A Model for Customization Reducing Reactance to Persuasive Messages

The Impact of Source and Message Customization on Reactance: A Model for Customization Reducing Reactance to Persuasive Messages

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Michael D. Hanus, M.A.

Graduate Program in Communication

The Ohio State University

2016

Dissertation Committee:

Jesse Fox, Advisor

Brad Bushman

Nancy Rhodes

Emily Moyer-Gusé

Copyrighted by

Michael David Hanus

2016

Abstract

As consumers are becoming increasingly jaded toward traditional advertising methods, creators of persuasive messages are turning to new ways to make their appeals.

Interactive technology allows the means to give users control over the persuasive message, message source, or product. When users are given control, a host of psychological benefits work in tandem to reduce resistance to being persuaded and ultimately increase favorable attitudes towards the advertised product.

These studies assess the means by which customizing a persuasive source or message can change attitudes towards an advertised product. Using the theory of interactive media effects (TIME) and the entertainment overcoming resistance model

(EORM) as theoretical foundations, an explanatory model, the customization reactance reduction model (CRRM), was created to assess the role of customization in reducing resistance to persuasive appeals.

Three studies were conducted to establish the means by which allowing users to customize can improve their attitudes toward a product and to give support for the

CRRM. Study 1 allowed users to create the avatar for a salesperson who would give them a persuasive pitch in a virtual environment. These users liked the product in the pitch better than those who could only watch an avatar customization video and had no direct control over the source’s appearance. It was also established that the customization

ii process increases intrinsic motivation, which ultimately increase favorable attitudes toward the product. Study 2 expanded on Study 1 by requiring participants to use a pre- selected avatar (zero choices), choose from one of four possible avatars (single choice) or create a new avatar (multiple choices) designed to represent the source of a persuasive message. This test was conducted in a two-dimensional, text-based environment. Study 2 found that although there were no direct effects between customization condition and product as shown in Study 1, increasing customization options led to higher perceptions of similarity and agency, and that those perceptions lead to a reduction in state reactance and counterarguments against the product. This reduction in reactance lead to an increase in favorable product attitudes.

Having established the important role of customization in Studies 1 and 2, Study 3 expanded on findings by allowing participants to customize the actual persuasive message, rather than the persuasive source. Study 3 allowed participants to create an advertisement based on goals described in a fictional company briefing, or edit or read an existing advertisement based on these goals. Results indicate that the overall model shows poor model fit. However, many of the hypothesized path relationships were significant. Study 3 demonstrates that both need fulfillment and perceptions of identity affect engagement, which reduces psychological reactance, which ultimately leads to more favorable product attitudes. Further, results demonstrate the important indirect effect of perceived interactivity on product attitudes through need fulfillment, identity perceptions, engagement, and reactance. Findings showed no support for executive functioning resources as a predictor variable in the model.

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The three studies taken together show evidence for the power of customizing a persuasive source or message in reducing psychological reactance to a persuasive attempt. The findings illustrate the important role of perceived interactivity and give support for the use of identity perceptions in the model. These findings have practical relevance for persuasive message creators by suggesting that the use of interactive media can provide a new, alternative way to reduce resistance to persuasion.

Acknowledgments

I could not have done this without the help of some very excellent people. I owe the completion of this dissertation to a helpful and accommodating committee; to an advisor who was always available with great advice, always pushed me to do better, and shaped me into the scholar I am today; to a supportive and loving fiancé; and to an amazing community of fellow graduate students who were there to commiserate, help with just about everything, and made these last six years fun.

Vita

June 2006 ...... Lexington Catholic High School

May 2010 ...... B.A. English, Psychology, Miami University

May 2012 ...... M.A. Communication, The Ohio State

University

2010 to present ...... Graduate Teaching Associate, Department

of Communication, The Ohio State

University

Publications

Hanus, M. D., & Fox, J. (2015). Persuasive avatars: The effects of customizing a virtual

s appearance on brand liking and purchase intentions. International ׳salesperson

Journal of Human-Computer Studies, 84, 33-40.

Cruz, C., Hanus, M. D., & Fox, J. (in press). The need to achieve: Players’ perceptions

and uses of extrinsic meta-game reward systems for video game consoles.

Computers in Human Behavior.

Mahood, C., & Hanus, M. D. (2015). Role-playing video games and emotion: How

transportation into narrative mediates the relationship between immoral actions

and feelings of guilt. Psychology of Popular Media Culture.

Hanus, M. D., & Fox J. (2015). Assessing the effects of gamification in the classroom: A

longitudinal study on motivation, satisfaction, effort, and grades. Computers &

Education, 80, 152-161.

Bushman, B. J., DeWall, C. N., Ponds, R. S., & Hanus, M. D. (2014). Low glucose

relates to greater aggression in married couples. Proceedings of the National

Academy of Sciences, 111, 6254-6257.

Hanus, M. D., & Cruz, C. (in press). Leveling up the classroom: A theoretical approach

to education gamification. In H. Gangadharbatla & D. Davis (Eds). The

Handbook of Research on Trends in Gamification. IGI Global.

Fields of Study

Major Field: Communication

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Table of Contents

Abstract ...... ii

Acknowledgments...... v

Vita ...... vi

List of Tables ...... xii

List of Figures ...... xiv

Chapter 1: Introduction to the Use of New, Interactive Technology in Persuasion ...... 1

Chapter 2: The Theory of Interactive Media Effects (TIME) with Conceptual

Considerations...... 11

The Theory of Interactive Media Effects (TIME) ...... 11

Issue 1: Conceptual Overlap of TIME affordances ...... 14

Interactive Media Affordances ...... 14

Modality, Agency, Interactivity, and Navigability (MAIN) ...... 16

Conceptual Overlap and the Four Affordances of TIME ...... 19

Finding a New Affordance Framework ...... 21

Issue 2: TIME and a Focus on Structural Elements ...... 25

viii

Concerns with Focus on Perceived Interactivity ...... 31

Issue 3: TIME & Lack of Executive Functioning as Predictor Variable ...... 32

Engagement ...... 36

Using the TIME as a Foundation for the CRRM ...... 38

The Next Stages of the CRRM: Identity and Need Fulfillment ...... 39

Identity ...... 39

Need Fulfillment ...... 41

Chapter 2: Rooting the CRRM within Persuasion ...... 45

Applying the Initial CRRM to Persuasive Messaging ...... 45

Psychological Reactance & Resistance to Persuasive Attempts ...... 46

Executive Functioning & Reactance ...... 49

Self-Determination Needs & Reactance ...... 51

Identity & Reactance ...... 52

Customization, Source Perceptions & Reactance...... 53

Additional Theoretical Perspectives on Customization and Persuasion ...... 54

Completing the CRRM: Considering Reactance & Attitudes ...... 58

Chapter 5: Initial Test for the CRRM Using Source Customization ...... 60

Study 1: The Effects of Customizing a Virtual Salesperson’s Appearance on Product

Liking ...... 62

Overview ...... 62

Study 1 Method ...... 66

Study 1 Results ...... 70

Study 1 Discussion ...... 74

Chapter 6: Exploring the Roles of Similarity, Agency, and Reactance in Mediating the

Effect of Source Customization on Product Liking ...... 77

Methodological Limitations and Expansion of Study 1 ...... 77

Contributions to CRRM Testing ...... 80

Overview ...... 82

Study 2 Method ...... 86

Study 2 Results ...... 95

Chapter 7: Message Customization and the Test of the CRRM ...... 107

Methodological Changes in Study 3 ...... 107

Contributions to Testing the CRRM ...... 108

Overview ...... 116

Study 3 Method ...... 118

Study 3 Results ...... 134

Study 3 Discussion ...... 156

Chapter 8: General Findings & Future Directions ...... 165

Summary of Findings ...... 165

Theoretical Implications ...... 168

Practical Implications ...... 179

Future Directions ...... 186

Conclusion ...... 195

References ...... 197

Appendix A: Study 1 Protocol ...... 209

Appendix B: Study 1 Confederate Script...... 213

Appendix C: Study 1 Measures ...... 216

Appendix D: Study 2 Protocol ...... 219

Appendix E: Study 2 Measures...... 225

Appendix F: Study 2 Stimuli ...... 229

Appendix G: Study 2 Avatar with Text ...... 241

Appendix H: Study 3 Protocol ...... 243

Appendix I: Study 3 Measures ...... 248

Appendix J: Study 3 Stimuli ...... 262

List of Tables

Table 1. Correlation matrix for study 1 variables...... 70

Table 2. Study 2 pre-tested Statements for reactance language...... 89

Table 3. Mean scores for Study 2 pre-tested products...... 92

Table 4. Correlation matrix for Study 2 variables...... 95

Table 5. ANOVA results for product stimuli on outcome measures...... 96

Table 6. MANOVA Results for product stimuli by choice condition...... 97

Table 7. ANOVA results for choice condition on similarity and agency...... 98

Table 8. Distribution of participants in Study 3 conditions...... 120

Table 9. Mean scores for all Study 3 dependent measures...... 128

Table 10. Correlation matrix for Study 3 measures...... 129

Table 11. Study 3 product pretest scores...... 131

Table 12. ANOVA for company briefing stimuli on dependent measures...... 135

Table 13. MANOVA results for company briefing by customization condition...... 137

Table 14. MANOVA results for company briefing by self-affirmation condition...... 138

Table 15. Individual path coefficients for CRRM test...... 143

Table 16. Indirect effects for perceived interactivity on hypothesis 8...... 145

Table 17. Indirect effects for executive functioning on hypothesis 8...... 146

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Table 18. Main effects for customization condition from customization by self- affirmation MANOVA...... 149

Table 19. Main effects for self-affirmation condition for those in edit and create conditions...... 152

Table 20. Main effects for self-affirmation condition for those in the read condition. .. 154

Table 21. Customization (create/edit) by self-affirmation MANOVA interaction results

...... 155

Table 22. Customization by time MANOVA interaction results...... 156

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List of Figures

Figure 1. Depiction of Jack Daniel's online billiards game...... 4

Figure 2. Depiction of M&Ms Red vs. Green online game board...... 6

Figure 3. The TIME model (Sundar et al., 2015)...... 13

Figure 4. Perceived interactivity as the key predictor variable for other perceptions proposed in the TIME...... 31

Figure 5. Executive functioning predicts engagement independently of perceived interactivity...... 37

Figure 6. Initial proposed relationships of the CRRM adding identity as a mediating variable between perceived interactivity, executive functioning, and engagement...... 41

Figure 7. Initial paths of the CRRM adding in need fulfillment as a mediator...... 44

Figure 8. Finalized model of CRRM with proposed paths now including source perceptions, reactance, and product attitudes...... 59

Figure 9. Path coefficients for simple mediation analysis of avatar customization on brand liking through intrinsic motivation...... 73

Figure 10. Path coefficients for simple mediation analysis of avatar customization on purchase intention through intrinsic motivation...... 74

Figure 11. Hypothesized relationship of similarity, agency as mediators between number of choice options and state reactance or counterarguing...... 85 xiv

Figure 12. Hypothesized serial mediations for similarity and agency on state reactance and counterarguing...... 86

Figure 13. Portrait Illustration Maker avatar customization interface...... 90

Figure 14. Proposed paths between variables in the CRRM...... 111

Figure 15. Hypotheses added to CRRM...... 115

Figure 16. Observed variable model used for testing the CRRM...... 139

Figure 17. Serial mediation pathway proposed by H8a...... 144

Figure 18. Serial mediation pathway proposed by H9d...... 145

Figure 19. Revised version of the CRRM...... 195

Chapter 1: Introduction to the Use of New, Interactive Technology in Persuasion

Now, more than ever, we have the ability to shape our experiences and possessions. With the aid of modern technology, the depth, breadth, and sheer ways in which we can customize our lives has increased. The ability to access a wide range of products and services has facilitated a world in which our experiences can be crafted to the precise degree of our desires. Where customizing a product or experience was previously limited to expensive specialist providers, digital technology now means that nearly anyone can customize their food, clothing, entertainment, housing, and even romantic experiences. The ability to customize leads to individuals having unprecedented access to catalogues of millions of digital streaming movies, the ability to purchase millions more products in one convenient digital storefront, and the ability to view online dating pools of hundreds of local, available matches.

As we become accustomed to this freedom, emerging technologies, products, and services offer us more choices and ways to customize. The ability to customize may affect individuals in ways unexplored by traditional approaches to communication.

Specialists interested in selling products, shifting political attitudes, or changing health behaviors may all benefit from examining the benefits that stem from the customization affordances of modern technology. Specifically, the psychological benefits that come

with customization may influence the way individuals engage with media and process persuasive messages.

Considerable research has been conducted on persuasive messaging in a number of communication contexts, but the majority of this research tends to look at persuasion from the perspective of mass communication. In this context, a message is created by a source and sent to an audience that has little opportunity to engage with the message beyond receiving it or not (Steuer, 1992). Audiences, however, have also become used to this form of persuasion and have developed resistance toward these approaches (Brehm,

1966, Brehm & Brehm, 1981; Wicklund, 1974). Thus, it may be beneficial to look outside the mass communication model of persuasive message design and distribution in order to find new ways for creating effective persuasive messages. One solution may be found in interactive media. Interactive media differ from mass communication in that the message target becomes a reciprocal part of the communication process, wherein a source can craft a message, deliver it to a recipient who can craft a response and direct it back to the source, who will respond again in a continual back-and-forth process. The ability to give the message recipient some control over the message is one unique to interactive media. Because the interactive message process differs from the traditional sender- receiver model of mass communication, persuasive message designers may benefit from using interactive media.

Interactive media allow for the ability to customize objects, people, and experiences. Customization is the ability for a user to tailor content according to the user’s desires. Used for persuasion, giving recipients the ability to customize a persuasive

message, source, or brand may empower the user and increase commitment toward the persuasive target. Thus, customization may be an effective way to use interactive media to reduce resistance to persuasive attempts. Unfortunately, the means by which customization affects attitudes in persuasive contexts has yet to be fully understood. As digital technology is relatively new, efforts have only begun to collate individual effects into larger, explanatory models of interactive media (e.g., Green & Jenkins, 2014;

Sundar, Jia, Waddell, & Huang, 2015). These models hypothesize a range of cognitive, attitudinal, and behavioral effects as a result of using interactive media but lack a focus on the persuasive process. Still, they are useful starting grounds for creating a model that predicts the process by which customization of a message or source could affect attitudes towards a persuasive target.

Persuasive message creators, particularly those in advertising, have made some attempts to use interactive technology to sell a product. Yet many of these attempts that place persuasive messages within interactive media still rely on mass communication methods and do not take advantage of the interactive technology. For example, a sports video game might place real brand advertisements on signs and billboards within the game (i.e., in-game advertising). The user may see these in the process of game play, but has little opportunity to interact with the messages. In this sense, a user is interacting around a persuasive message instead of interacting with it. In-game advertising then runs into the problem of distraction; users expending the effort to play the sports game may focus more on the game than the advertisement that they cannot interact with. For example, Jack Daniel’s website allows users to play an interactive billiards game with the

Jack Daniel’s logo on the pool table and on a nearby digital wall, but users cannot interact with the brand in any way or otherwise influence the content of the branding message (Figure 1).

Figure 1. Depiction of Jack Daniel's online billiards game.

Another approach to using interactive media for advertising is the use of advergames, wherein a video game is created based on selling a product (as opposed to in-game advertising, where a product is placed within a pre-existing game). Advergames allow users to more directly interact with a brand. The Honey Nut Cheerios: Honey Bust game takes the same game play mechanics from the popular smartphone application Angry

Birds and changes the main characters to feature the brand mascot Honey Bee and other 4

features of the cereal. Now users can interact with the brand by controlling Honey Bee in the game. Other advergames repurpose classic board games and put brand messaging around them. For example, M&Ms Red Vs. Green (Figure 2) takes the board game

Reversi and changes black and white pieces to red and green M&Ms while surrounding the board with other brand images. In this case users can interact with the brand in the sense that they are moving the M&Ms on screen, but only in a limited and managed way determined by created by the company. The users have no opportunity to change the persuasive branding message being displayed. Advergames avoid the issues with distraction associated with in-game advertising because users can directly interact with the brand. However, advergames run into another problem wherein the prominence of the branding may create persuasive resistance in users. This resistance, or reactance, occurs when individuals believe they are being told what to do, and it is very effective as a means to keep us from being persuaded (Brehm & Brehm, 1981). In other words, it is very clear that I am being told to buy cereal when I play Honey Bust, and so I will prepare myself to resist being told what to do in any way that I can.

Figure 2. Depiction of M&Ms Red vs. Green online game board.

Thus, there is a real need to use interactive media for persuasion purposes in a way that will not be too distracting from the persuasive message nor elicit high reactance from users. I posit that allowing users to customize a persuasive message or source may be the solution. Users who have the opportunity to customize a persuasive message to their liking (beyond the careful parameters set by the source) may be influenced in ways significantly different from exposure to a static message. Customization avoids distraction by placing the focus directly on the message, but it avoids reactance by giving users empowerment to make changes as they see fit.

The objective of this dissertation is to better understand the ways in which customization influences reactance within the persuasive process. Specifically, I am interested in how customization can lower resistance to persuasive messaging. Using customization as an interactive affordance, I conducted three studies to study the means by which customization can affect the persuasive process. The main goal of these studies was to establish and test an explanatory model that describes the means by which customization of a persuasive source or message can reduce reactance and ultimately increase favorable persuasive outcomes. In order to create an explanatory model of this process, existing literature on entertainment media, interactive technology, and persuasion were consulted and used to create a theoretical foundation.

From literature on technology, affordances, and interactivity, Sundar et al.’s

(2015) theory of interactive media effects was chosen as a foundation for understanding the means by which interactive media can affect an individual. This theory is a useful starting ground for understanding how customization might affect the persuasive process, because it is the most current and comprehensive approach to understanding interactive media effects to date, yet it has been untested as a comprehensive model. In creating a model to account for customization’s effect on reactance, I made a number of conceptual revisions to the TIME in order to adapt it to persuasive contexts as well as argue for some new predicting variables.

Where Sundar et al.’s (2015) model gives a framework for how interactive media can shape attitudes, the entertainment overcoming resistance model (EORM, Moyer-

Gusé, 2008; Moyer-Gusé & Nabi, 2010) provides a framework for how entertainment

media might affect resistance to persuasion. The EORM proposes and tests the key mediating variables that explain how embedding a persuasive message within a narrative can overcome resistance to persuasion by means of identification with characters and engagement with the story. The EORM offers clear guidelines on how to craft narratives that best lower resistance to persuasion, and gives researchers clear direction on how to further study the impact of persuasive narratives. In a similar way, my model discusses the key variables involved in the customization process that might affect reactance.

Using these two theoretical frameworks, I propose that giving users the ability to customize a persuasive source or message will reduce reactance and increase favorable persuasive outcomes. Reactance will decrease because customization will satisfy users’ key psychological needs for autonomy and competence, as well as cause them to establish a strong sense of shared identity with the object that they customize. In turn, need fulfillment and a sense of shared identity will influence their engagement with the interactive medium, which will in turn decrease reactance to the persuasive message. In this way, customization will reduce reactance and ultimately increase favorable product attitudes. This model, the customization reactance reduction model (CRRM), will be one of the first tests of a comprehensive explanatory model of interactive media effects.

On a broad level, the focus of this research is twofold: First and most importantly it will hypothesize the means by which customization can influence the persuasive process, which would allow for better understanding of a new tool that can be used to make effective persuasive messages. Interactive media represent an opportunity for persuasive message creators to take advantage of the newest technology and persuade

their target audience in a new and unfamiliar way. Second, the research will provide some evidence for some relationships between concepts as proposed in a larger model of interactive media effects (i.e., the TIME). The TIME has yet to be empirically tested as a whole, and though the research will not directly test this model, the relationships proposed and variables used in the customization and persuasion process should shed light on how to better understand the relationship between technology, perceptions, and attitude change.

This dissertation will start with a broad overview of the affordances of interactive technology, and how they might impact one’s attitudes and behaviors. Because the TIME provides the theoretical backbone for the CRRM, I elaborate on its propositions and propose some conceptual revisions based on other literature on interactive technology.

These revisions will establish the means by which customization can influence our perceptions. Following conceptual revisions to the TIME, I will discuss customization in a persuasive context by proposing the way in which our perceptions will influence engagement and reactance with a persuasive message. These arguments will result in the finalized model, the CRRM. Three studies have been conducted to test the propositions described by the CRRM. The first two studies serve to initially prove that customization can affect reactance and attitudes toward a persuasive message, as well as establish how mediating variables such as need fulfillment and perceptions of a shared identity might influence reactance. The third study attempted account for all important predictor and mediating variables in order to test the CRRM comprehensively. Following the testing of

the model, implications concerning the TIME, customization, persuasion, and new media will be discussed.

Chapter 2: The Theory of Interactive Media Effects (TIME) with Conceptual

Considerations

To begin to create a model that attempts to explain the means by which customization can affect reactance, it is important to establish a strong theoretical foundation in existing literature. The goal of this dissertation is not to directly test propositions of the TIME, but to use it as starting point to put together a model that can be applied specifically to customization and persuasion contexts. The TIME makes a number of propositions regarding importance of mediating or predictor variables that conflict with other literature on interactive media. The following will describe the propositions in the TIME and argue for a number of conceptual revisions in order to create the most effective explanatory model to be used for later testing.

The Theory of Interactive Media Effects (TIME)

The theory of interactive media effects (Sundar et al., 2015) is the most recent and comprehensive approach to theorizing the process by which interactive media can affect individual attitudes, knowledge, and behavior (Figure 3). The model suggests that interactive media might influence a user in one of two ways: by offering cues that influence perception of the medium and content presented on it, or by motivating action, ultimately influencing knowledge, attitudes, and behavior. In the cues path, each

perceived affordance activates certain heuristics, and those heuristics influence perceptions. For example, seeing pictures as opposed to text on a website is an affordance that activates the heuristic of realism (Sundar, 2008). This realism would then affect perceptions of the website, making it seem more familiar, trustworthy, or credible

(Sundar & Limperos, 2013). In the action path, each affordance offers the potential for action. The potential for action influences perceptions of engagement, which ultimately can affect one’s knowledge, attitudes, or behavior. Engagement, conceptualized by

Sundar as absorption into the medium and cognitive evaluation, is influenced by a number of important mediating variables, including need fulfillment and a sense of agency. These variables influence engagement to stronger or lesser degrees depending on the affordances present in the medium, which then affect knowledge, attitudes, or behavior. For example, seeing hyperlinks on a website would imply the ability to navigate between pages. Navigation would increase perceptions of contingency and user control, which would increase one’s engagement with the website. Ultimately that increased engagement could lead to better knowledge of the website, more positive attitudes towards the website, and influence intentions to continue using the website or recommending it to friends.

Figure 3. The TIME model (Sundar et al., 2015).

It is important to note that in this model, affordances of the medium influence mediating psychological variables. It is only through the changes in those psychological perceptions (e.g., control, motivation) that interactive media affordances can affect knowledge, attitudes, and behavior.

The TIME is one of the first attempts to consider all of the findings on interactive technology research and build a comprehensive explanatory model. Yet the TIME is only one way of considering these variables, and other research has made arguments for different relationships or placements between variables in the model. To limit the scope of this discussion, I will focus only on the action path proposed in the TIME. There are some considerations that should be taken into account when assessing the TIME in order to move forward to building the CRRM. First, the TIME relies on the four affordances of modality, agency, interactivity, and navigability, but these affordances are not comprehensive and overlap conceptually. Second, the TIME places a focus on structural aspects of interactive technology without accounting for the explanatory power of user perceptions of interactivity. Third, the TIME does not consider executive functioning as a key predictor variable. Each of these issues will be elaborated in the following sections.

Issue 1: Conceptual Overlap of TIME affordances

Interactive Media Affordances

The concept of an affordance was originally conceptualized to describe a relationship between an element of the environment and a potential actor on that element

(Gibson, 1977, 1979). To Gibson, an affordance was an inherent actionable property of a part of the environment. A table with four legs and a flat board on top contains a number

of affordances, but these depend on the capabilities of the actor. For one light enough to sit on the table without breaking it, the table offers the affordance of support, but that same affordance would not be present for someone who was too heavy.

Any given technology holds many potential affordances, depending on the capabilities of the actor. As Gibson (1977) characterized it, affordances are an inherent capability of the technology; an actor may not be aware of certain affordances provided, or those affordances might not have yet been discovered, yet they are still present within the object. Norman (1988, 1990), who popularized the term, discussed affordances in a different way (McGrenere & Ho, 2000). To Norman, affordances are dependent on the perceptions of the user rather than inherent abilities present in the object. In other words,

Norman posits that if a user does not perceive the table to be supportive, then the table cannot be said to have the support affordance. Though this affordance may be present to others, in this case it is meaningless to the user. In this sense, affordances may be real

(i.e., inherent) or perceived, and these two do not need to be the same (Norman, 1999).

The user will only benefit, however, from affordances that can be perceived. The distinction between these conceptualizations is particularly important when discussing new media technology and interactive media effects. Is it better to think about the real affordances present in an interactive technology, or is it better only to consider what individuals perceive to be interactive? A technology that offers a number of abilities loses meaning to a user that cannot understand or use these abilities.

Past experiences heavily influence the perception of affordances (Norman, 1988,

1990), and in emerging new media many affordances present within the media may not

be understood due to their novelty. To a new user who has never seen one, a hyperlink looks like oddly colored text. The affordance of the hyperlink is meaningless if the user never clicks. Getting the user to understand what affordances are present is a key concern for designers of new technology and user interfaces. The role of a good designer in part becomes one of making inherent affordances perceivable to novice users. For example, to help aid the perception of the clicking affordance a designer might change the mouse cursor to a hand or finger pointing to the hyperlink. Thus, users’ perceptions of affordances are very important in determining how the interactive media that they use will affect them.

Modality, Agency, Interactivity, and Navigability (MAIN)

As with any technology, interactive media have been studied to isolate their affordances (Rubin, 2000). According to Sundar, in order to best understand how interactive media can affect knowledge, attitudes, and behavior, we must understand affordances that are unique to interactive media. The theory of interactive media effects highlights four affordances that are hypothesized to be unique to interactive media. These affordances are drawn from Sundar’s MAIN model of interactive media, which categorizes the unique affordances that modern interactive media have, and offers predictions about how those affordances are perceived by users and fulfill users’ needs

(Kalyanaraman & Sundar, 2006; Sundar, 2004; Sundar, 2008; Sundar & Limperos,

2013). The MAIN model proposes that modality, agency, interactivity, and navigability are the four classes of affordances unique to modern interactive media. The TIME suggests that cataloging these affordances allows for careful exploration of their unique

effects; by understanding the affordances we can begin to test how they affect knowledge, attitudes, and behaviors in ways unique to interactive media (Sundar et al.,

2015).

Modality refers to the variety of ways information, or content, can be presented via modern interactive media (Sundar, 2008). For example, on the Internet one is able to see content as text, audio, pictures, or videos. Being able to engage with content in many different forms has its benefits, as humans process information from different modalities in very different ways with differing outcomes (Van Der Heide, D’Angelo, &

Schumaker, 2012), and the inclusion of multiple modalities can increase perceptions of credibility or source quality (Petty & Cacioppo, 1986; Simons, Berkowitz, & Moyer,

1970).

The agency affordance refers to the ability to be the source—or agent—of information (Sundar & Nass, 2001). Interactive media often present content created by others, but it is the ability to create one’s own content, or to shape one’s own experiences, that is a unique affordance of interactive media. For example, the popular video game

Minecraft presents players with the tools to create their own worlds; it is a video game version of playing with Legos. The game is less about focusing on the game designer’s content and more about creating one’s own work. The Internet facilitates agency through blogging, video sharing, and curation of all sorts of content, from one’s favorite video list on Netflix to carefully selecting which individuals to friend on social media.

According to Sundar (2008), interactivity is an affordance that refers to the ability for a user to make real-time changes to content. Where agency allows for us to be the

source of content, interactivity gives the ability to influence content in real time; users can receive and process content, make changes, receive modified content, and change content again quickly. Video games are an excellent place to see interactivity at work; a player must constantly monitor the game world and react to it, which causes further responses from the game world. Interactivity is also present in the ability to link between web pages; a user is constantly reacting to the page and clicking on it to change the page, which creates further interaction (Sundar & Marathe, 2010).

Finally, navigability refers to the sense of movement through a medium (Sundar,

2008). Whereas interactivity focuses on giving immediate change to source content, navigability concerns how one can move through content without necessarily influencing it directly. This affordance also comes with the expectation that we will be guided through content. For example, a shopping cart icon representing a checkout system on a website should make us feel comfortable that our money and information will be safe, and we will be walked through the purchase process without feeling confusion or a lack of direction to the completion of the purchase.

The TIME has some shortcomings by using modality, agency, interactivity, and navigability as a framework for categorizing interactive media affordances. The first issue concerns the four affordances and their conceptual overlap. In the case of creating an overarching theory of interactive media effects, these affordances do not offer enough conceptual distinction to be of use. Second, as conceptualized, the four affordances are not unique to interactive media, and are thus not the optimal starting point to use in determining interactive media effects.

Conceptual Overlap and the Four Affordances of TIME

The TIME makes the claim that the four MAIN affordances are unique to interactive media and are mutually exclusive. Thus, all of these elements can be tested experimentally by varying which affordances are present and examining how the affordances affect engagement. There are problems with the affordances in TIME, however, that indicate that these affordances are not conceptually distinct and are not uniquely present in interactive media. It is possible that some affordances are present in both interactive and traditional media (e.g., to search for information), which undermines assumptions in TIME and the MAIN model. In addition, the distinction between modality, agency, interactivity, and navigability is unclear. These problems are discussed, and an alternate framework for viewing interactive affordances as a non-independent set of requirements is proposed.

Pictures, text, video, and audio are all separate modalities for presenting information (Sundar, 2008; Sundar & Limperos, 2013; Sundar et al., 2015). The ability to change modality is an affordance of digital media, even interactive media, but it is also an affordance for traditional media. A book can present text and pictures. A movie features a combination of audio, visual, and text. Most media have the ability to present information in a variety of ways, but the presence of different modes of information does not imply interactivity. Sundar et al. (2015) argue that modality is an interactive affordance because the user has the ability to choose between different modalities. In other words, if one wishes to research a topic on the Internet, one can look up whatever mode of information best works for that individual, be it as a video lecture or an online encyclopedia. The

choice of which mode can be accessed is the user’s decision, and the ability to make that choice – selecting one over the other — is unique to interactive media. A book may feature both pictures and text, but the book does not offer the ability to choose between the two. So choice, or more specifically active control, may be a more descriptive affordance of interactive media, rather than the ability to see multiple types of information.

The navigability affordance runs into similar issues. Navigability is conceptualized as options that allow the user to navigate between information (Sundar,

2008). Navigability includes breadcrumbing or showing evidence of the navigation path so the user can return home or to previous steps if needed, or giving other signposts to indicate where the user is in a navigation process. Again, as conceptualized this is not something unique to interactive media. A book features breadcrumbing in the form of page numbers and chapter headers; readers have a clear sense of where they have been and they currently stand. Theater intermissions give watchers a sense of where they stand in the play, and characters recap the story so watchers have a sense of where they have been and where they will proceed in the narrative. Sundar et al. (2015) elaborate that navigability concerns the ability to actively direct oneself in the flow of information; signposts and breadcrumbing indicate the ability for one to move throughout the content, and that is an affordance unique to interactive media. Again, this affordance has less to do with navigation than the more general ability for one to have active control over one’s experience. Thus, navigation falls under a broader category of active control over the experience, as does switching between modalities.

Finally, navigability and modality affordances conflict with the other affordances of the MAIN model, interactivity and agency. According to MAIN, modality is a distinct affordance due to the ability to switch between modes, but this conceptualization does not account for the notion that a user is required to do the switching. The user determines which form of information to engage with, and it is that self-governance that drives the user’s experience. In other words, changing information modality requires the user to be source of the change (i.e., have agency). If the source itself changes modalities (e.g., book showing text on one page and pictures on the next) then the medium ceases to be interactive, precisely because it does not permit for user agency. Thus it is very difficult to conceptually distinguish modality from agency.

Likewise, switching between types of information, or actively navigating through content also falls under the purview of interactivity; users (as the source of content) often make real-time changes to their experiences. These cases indicate conceptual problems concerning the distinction between the MAIN affordances. One of the proposed benefits to the MAIN approach is that it allows for careful experimentation between the different affordances; each can be isolated and test to see which affordance feels the most interactive (e.g., testing breadcrumbing against different information modalities). Yet the overlap between these concepts prevents effective testing; the affordances are not often linked with later measures of perceived interactivity or vary from study to study in their effectiveness (Sundar, 2008). This overlap creates the need for a better conceptualization of the key affordances of interactivity.

Finding a New Affordance Framework

The degree to which a medium should be considered interactive is the subject of much debate. First, interactivity is looked at much differently between different fields of communication. To a mass communication scholar the concept of a receiver interacting with a message is relatively new and important, yet to the interpersonal communication scholar interactivity in a face-to-face conversation is a “native state” (Walther, Gay, &

Hancock, 2005, p. 640). One of the first attempts to unify the conceptual definition between fields discussed interactivity as a targeted third response; an actor speaking is an act, a response to that actor is reactive, but for the communicative act to be considered interactive the third message must refer to prior messages and “is interpretable and meaningful only by that referencing” (Rafaeli, 1988, p. 641).

This definition is useful in that interactivity is considered only a set of acts and is not medium dependent. It is flexible, and the study of interactivity as proposed by this definition has the benefit of allowing the study of a dynamic and changing concept in communication. This definition has been further refined. Steuer (1992) described interactivity as the extent to which users can modify form and content in real time. In this view, the ability to manipulate content sets interactive media apart from traditional media such as books or movies. Steuer saw interactivity as part of a technology’s structure; the extent to which something was interactive depended on speed of the medium’s response to input, the number of attributes that can be manipulated, and how a controller translates or maps actions into the digital environment. Downes and McMillan (2000) chose to outline six distinctive dimensions of interactivity: two-way communication, flexible timing, creation of a sense of place, perception that users have control, perception that the

communication is responsive, and goals focused on communicating, rather than persuading. Note that these dimensions include many of the essential elements of

Rafaeli’s definition, including responsiveness, but they elaborate into broader categories of message-based dimensions and participant-based dimensions, which are much more concerned with participants’ perceptions of what constitutes interactivity (Kiousis, 2002).

