The Effect of Black-And-White Versus Color Imagery on Consumer Behavior: a Construal Level Theory Approach

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The Effect of Black-and-White versus Color Imagery on Consumer Behavior: A Construal Level Theory Approach

DISSERTATION

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

Hyojin Lee

Graduate Program in Business Administration

The Ohio State University

2016

Dissertation Committee:

Xiaoyan Deng, Co-Advisor

H. Rao Unnava, Co-Advisor

Kentaro Fujita

Copyrighted by

Hyojin Lee

2016

Abstract

Advances in technology and digitalization in the 21st century has made color dominant to black-and-white in the marketing world. This dissertation, however, questions the assumption that color media is always superior to Black-and-White (BW) media in communications. Drawing from construal level theory (CLT; Trope and

Liberman 2003), this dissertation investigate the interplay between visual perception

(BW vs. color) and cognition (high-level vs. low-level construal), exploring conditions under which BW (vs. color) imagery can lead to more favorable consumer responses.

Marketing communications (e.g., advertising, packaging) can be either colorful or

BW. The first essay investigates how the presence or absence of color in media can change consumers’ information processing and affect product evaluations and choices. In six experiments, we show that people exposed to BW (vs. color) pictures and videos are more likely to engage in high-level (vs. low-level) construal, place greater weight on primary (vs. secondary) product features, and prefer an option that excels on those features. In particular, the result from one study raises an alarm to consumers by demonstrating that they sometimes pay more money for product features that are unnecessary or irrelevant to their needs when the product is presented in color (vs. BW).

To marketers, this research suggests that they may consider using BW (vs. color) media

ii to draw attention to the superior primary (vs. secondary) features of a product.

Theoretically, this work is the first to demonstrate that a basic component of visual imagery (presence or absence of color) can be an important antecedent variable that determines level of construal.

Whereas the first essay explores how BW vs. color media influences consumers’ information processing, the second essays examines consumer’s use of BW vs. color

imagery in forming their visual representations of the future. Consumers frequently make

purchase decisions about products to be consumed or experienced some time in the future.

Thus, marketers need to better understand how consumers imagine their future

interactions with the advertised products to develop more effective advertising appeals. In

nine experiments, we find that people are more likely to visually represent distant (vs. near) future events in BW (vs. color). Given this tendency, we further argue and

demonstrate that persuasive appeals about distant (vs. near) future events are more

effective when accompanied by BW (vs. color) images. This finding suggests marketers should use BW (vs. color) in visual appeals when attempting to change attitudes about temporally distant (vs. near) future events. Critically, this research provides new insight into what consumers’ representations of the future looks like in the mind’s eye – a question largely unaddressed in current marketing and psychology literature on future- directed thinking.

To summarize, this dissertation shows that BW media sometimes can function more effectively than color media in marketing communications, suggesting the need to carefully consider the color of advertising appeals. More importantly, this work is the

iii first to link the color of imagery with construal level and psychological distance, highlighting the subjective experience of these psychological mindsets.

Acknowledgments

I would like to express my sincerest gratitude to Xiaoyan Deng, Rao Unnava, and

Ken Fujita. Without their support and guidance, this dissertation would not have been

possible. First, I am extremely grateful to my wonderful advisors, Xiaoyan Deng and Rao

Unnava, for their continual enthusiasm and patience throughout my time in the graduate

program. I have learned a great deal about both research and life by having numerous

meetings and endless conversations with them. During my doctoral studies at Fisher, I

have truly felt nurtured and cared for by them. Thank you so much for helping me to

grow as a better researcher and as a better person. I am also indebted to Ken Fujita, who

is my secondary advisor at the department of psychology. Having the opportunity to join

his lab, I could have built on my research skills through regular interaction with him and his students in the social psychology department. I have learned the value of theory and rigor in developing science from him. I truly appreciate him for investing countless hours into my training in psychological research. I would also like to thank my collaborators,

Paul Stillman and Jessica Carnevale, who taught me various research tools that I

employed in this dissertation work.

I also want to thank my amazing friends who helped me along the way: Chris

Summers, Amit Singh, Danny Zane, Adam Smith, Marc Dotson, Hyowon Kim, Dongsoo

Kim, Sang Lee, Tatiana Dyachenko, Inyoung Chae, and Max Joo. I would especially like to express my special thanks to my CB colleagues, Chris, Amit, and Danny. I have so many happy and fun memories from my graduate studies at Fisher thanks to them. Thank you for being such sweet friends and colleagues to me.

Finally, I would like to dedicate this dissertation to my parents, Sounglae Lee and

Jungnam Sim, who have always given endless love to me and had faith in me. Without their continual support, I would not have been able to even begin my graduate studies in the States. I can’t thank them enough for everything they have done for me. Above all, a special thanks to my husband, Hyounkyu Cho. Without him, earning my degree would not have been possible. Thank you for making my life more beautiful, enjoyable, and meaningful. I love you.

Vita

2006...... B.S. Business Administration,

Seoul National University

2006 – 2008 ...... Assistant Manager, Samsung Electronics

2011...... M.S. Business Administration,

Seoul National University

2011 to present ...... Graduate Teaching and Research Associate,

Fisher College of Business, The Ohio State

University

Publications

Deng, Xiaoyan, Barbara E. Kahn, Rao Unnava, and Hyojin Lee, “A ‘Wide’ Variety: Effects of Horizontal versus Vertical Display on Assortment Processing, Perceived Variety, and Choice,” Journal of Marketing Research (in press).

Lee, Hyojin, Xiaoyan Deng, H. Rao Unnava, and Kentaro Fujita (2014), “Monochrome Forests and Colorful Trees: The Effect of Black-and-White versus Color Imagery on Construal Level,” Journal of Consumer Research, 41 (December), 1015-32.

vii

Yi, Youjae, Taeshik Gong, and Hyojin Lee (2013), “The Impact of Other Customers on Customer Citizenship Behavior,” Psychology & Marketing, 30 (April), 341-56.

Fields of Study

Major Field: Business Administration

viii

Table of Contents

Abstract ...... ii

Acknowledgments...... v

Vita ...... vii

List of Tables ...... xi

List of Figures ...... xii

Chapter 1: Introduction ...... 1

Chapter 2: Construal Level Theory...... 6

Chapter 3: The Effect of Black-and-White versus Color Imagery on Construal Level…...9

3.1. Theoretical Development ...... 10

3.2. Experiment 1 ...... 16

3.3. Experiment 2 ...... 18

3.4. Experiment 3 ...... 24

3.5. Experiment 4 ...... 29

3.6. Experiment 5 ...... 33

3.7. Summary and Managerial Implications ...... 36 ix

Chapter 4: On Visualizaing Distant and Near Future Events in Black-and-White versus

Color ...... 41

4.1. Theoretical Development ...... 43

4.2. Experiment 1 ...... 50

4.3. Experiment 2 ...... 54

4.4. Experiment 3 ...... 60

4.5. Experiment 4 ...... 64

4.6. Experiment 5 ...... 67

4.7. Experiment 6 ...... 69

4.8. Summery and Managerial Implications ...... 74

Chapter 5: General Discussion...... 78

References ...... 83

Appendix: Tables and Figures ...... 96

List of Tables

Table 1. Key assignments in IAT blocks...... 97

Table 2. BW (vs. color) increases the tendency to categorize products based on high-level

(low-level) features ……………………………………………………………………...98

Table 3. The effect of color on responses to the PANAS items…………………………99

Table 4. BW (vs. color) increases the tendency to segment behavior in fewer, broader (vs.

more, narrower) units ...... 100

Table 5. BW (vs. color) increases the tendency to interpret behaviors in high-level (vs. low-level) terms ...... 101

Table 6. Lists of the scenarios used in Experiment 2b ...... 102

Table 7. Factor analysis results ...... 103

Table 8. List of the behaviors and their descriptions ...... 104

List of Figures

Figure 1. Stimuli used in Experiment 1 (IAT) ...... 105

Figure 2. Stimuli used in Experiment 2 ...... 106

Figure 3. Stimuli used in Experiment 4 ...... 107

Figure 4. BW (vs. color) increases the perceived importance of the primary (vs.

secondary) feature ...... 108

Figure 5. Stimuli used in Experiment 5 ...... 109

Figure 6. Temporal distance moderates the focus on shape versus color ...... 110

Figure 7. Temporal distance moderates WTP for information on shape versus color ... 111

Figure 8. Measures used in Experiment 2a ...... 112

Figure 9. Effect of temporal distance on BW versus color imagery ...... 113

Figure 10. Line drawing used in Experiment 3...... 114

Figure 11. Color version of stimuli used in Experiment 4 (IAT) ...... 115

Figure 12. Temporal distance moderates the effectiveness of messages used BW versus

color ...... 116

Figure 13. Temporal distance moderates WTP for a new product presented in BW versus color ...... 117

Figure 14. Temporal distance moderates liking for a new product presented in BW versus

color ...... 118 xii

Chapter 1: Introduction

Color has become main stream in all forms of media in the digitalized 21st century, making it rare to observe any content presented in black-and-white (BW) format.

