Product Recalls Conceptualized As Social Dilemmas

PRODUCT RECALLS CONCEPTUALIZED AS SOCIAL DILEMMAS

By SKYLER MASAJI KING

A dissertation submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

WASHINGTON STATE UNIVERSITY Carson College of Business

MAY 2016

To the Faculty of Washington State University:

The members of the Committee appointed to examine the dissertation of SKYLER

MASAJI KING find it satisfactory and recommend that it be accepted.

______Jeff Joireman, Ph.D., Chair

______Andrew Perkins, Ph.D.

______Joyce Ehrlinger, Ph.D.

ACKNOWLEDGEMENT

Throughout my time here at Washington State University, I have had the opportunity to

meet exceptional scholars. First and foremost I would like to thank Dr. Jeff Joireman for his

mentorship and guidance from day one. I could not have asked for a better mentor and friend

throughout my time here. He has offered caring support throughout the program, allowing me to

make and learn from my mistakes and never letting me take the easy way out through any

process or project. Dr. Joireman, you have been a dedicated mentor and I sincerely hope to not

only grow into a successful scholar like you are, but also grow into the type of person you are.

I would also like to thank Drs. Andrew Perkins and Joyce Ehrlinger for the great resource

they have been throughout the dissertation process. I feel very fortunate to have learned from

them. Their academic pedigree is truly amazing. Additionally, their enthusiasm for research and

helping students is second to none and I hope to emulate their knowledge and work ethic

throughout my career in academia. Thank you.

Throughout the program, I have also had the benefit to work with Drs. Darrel Muehling

and Ioannis Kareklas. They have been an integral part of my research and experience as a PhD

student. They have also shown an incredible amount of patience and wisdom as I have learned

the research process from them. Truly, their experiences and insights will benefit me throughout

my career. I would also like to thank my fellow student colleagues at Washington State

University. All of them have been supportive, encouraging, and helpful throughout my time here.

There are too many names to list, though a heartfelt thank you for believing in me and for being good friends.

iii

Before I came to Washington State University, I had the privilege of studying at Weber

State University. My first class I took there was a Principles of Marketing course taught by Dr.

Tony Allred. I had never taken a marketing course before, but the way Dr. Allred taught the

course, I became more interested in the topic. To me the class was difficult and I had a limited

marketing background so I had little confidence that I would succeed. I remember going to his

office one day to get further clarification on an assignment and he told me that I was working

hard and I’ll succeed in the class. He let me know that I had a mind for marketing and while I did

not feel that, hearing that from him gave me the confidence I needed to succeed.

As time went on, I thought about pursuing a Ph.D. and I wanted to make sure that I

would like academic research. Dr. Allred as well as Dr. Erhard Valentin were kind enough to include me in their research and I enjoyed learning about the research process from them. Both professors have been supportive of me throughout this process and have continued to work with me on different projects. I feel honored to go back to Weber State University to continue collaboration with them.

I must also thank my two uncles, Michael King and Ron Vogel. I had the privilege to take collegiate courses from them in two subjects that I did not care much about; biology and accounting respectively. Although I did not enjoy the subject, I noticed how they cared for each

of their students including me. They have been an example to me and I hope to be as effective as they are at reaching students. They have also let me know, even when I did not feel like it, that I

was a good student and that I will be successful in my choice of studies.

Finally, I’d like to acknowledge all the love and support provided by my immediate

family members during this period of my life. To my father, Brad King, from a young age I have

iv always looked up to you and have learned daily from your example. You are the one person that

I try to model my life after. Because of you, I have had the confidence that I can make a difference in the lives of those I have the opportunity to serve through teaching, research, and any other opportunities that come my way. To my dear mother, Tami King, watching you pursue your education while simultaneously raising a family of three children and always putting your children first is a memory that continues to drive me personally and professionally. As successful as you were pursuing your degrees, I see your biggest success as having raised a family (with the help of dad) of good, kind, successful children.

To my sister, Kitani Anderson, you have been a great example to me in my life. Your hard work in school when you were younger and continued dedication to your family has and will continue to serve as a constant guide in my life. To my brother, Hunter King, you too have been a great help to me in my life. Your confidence in me throughout my life has helped me more than you will ever know. I too see you as a good example to me in your work and your dedication to your family. To my nephew, Cort Anderson, who is currently only 4 years old, thank you for your care and support. It was a long process studying for my comprehensive exams and it was you who offered a prayer at that time that I “wouldn’t be scared and wouldn’t be eaten by dinosaurs.” I am happy to say that I wasn’t scared and I was not eaten by dinosaurs.

Without intention to boast or brag but to give sincere thanks, I have been blessed to have had the best help to reach this point in my life. To my family, friends, and faculty members heartfelt thanks to all of you.

PRODUCT RECALLS CONCEPTUALIZED AS SOCIAL DILEMMAS

Abstract

by Skyler Masaji King, Ph.D. Washington State University May 2016

Chair: Jeff Joireman

This dissertation explores the product recall decision. I first posit that the product recall decision can be viewed as a social dilemma where short-term individual interests and long-term collective interests are at odds. Consistent with this reasoning, Study 1 finds that the product recall decision can be viewed as a social dilemma. Building on these findings, Studies 2-4 explore how factors found to influence cooperation in social dilemmas impact the product recall decision. Study 2 explores how decision makers’ time-horizons, CFC, and perception of the decision affect their willingness to recall a product. Results show that decision makers’ time- horizon does not affect one’s willingness to recall a product. However, CFC effects recall intentions through ethical perceptions of the decision. When decision makers’ CFC is high and when the decision is perceived as being an ethical decision, willingness to recall a product increases. Study 3 explores how group size affects willingness to recall a product and study 4 explores how anonymity and product defect severity affect willingness to recall. Study 3 and 4 replicates the effects of CFC and ethical perceptions of the decision on willingness to recall, however, group size, anonymity, and product defect severity did not affect willingness to recall.

TABLE OF CONTENTS

ACKNOWLEDGEMENT…………………………………………………………….…………iii

ABSTRACT………………………………………………………………………………….…..vi

LIST OF FIGURES……………………………………………………………………….……...ix

DEDICATION……………………………………………………………………………………x

CHAPTER 1………………………………………………………………………………………1

CHAPTER 2………………………………………………………………………………………4

CHAPTER 3……………………………………………………………………………………..11

CHAPTER 4……………………………………………………………………………………..22

Study 1…………………………………………………………………………………...22

Study 2…………………………………………………………………………………...31

Study 3…………………………………………………………………………………...39

Study 4…………………………………………………………………………………...47

General Discussion………………………………………………………………………53

REFERENCES…………………………………………………………………………………..58

APPENDIX A……………………………………………………………………………………66

APPENDIX B……………………………………………………………………………………67

APPENDIX C……………………………………………………………………………………68

vii

APPENDIX D…………………………………………………………………………………....69

APPENDIX E……………………………………………………………………………………70

APPENDIX F……………………………………………………………………………………71

viii

LIST OF FIGURES

1. FIGURE 1………………………………………………………………………………..26

2. FIGURE 2………………………………………………………………………………..29

3. FIGURE 3………………………………………………………………………………..37

4. FIGURE 4………………………………………………………………………………..37

5. FIGURE 5………………………………………………………………………………..37

6. FIGURE 6………………………………………………………………………………..44

7. FIGURE 7………………………………………………………………………………..44

8. FIGURE 8………………………………………………………………………………..45

DEDICATION

For their unconditional love and support throughout my life, I dedicate this work to my grandparents; LaVell and Mayzell King, Masaji and Tsuruko Imai

CHAPTER 1

INTRODUCTION

One ought never to turn one’s back on a threatened danger and try to run away from it. If you do that, you will double the danger. But if you meet it promptly and without flinching, you will reduce the danger by half. Never run away from anything. Never!

-Winston Churchill-

The relevance of ethical decision making organizational contexts has led scholars in a variety of disciplines to investigate drivers of ethical behavior (see Treviño, den Nieuwenboer, and Kish-Gephart, 2014 for a review). Stakeholders, including governments, have and will

continue to place pressure on organizations to minimize employees’ unethical conduct. One

ethical decision that has gained much recent media attention, and that organizations must often

face, is whether to issue a product recall. Product recalls occur frequently in today’s marketplace,

and most of the time they are very costly.

One of the most well-known product recalls occurred in 1982 when Johnson & Johnson

recalled its pain reliever Tylenol after seven people died when an unidentified person or persons

had replaced some Extra-Strength Tylenol capsules with cyanide capsules. While Johnson &

Johnson was not at fault for the deaths, they recalled all of the capsules, which ended up costing

the company more than $100 million. More recently, in early 2015, airbag maker Takata was

part of the largest auto recall in history with over 34 million recalled automobiles (CNN Money,

2015). Before the recall, Takata had been very successful with sales growth of about 15% in the

2015 fiscal year and a predicted profit of $177 million. However, the recall caused a net loss of approximately $250 million (CNN Money, 2015).

With the abundance of organizations issuing product recalls, marketing scholars have devoted attention to product recalls. The majority of the work on product recalls has focused on firm recall strategies (Chen, Ganesan, and Liu, 2009), consumer perceptions and responses of recalls (Cleeren, Dekimpe, and Helsen, 2008), and the consequences of recalls on firm performance (van Heerde, Helsen, and Dekimpe, 2007). Although these foci make sense, due to the implications a product recall has on consumer responses and firm performance, to date, research has disregarded the product recall decision itself. In particular, there has been little research on factors that drive the decision to issue a product recall.

To address this gap in the literature, the present dissertation attempts to conceptualize the product recall decision and identify factors that influence its likelihood. Specifically, I propose that the decision to issue a product recall can be conceptualized as a social dilemma, which is defined as a situation where there is a conflict between short-term individual interests and long- term collective interests (Messick and Brewer, 1983; Parks, Joireman, and Van Lange, 2013;

Van Lange, Joireman, Parks, and Van Dijk, 2013). Viewing product recalls as a type of social dilemma provides a theoretical lens through which to understand and predict the product recall decision.

This dissertation makes four distinct contributions to the marketing and social dilemma literatures. First, focusing on the product recall decision itself extends the literature on product recalls which has largely focused on the financial consequences of recalls for firms. Second, viewing product recalls through the lens of social dilemmas extends social dilemma research into

2 the domain of marketing, where social dilemmas have direct relevance but little exposure. Third, integrating the work on product recalls and social dilemmas allows dilemmas researchers who haven’t recognized that product recall decision may be another type of social dilemma to extend research on social dilemmas. Fourth, I address a recent call to develop theory aimed at improving the well-being of consumers and society through marketing (Davis and Pechmann, 2013).