There is no agreement on a conceptual definition of interactivity, but one approach makes a strong attempt to synthesize the conceptual disparity while accounting for individual perceptions and affordances of the technology. Liu and Shrum (2002) suggest that previous definitions of interactivity have been split between discussions of user-to-user, user-to-machine and user-to-message interaction. They attempt to combine these three dimensions into a single definition where interactivity is, “the degree to which two or more communication parties can act on each other, on the communication medium, and the degree to which such influences are synchronized” (p. 55). The authors suggest three dimensions required for categorizing interactivity: active control (how a user can voluntarily influence his or her experience), two-way communication (how effectively can the “other” respond), and synchronicity (how simultaneous the interaction is).

The conceptual overlap associated with the TIME affordances can be alleviated by mapping them onto these three dimensions. Essentially, interactivity according to Liu and Shrum (2002) boils down to the ability to make changes (active control), receive feedback based on those changes (two-way communication), and have that process occur nearly simultaneously (synchronicity). Many of the visual cues signaling modality or

navigability affordances presented by Sundar and colleagues indicate one of those three dimensions, particularly active control. Experience with websites and links and navigation over time bring about the expectation that one can influence the content, and that the website will respond in kind. The interactivity affordance of the TIME requires all three dimensions to make real-time changes to content, and the agency affordance is conceptually similar to the active control dimension.

The TIME affordances are proposed to act independently. An important distinction to make between these and the three dimensions of active control, two-way communication, and synchronicity, is that Liu and Shrum’s dimensions should not exist independently. The presence of any one requires the presence of the others to function, or the medium ceases to be interactive. Active control loses meaning if there is no meaningful response, and there can be no feedback without an initial, active input. If synchronicity low, and input and responses are separated by too much time, then the lack of response to an input should make one feel as if they have no control.

Consider playing chess against another individual. In order for the game to feel interactive, all three dimensions must be present. Isolating each dimension is meaningless, and so is attempting to understand which dimension is “better” at facilitating feelings of interactivity. We could remove active control from the chess game by making moves for the player. The opponent will still respond (two-way communication) in a synchronous time period, but the player should not feel a sense of interaction. Likewise we can remove the two-way communication dimension by randomly assigning the opponent’s moves. In this case the player’s active control of

pieces on the board is met with a response that is not directly related to the player’s input; the opponent’s moves would be senseless and the game would cease to be fun. This version may be perceived as somewhat interactive because the opponent does respond to the player with a move, but once the player realizes that his or her input will not affect the opponent’s moves in any way, then engagement and perceived interactivity should greatly decrease. Finally, removing synchronicity should also result in low perceptions of interactivity; lengthening the time between a player’s moves and an opponent’s response to a point where the opponent takes hours, or days, or years to respond to the player’s moves should result in very low perceptions of interactivity. Thus it is not appropriate to consider these dimensions as independent from one another; it is their interaction that comprises the experience of interactivity. And because it is difficult to anticipate which dimension might influence the user at a given time, it is more appropriate to judge interactivity based off user perceptions. This approach of combining the three dimensions in terms of their overall effect on the user suggests that an emphasis on perceived interactivity rather than structural interactivity may be more beneficial to a model assessing customization effects.

Issue 2: TIME and a Focus on Structural Elements

The degree to which a medium is interactive is typically conceptualized in one of two ways: structurally or perceptually (Liu & Shrum, 2002). Structural interactivity refers to the physical aspects of the medium that allow for interactivity. Hyperlinks between documents, the ability to write and post a personal story, the ability to fight and defeat and enemy in a video game, or a scroll bar on a website are all examples of structural

interactivity. Interactive media can significantly vary on the quantity and type of structural interactivity present; consider how different two websites can be based on available links or buttons to click alone. In contrast, perceived interactivity refers to how interactive a user believes a medium to be. In this case, interactivity lies within the user and the user’s perceptions (Liu & Shrum, 2002). Both structural and experiential interactivity can be present to varying degrees but are not necessarily connected; it is possible that a website with many buttons to press can be perceived as less interactive than one with fewer buttons, depending on other factors that influence the user (Liu &

Shrum, 2002). Both types of interactivity answer the question “how interactive is this?” in two different ways: by assessing the medium (structure) or assessing the user

(perception).

The distinction between structural and perceived interactivity echoes past debates concerning affordances. Some argue that interactivity is inherent in the structure of the technology itself (e.g., Sundar et al., 2015), following Gibson’s (1977, 1979) conceptualization of affordances as inherent in the object itself. The TIME takes this approach by emphasizing experimental manipulation of the MAIN affordances to assess effects of interactivity. From this perspective, it is better to focus on structural affordances because assessing the degree to which something is interactive by asking users solely about their perceptions of the medium is problematic:

These perceptual measures of interactivity may be conflated with user perceptions

of system attributes that are unrelated to interactivity, e.g., usability. As such,

perceived interactivity is a user variable, reflecting variations in usage, skills, and

user experience of the system. It makes interactivity an attribute of the user, rather

than the system…limiting our understanding of the role played by technology

(Sundar et al., 2015, p. 6).

In other words, Sundar and colleagues argue it is of little use to base our understandings of interactive media on how someone rates that media to be interactive, as a number of factors (including motivation or liking of the content) that have little to do with interactivity of the medium may influence this perception. Thus in order to create better, more interactive media we must focus on the structural affordances that are present.

However, a focus on structural affordances is problematic because it cannot offer clear boundary conditions. From a design perspective, a structural approach would require interactive technology to be created based entirely on affordances of the technology. Thus, a website designed to be very interactive should feature as many aspects of modality, agency, interactivity, and navigability as possible. The structural approach is contrasted with the user-centered approach advocated by Norman (1999), wherein the design process is iterative and relies heavily making structural elements understandable to users as well as relying on their feedback throughout the design process.

According to TIME, as affordances become prevalent and increase in quantity, then the positive effects associated with those affordances should also increase (Sundar,

2008; Sundar et al., 2015). This perspective posits a linear relationship between affordances and engagement or other outcome variables. Following this logic, four hyperlinks are more interactive than two, and eight even better. The models do not, and

cannot, specify an optimum amount of affordances; following this to its conclusion means that our finest and most interactive medium would feature thousands of links, buttons, and navigation elements. However, there is some evidence that suggests this is not the case. Research on choice and decision-making suggests that too many choices can become overwhelming, leading decision makers to feel less satisfied with their decision, desire unchosen alternatives more, and generally feel exhausted from the process of deciding between all the options (Iyengar & Lepper, 2000; Schwartz, 2004). Interactive media give users active control in the form of allowing them to make choices to actively guide their experience. Giving participants too many options to control their experience, or too much feedback, is overwhelming them and reduce their satisfaction, motivation, and ability to perform the task the same way having to choose between 20 different types of jam at a grocery store can (Iyengar & Lepper, 2000; Koch, 2011; Roberts, Beh, &

Stankov, 1988). Engaging with so many different technological tools could also fatigue a user or force them to stretch their attention too thin to have an enjoyable experience.

Perceived Interactivity as a Better Alternative

Creating interactive media that focus on user perceptions of interactivity would require an approach different from that of the structural perspective. Designers would create a product based on initial structural affordances, but would place an emphasis on making sure those affordances are understandable and available to the user. This design process would also involve numerous iterations of the product as the user is consulted and tested throughout the design process to create a product that is perceived as the most interactive product. An approach like this may be a better and more thorough design

process. Indeed, the concept of perceived affordances originated with an interaction designer; Norman (1988, 1990) viewed affordances as meaningless if they could not be understood by the user, and proposed that designers take great efforts to communicate meaning to users. The evidence suggests that perceived interactivity is very important

(Liu & Shrum, 2002). High perceived interactivity increases user satisfaction, perceptions of trust in websites (Hu, Wu, Wu, & Zhang, 2010), ratings of website effectiveness (Song

& Zinkhan, 2008), and video game enjoyment (Klimmt, Hartmann & Frey, 2007). Thus, instead of focusing efforts on placing structural affordances within the medium, we should work to make sure that those affordances are seen as available and usable.

A focus on perceived interactivity also aids in the nature of the interactive communication process. The TIME suggests that interactive media effects are unidirectional, in that affordances drive perceptions which drive engagement which influence attitudes, knowledge, and behavior. Interactive communication is a reciprocal, changing process. It is plausible that new attitudes, knowledge, and behavior further influence perceptions, which further influence engagement. Users’ perceptions (e.g., of enjoyment or need satisfaction) can change throughout this time, making it even more critical to understand the role that these perceptions play in every step of the interactive process. Because the user continues to have an active role in the interaction, the user’s perceptions about the medium will continue to change and influence their perceptions of the affordances of the technology, which will in turn influence attitudes. It is difficult to isolate the role played by technology in interactive media because the interaction process is constantly changing and updating.

Due to the lack of clear boundary conditions and the non-independent relationship between the core affordances, the TIME model can be refined with less of a focus on the structural affordances and more focus on user perceptions. Examining the psychological experience of interactivity allows researchers to focus on the mechanisms by which interactive media influence behavior, rather than the structural affordances. Focusing on perceived interactivity also removes the problem with varying boundary conditions between individuals; examining perceived interactivity allows each compare their experience relative to their own individual background and preexisting attitudes. Despite the focus on the structural affordances, perceptions of interactivity have a crucial mediating role in the TIME. Thus, a revised model of interactive media effects would place perceptions of interactivity as the key predictor variable.

Figure 4. Perceived interactivity as the key predictor variable for other perceptions proposed in the TIME.

Concerns with Focus on Perceived Interactivity

One of the downsides to focusing on perceived interactivity is in experimentally creating independent variables to manipulate and test. To assess how perceived interactivity affects the rest of the engagement process, perceived interactivity must be primed or signaled to the user in some way. Sundar et al. (2015) argue that this is what makes structural affordances imperative; they are the only means by which we can reliably prime perceived interactivity. In doing so a great deal of research has been conducted examining the role of different structural forms of interactivity and its role in experimentally affecting perceptions of interactivity.

Instead of asking which affordances better affect perceptions of interactivity, it is better to ask how perceiving a medium to be interactive affects the individual. This question can be answered by experimentally comparing interactive and non-interactive media with each other, rather than different affordances of interactive media. In this case, perceived interactivity remains primed by focusing on meeting a minimum threshold of interactivity comprised of the three affordances: synchronicity, two-way communication, and active control. Are there elements on a website that indicate the user will have active control over it, that it will respond to the user’s input, and that back-and-forth will happen in a reasonably timely manner? If so (and through rigorous pre-testing) there is a reasonable expectation of increasing perceptions of interactivity. The extent to which the experimenter meets these expectations in a reasonable way is the extent to which considering structural affordances is important. Once this minimum threshold is reached, perceived interactivity should take precedent. The perceived interactivity approach is flexible enough to be readily applied to new technologies; there is no need to spend time understanding if a new type of navigation is interactive or not (or to what degree) and the focus can remain on the core interactive process

Issue 3: TIME & Lack of Executive Functioning as Predictor Variable

The TIME overlooks executive functioning as a powerful predictor variable.

Executive functioning concerns the brain’s ability to perform three subsets of skills: self- regulation, memory, and directing attention (Nathanson, Alade, Sharp, Rasmussen, &

Christy, 2014). Interactive media differ from traditional media in their ability to tax a user’s mental resources. Interacting requires a substantial amount of effort; a user playing

a video game must devote attention to the screen, process the constant changes in the game environment, process the rules of the game, and translate desires into physical commands that are enacted through the controller. Even the process of creating one’s social network profile requires a combination of attention, processing, and concentrated effort.

It has been well established that mental resources are limited. Short-term memory is limited to holding between five and nine bits of information at a given time (Miller,

1956). Individuals vary in their ability to concentrate in the face of overwhelming attentional tasks as their cognitive load, the amount of mental effort used in working memory, increases (Schmeichel, 2007). Individuals are also limited in their ability to actively control, or regulate, their behavior. The more one regulates behavior by resisting impulses the more one’s ability to regulate in the future deteriorates. The strength model of self-control looks at the ability to regulate one’s behavior as a muscle that can grow tired with overuse (Baumeister, Vohs, & Tice, 2007; Denson, DeWall, & Finkel, 2012;

Muraven & Baumeister, 2000). Memory, attention, and self-regulation can be thought of as limited resource pools in which one can only draw on so many resources at a given time.

The ability to direct attention can be reduced by having difficult or rapid tasks.

Individuals who receive a number of stimuli have trouble focusing back and forth between stimuli. Attention resources are often studied in device multitasking contexts; as the amount of activities, screens, or devices increase, the ability to perform any given task decreases (Paas, Renkl, & Sweller, 2004; Sweller, 1988, 1994; Wang, 2014; Wang,

Irwin, Cooper, & Srivastava, 2015). Interactive media may aid in placing an individual under high cognitive load. A user must often juggle a number of stimuli within a single program. For example, a user playing an online team game might need to manage the attention tasks of playing the game, seeing a scrolling chat log, and even listening to and responding to voice communication over a headset. With so many different tasks to attend to, it is possible that one becomes overwhelmed, making it difficult to engage with the interactive medium. .

There are a number of ways to deplete self-control resources. Research experiments tend to use a two-task model to study self-regulation (Inzlicht & Schmeichel,

2012). Participants are given a resource depleting task at Time 1, and are then measured on their ability to perform another task that requires self-control at Time 2. Studies have depleted self-control by having participants hold a pair of handgrips squeezed together, submerge their arms in ice water, or actively memorize strings of numbers (Burkley,

2008). In addition, giving individuals a large amount of choices to make has been found to deplete self-control in subsequent tasks (Vohs, Baumeister, Schmeichel, Twenge,

Nelson, & Tice, 2014). Individuals who made 292 choices between various products drank fewer ounces of an ill-tasting drink (where more drinking resulted in greater payment to the participant) and showed less tolerance for pain. Participants who had to choose their own course schedules showed greater likelihood to procrastinate for an upcoming test, and others that made choices showed less willingness to persist at a puzzle solving task and took longer to notify the experimenter of an equipment problem (Vohs et

al., 2014). Thus, the act of making lots of choices results in a depletion of executive functioning.

Interactive media offer the opportunity to customize one’s experience according to one’s preferences. Modern technology emphasizes the ability to customize just about anything; users can choose between millions of movies to watch, decide which profile picture to display with what information on an online dating site, or browse through millions of products for purchase. All of these acts of customization require deliberation between choice options. As such, the affordances of interactive, customizable technology require one to actively make a large number of choices. Thus, the large amount of choices made when using interactive technology could result in depletion of self-control resources. There has been little research that examines whether the effects found for choices extend to customization with interactive media. In one study, participants were told to browse a website, customize it according to their preferences, or customize it for another individual. Those that customized the site according to their preferences persisted longer in an unsolvable puzzle task than those that customized the site for the others, though neither customization condition differed from those who browsed the website

(Kang & Sundar, 2013). The TIME does not consider executive functioning resources as an additional predictor variable that influences mediating perceptions and attitude, knowledge, and behavior outcomes. It is important to consider executive functioning, as the nature of interactive technology should place a strong demand on user attention and self-regulation. Depleting resources may affect other critical variables in the model; overwhelming one with stimuli could reduce feelings of competence as one struggles to

keep up, or draining one’s pool of self-regulation resources could reduce engagement or affect attitude change to future messages.

Engagement

Engagement is a concept taken primarily from advertising and technology literature, and its definition has been the source of considerable academic debate (Calder,

Malthouse & Schaedel, 2009; Mollen & Wilson, 2009; Wang, 2006). Mollen and Wilson

(2009) review the debate and conclude that the best definition of engagement is “a cognitive and affective commitment…” (p.12). Important here is the conceptualization that engagement has both cognitive and affective components. The affective component distinguishes engagement from the related concept involvement, which is conceptualized as a more general and passive interest to process information that typically focuses on cognitions concerning perceived relevance (Mollen & Wilson, 2009; Wang, 2006). Thus, strong engagement requires active attention and elaboration as well as an emotional stake in the medium. Due to the emphasis on cognitive attention and resources, executive functioning should directly affect engagement.

Thus, in addition to perceived interactivity, executive functioning is proposed as a second predictor variable for the CRRM. These two variables are proposed to be correlated but influence the customization process in distinctly different ways. Executive functioning should influence engagement with the medium by means of giving individuals the cognitive ability to focus on the task at hand. Perceived interactivity should influence engagement by giving individuals the belief that they can use the medium to achieve their desired outcomes. Both are important for engagement; without

executive functioning users could perceive that they could interact with a medium but be too mentally drained or unfocused to do so. Likewise, without perceived interactivity users could have all the executive functioning resources available but would not interact with the medium as it is not seen to be interactive.

Figure 5. Executive functioning predicts engagement independently of perceived interactivity.

Using the TIME as a Foundation for the CRRM

As discussed previously, the TIME is a strong starting point for building a model to explain how customization affects the persuasive process. Based on existing literature

I proposed that perceived interactivity and executive functioning should be placed as the predictor variables in the customization process, rather than the MAIN affordances that

Sundar et al. (2015) specify. On a basic level, these variables should influence engagement with the interactive medium.

Instead of a direct relationship, The TIME proposes four categories of variables that mediate the relationship between affordances and engagement: contingency, perceptual bandwidth, self-determination needs, and a sense of agency. I agree that these needs are important to the customization process, but propose a different means of categorizing these variables: variables concerning perception of the medium (e.g., ease of use, responsiveness), variables concerning perception of identity (e.g., self-affirmation, user identity), and variables concerning need fulfillment (e.g., self-determination needs).

Variables concerning perception of the medium have been discussed at length; these are measures of perceived interactivity. As a user sees the medium as responsive, contingent to the user’s input, and intuitive or easy to use, perceptions of interactivity should increase (Liu, 2003). Instead of keeping these perceptions as a mediating variable as the TIME proposes, I argued that they should be moved to the front as a predictor of perceptions of identity and need fulfillment. A sense of identity should also affect engagement; the more individuals see content as a reflection of their identity, the more reason they have to be engaged. In addition, need fulfillment should also increase

engagement; as the psychological needs for autonomy, competence, and relatedness are met by the interactive medium engagement should increase.

The Next Stages of the CRRM: Identity and Need Fulfillment

Identity

A user’s sense of identity may play an important role in influencing engagement.

The concepts of identification, similarity, empathy, and perspective taking have been researched at length and applied to traditional media (Cohen, 2001). This work primarily takes the form of discussing one’s relationship with other characters that occur within the medium’s content, though these concepts can also be applied to interpersonal communication contexts. Identification refers to the cognitive and emotional process where one takes on the thoughts, feelings, and goals of another character. It involves a loss of a sense of self while stepping into another’s identity (Cohen, 2001; Kelman,

1958). A related construct, similarity, refers to one’s judgments about the degree to which he or she shares characteristics, thoughts, or values with a character (Simons, Berkowitz,

& Moyer, 1970). Similarity is conceptualized as an attitude concerning shared characteristics, where identification involves the loss of a sense of self and the taking on of another’s perspective (Moyer‐Gusé & Nabi, 2010).

The entire process of interacting with media comes as a result of user decisions and input resulting in concrete changes or feedback from the environment. Everything a user sees is a reflection of decisions that have been made to suit one’s own needs. For example, an email service might allow users to set filters, create folders, create away messages, and set notifications for important deadlines. Each of these decisions made by

the user in some way reflects that user’s values, thoughts, and decisions. In this sense, the email software is less of a character that one can identify with but rather is a projection of one’s self into the virtual world. Thus, where identification with other characters might be a core variable of interest in narrative research (Moyer‐Gusé, 2008; Moyer-Gusé &

Nabi, 2010), it may not be as important when examining interactive virtual worlds when other characters are not present. Instead, it may be more important to consider similarity.

Because software or other messages may not physically resemble a player, perceived similarity to the user in the sense of shared goals and values should be especially predictive of engagement beyond that of physical characteristics.

It is also possible that users go beyond perceptions of similarity with the object that they customize and actively receive strong reflections of their core values and beliefs. Self-affirmation theory posits that receiving affirmations of one’s core values and worldview can mitigate the effects of self-esteem threat (Steele, 1988). It is possible that when viewing the customized object, one is reminded of all the choices one made to customize the object. In a sense, the object stands as an affirmation of one’s identity, and a way in which one in some small way can make an impact on the outside world. For example, researchers found that users’ created social network profiles provide self- affirmation and that users will gravitate to their profiles after receiving an ego blow (Kim

& Lee, 2011; Toma & Hancock, 2013). Thus it is possible that viewing a customized object may serve as a means for self-affirmation.

These predictions should apply to any space in which the user actively influences the content in a meaningful way, suggesting that any act of customization could influence

perceptions of similarity or identity (Kang & Sundar, 2013). In terms of influence on engagement, similarity and self-affirmation should positively affect engagement; as the content is considered more similar, or one identifies more with the values reflected by the content. Thus, perceived interactivity influences identity by facilitating the impression that one would have the ability to make meaningful choices when customizing and in doing so place a part of their identity within the medium. Executive functioning is proposed to affect identity by means of available cognitive resources. One must have the cognitive ability to focus and perceive impressions of identity within the medium.

Figure 6. Initial proposed relationships of the CRRM adding identity as a mediating variable between perceived interactivity, executive functioning, and engagement.

Need Fulfillment

In addition to a user’s perception of identity as present within the medium, it may be useful to look at a user’s perceptions of important need fulfillment. Self-determination theory (Deci & Ryan, 1980, 1985, 1987, 2000; Ryan & Deci, 2000) is a theory of human

motivation that outlines the degree to which human behaviors are volitional or willful.

That is, the theory states that one acts due to one’s internal desires rather than pressure from external forces. The theory posits that there are three core human psychological needs: autonomy, a sense that one’s behaviors stem from an internal locus of desire; competence, a need to show mastery and demonstrate outcomes; and relatedness, the need to feel connected with others. Successful fulfillment of these needs results in positive outcomes, such as increases in self-esteem, intrinsic motivation, and enjoyment

(Ryan & Deci, 2000). Because the revised model focuses on individuals viewing messages, relatedness needs will not be included. Future studies should add relatedness in as an important need fulfillment when other individuals or characters are present within the message.

To feel autonomous, one would need to feel that behaviors stem from an internal locus of desires (Deci & Ryan, 2000). In other words, people feel autonomous when the actions they commit are done because they want to do them, rather than due to any external force requiring the action. If students believe that they are learning because they enjoy the subject matter and want to learn more, their need for autonomy will be fulfilled.

If those students believe they are learning because their parents want them to get good grades, or they are afraid of failing and being removed from their group of friends, they will not feel autonomous. According to self-determination theory, people attribute the cause of their actions as either supporting or controlling of their autonomy (Deci & Ryan,

1987). Rewards, threats, deadlines, evaluations, and surveillance are all controlling factors that affect autonomy negatively, whereas situations that encourage personal

choice and offer positive feedback are seen as supporting and affect autonomy positively

(Deci & Ryan, 2000; Ryan & Deci, 2000).

The need for competence concerns the need to control our outcomes and achieve mastery over tasks (Deci & Ryan, 2000). To feel competent, we need to see evidence that what we are doing has an effect on a given task, and see evidence that we are getting better, or mastering, a task. Giving someone a video game controller that only works half the time will lower perceptions of competence (Sheldon & Filak, 2008). Likewise, making tasks too difficult or not showing proper progression undermines our need for competence.

Interactive media do a particularly good job in meeting self-determination needs.

Many studies on need fulfillment and media use interactive media to test their hypotheses

(Sheldon & Filak, 2008; Tamborini, Bowman, Eden, Grizzard, & Organ, 2010). The active control dimension should facilitate feelings of autonomy as users are given the ability to decide how they want to shape their experiences. Two-way communication should influence user’s perceptions of competence, as their input is met with responses that can affirm that they have done a task successfully. Synchronicity should facilitate both autonomy and competence as it allows users to quickly make decisions and receive important feedback before proceeding with new actions. Executive functioning should also influence perceptions of need fulfillment. As attention becomes overwhelmed and task performance decreases, one should feel less competent. As self-control resources are depleted, users will see choices as less autonomy fulfilling and more as difficult, draining tasks (Figure 7)..

Figure 7. Initial paths of the CRRM adding in need fulfillment as a mediator.

Chapter 2: Rooting the CRRM within Persuasion

Applying the Initial CRRM to Persuasive Messaging

The ultimate goal of this research is to understand how the ability to customize a persuasive message or source will affect attitudes toward the persuasive target. The model that has so far been proposed (Figure 7) is based off literature on interactive technology. It uses the TIME as a foundation to make arguments that a model accounting for customization effects should have executive functioning and perceived interactivity as predictor variables the influence identity and need perceptions and ultimately engagement with the medium. The next step to building the model is to apply it the context of persuasion. This section will focus primarily on the means by which customization (via mediating variables and engagement) will influence resistance to a persuasive message

(i.e., reactance). With the extreme exposure to advertisements and other forms of messaging that instruct us how to think and what to buy, humans have developed methods to block out or otherwise resist persuasive messages. Individuals have become jaded to traditional advertising, and as this occurs marketers and other developers of persuasive messaging must turn to other, less traditional ways to appeal to consumers or call attention to their particular message.

For example, some success has been found in using interesting, engaging stories to lower one’s defenses to a persuasive message (Moyer-Gusé, 2008; Moyer-Gusé & 45

Nabi, 2010). As one becomes caught up in a story, and identifies with the characters, it is harder to think about the potential persuasive messages written into the story, and harder to argue against them when made clear. Thus, distracting or otherwise engaging individuals might be important when considering how to get people to pay attention to persuasive messages. Distraction by means of an engaging narrative is one of the means by which product placement is effective (Lee & Faber, 2007).

The nature of interactive media should change the way persuasive messages are interpreted in unique ways. Where narratives can succeed through immersion into the story and identification with characters, interactive media may succeed through engaging cognitive resources, fostering a sense of identity, fulfilling key psychological needs, and increasing engagement. All of these factors should have a strong impact on one’s resistance to persuasive messages.

Psychological Reactance & Resistance to Persuasive Attempts

Psychological reactance (Brehm, 1966; Brehm & Brehm, 1981; Wicklund, 1974) is a theory that was created to understand why some attempts at persuasion fail. There is a long history of health and marketing campaigns that contain all the best attempts to persuade, but still fail. These failed attempts do not bring individuals around to the advocated position and at worst, they cause individuals to worsen their attitudes toward the position (Dillard & Shen, 2005; Petty & Cacioppo, 1977). The theory posits that when people feel an attempt to be influenced they are motivated to reject that attempt at influence (Bushman & Stack, 1996; Clee & Wicklund, 1980). Specifically, there are four key elements to reactance theory: freedom, a threat to freedom, reactance, and a

restoration of freedom (Brehm, 1966; Brehm & Brehm, 1981; Wicklund, 1974). The theory suggests that at any given time, individuals perceive a set of behaviors available to them that they are free to engage in. This perception requires that the individuals have knowledge of the behavior and feel like they can enact the behavior. Once a behavior is perceived as possible, any force that makes the behavior feel more difficult to enact is constituted as a threat. For example, a student might believe that they have the freedom to speak to a friend in class, and a teacher’s demands for quiet would constitute a threat to that freedom (Brehm & Brehm, 1981). A television viewer might perceive the freedom to make choices about household cleaners, but a commercial concerning a specific product would be seen as a threat to that freedom to choose.

Once a freedom is threatened, one is motivated to restore that freedom (Brehm &

Brehm, 1981). This motivation to restore a threatened freedom is known as reactance, and it might take place in a variety of ways. An individual might commit the forbidden act despite the threat for doing so. That individual might react indirectly to the threat by increasing liking for the threatened choice, or by derogating the source of the threat.

Additionally, one could deny the existence of the threat or exercise a different freedom in order to gain a feeling of control (Wicklund, 1974). Reactance has been found to influence the impact of persuasive messages in a variety of contexts (Petty & Cacioppo,

1977) from politics (Brehm & Brehm, 1981) to warning labels (Bushman & Stack, 1996).

Brehm (1966) originally conceptualized reactance as a motivation to restore a threatened freedom. As it was first discussed, however, reactance was not a concept that could be directly measured (Brehm, 1966, Brehm & Brehm, 1981). Rather, reactance

could only be seen indirectly via measuring outcomes to attempts at persuasion.

Experimental groups were often measured on their pre-attitude measures towards the topic of a persuasive speech. After receiving the speech, if their attitudes were further from the advocated message than originally indicated, reactance was said to occur

(Brehm, 1966). Other typical experiments involved giving participants a choice between a set of alternatives and measuring their preferences for each alternative before and after knowing they would be required to make a choice (Brehm, Stires, Sensenig, & Shaban,

1966; Clee & Wicklund, 1980). Individuals who showed higher preference for some alternatives after being told they must choose one were said to have shown reactance; once the choice was made salient to participants, the freedom to choose each alternative was threatened. Thus, the motivation to restore that freedom lead to higher ratings of the alternatives (Brehm et al., 1966).

This approach to studying reactance as a change in attitude in the direction away from persuasive attempts continued for the majority of the theory’s existence (Dillard &

Shen, 2005). Only recently have scholars begun to operationalize reactance as a combination of angry affect and cognitive responses in the form of thoughts against the advocated message (Dillard & Shen, 2005; Quick & Stephenson, 2007; Rains 2013;

Rains & Turner, 2007). Through this conceptualization, when a freedom is threatened an individual responds affectively with anger towards the message and the message source, and also responds by cognitively considering viable counterarguments that go against the persuasive message. This mix of affect and cognition occurs simultaneously (Quick &

Stephenson, 2007; Rains, 2013; Rains & Turner, 2007) and mediates the effect of threat on attitudes towards the persuasive message’s advocated position.

Reactance is a powerful form of resistance to persuasion, and the means by which to avoid or reduce reactance has been the subject substantial scholarly research (e.g.,

Brehm & Brehm, 1981; Dillard & Shen, 2005; Rains & Turner, 2007). Some of these attempts try new and creative ways to distract individuals from the realization that they are being persuaded (e.g., Moyer- Gusé & Nabi, 2010). Customization provides another opportunity to reduce reactance. An interactive medium that hides a persuasive message within may distract individuals from the message by giving them other tasks and stimuli to engage their attention. Customization might also allow for an individual to restore a threatened freedom by means other than reactance (e.g., making choices elsewhere within the medium). In this way, the engagement should have a negative relationship with reactance. Engagement should influence reactance as a distraction wherein users are too caught up in the medium to notice a persuasive attempt, and as a different way to occupy users’ executive functioning resources. A user with high engagement with the interactive medium will not have the executive functioning capacity to engage with the medium as well as to elaborate on the persuasive message and generate effective counterarguments.

Executive Functioning & Reactance

The cognitively demanding acts associated with interactive media may deplete the limited executive functioning resources, which ought to affect subsequent tasks that require those resources. Executive functioning depletion should affect one’s ability to resist persuasive messages. The ability to resist is an active, goal-directed process that

requires concentration and effort (Burkley, 2008). When presented with a counterattitudinal message, one desires to resist the temptation to give in and tries to retain a prior opinion. If that individual does not have the willpower to conduct resisting efforts, then that person should gravitate more toward the advocated position. This finding has been well documented; individuals who are deprived of self-control resources

(typically by using them at an earlier task) are less resistant to persuasion (Burkley, 2008;

Fransen, Verlegh, Kirmani & Smit, 2015) and social influence (Burkley, Anderson, &

Curtis, 2011). Thus, the act of resisting persuasion requires self-control. Depletion of self-control resources should then make it harder to subsequently resist efforts of persuasion.

It has been shown that choices can reduce self-control resources (Vohs et al.,

2014), and that the lack of self-control resources will reduce resistance to persuasive messages (Burkley, 2008). There is some evidence to suggest that the choices present in customizable media may also reduce self-control resources (Kang & Sundar, 2013), and this will be further investigated by Study 3. It remains unclear, however, the extent to which self-control resources depleted by the choices present in customizable media can affect one’s resistance to persuasion. The attentional and self-control resource demands placed on an interactive user are high. It is plausible that these demands on attention and cognitive resources reduce the ability to actively form counterarguments (via reducing self-regulation resources) or remove attention from the persuasive message entirely (via demanding the user’s attention). Thus, executive functioning resources should indirectly affect reactance through engagement.

Self-Determination Needs & Reactance

The relationship between self-determination theory and reactance is best examined through the need for autonomy from self-determination theory. Successful attainment of autonomy requires an individual to perceive that one’s actions are coming from one’s internal desire (Deci & Ryan, 2000). Autonomy is frequently operationalized in research experiments as giving participants choices to make. In a typical experiment manipulating autonomy, participants are either given a choice between a set of alternatives or assigned an alternative (Sheldon & Filak, 2008; Tamborini et al., 2010).

Those who were allowed to choose their own games showed higher ratings of autonomy fulfillment in post-test measures. Essentially, researchers are manipulating autonomy by giving individuals the freedom to choose or removing their freedom to choose. Here, reactance theory is a natural fit. Participants given the freedom to choose will feel their need for autonomy satisfied (Tamborini et al., 2010). As these participants had no freedoms removed, only gained, they should have little motivation for reactance.

However, participants who were given no freedom to choose by being assigned to a selection should have plenty of reason for reactance. Their freedom to choose has been removed, and reactance theory posits that they should be motivated to restore that freedom. In this example, both theories work together. As the need for autonomy is fulfilled individuals have little need for reactance; they are being granted the freedom to choose. As freedoms are removed, autonomy needs are not fulfilled, and individuals have reason to react against the loss, or threatened loss, of those freedoms.

