Resolving Impact Investment Disputes: When Doing Good Goes Bad
DOING GOOD, DOING BAD, AND DOING WELL: INVESTIGATING …
Transcript of DOING GOOD, DOING BAD, AND DOING WELL: INVESTIGATING …
The Pennsylvania State University
The Graduate School
The Mary Jean and Frank P. Smeal College of Business
DOING GOOD, DOING BAD, AND DOING WELL: INVESTIGATING THE DYNAMIC
EFFECTIVENESS OF SUSTAINABILITY STRATEGY
A Dissertation in
Business Administration
by
Charles Alfred Kang
© 2014 Charles Alfred Kang
Submitted in Partial Fulfillment
of the Requirements
for the Degree of
Doctor of Philosophy
August 2014
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This dissertation of Charles Alfred Kang was reviewed and approved* by the following:
Rajdeep Grewal
Irving & Irene Bard Professor of Marketing
Dissertation Advisor
Chair of Committee
Duncan K. H. Fong
Professor of Marketing and Professor of Statistics
Shrihari (Hari) Sridhar
Assistant Professor of Marketing
Saurabh Bansal
Assistant Professor of Supply Chain Management
Brent W. Ambrose
Smeal Professor of Risk Management
Director of Ph.D. Program at the Smeal College of Business
* Signatures are on file in the Graduate School
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ABSTRACT
In my dissertation, I investigate the dynamic effectiveness in sustainability strategy. In
essay 1, I examine the dynamic relationship among corporate social responsibility (CSR),
corporate social irresponsibility (CSI), and firm performance. Specifically, I address the
questions of whether and how CSR relates to firm value, and, in so doing identify four
mechanisms pertaining to this relationship that have been proposed in the literature: (1) slack
resources lead to CSR, (2) CSR improves performance, (3) CSR makes amends for past CSI, and
(4) CSR insures against subsequent CSI. I propose an economic theory model to demonstrate the
complex interplay among CSR, CSI, and firm value, and empirically test aforementioned four
mechanisms by using a structural panel vector autoregression specification. The results suggest
that firms benefit financially from CSR and that CSI antecedes CSR. In essay 2, I study the
effective sustainability practice management in the lens of portfolio theory. In particular, I seek
to address what types of sustainability portfolios strategy promise the greatest return in terms of
its breadth, depth, and the ratio of philanthropic vs. business related practices. The findings
suggest that the effect of a firm’s CSI breadth is negative. Yet, this effect is mitigated by
philanthropic/business ratio of CSI. Further, the findings suggest that this mitigation effect of
philanthropic / business ratio on the breadth of CSI – firm performance link become less strong
when the firm’s sustainability portfolio depth increases. In addition, the results show that the
effect of a firm’s CSR breadth on firm performance is negatively moderated by the depth of CSI
practices. Both essays contribute to the extant CSR / Sustainability literature and the marketing-
finance interface literature by investigating the roles of CSR, CSI on firm performance and
suggest guidelines to develop effective sustainability strategy to the practitioners.
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TABLE OF CONTENTS
LIST OF FIGURES ........................................................................................................................ v
LIST OF TABLES ......................................................................................................................... vi
ACKNOWLEDGMENTS ............................................................................................................ vii
CHAPTER 1: INTRODUCTION ................................................................................................... 1
1.1 Corporate Social Responsibility and Irresponsibility............................................................ 1
1.2 Triple Bottom Line (TBL)..................................................................................................... 2
1.3 Research Directions............................................................................................................... 4
CHAPTER 2: PERFORMANCE IMPLICATIONS OF CORPORATE SOCIAL
RESPONSIBILITY AND IRRESPONSIBILTY ........................................................................... 5
2.1 Introduction ........................................................................................................................... 6
2.2 Conceptual Background ...................................................................................................... 10
2.3 Model Development ............................................................................................................ 17
2.4 Data and Method ................................................................................................................. 27
2.5 Results ................................................................................................................................. 34
2.6 Discussion ........................................................................................................................... 40
CHAPTER 3: Portfolio Management in Sustainability Strategy and Firm Performance ............. 45
3.1 Introduction ......................................................................................................................... 46
3.2 Conceptual Background ...................................................................................................... 51
3.3 Data and Method ................................................................................................................. 65
3.4 Results ................................................................................................................................. 74
3.5 Discussion ........................................................................................................................... 77
CHAPTER 4: CONCLUSION ..................................................................................................... 83
APPENDIX ................................................................................................................................... 86
REFERENCES ............................................................................................................................. 92
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LIST OF FIGURES
Figure 1.1 Multi-dimensionality of Sustainability .......................................................................... 3
Figure 2.1The Four Mechanisms .................................................................................................. 10
Figure 2.2 Pairwise Correlation between CSR and Financial Performance ................................. 16
Figure 2.3 Pairwise Correlation between CSR and CSI ............................................................... 17
Figure 2.4 Impulse Response Functions ....................................................................................... 38
Figure 2.5 Forecast Error Variance Decomposition Results after 5 Years ................................... 39
Figure 3.1 Conceptual Framework ............................................................................................... 59
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LIST OF TABLES
Table 2.1 Strength and Concern Items of the KLD Social Rating Database ................................ 28
Table 2.2 Descriptive Statistics ..................................................................................................... 32
Table 2.3 Summary of Unit Root and Stationarity Tests of the Variables ................................... 34
Table 2.4 Estimation Results of Contemporaneous Effects .......................................................... 36
Table 2.5 Estimation Results from the Reduced-form Panel VAR Model ................................... 37
Table 2.6 Forecast Error Variance Decomposition Results after 5 Years .................................... 40
Table 3.1 Example of CSR/CSI Practice Portfolios ..................................................................... 69
Table 3.2 Descriptive Statistics ..................................................................................................... 72
Table 3.3 Hypotheses Testing Results .......................................................................................... 75
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ACKNOWLEDGMENTS
First of all, I would like to start by thanking my advisor, Rajdeep Grewal, for all his help
(including his gentle push), support, and patience throughout my five years in the PhD program
at Penn State. Raj is an exceptional mentor and I am sure that I would not be able to complete the
journey of Ph.D. without his help. I also want to thank other committee members: Hari Sridhar,
Duncan Fong, Saurabh Bansal, and Susan Xu for their guidance, suggestions, and feedback. I
feel sorry for the loss of Dr. Xu and hope she rests in peace. In addition, I would like to express
my appreciation to every faculty member and staff in the marketing department for the help and
encouragement.
I also owe a big thanks to my great colleagues whom I met during the Ph.D. program: to
name a few, Frank Germann, for helping me with developing research ideas and writing, Chen
Zhou, for being a great friend and peer mentor, Aditya Gupta, for being a great officemate, friend,
and peer reviewer, and M. K. Chin, for being a great friend and now a family. I feel so lucky to
meet you all. I also want to thank all Hoopers members and Yonsei Alumni group members for
making my life in State College exciting.
Finally, I would like to thank my parents, Seong Chul Kang and Jin Haeng Lee, who
always provided support, encouragement, and love, and my brother, Ji Hoon Kang, who cares his
little brother all the time. They have been a source of my encouragement. I love you all. Last but
not least, I would like to thank my beloved wife, Yang-Seon Kim, who makes me smile every
day. I will always love you and be grateful to you.
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Chapter 1
INTRODUCTION
Recent changes in the business environment have drawn researchers and practitioners’
attention to the topic of sustainability. For example, Tom Falk, Chairman and CEO of Kimberly-
Clark (K-C), stated that “Sustainability is an essential part of how we operates... The
sustainability movement is gaining momentum as more companies around the world implement
initiatives centered on environmental practices” in their annually issued sustainability report.1
Sustainability refers to “development that meets the needs of the present without compromising
the ability of future generations to meet their own needs” (World Commission on Environment
and Development 1987). Since this definition of sustainability seems to be too abstract for the
purpose of management decision making, Dow Jones Sustainability Indexes defines
sustainability in more practical way, “A business approach that creates long-term shareholder
value by embracing opportunities and managing risks that derived from economic,
environmental, and social developments.” This definition emphasizes two critical aspect of
sustainability: (1) two ways of achieving sustainability in business (i.e., embracing opportunities
and managing risks), and (2) the three pillars of sustainability the which are profit (i.e.,
economic), planet (i.e., environmental), and people (i.e., social).
1.1 Corporate Social Responsibility and Irresponsibility
Sustainability in business can be achieved in two ways: (1) by engaging in more socially
responsible practices, and (2) by minimizing social misbehavior that harms social welfare. The
former corresponds to engaging in corporate social responsibility (CSR), and the latter
1 http://www.sustainabilityreport2010.kimberly-clark.com/index.asp
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corresponds to reducing corporate social irresponsibility (CSI). For example, environmental
aspect of sustainability can be achieved by developing new recycling program, which is a CSR
practices. On the other hand, it can also be achieved by reducing the emission level of ozone
depleting chemicals, which is a CSI practice.
It is important to distinguish the ways of achieving sustainability for two reasons. First,
the benefits from engaging in CSR practices and minimizing CSI practices are different.
Engaging in CSR practices can benefit firms by trust, customer satisfaction, and positive attitude
toward company (e.g., Homburg, Stierl, and Bornemann 2013; Luo and Bhattacharya 2009;
Brown and Dacin 1997) because these firms meet not only societal and ethical obligations but
also philanthropic obligations. In contrast, minimizing CSI practices leads to minimum
penalization rather than positive rewards to the firm. In other words, reducing CSI practices is
perceived as societal and ethical obligations and meeting these obligations may be considered as
an extra effort that should be rewarded by stakeholders. Second, a firm’s decision to engage in
CSR practices and/or to reduce CSI practices can be interdependent. For instance, a firm may
decides to engage in CSR practices to compensate its recent socially irresponsible behavior. Or, a
firm may decide not to reduce its level of CSI practices engagement because it believes that its
previous CSR practice engagement creates good-will that will work as insurance against negative
publicity. In short, engaging in CSR and reducing CSI are two different ways to achieve
sustainability goal in business.
1.2 Triple Bottom Line (TBL)
In contrast to the previous belief of capitalism that firm’s responsibility is limited to
economical aspect, Elkington (1998) introduces Triple Bottom Line (TBL) principle which
views firm’s responsibility from three different angles: economic prosperity (profit),
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environmental quality (planet), and social equity (people). According to stakeholder theory
(Freeman 1984), firms are linked with many groups that can affect and are affected by firm
actions. Since companies have become more powerful and influential to the community and
environment than before, firms have to be more responsible for their actions. Thus, he argues
that firms should focus on the interdependencies among social, environmental, and economical
aspects to develop sustainable competitive advantage. First, the economic dimension focuses on
value creation and enhanced financial performance to satisfy the shareholders. Second, the
environmental dimension focuses on preserving environmental resources by, for example,
pollution prevention, clean energy, and recycling through corporate environmental management
(e.g., Bansal 2005). Finally, the social dimension focuses on firm activities that have impact on
society such as charitable giving, support for housing, and volunteer programs (e.g., Wood 1991).
To be considered as a responsible firm in terms of sustainability, the firm should meet all these
triple bottom lines. In short, sustainability is not uni-dimensional but multi-dimensional. Figure
1.1 displays the multi-dimensionality of sustainability.
Figure 1.1 Multi-dimensionality of Sustainability
Environmental
Social
Economic
CSI CSR
ty Sustainability
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Firms’ performances in these three dimensions can serve as integral market-oriented resources,
capabilities, and competitive advantage (e.g., Barney 1991; Hunt and Morgan 1995; Jaworski
and Kohli 1993). Further, this competitive advantage can develop into a sustainable competitive
advantage (e.g., Day and Wensley 1988) which leads to the greater firm performance.
1.3 Research Directions
Although the issue of sustainability has been drawn tremendous amount of attention from
academics as well as practitioners, previous research has not looked at the multi-dimensional
aspect of sustainability and its dynamic effect on firm performance. For example, researchers
have employed a global conceptualization of corporate social performance and inherently
assume that the effect of one CRI practice can be wiped out by engaging in one CSR practices
(e.g., Hillman and Keim 2001). In addition, most research in marketing has focused one societal
issue area of CSR such as “Green Marketing” or “Cause-related Marketing” rather than all three
pillars of sustainability (e.g., Lichtenstein, Drumwright, and Braig 2004; Robinson, Irmak, and
Jayachandran 2012).
To fill this gap, I look at the sustainability from the top and suggest critical findings in
my dissertation. In Chapter 3 (essay 1), I examine the dynamic relationship among corporate
social responsibility (CSR), corporate social irresponsibility (CSI), and firm performance.
Specifically, I focus on how CSR and CSI relate to firm performance. In Chapter 4 (essay 2), I
examine what types of CSR and CSI portfolios promise the best firm performance. Specifically,
building on financial portfolio theory, I seek to provide guidance on efficient sustainability
practice engagement management across three pillars of sustainability.
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Chapter 2
PERFORMANCE IMPLICATIONS OF CORPORATE SOCIAL
RESPONSIBILITY AND IRRESPONSIBILTY
ABSTRACT
We address the questions of whether and how Corporate Social Responsibility (CSR)
relates to firm performance, and, in so doing identify four mechanisms pertaining to this
relationship that have been proposed in the literature: (1) slack resources lead to CSR, i.e., slack
resources mechanism (2) CSR improves performance, i.e., good management mechanism, (3)
CSR makes amends for past Corporate Social Irresponsibility (CSI), i.e., penance mechanism,
and (4) CSR insures against subsequent CSI, i.e., insurance mechanism. To provide economic
foundations for CSR, we propose that firms exert CSR efforts as well as CSI efforts, where CSR
efforts promote social causes and CSI efforts reduce the probability of CSI incidents. With this
bifurcation of efforts we propose an economic theory model that builds on theory of the firm
primitives to demonstrate the complex interplay among CSR efforts, CSI efforts, and firm value.
To empirically model the complex dynamic interplay among CSR, CSI, and firm value (Tobin’s
q) and test for the four mechanisms, we propose a structural panel vector autoregression model to
empirically assess the four mechanisms. Results from panel data on over 4,500 firms across 19
years suggests that firms benefit financially from CSR and that CSI antecedes CSR, i.e., we find
empirical support for the good management and penance mechanisms. Our research adds to the
extant CSR literature by laying out the theoretical foundations for firms engaging in CSR and
CSI and demonstrating that CSR provides direct and indirect value to the firm.
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2.1 Introduction
Corporate social responsibility (CSR) – company actions that advance some social good
beyond that which is required by law (e.g., McWilliams and Siegel 2001) – continues to draw
interest from practitioners and academics alike. In 2008, The Economist (2008) reported that
about 56% of 1192 global executives surveyed considered CSR a “high” or “very high” priority
for their company, up from 34% just three years earlier. Of these same informants, 69% expected
CSR to be a “high” or “very high” corporate priority by 2011. Against this backdrop, most of the
extant academic CSR-related research has scrutinized the conception that companies do “well”
by doing “good” (e.g., McWilliams et al. 2006; in fact Margolis et al. (2007) use 167 empirical
studies in their meta-analysis that link organizational CSR and financial performance). However,
the debate on how doing “good” and doing “well” converge has yet to be resolved (e.g., Hull and
Rothenberg 2008; Mackey et al. 2007). Specifically, the following four mechanisms have been
proposed regarding the relationship between CSR and (positive) firm performance:
1. Slack Resource Mechanism: Companies engage in CSR because they are doing well
financially and have slack resources (e.g., McGuire et al. 1988).
2. Good Management Mechanism: CSR is part of “good management” and thus
improves financial performance (e.g., Freeman 1984).
3. Penance Mechanism: CSR acts as a form of penance to offset past Corporate Social
Irresponsibility (CSI)2(e.g., Kotchen and Moon 2012).
4. Insurance Mechanism: CSR builds a reservoir of goodwill that softens the blow if and
when things go wrong, i.e., CSR provides an insurance mechanism against CSI (e.g.,
Minor and Morgan 2011).
The good management, penance, and insurance mechanisms, explicitly or implicitly,
postulate positive effects of CSR on firm performance whereas the slack resource mechanism
suggests a positive effect of firm performance on CSR. In other words, while not mutually
2 We define CSI as incidents that appear to hurt the social good, i.e., the antipode of CSR. BP’s Deepwater Horizon
oil spill in 2010 is an example of a CSI incident.
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exclusive, good management and slack resource mechanisms propose reverse causal paths.
Likewise, while also not mutually exclusive, penance and insurance mechanisms again propose
reverse causal paths. Indeed, the penance mechanism suggests that firms engage in CSR in time t
to offset CSI that occurred in time t-1 whereas the insurance mechanism proposes that firms
engage in CSR in time t–1 to insure against CSI in time t.
The key purpose of this study is to unravel these four mechanisms and thus further the
debate on how doing “good” and doing “well” converge. Moreover, while addressing the how
question, we also shed light on the at least equally important question of whether doing "good"
and doing "well" converge. We find that the answer to the whether question appears to be “yes”;
hence, the answer to the how question has substantial managerial and academic significance.
Of note is that the CSR literature provides empirical support for each one of the four
mechanisms; however, a limitation of the literature is that it has not yet studied the four
mechanisms simultaneously. Indeed, the studies only examine one, and at the most two of the
mechanisms (i.e., slack resource and good management) at a time. Such an approach of studying
one or two mechanisms at a time is problematic as important concomitant effects among the four
mechanisms cannot be addressed thus resulting in either a partial picture of the phenomenon or
worse yet, false statistical findings. Also, most studies have employed econometric models that
are simplistic and correlational (and not causal) in nature. Highlighting the issues regarding these
models, Margolis et al. (2007, p. 27) urge that “causal mechanisms need to be […] tested”.
Similarly, King and Lenox (2001, p. 107) suggest that if “one cares merely about correlation and
little about causation, these correlative studies are informative [….]. From the perspective of
corporate managers and policy analysts, however, the distinction is critical.” In this study, we
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follow an integrative approach and examine all four mechanisms simultaneously. We also use
what we deem to be appropriate econometric techniques to test causal relationships.