This dissertation is organized as follows: First, I give an overview of theory and past research on product recalls (chapter 2) and social dilemmas (chapter 3) respectively. Next, I outline my four studies (chapter 4) developed to address two primary questions: (1) Can the decision to recall a product be conceptualized as a social dilemma? (2) What features of the situation influence the likelihood of recalling a product? As I will argue, the product recall decision shares important similarities with social dilemmas. Consequently, a number of factors that predict cooperation in social dilemmas should also predict the willingness to issue a product recall (e.g., time horizon of the decision maker, anonymity, and group size/diffusion of responsibility). At the broadest level, all of these factors share in common the potential to influence consequences for the decision maker (self) and the collective/society (other), in line with a social dilemma analysis of product recalls.

CHAPTER 2

PRODUCT RECALLS

In the United States, product safety is a concern and responsibility of the federal government. In order to protect consumers from product harm, the federal government has created separate agencies to oversee consumer protection from products in different categories.

Three of the main agencies include the Food and Drug Administration (FDA), The National

Highway Traffic Safety Administration (NHTSA), and the Consumer Product Safety

Commission (CPSC). For example, the FDA oversees the safety of six different product categories: food, drugs, medical devices, radiation-emitting products, vaccines, blood and biologics, animal and veterinary, cosmetics, and tobacco products (www.fda.gov). The NHTSA has jurisdiction over any type of automobile such as trucks and motorcycles (www.nhtsa.gov) and the CPSC has jurisdiction over the majority of consumer products such as toys, lawn movers, and coffee makers (www.cpsc.gov).

The recall process for the CPSC is important in order to understand the features of the situation managers have to deal with. The process that leads to a product recall usually begins with the firm or the CPSC receiving information from suppliers, buyers, or customers concerning the problem or potential problem of a product. The CPSC has a website that consumers or businesses can use to notify the CPSC of a potential problem (www.saferproducts.gov). The

CPSC also has a 24-hour hotline that can be used to address issues relating to product hazards.

From the years 2009-2012, the CPSC hotline received more than 526,000 calls with the majority relating to product recalls (www.cpsc.gov).

If a firm receives reportable information or evidence supporting a hazardous product, it

has a 24 hour window in which to report to the CPSC (http://www.cpsc.gov/en/Business--

Manufacturing/Recall-Guidance/Duty-to-Report-to-the-CPSC-Your-Rights-and-

Responsibilities/). After the report, the CPSC and the firm work together to determine whether the product needs to be recalled. If a product is deemed potentially harmful, the CPSC or the firm can decide to issue the recall. The firm can also decide to issue a recall without waiting for the research to be done on the potential dangers of the product. The CPSC created a program call the “Fast-Track recall program” where the firm issues a recall before going through the risk analysis (http://www.cpsc.gov/en/Business--Manufacturing/Recall-Guidance/CPSC-Fast-Track-

Recall-Program/).

In some cases, the CPSC may tell the firm that a recall should be issued and the firm does not agree. If this occurs, the CPSC can enforce a mandatory recall, however, these require legal proceedings which take time and money. After the recall has been issued, the public at large is notified and the defective products are removed as soon as possible. Firms differ in their reactions to potential product recalls. Firms can be cooperative or uncooperative with the federal agency, and can proactively work to recall the product as soon as possible or delay the decision.

With these differences between firms, many marketing implications can be studied in terms of how and when a firm goes about issuing a recall. Most research on product recalls to date has focused on the performance consequences, recall strategies, advertising efforts post-recall, and consumer responses.

In 2012, the CPSC publicized more than 250 product recalls, and the Food and Drug

Administration announced more than 300. Product recalls have also increased in recent years.

The National Highway Traffic Safety Administration (NHTSA) reported a 76% increase in automotive recalls between two ten year periods 1994-2003 and 2004-2013 (Gao, Xie, Wang, and Wilbur, 2015). With the abundance of product recalls in the marketplace, research in marketing has looked at different theoretical and practical implications. Some of these topics include firm recall strategies (Chen et al. 2009), consumer perceptions and responses of recalls

(Mowen, 1980; Mowen, Jolly, and Nickell, 1981; Jolly and Mowen, 1985), and consequences of firm performance (van Heerde et al. 2007).

Firm Recall Strategies

As firms anticipate making a recall on a product, many different strategies can and have been used. Past literature states there are four categories into which crisis management strategies can be classified: denial, forced compliance, voluntary recall, and “super-effort” (Siomkos and

Kurzbard, 1994; Laufer and Coombs, 2006). In a denial strategy, the company decides to deny any responsibility for their defective product on the market. In a forced compliance strategy

(involuntary recall), the company recalls the defective product after it is ordered to by one of government protection agencies.

When a company uses a voluntary recall strategy, in contrast, the company recalls the defective product before it is ordered to by one of the government protection agencies. Finally, in a “super-effort” strategy, the company will use its resources to be open and extensive in their communications with society and fully disclose the problem with their products and also offer a generous compensation package for those effected. More recently, literature has classified denial and forced compliance strategies as passive and voluntary and super-effort strategies as proactive

(Chen et al. 2009).

Consumer Responses to Product Recalls

In addition to documenting the financial consequences of recalling a product, research has investigated consumers’ perceptions of companies that have had to make a product recall.

Generally speaking, consumers have negative perceptions and responses of companies that recall

a product (Ahluwalia, Burnkrant, and Rao, 2000; Laufer, Gillespie, McBride, and Gonzalez,

2005). An empirical study has shown that the greater the extent of injury the product causes to

the consumer, the greater the number of previous recalls the company has had to make, and the

longer it takes the company to make the recall all increase negative consumer perceptions of and

responses to the company (Mowen, 1979a). In a subsequent study, Mowen (1979b), manipulated

how familiar the company is to consumers and whether the Consumer Product Safety

commission (CPSC) forced the company to recall the product. They found that a company that is

more familiar to consumers is perceived as less responsible for a defective product than a

company that is unfamiliar to them. Further studies have also shown similar effects in a non-

experimental setting. Using a survey approach, Mowen et al. (1980) investigated consumer

perceptions of actual product recalls. They found that the perceived danger of the product, the company’s social responsibility by making the recall, and the company’s perceived responsibility for the defective product were the best predictors of the consumers’ favorability toward the

company.

Consumers also differ in their perceptions depending on the type of recall strategy the

company uses. For example, when a company uses a denying strategy, consumers have a

negative image of the company and when a company uses a voluntary recall strategy, it will

mitigate the negative effects of the product recall (Mowen, 1976b; De Matos and Rossi, 2007;

Souiden and Pons, 2009). Overall, consumers have negative impressions of companies that make product recalls, but there are things that companies can do to mitigate the negative impressions consumers will have.

Impact of Product Recalls on Firm Performance

It should come as no surprise that recalling a product has performance implications for the issuing firm. Much research has looked at a myriad of performance measures as a way to gauge the negative effects of a product recall. Using a case study in Australia from Kraft peanut butter, Van Heerde et al. (2007) finds that firms can experience serious problems in four different areas. Specifically, but not limited to problems of baseline sales loss, reduced effectiveness for the firm’s marketing effectiveness, cross sensitivity to rival firms’ marketing efforts, and the negative impact of one product spilling over to other products within the same company.

In addition to sales, profit, and market share loss, issuing product recalls tend to sour consumers’ quality perceptions of the company’s products and tarnish the company’s reputation

(Laufer and Coombs, 2006; Rhee and Haunschild, 2006). While having devastating effects for the company issuing the product recall, another serious problem of a product recall is that it not only affects the company issuing the recall, but the entire industry which the recalling company is in could be perceived as having a problem of a similar nature after the recall is made (De

Alessi and Staff, 1994). Therefore a product recall by a company in the toy industry may lead to consumers losing confidence in the entire industry. In each of these cases, there are huge implications for the company making the recall, companies that are in the same industry as the

one making the recall, and society at large. However, companies tend to differ in how they

handle a product recall.

Key Gaps in the Product Recall Literature

Despite the research on product recalls, there are two key gaps in the literature. First,

scholars have yet to look at the individual factors that predict a product recall decision. Second,

there is not a strong theoretical framework that is being used to understand it. Past research has

been insightful as far as consequences at the firm and consumer levels for product recalls,

however, a theoretical framework of the product recall decision will help scholars understand the underlying mechanisms of the product recall decision to date. Efforts directed toward a theoretical and practical understanding of the product recall decision will help scholars develop further research questions about what could influence companies to be more willing to make a product recall.

Framing product recalls as a social dilemma is advantageous because research in social dilemmas has a strong theoretical background that offers explanations how individuals make decisions when there are tradeoffs between individual and collective interests. If the product recall decision can be conceptualized as a social dilemma, the marketing field would be able to use theories applicable in a social dilemma context to get an understanding of the product recall decision. This could also lead to the field identifying factors that would make companies more likely to issue a product recall.

The benefits of studying the product recall decision as a social dilemma have been noted in this chapter. In the following chapter, I give an overview of past research on social dilemmas and highlight their theoretical overlap with the product recall decision. Additionally, I describe

9 three factors that have been shown to influence cooperation in social dilemmas and which have direct relevance for the product recall decision (time horizon, anonymity, and group size).

CHAPTER 3

SOCIAL DILEMMAS

Consumers and businesses often find themselves faced with various types of social

dilemmas, which have been defined as situations where there is a tradeoff between short-term

individual interests and long-term collective interests (Van Lange et al., 2013). The prevalence of

social dilemmas has prompted scholars to understand how consumers act when they are

confronted with them. There two main types of social dilemmas that have been defined in

literature is social fences and social traps.

Types of Social Dilemmas

In a social dilemma context there are two different situations that exemplify the conflicts

between immediate and delayed consequences of one’s action; social fences and social traps.

Broadly stated, a social fence is a situation where a decision results in short-term negative

consequences for the individual making the decision, but has positive long-term consequences

for the individual and the collective. On the other hand, a social trap is a situation when a

decision results in short-term positive consequences for the individual making the decision, but

has long-term negative consequences for the individual and the collective.

Examples of social fences can be found in many public goods dilemmas. A public good is an “entity that relies in whole or in part on contributions to be provided” (Parks et al., 2013).

