich et al., 1987). Subsequently, this stage appears to be particularly useful to investigate the influence of CSR on the level of employee anxiety as anxiety and uncertainty related stress are particularly present during this stage (Buono & Bowditch, 1989; Halstenson & McLean, 2007).
3.2 Sample and data
17
which represents a subset of the Datastream dataset, and the Zephyr database. The ASSET4 database has been utilized as the primary database for this study as it provides extensive information related to a company's CSR-engagement (Schäfer, Beer, Zenker, & Fernandes, 2006). Thomson Reuters’ ASSET4 dataset is managed by a company located in Switzerland, specialized in providing objective and reliable data concerning firm’s CSR engagement. Specialists collect 900 evaluation points per firm annually and subsequently use these scores as input to a default equal-weighted framework to calculate 250 key performance indicators (KPIs). These KPIs are further split up into 18 categories, comprising of four different pillars, i.e. a) environmental performance score, b) social performance score, c) corporate governance score, and d) economic performance score. To ensure the data is of high quality, timeliness, and accuracy, the company is utilizing a multi-step verification process that contains - among others - historical comparisons and quality assuring frameworks (Ioannou & Serafeim, 2012). Moreover, the primary data has to be objective and available to the public (Cheng, Ioannou, & Serafeim, 2014).
The first step in constructing the sample for this study, the ASSET4 database has been used to determine for how many companies the database possess anxiety-related information, as measured by the difference in lost working days between t0 and t1. However, at this point, it has not been checked if the database possesses anxiety-related information pertaining the year a rumor for a potential M&A emerged (i.e., t0). Consequently, for a total of 1023 companies, there are at least one anxiety-related score within the time frame of 2007 and 2017. The reason for including 2017 in the search resides in the fact that this study is also interested in analyzing the level of anxiety employees experience one year after the emerge of the rumor (i.e., t1).
18
Subsequently, the preliminary sample of 873 firms was inserted into the Zephyr database to determine if the focal company was engaged in an M&A in the time frame of 2007 and 2016. For 653 firms the premise holds true. Given the change in study design, this sample still contains firms that were either the target or acquirer in the context of an M&A. Nevertheless, to streamline the focus of this study and given the limited amount of information available for the targets, this study exclusively uses the acquiring firms as the unit of analysis. More details pertaining to this decision and its implication can be found in the discussion and future research section of this study. Moreover, Zephyr enables its users to retrieve the exact data the rumor for a potential M&A first appeared. Nevertheless, ASSET4 collects its data only once a year which subsequently means that instead of working with the particular day or month of rumor emergence, the year of the rumor emergence has been chosen to represent t0. The ramifications of this reductionism can be found in the limitations of this study. However, accordingly, t0 differs for each firm as the timing of rumor emergence differs for each firm.
19
constructs and hence several companies had to be dropped from the sample. After conducting the three previously described steps, the sample size decreased from 653 to 152.
After that, the data required to measure the control variables were retrieved from Datastream, indicating that for all 152 firms corresponding data existed. Next, the data were screened for any apparent inconsistencies (i.e., invalid or biased data scores). As a result, six more companies had to be dropped, leading to a sample of 146.
Lastly, as previously indicated, all targets of M&As have been removed from the sample, leading to the final sample size of 118.
3.4 Measures
In this section, the various variables and their measurements are outlined. First, the dependent variable ‘employee anxiety’ is operationalized, followed by the main independent variable ‘CSR.’ Subsequently, the moderator variables (i.e., Social CSR aspirations, Historical CSR aspirations, and discrepancy between internal and external CSR) and the control variables (i.e., Size, Profitability, Debt level, and Industry) are operationalized.
3.4.1 Dependent variable
20
is calculated as follows: total lost working days/(number of employees*250). Consequently, ASSET4 normalizes the score to compute a relative score, whereby the firm’s score is benchmarked against all companies in the ASSET4 dataset. Moreover, to analyze the impact of the M&A upon the individual's level of anxiety, the dependent variable reflects the difference between the lost working days in t0 and t1. Nevertheless, to adequately reflect the intended construct, all negative differences within the sample will be substituted with a 0 as they do not represent the construct of anxiety in themselves. To account for that, the robustness test is constructed in a way to test the opposing construct, i.e., employee well-being, by only using the absolute values of the negative differences, while substituting all positive scores with 0. A more thorough explanation is given in the context of the robustness test.