Moreover, in the extant literature, there is no economic theoretical foundation for the
study of CSR. Such a foundation helps develop “a better understanding of economic activities
and outcomes” (Kreps 1990, p. 7). We thus develop an economic theory model which (1) builds
on theory of the firm primitives to view the firm as maximizing net present profit and (2) uses
optimal control theory to model the costs associated with CSR efforts and CSI efforts as well as
the evolution of sales with CSR efforts and CSI efforts. In contrast to the current singular
conceptualization of CSR efforts, we propose that firms exert CSR efforts as well as CSI efforts,
where CSR efforts promote social causes (e.g., for every pair of shoes that Toms sells, it donates
one to a child in need which is known as the “one for one” model), and CSI efforts reduce the
probability of CSI incidents (e.g., Exxon Mobile reinforces the hulls of its crude oil
transportation ships to reduce the probability of oil leaks when accidents occur).3 Our economic
theory model demonstrates a complex interplay among CSR efforts, CSI efforts, and firm value4
and thus suggests that our empirical model specification should capture the simultaneous
interplay among these three variables. Further, recognizing (1) that our annual data encompasses
more than 4,500 firms across 19 years (i.e., large cross section and small time series), (2) that
there is a need to model the interplay among CSR, CSI, and firm value simultaneously, and (3)
the possibility of contemporaneous effects among the three variables in our annual data, we
propose and estimate a structural panel vector autoregressive (SPVAR) model.
3 We include CSI efforts in our economic theory model to capture the costs associated with avoiding CSI. In our
econometric model, however, we model level of observed CSI and not CSI efforts (similar to CSR where the theory
model deals with CSR efforts and the empirical model with level of observed CSR). CSI and CSI efforts are, of
course, related, and a firm’s CSI is largely a manifestation of its CSI efforts (i.e., the lack thereof). We also note
that, throughout the manuscript, when we use the term CSI (CSR) we refer to level of CSI (CSR). 4 We conceptualize firm value as net present value of current and future profits and operationalize it as Tobin’s q.
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Our results show support for good management and penance mechanisms; thus, our
empirical findings suggest that (1) firms benefit financially from CSR, i.e., CSR leads to positive
financial performance and (2), CSI antecedes CSR temporally, i.e., firms seem to use CSR to
offset past CSI. Thus, our findings suggest that beyond the overt performance implications, CSR
might also have a more subtle and covert impact on a firm’s performance by potentially
offsetting and/or attenuating the negative effects of past CSI. This latter effect has often been
overlooked in the evaluations of the relationship between CSR and financial performance.
As we elaborate in the final section of the manuscript, we contribute to the extant CSR
literature in five important ways: First, we summarize the varying propositions of how CSR and
firm performance converge into four mechanisms, and, more importantly, we test these four
mechanisms simultaneously. Second, we separate CSI from CSR and integrate the two constructs
into the overall “CSR-CSI-financial performance” framework. Third, our economic theory model
provides a theoretical basis for the development of future econometric models that seek to study
the dynamic relationship among CSR, CSI, and firm performance. Fourth, we provide empirical
evidence that CSR has a positive impact on firm performance. We note that the SPVAR model
allows us to make causal claims regarding the relationship between CSR and firm performance.
And finally, we show that CSI tends to temporally antecede CSR; thus, we provide some
evidence for the notion that firms use CSR (at least partially) to offset past CSI.
We proceed as follows: We first elaborate on the four mechanisms that have been
proposed in the extant literature. Next we present the building blocks of our microeconomic
theory model (which is detailed in Appendix A) and then develop an empirical model
specification that allows us to examine the dynamic interplay among CSR, CSI, and firm
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performance. Subsequently, we present our data and empirical results. We conclude with a
discussion of the theoretical and managerial implications, as well as limitations, of our research.
2.2 Conceptual Background
The extant literature posits four mechanisms of how CSR and firm performance relate to
each other. As shown in Figure 2.1, the first two mechanisms are concerned with the direct link
between a firm’s CSR and its financial performance whereas the last two mechanisms examine
the link between CSR and CSI, where the performance implications of CSR are implicit in the
latter two mechanisms.
Figure 2.1The Four Mechanisms
Slack Resource Mechanism
A plethora of studies have examined the direct link between a firm’s CSR and its
financial performance (for a survey see Margolis et al. 2007). Some of these studies posit that
firms engage in CSR because they are doing well financially. Generally referred to as the slack
resources mechanism, supporters of this link tend to argue that good financial performance
provides firms with slack resources which, in turn, provides the firms with the opportunity to
Financial Performance CSR
Mechanism 1
Slack Resources:
Financial performance in (t-1)
causes CSR in t
time (t)CSI CSR
Mechanism 3:
Penance:
CSI in (t-1) causes CSR in t
time (t)
Financial Performance CSR
Mechanism 2:
Good Management:
CSR in (t-1) causes financial
performance in t
time (t)CSICSR
Mechanism 4:
Insurance:
CSI in t causes CSR in (t-1)
time (t)
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invest in CSR related activities, such as community relations (e.g., Waddock and Graves 1997).
In addition, proponents of the slack resources mechanism tend to view CSR activities are
voluntary, meaning that managers have a high flexibility to initiate or cancel them. Accordingly,
they argue that a firm’s decision to invest in CSR activities largely depends on the availability of
excess cash (McGuire et al. 1988). Similarly, advocates of the slack resources mechanism also
tend to believe that CSR related activities are not critical to the success of the company, i.e., that
they fall under the category of discretionary spending, and are hence especially sensitive to the
existence of slack resources (e.g., McGuire et al. 1988).
Supporters of the slack resources mechanism have used various examples to support their
mechanism. For example, Waddock and Graves (1997) reported that IBM had significant
philanthropic programs during good economic times but canceled many of those programs when
the going got tougher. Also, arguably the most cited scholarly article in support of the slack
resources mechanism is the one by McGuire et al. (1988) in which they find that a firm’s prior
performance is more closely related to its CSR than subsequent performance. Others, such as
Preston and O’Bannon (1997), conclude that the relationship between CSR and financial
performance is bi-directional, while Scholtens (2008) reports that only a few studies have used
CSR as the dependent and financial performance as the independent variable. Thus, empirical
substantiation of the slack resources mechanism, besides anecdotal evidence such as the IBM
example mentioned above, is relatively sparse.
Good Management Mechanism
Most of the extant empirical CSR related research has scrutinized the conception that
companies do “well” by doing “good” (e.g., McWilliams et al. 2006; Margolis et al. 2007). Of
these studies, roughly 50% find a positive relationship between CSR and financial performance,
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25% find no relationship, 20% find mixed results, and 5% find a negative relationship (Margolis
and Walsh 2001; Scholtens 2008).5
Proponents of the doing “well” by doing “good” viewpoint argue that the cost of CSR is
lower than the benefits that accrue from it (e.g., Hull and Rothenberg 2008) and that it is simply
a part of good management to engage in CSR. They suggest, for example, that superior CSR can
attract and retain quality employees (e.g., Greening and Turban 2000), enhance the morale,
productivity and satisfaction of employees (e.g., Waddock and Graves 1997), reduce costs by
increasing operational efficiencies (e.g., Hart and Ahuja 1996), increase customer satisfaction
(e.g., Luo and Bhattacharya 2006), and help the firm market its products (e.g., Fombrun 1996).
Advocates of this link have proposed that CSR can become a source of competitive advantage
due to, for example, the resulting positive stakeholder perceptions of the firm (e.g., Hull and
Rothenberg 2008). Accordingly, scholars who support the positive effect of CSR on financial
performance have argued that CSR improves stakeholder relationships, which leads to positive
firm performance (Freeman 1984; Hillman and Keim 2001).6
Penance Mechanism
Historically, most research has examined the slack resource and\or good management
mechanisms to address how CSR and firm performance relate to each other; more recently,
however, scholars are beginning to explore other mechanisms. Building on Heal (2005), who
proposed that CSR is a program of actions for firms to reduce externalized costs, Kotchen and
Moon (2012) argue that firms engage in CSR as a form of penance to offset its past CSI.
5 Financial performance is treated as the dependent and CSR as the independent variable in most of these studies.
6 As indicated above, a small fraction (i.e., about 5%) of the studies that have examined the CSR – financial
performance link reason that CSR results in negative financial performance (e.g., Margolis and Walsh 2001;
Scholtens 2008). Advocates of this negative effect usually argue that CSR unnecessarily raises a firm’s costs (e.g.,
Aupperle et al. 1985; McWilliams and Siegel 1997), and that it draws resources away from the core areas of
business (e.g., Jensen 2002) which ultimately results in subpar performance.
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Specifically, Kotchen and Moon (2012) argue that CSR is a type of Coasian solution that allows
firms to efficiently reduce externalized costs, i.e., costs that the firm has caused through CSI but
that it does not pay back in full. CSR allows the firm to make amends for the “unpaid bill”.
For example, in the case of an oil spill, the company that caused the spill usually only
pays a fraction of the long-term costs that accrue from the spill, largely because it is impossible
to estimate the precise long-term costs and damage caused. Or when firms treat their workers
poorly, it is difficult to gage the negative ripple-effect that this poor treatment can have on the
individual workers, their family, and the communities they live in. Yet, there is sufficient
empirical evidence that shows that firms are penalized if they are perceived as not holding their
end of the bargain, and, conducting their business in ways that conflict with social norms and
values. For example, following the Deepwater Horizon oil spill in 2010, US public opinion polls
were extremely critical of BP’s initial response to the spill, and sales at BP gas stations declined
by as much as 40% (WSJ, 2010). Thus, Kotchen and Moon (2012) argue that firms have an
incentive to engage in CSR because it acts as a penance mechanism that allows the firm to
compensate for externalized costs stemming from past CSI. The performance implications of this
approach, of course, are implicit.
Insurance Mechanism
Similar to the penance mechanism, advocates of the insurance mechanism argue that it is
imperative to consider CSR and CSI as separate constructs. Moreover, proponents of the
insurance mechanism also view CSR as a strategic mechanism that can protect against CSI (e.g.,
Fombrun et al. 2000; Peloza 2006; Minor 2011; Minor and Morgan 2011). The difference
between the two mechanisms, however, is that the proponents of the insurance mechanism posit
that CSR should not be used as a form of penance to atone for CSI but rather as insurance against
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CSI. Thus, compared to penance mechanism, where CSI in time t-1 causes CSR in time t,
proponents of the insurance mechanism propose that potential CSI in time t should cause CSR in
time t-1. The insurance mechanism is conceptually grounded in the literature that suggests that a
firm’s good reputation can serve as an intangible asset in times of crises and attenuate negative
stakeholder responses to bad news (e.g., Jones et al. 2000; Schnietz and Epstein 2005); i.e., CSR
presumably helps build a reservoir of goodwill among the firm’s stakeholders that endows the
firm with idiosyncrasy credits that act as safeguards, i.e., as an insurance, when bad things, i.e.,
CSI, happens.
Klein and Dawar (2004) provide empirical support for the notion that CSR acts as an
insurance mechanism against CSI. Specifically, they found that CSR attenuates negative
consumer responses in the case of a product harm crisis. Further, Minor (2011) and Minor and
Morgan (2011) propose that the primary role of CSR is to increase a firm’s value by insuring the
firm against potential losses caused by CSI. The performance implications of this mechanism are
thus again implicit; while the returns to CSR during “normal times” might be insignificant, the
financial benefits of CSR during adverse events can be substantial.
Summary and Initial Evidence
Although four mechanisms regarding the relationship between CSR and firm
performance have been proposed in extant literature, there has been no attempt to simultaneously
study these mechanisms. The majority of the literature focuses on one mechanism at a time
(typically on the direct influence of CSR on firm performance outcomes) and thus only paints a
partial picture for the influence of CSR. Further, the dichotomization of CSR into CSR and CSI
is also a recent phenomenon, where the recognition is explicit that a good deed need not
completely write off a bad deed. Also, no attempt has been made to provide a microeconomic
15
basis for CSR and CSI that would layout the primitives for the importance of these
organizational activities. Finally, as King and Lenox (2001) observe, the methods used in the
extant CSR literature have been either too simplistic, perhaps because they focus on only one
mechanism, or simply inappropriate (also see Margolis et al. 2007; Scholtens 2008).
To further corroborate the misgiving that can stem from correlational analysis focusing
on only one relationship at a time, we resort to model free analysis of our data. As we elaborate
subsequently, we have firm level annual data for up to 19 years (i.e., unbalanced panel) from
multiple sources on number of CSR actions, CSI incidents, firm performance (Tobin’s q), and
other variables. In Figure 2.2 we show the pairwise correlation between a firm’s lagged CSR (i.e.,
t-1), measured using the CSR ratings provided by the Kinder, Lydenberg, and Domini (KLD)
Social Ratings Database, and its current financial performance (i.e., t) as well as the pairwise
correlation between a firm’s CSR (i.e., t) and its lagged financial performance (i.e., t-1).
As can be seen, the correlation between lagged CSR and financial performance (solid line)
is positive from 1992 to 2002 and close to zero from 2003 to 2009. Thus, one might conclude
that firms benefit financially from CSR (i.e., that the data provides support for the good
management mechanism) given the positive correlation between the two constructs up until 2002.
However, a look at the dotted line in Figure 2.2 reveals that the correlation between lagged
financial performance (i.e., t-1) and CSR (i.e., t) looks quite similar. Indeed, financial
performance in t-1 is positively correlated with CSR from 1992 to 2005. Hence, based on this
“evidence”, one might conclude that companies engage in CSR because they are doing well
financially (i.e., support for the slack resource mechanism).
16
Figure 2.2 Pairwise Correlation between CSR and Financial Performance
Similarly, in Figure 2.3 we present the correlation between CSR and CSI. Specifically,
the solid line in Figure 2.3 shows the pairwise correlations between a firm’s lagged CSR (i.e., t-1)
and its CSI (i.e., t), as measured by the KLD Social Ratings Database. As can be seen, the
correlation between lagged CSR and CSI (solid line) increases from 0.03 in 1993 to 0.43 in 2003,
and remains at around 0.40 until 2009. Further, the dotted line in Figure 2.3 shows the pairwise
correlation between CSR (i.e., t) and lagged CSI (i.e., t-1) and shows a very similar pattern. Thus,
paradoxically, these patterns suggest that firms increasingly tend to do both “good” and “bad”,
and, it hence seems sensible to examine which comes first – CSI or CSR? We note that the
correlational analysis again does not shed much light on whether CSR antecedes CSI or vice
versa.
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
1992 1994 1996 1998 2000 2002 2004 2006 2008
Co
rrel
ati
on
Year
lag(CSR) & Tobin's q
17
Figure 2.3 Pairwise Correlation between CSR and CSI
Thus, we seek to provide a microeconomic basis for the relationship among CSR, CSI,
and firm performance and to develop an empirical model specification that would allow us to test
for the existence of the four mechanisms simultaneously.
2.3 Model Development
We begin by overviewing our theoretical model (which is an exercise in spirit similar to
Hanssens and Ouyang 2001), where for exposition purposes, the details are in Appendix A. The
objective of the theory model is to provide a microeconomic foundation for the CSR-CSI-
performance framework. We then elaborate on our empirical model specification – where we
recognize the structure of our data and our research objectives of simultaneously studying the
four mechanisms. We end this section by discussing our estimation approach for the SPVAR
empirical model specification we need for our research.
Theory Model
Building on the primitives from the theory of the firm (e.g., Becker 2007), we outline an
optimal control theory based model in Appendix A. In this model, we suggest that efforts related
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1992 1994 1996 1998 2000 2002 2004 2006 2008
Co
rrel
ati
on
Year
lag(CSR) & CSI lag(CSI) & CSR
18
to CSR and CSI influence sales and that there are costs associated with these efforts. Thus, as is
customary in optimal control theory (e.g., Kamien and Schwartz 1991) and recent applications of
the theory in marketing (e.g., Sridhar et al. 2011), we specify an infinite horizon problem in
which a firm maximizes its profits subject to constraints emanating from the sales evolution
function.
For the specific case of CSR, the uniqueness arises in the specification of costs and the
sales evolution function. For costs, we include direct costs associated with (1) CSR efforts and (2)
CSI efforts, as is usually done (e.g., Naik and Raman 2003), but we also include (3) costs
associated with CSI incidents, such as oil spills as in the case of BP. First, costs associated with
CSR are the direct costs the firm expends on CSR activities such as donating to a charitable
cause (e.g., Coca Cola donating bottled water during hurricane Katrina). It is important to note
that the costs of CSR activities are private information for the firm, while the outcomes are
publically observed; however, efforts should drive outcomes. Thus, our theory model focuses on
efforts and our empirical model on outcomes; the link between efforts and outcomes should be
apparent.
Second, similar to CSR costs, costs associated with CSI are also direct costs for CSI
activities. Further, here again efforts are private information for the firm while level of CSI is
publically observed. The distinction between CSR and CSI is in the outcomes; while CSR are
primarily actions, CSI are principally incidents. CSI incidents, such as oil spills, are truly
exogenous but firms can spend efforts to reduce the probability of such incidents. For example,
Nike could spend efforts on sustainability officers that scrutinize all important organizational
decisions such that it can ensure that its outsourcing manufacturing partners do not use child
19
labor.7 Nonetheless, CSI efforts should relate directly to CSI incidents and thus, the link between
theory model that focuses on CSI efforts and the empirical model that focuses on CSI actions and
incidents is similar to that for CSR.
Third, truly unique to our research context (see Appendix A for details), we model the
costs associated through the expected loss and buffering effects of CSR efforts and CSI efforts.
Three features of this specification are worth noting: (1) the buffering effects of effort increase as
efforts increase; (2) we allow for the possibility that the effect of the efforts can be reduced or
enhanced; and (3) we also allow for the possibility of difference in the buffering effects of CSR
efforts and CSI efforts.
For the evolution of the sales function, as is customary (e.g., Naik and Raman 2003), we
specify the rate of change in sales as a function of past sales and efforts in CSR and CSI; further,
we suggest that the efficacy of CSR efforts and CSI efforts depends on the level of sales such
that larger firms with higher sales tend to receive greater scrutiny. This model specification of
costs and sales evolution reveals that there is a complex interplay among CSR efforts, CSI efforts,
and firm sales and net present value of profits.
