The Pennsylvania State University

The Graduate School

The Mary Jean and Frank P. Smeal College of Business

WHEN TO SPEAK UP AND WHEN TO SHUT UP:

THE INTENDED (AND UNINTENDED) REPUTATIONAL CONSEQUENCES OF

SOCIAL AND ENVIRONMENTAL SIGNALING

A Dissertation in

Business Administration

by

Jenna P. Stites

2014 Jenna P. Stites

Submitted in Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

August 2014

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The dissertation of Jenna P. Stites was reviewed and approved* by the following:

Barbara Gray Professor and Smeal Executive Programs Faculty Fellow, Emerita Dissertation Advisor Chair of Committee

Timothy G. Pollock Professor of Management

Vilmos F. Misangyi Associate Professor of Management Denise Bortree Associate Professor of Advertising/Public Relations

Brent Ambrose Director of Ph.D. Programs

*Signatures are on file in the Graduate School

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ABSTRACT

Drawing on stakeholder, reputation, signaling, path dependence and communication

theories, this dissertation examines the relationship between social and environmental signaling

and firm reputation. In particular, it examines how signals sent by firms, firm partnerships, third

parties and the media regarding corporate social and environmental responsibility (CSER)

interact with a firm’s history of social and environmental actions to impact the firm’s CSER-

specific reputation as well as its general reputation. The results suggest that firm self-disclosure

lowers the general reputation of firms with strong CSER histories, whereas it enhances the

general reputation of firms with weak CSER histories. Additionally, forming CSER-oriented

partnerships increases general reputation for firms regardless of CSER history. On the other hand,

receipt of third-party awards only increases general reputation for firms with a history of CSER

strengths. In terms of CSER-specific reputation, however, CSER history appears to be the only

important predictor. These results present several theoretical contributions and managerial

implications.

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TABLE OF CONTENTS

List of Figures ......................................................................................................................... vi

List of Tables ........................................................................................................................... vii

Acknowledgements .................................................................................................................. viii

Financial Acknowledgements .................................................................................................. xii

Chapter 1 Introduction ............................................................................................................. 1 

Reputation ........................................................................................................................ 3 History .............................................................................................................................. 4 Signaling .......................................................................................................................... 5 Research Questions .......................................................................................................... 6 Dissertation Overview ...................................................................................................... 7 

Chapter 2 Theoretical Background .......................................................................................... 8 

The Stakeholder Perspective ............................................................................................ 8 CSER History ................................................................................................................... 9 Signaling .......................................................................................................................... 11 

Sources of CSER Signals ......................................................................................... 13 Source Credibility .................................................................................................... 19 

Reputation ........................................................................................................................ 21 

Chapter 3 Hypotheses .............................................................................................................. 23 

Firm Self-Disclosure ........................................................................................................ 24 Firm CSER Partnerships .................................................................................................. 28 Third-Party-CSER Awards .............................................................................................. 30 Media Favorability ........................................................................................................... 33 

Chapter 4 Methodology ........................................................................................................... 35 

Sample .............................................................................................................................. 35 Data and Measures ........................................................................................................... 36 

Independent Variables .............................................................................................. 36 Moderators ............................................................................................................... 39 Dependent Variables ................................................................................................ 40 Controls .................................................................................................................... 43 

Analytical Models ............................................................................................................ 44 

Chapter 5 Results ..................................................................................................................... 45 

Summary Statistics and Correlations ............................................................................... 45 General Reputation Results .............................................................................................. 47 CSER-specific Reputation Results ................................................................................... 51 

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Chapter 6 Discussion ............................................................................................................... 54 

Contributions .................................................................................................................... 55 Limitations ....................................................................................................................... 63 Future Research ................................................................................................................ 64 

Chapter 7 Conclusions ............................................................................................................. 68 

References ................................................................................................................................ 71 

Appendix A: Figures ................................................................................................................ 89 

Appendix B: Tables ................................................................................................................. 92 

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LIST OF FIGURES

Figure 1: Moderation Effect of Firm Self-Disclosure on the Relationship between CSER Historical Weaknesses and General Reputation ............................................................... 89 

Figure 2: Moderation Effect of Firm Self-Disclosure on the Relationship between CSER Historical Strengths and General Reputation ................................................................... 90 

Figure 3: Moderation Effect of Third-Party Awards on the Relationship between CSER Historical Strengths and General Reputation ................................................................... 91 

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LIST OF TABLES

Table 1. Distribution of Industries Represented ...................................................................... 92 

Table 2: Means, standard deviations and bivariate correlations .............................................. 93 

Table 3: Results of Linear Regression Predicting General Reputation .................................... 94 

Table 4: Results of Logistic Regression Predicting CSER-Specific Reputation ..................... 95 

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ACKNOWLEDGEMENTS

On Monday, June 2, 2014 I walked into Smeal’s Business Building wearing

business attire, carrying my laptop, ready to face my last hurdle as a doctoral candidate.

On Tuesday, June 3, 2014, after successfully passing my defense, I walked into the same

building, pushing my two year old daughter in a stroller through those same halls, this

time as a mom. What a juxtaposition!

Taking a trip down memory lane is always an eye-opening journey. As I think

back to before I began my doctoral career, I can’t help but be amazed at how life unfolds.

And, if there’s one thing I’ve learned continually throughout the last several years, it’s

that things rarely turn out the way you expect – but, instead, life’s twists and turns make

it all the more interesting and valuable. In the same way, though I never could have

expected my career to develop the way it has, I am incredibly thankful that it did.

Although a Ph.D. is, in many ways, a personal journey, its accomplishment would not

have been possible without the support and guidance of many very, very important

people. Though I left State College towards the end of my doctoral studies to finish at a

distance, the Management and Organization (M&O) department at Smeal will always feel

like home, and there are numerous people that I’d like to thank for their contributions to

my success.

First, and foremost, I want to thank my advisor, and friend, Barbara Gray.

Starting from the first day we met, Barbara has always challenged me to think beyond

and question my assumptions. She has been a mentor in my academic and personal life,

always encouraging me to take risks, push through obstacles and celebrate wins. She has

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even endured the wrath of law enforcement just to check in with me during the Academy

of Management annual meeting in 2010! (Who knew Montreal had such strict rules about

jaywalking?!?) She has supported me during both highs and lows and continually inspires

me to focus on what is most important. It has been a great joy to collaborate with her as

we study various interdisciplinary topics, including collaboration! Her wisdom,

perspective, and dedication to helping me succeed guided me through my doctoral career

and contributed invaluably to my research and teaching. I will always be thankful for the

role she plays in my life and the scholarly example she has set for me. And, I look

forward to continuing to work with and learn from her as we continue to collaborate.

I also want to specifically thank my committee members for their guidance: Tim

Pollock, Vilmos Misangyi and Denise Bortree. If it weren’t for Tim, I surely wouldn’t be

studying reputation. I remember talking with him about dissertation ideas earlier in my

career when I was trying to figure out how all of my interests could combine into a single

dissertation topic when he suggested that I consider a reputational framework, and the

rest is history (i.e., CSER history). Likewise, I will always appreciate the influence

Vilmos has had on me, evident through heated theoretical discussions that problematize

my thinking. Further, Denise has helped me see how my interests fit within the realm of

communication studies and has helped me see synergies in that regard. As a whole, my

committee has been an important sounding board and guiding rail, encouraging me and

helping me to work on impactful research, and I look forward to continuing these

relationships in the future.

There are also numerous others who have had a significant influence on this

journey and for whom I am incredibly grateful. I owe my interest in the Smeal M&O

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department to Gerry Susman, who saw my potential, and gave me a chance to get

involved with research as a freshly minted college graduate. We worked together on a

variety of projects before I began my graduate studies, and I will always be thankful for

his role in developing my interest in academic research and writing. In addition, my

accomplishments are due in large part to dedication of all of the M&O faculty, including

Vilmos Misangyi, Denny Gioia, Forrest Briscoe, Lance Ferris, Raghu Garud, Aparna

Joshi, Razvan Lungeanu, Srikanth Paruchuri, and Chuck Snow, but especially those who

taught my seminar courses (in addition to Barbara Gray and Tim Pollock): Linda

Trevino, Don Hambrick, Dave Harrison, Glen Kreiner, Stephen Humphrey and Wenpin

Tsai. While teaching these topics year after year must get old in some regards, they never

cease to show how exciting and foundational this work is to the core of management

research and practice and, as a result, the groundwork they laid in these courses continues

to stimulate my thinking and appreciation of the vast field of management. In addition, I

am so thankful for the help of two wonderful research assistants: Rita Young and Mia

Rendar – their work contributed greatly to my own. Also, our M&O support staff, Holly

Packard, Tena Ishler, Nicole Buckwalter, Nicole Force, Jamie Liner and Sue Cherry were

instrumental in navigating the bureaucratic side of getting a Ph.D. and their support is

greatly treasured.

Further, I am indebted to my fellow graduate students, as we have shared so many

experiences together throughout our graduate studies. In particular, Nathan Bragaw, Abhi

Acharya and Katie Wowak. We endured so very many trying, stressful, and absolutely

fun and hilarious times together! Their friendships made this journey an enjoyable one

and helped me to laugh when I wanted to cry! Similarly, I so value my cohort: Shubha

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Patvardhan, MK Chin, Chad Murphy and Jinyu Hu. Additionally, I value the friendship

and intellect of Abhinav Gupta, Kisha Lashley and Sungwon Min. I’ll treasure the times

we spent in class together, studying for candidacy, grabbing coffee, and just enjoying life

together—they are wonderful friends and I look forward to seeing them build their

careers as the fabulous scholars they are.

Next, I want to thank my family for their support and encouragement. I especially

thank Robert Richens, Marja Richens, Roy Richens and Michele Richens for always

encouraging me to rise above the rest and pursue my dreams. I’m grateful for their

inspiration. And to my better half, Ronald Stites – thank you, thank you, thank you. You

understand me in a way no one else does. Because we both pursued our Ph.Ds. at the

same time, you have understood the craziness of the Ph.D. journey and, most importantly,

have stood by me, cheering me on, every single step of the way. There is absolutely no

way I could have done this without you. You are my best friend and the most sacrificial

person I’ve ever met. You are a phenomenal husband and father, and I am so proud of

you – I know it was never easy for either of us, but we did it together!

And, finally, to the most inspiring person I know: my dearest daughter, Hannah

Stites. You have taught me more in two short years than any academic program could

teach in a lifetime. But, most importantly, you’ve reminded me time and again that you

can persevere through anything, and your triumphs remind me that nothing is too

difficult. Your smile and giggles help me to remember what’s truly important in life. I’m

so blessed to be your mom and to watch you grow and learn every day.

Soli Deo Gloria.

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Financial Acknowledgments

This research has been made possible by the following:

This project was supported by a Page Legacy Scholar Grant from The Arthur W.

Page Center at the Penn State College of Communications under the Page Legacy

Scholar Grant. Any opinions, findings, and conclusions or recommendations

expressed in this material are those of the author(s) and do not necessarily reflect

the views of The Pennsylvania State University.

This project was supported in part by grants from the Smeal College of Business.

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Chapter 1

Introduction

Corporate Social and Environmental Responsibility (CSER) generally describes the

movement within businesses to be responsive to stakeholders by managing economic, social and

environmental issues, and thus to address the triple bottom line (Elkington, 1997; Montiel, 2008).

In today’s business world, the idea that firms have stakeholders is not only commonplace

(Donaldson & Preston, 1995), but has also attracted considerable attention. Stakeholder theory

(Freeman, 1984; Jones & Wicks, 1999) arose in the era of Wall Street and Gordon Gekko, where

the emergence of “multinational corporations with economic powers comparable to those of

nations has brought awareness that these private-sector institutions have impacts on human lives

… and hence should … assume responsibility for the welfare of those over whom they wield

power” (Markley & Harman, 1982: 58). Although early industrialists such as John D. Rockefeller

Jr. and Henry Ford spoke of the social responsibilities of business1, it wasn’t until the 1960s when

Corporate Social and Environmental Responsibility (CSER) emerged as an important business

issue (Gavin & Maynard, 1975). In particular, CSER is defined as the collective set of socially

responsible and environmentally sustainable firm behaviors known as corporate social

responsibility (CSR) and environmental sustainability (ES), specifically “actions and policies that

take into account stakeholders’ expectations and the triple bottom line of economic, social, and

environmental performance” (Aguinis & Glavas, 2012: 934).

Though the topic of CSER was seen as important as early as the 1960s, it was (and some

would claim still is) characterized by intense debate. Economists, led by the late Milton Friedman

(1970), argued that the only responsibility of corporations is to create shareholder wealth. Others,

1The relationship among business and society and politics was noted as early as 1932 by Berle and Means.

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such as Archie Carroll (1979), argued that businesses should be responsible, not only to economic

objectives, but also legal, ethical and discretionary societal expectations. Studies have examined

both firms’ social and environmental strategies (e.g., Hunt & Auster, 1990; Russo & Fouts, 1997)

as well as their motivations for engaging in CSER (e.g., Bansal & Roth, 2000; Henriques &

Sadorsky, 1999). However, the debate has continued over time, as scholars attempt to justify the

pursuit of CSER in financial terms, that is, to make the “business case” for CSER (Dyllick &

Hockerts, 2002; Salzmann, Ionescu-Somers & Steger, 2004). For example, over the years,

numerous studies, including several meta-analyses, have examined the relationship between

CSER and financial performance (Spicer, 1978; Cochran & Wood, 1984; McGuire, Sundgren &

Schneeweis, 1988; Waddock & Graves, 1997; Margolis, Elfenbein & Walsh, 2007; Margolis &

Walsh, 2003; Orlitzky, Schmidt & Rynes, 2003). However, this empirical work connecting CSER

and important firm outcomes has often been inconclusive. In fact, Barnett (2007) claims that

“after more than thirty years of research, we cannot clearly conclude whether a one-dollar

investment in social initiatives returns more or less than one dollar in benefit to the shareholder”

(p. 794).

Scholars have offered various reasons for the conflicting findings (Barnett, 2007),

including a lack of theory (Ullmann, 1985), methodological differences in operationalization

(Carroll, 1991; Wood & Jones, 1995; Griffin & Mahon, 1997) and failure to control for important

variables (Cochran & Wood, 1984; McWilliams & Siegel, 2001). The lack of conclusive findings

about whether or not it pays to be socially and environmentally responsible has led researchers to

consider the conditions under which social and environmental responsibility might pose a

competitive advantage for firms (Porter & van der Linde, 1995; Shrivastava, 1995). Research

along these lines has shown that investment in CSER activities can improve firms’ resource

acquisition (Hall, 1992; Rindova & Fombrun, 1999), attract increased investment from

institutional investors (Graves & Waddock, 1994), lower costs through waste elimination

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(Schmidheiny, 1992), influence consumer purchasing decisions (Brown & Dacin, 1997;

Vandermerwe & Oliff, 1990), enhance ability to attract and retain a quality workforce (Turban &

Greening, 1996; Greening & Turban, 1997; Maignan, Ferrell & Hult, 1999; Albinger & Freeman,

2000; Backhaus, Stone & Heiner, 2002; Cable & Graham, 2000), increase financial performance

(Johnson & Greening, 1999; Klassen & McLaughlin, 1996), and improve firms’ general

reputations (Brammer & Pavelin, 2006a; Fombrun & Shanley, 1990; Melo & Garrido-Morgado,

2012).

Reputation

Firm reputation is a particularly important strategic resource for firms because of its

inimitability (Flanagan & O’Shaughnessy, 2005; Roberts & Dowling, 2002; Barney, 1991).

Reputation is defined in terms of collective judgments made by stakeholders (Fombrun &

Shanley, 1990). However, researchers have begun to consider reputation as a multidimensional

construct (Lange, Lee & Dai, 2011), meaning that firms can have both general (i.e., overall

reputations) as well as specific reputations (i.e., reputation based on a given dimension of

corporate activity). General reputation is “a perceptual representation of a company’s past actions

and future prospects that describes the firm’s overall appeal” (Fombrun, 1996: 72), whereas

specific reputation “emphasizes that firms have reputations about specific attributes with

particular stakeholder groups, based on past actions of a given type” (Rindova & Martins, 2012:

20).

Reputation, both in its general and specific forms, is referred to as a “social approval

asset” because its value is derived “from favorable collective perceptions” (Pfarrer, Pollock &

Rindova, 2010: 1131) in the eyes of stakeholders. Stakeholders are generally defined as actors

who can affect or be affected by firm actions (Freeman, 1984), and typically include “customers,

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suppliers, employees, local communities, governments and shareholders” (Berman, Wicks, Kotha

& Jones, 1999: 491). Stakeholder perceptions are important because they have the potential to

influence market transactions (Riordan, Gatewood & Bill, 1997). For example, “favorable

stakeholder impressions are valuable to firms because they increase stakeholders’ willingness to

exchange resources with them … increase prices to consumers … provide a cushion for firms to

recover from crises … create mobility barriers within an industry … and have other direct and

indirect effects on firms’ profitability” (Basdeo, Smith, Grimm, Rindova & Derfus, 2006: 1206).