3.4.2 Independent variable
21
inconsistency and lack of generalizability” (Graves & Waddock, 1994, p.1038). Hence, to surmount these limitations and to follow the advice forwarded by Graves and Waddock (1994), this study utilizes a CSR score that is measured consistently across a wide range of firms and time, comprising of four CSR-related themes, i.e., economic, environmental, social and corporate governance. Due to the lack of theoretical guidance on how to weigh each measure to construct an aggregated CSR score, this study follows the established practice of various scholars (i.e., Waddock & Graves 1997; Sharfman, 1996; Waldman, Siegel, & Javidan, 2006) and assigns equal weight to each of the four constituents. More precisely, the glossary of ASSET4 defines the variable CSR index as the “equally weighted rating reflecting a balanced view of a company’s performance in all four areas, economic, environmental, social and corporate governance for the focal company for every year” (Thomson Reuters, 2018). To understand the impact of CSR upon an individual's level of anxiety, the CSR score one year prior to the M&A will be utilized (i.e., t-1).
3.4.3 Moderator variables
A moderator analysis is employed to ascertain if the relationship between the dependent and independent variable is moderated by potentially third variables, i.e., a) the level of engagement in CSR activities within the industry, b) the length of engaging in CSR activities, and c) a discrepancy between internal and external CSR activities.
3.4.3.1 Social CSR aspirations
22
beneficial influence as predicting variable for individuals in highly anxious and ambiguous situations such as M&As. To investigate the phenomena empirically, both the firms within this sample as well as the remaining companies listed in ASSET4 are clustered according to Waddock and Graves (1997) industry classification. Consequently, for each company, their industry peers CSR performance in t0 is calculated by averaging all CSR scores for that industry in that year.
3.4.3.2 Historical CSR aspiration
When evaluating historical performances, individuals do not weigh their experience of past CSR performance equally. Instead, more recent events are given higher weights in their estimation as these actions are easier to be recalled. Accordingly, this study follows Edwards and Barron’s (1994) advice, using the rank-order centroid weights to determine the best multi-attribute alternative: 𝐻𝑖𝑠𝑡𝑜𝑟𝑖𝑐𝑎𝑙 𝐶𝑆𝑅 𝑎𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛𝑠𝑖𝑡 = 11 18 𝐶𝑆𝑅𝑖𝑡−3+ 5 18𝐶𝑆𝑅𝑖𝑡−4 + 2 18𝐶𝑆𝑅𝑖𝑡−5
whereby historical CSR aspirationsit represents the average CSR engagement of firm i in year t. The equation assumes that the impact of long-term CSR engagement is increasingly reduced over a span of three-year. Hence, to equal out responsiveness versus stability, placing higher emphasis upon more recent observations, as these are likely to have a more significant influence upon an individual’s assessment regarding a company’s CSR engagement. Following this observation, historical CSR aspiration is measured within the timeframe of t-3 until t-5.
3.4.3.3 Internal and external CSR
23
a measurable internal and external CSR score. Nevertheless, as previously argued, the study is primarily interested in the discrepancy between the two constructs. Hence, withstanding any positive or negative directionality, the discrepancy between internal and external CSR reflects the absolute difference between the two and is measured at t0. Thus,
𝐷𝑖𝑠𝑐𝑟𝑒𝑝𝑎𝑛𝑐𝑦𝑡0 = |𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙𝐶𝑆𝑅𝑡0− 𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙𝐶𝑆𝑅𝑡0|
3.4.4 Control variables
24
variable is included as a control variable (Gromley & Matsa, 2013). Consequently, all control variables are measured at t0.
Figure 1. Conceptual model 3.5 Data Analysis
25
additional variables to the model each step, it is possible to determine if the addition of that variable led to a significant increase in predictive capacity for the overall model.