Empirical Model Specification
Based on the economic model specification, it is apparent that an ideal dataset would
have information on firm sales and profits as well as CSR and CSI efforts over time. However,
as we elaborate subsequently, we have annual panel data on firms, where we observe firm value
(Tobin’s q to be specific) and the attained levels of CSR and CSI as opposed to CSR efforts and
CSI efforts. In the spirit of econometric models, which are “concerned with the empirical
7 The distinction between CSR efforts and CSI efforts is of theoretical importance; however, it is not always possible
to isolate effort as either CSR or CSI. For example efforts concerning sustainability officers can be seen as CSR
efforts or CSI efforts. Nevertheless, for vast majority of efforts, it is easy to classify them as either CSR efforts or
CSI efforts.
20
estimation of economic relationships,” we follow Intriligator (1983, p. 182) in that “the theory of
the phenomena under investigation is developed into a [economic] model which is further
refined into an econometric model.” As the theoretical model recognizes the endogeneity of firm
value and CSR efforts and CSI efforts, the level of CSR and CSI, which are attained by CSR
efforts and CSI efforts, also become endogenous and are determined by firm value (i.e., net
present profits that reflect the difference between sales and costs for an infinite horizon). Thus,
we seek to specify a system of equations in which Tobin’s q, CSR, and CSI influence each other
over time. In addition, the panel data model specification is required since our data set contains a
large number of firms (approximately 25,600 overall) which exceed the time dimension (19
years) (Baltagi 2005). Recognizing that we have data on a large number of firms as well as a
system of equations, and that we seek to model dynamics, we employ a panel vector
autoregression (VAR) specification (e.g., Holtz-Eakin et al. 1988, Love and Zicchino 2006).
Further, we require a model specification that incorporates contemporaneous effects among the
endogenous variables. As we have annual-level data, it seems reasonable to assume that there are
contemporaneous effects among some of the focal variables (i.e., CSR, CSI, and firm value).
Hence, we employ a SPVAR specification where a vector of endogenous variables is linearly
represented by its current and lagged effects (e.g., Cooley and Dwyer 1998, Enders 2004).
To summarize, our model specification incorporates three key features: (1) the dynamic
interplay and endogeneity among CSR, CSI, and firm value, (2) a large number of firms
compared to a short time dimension, and (3) possible contemporaneous effects due to the annual
level data. Hence, we specify the relationship among CSR, CSI and firm value through the
following structural panel VAR model:
21
(1) [
] ∑ [
] [
]
where
[
]
and is the firm index, { } is the time period index, , , and
are the endogenous variables in the system, , is
the matrix which indicates the contemporaneous relationships among the endogenous
variables, where , and represent the contemporaneous effect of CSI on CSR, the
contemporaneous effect of CSI on Tobin’s q, and the contemporaneous effect of CSR on Tobin’s
q, respectively, are the coefficient matrices of the lags of the endogenous variables
where ,
, , and
are associated with the four mechanisms, i.e., slack
resources, good management, penance, and insurance mechanism, respectively, is the number
of lags, is the vector of the control variables for firm at time , are the
coefficients of the control variables, is the unobserved firm-specific fixed effect, and
[
]
is the error term for the system of equations. Also the
composite error term [
]
is expressed as the usual ‘fixed effect’
decomposition where . Further, we assume that is independently and
identically distributed across and with the assumption that ( | )
and, ( | ) {
}
22
where is a positive definite matrix.8
Compared to the reduced-form panel VAR specification, our structural panel VAR model
is multiplied by the matrix to account for potential contemporaneous effect. Specifically, we
assume that CSI has a contemporaneous effect on CSR (i.e., ), but not the other way
around. This seems reasonable as firms frequently engage in CSR activities shortly after
committing CSI to attenuate (e.g., following its toy recall in late 2007, Mattel started testing
every production batch of toys for containing potentially dangerous levels of chemicals and
toxins) negative consumer responses (please see discussion above). However, we do not see any
reasons why firms would engage in CSI activities immediately after engaging in CSR activities.
Further, we also assume that CSI has a contemporaneous effect on firm value (i.e., ), but
not vice versa. Firms’ stock prices and/or sales often decrease after a significant CSI incident
(e.g., BP’s stock price decreased after the oil spill in 2010). Yet, current firm value should not
affect the current level of CSI. Finally, we assume that CSR has a contemporaneous effect on
firm value (i.e., ), but not vice versa. Firms evaluate and plan their CSR activities and
goals annually and do not change their CSR strategy based on short-term financial performance.
In contrast, as shown by Cellier and Chollet (2011)’s event study, CSR announcements can
influence short-term financial performance. In summary, we let the matrix be a lower triangle
matrix since we believe there are no contemporaneous effects on CSI from CSR and firm value
and on CSR from firm value. Hence, we use this recursive causal ordering to identify the
structural parameters in the matrix .
Estimation Procedure
8 This assumption ensures that the equation-by-equation estimator (e.g., Arellano and Bond 1991; Blundell and
Bond 1998) is asymptotically equivalent to the corresponding system-of-equations estimator of panel VAR models
(Cao and Sun 2011).
23
We follow a two-step approach to estimate the structural VAR model (e.g., Blanchard
and Perotti 2002; Blanchard and Quah 1989; Sims 1980). That is, we first estimate the reduced-
form VAR model and then estimate the structural parameters from the variance-covariance
matrix of residuals from the reduced-form VAR estimation.
First, we multiply equation (1) by (the inverse of the contemporaneous effect matrix)
and derive the reduced-form representation of equation (1).
(2) [
] ∑ [
] [
]
where, [
] [
] , , , and
[
]
.
From the mapping between and , we can derive the relationship between the
variance-covariance matrix of the reduced-form residual ( ) and the variance-covariance matrix
of the structural-form residual ( ) such that . Second, we obtain estimates of
and by using the estimate of . In general, several identification restrictions are needed since
there are knowns (the distinct elements of ) and unknows (the
elements of and the distinct elements of ). For identification, we set the
diagonal elements of equal to 1 by scaling and let be the lower triangle matrix based on our
recursive causal ordering. In other words, we impose some short-run restrictions which rely on
the contemporaneous effect assumptions. In addition, as suggested in the literature (e.g.,
Bernanke 1986; Sims 1986), we assume that is a diagonal matrix. Thus, our SPVAR model is
just identified and we can obtain structural parameter estimates of and .
24
When estimating equation (2), we have to consider the following three econometric
issues: (1) endogeneity, (2) unobserved heterogeneity, and (3) dynamic panel bias. First, CSR,
CSI and financial performance are assumed to be endogenous because, as discussed above, the
causality may run in both directions. That is, doing “good” may lead to doing “well” financially
and/or vice versa. Similarly, companies may be doing “good” to protect the firm against
subsequent mishaps and/or, alternatively, to compensate for their past mishaps. In other words, it
is possible that our variables of interest can be explained by their lagged values and/or by the
lagged values of the respective other endogenous variables (Pauwels et al. 2004). These potential
feedback effects among the regressors may be correlated with the error term. Dynamic panel
GMM estimators such as the Blundell and Bond (1998) estimator account for this type of
endogeneity that arises from direct and indirect feedback effects among the regressors.
Specifically, by using lagged values of the endogenous regressors and lagged first-difference
scores of the regressors as additional instruments, the endogenous variables become pre-
determined and are therefore not correlated with the error term (Arellano and Bond 1991;
Arellano and Bover 1995; Holtz-Eakin et al. 1988).
Second, unobserved heterogeneity may play a critical role in determining a firm’s CSR
and CSI scores. For example, companies operating in the oil and gas industry may engage in
more environmentally harmful activities than companies that operate in the food and beverage
industry. Thus, we need to control for this unobserved heterogeneity to detect the true
relationship among CSR, CSI and financial performance. We use first-differencing which allows
us to control for unobserved heterogeneity stemming from firm-specific and industry-specific
effects (Cameron and Trivedi 2005). In short, by first-differencing, time-invariant firm-specific
and industry-specific effects are removed. In other words, the unobserved firm-specific effect
25
cancels out in the model and, considering the iid assumption of , our estimation gives
consistent slope estimates.
Third, as we will show, our panel data has a relatively short time series dimension (T) and
a large cross-sectional dimension (N). Estimating equation (2) using a first-difference ordinary
least square approach or a least square dummy variable approach would give inconsistent and
biased estimates (i.e., result in a dynamic panel bias; Nickell 1981). That is, in the dynamic panel
models, the first-difference OLS estimator is inconsistent because the regressors include lagged
dependent variables (Cameron and Trivedi 2005). In contrast, the dynamic panel GMM estimator
allows us to overcome the dynamic panel bias. To obtain consistent estimates, Anderson and
Hsiao (1981) proposed an instrumental variable (IV) approach that estimates the first-difference
model using the lags of the dependent variable as an instrumental variable. Later, Holtz-Eakin et
al. (1988) and Arellano and Bond (1991) extended Anderson and Hsiao’s (1981) idea and
proposed a panel GMM estimator using not only the additional lags of the dependent variables
but also the lags of the difference of the dependent variables as instruments. Subsequently,
Arellano and Bover (1995) and Blundell and Bond (1998) developed a system GMM estimate
which uses lags of differences for equations in levels and also lags of levels as instruments for
equations in first differences. They showed that an efficiency gain in estimation is possible even
when the time series is nearly unit root.
Thus, we use the Blundell and Bond (1998) estimator to deal with the weak instruments
problem in first-differenced models as well as the dynamic panel bias which is a common
problem in small and large panels such as the one we are using. We also note that the
Blundell and Bond (1998) estimator has been widely used to test causal relationships when using
26
panel data (e.g., Huang et al. 2008). In the following, we briefly present the Blundell and Bond
(1998) estimator as well as the moment conditions.
We first derive the first-difference of equation (2) to remove the unobserved firm-specific
time invariant effect .
(3) [
] ∑ [
]
where is the first-difference operator.
Note that is cancelled out since = ( ) . For
identification, we assume the standard initial conditions on
that for and (e.g., Ahn and Schmidt 1995). The standard
moment condition is the orthogonality condition between the dependent variable and the lagged
error term: ( ) . In addition, we impose two extra
moment conditions for the GMM estimation. These are T-3 linear moment conditions:
( ) for and =0. Due to these two moment conditions, the
lagged differences of the dependent variable can be used as a possible instrument. In general, the
asymptotically efficient GMM estimation based on the set of moment conditions is as follows:
Let where is a matrix of stacked coefficients of lagged
dependent variables. The GMM estimator of , where denotes the column
stacking operator, is given by (Cao and Sun 2011; note that we modified their equation (7)),
( ) (( ) )
where
∑
∑
(
∑
)
27
is a identity matrix, is the Kronecker product, is the weight matrix, and are
consistent estimates of the first-differenced residual obtained from a preliminary consistent
estimator (this is known as a two-step GMM estimator). is a matrix with -
th row , , is a vector with -th row , and is the
instrument matrix such that,
(
)
where (
) ].
To estimate the dynamic relationship among CSR, CSI and financial performance, we
calculate the orthogonalized impulse response function. To do so, we need to estimate the
covariance matrix of the error . The estimator of is given by,
∑∑
where ∑ ( ) , and
are the averages of the dependent variables and the control variables over time, respectively.
2.4 Data and Method
KLD Social Ratings Database
Our data comes from two sources: We first obtained corporate social performance data
from the Kinder, Lydenberg, and Domini (KLD) Social Ratings Database. This database has
been widely used in the academic literature (e.g., Hull and Rothenberg 2008; Kotchen and Moon
28
2012), and it provides annual data on firms’ performance in seven social issue areas, including
community, corporate governance, diversity, employee relations, environment, human rights and
product quality and safety. Further, the KLD database provides multiple indicators regarding a
firm’s strengths and concerns in each of the seven social issue areas. For instance, the
community area consists of 8 strength indicators (e.g., charitable giving, support for housing,
support for education) and 6 concern indicators (e.g., investment controversies, negative
economic impact). Table 2.1 lists all strength and concern indicators across the 7 issue areas.
Altogether, the database covers approximately 80 indicators.
Table 2.1 Strength and Concern Items of the KLD Social Rating Database
Qualitative Issue
Area
Type Categories # of
Categories
Corporative
Governance
Strengths
Limited Compensation
Ownership Strength
Transparency Strength (added ’05)
Political Accountability Strength (added ’05)
Other Strength
5
Concerns
High Compensation
Ownership Concern
Accounting Concern (added ’05)
Transparency Concern (added ’05)
Political Accountability Concern (added ’05)
Other Concerns
6
Community
Strengths
Charitable giving, Innovative giving
Non-US Charitable giving
Support for Housing
Support for Education (added ’94)
Indigenous Peoples Relations (added ’00,
moved ’02)
Volunteer Programs (added ’05)
Other Strength
8
Concerns
Investment Controversies
Negative Economic Impact
Indigenous Peoples Relations (’00-’01)
Tax Disputes (added ’05)
Other Concerns
5
Diversity
Strengths
CEO
Promotion
Board of Directors
8
29
Work/Life Benefits
Women & Minority Contracting
Employment of the Disabled
Gay & Lesbian Policies
Other Strength
Concerns
Controversies
Non-Representation
Other Concerns
3
Employee
Relations
Strengths
Union Relations
No-Layoff Policy (ended ’94)
Cash Profit Sharing
Employee Involvement
Retirement Benefits Strength
Health and Safety Strength
Other Strength
7
Concerns
Union Relations
Health and Safety Concern
Workforce Reductions
Retirement Benefits Concern (added ’92)
Other Concerns
5
Environment
Strengths
Beneficial Products and Services
Pollution Prevention
Recycling
Clean Energy
Communications (added ’96, moved ’05)
Property, Plant, and Equipment (ended ’95)
Management Systems
Other Strength
8
Concerns
Hazardous Waste
Regulatory Problems
Ozone Depleting Chemicals
Substantial Emissions
Agricultural Chemicals
Climate Change (added ’99)
Other Concerns
7
Human Rights
Strengths
Positive Record in South Africa (’94-’95)
Indigenous Peoples Relations Strength (added ’02)
Labor Rights Strength (added ’02)
Other Strength
4
Concerns
South Africa (ended ’94)
Northern Ireland (ended ’94)
Burma Concern (added ’95)
Mexico (’95-’02)
Labor Rights Concern (added ’98)
Indigenous Peoples Relations Concern (added ’00)
Other Concerns
7
Product
Strengths
Quality
R&D/Innovation
Benefits to Economically Disadvantaged
Other Strength
4
30
Concerns
Product Safety
Marketing/Contracting Concern
Antitrust
Other Concerns
4
Consistent with Kotchen and Moon (2012), we consider all strength indicators as CSR
and all concern indicators as CSI of the firm. This approach of treating the strength and concern
indicators as separate items is also in line with Mattingly and Berman (2006) who show that the
strength and concern indicators are divergent constructs and should not be combined.
Further, the KLD database provides a yearly binary summary of a firm’s strengths (i.e.,
CSR) and concerns (i.e., CSI) for each indicator belonging to the seven social issue areas. For
example, if a firm has consistently given over 1.5% of trailing three-year net earnings before
taxes to charity, then the “charitable giving” CSR indicator for the firm and year is coded as 1,
otherwise 0.
To determine each firm’s CSR in a given year, we followed Kotchen and Moon’s (2012)
approach and summed up the firm’s scores of all “strength” items in and across all seven issue
areas. We repeated the same procedure to determine each firm’s CSI in a given year summing up
the scores of all “concern” items in and across all seven issue areas. Thus, for each year, we
calculated two scores for each firm – one representing the firm’s overall CSR and the other one
its overall CSI. We note that this procedure places equal weight on each item. Then, we created
the standardized overall CSR and CSI scores for each firm and year.
We standardized the scores for two reasons: First, some of the items were added and/or
removed over the years. Thus, the total number of “strengths” and “concerns” varies over time.
Second, the number of companies included in the KLD database also varies over time. To
minimize the effect of different samples sizes and to make the CSR and CSI variables
comparable across the years, we used their standardized scores in our analysis.
31
The KLD data begins in 1991, and we used the complete KLD dataset up until 2009.
Thus, all firms for which KLD provides data for the time period between 1991 and 2009
constituted our initial sample. As mentioned above, the number of companies included in the
KLD database is not constant over time. Instead, the KLD database includes approximately 650
firms from 1991 to 2000, approximately 1,100 firms from 2001 and 2002 and approximately
3,100 firms from 2003 onwards. We included all available KLD data in our sample.
Financial Variables
We obtained financial performance data as well as control variables for as many of our
initial sample firms and years as possible using COMPUSTAT, our second data source. We
selected Tobin’s q as our financial performance measure because it is a market-based measure
which reflects the investors’ long-term expectation of the firm’s future earnings (Miller 2004). In
contrast to short-term marketing efforts, such as promotion, the financial benefits of CSR
activities might only manifest over time. For example, Cox et al. (2004) argue that improved
corporate social performance should lead to significant financial gains only in the long run.
Hence, compared to accounting-based financial performance measures such as return-on-asset
(ROA) or return-on-equity (ROE) which only capture short-term performance, Tobin’s q is a
more appropriate financial performance measure to understand the benefits as well as potential
costs of a firm’s social performance. We calculated Tobin’s q using the method proposed by
Chung and Pruitt (1994).
Further, Steenkamp and Fang (2011) suggest that it is important to control for firm size,
market share, and market concentration (i.e., Herfindahl-Hirschmann index; HHI) when studying
firm performance. Firm size might have a positive impact on market profitability (Boulding and
Staelin 1990), and we hence include the natural log of the number of employees (in million) in
32
our model. Likewise, market share might positively impact profitability (Szymanski et al. 1993),
and we thus include market share, which we calculated as the firm’s sales divided by the sales of
all firms in the firm’s industry (i.e., the same four-digit SIC code in COMPUSTAT), in our
model. Finally, we control for the degree of market concentration by including the normalized
HHI9 in the model. Large HHI values indicate a higher market concentration, and larger values
of HHI have been found to correlate positively with firm profitability (Lipczynski et al. 2005).
We retrieved the pertinent data to calculate the control variables from COMPUSTAT.