Charities such as the American Red Cross are good examples of public goods as they use societal donations in order to help those who need assistance. The difficulty for individuals deciding whether or not to donate money to a charity or any other public good is that everyone including non-donors can use the service offered, regardless of whether (or how much) they donated. For

example, the American Red Cross will help an individual in need regardless of whether he or she

has made donations in the past. This makes it tempting for people to take advantage of others’ monetary donations. In addition, when individuals decide to give to a public good, they usually won’t see an immediate benefits but rather delayed ones. Therefore, individuals contemplating whether to donate deal with a conflict of an individual short-term negative consequence vs. a

long-term positive result for the collective.

Examples of social traps can be found in any resource dilemma. A resource dilemma

occurs when there is a common resource for a group of individuals and individuals must decide

how much of the resource to use. For example, many areas of the world have a shortage of water

and it is not uncommon for government leaders to ask its citizens to conserve water. Individuals

have a decision to make whether they want to ignore the request and use as much water as they

want to or comply with the request and curb their water usage. An individual in this situation will

stand to benefit most in the short-term by ignoring the request and using all the water he or she

wants, but if everyone ignores the request and uses as much water as they want to, the resource

may become depleted and everyone will be worse off than if everyone had complied.

Much research on social dilemmas, has taken place in a number of disciplines and a

number of theories have been used to understand how people make decisions when facing social

dilemmas. One prominent theory is the appropriateness framework (Weber, Kopelman, and

Messick, 2004).

Appropriateness Framework

According to the appropriateness framework (Weber et al. 2004), individuals make

decisions based three factors; their definition of a situation, their identity, and their selection of

12 decision rules or heuristics (March, 1994). First, an individual in a social dilemma tries to make sense of the situation he or she is in. The individual will ask him or herself questions like “What is expected of me in this situation?” or “What would others do in this situation?” External factors also play a role in how an individual will define the situation he or she is in. For example, group size may play a role in whether an individual will decide to act in the best interests of the group.

An individual’s identity will also play a big role in how the situation is interpreted. An individual’s identity at a broad level is made up of social motives, personal history, gender, and personality. Social motives or one’s social value orientations are individuals’ “relatively stable preferences with respect to their own and others’ outcomes in social dilemmas” (Weber et al.

2004). Broadly stated, individuals tend to be either prosocial or proself. If an individual is prosocial, they tend be more cooperative in a social dilemma setting and seek to maximize joint outcomes. Proselfs tend to look at a decision context as what will maximize their own outcomes relative to others.

One’s personal history will also affect how a situation is interpreted. Individuals may have been through certain situations where a tradeoff between individual interests and collective interests are at odds. If this is the case, they may decide to do something similar if the outcome was pleasing to them in the past. Gender is also related to individuals’ identity that will influence how the act in a social dilemma. Research has shown that women more than men, are motivated by prosocial motives and men more than women are motivated by proself motives (Van Lange,

De Bruin, Otten, and Joireman, 1997). Finally, personality, or individual traits that influence how individuals make decisions in a social dilemma are a part of one’s identity. For example, some individuals are motivated to please others when they make a decision. Specifically, individuals

who are high self-monitors tend to cooperate more than low self-monitors in a social dilemma

context (Boone, De Brabander, and van Witteloostujin, 1999). High self-monitors tend to be

highly responsive to situations where they can appear favorably to others and a social dilemma

context is a situation where they can impress others by sacrificing self-interests to benefit the collective.

In the end, individuals use heuristics as a guide to make a decision how to act. One heuristic that an individual might use is utility maximization where one looks to obtain the greatest payoff for the least expenditure of effort or money. Another heuristic that individuals use it that in a social dilemma context, the benefit of women and children come first (Allison and

Messick, 1990). At the broadest level, the appropriateness framework shows that features of the situation influence the decision maker’s identity which leads to how the decision to be made is perceived. The perception of the situation will then lead to the decision maker’s choice of heuristics, which leads to the ultimate decision.

Integrative Model of Decision Making in Social Dilemmas

Building and extending off of the appropriateness framework, a new integrative model of decision making in social dilemmas has been developed (Parks et al., 2013). This framework of decision making stresses the importance of situational factors in the social dilemma, including features of the decision and features of the situation. According to Parks et al. (2013), features of the decision in a social dilemma include incentive structures, framing, understanding of the dilemma, nature of resources, decision protocol, time horizon, and uncertainty. Common features of the situation include: group size, identifiability of choices, communication, norms, commitment to cooperate, sanctions, roles, respect, social identification, and presence of an out-

group (Parks et al., 2013). These structural influences have been thoroughly researched in a

variety of literary domains to show differing effects on cooperation within a social dilemma

context.

Product Recalls as Social Dilemmas

Within a marketing context, one example of a social dilemma is the decision to recall a

product. Specifically, a product recall could be costly to the organization in the short term but

beneficial to society in the long term. If the product recall decision can be conceptualized as a

social fence, there must be negative consequences for the organization in the short-term leading

to positive long-term consequences for the collective society. Additionally, if when an

organization decides not to issue a product recall can be conceptualized as a social trap, there

must be short-term benefits for the organization leading to long-term costs for the collective society. Therefore, assuming the product recall decision is conceptualized as a social dilemma, it is worthwhile to discuss factors that influence social dilemma decisions that might be relative to the product recall decision two of which include the perception of the decision to be made, and the individual’s consideration of future consequences.

Perception of the Decision. Tenbrunsel and Messick (1999) found that the way a decision is framed in a social dilemma context affects levels of cooperation. Individuals may perceive a business decision as personal, business, ethical, environmental, or legal. Tenbrunsel and Messick

(1999) found that when a decision is framed as ethical, cooperation was at the highest level and when the perception was a business decision frame, cooperation levels were at its lowest level.

Similarly, the decision on whether or not to recall a product may be explained by how it is perceived. Like past results in social dilemmas have shown, when the product recall decision is

perceived as an ethical decision, the likelihood of recalling should be higher than if the decision is perceived as being a business or personal decision.

Consideration of Future Consequences. One individual difference variable that has

received a lot of attention in the consumer behavior literature lately and is directly applicable to

social dilemmas in a marketing context and may be related to the product recall decision is the

Consideration of Future Consequences (Strathman, Gleicher, Boninger, and Edwards, 1994). The

Consideration of Future Consequences or CFC is defined as “the extent to which people consider

the potential distant outcomes of their current behaviors and the extent to which they are

influenced by these potential outcomes” (Strathman et al. 1994, p. 743). The CFC construct has

predicted many important consumer behaviors in a variety of domains dealing with social

dilemmas (for reviews, see Joireman and King, in press; Joireman, Strathman, and Balliet, 2006).

When confronted with a social dilemma, individuals high in CFC place a high degree of importance on the possible delayed outcomes of their present actions when making a decision that has a tradeoff between immediate and future benefits.

The consideration of future consequences has been used in many outcome domains such as health behavior, financial decision-making, work-related behavior, environmental decision- making, and ethical decision making in organizational contexts. Reviewing findings from previous research on CFC, a common theme among these outcomes becomes clear. Most of the behaviors that CFC has been associated with involve trading immediate individual benefits for longer term benefits to oneself, society, or both. The most relevant of these outcomes to the product recall decision is ethical decision making in an organizational context.

Previous findings on the relationship between CFC and ethical decision making shows

that individuals high in CFC are more likely to demonstrate a stronger moral reasoning than

individuals low in CFC (Hafer, 2000). Additionally, studies in this domain have also shown that

individuals high in CFC use more ethical negotiation strategies (Hershfield, Cohen, and

Thompson, 2012), place a stronger emphasis on ethics and social responsibility in business

(Robbins, 2012), and display higher moral character in the workplace (Cohen et al., 2014).

Because product recall decisions are common in the workplace, if individuals perceive the

product recall decision to be a social dilemma, CFC may act as a factor to explain the recall

decision.

In addition to an individual’s consideration of future consequences and the way social

dilemmas are perceived, past research has shown that factors like a decision-maker’s time

horizon and anonymity, as well as group size predict acting cooperatively in a social dilemma context. While many factors could affect the product recall decision, I have chosen these three to test because they are directly relevant in a social dilemma context. Additionally, these three factors deal with consequences for the self and others and are therefore connected theoretically. I begin with a discussion of factors at the individual level (time horizon, anonymity) that affect cooperation levels followed by a logical transition to the factors at the group level (group size) that affect cooperation levels.

Factors Influencing Cooperation

Individuals’ Time Horizon. Social dilemmas often have a temporal aspect to them. In other words, the actions that benefit the individual in the short-term often produce opposing outcomes in the future. As a result, a decision makers’ time horizon in social dilemmas is a key

17 determinant of whether they will cooperate. Axelrod (1984) introduced the concept of “the shadow of the future” which suggests that individuals adopt a long-term perspective when they are involved in social dilemmas that require repeated choices (which increases the odds that others will know the person’s choice and be able to respond accordingly, for example, by punishing non-cooperation.). Moreover, research has shown that when individuals merely anticipate repeated interaction with others in a social dilemma, cooperation levels increase (Van

Lange, Klapwijk, and Van Munster, 2011).

Relevant to a social dilemma context, the use of natural resources has always been a topic of interest to government and public policy makers. Often the decision to conserve water requires short-term personal sacrifice in order to benefit the long-term societal interests.

However, individuals may not be strongly motivated to use these resources in a conservative way if they know that the negative consequences of using them haphazardly won’t be manifest for a long period of time. Moreover, research in an experimental setting has shown that individuals have an increased willingness to support public policies that are in favor of conserving natural resources when the policies will be implemented in the distant future (Rogers and Bazerman,

2008).

In a product recall context, individuals who have a short-time horizon may not consider the possible negative future consequences because they will not be around to face them. This may lead individuals to not recall a product. Many individuals change jobs or switch careers multiple times throughout their working lives. Therefore, it is common for individuals to only be working for a particular company for a short time. As a result, if an individual knew that they

18 would only be there for a short time, they would not need to worry or about long-term consequences of their behavior.

Anonymity. Another factor that would lead individuals to feel that there are no consequences for their actions and is also relevant to social dilemmas is anonymity. Anonymity has typically been defined as a situation where one’s identity has been concealed. Additionally,

Wallace (1999) defines anonymity as a situation where one’s identity is not only concealed, but his or her accountability for their action has also been minimized. Although much research has shown that anonymity where one’s identity only has been concealed has an effect on prosocial behaviors, Nogami and Takai (2008) found that in an experimental setting, individuals “break rules” when their identity was concealed in addition to their accountability being minimized.

Additional studies have supported these findings by showing that when individuals are anonymous, they tend to participate in rule breaking in order to obtain material gains (Nogami

2009; Zhong, Bohns, and Gino, 2010).