The need for autonomy neatly demonstrates the relationship between need satisfaction and reactance motivations. Competence needs should also theoretically be linked to reactance motivations. Removal of perceptions of competence should spur reactance in a way similar to removing one’s ability to be autonomous. Individuals experience competence when they feel they have control over a given task and can see evidence that they are having an effect on that task (Deci & Ryan, 2000). In terms of individual freedoms, individuals might be said to feel competent when they believe they have the freedom to control their outcomes on a given task. Competence is often operationalized as the ability to complete the actions one wishes to do; in some studies participants are given a video game controller that either works all the time or the buttons only respond to participant inputs half of the time (Sheldon & Filak, 2008; Tamborini et al., 2010). Individuals who have a working controller can easily see that their attempts to control what happens on screen have an effect. In this condition, there is no present threat to freedom. In the non-working controller condition, there is a clear threat to freedom; one’s perceived freedom to control the game is removed by the faulty controller. In this situation, reactance should be high. Thus, reactance and need fulfillment should have an inverse relationship. Reactance may be reduced by providing individuals with the opportunity for need satisfaction, and reactance may be created by removing or restricting opportunities for need fulfillment. As such, the CRRM hypothesizes that need fulfillment will indirectly affect reactance through engagement.

Identity & Reactance

Narrative entertainment in part reduces reactance through one’s high identification with, and liking of, characters or events in the story (Moyer-Gusé, 2008;

Moyer-Gusé & Nabi, 2010). Individuals that strongly identify with characters or like watching them are less likely to argue against persuasive messages present, or are too busy being distracted by the characters and events to form strong reactance motivations.

In a similar way, the ability to customize might also influence reactance through perceptions of identity. In a narrative, we might see traits in other characters that we feel in ourselves. When customizing, seeing the choices and input we have made might facilitate feeling a strong connection with what we have made. Thus, identification with a character may be less relevant (or non-existent, for media with no characters) than perceiving a customized space as a reflection of one’s own identity and as being reaffirming of one’s core values. As a sense of identity within the customized content increases, engagement should increase, leading to a decrease in reactance.

Customization, Source Perceptions & Reactance

In addition to considering the means by which identity and need fulfillment indirectly affect reactance through engagement, it is worth considering how a user’s perceptions of a persuasive source might affect reactance. Customization will give users the ability to manipulate a message, source, or brand within the interactive medium. In all cases, considerations of the source should affect engagement.

There has been a long history establishing the importance of source perceptions in the persuasive process (Chaiken, 1980; Petty & Cacioppo, 1984; Sternthal, Dholakia, &

Leavitt, 1978; Wilson & Sherrell, 1993). Viewing a source as more credible can lead to

more positive perceptions of the source’s message (Chaiken, 1980). Research indicates that source perceptions also matter in digital online environments (e.g., Bente, Baptist, &

Leuschner, 2012; Qiu & Benbasat, 2010). The ability to customize should make users cognizant of a message source. If we ask users to customize a message without specifying a source, they might still consider who originally wrote the material. In addition, if we ask users to directly customize a source (e.g., choosing which outfit a company mascot should wear) then the imprint of identity and need fulfillment that comes as a result of the customization process should influence perceptions of the source.

Thus, source perceptions are added to the CRRM as a direct predictor of engagement. As positive perceptions of the source increase, engagement with the medium should also increase. Source perceptions are placed as a third predictor variable due the differences of types of customization tasks (i.e., some require customizing a source, others require customizing a message with no source indicated). Even without a source specifically mentioned, individuals may generate source perceptions cues as part of customizing the message. These perceptions would be independent from perceptions of interactivity or executive functioning, but should still influence engagement.

Additional Theoretical Perspectives on Customization and Persuasion

In examining the role of customization on the persuasive process, it is worthwhile to consider other important theoretical outlooks on persuasion. Cognitive dissonance suggests that when individuals are faced with performing behavior discrepant to their held beliefs, attitude change is most likely to occur (Festinger, 1962). This attitude change will happen when the individual does not have sufficient reason to otherwise

justify the behavior. For example, consider paying a person who professes to hate eating fruit $100 to eat an orange. This person would experience little dissonance in taking money and eating the fruit; the large reward justifies the behavior that is discrepant with the held belief. But if the person were faced with less of a justification (e.g., they were simply asked to eat the orange), dissonance would occur between the discordant behavior and belief. This dissonance is conceptualized to be an unpleasant experience that humans attempt to resolve quickly. It is in this state that attitude change may occur (e.g., the person eating an orange resolves the dissonance by thinking that fruit is not as bad as originally thought).

One of the important findings in the considerable research conducted on dissonance theory is the demonstration that effort is a major determinant of dissonance

(Brehm & Cohen, 1959, 1962; Cohen, 1960; Festinger & Aronson, 1960). The more effort one puts into a discrepant behavior, the harder it is to justify discordant attitudes.

Using the previous example, if the orange eater went to great lengths to drive across the state and seek out oranges, it would be very difficult to hold the attitude that the person does not like fruit. In the same way, customization might be a means of demonstrating effort. As one puts more effort into the customization of an object or persuasive message, the more difficult it may be to believe that the product is undesirable. Why else would one put in the time to customize, unless the product were somewhat desirable? In this way, the effort expended in the customization process may aid in changing attitudes toward the advocated object.

One of the means by which cognitive dissonance is induced is through the forced compliance paradigm (Wicklund & Brehm, 1968). In this method, individuals are induced to perform a behavior that is discrepant with currently held beliefs. Again, if individuals find sufficient justification for their actions then there will be no dissonance and no attitude change. But Zimbardo (1965) suggests that if the inducement is “just sufficient to force the performance of the act, but not strong enough to…justify the behavior completely” (p. 105) then individuals are faced with their conduct of a behavior that flies in the face of their existing attitudes. In other words, a mechanism that induces compliance but does it in a subtle way may be an avenue for creating attitude change.

Zimbardo (1965) argues that inducing individuals to role-play someone with counterattitudinal beliefs may be one such subtle way of creating dissonance and explain the attitude change found in studies that use role-play. Customization may also be a means of subtly creating dissonance. Participants may enter a lab and be asked to customize a persuasive source or product. Yet beyond that, the control over how to customize is in participants’ hands. Even with a required time limit (e.g., take 10 minutes to customize your avatar as you wish) participants will quickly find themselves in a situation where they are making decisions of their own free will (e.g., picking a red hat over a blue one) and it will be harder to justify their actions as due to an external force. If the object of customization is related to a persuasive goal, participants may experience dissonance in facing the expenditure of 10 minutes’ worth of effort on a product while holding the belief that they do not need the product or are not one to be persuaded easily.

Customization is interesting in that it also reflects another core paradigm of inducing dissonance, the free choice paradigm. In this method, the subject is presented with an array of options and is required to make a selection. Findings have shown that participants who select an object will then distort the attractiveness of the unchosen alternatives as less attractive and increase their preference for the chosen object.

Dissonance occurs in this paradigm when individuals are confronted with the alternative options. You would be a fool to make a selection when there is a better alternative available, so you increase favorable attitudes towards your selection and decrease liking for the alternatives. Customization offers free choices repeatedly. With every selection, users are making statements about their preferences. The finished customized object then stands as a representation of all choices, freely made, during the customization process.

In accordance with dissonance theory, this would then suggest that individuals should show strong preference to their creation and their reasons in doing so. Thus, customization provides an excellent means for creating attitude change via dissonance by providing a subtle way in which to induce engagement with a persuasive object and by allowing individuals to freely and repeatedly make selections that highlight their attitudes.

Self-perception theory (Bem, 1965, 1967) stems from cognitive dissonance and posits that behaviors can create attitudes. In this view, an individual is “regarded as an observer of his own behavior and its controlling variables; accordingly, his belief and attitude statements are viewed as ‘inferences’ from his observations” (p. 185). For example, you might look at your watch to see what time it is to decide if you are hungry.

Researchers have shown that asking individuals to make facial expressions (e.g., smiling or frowning) can trigger changes in emotion (e.g., participants reported feeling more angry when frowning; Ito, Chiao, Devine, Lorig, & Cacioppo, 2006; Laird, 1974). Self- perception offers another perspective to the forced compliance paradigm results shown in cognitive dissonance. Individuals forced to perform a counterattitudinal behavior will observe themselves performing the behavior, assess that there are no strong controlling forces causing the behavior, and derive that their behavior indicates their attitude should be positive. The smaller the reward, or justification present, the more likely the individual is to infer that the behavior reflects one’s true attitudes (Jones, Linder, Kiesler, Zanna, &

Brehm, 1968).

The act of customization provides another opportunity for users to complete a behavior and infer their attitudes as a result. Although participants may have been given sufficient justification for starting the customization process, as it continues users continue to observe their acts of making decisions and influencing the outcome of the customized object. From these actions, it is reasonable to assume that one must have strong positive attitudes regarding the customized object.

Completing the CRRM: Considering Reactance & Attitudes

In the following model, high engagement is predicted to decrease reactance through means of identity perceptions, need fulfillment perceptions, source perceptions, and executive functioning resources. Perceived interactivity is proposed to work indirectly through perceptions of need fulfillment and identity to increase engagement and decrease reactance. Finally, reactance is hypothesized as the sole predictor variable

of product attitudes, the measure for persuasive outcomes. As reactance increases, attitudes for the advocated product should decrease. These hypothesized relationships result in the final version of the customization reactance reduction model (Figure 8).

Figure 8. Finalized model of CRRM with proposed paths now including source perceptions, reactance, and product attitudes.

Chapter 5: Initial Test for the CRRM Using Source Customization

To begin to assess the viability of customization affecting psychological resistance two studies were conducted. These studies test pieces of the larger CRRM as a proof of concept, and build upon each other in testing these effects in multiple contexts and with a variety of measures. These two studies assess the effects of source customization in a persuasive message context.

Customizing the source of a persuasive message might reduce reactance to a persuasive message. Individuals often have connections with the source of a persuasive message. A door-to-door salesperson offers the opportunity to build a connection with another person, which may lead to liking the persuasive message better.

Recent scholarship has focused on the use of virtual humans as persuasive agents.

Consumers on e-commerce websites seek interpersonal connection, and the inclusion of recommendation agents, or virtual human salespersons, have been shown create perceptions of interpersonal interaction (Holzwarth, Janiszewski, & Neumann, 2006;

Puzakova, Rocereto, & Kwak, 2013). Consumers who interacted with a recommendation agent were more satisfied with the retailer and had more favorable attitudes and higher purchase intentions than those who did not have an agent (Aksoy, Bloom, Lurie, & Cooil,

2006).

In a virtual interaction, users should be more persuaded by an avatar or agent that delivers a persuasive message rather than just seeing the message (Aksoy et al., 2006;

Holzwarth, et al., 2006). Recommender agents that have been customized by designers, rather than users, have been shown to increase liking and persuasive outcomes (Ahn &

Bailenson, 2011; Qiu & Benbasat, 2010), but little is known about shifting this power to the user. Interactive media offer the opportunity for individuals to customize the source through virtual environments (Bailenson, Beall, Loomis, Blascovich, & Turk, 2004).

Giving users the ability to customize a source creates an opportunity to assess the psychological benefits of customization (i.e., more need fulfillment and a sense of identity) while allowing for experimental control by keeping the message constant.

In these studies, participants were directed to customize the source of a persuasive message. Study 1 tests whether customizing a persuasive source causes participants to like a product described in a persuasive message better. It hypothesizes that intrinsic motivation (comprised of need fulfillment, enjoyment, and perceptions of tension) mediates the relationship between customization and product liking. Study 2 tests whether customizing a persuasive source increases need fulfillment and enhances a sense of identity with, and attachment to, the persuasive source. It also measures how identity and agency decrease psychological reactance and in doing so increase positive perceptions of the product featured in the message. The results from both studies lead to the development of the CRRM, which is tested in Study 3. The third study, presented in

Chapter 6, will build on these findings of source customization by assessing the entire

CRRM in addition to focusing on customization of the message.

Study 1: The Effects of Customizing a Virtual Salesperson’s Appearance on

Product Liking1

Overview

A virtual environment is a digital space in which a user’s movements are tracked and his or her surroundings are rendered, or digitally composed and displayed to the senses, in accordance with those movements. For example, in a computer game, a user’s joystick motions can be tracked and his or her character will move forward, rendering a new environment. Or, Xbox Kinect players can physically swing their arms remote, and the screen will show a bowling ball rolling down the lane. The goal of a virtual environment is to replace the cues of the real world environment with digital ones. Thus, the affordances of VEs can be used to dramatically change the nature of communication beyond the boundaries of the physical world.

Common elements of virtual environments are avatars and agents. The term avatar refers to any representation of a user in a virtual environment. These representations can vary in their form and detail, or whether they are enacted in real time or not. Avatars are controlled by humans and should be distinguished from agents, which are digital representations controlled by computer algorithms (Fox et al., 2015).

Typically, avatars are used to represent people in Internet chat, video games, virtual reality, and other mediated contexts. In 3D environments, avatars provide an essential, functional representation with which the user can enact virtual behaviors such as

1 This study has been published: Hanus, M. D., & Fox, J. (2015). Persuasive avatars: The effects of s appearance on brand liking and purchase intentions. International ׳customizing a virtual salesperson Journal of Human-Computer Studies, 84, 33-40. 62

navigating virtual space or engaging virtual objects or other avatars. A recent meta- analysis revealed that when virtual interactants are believed to be avatars, they are more persuasive than those believed to be agents (Fox et al., 2015).

Because of their immersiveness and unique affordances, virtual environments are ideal for many types of persuasive messages (Aksoy et al., 2006). Studies conducted in advertising contexts have found that interacting with virtual objects and virtual salespeople has a strong positive effect on persuasive outcomes. Li, Daugherty, and

Biocca (2001, 2002) demonstrated that interacting with three-dimensional representations of products caused users to rate the experience as more natural and engaging, and users felt more present than those who saw and could not interact with two-dimensional representations. Interacting with three-dimensional objects also increases product attitude accessibility (Schlosser, 2003), and being able to interact with an object generates more mental imagery of product use, which increases purchase intentions (Lee, Li, & Edwards,

2012).

Virtual worlds typically come with the ability to create one’s avatar in order to interact with the environment or other people in the world. Options for customizing these avatars vary across the virtual worlds, and users are often faced with customization systems when entering a virtual world. Because of this familiarity and the rich ability to customize, virtual worlds are an excellent space in which to test the effects of having control over a digital salesperson. By allowing participants to customize the appearance of a human salesperson’s avatar we can examine the affordances unique to virtual worlds

and examine their effects on advertising reception and attitudes towards a persuasive salesperson making a pitch.

By giving users control over a virtual salesperson, users should experience more autonomy and have more motivation to continue with the task which should lead to a more enjoyable and engaging experience. This satisfaction of needs may make the persuasive message more appealing, despite what the user chooses to do with the speaker’s avatar. If control and motivation are the driving forces behind taking control over a persuasive speaker’s avatar then we would expect to see individuals who have more preference for the brand and report higher purchase intentions. It is possible that this occurs even for individuals who use customization as a means to not be persuaded, perhaps by making the salesperson’s avatar look silly or non-threatening. The act of making choices and exercising control over the persuasive source should increase motivation in any case (Deci & Ryan, 1987, 2000; Ryan & Deci 2000), making it possible that need fulfillment actually overrides, or reduces, one’s initial inclination to resist persuasion.

Individuals will be asked to create or view the creation of an avatar that represents a person they will later interact with. I hypothesize that the positive benefits of source customization (Sundar, 2008) will influence ratings of the product described in the sales pitch.

H1: Those who customize a salesperson’s avatar will like the brand more than those who do not.

H2: Those who customize a salesperson’s avatar will report higher purchase intentions than those who watch the creation of the salesperson’s avatar.

Due to the interactive nature of the customization process, individuals customizing a source’s avatar should show increased enjoyment and need fulfillment

(Sundar, 2008; Sundar et al., 2015). Intrinsic motivation is conceptualized as perceptions of enjoyment, autonomy, competence, and perceived tension (Ryan, Koestner, & Deci,

1991). Thus individuals who customize should experience increased intrinsic motivation towards speaking with the salesperson. It is possible that the positive feelings stemming from increasing intrinsic motivation then affect perceptions of the source and the product.

Thus customization should influence product attitudes indirectly through intrinsic motivation.

H3: Intrinsic motivation will mediate the relationship between customizing a salesperson’s avatar and brand liking.

H4: Intrinsic motivation will mediate the relationship between customizing a salesperson’s avatar and purchase intentions.

This study will also assess how customization of a source’s avatar affects those who are already in a state of high reactance, compared to those who are in a neutral state.

It may be the case that customization of a source improves product attitudes for those in a neutral state, but cannot overcome the negative effects of those currently in a high reactance state. To test this, half of the participants were told that they would creating an avatar that would later be represented by someone who would attempt to sell them a product. This means of early warning, called forewarning, has been demonstrated to be a

reliable way to create reactance (Petty & Cacioppo, 1977, 1979). When a forewarned individual is told a persuasive message is coming, that individual has time to ruminate on this potential loss of freedom, grow angry and generate counterarguments, or thoughts against the advocated position of the persuasive message. Then, when the individual hears the persuasive message, the counterarguments and affective reactance are already in place and are actively used to resist the message (Benoit, 1987; Petty & Cacioppo, 1977,

1979). It is possible that forewarned individuals use the time watching or customizing the avatar to generate counterarguments about the message that will come, which would reduce persuasive outcomes. I suggest forewarning negatively affects persuasive outcomes only for individuals who do not customize the salesperson’s avatar. Individuals who have the ability to customize will be too engaged and intrinsically motivated to effectively counterargue, thus negating forewarning’s effects.

H5: Forewarned individuals who do not customize the salesperson’s avatar will have lower brand attitudes than those who are not forewarned.

H6: There will be an interaction between forewarning and customization conditions such that forewarned individuals who do not customize the salesperson’s avatar will have the lowest purchase intentions compared to any other subgroup.

Study 1 Method

Sample

Participants (37 men and 57 women) were recruited from a large Midwestern university. Participants received course credit for their participation. Given that

individuals respond differently when they believe a virtual representation is controlled by a person versus a computer (Blascovich et al., 2003; Fox et al., 2015), participants (n =

14) that indicated they did not believe the salesperson was controlled by a real human were excluded from analysis.2 The final sample (N = 80) consisted of 28 men and 52 women, ranged in age from 18 to 51 (M = 20.57, SD = 4.47) and reported their race/ethnicity as: Caucasian/ European-American/White (n = 47); Black/African/African-

American (n = 17); Asian/Asian-American (n = 8); Latino/Latina/Hispanic (n = 1); multiracial (n = 4); and other (n = 2).

Procedure3

This study uses a 2 (create/view only) customization x 2 (warned, not warned) forewarning between-subjects design. Upon arrival at the laboratory, participants were randomly assigned to one of four conditions: Customization, No Forewarning (n = 22);

Customization, Forewarning (n = 18); No Customization, No Forewarning (n = 22); and

No Customization, Forewarning (n = 18). Participants in all conditions were told that they would be interacting through a virtual world equipped with voice chat with Alex, a representative from Ternio (a fictional company), in a test of the “effectiveness of using virtual worlds to communicate with companies.” Voice chat was selected to ensure that participants felt like they were talking with a real, responsive person and not a bot. These measures were necessary to bolster the feeling that participants were interacting with an avatar rather than an agent, because variations in these perceptions can cause undesired variance in measured outcomes (Fox et al., 2015).

2 Results did not vary whether or not these participants were included. 3 See Appendix A for a detailed protocol for Study 1. 67

In the Forewarning conditions, participants were told that Alex was going to try to persuade them to support the company’s bid for a contract with the university’s vending services. In the No Forewarning conditions, Alex’s persuasive intent was not revealed.

Thus, participants were made aware or not aware of Alex’s attempt to persuade before the avatar customization step. In the Customization conditions, participants were given seven minutes to use the virtual world’s interface to modify Alex’s avatar. They had complete control over how Alex would appear to them in the virtual world; participants could change Alex’s clothes, face, hair style, and hair color. All participants in the

Customization completed the task, and made a number of changes to the avatar. In the No

Customization conditions, participants observed the video from another person’s avatar customization process. All of the Customization videos were recorded. Each participant in the No Customization condition was randomly assigned a video from another same sex participant. Thus, participants in the No Customization condition had no control over how Alex would appear.

After this step, participants then entered the virtual world, which was set up as a casual room. To improve the cover story, the researcher made a call to Alex, made introductions, and then handed the headset to the participant. Then, the avatar they had customized (or watched being customized) that represented Alex walked into the room and sat down as Alex spoke with the participant. A second research assistant playing the role of Alex in a separate room then followed a script (Appendix B) featuring information about the product, a fictional energy drink. Some interactive questions were included in the script so that the dialogue seemed more natural and so that Alex’s humanity (i.e., that

Alex was a real person, not a computer or a recording) was reinforced. After the interaction with Alex, participants completed survey measures on a separate computer and were subsequently debriefed.

Measures4

Intrinsic Motivation

Participants completed the Intrinsic Motivation Inventory (Ryan, Koestner, &

Deci, 1991), which contains 22 items with statements such as, “I felt like it was my choice to do the task,” “I think I am pretty good at this task,” “I would describe the task as enjoyable,” and “I felt tense during the task” (Cronbach’s α = .82). Items were measured on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree).

Brand Liking and Purchase Intention

All items were measured on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Brand liking was measured with four items that included statements such as “I like Ternio energy drinks” and “I would want to hear more about

Ternio energy drinks” (Cronbach’s α = .82). Purchase intention was measured with three statements, such as “I would buy Ternio energy drinks” and “I was convinced by the speech to buy Ternio energy drinks” (Cronbach’s α = .82).

Perception of Agency

One item was included as a manipulation check where participants were asked to rate their perceptions of whether Alex was human on a 7-point Likert scale ranging from

1 (strongly disagree) to 7 (strongly agree). Because previous research has shown

4 See Appendix C for full measures. 69

dramatic differences in effects based on perceived agency (Fox et al., 2015), participants who did not agree that Alex was human were excluded from analysis.

1 2 3 4

1. Customization condition 2. Forewarning condition .07 3. Intrinsic motivation .30** -.07 4. Product liking -.20 .08 .53** Table 1. Correlation matrix for study 1 variables. Note. Individuals who customized the avatar were coded as 1, and individuals who watched the video were coded as in a point- biserial correlation. Individuals who were not forewarned were coded as 0, and individuals who were forewarned were coded as 1. ** denotes p < .001

Study 1 Results

Due to the imbalance in participant sex, a series of preliminary analyses were conducted to ensure that sex was not a confounding factor. There were no differences in assignment to the customization condition; males and females were equally likely to be assigned to the Customization and No Customization conditions, χ2(1, N = 80) = .88, p =

.348. There were no differences in assignment to the forewarning condition; males and females were equally likely to be assigned to forewarning and non-forewarning conditions, χ2(1, N = 80) = 1.28, p = .258. Independent samples t-tests found that there were no significant differences between participant sex on brand liking, t(78) = 1.02, p =

.313, purchase intention, t(78) = 1.78, p = .078, or intrinsic motivation, t(78) = .10, p =

.924. 70

H1 predicted that those who customize an avatar will have higher brand liking than those who do not. To address H1, a 2x2 MANOVA was run. There was a significant main effect for avatar customization on brand liking, F(1, 76) = 6.42, p = .01, partial η2 =

.08, supporting H1. Those who customized the source (M = 5.32, SD = .69) expressed greater brand liking than those who did not (M = 4,74, SD = 1.26). H2 predicted that those who customize an avatar will have higher purchase intention than those who do not.

Tests on H2 show that the effect of avatar customization on purchase intentions only bordered on significance, F(1, 76) = 3.28, p = .07, partial η2 = .04. Those who customized the source (M = 5.54, SD = .77) demonstrated greater purchase intentions than those who did not (M = 5.12, SD = 1.21), although this difference was not significant. We predicted interactions between forewarning and avatar customization such that those who were forewarned but did not customize would have the lowest brand liking (H5) and purchase intention (H6). There were no main effects for forewarning on brand liking, F(1, 76) =

.51, p = .47, partial η2 = .01, or purchase intentions, F(1, 76) = .57, p = .43, partial η2 =

.01. There was also no interaction effect for brand liking, F(1, 76) = .65, p = .42, partial

η2 = .01, or purchase intentions, F(1, 76) = .78, p = .38, partial η2 = .01, offering no support for H5 or H6.

To address H3, a mediation analysis was run using PROCESS (Hayes, 2013).

Avatar customization was entered as the independent variable, intrinsic motivation as the mediating variable, and brand liking as the dependent variable by generating 10,000 bootstrap confidence intervals in PROCESS model 4 (Figure 1). The amount of energy drinks a participant had during the week was not a significant covariate and was dropped

from the model. Direct and indirect effects can be viewed in Table 1. Results show that avatar customization directly affects intrinsic motivation, where those in the customization condition have higher intrinsic motivation scores, a = .41; 95% CI [.09,

.73], and that higher intrinsic motivation scores lead to higher brand liking regardless of condition, b = .76; 95% CI [.53, 1.06]. There is a direct effect of avatar customization on brand liking when holding intrinsic motivation constant, c = .58; 95% CI [.13, 1.03]. The data indicate that avatar customization affects brand liking indirectly through intrinsic motivation, ab = .32; 95% CI [.07, .63]. Relative to those in the non-customization condition, those that customized were more intrinsically motivated, which was associated with higher brand liking, supporting H3 (Figure 9).

Figure 9. Path coefficients for simple mediation analysis of avatar customization on brand liking through intrinsic motivation.

To address H4, a second mediation analysis was run using PROCESS. Avatar customization was entered as the independent variable, intrinsic motivation as the mediating variable, and purchase intentions as the dependent variable in PROCESS model 4 (Figure 2). Number of energy drinks participants consumed per week was not a significant covariate in the model and was removed from analysis. Direct and indirect effects can be viewed in Table 2. Results show that avatar customization directly affects intrinsic motivation, where those in the customization condition have higher intrinsic motivation scores, a = .41; 95% CI [.09, .73], and that higher intrinsic motivation scores lead to greater purchase intention, regardless of condition, b = .59; 95% CI [.22, .96].

There is no direct effect of avatar customization on purchase intention when holding intrinsic motivation constant, c = .33, 95% CI [-.23, .88]. Avatar customization affected 73

purchase intention indirectly through intrinsic motivation scores, ab = .24; 95% CI [.05,

60]. Relative to those in the non-customization condition, those that customized were more intrinsically motivated, which was associated with greater purchase intention, supporting H4 (Figure 10).

Figure 10. Path coefficients for simple mediation analysis of avatar customization on purchase intention through intrinsic motivation.

Study 1 Discussion

The results confirm the primary hypotheses: individuals who customized a salesperson’s avatar had higher brand liking scores and purchase intentions than those who watched the customization of the salesperson’s avatar. The results suggest that customizing an avatar leads to increases in intrinsic motivation, and these feelings of autonomy, competence, and enjoyment then lead to increases in brand liking and purchase intention. These feelings carried over from the customization phase to listening to the sales pitch even though the avatar was removed from the participants’ control and given to the speaker. These results persisted across participants who varied in their level 74

of drinking energy drinks during the week. Contrary to expectations, the results also show that the manipulation of forewarning had no effect on persuasive outcomes.

It should be noted that the positive effects on brand liking and purchase intention emerged through voice-to-voice communication between the salesperson and participant.

To ensure that effects were attributable to the manipulation, participants in this study saw no brand logos or prototypes of the product itself; it was only described by the salesperson’s pitch. Incorporating visuals may make the product more memorable and future work might benefit from incorporating brand logos and looking at recall effects days or weeks after the initial introduction to the product.

This study was conducted as a proof of concept to demonstrate that customization, in this case of a persuasive source’s digital avatar, can play an important role in shaping attitudes toward a persuasive message. It is noteworthy that the benefits of source customization extended into attitudes about the product. Presumably, direct customization of the product message may have even stronger effects.

These findings also give support for the CRRM’s assertion of the mediating role of need fulfillment in the customization process. The intrinsic motivation scale used assesses both autonomy and competence, two core psychological needs, in addition to enjoyment and perceived tension. The results demonstrating that intrinsic motivation mediates the effects of customization on product liking indicate that need fulfilment occurs on some level as a result of the customization process. With these findings in mind, Study 2 was created to address some of the methodological limitations, replicate

the findings of Study 1 in a new context, and to add in new mediating variables in order to test more elements of the CRRM.

Chapter 6: Exploring the Roles of Similarity, Agency, and Reactance in Mediating the Effect of Source Customization on Product Liking

Study 1 proved an important proving ground for the role of customization in the persuasive process. It demonstrated that customization did matter, and that the positive benefits of customizing the source of a persuasive speech could spread onto attitudes toward the product in the source’s speech. It also established intrinsic motivation as an important mediating variable, demonstrating that the act of customization triggers positive attitudes and that those attitudes can then affect perceptions of the product. Study

1 was not without its limitations and Study 2 was established to address these limitations, expand on the findings, and test the results in a new context.

Methodological Limitations and Expansion of Study 1

Study 1 mismatched a male confederate voice with a female avatar on screen for female participants. Participants were initially asked to create an avatar that shared their sex. Alex was chosen as a gender-neutral name, but the confederate researcher who played the role of Alex was a male for all participants. The voice remaining male was done to maximize experimental control by keeping the confederate voice the same for all participants, though it is possible that females hearing a male voice may react to the message differently than males hearing a male voice. However, there were no sex differences in brand liking, purchase intention, or belief that Alex was a real

representative of the company. Study 2 will remove the possibility of a sex mismatch from occurring by removing conversation between participant and persuasive source.

Instead, participants will read text written to them by a persuasive source, and a two- dimensional avatar will be displayed next to the text, matching the participant’s sex.

Results from Study 1 indicated that the forewarning manipulation was not sufficient to affect the results. Previous research has demonstrated that forewarning effectively increases resistance to persuasion (Petty & Cacioppo, 1977, 1979), yet we found no differences between forewarning or not forewarning participants. Forewarning participants, particularly in the no customization condition, should give them ample time to generate counterarguments and resistance to the persuasive message, but no such effects were found. The lack of effects was surprising, in light of the strong support for reactance theory (Brehm, 1966; Brehm & Brehm, 1981; Wicklund, 1974), which states that individuals are strongly motivated to restore a freedom once it is perceived to be threatened. An attempt to persuade an individual should be perceived as a threat to one’s freedom to choose, and thus the individual would be motivated to restore that freedom.

Unfortunately, reactance (and counterarguing) was not directly measured. It is possible that the customization process in itself was a way to negate the effect of forewarning.

Because forewarning is a cognitive process shown to generate countearguments, it may be the case that the activity of customization (e.g., learning the software, making choices about the avatar’s appearance) was mentally engaging to the point that counterarguments were not made. It is also possible that the positive and beneficial aspects of customization

(e.g., need fulfillment) may have increased positive affect towards the source’s messages,

and that affect ultimately overroad any negative countearguments generated by forewarning. Finally, it is also possible that the forewarning manipulation in Study 1 was too weak. Participants were forewarned with only a single sentence during the instruction phase, and then spent a long time customizing the avatar so they may have forgotten the forewarning instructions by the time they encountered the persuasive message. Because reactance was not directly measured, it is impossible to tell whether forewarning had no effect because of customizations increase in intrinsic motivation or because the forewarning manipulation lacked strength. To address this, two changes were made.

Reactance will be directly measured, both in the form of self-reported affective responses and as counterarguments listed. Second, a more robust manipulation of reactance will be used wherein the persuasive message will be peppered with comments designed and pretested explicitly to elicit strong reactance.

In Study 1, participants either customized the avatar for a persuasive source or watched the video of this avatar creation. These participants saw the same stimuli but varied in their level of control over the avatar. It is possible that the difference in conditions is attributable to viewers being bored and liking the product less rather than customizers being motivated and liking the product more. Study 2 will use three conditions in which participants either fully customize an avatar (multiple choices) select an avatar out of four potential ones (single choice) or are assigned a random avatar (zero choice). In this way Study 2 will be able to better pinpoint the role of choices in the customization process and provide a better means of comparison between conditions.

Finally, participants all heard the persuasive speech about a single product (a fictional energy drink) in Study 1. It is possible that some of the findings were due to the nature of the message rather than customization. To reduce the effects of the message,

Study 2 pre-tested six different products and selected three of them to be randomly assigned to participants.

Contributions to CRRM Testing

The CRRM asserts that the benefits of customization indirectly affect product attitudes by means of reducing resistance to the persuasive message. Study 1 attempted to manipulate participants’ levels of resistance by forewarning that a persuasive message would later be shown to them. This manipulation was ineffective and ultimately relied on an indirect way to assess the presence of reactance. Study 2 expands on the CRRM by directly assessing participants’ levels of reactance in two ways: assessing their current state reactance through means of a self-report scale and measuring for counterarguments generated against a product. Reactance has been established to be composed of both affective (e.g., anger) and cognitive (e.g., counterarguing) components (Dillard & Shen,

2005; Quick & Stephenson, 2007; Rains, 2013; Rains & Turner, 2007). The state reactance scale assesses both affective components and cognitive components for reactance. Study 2 will assess participants on both accounts and then assess the role of reactance in the customization process. It will essentially plug in an important variable in the CRRM with reactance as a mediating variable between need fulfillment and product attitudes.

Study 2 also will add an assessment of identity perceptions to test additional claims made in the CRRM. Study 1 indicated that customization of a source’s avatar in part increased need fulfillment, which in turn increased product liking. But it is also possible that participants felt a strong connection with the avatar that they created, and thus the source that was speaking and in turn the product he was selling. As participants are customizing the source’s avatar, they are continually viewing reflections of their choices embodied on the avatar. Every hair color, shirt pattern, and jean choice reflect a decision that the participant has made. In this way, viewing the customized avatar should in part remind participants of themselves. It is possible that they receive an impression of their identity by seeing a stronger similarity between themselves and the avatar. Research

(Simons, Berkowitz, & Moyer, 1970; Woodside & Davenport, 1974) has demonstrated that feeling similar to a source can increase perceptions of source credibility (and thus attitudes towards the source’s message). Other work demonstrated that participants who believed they were highly similar to a communicator agreed strongly with the communicator’s message and demonstrated less resistance to the persuasive attempt

(Silvia, 2005).