Our final sample, which is an unbalanced panel with time gaps, consists of approximately
4,500 firms, 25,000 data points, and data from 1991 to 2009. In addition, our sample firms are
publically traded firms from a wide range of industries. We present the descriptive statistics in
Table 2.2.
Table 2.2 Descriptive Statistics
Variables Mean Std. Dev. Min Max
Corporate Social Irresponsibility (CSI) 1.772 1.893 0 18
Corporate Social Responsibility (CSR) 1.468 2.043 0 22
Tobin’s q 1.669 1.999 0.030 148.802
Number of Employees (1,000s) 16.785 54.086 0.00 2100
Market Share 0.105 0.186 -0.295 1
HHI(Market Concentration Index) 0.212 0.188 0.014 1
The summary statistics are based on 4,539 firms. The statistics for CSR and CSI are based on data before
standardization.
Data Analysis Approach
We performed our analysis as follows: First, we tested for stationarity and unit roots.
Second, we estimated the dynamic panel GMM model using the Blundell and Bond estimator.
Third, we applied these estimators to each equation in the reduced-form panel VAR system and
9
where is the number of firms in the market, and ∑
where is the market share of firm .
33
recovered the contemporaneous effects based on the identification restrictions. Fourth, we
estimated the dynamics of the carryover effects (over time) using generalized impulse response
functions. Finally, we estimated the relative importance of the variables using generalized
forecast error variance decomposition (Pesaran and Shin 1998).
Stationarity in Time Series
To ensure that our analysis does not produce spurious results, we used the Augmented
Dickey-Fuller (ADF; Dickey and Fuller 1979) to examine stationarity and unit root for each time
series to determine whether the underlying data generation process of each variable is evolving
over time or is stationary (Granger and Newbold 1974; Hanssens et al. 2001). Since we have
unbalanced panel data with time gaps, the Im-Pesaran-Shin (2003) unit root test, which has been
widely used to test individual unit root processes in unbalanced panel data, cannot be used.
Hence, we used the ADF test to examine the null hypothesis of unit root. In addition, we tested
stationarity after first differencing as our model estimation is based on the first-difference.
Impulse Response Functions and Variance Decomposition
To examine the dynamic effect of one endogenous variable on another, we use impulse
response functions (IRFs). Generalized IRFs (Dekimpe and Hanssens 1999; Pesaran and Shin
1998) trace the effect that a one unit (e.g., one standard deviation) shock to one variable in the
system has on another variable over subsequent time periods while holding all other variables’
shocks equal to zero. We derived the generalized orthogonal IRFs by using the panel GMM
estimates and the covariance matrix of the equation residuals ( . Further, we used Monte Carlo
simulation to obtain upper and lower 95% confidence bands (see Doan 1992 for details). Finally,
we used the generalized forecast error variance decomposition (Pesaran and Shin 1998) to
34
examine the relative importance, i.e., effect size, of one variable in forecasting another (Grewal
et al. 2001).
2.5 Results
We present the results as follows: (1) unit root tests, (2) SPVAR estimates, (3) IRF
results, and (4) generalized forecast error variance decomposition estimates.
Stationarity and Unit Root Tests
As we show in Table 2.3, the null hypothesis of unit root is rejected for all three variables
of interest. Further, ADF test statistics of the first-differenced CSR, CSI and Tobin’s q variables
are -16.75, -16.09, and -15.28, respectively (p < .05); thus, our focal variables are difference
stationary.
Table 2.3 Summary of Unit Root and Stationarity Tests of the Variables
Variable Statistics P-value Conclusion
-16.089 0.000 Stationary
-16.747 0.000 Stationary
-15.281 0.000 Stationary
We use three lags in the ADF regression. The reported statistic is the inverse normal Z statistic. Choi’s
(2001) simulation results suggest that this statistic offers the best trade-off between size and power.
Model Estimation and Optimal Lags Selection
In the first step of our two-step estimation procedure, we estimated a reduced-form VAR
model (i.e., equation 2) using the Blundell and Bond estimator. We first determined the optimal
number of lags , where, consistent with research on dynamic panel data models (e.g., Huang et
al. 2008), we use the statistic (where stands for the order of autocorrelation) suggested by
Arellano and Bond (1991). The idea behind the statistics is that the residual from the dynamic
panel data model should be free of serial autocorrelation. Doornik et al. (2006) suggest that, if
the error term is not serially correlated, there would be significant and negative first order
35
serial correlation in the differenced residuals (i.e., ) and no significant second order
serial correlation. Thus, we examined the and statistic, and obtain the optimal number of
lags when the statistic is negative and statistically significant and the statistic is not
statistically significant. The last two rows of Table 2.5 illustrate the first and second order serial
autocorrelation results. In the equation in which CSR is the dependent variable, the statistic is
negative and statistically significant ( = -13.436) while the statistic is not significant at the
0.01 level ( = 2.339) when the number of lags specified is 3. Similarly, in the equation in
which CSI is the dependent variable, a three lags specification satisfies the criterion suggested by
Arellano and Bond (1991) ( = -15.567 and = 2.397). The three lags specification in the
equation in which Tobin’s q is the dependent variable is also sufficient to remove the serial
autocorrelation in the residual. Thus, the optimal lag length for our dynamic panel data model is
three.
In the second step of our two-step process, we estimated the contemporaneous effects
from the variance-covariance matrix of residuals from the reduced-form panel VAR model. The
results in Table 2.4 suggest that as the level of CSI increases, the level of CSR increases
( ); thus, it seems that firms engage in CSR activities reactively to cope with
their CSI activities. Further, the level of CSR has a positive impact on firm value (
) which suggests doing “good” leads to doing “well” immediately. The
contemporaneous effect of CSI on firm value is not statistically significant (
.
36
Table 2.4 Estimation Results of Contemporaneous Effects
Independent Dependent
CSI CSR Tobin’s q
CSI 1 0.23419(0.00954) 0.07487(0.01371)
CSR 0 1 0.16147(0.01843)
Tobin’s q 0 0 1
Standard errors are reported in parentheses. They are calculated based on 1,000 bootstrap samples.
We present the estimation results from the reduced-form panel VAR model with a three
lags specification in Table 2.5. We first discuss the results for the control variables. As can be
seen in Table 2.5, firm size (i.e., number of employees) does not have a significant effect on CSR.
This result is analogous to Kotchen and Moon (2012)’s finding. However, firm size does have a
positive effect on CSI ( = 0.597). Further, market concentration does not play a
significant role in forecasting CSR, CSI, and Tobin’s q after controlling for other variables.
Finally, market share has a positive impact on CSR ( = 0.3944) and CSI ( = 0.4578).
It is difficult to understand the effect of one endogenous variable on another variable by
merely looking at the estimates in Table 2.5. For example, the second column of Table 2.5 shows
the estimation result when the dependent variable is CSI. All lagged CSR variables are
significant. However, the coefficients of and are negative whereas the coefficient
of is positive. In short, to understand the dynamic effect of the lagged independent
variables on the dependent variable, we need to investigate the IRFs.
37
Table 2.5 Estimation Results from the Reduced-form Panel VAR Model
Independent Dependent
CSI(t) CSR(t) Tobin’s q(t)
CSI(t-1) .6386*** -.0287* .0275
CSI(t-2) .0415*** .0169 .0153
CSI(t-3) -.0035 -.0127 -.0339*
CSR(t-1) -.0611*** .7676*** -.0568**
CSR(t-2) .0799*** .0406*** .0428*
CSR(t-3) -.0371** -.0051 -.0671**
Tobin’s q(t-1) -.0018 -.0120 .6731***
Tobin’s q(t-2) .0033 .0203** .0118
Tobin’s q(t-3) .0137** .0096 .0939*
Log(Emp) .0597*** .0273 .0959
HHI .1964* .1902* .9495*
Market Share .4578** .3944** .4944
AB Test (m1) -15.567*** -13.436*** -5.4425***
AB Test (m2) 2.3971** (p-value:
0.0165)
2.3393** (p-value:
0.0193)
-.62535
***, **, and * represent 1%, 5%, and 10% significance level, respectively
Impulse Response Functions
As we are interested in testing the four mechanisms, i.e., whether and how doing “good”
and doing “well” converge, we focus on the relationship between CSR and CSI and the
relationship between CSR and financial performance for generating IRFs. In Figure 2.4, we
present the graphs of the IRFs for these two relationships along with the 95% confidence bands
generated by the Monte Carlo simulation. Panel A in Figure 2.4 shows the relationship between
CSR and financial performance, where Graph 1 of Panel A shows the response of financial
performance to a CSR shock. In support of the good management mechanism, Graph 1 shows
that CSR influences financial performance positively in the short run (0.07) and this positive
effect fades away after about a year. Graph 2 shows that a shock to Tobin’s q does not seem to
38
have any impact on CSR as the 95% confidence band always contains zero. Hence, the slack
resource mechanism is not supported by our results.
Panel B in Figure 2.4 depicts the relationship between CSR and CSI. As Graph 1 in Panel
B shows, CSR has a negative impact on CSI in the short run (-0.026), and this negative impact
wears out after about 2 years. Thus, the insurance mechanism which argues that CSR antecedes
CSI in a positive manner is not supported. In contrast, in support of the penance mechanism,
Graph 2 in Panel B shows that there is a large and positive impact of CSI on CSR that lasts for
about 4 years.
Figure 2.4 Impulse Response Functions
Panel A: Impulse Response Functions for the Dynamic Relationship between CSR and Financial
Performance
39
Panel B: Impulse Response Functions for the Dynamic Relationship between CSR and CSI
The graphs show the 2.5% and 97.5% confidence band (dashed line) on either side of the
response function (solid line).
Figure 2.5 Forecast Error Variance Decomposition Results after 5 Years
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
CSI after 5 years CSR after 5 years Tobin's q after 5
years
Per
cen
tage o
f V
ari
an
ce
Tobin's q
CSR
CSI
40
Table 2.6 Forecast Error Variance Decomposition Results after 5 Years
Independent Dependent
CSI(t+5) CSR(t+5) Tobin’s q(t+5)
CSI 99.75% 6.16% 0.75%
CSR 0.17% 93.69% 0.53%
Tobin’s q 0.08% 0.15% 98.72%
Forecast Error Variance Decomposition
To assess the relative importance of one variable when forecasting the other variable, we
use forecast error variance decomposition. We present these decompositions for a five year
period in Table 2.6 and Figure 2.5, which show that CSI is mainly explained by its lag values
(99.75%) with CSR and financial performance jointly explaining only 0.25% of the forecast error
variance in CSI. In contrast, CSR is explained by its lag values (93.69%) and CSI (6.16%) but
Tobin’s q explains only 0.15% of CSR. Finally, as would be expected, past Tobin’s q explains
most variance in current Tobin’s q (98.72%) with CSR accounting for 0.53% and CSI for 0.75%
of variance.
2.6 Discussion
Various mechanisms of how CSR and positive firm performance converge have been
proposed in the literature. Some scholars argue that CSR results in positive firm performance and
that it is thus a manifestation of the firm’s good management (e.g. Freeman 1984; Hull and
Rothenberg 2008). Others, however, argue that a firm’s slack resources result in CSR; i.e., these
scholars argue that CSR does not impact financial performance but that financial performance
leads to CSR (e.g., McGuire et al. 1988). More recently, scholars have posited that CSR acts as a
form of penance and can at least partially offset CSI (e.g., Kotchen and Moon 2012). In contrast,
scholars also posit that CSR provides an insurance mechanism against CSI (i.e., CSR antecedes
CSI temporally) (e.g., Peloza 2006; Minor and Morgan 2011). While these four mechanisms are
41
not mutually exclusive, the good management and slack resources as well as penance and
insurance mechanisms do propose reverse causal paths. The primary goal of our study is to
unravel these four mechanisms and identify (1) whether and (2) how firm performance and CSR
converge.
Implications
We believe that our contributions to the extant CSR literature are on five dimensions:
First, the literature on why firms engage in CSR is quite scattered. We summarize the varying
propositions and integrate the same into four mechanisms. More importantly, we test these four
mechanisms simultaneously. Extant literature examines only one or at best two mechanisms
simultaneously; such an approach, however, is cumbersome as it does not permit addressing
concomitant effects among the four mechanisms resulting in either a partial picture or even false
statistical findings.
Second, we separate CSI from CSR, and we also integrate the CSI construct into the
overall “CSR-CSI-financial performance” framework, which is also new in the literature.
Separating CSI from the CSR construct is meaningful because failure to do so can effectively
cancel out important granularities in the data. We note that many past studies have simply
averaged a firm’s CSR and CSI scores into one overall CSR score. Moreover, separating CSI
from CSR is critical to shed light on the question of how CSR and financial performance
converge. Using comprehensive data, we show that one reason of why firms engage in CSR
seems to be that they use it to offset past CSI, i.e., that the penance mechanism is at play.
Third, our economic theory model provides a theoretical basis for the development of
empirical models that seek to examine the dynamic relationship among CSR, CSI, and financial
performance. The model also provides the basis for the link between organizational efforts and
42
the level of CSR and CSI that researchers typically empirically study. We believe that our
economic theory model, which is based on theory of the firm primitives, would provide bases for
future theoretical and empirical research.
Fourth, we provide empirical evidence that CSR has a positive impact on firm
performance. Although this finding is documented in the extant literature (e.g., Margolis et al.
2007), we augment the extant literature in two important directions. First, we model the four
mechanisms simultaneously thus allowing for the possibility of finding evidence for each of the
mechanism and correcting for the possibility of any statistical simultaneity bias. Second, we use
the SPVAR model for a large number of firms (around 4500) over a period of 19 years; thus the
SPVAR specification enables us to control for unobserved heterogeneity (through fixed effects)
and correct for endogeneity (using an adapted Blundell and Bond estimator), in addition to
modeling simultaneity; further, the large data set provides confidence in the findings. Thus, we
do establish causality for the influence of CSR on firm performance (as assessed by Tobin’s q).
In the process, we provide fodder for Margolis et al.’s (2007, p. 4) assertion that “if only doing
“good” could be connected to doing “well”, then companies might be persuaded to act more
conscientiously.”
Fifth, we provide support for the penance mechanism such that firms have a tendency to
invest in CSR after CSI has occurred. Thus, CSR might also have more subtle and covert
performance implications not captured by the positive direct link between CSR and firm
performance; CSR seems to attenuate negative effects stemming from CSI. Our secondary data,
of course, does not allow us to say for certain that firms in fact use CSR to offset previous CSI.
However, the fact that CSI is a strong driver of CSR provides at least some face validity for the
43
notion (i.e., penance mechanism). It also sheds light on the direction of causality behind the
relatively large correlation between CSR and CSI shown in Figure 2.3.10
Limitations and Further Research
While we believe that we have broken some new ground with this research, there are
clear limitations, some of which might provide fruitful avenues for future research. For example,
a potential limitation that we must acknowledge is the CSR and CSI data that we employ.
Although the KLD data has been used extensively in extant research, the CSR and CSI measures
are based on somewhat subjective rather than objective evaluations. Future research should try to
replicate our findings using different CSR and CSI data. Unfortunately, as we write this, we are
not aware of a source that could provide such data (other than KLD, of course).
Further, although we believe that the identification restrictions we imposed to estimate
the SPVAR model are sensible, we need to acknowledge that our results are sensitive to them
(e.g., Canova et al. 1993; Uhlig 2005). We note that we conducted a survey among 31 US-based
senior executives to validate our identification restrictions. The survey results provided strong
support for our assumptions. For example, to support our argument that firm value does not have
a contemporaneous effect on CSR, we asked the executives how often they change their CSR
strategy. 87.5% of the respondents reported that they change their CSR strategy “annually” or
even less frequent, and that short-term firm value does not affect their firm’s CSR.
Conclusion
Scholars have scrutinized the conception that companies do “well” by doing “good” for
many years (e.g., McWilliams et al. 2006). However, the debate on whether and how doing
10 Our data also provides evidence that firms do not tend to use CSR to insure against CSI (i.e., insurance
mechanism). Otherwise, we should see in our data that CSR positively drives CSI, which we do not. In fact, our data
suggests that past CSR has a slight negative impact on current CSI, which seems sensible. We note, however, that
this non-finding does not suggest that the insurance mechanism would not work. It simply suggests that few firms
make use of it.
44
“good” and doing “well” converge has yet to be resolved (e.g., Mackey et al. 2007). In this study,
we provide strong evidence that CSR has a positive effect on firm performance, and we also
show that firms tend to increase their CSR after CSI has occurred. We believe that these findings
are a significant contribution to the extant CSR literature.
45
Chapter 3
Portfolio Management in Sustainability Strategy and Firm Performance
ABSTRACT
Firms can engage in various Corporate Social Responsibility (CSR) practices, including
charitable giving, environmental protection, and employee empowerment, among others.
Moreover, firms can also direct their attention to avoiding Corporate Social Irresponsibility
(CSI), such as accounting irregularities, investment controversies, and health and safety
concerns. Yet, evidence suggests that many firms struggle to decide which CSR and CSI
avoidance practice(s) they should engage in, partially because there are so many different
options. Against this backdrop, we argue that a firm’s CSR and CSI avoidance practices can be
viewed akin to financial investment portfolios, and, borrowing from portfolio theory, develop
hypotheses on how firms should manage their CSR and CSI portfolios. We test our hypotheses
using panel data from over 3,000 firms across 11 years (2001 – 2011) and employ a dynamic
panel data model that controls for unobserved heterogeneity and endogeneity. Our findings
suggest that firms should strive to engage evenly in CSR practices across several societal issue
areas rather than heavily engage in multiple CSR practices in a few societal issue areas. Further,
firms should avoid CSI whenever they can. However, if that is not possible, firms should focus
on minimizing business- related (as opposed to philanthropic-related) CSI practices.
