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CORPORATE SOCIAL PERFORMANCE AND CORPORATE FINANCIAL
PERFORMANCE: THE MEDIATING AND MODERATING EFFECTS OF
CORPORATE REPUTATION
Mounting evidence suggests that the Corporate Social Performance (CSP) - Corporate
Financial Performance (CFP) relationship is nonlinear and non-direct (Barnett & Solomon, 2006;
Gardberg & Fombrun, 2006; Gardberg & Schepers, 2008; Griffin & Mahon, 1997). In this paper,
we further this line of inquiry by investigating the mediating and moderating effects (Baron and
Kenny, 1986; Judd, Kenny & McClelland, 2001; Muller, Judd & Yzerbyt, 2005) that Corporate
Reputation (CR) can have on the CSP-CFP relationship. First, by investigating the mediating
effect that CR has within the CSP-CFP relationship, we examine the hypothesis that CR accounts
to some extent for the process through which CSP impacts CFP. Second, by investigating the
moderating effect that CR has on the CSP-CFP relationship, we examine how CR modifies the
effect that CSP has on CFP. Following, we draw on the extant literature to theorize about CR’s
dual role as both a mediator and a moderator in the CSP-CFP relationship.
HYPOTHESES DEVELOPMENT
Drawing on the extensive CSP and CR literatures, we argue that CSP can contribute to
the firm’s CR, which in turn has a positive impact on its CFP. First, CSP can have a positive
impact on a firm’s CR, as many have argued (Orlitzky, Schmidt & Rynes, 2003; Gardberg &
Fombrun, 2006; Brammer & Pavelin, 2006; Fombrun & Shanley, 1990). According to Fombrun
and Shanley (1990), CSP can be seen as a positive reputational signal to external stakeholders,
like customers, investors, bankers and suppliers, who mostly operate under incomplete
information. Gardberg and Fombrun (2006) argued that CSP and particularly Corporate
Citizenship, creates intangible assets such as CR and Legitimacy by making the focal firm mode
acceptable within a specific national context. In addition, Brammer and Pavelin (2006) found
that CSP played an important role in the CR assessments of managers and market analysts.
Second, extensive research indicates that CR has a positive effect on CFP. A number of
resource-based view theorists have argued that CR, as an intangible resource, which is valuable,
rare and difficult to imitate, contributes significantly to CFP (Dierickx & Cool, 1989; Rumelt,
1987; Weigelt & Camerer, 1988; Barney, 1991; Grant, 1991). Moreover, through extensive
empirical research, Roberts and Dowling (2002) found that firms with good CRs are better able
to sustain superior CFP over time. The above then would lead us to expect that CSP contributes
to the creation of CR, which in turn enhances the firm’s financial performance (CFP).
Hypothesis 1 follows:
H1: Corporate reputation mediates the positive relationship between corporate social
performance and corporate financial performance.
It is also possible that CR has a moderating effect on the CSP-CFP relationship. Prior CR
can influence a firm’s CSP valence for various stakeholders and therefore how stakeholders act
towards the firm. Research has found that prior reputation influences arbiters’ attribution of
authenticity to firms’ corporate philanthropy (Bae & Cameron, 2006; Lii & Lee, 2012). Arbiters
judge corporate philanthropy of firms with weak reputations negatively while judging the
corporate philanthropy of firms with strong reputations positively. We propose that prior
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reputation will influence arbiters’ attribution of CSR authenticity, which in turn will affect the
way in which arbiters, in their different stakeholder capacities, patronize the firm for given levels
of the firm’s CSP. Specifically, the stronger a firm’s reputation the more stakeholders will
financially support the firm for given levels of CSP. Hypothesis 2 follows:
H2: Corporate reputation positively moderates the relationship between corporate social
performance and corporate financial performance.
Figure 1 illustrates our model of the relationships among corporate social performance,
corporate reputation and corporate financial performance.
METHODS
Data
We examine our research hypotheses based on CSP, CR, and CFP data we collected from
the Reputation Institute’s RepTrak Pulse database, Thomson Reuters ASSET4 database, and
Compustat, respectively.