Need fulfillment was partially accounted for in the intrinsic motivation measure in

Study 1, which was composed of subscales concerning autonomy, competence, enjoyment, and perceived tension (Ryan et al., 1999). To assess need fulfillment more directly, Study 2 will ask questions concerning participants’ perceptions of their agency.

Agency is a variable commonly used in studies assessing customization and interactive media, and is conceptualized as the perception that one has the ability to create or

influence content (i.e., the “self as source” of content, Sundar, 2008; Sundar et al., 2015).

Asking questions concerning participants’ perceptions of their ability to shape content allows for the use of a measure conceptually distinct from similarity and also understand the role of need fulfillment better, as agency is conceptually very similar to that of autonomy.

In addition, Study 2 will attempt to replicate the findings from Study 1 in a more limited environment. In Study 1, participants interacted with an avatar in a three- dimensional virtual world. The avatar walked, talked, and sat down. Participants then spoke with a confederate through the computer. The confederate not only delivered a sales pitch but asked participants a few questions (e.g., “do you think that’s a good idea?”) to really give participants the impression of interacting with a real human being.

Study 2 will assess if the benefits of customization can extend into a significantly sparser setting. Participants will create a two-dimensional avatar that consists only of a head, shoulders, and background. These avatars will be placed next to the text of a persuasive speech (e.g., “Hi! Today I would like to talk to you about…”). Demonstrating that customization continues to affect product attitudes in this environment will give strong evidence for the strength of customization in changing attitudes. In addition, a two- dimensional avatar placed next to text strongly increases the ability for this research to be applied in real persuasion contexts.

Overview

Study 2 used a 3 (zero, single, multiple) choice x 2 (high/low) reactance between- subjects design. Participants were measured on counterarguments generated, their state

reactance, their similarity to the avatar, their perceptions of agency, and their perceptions of a fictional product. The CRRM posits that both perceptions of identity and need fulfillment can affect user attitudes. Here, autonomy is conceptualized as the perception of having agency and user identity is conceptualized as similarity to the customized avatar. The CRRM indicates that as these perceptions increase, reactance should decrease and favorable attitudes toward the product should increase.

H1: As avatar choice options increase, perceptions of similarity (H1a) and agency

(H1b) will increase.

Reactance is conceptualized as a motivation to restore a threatened or lost freedom (Brehm, 1966; Brehm & Brehm, 1981). Interactive media, and the customization process specifically, concern giving individuals the freedom to choose, create, and experience content as they wish. Thus, the freedoms given by the customization process should decrease reactance.

H2: As avatar choice options increase, state reactance (H2a) and counterarguments (H2b) will decrease.

Agency is conceptualized as a sense of control in which users can create their own content (Sundar, 2008; Sundar et al., 2015). In order to create their own content, users must be given agency, or the freedom to make their own choices. The more agency a participant has, the less one should believe freedoms are being taken away. In addition, perceived similarity to a persuasive source has been demonstrated to increase perceptions of source credibility and positively influence attitudes toward the source’s message

(Silvia, 2005; Simons et al., 1970; Woodside & Davenport, 1974).

Reactance is conceptualized as a combination of affect and cognition (Dillard &

Shen, 2005; Quick & Stephenson, 2007; Rains, 2013; Rains & Turner, 2007). Research on reactance suggests that the affective and cognitive components are “intertwined” and should be assessed together (Quick & Stephenson, 2007; Rains, 2013; Rains & Turner,

2007). The state reactance scale (Gardner, 2010; Quick, Scott, & Ledbetter, 2011) measures self-reported scores for both emotion (e.g., anger) and cognition (i.e., counterarguing). Because the state reactance scale will measure both affective and cognitive components together, this is the best representative of the intertwined model and will be used as the primary measure of reactance. It is possible that similarity and agency perceptions will affect the affective or cognitive components of reactance in different ways. For example, a strong sense of similarity may make one less likely to cognitively elaborate and argue with a message, but not reduce initial angry affect at a perceived threat to freedom. Because similarity or agency might influence affect or cognition differently, an additional measure was assessed to measure only the cognitive aspects of reactance (i.e., counterarguing). In addition to completing the state reactance scale, participants will also be asked to list counterarguments they had when thinking about the product. Use of counterarguing as an additional measure allows to see whether similarity or agency affect cognition alone differently, and it also gives another direct measure of reactance that does not rely on self-reported data (Miller & Baron, 1973).

Thus, it was important to create two models: one that tests the typical conceptualization of reactance as a mix of affect and cognition using state reactance scores (i.e., the intertwined model), and a second one that tests the effects of similarity and agency on a

strictly cognitive measure, counterarguing. See Figure 11 for an illustration of both hypotheses.

H3: Similarity (H3a) and agency (H3b) will mediate the relationship between number of choice options and state reactance.

H4: Similarity (H4a) and agency (H4b) will mediate the relationship between number of choice options and counterargument generation.

Figure 11. Hypothesized relationship of similarity, agency as mediators between number of choice options and state reactance or counterarguing.

Finally, as reactance increases, preference for the persuasive message should decrease (Brehm & Brehm, 1981; Bushman & Stack, 1996; Petty & Cacioppo, 1977). To test the larger serial mediation, four models will be created in order to independently test

the effects of similarity on state reactance, similarity on counterarguments, agency on state reactance, and agency on counterarguments (Figure 12).

H5: There will be serial mediation wherein choice options indirectly affect product attitudes via similarity and state reactance (H5a) or counterarguments (H5b).

H6: There will be serial mediation wherein choice options indirectly affect product attitudes via agency and state reactance (H6a) or counterarguments (H6b).

Figure 12. Hypothesized serial mediations for similarity and agency on state reactance and counterarguing.

Study 2 Method

Sample

Participants (N = 133; 77 men and 56 women) were recruited from a large

Midwestern university and received course credit for their participation. The sample ranged in age from 18 to 66 (M = 21.11, SD = 4.62) and reported their race/ethnicity as

Caucasian/ European-American/White (n = 95); Black/African/African-American (n =

20); Asian/Asian-American (n = 14); Latino/Latina/Hispanic (n = 3); and Pacific Islander

(n = 1).

Procedure5

Participants were randomly assigned to choice and reactance conditions. All participants were told that they would view text written by another person with a picture of that person’s avatar placed next to the text. Participants in the zero choice condition (n

= 45) were shown a pre-selected avatar. Participants in the single choice condition (n =

40) were shown a selection of four randomly chosen avatars and were told to “select the one you think would be best to represent the person who wrote the text that you are going to read.” In the multiple choice condition, participants (n = 48) created an avatar to represent the writer. Participants then completed a brief filler essay task in which they were asked to describe their previous day so that the researcher had time to place the assigned, selected, or created avatar on the screen with the advertisement text.

Participants were also randomly assigned into reactance conditions. In the low reactance condition, participants were given no additional instructions beyond those provided in the choice condition. In the high reactance condition, participants completed the filler task and were told that the text they would be reading was taken from a

5 See Appendix D for detailed Study 2 protocol. 87

marketing company and was designed to get “students like you” to purchase a product. In addition to these instructions, the text was manipulated to increase reactance while reading. For example, a sentence that read “I think you might like this product” was changed to “I know you will like this product.” This is consistent with other studies that have manipulated reactance (Clee & Wicklund, 1980; Wicklund & Brehm, 1968).

These statements were pretested, wherein participants also asked to rank eight statements designed to produce reactance (e.g., “You’re young, so I’ll explain this slowly”). We selected the four statements participants ranked as the most annoying to include in the high reactance condition (Table 2).

Statement M (SD)

You’re young, so I’ll explain this slowly. 4.56 (2.30)

You have to listen to me, because I’m the most qualified to talk about this. 4.33 (1.22)

There’s no arguing with this! 2.89 (1.76)

There’s really no other choice; you cannot argue with perfection. 2.78 (1.72)

I can guarantee that after you hear this speech, you will buy this product. 2.56 (2.55)

Everyone who listens to my speech ends up agreeing with me. 1.67 (1.94)

Today, you are going to listen to someone try to convince you to buy a 1.11(1.36) product.

Today, you are going to listen to a salesperson give you their product pitch. .11 (2.03)

Table 2. Study 2 pre-tested Statements for reactance language. Note. Participants ranked the statements from most to least annoying. The top four scoring statements were used in the advertisement stimuli (Appendix F).

All participants were given five minutes to read the text. After reading, participants were asked to list any thoughts they had about the product mentioned in the advertisement. This thought-listing task is a commonly used method to measure counterarguments (Cacioppo & Petty, 1981; Miller & Baron, 1973). After the thought- listing task, participants completed a questionnaire that assessed product liking, purchase intentions, state reactance, perceptions of agency, and perceptions of similarity.

Materials

Avatar Creation

Study 1 found that customizing an avatar increase brand liking and purchase intention when they used a three-dimensional avatar in a virtual world. To test the extent of these findings, we used a two-dimensional avatar. This avatar consisted of a portrait- style picture with the body cut off below the neck. All avatars were created by participants using the online tool Portrait Illustration Maker. This system allows users to change the avatar’s hair style and color, facial features, clothing, background, and add props (such as sunglasses) to the avatar’s face (Figure 13).

Figure 13. Portrait Illustration Maker avatar customization interface.

An initial pool of five avatars was created during pretesting. Five volunteers who did not participate in the final study were asked into the lab, given instructions on how to create an avatar, and told to create any avatar that they wished. Two male and three female avatars were created by these volunteers. Each new avatar that was created by participants in the multiple choice condition was added to the pool. When a participant 90

was assigned to the zero choice or single choice conditions, one avatar (zero choice) or four avatars (single choice) were randomly selected from the pool.6 Participants in the single choice condition were shown the avatars in a 2x2 grid and were asked to tell the researcher their selection after deliberating for two minutes.

Advertisement Text

To reduce the chance of message effects, in this study we created six products designed to appeal to college students. We pretested these products for their appeal to college students, whether it was a good idea for a product, and whether participants were interested in buying the product. We eliminated products that indicated a negative score

(i.e., mean scores less than the midpoint of 4) then selected three products that had the highest combined scores in their appeal to college students and purchase intention (Table

3; Appendices F and G).

6 The single choice condition was not conducted until at least four avatars of each sex were created. 91

Product 1 Product 2 Product 3 Product 4 Product 5 Product 6

M(SD) M(SD) M(SD) M(SD) M(SD) M(SD)

Purchase 4.11 3.33 4.44 3.78 2.67 4.78

Intention (2.26) (2.45) (1.51) (1.99) (2.29) (1.64)

Appeal to 6.00 5.11 4.78 6.00 3.67 5.56

College (1.25) (2.61) (1.64) (1.32) (1.22) (1.24)

Students

Table 3. Mean scores for Study 2 pre-tested products. Note. Products 1, 3, and 6 were selected.

Measures7

Counterarguments

Counterarguments were measured using the thought-listing procedure (Cacioppo

& Petty, 1981; Miller & Baron, 1973). After reading the persuasive text, participants were instructed to list any thoughts they had about the product. At the end of the experiment, before leaving, participants were instructed to label each thought they had listed, indicating whether each thought was positive, negative, neutral, or unrelated to the product. These were then scored as 1 (positive), 0 (neutral) or -1 (negative) and summed together creating a valenced score. Research measuring counterarguments typically uses total number of negative thoughts as the dependent measure from this task (Rains, 2013;

Rains & Turner, 2007). Although this is a direct way of measuring counterarguments, use

7 See Appendix E for full Study 2 measures. 92

of only negative thoughts listed removes the context of the remaining thoughts from participant scores. By using the valenced score in place of the total number of negative thoughts, the measure more accurately estimates a participant’s full thought process towards the product. If a participant were to list 10 thoughts, with three negative thoughts and seven positive, that participant would be scored as having more reactance than an individual who wrote three thoughts with two negative and one positive, or equal with one who wrote only three negative thoughts.

Product Liking and Purchase Intention

All items were measured on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Product liking was measured with four items that included statements such as “I like the product I read about” and “I would want to hear more about the product” (Cronbach’s α = .94). Purchase intention was measured with three statements, such as “I would buy the product I read about” and “I was convinced by the advertisement to buy the product” (Cronbach’s α = .91).

State Reactance

Participants were given the 14-item State Reactance Scale (Gardner, 2010; Quick,

Scott, & Ledbetter, 2011). All items were measured on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The scale is comprised of four subscales: perceived threat to choice (e.g., “the advertisement tried to manipulate me,”

Cronbach’s α = .77); counterarguing (e.g., “I criticized the advertisement while I was reading it,” Cronbach’s α = .79); cognitive appraisal (e.g., “the advertisement was

pleasant,” Cronbach’s α = .85); and anger (e.g., “the advertisement made me feel

irritated,” Cronbach’s α = .93).

Similarity

The extent to which the avatar was seen as similar to the participant was measured with a 4-item scale. All items were constructed and measured on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) and consisted of statements such as “I think the avatar is similar to me” and “The avatar reflects who I am” (Cronbach’s α =

.88). These items reflect similar scales used to assess this concept (e.g., Nowak & Rauh,

2005; Van Looy, Courtois, De Vocht, & De Marez, 2012).

Agency

Participants were given a 6-item scale designed to assess their perceptions of

agency. These items were created based off previous research on agency and

customization (Marathe & Sundar, 2011). All items were measured on a 7-point Likert

scale ranging from 1 (strongly disagree) to 7 (strongly agree) and consisted of questions

such as “I felt like I was able to influence how the avatar looked” and “If I could, I would

have done more to customize the avatar that I saw” (Cronbach’s α = .75).

1 2 3 4 5 6 7

1. Choice options 2. Low/High reactance .01 3. Similarity .34** -.10 4. Agency .72** .01 .33** 5. Valenced thought-listing .03 -.38** .18* .16 6. State reactance -.09 .62** -.16 -.07 -.56** 7. Product liking -.12 -.25** .15 .05 .58** -.26** Table 4. Correlation matrix for Study 2 variables. Note. Choice options were coded as zero choice (0), single choice (1) and multiple choices (2). Reactance was coded as low reactance (0), high reactance (1) in a point-biserial correlation. * denotes p < .05, ** denotes p < .001

Study 2 Results

Preliminary Analyses

Three products were determined through pretesting be equal on appeal to college students. Despite choosing three ads that scored similarly during pretesting, the type of product that participants viewed did have an effect on how much participants liked the product, how much they wanted to purchase the product, and the valenced score (Table 5).

Product 1 Product 2 Product 3 F(2, 133) p partial M (SD) M (SD) M (SD) η2 Product liking 14.73 < .001 .19 3.71 3.87 5.20 a b (1.49)a (1.54) (1.53) Purchase intention 5.05 .008 .07 2.96 3.08 3.99 a b (1.64)a (1.66) (1.62) Valenced thought- 3.84 .024 .06 -1.17 .01 .60 listing (2.91)a (3.45)ab (2.76)b Table 5. ANOVA results for product stimuli on outcome measures.

To assess whether the product viewed interacted with the choice condition, a 3x3

MANOVA between product type and choice condition was conducted on all dependent variables of interest. Product viewed did not interact with number of choice options on similarity, agency, product liking, purchase intention, state reactance, or valenced thought- listing (Table 6).

F(2, 133) p partial η2 Similarity .62 .650 .02 Agency 1.45 .223 .05 Product liking .33 .855 .01 Purchase intention .06 .994 .002 State reactance .75 .559 .02 Valenced thought- .31 .869 .01 listing Table 6. MANOVA Results for product stimuli by choice condition.

Primary Analyses

H1 predicted that perceptions of similarity to the avatar (H1a) and agency (H1b) would increase as amount of avatar choice options increased. To address H1, an ANOVA was run. There was a significant main effect for choice option on similarity. Mean scores in similarity and agency increased as choice options increased from zero to single to multiple (Table 7). Thus, H1 is supported. There were no significant effects for high or low reactance condition on similarity, F(2,133) = 1.49, p = .224, partial η2 = .01, or agency, F(2,133) = .01, p = .969, partial η2 < .001, and the reactance condition did not significantly interact with customization condition on similarity F(2,133) = .19, p = .827, partial η2 = .003, or agency scores F(2,133) = .11, p = .899, partial η2 = .002.

Zero Single Multiple Choice Choice Choices F(2, 133) p partial η2 M (SD) M (SD) M (SD) Agency 73.05 < .001 .54 2.73 3.53 5.09 a (.81) (.89)b (1.07)c Similarity 8.90 < .001 .12 1.64 2.20 2.54 (.74)a (1.08)b (1.22)b Table 7. ANOVA results for choice condition on similarity and agency.

H2 predicted that as amount of choice options increased, participants’ state

reactance would decrease (H2a) and amount of counterarguing would decrease (H2b).

Counterarguing was measured by summing the total number of positive, negative, and

neutral thoughts listed. The valenced total number takes into account all of a participant’s

thoughts on the product, thus this was the key variable of interest. However, total number

of negative thoughts also strictly measures the number of counterarguments generated

and is the measure typically assessed in the literature (Rains, 2013, Rains & Turner,

2010), so analyses were run on both. Total number of negative thoughts and valenced

scores were assessed via ANOVA. Amount of choice options did not affect state

reactance scores, F(2,133) = .773, p = .464, partial η2 = .05, total negative thoughts listed,

F(2,133) = .30, p = .739, partial η2 = .005, or valenced scores, F(2,133) = .10, p = .908,

partial η2 = .002, H2 was not supported. The reactance condition had significant effects

on state reactance scores such that those in the high reactance condition scored higher (M

= 4.78, SD = .10) than those in the low reactance condition (M = 3.00, SD = .76),

F(2,133) = 81.18, p < .001, partial η2 = .55. Those in the high reactance condition also wrote significantly more negative thoughts, F(1,133) = 10.92, p = .001, partial η2 = .08, and had lower valenced totals F(1,133) = 21.41, p < .001, partial η2 = .15, than those in the low reactance condition. These findings indicate that the reactance manipulation worked as intended.

H3 predicted that choice options would decrease state reactance indirectly, by increasing perceptions of similarity (H3a) and agency (H3b). To address H3, a parallel mediation analysis was run using PROCESS Model 4 (Hayes, 2013). Number of choice options was entered as the independent variable, similarity and agency as mediating variables, and state reactance as the dependent variable by generating 10,000 bootstrap confidence intervals in PROCESS model 4 (Figure 1). Because number of choice options is a categorical variable, this variable was dummy coded, which allows for a multicategorical variable to assessed as a dichotomous variable wherein groups are compared to each other. Results indicate that relative to the zero choice condition, those who were given a single choice had higher ratings of similarity (β = .89, SE = .22, p <

.001) and agency (β = 2.36, SE = .19, p < .001). Relative to the zero choice condition, those who were given multiple choices also showed higher ratings of similarity (β = .56,

SE = .22, p = .014) and agency (β = .80, SE = .20, p < .001). Relative to the single choice condition, those who were given multiple choices did not have significantly higher scores of similarity (β = .33, SE = .22, p = .132), but did have higher scores of agency (β = 1.56,

SE = .20, p < .001). Results indicate no indirect effect. Relative to the zero choice condition, the single choice condition does not indirectly result in more state reactance

through similarity, ac = -.13; 95% CI [-.37, .04], or agency bd = .02; 95% CI [-.53, .53].

Relative to the zero choice condition, the multiple choice condition does not indirectly result in more state reactance through similarity ac = -.08; 95% CI [-.26, .02], or agency bd = .01; 95% CI [-.18, .18]. Relative to the single choice condition, the multiple choice condition does not indirectly result in more state reactance through similarity , ac = -.05;

95% CI [-.24, .02], or agency bd = .01; 95% CI [-.36, .36]. Thus, H3 is not supported.8

To test H4, the same model was created using valenced thought-listing scores as the dependent variable. Results indicate that relative to the zero choice condition, the single choice condition indirectly affected thought valence through both similarity and agency, ac + bd = .78; 95% CI [.25, 1.57]. Relative to the zero choice condition, the multiple choice condition indirectly affected thought valence through both similarity and agency, ac + bd = 1.94; 95% CI [.59, 3.46]. Relative to the single choice condition, the multiple choice condition indirectly affected valenced thoughts through both similarity and agency, ac + bd = 1.16; 95% CI [.28, 2.25]. Thus, H4 is supported. Number of choice options affects counterarguing indirectly through both similarity and agency perceptions.

H5 predicted a serial mediation in that choice options indirectly affect brand liking through similarity and state reactance (H5a) or counterarguing (H5b). As the number of choices increases, perceptions of similarity with the avatar will increase, which in turn will decrease resistance to the persuasive message. It is the lack of resistance which ultimately will increase product liking. To address this hypothesis, a

8 All mediation tests here and following were also conducted controlling for participants’ assignment to reactance condition. All of the results remained the same. 100

serial mediation was run using PROCESS model six (Hayes, 2013). Choice number was entered as the independent variable, similarity as the first mediator, state reactance as the second mediator, and product liking as the dependent variable. Results indicate that relative to the zero choice condition, the single choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through similarity and state reactance, abc = .04; 95% CI [-.01, .15]. Relative to the zero choice condition, the multiple choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through similarity and state reactance, abc = .07;

95% CI [-.02, .21]. Relative to the single choice condition, the multiple choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through similarity and state reactance, abc = .03; 95% CI [-.01, .13]. Thus, H5a is not supported. To assess H5b, the serial mediation was run again using valenced thought-listing total as second mediator in place of state reactance. Results indicate that relative to the zero choice condition, the single choice condition showed an indirect serial mediation of choice options influencing product liking indirectly through similarity and valenced thoughts, abc = .09; 95% CI [.01, .24]. Relative to the zero choice condition, the multiple choice condition showed an indirect serial mediation of choice options influencing product liking indirectly through similarity and valenced thoughts, abc = .14;

95% CI [.02, .32]. Relative to the single choice condition, the multiple choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through similarity and valenced thoughts, abc = .05; 95% CI [-.001, .21].

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H6 predicted a serial mediation wherein choice options indirectly affect product liking through agency to state reactance (H6a) or counterarguing (H6b). Results indicate that relative to the zero choice condition, the single choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through agency and state reactance, abc = .001; 95% CI [-.09, .12]. Relative to the zero choice condition, the multiple choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through agency and state reactance, abc = .02; 95%

CI [-.26, .34]. Relative to the single choice condition, the multiple choice condition showed no indirect serial mediation of choice options influencing product liking indirectly through agency and state reactance, abc = .01; 95% CI [-.17, .23]. Thus, H6a is not supported. To assess H6b, the serial mediation was run again using valenced thought- listing total as second mediator in place of state reactance. Results indicate that relative to the zero choice condition, the single choice condition showed an indirect serial mediation of choice options influencing product liking indirectly through agency valenced thoughts, abc = .16; 95% CI [.03, .39]. Relative to the zero choice condition, the multiple choice condition showed an indirect serial mediation of choice options influencing product liking indirectly through agency and valenced thoughts, abc = .47; 95% CI [.09, 1.00].

Relative to the single choice condition, the multiple choice condition showed an indirect serial mediation of choice options influencing product liking indirectly through agency and valenced thoughts, abc = .31; 95% CI [.06, .67], giving support for H6b.9

9 Note that in all of the tested serial mediations, the relationship between reactance and similarity or agency was also tested in the reverse direction, wherein reactance measures were input as the first mediator and similarity or agency the second. In all cases, there were no demonstrated serial mediations, 102

Study 2 Discussion

The results suggest that source customization facilitates perceptions of agency and also creates a bond between user and customized object, where users feel greater similarity with the avatar that they created. The results also demonstrate some important differences in reactance variables. The state reactance scale is a self-report questionnaire comprised of subscales measuring anger, perceived choice, cognitive appraisal, and counterarguments. This scale gives a good impression of both the current emotional state of the participant with regards to perceived threats to their freedom and the cognitions that they are generating in opposition to the product. The thought-listing measure is a heavily cognitive measure, wherein participants are indicating the extent to which they actively considered and wrote down negative thoughts about a given product. Similarity and agency were shown to influence product liking through counterarguments generated

(i.e., primarily cognition), but not through state reactance (an intertwined mixture of cognition and affect). The findings suggest that the process of source customization and subsequent perceptions of similarity and agency may affect resistance primarily through cognitive means.

Study 2 again establishes the importance of source customization on shaping product attitudes. Unlike in Study 1, there was no direct effect shown between number of choice options and product liking. The lack of direct effect may be a result of fewer cues available in this study compared to Study 1; in Study 1, participants could customize all

offering support for the paths in the hypothesized directions; perceptions of similarity and agency influence reactance, rather than reactance influencing these perceptions.

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aspects of an avatar’s three-dimensional body and then see it interacting in a virtual environment. Study 1’s participants were able to see the avatar walk, talk, and sit while delivering a persuasive message. In Study 2, participants saw two-dimensional portraits consisting of the avatar’s head, shoulders, and background all of which remained unchanging through the duration of the experiment. Despite the lack of direct effect between choice options and product liking in Study 2, it still demonstrates that choice options are influential in shaping product attitudes, albeit indirectly through similarity and agency to cognitive components of reactance.

In terms of contribution to testing the CRRM, Study 2 advances the findings from

Study 1 in three key ways. First, Study 2 demonstrates that similarity is an important mediating concept between customization and product attitudes. Study 1 demonstrated that customization influenced intrinsic motivation in part through need fulfillment, and

Study 2 establishes that in addition to the benefits that occur as a result of increased intrinsic motivation, users are seeing reflections of their own identity in their creations.

These results indicate that two distinct processes are occurring when customizing: users are receiving the positive psychological benefits from the act of customization itself, and users are also seeing reflections of their identity in the creation that they have made.

Results from Study 2 support the hypothesized two distinct pathways in the CRRM, one through identity perceptions and the other through need fulfillment.

Second, Study 2 established that agency may be an additional measure to use to assess need fulfillment. The intrinsic motivation scale is comprised of fulfillment of two needs, autonomy and competence, in addition to measuring enjoyment and perceptions of

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tension. Thus, Study 1 indicated that need fulfillment in some form influence product attitudes. The use of agency as another measure to assess need fulfillment (in this case, autonomy specifically) further narrows down the role of need fulfillment in the customization process.

Third, and perhaps most importantly, Study 2 makes some interesting contributions to studying reactance. In Study 1, the forewarning manipulation failed to have an effect on participants’ product liking and did not interact with the customization condition in any meaningful way. However, the brief way in which forewarning was manipulated (i.e., a single added instruction at the beginning of the task) may have been too weak to create the intended effects. To remedy these shortcomings, Study 2 directly manipulated text within the persuasive speech using pretested language proven to annoy participants and elicit reactance. The results indicate that this manipulation was effective; participants in the high reactance condition scored higher on the state reactance measure and lower on the valenced thoughts, as well as writing the most negative thoughts.

Despite the success of this manipulation, the reactance condition did not interact with the customization condition, and the customization condition was shown to influence product attitudes even when controlling for participants’ assignment to reactance condition. The strength and persistence of the effects for customization may suggest that customization has a very powerful effect on reactance, wherein the benefits given to those who have the most opportunities to customize overcome strong reactance as easily as weak reactance.

Regarding the measuring of counterarguments, results showed that both negative thought total and valenced thought total were valid predictors. As expected, the two are

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highly correlated, r = -.87, p < .001. This correlation suggests that using valenced thought total as the dependent measure is very similar to using total number of negative thoughts.

Due to its encompassing of all participant thoughts, this number will be used in future analysis.

In order to operationalize reactance-inducing language, Study 2 added pre-tested sentences designed to annoy participants. These statements were a combination of statements to get the participants angry (e.g., “you’re young, so I’ll explain this slowly”) and statements designed to create a threat to perceived freedom (e.g., “you have to listen to me” or “there’s really no other choice”). The freedom-threatening language more closely conceptualizes reactance according to the original definition (Brehm & Brehm

1981). Yet it may be worthwhile to consider the role of inciting angry affect in participants as a means to elicit reactance. In this case, freedom is not explicitly threatened, and participants may be experiencing anger, but not necessarily reactance. It is possible that when one is angry at a persuasive source then anything the source asks

(even nicely) will elicit reactance, as any request may be more likely to be seen as a threat to one’s freedom. It is clear that the combination of these statements used generated reactance in participants in Study 2, and it may be worthwhile for future research to examine how priming angry affect might affect individual reactance, even when a freedom is not specifically threatened.

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Chapter 7: Message Customization and the Test of the CRRM

Study 3 seeks to further elaborate on the role of customization in the persuasive message process. The first two studies firmly established that the source customization process can change product attitudes. They also provided initial evidence for claims made in the CRRM. Study 3 is the first attempt to put all the variables posited in the CRRM together and test the model as a whole process. Study 3 will build on the previous studies in the following ways.

Methodological Changes in Study 3

Study 3 will require participants to customize a persuasive message, rather than the source of a persuasive message. Studies 1 and 2 suggest that the benefits of the customization process of a persuasive source bleed onto the product that the source is selling. Study 3 will allow participants to interact with the product much more directly by allowing them to customize the message (in this case, an advertisement) that the product appears in. Customizing the message should allow individuals to engage deeply with the content. In non-interactive contexts, a focus on the persuasive message may normally result in higher reactance as the individual is encouraged to engage with the message and has the opportunity to create strong counterarguments. I hypothesize that in an interactive context the benefits of customization will reduce or remove any negative effects increased scrutiny might have. It could be argued that source customization distracts 107

individuals from the persuasive message, thus decreasing their reactance through a lack of scrutiny. By allowing participants to customize the persuasive message, I will test whether the results in the first two studies can be attributed to distraction or to the increased needs and perceptions of identity that decrease reactance by encouraging more liking of the source and product. If it can be demonstrated that the positive effects of customization continue to work despite an increase in scrutiny, it would make a strong case for the benefits of customization in the persuasive process.

Contributions to Testing the CRRM

It was demonstrated in Study 2 that similarity to the avatar mediated the relationship between source customization and counterarguing independently of need fulfillment. This finding demonstrates that individuals are in some way considering their own identity, choices, and values when viewing their customized avatar. Study 3 will expand on the concept of identity by evaluating two new variables: connection with the created message and self-affirmation. Both of these variables are used instead of similarity to better understand the nuances of the process and to provide a better fit with message, rather than source, customization. Connection with the message assesses the extent to which one sees the message as important and would feel personally attacked if the message were to be attacked. Self-affirmation theory (Cohen & Sherman, 2007;

Sherman & Cohen, 2006; Steele, 1988) posits that being reminded of one’s values, beliefs, and roles that are important to one’s identity can reduce perceived threat to the self. In addition to becoming connected with a customized object (perhaps as a result of the effort and thought placed in it), the customized object may be a reflection of a

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person’s values. In this way, viewing the customized object will affirm the individual in the face of perceived threat (i.e., faced with the freedom loss that stems from being the target of a persuasive attempt). Both connection and self-affirmation are hypothesized to affect engagement.

Study 3 will also directly measure autonomy and competence need fulfillment.

Study 1 measured these needs in combination with enjoyment and perceived tension to comprise an intrinsic motivation score. Study 2 used agency as a proxy by means to measure need fulfillment, in this case autonomy only. Study 3 will isolate these needs and assess them independently. The TIME model (Sundar et al., 2015) looks at need fulfillment wherein all three needs combine to affect engagement. It could be argued that these needs should be looked at separately. Although related to each other, the needs were originally conceptualized as distinct (Deci & Ryan, 2000; Ryan & Deci, 2000) and may affect engagement in different ways.

Despite manipulating the ability to customize a persuasive source, Studies 1 and 2 did not measure source credibility perceptions. Study 3 will remedy this limitation by directly measuring perceptions of the persuasive source. Even though participants’ attention will be more directly on the message, rather than the source, source perceptions have been shown to affect product liking. Perceptions of the source often influence perceptions of the message (Chaiken, 1980; Petty & Cacioppo, 1984; Wilson & Sherrell,

1993). All participants will be made aware of a source (i.e., a company that created the product) but otherwise will be directed to thinking about the message. Assessing source credibility will give important additional insight into the variables that influence

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engagement. In addition, findings for source credibility will illustrate whether the benefits of customization of the message bleed onto perceptions of the source, an informative reverse of the findings from the first two studies.

The CRRM hypothesizes two key predictor variables in the customization process: executive functioning and perceived interactivity. Study 3 will assess both variables. To measure executive functioning, participants will complete a customization task and then be given a cognitively difficult task. Executive functioning will be measured based on self-reported scores of difficulty with the task, total time it takes to complete the task, and number of errors made during the task. Perceived interactivity will be assessed via self-report measures assessing one’s perceptions of active control, two- way communication, and synchronicity. In this case these measures will ask the participants about their experience with common text editing software.

Finally, Study 3 will measure the concept of engagement as the mediating variable that is influenced by need fulfilment and identity perceptions and predicts reactance. Here, engagement is conceptualized as a combination of positive affect and elaboration on the message (Mollen & Wilson, 2009; Wang, 2006). Engagement will be added as the final additional variable to mediate the pathways between autonomy, competence, connection, self-affirmation, and executive functioning on reactance.

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Based on this, the following pathways are posed in the CRRM (Figure 14):

Figure 14. Proposed paths between variables in the CRRM.

The CRRM posits that perceived interactivity is one of two key predictor variables used to indirectly affect psychological reactance. Using perceived interactivity as a predictor variable allows us to account for a large number of individual differences including technology experience, use, and understanding. Study 3 experimentally manipulates the extent to which one can customize an advertisement. Users will read, edit, or create an advertisement. Both the create and edit conditions give participants an essentially infinite amount of choices to make – they can change or rewrite anything they like about the advertisement. The CRRM argues that to test the effects of perceived interactivity, an experimental manipulation should go far enough to make sure that the medium meets a minimum threshold wherein individuals have the ability to have active 111

control over the content, participate in two-way communication with the medium, and do so in a synchronous fashion. Once these criteria are met, the perception of how interactive the medium is becomes an important predictor variable. Studies have indicated that high perceived interactivity increases user satisfaction, and perceptions of trust in online websites (Hu, Wu, Wu, & Zhang, 2010), and website effectiveness (Song

& Zinkhan, 2008). Both the TIME and the CRRM suggest that need fulfillment and aspects of the user identity are important mediating variables in influencing attitudes when using interactive media. The CRRM differs from the TIME in that it places perceived interactivity as the key predictor, rather than another mediating variable

(Figure 15).