In other words, when stakeholders view firm behavior favorably, a myriad of benefits may accrue

to the firm (Boyd, Bergh & Ketchen, 2010). However, research has yet to empirically examine

the similarities and differences in the formation of firms’ general and specific reputations. In

particular, given that both general and specific reputations are rooted in firms’ previous behavior,

it follows that the role of history should be empirically examined. However, research on the firm-

stakeholder interface has been generally ahistorical (Lamberg, Pajunun, Parvinen & Savage,

2008).

History

As noted in their definitions, both general and specific conceptualizations of reputation

are based on “past actions”. Hence, stakeholder evaluations of firm reputation are based, at least

in part, on the firm’s history, making them potentially path dependent, as path dependence theory

suggests that a firm’s history imposes constraints on its future, limiting deviation from past

practices (David, 1985; Arthur, 1989; 1994; Garud & Karnoe, 2001; Lamberg et al., 2008;

Sydow, Schreyogg & Koch, 2009). The idea behind path dependence is that early conditions

predispose a firm to a certain pattern of behavior, setting the stage for future behavior and

interpretations of that behavior (Lamberg et al., 2008). Thus, integrating path dependence into the

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study of stakeholder perceptions provides an opportunity to understand how historical conditions

form a starting point (Lamberg et al., 2008) by providing stakeholders “a lens through which to

interpret subsequent cues” (Mishina, Block & Mannor, 2012: 464). However, even though a

firm’s reputation is anchored on its past actions, and is potentially bound to them, the provision of

new information may lead stakeholders to question their judgments about firms (Lange et al.,

2011: 154). Hence, though reputation is commonly conceptualized as a “sticky” phenomenon

(Schultz, Mouritsen & Gabrielsen, 2001: 25; Fombrun & Van Riel, 2004), as a collection of

stakeholder perceptions it can also change as new information becomes available to stakeholders

(Lange et al., 2011), resulting in a reputational ebb and flow (Love & Kraatz, 2009). Further,

although research has focused a great deal on the consequences of reputation (Barnett & Pollock,

2012), scholars “still know relatively little about … how such judgments might be adjusted in

light of new information” (Mishina, Block & Mannor, 2012: 459).

Signaling

Despite the importance of history as a predominant element of reputation, research has

shown that firms (and/or other organizations) can build or enhance firm reputations via signaling

within contexts characterized by information asymmetry (Basdeo et al., 2006; Connelly, Certo,

Ireland & Reutzel, 2011), which refers to a situation where “different people know different

things” (Stiglitz, 2002: 469). According to signaling theory (Spence, 1973; 1974), stakeholders,

lacking perfect information about firms, form opinions and perceptions on the basis of signals

(Kotha, Rjgopal & Rindova, 2001) or pieces of information transmitted by various parties

(Herbig, 1996). These signals are intended to reduce uncertainty and asymmetric information, and

improve corporate reputation in the eyes of stakeholders, making signaling a way for firms (or

other organizations) to communicate information about firms’ actions that may otherwise go

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unnoticed. Additionally, these signals may indicate a firm’s deviation from its historical stance.

Thus, in addition to path dependence, a firm’s “reputation is determined by the signals that

publics receive concerning its behaviors, whether directly from the firm or via other information

channels” (Brammer & Pavelin, 2006a: 437). Signals may originate from various sources, such as

firms themselves, firm partnerships, third parties and infomediaries. However, questions remain

regarding the relative efficacy of these signals in shaping reputation, their effects on firms with

differing histories, and whether they impact general versus specific reputations in the same way.

Research Questions

In this study, these research opportunities are addressed by examining how various

signals moderate the relationship between history and both general and specific reputation. In

particular, because CSER is a critical reputational context for firms (Mahon, 2002), and

stakeholders ranging from NGOs to customers are increasing their scrutiny of firms’ social and

environmental practices (Greening & Gray, 1994), it examines how CSER history relates to both

overall and CSER-specific reputation. Further, to investigate their impacts on the relationship

between history and reputation, it examines signals sent from four different sources: firms, firm

partnerships, third parties and the media. Therefore, the purpose of this study is to examine the

reputational consequences of social and environmental signaling. This dissertation is guided by

the following research questions:

(1) How do CSER signals influence the relationship between CSER history and

reputation? Are the effects the same for general and CSER-specific firm reputation?

(2) Are there differences in the effectiveness of signals sent by firms, firm partnerships,

third parties and the media? If so, how does the effectiveness differ?

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Dissertation Overview

Chapter 2 examines the theoretical background for this study, including the role of

history and signaling with regard to firm reputation. Next, in Chapter 3, hypotheses about how

signals sent by firms, firm partnerships, third parties and the media may moderate the relationship

between a firm’s CSER history and its general and CSER-specific reputation are developed.

Subsequently, Chapter 4, describes the methodology used to address the study’s research

objectives, including the sample, variables and the analyses used for hypothesis testing. The

results of the study are presented in Chapter 5, followed by a discussion of the contributions,

limitations and future research directions in Chapter 6. Practical implications of the study are

considered in Chapter 7.

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Chapter 2

Theoretical Background

The Stakeholder Perspective

Stakeholder theory, developed by Freeman (1984), was proffered as an alternative to the

predominant view of the 1980s “that social well-being is maximized when shareholder wealth is

maximized” (Laplume, Sonpar & Litz, 2008). Counter to economists who argue that “there is one

and only one social responsibility of business--to use its resources and engage in activities

designed to increase its profits” (Friedman, 1970: 126), stakeholder theorists argue that

stakeholder relations form the bridge between organizations and society, making their

management crucial (Hinings and Greenwood, 2003). Much of stakeholder theory has been

focused on three main avenues of research: descriptive, normative and instrumental (Donaldson

& Preston, 1995). Whereas descriptive stakeholder theory focuses on the state of stakeholder

management, as well as the way managers think about stakeholders, normative stakeholder theory

examines the notion that each group of stakeholders has intrinsic value and warrants

consideration by the firm, and instrumental stakeholder theory links stakeholder management

with the attainment of important firm objectives, such as financial performance.

Much of instrumental stakeholder research has focused on whether there is a relationship

between CSER and financial performance (c.f., Cochran & Wood, 1984; Margolis & Walsh,

2003; Orlitzky, Schmidt & Rynes, 2003). However, extant research reveals mixed findings as to

whether or not CSER efforts actually pay off (Orlitzky, Schmidt & Rynes, 2003), leaving open

the question of why firms engage in CSER initiatives, and what they hope to gain from them.

Hence, research has shifted towards understanding the conditions under which stakeholder

relations might be positively related to financial performance, or other important firm outcomes,

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such as reputation (Barnett & Salomon, 2012). Recently, although researchers have begun to

show how a firm’s previous reputation may insulate it from repercussions of negative events,

such as product recalls (e.g., Rhee & Haunschild, 2006) and financial restatements (e.g., Janney

& Gove, 2011), most research on CSER and stakeholder relations generally focuses on a firm’s

current actions, neglecting the historical context in which those actions are situated. For example,

studies have shown a strong positive relationship between corporate philanthropy and corporate

reputation (e.g., Brammer & Millington, 2005), without considering the historical context in

which donations are made. Realistically, however, firm-stakeholder relationships are not static

and do not exist in a vacuum, but evolve from the past, to the present, and into the future (Zietsma

& Winn, 2008; Mosakowski & Earley, 2000). Thus, it follows that CSER history should be

included in the study of how stakeholders form judgments about firms’ reputations.

CSER History

Stakeholder views of firms depend on their knowledge of the firm, including its past

behavior. In particular, stakeholders make judgments of a firm’s character with respect to

“behavioral tendencies based on observations of its prior actions” (Mishina, Block & Mannor,

2012: 460). As mentioned in Chapter 1, the idea behind path dependence is that early conditions

predispose a firm to a certain pattern of behavior (Lamberg et al, 2008), which in turn constrains

its future choices by providing a starting point from which further actions and interpretations are

grounded. Extending this view, stakeholders interpret information about firms through the lens of

their past behavior (Mishina et al., 2012; Barnett & Pollock, 2012), which serves as a base for

interpretation of additional CSER involvement. Stakeholders, then, have differing expectations of

firms based on their track records, and as a result, interpret subsequent actions in light of this

historical context. Hence, “the actions of a firm and the responses by its stakeholders in regard to

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CS[E]R are path dependent such that different firms obtain different results from CS[E]R,

depending on their unique histories” (Barnett, 2007: 803). For example, Barnett (2007) poses the

following scenario:

Consider your reaction were Union Carbide to announce a $10 million donation to community hospitals in Bhopal, India, or were Exxon to announce a $10 million donation to improve wildlife habitats along the Alaskan coast. Now consider your reaction were Ben & Jerry’s to do either of the above (p. 808).

This scenario exemplifies how stakeholder judgments about new information depend on

CSER history, which is defined as a firm’s record of past social and environmental actions. For

example, Union Carbide suffered hugely negative reputational consequences in late 1984 when a

gas leak at one of the firm’s plants in Bhopal, India killed thousands of people (Lapierre & Moro,

2002). In another disaster, in 1989, the Exxon Valdez oil barge spilled hundreds of thousands of

barrels of oil into the Prince William Sound (Leacock, 2005). Because of their history,

information about these firms’ philanthropy, a facet of CSER, is interpreted differently from

information about Ben & Jerry’s, a well-known and socially- and environmentally-progressive ice

cream producer. In particular, because Union Carbide and Exxon both have a negative CSER

history, stakeholders would likely be skeptical, reacting unfavorably to CSER announcements,

like the one above, whereas, because of Ben & Jerry’s history, stakeholders would likely have a

more favorable response and, in fact, expect continued positive CSER performance. Thus,

differences in firms’ past histories of social and environmental actions are expected to influence

how stakeholders react to the firms’ current signaling of CSER actions.

Though Barnett and Salomon (2012) examined how the path dependent nature of

stakeholder relations affected the relationship between corporate social performance and financial

performance, finding that a firm’s CSER history affects its financial performance, research has

yet to explore the impact of CSER history on other key corporate assets, such as firm reputation.

This, however, is an important avenue for research as scholars are looking for explanations as to

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why the same CSER efforts can result in different reputational evaluations for firms. In particular,

path dependence suggests that a firm’s past CSER actions are likely to have an impact on how

stakeholders interpret subsequent social and environmental communications, or signals, as shown

in the Union Carbide, Exxon and Ben & Jerry’s example. However, although the path dependent

nature of CSER history predisposes stakeholders to have preconceived notions about firms’

subsequent CSER actions, signaling may provide an avenue of “path creation” (Garud & Karnoe,

2001: 2) for firms by enabling them to overcome reputational deficits.

Signaling

Signaling theory suggests that signals, or cues, can be used to reduce information

asymmetry in situations where the parties involved have access to different information (Stiglitz,

2002), such as in the case where educational credentials serve to communicate a candidate’s job

suitability to corporate recruiters (Spence, 1973; 1974). Similarly, because stakeholders exist in a

state of information asymmetry (Basdeo et al., 2006), lacking perfect information about firms’

qualities, they look for signals, or cues, to interpret and judge firm behavior and reduce

uncertainty (Connelly et al., 2011). For example, some previously studied signals include

affiliations with prominent others which signals legitimacy (Baum & Oliver, 1991), initial public

offerings (IPO) characteristics which signal a firm’s attractiveness as an alliance partner (Pollock

& Gulati, 2007), and market reactions which signal profitability (Fombrun & Shanley, 1990).

With regard to CSER, however, much of the extant research regarding firms’ CSER

efforts implicitly assumes that stakeholders are aware of the firm’s activities (Du, Bhattacharya &

Sen, 2010), ignoring communication, which “remains the missing link in the practice of corporate

responsibility” (Dawkins, 2004: 108). Signals serve to reduce uncertainty and asymmetric

information by communicating information about firm actions that may otherwise go unnoticed

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or be publicly unavailable. This is particularly relevant with regard to CSER as firms attempt to

become more socially and environmentally responsive via actions that, though requiring costly

investments, are often unobservable to external stakeholders. Thus, CSER actions are signaled via

the communication of social and environmental progress to stakeholders (Toms, 2002;

Hasseldine, Salama & Toms, 2005) where signaling can be regarded as “a piece of information”

(Herbig, 1996: 37) about a firm’s social and environmental activities.

For example, price is a piece of information that acts as a signal of underlying quality

(Shapiro, 1983). Because producing a quality product is likely more costly than producing an

inferior one, high quality producers ratchet up the price to recoup their initial investment and

enhance profitability (Kirmani & Rao, 2000). Thus, in this case, a signal is an indicator of an

underlying firm’s action or characteristic, such as quality, which is costly to develop. According

to signaling theory, entities will only send signals when they are likely to increase payoff

(Connelly et al., 2011) as is the case with high quality firms that charge a premium price to signal

underlying quality. Further, following the tenets of signaling theory, low quality entities are

unlikely to charge a higher price (i.e., send a deceptive signal) because of the threat of

reputational and financial backlash facing the entity if its actual level of quality was revealed

(Rao, Qu & Ruekert, 1999).

CSER signals are important for firms because “stakeholders are influential as they can

either give support in terms of purchasing habits, showing loyalty and praising the company, or

they can show opposition in terms of demonstrating, striking, or boycotting the company”

(Morsing & Schultz, 2006: 327). Building from the proposition that a firm’s “reputation is

determined by the signals that publics receive concerning its behaviors, whether directly from the

firm or via other information channels” (Brammer & Pavelin, 2006a), it makes sense to explore

the implications of various signals that firms and other organizations send about firm behavior. In

fact, a firm’s CSER history is also a signal, as it is a piece of information that informs

13

stakeholders about how the firm has previously addressed social and environmental issues.

However, given the path dependent nature of history, firms may use signaling in an attempt to

break free from path dependent behavior by providing stakeholders with new information about

CSER actions in an attempt to “convey positive organizational attributes” (Connelly et al., 2011:

44).

Sources of CSER Signals

In addition to history, additional signals can be sent from a variety of sources, including

firms themselves (e.g., Akerlof, 1970; Shapiro, 1983), firm relationships (e.g., Baum & Oliver,

1991; Gulati & Higgins, 2003), such as partnerships, and infomediaries- including third parties

and the media (e.g., Deephouse & Heugens, 2009, Rao, 1994; Wade, Porac, Pollock & Graffin,

2006). Whereas firms inform their stakeholders about their own CSER efforts, they also signal

firm characteristics through their partnerships with other organizations (such as NGOS).

Additionally, infomediaries also send signals about a firm’s CSER activities, catering to their

own stakeholders by providing information “about otherwise unobservable characteristics of the

organization” (Riordan et al., 1997: 402).

Firms Themselves

Despite the belief that a firm “must inform stakeholders about its good intentions,

decisions and actions to ensure positive stakeholder support” (Morsing & Schultz, 2006: 327),

few studies actually examine how firms convey information about their CSER activities to others.

Nonetheless, for signals to have an impact on stakeholder perceptions, they must be

communicated to stakeholders. In other words, stakeholders must be able to acquire information

14

about the firm in order to form an impression of it (Eisenegger & Schranz, 2011). Thus, firm

communication is “missing link in the practice of corporate responsibility” that “is essential if

companies are to break through the communications barrier and capitalize on the potential

reputational benefits of corporate responsibility” (Dawkins, 2004: 108-109). This is an important

area of research for reputation as it moves past studies that are primarily concerned with

reputation as a passive by-product of firm performance, and instead considers the agency firms

have in constructing stakeholder perceptions.

An emerging area of research has to do with how firms use communication to influence

stakeholder impressions, and hence, reputation (Whittington & Yakis-Douglas, 2012). By

viewing firms as “social actors” (King, Felin & Whetten, 2010) with “self-presentation goals”

(Highhouse, Brooks & Gregarus, 2009), it follows that firms can use signals to attempt to

“strategically manipulate the images they project to gain favor with constituents” (Fombrun,

1996: 386) via the “deliberate and discretionary use of communications” (Whittington & Yakis-

Douglas, 2012: 404). In line with signaling theory (Spence, 1973; 1974), because stakeholders do

not have perfect information about firms, they rely on firm communications to understand

corporate strategy and action. As a result, “corporate communications help shape collective

perceptions and therefore contribute to building and/or sustaining social approval assets within

organizations” (Angwin, Meadows & Yakis-Douglas, 2011: 1). For example, CEO charismatic

language has been found to influence security analyst recommendations because charisma acts as

a signal for shareholder wealth (Fanelli, Misangyi & Tosi, 2009). Thus, firms can take an active

role in helping stakeholders to form favorable impressions by signaling positive firm attributes

via firm communications (Highhouse et al., 2009).