Supporting this trend, previous research in marketing has shown that color media is more effective than BW media in various aspects. For example, color leads consumers to judge ad content as more attractive, interesting, and powerful (Bohle and Garcia 1986; Click and Stempel 1976; Schindler 1986), attracts viewers’ attention (Gronhaug, Kvitastein and

Gronmo 1991; Hornik 1980; Lohse 1997), and promotes favorable attitudes (Berdie 1992;

Fernandez and Rosen 2000; Meyers-Levy and Peracchio 1995; Pallak 1983; Percy and

Rossiter 1983). Extensive work also suggests that people remember color images more accurately or for longer time than black-and-white (BW) images (Gardner and Cohen

1964; Homa and Viera 1988; Suzuki and Takahashi 1997; VanderMeer 1954; Wichmann,

Sharpe, and Gegenfurtner 2002). These findings may explain why color tends to be more common than BW imagery in most media advertisements.

Although color is generally considered to be superior to BW in marketing communication (e.g., television and magazine advertising, package design), we question this assumption. Drawing from construal level theory (CLT; Trope and Liberman 2003),

this dissertation critically evaluates the effectiveness of BW vs. color imagery in

communications and explores conditions under which BW (vs. color) imagery can lead to more favorable consumer responses.

CLT provides a theoretical framework for understanding how people think and interpret objects or events that are psychologically distant. People can use their perceptual systems to construct rich and detailed representations of events that are directly experienced. When events extend beyond the scope of direct perception, however, detailed specifics about distant events are often unavailable and subject to change. To address this challenge, CLT suggests that people engage in high-level construal – a representational process that extracts essential and primary features of events while ignoring incidental and secondary features. This process is highly functional because the essential and abstract features of events tend to be invariant and apparent across all possible manifestations of those events. As events become more proximal and detailed information become more available, people engage in low-level construal – a representational process that highlights the secondary and incidental details of events that render them unique.

We apply these principles to understand BW vs. color visual imagery. Shape and color comprise two of the most important elements in visual representation. Of the two, research suggests that shape more effectively conveys the essential meaning of the depicted objects and events. Moreover, whereas the perception of color is highly sensitive to contextual factors (such as lighting and viewing angle), the perception of shape is less contextually variable. We thus propose that shape represents high-level visual information, whereas color represents low-level visual information. Given that BW (vs.

color) imagery captures shape but not color, we suggest that BW (vs. color) imagery may

be fundamentally related to high-level (vs. low-level) construal. Two dissertation essays combinedly test and provide supports for this idea, exploring conditions in which BW

(vs. color) imagery is more effective in marketing communication.

The first essay, titled ‘The Effect of Black-and-White vs. Color Imagery on

Construal Level,’ examines whether the presence or absence of color in media can change the style consumers perceive and understand visual information, and further affect their product evaluation and choice. BW (vs. color) pictures highlight high-level shape information about the depicted object while absenting low-level color information. As exposure to BW (vs. color) media promotes a focus on high-level (vs. low-level) visual features, we hypothesize that people engage more generally in high-level (vs. low-level) construal, respectively. Across five experiments, we find that people exposed to BW (vs. color) media process visual information more abstractly and broadly and prefer a product that is superior on its primary (vs. secondary) features. Especially, the last study demonstrates that consumer sometimes pay more money for product features that are unnecessary or irrelevant to their needs when products are presented in color (vs. BW), raising an alarm to consumers. To marketers, this research suggests that they should choose BW (vs. color) media if they want their consumers to pay attention to primary (vs. secondary) features of products.

Whereas the first essay explores how BW vs. color media influences consumers’ information processing, the second essay, titled ‘On Visualizing Distant and Near Future

Events in Black-and-White versus Color,’ examines consumer’s use of BW vs. color

imagery in forming their visual representations of the future. Consumers frequently make

purchase decisions about products to be consumed sometime in the future. Thus,

marketers need to better understand how consumers imagine their future interactions with

the advertised products to develop more effective advertising appeals. Given that shape

(vs. color) is a high-level (vs. low-level) visual feature that is more available and reliable in forming mental images of future events, we argue that when consumers visualize the distant (vs. near) future, they increasingly engage in processing that captures this high- level (vs. low-level) visual feature - namely, BW (vs. color) imagery. Using image matching, image reconstruction, and behavioral response time measure, we find that people visualize the distant (vs. near) future relatively more in BW (vs. color) and further show that persuasive appeals about distant (vs. near) future events are more effective when accompanied by BW (vs. color) images. This research suggests that marketers should consider using BW (vs. color) when advertising appeals target the distant (vs. near) future.

To summarize, this dissertation work shows that BW media sometimes can function more effectively than color media in marketing communications, suggesting the need to carefully consider the color of advertising appeals. More importantly, this dissertation extends the existing CLT literature in a number of ways. Theoretically, this work is the first to demonstrate that a basic component of visual imagery (presence or absence of color) can be an important antecedent variable that determines level of

construal. Given that previous CLT research has extensively demonstrated how high-

level construal affects various judgments and decision makings (i.e., self-control,

negotiation), these findings suggest that marketers can use BW vs. color imagery as a

psychological nudge to leverage such consumer behaviors. More broadly, this work

provides insights into how people visually experience high-level vs. low-level construal.

Although we know much about the antecedents and consequences of different levels of construal, less has been done to elaborate on the visual representation of construal. By establishing the relationship between the color of imagery, construal level, and psychological distance, the current work highlights the subjective experience of these psychological mindsets.

Chapter 2: Construal Level Theory

A central concept in construal level theory (CLT) is psychological distance – the removal of an event from direct experience (Liberman and Trope, 2008; 2014; Trope and

Liberman, 2003; 2010). Events that occur in the distant vs. near future, for example, are psychologically distant vs. near, respectively. Events can also be psychologically distant vs. near as a function of space (there vs. here), social distance (you vs. me, them vs. us), and probability (uncertain vs. certain, hypothetical vs. real). People can use their perceptual systems to construct rich and detailed representations of events that are directly experienced. To construct representations of events that extend beyond the scope of direct perception, however, people must use the knowledge that they have in memory.

A critical challenge people face is that specific and detailed information about psychologically distant relative to near events is typically unknown or subject to change.

To address this challenge, CLT suggests that people engage in high-level construal – a representational process that extracts the abstract and essential elements of events while ignoring concrete and surface-level details. This process is functional because the abstract and essential features of events tend to be invariant and unlikely to change. As events become more proximal and detailed information because more reliable, people engage in low-level construal – a representational process that highlights

6 the concrete and incidental features of events that render them unique. Thus, whereas high-level construal allows people to consider remote content, low-level construal allows people to tailor their decisions and actions to the idiosyncratic demands of the more immediate here-and-now (Ledgerwood, Trope, and Liberman, 2010; Trope and

Liberman, 2010).

To illustrate these principles, consider going on a camping trip. When the event is in the distant future (e.g., in a year’s time), we might not know what the weather will be like or what clothes we need to bring, but what we do know is that generally speaking, camping trips involve spending time with family and friends while communing with nature. By directing our attention to the latter, engaging in high-level construal allows us to start planning and to make appropriate decisions (e.g., who do I want to invite, and where should we go?). As the event becomes nearer in time, detailed specifics like what the weather will be like becomes more reliable. By directing our attention to this more context-specific, concrete information, engaging in low-level construal allows us to ensure that our decisions are sensitive to the idiosyncratic features of the present (e.g., should I pack this poncho, and do I need this extra sweater?). CLT suggests that this relationship between psychological distance and construal level is over-generalized and is evident even when information about distant and near events is held constant (Bar-Anan,

Liberman, and Trope, 2006).

An extensive literature supports the assertion that people engage in high-level construal to represent psychologically distant events and low-level construal to represent psychological near events (Liberman and Trope, 2014; Trope and Liberman, 2010).

Research shows, for example, that when asked to categorize objects associated with

psychologically distant vs. near events (such as those that occur in the distant vs. near

future), people are more likely to sort those objects into fewer, broader categories (e.g.,

Liberman, Sagristano, and Trope, 2002). People, moreover, are more likely to identify

behaviors associated with psychologically distant vs. near events in terms of the abstract,

superordinate ends they achieve (i.e., “why” aspects) rather than the concrete,

subordinate means by which to execute them (i.e., “how” aspects; Liberman and Trope,

1998). People pair psychological distance vs. proximity with high-level vs. low-level construal, respectively, so frequently that the two pairs of concepts become cognitively associated. Research suggests, for example, that they associate temporally distant vs. near events (e.g., “later” vs. “now”) with abstract vs. concrete concepts, respectively

(e.g., “food” vs. “beet;” Bar-Anan et al., 2006). Empirical evidence thus supports the assertion that people engage in high-level construal when thinking about psychologically distant events, and in low-level construal when thinking about psychologically near events.

Chapter 3: The Effect of Black-and-White versus Color Imagery on Construal Level

In this first essay, we focus on the impact of BW vs. color imagery on how people process information, and how this change in information processing influences feature evaluation and choice. We propose that BW vs. color imagery directs attention to different types of information and product attributes, which in turn systematically affects preferences. One implication of our approach is that there may be conditions under which

BW (vs. color) imagery can lead to more favorable consumer responses.

Drawing from construal level theory (CLT; Liberman and Trope 2008; Liberman,

Trope, and Stephan 2007; Trope and Liberman 2010; Trope, Liberman, and Wakslak

2007), we propose the novel hypothesis that whereas BW imagery promotes high-level construal, color imagery promotes low-level construal. We first present the theoretical argument as to why BW (vs. color) imagery should be associated with high-level (vs. low-level) construal, and present empirical evidence for this assertion (Experiment 1).