Past research has established that people are less cooperative when their decisions are anonymous (Bixenstine et al. 1966; Burnham, 2003; De Cremer and Bakker, 2003; Fox and

Guyer, 1979; Hoffman, McCabe, Shachat, and Smith, 1984; Jerdee and Rosen, 1974; Kahan,

1973; Kerr, 1999; Kollock, 1998; Messick and Brewer, 1983). Additionally, anonymity leads to more self-interested and unethical behavior (Bersoff, 1999; Diener, Fraser, Beaman, and Kelem,

1976; Hegarty and Sims, Jr., 1978; Loe, Ferrell, and Mansfield, 2000; Mathes and Guest, 1976;

White, 1977). Thus, it seems that anonymity may have an influence on whether an individual decides to issue a product recall because of its empirical relevance in social dilemma and ethical decision making research.

In a product recall context, individuals are in charge of making the decision whether to issue a recall. If they know that the decision they make will not be known to the people it negatively effects (e.g., not issuing a product recall), they may be motivated to make the decision not to recall a product to because it would benefit their own short-term interests. Along with a

short time horizon, anonymity should lead to the decision maker feeling less responsible for their

decision. While individual factors like time horizon and anonymity can lead to individuals not

feeling the effects of consequences from their decisions, there are also group factors that can lead

individuals to not feel the same way.

Group Size & Diffusion of Responsibility. Diffusion of responsibility is a group factor

that leads individuals to not feel the effects of consequences for their own decisions. Individuals

in larger groups, relative to smaller groups, are more inclined to feel less responsibility for the

decisions or actions that they are a part of. This phenomenon is called the “diffusion of

responsibility” (Darley and Latane, 1968). As individuals feel less responsible, they will be less

likely to act cooperatively.

Research has looked at group size as a situation that impacts cooperation levels in a

social dilemma. Specifically, research has found that overall levels of cooperation are greater in

smaller groups (Brewer and Kramer, 1986; Hamburger, Guyer, and Fox, 1975). According to the

theory of self-efficacy (Bandura, 1986), the smaller the group, the more individual group

members will feel that their contributions will make a difference. This knowledge motivates

individuals in small group settings to cooperate.

However, in a product recall decision, having a large group of individuals representing

the interests of the organization might not be the most effective way to encourage cooperation

20 between the individuals representing the organization and members of society. While small groups may promote a stronger cooperative orientation in many social dilemma contexts, in a product recall decision, a small group size may have the opposite effect. Having a strong sense of personal responsibility tends to motivate helping behavior (Schwartz, 1977). However, it is entirely possible that if there is a large group of decision makers deciding whether or not to issue a product recall, each individual may not feel personally responsible for any backlash that may occur for not acting in the best interests of society.

In the following chapter, I outline the studies. I first investigate whether the product recall can be conceptualized as a social dilemma (study 1). Next, I use individuals’ consideration of future consequences, perceptions of the recall decision, and three different factors that have been shown to be relevant in social dilemma research and which all focus on the consequences for the self and others. These factors include: time horizon (study 2), group size (study 3), and anonymity (study 4).

CHAPTER 4

Study 1

Product Recalls as a Social Dilemma

There are varying levels of severity to product defects (Cheah, Chan, and Chieng, 2007;

Germann, Grewal, Ross Jr., and Srivastava, 2014). The U.S. Food and Drug Administration

(FDA) classifies severity into Class 1, Class 2, or Class 3. Class 1 recalls are the most severe which can cause serious health problems and even death. Class 2 recalls are for products that may cause a health problem, but not as severe as class 1 recalls. Class 3 recalls are unlikely to cause any serious health problem, yet labelling or manufacturing regulations have been violated.

Depending on the severity of the recall, decision makers in an organization may choose not to issue a recall if it is not life threatening or have the potential for serious physical harm. Product recalls in all likelihood would cost the organization a lot of money and if the defect in the product isn’t to the severity level of being life threatening or causing serious harm, then the organization may be tempted to postpone issuing the recall or even plan not to make the recall unless forced to by the CPSC.

The objective of this study is to determine whether the product recall decision reflects a social dilemma. First, it is important to find out if decision makers perceive a product recall decision as a social dilemma to justify a social dilemma analysis of the decision. If the product recall decision is perceived as a social dilemma, then the underlying structure of the product recall decision should be similar to the underlying structure of a social dilemma. A social dilemma analysis of the product recall decision would then be fruitful to understand how the decision is made.

This objective will be accomplished by paralleling an experiment from Joireman et al.

(2006) where participants will be asked if the product recall decision is costly to the organization

in the short-term and beneficial for society in the long-term. If individuals view product recall decisions as social dilemmas, there should be two underlying conflicts of interest the decision maker must deal with: a social conflict (individual vs. collective interests), and a temporal conflict (immediate vs. future consequences). However, there is a key difference between traditional social dilemma research and what I seek to establish in this first study. Most social dilemma research includes conflicts between individual and collective interests. However, in this context the CEO (decision maker) will represent individual interests and potential consumers or society will represent collective interests. Additionally, the decision maker and company should have similar interests in this context.

I believe that the product recall decision share similarities with social dilemmas, in that there is a conflict between a CEO’s and organization’s interests and the interests of the collective society. Product recalls are very costly for the organization making them. Specifically, issuing a product recall would represent a short-term (possible long-term) cost for the CEO and organization. However, if the CEO/organization issues a product recall, society at large would benefit from this decision long-term because there won’t be a dangerous product available for consumption.

Conversely, not issuing a product recall could benefit the organization in the short-term by allowing it to continue to bring in profits from sales from the product. Additionally, the organization would benefit short-term by not spending money to recall the products. The

collective society, however would suffer negative long-term consequences because the faulty

products could cause physical harm to those who purchase them.

Hypotheses

H1a: The decision to recall a product will be viewed as a social fence.

H1b: The decision not to recall a product will be viewed as a social trap.

Method

Participants and design. Participants were recruited from Washington State University’s online MBA program (N = 153, ages 21-58, mean age 35, 34% female, 75% Caucasian) and received partial course credit for participating.

Procedure. Participants first read a scenario about a fictitious company called Cellular

Connection. They were told that Cellular Connection is a smart phone producer that has developed a new smart phone that has sold well but has had customers call in and complain about either developing migraine headaches after use (high severity condition), or very low battery life (low severity condition). The stimuli is adapted from Germann et al. (2014) where they pre-tested severe and non-severe defects of a smart phone. The participants were then informed that the CEO could either recall the phones available for sale, wait for more customer complaints to come in, or decide not to issue a recall and continue selling the phone. This scenario is found in Appendix A.

Measures. For the main outcome measure, participants were asked to rate how costly or beneficial each decision would be for the CEO (decision maker), company, and society

(customers) in the short-term and long-term on a scale from 1 (very costly) to 7 (very beneficial).

Participants also rated how real the scenario felt to them using three 7-point semantic differential items (unbelievable…believable; not possible…possible; inconceivable…conceivable; α = .88) and the extent they felt the recall decision was a personal, business, ethical, and legal decision on a scale from 1 (strongly disagree) to 7 (strongly agree). Finally, participants rated their tendency to consider the future consequences of their behavior using the CFC-14 scale (Joireman et al.

2012) ranging from 1 (extremely uncharacteristic) to 7 (extremely characteristic). The CFC-14 scale verified adequate reliability in this study (α = .84).

Results

I ran a single-sample t-test to see if participants felt that the scenario was a realistic one.

Results showed that participants rated the believability of the scenario as significantly greater than the mid-point of 4 (M = 6.16, SD = 1.05; t(144) = 24.75, p < .001). Additionally, I ran regression analysis to determine if CFC is related to perceptions of the costs and benefits for the

CEO and society. Results show that when a product defect is high in severity, CFC is related to the perceptions of the costs and benefits of society in the short- and long-terms. Specifically higher levels of CFC lead to perceptions of greater costs to society in the short-term (β = -.65, t(68) = 2.57, p < .02) and long-term (β = -.51, t(68) = -2.55, p < .02). This is consistent with the awareness model (Joireman, Strathman, and Balliet, 2006) which suggests that CFC makes individuals aware of the consequences of their behavior. Even though I did not test behavior, these results suggest that individuals high in CFC notice the future consequences of a decision made, in this case not to recall a product.

For the main analysis of this study, I analyzed the participants’ ratings of the short- and long-term costs and benefits for the CEO, company, and society for a situation where there was a

product recall and when there was not a product recall and when the product defect was low and high in severity. As expected, in the recall decision in both low and high severity conditions, costs and benefits for the CEO and company had the same ratings. Therefore, I averaged 16 types of ratings (4 scenario ratings: CEO short-term, CEO long-term, society short-term, society long-term x 2 product recall decision: recall, no recall x 2 severity: low, high).

In order for the decision to recall to be viewed as a social fence, participants must rate the recall decision as having short-term costs for the CEO, long-term benefits for society, and the long-term benefits for society should be greater than the long-term benefits for the CEO. In order for the decision to not recall be viewed as a social trap, participants must rate the no recall decision as having short-term benefits for the CEO, long-term costs for society, and the long- term costs for society should be greater than the long-term costs for the CEO.

Recall

ST-CEO LT-Society ST-Society LT-CEO 7

5 Benefit --- 4 Cost 3

1 Low Severity High Severity

Figure 1.

When Product is Recalled

Supporting hypothesis 1a as seen in Figure 1 above, participant ratings of the recall

decision showed evidence that the decision is seen as a social delayed fence when the product is

recalled. To qualify as a social fence the decision must be viewed as: (1) having short-term costs to the CEO (i.e., values below the scale midpoint of 4); (2) having long-terms benefits to society

(i.e., values above the scale midpoint of 4); and (3) the long-term benefits to society should

exceed the long-term benefits of the CEO.

Low Severity Product Defect. The short-term costs to the CEO were significantly below the scale midpoint of 4; (M = 2.26, SD = 1.90), t(73) = -7.88, p < .001) and the long-term

benefits to society were significantly above the scale midpoint of 4; (M = 5.66, SD = 1.27), t(73)

= 11.22, p < .001. Lastly the long-term benefits to society were significantly greater than the

long-term benefits of the CEO (MSociety = 5.66, SD = 1.27; MCEO = 5.14, SD = 1.92), t(73) =

2.458, p < .02.

High Severity Product Defect. The short-term costs to the CEO were significantly below the scale midpoint of 4; (M = 2.11, SD = 1.90), t(70) = -9.34, p < .001 and the long-term benefits to society were significantly above the scale midpoint of 4; (M = 5.68, SD = 1.33), t(70) = 10.63, p < .001. Lastly the long-term benefits to society were significantly greater than the long-term benefits of the CEO (MSociety = 5.68, SD = 1.27; MCEO = 4.52, SD = 1.99), t(70) = 5.40, p < .001.