The first model solely contains all control variables to determine their effect on the dependent variable. Model two contains all control variables in addition to the main independent variable (i.e., CSR). Subsequently, model three, four, and five include one additional independent variable plus their interaction effect. Finally, model six reflects the fully specified model including all variables. To summarize, the following formula builds the foundation for the succeeding models:
𝑌(𝐴𝑛𝑥𝑖𝑒𝑡𝑦) = 𝛽0(𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡) + 𝛽1𝑋1(𝐶𝑆𝑅𝑡−1) + 𝛽2𝑋2(𝑆𝑜𝑐𝑖𝑎𝑙 𝐶𝑆𝑅 𝑎𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛𝑠𝑡0) + 𝛽3𝑋3(𝐻𝑖𝑠𝑡𝑜𝑟𝑖𝑐𝑎𝑙 𝐶𝑆𝑅 𝑎𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛𝑠𝑡−3−5) + 𝛽4𝑋4(𝐷𝑖𝑠𝑐𝑟𝑒𝑝𝑎𝑛𝑐𝑦 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑖𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝑎𝑛𝑑 𝑒𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐶𝑆𝑅𝑡0) + 𝛽5𝑋5(𝑆𝑜𝑐𝑖𝑎𝑙 𝐶𝑆𝑅 𝑎𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛𝑠𝑡0∗ 𝐶𝑆𝑅𝑡−1) + 𝛽6𝑋6(𝐻𝑖𝑠𝑡𝑜𝑟𝑖𝑐𝑎𝑙 𝐶𝑆𝑅 𝑎𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛𝑠𝑡−3−5∗ 𝐶𝑆𝑅𝑡−1) + 𝛽7𝑋7(𝐷𝑖𝑠𝑐𝑟𝑒𝑝𝑎𝑛𝑐𝑦 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑖𝑛𝑡𝑒𝑟𝑛𝑎𝑙 𝑎𝑛𝑑 𝑒𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐶𝑆𝑅𝑡0∗ 𝐶𝑆𝑅𝑡−1) + 𝛽8𝑋8(𝐹𝑖𝑟𝑚 𝑠𝑖𝑧𝑒𝑡0) + 𝛽9𝑋9(𝑃𝑟𝑜𝑓𝑖𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦𝑡0) + 𝛽10𝑋10(𝐷𝑒𝑏𝑡 𝑙𝑒𝑣𝑒𝑙𝑡0) + 𝛽11𝑋11(𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑡0) + 𝜀(𝑒𝑟𝑟𝑜𝑟 𝑡𝑒𝑟𝑚)
26
4. Results
In this section, the data is analyzed the hypotheses are tested. First, a general overview of the statistics is introduced. Subsequently, the preliminary analysis results are provided which examine the various assumptions required to run a hierarchical multiple regression. Lastly, the hypotheses are tested, and a first contextual evaluation is given.
Table 1. Descriptive statistics
N Minimum Maximum Mean Std.
Deviation Anxiety 118 .00 34.62 1.55 4.95 CSR t-1 118 15.67 97.96 73.58 22.89 Social CSR aspirations 118 41.40 63.37 51.21 5.08 Historical CSR aspiration 118 17.93 98.07 68.43 23.28 Discrepancy between internal and external CSR 118 27.27 79 52.18 14.22 Firm size 118 8.67 10.96 9.87 .50 Profitability 118 -68.88 104.86 17.15 21.19 Debt level 118 .01 .62 .21 .14 Industry 118 0.05 6.45 1.55 1.49 Valid N 118 4.1 Descriptive Statistics
27
28
To account for differences in industries, the industry sector classification by Waddock and Graves (1997) has been utilized, resulting in twelve industry sectors (see table 2). The comprehensive list of industry classification by Waddock and Graves (1997) can be found in Appendix X. In this sample, the most prominent industry sectors in this sample are the computers, autos, and aerospace sector, and the telephone and utilities sector, which accumulated account for 37.2% of all companies within this sample. In contrast, the least present industry sector is the transportation industry that only accounts for 2.5% of the total sample.
Table 2. Industry distribution
Industries Frequency Percent Cumulative
29
Table 3. Zero-order correlation 1 2 3 4 5 6 7 8 Dependent variable 1. Anxiety Independent variables 2. CSR t-1 -.172* 3. Social CSR aspirations -.056 .023 4. Historical CSR aspirations -.079 .787*** .170* 5. Discrepancy between internal and
31 4.2 Preliminary Analysis
Before testing the hypotheses employing a hierarchical regression model, one has to make sure that a number of assumptions are met to ensure that the data can be analyzed by using this particular statistical instrument. The first two assumptions relate to the chosen study design and the type of variable included in the study design. The dependent variable ought to be continuous whereas the independent variables have to be either continuous or categorical. Both assumptions are met within this study context. Next, five other assumptions have to be tested to ensure the data fit the regression model and is thus suited to be tested via SPSS. These assumptions are (1) independence of observations, (2) linearity between the dependent and predictor variables, (3) homoscedasticity of residuals, (4) multicollinearity, (5) no significant outliers, high leverage points or high influential points, and (6) approximately normally distributed residuals.
First, to test the independence of observations, a Durbin-Watson test has been conducted. The test statistics can range from 0 to 4, whereby a score of approximately two is desirable as it indicates no correlation between residuals. The Durbin-Watson statistic for this sample suggests a score of 2.021, indicating independence of residuals.
Second, to test linearity between the dependent and predictor variables a scatterplot is created, whereby the studentized residuals are plotted against the unstandardized predicted values. Besides, partial regression plots were created to determine if there is a relationship between the dependent variable and each predictor variable. The results (see Appendix B) indicate that there was linearity as checked by partial regression plots and a scatterplot of studentized residuals against the predicted values.