We then test to what degree BW (vs. color) imagery evokes high-level (vs. low-level) construal (Experiments 2–3), and examine the consequences of BW vs. color imagery in feature evaluation and choice within consumer behavior contexts (Experiments 4–5). We end the essay with a discussion of how this work contributes to our understanding of color perception, construal, and practices in marketing.

3.1. Theoretical Development

Association between Black-and-White vs. Color Imagery and Construal Level

There are at least three reasons why we might expect BW vs. color imagery to be associated with high-level vs. low-level construal, respectively. The first reason stems from people’s tendency to associate BW vs. color media with the distant vs. near past, respectively. Given that color in pictures and video is a more recent technological development, people may view color imagery as something temporally proximal and BW imagery as something temporally distant. CLT would suggest that the temporal distance

(vs. proximity) of BW (vs. color) imagery in turn should evoke high-level (vs. low-level) construal. Over time, this pairing between BW vs. color and construal level might over- generalize and emerge even when temporal distance is held constant.

A second reason why BW vs. color imagery might be associated with high-level vs. low-level construal, respectively, stems from people’s direct experience of their environments. The human eye is relatively advanced in its perception of color, compared to many other animals (e.g., dogs, cats). The human eye has four types of light receptors; among them are three types of cones, each of which responds to a different range of color

(i.e., red, green, and blue), working together to allow perception of the entire rainbow spectrum (Gegenfurtner and Sharpe 2001; Kaplan, Lee, and Shapley 1990; Stockman and

Sharpe 1999). Although the fourth type of light receptor, rods, are sensitive only to black, white and shades of grey, the fact that our environment is mostly colorful rather than black-and-white suggests that our visual experience of the environment is predominately

in color. In contrast, the experience of BW imagery is psychologically removed, reflecting an experience that deviates from the colorful experience of “me” in the “here- and-now.” So, the perception of BW (vs. color) imagery is different from the reality that is directly experienced, which CLT suggests should therefore promote high-level (vs. low-level) construal (Amit, Algom, and Trope 2009). The repeated pairing of BW vs. color with high-level vs. low-level construal, respectively, should lead the concepts to become associated.

Finally, a third reason for an association between BW vs. color imagery and construal level is that the cognitive operations entailed in the perception of BW vs. color imagery are highly similar to those entailed in high-level vs. low-level construal, respectively. Relative to color imagery, BW imagery highlights contour and boundary information that facilitates attention to the form or shape of an object, yet reduces the contrast between various image components, rendering smaller details less salient and distinctive (Arnheim 1957, 1974; Davidoff 1991). For example, in a BW image of a chair, the wood color and texture of the chair may not be noticeable, but the shape of the chair is still easily perceived. By contrast, vivid colors accentuate different hues and textures, drawing attention to specific detail (Brockmann 1991; Dooley and Harkins

1970; Itti and Koch 2001; Janiszewski 1998). Thus, perception research indicates that

whereas BW imagery directs attention to global form and shape, color directs attention to

constituent detail.

This directing of attention to form vs. detail is important to note because whereas

form constitutes a high-level feature, detail constitutes a low-level feature. Two lines of

logic support this assertion. First, perception of color is sensitive to changes in the angle

from which a viewer perceives them as well as by the brightness of the environment,

whereas perception of form is less affected by such situational variation (Arnheim 1974).

Thus, whereas color represents a context-dependent feature, form is relatively more invariant. Second, form more so than detail, provides information about the essential nature of depicted objects (Arnheim 1974). People use the global shape of objects to identify and understand their meaning and functionality (Arnheim 1974; Biederman

1987; Biederman and Ju 1988; Lowe 1984; Mapelli and Behrmann 1997). Although there may be times in which color can be critical for identification – such as when the color of a tomato (green vs. red) signals its palatability (less edible vs. more edible, respectively)

– generally speaking, color relative to form is less useful in conveying the essential nature of objects (Brockmann 1991; Dooley and Harkins 1970; Rossiter 1982). Thus, research suggests that form is a high-level feature and detail is a low-level feature, and that BW vs. color imagery may direct attention to these features in a manner akin to high- level and low-level construal, respectively. This overlap in cognitive procedures should therefore lead the concepts to become associated.

The Present Research

The present research has three goals. First, based on the three reasons discussed above, we aim at testing the central theoretical assertion of this paper: BW vs. color imagery is cognitively associated with high-level and low-level construal, respectively

(Experiment 1). Second, assuming the two concepts are cognitively associated, we intend

to test whether BW vs. color imagery promotes high-level and low-level construal,

respectively (Experiments 2–3). Third, extending this research into consumer decision-

making, we investigate whether BW vs. color imagery affects feature evaluation and choice (Experiments 4–5).

First, we use the Implicit Association Test (IAT; Greenwald, Nosek, and Banaji

2003) to assess the association between BW vs. color imagery and construal level

(Experiment 1). The IAT is a reaction time measure that gauges the strength of association between different concepts. It has been used in previous research (Bar-Anan,

Liberman, and Trope 2006) to document the association between psychological distance dimensions (time, space, social distance, and hypotheticality) and construal level. We adapted this IAT for our critical test.

Second, we test the hypothesis that BW (vs. color) imagery promotes high-level

(vs. low-level) construal via three different tasks: categorization task (Experiment 2), as well as behavior segmentation and identification tasks (Experiment 3), all derived from the CLT literature. This literature supports the assertion that when thinking about psychologically distant (vs. proximal) events, people engage in high-level (vs. low-level) construal (Liberman and Trope 2008; Liberman et al. 2007; Trope and Liberman 2010;

Trope et al. 2007). For example, people are more likely to sort objects associated with the distant vs. near future into fewer, broader categories, suggesting more abstract, high-level

features rather concrete, low-level features as the basis for categorization (Liberman,

Sagristano, and Trope 2002). People are also more likely to organize and segment continuous streams of behavior associated with psychologically distant vs. near events

into larger, broader units, suggesting more abstract rather than concrete processing

(Henderson et al. 2006; Wakslak et al. 2006). Similarly, people are more likely to identify

behaviors in terms of the general ends they achieve (“why” one does something), rather

than the specific means by which to achieve them (“how” one does something) when they are situated in the distant rather than near future (Liberman and Trope 1998). In our research, we argue that the perception of BW (vs. color) imagery promotes high-level (vs. low-level) construal, which in turn should increase the tendency to (1) categorize objects based on high-level (vs. low-level) feature (Experiment 2), (2) segment continuous streams of behavior into fewer, broader (vs. more, narrower) units, and (3) interpret various actions as ends (vs. means) (Experiment 3).

Finally, applying our key hypotheses (i.e., BW vs. color imagery is associated with and promotes high-level and low-level construal, respectively) to consumer decision-making, in the last two studies of this paper, we test whether consumers exposed to BW (vs. color) product imagery will weigh the primary and essential (vs. secondary and superficial) product features more (Experiment 4) and prefer an option that excels on these features (Experiment 5), leading those exposed to color imagery to make a suboptimal choice. Research suggests that high vs. low construal level systematically impacts evaluation, judgment, and choice. The focus on abstract and essential properties that high-level construal promotes also leads people to prefer decision options that maximize the primary and central aspects of a choice rather than the secondary and superficial features (Eyal et al. 2009; Fujita et al. 2008; Fujita et al. 2006; Torelli and

Kaikati 2009; Trope and Liberman 2000). In one study, for example, Trope and Liberman

(2000) asked participants to select a radio for listening to music in the near vs. distant

future. One radio had excellent sound (primary feature) but a mediocre clock display

(secondary feature), whereas the alternative had mediocre sound but an excellent clock.

Those selecting a radio for purchase in the distant future were more likely to pick the

radio with superior primary (rather than secondary) features – i.e., the radio with

excellent sound but poor clock display. Thus, research highlights the central role of

construal level in consumer judgment and decision making. We join this stream of

research by assessing the proposed, paralleling effects of BW vs. color imagery.

We should note that our hypotheses find some support in prior research

examining the impact of BW vs. color on learning and memory. For example, Katzman

and Nyenhuis (1972) found that people were more likely to recall story-irrelevant information when scenes from a comic book were presented in color rather than BW.

Similarly, Dooley and Harkins (1970) presented BW vs. color bar charts to participants,

and found that those exposed to color charts spent more time looking at irrelevant graphic

stimuli. Although this past work provides some initial support for our hypotheses, it was

not designed to test the construal level framework specifically and did not explore this

research question systematically. The present research extends this past work by examining the effect of BW vs. color imagery on construal level and on consumer decision making.

3.2. EXPERIMENT 1

Experiment 1 adopts the IAT to assess the association between BW vs. color

imagery and high-level vs. low-level construal, respectively. In the IAT paradigm,

participants categorize stimuli into one of two categories, which are mapped onto the

same response keys. People respond faster when the two categories mapped on to a given

key are associated. We predicted that participants would be faster to categorize stimuli

when the concepts BW and high-level construal (and color and low-level construal) were

paired, as compared to when the concepts BW and low-level construal (and color and high-level construal) were paired.

Method

182 undergraduates completed this study in a laboratory for partial course credit.

Past research indicates that whereas superordinate categories are associated with high-

level construal, subordinate exemplars are associated with low-level construal (Bar-Anan

et al. 2006; Liberman et al. 2002). Thus, as stimuli for the IAT, we selected 12 stimulus

words to represent high-level vs. low-level terms: 6 that referred to general categories

(electronics, animal, plant, jewelry, furniture, and vehicle) and 6 that referred to specific exemplars of those categories (digital camera, poodle, tulip, ring, sofa, and convertible).