H1: Perceived interactivity will positively predict autonomy (H1a), competence

(H1b), connection (H1c), and self-affirmation (H1d).

The CRRM also expands on the TIME by adding executive functioning as a second key predictor variable. Executive functioning is the extent to which a brain can self-regulate, use memory, and direct attention (Nathanson et al., 2014). Interactive media should place high demands on executive functioning, as users must mentally juggle input, feedback, changing visual stimuli, and a number of other rules specific to the interactive medium. A lack of executive functioning can make it harder for participants to succeed on future tasks and also make it easier to quit those tasks (Baumeister et al., 2007;

Denson et al., 2012). As one’s levels of executive functioning are taxed (i.e., decrease), one’s perceptions of autonomy and competence may also decrease; too many stimuli could make it difficult to succeed, reducing competence, and needing to remember and

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follow the requirements of the medium could be seen as a threat to autonomy. Moreover, fewer cognitive resources may also lead to lower perceptions of connection with the customized object (i.e., it is harder to care about something when one is mentally exhausted), and receive less self-affirmation from the customized object (i.e., the struggle on a task due to low executive functioning would remove perceptions of self-worth).

Because engagement has a component of focus and elaboration, executive functioning is predicted to directly influence engagement. A lack of executive functioning resources should also make it harder to feel engaged, as attention becomes harder to direct and the willpower to remain engaged drains.

H2: As executive functioning decreases, autonomy (H2a), competence (H2b), connection (H2c), self-affirmation (H2d), and engagement (H2e) will decrease.

Both the TIME and CRRM use the fulfillments of autonomy and competence needs as predictors of engagement. As autonomy and competence needs are met, intrinsic motivation to continue with the task increases (Ryan et al., 1991). Individuals will be drawn to an activity that fulfills their needs, thus:

H3: Autonomy (H3a) and competence (H3b) will positively predict engagement.

The TIME and CRRM also suggest that considerations of a user’s identity will be important predictors of engagement. The CRRM looks at a user’s identity in the customized object in two ways: the extent to which one feels connected with the customized object, and the extent to which one sees a reflection of one’s core values, beliefs, and self-worth from the customized object. Users should pay more attention to an object they feel connected with and receive self-affirmation from.

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H4: Connection (H4a) and self-affirmation (H4b) will positively predict engagement.

Source perceptions influence perceptions of a persuasive message (Chaiken,

1980; Petty & Cacioppo, 1984; Wilson & Sherrell, 1993). Findings from Studies 1 and 2 suggest that customization of a source causes source perceptions to affect attitudes about the message. Study 3 will assess if the reverse is true, wherein customization of a message influences source perceptions. Changing source perceptions via message customization may then influence engagement with the message; individuals should enjoy and focus more on a message from a source they rate as credible and trustworthy.

H5: Source credibility will positively predict engagement.

As demonstrated in previous research, narrative engagement has been shown to decrease reactance (Moyer‐Gusé, 2008; Moyer‐Gusé & Nabi, 2010). In the same way, interactive engagement should also decrease reactance by means of distracting users from the notion that they are being persuaded, occupying their cognitive resources so they do not have the time nor energy to effectively counterargue, and by spreading the positive and enjoyable benefits of need fulfillment and increase connection and self-affirmation to the point that individuals are less motivated to resist the persuasive attempt.

H6: Engagement will be negatively related to reactance.

H7: Reactance will be negatively related to product attitudes.

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Figure 15. Hypotheses added to CRRM.

The CRRM was created to hypothesize the process by which customization can ultimately decrease reactance and increase attitudes toward the persuasive message. As such it hypothesizes not only the predicted paths between variables, it hypothesizes that these variables work in tandem to indirectly affect product attitudes through all the mediating variables. As exogenous predictor variables, perceived interactivity and executive functioning should indirectly affect product liking through their intermediary variables; both perceived interactivity and executive functioning will separately indirectly affect product liking through the chain of variables in the various stages of the model: via autonomy, competence, connect, self-affirmation, engagement, and reactance.

H8: Perceived interactivity will indirectly affect product attitudes through autonomy (H8a), competence (H8b), connection (H8c), and self-affirmation (H8d).

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H9: Executive functioning will indirectly affect product attitudes through autonomy (H9a), competence (H9b), connection (H9c), and self-affirmation (H9d).

Overview

Participants will be randomly assigned to read, edit, or create an advertisement based on goals set forth in a company product “briefing.” In addition, participants will be randomly assigned into high or low self-affirmation conditions. Because self-affirmation may be a means by which to reduce reactance (Schuz, Shuz, & Eid, 2013), it is important to isolate its effects on the customization process. Participants assigned to the high self- affirmation condition will be told to edit or create an advertisement designed to reflect their values, beliefs, and personality. Participants in the low self-affirmation condition will be told to complete the customization task in a way that reflects the values, beliefs, and personality of someone “the exact opposite from you.” This language is a common tactic used to manipulate self-affirmation (Aronson, Blanton, & Cooper, 1995; Sherman

& Cohen, 2006). Participants will be randomly assigned into customization and self- affirmation conditions. They will read the briefing, and then complete the customization task. Following this they will be given the task designed to test executive functioning, followed by the other measures. Although the focus of Study 3 is on testing the CRRM and using perceived interactivity as a key predictor variable, it may be worthwhile to examine group differences in the manipulated conditions. Group difference testing can help determine whether the manipulations succeeded in meeting the threshold for creating perceptions of interactivity, and replicate the findings in Studies 1 and 2. In this case, it is hypothesized that edit and create conditions will outperform the read condition,

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but not necessarily each other. Thus, in addition to the predicted hypotheses for the

CRRM, the following group differences are hypothesized:

H10: There be a main effect for customization condition on perceived interactivity (H10a), executive functioning (H10b), autonomy (H10c), competence

(H10d), connection (H10e), self-affirmation (H10f), source credibility (H10g), engagement (H10h), and product attitudes (H10i) such that individuals who create or edit the advertisement will have the highest scores compared to those who read. In the case of reactance, individuals who create or edit the advertisement will have the lowest state reactance scores (H10j) and highest valenced thought-listing total (H10k) compared to those who read.

H11: There be a main effect for self-affirmation condition on perceived interactivity (H11a), executive functioning (H11b), autonomy (H11c), competence

(H11d), connection (H11e), self-affirmation (H11f), source credibility (H11g), engagement (H11h), and product attitudes (H11i) such that individuals who create or edit advertisements in the high self-affirmation condition will score higher compared to those in the low self-affirmation condition. In the case of reactance, individuals who are in the high self-affirmation condition will have the lowest state reactance scores (H11j) and highest valenced thought-listing total (H11k) compared to those in the low self- affirmation condition.

H12: Customization condition will interact with self-affirmation condition such that those in the create and high self-affirmation conditions will score the highest on perceived interactivity (H12a), executive functioning (H12b), autonomy (H12c),

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competence (H12d), connection (H12e), self-affirmation (H12f), source credibility

(H12g), engagement (H12h), and product attitudes (H12i). In the case of reactance, individuals who create advertisements and are in the high self-affirmation condition will score the lowest on state reactance (H12j) and highest valenced thought-listing total

(H12k) compared to those in any other cell.

To determine if customization can influence product liking beyond a short time frame, participants were also given a post-test assessing their autonomy, competence, self-affirmation, product liking, and purchase intention. As time after the customization task increases, participants who participated in the create or edit advertisement tasks should maintain their attitudes longer than those in the read condition.

H13: Time will interact with customization task such that autonomy (H13a), competence (H13b), connection (H13c), self-affirmation (H13d), and product liking

(H13e) will decrease from Time 1 to Time 2 for those in the read condition, but not for those in the edit or create conditions.

Study 3 Method

Sample

Participants (N = 309) were initially recruited from The Ohio State University.

Participants were recruited from a research pool within the Communication department and received course credit for their participation. Participants were prescreened for their

English speaking and writing skills, and screened for colorblindness. Despite the screening process, two participants revealed after the experiment that they were colorblind and were excluded from final analysis. A manipulation check was conducted

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on participants based on the task they completed (reading, editing, or writing an ad).

Participants who did not indicate the task that they completed (i.e., a participant said they read an ad when they wrote one from scratch) were excluded from final analysis (n = 15).

One participant was removed for failure to complete the survey.

The remaining 291 participants were used in the analysis. These participants identified as 61.2 percent female and 38.1 percent male, ranged in age from 18 to 57 (M

= 20.49, SD = 4.15), and reported their race/ethnicity as: Caucasian/ European-

American/White (n = 202); Asian/Asian-American (n = 44); Black/African/African-

American (n = 31); Latino/Latina/Hispanic (n = 12); and Pacific Islander (n = 2).10

Procedure11

Participants were told that they were taking part in a study designed to assess their attitudes about new products proposed by marketing companies. Participants entered the lab, gave their informed consent, and then were told that they would take part in a study with a number of different tasks. Participants were told that the study was designed to get their opinions on new products proposed by marketing companies but not yet released.

They were given a “briefing” about a product that contained information about the company, the product, the company’s target audience, and three important points that the company wished to communicate about the product (Appendix). Participants were given two minutes to read and familiarize themselves with the briefing. After reading the

10 Due to an error in the survey design, participants selected a single option from a multiple choice category instead of selecting all the races or ethnicities that applied. 11 See Appendix H for detailed Study 3 protocol. 119

briefing, participants were given the first instructions unique to their randomly assigned condition (Table 8).

Self-affirmation Customization Condition Condition Read Edit Create High n = 45 n =49 n =49 Low n =50 n =53 n =44 Table 8. Distribution of participants in Study 3 conditions.

Message Reading

These participants were told that they were to read an advertisement that was created to comply with the goals and target audience specified in the briefing. These participants were given five minutes to read and evaluate the advertisement.

Message Editing

These participants were told that they were to edit an advertisement that was previously created to comply with the goals and target audience specified in the briefing.

These participants were given permission to edit anything that they liked: names, descriptions, font color, font size, spacing, and sentences. They were instructed to make the edits according to the goals described in the briefing and to tailor the edits to comply with their self-affirmation condition. These participants were given 10 minutes to edit the advertisement. 120

Message Writing

These participants were told that they were to write an advertisement to comply with the goals and target audience described in the briefing. Participants were told to write two paragraphs worth of text, and to imagine that the text would appear in a newspaper next to a picture of the product. They were instructed to be as creative, inventive, or silly as they wished, keeping the goals of the briefing in mind and the instructions in their self-affirmation condition. These participants were given 10 minutes to create the advertisement.

Self-affirmation

In addition to the message condition, participants were also randomly assigned to high and low self-affirmation conditions. Participants in the high self-affirmation condition were told to edit/write the advertisement to make it as appealing as possible to them, illustrating their core values and interests. Participants in the low self-affirmation condition were told to edit/write the advertisement to make it as appealing as possible to someone the exact opposite of them, appealing to someone with the exact opposite values and interests from the participant. For example, a participant in the writing and high self- affirmation conditions would hear “write the advertisement to make it as interesting as possible to you. You should try your best to make the advertisement be a reflection of your values and interests.”

Following the reading, editing, or writing period, participants were given either the thought-listing task or the Stroop task, followed by the opposite task. Because both writing and completing the Stroop task may tax executive functioning and it is not clear

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which task would affect the other, these tasks were counterbalanced in their presentation to participants. After completion of these tasks, participants were directed to an online survey where they completed a questionnaire that included assessments of engagement, product attitudes, product purchase intention, source credibility and liking, state reactance, self-affirmation, need fulfillment, and perceived interactivity. When participants completed this questionnaire, they were directed back to the statements they wrote during the thought-listing task. They were asked to go back and code their thoughts, placing a plus sign next to thoughts they listed that were positive about the product, a minus sign next to thoughts that were negative about the product, and a zero next to thoughts they could not decide or were neutral about the product. This self-coding procedure is commonly used in thought-listing experiments to measure counterargument

(Cacioppo & Petty, 1981; Miller & Baron, 1973).

Measures12

Perceived Interactivity

The Interactivity Scale (Liu, 2003) is an 11-item scale consisting of three subscales: active control (e.g., “I felt that I had control over my experience,” Cronbach’s

α = .74); two-way communication; (e.g., “The software makes me feel it wants to listen to its users,” Cronbach’s α = .76); and synchronicity (e.g., “The software processed my input very quickly,” Cronbach’s α = .72). The scale was modified slightly to be relevant to the customization task. Statements were answered on a scale ranging from 1 (strongly disagree) to 7 (strongly agree).

12 See Appendix I for full Study 3 measures. 122

Executive Functioning

Participants were measured on how many seconds it took to complete the Stroop task (M = 57.90, SD = 12.03). Participants were given an explanation of the task and had the opportunity to practice on two different cards. Time began when the first card was shown to the participant and ended when the participant correctly answered the last card.

Time was kept on a stopwatch. Participants were also measured on how many mistakes they made during the Stroop task (M = .73, SD = 1.17). A mistake was counted when the participant said a different color than the correct answer. Half-statements (i.e., when the participant starts to say orange but self-corrects to the proper color) were not counted as mistakes. Number of incorrect answers was used in the model for hypotheses testing.

Cognitive Resources

As an additional measure of cognitive stress, immediately following the Stroop task participants were asked three questions concerning their perceived difficulty on the

Stroop task. These statements were answered on a scale ranging from 1 (strongly disagree) to 7 (strongly agree) and included “the flashcard task wore me out,” and “the flashcard task was mentally exhausting” (Cronbach’s α = .80).

Self-determination Needs

Participants were given 10 items from the Intrinsic Motivation Inventory (Ryan,

Koestner, & Deci, 1991).They were measured on two distinct dimensions: perceived competence (Cronbach’s α = .92) and perceived autonomy (Cronbach’s α = .69). The scale consists of statements answered on a 1 (strongly disagree) to 7 (strongly agree) scale, such as “I felt like I was doing what I wanted to do while I was working on the

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task” and “I felt that it was my choice to do the task.” This inventory has been used in other studies and shown to have high reliability (Ryan, Mims, & Koestner, 1983; Tsigilis

& Theodosiou, 2003).

Connection to Advertisement

To measure the extent to which participants felt connected to the advertisement, participants were given a 9-item scale used to assess attachment in consumer behavior

(Ball & Tasaki, 1992). All items were measured on a 7-point Likert scale ranging from 1

(strongly disagree) to 7 (strongly agree). The scale included questions such as “If someone ridiculed the advertisement, I would feel irritated” and “If someone deleted the ad, I would feel a little bit personally attacked” (Cronbach’s α = .85).

Self-affirmation

The extent to which one self-affirms during the customization task was measured on an 8-item scale (Tate, 1996) with answers ranging from 1 (not at all) to 9 (very).

Participants were asked the extent to which their advertisement task made them feel confident, proud, satisfied, skilled, secure, like a good person, strong, and powerful

(Cronbach’s α = .95).

Source Credibility

Source credibility was measured on an 18-item scale (McCroskey & Teven, 1999) designed to assess three dimensions of credibility participants felt toward the company that created the product: trustworthiness (Cronbach’s α = .89); goodwill (Cronbach’s α =

.83); and competence (Cronbach’s α = .89). Participants scored the source on 7-point

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semantic differential items, such as intelligent/unintelligent, informed/uninformed, or sensitive/insensitive.

Engagement

Engagement was measured on a 4-item scale that asked questions such as “I felt engaged in the advertisement task” and “the advertisement task really pulled me into it”

(Cronbach’s α = .92). Statements were answered on a scale ranging from 1 (strongly disagree) to 7 (strongly agree).

State Reactance

Participants completed the 15-item state reactance scale (Quick & Stephenson,

2008). The scale is composed of four subscales: perceived threat to choice (e.g., “the advertisement tried to manipulate me”); counterarguing (e.g., “I criticized the advertisement I just saw, while I was reading it”); cognitive appraisal (e.g., “the advertisement was pleasant”); and anger (e.g., “the advertisement made me feel angry”).

Items were measured on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Counterarguments

Counterarguments were measured using the thought-listing procedure (Cacioppo

& Petty, 1981; Miller & Baron, 1973). After reading the persuasive text, participants were instructed to list any thoughts they had about the product. At the end of the experiment, before leaving, participants were instructed to label each thought they had listed, indicating whether each thought was positive, negative, neutral, or unrelated to the product. The total number of positive, negative, and neutral thoughts listed were counted

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and summed, creating a valenced number indicating whether the majority of thoughts were positive, negative, or neutral about the product. These were then scored as 1

(positive), 0 (neutral) or -1 (negative) and summed together. This valenced total number was used in the analysis.

Message Attitudes

All items were measured on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Product liking (Cronbach’s α = .91) was measured with five items that included statements such as “I liked the product featured in the ad” and “I would want to hear more about the product.” Purchase intention (Cronbach’s α = .88) was measured with three statements, such as “I would buy the advertised product” and “I was convinced by the ad to buy the product.”

Covariates

Familiarity with the Product

Participants were given three items to assess their familiarity with their randomly assigned product. Statements were measured on a scale ranging from 1 (strongly disagree) to 7 (strongly agree) and included “I am familiar with the [type of product] that was originally shown to me,” and “I have heard of the [product] that was originally shown to me” (Cronbach’s α = .76).

Familiarity with Microsoft Word

Participants were given four items to assess their familiarity with the word processing software. Statements were measured on a scale ranging from 1 (strongly disagree) to 7 (strongly agree) and included “I am familiar with Microsoft Word,” and “I

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know how to make formatting changes (e.g., changing font, changing line spacing) in

Microsoft Word” (Cronbach’s α = .84).

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Dependent Measure M (SD)

Perceived interactivity 4.66 (.66)

Stroop task time 57.90 (12.03)

Stroop incorrect .73 (1.17)

Stroop difficulty 2.54 (1.26)

Autonomy 4.28 (1.15)

Competence 4.83 (1.17)

Connection 2.80 (1.02)

Self-affirmation 5.37 (1.83)

Source credibility 4.81 (1.0)

Engagement 5.08 (1.05)

State reactance 3.08 (.84)

Negative thoughts listed 1.59 (1.53)

Valenced total thoughts listed 1.36 (3.40)

Product liking 5.09 (1.31)

Purchase intentions 4.08 (1.57)

Product familiarity 3.66 (1.69)

Word familiarity 6.56 (.63)

Table 9. Mean scores for all Study 3 dependent measures.

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1 2 3 4 5 6 7 8 9 10 11

1. Perceived interactivity

2. Executive functioning .01

3. Autonomy .37** .06

4. Competence .26** .03 .08

5. Connection .25** .17* .33** .18**

29 6. Self-affirmation .28** .02 .31** .56** .45**

7. Source credibility .15** -.01 .18** .18** .22** .33**

8. Engagement .26** -.07 .34** .28** .33** .50** .26**

9. Valenced thought-listing .04 -.04 -.04 .08 .13* .11 .28** .15*

10. State reactance -.14* .01 -.19* -.15* -.06 -.24** -.43* -.18* -.14*

11. Product liking .13* .01 .08 .19** .22** .31** .65** .28** .33** -.37**

12. Purchase intention .13* .04 .09 .11 .31** .29** .54** .27** .30** -.33** .76**

Table 10. Correlation matrix for Study 3 measures. Note. * denotes p < .05, ** denotes < .001 129

Materials

Product Pre-test

Ten briefings were created. Each briefing contained information about a fictional company, product, and three things that the company wished to communicate about the product. Participants (N = 26) were asked to rate each briefing on the product’s appeal to college students, how much they liked the product, whether a similar product already existed, and whether they would want to write an advertisement about the product (Table

11). Participants answered each item on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly agree). Any item that scored over a mean score of four on “a product like this already exists” was removed. Any item that scored lower than a mean score of four on “I would want to write an advertisement for this product” was removed, leaving six briefings in the pool. Then four briefings were selected based on their highest combined scores on the items “this product would appeal to college students” and “I like this product.”

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1 2 3 4 5 6 7 8 9 10 M(SD) M(SD) M(SD) M(SD) M(SD) M(SD) M(SD) M(SD) M(SD) M(SD) Appeal to 5.69 4.57 5.38 4.33 5.95 5.94 5.26 4.68 4.47 4.71 College (.88) (1.17) (1.36) (1.56) (1.40) (.80) (1.24) (1.73) (1.33) (1.57) Students Like Product 4.85 4.71 3.29 4.9 5.5 4.15 4.47 4.58 4.82 3.94 (1.4) (1.23) (1.74) (1.73) (1.47) (1.42) (1.71) (1.6) (1.51) (1.20) Table 11. Study 3 product pretest scores. Note. Products 1, 4, 5, and 9 were selected (Appendix J).

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Stroop Task

When participants finished with the customization task, they were given the

Stroop task (Golden, 1978; Logan & Zbrodoff, 1979). This task consists of participants being shown the names of various colors (e.g., blue, yellow) that are printed in different colors of ink (e.g., the word blue may be printed in green ink). Participants must then name the color of the ink. Words were written in 130-point font in capital letters. First, a pool of colors was created: purple, yellow, red, blue, black, pink, orange, and green.

These colors were randomly sampled from and written in black font. Then for each individual word the color of the ink was randomly selected from the color pool. If a color was chosen that matched the color printed, a new color was randomly selected from the pool. These words were then printed on flashcards that were 8.5 x 5.5 inches in size. The correct answer (i.e., the color participants needed to speak aloud) was lightly printed in pencil on the back of each flashcard.

A desk was set up to be three feet away from the participant’s chair. Participants sat in the chair while the researcher sat at the desk. The researcher then described the nature of the task to the participant, holding up some sample flashcards and walking the participant through the procedure. Participants were told that their goal was to complete the task as fast as possible, and that they would be timed on a stopwatch. Participants were instructed that cards would be lifted and displayed to them one at a time, and their job was to speak aloud the color of the ink that the word was printed in. When a correct answer was given, the flashcard was set down and the next lifted up. In the event of a

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wrong answer the researcher continued to hold up the card until the participant said the correct answer. The researcher counted the number of times the participant said an incorrect color.

This assessment is a common and well-established measure of executive functioning. In general, individuals who have had executive functioning resources depleted take longer to complete the task and make more errors when doing so

(Baumeister et al.,2007; Gailliot et al., 2007).

Post-test

Upon completing the study, participants were asked if they would like to sign up to receive a follow-up survey. Participants who opted in were then emailed two days after their participation in the lab portion of the experiment. They were then subsequently reminded, if they had not completed the survey, three days following the initial email and then three days following the second email. The post-test contained repeated items from the lab portion of the questionnaire: autonomy, competence, self-affirmation, product liking, and purchase intention. Of the 291 participants, 114 opted to not sign up for the follow-up survey, leaving 177 remaining. Of these participants, 108 completed the survey after three email contact attempts, giving a response rate of 61.02%. Participants completed the survey an average of 5.84 (SD = 4.39) days after completing the laboratory portion of the study.

There was no statistically significant association between assignment to customization condition and completion of the post-test survey; individuals in the read, edit, or create conditions equally completed the post-test, χ2 = .14, p = .935. There was

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also no significant association between completion of the post-test and self-affirmation condition; individuals who received high or low self-affirmation instructions completed the post-test equally, χ2 = .18, p = .672. Because participants low in executive functioning resources may have opted to not sign up for the survey, a linear regression predicting survey completion from executive functioning resources was conducted.

Results indicate that executive functioning scores were not predictive of survey completion, β = .02, p = .330. Still, the self-selection of participants to take the survey or not means there is a possibility of a biased sample.

Study 3 Results13

Preliminary Testing

Company Briefings

The four briefings were pretested and selected for their similarity in their appeal to college students and appeal of the product. Despite the initial preliminary testing, some significant differences in outcome variables were found to be dependent on the company briefing that participants saw. An initial ANOVA was conducted between the four products to determine if there were significant differences in dependent measures. The results show that source credibility and product liking were significantly different between company briefings (Table 12).

13 Due to the number of statistical tests, the p value was restricted using a Bonferroni correction. For the primary analyses concerning group comparison, the critical p value (p = .05) was divided by the number of hypotheses and for the group hypotheses (n = 38). Thus, a conservative p value of .001 was used for the group comparison testing.

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Product 1 Product 2 Product 3 Product 4 F(3, 289) p partial η2 M (SD) M (SD) M (SD) M (SD) Perceived .64 .587 .007 4.56 (.62)a 4.71 (.62)a 4.69 (.69)a 4.66 (.66)a interactivity Executive functioning 1.40 .243 .01 .69 (.98)a .96 (1.56)a .67 (1.04)a .59 (.98)a Autonomy .53 .661 .007 4.22 (1.19)a 4.20 (1.19)a 4.31 (1.09)a 4.42 (1.14)a Competence .81 .489 .007 4.76 (1.24)a 4.80 (1.20)a 4.76 (1.19)a 5.02 (1.03)a Connection .78 .508 .007 2.70 (.89)a 2.91 (1.09)a 2.84 (.99)a 2.70 (1.06)a Self-affirmation 1.13 .336 .01 5.16 (1.90)a 5.21 (1.90)a 5.44 (1.80)a 5.66 (1.70)a

13 a a b ab 5 Source credibility 5.49 .001 .06 4.58 (1.01) 4.70 (.90) 5.12 (.89) 4.80 (.96)

Engagement 3.12 .026 .03 4.76 (1.18)a 5.18 (.86)a 5.24 (.87)a 5.11 (1.21)a Product liking 5.71 .001 .06 4.86 (1.51)a 4.82 (1.32)a 5.59 (1.03)b 5.07 (1.21)ab State reactance 2.37 .075 .02 3.12 (.77)a 3.12 (.87)a 2.86 (.91)a 3.15 (.79)a Valenced thought- 1.08 .358 .01 1.56 (3.81)a .77 (2.75)a 1.40 (2.74)a 1.71 (4.13)a listing score Table 12. ANOVA for company briefing stimuli on dependent measures. Different superscripts denote significant differences between groups.

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To determine if these differences would affect scores on the other conditions, a

MANOVA was conducted between company briefing type and customization condition on the relevant outcome variables. There were zero significant interactions between company briefing and customization condition (Table 13). Thus, the type of briefing participants saw did not affect them based on their customization condition. As a result, for analyses concerning customization condition, company briefing will be dropped as a covariate.

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F(6, 289) p partial η2

Perceived interactivity .77 .591 .02

Executive functioning .19 .978 .004

Autonomy 1.27 .273 .03

Competence 1.23 .241 .05

Connection .22 .969 .005

Self-affirmation 1.50 .179 .03

Source Credibility .89 .504 .02

Engagement .24 .962 .005

Product Liking .70 .652 .02

State Reactance 1.09 .366 .02

Valenced thought- 1.54 .166 .03 listing score

Table 13. MANOVA results for company briefing by customization condition.

A separate MANOVA was conducted between company briefing type and self- affirmation condition on all relevant outcome variables. This analysis revealed two significant interactions between company briefing and self-affirmation condition for state reactance and connection scores. There were no other significant interactions between self-affirmation and company briefing on any other variable (Table 14).

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F(3, 289) p partial η2

Perceived interactivity 1.47 .223 .02

Executive functioning 1.08 .357 .01

Autonomy 2.12 .097 .02

Competence .245 .865 .003

Connection 3.43 .018 .04

Self-affirmation .21 .891 .003

Source Credibility .94 .421 .01

Engagement .40 .754 .004

Product Liking .55 .647 .007

State Reactance 4.21 .006 .04

Valenced thought-listing score 1.16 .327 .01

Table 14./ MANOVA results for company briefing by self-affirmation condition.

Primary Analyses

Testing the Model

In order to test the final model, a covariance matrix was constructed which was then used to estimate the parameters of the model using the maximum likelihood procedure for structural equation modeling (SEM). In general, use of SEM requires relatively high sample size. It is recommended that models employ at least 200 samples, or maintain a ratio of 4:1 sample size-to-parameter ratio (Holbert & Stephenson, 2002;

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Tanaka 1987). The complexity of this model requires a large sample size and was tested with 291 samples, meeting the ratio suggestions with a 11.64:1 sample size-to-parameter ratio. All of the variables were input into the model as mean scores for their respective scales. The observed variable model was used for simplicity and will be reported further.

It should be noted that these analyses were repeated using a latent variable hybrid model, wherein latent variables were constructed using the individual indicators for each scale

(e.g., the latent construct for perceived interactivity was comprised of all 11 items from the perceived interactivity scale). The hybrid latent variable model is useful for accounting for error in measurement. Due to the very high reliability in the scale items, the observed model was determined to be a better and more parsimonious form of testing.

Figure 16. Observed variable model used for testing the CRRM.

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Initial model testing. The model tested was the hypothesized CRRM (Figure 16).

Perceived interactivity, executive functioning (here conceptualized as the number of incorrect answers given on the Stroop task), and source credibility were input as exogenous (i.e., predictor) variables. Paths were drawn to the endogenous variables in the hypothesized directions. These variables included autonomy, competence, connection to the advertisement, self-affirmation, engagement, state reactance, and product liking mean scores. The model was run using the AMOS structural equation modeling software. The model was judged based on the significance of the path coefficients and overall model fit.

Path significance was assessed via statistical significance at the p < .025 level. Model fit was based on three values: the standardized root mean squared residual (SRMR), the root mean squared error of approximation (RMSEA) and the confirmatory fit index (CFI).

The cutoff value indicating strong fit is less than .08 for the SRMR and RMSEA, and a score greater than .95 for CFI indicates a strong model fit (Holbert & Stephenson, 2002).

Covariates familiarity with the advertisement viewed and familiarity with

Microsoft Word were regressed on the three exogenous variables: perceived interactivity, executive functioning, and source credibility. Results indicate that familiarity with advertisement did not predict perceived interactivity, β = -.02, p = .367, executive functioning, β = .01, p = .877, or source credibility, β = -.04, p = .185. Familiarity with

Microsoft Word did not predict perceived interactivity, β = .02, p = .702, executive functioning, β = -.07, p = .498, or source credibility, β = -.02, p = .478. Thus these covariates were dropped from the model.

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The overall model fit indices were poor, indicating weak model fit. The SRMR is

.18, the RMSEA is .22 and the CFI is .40. Although this model does support some of the individual hypothesized paths, as a means for accounting the entire process it is a poor fit.

Hypotheses 1 through 7 were tested via examining individual regression paths in the model. The path coefficients indicate nine statistically significant paths in the hypothesized direction, confirming H1a, H1b, H1c, H1d, H2c, H3a, H4b, H6, and H7

(see Table 15 for all path coefficients and significance tests). A number of paths were not significant, including cognitive resources to need fulfillment measures, competence to engagement, and source credibility to engagement.

Results indicate the important predicting role of the perceived interactivity measure. Perceived interactivity positively predicted increased perceptions of connection, self-affirmation, autonomy, and competence. Contrary to the hypothesized model, executive functioning was a significant predictor of only perceptions of connection, and in the opposite direction; results indicate that as executive functioning resources decrease, connection with the customized object increases. Executive functioning was shown to predict engagement under the typical p value cutoff of .05, but not under the more conservative p value of .025 used here, wherein individuals with more incorrect answers felt less engaged. As such, this finding deserves more investigation.

For the next stage in the model, autonomy and self-affirmation perceptions positively predicted engagement. Connection was shown to positively predict engagement.. There was no evidence for source credibility as an exogenous predictor of engagement. Finally, the next two stages of the model were significant in the

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hypothesized direction. Engagement was shown to predict state reactance wherein high engagement lead to less reactance, and reactance predicted product liking wherein low reactance led to increased product liking.

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Path Hypothesis Coefficient S.E. p Supported? Perceived interactivity ---> Autonomy .632 .095 ** H1a Supported Perceived interactivity ---> Competence .461 .100 ** H1b Supported Perceived interactivity ---> Connection .387 .086 ** H1c Supported Perceived interactivity ---> Self-affirmation .767 .155 ** H1d Supported Executive functioning ---> Autonomy .061 .054 .257 H2a No evidence Executive functioning ---> Competence .024 .057 .673 H2b No evidence Executive functioning ---> Connection -.144 .049 .003 H2c Not supported

3 Executive functioning ---> Self-affirmation .027 .088 .762 H2d No evidence

Executive functioning ---> Engagement .098 .044 .027 H2e Supported Autonomy ---> Engagement .170 .045 ** H3a Supported Competence ---> Engagement .032 .044 .475 H3b No evidence Connection ---> Engagement .112 .051 .029 H4a Supported Self-affirmation ---> Engagement .201 .028 ** H4b Supported Source credibility ---> Engagement .091 .053 .086 H5 No evidence Engagement ---> State reactance -.145 .049 .003 H6 Supported State reactance ---> Product liking -.579 .085 ** H7 Supported Table 15. Individual path coefficients for CRRM test. Note. ** denotes p < .001

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Hypothesis 8 was tested by examining the indirect effects of perceived interactivity and executive functioning on product attitudes. To probe for these indirect effects, a serial mediation was run using PROCESS (Hayes, 2013). Perceived interactivity was input as the predictor variable predicting the hypothesized pathway. For example, to test hypothesis H8a (Figure 17), perceived interactivity predicted autonomy, which predicted engagement, which predicted state reactance, which predicted product attitudes. This model was repeated for each hypothesis, switching out the second predictor variable as required (e.g., moving from H8a to H8b substituted competence for agency in the mediation chain). The results can be seen in Table 16 and 17. Results indicate that perceived interactivity indirectly effects product liking through a chain of autonomy, competence, or connection, followed by engagement and then state reactance.

Results show that this serial mediation does not occur with self-affirmation in the model, offering no support for H8d.

Figure 17. Serial mediation pathway proposed by H8a.

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Indirect Effect C.I. Hypothesis Coefficient supported? via Autonomy .008 [.001, .02] H8a Supported via Competence .004 [.001, .01] H8b Supported via Connection .007 [.002, .02] H8c Supported via Self-affirmation .005 [-.005, .02] H8d No evidence Table 16. Indirect effects for perceived interactivity on hypothesis 8.

Hypothesis 9 was tested in the same way, substituting executive functioning for perceived interactivity (Figure 18). Results indicate that executive functioning indirectly affected product liking only through the chain of connection, engagement, and state reactance, giving support for H9c.

Figure 18. Serial mediation pathway proposed by H9d.