In sum, a firm’s communications send signals on which stakeholders base their

judgments and “are central to the reputational question of how stakeholders regard a firm’s

potential to deliver value” (Whittington & Yakis-Douglas, 2012: 402). Further, because “creating

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stakeholder awareness of and managing stakeholder attributions towards a company’s CS[E]R

activities are key prerequisites for reaping CS[E]R’s strategic benefits, it is imperative for

managers to have a deeper understanding of key issues related to CS[E]R communication” (Du et

al., 2010: 9). However, firms can also send signals in other ways, such as through the partnerships

they form with other key players.

Firm Partnerships

Firms can also send signals about their involvement in CSER by forming associations

and partnerships, or alliances, with other organizations. These interorganizational ties serve

several purposes including reducing uncertainty about the organizations involved (Stuart, Hoang

& Hybels, 1999; Podolny, 1994) as well as increasing their legitimacy (Brown, 2008; Suchman,

1995). For example, with regard to initial public offering (IPO), a firm’s ties to venture capitalists

can serve as a signal of firm quality, which can impact the IPO’s success (Gulati & Higgins,

2003). Though, in general, partnerships occur among business entities, CSER partnerships are

generally “public-private”, or even “cross-sector” partnerships, which are designed to merge

public- and private-sector resources to address problems at the institutional field level that create

uncertainty for firms (Gray, 1989; Lepoutre, Dentchey & Heene, 2007). There has been a

tremendous increase in the use of these kinds of partnerships to meet CSER initiatives, ranging

from “alliances between businesses and NGOs, to networks of small rural farmers working with

micro-financiers, to government-led efforts to manage natural resources or design transportation

infrastructure, to industry-level, norm-setting bodies designed as substitutes for government

intervention” (Gray & Stites, 2013: 11). Many of these are targeted toward improving the firm’s

sustainability efforts (Gray & Stites, 2013). By engaging in CSER-oriented partnerships, firms

signal (or alert stakeholders) that they are taking their social and environmental responsibilities

16

seriously, while simultaneously gaining important expert insight from the partnering

organizations (Rondinelli & London, 2003; Selsky & Parker, 2005; Yaziji & Doh, 2009). Thus, a

firm’s social and environmental responsiveness can also be signaled by its association with

CSER-oriented organizations.

A second purpose of engaging in CSER alliances is “reputation-borrowing” (Petkova,

2012), by basking in the glory (Cialdini, 1989) of the partner’s proclivity for CSER. For example,

in the context of new entrepreneurial firms, reputation-borrowing is beneficial “because through

their decision to affiliate with the new firm, prestigious third parties signal to more distant

stakeholders the worthiness, quality, and potential of the new firm” (Petkova, 2012: 385). By

analogy, “participation in socially responsible organizations distances the firm from any alleged

deviance” (Laufer, 2003: 257). These partnerships and associations can furnish a unique level of

credibility as firms are unlikely to risk being associated with an illegitimate partner because of the

threat of delegitimation (Baur & Schmitz, 2012). For example, a 2003 public survey by

GlobeScan indicated that more than 66% of people claimed that their respect for any company

would increase “if it partnered with an NGO to help solve social problems” (Austin & Seitanidi,

2012: 730). Additionally, by partnering with potential enemies, such as environmental NGOs

(i.e., ENGOs), firms may be able to stave off threats of anti-corporate campaigns. For example,

by partnering with Global Exchange, a human rights NGO, Starbucks was able to address the

NGO’s concerns and improve its CSER while bolstering its image (Argenti, 2004). Similarly, by

partnering with organizations that are more CSER-oriented, firms have the opportunity to gain

new knowledge and points of view useful for improving CSER and expanding capabilities by

leveraging each partner’s strengths (Sagaw & Segal, 2000; LeBer & Branzei, 2010). For example,

through a partnership with the Environmental Defense Fund, focused on implementing various

environmental initiatives, “McDonalds has benefitted through both lower disposal, packaging and

building costs as well as a more positive environmental image” (Hartman & Stafford, 1997: 185).

17

Thus, firm CSER partnerships and associations serve as a signal of a firm’s commitment to

CSER. In addition to these firm partnerships, third parties themselves may also send signals

regarding a firm’s CSER.

Third Parties

Research has shown that third-party recognition of firms has resulted in increased

legitimacy, survival and performance in situations of uncertainty (Rao, 1994; Wade et al., 2006;

Doh, Howton, Howton & Siegel, 2010). A third party refers to an entity that is separate from the

focal entity. Hence, third-party-CSER signals refer to messages sent by an entity separate from

the firm regarding the focal firm’s social and environmental activities. Stemming from

stakeholders’ increasing skepticism of firm-sent communications, a variety of entities supplying

information concerning firms’ social and environmental activities have emerged to reduce the

asymmetry in information available to firms and stakeholders regarding social and environmental

performance (Doh et al., 2010). These organizations often create value for themselves by rating

firms’ CSER efforts and advertising the ratings, or bestowing awards on top performers, catering

to stakeholders who have begun to lean “toward third-party assessments for guidance regarding

companies’ environmental performance (Amato & Amato, 2012: 322). Whereas firms are

generally thought to act in their own self-interest, third parties are considered more objective

(Pomering, 2011), making their assessments more credible (Rhee & Valdez, 2009; Pollock &

Gulati, 2007; Morsing & Schultz, 2006). Though third parties have agendas of their own, because

they are, by definition, separate from the focal entity, and hence an independent source, they lend

legitimacy to those organizations they recognize as good social and environmental corporate

citizens. This “associational legitimacy” (Brown, 2008) reduces uncertainty about the firm and

enhances stakeholder impressions (Dean & Biswas, 2001). For example, in the auto industry,

18

third-party certification contests were found to increase the legitimacy and success of auto makers

(Rao, 1994). In fact, third-party recognition is often compared to having an external audit of

financial reporting (Pomering, 2011). Thus, third-party recognition serves as an objective signal

of a firm’s commitment to CSER.

Media

The media also provide information to stakeholders which may signal characteristics of

the firm’s investment in CSER. As important disseminators of information, “the media frame

stories and influence stakeholders’ perceptions about firms through their use of positive or

negative language” (Zavylova, Pfarrer, Reger & Shapiro, 2012: 1086). However, while

disseminating information, the media also spin it, “framing events and issues in positive or

negative terms”, which “provides audiences with visible public expressions of approval or

disapproval of firms and their actions” (Pollock & Rindova, 2003: 634). In particular, “the media

magnify a company’s actions for other stakeholders, and so influence how they come to regard a

company” (Fombrun, Gardberg & Barnett, 2000: 94). Though there is a “widely observed

positivity bias in the business press” (Zavylova et al., 2012: 1089), some research has found that

the media is more likely to cover CSER crises concerning companies with a positive history since

stories are more interesting to media consumers (Luo, Meier & Oberholzer-Gee, 2012). Thus, the

media provide information about firms’ CSER activities that stakeholders may use to form

impressions of their commitment, or lack thereof, to CSER.

In sum, firms, firm relationships, third parties and the media have been described as four

sources of CSER signals. These signals can help firms to build legitimacy, which refers to “social

acceptance resulting from adherence to regulative, normative, or cognitive norms and

expectations” (Deephouse & Carter, 2000: 332). Legitimacy is important for firms’ survival and

19

access to critical resources (Pfeffer & Salancik, 1978), and can provide a buffer in the event of a

crises, helping firms “to protect and decouple the illegitimate activity from the rest of the

organization and serve to reassure organizational constituents that the incident is out of the

ordinary” (Bansal & Clelland, 2004: 95). Further, by appearing legitimate, firms reduce the need

for monitoring (Meyer & Rowan, 1977) and have lower variability in stock prices associated with

unsystematic risk (Bansal & Clelland, 2004). Moreover, because “legitimacy is a necessary—but

not always sufficient—condition for the attainment of positive reputation” (Doh et al., 2010:

1466), these signals serve to communicate firms’ CSER activities, and garner social acceptance.

However, the extent to which these signals may influence firm reputation is likely to depend on

the credibility of the signal’s source.

Source Credibility

Whether signals are sent by firms, firm partnerships, third parties or the media, the

impression they leave on a stakeholder will depend on the source’s perceived credibility, which

“is an important factor in any impression management process and will have a significant impact

on its effectiveness” (Aerts & Cormier, 2009: 4). Source credibility is defined as the extent to

which the party or medium disclosing the information in question is “perceived as possessing

expertise relevant to the communication topic and can be trusted to give an objective opinion on

the subject” (Goldsmith, Lafferty & Newell, 2000: 43, emphasis in original), where “a highly

credible source is commonly found to induce more persuasion” (Pornpitakpan, 2004: 244).

Sources may be perceived as more or less credible origins of information regarding corporate

activities (Kiousis, 2001) because of the underlying interests of the signalers. For example,

research has shown that self-interested sources (i.e., those having a conflict of interest) are less

credible (Hovland & Weiss, 1951) than sources that aren’t in a position to directly benefit from

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the signal. With regard to CSER communication and signaling, the firm itself, firm partnerships,

third parties and the media each differ in their level of source credibility.

Firm-sent signals refer to messages sent by the focal company to convey information

regarding its activities. The primary CSER signal that firms send is social and environmental

disclosure (Michelon, 2011; Gray, Houhy & Lavers, 1995), which is aimed at providing

information in an effort to satisfy stakeholder needs (Gelb & Strawser, 2001; Wood, 1991) and to

reduce information asymmetry between firms and stakeholders (Brammer & Pavelin, 2006b). In

terms of CSER, firm self-disclosure is defined as “timely provision of relevant information that

results in a transparent and accurate picture of corporate operations, financial performance, and

governance” (Dawkins & Fraas, 2008: 2). However, firm-sent signals are likely to have a low

level of perceived credibility because the firm may see a direct benefit of positive CSER

communication without bearing any confirmed cost. Though decoupling signals from action

would be an irrational move for firms under the tenets of signaling theory, stakeholders are

nonetheless cynical regarding firm-sent communication because of its potential to be self-serving

(Mendleson & Polonsky, 1995). Thus, firm self-disclosure has low source credibility.

Though firm relationships are considered a firm-sent signal when such relationships are

advertised by the focal firm, they are more likely a hybrid between firm-sent and third-party-sent

signals, because, by affiliating with social and environmental organizations, firms can “borrow”

credibility from the partnering organization (Petkova, 2012; Crane, 1998). Further, as “ties to

prominent actors mitigate uncertainty” (Gulati & Higgins, 2003: 129), such affiliations suggest

that the firm’s CSER actions are credible. On the other hand, signals sent wholly by third parties,

are likely to be more credible than firm-sent or firm-relationship-sent signals because the

signaling organization is completely separate from the focal firm and presumably unbeholden to

it, thereby reducing the possibility of a conflict of interest. In fact, research has found third-party-

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sent-CSER signals, such as “claims made by environmental groups to be four times as credible as

those of manufacturers” (Mendleson & Polonsky, 1995: 10).

News media provide another source of CSER signals and serve as a particularly

important influence on public opinions (Kotha, Pajgopal & Rindova, 2001: 574), including “the

way stakeholders interpret and evaluate information about firms” (Pollock & Rindova, 2003:

631). In particular, “the media report the evaluations of other information intermediaries and

provide a consolidated source of information for stakeholders … that reduces stakeholders’

uncertainty about a firm’s characteristics” (Deephouse, 2000: 1098). Though the perceived

credibility of news media is likely to depend on the type of news (Rimmer & Weaver, 1987), and

media also often lean right or left on politically-charged issues (Zoch & Molleda, 2006;

McCombs & Shaw, 1972), research has shown that “it is media-provided, rather than company-

provided, information that has the credibility and/or reach necessary to influence stakeholders”

(Pollock & Rindova, 2003: 640). Because firm-, third-party- and media-sent signals have

differing levels of credibility, they are likely to have different implications for firms’ reputations.

Reputation

The preceding discussion emphasizes that signals from various sources, including the

firm itself, firm relationships, third parties and the media can provide information about otherwise

unobservable firm attributes. Stakeholders then use this information to form reputational beliefs

about firms (Fombrun, 1996). The signaling perspective highlights that though reputation is

“possessed by an organization […] it must be granted by external audiences on an ongoing basis”

(Love & Kraatz, 2009: 314, emphasis in original). This is a particularly important point because

firms often face diverse groups of stakeholders with diverse interests (Pratt & Foreman, 2000).

Thus, perceptions about reputation will not be unanimous across these groups. In fact, a limitation

22

of previous research is that it has tended to assume that stakeholders are all alike, when in fact

each stakeholder group “selectively attends to different informational cues, or signals” (Fombrun

& Shanley, 1990: 234), which means that stakeholders, such as “employees, customers, business

partners, and the general public have differing needs from, and relationships with, companies

such that their views of the same company will differ substantially” (Dowling & Gardberg, 2012:

40). Though a firm’s reputation is increasingly conceived of as multidimensional, researchers

have yet to conclude whether signals have equivalent effects on both general and specific firm

reputations.

Further, because reputation is built on history, much is to be gained by taking a more

nuanced view of reputation repair. Whereas reputation repair following discrete events has

garnered considerable attention by researchers (Rhee & Kim, 2012; Elsbach, 2012; Dukerich &

Carter, 2000; Elsbach & Kramer, 1996), less attention has been devoted to understanding whether

firms can repair poor reputation that stems from more longitudinal deficits. Some of these deficits

may arise from the very nature of the firm’s business. For example, firms that chiefly operate on

the basis of natural resource extraction are likely to have historical deficits in regards to CSER.

Thus, firms that have marred CSER histories because they are operating from a longitudinal

deficit, are likely to signal in an attempt to influence stakeholder perceptions, “which are key to

regaining the confidence of the public and other key stakeholders” (Dukerich & Carter, 2000: 98).

Thus, CSER signaling is likely to have reputational consequences for firms, dependent on the

focal firm’s track record of CSER and the sources of signals sent. However, though research has

shown that CSER may be related to general corporate reputation (Brammer & Pavelin, 2006a;

Fombrun & Shanley, 1990; Janney & Gove, 2011; Melo & Garrido-Morgado, 2012), it is unclear

whether the reputational consequences of CSER signaling are multidimensional in nature.

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Chapter 3

Hypotheses

As already explained in Chapter 2, stakeholder perceptions of a firm depend on a focal

firm’s social and environmental track record, known as its CSER history, such that “stakeholders

draw from their prior knowledge of a firm when they assess the implications of new information

generated by that firm's CS[E]R activities” (Barnett, 2007: 803). In other words, once a

perception of a firm is established by stakeholders on the basis of CSER, it becomes difficult to

change the nature of that relationship as stakeholders base social judgments on prior beliefs

(Mishina et al., 2012). Because of bounded rationality (Simon, 1955) and the proclivity to rely on

cognitive heuristics (Cyert & March, 1963), logics (Friedland & Alford, 1991), or frames

(Lewicki, Gray & Elliott, 2003; Dewulf, et al., 2009), it is difficult to change cognitive

associations, or perceptual filters (Starbuck & Milliken, 1988), once they are established, leading

to path dependence in how stakeholders view firm behavior. An implication of this perspective is

that two different firms within the same setting may face different stakeholder reactions towards a

single event because of the differences in the CSER history.

In as much as a firm’s reputation is defined by its past actions, the baseline assumption in

this study is that history is expected to be related to reputation. More specifically, firms with a

weak CSER history are likely to have poorer general reputations than firms with a strong CSER

history. Additionally, because CSER is an increasingly integral part of organizational legitimacy

and survival, these effects are likely to be evident for a firm’s CSER-specific reputation as well.

Building on this expected relationship between CSER history and reputation, it is hypothesized

that CSER signals sent by firms, their CSER-oriented partnerships, third parties and the media

impact general and CSER-specific firm reputation. In particular, it is hypothesized that the

24

effectiveness of signals sent by these sources is likely to depend on the source’s credibility with

the firm’s stakeholders.

Firm Self-Disclosure

In light of increased stakeholder demands for transparency regarding firm’s CSER

activities, many firms signal their social and environmental responsiveness by voluntarily

disclosing social and environmental information. One of the main ways for firms to employ

disclosure as a CSER signal to help build their reputations is by engaging in voluntary social and

environmental reporting (Toms, 2002; Hasseldine et al., 2005). Firms can do this through

publishing their own CSER reports and via the Carbon Disclosure Project (Kolk, Levy & Pinkse,

2008; Hassan & Ibrahim, 2012; Stignitzer & Prexl, 2007; Godemann & Michelsen, 2011). Such

disclosure offers a “means by which stakeholders can evaluate corporate social performance”

(Dawkins & Fraas, 2008: 2). Social and environmental reporting has become more commonplace

in recent years as “public awareness and interest in environmental and social issues and increased

media attention have led to more voluntary social disclosures from corporations” (Nikolaeva &

Bicho, 2011: 145). As such, reporting “is perceived as fulfilling a role in how companies account

for their CS[E]R, a concept that is seen to embody companies’ economic, legal, ethical and

philanthropic responsibilities towards society in general and their range of stakeholders in

particular” (Kolk, 2008: 3).