We also selected 6 pictures depicting each of the 6 low-level exemplars, and presented them either in BW or in color (see Figure 1).

Instructions regarding the key and item assignments were presented at the beginning of each block (Table 1 summarizes these assignments). The first two blocks of

the IAT were practice blocks: Block 1 required categorizing all of the picture stimuli as

either BW or color. Block 2 required categorizing all of the word stimuli (e.g.,

electronics, digital camera) as either “general category” or “specific exemplar.” Blocks 3

and 4 represented critical combined blocks in which the identification of BW pictures and

general category words were assigned to the same key, whereas identification of color

pictures and specific exemplar words were assigned to the other key (or vice versa,

counter-balanced between-subject). Block 5 was another practice block, with the key

pairings reversed from Block 1. Blocks 6 and 7 represented a second set of critical

combined blocks with key assignments reversed from those of Blocks 3 and 4. In these

blocks, identification of color pictures were paired with general category words and

identification of BW pictures were paired with specific exemplar words (or vice versa,

counter-balanced between-subject).

Results and Discussion

IAT responses were analyzed using the D-score algorithm with a 600 ms penalty

for incorrect responses; we eliminated one participant who responded in less than 300 ms

for 10% or more of trials (Greenwald et al. 2003). We identified blocks in which BW pictures and general category words (and color pictures and specific exemplar words) were paired as the compatible blocks. By contrast, we identified those blocks in which

BW pictures and specific exemplar words (and color pictures and general category words) were paired as the incompatible blocks. We expected that the response time will be faster for compatible blocks than for incompatible blocks.

We did find the mean response time to be shorter in compatible blocks paring BW

with general category and color with specific exemplar (965.75 milliseconds), compared

with incompatible blocks paring BW with specific exemplar and color with general

category (1097.52 milliseconds). Following procedures recommended by Greenwald et

al. (2003), we converted this difference in response time into D-scores. Consistent with

our expectation, we found that the mean D-score significantly differed from zero (M

=.28, SD =.45, t (180) = 8.19, p <.001). Thus, participants were faster on compatible vs.

incompatible blocks. That participants were able to respond significantly faster when

asked to group BW with high-level and color with low-level concepts suggests that

people have a stronger implicit association between BW (vs. color) and high-level (low-

level) concepts. Thus, the result from the IAT supports our assertion that there is a

cognitive association between BW vs. color imagery and high-level and low-level construal, respectively.

3.3. EXPERIMENT 2

Experiment 2 intends to demonstrate that BW (vs. color) increases the tendency to categorize objects based on high-level (vs. low-level) features. We test this hypothesis in two steps. First, we confirm that form vs. detail is high-level vs. low-level feature of objects, respectively (Experiment 2a). Second, we show that BW vs. color leads people to sort objects in terms of form vs. detail, respectively (Experiment 2b).

Experiment 2a consisted of two parts. In part one, we induced the tendency to construe objects in high-level vs. low-level terms, using procedural mindset procedures

validated in previous research (Fujita et al. 2006). In part two, we presented participants

with four consumer products that varied in functional form and aesthetic detail, and asked

them to categorize these stimuli into groups. To the extent that form represents an

essential high-level feature relative to detail, we would expect that those induced to high-

level vs. low-level construal would sort these products on the basis of form rather than

detail.

Experiment 2b subsequently applied this categorization methodology to examine

the impact of BW vs. color on level of construal. It also consisted of two parts. In part

one, participants completed the same categorization task as in Experiment 2a (part two),

but with the stimuli presented in BW or color format. Assuming that form is a high-level

feature relative to detail (an assumption tested in Experiment 2a), we predicted that those

presented with the products in BW (vs. color) format should be more likely to sort the

products on the basis of form rather than detail. In part two, participants completed the

Positive and Negative Affect Schedule (PANAS) Short-Form, which was to assess whether being exposed to BW vs. color pictures could have led to any differences in their experience of various types of emotion.

Method

We recruited 138 and 149 participants for Experiment 2a and 2b, respectively, via

Amazon Mechanical Turk. They participated in the study in exchange for payment.

Construal level manipulation (Experiment 2a). The category vs. exemplar procedural mindset manipulation of construal level (Fujita et al. 2006) presented

19 participants with 30 words, such as actor, beer, book, and candy. Those in a high-level construal condition were instructed to generate superordinate category labels for each word by answering the question (i.e., an ACTOR is an example of ______). Those in low-level construal condition were instructed to generate subordinate exemplars for each word by answering the question (i.e., an example of an ACTOR is ______).

Main categorization task (Experiment 2a and 2b). The categorization task presented participants with six sets of four products each (see Figure 2). In Experiment

2a, the products were presented in color. In Experiment 2b, the products were presented either in BW or in color. The participants’ task was to sort the four products within a given set into two categories of two products each. Each product was labeled with a letter

(A, B, C, and D). Participants indicated their groupings by writing down the letter corresponding to each product into one of two boxes, with each box representing a category grouping. The stimuli within each set could be categorized on the basis of either functional form or aesthetic detail. The first set, for example, included four shoes: two high heels and two sneakers. The form of the shoes instantaneously informs their functionality (Arnheim 1974; Biederman 1987; Biederman and Ju 1988; Lowe 1984;

Mapelli and Behrmann 1997) and therefore serves as a basis for categorization. The detail of the shoe design can also be used as a basis for differentiation: two shoes (one high heel and one sneaker) were plain whereas the other two had a leopard print. So, the shoes could be categorized by either form (i.e., heels vs. sneakers) or detail (i.e., plain shoes vs. leopard print shoes). Across the six sets of stimuli, whether AB/CD or AC/BD grouping

represented form-based (vs. detail-based) categorization was randomly determined across all six sets.

PANAS (Experiment 2b). After completing the main categorization task, participants in Experiment 2b were asked to complete the Positive and Negative Affect

Schedule (PANAS) Short-Form (Watson and Clark 1994; Watson, Clark, and Tellegen

1988). This was to capture any potential differences in affective states as a function of being exposed to BW vs. color stimuli. We added the item “nostalgia” to address the potential possibility that BW imageries evoked a feeling of nostalgia which might account for our results. Participants indicated to what extent they felt, at that moment, each of the affective states listed on the form, using a 7-point Likert-type scale, with 1 = not at all and 7 = extremely.

Results and Discussion

We coded responses for each set such that categorization based on detail was given the value of 0, and categorization based on form was given the value of 1. We summed these item scores and created a categorization index ranging from 0 to 6, with higher scores indicating greater tendency to focus on form rather than detail. In our analysis, we excluded 9 participants in Experiment 2a and 10 participants in Experiment

2b, who did not follow instructions or categorized on the basis of neither form nor detail

(AD and BC grouping).

Categorization as a function of procedural mindsets (Experiment 2a). In general, participants were more likely to categorize products in terms of form, confirming that

form represents an essential high-level feature and detail represents a superficial low-

level feature. Across all six sets, we found a consistent pattern that a greater percentage

of participants categorized products based on their form when induced to high-level of

construal (see Table 2). Analyses of our categorization index indicated that, as predicted,

participants who engaged in high-level construal (via generating superordinate

categories) were more likely to categorize products in terms of form than those who

engaged in low-level construal (via generating subordinate exemplars) (Mhigh = 5.63 vs.

Mlow = 5.18; t(128) = 2.01, p < .05). This result confirms that form relative to detail represents a high-level feature.

Categorization as a function of BW vs. color (Experiment 2b). As in Experiment

2a, participants were more likely to categorize products in terms of form. Across all six sets, we again found a consistent pattern that a greater percentage of participants categorized products based on their form when presented with BW imagery (see Table 2).

More importantly, as predicted, analyses of the categorization index revealed that

participants who saw products in BW were more likely to categorize products based on

form than those who saw products in color (MBW= 5.71 vs. Mco= 5.21; t(138) = 2.10, p <

.05). So, findings from Experiments 2a and 2b support our argument that BW (vs. color) imagery promotes a focus on high-level features such as the product’s form, much like high-level (vs. low-level) construal does.

PANAS results. We analyzed responses to the PANAS scales to test whether there were any differences in (positive or negative) affective states as a function of BW vs. color presentation format. Analyses revealed no significant difference in either positive

(t(138)= .01, p=.99) or negative (t(138)= .73, p=.47) affective state (see Table 3), nor did

these variables significantly correlate with our categorization index. Moreover, when we

included positive and negative mood as a covariate in our analysis, the pattern of results

did not change. These data are inconsistent with the possibility that differences in

affective states served as an alternative mediator (or confound) for the effect of BW vs.

color imagery on categorization in Experiment 2b.

One might similarly suggest that specific emotions elicited by exposure to BW vs.

color imagery, such as nostalgia, may underlie the effects. To address this issue, we

analyzed responses to each individual item of the PANAS (with the addition of

nostalgia). As Table 3 shows, there were no significant differences between BW and color condition on any of the items, including how nostalgic participants felt (t(138)= .11, p=.91). Although nostalgia was significantly correlated with the categorization index (r=

-.19, p=.02), including it as a covariate in our analysis did not change the effect of BW

vs. color imagery on the categorization index (t(137)=2.16, p<.05 ). These data are

inconsistent with the assertion that nostalgia served as an alternative mediator (or

confound) for the effect of BW vs. color imagery on categorization.