When Product is Not Recalled

Hypothesis 1b states that the decision not to recall a product will be viewed as a social trap. To qualify as a social trap, the decision must be viewed as: (1) having short-term benefits to

the CEO (i.e., values above the scale midpoint of 4); (2) having long-term costs to society (i.e.,

values below the scale midpoint of 4); and (3) the long-term costs to society should exceed the

long-term costs of the CEO.

Low Severity Product Defect. The short-term benefits to the CEO were below the scale midpoint of 4; (M = 3.57, SD = 1.89) suggesting that not recalling a product has a cost to the

CEO instead of a benefit. The long-term costs to society were rated significantly below the midpoint of 4; (M = 2.09, SD = 1.16), t(73) = -14.12, p < .001. Lastly, the long-term costs to the society were rated significantly less than the long-term costs to the CEO (MSociety = 2.09, SD =

1.16; MCEO = 1.62, SD = 1.03), t(73) = 3.194, p < .01 which is opposite of what the social trap is

viewed as. Although these results show that the decision to not recall the product is not viewed

as a social trap when the product defect is low in severity, there is still a temporal dilemma in the

decision to not recall the product.

A temporal dilemma needs only to have short-term costs for an individual and long-term benefits for society or short-term benefits for an individual and long-term costs for society. There was a significant difference between the short-term benefits to the CEO and the long-term costs to society (MSociety = 2.09, SD = 1.16; MCEO = 3.57, SD = 1.89, t(73) = 5.97, p < .001). Even

though the means show that there is a cost to the CEO for not recalling the product, the

significant difference between the means of the costs and benefits for the CEO and society show

that the decision not to recall the product is still viewed as a temporal dilemma.

High Severity Product Defect. The short-term benefits to the CEO were below the scale

midpoint of 4; (M = 3.70, SD = 2.17) suggesting that not recalling a product has a cost to the

CEO instead of a benefit. The long-term costs to society were rated significantly below the

midpoint of 4; (M = 1.89, SD = 1.19), t(70) = -14.96, p < .001. Lastly, the long-term costs to society were not rated significantly greater than the long-term costs to the CEO (MSociety = 1.89,

SD = 1.19; MCEO = 1.82, SD = 1.33), t(70) = .55, p > .1. These results show that the decision to not recall the product is not viewed as a social trap when the product defect is high in severity.

However, like the low severity product defect situation, the decision to not recall a product is still viewed as a temporal dilemma because there is a significant difference between the CEO’s short- term benefits and society’s long-term costs (MSociety = 1.89, SD = 1.19; MCEO = 3.70, SD = 2.17,

t(70) = 6.67, p < .001). Overall, when the decision is made to not recall the product, it is not

viewed as a social delayed fence as seen below in Fig 2 for either low or high severity product

defects. However, the decision not to recall the product is still viewed as a temporal dilemma

where the short-term individual interests are at odds with the long-term collective interests.

No Recall

ST-CEO LT-Society ST-Society LT-CEO

5 Benefit --- 4 Cost 3

1 Low Severity High Severity

Figure 2.

Discussion

The goal of Study 1 was to determine if the product recall decision can be viewed as a

social dilemma. Study 1 supported hypothesis 1a that the decision to recall a product can be

viewed as a social fence where the decision is viewed as having short-term costs for the CEO, long-term benefits for society, and the long-term benefits for society are greater than the long-

term benefits for the CEO. Because the product recall decision is viewed as a social dilemma,

factors that influence cooperation in a social dilemma may also play a role in determining

whether a product recall is issued. Moreover, this evidence allows me to investigate the product

recall decision using a social dilemma framework.

Additionally, the product recall decision was viewed as a social fence in both the severe

and non-severe conditions suggesting that severity is a factor that I may not need to consider

further. In Study 2, I look at the decision maker’s time horizon as a predictor of the product

recall decision. As noted, past results in the social dilemma literature suggest that individuals are

less likely to cooperate if they will not be around the situation to receive the negative

consequences of not participating. If the decision maker will not be around to see the

consequences of not cooperating, he or she may be inclined to act in way to serve self-interests

(i.e., saving money by not recalling the product). Additionally, in-line with past research, a high consideration of future consequences, and an ethical perception of the decision should lead to higher levels of cooperation or likelihood of issuing a product recall.

Study 2

Decision Makers’ Time Horizon as a Predictor of the Product Recall Decision

Study 1 provided initial evidence that the product recall decision can be viewed as a

social dilemma. Having this theoretical base from which to draw from, I use the situations that

are relevant to social dilemmas and that deal with consequences to the self (individual) and other

(collective). As I have reviewed in chapter 3, time horizon is a factor at the individual level of analysis which has direct influence on cooperation in social dilemmas. For example, individuals who need to decide how much of a common resource to use may be tempted not to cooperate if they are not going to be around the area long-term. Likewise, in a public goods dilemma, an individual deciding whether or not to contribute to support a public good may be tempted not to contribute if he or she is not going to be around long-term. This could also have implications for decision makers contemplating whether or not to issue a product recall.

Whether one decides to issue a product recall or not, there will likely be negative consequences that he or she will have to deal with in the future. Recalling a product could have negative financial consequences for the decision makers. Not recalling a product could have negative societal consequences such as members of society being injured which could also lead to a lot of anger targeted at the organization and its employees. If, however, decision makers knew that they would only be working for the organization short-term, they would not fear the negative future consequences such as potential lawsuits and loss of employment because they won’t be there to face them. Therefore, the decision makers could act in their own interest by deciding not to issue a recall knowing that they will not have to face the societal consequences.

As reviewed in chapter 3, those who consider the future consequences of their decisions are more likely to cooperate in a social dilemma context. Additionally, those higher in a consideration of future consequences should be more willing to issue a product recall because the recall is viewed as a social dilemma and CFC is related to ethical decision making. Those high in

CFC have been shown to use more ethical negotiation strategies (Hersfield, Cohen, and

Thompson, 2012) and make ethics and social responsibility a higher priority in business settings

(Robbins, 2012). Therefore CFC should not only be linked with viewing the product recall decision as an ethical decision but also should lead to one issuing a product recall.

Hypotheses

H2: Individuals will be less likely to issue a product recall when they are leaving the organization in the near future.

H3: Individuals will be more likely to issue a product recall when they are higher in CFC.

H4: Individuals will be more likely to issue a product recall the more they perceive the decision to be ethical in nature.

H5: There will be an interaction between CFC and time horizon such that those high in CFC will be more likely to recall the product, but only when the time horizon is long-term.

H6: There will be an interaction between ethical perception of the decision and time horizon such that when the decision is perceived as being highly ethical, the participants will be more likely to recall the product, but only when the time horizon is long-term.

H7: There will be a significant indirect effect of CFC on recall intentions through ethical perception of the decision.

Method

Participants. Participants were recruited from Amazon’s Mechanical Turk (N = 114, ages

19-69, mean age 36, 39% female, 76% Caucasian) and were compensated $0.75.

Procedure. Participants first read a scenario where they are asked to imagine they are a product manager for Cellular Connection (Appendix B). Participants were told that they would

remain with the company for either one month (short-term) or at least 12 months (long-term). To check the manipulation, participants were asked a comprehension check question to see if they remembered the time time-horizon (short vs. long). Participants were also asked to see if they could remember the problem with the product in question. Seventeen participants failed to complete the comprehension check and were eliminated from further analysis. This left a total of

N = 97 participants.

For the main outcome measure, participants rated their likelihood of recalling the product

(α = .96), waiting to recall the product (α = .98), and not recalling the product (α = .98) on a three-item scale from 1 (Very Unlikely) to 7 (Very Likely). Additionally, participants rated their perception of how real the scenario felt to them on a three item scale from 1 to 7 (Unbelievable,

Believable; Not Possible, Possible; Inconceivable, Conceivable; α = .96). Participants also rated

their concern for future consequences using Joireman et al.’s (2012) 14-item consideration of future consequences (CFC) scale (1 = extremely uncharacteristic to 7 = extremely characteristic;

α = .79). Lastly, participants rated the extent that they believed the recall decision is a personal, business, ethical, and legal decision on a one-item scale from 1 (Strongly Disagree) to 7

(Strongly Agree).

Results

Comprehension Checks. The majority of participants (85%) correctly stated which time- horizon condition they were in and the nature of the product defect. I ran a single-sample t-test on the realism index to ensure that participants felt that the scenario is realistic. As expected, respondents ratings were significantly higher than the mid-point of the scale, 4, signifying that participants found the scenario to be realistic (M = 5.89, SD = 1.33), t(96) = 13.98, p < .001.

Recall Intentions. To test my primary hypothesis, I conducted independent-sample t-tests on my three dependent variables (recall, wait to recall, don’t recall). Results show a lack of support for H2; there is not a significant difference in issuing a product recall between short and long term horizons t(95) = -.18, p > .1. Additionally, there is not a significant difference in waiting to recall the product between short and long term horizons t(95) = -.98, p > .1 or not recalling the product between short and long term horizons t(95) = .65, p > .1.

I first ran a multiple regression testing the subscales of CFC; CFC-Immediate (CFC-I) and CFC-Future (CFC-F). Each subscale showed a significant simple correlation but in a multiple regression each subscale predicted the same variance in the model, so I used the CFC-

Total measure for the rest of the analysis. To test H3 that higher levels of CFC is related to higher levels of willingness to issue a product recall, I ran a regression analysis. Results show that there is support for H3 that higher levels of CFC lead to higher levels of willingness to issue a product recall (β = .60, t(95) = 2.57, p < .02). Also, supporting H4, the more one perceives the recall decision to be an ethical decision, the more likely he or she is to issue a product recall (β =

.63, t(95) = 4.74, p < .001). Next, I ran a two-step regression analysis on the three dependent variables to test H5.

I entered the main effects of time horizon (short term = 0, long term = 1) and CFC on step 1 and the 2-way interaction on step 2. CFC was the only significant predictor of willingness to recall (β = .60, p < .02). The hypothesized interaction between time horizon and CFC on willingness to recall was not significant. To investigate whether participants would wait to recall the product, I followed the same procedure as above. CFC was a significant predictor of willingness to wait to recall (β = -.96, p < .01). The interaction between time horizon and CFC on waiting to recall the product was not significant. Lastly, CFC was a significant predictor of not recalling the product (β = -.65, p < .01) and there was not an interaction between time horizon and CFC on not recalling the product. Overall, there was no statistical evidence for support for H5.