The Global Reporting Initiative (GRI), which is a nonprofit organization providing

guidance on social and environmental reporting (GRI, 2012), has “successfully become

institutionalized as the preeminent global framework for voluntary corporate environmental and

social reporting” (Levy, Brown & de Jong, 2010: 88). According to the KPMG International

Survey of Corporate Responsibility Reporting report in November 2011, 95% of the 250 largest

25

global companies report their CSER performance in some way, and 80% of those companies use

the GRI framework. The GRI reporting framework emerged from social and environmental codes

of conduct that were developed by the Coalition for Environmentally Responsible Economies

(CERES) and the United Nations Environmental Programme (UNEP) in response to the Exxon

Valdez oil spill in 1989 (CERES, 2002; Haugh & Talwar, 2010). The framework was launched in

1999 “with the goal of enhancing the quality, rigor and utility of sustainability reporting” (GRI,

2002: i). The GRI has created a common language for firms and stakeholders, by promoting and

developing “a standardized approach to reporting” (Nikolaeva & Bicho, 2011: 136). Although the

GRI is the predominant reporting schemata, not all firms use the GRI framework; however,

“regardless of specific approach, by engaging in sustainability reporting, firms signal that

sustainability has their attention” (Gehman, 2012: 41).

In addition to CSER reporting, firms may also signal their social and environmental

efforts through participation in the Carbon Disclosure Project (CDP). The CDP is a nonprofit

organization geared towards measuring environmental impact, claiming that “companies that

measure their environmental risk are better able to manage it strategically” (CDP, 2014). The

CDP solicits environmental information from firms by sending data-intensive surveys which are

then made public (Stanny, 2013). Participation is voluntary for firms, and firms can participate

even if they were not selected as a survey recipient. Hence, “by publishing reports and making

disclosures available to the public, the CDP attempts to compel firms to disclose by increasing the

benefits and/or reducing the costs of disclosing” (Stanny, 2013: 145). Further, this approach

appears to work as 81% of the 500 largest global companies by market capitalization responded

to the CDP survey in 2011 (CDP, 2011). Although firms’ motivations for disclosing CSER

activities may differ (Brown & Fraser, 2006), research from the UK suggests that, with regard to

CSER, “firms can improve reputation through making disclosures” (Toms, 2002: 278) because

26

firm self-disclosure, via the publication of CSER reports or participation in the CDP, signals a

firm’s commitment to CSER.

However, there is also a significant managerial challenge surrounding a firm’s decision to

self-disclose its CSER activities, whether via CSER reports or the CDP. In fact, some refer to this

challenge as a “double-edged sword” or “the self-promoter’s paradox” (Morsing & Schultz,

2006), where “the more companies expose their ethical and social ambitions, the more likely they

are to attract critical stakeholder attention” (Morsing & Shultz, 2006: 323; Lewis, 2003). Though

stakeholders increasingly demand information from firms regarding CSER, these same

stakeholders are also increasingly skeptical of firm self-disclosure as overall trust in corporations

has fallen because of recent corporate scandals (Waddock & Googins, 2011). In fact, whereas

firms use disclosures in an attempt to gain legitimacy, stakeholders may be skeptical of a firm’s

disclosure because such disclosures are more likely when the firm has something to hide

(Ashforth & Gibbs, 1990). In other words, “while stakeholders claim they want to know about the

good deeds of the companies they buy from or invest in, they also quickly become leery of

CS[E]R motives when companies aggressively promote CS[E]R efforts” (Du et al., 2010: 17).

In response, firms try to avoid the appearance of greenwashing (Lawrence, 1992), known

as communications that mislead stakeholders regarding sustainable behaviors (Parguel, Benoit-

Moreau & Larceneux, 2011; Laufer, 2003). Though the possibility of greenwashing exists,

signaling theory suggests that only firms having substantial investments in CSER activities will

send CSER signals. This is because firms that have made substantial investments in CSER

activities stand to benefit greatly from making stakeholders aware of their actions, whereas firms

that have not made such investments and are engaging in empty rhetoric have much to lose if and

when their empty claims are discovered. Thus, in line with signaling theory, it is presumed that

CSER signals are indicative of actual firm investment in CSER activities and that signals are sent

27

to enhance the potential return on such investments via improving stakeholder impressions and

consequently, enhancing reputation.

In fact, the effects of firm-sent signals on reputation can be predicted by role expectation

theory (Jensen, Kim & Kim, 2012), which argues that observers have high expectations of firms

with favorable performance and low expectations of firms with less favorable performance.

Similarly, path dependence theory suggests that a firm’s prior performance may differentiate the

efficacy of its signaling efforts, because observers use existing information “to determine what

the most plausible interpretation for a given cue is likely to be” (Mishina et al., 2012: 464).

Hence, the same signals may have different effects for firms whose CSER history is weak or

strong. It follows that observers expect to receive positive signals from firms with a history of

CSER strengths and are likely to interpret such signals as consistent with a favorable reputation.

However, for firms with a history of CSER weaknesses, positive firm-sent signals are likely to

trigger cognitive dissonance in observers as they are inconsistent with low expectations stemming

from poor past behavior; thus, these signals are more likely to be viewed with skepticism,

reducing (or even reversing) the positive intention of the signal.

Consequently, firm self-disclosure is likely to worsen the negative relationship between

CSER historical weaknesses and reputation because stakeholders are remarkably skeptical of

inconsistent signals; they are difficult to interpret and therefore lack credibility. Because signaling

is likely to generate skepticism and negative reputational attributions for these firms, they may be

locked into a downward reputational spiral. Thus, counterintuitively, firm self-disclosure is likely

to lower reputation for firms with a history of CSER weaknesses rather than improve it. On the

other hand, for firms with a history of CSER strengths, because firm self-disclosure conforms to

stakeholder expectations, stakeholders may discount any lack of credibility in the firm’s

disclosure, leading to an increase in the positive relationship between CSER historical strengths

and firm reputation. In other words, firm self-disclosure is expected to raise the reputation of

28

firms with histories of CSER strengths even higher. Moreover, because CSER is increasingly an

integral part of organizational legitimacy and survival, these effects are likely to be evident for

firms’ CSER-specific reputation as well as its general reputation. Therefore, the following is

hypothesized:

Hypothesis 1: Firm self-disclosure will amplify the negative effect of a firm’s history of

CSER weaknesses on its (a) general and (b) CSER-specific reputation.

Hypothesis 2: Firm self-disclosure will amplify the positive effect of a firm’s history of

CSER strengths on its (a) general and (b) CSER-specific reputation.

Firm CSER Partnerships

As firms begin to acknowledge their impacts on the societies and environment in which

they operate, they also begin to realize that they are unable to solve social and environmental

problems alone (Gray & Stites, 2013). This has led to an increase in CSER affiliations and

partnerships aimed at improving social and environmental welfare. By partnering, organizations

are able to share and leverage resources, improving learning and innovation (Lin, 2012). Further,

“by becoming part of a partnership that promotes sustainable development, companies have an

opportunity to present a ‘good global citizen’ side to their operations and may be able to bolster

their public image” (LaFrance & Lehmann, 2005: 219). Further, partners that both have positive

reputations are likely to complement one another (Baur & Schmitz, 2012) and enhance each

other’s reputations. Case studies have shown that CSER-partnerships result in positive

reputational consequences for firms (e.g., Argenti, 2004; Dahan, Doh, Oetzel & Yaziji, 2010;

Yarnold, 2007; Austin & Seitanidi, 2012; Kolk, van Dolen & Vock, 2010), and that firms can

29

distance themselves from activities that were judged deleterious to their reputation through

partnerships, as in the Kimberly Process designed to eradicate the use of conflict diamonds

(Brown, 2008). Additionally, though firm relationships are generally disclosed by all involved

parties, research suggests that the extent to which a firm advertises its relationship to CSER

organizations is likely important (Kolk et al., 2010). However, these propositions have yet to be

empirically tested.

In as much as firm relationships, by definition, include the firm’s association with

another party, the firm may borrow reputation (Petkova, 2012) from that party. Hence, a firm’s

social and environmental responsiveness can also be signaled by the extent to which it is

associated with CSER-oriented organizations. For example, the World Business Council for

Sustainable Development (WBCSD), is a prestigious organization for which membership

indicates that firms meet a threshold of CS[E]R activities, because for firms “to get into these

organizations, to be accepted or to try to reach a hurdle, it is in fact a hurdle, you are

demonstrating that you are already at a certain level of sustainability practices […] to even be

considered to be a part of these” (Stites & Gray, 2012:20). Thus, by partnering and associating

with these organizations, firms can engage in “reputation-borrowing” (Petkova, 2012). Such

relationships are likely to be viewed as more credible than wholly firm-sent signals because they

are tied to an additional entity, which has its own reputation on the line when it partners or

associates with other organizations. Further, because firm relationships are interorganizational

ties, and the focal firm borrows reputation from the partnering or associating organization(s) they

are likely to have positive reputational effects for all firms, regardless of CSER history. Thus,

because firm relationships signal to stakeholders that the firm’s CSER is credible, it is

hypothesized that they should therefore improve stakeholder impressions and consequently, firm

reputation, for all firms who participate in them.

30

Hypothesis 3: Firms that advertise their CSER partnerships will have more positive (a)

overall and (b) CSER-specific reputation, regardless of CSER history.

Third-Party-CSER Awards

As hypothesized previously, firm reputations depend on historical actions, which temper

the efficacy of firm-sent signals. Therefore, firms with lackluster CSER histories are not likely to

benefit from firm-based signaling because stakeholders will view such signals with skepticism as

they are perceived to lack credibility. However, stakeholders may be more receptive to highly

credible third-party-sent signals (Rhee & Valdez, 2009; Pollock & Gulati, 2007), as they are

thought to represent a “true image of corporate initiatives such as CS[E]R” (Morsing & Schultz,

2006: 334). In particular, third-party recognition of the focal firm’s CSER actions may help firms

working from a reputational deficit to realign stakeholder perceptions (Rhee & Valdez, 2009)

because “the use of a recognized and credible third-party organization acts to overcome …

scrutiny of the message source” (Pomering, 2011: 392). For example, Doh and colleagues (2010)

found that firms with poor CSER histories experience a larger increase in price appreciation when

endorsed by the Calvert Social Fund than firms with better CSER histories. In particular, CSER

awards conferred by third parties are likely to provide a strongly credible signal of the focal

firm’s CSER, as “these awards are considered to be good indicators of best practice” (Hassan &

Ibrahim, 2012: 33).

Although there are a variety of sector-specific third-party-CSER awards, awards that

have broad coverage are likely to be the most influential for firm reputation. For example, the

Corporate Knight’s Global 100 Most Sustainable Corporations award and the Carbon Disclosure

Project’s Leadership Index (CDLI) are two “prestigious awards for environmental performance”

(Hassan & Ibrahim, 2012), that cover a wide spectrum of companies. In particular, The Corporate

31

Knights Global 100 award begins by selecting companies with market capitalization greater than

$2 billion USD, and then screens companies for social and environmental key performance

indicators. Companies that pass all screens are awarded the “100 Most Sustainable Corporations”

award recognizing that “the Global 100 companies serve as ambassadors for a better, cleaner kind

of capitalism” (Heap, 2012). The CDLI is an award given to the top 10% of firms that participate

in the CDP, based on a scoring of the quality and extent of the firm’s voluntary environmental

disclosure (CDP, 2011).

In addition, there are three other important wide spectrum CSER awards: Newsweek’s

Green Rankings, Ethisphere’s World’s Most Ethical companies and Corporate Responsibility

Officer’s (CRO) 100 Best Corporate Citizens. Newsweek’s Green Rankings rate all of the 500

largest US firms in a systematic way and because Newsweek is a household name, the ratings

have become an important metric for firms (Amato & Amato, 2012; Lyon & Shimshack, 2012).

Additionally, Ethisphere’s World’s Most Ethical Companies evaluates the ethical behavior of

more than 5,000 companies globally (Bernardi, Bosco & Columb, 2009), selecting firms that are

“leaders of their respective industries when it comes to key ethical criteria such as tone from the

top, employee well-being, CSR, compliance programs, and other important areas” (Brigham,

2013). Finally, the CRO 100 Best Corporate Citizens Award identifies the top 100 companies

each year that “excel at serving a variety of stakeholders well” (cf. Brammer, Brooks & Pavelin,

2009).

Although there is some concern as to whether these individual awards measure what they

claim to measure (e.g., Gunther, 2010), the focus in this study is on the signaling value of the

third-party-CSER award in regards to corporate reputation, not on their validity, per se. For

example, research has shown that there is a positive market reaction when firms are awarded

publicly announced CSER awards. In particular, being named as one of the 100 Best Corporate

Citizens or being included as a top performer in the Newsweek Green Rankings, has resulted in

32

positive stock market returns, while receiving poor ratings has negatively impacted market value

(Brammer et al., 2009; Amato & Amato, 2012; Lyon & Shimshack, 2012). Although some of

these awards have been shown to influence firms’ market-based performance, less is known about

how these awards may impact firms’ general and CSER-specific reputations.

Though these signals are likely to influence reputation for all firms, their impact is likely

to be greater than firm-sent signals on stakeholder perceptions of firms that have historically poor

social and environmental histories. This is because skeptical stakeholders are more likely to be

impressed by CSER signals sent by third parties than by the firms themselves as such signals are

more credible. Hence, third-party-sent signals are likely to challenge stakeholders to reevaluate

the company because other well-reputed organizations have put their own reputation on the line

in legitimating them. Whereas firm-sent signals will have a negative influence on reputation for

firms with a poor history of social and environmental action, third-party-sent signals are likely to

help firms break free from their negative pasts. Similarly, because they confirm expectations,

these awards are likely to amplify the positive relationship between CSER history and reputation

for firms with a history of CSER strengths. Thus, it is hypothesized that:

Hypothesis 4: Third-party awards will attenuate the negative relationship between a

firm’s history of CSER weaknesses and (a) overall reputation and (b) CSER-specific

reputation.

Hypothesis 5: Third-party awards will amplify the positive relationship between a firm’s

history of CSER strengths and (a) overall reputation and (b) CSER-specific reputation.

33

Media Favorability

In addition to the signaling value of firm self-disclosure, firm partnerships and third-party

awards, the media also communicate information about firms’ CSER behavior, which signals

their involvement in CSER (Eisenegger & Schranz, 2011). The media are viewed as credible

sources of information on the basis of their “superior ability to access and disseminate

information” (Aerts & Cormier, 2009: 3). Media attention has also been shown to affect

stakeholder impressions (Pollock & Rindova, 2003; Wartick, 1992). In particular, “by selecting

which issues to cover and how to frame them”, as well as by defining “what constitutes a good

firm” (Zavylova et al., 2012: 1081), the media shape stakeholder judgments about firms.

Moreover, “to the degree that the media make such expressed evaluations widely available in

public discourse, it creates availability cascades that increase the tendency to perceive expressed

evaluations as more plausible” (Pollock & Rindova, 2003: 634).

In addition, research has shown that though media generally present a positivity bias, the

favorability of a firm’s media coverage, defined as the tenor of media coverage, also has

implications for important firm outcomes, such as financial performance and reputation

(Deephouse, 2000; Pollock & Rindova, 2003; Zavylova et al., 2012). In particular, Deephouse

(2000) found that favorable media coverage increases financial performance of firms by

influencing “the information held and interpretations made by stakeholders about the validity and

merits of the firm’s initiatives and communications” (Fombrun, 2012: 103), and, presumably,

consumers’ faith in their products or services. Along these lines, news media signals can either

build support for firm-sent and/or third-party-sent signals, or can void them. Moreover, because

media accounts accumulate over time and thus include a record of many firm activities

(Deephouse, 2000), the overall favorability of media coverage is likely to impact stakeholder

impressions of firms. Specifically, positive media coverage (i.e., media favorability) is likely to

34

improve reputation for all firms, weakening the negative relationship between CSER weaknesses

and poor reputation and strengthening the positive relationship between CSER strengths and

strong reputation. Therefore, the following is hypothesized:

Hypothesis 6: Media favorability will attenuate the negative effect of a firm’s history of

CSER weaknesses on its (a) overall and (b) CSER-specific reputation.

Hypothesis 7: Media favorability will amplify the positive effect of a firm’s history of

CSER strengths on its (a) overall and (b) CSER-specific reputation.