To summarize, Experiment 2a showed that when participants were induced to

high-level (vs. low-level) of construal, they tended to sort objects based on form (vs.

detail). Experiment 2b showed that when participants were presented with BW (vs. color)

imagery, they demonstrated the same tendency of categorizing objects on the basis of

form (vs. detail). Taken together, these results confirmed that form (vs. detail) is a high-

level (low-level) feature (Experiment 2a) and supported that BW (vs. color) promotes a

focus on high-level (vs. low-level) feature. We also found no systematic differences in

the experience of any emotions, including nostalgia, as a function of BW vs. color.

3.4. EXPERIMENT 3

Experiment 3 is designed to show that BW (vs. color) increases the tendency to

segment continuous streams of behavior into fewer, broader (vs. more, narrower) units, as well as interpret various actions as ends (vs. means). It consists of two parts. In part one,

we used a classic assessment of abstract, schematic processing: how perceivers segment

or “chunk” continuous streams of behavior (Newtson 1973; Newtson and Engquist 1976).

Past research shows that those who engage in more abstract, high-level information

processing tend to ignore incidental details and instead focus on broader patterns of

behavior, leading to behavior segmentation that emphasizes fewer, larger units

(Henderson et al. 2006; Markus, Smith, and Moreland 1985; Wakslak et al. 2006). Thus,

we expect that BW (relative to color) imagery to produce parallel effects. Using videos as

stimuli, another purpose of this study is to see whether the effects of BW vs. color

imagery extended beyond pictures to videos. We expect similar effects irrespective of

whether BW vs. color imagery is presented in picture or video format.

In part two, we used the classic Behavioral Identification Form (BIF; Vallacher

and Wegner 1989) to measure the tendency to construe behaviors in high vs. low level

terms. An important goal of this study is to test the possibility that BW vs. color imagery

can create high-level vs. low-level construal as a procedural mindset. Past CLT research indicates that inducing participants to construe an event in higher- vs. lower-level terms

can promote a tendency to construe subsequent unrelated events in a similar fashion

(Freitas, Gollwitzer, and Trope 2004; Förster, Friedman, and Liberman 2004; Fujita et al.

2006). To test this, after participants completed the behavior segmentation task in part

one of the study, we used the BIF to assess their construal of behaviors unrelated to those depicted in the segmentation task. To the extent that BW vs. color videos can induce

high-level and low-level construal as procedural mindsets, we might expect that those

exposed to BW (vs. color) videos would construe subsequent unrelated behaviors in

higher-level (vs. lower-level) terms.

Method

We recruited 40 undergraduate students taking summer courses to participate in

this computer-based study in exchange for course credit. The critical manipulation was

whether the videos shown in part one of the study were BW or color. Participants were

randomly assigned to one of the two conditions. We asked them to imagine that they had

secured a new position in a film production company and had been asked to view three

short videos that were currently in production, with following instructions (Henderson et

al. 2006; Wakslak et al. 2006):

“The assignment your boss gave you is to watch three videos and to segment what

you see into actions that seem natural and meaningful to you. While watching these

videos, you will be asked to click a button when, in your judgment, one meaningful

action ends and another begins. There is no right or wrong way to do this; it’s up to you

to decide whether or not an action seems natural and meaningful to you.”

We then presented three videos in the same sequence to all participants. They first watched the classic Heider and Simmel’s (1944) animated film of shapes moving around a rectangular object (90 seconds long). Henderson and colleagues (2006) used this video in a behavior segmentation task to assess changes in construal level. Following their lead, we told participants that the moving shapes in the video symbolically represented an event that took place during a camping trip for young teenagers. Participants then watched a stop motion animation video (103 seconds long) that presented a sequence of what appear to be unrelated actions (e.g., washing a knife, measuring and sawing a board, using a screwdriver, cooking a lobster and vegetables). Finally, they watched an animated film (216 seconds long) depicting an elderly man selling noodles on a street for his living despite his shaking hands (e.g., receiving order, cooking noodles, serving noodles, changing a light bulb). We selected these three videos to vary in content and format.

While watching each video, participants were instructed to press a key each time they perceived that a meaningful action had ended and another had begun. The number of meaningful behavioral segments served as the measure of construal level, with fewer segments suggesting enhanced high-level construal.

In part two of the study, to examine whether any change in construal level induced by the videos would “carry over” to subsequent unrelated contexts as a procedural mindset, we asked participants to complete a second task adapted from the

Behavioral Identification Form (BIF; Vallacher and Wegner 1989). The BIF presents participants with target behaviors (e.g., making a list) and asks them to choose which of two re-descriptions of this behavior they prefer. One description emphasizes the abstract

ends achieved by the behavior (“why” one engages in the behavior: e.g., getting

organized) whereas the other emphasizes the concrete means by which to achieve the

behavior (“how” one engages in the behavior: e.g., writing things down). We presented

only eight of the original BIF items for the sake of time. To ensure that any effect was not

dependent on the frequency or commonality of a given behavior, we selected four items

that reflected what we intuited would be more common for undergraduate students, and

four items that were less common (see Table 4). We coded responses such that

preferences for the concrete, low-level identification were given the value of 0, and preferences for the abstract, high-level identification were given the value of 1. We summed these item scores and created an abstraction index ranging from 0 to 4 for both common and uncommon behaviors, with higher scores indicating greater high-level construal.

Results and Discussion

We analyzed the data from the behavior segmentation task using a 2 (presentation format: BW vs. color) X 3 (video clip: video 1 vs. video 2 vs. video 3) repeated measure

ANOVA with presentation format as a between-subjects factor and video as a within- subjects factor. Because the distribution of behavioral segments was positively skewed, we transformed the data using a logarithmic function and conducted our analysis on this transformed variable (for ease of interpretation though, we present the raw means in

Table 4). As predicted, our analysis revealed a significant main effect of presentation format (F(1, 38) = 6.36, p <.05). More specifically, participants who watched BW videos

27 segmented the behaviors into fewer units (MBW=2.21) than did those who watched color videos (Mco = 2.67). Neither the main effect of video (F(2, 76) = 1.03, p =.36) nor the interaction between presentation format and video (F(2, 76) = 2.00, p =.14) was statistically significant. These data suggest that watching BW (vs. color) videos promotes high-level (vs. low-level) construal. Not only do they conceptually replicate Experiment

1 and 2, they also suggest that the effect of BW (vs. color) imagery on construal level is not limited to pictures, but may also extend to videos.

We next analyzed the abstraction index calculated from participants’ responses to eight BIF items using a 2 (presentation format: BW vs. color) X 2 (commonality: high vs. low) repeated measure ANOVA with presentation format as a between-subjects factor and commonality as a within-subjects factor. The interaction between presentation format and commonality was not statistically significant (F(1, 38) = .03, p = .87), but the main effect of commonality was significant (F(1, 38) = 11.65, p < .01). The latter revealed that participants generally preferred to describe common relative to uncommon behaviors

(Mcommon = 2.85 vs. Muncommon = 2.33) in more abstract, high-level terms. More importantly, however, as predicted, participants who watched the BW videos tended to prefer more abstract re-descriptions of behaviors (MBW = 3.03) than those who watched color videos (Mco = 2.15; F(1, 38) = 13.67, p < .001). Table 5 describes the choice probability for each of the eight items as a function of condition. Thus, these findings suggest that not only can BW vs. color imagery impact construal of the focal objects and events, it can also impact people’s construal of subsequent unrelated stimuli by inducing construal level mindsets.

To summarize, Experiment 3 showed that the perception of BW (vs. color)

imagery promotes high-level (vs. low-level) construal in the sense that it led people to

segment continuous streams of behavior into fewer, broader units (vs. more, narrower

units; in part one) and interpret various actions as ends (vs. means; in part two). We also

found that the effect of BW vs. color imagery extended beyond pictures to videos, and

carried from one task (i.e., behavior segmentation task in part one) to another, unrelated

one (i.e., action identification task in part two).

3.5. EXPERIMENT 4

Experiments 1-3 support our main propositions that BW (vs. color) imagery is

associated with and promotes high-level (vs. low-level) construal. Experiments 4 and 5

are designed to investigate the implications of these findings for common consumer

decisions. As noted earlier, CLT research indicates that high-level relative to low-level construal enhances sensitivity to the primary and essential features rather than the secondary and incidental features of objects and events, leading people to weight these attributes differently in evaluation and choice (Eyal et al. 2009; Fujita et al. 2008; Fujita

et al. 2006; Torelli and Kaikati 2009; Trope and Liberman 2000). Drawing from these

findings, we reason that to the extent that BW (vs. color) imagery evokes high-level (vs.

low-level) construal, it should lead people to become more sensitive to the primary and

essential (vs. secondary and incidental) features of consumer products. Thus, we predict

that BW vs. color presentation of products should increase the perceived importance of

the primary, goal-related attributes of the product relative to the secondary, goal-

irrelevant attributes. We tested this hypothesis in Experiment 4.