To find which of the perceptions of the decision the best predictor of recall intentions is, I ran three separate multiple regression analysis using recall, wait to recall, and no recall as the three dependent variables. Ethical perceptions was the only variable to significantly predict recall decisions on every dependent variable (recall: β = .50, p < .001, wait to recall: β = -.52, p < .01, no recall: β = -.47, p < .01). Because ethical perceptions was the only variable to significantly predict recall decisions on every dependent variable, the other perceptions were excluded from further analysis. To determine whether there is an interaction between time horizon and CFC on ethical perceptions of the recall decision, I ran a 2-step moderated regression analysis on the three dependent variables to test H6.

I entered the main effects of time horizon (short term = 0, long term = 1) and ethical perception of the decision on step 1 and the 2-way interaction on step 2. Ethical perception of the decision was a significant predictor of willingness to recall (β = .63, p < .001). The hypothesized

interaction between time horizon and ethical perception of the decision on willingness to recall

was not significant. To investigate whether participants would wait to recall the product, I

followed the same procedure as above. Ethical perception of the decision was a significant

predictor of willingness to wait to recall (β = -.57, p < .01). The interaction between time horizon

and ethical perception of the decision on waiting to recall the product was not significant. Lastly, ethical perception of the decision was a significant predictor of not recalling the product (β = -

.59, p < .001) and there was not an interaction between time horizon and CFC on not recalling

the product. Overall, there was no statistical evidence for support for H6.

Indirect Effects. In the previous analysis, I found that ethical perceptions of the decision

was the only variable to significantly predict all of the three recall dependent variables. In

addition, CFC and ethical perceptions of the decision were positively correlated (r = .33, p <

.001), suggesting that ethical perceptions may mediate the relationship between CFC and recall decision. As shown in Figures 3, 4, and 5 running a test of indirect effects showed that there is a significant indirect effect of CFC recall intentions through perceptions of the decisions as ethical decisions (Recall: b = .31, 95% CI: .13, .60; Wait: b = -.24, 95% CI: -.52, -.06; No Recall: b = -

.28, 95% CI: -.55, -.10) supporting H7.

Figure 3. Recall

Figure 4. Wait

Figure 5. No Recall

Discussion

The goal of Study 2 was four-fold. First, I tested the hypothesis that a longer employee time-horizon would lead to a greater likelihood of issuing a product recall. The results show that

37 there is not an effect of time-horizon on one’s willingness to issue a product recall nor were there any interactive effects of time-horizon and ethical perception of the decision and CFC. Secondly,

I tested the hypothesis that a high consideration of future consequences would lead to a greater willingness to issue a product recall which was supported by the data. Thirdly, I tested the hypothesis that when the product recall decision is viewed as an ethical decision, one would be more willing to issue a product recall. This hypothesis was also supported. Lastly, I tested the indirect effect of CFC on recall intentions through an ethical perception of the decision. Results show that CFC explains recall intentions through ethical perceptions of the decision.

In study 3, I investigate another factor that has been prominent in the social dilemma literature to see how it affects product recall decisions. Group size has shown to influence levels of cooperation in a social dilemma context. However, I test the hypothesis that having a larger group will lead to a lower probability of issuing a product recall because of the diffusion of responsibility effect. Moreover, I also test the effects of an individual’s consideration of future consequences and perceptions of the recall decision.

Study 3

Group Size as a Predictor of the Product Recall Decision

As I have reviewed in chapter 3, group size is a factor which has direct influence on cooperation in social dilemmas. Research in past social dilemma literature has shown that overall levels of cooperation are greater in smaller groups (Brewer and Kramer, 1986; Hamburger,

Guyer, and Fox, 1975). However, according to diffusion of responsibility, individuals in larger groups, relative to smaller groups, are more inclined to feel less responsibility for the decisions or actions that they are a part of. The mere presence of other people in an emergency situation has been shown to reduce an individual’s feeling of responsibility and actual helping behavior

(Darley and Latance, 1968).

In a product recall decision, individuals who are making the decision that could potentially affect many would most likely would feel some type of responsibility for what they choose. Results in studies 1 and 2 show that the product recall decision is perceived as being an ethical decision and when the decision is perceived as being an ethical decision, those high in

CFC are more likely to recall the product. However, if there are many involved with the decision to recall the product, individuals may feel less individual responsibility for the decision that will be made. Indeed, having a strong sense of personal responsibility tends to motivate helping behavior (Schwartz, 1977).

Hypotheses

[H3: As shown in study 2, individuals will be more likely to issue a product recall when they are higher in CFC.]

[H4: As shown in study 2, individuals will be more likely to issue a product recall the more they perceive the decision to be ethical in nature.]

[H7: As shown in study 2, there will be a significant indirect effect of CFC on recall intentions through ethical perception of the decision.]

H8: Individuals will be more likely to issue a product recall when they are making the decision alone.

H9: There will be an interaction between CFC and group size such that those high in CFC will be more likely to recall the product, but only when the decision maker is making the decision alone.

H10: There will be an interaction between ethical perception of the decision and group size such that when the decision is perceived as being highly ethical, the participants will be more likely to recall the product, but only when the decision maker is making the decision alone.

Method

Participants. Participants were recruited from Amazon’s Mechanical Turk (N = 125, ages

19-68, mean age 36, 33% female, 76% Caucasian) and were compensated $0.75.

Procedure. Participants first read a scenario where they are asked to imagine they are a product manager for Cellular Connection (Appendix C). Participants were told that customers have been calling and complaining about developing migraine headaches after multiple uses of

the company’s new smart phone. Additionally, participants were told that they are a part of a six- member management team (group condition) that is responsible for making the recall decision or they are responsible for making the decision alone (individual condition). To check the

manipulation, participants were asked a comprehension check question to see if they

remembered who is in charge of making the recall decision. Participants were also asked to see if

they could remember the problem with the product in question. Fourteen participants failed to

complete the checks and were eliminated from further analysis. This left a total of N = 111

participants.

For the main outcome measure, participants rated their likelihood of recalling the product

(α = .97), likelihood of waiting to recall the product (α = .98), and likelihood of not recalling the

product (α = .97) on a three-item scale from 1 (Very Unlikely) to 7 (Very Likely). Additionally,

participants rated their perception of how real the scenario felt to them on a three item scale from

1 to 7 (Unbelievable, Believable; Not Possible, Possible; Inconceivable, Conceivable; α = .96).

Participants also rated their concern for future consequences using Joireman et al.’s (2012) 14-

item consideration of future consequences (CFC) scale (1 = extremely uncharacteristic to 7 =

extremely characteristic; α = .81). Lastly, participants rated the extent that they believed the

recall decision is a personal, business, ethical, and legal decision on a one-item scale from 1

(Strongly Disagree) to 7 (Strongly Agree).

Results

Comprehension Checks. The majority of participants (89%) correctly stated which

condition they were in and the nature of the product defect. I ran a single-sample t-test on the

realism index to ensure that participants felt that the scenario is realistic. As expected,

respondents ratings were significantly higher than the mid-point of the scale, 4, signifying that

participants found the scenario to be realistic (M = 5.76, SD = 1.32), t(110) = 14.07, p < .001.

Recall Intentions. To test my primary hypothesis, I conducted independent-sample t-tests on my three dependent variables (recall, wait to recall, don’t recall). Results show a lack of support for H8; there is not a significant difference in issuing a product recall between individual and group conditions t(109) = .95, p > .1. Additionally, there is not a significant difference in waiting to recall the product between individual and group conditions t(109) = -1.60, p > .1 or not recalling the product between individual and group conditions t(109) = -.97, p > .1.

I also ran a regression to test H3 that higher levels of CFC is related to higher levels of willingness to issue a product recall. Replicating study 2, results show that there is support for

H3 that higher levels of CFC lead to higher levels of willingness to issue a product recall (β =

.45, t(109) = 2.13, p < .03). To find which of the perceptions of the decision the best predictor of recall intentions is, I ran three separate multiple regression analysis using recall, wait to recall, and no recall as the three dependent variables. Ethical perceptions was the only variable to significantly predict willingness to recall and not recall (recall: β = .64, p < .001, no recall: β = -

.65, p < .001). Because ethical perceptions was the only variable to significantly predict willingness to recall and not recall, the other perceptions were excluded from further analysis.

Replicating study 2 and supporting H4, the more one perceives the recall decision to be an ethical decision, the more likely he or she is to issue a product recall (β = .76, t(109) = 7.18, p <

.001). Next, I ran a two-step regression analysis on the three dependent variables to test H9.

I entered the main effects of group size (individual = 0, group = 1) and CFC on step 1 and the 2-way interaction on step 2. CFC was a significant predictor of willingness to recall (β = .46,

p < .02). The hypothesized interaction between group size and CFC on willingness to recall was not significant. To investigate whether participants would wait to recall the product, I followed the same procedure as above. Neither group size nor CFC was a significant predictor of willingness to wait to recall and the interaction between group and CFC on waiting to recall the product was not significant. Lastly, CFC was a significant predictor of not recalling the product

(β = -.60, p < .01) and there was not an interaction between time horizon and CFC on not recalling the product. Overall, there was no statistical evidence for support for H9. To determine whether there is an interaction between time horizon and CFC on ethical perceptions of the recall decision, I ran a 2-step moderated regression analysis on the three dependent variables to test

H10.

I entered the main effects of group size (individual = 0, group = 1) and ethical perception of the decision on step 1 and the 2-way interaction on step 2. Ethical perception of the decision was a significant predictor of willingness to recall (β = .87, p < .001). The hypothesized interaction between group size and ethical perception of the decision on willingness to recall was not significant. To investigate whether participants would wait to recall the product, I followed the same procedure as above. Ethical perception of the decision was not a significant predictor of willingness to wait to recall and the interaction between group size and ethical perception of the decision on waiting to recall the product was not significant. Lastly, ethical perception of the decision was a significant predictor of not recalling the product (β = -.72, p < .001) and there was not an interaction between group size and CFC on not recalling the product. Overall, there was no statistical evidence for support for H10.

Indirect Effects. Ethical perceptions of the decision was the only variable to significantly predict willingness to recall and not recall the product. In addition, CFC and ethical perceptions

of the decision were positively correlated (r = .24, p < .05), suggesting that ethical perceptions may mediate the relationship between CFC and recall decision. As shown below in Figures 6, 7,

and 8, running a test of indirect effects showed that there is a significant indirect effect of CFC

recall intentions through perceptions of the decisions as ethical decisions (b = .27, 95% CI: .06,

.51) supporting H7.