46
3.1 Introduction
Recent changes in the business environment have increased calls for firms to expand their
responsibilities and to use firms’ resources to alleviate a wide variety of social and
environmental problems (Hillman and Keim 2001). These calls are in line with sustainability,11
which is an approach firms are increasingly adopting to conduct business to deliver not only
economic benefits but also social and environmental benefits worldwide (Elkington 1998). The
sustainability movement is gaining momentum as firms try to build better relationships with
stakeholders such as employees, customers, community residents, and non-profit organizations
(NGO), because firms have realized that better relationships with stakeholders lead to increased
shareholder values (Hillman and Keim 2001; Freeman 1984). Responding to this shift of
momentum, the topic of sustainability has drawn particular attention from academic researchers
in business and related fields (e.g., Brown and Dacin 1997; Banerjee, Iyer, and Kashyap 2003;
Chabowski, Mena, and Gonzalez-Padron 2011; Hombug, Stierl, and Bornemann 2013).
Due to the strategic importance of sustainability in business, sustainability now reaches to
C-Suite: Chief Sustainability Officer (CSO). The title of CSO started to appear around 9 years
ago in the US and is increasingly being adopted globally (Acre 2011). According to the article by
Forbes (2011), 29 publically traded firms such as Coca Cola, AT&T, DuPont, and Kellogg have
appointed CSOs. The CSOs, along with other sustainability executives, typically focus on two
strategic functions: (1) they explore business opportunities from sustainability practices that will
increase shareholder values, and (2) they review firms’ management and monitor their impacts
and risks to firm reputation, ultimately, firm profitability (Acre 2011). These roles of CSOs are
challenging and complex for several reasons. First, the number of sustainability practices
11
We define sustainability as a business approach that creates long-term shareholder value by enhancing strengths
(i.e., engaging in corporate social responsibility (CSR) practices) and reducing concerns (i.e., minimizing corporate
social irresponsibility (CSI) practices) that derive from economic, environmental and social developments.
47
increases and their priorities are changing because the policy, consumer awareness and needs,
and firm’s strategic direction change. For example, Greg Morris, head of environment at
Newcrest Mining, stated that “The environmental skill set changes. In the beginning, you had to
know how to grow trees and plant grass. Then you had to know how to manage waste, water, and
other impacts. Now you have to know how to translate the issues and ideas into workable
solutions in a broader policy context.” Second, it is hard to identify each sustainability practice’s
strategic priority due to the difficulty in quantifying intangible effects and predicting customer
responses. According to the 2012 Sustainability & Innovation Global Executives Study, 37% of
survey respondents identified that the most significant obstacles to evaluating the business case
for sustainability-related strategies is competing priorities (Kiron et al. 2012). In addition,
according to The Sustainability Executives: Profile and Progress report, sustainability
executives responded that ‘choice, paring, and specialization’ is one of the specific challenges
ahead (PwC 2012). Specifically, sustainability executives wanted answers to the questions such
as “We can’t do everything, so how do we prioritize our efforts?” and “What adds value?” Third,
sustainability practices not only have to compete among themselves but also with other critical
marketing instruments such as advertising and research and development (R&D) because of
limited resources (Friedman 1970; Luo and Bhattacharya 2009). In sum, although firm’s
sustainability practice engagement management has become one of the critical strategic issues,
there has been scarce guideline for managing a wide range of sustainability practices.
In the similar vein, extant research has not provided holistic view of sustainability
practice engagement management. Rather, most extant studies either focus on only one societal
issue area (e.g., Klassen and McLaughlin 1996; Lichtenstein, Drumwright, and Braig 2004;
Robinson, Irmak, and Jayachandran 2012) or look at the global sustainability performance (e.g.,
48
Brown and Dacin 1997; Wagner, Lutz, and Weitz 2009; Luo and Bhattacharya 2009). For
example, Klassen and McLaughlin (1996) focus on environmental management, and investigate
the effect of environmental strength and concern on financial performance. Luo and
Bhattacharya (2009) investigate the relationship between firm-idiosyncratic risk and corporate
social performance (CSP) which refers to “a company’s overall performance in these diverse
corporate prosocial programs” (p. 201). However, these studies failed to consider the
interdependence in returns and risks from diverse sustainability practices. For instance, engaging
in multiple practices (e.g., pollution prevention, recycling, using clean energy) in environment
area may increase consumers’ awareness on firm’s green image and provide higher returns than
engaging in one practices in three different societal issue areas (e.g., environment – recycling,
employee relations – no-layoff policy, community – charitable giving). In addition, previous
research has shown that each CSR practice has distinct benefit mechanism depending on whether
the practice targets primary or secondary stakeholders (Homburg, Stierl, and Bornemann 2013).
Hence, they argue that expressive customer outcomes from different sustainability practices vary.
In short, researchers have neglected the interdependence and synergy effect among a wide
variety of sustainability practices and previous research has not been able to shed lights on the
effective sustainability practice management. Indeed, Chabowski, Mena, and Gonzalez-Padron
(2011) argue that “the influence of multiple sustainability-focused marketing assets on financial
returns” has not been examined thoroughly (p.66).
To answer these calls, the purpose of this paper is to provide insights into effective
strategies to manage a wide variety of sustainability practices. Specifically, building on financial
portfolio theory (Markowitz 1952), we propose three portfolio descriptors which capture the
characteristics of a firm’s sustainability practice engagement: breadth, depth and the ratio of
49
philanthropic/business-related practices. We posit that the effective sustainability practice
engagement decisions can be made in the similar manner to find optimal composition of assets in
financial portfolio for several reasons. First, both involve the choice decisions among diverse
sustainability practices and financial assets (Hillman and Keim 2001). Second, like financial
assets, sustainability practices create returns such as consumer loyalty and high purchase
intentions through psychological processes and these returns are interdependent (e.g., Du,
Bhattacharya, and Sen 2007; Sen, Bhattacharya, and Korschun 2006). Third, similar to financial
assets’ risks, sustainability practices also have inherent risks such as high operating costs and
green product failure.
Further, building on stakeholder theory, we hypothesize and test the relationship between
three portfolio descriptors and firm performance. First, we argue that the breadth of CSR
practices increases firm performance whereas the breadth of CSI practices decreases firm
performance. We also predict that the depth of CSR practices mitigates the positive effect of
CSR breadth on firm performance. In addition, with respect to the negative effect of CSI breadth,
we argue that this negative effect is less profound when the ratio of philanthropic vs. business-
related CSI practices is high. Lastly, we predict that the depth of CSI practices mitigates the
positive moderating effect of the ratio of philanthropic vs. business-related CSI practices on the
negative link of the breadth of CSI – firm performance. In our analysis, we combine the KLD
Social Rating Database, which provides annual snapshot of firm’s sustainability practices in
seven societal issue areas, with financial performance data from COMPUSTAT over the period
2001-2011. We employ dynamic panel data analysis which controls for unobserved
heterogeneity and endogeneity issues to test our hypotheses in rigorous way. In CSR practices,
although we do not find positive effect of the breadth of CSR on firm performance, we find a
50
mitigation effect of the depth of CSR on the link of the breadth of CSR – firm performance. In
CSI practices, we find that the breadth of CSI negatively impacts firm performance while its
effect is positively moderated by the ratio of philanthropic vs. business-related CSI practices.
Moreover, we find negative three-way interaction among breadth, depth, and philanthropic vs.
business-related practice ratio for CSI. In short, we find that three sustainability practice
portfolio descriptors, i.e., breadth, depth, and philanthropic vs. business-related practice ratio,
can effectively predict firm performance and the interactions among them are critical.
We seek to make several important contributions to both academia and practitioners. First,
we advance research on CSR by adapting a portfolio prospective which enables us to capture the
interdependence and synergy among a wide variety of sustainability practices. We propose three
simple sustainability practice engagement portfolio descriptors and provide holistic view of the
relationship between sustainability practice engagement and firm performance. Second, while
most CSR and sustainability research has extensively conceptualized CSR globally or looked at
only one societal area of CSR (e.g., Klassen and McLaughlin 1996; Brown and Dacin 1997;
Lichtenstein, Drumwright, and Braig 2004; Wagner, Lutz, and Weitz 2009), we distinguish
sustainability into positive practices (i.e., CSR) and negative practices (i.e., CSI), and further into
business-related practices and philanthropic-related practices. We extend CSR and sustainability
research by examining the link between specific types of sustainability practices and financial
outcome. Third, we contribute to the marketing-finance interface literatures by investigating the
impact of sustainability practice portfolio on stock market-based long term measure of a firm
value. Further, we provide insights into the debate on the role of CSR in firm performance. We
suggest that not only the breadth but also the depth and philanthropic vs. business-related
practice ratio should be considered. Finally, we provide managerial guidelines for the effective
51
sustainability practice engagement management under the condition of limited resources. Based
on our findings, we propose two simple rules: (1) be the generalist in CSR practices, and (2)
minimize business-related CSI practices first, but don’t let the philanthropic-related CSI
practices stand out.
The remainder of this article is organized as follows: in the following section, we provide
an overview of sustainability, stakeholder theory, and financial portfolio theory. Based on the
overview, we propose three descriptors of firm’s sustainability practice engagement portfolio.
Then, we predict the relationship between these sustainability practice portfolio descriptors and
firm performance. Next, we test our hypotheses empirically while describing our data, variable
operationalization, and modeling issues. We conclude with a discussion of our findings, and
outline the implications of our research as well as the limitation of the current study.
3.2 Conceptual Background
In this section, we first provide a theoretical background of stakeholder theory and
portfolio theory relating to CSR/CSI practices. Based on portfolio theory and stakeholder theory,
we propose three sustainability practice engagement portfolio descriptors –portfolio breadth,
portfolio depth, and the ratio of philanthropic/business-related sustainability practices. Then, for
each of CSR/CSI practice, we discuss the role of these descriptors on firm performance.
CSR, CSI, and Stakeholder Theory
Sustainability can be achieved in two ways: (1) by engaging in more socially responsible
practices, and (2) by minimizing societal misbehaviors. These two ways correspond to corporate
social responsibility (CSR) and corporate social irresponsibility (CSI), respectively. CSR refers
to firm’s pro-social practices, ranging from corporate governance and green marketing to any
activities that advance social welfare beyond that which is required by law (McWilliams and
52
Siegel 2001; Luo and Bhattacharya 2009). In contrast, CSI refers to corporate anti-social
behaviors, ranging from tax disputes and labor right concern to any practices that appear to hurt
the social goods (Kotchen and Moon 2012).
While various theoretical bases such as the resource-based view (Barney 1986; McGuire
et al. 1988) , risk management theory (Godfrey 2005), and institutional theory (Handelman and
Arnold 1999), have been applied to understand the effect of firm’s sustainability practices to firm
performance, we primarily use stakeholder theory (Freeman 1984) in our research because our
research focuses on investigating the link between sustainability practice engagement and firm
performance outcome, operationalized as Tobin’s q. Stakeholder theory provides an appropriate
explanation for the linkage between stakeholder-directed activities and firm performance
(Donaldson and Preston 1995; Freeman 1984). Specifically, stakeholder theory argues that
stakeholder-directed activities such as firm’s CSR practices should create benefits to
shareholders which, in turn, should enhance firm performance (Bhattacharya, Korschun, and Sen
2009; Jones 1995). Moreover, Homburg et al. (2013) illustrate that different CSR practices have
different impacts on consumers’ mindset, and further, organizational customer outcomes in B2B
context. In fact, stakeholder theory proposes that the benefits from stakeholder-directed activities
are different from one stakeholder groups to another depending on stakeholders’ interests. For
example, primary stakeholders, who engage in market exchange with a firm, such as employees
would value a firm’s CSR practices such as no-layoff policy and employee involvement. In
contrasts, secondary stakeholders, who influence or are influenced by a firm’s behavior but are
not engaged in direct market exchange, such as the community would be more interested in
secondary stakeholder-directed practices such as charitable giving and a firm’s volunteer
programs. Similarly, primary stakeholders may not concern deeply about criticism by NGOs
53
which is one of CSI practices in community area,12
while primary stakeholders concern such as
workplace health and safety program may not be a critical problem to secondary stakeholders.
Since we argue that, depending on the target stakeholder group, CSR/CSI practices may have
different impacts on firm performance, we rely on stakeholder theory.
Portfolio Theory
Financial portfolio theory describes the effective way to construct investment portfolio
that balances the cash flow opportunities (return) and the cash flow vulnerability (risk) by
diversification on stocks and bonds (Markowitz 1952). The key tenet of financial portfolio theory
is to compose portfolio with various stocks and bonds, each of which has low total correlation
with the total return. By doing so, investors can still enjoy positive cash flow opportunities while
smooth out negative cash flow vulnerability from unanticipated environmental and economic
changes because diversified stocks act differently to these market changes.
Financial portfolio theory has been applied in several other business domains including
marketing. For example, Tarasi et al. (2011) adopt portfolio theory in customer management and
demonstrated that the efficient customer portfolio consistently yields low risk. Bordley (2003)
uses portfolio theory in the context of a firm’s product portfolio. Grewal et al. (2008) illustrate
the relationship between new product development portfolio and firm performance in the
pharmaceutical industry. Sridhar et al. (2014) investigate manager’s advertising investments
decision through the lens of portfolio theory. In many marketing applications, researchers have
looked at the number of portfolio components (e.g., new products, media outlets) and variability
among portfolio components which represent the degree of diversification in portfolio (e.g.,
Bordley 2003; Grewal et al. 2008).
12
For example, SodaStream has been criticized by Oxfam for its operations in the occupied West Bank. However,
SodaStream’ Palestinian employees who work at the factory said that they are just trying to make a living regardless
of the political issue and they just wanted to work and live (International Business Times 2014).
54
Sustainability Portfolio Strategy
In this section, we argue that top management’s (e.g., CSO) strategic decision to engage
in certain sustainability practices resembles investor’s financial portfolio decision. According to
the report from Acre (2011), the major role of CSO is to explore sustainability practices that
should make a significant difference to shareholder value, and at the same time, to manage the
impacts and risks of sustainability-related concerns (i.e., CSI). This strategic decision by CSO is
similar to investor’s financial portfolio decision with respect to (1) choices of assets, (2) returns,
and (3) risks.
First, similar to the financial portfolio decision which involves choice of various types of
stocks and bonds, sustainability practice engagement management decision involves choices of
sustainability practices within and among various societal issue areas such as corporate
governance, environment, and community. Indeed, recent changes in the business environment
have increased calls for firms to expand their responsibilities and to use their resources to
alleviate a wide variety of social and environmental problems (Hillman and Keim 2001). For
example, traditionally, firms have dealt with sustainability issues such as employee safety in
employee relations area (e.g., Buehler and Shetty 1974; Foote 1984), product safety in product
area (e.g., Siomkos 1999; Chen, Ganesan and Liu 2009), and pollution reduction in environment
area (e.g., Nehrt 1998). In addition to these sustainability practices, as consumers’ awareness on
environmental issues has been growing and firms recognition on the importance on
environmental practices as the sources for future corporate competitiveness (Nidumolu, Prahalda,
and Rangaswami 2009; Sharma, Mehrotra, and Krishnan 2010), firms are now engaging in more
and more environmental practices such as preventing water depletion, recycling, and building
sustainable management systems. Moreover, firms’ efforts to reach out community and the
55
emergence of cause-related marketing (e.g., Arora and Henderson 2007; Krishna and Rajan 2009)
added another dimension of sustainability practices. Overall, as shown in Table 2.1, our KLD
database covers approximately 80 sustainability practices. In addition, these sustainability
practices differ in their implementing costs and expected benefits or returns, as we describes in
next paragraph.
Second, like assets in financial portfolio, sustainability practices generate the returns and
they are interdependent. Previous research has shown that firm’s sustainability practice
engagements create the returns. For example, it has been shown that sustainability practice
engagements have positive influence on psychological outcomes such as trust (e.g., Homburg,
Stierl, and Bornemann 2013; Vlachos et al. 2009), customer satisfaction (e.g., Luo and
Bhattacharya 2009), attitude toward the company (e.g., Brown and Dacin 1997), customer-
company identification (e.g., Lichtenstein, Drumwright, and Braig 2004), and resistance to
negative company information (e.g., Klein and Dawar 2004). Further, these engagements result
in behavioral outcomes such as increase in consumer loyalty (e.g., Du, Bhattacharya, and Sen
2007; Maignan, Ferrell, and Hult 1999), higher purchase intention (e.g., Sen, Bhattacharya, and
Korschun 2006), and higher willingness to pay (e.g., Auger et al. 2003). In addition, the returns
of sustainability practices are interdependent. In other words, engaging in one CSR practices can
affect the returns from the other CSR/CSI practices. For instance, Klein and Dawar (2004) found
that CSR mitigate the negative consumer responses to the product harm crisis. Similarly, if the
firm has bad sustainability reputation in general while well in one or two practices, the returns
from the CSR practices for this firm may be lower than the level of the returns for the firm
whose sustainability reputation is good.
56
Third, sustainability practices are inherently risky as assets in financial portfolio. The risk
is characterized by the uncertainty in the returns of the practices. For example, although firms
have gone through intensive market research and R&D process, firms’ practices to develop and
sell green products can go wrong. According to the article by Clifford and Martin (2011), Green
Works, which is Clorox’s environmental-friendly cleaning line, experienced sharp sales decrease
in 2009 not because of the product failure but because of the recession and price-conscious
customers. In addition, although firms invest huge amount of money in sustainability practices
which target secondary stakeholders such as community and third-parties,13
the returns from
these sustainability practices are hard to be measured and it takes time to understand the realized
returns. According to the 2012 Sustainability & Innovation Global Executive Study, 22% of
executives and managers said there are no revenues from sustainability for our company, and 14%
of them said sustainability is pure philanthropic investments which subtract profits (Kiron et al.
2012). Also, accidental events such as Deep Water Horizon Oil Spill by British Petroleum (BP)
in 2010 can increase the vulnerability in the returns of other sustainability practices.
In sum, given the similarity of sustainability practice engagement decision to financial
portfolio decisions in terms of assets, returns, and risks, we argue that portfolio theory principles
can be applied to the decision of developing effective sustainability practice engagement
management.
Constructs
Before delving into our hypotheses, we propose three constructs that capture the structure
of sustainability practice portfolio, namely CSR/CSI breadth (number of engaged practices),
CSR/CSI depth (variation in engaged practices among different societal areas), and the ratio of
13
For example, Johnson & Johnson spent 588.1, 603.3, and 706.1 million dollars on charitable giving in 2009, 2010,
and 2011, respectively, which account for 3.7%, 3.6%, and 5.7% of each year’s pretax income.