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Indirect Effect C.I. Hypothesis Coefficient supported? via Autonomy .001 [-.001, .005] H9a No evidence via Competence .001 [-.001, .003] H9b No evidence via Connection .004 [.001, .01] H9c Supported via Self-affirmation .001 [-.001, .003] H9d No evidence Table 17. Indirect effects for executive functioning on hypothesis 8.

Group Differences

It was hypothesized that there would be significant interactions between customization condition and the self-affirmation condition. To assess Hypotheses 10-12, a 2(self-affirmation) x 3(customization condition) MANOVA was conducted on the relevant outcome variables using ad familiarity and Word familiarity as covariates.

Customization There were significant main effects for customization condition on a number of outcome variables (Table 18). On outcome variables concerning the product (e.g., product liking), participants in the create condition scored the highest compared to those in read or edit conditions. This result replicates findings from Study 1, demonstrating that the experience of full customization affects perceptions of the product.

In addition, participants in the create condition scored highest on measures of connection to the ad, which suggests that the act of creation places a strong sense of self within the ad. Making choices and creating an advertisement from scratch is a strong

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reflection of one’s personality and choices, even in conditions where participants were explicitly told to create the advertisement for someone the exact opposite of themselves.

On measures of need fulfillment (i.e., autonomy and competence perceptions) the findings were mixed between conditions. Participants in the create and edit conditions scored higher than those in the read condition on autonomy (with create scoring the highest of the three). However, participants in the read condition had the highest scores on competence. These findings suggest that the ability to make decisions present in the edit and create conditions may boost perceptions of autonomy, but also might be placing perceptions of competence at risk, as the more demanding task offers more room for failure. The difference in autonomy and competence needs offers an interesting avenue of exploration for future research to determine which of these needs is more important in determining product attitudes.

On measures of psychological resistance (i.e., counterarguing and state reactance) the findings indicate that those in the edit condition had the highest amount of resistance. Participants in the edit condition listed the most negative thoughts and had the lowest overall score for the valenced total of all thoughts listed. These participants also showed the highest state reactance scores compared to those in the read or create conditions. These findings were contrary to expectations; I hypothesized that the act of making choices to edit a preexisting ad would reduce reactance by the same means that making choices in the create condition did. That editors showed high reactance scores suggests that participants were averse to editing something already created. This aversion may be due to a “stamp” of the previous creator’s identity interfering with participants’

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ability to create a strong bond with the advertisement. Findings on perceived interactivity measures indicate that the edit and create conditions were sufficient in increasing perceived interactivity.

Finally, of interest are the scores on source credibility. The source credibility scale showed differences between those in the customization conditions, such that those in the edit condition had the lowest scores and those in the create condition the highest.

Source credibility questions assessed how participants felt about the company described in the briefing. All descriptions of the company were kept constant across conditions, and these findings suggest that creation of an advertisement from scratch makes participants feel better about the company that created the product, where those that edited an advertisement feel relatively the worst about the company. These findings may be attributable to a sense of identity within the advertisement. Those in the edit condition who are attempting to mold the advertisement according to their decisions may be aware of the original creator of the content, and being told to edit the advertisement might suggest that the original creator did something wrong or is less trustworthy.

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Read Edit Create F(2, 289) p partial M (SD) M (SD) M (SD) Hypothesis η2 supported? Perceived interactivity 5.02 .007 .04 4.48 (.71)a 4.75 (.58)b 4.71 (.67)b H10a I.E.14 Executive functioning .34 .711 .003 .72 (1.07)a .80 (1.19)a .67 (1.28)a H10b No evidence Autonomy 40.93 < .001 .23 3.53 (1.00)a 4.83 (.95)b 4.45 (1.11)b H10c Partial support Competence 16.75 < .001 .11 5.34 (.70)a 4.44 (1.26)b 4.76 (1.24)b H10d No evidence Connection 13.19 < .001 .09 2.41 (1.05)a 2.84 (.95)b 3.15 (.92)b H10e Supported Self-affirmation 2.89 .074 .02 5.13 (1.99)a 5.31 (1.77)a 5.75 (1.64)a H10f No evidence Source credibility 4.03 .014 .03 4.87( .10)ab 4.62( .10)a 5.00 (.10)b H10g I.E.

149 a ab b

Engagement 6.73 .003 .04 4.79 (1.11) 5.14 (.94) 5.34 (1.00) H10h I.E. Product liking 4.70 .013 .03 5.23 (1.35)a 4.78 (1.28)b 5.30 (1.26)a H10i Supported State reactance 5.84 .004 .04 3.11 (.82)ab 3.23 (.81)a 2.84 (.82)b H10j I.E. Valenced thought- 4.35 .016 .04 1.53 (3.01)ab .62 (2.97)a 2.00 (3.37)b H10k I.E. listing score Table 18. Main effects for customization condition from customization by self-affirmation MANOVA.

14 The adjusted p value used was p = .001. Hypotheses that met the standard (p = .05) value but not the conservative Bonferroni-corrected value were coded as having insufficient evidence (I. E.) and require further investigation. 149

Self-affirmation. Participants in the edit and create conditions were told to make their changes reflect their values (high self-affirmation) or the values of someone the exact opposite of themselves (low self-affirmation). Participants in the read condition were given no such instruction, but were randomly assigned to see previously created ads that were created with high or low self-affirmation instructions. Thus, the three conditions are not directly comparable. First, participants in the edit or create conditions were selected and compared to each other to test how the self-affirmation manipulation affected their perceptions of the outcome variables. The differences between edit and create conditions are shown in Table 19.

For all group differences, individuals in the high self-affirmation condition (i.e., those that were told to create or edit the advertisement to make it appeal to participants’ interests and reflect participants’ values) scored higher than those in the low self- affirmation condition (i.e., those that were told to edit or create the advertisement to make it appeal to someone the exact opposite of the participant). Self-affirmation condition did not affect perceptions of the product (e.g., product liking). Contrary to hypotheses and to previous research concerning self-affirmation and reactance (Schuz et al., 2013), the self- affirmation condition did not affect levels of state reactance or counterarguing.

Participants in the high self-affirmation condition showed higher perceptions of connection with the advertisement, and felt more competent in completing the task.

Interestingly, the self-affirmation condition also affected individual perceptions of the interactivity of the task. Participants who were told to create or edit the advertisement to

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appeal to their interests thought the software was more interactive. This finding indicates that considering one’s own values may reflect onto the medium itself.

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High Low Edit (n = 100)/Create (n = 89) F(1, 289) p partial η2 M (SD) M (SD) Hypothesis supported? Perceived interactivity 8.90 .003 .05 4.87 (.54) 4.60 (.68) H11a I.E.15 Executive functioning 1.19 .276 .01 .83 (1.28) .64 (1.18) H11b No evidence Autonomy 1.28 .260 .01 4.73 (1.01) 4.57 (1.08) H11c No evidence Competence 9.43 .002 .05 4.85 (1.13) 4.31 (1.31) H11d I.E.

152 Connection 10.65 .001 .05 3.20 (.86) 2.77 (.98) H11e Supported

Self-affirmation 7.27 .008 .04 5.84 (1.57) 5.18 (1.79) H11f I.E. Source credibility .45 .505 .001 4.86 (.88) 4.79 (1.02) H11g No evidence Engagement 8.91 .003 .04 5.43 (.83) 5.02 (1.06) H11h I.E. Product liking .98 .323 .003 5.12 (1.31) 4.94 (1.28) H11i No evidence State reactance .59 .442 .001 3.00 (.76) 3.09 (.91) H11j No evidence Valenced thought-listing score .06 .815 < .001 1.32 (3.70) 1.20 (3.39) H11k No evidence Table 19. Main effects for self-affirmation condition for those in edit and create conditions.

15 The adjusted p value used was p = .001. Hypotheses that met the standard (p = .05) value but not the conservative Bonferroni-corrected value were coded as having insufficient evidence (I. E.) and require further investigation. 152

Participants in the read condition were also assessed (n = 94). These participants were not given instructions regarding self-affirmation in any way; they were simply instructed to read the advertisement in front of them. However, these participants saw ads that were created under high or low self-affirmation instructions. In a way, these participants serve as judges of the quality of the ads that were created under high or low self-affirmation conditions. The results show two group differences for readers (Table

20). Individuals that read advertisements created under high self-affirmation felt more engaged with the reading task and felt more attached to the advertisement than with ads created under low self-affirmation instructions. Contrary to expectations, there were no significant interactions between the customization and self-affirmation conditions (Table

21).

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High Low Read (n = 94) F(2, 289) p partial η2 M (SD) M (SD) Hypothesis supported? Perceived interactivity 1.55 .216 .02 4.57 (.60) 4.39 (.78) H11a No evidence Executive functioning .36 .549 .004 .67 (.98) .80 (1.16) H11b No evidence Autonomy .143 .706 .002 3.50 (1.01) 3.58 (1.00) H11c No evidence Competence .91 .343 .01 5.43 (.81) 5.29 (.62) H11d No evidence Connection 2.28 .135 .02 2.58 (1.13) 2.25 (.95) H11e No evidence

154 Self-affirmation .43 .514 .01 5.27 (2.09) 5.01 (1.89) H11f No evidence

Source credibility .71 .402 .01 4.95 (.96) 4.79 (.94) H11g No evidence Engagement 5.95 .017 .06 5.09 (1.05) 4.55 (1.10) H11h I.E.16 Product liking .08 .754 .001 5.20 (1.55) 5.28 (1.15) H11i No evidence State reactance .44 .505 .01 3.16 (.84) 3.04 (.84) H11j No evidence Valenced thought- 6.76 .011 .07 2.36 (3.11) .80 (2.72) H11k I.E. listing score Table 20. Main effects for self-affirmation condition for those in the read condition.

16 The adjusted p value used was p = .001. Hypotheses that met the standard (p = .05) value but not the conservative Bonferroni-corrected value were coded as having insufficient evidence (I. E.) and require further investigation. 154

F(1, 289) p partial η2 Hypothesis supported? Perceived interactivity .30 .743 .001 H12a No evidence Executive functioning 1.92 .149 .01 H12b No evidence Autonomy 1.32 .270 .01 H12c No evidence Competence 1.72 .181 .004 H12d No evidence Connection .08 .926 < .001 H12e No evidence Self-affirmation .41 .667 < .001 H12f No evidence Source credibility .13 .882 .001 H12g No evidence Engagement .62 .537 .01 H12h No evidence Product liking .70 .498 .01 H12i No evidence State reactance .64 .527 .004 H12j No evidence Valenced thought- 1.93 .148 < .001 H12k No evidence listing score Table 21. Customization (create/edit) by self-affirmation MANOVA interaction results.

Post-test Results

To test H13 and assess how the customization process affects product attitudes over time, a 2(time point) x 3(customization) within-subjects repeated-measures ANOVA was conducted. Number of days from the original experiment was entered as a covariate with ad and Word familiarity. Results indicate no significant interactions between time points and customization condition on autonomy, competence, self-affirmation, product liking, or purchase intention scores (Table 22).

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F(1, 104) p partial η2 Hypothesis supported? Autonomy 2.05 .133 .04 H13a No evidence Competence 3.803 .025 .07 H13b No evidence Connection .47 .626 .03 H13c No evidence Self-affirmation 1.14 .324 .02 H13d No evidence Product liking .83 .437 .02 H13e No evidence Table 22. Customization by time MANOVA interaction results.

Study 3 Discussion

The focus of this study was to test the means by which perceived interactivity perceptions shape and influence product attitudes. As an explanatory model, the model does not fit the data. Still, a number of pathways were significant in the hypothesized direction, and the results have important implications for the CRRM and the means by which perceived interactivity and executive functioning influence product liking.

The model illustrates how important perceived interactivity is in determining product attitudes; these perceptions directly influence autonomy, competence, connection, and self-affirmation. Perceived interactivity also works indirectly through autonomy, competence, and connection to increase engagement, leading to less reactance and more favorable product liking. On a group differences level, perceptions of interactivity were higher in the edit and create conditions compared to those in the read condition.

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In addition, results indicate a lack of support for executive functioning as an exogenous predictor variable. Executive functioning (operationalized as the number of incorrect answers on the Stroop task) did not predict autonomy, competence, connection, self-affirmation, or engagement. On a group differences level, there were no significant differences in customization condition on self-reported scores of difficulty or number of incorrect answers given on the Stroop task, which suggests that there were limitations with the executive functioning measurement.

The second stage of the model predicted that autonomy, competence, connection, self-affirmation, and source credibility would predict engagement. The results for these hypothesized paths are mixed. Autonomy and self-affirmation perceptions positively predicted engagement, while competence and connection did not. There was no evidence for source credibility as an exogenous predictor of engagement.

The findings illustrate the importance of assessing autonomy and competence needs independently. Only autonomy was shown to predict engagement. On a group differences level, those in the create and edit conditions scored higher on perceptions of autonomy while individuals in the read condition scored highest on measures of competence. These findings suggest that giving users the ability to customize might lead to conflicts in need fulfillment; increased choices mean more autonomy, but also more opportunity to fail, which could decrease competence.

The results also show support for the inclusion of connection and self-affirmation in the model. Perceived interactivity predicted both connection and self-affirmation, but indirectly affected product liking only through connection. In addition, self-affirmation

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predicted engagement where competence did not. Overall the results indicate that users are placing their identities into their customized objects, creating strong bonds with their creations, and seeing reflections of their core values while customizing. The positive associations that arise as a result of connection and self-affirmation with the customized object influence engagement in ways distinct from autonomy or competence. Still, the mixed results between connection and self-affirmation suggest that it might be better to consider the two related in a stepwise fashion, wherein perceived interactivity predicts connection which predicts self-affirmation. Because self-affirmation involves perceiving a reflection of one’s core values and beliefs, it might be a prerequisite that individuals feel a sense of connection with the object first.

Finally, the next two stages of the model were significant in the hypothesized direction. Engagement was shown to predict state reactance wherein high engagement lead to less reactance, and reactance predicted product liking wherein low reactance lead to increased product liking. The results give support for the inclusion of engagement as an intermediary variable between need fulfillment and identity perceptions.

The self-affirmation manipulation was successful in that individuals who were given instructions to create or edit an advertisement to reflect their values and interests believed that the medium was more interactive, felt more competence, and felt greater connection with the advertisement as well as saw the advertisement as a reflection of their core values. Those in the high self-affirmation condition also showed higher perceptions of engagement relative to those in the low self-affirmation condition. There were no differences in self-affirmation condition on state reactance or product liking.

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Results for those who read advertisements made by those under different self-affirmation conditions also showed that when individuals wrote to reflect their own values, readers viewed those advertisements as more engaging and had a higher valenced thought-listing total. These findings have implications for message creation wherein individuals craft persuasive messages for one another (e.g., on social media). Reminding individuals to make sure their messages reflect their core values may make their messages more persuasive to others.

It was hypothesized that self-affirmation condition would interact with the customization condition, but results indicated no significant interactions. Considering the main effects for each condition, these results were surprising. It is possible that customization results in strong enough self-affirmation on its own that giving additional instructions to think about one’s core values are not enough to benefit users any further.

In a practical sense, the findings replicate results from Studies 1 and 2 and demonstrate the power of giving users the ability to customize. Where Studies 1 and 2 showed that customization of a source could lead to higher product liking, Study 3 demonstrated that customization of a message could do the same thing, despite the increased scrutiny that message customization might bring upon the persuasive message.

Individuals who created an advertisement showed the highest scores in connection and self-affirmation associated with viewing the advertisement. They also showed the highest engagement scores, saw the source as the most credible, and showed the lowest amount of psychological resistance to a persuasion attempt (seen in both valenced total thoughts listed and state reactance scores).

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Limitations

Cognitive Resource Depletion Measurement

In general, participants performed extremely well on the Stroop task. Participants averaged less than one incorrect answer over 40 words (M = .73, SD = 1.17) and completed the task in under a minute (M = 57.91, SD = 12.03). Typical tests of executive functioning are often very difficult and require strong mental effort from the participant

(e.g., submerging a hand in an ice bath for as long as possible), and it is possible that this

Stroop task was not difficult enough. The experimental setup of the task may have facilitated participants’ success. Because flashcards were shown by a researcher by hand, participants had time to reorient their attention between each card. It may have been easier to fixate on the color of the ink using peripheral vision as the card was lifted; in this way the color could be noticed before the word was processed.

The task might also have been improved by surprising participants with a color switch. Participants could have been told the nature of the task and first shown ten colors that matched with the written word (e.g., the word red written in red ink). Then, after the first ten trials the colors could be switched to mismatched ink/written word combinations.

A switch in this fashion would have created additional strain on the participant, and eliminated any effects of the training process that might have oriented participants to color without processing the word. Given that the test was dependent on reaction time, it may have been more appropriate to administer the task via a computer to both assess time to the thousandth of a decimal and to remove any unintended variation in the researcher’s administration. Finally, it may have been appropriate to ask participants who have

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finished the study about their experience with the Stroop task. It is possible some individuals used specific strategies to “beat” the task, and a thorough debriefing would have helped identify in what ways this assessment was ineffective.

Testing for executive functioning typically involves two separate mentally draining tasks; participants are given a difficult task at Time 1 and then later measured on their performance on another difficult task at Time 2 (Burkley, 2008; Inzlicht &

Schmeichel, 2012, Vohs et al., 2014). I chose the Stroop task as a dependent measure to serve as a second time point when using the customization condition as the first mentally demanding time point. It was important to pick a test that would not be overly draining on participants, as an extremely difficult task at Time 2 might affect their responses to survey items and thought-listing measurements (although this was avoided through counterbalancing of the thought-listing and Stroop task) independently of the customization condition. Finally, research that previously demonstrated a decrease in executive functioning as a result of making many choices bombarded participants with hundreds of choices as their manipulation (Vohs et al., 2014). It is possible that the amount of choices participants faced was not enough to deplete executive functioning.

Even though participants in the create or edit conditions have nearly unlimited options for what they choose to write, they may not have perceived each word as an individual choice. Ultimately, it may have been too difficult to attempt to measure executive functioning depletion in addition to the many other perceptions and dependent measures.

It is also possible that no customization condition was sufficiently draining (and in comparison with typical tasks used to assess executive functioning, editing, creating,

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or reading an advertisement is far easier), or that a more sensitive dependent measure was required in order to test the smaller effects stemming from the customization condition.

As such, it is difficult to make meaningful inferences about the role of executive functioning resources in response in the customization process.

In the future, a stand-alone study assessing the role of executive functioning depletion may be most beneficial. This study may manipulate customization conditions and then focus entirely on elements of resource depletion (such as shifts in attention or changes in willpower). It may also be beneficial to examine the role of customization in restoration of depleted resources. This study has demonstrated the powerful psychological benefits of customization. A study that gives individuals a depleting task first (e.g., the Stroop task, or submerging a hand in an ice bath) and then allows them to customize may demonstrate how these psychological variables benefit recovery.

Research in this area would also give insight into individuals using interactive media

(e.g., playing video games) as a way to recover from mentally draining tasks (e.g., after a hard day at work). Some research has been done along these lines and indicates that individuals can repair negative moods through interactive media (Bowman & Tamborini,

2012, 2013; Rieger, Frischlich, Wulf, Bente, & Kneer, 2014) despite the increase in cognitive effort that these media may require in comparison to more passive media such as television or radio.

Engagement Operationalization

Engagement was measured based on four items that assessed whether the participant “felt engaged,” or “felt fully invested” in the advertisement task. Although

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these perceptions were statistically significant predictors of state reactance, ultimately this operationalization falls short of the broader conceptualization of engagement used in media research. Engagement is typically conceptualized as a mix of elaboration and affect and Study 3’s measurement fails to adequately represent those concepts. As a result, determining its role in the process of customization on reception to persuasive messages is difficult. The items are ambiguous in their regard to the advertisement assessment task, or completing the experiment as a whole. Future research should further elaborate on this concept and make it conceptually distinct from related elements of connection, self-affirmation, and attention used in the study.

Observed Variable Model Versus a True Latent Variable Model

It is generally recommended that users of SEM attempt to use model that uses latent variables in order to reduce measurement error (Holbert & Stephenson, 2002).

Study 3 used an observed variable model in order to create the greatest amount of parsimony and to assess model fit in a simple way. The use of an observed variable model does restrict the findings to be limited to mean scores of variables, and requires selection between certain variables (e.g., choosing product liking mean score over of purchase intention instead of using both). A latent variable model would allow for each individual indicator (e.g., all five items for product liking and all three items for purchase intention) to construct a latent variable. A true latent variable model was created with all the key indicators for both the original hypothesized model and the modified model, but this version showed significantly poorer model fit. For most variables the latent model

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did not offer much additional explanation, as the reliability shown in the scales was already very high and the mean observed scores could be just as descriptive.

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Chapter 8: General Findings & Future Directions

Summary of Findings

The goal of these three studies was hypothesize and test the underlying process by which interactive technology (here, specifically tested as customization) could affect attitudes towards a persuasive message. Studies 1 and 2 were designed to test the possibility that customization could affect persuasive outcomes by means of reducing resistance to a persuasive message, and Study 3 tested an overall model hypothesized to explain the process by which customization can improve product attitudes. Taken together, the findings from these studies provide ample evidence for the benefits of customization, and begin to illustrate the means by which customization can affect one’s attitudes towards a persuasive message.

The first two studies allowed participants to customize the source of a persuasive message. It was hypothesized that customizing a persuasive source would lead to an increase in positive feelings and psychological need fulfillment, and by those means would affect attitudes towards the product in the source’s message. Study 1 found that individuals who were able to customize the appearance of a persuasive source had higher preference for the product that the persuasive source was selling. In this case, customizers liked the product better than those who did not get to customize the persuasive source. In addition, Study 1 also illustrated why customizers might like the persuasive source’s 165

message better. Being allowed to customize increased users’ intrinsic motivation (i.e., they felt more autonomous and competent, they enjoyed the task more, and they felt less tense). It is these increases in intrinsic motivation that ultimately mediated the relationship between customization and product liking. Thus, initial support indicated that customization in itself can be beneficial and that this occurs in part due to increases in intrinsic motivation.

Study 2 was designed to improve, expand, and replicate findings from Study 1 in a new context. Instead of a interacting with a persuasive source in a virtual world, participants saw a two-dimensional avatar representing the source placed next to text of the source’s persuasive speech. Study 2 used three conditions wherein participants were either assigned an avatar representing the source (zero choices), were asked to choose one out of four potential avatars (single choice), or were asked to create one from scratch

(multiple choices). In addition, Study 2 added the concept of identity (measured as similarity to the avatar) as an additional explanatory variable to intrinsic motivation.

Study 2 also used direct measures of reactance (both state reactance as well as counterarguing). This study found that as customization choices increased, state reactance and counterarguing decreased. Study 2 helped demonstrate that having customization options can increase perceptions of agency and can create an important sense of identity with the customized avatar, boosting a user’s connection to the source and what the source has to say. Again, this gives further support to the viability of using customization to affect reception of a persuasive message; even in a very minimal text-only

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environment with a two-dimensional avatar, the benefits of customization indirectly increased product attitudes.

Taken together, Studies 1 and 2 establish that source customization is a viable means for reducing resistance to a persuasive message and increasing attitudes toward a product in a persuasive message. The studies also illustrate how both need fulfillment and perceptions of identity are important intermediary variables in this process.

The first two studies laid the foundation for the test of the CRRM. Study 3 was designed to take lessons learned from the methodology of the first two studies and test a model that could comprehensively account for the process by which customization affected product attitudes by means of reducing resistance. The first two studies illustrate the indirect influence of customization wherein customization of a source could affect attitudes towards a product in the source’s message. Still, it is possible that customization of a source is successful in reducing resistance due to distracting users from the persuasive message. To establish that customization can be successful despite the full attention of a user, Study 3 allowed participants to read, edit, or create a persuasive message directly.

Study 3 gave users a company briefing that contained information about a company, its newest product, and three important points that the company wished to communicate about the product. Participants then either created an advertisement based on those goals, or read or edited an existing advertisement. The results again highlight the benefits of customization: individuals who edited or created the advertisement scored higher in autonomy, connection to the advertisement, engagement, product liking, and

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rated the source (i.e., the company) as more credible. These participants also showed the lowest levels of state reactance and had the lowest valenced totals for counterargument thoughts listed, demonstrating that customization can have a beneficial effect even when participants theoretically should be placing considerable scrutiny on the persuasive message. Results also indicate that perceptions of identity (in this study measured as both connection to the advertisement and self-affirmation perceptions) as well as need fulfillment (in this study, autonomy and competence perceptions) are strongly influenced by perceptions of interactivity, and in turn can affect engagement with the message. This study illustrates that self-affirmation and autonomy fulfillment are strong predictors of engagement, which then influences both state reactance and counterarguments, which ultimately influence product liking. These findings suggest that customization can increase favorable product attitudes by means of reducing or eliminating resistance to a persuasive attempt.

Taken together, all three studies advance our understanding of interactive media and how they shape attitudes toward a persuasive message. These studies illustrate that customization is a very powerful tool in reducing psychological reactance to persuasive attempts, and can be an additional tool for persuaders to consider when looking to circumvent strongly established resistance toward traditional persuasive messages.

Theoretical Implications

These three studies have a number of important theoretical implications. The focus of the dissertation was to understand how customization can affect the persuasive process. To do so, a model that hypothesized the process by which customizing an object

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affected resistance and product attitudes was created (the CRRM). In order to create the

CRRM, existing models for both persuasion and interactive media effects were assessed and revised.

From literature on technology, affordances, and interactivity, Sundar et al.’s

(2015) theory of interactive media effects was chosen as the starting point for building the CRRM. The TIME is one of the first attempts to bring together all of the variables that influence one’s attitudes as a result of engaging with interactive media, yet it remains untested as a whole. The TIME is meant to fit all interactive media and is not specific to the persuasion process. The CRRM modified the TIME by adding executive functioning as a key predictor variable, making an argument for the use of perceived interactivity over structural interactivity as a key predictor variable, changing the TIME’s intermediary variables to need fulfillment and identity perceptions, and adding reactance as a consideration for the persuasion context. Although the CRRM was not meant to be a test of the TIME’s propositions, a number of hypothesized relationships found in both models were tested. As such, results from testing the CRRM have implications for the

TIME as a larger model for interactive media effects.

From literature on persuasion, reactance, and entertainment media, Moyer-Gusé’s

(2008) entertainment overcoming resistance model (EORM) was chosen as a starting point for understanding the ways in which media can affect resistance to persuasive attempts. Where the EORM gave evidence for the process by which entertainment narratives can overcome psychological reactance, the CRRM worked to demonstrate the means by which customization of a persuasive source or message could reduce

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psychological reactance. The EORM suggested that identification with characters and engagement with the narrative would distract individuals from an embedded persuasive message. Building on these concepts in interactive media, the CRRM hypothesized that perceptions of users’ identity and need fulfillment would increase engagement with the medium, leading to favorable attitudes of the message within. The CRRM specifically focused on customization as a means to reduce reactance. Focusing on customization would move interactive persuasion research beyond advergames and in-game advertising to demonstrate how using the most unique aspect of interactive media—user control— could also aid in the persuasive process. Success using customization would give persuasive message designers another means by which to reduce resistance to a persuasive attempt.

Implications for TIME and a Comprehensive Model of Interactive Media Effects

Although the CRRM was not meant to be a direct test of the propositions in the

TIME, the two share a number of hypothesized relationships. The TIME is meant to explain how interactive media affect attitudes, knowledge, and behavior in a broad explanatory way. Because the TIME has not been tested as a whole, the CRRM represents a test of some interactive effects on specific attitudes (i.e., those related to persuasion). Although support for the CRRM as a comprehensive model was not found, the results for individual path and indirect path analysis make a strong case for a number of intermediary, explanatory variables that can be used to build on the paths proposed in the TIME. The CRRM differs from the TIME in four key ways.

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First, the CRRM makes an argument for placing increased emphasis on perceptions of interactivity, rather than the structural affordances of interactive media.

Conceptually, assessing perceived affordances removes a number of problems associated with a focus on structural affordances. By placing the focus on structural affordances, an assumption is made by the researcher that these affordances will be seen as interactive by users and in the same way between users. Individual differences on a number of factors

(e.g., age, experience with technology) should strongly influence their perceptions of a structural affordance, and the use of perceived interactivity as a predictor variable would account for these variations. These studies were ill-equipped to empirically validate the use of perceived interactivity in place of the customization condition in the CRRM, but the variations between create and edit conditions in Study 3 help illustrate how similar prompts can result in widely different perceptions from individuals. Future research should work to more directly empirically assess whether perceived interactivity can stand as a better predictor variable. This research posits that researchers ought to focus (through rigorous pre-testing) on creating a minimum threshold of structural interactivity, wherein affordances meet the criteria of active control, two-way communication, and synchronicity in a way that is recognizable by the user. Once this threshold is met, to still account for individual differences on a number of factors, perceived interactivity should be strongly considered as the predictor variable of choice in a model that assesses interactive media effects. It may also be worth considering manipulations of the illusion of structural interactivity. It is possible that giving individuals the instructions that a medium is interactive when it is not may still influence user perceptions of interactivity,

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which would give additional support for the conceptual use of perceptions over structural affordances.

Second, the CRRM suggests an alternative affordance framework to use in place of Sundar’s MAIN model (Kalyanaraman & Sundar, 2006; Sundar, 2004; Sundar, 2008;

Sundar & Limperos, 2013). The four MAIN affordances, modality, agency, interactivity, and navigability, have considerable conceptual overlap. By using Liu and Shrum’s (2002) conceptualization of interactive affordances of active control, two-way communication, and synchronicity I eliminate conceptual overlap found in the MAIN and provide an alternative framework for which to assess interactive media effects. The MAIN model and the three affordances proposed by Liu and Shrum were not directly compared, as the

MAIN affordances were not manipulated or assessed. Thus the results cannot determine which set of affordances is more useful for model building. However, Study 3 does indicate that Liu and Shrum’s (2002) affordances are significant predictors of autonomy, competence, connection, and self-affirmation as well as indirectly affect reactance and product attitudes. Thus, this study demonstrates that the combination of active control, two-way communication, and synchronicity affordances is at least a viable alternative to the MAIN framework. Future research should directly compare these affordance systems.

Third, the CRRM deviates from TIME in that the CRRM focuses only on customization as a form of interactivity, and the CRRM is limited to persuasion contexts.

Focusing the CRRM around customization was done for practical reasons; it would not be possible to account for all the different types of interactive media in three studies, and customization meets all the requirements for interactive media while allowing for

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experimental manipulation of the extent to which one can customize. In addition, focusing the studies on the persuasive process allow for the extension of research on using entertainment media to reduce reactance (Moyer-Gusé, 2008; Moyer-Gusé & Nabi,

2010). Thus, all of these findings are limited to customization and not interactivity as a whole. Both models suggest that engagement is a crucial intermediary variable that takes all of the benefits associated with increased need fulfillment or identity and causes users to more strongly focus and elaborate on the interactive medium. Findings from the

CRRM support the important placement of engagement as an intermediary between need fulfillment and identity perceptions with reactance and product attitudes. The CRRM also gives support for the TIME’s proposition of need fulfillment as an important variable for influencing engagement.

Fourth, the CRRM adds the concept of executive functioning as an important predictor variable. Due to the increased demands of user activity, interactive media should place more of a burden on the cognitive resources of the user. The lack of this variable in the TIME may be a conceptual oversight, as the determination of how interactive media affect executive functioning resources should be an area of considerable importance. Despite this importance, initial tests of executive functioning in the CRRM offered little support for executive functioning as a predictor variable, although these results may be due to limitations in the study design and the way in which executive functioning was assessed. Future research should continue to work to assess the way attention and elaboration changes during interactive media use.

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In addition, it may be worthwhile to assess one’s addition of cognitive resources

(i.e., elaboration) on the task at hand, rather than the depletion of those resources. While engaging with an interactive medium, an individual must shift focus between the medium

(e.g., using the controls, responding to feedback) and the message within it (e.g., listening to a persuasive message within a video game). For example, in Study 3, individuals were required to shift focus between typing on the keyboard and using the mouse to reading and thinking about the message. To further complicate things, it is unlikely that these two acts occur entirely independently, where one loses all focus of the message to engage with the medium or vice versa. Thus, it may be worthwhile for future research to examine the extent to which one’s elaboration on the medium and message switches or acts in tandem, rather than examining the extent to which engagement with the medium depletes resources to the point that it makes elaboration on the message difficult.

Implications for Persuasion

The findings suggest a number of important variables that mediate the relationship between perceptions of interactivity and product attitudes. Need fulfillment was shown to affect product attitudes, psychological reactance, and engagement. As individuals are given the opportunity to customize, need fulfillment was consistently shown to increase and in turn positively affect product attitudes, reduce resistance, and increase engagement. Literature on self-determination needs and intrinsic motivation indicates that giving individuals the opportunity to fulfill their needs can result in them working harder, longer, and being more satisfied with their given task (Deci & Ryan,

2000; Ryan & Deci, 2000). Put another way, need fulfillment can improve attitudes

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toward a potential behavior, and increasing need fulfillment may be a way to influence individuals to change their behavior. Yet little research has been done looking at need fulfillment and processing of a persuasive message. This lack of research makes sense, as typical mass communication persuasive messages require little activity from the recipient beyond paying attention. Interactive media create the possibility for one to engage with a message in a way that fulfills the core psychological needs for autonomy and competence. When individuals are given the ability to interact with (i.e., customize) a persuasive message, or even interact near a persuasive message (i.e., source customization), needs can be satisfied, and the benefits of that fulfillment can be applied to processing of the persuasive message.

Need fulfillment was shown to reduce psychological reactance through engagement. The empowerment that interactive media give an individual can be very satisfying, and lead to increased enjoyment of the task. Reactance is conceptualized as a motivation to regain a threatened freedom (Brehm, 1966, Brehm & Brehm 1981), and interactive media offer a means for one to receive new freedoms (e.g., the ability to make new choices or influence a new environment). Though it is beyond the scope of these studies to assess whether need fulfillment is increasing enjoyment, providing freedoms to the extent that one can replenish lost freedoms from the persuasive attempt, or a combination of both, these findings suggest that need fulfillment is a powerful way in which to reduce psychological reactance.