Figure 6. Recall

Figure 7. Wait

Figure 8. No Recall

Discussion

The goal of Study 3 was four-fold. First, I tested the hypothesis that individuals making a

product recall decision by themselves are more likely to recall a product than when they are

making the decision in a group. The results show that there is not an effect of group size on one’s

willingness to issue a product recall nor were there any interactive effect of group size and

ethical perception of the decision and CFC. Secondly, I tested the hypothesis that a high

consideration of future consequences would lead to a greater willingness to issue a product recall

which was supported by the data. Thirdly, I tested the hypothesis that when the product recall

decision is viewed as an ethical decision, one would be more willing to issue a product recall.

This hypothesis was also supported. Lastly, I tested the indirect effect of CFC on willingness to

recall through an ethical perception of the decision. Results from study 2 are replicated in study 3

and show that CFC explains recall intentions through ethical perceptions of the decision.

In study 4, I investigate the effect of anonymity to see how it affects product recall decisions. Both study 2 and study 3 looked at factors that could minimize negative consequences for making a decision that would be beneficial for oneself at the expense of the collective.

Anonymity, like employee time-horizon and group size, is similar in that it has also been shown to influence levels of cooperation in a social dilemma context and could minimize felt negative consequences for making a proself decision. Moreover, I also test the effects of severity of product defect on the recall decisions and CFC and perceptions of the recall decision.

Study 4

The Impact of Anonymity on the Product Recalls Decision

Research has shown that when the choice whether or not to cooperate is anonymous, there will be lower levels of cooperation than when the choice to cooperate is known by others

(Bixenstine et al. 1966, Jerdee and Rosen, 1974, Fox and Guyer, 1979). Furthermore, when individuals know that they are being watched or what they are doing will be known to others, levels of cooperation may change. Research has also shown that individuals merely anticipating meeting with others who will be effected by their decision tend to cooperate more than if they do not anticipate a future meeting (Van Lange et al. 2011). Therefore, if individuals are pondering

issuing a product recall, anonymity may persuade them to act in a way that would benefit their

short-term consequences because they won’t have future consequences if no one knows who

made the decision.

Similar to time horizon, anonymity is directly relevant to the product recall decision at the individual level of analysis. The individuals within the organization that are in charge of making the decision to recall a product may feel a lot of pressure from society to issue a product recall as it could have negative consequences for consumers. However, if no one knows who is making the decision to issue a recall, there may be less pressure on the individual to make the

decision that would be in the best interest of society. Similar to a short time horizon, if the

decision context is anonymous, the decision maker would not have to worry about facing the

negative consequences because his or her identity is concealed.

Hypotheses

[H3: As shown in studies 2 and 3, individuals will be more likely to issue a product recall when they are higher in CFC.]

[H4: As shown in studies 2 and 3, individuals will be more likely to issue a product recall the more they perceive the decision to be ethical in nature.]

H11: Individuals will be less likely to issue a product recall when the product recall decision is anonymous in nature.

H12: Individuals will be less likely to issue a product recall when the product recall decision is low in severity.

H13: Individuals will be less likely to issue a product recall when the decision is anonymous in nature, but only when the defect is low in severity.

H14: There will be an interaction between CFC and anonymity such that those high in CFC will be more likely to recall the product, but only when the decision maker is not anonymous.

H15: There will be an interaction between CFC and severity of defect such that those high in

CFC will be more likely to recall the product, but only when severity is high.

H16: There will be a significant indirect effect of CFC on recall intentions through ethical perception of the decision only when the product defect is severe.

Method

Participants. Participants were recruited from Amazon’s Mechanical Turk (N = 244, ages

18-73, mean age 37, 43% female, 75% Caucasian) and were compensated $0.75.

Procedure. Participants first read a scenario where they are asked to imagine they are a product manager for Cellular Connection (Appendix D). Participants were told that customers

have been calling and complaining about low battery life (low severity) or developing migraine

headaches (high severity) after multiple uses of the company’s new smart phone. Additionally,

participants were told that they are responsible for making the recall decision either

anonymously or not anonymously. To check the manipulation, participants were asked a

comprehension check question to see if they remembered if the decision was anonymous or not

anonymous. Participants were also asked to see if they could remember the problem with the

product in question (low battery life or migraine headache). Thirty-two participants failed to

answer these checks and were eliminated from further analysis. This left a total of N = 212

participants.

For the main outcome measure, participants rated their likelihood of recalling the product

(α = .98), waiting to recall the product (α = .98), and not recalling the product (α = .97) on a

three-item scale from 1 (Very Unlikely) to 7 (Very Likely). Additionally, participants rated their

perception of how real the scenario felt to them on a three item scale from 1 to 7 (Unbelievable,

Believable; Not Possible, Possible; Inconceivable, Conceivable; α = .95). Participants also rated

their concern for future consequences using Joireman et al.’s (2012) 14-item consideration of

future consequences (CFC) scale (1 = extremely uncharacteristic to 7 = extremely characteristic;

α = .80). Lastly, participants rated the extent that they believed the recall decision is a personal,

business, ethical, and legal decision on a one-item scale from 1 (Strongly Disagree) to 7

(Strongly Agree).

Results

Comprehension Checks. The majority of participants (87%) correctly stated which anonymity condition they were in and the nature of the product defect. I ran a single-sample t- test on the realism index to ensure that participants felt that the scenario is realistic. As expected, respondents ratings were significantly higher than the mid-point of the scale, 4, signifying that participants found the scenario to be realistic (M = 5.98, SD = 1.23), t(211) = 23.45, p < .001.

Recall Intentions. To test H11, I conducted independent sample t-tests on the three dependent variables recall, wait to recall, and no recall. Results show a lack of support for H11; there is not a significant difference in issuing a product recall between anonymity and non- anonymity conditions t(210) = .57, p > .1. Additionally, there is not a significant difference in waiting to recall the product t(210) = .82, p > .1 or not recalling the product between anonymity and non-anonymity conditions t(210) = .15, p > .1. To test H12, I conducted independent sample t-tests on the three main dependent variables recall, wait to recall, and no recall. Results show a lack of support for H12; there is not a significant difference in issuing a product recall between low and high severity conditions t(210) = -.76, p > .1. Additionally, there is not a significant difference in waiting to recall the product t(210) = -.68, p > .1 or not recalling the product between low and high severity conditions t(210) = .96, p > .1. The hypothesized interaction between anonymity and severity (H13) was also not significant on willingness to recall (F(1,

208) = .01, p > .1), wait to recall (F(1, 208) = .51, p > .1), and not recall the product (F(1, 208) =

.05, p > .1).

I also ran a regression to test H3 that higher levels of CFC is related to higher levels of willingness to issue a product recall. Results show that there is support for H3 that higher levels

50 of CFC lead to higher levels of willingness to issue a product recall (β = .38, t(209) = 2.41, p <

.02). Also, supporting H4, the more one perceives the recall decision to be an ethical decision, the more likely he or she is to issue a product recall (β = .59, t(210) = 8.23, p < .001). Next, I ran a two-step regression analysis on the three dependent variables to test H14.

I entered the main effects of anonymity (anonymous = 0, not anonymous = 1) and CFC on step 1 and the 2-way interaction on step 2. CFC was a significant predictor of willingness to recall (β = .38, p < .02). The hypothesized interaction between anonymity and CFC on willingness to recall was not significant. To investigate whether participants would wait to recall the product, I followed the same procedure as above. Neither anonymity nor CFC was a significant predictor of willingness to wait to recall and the interaction between group and CFC on waiting to recall the product was not significant. Lastly, CFC was a significant predictor of not recalling the product (β = -.37, p < .03) and there was not an interaction between time horizon and CFC on not recalling the product. Overall, there was no statistical evidence for support for H14.

Finally, I entered the main effects of severity (low severity = 0, high severity = 1) and

CFC on step 1 and the 2-way interaction on step 2. CFC was a significant predictor of willingness to recall (β = .37, p < .03). The hypothesized interaction between severity and CFC on willingness to recall was not significant. To investigate whether participants would wait to recall the product, I followed the same procedure as above. Neither severity nor CFC was a significant predictor of willingness to wait to recall and the interaction between group and CFC on waiting to recall the product was not significant. Lastly, CFC was a significant predictor of not recalling the product (β = -.36, p < .03) and there was not an interaction between time

horizon and CFC on not recalling the product. Overall, there was no statistical evidence for

support for H15.

Indirect Effects. Unlike studies 2 and 3, running a test of indirect effects showed that

there is not a significant indirect effect of CFC willingness to recall the product through ethical perceptions of the decision (b = .09, 95% CI: -.20, .36) thus H16 is not supported.

Discussion

The goal of Study 5 was five-fold. First, I wanted to be able to replicate the effects of

CFC and ethical perceptions of the decision on willingness to recall the product. The results confirm that CFC and ethical perceptions of the decision are related to willingness to recall the product. Second, I tested the hypothesis that when the decision is anonymous and the product defect is low in severity, one will be less likely to recall the product. The results show that there is not an effect of anonymity or severity on willingness to recall. Third, I tested the hypothesis that there would be interactive effects between CFC and anonymity and severity. The results show that there were not any interactive effects of these variables on willingness to recall the product. Fourth, I tested the indirect effect of CFC on willingness to recall through an ethical perception of the decision. Results from studies 2 and 3 were not replicated and there was not an indirect effect of CFC through willingness to recall through ethical perceptions of the decision.

General Discussion

With the abundance of organizations issuing product recalls, it is important for marketing scholars and practitioners to understand the product recall decision. As past research has thoroughly investigated the consequences of recall on consumer responses and firm performance, research has not looked at the decision in isolation. This is a key omission in research as there could be factors that drive decision makers to recall a product when it could have harmful effects to society. My studies utilized a series of scenarios to investigate factors that may lead to a willingness to recall a product.

This work shows that individuals view the product recall decision as a social dilemma.

This was an important finding because it gave me a theoretical lens from which to look at the product recall decision. I looked at factors that have been shown to promote cooperation in social dilemmas to see if they would lead to increases in willingness to recall a defective product.

While factors such as time-horizon, group size, and anonymity were shown not to affect the recall decision, CFC and ethical perceptions of the decision did affect the recall decision.

Through these studies, I show that high CFC and an ethical perception of the decision leads to increased willingness to recall a defective product.

Theoretical and Practical Implications

The results of this dissertation offer theoretical insights to extend the work on product recalls, social dilemmas, and CFC. First, my studies show that individuals view the product recall decision through the lens of a social dilemma. This finding extends the literature on product recalls which has largely focused on the financial consequences for firms and consumer responses. This is the first time that the product recall decision has been looked at in isolation

and offers insights that there are factors similar in social dilemmas that would impact the

decision to issue a product recall.