57
philanthropic vs. business-related CSR/CSI practices (focus on philanthropic-related practices
compared to business-related practices). Compared to assets in financial portfolio, the challenge
in assessing sustainability practice portfolio stems from the fact that there are no objective
measures of the potential returns and risks from sustainability practices. Thus, we rely on simple
portfolio descriptors which have been frequently used in empirical works (e.g., Bordely 2003;
Grewal et al. 2008; Wassmer 2010; Sridhar et al. 2014).
First, Portfolio Breadth refers to the number of engaged CSR/CSI practices by a firm in a
given year. The greater the number of engaged CSR/CSI practices, the broader is a firm’s
CSR/CSI portfolio breadth. Specifically, if a firm’s CSR portfolio breadth is broad, this firm
engages in diverse range of sustainability practices. In contrast, if a firm’s CSI portfolio breadth
is broad, this means that a firm does harm to social welfare. In short, this construct represents the
size of the portfolio in the sustainability practice engagement. Second, Portfolio Depth refers to
the variance in strategic engagement in the sustainability practices. This captures the extent of
concentration on a few societal issue areas (e.g., environment) compared to other areas (e.g.,
corporate governance, community, and so on) in terms of engaged CSR/CSI practices. The
greater the concentration on a few societal areas over other areas, the deeper is a firm’s CSR/CSI
portfolio depth. In details, if a firm’s CSR portfolio depth is deep, this firm put more emphasis
on selected societal issue areas than other areas. CSI portfolio depth is deep if a firm fails to
comply with sustainability issues in a few societal issue areas while it meets sustainability
requirements in other areas. Third, we define the ratio of philanthropic vs. business-related
CSR/CSI practices as the extent to which strategic engagement varies across philanthropic-
related CSR/CSI practices over business-related CSR/CSI practices. Following Hombug, Stierl,
and Bornemann’s approach (2013), we distinguish firms’ CSR/CSI practices into two parts:
58
philanthropic-related practices and business-related practices. We define philanthropic-related
CSR/CSI practices as CSR/CSI practices which involve philanthropic obligations to secondary
stakeholders such as the community and non-profit organizations (Carroll 1991; Peloza and
Shang 2011). In contrast, we refer to CSR/CSI practices which target at primary stakeholders as
business-related CSR/CSI practices. These business-related CSR/CSI practices are related to the
societal and ethical obligations of the firm (Carroll and Shabana 2010; Carroll 1991). Hence, the
less emphasis on philanthropic obligations relative to societal and ethical obligations, the smaller
is the ratio of philanthropic vs. business-related practices.
Hypothesis
We develop hypotheses on the relationship between the descriptors of sustainability
practice engagement portfolio and firm performance. In essence, our theoretical framework
predicts (1) the impact of the CSR/CSI breadth on firm performance, and (2) the moderating
roles of the CSR/CSI depth and the ratio of philanthropic vs. business-related CSR/CSI practices
on the relationship between the CSR/CSI breadth and firm performance.
In essence, we expect that broad range of CSR practice engagement should lead to a
positive firm performance while broad range of CSI practice engagement should result in
negative firm performance. We also expect that the depth of CSR practices play a negative
moderating role on the (positive) effect of the breadth of CSR practices on firm performance,
whereas we assume that the ratio of philanthropic vs. business CSI practices mitigates the
negative impact of the breadth of CSI practices on firm performance. Finally, we expect that the
mitigating role of the ratio of CSI practices on the effect of the breadth of CSI practices on firm
performance becomes less prominent when the depth of CSI practices increases. The overview of
hypotheses is shown in Figure 3.1.
59
Figure 3.1 Conceptual Framework
Role of the breadth of CSR/CSI practices
We first focus on the link between the breadth of CSR/CSI practices and firm
performance. With respect to CSR practices breadth, the link between good sustainable moves
and firm performance has been widely studied (e.g., Brown and Dacin 1997; McWilliams et al.
2006; Margolis et al. 2007). Roughly speaking, 50% of empirical studies on this link have found
a positive relationship. For example, researchers have found that CSR delivers benefits to the
firm through quality employees attraction and retention (e.g., Greening and Turban 2000), cost
reduction form increased operation efficiencies (e.g., Hart and Ahuja 1996), customer
satisfaction and loyalty (e.g., Du, Bhattacharya, and Sen 2007), customer-company identification
(e.g., Lichtenstein, Drumwright, and Braig 2004), trust (e.g., Vlachos et al. 2009), and favorable
purchase intention (e.g., Du, Bhattacharya, and Sen 2007). In addition, researchers have argued
that CSR may create “good will” which works as protection mechanism against firm reputation
crisis (e.g., Klein and Dawar 2004; Godfrey 2005). For example, Klein and Dawar (2004)
provide empirical support that CSR provides resistance to negative company information. In the
Depth of CSR Practices H3(-)
CSR Phil/Biz Ratio
Control Variables
Breadth of CSR Practices
Firm Performance
Breadth of CSI Practices
H1 (+)
H2 (-)
Depth of CSI Practices
CSI Phil/Biz Ratio H4(+)
H5 (-)
60
similar vein, Luo and Bhattacharya (2009) argue that higher corporate social performance lowers
firm-idiosyncratic risk with all else (i.e., advertising spending and R&D spending) being equal.
Hence, we suggest that the link between the breadth of CSR practices and firm performance is
positive.
Regarding the breadth of CSI practices, we postulate that the more a firm engages in CSI
practices, the lower is firm performance. By not pursuing sustainability, firms may experience
substantial direct/indirect losses and high volatility. For example, vast literature on product
recall has been documented negative abnormal return due to the product safety issue. Chu, Lin
and Prather (2005) found that the recall announcement induces significant negative abnormal
return especially in drugs/cosmetics industry. Similarly, Thomsen and McKenzie (2001) found
significant shareholder losses from food companies when a recall is involved in serious food
safety hazards. In addition, engaging in CSI practices may incur penalties and fines. For instance,
British Petroleum (BP) paid 4.5 billion dollars in government penalties due to the Deepwater
Horizon Oil Spill in 2010, which caused harm to the environment around the Gulf of Mexico
(Isidore, Riley, and Frieden 2012). This incident also induced loss of sales at BP gas stations by
as much as 40% (Rudolf 2010). Furthermore, engaging in CSI practices such as child labor
issues may negatively affect firm reputation and potential customer loss because consumers
believe that firms need to meet not only business obligations but also societal and ethical
obligations. Thus, we posit that the link between the breadth of CSI practice and firm
performance is negative.
H1: The breadth of firm’s CSR practices is positively related to firm performance.
H2: The breadth of firm’s CSI practices is negatively related to firm performance.
Moderating role of CSR depth on the CSR breadth-firm performance link
61
We expect that the strength of the effects of the breadth of CSR on firm performance is
context dependent. In particular, we posit that an increase in the depth of CSR leads to weaker
link of the CSR breadth and firm performance. In other words, if a firm concentrates a few
sustainability societal issue areas and shallow in other areas, its performance would be lower
than balanced CSR practice engagement approach across multiple societal issue areas.
The effectiveness of the CSR breadth on firm performance should decrease as the depth
of CSR practices increases for three reasons. First, focusing on a few societal issue areas may
results in unsuccessful appeal to certain stakeholder groups. For example, Homburg, Stierl, and
Bornemann (2013) distinguish CSR engagement into two facets, business practice CSR
engagement which targets at primary stakeholders and philanthropic CSR engagement which
targets at secondary stakeholder based on stakeholder theory (Freeman 1984). They further argue
that different CSR engagements facilitate different psychological outcomes. Business practice
CSR engagement increases consumer trust, while philanthropic CSR engagement induces
customer-company identification. Hence, to concentrate on only business practice CSR
engagement may not be able to achieve customer-company identification whereas to focus on
only philanthropic CSR engagement cannot build trust in consumers’ mind. Second, not only
business practice CSR engagement but also philanthropic CSR engagement provides explicit
benefits to firms. For example, Zhang et al. (2010) argue that firms may take advantage of their
philanthropic engagement against their competitors in highly competitive market. Third, there
exist interdependencies not only between the firm and various stakeholder groups but also
among stakeholder groups themselves (Bhattacharya and Korschun 2008). Previous research in
marketing (e.g., Luo and Bhattacharya 2009) has argued that being a customer (i.e., primary
stakeholder) is only one part of a personal identity; the same person can also be the part of non-
62
profit organizations. Hence, being the generalist in CSR engagement may create synergy from
the interdependencies among stakeholder groups themselves rather than being the specialist. In
sum, we posit that the positive link between the breadth of CSR practices and firm performance
is negatively moderated by the depth of CSR.
H3: The depth of firm’s CSR practices negatively moderates the positive relationship
between the breadth of CSR practices and firm performance.
Moderating role of the ratio of philanthropic vs. business-related CSI practices
Although we believe that an increase in the breadth of CSI leads to negative firm
performance, we argue that this negative effect is mitigated by an increase in the ratio of
philanthropic vs. business CSI practices. To elaborate, we argue that when a firm engages in a
few sustainability concerns in philanthropic-related issues such as a criticism by NGOs but not in
business-related issues such as employee health and safety concerns or product safety concerns,
its firm performance would be less panelized by stakeholders compared to a firm which engages
in CSI practices mainly in business-related issue areas.
The negative effect of the CSI breadth on firm performance should be mitigated as the
ratio of philanthropic vs. business-related CSR practices increases, because philanthropic-related
sustainability concerns are less critical to primary stakeholders than business-related
sustainability concerns. Indeed, Maignan, Ferrell, and Ferrell (2005) suggest that “stakeholder
research indicates the treatment of customers and employees has the most influence on firm
performance” (p. 958). Customers are the ones who engage in direct market exchange with firm
and create demand, and employees are the ones who produce the goods and services for the
company and create supply (Clarkson 1995). Also, investors are the ones who affect firm’s stock
market values. Thus, when a firm’s CSI practices are highly relevant to the concerns of these
63
primary stakeholders, its performance would decrease much sharper through sales decrease,
labor unions’ protest, and stock price decrease (e.g., Pruitt and Peterson 1986; Salin and Hooker
2001). In addition, business-related CSI practices may involve in direct losses such as fines or
factory operation suspensions (e.g., BP’s Deepwater Horizon Oil Spill). In contrast, secondary
stakeholders are the ones who “are not engaged in transactions with the corporation” (Clarkson
1995, p. 107) and philanthropic-related CSI practices in general do not bear direct losses (e.g.,
Sodastream’s controversy with Oxfam). Hence, we posit that expected loss from philanthropic-
related CSI practices would be less than that from business-related CSI practices, and hence, the
breadth of CSI may induce less decrease in firm performance with higher ratio of philanthropic
vs. business-related CSI practices.
H4: The ratio of firm’s philanthropic vs. business-related CSI practices positively
Interaction among three sustainability practice portfolio descriptors in CSI practices
Building on the mitigation effect of the philanthropic vs. business-related ratio in CSI
practices on the link of breadth of CSI-firm performance (H4), we develop an argument for the
three-way interaction among breadth, depth and the ratio of philanthropic vs. business-related
practices in CSI practices.
For a given level of the CSI breadth, an increase in the depth of CSI practices with higher
ratio of philanthropic vs. business-related practices means that a firm reduces the number of
engaged CSI practices in business-related practices and adds the same number of CSI practices
in philanthropic-related practices. That is, the number of business-related CSI practices decreases
while the number of philanthropic-related practices increases, and this change increases overall
disparity among CSI practice engagement (i.e., increase in depth). For example, if a firm changes
its CSI practice engagement from ‘two from corporate governance issue areas (e.g., high CEO
64
compensation, transparency concern) and two from community issue areas (e.g., investment
controversies, indigenous peoples relations)’ to ‘one from corporate governance issue area (e.g.,
transparency concern) and three from community issue areas (e.g., investment controversies,
indigenous peoples relations, negative economic impact)’, both the CSI depth and the ratio of
philanthropic vs. business-related CSI practices increase while its CSI breadth stays the same as
four.
We argue that simultaneous increase in both the CSI depth and the ratio of philanthropic
vs. business-related CSI practices (at a given level of the CSI breadth) decreases the
effectiveness of the positive moderating role of the ration of philanthropic vs. business-related
CSI practice on the breadth of CSI – firm performance link. We expect this negative three-way
interaction in CSI practices because simultaneous increase in both the depth and the
philanthropic vs. business ratio could provide stronger signal to stakeholders that a firm
intentionally fails to meet philanthropic obligations. If the ratio of philanthropic vs. business-
related CSI practices is high and the depth of CSI is low, stakeholders (especially primary
stakeholders) may suspect that firm’s poor philanthropic performance may be the outcome of
other decisions and unavoidable consequence. For example, if a firm engages in one employee
relationship concern and one community concern, stakeholders may not believe that this is an
intentional strategic move to focus only on primary stakeholders’ concern. However, if a firm
engages two community concerns while none in other societal issue areas, this may create a
suspicion that a firm only focuses on primary stakeholders’ concern and ignores secondary
stakeholders’ concern, and may further form negative firm image because of the
interdependencies among stakeholders. In addition, simultaneous increase in both the depth and
the philanthropic vs. business ratio may increase probability that stakeholders would aware
65
firm’s poor philanthropic performance. Thus, this suspicion would further weaken the positive
moderating effect of the ratio of philanthropic vs. business-related practices.
H5: The deeper a firm’s depth of CSI practices, the weaker is the positive moderating
effect of the ratio of philanthropic vs. business-related CSI practices on the breadth of CSI – firm
performance link.
3.3 Data and Method
Data Sources
To test the hypotheses, we assemble the secondary data sets from two sources:
KLD Social Rating Database, and COMPUSTAT. We use Kinder, Lydenberg, and Domini
(KLD) Social Ratings Database as the data source for firms’ CSR and CSI performance,14
which
has been widely used in the academic literature (e.g., Hull and Rothenberg 2008; Kotchen and
Moon 2012). The KLD database provides a firm’s yearly binary (0\1) CSR/CSI practice
performance indicators across seven social issue areas, including community (e.g., charitable
giving / negative economic impact), corporate governance (e.g., transparency strength /
transparency concern), diversity (e.g., gay & lesbian policies / controversies), employee relations
(e.g., union relations / health & safety concern), environment (e.g., pollution prevention /
hazardous waste), human rights (e.g., labor rights strength / labor rights concern) and product
quality/safety (e.g., benefits to economically disadvantaged / product safety concern). Compared
to other widely used database for sustainability research such as Fortune’s MAC source which
provides survey-based aggregated corporate social performance rating (e.g., Luo and
Bhattacharya 2009; Houston and Johnson 2000), the KLD database is more suitable for our
research purpose because the disaggregated nature of CSR/CSI practice performance indicators
14
Consistent with Kotchen and Moon (2012), we consider all strength indicators as CSR and all concern indicators
as CSI of the firm.
66
allows us to construct the firm’s sustainability portfolio variables. In Table 2.1, we list all
CSR/CSI indicators across the seven social issue areas.
We focus on the data after 2001 and onwards since the number of companies in the KLD
database is not consistent over time and the main structural change happened in 2001.
Specifically, the KLD database covers approximately 650 firms from 1991 to 2000, while it
covers approximately 1,100 firms from 2001 and 2002 and approximately 3,100 firms from 2003
onwards. Also, some of the CSR/CSI practices were added, deleted or relocated from one social
issue area to another, yet the data structure after 2001 and onwards has been more stable than
before.
We obtain financial performance data as well as control variables from COMPUSTAT
Industrial Annual database. After concatenating the two databases, the final sample consists of
26698 observations, representing 3238 firms from 2001 to 2011. These firms are publically
traded firms from a wide range of industry.
Variable Operationalization
Dependent Variable
We use a firm’s Tobin’s q (TQ) as the measure of firm performance. Tobin’s q is a
market-based measure which captures the investors’ long-term expectation of the firm’s future
earnings (Miller 2004) and it has been regarded as a robust measure of firm performance (Mittal
et al. 2005). We choose to use Tobin’s q as our dependent variable for two reasons. First, in
contrast to short-term marketing efforts such as promotion, firms’ CSR/CSI practices may take
time to be realized by stakeholders and to change firms’ reputation as well as their financial
performances. For example, Cox, Brammer, and Millington (2004) argue that improved
corporate social performance should lead to significant financial gains only in the long run.
67
Second, Tobin’s q is not vulnerable to the distortion from tax laws or latitude in interpreting
regulations (Anderson et al. 2004). In other words, Tobin’s q is not affected by accounting
convention and can be used to compare firm performances across industries (e.g., Lee and
Grewal 2004). Thus, we argue that Tobin’s q is the best measure to test the link between firm
performance and sustainability practice engagement portfolio strategies. We calculate Tobin’s q
using the method proposed by Chung and Pruitt (1994).
Independent Variables
To provide concise picture of sustainability practice engagement, we propose three
descriptors of sustainability practice engagement portfolio, namely portfolio breadth (number of
different CSR/CSI practices that firm engages in), portfolio depth (variation in engaged CSR/CSI
practices in seven societal issue area), and philanthropic/business ratio (the ratio of engaged
philanthropic-related CSR/CSI practices over business-related CSR/CSI practices).
Portfolio Breadth of CSR/CSI (Breadth). Portfolio breadth refers to the number of
CSR/CSI practices that a firm engages in. Hence, the greater the number of engaged CSR/CSI
practices by a firm, the wider is its portfolio breadth. We operationalize portfolio breadth of CSR
(CSI) as the number of engaged CSR (CSI) practices across seven societal issue areas.
Specifically,
∑ (1)
where I is an indicator function which is set to 1 if the firm engages in particular CSR (CSI)
practices and 0 otherwise, and J is the total number of CSR (CSI) practices in the KLD database
in particular year. For example, Whole Foods Market, Inc. engaged in one CSR practice (limited
compensation) in corporate governance area, two CSR practices (promotion, gay & lesbian
policy) in diversity area, one (employee involvement) in employee relations and one (beneficial
68
products and services) in environment area in 2002. Thus, as shown in Table 2, Whole Foods
Market, Inc.’s portfolio breadth of CSR practices is five in 2002.