Method

Experiment 4 implemented a 2 (presentation format: BW vs. color) x 2 (attribute:

primary vs. secondary) mixed factorial design, with imagery as a between-subjects factor

and attribute as a within-subjects factor. We recruited 125 undergraduate students from

an introductory marketing class, who participated in this computer-mediated study in

exchange for course credit. We introduced our study to participants as an experiment

designed to develop advertising tag lines for a camping radio. Participants read the

following information:

“This radio is targeted at people who go on camping trips. Many camp locations

in the U.S. have poor reception and most radios don’t work as well. A recent study

showed that over 80% of the popular camping sites in the U.S. received an acceptable

signal from only one radio station nearby. Yet, many people like to take a radio on their

camping trips because it makes them feel like they are still part of the ‘civilization’ even

though they are away from people. This radio puts out nice sound and is rugged enough

to be used for camping trips. Many campers rent this type of a radio from camp offices

across the country.”

We reasoned that informing participants that the radio is to be used on camping

trips would lead them to understand that physical attributes such as size and weight are

goal-relevant and primary features, as the radio would have to be carried and transported.

At the same time, since camping sites can only tune to only one radio station, station- related features, such as “multi-station presets” (a feature which allows users to quickly tune to their favorite radio stations) and “high precision tuner” (which allows the radio to distinguish two stations that share similar radio frequencies), are less useful and thus secondary. To provide empirical support for these assumptions, we conducted a pilot study (N = 55). Participants were presented with the scenario above and asked to rate how important each of the four attributes was using a 9-point Likert scale (1 = Not at all important, 9 = Very important). Results confirmed that participants considered the two physical attributes to be more important and primary (Msize = 6.33; Mweight = 6.35) than

the two station-related attributes (Mpresets = 5.53; Mtuner = 5.13). Specifically, the average

of the two primary attributes (Mprimary = 6.34) was significantly higher than the average of

the two secondary attributes (Msecondary = 5.33; F (1, 54) = 21.41, p < .001).

Consistent with the cover story, participants in Experiment 4 generated taglines

for the target product. Afterwards, they rated the importance of four attributes of the radio

(primary attributes: size and weight; secondary attributes: multi-station presets and high-

precision tuner) on a 9-point scale (1 = Not at all important, 9 = Very important).

Critically, we presented the picture of the radio either in BW vs. color when participants

read the scenario and rated the importance of attributes (see Figure 3). Our interest was

whether or not BW vs. color presentations of the radio would influence the relative

weighting of these primary and secondary attributes. If BW (vs. color) presentation

enhances high-level (vs. low-level) construal, we would expect that participants would

perceive the physical attributes to be more important relative to the station-related attributes in BW condition relative to color condition.

Results and Discussion

Ratings within attribute type (primary vs. secondary) were averaged to create a single index for each attribute type. We then analyzed these data using a 2 (presentation format: BW vs. color) x 2 (attribute: primary vs. secondary) repeated-measure ANOVA with presentation format as a between-subjects factor and attribute as a within-subject factor. Results revealed a significant main effect of attribute (F(1, 123) = 28.58, p <

.0001). This effect replicates our pilot data, and supports our assumption that the physical

attributes of the radio (Mprimary = 6.47) were more goal-relevant and primary compared to

the station-related attributes (Msecondary = 5.58), based on the scenario presented to participants. Results also indicated a significant main effect of presentation format. Color

(Mco = 6.28) relative to BW (MBW = 5.77) pictures increased the perceived importance of

all of radio attributes (F(1, 123) =7.07, p < .01). Critically, as predicted, the interaction

between attribute and presentation format was marginally significant (F(1, 123) = 3.58, p

= .06). More specifically, as depicted in Figure 4, planned comparison revealed that

participants tended to weight the primary over secondary attributes to a greater extent

when exposed to BW (Mprimary = 6.38 vs. Msecondary = 5.16; F(1, 55) = 21.68, p < .0001) as compared to color imagery (Mprimary = 6.57 vs. Msecondary = 5.99; F(1, 68) = 7.21, p = .01).

Looked at another way, whereas presentation format did not impact the consideration of primary features (MBW = 6.38 vs. Mco = 6.57; F(1,123) = .59, p = .44), those presented

with BW imagery were significantly less likely to give consideration to secondary

features as compared to those exposed to color imagery (MBW = 5.16 vs. Mco = 5.99;

F(1,123) = 10.55, p < .01). These results support our prediction that BW (vs. color) imagery increases the perceived importance of the primary, goal-related attributes of the product relative to the secondary, goal-irrelevant attributes.

Some might interpret the lack of a cross-over interaction as inconsistent with predictions. That is, both BW and color imagery appear to have led to similar weighting of primary features. Generally speaking, one should expect to find that primary features receive more weight in general in consumer evaluation and decision-making context than secondary features. As such, consistent with other CLT research, we emphasize the relative rather than absolute weighting of primary and secondary features. We might note that the absence of condition effects on the absolute weighting of primary features is common in the literature (Fujita et al. 2008; Trope and Liberman 2000). Thus, the absence of a cross-over interaction does not undermine our theoretical assertions.

3.6. EXPERIMENT 5

In Experiment 4, we showed that BW (vs. color) imagery can influence how people weight primary vs. secondary features in the consideration of consumer products.

Experiment 5 examines the implications of these changes in feature weighting for consumer choice. That is, can BW (vs. color) imagery enhance preferences for consumer products that are superior on primary (vs. secondary) features?

Method

Experiment 5 implemented a one-factor (BW vs. color) between-subjects design.

We recruited 94 undergraduate students from an introductory marketing class, who participated in this computer-mediated study in exchange for course credit. To facilitate introduction of consumer products that differ in superiority of primary vs. secondary features, we presented participants with a scenario similar to the one used in Experiment

“Imagine you went camping with your close friends. There would be no electricity in the camping site. But you and your friends are hoping to enjoy some music while camping. You don’t have a portable radio with you, and are looking for something that can play music and give decent sound. Fortunately, the campsite manager is able to rent a radio which operates without electricity. The manager told you that because the camp location is remote, you can play only one station.”

Given this camping scenario, we assumed that participants would understand that rental price, in addition to physical characteristics (e.g., size and weight), represents primary attributes for evaluation and choice. By contrast, we assumed that they would understand that aesthetic design (e.g., a nice display) and station-related features (e.g., multiple station pre-sets and high precision tuner) represent secondary attributes. To provide empirical support for these assumptions, we conducted a pilot study (N = 84) in which participants read the scenario and rated how important each of the four attributes was using a 9-point Likert scale (1 = Not at all important, 9 = Very important). Results confirmed that participants considered the two primary attributes to be more important

(Mprice = 6.17; Mphysical = 4.44) than the two secondary attributes (Mstation-related = 3.24;

Mdisplay = 3.57). Specifically, the average of the two primary attributes (Mprimary = 5.30) was significantly higher than the average of the two secondary attributes, (Msecondary =

3.40; F (1, 83) = 62.16, p < .0001).

Drawing from these pilot data, we presented participants in Experiment 5 with information and pictures of two radios (see Figure 5), and asked them which one they preferred. One radio (Option A) was superior on the basis of the primary attributes, whereas the other (Option B) was superior on the basis of the secondary attributes.

Specifically, both radios were described as having equally good sound quality, as indicated by their star ratings. However, Option A had a lower rental price ($10 per day) and appeared smaller and lighter. By contrast, Option B featured a more attractive display design along with multi-station presets and high precision tuner buttons, but had a higher rental price ($18 per day) and appeared larger and heavier. If BW (vs. color) presentation enhances high-level (vs. low-level) construal, we would expect that participants prefer

Option A over Option B in the BW relative to color condition.

Results and Discussion

Among the 94 participants, 58 chose Option A and 36 chose Option B. That participants were generally more likely to choose Option A over Option B, together with our pilot data, supports our assumption that the former was viewed as the choice option with superior primary (relative to secondary) features. More critically, as expected, a chi- square test revealed that those presented with BW pictures of the two radios were

significantly more likely to choose Option A over Option B (73.91%), compared to those

presented with color pictures (50.00%; X2(1, N = 94) = 5.68, p < .05). These results support our prediction that BW (vs. color) presentations of products can increase the choice probability of the option with superior primary, but inferior secondary, attributes.

In other words, in this particular study, participants in the color condition showed a greater willingness to spend more money for the choice option that contained unnecessary secondary features. This suggests that at times, by emphasizing secondary features, color relative to BW imagery may lead to sub-optimal consumer decisions.

3.6. Summary and Managerial Implications

In this research, we focus on studying the relationship between BW (vs. color) imagery and high-level (vs. low-level) construal. Using an IAT, Experiment 1 provided the important evidence that people associate BW vs. color pictures with high-level vs. low-level construal, respectively. Based on this association, the next two studies tested the novel hypothesis that perception of BW (vs. color) imagery promotes high-level (vs. low-level) construal. Experiment 2a and 2b adopted a categorization task and confirmed that form relative to detail is an essential, high-level feature, and that BW (vs. color) imagery leads people to focus on form (vs. detail) in a manner similar to high-level (vs. low-level) construal. Experiment 3 demonstrated that BW vs. color imagery not only influences the construal of the focal objects (as assessed by a behavior segmentation task), but may also induce procedural mindsets that impact the construal of subsequent unrelated material (as assessed by a subsequent action identification task). This study also

showed that the effect of BW vs. color can extend beyond pictures to videos.

Experiments 4 and 5 explored the implications of this effect for consumer behavior,

examining the impact of BW vs. color imagery on consumer product feature evaluation

(Experiment 4) and product choice (Experiment 5). Specifically, BW vs. color imagery

enhances the perceived importance of primary vs. secondary product features, and leads

consumers to prefer products with superior primary relative to secondary features.