It should be noted that Study 3 assessed autonomy and competence as independent variables. The results indicate that these variables should be considered

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conceptually distinct and each had very different effects on engagement. Autonomy was shown to predict engagement, whereas competence was not. In addition, individuals who read the advertisement scored highest in ratings of competence, but lowest in ratings of autonomy when compared to the other two groups. These results suggest that when it comes to the use of interactive media, autonomy and competence might be in opposition to one another. Use of interactive media gives users the opportunity to make plenty of choices according to their desires, a process that should strongly increase perceptions of autonomy. However, interactive media also give users a more demanding task; users must consider following the rules of the medium, giving input, and must keeping track of the changing stimuli in front of them. This activity could give users increased opportunities to fail, which would decrease their perceptions of competence. The results still indicate that perceived interactivity works indirectly through both competence and autonomy needs to influence product liking, so both are important for consideration in the overall model. These findings are contrary to similar research conducted on interactive media and need fulfillment. One study indicated that as a video game task became more interactive, perceptions of both competence and autonomy needs increased

(Tamborini,Grizzard, Bowman, Reinecke, Lewis, & Eden, 2011). The difference in results may be due to the presence of a clear goal. In the Tamborini et al. study, participants were required to land a plane, so it was very clear if they succeeded or not. In the message creation task in Study 3, participants were required only to write an advertisement that conformed to the briefing, but it was unclear how success would be measured. Thus the presence of concrete feedback indicating success or failure of

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performance may be an important consideration when assessing need fulfillment within interactive media. Future research would do well to continue to measure these needs separately, rather than as a single need fulfillment measure. In addition, this opens opportunities for research to put these needs in conflict with one another and determine how persuasive outcomes might be affected.

In addition, a sense of identity was also demonstrated to affect engagement, reactance, and product attitudes. It should be stressed that here a sense of identity is distinct from related concepts, such as identification in literature focused on narrative persuasion. Identification has typically been conceptualized in relation to a different person or character, and involves a loss of a sense of self while stepping into another’s identity (Cohen, 2001). Interactive media instead allow for one to place their sense of self into another; instead of a loss of self, the self present in the new character or object.

Giving individuals the opportunity to customize a persuasive source that walked, talked, and thought independently from the user allowed for the user to make changes to the source that reflected the user’s identity. In this situation, the individual might experience identification with the source in addition to seeing reflections of the individuals’ identity.

In Study 2, identification may have become more difficult as the source was a static object. Yet the ability to customize the persuasive source still allowed for users to place their identity into the source. In other words, instead of thinking that a character acts similar to me, customization allows me to think that I am similar to a character because I made it. When viewing the source, users should be reminded of all the choices they have made that resulted in the source’s appearance. In this way, the source’s appearance is a

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reflection of the user. In Study 3, the potential for identification should be at its lowest, as there is no distinct separate character for the user to identify with. Yet these users still have the ability to place their identity into the customized message through the choices that they make.

The results show initial proof for the concept of placing one’s identity into the customized object. Study 2 indicated that users felt more similar to avatars that they could create. Study 3 elaborated further on identity by demonstrating that users felt more connected to the advertisements that they created. Beyond that, the customization choices users made became reflections of their own values, beliefs, and thoughts, becoming a form of self-affirmation. As such, these results demonstrate that when considering interactive media one must consider the ability for users to place a piece of their identity within the customized object. Results also show that placing a sense of identity within a customized object lead to positive persuasive outcomes by increasing engagement, reducing reactance, and indirectly increasing product attitudes.

Finally, the results for Study 2 and Study 3 indicate that it may be worthwhile to consider reactance from a dual process perspective, in spite of the significant support for the intertwined model (Quick & Stephenson, 2007; Rains, 2013; Rains & Turner, 2007).

Both studies indicate that the customization influences product attitudes particularly through cognition, measured in these studies as counterarguments. The state reactance scale assesses both affect and cognition as a self-report questionnaire, but the stand-alone

(and more direct) measure of cognitive reactance—the thought listing task—indicates that customization leads to less counterarguing which in turn creates favorable product

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attitudes. It is possible that the nature of a customization task is cognitively engaging to the point of being distracted from emotions such as anger, and thus increased emphasis is placed on the cognitive aspect of counterarguing. Perhaps all of the positive psychological benefits stemming from the customization process are enough to cancel out and negative effects as a result of anger or annoyance. Future research on customization should further explore the role of anger and cognition in the customization process and it may be worth considering them as two distinct processes in the customization context.

The EORM demonstrates that receiving a persuasive message within a narrative can reduce reactance by means of distracting individuals from the persuasive message and increasing identification with characters and enjoyment of the story to the point that counterargument becomes more difficult and angry affect is reduced. The CRRM indicates that in interactive media contexts, need fulfillment and a sense of identity are two means by which reactance can be reduced by influencing it indirectly through engagement. Thus, these findings indicate an additional means by which to circumvent reactance to a persuasive message. At this point, it cannot be said whether use of a narrative or use of interactive media is more effective at reducing resistance. Future research into reactance reduction would do well to compare both narrative, non-narrative, interactive, and non-interactive contexts.

Practical Implications

Equivalence of Customization Conditions

From a methodological standpoint, the three studies highlight the difficulty of manipulating interactive media. When comparing having choice with not having any

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choices, it is difficult to say that participants are having comparable experiences. For example, it is possible that individuals in the read condition in Study 3 had a different experience to those in edit or create conditions such that meaningful comparison between the three groups is impossible. Specifically, participants in the read condition spent much less time engaging with the advertisement and product. Where participants in the edit and create conditions had 10 minutes to work with the advertisement, individuals in the read condition were given only five minutes to read and consider the advertisement. This difference in times was deliberate. In Study 1, participants in the customize and view- only conditions were given equal time to engage with the source’s avatar. Both groups either customized or watched the customization of an avatar for seven minutes. We found differences between these groups in their product attitudes where customizers liked the product more than viewers. However, individuals in the view-only condition continually mentioned during the debriefing that they did enjoy the task at all. It was difficult to tell whether customizers liked the product more because of the avatar creation, or if viewers liked the product less because they had to sit through a boring 7-minute avatar creation video. Ultimately it was determined that it would be better to mitigate the boredom problem by giving participants in the assigned avatar condition (Study 2) or read condition (Study 3) less time than those in the create or edit conditions, having already established that equivalent time conditions still resulted in a significant difference in product attitudes in Study 1.

Condition equivalence is a problem typical to studies manipulating aspects of interactivity. For example, it is difficult to compare playing a video game with watching a

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video because so many elements differ between the two conditions. There are drawbacks to all possibilities of creating equivalence. One could find a safari-themed video game and a safari-themed movie and have participants engage with each for 30 minutes. In this case the stimuli that the video game player sees would be very different from that of the video viewer, both in quality of graphics and resolution, and in literal images; video game players could choose to interact with the giraffe but not the tiger, but viewers would watch both. One could instead record footage of the safari video game and show that to participants; in this sense both groups are seeing the same images for equivalent amounts of time (this was the path chosen for Study 1). However, in this setup individuals in the watch condition are viewing images intended for interaction and not for the sole purpose of viewing. Television and cinema go to great lengths to tailor the material to the viewers using a number of visual (e.g., engaging cuts between scenes), audio (e.g., a musical score), and writing elements (e.g., an engaging story). Although some interactive media

(especially video games) have these features, the features were still created with the intent of one interacting and viewing, not for viewers only. In manipulations of more mundane interactive footage (such as customization of an avatar) none of these engaging features are present in recorded video game play footage, and thus it is possible to run into issues of boredom or frustration from those who must watch the footage but not interact with the medium.

Ultimately it may be most beneficial to take a product created for viewers and add interactive features to it (although this creates a viewed-stimuli difference again). This approach may be particularly useful with text; a story could be written intended for a

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reader and then given interactive features in a choose-your-adventure style for interactive users. This approach is closer, but still not satisfactory, to condition equivalence. Using this method for a visual medium would be even more difficult, as it would require substantial time and financial resources to create an interactive version of a video or television show. Researchers are continuing to struggle with these decisions, and some concessions must be made with these methodologies. Ultimately, because Study 1 demonstrated that there were still clear differences between those who interacted and those who did not, I opted to eliminate the potential issue of boredom and frustration with those who did not interact in Study 2 and Study 3.

Finally, in the future it may be worthwhile to work to make the customization conditions more directly comparable. This would allow for easier analyses between conditions and may also allow for better comparison between concepts such as structural affordances versus perceived affordances. Thus, future research should perhaps consider concrete choice numbers that can be directly compared (e.g., zero, one, two, or three choice conditions). Studies could also could compare zero choices with having any choice at all. In addition, it would be possible to record participants and code the number of choices they have made (e.g., number of different features customized on an avatar, or number of choices made in an interactive narrative) during the customization process in some settings. This would make customization choices a continuous variable that could be better directly compared with other continuous dependent measures.

Implications for Persuaders

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From an advertising standpoint, these studies suggest new directions for persuasive message creators and ought to eliminate many reservations advertisers may have about placing their product or brand in users’ hands. These studies repeatedly demonstrate that the benefits of customization outweigh any potential downsides to the process. Customization satisfies important psychological needs, places a sense of identity within the customized object making users more attached and reflecting their core values, and reduces reactance. Giving users the opportunity to customize may also help persuaders to avoid many of the strongly entrenched resistances consumers have to more traditional mass communication attempts to persuade. The relative newness of the technology is one of the benefits of advertising using interactive media; users have had less time to build strong walls of resistance to these attempts. Thus, understanding the underlying process through which using an interactive advertisement can affect users’ reactance and attitudes toward the product will become increasingly important in a world where interactive technology is growing in popularity and ubiquity.

The use of customization may be the best way to persuade using the advantages of interactive media while avoiding potential pitfalls of reactance (when using advergames) or distraction (when using in-game advertising) that arise from initial attempts to combine interactive media and persuasion. Giving users the opportunity to customize an advertisement’s message or source ought to increase need fulfillment, positive affect, and create strong connection between the user and customized object. Advertisers may be hesitant, however, to give a user full control over a persuasive message (i.e., the advertisement itself). In this regard, customization of a persuasive source may offer the

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best of both worlds. Users receive all the benefits of customization while the advertisers get to keep their message intact.

Although advertisers may be hesitant to place control of their content in users’ hands, the results indicate that even message customization ultimately improves product attitudes. This effect occurs despite the increased scrutiny that users bring to the message.

Early signs indicate that advertisers have begun to experiment with the possibility of placing control in the user’s hands. For example, television-streaming site Hulu allows users to choose between three different advertisements. Although this keeps the individual message controlled, users are allowed to determine which message they see.

Lay’s Potato Chips has recently created the “Do Us a Flavor” contest, wherein users are invited to create a new chip flavor. User submissions are then voted on by other users, and Lay’s will actually create and distribute the top flavors for sale. If the new flavor is popular enough, Lay’s will make it a regular part of its product line. Here, the opportunity to completely customize the product is in users’ hands. With this control, users have created a wide range of flavors, from practical (and tasty) Sriracha to flavors such as “An actual frog” or “Regret.” Regardless of the flavor that users create, users should be experiencing from the benefits of customization. These feelings may transition over into positive feelings about Lay’s chips or about the Lay’s brand. It will also increase a strong sense of connection with Lay’s.

Future research should also consider user-empowerment attempts that go wrong, wherein a company opens itself to ridicule (e.g., “bashtagging,” Hill, 2012) by inviting users to create a message related to the brand or product. For example, McDonald’s paid

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for a spot on Twitter to ask followers to post their favorite #McDStories. Instead, users posted their #McDHorrorStories and McDonald’s had to pull the advertising campaign within two hours (Hill, 2012). It is unclear how the benefits of customization demonstrated in these studies influence individuals when individuals use the customization affordance for the sole purpose of attacking the product. These attackers should still feel a strong sense of connection with their creation, and the act of creation is need fulfilling, so it is possible that even if the goal was to attack the product that over time individuals might show more preference to the product compared to those who do not customize.

The sleeper effect in persuasion refers to the delayed persuasive impact of a message when accompanied by a discounting cue. For example, individuals who hear a persuasive message and are then told the message source is untrustworthy are initially less persuaded immediately after hearing the message than they are later in time (Kumkale & Albarracin,

2011; Pratkanis, Greenwald, Leippe, & Baumgardner, 1988). This occurs when the impact of the discounting cue leaves the mind faster than the impact of the message. It is possible that customization with the intent of attacking a persuasive message may result in a version of a sleeper effect as well. Users who take the time to create a video bashing a particular product are demonstrating strong reactance against the brand’s message. Yet the benefits of customization may still hold out over time, and as the initial anger wears off, the benefits of the customization process as well as all of the time (i.e., commitment) spent with the brand may lead to a delayed change of attitudes toward the product.

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It may also be worth considering certain types of customization tasks can be more or less reactance-inducing than others. For example, the Hulu advertisement choosing task forces viewers to stop watching their program and select an advertisement, something they do not want to be watching anyway. The customization task here is even more inconvenient than a traditional ad because no ad will play until a decision is made, and could result in an even longer delay than with a traditional advertisement.

Interruption and forced-choice tasks may increase reactance where other incentive-based approaches may not.

It is also worth considering the novelty of the customization process in these findings (Tokunaga, 2013). It is possible that individuals receive positive benefits from customization in part because it is not something they are familiar with. If these effects occur due to novelty, it is possible that as persuaders create more opportunities for source or message customization individuals will grow as resistant to these methods as they have done with traditional advertising. Despite this possibility, these studies show that individuals are receiving important psychological need fulfillment as well as viewing themselves as closer and more connected with the customized object. Individuals are constantly seeking opportunities to satisfy their needs throughout their lives (Deci &

Ryan, 2000; Ryan & Deci, 2000), so it is unlikely that they will become desensitized to media that fulfill their needs. These studies indicate that powerful, validated psychological forces are accounting for the shifts in reactance in product liking which suggests that the effects are likely attributable to more than novelty.

Future Directions

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These studies indicate that customization is beneficial in terms of reducing psychological reactance and increasing product liking. It is recommended that advertisers give users the opportunity to customize products, messages, or the brand itself. However, it is worth thinking about the practical nature of users doing this customization. For users highly interested in a product or brand, the ability to customize should be very helpful.

These are consumers who have sought out the product or brand and already have some vested interest. Thus, the opportunity to customize should help highly involved users create an even stronger bond between with the product or brand.

More attention should be given to bringing in new consumers and understanding the role of customization in creating positive product attitudes. The current studies explore what happens when we give users the ability to customize (and in an experimental setting they are essentially required to do so), but say little about how we can get users to choose to customize in the first place. For example, users with a strong connection to Nike might be very willing to go on Nike’s website and customize new shoes according to their preferences. These users should experience a stronger and more positive bond with Nike after customizing the shoes. Yet, users who are comparing between Nike, Reebok, and Adidas may not want to take the time to stop at each (or any) individual website and customize. Thus, future research needs to focus in part on what will cause users to stop and customize as well as the role of preexisting consumer involvement in this process. In this case, it may be most appropriate to consider a user’s initial involvement with the product, brand, and customization task in order to assess how involvement influences the customization process. Involvement concerns the extent to

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which an issue is of personal importance (Petty & Cacioppo, 1979). One’s initial involvement with a product could strongly influence whether or not they decide to spend the time conducting a customization task. In addition, involvement could increase in strength as a result of conducting the customization task and receiving need fulfillment and reflections of identity. Thus, future research should be sure to measure participants initial and post-experimental involvement with the product, brand, and persuasive source.

Choosing to customize represents a considerable commitment of time and effort from the user, and companies must decide the best way to incentivize users to customize.

In some cases, companies are forcing customization upon users; Hulu will not continue to the next segment of the show until a user chooses between one of three advertisements.

The Hulu approach is a less than ideal solution as it may create increased reactance to the chosen message. It is possible that giving users rewards as incentives (e.g., receiving a coupon if they take the time to customize) may be beneficial. This may have the added benefit of increasing cognitive dissonance between user and customized object. In this case, a small incentive would be most appropriate in order to facilitate dissonance between the incentive offered and the customization task.

These studies tested customization in three different contexts: a virtual world, a two-dimensional avatar with text, and text-only advertisements. Future research should also consider additional contexts to further explore the role of customization, such as in virtual reality or social networks. Advertisers have the ability to interact with consumers via social media, and it remains in question as to how these interactions shape consumer attitudes. Here the user is more limited in options for interaction (as the company can

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manage what comments are shown, or only respond to some comments) but is still able to influence the brand in some way (e.g., by asking questions or making comments).

These studies are limited in their generalizability to the larger population as they were limited to a sample of college students. It is possible that this particular group may be more apt to experience the benefits of customization as they tend to have more experience with new, interactive technology than much of the general populace. As such, these findings may be constrained by those who are familiar with using interactive technology and are comfortable customizing their experiences. Thus, future research should consider a broader range of individuals who vary in ages and experience with technology in order to truly assess the benefits of customization. In addition, it is possible that the constraints of the laboratory experiment had some effect on participants. In all three studies, participants took the study in exchange for course credit and may have spent time customizing when they would not normally choose to do so. Through cursory analyses, all participants attempted to make a persuasive ad and did not create anything offensive or counter to instructions, so it is possible participants felt watched and were on better behavior than normal. Future research should assess how individuals approach customization without direction and assess how much time is spent on the customization task, if any.

Theorizing a New Model

Based on the findings from the three studies, it may be useful to revise some of the hypothesized relationships in the CRRM. An improved model will provide new directions to pursue when continuing to study this area. These theoretical considerations

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include assessing the customization process as a reciprocal process, assessing self- affirmation has a higher order form of identity, following connection, focusing on attention resources as a moderator for perceptions of interactivity, and reconceptualizing engagement as a combination of elaboration and enjoyment (Figure 19).

A Reciprocal Model

At the core of the interactive process is a dynamic exchange of information. A message is crafted, responded to with a message, which is then again responded to. A response must be relevant to the previous message for the process to be considered interactive (Rafaeli, 1988). The first iteration of the CRRM assesses the customization process in a single direction, without accounting for the reciprocal exchange of information. The customization process is an ongoing one; as users customize their object they make decisions, implement these decisions into the medium, see the results, and make new decisions. Future choices are contingent upon their previous choices, and their connection with the object will have changed over time as the customization process occurs. Thus, it is more appropriate to consider the customization process as recursive model, wherein perceptions of interactivity influence key mediating variables and engagement, which in turn (and over time) will influence perceptions of interactivity and the mediating variables in addition to reactance. Testing a recursive model would require some methodological changes to future experiments. Specifically, multiple time points would need to be assessed to see how individuals change over time during the customization process.

Reconceptualizing Executive Functioning

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In the initial test of the CRRM, executive functioning was conceptualized as resource depletion, specifically related to self-regulation resources. The number of incorrect answers given on the Stroop task was used as the primary means of measuring this self-regulation resource depletion. Upon further consideration, it may be more appropriate to use a different measure related to executive functioning: attention.

Although it cannot be determined whether the results for executive functioning are due to the task methodology or to poor fit theoretically, from a conceptual standpoint attention may be more relevant for the customization process. The results indicate that customization improves one’s self-affirmation, which has been demonstrated to restore depleted self-regulation resources (Schmeichel & Vohs, 2009). Thus, while the choices given during the customization task may be taxing one’s self-regulation resources, the benefits of affirming one’s values may be offsetting this depletion.

Executive functioning concerns the brain’s ability to perform three subsets of skills: self-regulation, memory, and directing attention (Nathanson et al., 2014). Because self-regulation may be influenced by the self-affirmation present in the customization process, it may be most appropriate to focus on attention. In the revised version of the

CRRM, attention is hypothesized to be a moderator between perceived interactivity and the mediating variables of need fulfillment and identity. If a user gives the medium zero attention, then the medium cannot be seen as interactive or anything at all. On the other end of the spectrum, high attention should allow the user to better see the interactive features present in the medium and thus interact with perceived interactivity to influence need fulfillment and identity perceptions. In order to assess attention, eye-tracking

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measures could be used. Eye-tracking would be a relatively unobtrusive way to observe where users are looking and how they are directing their focus prior to and during the customization task.

Reconceptualizing Engagement

Engagement was conceptualized as a combination of affect and elaboration, but the initial test of the CRRM measured engagement very broadly with the task as a whole.

Future research should consider assessing engagement as a combination of affect

(conceptualized here as enjoyment) and elaboration (operationalized as self-report scores on interest and rumination on the topic). In addition, it may be appropriate to consider engagement in two ways: engagement with the medium and engagement with the message. Users may be diverting their focus between the medium and the message during the customization task. For example, in Study 3 users may have been changing their focus between writing the message and using the word processing software. For video game players, in-game advertising requires users to shift their attention between the game they are playing and the advertising messages they encounter. It is not clear how these shifts in engagement occur, but it would be worthwhile to assess user attitudes on both in order to truly determine how customization can affect the persuasive process.

Shifting the Relationship between Connection and Self-Affirmation

As initially hypothesized in the CRRM, both connection and self-affirmation perceptions were proposed as independent facets of identity that predicted engagement.

Because self-affirmation concerns seeing reflections of one’s core values and personality within the customized object, it may stand as a higher-order perception wherein

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connection is required in order for self-affirmation to occur. Thus, an improved CRRM would place connection as predicting self-affirmation in addition to engagement.

Removing Source Credibility as an Exogenous Predictor Variable

Source credibility was initially proposed as a standalone exogenous predictor variable influencing engagement. Yet it is likely that source credibility is influenced by other factors present in the model, particularly identity perceptions. For source customization (e.g., Study 1) the link should be especially apparent; as one customizes the source and develops perceptions of connection, similarity, and self-affirmation, then those perceptions should influence how the source is perceived. For message customization, the same spread of the positive feelings of connection and self-affirmation should also influence perceptions of the perceived source, which should ultimately influence engagement. In addition, source credibility perceptions should also directly influence reactance.

Considering Embodiment

Study 1 was conducted with a virtual world. Once the persuasive source was customized it walked and talked with participants inside a virtual environment.

Interactive media using virtual environments allows for users to inhabit a virtual body and move within the digital world. This ability, called embodiment, may give additional benefits to the customization process. Embodiment refers to the ability for one place the mind within a separate body (Riva & Mantovani, 2012). It involves an extension of perceptions and cognitions into another. Embodiment is a concept different from identification, in which one takes on the thoughts and goals of another. Identification

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requires a loss of a sense of self while taking on another’s attitudes, and embodiment takes a sense of self and projects it into another body (Cohen, 2001). Through this process we extend our conception of our body schema, and move through the avatar as an extension of our own body (Biocca, 2006; Taylor, 2003).

Embodiment allows us to have more direct experiences. Because the body schema is extended to the avatar, what happens to the avatar feels like it is happening to us

(Taylor, 2003). Embodiment can have a host of powerful effects. Embodying an avatar that looks differently from us can change our perceptions; embodying an attractive avatar can make us feel more attractive and confident (Yee & Bailenson, 2007; Yee, Bailenson,

& Duchenaut, 2009). Embodiment should increase our perceptions of presence, or “being there” inside a virtual environment that we can act upon and within (Lee, 2004). Higher presence has been shown to increase engagement, motivation, and enjoyment of media

(Skalski, Tamborini, Shelton, Vuncher, & Lindmark, 2011). Thus, embodiment (when applicable) should be considered as an additional mediating variable for the CRRM. It should be noted that embodiment is only one distinct example; as interactive media continue to change, other individual affordances based on the specific medium should be considered.

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Figure 19. Revised version of the CRRM.

Conclusion

Customization is only one aspect of interactive media. These studies seek to create a better understanding of interactive media processes through examining the effects of source and message customization on product attitudes. Despite being limited to customization, these findings place important light on the process through which one interacts with media in a way that changes attitudes. Although these findings are limited to their context with advertisements, it is plausible that persuasive message designers in many contexts could use customization and interactive media to their greater benefit

(e.g., health message design).

Interactive media will only become more popular as individuals gain increased opportunity to buy the software and technology that allows for interacting. It is clear that individuals have a strong demand for opportunities to customize their experiences and belongings. By working to create a model that can account for interactive media effects in general (and customization effects specifically), we can account for processes 195

occurring with existing technology and also make strong predictions about technology yet to be created. This research gives suggestions for how customizers can reduce resistance as a practical solution, but it also takes steps towards understanding the underlying process by which humans interact with technology and how that shapes their understanding, attitudes, and behavior of the world around them.

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Appendix A: Study 1 Protocol

When they walk in, check their name.

Give Consent Form. After they fill it out, go in the cubicle (shut door behind you). Based on their condition, read the following:

(Create, No warning)

“Hi! Today you are going to participate in a study that looks at the effectiveness of using virtual worlds to communicate with companies. We’ve teamed up with some representatives at Ternio, a company in Europe looking to break into the American market and are running a test at Ohio State. We’ll be setting up a virtual chat with you and Alex Walsh, a representative from the company. Right now your job is to create the avatar that Alex is going to use to talk to you. After you create it, she’ll log on and talk to you through the game.”

(Watch, No Warning)

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creation of Alex’s avatar. It will take about 10 minutes, and should help you familiarize yourself with the virtual system.”

(Create, Warning)

“Hi! Today you are going to participate in a study that looks at the effectiveness of using virtual worlds to communicate with companies. We’ve teamed up with some representatives at Ternio, a company in Europe looking to break into the American market and are running a test at Ohio State. We’ll be setting up a virtual chat with you and Alex Walsh, a representative from the company who will talk to you about buying their new product, Ternio Splash! Energy Drink. Right now your job is to create the avatar that Alex is going to use to talk to you. After you create it, she’ll log on and talk to you through the game.”

(Watch, Warning)

“Hi! Today you are going to participate in a study that looks at the effectiveness of using virtual worlds to communicate with companies. We’ve teamed up with some representatives at Ternio, a company in Europe looking to break into the American market and are running a test at Ohio State. We’ll be setting up a virtual chat with you and Alex Walsh, a representative from the company who will talk to you about buying their new product, Ternio Splash! Energy Drink. Right now your job is to watch the creation of Alex’s avatar. It will take about 10 minutes, and should help you familiarize yourself with the virtual system.”

THEN

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Here’s how the controls to this work. You’ll see in front of you a basic model of an avatar. On the right you’ll see a smaller window labeled the “Try It On Window,” and two dropdown menus. The bottom, “Available types of clothes” is the category of clothing, like shirts, pants or hats. The above menu shows you all the items in that category, like striped shirts, dress shirts and things like that. Some items let you change their color, which you can do at the top right by clicking. So if you want to give your avatar a pair of pants, you would select Pants in the second menu, and then click on the different kind of pants in the first menu.” –show them how to do this.

You can sift through the categories you like, changing the avatar in the Try It On

Window as you see fit. You can change the view in this window by scrolling the mouse wheel (which moves the avatar up or down) or by clicking on the portrait and pulling in or pushing out with the mouse to zoom.

Keep changing things in the Try It On Window, and click ACCEPT to put them on your avatar. You’ll have 10 minutes to do this, then we’ll get you and Alex all set up. After you’re done with that talk, we’ll have some questions for you about your experience.

AFTER THEY FINISH

Walk in and say:

“Ok excellent. I’m going to save your avatar and send the information over to Alex, so he can use it.”

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“I’ll set you up in a room and Alex will log on with the avatar [you made] and you can begin.”

Go to SKYPE. Call Alex Walsh.

Ring ring.

“Hello?”

“Hi Alex, this is [Your name] from Ohio State. I have a [Subject’s name] ready to go.

Are you ready to begin?”

“Absolutely! Hi [Subject’s name]! Let’s get started.”

WHEN CALL ENDS

“Now you’ll just take a short survey about your experience talking with Alex. Fill it out, and then you’re all finished when you’re done. Thanks!”

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Appendix B: Study 1 Confederate Script

Hi! I’m Alex Walsh and I am a marketing representative for Ternio brand natural energy drinks. How are you doing today?...Great! ok give me a second to get this started

– I need to get the avatar in position—there we go! Ok, Let me tell you about what we’re going today. Basically, we have this new energy drink that we think college students like you will really like. We worked out an arrangement through Ohio State to test how well we can use virtual worlds to promote it. You’ll have to bear with me a bit, because I have to read some of this straight from a script, but I’ll ask you questions during and then you’ll fill out some questionnaires we have. Does that sound ok? …Awesome.

Ok, here goes: Let me give you a bit of background information about Ternio. We are a company originally based in Italy. We originally started as a spring water bottling company, but we became very interested in energy drinks and how low calorie ones are taking off. We decided to create a natural energy drink that’s low in calories and gives you a kick without excessive levels of caffeine –more about you feeling refreshed than you’ll feel buzzed. Do you drink energy drinks? What kinds? Do you like them?

Well, we like this program we’re using now because it really gives us a lets us try marketing in a new way, and we’re hoping to use this as a launching platform to meet folks in the United States and get them excited about Ternio.

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Alright, so here’s the spiel, bear with me for a minute while I read all this:

Ok. First, the flavor. These are not your ultra-rich or super sugary energy drinks. We use all natural filtering methods with different fruits to flavor our water, and we stay away from processed chemicals and food colorings. The result is a crisp and sweet taste without overpowering your taste buds and leaving a refreshing feeling afterwards.

Next is….the calories. Because of our stance against fructose sweeteners, this is a very low calorie energy drink. We incorporate some bits of fruit into the drinks and weigh in about 35 calories per bottle. We aren’t stressing about a 0 calorie bottle and don’t think you should be either, and this keeps us from having to use artificial sweeteners like Splenda and stuff, which personally, always gives me headaches. The idea is to drink this during a game, or to perk up before or during class, or after a long run. It should leave you feeling energized and refreshed. Any questions so far?

We are also committed to keeping the price low, especially for students. We’ve always been interested in education, and Ternio has been able to negotiate a deal with

Ohio State that would allow us to place Ternio right in the vending machines and shops you have around campus. In exchange, we keep every drink below a dollar, so you can afford it and use it from day to day, whether it is to wake up for that big exam or recharge after an intramural game of flag football. You’ll be able to grab a 16oz bottle for just 95 cents. I was a college student not very long ago too, believe me, I know how much things cost.

To be honest, we aren’t here to compete with other high-sugar, high-caffeine energy drinks. Ternio probably won’t be able to keep you up for an all-nighter. But we

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can guarantee that you’ll feel better, more refreshed and ready to go in the mornings or during workouts, and that’s without all the sugar and calories you get from traditional sports drinks.

Hmm, where were we? We stick to using all natural, fresh fruits, vegetables and waters in our drink lineup, and you can look forward to some delicious flavors like

Banana-Mango, Cherry Splash, and Orange-Kiwi!

Ternio hopes to launch on the Ohio State campus in the next few months, and we really hope you’ll keep an eye out for our drinks when you’re next thirsty or walking by a vending machine. Remember: Ternio: refreshing taste for an affordable price.

That’s it! Thank you so much for letting me talk to you today! Do you have any questions about anything? You were great to talk to, thanks for being so patient (I know how these things can be on your end). Remember, I’m Alex Walsh and [RA] can give you my email if you have any other questions.

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Appendix C: Study 1 Measures

All statements were answered on a 7-point Likert scale ranging from 1(strongly disagree) to 7 (strongly agree)

Intrinsic Motivation Inventory (Ryan, Koestner, & Deci, 1991)

1. While I was working on the task I was thinking about how much I enjoyed it.

2. I did not feel at all nervous about doing the task.

3. I felt that it was my choice to do the task.

4. I think I am pretty good at this task.

5. I found the task very interesting.

6. I felt tense while doing the task.

7. I think I did pretty well at this activity, compared to other students.

8. Doing the task was fun.

9. I felt relaxed while doing the task.

10. I enjoyed doing the task very much.

11. I didn’t really have a choice about doing the task.

12. I am satisfied with my performance at this task.

13. I was anxious while doing the task.

14. I though the task was very boring.

15. I felt like I was doing what I wanted to do while I was working on the task. 216

16. I felt pretty skilled at this task.

17. I thought the task was very interesting.

18. I felt pressured while doing the task.

19. I felt like I had to do the task.

20. I would describe the task as very enjoyable.

21. I did the task because I had no choice.

22. After working at this task for a while, I felt pretty competent.

Scoring information. Begin by reverse scoring items # 2, 9, 11, 14, 19, 21.

Interest/enjoyment: 1, 5, 8, 10, 14(R), 17, 20

Perceived competence: 4, 7, 12, 16, 22

Perceived choice: 3, 11(R), 15, 19(R), 21(R)

Pressure/tension: 2(R), 6, 9(R), 13, 18

Product Liking

1. I like Ternio energy drinks.

2. I think Ternio energy drinks sound like a good product

3. I want to hear more about Ternio energy drinks

4. I would like to see Ternio on campus

Purchase Intentions

1. I would buy Ternio energy drinks

2. I was convinced by the speech to buy Ternio energy drinks

3. I would recommend Ternio energy drinks to a friend or family member

About the Confederate

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1. I liked Alex, the representative from Ternio.

2. I felt like I was talking with a real representative from Ternio.

3. I think Alex, the Ternio representative, was controlled by a real person.

4. I think Alex was controlled by a real person, but probably not a representative.

5. I think Alex wasn’t a real person; rather the avatar was controlled by a computer

program.

About how many energy drinks do you drink each week?

Have you used the virtual environment Moove before? (Yes/No).

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Appendix D: Study 2 Protocol

Seat the participants in front of the computer. The consent form should be on the screen.

Ask them to take a minute to read and sign the consent form, and you’ll get started once everyone is finished. Wait until everyone has finished with this, then begin based on the current condition they are in.

a. Make sure to bring up the next appropriate screen (either assigned,

selection, or creation for avatars)

To everyone, say: “Thanks for coming to our study. Today we are interested in avatars, which are digital representations of people. In a short while, you are going to read some text written by another person, with a picture of that person’s avatar next to the text.”

Condition 1 (assigned)

Say: “As you can see, this is the avatar of the person who has written the text. Take two minutes to look it over and think about it.”

When the time is up, ask them to have a seat at the table and start them on the filler task.

“While I get this set up, we would like to take this chance to get to know you better.