32
Fourth, to test for multicollinearity, VIF (variance inflation factor) scores were investigated, whereby VIF of greater than ten might indicate that there is collinearity problem. The highest VIF scores resides at 4.640. Conclusively, no variable shows signs of multicollinearity as indicated by VIF scores of <10. Nevertheless, table 3 shows a suspiciously high correlation between CSR t-1 and historical CSR aspirations (r=.787; p ≤ 0.01). The further implications are discussed in the limitations of this study.
Fifthly, outliers, and high leverage points or high influential points are assessed. To deal with potential outliers, a winsorization transformation of the upper and lower 1% of was applied to the dependent and independent variables. Moreover, no high leverage cases are identified, with the highest value being 0.348. Lastly, to test also account for high influential points, Cook’s distance was calculated, indicating that one case had a higher score than the critical value of 1 (i.e., 1.242). Nevertheless, after visually inspecting the case, no apparent bias or mismeasurement was identified, and hence the focal firm remained within the sample.
Lastly, to test if the residuals are approximately normally distributed, the histogram with a superimposed normal curve in Appendix C indicates that the residuals are approximately normally distributed.
4.3 Hypotheses testing
33
35 4.3.1 Hypothesis 1
Hypotheses 1 predicts a negative relationship between CSR and the level of employee anxiety prior to an M&A. Accordingly, the B is expected to be negative and significant. Model two reveals that there is a significant negative relationship between CSR and employee anxiety prior to an M&A. Hence, higher levels of CSR lead to lower levels of anxiety among employees prior to an M&A with a B-value of -.043 (p ≤ 0.05). Moreover, by adding the main independent variable to the model the explained variance increases significantly by .036, resulting in a R² of .175. Concluding, there is evidence to support hypothesis 1.
4.3.2 Hypothesis 2
Hypothesis 2 predicts that social CSR aspirations positively moderates the relationship between CSR and the level of employee anxiety prior to an M&A. Hence, it is expected that the interaction term shows a statistically significant moderation effect. Model 3 shows that the moderating interaction term is statistically significant (p ≤0.001) with a beta coefficient of .012. By including the moderating variable into the model, the explained variance showed a significant increase by .092 to a total R² of .267. Hence, there is evidence to support hypothesis 2.
4.3.3 Hypothesis 3
36
the change in the F-value exposes that the difference is not statistically significant. In conclusion, there is not sufficient evidence to support hypothesis 3 and thus has to be rejected.
4.3.4 Hypothesis 4
Hypothesis 4 predicts that a discrepancy between internal and external CSR positively moderates the relationship between CSR and the level of employee anxiety prior to an M&A. Hence, it is expected that the interaction term shows a statistically significant moderation effect. Model 5 shows that both discrepancy between internal and external CSR and its interaction effects does not significantly influence the posed relationship. Although the explained variance R² increases by .009, the models' explanatory power does not change significantly.
All in all, there is not sufficient evidence to support hypothesis 4 and thus has to be rejected. To summarize the given findings, table 5 provides a general overview.
Table 5. Hypotheses overview
Hypothesis Expectation Result
H1 CSR has a negative influence on the level of employee anxiety prior to an M&A.
Supported
H2 Social CSR aspirations positively moderates the relationship between CSR and the level of
employee anxiety prior to an M&A.
Supported
H3 Historical CSR aspirations negatively moderates the relationship between CSR and the level of
employee anxiety prior to an M&A.
Rejected
H4 A discrepancy between internal and external CSR positively moderates the relationship between CSR and the level of employee anxiety
prior to an M&A.
Rejected
4.4 Robustness Test
37
39
5. Discussion
M&As are accompanied by a significant degree of stress and anxiety that resonate throughout the organizations affected by it. Particularly employees experience a great deal of uneasiness in the context of M&As as the event is often supplemented by a great deal of secrecy, ambiguity, and uncertainty (Werhane, 1988). Typically, little information is disseminated to the employees before the announcement of the M&A in an attempt to prevent potential negative ramifications from its business environment (e.g., stock fluctuations) (Werhane, 1988). Consecutively, rumors emerge that can take a substantial psychological toll on the people concerned. Employees start ruminating and worrying about their employment status or general position within the newly formed organization. Hence, to restore one’s psychological equilibrium, employees search for indications from the past or the direct environment that enables them to predict how they might be treated in the future. As such, CSR - which corresponds to a “voluntary auto-regulation process” (De Roeck & Swaen, 2010, p.4) that signals stakeholders inside and outside the organization that the focal firm is interested in increasing social welfare, while withstanding from harmful action – may be a suitable mechanism to reduce the amount of anxiety experienced by the employees as it provides behavioral cues to the employees affected by the M&A. Conclusively, this study set out to stimulate the discussion among practitioners and scholars to further investigate the ethical implications of M&A on the employees affected by it by asking how an organization’s CSR engagement may lead to lower levels of anxiety in the context of an upcoming M&A.