The RepTrak Pulse database provides an overall assessment of the health of a company’s
reputation. The Reputation Institute conducts large yearly surveys asking more than 115,000
consumers from different countries to rate the largest companies in their country across seven
key CR dimensions: Products/Services, Innovation, Workplace, Governance, Citizenship,
Leadership and Financial Performance. Then, it evaluates the degree to which a particular
dimension affects the emotional bond between a particular stakeholder group and a company,
and determines which dimensions have the highest impact on support and recommendation. A
company’s reputation is measured on a scale from 0-100 providing a normative base for
companies to benchmark against across stakeholders. The database covers 1502 companies from
34 countries from 2006 through 2013.
Thomson Reuters ASSET4 database is an established source for environmental, social
and governance (ESG) information used for empirical research in corporate social performance
(e.g. Cheng, Ioannou, & Serafeim, 2013; Ioannou & Serafeim, 2012). It comprises a large
sample of more than 3,500 global companies for the period 2002-2012. Thomson Reuters
systematically collects ESG data from companies, news sources, stock exchange filings and nongovernment organizations, ensuring the content is consistent and comparable between companies.
The methodology used to calculate the ESG scores allows researchers to rate and compare
companies against approximately 700 individual data points, which are combined into over 250
key performance indicators (KPIs). The KPI scores are then aggregated into 18 categories
grouped within 4 pillars that are integrated into a single overall ESG performance score.
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Indicators, categories, pillars, and the overall score are calculated by equally weighting and zscoring all underlying data points and comparing them against all companies in the ASSET4
universe on a yearly basis. The resulting percentage is a relative measure of performance, zscored, and normalized to better distinguish values and position the score between 0 and 100.
Last, Compustat is a database of financial, statistical and market information on active
and inactive global companies throughout the world. The database covers more than 99,000
global securities, covering 99% of the world’s total market capitalization with annual company
data history available back to 1950.
Model
We will test our hypotheses using two complementary methods of analysis that will allow
us to exploit different attributes of our dataset: multiple regression analysis and structural
equation modeling (SEM). First, we will use multiple regression analysis to estimate the
mediated and moderated effects following the work of Baron and Kenny (1986) and Muller,
Judd, and Yzerbyt (2005) and attempt to utlisize the panel structure of our dataset. The second
method of analysis will be based on path models estimation (Kline, 2010). This method will
allow us to test the robustness of our main analysis with regard to the mediating and moderating
roles of CR in the CSP-CFP relatiosnhip.
Dependent Variable
Our dependent variable is aimed to capture corporate financial performance. We
operationalize corporate financial performance using accounting and financial performance data
from Compustat. Thereby, we calculate both an accounting measure (ROA) and a market
performance measure (Tobin’s Q) to examine the sensitivity of our model estimates when
different performance measures are considered.
Independent Variables
We operationalize CSP through multiple indicators obtained from Thomson Reuters
ASSET4 database. Specifically, we use 3 pillars from ASSET4 that pertain to a firm’s corporate
governance, social performance, and environmental performance. The corporate governance
pillar measures a company’s systems and processes, which ensure that its board members and
executives act in the best interests of its long term shareholders. It reflects a company's capacity,
through its use of best management practices, to direct and control its rights and responsibilities
through the creation of incentives, as well as checks and balances in order to generate long term
shareholder value. The environmental pillar measures a company's impact on living and nonliving natural systems, including the air, land and water, as well as complete ecosystems. It
reflects how well a company uses best management practices to avoid environmental risks and
capitalize on environmental opportunities in order to generate long term shareholder value. Last,
the social pillar measures a company’s capacity to generate trust and loyalty with its workforce,
customers and society, through its use of best management practices. It is a reflection of the
company’s reputation and the health of its license to operate, which are key factors in
determining its ability to generate long term shareholder value. The 3 pillars are calculated by
equally weighting and z-scoring all underlying data points and comparing them against all
companies in the ASSET4 universe on a yearly basis. The resulting percentages are relative
measures of (corporate governance, social and environmental) performance, z-scored, and
normalized to better distinguish values and position the scores between 0 and 100.
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Hypothesized Moderator/Mediator
We operationalize corporate reputation using RepTrak Pulse scores collected and
published by the Reputation Institute (RI). The RI annually surveys a representative sample of
the general public regarding corporate reputations of large, visible firms. The variable ranges
from 0-100 with lower values reflecting weaker corporate reputation.
Control variables
Several other factors that influence CFP will be controlled for such as industry
membership, past performance, firm productivity, country of origin, inter alia.
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