Collectively, these findings support our assertion that BW vs. color imagery is associated

with and promotes high-level vs. low-level construal, respectively.

Implications for Marketing and Consumer Behavior

Marketing research on the effects of BW vs. color imagery has generally focused on whether the high cost of using color in marketing can be justified by any positive effects (e.g., which attracts greater attention? Which is remembered better? Which promotes positive evaluations of products?). Fewer studies have examined more nuanced predictions, such as the possibility that BW vs. color imagery directs attention to distinct aspects of ads and products. Research that has addressed this issue has largely been conducted in isolation and has lacked an integrative theoretical framework (Bohle and

Garcia 1987; Katzman and Nyenhuis 1972; Kumata 1960). In the present work, we have attempted to present a theoretical framework that not only accounts for these past findings, but also generates new predictions. Not only do these studies explore how BW

vs. color imagery impacts representation or construal of consumer products, but they are

also among the first to explore directly the consumer behavior implications of such

differences in attention and information processing.

One key implication of our theoretical perspective is that it questions the assertion that color is always superior to BW in advertisement. Although color may have positive effects, such as promoting attention, memory, and general positive evaluations

(Fernandez and Rosen 2000; Gardner and Cohen 1964; Gronhaug et al. 1991; Hornik

1980; Lohse 1997; Pallak 1983; Percy and Rossiter 1983), the present findings also suggest that by highlighting secondary and incidental aspects, color ads may also distract consumers from attending to the more essential and primary features of the advertisement and advertised product. For marketers, the present work provides profitable opportunities by suggesting the need to consider carefully whether to use BW vs. color imagery in advertisements. If a product is superior on a primary feature, for example, marketers should consider using BW imagery to draw attention to these positive features. By contrast, if a product is superior on a secondary feature, marketers should consider using color imagery. Thus, the decision to use BW vs. color imagery may be an important one when tailoring messages to consumers. Our findings also ring the alarm to consumers and guide wiser consumption. As suggested in Experiment 5, color can re-direct our attention

from primary to secondary attributes of consumer products, leading to a greater

willingness to pay premiums for products with unnecessary and superfluous features.

Background and Motivation for the Second Essay

The present findings may have implications for understanding how people visualize various events in their “mind’s eye.” To the degree that the processing of BW

vs. color imagery and construal level are associated, we should not only expect that BW

(vs. color) imagery promotes high-level (vs. low-level) construal, but we might also

expect the reverse. That is, whereas high-level construal may promote visualization of

objects and events in BW, low-level construal may promote visualization of objects and events in color. To the extent that this is true, we might also predict that people will use

BW to visualize psychologically distant events, and use color to visualize psychologically proximal events. This suggests, for example, that people may picture the distant future in

BW and the near future in color. These possibilities may provide insight into the subjective experience of high-level and low-level construal, an insight largely lacking in the current CLT literature. We investigate these possibilities in the next essay.

Knowing that BW vs. color imagery impacts construal level may also have important implications for matching effects in persuasive advertisements. Research suggests that a match in construal level between consumer and advertisement enhances persuasion (Fujita et al. 2008; Kim, Rao, and Lee 2009; Tsai and Thomas 2011). Similar effects should emerge with a match between BW vs. color and whether consumers are engaged in high-level vs. low-level construal. Thus, a persuasive appeal concerning a temporally distant vs. near event (which should evoke high-level vs. low-level construal among consumers, respectively; Trope et al. 2007) should be more persuasive if accompanied by a BW vs. color image, respectively. Matching, however, may also be

important to consider within aspects of the persuasive appeal itself. A persuasive appeal

that highlights high-level, “why” arguments vs. low-level, “how” arguments should be more persuasive when accompanied by BW vs. color imagery, respectively. The next essay also tests these predictions.

Chapter 4: On Visualizing Distant and Near Future Events in Black-and-White vs. Color

In this second essay, we focus on the degree to which people’s visual representations of the future are characterized by black-and-white (BW) relative to color imagery. The presence of rods and cones in the human eye allows people to process both

BW and color visual information, respectively (Gegenfurtner and Sharpe 2001). Just as human eye can perceive both BW versus color stimuli, we propose that the mind’s eye can similarly construct both BW versus color images. On the basis of construal level theory (CLT; Trope and Liberman 2003; 2010), we postulate a novel hypothesis that as the temporal distance of future events increases (vs. decreases), people’s visual representations of these events will become increasingly BW (vs. colorful).

Consumers frequently make purchase decisions about products to be consumed or experienced some time in the future. Activities such as planning a vacation, deciding on whether to purchase insurance or product warranty, and selecting an appropriate retirement program all require imagining what the future will look like. Indeed, a common advertising tactic is to encourage consumers to imagine the future experience of consuming or interacting with the advertised product. For example, ads prompt consumers to imagine themselves in a new car, or to picture what their living rooms would look like with new furniture. Supporting this marketing practice, research

41 demonstrates that consumers are more likely to purchase or use products after they visualize future interactions with those goods (Babin and Burns 1997; Carroll 1978;

Gregory, Cialdini, and Carpenter 1982; Dahl and Hoeffler 2004; Phillips 1996; Phillips,

Olson, and Baumgartner 1995). Visualizing the future can also motivate consumers to engage in important future-directed behavior, such as saving for retirement (Hershfield et al. 2011). Future-directed imagery therefore can play an important role in consumer behavior.

What we investigate in the present paper is how consumers form these images of future events, and what these images look like in their “mind’s eye.” This is a critical question given previous work suggesting that advertising appeals are more successful to the degree that marketers can match the image that their materials conjure with the image that consumers “see” in their own mind’s eye (Higgins 2000; Petrova and Cialdini 2005;

Petty and Wegener 1998; Zhao, Dahl, and Hoeffler 2014). To develop more effective advertising appeals, then, marketers must understand what consumers see when they imagine the future. What is surprising is that although there is an extensive body of research both in marketing and psychology that examines people’s future-directed thinking (Atance and O’Neil 2001; Gilbert and Wilson 2007; Suddendorf and Corballis

2007; Trope, Liberman, and Wakslak 2007), no work to date has specifically addressed how people visually represent the future. Thus, what people “see” when they are asked to visualize the future is largely unknown. Our research attempts to fill this gap.

In what follows, we present a theoretical argument as to why people increasingly

rely on BW vs. color imagery when constructing visual representations of events that temporally extend into the future.

4.1. Theoretical Development

Shape versus Color

Research suggests that shape and color comprise two o f the most important

elements in visual representation (Hanna and Remington 1996; Lafer-Sousa and Conway

2013; Tsal and Lavie 1988). They may differ, however, in their informational value and

function. We propose that whereas shape represents an essential, high-level visual feature

of objects and events, color represents an incidental, low-level visual feature.

We highlight two principles from visual perception theories – the principle of invariance and the principle of essentiality – to support this assertion. First, shape is generally more resistant to contextual variation relative to color (Arnheim 1974). The perception of color changes as a function of viewing angle and surrounding brightness of the environment. Shape, by contrast, is less affected by such situational variation and thus represents more invariant information relative to color (Steidle, Werth, and Hanke 2010).

Second, research suggests that people use shape rather than color to identify objects because it has a greater power of discrimination (Arnheim 1974; Biederman 1987;

Biederman and Ju 1988; Lowe 1984; Mapelli and Behrmann 1997). For instance, some early studies showed that when participants were asked to identify an ambiguous image

(e.g., ink blots), their responses were predominately based on the shape rather than the

color of the image (Oeser 1932; Vernon 1933).

The principle of essentiality is further consistent with the two criteria posited by

CLT to distinguish when a feature can be considered high-level versus low-level: centrality (changing a high-level feature has greater impact on the meaning of an object than changing a low-level feature) and subordination (the meaning of low-level features depends on high-level features more than vice-versa; Trope and Liberman, 2010). First, whereas differences in color reflect relative differences on a continuous wavelength of light (e.g., blue vs. red sedan), differences in shape can reveal qualitative differences between classes of objects (sedan vs. SUV). Thus, changing the color of an object has less impact on its meaning than changing its shape. Second, although color is key to some judgments – such as when the color of a fruit signals its palatability (e.g., we identify a yellow banana to be more edible than a green banana) – shape plays an even more important role in object identification as it helps us identify what the fruit is (e.g., a banana or a grape) in the first place. The color green is diagnostic of the palatability of banana, but not so much for grape—that is, the meaning of color (as a low-level feature) will depend on shape (as a high-level feature) more than vice versa. This analysis shows that color relative to shape is generally less effective in conveying the essential nature of objects and is thus treated as redundant or unnecessary information in object identification (Brockmann 1991; Dooley and Harkins 1970; Rossiter 1982).

On the Function of BW versus Color Imagery

To the extent that shape is indeed a high-level visual feature – and color a low-

level visual feature – CLT would then suggest that temporal distance should moderate the

extent to which people use these two types of information in the construction of visual

representations. When events are temporally distant, people should engage in high-level

construal, focusing on high-level shape information relative to low-level color

information to generate mental images. By contrast, when events are temporally

proximal, people should engage in low-level construal, incorporating low-level color

information into their visualizations. This enhanced focus on shape (relative to color)

when visualizing distant (relative to near) future events should result in mental images

that are increasingly marked by BW rather than color imagery.