40
Moreover, the findings from both analyses further indicate that the posed relationship is in fact positively moderated by social CSR engagement. As such, it appears that the CSR performance of industry peers have a significant moderating impact upon the anxiety-reducing influence of CSR in the context of an M&A. Thus, in line with prior findings by Bertels and Peloza (2008), just as a firm’s reputation is not absolute, so does CSR engagement in itself does not appear to be absolute. Instead, CSR represents relative construct which exists in relation to the CSR engagement of direct industry competitors. However, industries that are under close public scrutiny due to their bad public image (e.g., tobacco, oil industry) often feel obliged to engage in additional CSR efforts to retain their legitimacy to operate (Lewis, 2003). Hence, the CSR engagement of these firms are often assessed as being opportunistic and self-centered (Vlachos et al., 2013; Bertels & Peloza, 2006), thereby weakening their potentially anxiety-reducing properties in the context of an M&A. Conclusively, the analyses provide empirical evidence to support the second hypothesis.
Besides, contrary to the third hypotheses, the historical CSR aspirations of the organization do not appear to have a significant influence upon the level of anxiety experienced by its employees prior to an M&A. A potential explanation can be found within the psychology literature which argues that individuals who are under the influence of heightened levels of stress have an impaired ability to retrieve memories (Dominique, Roozendaal, & McGaugh., 1998). Hence, it may be plausible that employees in these highly anxious times do not have the mental capacity to make a clear value judgment regarding the focal company’s CSR engagement by looking at past experience. Nevertheless, further research is warranted to support this claim.
41
hint at the fact that a discrepancy between internal and external CSR may have an influence within the present study context; however, further research is necessitated to investigate the phenomena further.
5.1 Theoretical contribution
Although the CSR literature stream received increasing attention from scholars around the globe, the field remains a highly fragmented one as scholars study its construct through divergent conceptually and disciplinary lenses (Aguinis & Glavas, 2012). In this context, most studies are mainly interested in analyzing the impact of CSR from a macro level (i.e., organizational or institutional view), while often neglecting its effects on the micro level (i.e., the individual) (Aguinis & Glavas, 2012). However, a number of studies have investigated its impact of CSR upon the individual. Among others, these studies have shown the potentially positive influence of CSR on employee engagement, firm identification, OCB, retention rate, commitment and the attractiveness for applicants to work for the focal company (Aguinis & Glavas, 2012). Hence, the present study further enhanced our understanding of the impact of CSR on the individual.
42
where reliable information is rare, temporal heuristics may be utilized to compensate for the lack of available information.
5.2 Practical implications
43 5.3 Limitations
The present study has several limitations that are addressed next. First, one could argue that the number of lost working days is not a perfect fit to operate as a proxy for the chosen dependent variable as an increase in the level of anxiety does not necessarily have to lead to people being absent from work. Nevertheless, given the restricted opportunities to operationalize the construct empirically in the context of this thesis, the chosen proxy appeared to capture its effect most accurately. Moreover, the sample size for the present study is comparatively small, which - in future studies - could be enlarged to ensure the reliability and validity of the present findings. Besides, the predictive capacity of the fully specified model resides at a value of .285 and hence only 28.5% percent of the change in the dependent variable can be accounted for with the present variables. Other unknown variables might still have a significant influence upon the dependent variable, which this study; however, cannot account for. Lastly, in table 4, model 4, when testing the third hypothesis, the previously significant relationship between CSR and anxiety turns insignificant which indicates that there might be some multicollinearity issue within the sample. Hence, the coefficients in model 4 and 6 may be slightly inflated or deflated respectively. Nevertheless, given the comparably small VIF values, it is not certain that multicollinearity is, in fact, a problem within the present study. However, it is advised that the reader keeps this potential limitation in mind when interpreting the results.
5.4 Future research
44
why some M&As still fail to accomplish their stated goal. To provide further inside in this debate, the present study was conducted. Nevertheless, given the posed restrictions of this study, there is still amid room for potential future research. For one, to fully grasp the psychological impact of M&As in the form of anxiety upon the individual, it is advisable to conduct a longitudinal multiple case study approach to experience and measure the level of anxiety and stress more reliably. Moreover, it is desirable that future studies aim to investigate the anxiety-reducing properties on the targets of the M&As as the firms of these firms are expected to experience even higher levels of anxiety compared to the employees of the acquiring firm.