35

Chapter 4

Methodology

In the previous chapter, hypotheses were developed about the effects of firms’ CSER

history, self-disclosure, firm partnerships, third-party awards and media favorability on both

general and CSER-specific firm reputations. This chapter describes the sample and explains the

operationalization of the variables as well as the analytic methods used to test the hypotheses.

Sample

Testing the hypotheses derived from the aforementioned theories required a sample of

firms that were subject to both CSER historical record keeping and reputational ratings. The

Fortune Most Admired Companies (FMAC) annual reputational survey offered such a sample.

The FMAC rates firms as either “most admired” companies or “contenders” for the title. The

FMAC ratings began in 1984 and are composed of ratings made by executives, directors and

security analysts regarding companies they admire most. As such, firms included in this sample

may be thought of as “the best and ‘worst of the best’” (Dowling & Gardberg, 2012: 46). Because

the firms included in the FMAC ratings are generally large and visible firms, they are also subject

to CSER historical record keeping via MSCI STATS (formerly known as the Kinder, Lydenberg,

and Domini (KLD) database), which rates firms based on seven dimensions of social,

environmental and governance criteria and is the most widely used CSER data in academic work

(c.f., Graves and Waddock, 1994; Agle, Mitchell, and Sonnenfeld, 1999; Johnson and Greening,

1999; Hillman and Keim, 2001; Margolis & Walsh, 2003). The sample consisted of 412

companies rated by the FMAC as either a “most admired” (n = 253) or “contender” (n = 159)

36

company in the year following the focal year (i.e., t+1). Firms included in the analysis represent a

wide variety of industries, as shown in Table 1.

--------------------------------------------------

Insert Table 1 Here

--------------------------------------------------

Data and Measures

Data on the 412 firms in the sample were collected via archival records, including firm

websites, firm-issued CSER reports, sustainability and corporate responsibility databases,

including the Global Reporting Initiative (GRI) and the Carbon Disclosure Project (CDP), as well

as media coverage available through LexisNexis. Additional data were collected from MSCI

STATS, the Dow Jones Sustainability Index (DJSI), FTSE4GOOD and the Calvert Social Fund.

All predictors were lagged by one year.

Independent Variables

CSER History. CSER History, which was defined in Chapter 2, refers to a firm’s record

of past social and environmental actions. The idea behind CSER History is that “as firms engage

in CSR acts to improve stakeholder relations, a record of social performance incidentally accrues”

(Barnett, 2007: 803). Hence, CSER History refers to a longitudinal view of a firm’s social and

environmental behavior, including both positive and negative impacts. Following Barnett &

Salomon (2012), CSER History was measured by the MSCI STATS data, which is an annual

dataset of environmental, social and governance ratings of publically traded companies covering

approximately the largest 3,000 US companies by market capitalization (MSCI, 2012). The MSCI

37

STATS data, previously referred to as the Kinder, Lydenberg & Domini (KLD) SOCRATES data

has a proprietary method for tracking firms’ strengths and weaknesses (concerns) in each of seven

dimensions including the environment, community, human rights, employee relations, diversity,

products and governance, by assigning a 1 for the presence (or a 0 for the absence) of a strength

(or weakness) in each dimension. As the data is based solely on publicly available information,

these ratings are considered fairly objective (Delmas, Etzion & Nairn-Birch, 2013). Further, these

data have been used in numerous academic studies and are generally accepted as the “the de facto

[CSER] research standard at the moment” (Waddock, 2003: 369; Etzion, 2007).

Using these data, the CSER Historical Weaknesses variable was created by summing all

weaknesses (concerns) across each of the seven dimensions for each firm in the five-year period

including and preceding the focal year (2007-2011). Similarly, the variable CSER Historical

Strengths was constructed by summing all strengths across each of the seven dimensions for each

firm in the five-year period including and preceding the focal year (2007-2011). Thus, CSER

Historical Weaknesses represents the sum of negative environmental, social or governance-

related firm impacts for the previous five-year period including the focal year (2007-2011).

Similarly, CSER Historical Strengths represents the sum of positive environmental, social or

governance-related firm impacts for the previous five-year period including the focal year (2007-

2011). Though many studies compose a single measure of “net” CSER actions (e.g., Graves &

Waddock, 1994; Hillman & Keim, 2001; Ruf et al., 2001; Chin, Hambrick & Trevino, 2013), in

2006, Mattingly and Berman conducted an exploratory factor analysis of the KLD ratings and

came to the conclusion that “positive and negative social action are both empirically and

conceptually distinct constructs and should not be combined in future research” (p. 20). Hence,

strengths and weaknesses were treated separately in this analysis. CSER historical weaknesses

ranged from 0 weaknesses to a total of 53 weaknesses accumulated from 2007-2011, whereas

CSER historical strengths ranged from 0 strengths to a total of 34 strengths from 2007-2011.

38

Though the KLD began rating firms on the aforementioned criteria in 1991, both KLD

and MSCI have made methodological changes over time. With regards to the 2007-2011 data,

because MSCI changed its methodology in 2010, introducing new ratings and discontinuing

previous ratings, it was necessary for the ratings to be mapped to ensure continuous coverage of

the ratings actively maintained during this time period. Hence, indicators were mapped to ensure

continuity of coverage from 2007-2011, where possible, using the description of indicator

definitions, relationships and mapping provided by MSCI. Because the MSCI STATS data is

proprietary, it is not possible to reproduce the actual mapping here, though an example of what

the mapping entailed is provided. A more in-depth explanation of mapping may be obtained

directly from MSCI. For example, assume that three firm strengths in area A (denoted A-

strength1, A-strength2, A-strength3) were rated in 2007-2009, but in 2010 and 2011 two of these

area A strengths were collapsed into a new variable named A-strength4. Additionally, assume

that the two previous variables A-strength1 and A-strength 2 were discontinued. To ensure the

best possible data coverage, using mapping schemata provided by MSCI, the data would be

mapped so that the total strength for area A in 2007-2009 would equal A-strength1 + A-strength2

+ A-strength3, but total strengths for area A in 2010-2011 would equal A-strength3 + Astrength4.

Firm Partnerships. Within the context of CSER, firm partnerships are a type of firm

relationships that signal a firm’s CSER credibility by lending legitimacy from the partnering

organization. Firm partnerships were measured via counting the number of memberships,

associations and partnerships firms listed in their CSER reports. Because firms list these

memberships, associations and partnerships at their own discretion, this measure does not

represent the actual number of memberships, associations and partnerships firms were engaged in

during the focal year, nor does it represent the quality of such relationships, but it does measure

the number of partnerships to which the firm chose to draw attention. Examples of these

partnerships include membership the World Business Council for Sustainable Development; work

39

with the World Wildlife Fund, as well as more local partnerships focusing on community

development. The variable ranges from 0 to 92 and the variable was log transformed because of

its large positive skew.

Moderators

Firm Self-Disclosure. As discussed in Chapters 2 and 3, firm self-disclosure, which is a

firm-sent signal, refers to a firm’s provision of social and environmental data via social and

environmental reports as well as participation in public disclosure initiatives, such as the Carbon

Disclosure Project (CDP). Firm Self-Disclosure was measured via counting whether a firm

published a CSER report in the focal year (2011) and/or disclosed its CSER activities to the

Carbon Disclosure Project (CDP) in the focal year. This original measure ranged from 0 for firms

that did not disclose via CSER reports or the CDP, the two most commonly used means of

disclosure (Kolk, 2008; Kolk, Levy & Pinkse, 2008) to 2 for firms that disclosed via both CSER

reports and the CDP in the focal year.

Third-Party Awards. Third parties recognize firms for their CSER activities by conferring

awards (Hassan & Ibrahim, 2012). Though it is unclear whether the awards are based on valid

measures of performance, the award may act as a signal showing legitimacy of the firm’s CSER

efforts. The Third-Party Awards variable was operationalized as the number of wide spectrum

awards the sample firms received during the focal year (2011). Awards included the Corporate

Knight’s Global 100 Most Sustainable Companies, Corporate Responsibility Officer’s (CRO) 100

Best Corporate Citizens, Ethisphere’s World’s Most Ethical Companies, Newsweek’s Green

Rankings and the Carbon Disclosure Project’s Leadership Index. The measure ranges from 0 to 5.

Media Favorability. Media favorability refers to the tenor of news coverage, with more

positive tenor reflecting favorability and less positive tenor reflecting disfavorability (Deephouse,

40

2000). Media coverage of focal firms in two major news outlets, the New York Times and the

Wall Street Journal, were collected via LexisNexis. The average number of articles per firm in the

focal year was 27.86. Using the Linguistic Inquiry and World Count (LIWC) software, and

following previous research (Pfarrer, Pollock & Rindova, 2010; Zavylova et al., 2012) each

article was coded as positive if positive affective content accounted for at least 55 perfect of the

total affective content of each article and as negative if 55 percent or more of the total affective

content in each article was negative (those falling in between were coded as neutral). Media

favorability was then measured via computing the Janis-Fadner coefficient of imbalance (Janis &

Fadner, 1965; Deephouse, 2000; Pollock & Rindova, 2003; Fanelli, Misangyi & Tosi, 2009;

Zavylova et al., 2012), using the following formulae:

media favorability = / if P>N; 0 if P=N, and / if N>P,

where P is the number of positive articles about a firm, N is the number of negative articles about

the firm, and V is the total volume of articles about the firm, including neutral articles. The range

of the variable is –1 to +1, where -1 equals all negative coverage and +1 equals all positive

coverage.

Dependent Variables

General Reputation. General reputation refers to a firm’s “overall appeal” (Fombrun,

1996: 72) and was measured via the Fortune’s Most Admired Companies (FMAC) ratings for

each focal firm in the year subsequent to the focal year. The FMAC measure of firm reputation

has been widely used (e.g., Staw & Epstein, 2000; Basdeo et al., 2006; Carter, 2006; Love &

Kraatz, 2009; Pfarrer et al., 2010; Melo & Garrido-Morgado, 2012; King & McDonnell, 2012),

41

though it focuses squarely on financially-oriented stakeholders. It is likely, however, that other

stakeholder audiences may form different impressions of firms that are not captured by the

FMAC reputation ratings. Although the FMAC ratings “do not capture the opinions of all

relevant publics, the audiences who ascribe them are knowledgeable and influential ones” (Love

& Kraatz, 2009: 322).

Each year, the FMAC list is composed by collecting ratings of firms from financial

analysts, senior executives and investors (Luo & Bhattachyra, 2006). Further, as the FMAC

measure is based on ratings from actors focused on financial markets, some have claimed that it

has a “financial halo” (Dowling & Gardberg, 2012). However, this effect is controlled for by

regressing reputation on financial performance and using the residuals from that analysis as the

dependent variable in subsequent analyses, dampening financial determinants of reputation

(Brown & Perry, 1994; Roberts & Dowling, 2002; Pfarrer et al., 2010). Additionally, critics argue

that the list focuses only on large, public companies (Fombrun, 1998) – however, that

characteristic makes the list beneficial for this study because of the need for highly visible firms.

Firms are rated on 9 attributes: financial soundness, investment value, use of corporate assets,

innovativeness, management, products and services, employees, social responsibility and global

competitiveness. Although the ratings are presented each year, the 2013 FMAC data were used in

this study, which was published in March 2013 and are based on data pertaining to the previous

year, 2012, which is the focal year for the dependent variable. Theoretically, the scores may range

from 1 to 10, though the data used in this study range from 2.64-8.78.

CSER-specific Reputation. In previous research, scholars that have used the MSCI/KLD

data have often treated a firm’s CSER history as equivalent to its CSER reputation. However,

because historical MSCI/KLD ratings are formed by independent analysts working from solely

publicly available documents, it is better conceived of as a record of activity than an indicator of

stakeholder evaluations of that activity. In particular, because CSER-specific reputation

42

represents stakeholder impressions of a firm’s social and environmental responsiveness, it is

better operationalized by a measure that takes into account stakeholder impressions. Further,

because there is not an existing clear measure of CSER-specific reputation based on stakeholder

impressions of CSER activities, CSER-specific reputation was operationalized using inclusion in

Socially Responsible Investment (SRI) indices as a proxy variable. In particular, the SRI

Inclusion variable was calculated based on whether firms were listed in at least one of three major

SRI indices (Fowler & Hope, 2007), including the Dow Jones Sustainability Index, the

FTSE4Good Index and the Calvert Social Fund in the year subsequent to the focal year, which in

this case is 2012.

Although the idea of socially responsible investing was present in as early as the 1970s as

a way for investors to match investments with their values, these indices have recently become

more prominent (Fowler & Hope, 2007; Doh et al., 2010) with the rapid increase in socially

responsible investment. For example, in the US, socially responsible investment grew from about

$639 billion to than $3.74 trillion in 2011, meaning that more than one out of every nine US

dollars was invested via socially responsible investing strategies (USSIF, 2012). Inclusion in SRI

indices is based on judgments made by the index stakeholders regarding the CSER activities and

merits of each firm considered. Each SRI index has its own proprietary method for selecting

companies; however, they all exclude companies based on corporate involvement in ethically

questionable activities, such as gambling, weaponry and tobacco. Therefore, a dummy variable

was constructed to control for ethical exclusion from the indices. To determine inclusions, each

index begins with an eligible universe and then screens companies on the basis of proprietary

judgments. Hence, instead of providing a tally of weak or strong CSER activities, SRI indices

represent a judgment of firms’ CSER-specific attributes within the socially responsible

investment stakeholder group, based on CSER actions, akin to the idea that specific reputation is

defined as firms’ “reputations about specific attributes with particular stakeholder groups, based

43

on past actions of a given type” (Rindova & Martins, 2012: 20). The variable ranges from 0 for

firms that were not listed on any of the three SRI indices (n = 156) to 1 for firms that were listed

on at least one of the indices (n= 256).

Controls

Firm Financial Performance. Firm financial performance was controlled for by using

both accounting and marketing measures. To correct for the “financial halo” (Dowling &

Gardberg, 2012) associated with the FMAC measure of general reputation, general reputation was

regressed on return on assets (ROA), which is an accounting-based measure of firm financial

performance (Hamilton & Kayande, 2012). Following previous research (Roberts & Dowling,

2002; Brown & Perry, 1994; Pfarrer et al., 2010), the residuals, ROA Residuals, from this analysis

was then used as the dependent variable in subsequent analyses of general reputation. For CSER-

specific reputation, ROA was standardized and entered directly into the equation as a control.

Additionally, a control for each firm’s Market-to-Book Ratio, which is a market-based measure of

firm financial performance, was included in the analyses for both dependent variables (this

variable was log transformed because of skew). Both accounting- and market- based measures

were included because they tap different aspects of performance (Hamilton & Kayande, 2012).

Whereas ROA captures a firm’s internal efficiency, market-to-book ratios capture shareholder

evaluations of the firm (Orlitzky et al., 2003). Industry effects were also controlled using a

dummy variable indicating whether firms were substantially service- or manufacturing- oriented.

The variable Services was coded as 1 for firms in the healthcare or financial industries, using the

other remaining industries as the reference category. Firm Size was controlled for by taking the

natural log of the number of employees employed by the firm. The Total Volume of Media

44

Coverage in the New York Times and the Wall Street Journal during the focal year were included

to control for firm visibility.

Analytical Models

Addressing the (a) and (b) components of the hypotheses presented in Chapter 3 required

running separate analyses for two different dependent variables. To address the (a) components of

the hypotheses, linear ordinary least squares (OLS) regression models were run with general

reputation, a continuous measure, as the dependent variable. On the other hand, because the

dependent variable for the (b) hypotheses, CSER-specific reputation, was binary, logistic

regression models were run with inclusion in SRI indices as the dependent variable. Logistic

regression is a maximum likelihood estimation procedure, using an iterative approach until the

solution with maximum likelihood is found (Acock, 2012). Logistic regression is more

appropriate than OLS regression for binary dependent variables, because they have limited range,

which would bias coefficient estimates and inflate standard errors (Harrison, 2001). Because six

of the hypotheses predict a moderation effect, all continuous independent variables were centered

to reduce for possible multicollinearity between the main effects and interaction effects (Aiken &

West, 1991; Acock, 2012).

45

Chapter 5

Results

In this chapter, the results testing the hypotheses regarding the effects of CSER signals on

the relationship between firm CSER history and general and CSER-specific firm reputation are

presented. Following the methods described in the previous chapter, two separate models were

used for the analyses: first, Hypotheses 1a, 2a, 3a, 4a, 5a, 6a and 7a were tested using a linear

regression model; second, Hypotheses 1b, 2b, 3b, 4b, 5b, 6b and 7b were examined using a

logistic regression model. The results reveal varying support for the hypotheses, as described

below. Nonetheless, there are statistically significant and interesting results even if counter to the

hypothesized effects.