Portfolio Depth of CSR/CSI (Depth). Portfolio depth refers to the extent to which the
number of engaged CSR/CSI practices varies across different societal issue areas. The greater the
number of engaged CSR (CSI) practices in one societal issue area compared to other six areas,
the deeper is a firm’s portfolio depth of CSR (CSI) practices. We operationalize portfolio depth
of CSR (CSI) practices as the variance in the ratio of engaged CSR (CSI) practices over total
number of CSR (CSI) practices in particular societal issue areas. Specifically,
∑
∑ ( )
(2)
where
(3)
Although the data structure for CSR/CSI practices in seven societal issue areas is stable
in our final dataset, there are still some changes in total number of CSR/CSI practices in
particular societal issue area over time because of adding/removing practices or changing
societal issue area of particular practice from one to another. Hence, we look at the variance in
ratio instead of absolute number of practices.
Philanthropic/business ratio of CSR/CSI (Phil/Biz). Philanthropic/business ratio of
CSR/CSI refers to a firm’s emphasis on philanthropic-related CSR (CSI) practices compared to
its emphasis on business-related CSR (CSI) practices. If a firm engages high in business-related
CSR (CSI) practices and low in philanthropic-related CSR (CSI) practices,
philanthropic/business ratio is low and it suggests that the firm focuses on CSR (CSI) practices
that mainly influence primary stakeholders rather than secondary stakeholders. Following
Homburg, Stierl, and Bornemann’s (2013) approach, we divide seven societal issue areas in the
KLD database into two parts: community as philanthropic-related societal issue area vs.
69
corporate governance, diversity, employee relations, environment, human rights, and product as
business-related societal issue areas. Specifically, we define philanthropic/business ratio of CSR
(CSI) as:
(4)
We provide examples of firm’s sustainability portfolio strategy descriptors for six
randomly selected firms in our data, over three different years in Table 3.1. Over the years,
selected firms’ portfolio breadth of CSR/CSI practices, the depth of CSR/CSI practices, and the
ratio of philanthropic/business-related CSR/CSI practices have been changing over time.
Table 3.1 Example of CSR/CSI Practice Portfolios
Panel A: Examples of CSR Practice Portfolios
Company
SIC
Portfolio Breadth Portfolio Depth Philanthropic/Business
Ratio
2002 2006 2011 2002 2006 2011 2002 2006 2011
Johnson & Johnson 2834 7 16 19 0.128 0.235 0.309 0.889 0.324 1.219
Valero Energy Co 2911 3 4 7 0.131 0.162 0.205 2.667 1.619 0
Goodyear Tire &
Rubber Co 3011 3 2 9 0.131 0.076 0.232 0 0 0
Whole Foods Market 5411 5 7 11 0.116 0.147 0.244 0 0.810 0.65
Allstate Corp 6331 5 4 11 0.189 0.131 0.297 1.333 4.857 0.65
Microsoft Co 7372 5 9 15 0.108 0.208 0.213 1.333 1.388 1
70
Panel B: Examples of CSI Practice Portfolios
Company
SIC
Portfolio Breadth Portfolio Depth Philanthropic/Business
Ratio
2002 2006 2011 2002 2006 2011 2002 2006 2011
Johnson & Johnson 2834 6 9 3 0.366 0.255 0.197 0 0 0
Valero Energy Co 2911 5 8 6 0.176 0.215 0.360 1.813 1.107 5
Goodyear Tire &
Rubber Co 3011 4 9 6 0.115 0.155 0.399 2.417 0.969 5
Whole Foods Market 5411 2 3 2 0.104 0.131 0.189 0 0 0
Allstate Corp 6331 6 7 1 0.173 0.292 0.126 1.45 0 0
Microsoft Co 7372 4 4 4 0.192 0.192 0.207 0 0 0
Control Variables
Previous research has suggested that it is important to control for several factors which
might be associated with firm performance. Boulding and Staelin (1990) suggest that firm size
might have a positive impact on firm performance. Thus, we include the firm’s total assets
(Assets) and the natural log of the number of employees (in million; log(Emp)) in the model.
Also, various researches have suggested that advertising spending increases the sales and
profitability (e.g., Villanueva, Yoo, and Hanssens 2008; Naik, Mantrala, and Sawyer 1998).
Krasnikov and Jayachandran (2008) demonstrate a critical role of research and development
(R&D) on firm growth and performance. In addition, Steenkemp and Fang (2011) suggest that it
is important to control for market share when studying firm performance. Hence, we control for
advertising-to-sales ratio (AD), R&D-to-sales ratio (R&D) and market share (MS). Moreover, we
control for state dependence in firm performance by including the first-lag of Tobin’s q in the
model. Finally, we include year dummy to control for time trend and firm specific fixed-effect to
control for firm’s idiosyncracy. Note that firm fixed-effect term is also included in our model to
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capture unobserved heterogeneity in firm performance, yet this term drops out since our model is
first-differenced model. We present the descriptive statistics of the key variables Table 3.2.
Model Specification
To test our hypotheses of the relationship between sustainability portfolio strategy and
firm performance, we examine the following model for firm i in year t:
(5)
In equation (5), captures the inertia of firm performance. The terms represent
the main effects of three sustainability practice engagement portfolio descriptors, the breadth of
CSR (H1) / CSI (H2), the depth of CSR/CSI, and philanthropic/business ratio of CSR/CSI,
respectively. The terms represent the two-way interaction between the breadth and the
depth of CSR (H3 / CSI, the breadth and philanthropic/business ratio of CSR/CSI (H4 , and the
depth and philanthropic/business ratio of CSR/CSI, respectively. Three-way interaction effects
among portfolio breadth, depth, and philanthropic/business ratio of CSR/CSI (H5) are captured
by the terms and , respectively. The effects of control variables such as total assets,
advertising spending, R&D spending, market share, and number of employees are captured by
the terms , respectively, and the vector and capture year fixed effects and firm
fixed effects, respectively. Finally, is a normally distributed error term which is independent
and identical across firm i and year t.
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Table 3.2 Descriptive Statistics
Variable Correlation
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
1. Tobin’s q(TQ) 1.000
2. Breadth (CSR) -0.024 1.000
3. Breadth (CSI) -0.080 0.373 1.000
4. Depth (CSR) -0.026 0.883 0.290 1.000
5. Depth (CSI) -0.047 0.155 0.714 0.093 1.000
6. Phil/Biz (CSR) -0.052 0.025 0.053 -0.082 0.101 1.000
7. Phil/Biz (CSI) -0.058 0.106 0.028 0.123 -0.010 -0.014 1.000
8. Total Assets -0.078 0.326 0.264 0.262 0.146 0.094 0.046 1.000
9. Advertising-to-sales Ratio 0.101 0.037 -0.012 0.027 -0.010 0.009 -0.010 -0.007 1.000
10. R&D-to-sales Ratio 0.009 0.000 -0.001 -0.001 -0.003 -0.006 -0.004 -0.002 -0.002 1.000
11. Market Share -0.035 0.240 0.221 0.208 0.089 0.009 0.019 0.083 0.008 -0.007 1.000
12. Number of Employees
(natural log) (Emp) -0.173 0.425 0.397 0.391 0.168 0.043 0.042 0.214 0.010 -0.014 0.417 1.000
Mean 1.618 1.332 1.922 0.050 0.107 0.699 0.451 11338.35 0.012 2.381 0.089 0.867
Standard Deviation 1.926 2.241 1.849 0.062 0.079 0.942 1.245 75067.46 0.046 178.420 0.177 1.926
Estimation Strategy
When estimating equation (5), we consider the following econometric issues to provide a
robust and consistent evaluation on the effect of sustainability portfolio strategy on firm
performance: (1) endogeneity, and (2) unobserved heterogeneity. We overcome these
econometric issues by using Arellano-Bond (1991) estimator.
First, sustainability practice engagement portfolio and firm performance are assumed to
be endogenous because firm may decide its sustainability practice engagement portfolio based on
its actual performance or other unobserved factors. For example, Luo and Bhattacharya (2009)
argue that there may be reverse causality concern such that “firms that are performing well with
lower firm-idiosyncratic risk are more likely to engage in CSR” (p. 205). This reverse causality
argument suggests that the regressors may be correlated with the error term in equation (5).
Hence, following Arellano and Bond (1991), we use dynamic panel GMM estimator to account
for this type of endogeneity. Specifically, our panel data structure allows us to use lagged values
of the endogenous regressors as instruments. Due to these instruments, the endogenous variables
become pre-determined and not correlated with error term (Arellano and Bond 1991; Arellano
and Bover 1995; Holtz-Eakin et al. 1988).
Second, time-invariant unobserved firm characteristics may play a crucial role in firm
performance. For example, industry specific political economic factors such as industry
protection can influence firm performance differently across the firms from different industry. If
the unobserved heterogeneity is not controlled, then the estimation results would be inconsistent
and unreasonable (Wooldridge 2010). To control for this time-invariant unobserved
heterogeneity, we use first-differenced model which removes time-invariant firm-specific effects
by canceling out the term in equation (5).
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3.4 Results
Hypotheses Testing
To test the hypotheses, we rely on the dynamic panel estimator results. We present the
estimation results in Table 3.3. Overall, our model is significant ( statistic = 1260.02, p <
0.000). In addition, to check the validity of our model, we test the autocorrelation of the residuals
and over-identification restriction for the instruments. The AR(2) test for autocorrelation of the
residuals suggests that the differenced residuals do not exhibit significant AR(2) behavior (z
value = -0.98, p = 0.326). The over-identifying restrictions test result suggests that the
instruments are valid ( statistic = 258.73, p = 0.159). Thus, we conclude that our model is
valid and our dynamic panel estimation is meaningful. We now discuss hypothesis-testing results
followed by the effects of the control variables.
Main effects. For the main effects of the CSR/CSI breadth, we do not find a support for
H1, but we find a support for H2. The effect of a firm’s CSR breadth is positive but not
significant ( = 0.030, not significant [ns]), while the effect of a firm’s CSI breadth is negative
and significant ( = -0.036, p < .01). This result suggests that shareholders have negative
expectations of a firm’s future cash flows when firm’s portfolio breadth of CSI is high. However,
the limited information on the number of engaged CSR practices does not have significant
impact on shareholders’ expectations. Notably, the main effects of the portfolio depth of CSR
( = 0.682, ns) / CSI ( = 0.141, ns) and philanthropic/business ratio of CSR ( = 0.011, ns) /
CSI ( = 0.001, ns) on firm performance are not significant. These results are in line with the
findings that the influence of negative CSR performance (i.e., CSI practices) is much stronger
than that of positive CSR performance (i.e., CSR practices) in reducing information asymmetry
in investors (e.g., Cho, Lee, and Pfeiffer 2012).
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Table 3.3 Hypotheses Testing Results
Variables Hypotheses Model 1
Estimate Std. Err
Breadth (CSR) H1 0.0300 0.0247
Breadth (CSI) H2 -0.0361***
0.0129
Depth (CSR) 0.682 0.581
Depth (CSI) 0.141 0.288
Phil/Biz Ratio (CSR) 0.0114 0.0171
Phil/Biz Ratio (CSI) 0.0014 0.0075
Breadth × Depth (CSR) H3 -0.186***
0.0678
Breadth × Depth (CSI) 0.0783 0.0637
Breadth × Phil/Biz Ratio (CSR) -0.0043 0.0136
Breadth × Phil/Biz Ratio (CSI) H4 0.0139**
0.00662
Depth × Phil/Biz Ratio (CSR) -0.507 0.349
Depth × Phil/Biz Ratio (CSI) -0.0514 0.0416
Breadth × Depth × Phil/Biz Ratio (CSR)
0.0667 0.0708
Breadth × Depth × Phil/Biz Ratio (CSI) H5 -0.0883***
0.0342
Total Assets 6.10e-08 2.71e-07
Advertising-to-sales Ratio -0.416 0.844
R&D-to-sales Ratio -0.000038***
0.000014
Market Share -0.163 0.292
Number of Employees -0.305***
0.0497
Lag(Tobin’s q) 0.141***
0.0498
Firm Fixed Effects First-differenced
Time Fixed Effects Included
- Test Statistics (d.f. = 29) 1260.0
Arellano-Bond test for AR(2)
-0.98 (p-value: 0.326)
Sargan test of over-identifying restrictions
258.73 (p-value: 0.159)
*p< 0.10; **p< 0.05; ***p < 0.01.
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Moderating effects. To test the moderating effects of the depth and philanthropic/business
ratio on the breadth of CSR/CSI practices, we create the interaction terms by multiplying mean-
centered independent variables as suggested in the literature (e.g., Homburg, Stierl and
Bornemann 2013). Our analysis result shows a negative moderating effect of the depth on the
link between sustainability portfolio breadth of CSR practices and firm performance ( = -0.186,
p < .01), in support of H3. In other words, the higher the variance in a firm’s sustainability
practice engagement portfolio, the weaker the positive effect of portfolio breadth of CSR
practices on firm performance. However, we do not find a significant moderating effect of the
depth of CSI practices on the relationship between the breadth of CSI and firm performance (
= 0.078, ns). For the moderating effect of philanthropic/business ratio on the link between the
breadth of CSR practices and firm performance, we do not find a significant two-way interaction
for CSR ( = -0.004, ns), while we find a significant positive moderating effect of
philanthropic/business ratio for CSI ( = 0.014, p < .05). This finding suggests that the
negative effect of portfolio breadth of CSI practices on firm performance is mitigated when a
firm has high philanthropic/business ratio, in support of H4. All other two-way interactions are
not significant.
Finally, turning to the three-way interaction, although we do not find a moderating effect
of philanthropic/business ratio of CSR practices on the negative moderating effect of the depth
on the breadth of CSR – firm performance relationship ( = 0.067, ns), we find a negative
moderating effect of the depth on the positive moderating effect of philanthropic/business ratio
on the breadth of CSI – firm performance link ( = -0.088, p < .05), providing support for H5.
To elaborate, the mitigation effect of philanthropic/business ratio of CSI practices on the breadth
of CSI – firm performance link become less strong when a firm’s sustainability practice
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engagement portfolio depth of CSI practices increases. Thus, simultaneously pursuing for high
depth, high philanthropic/business ratio sustainability portfolio can actually be harmful for
reducing the negative impact of the breadth of CSI on firm performance.
Control variables. In terms of control variables, we do not find significant effects of the
firm’s total assets ( = 0.000, ns), advertising spending ( = -0.416, ns), and market share
( = -0.163, ns). However, interestingly, we find negative effect of R&D spending ( = -
0.00004, p < .01) on firm performance. Previous research has pointed out that stakeholder may
perceive a trade-off between firm’s sustainability practices and other key strategic marketing
levers such as R&D because firms have limited resources (Sen and Bhattacharya 2001). In
addition, Luo and Bhattacharya (2009) found that the simultaneous pursuit of corporate social
performance, advertising, and R&D leads to increase firm idiosyncratic risk. In line with
previous research, we also find that the effect of R&D spending is negative after accounting for a
firm’s sustainability practice engagement portfolio strategy. The year fixed effects which
captures temporal variation in firm performance are significant for all years except 2009.
3.5 Discussion
Sustainability continues to draw special attentions from practitioners and academics alike.
Sustainability is considered a “high” or “very high” priority for the firms (The Economist 2008)
and it now reaches to C-Suite level: Chief Sustainability Officer. As firms engage in a wide
range of sustainability practices in the area of economic, social, and environmental development,
CSOs often encounters complex and challenging decision of how to strategically engage in
various sustainability practices and to prioritize firm’s efforts in these sustainability practices.
The goal of this research is to provide guideline on how firms should manage their sustainability
practice engagement portfolio to increase their firm performance. To provide a holistic view of
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sustainability practice engagement, we utilize three constructs, i.e., breadth, depth, and the ratio
of philanthropic vs. business-related practices, for CSR and CSI practices and empirically test
the roles of these constructs on firm performance. We show that the deep engagement in a few
CSR practices mitigates the positive impact of the breadth of CSR on firm performance. In
addition, we show that a firm’s high concentration on philanthropic-related CSI practices
compared to business-related CSI practices mitigates the negative impact of the breadth of CSI
on firm performance. Yet, simultaneous increase in the breadth, depth, and philanthropic vs.
business-related ratio in CSI practices incur negative impact on firm performance. We now
discuss the implications of our finding.
Theoretical Implication
Our research contributes to prior CSR and sustainability research in several ways. First,
building on financial portfolio theory (Markowitz 1952), we advance research on CSR by
examining the link between a firm’s holistic engagements in a wide range of sustainability
practices and firm performance. Although prior studies examine the relationship between CSR
and firm performance, most of the studies either focus on only one part of CSR (e.g., Klassen
and McLaughlin 1996; Lichtenstein, Drumwright, and Braig 2004; Robinson, Irmak, and
Jayachandran 2012) or look at the impact of aggregated sustainability performance on firm
performance (e.g., Brown and Dacin 1997; Wagner, Lutz, and Weitz 2009; Luo and
Bhattacharya 2009) which fail to capture the interdependence and synergy among various
sustainability practices. In contrast, our portfolio theory based approach enables us to capture
these interdependence and synergy effect. In other words, this study provides a theoretical
framework for a simultaneous investigation of multiple sustainability practice engagement. Thus,
we respond to calls to the argument that “the influence of multiple sustainability-focused
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marketing assets on financial returns” has not been examined thoroughly (Chabowski et al. 2001,
p.66).