5.5 Conclusion
45
Bibliography
Aguilera, R. V., Rupp, D. E., Williams, C. A., & Ganapathi, J. (2007). Putting the S back in corporate social responsibility: A multilevel theory of social change in organizations.
Academy of management review, 32(3), 836-863.
Aguinis, H., & Glavas, A. (2012). What we know and don’t know about corporate social responsibility: A review and research agenda. Journal of management, 38(4), 932-968. Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting
interactions: Sage.
Appelbaum, S. H., Gandell, J., Yortis, H., Proper, S., & Jobin, F. (2000). Anatomy of a merger: behavior of organizational factors and processes throughout the pre-during-post-stages (part 1). Management decision, 38(9), 649-662.
Aupperle, K. E. (1991). The use of forced-choice survey procedures in assessing corporate social orientation. Research in corporate social performance and policy, 12(1), 479-486.
Aupperle, K. E., Carroll, A. B., & Hatfield, J. D. (1985). An empirical examination of the relationship between corporate social responsibility and profitability. Academy of
management journal, 28(2), 446-463.
Barone, M. J., Miyazaki, A. D., & Taylor, K. A. (2000). The influence of cause-related marketing on consumer choice: does one good turn deserve another? Journal of the
Academy of Marketing Science, 28(2), 248-262.
Bauman, C. W., & Skitka, L. J. (2012). Corporate social responsibility as a source of employee satisfaction. Research in Organizational Behavior, 32, 63-86.
Becker-Olsen, K. L., Cudmore, B. A., & Hill, R. P. (2006). The impact of perceived corporate social responsibility on consumer behavior. Journal of Business Research, 59(1), 46-53.
Bertels, S., & Peloza, J. (2008). Running just to stand still? Managing CSR reputation in an era of ratcheting expectations. Corporate Reputation Review, 11(1), 56-72.
Brammer, S., Millington, A., & Rayton, B. (2007). The contribution of corporate social responsibility to organizational commitment. The international journal of human
46
Buono, A. F., & Bowditch, J. L. (1990). Ethical considerations in merger and acquisition management: A human resource perspective. SAM Advanced Management Journal,
55(4), 18.
Cartwright, S., & Cooper, C. L. (1996). Coping in occupational settings.
Cheng, B., Ioannou, I., & Serafeim, G. (2014). Corporate social responsibility and access to finance. Strategic management journal, 35(1), 1-23.
Chun, R. (2009). A corporate's responsibility to employees during a merger: organizational virtue and employee loyalty. Corporate Governance: The international journal of
business in society, 9(4), 473-483.
Clarkson, M. E. (1995). A stakeholder framework for analyzing and evaluating corporate social performance. Academy of management review, 20(1), 92-117.
Cobb, A. T., Folger, R., & Wooten, K. (1995). The role justice plays in organizational change.
Public Administration Quarterly, 135-151.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple
regression/correlation analysis for the behavioral sciences: Routledge.
Colquitt, J. A., Conlon, D. E., Wesson, M. J., Porter, C. O., & Ng, K. Y. (2001). Justice at the millennium: a meta-analytic review of 25 years of organizational justice research.
Journal of Applied Psychology, 86(3), 425.
Cooper, C., & Dewe, P. (2008). Well-being—absenteeism, presenteeism, costs and challenges. Occupational medicine, 58(8), 522-524.
De Roeck, K., Marique, G., Stinglhamber, F., & Swaen, V. (2014). Understanding employees' responses to corporate social responsibility: mediating roles of overall justice and organisational identification. The international journal of human resource
management, 25(1), 91-112.
De Roeck, K., & Swaen, V. (2010). The role of CSR on employees’ post-merger
organizational identification. Louvain School of Management Working Paper, 1-23. Deller, J., & Klendauer, R. (2008). M&A–Der Erfolgsfaktor Mensch: Strategische
Personalauswahl und-entwicklung im Kontext von Mergers & Acquisitions: Mit konkreten Anleitungen zur Diagnostik und Förderung erfolgskritischer Kompetenzen:
Rainer Hampp Verlag.
47
Dominique, J.-F., Roozendaal, B., & McGaugh, J. L. (1998). Stress and glucocorticoids impair retrieval of long-term spatial memory. Nature, 394(6695), 787.
Donia, M. B., Tetrault Sirsly, C. A., & Ronen, S. (2017). Employee attributions of corporate social responsibility as substantive or symbolic: Validation of a measure. Applied
Psychology, 66(1), 103-142.
Du, S., Bhattacharya, C. B., & Sen, S. (2010). Maximizing business returns to corporate social responsibility (CSR): The role of CSR communication. International Journal of
Management Reviews, 12(1), 8-19.