Summary Statistics and Correlations

Table 2 presents means, standard deviations and correlations for the variables of interest

in this study: CSER historical weaknesses and strengths, firm self-disclosure, firm partnerships,

third-party awards, media favorability, general firm reputation and CSER-specific firm

reputation, as well as the control variables. Multicollinearity was investigated in multiple ways,

including examining correlations, variance inflation factors and tolerances, as well as the

“coldaig” command in STATA 13.1. The highest correlation is between firm self-disclosure and

historical CSER strengths (.70). Although there is no definitive agreement on the criteria that

define a significant collineartiy problem (or lack thereof), correlations less than .8 are generally

allowable (Berry, 1985). Additionally, all variance inflation factors (VIFs) were well below the

threshold of 10, with an average of 2.33 in the full linear regression model and 2.23 in the full

46

logistic regression model, confirming that multicollinearity was not a concern (Chatterjee &

Price, 1991; Acock, 2012). All condition numbers from “coldiag”, which analyzes the

conditioning of the matrix of independent variables (Belsley, Kuh & Welsch, 1980), were under

the threshold of 30, which also suggests that collinearity does not pose a serious threat to the

analyses. Finally, as coefficients and odds ratios remained stable with the model changes, the

degree of multicollinearity is not likely severe enough to hamper the analyses.

--------------------------------------------------

Insert Table 2 Here

--------------------------------------------------

Consistent with findings from meta-analytic investigations of the relationship between

CSER and firm financial performance, the correlation results show that CSER history is more

highly correlated with accounting-based measures of firm financial performance than with

marketing-based measures (Orlitzky, et al., 2003). However, counter to Hamilton & Kayande

(2012), general reputation had a higher correlation with accounting-based measures of firm

performance (r= .39, p< .001) than market-based measures of firm performance (r= .16, p <.01).

Interestingly, CSER-specific reputation has a positive and statistically significant bivariate

correlation with general reputation (r= .20, p<.001), indicating that improvement of CSER-

specific reputation will be positively associated with improvement of general reputation, and vice

versa. In other words, events that might hurt a firm’s CSER-specific reputation would likely also

hurt its general reputation, indicating that both general and specific facets of firm reputation are

important.

Several statistically significant bivariate correlations were found for the control variables.

For example, the results suggest that firms in service industries, such as finance and healthcare

have more positive CSER-specific reputations than firms in non-service industries. It is also

interesting that firms operating in ethically questionable business activities, including tobacco and

47

gambling, are more likely to draw attention to the CSER-oriented partnerships in which they are

involved. Firm size is significantly positively related to media coverage, as expected and as

shown in previous research, because larger firms generally attract more media attention (Strike,

Gao & Bansal, 2006). Larger firms are also more likely to have histories of both higher CSER

weaknesses and strengths, as well as levels of disclosure and third-party awards.

For the independent variables, CSER history is significantly related to firm self-

disclosure, partnerships and third-party awards, while media favorability appears not to have any

statistically significant relationship with any of the other variables in the study. Also, importantly,

while the correlation between historical CSER weaknesses and reputation is not statistically

significant (for either general or CSER-specific reputation), there are statistically significant

positive relationships between CSER historical strengths and both general (r =.33, p <.001) and

CSER-specific reputation (r =.30, p <.001), supporting the baseline assumption for CSER

strengths. Further, consistent with previous research (Chatterji, Levine & Toffel, 2009), the

correlation between CSER historical strengths and CSER historical weaknesses is positive,

suggesting that firms with more strengths also have more weaknesses (Delmas & Blass, 2010).

General Reputation Results

Table 3, presents the results of the linear regression predicting general reputation for

Hypotheses 1a, 2a, 3a, 4a and 5a. The controls-only analysis is presented in Model 1, followed by

a main-effects analysis in Model 2, interaction analyses in Models 3-5, and finally, Model 6

contains the full model. All models were statistically significant. The results for each hypothesis

appear next.

48

--------------------------------------------------

Insert Table 3 Here

--------------------------------------------------

Hypothesis 1a predicted that firm self-disclosure of CSER activities would amplify the

negative effect of a firm’s history of CSER weaknesses on its general reputation. The results for

Model 3 in Table 3 show that the interaction between firm self-disclosure and historical CSER

weaknesses was positive and statistically significant (β = .16, p < .05). To interpret this result in

more detail, the interaction was graphed (Aiken & West, 1991). Figure 1 shows the moderation

effect of self-disclosure on the relationship between CSER historical weaknesses and general

reputation. The graph is drawn using three levels of self-disclosure: no firm self-disclosure, firm

self-disclosure via only CSER reporting or the CDP, and firm self-disclosure via both CSER

reporting and the CDP. Figure 1 indicates that the negative relationship between CSER historical

weaknesses and general reputation is actually attenuated for firms that disclose through either

disclosure method. Further, firm self-disclosure via both CSER reports and the CDP actually

changes the slope of the line from negative to slightly positive, suggesting that firm self-

disclosure helps improve general reputation for firms with weak CSER histories. Thus,

hypothesis 1a is not supported.

----------------------------------------------------------

Insert Figure 1 Here

----------------------------------------------------------

Similarly, Hypothesis 2a predicted that firm self-disclosure of CSER activities would

amplify the positive effect of a firm’s history of CSER strengths on its general reputation. The

results in Model 3 in Table 3 show that the interaction between firm self-disclosure and historical

CSER strengths was negative and statistically significant (β = -.36, p<.001). To interpret this

result in more detail, the interaction was graphed. Figure 2 shows the moderation effect of self-

49

disclosure on the relationship between CSER historical strengths and general reputation. As with

the graph showing hypothesis 1a, the graph is drawn using three levels of self-disclosure: no firm

self-disclosure, firm self-disclosure through either CSER reporting or the CDP, and firm self-

disclosure via both CSER reporting and the CDP. Figure 2 indicates that the positive relationship

between CSER historical strengths and general reputation is actually attenuated for firms that

disclose via either CSER reports or the CDP. Further, firm self-disclosure via both CSER reports

and the CDP actually changes the slope of the line from positive to slightly negative, suggesting

that firm self-disclosure reduces general reputation for firms with strong CSER histories. Thus,

hypothesis 2a is not supported. This finding, combined with the findings from hypothesis 1a is

provocative – while firm self-disclosure may help improve general reputations for firms that are

mired in weak CSER histories, the same type of disclosure may harm general reputation for firms

that are basking in the glow of strong CSER histories. Thus, not all firms conform to the

theoretical tenets of stakeholder theory, which suggests that response to stakeholder demands for

information should improve firm performance and reputation. In fact, response to stakeholder

demands for information by means of self-disclosure could actually decrease general reputation –

at least for those firms with strong CSER histories.

----------------------------------------------------------

Insert Figure 2 Here

----------------------------------------------------------

Hypothesis 3a predicted a positive relationship between a firm’s declaration of CSER-

oriented partnerships and its general reputation. As shown in Model 2 in Table 3, the main effect

of firm partnerships was positive and statistically significant (β = .14, p <.01). These results

suggest that firms that increasingly draw attention to the CSER partnerships in which they are

engaged will have better reputations than firms that don’t advertise their CSER partnerships.

Thus, hypothesis 3a is supported.

50

Hypothesis 4a predicted that the receipt of third-party awards would attenuate the

negative relationship between a weak CSER history and a firm’s general reputation. The results

in Model 4 in Table 3 show that the interaction between receipt of third-party awards and

historically weak CSER was not statistically significant. Hence, hypothesis 4a is not supported.

On the other hand, for Hypothesis 5a, Model 4 shows a statistically significant interaction

between third-party awards and historical CSER strengths (β = -.18, p<.05, note: the negative

beta coefficient is misleading as the hypothesis predicted that the receipt of third-party awards

would amplify the positive relationship between a CSER historical strengths and a firm’s general

reputation). By graphing the moderating relationship, the effect becomes clearer, showing support

for hypothesis 5a. As shown in Figure 3, the moderation effect of third-party awards on the

relationship between CSER historical strengths and general reputation is shown in a graph drawn

using two levels of third-party awards: No third-party awards received and third-party awards

received. Figure 3 indicates that while there is a negative relationship between CSER historical

strengths and general reputations for firms that do not receive third-party awards, there is a

positive relationship between CSER historical strengths and general reputation for firms that do

receive third-party awards, supporting hypothesis 5a. The results suggest that third-party awards

help to improve reputation for firms that have strong histories of CSER strengths.

--------------------------------------------------------------

Insert Figure 3 Here

--------------------------------------------------------------

Next, the results for hypotheses 6a and 7a are presented in Model 5 in Table 3.

Hypothesis 6a predicted that media favorability would attenuate the negative effect of a firm’s

historical CSER weaknesses on its general reputation, whereas hypothesis 7a predicted that media

favorability would amplify the positive effect of a firm’s historical CSER strengths on its general

reputation. Since the results for both hypotheses were not significant, neither hypothesis 6a nor 7a

51

were supported. Additionally, media favorability did not have a significant main effect on general

reputation. Hence, the results suggest that media favorability does not affect general reputation,

regardless of firm CSER history.

In sum, hypotheses 3a and 5a were supported in individual models, although the

interaction term testing hypothesis 5a fell out of significance in the full model (i.e., Model 6),

which was presented in Table 3 above. Hypotheses 1a, 2a, 4a, 6a and 7a were not supported. The

results of the logistic regression analysis predicting CSER-specific reputation are presented next.

CSER-specific Reputation Results

Table 4 presents the results of the logistic regression analyzing the effects of CSER

history and signals on Socially Responsible Investment (SRI) index inclusion as a proxy for

CSER-specific reputation for Hypotheses 1b, 2b, 3b, 4b, 5b, 6b and 7b. Model 1 presents a

controls-only model, Model 2 the main-effects model , Models 3-5 the interaction models, and

finally, Model 6 presents the full model. All models were statistically significant. Odds ratios are

reported to allow for easier interpretation of effects. Specifically, odds ratios greater than 1

specify that the likelihood of the dependent variable event increases with each unit increase in the

focal independent variable, whereas odds ratios less than 1 specify that the likelihood of the

dependent variable event decreases with each unit increase in the focal independent variable. The

results of the logistic regression hypothesis testing appear next.

--------------------------------------------------

Insert Table 4 Here

--------------------------------------------------

Hypothesis 1b predicted that firm self-disclosure of CSER activities would amplify the

negative effect of a firm’s history of CSER weaknesses on its CSER-specific reputation. The

52

results for Model 3 in Table 4 show that the interaction between firm self-disclosure and

historical CSER weaknesses was not statistically significant. Thus, hypothesis 1b is not

supported. Similarly, hypothesis 2b, which predicted that firm self-disclosure of CSER activities

would amplify the positive effect of a firm’s history of CSER strengths on its CSER-specific

reputation, was also not supported. Additionally, hypothesis 3b, which predicted a positive

relationship between a firm’s declaration of CSER-oriented partnerships and its general

reputation was also not statistically significant. Hypotheses 4b and 5b, which predicted that third-

party awards would moderate the relationships between CSER history and CSER-specific

reputation were not supported. Finally, hypotheses 6b and 7b, which predicted that media

favorability would moderate the relationships between CSER history and CSER-specific

reputation were also not statistically significant. Thus, none of the hypotheses predicting CSER-

specific reputation were supported.

However, even though none of the moderating hypotheses for CSER-specific reputation

were supported, there were statistically significant main effects of CSER history and marginally

significant effects for third-party awards on CSER-specific reputation, as shown in Model 1 in

Table 4. In particular, CSER historical weaknesses has a statistically significant main effect on

CSER-specific reputation (odds ratio .86, p <.001), suggesting that the likelihood of firms being

listed on SRI indices as a proxy for CSER-specific reputation decreases with increases in CSER

historical weaknesses. On the other hand, the direct effect of CSER historical strengths on CSER-

specific reputation was greater than one and statistically significant (odds ratio 1.22, p <.001),

suggesting that the likelihood of firms being listed on SRI indices as a proxy for CSER-specific

reputation increases with increases in CSER historical strengths . Additionally, third-party awards

had a marginally significant main effect on CSER-specific reputation (odds ratio 1.58, p <.10),

indicating that the likelihood of firms being listed on SRI indices as a proxy for CSER-specific

reputation increases with receipt of third-party awards. These results suggest that CSER history is

53

an important predictor of CSER-specific reputation, and that firms are not likely to be able to

improve their CSER-specific reputation via self-disclosure, or drawing attention to partnerships,

though receipt of third-party awards may help improve CSER-specific reputation. In other words,

CSER-specific reputation appears highly path dependent.

54

Chapter 6

Discussion

The aim of this study was to examine how firm-sent, firm-partnership, third-party and

media-sent-CSER signals interact with firms’ CSER history to affect both general and CSER-

specific firm reputation. In particular, this dissertation set out to analyze how signaling influences

the relationship between a firm’s CSER history and its reputation (both general and CSER-

specific), looking specifically at how firm reputations may be influenced when firms engage in

self-disclosure, participate in partnerships, are recognized by third-party-CSER awards and

receive favorable media attention. The results of the analyses suggest that though CSER history,

in terms of both strengths and weaknesses has an impact on general and CSER-specific firm

reputation, firm self-disclosure, partnerships, third-party awards and media favorability have

differing moderating effects on the relationship between CSER history and reputation. In this

chapter, results are discussed in light of this study’s research questions:

(1) How do CSER signals influence the relationship between CSER history and

reputation? Are the effects the same for general and CSER-specific firm reputation?

(2) Are there differences in the effectiveness of signals sent by firms, firm partnerships,

third parties and the media? If so, how does the effectiveness differ?

In particular, the theoretical contributions of the study are discussed, as well as implications for

organizational theory. The chapter concludes by discussing the limitations of this study and

avenues for future research.

55

Contributions

This study began with the baseline assumption that history matters. Although it is

generally conceived that reputation is based on past corporate actions (Fombrun, 1996), research

has tended to ignore firms’ contextual history while considering the ways that CSER may affect

their reputations. In other words, in as much as scholars have advocated for a multidimensional

view of reputation (Lange et al., 2011; Rindova & Martins, 2012), empirical research has

generally neglected to address that “firms have reputations about specific attributes with

particular stakeholder groups, based on past actions of a given type” (Rindova & Martins, 2012:

20). To address these deficiencies, this study empirically examined the relationship between a

firm’s specific (CSER) history and its general reputation and between its CSER history and a

specific dimension of reputation (its current CSER-specific reputation); in addition, it examined

signals that may influence reputation (both general and CSER-specific). Although many of the

hypothesized effects were not supported, the counterintuitive findings are interesting nonetheless

and make several contributions to CSER and signaling theories, respectively.

First, by studying how signals moderate the relationship between CSER history and firm

reputation, this study sheds light on which signals are most likely to enhance or lessen firm

reputation in given contexts, challenging the assumption that signals intended to enhance firm

reputation have unequivocal effects and contributing to explanations of how reputation ebbs and

flows as stakeholders change their evaluations of firms (Love & Kraatz, 2009). Further, this study

was able to explain how firm self-disclosure and partnerships can impact firm reputation by

considering the unintended consequences firms may face by taking an “active role” in reputation

building through signaling (Whittington & Yakis-Douglas, 2012). In particular, the results of the

analyses show that when firms with a history of CSER weaknesses self-disclose their CSER

activities (via either CSER reports or the CDP), there is a positive uptick in general reputation, as

56

intended by the firm. Though counter to the hypothesized effect, this may be explained by the

perspective of institutional theory, which suggests that “social disclosure is thus seen as a part of

the dialogue between the company and its stakeholders” (Gray et al., 1995: 53), which is

maintained to build or enhance legitimacy, because “although companies with lower levels of

CSP will have less favorable information to disclose, institutional pressures bring about increased

disclosure” (Dawkins & Frass, 2008: 10). In other words, that firm self-disclosure can make the

negative relationship between CSER weaknesses and general reputation more positive suggests

that firms with CSER weaknesses may be attempting to “claim legitimacy to external

stakeholders by showing them that the company adheres to social norms and expectations”

(Nikolaeva & Bicho, 2011: 139). As firms conform to institutional standards they are increasingly

viewed as legitimate (Suchman, 1995), and may be able to break free from path dependence (i.e.,

a trajectory of maintaining a negative reputation) as CSER signals challenge stakeholders to view

firms in light of new information. Hence, as social actors, when firms with a poor CSER history

self-disclose their CSER activities, they engage in “path creation” (Garud & Karnoe, 2001), by

providing information intended to create a new, or at least refreshed, firm image, which may help

the firm break free from historical perceptions of irresponsibility. Alternatively, perhaps signals

are most influential in contexts where a firm’s qualities have previously been called into question

as in the case of firms with CSER historical weaknesses.