Second, while most research in marketing has conceptualized CSR globally or has looked
at one societal area of CSR (Homburg, Stierl, and Bornemann 2013), we refine this approach by
(1) separating out CSI practices from CSR and (2) distinguishing CSR/CSI practices into two
distinct groups which are philanthropic-related and business-related. In this paper, we look at the
portfolio descriptors for both CSR and CSI and investigate the holistic framework of “CSR-CSI-
firm performance,” which is new in the literature. Indeed, while researchers who utilized global
conceptualization of CSR (e.g., Hillman and Keim 2001) inherently assumed that the effect of
one CSI practices can be canceled out by another CSR practices (e.g., if the breadth of CSR is
equal to the breadth of CSI, then a firm’s global CSR score is 0), we show that the effect of one
CSI practice may not be wiped out by engaging in one CSR practice since we find support for H2
but not for H1, which suggests the separation of CSI from CSR. Further, we find that the effects
of CSR and CSI practices on firm performance are differently moderated by their own depth and
the ratio of philanthropic/business-related practices. In addition, we introduce the ratio of
philanthropic/business-related practices as one of the key descriptor of sustainability practice
portfolio based on stakeholder theory. Thus, we partially answer calls to examine the link
between specific types of CSR and customer outcomes (Barnett 2007). Our research
demonstrates that the link between the breadth of CSR and firm performance is not affected by
the type of CSR, while the negative relationship between the breadth of CSI and firm
performance is mitigated by the type of CSI. That is, if a firm engages in multiple CSI in
philanthropic-related cases, the customers would less panelize the firm compared to the situation
of multiple CSI in business-related practices.
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Third, we contribute to the marketing-finance interface (Luo and Homburg 2008;
Srivastava, Shervani, and Fahey 1998) by examining the impact of CSR/CSI practices on
Tobin’s q, stock market-based long-term measure of a firm value (Wernerfelt and Montgomery
1988; Miller 2004). In particular, we directly respond to call for the research on the marketing-
finance interface to examine the stock market impact of CSR initiatives on [long-run] firm
valuation by Srinivasan and Hanssens (2009). While prior marketing literature has focused on
the short-term financial measures such as the level of stock return and firm idiosyncratic risk
(e.g., Luo and Bhattacharya 2009), our study suggest a long-term impact of CSR/CSI on firm
valuation. Moreover, we contribute to the debate on whether “doing good” leads to “doing well.”
While roughly 50% of the literature finds a positive relationship between CSR and firm
performance, 25% finds no relationship, 20% find mixed results, and 5% find even a negative
relationship (Margolis and Walsh 2001; Scholtens 2008). Our finding suggests that “doing good”
may lead to “doing well” when the breadth of CSR practices is high and the depth of CSR
practices is low. Further, we suggest that not only the breadth but also the depth and
philanthropic vs. business-related practice ratio should be considered in sustainability-finance
interface.
Managerial Implication
Our research shed lights on the problem of effective sustainability practice management.
Anonymous respondent’s comments from The Sustainability Executive: Profile and Progress
report (PwC 2012) echoes one of the most challenging decisions for sustainability executives:
“You have to make hard choices, and you have to piss some people off, and you have to say that
there are some things that I am not going to do.” In other words, we address managerial
questions of how a manager should prioritize firm’s effort across various sustainability practices
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under the resource constraints. Indeed, Luo and Bhattacharya (2009) argue that “[corporate
social responsibility] competes for the resources that instead could be invested in adverting
and/or R&D” which are key strategic marketing levers (p.204). We advise managers to apply
two simple rules for sustainability practice engagement. First, be the generalist in CSR practices.
Our finding suggests that when a firm increases both the breadth and the depth of CSR practices,
firm performance decreases. Thus, when the resources are limited and a firm may not be able to
increase the number of CSR practice engagement, it would be better to evenly engage in CSR
practices across multiple societal issue areas than engage heavily on multiple CSR practices in a
few societal issue areas. In other words, an effort to build a corporate image of “Green Giant” or
“Ultimate Philanthropist” can be misguided sustainability strategy. Second, minimize business-
related CSI practices first, but don’t let the philanthropic-related CSI practices stand out. Our
findings suggest that less CSI practice engagements lead to better firm performance. Yet, due to
the limited resources, reducing all the CSI practice engagement may not be possible. In this case,
the best sustainability practice engagement strategy would be increase the ratio of philanthropic
vs. business-related CSI practices. However, if high engagement in philanthropic-related CSI
practices speaks out to stakeholders, they would panelize firm performance.
Limitations and Future Research Areas
Although our study presents fruitful insights into sustainability practice engagement
management, there are some limitations. First, although we focus on the link between actual
CSR/CSI practice engagement and firm performance, there may exists a gap between actual
CSR/CSI practice engagement and firm’s CSR/CSI reputation, which may actually drives
customer outcomes such as trust and customer-company identification, and further, firm
performance. In fact, Homburg, Stierl, and Bornemann (2013) found that CSR engagements are
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highly correlated with CSR reputation, but not perfectly. However, since our main research
objective is to provide a management guideline for the effective engagement in various
sustainability practices, we believe that the actual engagement is more appropriate construct than
the reputation. Further research could expand our link and investigate “actual sustainability
engagement – sustainability reputation – firm performance” chain and provide more insights.
Second, although we investigate the relationship between three descriptors of
sustainability practice engagement and firm performance, further research could utilize other
financial indicators. For example, building on the risk management theory, Luo and
Bhattacharya (2009) look at the risk-reduction benefit of corporate social performance.
Recognizing the possible trade-offs between different financial indicators such as risks and
market share growth (Grewal et al. 2008), developing a holistic framework of effective
sustainability practice engagement management regarding different financial goals would be an
interesting extension of this research.
In conclusion, we suggest a guideline for the sustainability practice engagement
management. In particular, our findings show that the generalists in CSR practices are “doing
well.” Also, our research suggests that business-related CSI practices have priorities to be
minimized compared to philanthropic-related CSI practices. We contribute to both ends of our
readers by extending CSR and sustainability research and providing practical insights to
practitioners.
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Chapter 4
CONCLUSION
In my dissertation, I investigate the effectiveness of sustainability strategy. In particular, I
address two interesting questions: (1) how and why firms are engaging in corporate social
responsibility practices (chapter2 - essay 1) and (2) what types of sustainability strategy
portfolios promise the greatest return (chapter 3 - essay 2). The findings from essay 1 suggest
that firms are engaging in CSR practices to compensate for their previous misbehaviors (i.e., CSI)
while engaging in CSR practices promises greater return. In essay 2, the findings provide a
guideline for the effective sustainability practices engagement management with respect to its
portfolio breadth, depth, and philanthropic-focus. Both essays contribute to marketing literatures,
especially CSR and sustainability literatures, and practice in several ways.
First, unlike previous research that studied the effectiveness of overall sustainability
performance or the influence of sustainability performance in one specific societal dimension on
firm value, both essays distinguish the roles of sustainability practices from different
sustainability dimensions and examine the link between multi-dimensional sustainability
practices and firm performance. In particular, in essay 1, I distinguish engaging in CSR practices
from minimizing CSI practices and investigate the dynamic interplay among CSR, CSI and firm
performance. In essay 2, I further divide sustainability practices into business-related and
philanthropic-related practices. This directly responds to calls to the argument that “the influence
of multiple sustainability-focused marketing assets on financial returns” has not been examined
thoroughly (Chabowski et al. 2001, p.66).
84
Second, both essays expend current marketing-finance interface literature (e.g., Luo and
Homburg 2008; Srivastava, Shervani, and Fahey 1998) by examining the impact of CSR and CSI
practices on firm performance. While marketing-finance interface literature has revealed the
impact of marketing and other marketing-related functions (e.g., R&D) on firm performance
(e.g., Luo and Homburg 2008; Sridhar et al. 2011), the link between one of the most popular
components of recent marketing (i.e., CSR/sustainability) and financial outcome has not been
fully investigated. In essay 1, I disentangle the dynamic interplay among CSR-CSI-firm
performance by using advanced econometric method, and find a support for the argument that
“doing good” leads to “doing well.” To the best of my knowledge, my essay 1 is the first study
that uses panel vector autoregression model to separate CSI from CSR-firm performance to
understand the true relationship between CSR and firm performance. In essay 2, I take slightly
different stance and propose additional constructs to understand the complex relationship
between CSR-CSI-firm performances.
Third, both essays provide useful managerial implications for CSO and sustainability
executives who face complex sustainability practice management decisions. The findings from
essay 1 provide an insight to CSO and executives that CSR has a positive and long-term effect
on firm performance. This insight can motivate firms to engage in CSR practices. Further, the
findings from essay 2 should help managers decide on their sustainability practice engagement
strategy for both embracing opportunities and managing risks. The findings suggest that, under
the condition of limited resources, managers need to diversify firm’s effort on engaging in CSR
practices and to focus on minimizing business-related CSI practices while not letting the
philanthropic-related CSI practice stand out. These noble findings should guide sustainability
executives when they question about the priority of sustainability practice engagement decision.
85
In summary, my two dissertation essays examine the performance implications of multi-
dimensional sustainability strategy that extant research has so far not considered. I hope that my
first step will provoke additional work in this important area.
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APPENDIX
THEORETICAL MODEL
We rely on the basic economic notion that firms seek to maximize utilities and profits to
develop a theoretical model for the effect of CSR and CSI; specifically, we use primitives from
theory of the firm (e.g., Becker 2007, Chapter 5). Within the theory of the firm framework, profit
maximizing can be subsumed within utility maximization, such that a “firm may act as if it
maximized a utility function that depends not only on its profits, but also on color, sex, and
family background of employees” i.e., CSR and CSI (Becker 2007, p. 70); thus, we focus on
long-term profit maximization. In this framework, we define profits (π) at a given time t as:
(A1) ,
where, and represent revenues and costs respectively.
With the profit function described in equation A1, we seek to develop a dynamic
optimization problem for a firm where the firm chooses an optimal level of efforts for CSR and
CSI. To layout this specification we represent revenues as (where is the product operator):
(e.g., Naik and Raman 2003), where m represents the margins that account for all
expenses other than those associated with CSR and CSI and is the sales at time t; thus can
be seen as the costs associated with CSR and CSI. If ρ represents the discount rate and and
the efforts for CSR and CSI respectively, , then the firms net present value of its
current and future profits ( ) can be given as:
(A2) ∫
∫
∫
Equation A2 represents continuous time infinite horizon profit flows and, as is common
in this literature (e.g., Rao 1986), we will not index variables by t to facilitate reading. As is
87
typical in dynamic optimization (e.g., Kamien and Schwartz 1991; Sethi and Thompson 2006),
we seek to maximize equation A2 subject to constraints that emanate due to the dynamic
response function of sales ; that is:
(A3a) ∫
Subject to:
(A3b)
where, is an appropriate dynamic response function for sales.
In the parlance of optimal control theory (e.g., Kamien and Schwartz 1991), S represents
the state variable and r and i are the control variables (i.e., variables that firms make decisions
on). To maximize the system in equation A3, we define the Hamiltonian as:
(A4)
where, is the costate variable.
At optimality, the necessary conditions, which are sufficient when is concave in and
, are (e.g., Kamien and Schwartz 1991):
(A5)
With this dynamic CSR decision problem in place, we now seek to develop the
specification for cost and evolution of sales as specified in
.
Cost Function Specification
There are three components for the CSR relevant costs that we need to consider. First we
need to consider the direct costs associated with CSR efforts r. Firms exert such efforts to
promote social causes; for example, for every pair of shoes that Toms sells, they donate one to a
child in need (known as the “one for one” model). Thus, we use the function to represent
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these costs, where is a typical continuous twice differentiable indirect cost function that
satisfies properties of cost functions (e.g., Kreps 1990, p. 251-253). As costs typically increase
with efforts and are convex, a popular form for costs is quadratic (e.g., Naik and Raman 2003),
such that one could specify
.
Second, similar to CSR efforts r, one needs to consider costs associated with direct CSI
efforts i. Firms exert these CSI efforts to reduce the probability of CSI incidents. For example,
accidents during the transportation of crude oil are imminent; thus, oil firms such as Exxon
Mobile reinforce the hulls of their transportation ships to reduce the probability of oil leaks when
such accidents occur. Thus, CSR efforts represent doing social good, while CSI efforts serve to
reduce harm from CSI incidents. Similar to CSR efforts, we use the function to represent
costs associated with CSI efforts. Again, a quadratic functional form can be used for such costs,
i.e.,
.
Third, we need to consider the costs that firms can expect to incur when CSI incidents
occur; examples of such incidents include oil spills as in the case of BP or unforeseen product
harm crises. As CSI is associated with incidents, we model the costs associated through expected
loss and the buffering effects of CSR and CSI efforts. Expected loss can be seen as a firm-
specific typical or average loss associated with a CSI incident; for example, for a firm in a
particular business, could represent the average over the last 10 years. To specify these
buffering effects we recognize that the buffering effects should increase as efforts increase and
there should be some difference in the buffering between CSR efforts and CSI efforts. Thus, we
specify the costs due to such incidents as: , where . As
efforts r and i are positive and θ and λ are positive, the expression “ ” is positive
and thus as efforts increase, ; thus efforts reduce the costs associated with CSI
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incidents. Further, θ instruments the nature of the buffering effect of efforts; implies that
the level of CSR efforts proportionally reduce expected loss; , implies that the translation
of efforts for expected loss is lower than when ; implies an amplification of effort
such that the translation of effort is higher than . λ ensures that the effects of CSR efforts r
are different from those of CSI efforts i. If λ is less than 1, then CSR efforts buffer more than CSI
efforts; if λ is equal to 1, then both efforts buffer equally; and if λ is greater than 1, then CSI
efforts buffer more than CSR efforts.
With the above discussion, we can write the costs as:
(A6)
Sales Function Specification
As is typical in optimal control applications in marketing, we need to specify the
evolution of the sales function S (e.g., Naik and Raman 2003), which serves as a constraint in the
Hamiltonian specification (equation A3b). Thus, now we elaborate on the functional form of
. We recognize that change in sales (
) should be a function of CSR efforts and CSI
efforts and the level of sales (i.e., consistent with extant research, we do expect persistence in
sales; e.g., Sridhar et al. 2011). Further, it is reasonable to expect that the efficacy of CSR efforts
and CSI efforts depend on the level of sales. For example, larger firms (i.e., firms that have
higher sales) tend to be better known, and better known firms tend to get scrutinized, i.e.,
condemned, more often by the media than smaller firms (e.g., Brooks et al.2003). Thus, it seems
reasonable to assume that larger firms’ CSR efforts and CSI efforts also receive greater scrutiny
by the media. Hence, in our specification for
, we include the interaction between CSR efforts
and sales and CSI efforts and sales, i.e.,:
90
(A7)
Profit Maximization
Optimal efforts for CSR and CSI, i.e., r and i respectively, can be obtained by
maximizing infinite horizon profits, i.e., firm value given in equation A2. To maximize firm
value in equation A2, the cost function and evolution of sales function in equations A6 and A7
are substituted into the Hamiltonian in equation A4, which gives us:
(A8) ( ) ( )
With the Hamiltonian in equation A8, the first order conditions would be:
(A9a)
(A9b)
(A9c)
In theory one could solve equations A9a and A9b for efforts r and i as functions of other
parameters including the costate variable . However, due to the presence of the exponent (with
both r and i in the exponent), these equations are referred to as transcendental equations that
require the use of the Lambert W function and thus, numerical methods to solve them (e.g.,
Hayes 2005). To solve for , one has to use the transversality conditions obtained from steady-
state conditions on state and costate variables, i.e.,
and
respectively.
Further, we consider two alternate specifications for costs associated with CSI incidents,
i.e., . For both these specifications, we do not make changes to expected loss but argue
that the buffering effect depends only on CSR efforts r. As expected losses can be seen as a
typical or average firm-specific loss associated with a CSI incident, CSI efforts should reduce the
probability of CSI incidents, and, as a result, the benefits of CSI efforts i are built into . Thus,
91
buffering effects only depend on CSR efforts r. To specify these buffering effects we recognize
that the buffering effects should increase as efforts increase. Thus, there are two options to
specify these efforts: (1) similar to our earlier specification we use the exponential function to
specify and (2) we can use a much simpler inverse function, such that:
, where . In this second specification, as efforts r are positive, the
expected loss is positive, is positive, and the expression
is positive and decreases as
effort r increases; thus CSR efforts reduce the costs associated with CSI incidents. If is less
than 1, then the buffering effect of CSR efforts is amplified, if equals 1 then the CSR efforts
proportionally reduce expected loss, and if is greater than 1, then CSR efforts do not have
much of a buffering effect. The solution to the first specification, where ,
would still involve the Lambert W function and the use of numerical methods. The solution to
the second specification, where
, would lead to a cubic functional form for r and a
linear functional form for i; thus there would be three solutions for r and one for i.
92
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VITA
Charles Kang [email protected]
Education
Smeal College of Business, Pennsylvania State University
PhD in Business Administration
Concentration: Marketing
August 2014 (Expected)
University of Illinois at Urbana-Champaign
Master of Science in Statistics
May 2009
Yonsei University, Seoul, South Korea
B.S. in Business Administration
B.S. in Applied Statistics (Second Major)
February 2006
Research Interests
My research interests are in the area of quantitative marketing strategy. Specifically, I am in
interested in dynamic empirical modeling of issues relating to sustainability strategy in
marketing, and its influence on firm performance.
Working Papers
Kang, Charles, Frank Germann, & Rajdeep Grewal. “Performance Implications of Corporate
Social Responsibility and Irresponsibility”
Kang, Charles, and Rajdeep Grewal. “Portfolio Management in Sustainability Strategy and
Firm Performance”
Sridhar, Hari, Charles Kang, Frank Germann & Rajdeep Grewal. “Portfolio Perspectives on
Organizational Media Advertising Spending ”
Kang, Charles, Rajdeep Grewal & Duncan Fong. “Understanding Common Trends in
Sustainability Strategy”
Academic Honors and Awards
Jerome E. Scott Memorial Scholarship for outstanding doctoral students, Department of Marketing,
Pennsylvania State University (2013)
Haring Symposium Best Discussant Award, Indiana University (2013)
Haring Symposium Fellow, Discussant, Indiana University (2013)
Competitive Smeal Small Research Grant, Smeal College of Business, Pennsylvania State University
(2013, 2014)
Consortium Fellow, INFORMS Marketing Science Doctoral Consortium (2012)
Frank P. and Mary Jean Smeal Endowment Fund Scholarship, Smeal College of Business,
Pennsylvania State University (2009-2011)
Tuition Scholarship, ISBM PhD Seminar Series, Pennsylvania State University (2008)