Please write down the things you did yesterday, starting in the morning and ending in the evening.”

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“Now I’ll show you the text with the writer’s avatar. Your job is to carefully read the text and think about it. We’ll give you about 5 minutes to carefully read the text as you will be asked specific questions about it later [+ reactance condition instructions]. Once that’s finished, you’ll complete a brief online survey asking about the avatar and the text that you have read.”

When the reading time is up, direct them back to the table for the thought-listing task.

Say “Now we would like to get your impressions about the text that you just read. Please write down any thoughts you had about the product in the text you just read. Feel free to write as much as you wish.”

Then direct participants to the online survey.

When they are finished, give them their thought-listing paper and a writing utensil. Say

“You are almost finished. For your last task, I’d like you to go through the thoughts you have listed about the product and place a + next to ones you wrote that are positive about the product, a – next to ones that are negative about the product, a 0 if the thought is neutral or you can’t decide.”

Condition 2 (selection)

Say: “In this case, you get to choose what that person’s avatar will look like out of the following selections. Take two minutes to carefully look at each avatar and select the one

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that you think would be best to represent the person who wrote the text that you will read.”

When they have a selection, go to each computer and ask “Which have you selected?”

Highlight it on the computer, then direct them to sit at the table. Once everyone is seated at the table, get them started on the filler task.

“While I get this set up, we would like to take this chance to get to know you better.

Please write down the things you did yesterday, starting in the morning and ending in the evening.”

At this point, copy each picture into the PowerPoint in the appropriate spaces. Then collect their writing samples, and direct them back to the computer.

“Now you will read the written text next to the avatar you have chosen to represent the writer. Please take your time to carefully read the text, as you will be asked specific questions about it later [+ reactance condition instructions]. You will have 5 minutes to read the text. Once five minutes has passed, I’ll open up the surveys for you.”

When the reading time is up, direct them back to the table for the thought-listing task.

Say “Now we would like to get your impressions about the text that you just read. Please

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write down any thoughts you had about the product in the text you just read. Feel free to write as much as you wish.”

Then direct participants to the online survey.

When they are finished, give them their thought-listing paper and a writing utensil. Say

Condition 3 (create)

Say: “In this case, you get to create the writer’s avatar. Think of it as giving them a face.

You are free to create whatever kind of avatar you like to represent the writer. As you can see, the page open in front of you features an avatar creation system. In it you can customize the writer’s hair, eyes, facial features and colors. At the top you’ll see options for all sorts of customization, and you’ll see what the avatar looks like in the picture on the left. Take about 5 minutes to carefully customize the avatar. When five minutes are up, I’ll stop everyone and move you on to the next task.

When the time is up, ask them to have a seat at the table and start them on the filler task.

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“While I get this set up, we would like to take this chance to get to know you better.

Please write down the things you did yesterday, starting in the morning and ending in the evening.”

At this point, copy each picture into the PowerPoint in the appropriate spaces. Then collect their writing samples, and direct them back to the computer.

“Now you will read the written text next to the avatar you have created to represent the writer. Please take your time to carefully read the text, as you will be asked specific questions about it later [+ reactance condition instructions]. You will have 5 minutes to read the text. Once five minutes has passed, I’ll open up the surveys for you.”

When the reading time is up, direct them back to the table for the thought-listing task.

Then direct participants to the online survey.

When they are finished, give them their thought-listing paper and a writing utensil. Say

“You are almost finished. For your last task, I’d like you to go through the thoughts you have listed about the product and place a + next to ones you wrote that are positive about

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the product, a – next to ones that are negative about the product, a 0 if the thought is neutral or you can’t decide.”

Condition 4 (low reactance)

Say nothing.

Condition 5 (high reactance)

Say: “The text you will be reading has been pulled from a marketing company that is working on ad copy to get college students like you to buy their products. You’ll be reading a text concerning a specific product that is made to convince you to buy the product.”

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Appendix E: Study 2 Measures

Thought-Listing Procedure

In the space below, list ten thoughts you had about the product while reading the advertisement

(after) – Now, go back through the thoughts that you have written down. Write a + if you think your thought about the advertisement is positive. Write a – if you think it is negative, or a 0 if you think it is neutral about the ad.

State Reactance Scale

Perceived threat to choice (Gardner, 2010; Quick, 2011)

1. The advertisement threatened my freedom to choose

2. The advertisement tried to make a decision for me

3. The advertisement tried to manipulate me

4. The advertisement tried to persuade me

Participants rated their agreement on seven-point Likert scales ranging from 1 = Strongly disagree to 7 = Strongly agree.

Counter-arguing

1. Did you criticize the advertisement you just saw while you were reading it?

2. Did you think of points that went against what was being said while you were

reading the advertisement? 225

3. While reading the advertisement, were you skeptical of what was being said?

Participants rated their agreement on seven-point scales ranging from 1 = No, not at all to

7 = Yes, very much so.

Cognitive appraisal

 The advertisement was pleasant (valence)

 The advertisement got in the way of what I wanted (obstacle, reverse coded)

 The advertisement was reasonable (legitimacy)

 The advertisement was fair (legitimacy)

Participants rated their agreement on seven-point Likert scales ranging from 1 = Strongly disagree to 7 = Strongly agree.

Anger

To what extent did this advertisement make you feel ...

1. irritated

2. angry

3. annoyed

Participants rated their response on seven-point scales ranging from 1 = Not at all to 7

= Very strongly.

Similarity

1. Overall, how similar are you to the avatar?

2. The avatar I made reflects who I am.

3. The avatar I made reflects my values.

4. I think the avatar I made is very similar to me.

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Agency

1. I believed it was easy to customize/choose/select the avatar.

2. I felt like the interface to customize/choose/select the avatar was rigid and

inflexible.

3. I felt like I could adapt the avatar to my personal taste.

4. I felt in charge of how I wanted to customize/choose/select the avatar.

5. I felt like I was free in how I wanted to customize/choose/select the avatar.

6. I felt I was able to make different choices when customizing/choose/select the

avatar.

7. I felt like I was able to influence/choose/select/customize how the avatar looked.

8. I felt like I was able to influence/choose/select/customize what the avatar said.

Liking

1. On a scale of 1 – 7, with one being strongly disagree and seven strongly agree,

please rate the degree to which you agree or disagree with the following

statements:

2. I liked [the product].

3. I think [the product] sounds like a good product.

4. I would want to hear more about [the product].

5. I would recommend [the product] to a friend or family member.

6. I liked the ad about [the product].

Purchase Intention

1. I would buy [the product].

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2. I was convinced by the speech to buy [the product].

3. If I saw [the product] in the grocery store, I would buy one.

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Appendix F: Study 2 Stimuli

Doublesip – Low Reactance

Hi, I am a marketing representative who is going to tell you about our newest product, the advanced beverage bottle the DoubleSip.

I think we’ve all been there before – it’s the morning, you’re getting ready for class and you’re trying to decide what to pack with you to get you through the day. You could take coffee, which will be great in the morning for waking you up, but it’s going to get cold over the course of the day and you definitely won’t want it later. Or you can take water, or a refreshing sports drink, but it’s cold outside and that isn’t going to help you wake up.

If you’re lucky, you pick one and the weather cooperates and you can get through half the day. If you aren’t, you end up tired, or drinking cold coffee or something else you did not want.

So I want to tell you all about our latest product. We put a lot of a time and effort into figuring out the problems that college students have and work hard on them to get rid of them or make them more manageable. We keep hearing, time and time again, that college students like you want options and aren’t totally satisfied with your typical beverage container. So we think that our newest product, the DoubleSip bottle, would be perfect for you. 229

The DoubleSip is a beverage bottle with two separate containers. Both are heavily insulated, so it is easy to keep hot drinks hot on one side and cold drinks cold on the other. Both containers feed into a single nozzle at the top, with an easy to use switch that flips between one container and the other. This will let you mix and match your drink preferences in any way you wish, allowing for the maximum amount of flexibility for the most amount of time. Keep one free to refill with water as you go about your day, while your coffee stays hot in the other. Or mix and match soothing and energy teas depending on what situation you might need.

The DoubleSip is a very practical way to give you the most amount of flexibility to meet your needs. It has all the benefits of other beverage containers, including excellent insulation, durable parts, easy clip-on hooks to attach to your backpack or clothing, and comes in a variety of colors and patterns that you can choose to match your own style.

This is the best, most efficient, flexible way to manage all your thirst needs. The

DoubleSip is affordable and is always there when you need it. So if you want to have a choice between drinks to best plan for your day, consider the DoubleSip.

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Doublesip – High Reactance

Hi, I am a marketing representative who is going to tell you about our newest product, the advanced beverage bottle the DoubleSip. There’s no arguing with this, I can guarantee that after you hear this speech, you will buy this product.

If you’re lucky, you pick one and the weather cooperates and you can get through half the day. If you aren’t, you end up tired, or drinking cold coffee or something else you did not want. You don’t want that to happen, so you’ll have to buy the DoubleSip!

So I want to tell you all about our latest product. You have to listen to me, because I’m the most qualified person to talk about this . We put a lot of a time and effort into figuring out the problems that college students have and work hard on them to get rid of them or make them more manageable. We keep hearing, time and time again, that college students like you want options and aren’t totally satisfied with your typical beverage container. So we think that our newest product, the DoubleSip bottle, would be perfect for you.

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Now you’re young, so I’ll explain this slowly. The DoubleSip is a very practical way to give you the most amount of flexibility to meet your needs. It has all the benefits of other beverage containers, including excellent insulation, durable parts, easy clip-on hooks to attach to your backpack or clothing, and comes in a variety of colors and patterns that you can choose to match your own style.

Everyone who listens to my speech ends up agreeing with me. This is the best, most efficient, flexible way to manage all your thirst needs. The DoubleSip is affordable and is always there when you need it. So if you want to have a choice between drinks to best plan for your day, consider the DoubleSip. There’s no other option!

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OrganizeMe – Low Reactance

Hi, I am a marketing representative who is going to tell you about our newest product, the mobile phone application Organize Me.

I think we’ve all been there – you wake up happy, ready to go about your day only to realize in a panic that you have an assignment due that day that you completely forgot about. If you’re lucky, your teacher will give you a little extra time to turn it in and you happen to have the time in your busy schedule to fit in the work. If you aren’t, your whole week is ruined and this could end up even seriously harming your GPA.

So I want to tell you all about our latest product. We spend a lot of time and effort into figuring out the problems that college students have and working to get rid of them or make them more manageable. We keep hearing, time and time again, that time management and keeping assignments organized and on track is a huge problem and stressor for a college student. So we think that our app Organize Me would be perfect for a busy college student like you.

Organize Me is a mobile phone calendar application that syncs with your university’s class schedule and course syllabi. Other calendar apps can connect let you know what time your classes are, but only ours allows you to input PDF or word documents of your course syllabi and it will automatically find your assignments and upload them to your calendar.

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Then, Organize Me will send you notifications a week, three days, and a day before any assignment is due, or you can customize it to your own preferences. Organize Me will run in the background so its one less thing you have to worry about. It also has all the functionality of a standard calendar app – you can create reminders, set meetings, and share your calendar with friends or family. With Organize Me, you’ll never miss an assignment again!

This is the most efficient, easiest way to keep track of all your assignments. It is affordable, and always there when you need it. So if you want to keep your life on track and be mindful of all your assignments, consider Organize Me.

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OrganizeMe – High Reactance

Hi, I am a marketing representative who is going to tell you about our newest product, the mobile phone application Organize Me. There’s no arguing with this, I can guarantee that after you hear this speech, you will buy this product.

So I want to tell you all about our latest product. You have to listen to me, because I’m the most qualified person to talk about this. We spend a lot of time and effort into figuring out the problems that college students have and working to get rid of them or make them more manageable. We keep hearing, time and time again, that time management and keeping assignments organized and on track is a huge problem and stressor for a college student. So we think that our app Organize Me would be perfect a busy college student like you.

Organize Me is a mobile phone calendar application that syncs with your university’s class schedule and course syllabi. Other calendar apps can connect let you know what

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time your classes are, but only ours allows you to input PDF or word documents of your course syllabi and it will automatically find your assignments and upload them to your calendar.

Now you’re young, so I’ll explain this slowly. Organize Me will send you notifications a week, three days, and a day before any assignment is due, or you can customize it to your own preferences. Organize Me will run in the background so its one less thing you have to worry about. It also has all the functionality of a standard calendar app – you can create reminders, set meetings, and share your calendar with friends or family. With

Organize Me, you’ll never miss an assignment again!

Everyone who listens to my speech ends up agreeing with me. This is the most efficient, easiest way to keep track of all your assignments. It is affordable, and always there when you need it. So if you want to keep your life on track and be mindful of all your assignments, consider Organize Me. There’s no other option!

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Quikwrap – Low Reactance

Hi! I am a marketing representative who is going to tell you about our newest product, the book and technology Quikwrap.

I think we’ve all been there – your alarm clock doesn’t go off and you wake up in a panic and have to run to class. In your hurry you forgot to check the weather, and two minutes out the door it starts to pour down rain. And you didn’t even think about grabbing an umbrella! If you’re lucky, all those expensive textbooks and electronics you have in your pocket or backpack won’t get soaked and you’ll still make it to class in time.

If you’re not so lucky, the books could get wet and the electronics get ruined, causing you hundreds of dollars in replacement fees. Backpacks aren’t perfect, and neither are pockets. Some water is going to get through.

So I want to tell you about our latest product. We spend a lot of time and effort into making the best water resistant gear for all walks of life. And we think our Quikwrap would be perfect for a college student like you in a hurry.

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your back in a convenient and completely water resistant covering. You can throw your pocket stuff in the bag too to cover all your bases.

This is the fastest, safest way to keep your stuff from getting wet. Many backpacks are not designed to be water resistant, and can develop holes over time. Umbrellas are nice, but they’re designed to keep your head, not your stuff, from getting wet. How many times have you had water pour off an umbrella all over your backpack? In addition, umbrellas are bulky, easy to lose, and annoying to deal with. The Quikwrap is small, always attached to your bag, deploys quickly, and keeps all your stuff safe.

It is affordable, and always there when you need it. So if you want to keep your books and electronic safe from rain or snow when you are in a hurry, consider the Quikwrap.

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Quickwrap – High Reactance

Hi! I am a marketing representative who is going to tell you about our newest product, the book and technology Quikwrap. There’s no arguing with this, I can guarantee that after you hear this speech, you will buy this product.

So I want to tell you about our latest product. You have to listen to me, because I’m the most qualified person to talk about this. We spend a lot of time and effort into making the best water resistant gear for all walks of life. And we think our Quikwrap would be perfect for a college student like you in a hurry.

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The Quikwrap comes in a small keychain you can attach to your backpack or carrying bag. If rain comes, you pull the tab and stretch a water resistant sheet over your things, and click it back into the keychain. It takes less than 3 seconds to do, and it will wrap your back in a convenient and completely water resistant covering. You can throw your pocket stuff in the bag too to cover all your bases.

Now you’re young, so I’ll explain this slowly. This is the fastest, safest way to keep your stuff from getting wet. Many backpacks are not designed to be water resistant, and can develop holes over time. Umbrellas are nice, but they’re designed to keep your head, not your stuff, from getting wet. How many times have you had water pour off an umbrella all over your backpack? In addition, umbrellas are bulky, easy to lose, and annoying to deal with. The Quikwrap is small, always attached to your bag, deploys quickly, and keeps all your stuff safe.

Everyone who listens to my speech ends up agreeing with me. It is affordable, and always there when you need it. So if you want to keep your books and electronic safe from rain or snow when you are in a hurry, consider the Quikwrap. There’s no other option!

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Appendix G: Study 2 Avatar with Text

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Appendix H: Study 3 Protocol

Participants will enter the lab and be given a consent form. At this point they will be randomly assigned into one of seven possible cells: appearance-only, high self- affirmation; appearance-only, low self-affirmation, full customization, high self- affirmation; full customization, low self-affirmation; content-only, high self-affirmation, content-only, low self-affirmation; and a control group.

All participants will be told: “Today you will be doing a number of different tasks. Your job today will involve looking at advertisements. First, you will read the bullet point descriptions from an advertising company that describes their brief for creating an advertisement. This will have the main goals of the advertisement, and other relevant information about the product. Please take a few minutes to carefully read this briefing before we begin the next task. It’s important you pay careful attention to the descriptions.” Instructions will then vary based on condition.

CONTROL GROUP

“Once you have read the briefing and are familiar with it, we will show you text from an advertisement that has been created based on the goals and points described in the briefing. Your job is to carefully read and evaluate the ad based on how well it matches the items described in the briefing. You will have 10 minutes to complete this task. When 10 minutes is complete, I will start you on the next task.” 243

APPEARANCE-ONLY CUSTOMIZATION

“Once you have read the briefing and are familiar with it, we will show you text from an advertisement that has been created based on the goals and points described in the briefing. As you can see, it is presented as one long block of text. Your job is to make the description as interesting looking as possible [+ self-affirmation directions]. To do this you can use all the different tools available in the word formatting software. For example, you can change the font color, size, or type. You can change the margins, or spacing. The goal is to make it as interesting and visually appealing as you can [+ self- affirmation directions]. You will have 10 minutes to format this as you wish.”

CONTENT-ONLY CUSTOMIZATION

“Once you have read the briefing and are familiar with it, we will show you text from an advertisement that has been created based on the goals and points described in the briefing. As you can see, it is presented as one long block of text. Your job is to make the description as interesting as possible [+ self-affirmation directions]. To do this you get to change all the content in any way you wish. For example, you can change the names of things, add descriptions, or even delete and re-write all the words in there to something completely new. The goal is to make it as interesting as you can [+ self- affirmation directions]. You will have 10 minutes to do this as you wish, however, you cannot change the appearance of the ad, just the words in it. “

FULL CUSTOMIZATION

“Once you have read the briefing and are familiar with it, your job will be to write the text for an advertisement that best meets the goals described in the briefing. Your job

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is to write it to make it as interesting as possible [+ self-affirmation directions]. It does not matter if it is factual, or silly, or follows what’s written at all, you can be as inventive as you wish. Your goal is to be as interesting as possible with this writing. We encourage you to change names or key points to make the description more interesting [+ self- affirmation directions]. You will have 10 minutes to complete this task.”

HIGH SELF-AFFIRMATION

In the instructions concerning the customization task, participants will also be told

“…to make it as interesting as possible [to reflect your values and interests. Try to make your changes be a reflection of who you are and what you believe to be important].” This will be repeated twice within the instructions.

LOW SELF-AFFIRMATION

In the instructions concerning the customization task, participants will also be told

“…to make it as interesting as possible [to reflect the values and interests of someone the exact opposite from you. Somewhat that holds the opposite values and interests from you.].” This will be repeated twice within the instructions.

Dependent measures.

Following the customization task, participants will be given the thought-listing task. Participants will be told,

“Now that you have finished, take this piece of paper and write any thoughts you had about the advertisement. Start with the first thing that comes to your mind and continue downward. You can write in bullet points if you like. You can write anything

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you want, as long as its about the advertisement. You can stop when you run out of thoughts, or when I come in after about 3 minutes or so.

Following the thought-listing task, participants will be given the Stroop task. At the participants’ computers, the research assistant will open up a program that will run the Stroop task. Participants will be told,

“Now we would like you complete what is called the Stroop task. On the screen before you, the name of a color will appear, such as blue or red. That name will also be in a different color font. For example, the word BLUE may be written with red font color.

Your job is to speak out loud the name of the color the text is written in. So if blue was written with red ink, you would say “RED” out loud. Then press the arrow key to proceed to the next word. Try this twice now.

“Press the arrow key only when you have correctly said the color the word is written in. That camera behind you will record your progress and score on this task. Your goal is to proceed with this task as quickly as possible. Follow the directions and use the arrow key to move to the next word. You will be timed on how long it takes you to complete the task. Your time will start as soon as the first word appears on the screen following the directions.”

Participants will complete this task in individual, enclosed rooms with computers.

Their room will be viewed and recorded via a camera, and their responses will be later timed and scored. When participants finish the task, the research assistant will again enter the room.

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“Now that you have finished this task, please complete the following online survey, that will ask you about the text description you saw and a number of other questions.”

Participants will be directed to an online survey that contains the executive functioning self-report, perceived interactivity, perceived identity, perceived need fulfillment, reactance, source perceptions, message attitudes, and engagement questions.

Following their completion of the survey they will be given back their previously written list of thoughts and told: “For your last task, you will go back over the thoughts that you listed about the advertisement. For any thought that you had that was positive about the ad, for example that it was interesting or you liked it, put a plus sign next to the thought. For any thoughts you had that were negative about the ad, for example that you didn’t like it or thought it was a bad idea, put a minus sign next to the thought. For anything that was not positive or negative, or you can’t decide, put a 0 next to it.”

Following this, participants will be thanked and debriefed.

Before leaving, participants will be asked if they would like to participate in a follow-up email survey study concerning the experiment they just conducted. If the participants agree, their email will be recorded and they will be sent the survey within 3 – 7 days.

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Appendix I: Study 3 Measures

Thought-Listing Procedure

In the space below, list the thoughts you had while reading the advertisement. Start with the first thing that comes to mind, and continue listing until you’re out of thoughts or your time is up. I’ll give you about 3 minutes to do this.

(later) Now, go back through the thoughts that you have written down. Write a + if you think your thought about the advertisement is positive. Write a – if you think it is negative, or a 0 if you think it is neutral about the ad. Additionally, write REL next to the thoughts you have listed that seem relevant about the advertisement.

Stroop Task

“Press the arrow key only when you have correctly said the color the word is written in. That camera behind you will record your progress and score on this task. Your 248

goal is to proceed with this task as quickly as possible. Follow the directions and use the arrow key to move to the next word. You will be timed on how long it takes you to complete the task. Your time will start as soon as the first word appears on the screen following the directions.”

Participants will complete this task in individual, enclosed rooms with computers.

Their room will be viewed and recorded via a camera, and their responses will be later timed and scored. When participants finish the task, the research assistant will again enter the room.

Stroop Difficulty

1. The flashcard task was difficult

2. The flashcard task wore me out

3. The flashcard task was mentally exhausting

4. I would enjoy doing the flashcard task again*

State Reactance

Perceived threat to choice (Gardner, 2010, α =.83; Quick et al., 2011, α = .85)

1. The advertisement threatened my freedom to choose

2. The advertisement tried to make a decision for me

3. The advertisement tried to manipulate me

4. The advertisement tried to persuade me

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Participants rated their agreement on seven-point Likert scales ranging from 1 = Strongly disagree to 7 = Strongly agree.

Counter-arguing (α = .94)

1. Did you criticize the advertisement you just saw while you were reading it?

2. Did you think of points that went against what was being said while you were

reading the advertisement?

3. While reading the advertisement, were you skeptical of what was being said?

Participants rated their agreement on seven-point scales ranging from 1 = No, not at all to

7 = Yes, very much so.

Cognitive appraisal (α = .87)

1. The advertisement was pleasant (valence)

2. The advertisement got in the way of what I wanted (obstacle, reverse coded)

3. The advertisement was reasonable (legitimacy)

4. The advertisement was fair (legitimacy)

Participants rated their agreement on seven-point Likert scales ranging from 1 = Strongly disagree to 7 = Strongly agree.

Anger (α = .97)

1. To what extent did this advertisement make you feel ...

2. irritated

3. angry

4. annoyed

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Participants rated their response on seven-point scales ranging from 1 = Not at all to 7

= Very strongly.

Perceived Interactivity (Liu, 2003)

Items presented on a scale from 1 (strongly disagree) to 7 (strongly agree).

Please answer the following with the degree to which you disagree or agree with the following statements about the text description and the text software.

[Active control]

1. I felt that I had a lot of control over my experiences with the customization task.

2. While I was doing customization task, I could choose freely what I to do.

3. While doing customization task, I had absolutely no control over what I could do.

4. While doing customization task, my actions decided the kind of experiences I got.

[Two-way communication]

1. The software is effective in giving feedback.

2. This software facilitates two-way communication between me and the text.

3. It is difficult to offer feedback to the software. *

4. The software makes me feel it wants to listen to its users.

5. The software does not at all encourage me to talk back.

6. The software gives me the opportunity to talk back.

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[Synchronicity]

1. The software processed my input very quickly.

2. Getting information from the text is very fast.

3. I was able to obtain the information I want without any delay.

4. When I used the software, I felt I was getting instantaneous information.

5. The software was very slow in responding to my requests. *

Need fulfillment (Ryan, Koestner, & Deci, 1991)

Items presented on a scale from 1 (strongly disagree) to 7 (strongly agree).

Please answer the following with the degree to which you disagree or agree with the following statements about the text description.

[Autonomy]

1. I felt that it was my choice to customize as I saw fit.

2. I didn’t really have a choice about the customization task.R

3. I felt like I was doing what I wanted to do while I was working on the

customization task.

4. I felt like I had to do customization task.R

5. I did the customization task because I had no choice.R

[Competence]

1. I think I was pretty good at doing the customization task.

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2. I think I did pretty well at doing the customization task compared to other

students.

3. I am satisfied with my work on doing customization task.

4. I felt pretty skilled doing customization task.

5. After working on the task for a while, I felt pretty competent.

Engagement

1. I felt engaged in the advertisement task.

2. I felt involved in the advertisement task.

3. I felt caught up in what was going on in the advertisement task.

4. This task was not enjoyable.

Connection

Ball & Tasaki 1991

1. If someone ridiculed the advertisement I made, I would feel irritated.

2. The advertisement I made reminds me of who I am.

3. If I were describing myself, the advertisement would likely be something that I

mention.

4. If someone deleted the advertisement I made, I would feel a little bit personally

attacked.

5. If I lost the advertisement I made, I would feel like I lost a little bit of myself.

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6. I don’t really have too many feelings about the advertisement I made.*

7. If someone praised the advertisement I made, I would feel somewhat praised

myself.

8. Probably, people who know me might sometimes think of the advertisement I

made when they think of me.

9. If I did not have the advertisement I made, I would feel a little less like myself.

Self-affirmation (Tate, 1996)

On a scale ranging from 1 (not at all) to 9 (very).

Answer with the degree to which the text description task made you feel:

1. Confident

2. Proud

3. Satisfied

4. Skilled

5. Secure

6. Like a good person

7. Strong

8. Powerful

Source Credibility

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McCroskey, J. C., & Teven, J. J. (1999).Goodwill: A reexamination of the construct and its measurement. Communication Monographs, 66, 90-103.

Instructions: On the scales below, indicate your feelings about the company that you think designed the briefing for the product. Numbers 1 and 7 indicate a very strong feeling. Numbers 2 and 6 indicate a strong feeling. Numbers 3 and 5 indicate a fairly weak feeling. Number 4 indicates you are undecided.

1) Intelligent 1 2 3 4 5 6 7 Unintelligent*

2) Untrained 1 2 3 4 5 6 7 Trained

3) Cares about me 1 2 3 4 5 6 7 Doesn't care about me*

4) Honest 1 2 3 4 5 6 7 Dishonest*

5) Has my interests at heart 1 2 3 4 5 6 7 Doesn't have my interests at heart*

6) Untrustworthy 1 2 3 4 5 6 7 Trustworthy

7) Inexpert 1 2 3 4 5 6 7 Expert

8) Self-centered 1 2 3 4 5 6 7 Not self-centered

9) Concerned with me 1 2 3 4 5 6 7 Not concerned with me*

10) Honorable 1 2 3 4 5 6 7 Dishonorable*

11) Informed 1 2 3 4 5 6 7 Uninformed*

12) Moral 1 2 3 4 5 6 7 Immoral*

13) Incompetent 1 2 3 4 5 6 7 Competent

14) Unethical 1 2 3 4 5 6 7 Ethical

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15) Insensitive 1 2 3 4 5 6 7 Sensitive

16) Bright 1 2 3 4 5 6 7 Stupid*

17) Phony 1 2 3 4 5 6 7 Genuine

18) Not understanding 1 2 3 4 5 6 7 Understanding

Competence Factor (1, 2, 7, 11, 13, and 16)______

Caring/Goodwill Factor (3, 5, 8, 9, 15, and 18)______

Trustworthiness Factor (4, 6, 10, 12, 14, and 17)______

Product Liking

On a scale of 1 – 7, with one being strongly disagree and seven strongly agree, please rate the degree to which you agree or disagree with the following statements:

1. I like [the product].

2. I think [the product] sounds like a good product.

3. I would want to hear more about [the product].

4. I would recommend [the product] to a friend or family member.

5. I liked the ad about [the product].

Purchase Intention

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On a scale of 1 – 7, with one being strongly disagree and seven strongly agree, please rate the degree to which you agree or disagree with the following statements:

1. I would buy [the product].

2. I was convinced by the speech to buy [the product].

3. If I saw [the product] in the grocery store, I would buy one.

Recall

What was the name of the product you viewed?

Pay Amount

If you were going to buy the product, about how much would you be willing to pay for the product? (in dollars).

Familiarity with Microsoft Word

Items presented on a scale from 1 (strongly disagree) to 7 (strongly agree).

Please answer the following with the degree to which you disagree or agree with the following statements about the text description.

1. I am familiar with Microsoft Word.

2. I use Microsoft Word all the time.

3. I know how to make formatting changes (e.g., changing font, changing font color,

changing line spacing) in Microsoft Word.

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4. I know how to make content changes (e.g., writing and deleting words) in

Microsoft Word.

Familiarity with the advertisement.

Items presented on a scale from 1 (strongly disagree) to 7 (strongly agree).

Please answer the following with the degree to which you disagree or agree with the following statements about the text description.

1. I am familiar with the [type of product] that was originally shown to me.

2. I have heard of the [product] that was originally shown to me.

3. I use something like [the product] at least once a week.

4. I have never used anything like [the product].R

Items presented on a scale from 1 (strongly disagree) to 7 (strongly agree).

Please answer the following with the degree to which you disagree or agree with the following statements about the text description.

In my task, I was allowed to:

Read the ad.

Make changes to the ad.

Write an entirely new ad.

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Demographics

Age: ______

Sex: ______

Year in School: ______

Race/Ethnicity (Check all that apply)

 African/African-American/Black

 American Indian

 Asian/Asian-American

 Caucasian/European/White

 Latino/a

 Pacific Islander

 Other

FOLLOW-UP ONLINE SURVEY

Product Liking

On a scale of 1 – 7, with one being strongly disagree and seven strongly agree, please rate the degree to which you agree or disagree with the following statements:

1. I like [the product].

2. I think [the product] sounds like a good product.

3. I would want to hear more about [the product].

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4. I would recommend [the product] to a friend or family member.

5. I liked the ad about [the product].

Purchase Intention

On a scale of 1 – 7, with one being strongly disagree and seven strongly agree, please rate the degree to which you agree or disagree with the following statements:

1. I would buy [the product].

2. I was convinced by the speech to buy [the product].

3. If I saw [the product] in the grocery store, I would buy one.

Need fulfillment (Ryan, Koestner, & Deci, 1991)

Items presented on a scale from 1 (strongly disagree) to 7 (strongly agree).

Please answer the following with the degree to which you disagree or agree with the following statements about the text description.

[Autonomy]

6. I felt that it was my choice to customize as I saw fit.

7. I didn’t really have a choice about the customization task.

8. I felt like I was doing what I wanted to do while I was working on the

customization task.

9. I felt like I had to do customization task.

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10. I did the customization task because I had no choice.

[Competence]

6. I think I was pretty good at doing the customization task.

7. I think I did pretty well at doing the customization task compared to other

students.

8. I am satisfied with my work on doing customization task.

9. I felt pretty skilled doing customization task.

10. After working on the task for a while, I felt pretty competent.

Self-affirmation (Tate, 1996)

On a scale ranging from 1 (not at all) to 9 (very).

Answer with the degree to which the text description task made you feel:

1. Confident

2. Proud

3. Satisfied

4. Skilled

5. Secure

6. Like a good person

7. Strong

8. Powerful

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Appendix J: Study 3 Stimuli

Company 1 Briefing

About the company

We are an upcoming app creator focusing on bringing the hottest, most interesting music right to your phone. We focus on visuals and trivia that are cool, fun and very interesting.

Things to communicate:

Free music without restrictions

Interesting facts and information about musicians

Opportunities to win prizes

Product: Flyby Music. A music app that focuses on trivia, good visuals, and interesting band information. When the music is playing, if the listener is looking at the screen, they can collect things to win prizes like a shirt from the musician. We only distribute the most popular or "Hit" songs.

Company 2 Briefing

About the company: We know that technology is everywhere in our lives, and our goal is to make it a little less of a nuisance. We make a range of accessories that help lower some 262

of the annoyances of technology, especially cell phones, so you can go about your day a little easier off.

Things to communicate:

Blue light makes it harder to sleep

The screen filters out harmful light to improve sleep

Can buy screens that fit any device

Product: Sleep Easy Screen. “Blue” light from cell phone, tablet, and laptop screens has been shown to contribute to lack of sleep. The Sleep Easy Screen slips over your screen and filters out this light, so your body can sleep easier. Use this when using a screen before bed and you will get to sleep faster, and sleep better.

Company 3 Briefing

About the company: We have gotten very tired of driving around and around for parking in the city. So we leveraged existing, public-access satellite technology to create a product that reduces the need to drive in circles and gets people where they are going faster.

Things to communicate:

Easy notification and navigation to open parking spaces

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Includes directions and other information about the parking spot

Emphasize that the product should be used carefully while driving

Product: Easy Park. This app helps you find open parking spaces on and around campus.

It is connected to constantly updated satellite pictures of the area, and can notify you quickly and easily direct you to the closest open parking spot. It also provides information on required permits for the area and meter fees.

Company 4 Briefing

About the company: We specialize in household electronics that can be used by everyone and are fun to use. A new patent in rotor technology and the use of an internal computer allows us to make a fan that will adjust to best accommodate your home.

Things to communicate:

Small, efficient, affordable

One fan is enough to cool the entire house

Uses new, cutting edge technology

Product: Cyclone fan. This small, powerful fan can be placed in one room and will efficiently circulate air throughout the house. It’s the only fan you’ll ever need to buy.

Place it by an open window or an air conditioning duct for extra cooling.

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