Ellen, P. S., Webb, D. J., & Mohr, L. A. (2006). Building corporate associations: Consumer attributions for corporate socially responsible programs. Journal of the Academy of
Marketing Science, 34(2), 147-157.
Folger, R., Cropanzano, R., & Goldman, B. (2005). What is the relationship between justice and morality. Handbook of organizational justice, 215, 215.
Foreh, M. R., & Grier, S. (2003). When is honesty the best policy? The effect of stated company intent on consumer skepticism. Journal of consumer psychology, 13(3), 349-356.
Gormley, T. A., & Matsa, D. A. (2013). Common errors: How to (and not to) control for unobserved heterogeneity. The Review of Financial Studies, 27(2), 617-661. Graves, S. B., & Waddock, S. A. (1994). Institutional owners and corporate social
performance. Academy of management journal, 37(4), 1034-1046.
Guenster, N. (2010). The effect of differences in corporate social responsibility between bidder and target on stock returns around the announcement date of mergers and acquisitions 2010.
Halstenson, H., & McLean, G. N. (2007). The Role of Human Resources in Mergers and Acquisitions in the Healthcare Industry in the United States: A Case Study.
Hameed, I., Riaz, Z., Arain, G. A., & Farooq, O. (2016). How do internal and external CSR affect employees' organizational identification? A perspective from the group engagement model. Frontiers in psychology, 7, 788.
Hawn, O. (2013). Strategic role of corporate social responsibility in international expansion
48
Hawn, O., & Ioannou, I. (2016). Mind the gap: The interplay between external and internal actions in the case of corporate social responsibility. Strategic management journal,
37(13), 2569-2588.
Hogan, E. A., & Overmyer-Day, L. (1994). The psychology of mergers and acquisitions.
International review of industrial and organizational psychology, 9, 247-247.
Ioannou, I., & Serafeim, G. (2012). What drives corporate social performance? The role of nation-level institutions. Journal of International Business Studies, 43(9), 834-864. Ivancevich, J. M., Schweiger, D. M., & Power, F. R. (1987). Strategies for Managing Human
Resources During Mergers and. People and Strategy, 10(1), 19.
Jaccard, J., Wan, C. K., & Turrisi, R. (1990). The detection and interpretation of interaction effects between continuous variables in multiple regression. Multivariate behavioral
research, 25(4), 467-478.
Jones, D.A., Willness, C., & MacNeil, S. (2009). Corporate social responsibility and recruitment: Testing person-organization fit and signaling mechanisms. Paper presented at the Academy of Management Proceedings.
King, D. R., Dalton, D. R., Daily, C. M., & Covin, J. G. (2004). Meta‐analyses of post‐ acquisition performance: Indications of unidentified moderators. Strategic management journal, 25(2), 187-200.
Lange, D., & Washburn, N. T. (2012). Understanding attributions of corporate social irresponsibility. Academy of management review, 37(2), 300-326.
Levinson, H. (1976). Psychological man.
Lewis, S. (2003). Reputation and corporate responsibility. Journal of Communication
Management, 7(4), 356-366.
Lin, C. Y.-Y., & Wei, Y.-C. (2006). The role of business ethics in merger and acquisition success: An empirical study. Journal of Business Ethics, 69(1), 95-109.
Lind, E. A. (2001). Fairness heuristic theory: Justice judgments as pivotal cognitions in organizational relations. Advances in organizational justice, 56(8).
Mael, F., & Ashforth, B. E. (1992). Alumni and their alma mater: A partial test of the reformulated model of organizational identification. Journal of organizational
49
McGuire, J. B., Sundgren, A., & Schneeweis, T. (1988). Corporate social responsibility and firm financial performance. Academy of management journal, 31(4), 854-872. McWilliams, A., & Siegel, D. (2000). Corporate social responsibility and financial
performance: correlation or misspecification? Strategic management journal, 21(5), 603-609.
McWilliams, A., Siegel, D. S., & Wright, P. M. (2006). Corporate social responsibility: Strategic implications. Journal of management studies, 43(1), 1-18.
Meckl, R., & Theuerkorn, K. (2015). CORPORATE SOCIAL RESPONSIBILITY AS A SUCCESS FACTOR FOR M&A TRANSACTIONS. European Journal of Business
and Social Sciences, 4(01), 213-226.
Melkonian, T., Monin, P., & Noorderhaven, N. G. (2011). Distributive justice, procedural justice, exemplarity, and employees' willingness to cooperate in M&A integration processes: An analysis of the Air France‐KLM merger. Human Resource
Management, 50(6), 809-837.
Moran, V., & Panasian, C. (2005). The human side of mergers and acquisitions: A look at the evidence.