However, when firms with a history of CSER strengths self-disclose CSER activities (via

either CSER reports or the CDP), there is an unintended consequence (Merton, 1936): a decrease

in general reputation. This finding is counterintuitive to both disclosure and stakeholder theories,

which suggest that firms use disclosure as a means of responding to stakeholder pressures and

favorably managing their impressions (Cormier & Maignan, 1999; Neu, Warsame & Pedwell,

1998; Gelb & Strawser, 2001). For example, Dierkes and Antal (1985: 29) argue that “the

development of corporate social reporting has been propelled by … the need to document

57

corporate social responsibility and to publicly disclose this information”. Hence, the general

proposition that “firms which are acting in a socially responsible way will have greater incentive

to provide more discretionary disclosure than those behaving less responsibly” (Cahan & Malone,

2005: 25) is not supported by the results of this study. Instead, the results show that it is only

firms with a history of CSER weaknesses that have a greater (reputational) incentive to disclose.

Interestingly, as social actors, firms may also exercise agency in ways that have unintended, and

even unfavorable consequences for firm reputation.

Though these findings are counter intuitive to existing theories, they help us understand

sources of difference in “the reception of CS[E]R communication” (Schultz & Wehmeier, 2012:

23) and the relative effectiveness of distinct signals and distinct sources (Pollock & Gulati, 2007;

Love & Kraatz, 2009). Thus, the results highlight the double-edged sword of meeting stakeholder

demands. That is, “while stakeholders claim they want to know about the good deeds of the

companies they buy from or invest in, they also become leery of the CSR motives when

companies aggressively promote their CSER efforts” (Du et al., 2010: 9). Moreover, interviews

with executives responsible for social and environmental activities within their firms have shown

that some firms choose to underemphasize their CSER efforts to avoid potential harm (Stites &

Gray, 2012). For example, in an interview published by Fast Company, the chief sustainability

officer of Verizon noted, “we say do what you say 100% and only talk about 10%. We are doing

so much more than what I am sharing right now, so that our story can be out there and be

respected” (Schwartz, 2010). This is also known as the “self promoter’s” paradox (Ashforth &

Gibbs, 1990; Morsing & Shultz, 2006), which highlights that “conspicuous attempts to increase

legitimacy may in fact decrease legitimacy” (Ashforth & Gibbs, 1990: 188). Further, “too much

‘sensegiving’ regarding CS[E]R efforts may be counter-productive … as companies already

perceived as legitimate constituents do not need to communicate their CS[E]R efforts loudly”

(Morsing & Schultz, 2006: 332). Thus, disclosure by firms with a history of CSER strengths

58

might make these firms more vulnerable by opening them up to criticism as it may suggest “areas

for improvement” (Lyons & Shimshack, 2012: 11). Whereas the view of firms as social actors

suggests that firms’ efforts to improve the impressions they make will be successful, this study

shows that such activities may have unintended negative consequences for stakeholder

impressions. In sum, these findings show that although it is assumed that disclosure should help

firms enhance their reputations ceteris paribus, in this study, this is only true for firms with weak

CSER histories. Hence, theories of stakeholder communication need to take into account

contextual factors that may make responding to stakeholder demands for information a less

advantageous route for firms to take.

Next, this study reaffirms the study of CSER partnerships (Gray & Stites, 2013) as useful

ways to signal firms’ commitment to CSER. CSER partnerships have been the focus of several

in-depth case studies, resulting in the conclusion that CSER partnerships enhance firm reputation

(e.g., Argenti, 2004; Dahan, Doh, Oetzel & Yaziji, 2010; Yarnold, 2007; Austin & Seitanidi,

2012; Kolk et al., 2010). However, prior to this study, this proposition was not confirmed through

hypothesis testing. The results of this study show that when firms draw attention to the CSER

partnerships in which they are engaged, they see a positive return in general reputation. These

results lend support to the proposition that positive outcomes for businesses increase when

partnerships are publicized (Gray & Stites, 2013; Kolk et al, 2010), because participation in

socially- and environmentally- oriented partnerships helps firms to present themselves as

responsible corporate citizens (LaFrance & Lehmann, 2005).

Third, this study offers contributions to theory by examining the role of signals sent by

third parties as moderators of the relationship between CSER history and general firm reputation.

Previous research has suggested that third parties play the role of “infomediaries” (Pollock &

Rindova, 2003; Deephouse & Heugens, 2009; Zavylova et al., 2012) through the way they

“disseminate information, frame issues, and assist stakeholders in making sense of firm actions”

59

(Zavylova et al., 2012: 1079). The results of this study show that third-party awards affect general

reputation for firms, but in a counterintuitive way. Instead of third-party awards having a

significant moderating effect on the relationship between CSER history and general reputation for

firms with histories of weak CSER, helping firms ‘dig out’ of path dependent histories of poor

CSER actions, the awards only have a significant effect for firms with histories of CSER

strengths.

Presumably stakeholders want to see these awards as confirmations of their expectations.

In fact, for firms with histories of CSER strengths, there may be an aspirational effect, where

histories provide a “reference point” (Kahneman & Tversky, 1979; Tversky & Kahneman, 1981;

Lant, 1992), from which stakeholders form “expectations that high relative levels of performance

will be maintained” (Mishina, Dykes, Block & Pollock, 2010: 702). This notion is known as the

“Red Queen effect” in competitive strategy (Derfus, Maggitti, Grimm & Smith, 2008), and refers

to “a circumstance in which a firm must perform better and better relative to its competition to

maintain its current market position” (Mishina et al., 2010: 704), much like Alice in Wonderland

is told by the Red Queen that “it takes all the running you can do, to keep in the same place. If

you want to get somewhere else, you must run at least twice as fast as that!” (Carroll, 1960: 345).

Accordingly, when firms with histories of CSER strengths do not receive third-party CSER

awards, stakeholders may perceive a loss in performance even in light of above average

performance, and, because “losses loom larger than gains” (Mishina et al., 2010: 702; Kahneman

& Tversky, 1979; Tversky & Kahneman, 1981), firms may suffer a reputational penalty.

Following the above analogy, firms with positive CSER histories may be conceived of as

experiencing a “Green Queen effect”, where they may not be able to maintain a positive

reputation by riding their own coattails of previous CSER strengths, but must continually engage

in CSER advancements to maintain or improve their general reputation. These findings

complicate intuitive theorizations of a simple relationship between third-party CSER awards and

60

reputation suggesting that predictions may be misleading when the relationship is considered

outside of the context of CSER history.

Next, this study poses interesting results for the study of media in relation to reputation.

Whereas previous studies have uncovered a link between the favorability of media coverage and

reputation, the same relationship is not shown in this data set. One plausible explanation for this

discrepancy is that previous studies examining the relationship of media coverage and reputation

focus on media coverage around specific events, such as product recalls (Zavylova et al., 2012)

environmental disasters (Luo, Meier & Oberholzer-Gee, 2012) or initial public offerings (Pollock

& Rindova, 2003; Pollock, Rindova & Maggitti, 2008). While media coverage regarding such

discrete events is likely to be emotionally laden, and thus influential, by analyzing media

coverage over a more general, disperse, time period, specific events are likely to be less salient,

tempering (un)favorability. For example, in his study of how non-event-specific media

favorability relates to firm profitability, Deephouse (2000) found the nearly the same media

favorability as in this study (the coefficient of media imbalance = .22 with a standard deviation of

.37, compared to .23 with a standard deviation of .36 in this study). Although Deephouse (2000)

did not examine the specific relationship between media favorability and general firm reputation,

he did find a positive relationship between media favorability and firm ROA. Instead of viewing

non-event-specific media favorability as a research limitation, it can be seen as an important

reminder that the media surrounding an important firm event isn’t the only media coverage a firm

receives in a given time period, and it may be that this continuous media coverage may temper

the event-specific coverage the firm receives. Thus, future studies examining media favorability

in regards to reputation should include a larger time span in addition to event-specific media

coverage to account for the differing roles of event-salient versus continuous media coverage.

Finally, this study contributes to the scholarly understanding of reputation as a

multidimensional construct (Lange et al., 2011; Rindova & Martins, 2012). Core to the argument

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supporting the multidimensional view of reputation is that “different types of stakeholders have

different priorities” (Mishina & Devers, 2012: 204) and “specific types of actions are perceived

and valued differently by different stakeholder groups” (Rindova & Martins, 2012: 20). These

groups have different “authorizing contexts” with “different criteria for value creation” (Brown,

2008: 144). Although the stakeholder group evaluating general reputation (presumably a

financially-oriented one) seems to be concerned with firm self-disclosure, partnerships and third-

party awards, these signals appear to be less-valued by the CSER-specific socially responsible

investing (SRI) stakeholder group. However, it is important to note that this study only examined

two of many possible audiences for CSER and hence, findings may differ for various audiences.

In fact, counter to expectations, for CSER-specific reputation, all that seems to matter is

history, which is an incredibly surprising result, as one would expect that firm self-disclosure of

CSER activities and partnerships, as well as receipt of third-party-CSER awards would

significantly affect CSER-specific reputation because these signals are uniquely related to CSER.

However, because inclusion on SRI indices was used as a proxy for CSER-specific reputation in

this study, the explanation for this finding may have to do with stakeholder values. Perhaps

because the stakeholders that evaluate CSER-specific reputation (i.e., SRI inclusion) see SRI as

an extension of their own values (Fowler & Hope, 2007; Domini, 2001), they refrain from

including firms with a socially irresponsible history because to do so would tarnish the very idea

of SRI. What is more, by definition, “SRI is an investment strategy that seeks to align investors’

prosocial values with particular manifestations of CS[E]R” (Orlitzky, 2013: 244). Because

inclusion on SRI indices is based on value judgments, it’s possible positive CSER signals do not

help firms with substantial CSER weaknesses improve their CSER-specific reputation, because

they are stigmatized as being socially irresponsible, resulting in the possibility that positive CSER

signals “might be viewed as instrumental attempts at ingratiation” (Mishina & Devers, 2012;

Godfrey, 2005). That CSER signals, including firm self-disclosure, partnerships and third-party

62

awards have differing impacts on general (i.e., overall) versus specific (i.e., CSER) reputation

shows empirical support for multidimensional conceptualizations of corporate reputation.

Additionally, these findings answer calls for research on the reasons why similar CSER actions

lead to differing outcomes (Aguinis & Glavas, 2012), enabling “managers to better understand

how different strategies affect their reputational assets” (Rindova & Martins, 2012: 18).

Moreover, this study highlights the complexity of stakeholder communication processes

(Eisenegger & Schranz, 2011) by showing how multiple sources of information have differential

impacts on stakeholder judgments about a firm’s reputation. Overall, the results of this study

show that CSER signals have differing impacts on a firm’s reputation dependent on the firm’s

CSER history, complicating research on signaling theory which has tended to focus primarily on

signals sent to “intentionally communicate positive, imperceptible qualities” (Connelley et al.,

2011: 46; Fischer & Reuber, 2007). As a consequence of showing that intentionally positive

signals may have unintentionally negative implications for firms, this study calls for theorizations

of signaling that consider the various factors that may inhibit a given signal from realizing its

objective, or even having an effect that is opposite of that which was intended. In sum, though the

chief aim of signaling theory is to reduce information asymmetries to gain stakeholder approval,

the theory should also address ways in which the reduction of asymmetric information may result

in unpropitious outcomes. These findings are especially compelling in regards to stakeholder

theory since firm communications (i.e., signals) aimed at informing and gaining favor with

stakeholder audiences actually reduced favor. On the other hand, the results are also clear that

firm relationships and third parties can send positive signals about firms that increase a firm’s

general reputation without unintended reputational consequences. An explanation for why firm-

sent, firm-relationship, and third-party signals have implications for general reputation and not

CSER-specific reputation is not clear, but nonetheless indicates that signaling theory should

63

account for how the same signal sent by the same source can have differing impacts on various

dimensions of the same outcome.

Limitations

Although the findings of this study are provocative, there are several potential limitations

to keep in mind when evaluating the results. First, because the creation of reputation is an area of

inquiry that has been under researched (Barnett & Pollock, 2012), studying it requires sampling

on the dependent variable in order to acquire data. That is, firms need to be rated on reputation in

order to be included in a study of the microfoundations of reputation. Additionally, because the

firms in this sample were either rated as “most admired” or “contenders” for the most admired

title, these companies can be seen as the best and ‘worst of the best’” (Dowling & Gardberg,

2012: 46). However, even if the sample were selected based on different criteria, many firms

would have been dropped because they would not have scores for the dependent variable,

resulting in a similar type of sample. Further, by employing the FMAC data, this study is

comparable to the majority of existing reputation studies which commonly include the FMAC

data as a predictor. In this regard, sampling based on the dependent variable is actually beneficial

in conjunction with other research it allows us “to gain certain insights that other organizations

would not be able to provide” (Siggelkow, 2007: 20).

As with all research, there are tradeoffs that need to be made with regard to precision,

generalizability and realism (McGrath, 1982). In order to study how reputations can be built (or

destroyed) via CSER signals, it was necessary to select a sample for which reputational data

exists. As a result, care should be taken with generalizing the findings of this study and future

research should develop additional measures of reputation and CSER-specific reputation to

determine whether the findings produced in this study are replicated in other samples. Further, as

64

the firms included in this study were generally quite large, and hence visible, results might differ

for smaller, less visible firms or firms with lesser or less visible reputations. Additionally, the

audience in this study was limited to those interested in firms’ general and CSER-specific

reputations, whereas other audiences may form different evaluations of the CSER-signals

addressed in this study.

Another limitation stems from the binary nature of many of the variables in the study.

Though more fine-grained measures are generally desired to enhance precision, the availability of

fine-grained data is limited with regards to the variables studied. For example, the data for third-

party awards was simply based on whether or not a firm received such recognition as opposed to

a more distributed rating relative to other firms. Additionally, the measure of firm partnerships is

based on the number of partnerships firms draw attention to and cannot be regarded as the true

number of CSER partnerships in which firms are engaged, as firms have the discretion to

highlight or neglect to mention various partnerships in their publicity. And, finally, the CSER

historical data was based on the presence or absence of social and environmental actions as

opposed to the severity or impact of those actions. In addition, because this study focused on U.S.

firms, it is unclear whether these findings are generalizable to other firms with headquarter in

other cultures (Stignitzer & Prexl, 2007: 11). These limitations, however, provide fruitful avenues

for future research.

Future Research

Numerous opportunities for future research are triggered by this study. First, future

research could examine whether firms with historical CSER weaknesses ever gain positive

CSER-specific reputations, and if so, how they are able to do so without self-disclosure,

partnerships, third-party awards or media favorability. In other words, what other tools for

65

reputational repair are available to firms who are historically weak in CSER? On a related note,

future research could also examine whether firms with strong CSER histories that self-disclose

actually weather reputational crises better. A variety of studies have examined the proposition of

“reputation as insurance” (Godfrey, 2005; Godfrey, Merrill & Hansen, 2009) with mixed results.

In the case of deletion from socially responsible investment (SRI) indices, Doh and colleagues

(2010) found that CSER strengths mitigated the negative effect of deletion. Additionally, Godfrey

et al. (2009) found support for the insurance perspective as loss from negative events was less for

firms engaged in CSER. However, other studies have found that firms with better reputations

suffer greater penalties for malfeasance (e.g., Rhee & Haunschild, 2006; King & McDonnell,

2012; Luo, Meier & Oberholzer-Gee, 2012). King and McDonnell’s (2012) findings also suggest

“that for all of their positive benefits, attempts to enhance CS[E]R and reputation may have an

unintentional negative side effect: they amplify a firm’s attractiveness as an activist target” (p.4).

Given these findings, it is clear that more research is needed in this area to tease out the meaning

of these mixed results. Further, though inclusion on socially responsible investment (SRI) indices

was used as a proxy to measure CSER-specific reputation in this study, future research should

strive to identify and employ other means of assessing CSER-specific reputation.

In addition to these avenues, a more fine-grained measure of disclosure should be

included in future studies. For example, within the UK context, some studies have examined the

difference between the quantity (i.e., volume) and quality (i.e., verifiability) of environmental

disclosures made in annual reports (Toms, 2002; Hasseldine et al., 2005; Brammer & Pavelin,

2006b), with findings indicating that “while environmental performance plays no significant role

in influencing the decision to make a voluntary environmental disclosure, it plays a highly

significant role in influencing the quality of environmental disclosures” (Brammer and Pavelin,

2006b: 1185). Hence, future research could examine whether an explanation for the different

results between general and specific reputation has to do with the quality, or verifiability of the

66

information provided in the disclosures. It may be that the mere act of disclosure affects general

reputation whereas the verifiability of disclosed data may be what matters for CSER-specific

reputation.

Additionally, future research should examine the accountability of signals (Kolk, 2008).