As past research has shown, it is important to understand the consequences of recalls to

firms and consumers, but since there is no heuristic or rule of thumb that states when a product

recall must be issued, it leaves it to reason that there are individual factors that are at play in

determining the likelihood of recalling a product. As such, this work suggests that decision makers have to face the conflict between what may appear to be best for them in the short-run and what is best for society in the long-run. This result may also be helpful to academics because they now have a theoretical base from which to look at the product recall decision. Additionally, this knowledge may be of use to practitioners as results suggest that helping decision makers realize that the product recall decision is an ethical one, is related to a greater willingness to recall a defective product. Relatedly, helping individuals realize the future consequences of product recall decision should increase the likelihood of recalling the product.

In addition to the literature on product recalls, the results of this dissertation offer theoretical insights to extend the work on social dilemmas. Research on social dilemmas is rich in theory and public policy implications which should be of interest to marketing scholars as there has been a recent call to develop theory aimed at improving the well-being of consumers and society through marketing (Davis and Pechmann, 2013). However, the domain of social dilemmas has had little exposure in the marketing literature despite the direct relevance it has on everyday consumer behavior. By integrating the work on product recalls and social dilemmas, I have assisted researchers by helping them understand that the product recall decision should be another type of social dilemma that warrants further investigation. Of greater importance, the

results of my dissertation should encourage the bridging of the social dilemma literature with the

marketing literature where it has direct relevance.

Tenbrunsel and Messick (1999) found the way a decision is framed in a social dilemma

context affects levels of cooperation. Specifically, when a decision is framed as ethical,

individual cooperation is higher than when a decision is framed as being a business decision. My

results replicate the finding that when a decision is framed as ethical, decisions made to benefit

long-term collective interests are made (e.g., a product recall). In addition to replicating the work

of Tenbrunsel and Messick (1999), my results also are the first to experimentally show that CFC

is related to how one perceives the decision. This is an important addition to the literature on

social dilemmas because we now have an additional explanation why individuals high in CFC

are more likely to act in an ethical manner.

From a practical perspective, my results suggest that having individuals who are high in

CFC making decisions that affect a large number of people may be essential for collective well-

being. Furthermore, having individuals high in CFC in a decision making role would increase the

probability that business decisions involving tradeoffs between short-term individual interests and long-term collective interests are perceived as ethical decisions. This will lead to more decisions being made that have positive outcomes for the collective in the long-term. Companies may benefit from placing employees who are high in CFC in a decision making role.

CFC has been studied in many contexts (for a review see Joireman and King, in press).

Much of this research shows that CFC predicts a range of behaviors that have implications for

personal and collective well-being. These domains include health behavior, work place behavior,

financial decision-making and environmental decision-making. More recently research has

looked at CFC as a factor that predicts ethical decision making. Research has shown that those

55 high in CFC exhibit higher moral character in an organizational context (Cohen et al., 2014), use more ethical negotiation strategies (Hershfield, Cohen, and Thompson, 2012), and is linked with perceived importance of social responsibility and ethics in a business context (Robbins, 2012).

My results show add to this stream of literature by experimentally showing that CFC is related to one’s willingness to issue a product recall through the perception of the decision as being ethical. At present, there has been little research done on the effect of CFC on managerial decision making. My findings suggest that CFC with perceptions of the decision can be a foundation from which to look at ethical managerial decision making.

Limitations and Future Directions

Limitations of this work should be mentioned on a broad level as they will suggest opportunities for future research projects on social dilemmas and product recalls. First, participants were exposed to scenarios that they may have little experience with. The first study was a panel of MBA students. This sample was useful as there is a strong likelihood that they have studied different managerial decisions. However, the rest of the studies used a sample from

Mechanical Turk and many of them have probably never had to make a product recall or even have managerial work experience.

Second, considering the product recall decision has not been looked at through the lens of a social dilemma, further studies to incorporate social dilemma factors into the product recall decision could offer insight into the overall effect of these factors on the product recall decision.

Third, on a practical level, the product recall decision is made by a team of individuals. CFC has not been studied in a group context. While my results show that an individual’s CFC is related to the product recall decision, they may not hold true in a group decision making context. It would

be beneficial to test the effect of CFC in a group decision making context to further understand

CFC and see if its effects are seen in a group decision making context.

Finally, other research methods besides a scenario would prove useful to investigate the

relationship between social dilemmas and product recalls. Real contexts where participants make

decisions that affect the outcomes of others could offer additional theoretical and practical

implications to my studies. As such, future work should consider other research methods besides a scenario to offer even greater guidance for practitioners and academics.

Conclusion

With the number of product recalls being issued and not issued in recent time, it is important to understand the factors that drive the recall decision. Looking at the product recall decision through the lens of a social dilemma will offer more insights into the product recall decision and will help us find out what can be done to encourage additional recalls when necessary. Despite areas of theoretical and managerial importance, this domain has not been explored. This area of research has a lot of untapped potential with a lot of public policy implications that would benefit many.

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APPENDIX A

SCENARIOS FOR STUDY 1

Low Severity Scenario

Cellular Connection, a successful smart phone producer has recently developed a new smart phone. The new phone has been selling well but recently multiple customers have been calling in complaining about the durability of the battery (very low battery life) after multiple uses of the phone throughout the day.

The CEO meets with the management team and decides that there are three different options the company can make moving forward.

1) Recall all the phones that are available for sale. 2) Wait for more customer complaints to come in. 3) Decide not to recall the phones and keep selling them as is.

High Severity Scenario

Cellular Connection, a successful smart phone producer has recently developed a new smart phone. The new phone has been selling well but recently multiple customers have been calling in complaining about developing migraine headaches after multiple uses of the phone throughout the day.

The CEO meets with the management team and decides that there are three different options the company can make moving forward.

1) Recall all the phones that are available for sale. 2) Wait for more customer complaints to come in. 3) Decide not to recall the phones and keep selling them as is.

Outcome Measure Participants rated how costly or beneficial each decision would be in terms of six targets (1 = very costly to 7 = very beneficial) 1) Short-term consequences for the CEO 2) Long-term consequences for the CEO 3) Short-term consequences for society 4) Long-term consequences for society 5) Short-term consequences for the company 6) Long-term consequences for the company

APPENDIX B

SCENARIOS FOR STUDY 2

Short-Term Time Horizon

Imagine you are a product manager for Cellular Connection. You have enjoyed working with the current company but as a result of family issues, you have made the decision to accept another job and will be leaving in three weeks.

Your company has recently marketed a new smart phone which has sold well. Lately, however, multiple customers have called in complaining about developing migraine headaches after multiple uses of the phone throughout the day. As a product manager, you have the responsibility to decide whether or not to issue a product recall.

Long-Term Time Horizon

Imagine you are a product manager for Cellular Connection. You have enjoyed working with the current company and plan to stay with the company in your current position for at least another year.

APPENDIX C

SCENARIOS FOR STUDY 3

Individual Condition

Imagine you are a product manager for Cellular Connection. Your company has recently marketed a new smart phone which has sold well. Lately, however, multiple customers have called in complaining about developing migraine headaches after multiple uses of the phone throughout the day.

The CEO has given you the product manager final say on all major product decisions. As a result, you have the responsibility to decide whether or not to issue a product recall.

Group Condition

You are part of a six-member management team and the CEO has given your team final say on all major product decisions. Your team has the responsibility to decide whether or not to issue a product recall.

APPENDIX D

SCENARIOS FOR STUDY 4

Anonymous High Severity Condition

Although your name will be anonymous to the public, as a product manager, you have the responsibility to decide whether or not to issue a product recall.

Anonymous Low Severity Condition

Imagine you are a product manager for Cellular Connection. Your company has recently marketed a new smart phone which has sold well. Lately, however, multiple customers have called in complaining about the durability of the battery (very low battery life) after multiple uses of the phone throughout the day.

Although your name will be anonymous to the public, as a product manager, you have the responsibility to decide whether or not to issue a product recall.

Not Anonymous High Severity Condition

As a product manager, you have the responsibility to decide whether or not to issue a product recall. As a result, your decision will not be anonymous.

Not Anonymous Low Severity Condition

Imagine you are a product manager for Cellular Connection. Your company has recently marketed a new smart phone which has sold well. Lately, however, multiple customers have called in complaining about the durability of the battery (very low battery life) after multiple uses of the phone throughout the day.

As a product manager, you have the responsibility to decide whether or not to issue a product recall. As a result, your decision will not be anonymous.

APPENDIX E

CONSIDERATION OF FUTURE CONSEQUENCES SCALE USED IN ALL STUDIES

(Joireman et al. 2012)

(1=Extremely Uncharacteristic to 7=Extremely Characteristic)

1. I consider how things might be in the future, and try to influence those things with my day to day behavior. 2. Often I engage in a particular behavior in order to achieve outcomes that may not result for many years. 3. I only act to satisfy immediate concerns, figuring the future will take care of itself. 4. My behavior is only influenced by the immediate (i.e., a matter of days or weeks) outcomes of my actions. 5. My convenience is a big factor in the decisions I make or the actions I take. 6. I am willing to sacrifice my immediate happiness or well-being in order to achieve future outcomes. 7. I think it is important to take warnings about negative outcomes seriously even if the negative outcome will not occur for many years. 8. I think it is more important to perform a behavior with important distant consequences than a behavior with less important immediate consequences. 9. I generally ignore warnings about possible future problems because I think the problems will be resolved before they reach crisis level. 10. I think that sacrificing now is usually unnecessary since future outcomes can be dealt with at a later time. 11. I only act to satisfy immediate concerns, figuring that I will take care of future problems that may occur at a later date. 12. Since my day to day work has specific outcomes, it is more important to me than behavior that has distant outcomes. 13. When I make a decision, I think about how it might affect me in the future. 14. My behavior is generally influenced by future consequences.

APPENDIX F

Outcome Measures for Studies 2-4

1. Thinking about the situation, how likely would you be to recall the product?

7-point scale anchored at: - Unlikely/Likely - Improbable/Probable - Definitely Not/Definitely

2. Thinking about the situation, how likely would you be to wait for more customer complaints to come in before making a recall decision?

7-point scale anchored at: - Unlikely/Likely - Improbable/Probable - Definitely Not/Definitely

3. Thinking about the situation, how likely would you be to NOT recall the product?

7-point scale anchored at: - Unlikely/Likely - Improbable/Probable - Definitely Not/Definitely