Morgan, S. M. (2009). The Impact of Corporate Social Responsibility on Mergers and Acquisitions.
Nahavandi, A., & Malekzadeh, A. R. (1988). Acculturation in mergers and acquisitions.
Academy of management review, 13(1), 79-90.
Napier, N. K., Simmons, G., & Stratton, K. (1992). Communication during a merger: the experience of two banks Human Resource Planning (pp. 119-136): Springer. Neves, P., & Caetano, A. (2006). Social exchange processes in organizational change: The
roles of trust and control. Journal of change management, 6(4), 351-364.
Rentsch, J. R., & Schneider, B. (1991). Expectations for postcombination organizational life: A study of responses to merger and acquisition scenarios. Journal of Applied Social
Psychology, 21(3), 233-252.
Robinson, C., & Schumacker, R. E. (2009). Interaction effects: centering, variance inflation factor, and interpretation issues. Multiple Linear Regression Viewpoints, 35(1), 6-11. Rupp, D. E., Ganapathi, J., Aguilera, R. V., & Williams, C. A. (2006). Employee reactions to
corporate social responsibility: An organizational justice framework. Journal of
50
Rupp, D. E., Shao, R., Thornton, M. A., & Skarlicki, D. P. (2013). Applicants' and employees' reactions to corporate social responsibility: The moderating effects of first‐party justice perceptions and moral identity. Personnel Psychology, 66(4), 895-933. Schuler, D. A., & Cording, M. (2006). A corporate social performance–corporate financial
performance behavioral model for consumers. Academy of management review, 31(3), 540-558.
Schweiger, D. M., & Denisi, A. S. (1991). Communication with employees following a merger: A longitudinal field experiment. Academy of management journal, 34(1), 110-135.
Seo, M.-G., & Hill, N. S. (2005). Understanding the human side of merger and acquisition: An integrative framework. The Journal of Applied Behavioral Science, 41(4), 422-443.
Serpa, R. (1988). The often overlooked ethical aspect of mergers. Journal of Business Ethics,
7(5), 359-362.
Sharfman, M. (1996). The construct validity of the Kinder, Lydenberg & Domini social performance ratings data. Journal of Business Ethics, 15(3), 287-296.
Sharma, S., Sharma, J., & Devi, A. (2009). Corporate social responsibility: the key role of human resource management. Business Intelligence Journal, 2(1), 205-213.
Skarlicki, D. P., & Kulik, C. T. (2004). Third-party reactions to employee (mis) treatment: A justice perspective. Research in Organizational Behavior, 26, 183-229.
Stengel, R. (2009). For American consumers, a responsibility revolution. Time magazine,
174(11), 38-42.
Ullman, A. (1985). Data in search of a theory: A critical examination of the relationship among social disclosure and economic performance measures. Academy of
management review, 19(3), 30-39.
Van den Bos, K. (2001). Uncertainty management: the influence of uncertainty salience on reactions to perceived procedural fairness. Journal of personality and social
psychology, 80(6), 931.
Van den Bos, K. (2003). On the subjective quality of social justice: the role of affect as information in the psychology of justice judgments. Journal of personality and social
51
Vanhamme, J., & Grobben, B. (2009). “Too good to be true!”. The effectiveness of CSR history in countering negative publicity. Journal of Business Ethics, 85(2), 273. Vlachos, P. A., Panagopoulos, N. G., & Rapp, A. A. (2013). Feeling good by doing good:
Employee CSR-induced attributions, job satisfaction, and the role of charismatic leadership. Journal of Business Ethics, 118(3), 577-588.
Waddock, S. A., & Graves, S. B. (1997). The corporate social performance-financial performance link. Strategic management journal, 303-319.
Waldman, D. A., Siegel, D. S., & Javidan, M. (2006). Components of CEO transformational leadership and corporate social responsibility. Journal of management studies, 43(8), 1703-1725.
Webb, D. J., & Mohr, L. A. (1998). A typology of consumer responses to cause-related marketing: From skeptics to socially concerned. Journal of Public Policy &
Marketing, 226-238.
Werhane, P. H. (1988). Two ethical issues in mergers and acquisitions. Journal of Business
Ethics, 7(1-2), 41-45.
Wokutch, R. E., & McKinney, E. W. (1991). Behavioral and perceptual measures of corporate social performance. Research in corporate social performance and policy, 12, 309-330.
Wolfe, R. (1991). The use of content analysis to assess corporate social responsibility.
Research in corporate social performance and policy, 12, 281-307.
52
APPENDICES
Appendix A: Industry classification by Graves and Waddock (1997)
53
Appendix C: Testing normality