Although it was shown that CSER signals influence reputation, this analysis could not distinguish

between signals that were “ceremonial “versus “technical” (Meyer & Rowan, 1977; Zavylova et

al., 2012). In other words, it is possible that signals may have an impact on reputation because of

their symbolic value, apart from any real accountable substance. In other words, it would be

interesting for future research to compare the effects of signals with the effects of actual

performance measures to see if the impacts are the same or different. In a similar vein, in regards

to the signaling value of firm relationships, future research could examine whether the identity of

the partner or the type of partnership has implications for reputation (Gulati & Higgins, 2003). In

addition, communications theorists have suggested that involving stakeholders in the CSER

communication process improves reputation – future research should address whether firms that

have stakeholder input in disclosure have better reputations than firms that rely on one-way

communications (Morsing & Schultz, 2006; Eseneggert & Schranz, 2011), and whether bilateral

communications with stakeholders help firms weather crises, or otherwise improve CSER efforts

Finally, and perhaps most importantly, future research should examine whether a firm’s

reputation is the missing link between CSER history and future financial performance. Though

studies of the link between CSER and financial performance have produced mixed results, some

scholars have suggested that, perhaps, reputation mediates the relationship. The findings of this

study show that CSER actions do in fact influence a firm’s general reputation, and previous

research has shown that a firm’s general reputation is positively related to subsequent financial

performance. Thus, building on the findings of this study, researchers could examine whether

reputation, in fact, mediates this relationship, potentially answering the decades old question of

67

‘does it pay to be responsible?’. Along the same lines, research could investigate how long it

takes for firms to overcome negative CSER histories with regard to CSER-specific reputation, if

at all.

68

Chapter 7

Conclusions

In addition to its theoretical contributions, this study also has practical implications for

managers, and supports the idea that CSER communication is a complicated, but nonetheless

important task for firms. The implications resulting from this study are, however, somewhat

sobering. The general takeaway appears to be that firms need to know ‘when to speak up and

when to shut up’. The findings of this study counterintuitively suggest that firms with histories of

CSER strengths should ‘shut up’, while firms with histories of CSER weaknesses should ‘speak

up’. These findings provide important managerial implications, as firms attempt to meet

increasing stakeholder demands, supporting the idea that “communicating CS[E]R is a very

delicate matter, and a key challenge of CS[E]R communication is how to minimize stakeholder

skepticism” (Du et al., 2010: 10).

In an environment where firms face ever-sharper scrutiny from stakeholders who demand

information, managers must walk the fine line of CSER communication. Managers of firms with

CSER historical weaknesses should engage in self-disclosure via CSER reports and or other

channels such as the Carbon Disclosure Project, as such disclosure may communicate to

stakeholders that the firm has broken free from its historical record of irresponsibility and is

creating a path to towards improving CSER. This may improve stakeholder impressions and, as a

result, reputation. Managers at these firms should also advocate for increased firm commitment to

the development of better CSER practices to build a stronger CSER future. On the other hand,

managers of firms with CSER historical strengths should remain quiet about the firm’s CSER

efforts, while continuing to improve so that they may be conferred awards by third-party

infomediaries, without suffering a reputational penalty for self-disclosure. Managers at these

69

firms must be especially geared towards improving CSER, as the “Green Queen effect” would

suggest that the firm must continually enhance CSER activities just to maintain reputation,

whereas improving reputation would require improvement over and above the CSER status quo.

Additionally, managers of all firms should forge partnerships with CSER-oriented organizations,

such as NGOs to enhance general reputation and CSER activities. However, while these

managerial practices may improve general reputation, the findings of this study suggest that they

will not significantly impact CSER-specific reputation.

It is important to underscore that though this study would suggest that firms with strong

CSER histories shouldn’t self-disclose, it does not suggest that they shouldn’t improve their

CSER efforts. In fact, it may be that although firms with a strong CSER history may see a slight

reputational penalty for self-disclosure, this disclosure may provide a long term benefit by

building a “reservoir of goodwill” (Jones, Jones & Little, 2000: 21; Fombrun, 1996). Such a

reservoir could be held as insurance in case of crises (Godfrey et al., 2009; Doh et al., 2010),

encouraging “stakeholders to give the firm the benefit of the doubt regarding intentionality,

knowledge, negligence, or recklessness” (Godfrey, 2005: 788) and allowing firms to frame

occasional missteps as exceptions rather than the rule. In addition to building “safety nets”

(Fombrun, Gardberg & Barnett, 2000: 95), self-disclosure and partnerships may also help firms to

build “opportunity platforms” (Fombrun, Gardberg & Barnett, 2000: 89) from which additional

prospects to grow CSER efforts and hence, reputation, may spring.

However, in terms of CSER-specific reputation, the implications are quite simple –

actions do speak louder than words. So, while disclosure, partnerships, awards and media

favorability may neither help nor hurt a firm’s CSER-specific reputation, history has an important

effect. Consequently, managers wishing to improve their firm’s CSER-specific reputation

shouldn’t bother doing so via self-disclosure, partnerships, or media coverage, but instead focus

on business activities that reduce CSER weaknesses and improve CSER strengths, and potentially

70

attract third-party awards. For sure, these results suggest that it is in fact quite “important for

companies to avoid serious violations of CS[E]R standards” (Eisenegger & Schranz, 2011: 133)

so that they don’t build a history of CSER weaknesses in the first place. In particular, the findings

of this study challenge practitioners to consider the complicated and unintended effects that

CSER signaling may have. Whereas common sense would indicate that firms with positive CSER

records should toot their own horns to make sure stakeholders are aware of their CSER qualities,

such an act may backfire, resulting in reputational decline. Hence, practitioners and theoreticians

alike should take heed of the double-edged nature of CSER communications, searching for

signals that are most likely to bear the intended effects.

In conclusion, this study examined the role CSER history plays in relation for firm’s

reputations, as well as the ways in which CSER signals may affect that relationship. As such,

instead of focusing on the consequences of reputation, this research sought to examine ways in

which reputations are built in light of corporate social and environmental responsibility. Taken

together, the results of this study support the age-old adage that actions speak louder than words,

and that knowing when to speak up and when to shut up is an important component of general

reputation. Further, these findings support the multidimensional view of reputation,

distinguishing general (i.e., overall) from specific (i.e., CSER-specific) and offer practical

implications for how managers can affect firm reputation.

71

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Appendix A: Figures

Figure 1: Moderation Effect of Firm Self-Disclosure on the Relationship between CSER Historical Weaknesses and General Reputation

90

Figure 2: Moderation Effect of Firm Self-Disclosure on the Relationship between CSER Historical Strengths and General Reputation

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Figure 3: Moderation Effect of Third-Party Awards on the Relationship between CSER Historical Strengths and General Reputation

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Appendix B: Tables

Table 1. Distribution of Industries Represented

GICS Industry Sector Quantity of Firms

Representing Sector Energy 7 Materials 20 Industrials 63 Consumer Discretionary 85 Consumer Staples 49 Healthcare 49 Financials 56 Information Technology 68 Telecommunication Services 2 Utilities 13

Total 412

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Table 2: Means, standard deviations and bivariate correlations

Ϯ < .10 * p < .05 ** p < .01 *** p <.001

Mean Std. Dev.

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Controls

1. Return on Assets .06 .06

2. Market-to-Book 1.28 31.31 .19***

3. Service Industry .23 .42 -.16** -.03

4. Ethical Exclusions .01 .11 .08 .43*** -.06

5. SRI Eligibility .91 .29 .04 .01 .09 .03

6. Firm Size (Emps) 63.41 131.72 .06 .01 -.08 -.02 .06

7. Vol. Media Cov. 27.87 89.01 .09 -.01 .01 -.02 .08 .18***

Independent Variables

8. CSER Weaknesses 14.15 9.91 -.11* .06 -.14** .00 .07 .41*** .39***

9. CSER Strengths 8.49 8.27 .18** .02 -.10 -.04 .11 .23*** .23*** .47***

10. Firm Self-Disc. .89 .83 .12* -.01 .01 -.01 .29*** .24*** .14** .37*** .70***

11. Firm Partnerships 5.53 12.85 .01 -.03 -.03 .11* .09 .03 .05 .11* .20*** .33***

12. Third-Party Awards 1.10 .98 .19*** .03 -.05 -.01 .32*** .25*** .16*** .34*** .68*** .66*** .24***

13. Media Favorability .23 .36 -.03 -.02 .05 .02 .05 -.00 .03 -.06 .04 .02 .05 -.01

Dependent Variables

14. General Reputation 5.91 .99 .39*** .16** -.03 .02 .08 .14** .17*** .10 .33*** .29*** .18*** .37*** .08

15. CSER Reputation .62 .49 .24*** -.08 .17*** -.10* .38*** -.01 .06 -.09 .30*** .37*** .06 .40*** .05 .20***

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Table 3: Results of Linear Regression Predicting General Reputation

(DV: General Reputation)

Model 1: Controls Only

Model 2: Main Effects Hypothesis 3

Model 3: Firm Self-Disclosure

Hypotheses 1-2

Model 4: Third-Party Awards

Hypotheses 4-5

Model 5: Media Favorability

Hypotheses 6-7

Model 6: Full Model

Std. Beta

S.E. Std. Beta

S.E. Std. Beta

S.E. Std. Beta

S.E. Std. Beta

S.E. Std. Beta

S.E.

Controls Market to Book (log) .19*** .05 .17** .06 .15** .06 .15** .06 .16** .06 .15** .06 Services (ind control) .03 .11 .08 .12 .06 .11 .07 .12 .08 .12 .06 .11 Firm Size (ln ) .12* .04 .02 .05 -.03 .05 .01 .05 .02 .05 -.04 .05 Total Vol Media (log) .14*** .03 .09 .04 .09 .04 .09 .04 .09 .04 .09 .04 Independent Variables CSER Hist. Weaknesses -.02 .01 -.12 .01 -.08 .01 -.02 .01 -.12 .01 CSER Hist. Strengths .16 Ϯ .01 .51*** .01 .28** .01 .16 Ϯ .01 .51*** .01 Firm Self-Disclosure -.04 .09 -.18* .09 -.09 .09 -.04 .09 -.18* .10 Firm Partnerships .14** .04 .14** .04 .13* .04 .14* .04 .14* .04 Third-Party Awards .16* .07 .17* .07 .22** .08 .16* .07 .17* .08 Media Favorability .08 .14 .05 .14 .07 .14 .08 .15 .05 .15 Interactions Firm Self-Disc_X_ Weaknesses .16* .01 .17* .01 Firm Self-Disc_X_ Strengths -.36*** .01 -.37*** .01 Third-Party_X_ Weaknesses .07 .01 -.02 .01 Third-Party_X_ Strengths -.18* .01 .01 .01 Media Favorability_X_ Weaknesses -.03 .02 -.05 .02 Media Favorability_X_ Strengths .03 .03 .03 .03 F-value 13.72*** 7.38*** 8.14*** 6.66*** 6.13*** 6.08*** Adj. R-sq (Δ adj. R-sq from controls) .12 .17 (.05) .21 (.09) .18 (.06) .16 (.04) .21 (.09) n 361 314 314 314 314 314 coldiag condition 4.13 5.43 6.81 6.09 5.47 7.75 avg. VIF (range) 1.17 (1.05,1.28) 1.68 (1.07, 2.78) 2.10 (1.08, 5.54) 1.93 (1.08, 3.86) 1.69 (1.17, 2.79) 2.33 (1.19, 5.62) Ϯ < .10 * p < .05 ** p < .01 *** p <.001

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Table 4: Results of Logistic Regression Predicting CSER-Specific Reputation

(DV: SRI Inclusion)

Model 1: Controls Only

Model 2: Main Effects Hypothesis 3

Model 3: Firm Self-Disclosure

Hypotheses 1-2

Model 4: Third-Party Awards

Hypotheses 4-5

Model 5: Media Favorability

Hypotheses 6-7

Model 6: Full Model

Odds Ratio

S.E. Odds Ratio

S.E. Odds Ratio

S.E. Odds Ratio

S.E. Odds Ratio

S.E. Odds Ratio

S.E.

Controls ROA (standardized) 2.14*** .40 1.43 .33 1.42 .33 1.44 .34 1.40 .33 1.39 .33 Market to Book (log) .95 .16 1.20 .27 1.20 .27 1.18 .27 1.25 .29 1.24 .29 Services (ind control) 2.14* .64 2.83** 1.13 2.86** 1.16 2.82* 1.14 2.88** 1.16 2.91** 1.20 Ethical Exclusions .06* .07 .22 .26 .22 .26 .20 .25 .24 .29 .21 .26 Firm Size (ln ) 1.11 .12 1.31 Ϯ .20 1.34 Ϯ .21 1.26 .20 1.31 Ϯ .20 1.29 .21 Total Vol Media (log) 1.28** .12 1.23 Ϯ .16 1.23 .16 1.25 Ϯ .16 1.25 Ϯ .16 1.26 Ϯ .17 Independent Variables CSER Hist. Weaknesses .86*** .02 .86*** .02 .87*** .02 .86*** .02 .86*** .02 CSER Hist. Strengths 1.22*** .06 1.23*** .06 1.23*** .06 1.22*** .06 1.21*** .06 Firm Self-Disclosure 1.03 .30 1.11 .39 .97 .29 1.04 .30 1.22 .45 Firm Partnerships .81 .11 .81 .11 .80 .11 .81 .11 .80 .11 Third-Party Awards 1.58 Ϯ .43 1.59 Ϯ .43 1.58 .45 1.58 Ϯ .43 1.55 .44 Media Favorability 1.37 .59 1.39 .60 1.34 .59 1.47 .79 1.60 .89 Interactions Firm Self-Disc_X_ Weaknesses 1.00 .03 .99 .03 Firm Self-Disc_X_ Strengths 1.02 .06 1.07 .07 Third-Party_X_ Weaknesses 1.00 .02 1.00 .03 Third-Party_X_ Strengths .98 .04 .95 .04 Media Favorability_X_Weaknesses 1.04 .08 1.04 .08 Media Favorability_X_ Strengths 1.01 .12 1.02 .12 Log Likelihood -201.65 -132.53 -132.46 -132.11 -132.13 -131.07 LR Chi-Square 47.74*** 110.00*** 110.14*** 110.84*** 110.80*** 112.91*** Psuedo R-sq (Δ R-sq from controls) .11 .29 (.18) .29 (.18) .30 (.19) .30 (.19) .30 (.19) n 362 315 315 315 315 315 coldiag condition (good > 30 4.95 6.32 7.46 7.34 6.36 8.05 avg. VIF (range) (good >10) 1.25 (1.04, 1.48) 1.66 (1.03, 2.92) 2.02 (1.03, 5.83) 1.89 (1.03, 2.66) 1.68 (1.05, 2.93) 2.23 (1.05, 5.93) Ϯ < .10 * p < .05 ** p < .01 *** p <.001

96

Vita

Jenna P. Stites

EducationPh.D., Pennsylvania State University, University Park, PA, August 2014 M.S., Pennsylvania State University, University Park, PA, August 2008 B.S., Miami University, Oxford, OH, August 2005

Research Interests

Broadly speaking, I am interested in how organizations interact with their environments. In particular, my research focuses on the intersection of Organization Theory and Corporate Social Responsibility and Environmental Sustainability, with regard to corporate image and reputation. I seek to understand how organizations make sense of their social and environmental responsibilities, act on them, and communicate their efforts to stakeholders.

Publications

Gray, B. & Stites, J. P. 2013. Sustainability through partnerships: Capitalizing on collaboration. Network for Business Sustainability. Gray, B. & Stites, J. P. 2011. In search of integrated logics: Reframing the climate change debate. Strategic Organization 9(1): 85-90. Stites, J. P. & Michael, J. H. 2011. Organizational commitment in manufacturing employees: Relationships with corporate social performance. Business & Society 50(1): 50-70.

Awards, Grants and Scholarships John & Kara Arnold Scholarship, Smeal College of Business, Penn State, 2011-2014. Network for Business Sustainability $25,000CDN Grant, with Barbara Gray, 2013. Page Legacy Scholar, Arthur W. Page Center, Penn State. College of Comm., 2012-2013. Grace G. Albrecht Scholarship, Smeal College of Business, Penn State, 2012-2013. Jeanne and Charles Rider Fellowship, Smeal College of Business, Penn State, 2011-2012. Dean’s Scholarship, Smeal College of Business, Penn State, 2011-2012. Outstanding Reviewer Award, Academy of Management, SIM Division, 2011. Frank & Mary Jean Smeal Scholarship, Smeal College of Business, Penn State, 2009-2010, 2010-2011. Smeal Research Grant Awards, Penn State, Spring 2010, Fall 2010(2), Spring 2011, Fall 2011, Fall 2012, Fall 2013, Spring 2014