In evaluating this prediction, it is important to consider the functional basis of visually focusing on shape relative to color when representing the distant relative to near future. When events (e.g., buying a car) are in the distant future, detailed information about color (e.g., blue vs. red cars) is generally unavailable and subject to change. Rather than incorrectly make assumptions about what colors may be present, it may be more adaptive to construct visual representations on the basis of information that is more stable and thus more likely to be true – i.e., shape (sedan, SUV, or truck). BW images should result from this focus on shape but not color. As color information becomes increasingly available and reliable with the passage of time, however, it makes sense to incorporate this newly acquired information. As such, it may become increasingly adaptive to engage in color imagery as events become closer in time. Metaphorically, just as artists might

draw the global shapes of objects in BW first and then fill in the color details afterward,

people may first primarily rely on BW to “sketch” distant future events and then

increasingly incorporate color as those events loom closer in time.

The first essay provides some preliminary evidence consistent with this

theoretical framework. In the first essay, we proposed and found that exposure to BW

relative to color media (such as pictures and videos) evoked high-level relative to low-

level construal. This suggests that there is an association between BW imagery and high-

level construal, and color imagery and low-level construal. Although evidence of this

association is consistent with the predictions of the second essay, it is important to note

that the first essay tested a hypothesis that is distinct from that of the current essay. First, the present essay explores this association in the opposite causal direction of previous essay – i.e., we examine the effect of temporal distance (vs. proximity), and corresponding high-level (vs. low-level) construal, on BW (vs. color) imagery.

Examining this reverse causal direction not only reveals the cognitive operations by which people construct visual representations of distant versus near future events, but also provides new insight into what those representations “look” like in the mind’s eye.

To the best of our knowledge, the present work is the first to explore the influence of psychological distance (and correspondingly, construal level) on visual representation.

Second, whereas the first essay focused on the use of BW versus color images in visual media, this paper focuses on people’s mental imagery – what they “see” when they imagine an object or event. Although related, the two types of imagery are distinct.

Finally, although the first essay provides evidence for an association between construal

level and BW (vs. color) imagery, the present work proposes a functional account for

why this association exists. That is, we propose that it is useful for people to visualize

distant (vs. near) future events in BW (vs. color) given constraints on the types of visual

information available. As such, this work goes beyond merely demonstrating an

association between two concepts – it attempts to articulate why people associate these

concepts in the first place.

The Current Research

Note the following two important points about the current research. First, our

predictions about what mental images of the distant versus near future look like are

necessarily relative. We cannot logically deduce that distant future images will be

exclusively BW whereas near future images will be vivid color. What we propose instead is that given that people are more sensitive to shape relative to color information as

temporal distance increases, their visual representations of distant relative to near future

events will increasingly appear in BW. We constrain ourselves to making a relative comparison – the claim that the distant future is seen relatively more in BW is essentially the same as the claim that the near future is seen relatively more in color.

Second, it is also worth contrasting our logical argument from a simpler claim that visualizations of distant relative to near future events are more impoverished. We do not dispute that images of the distant relative to near future may be less rich or nuanced. The key contribution of the present work, however, is that it highlights what kind of information gets subtracted over time, and what kind of information is retained.

Specifically, by suggesting that shape is a high-level visual feature and color is a low- level visual feature, we are able to predict that color will be removed from visual representations sooner than shape. Thus, whereas the simple impoverishment mechanism assumes that shape and color will be discounted at the same rate as temporal distance increases, our theory contents that increasing temporal distance shifts people’s focus toward shape rather than color and thereby creates increasingly BW rather than color imagery.

To test the prediction that people increasingly engage in BW (relative to color) imagery to visually represent distant (relative to near) future events, we conducted nine experiments. Experiment 1 first tests two key assumptions. First, we sought to provide evidence that shape represents an essential, high-level visual feature whereas color represents an incidental, low-level visual feature. Second, we tested whether temporal distance moderates the extent to which people are concerned with shape versus color in the construction of visual representations such that focus on color relative to shape decreases more steeply as temporal distance increases. After providing empirical evidence for these assumptions derived from both visual perception and construal level theories, we test our focal hypothesis that people’s visualization of events becomes increasingly less colorful as these events extend into the future in Experiments 2a, 2b, 2c,

3, and 4. Experiments 2 and 3 ask participants to visualize distant versus near future events and assess to what extent those visual representations are characterized by BW relative to color imagery. Whereas the methodology of Experiments 2 and 3 rely on introspection, Experiment 4 tests our hypothesis behaviorally by using a reaction time-

based performance task. Experiment 5 serves as a test of mechanism. We propose that

temporal distance shifts the relative attention to high-level shape versus low-level color information. To the extent that this is true, directly manipulating people’s attention to high-level versus low-level features should produce similar effects as time on BW and color imagery. Finally, Experiments 6a and 6b explores the implications of visualizing the distant versus near future in BW versus color for consumer behavior. Given that matching messages to message recipients’ mental representations enhances persuasion

(Cesario, Higgins, and Scholer 2004; Katz 1960; Petrova and Cialdini 2005; Petty and

Wegener 1998; Snyder and DeBono 1985; Thompson and Hamilton 2006; Zhao et al.

2014), marketing appeals concerning distant (vs. near) future events should increase product evaluations and willingness-to-pay when accompanied by BW relative to color imagery.

All experiments reported in this paper were computer-mediated. Participants of

Experiment 2c and Experiment 6a were Amazon Mechanical Turk workers who completed the study for payment. Participants of all the other experiments were undergraduate students from an introductory marketing class who took part in the study in exchange for partial course credit. Most experiments were conducted in a laboratory; the sample size was determined by recruiting as many participants as possible in one day in our lab, with a minimum requirement of 35 participants per cell. The exceptions were there online studies – Experiment 2c, Experiment 5, and Experiment 6a – for which we adjusted our “stop-rules” of data collection: recruiting as many participants as possible

49 within a predetermined time window, with a minimum requirement of 35 participants per cell.

4.2. EXPERIMENT 1

The purpose of this first study is to assess two assertions. First, we test our proposition that shape represents a high-level visual feature and color represents a low- level visual feature. Second, we test the prediction that temporal distance moderates people’s sensitivity to shape versus color such that the influence of color, as a low-level visual feature, in the generation of visual representations should decay more rapidly over time relative to shape as a high-level visual feature.

Method

Experiment 1 (N = 228, 106 females) utilized a 2 (temporal distance: distant vs. near) X 2 (product feature: shape vs. color) mixed design. Temporal distance was a between-subjects factor and product feature was a within-subject factor. Upon arrival, participants were informed that the study was to collect their thoughts on electric car. We presented a cover story in which Elon Musk, the co-founder and CEO of Tesla Motors, announced that he would give away ten cars. We then asked participants to imagine that they were one of the winners of the latest design of Tesla and would be given the car five years later (vs. the next day). We also instructed them to spend a few minutes visualizing the car in their mind and then write down three things they would do with the new Tesla they would be receiving. An image of a calendar with the car arrival date circled in red

accompanied the instruction; in the distant (near) future condition, the circled date was exactly five years later (the following day).

After the visualization task, participants engaged in a bidding game frequently used in the literature to elicit WTP (willingness-to-pay) values. Participants first learned that they could ask Elon Musk questions about the car they would be receiving five years later (vs. the next day). However, they had to pay for each answer and Musk won’t answer their question if they pay too low. Therefore, their strategy was to make the best offer they could make for car features they were really concerned about at the moment, and lower offers for features they would like to know but would be okay if Musk did not take their offer. We then presented six car features including the shape of the car and the color of the car and asked participants to indicate how much they would be willing to pay

(between $0 and $500) to get information on each feature. They were told to indicate

WTP for at least three features.

Afterwards, participants indicated the extent to which they focused on the shape of the car when they visualized the car in their mind on a nine-point scale (1 = No, not at all; 9 = Yes, very much). The same question was repeated for the color of the car. Finally, participants’ prior knowledge about Tesla, Elon Musk, and electric car was assessed; their demographic information was also collected. None of these potential covariates was significant, so these variables will not be discussed further.

Results and Discussion

We subjected participants’ ratings on how much they focused on shape versus

color while visualizing the car to a 2 X 2 ANOVA. The analysis revealed a significant

main effect of product feature (F(1, 226) = 47.76, p < .0001, r = .32) such that in general,

participants focused more on shape (M = 6.59, SD = 1.81) than on color (M = 5.25, SD =

2.33) when they visualized the car in their mind. This finding supported the assertion that

whereas shape is a high-level feature, color is a low-level feature.

Importantly, this main effect was qualified by a significant two-way interaction

(F(1, 226) = 4.87, p = .028, r = .10, see Figure 6). Planned comparisons indicated that whereas participants’ focus on shape stayed unchanged across the distant and near future

conditions (Mdistant = 6.62, SDdistant = 1.67 vs. Mnear = 6.57, SDnear = 1.94; t(226) = .20, p =

.844), their focus on color decreased over time (Mdistant = 4.85, SDdistant = 2.27 vs. Mnear =

5.65, SDnear = 2.34; t(226) = -2.92, p = .004, r = .14). These results thus confirmed our

prediction that the attention people place on color decays more rapidly over time relative

to shape. Looking at the results in a different way, people’s relative attention to shape

versus color increases over time as the difference between shape and color in self-

reported focus of visualization was much greater in the distant future condition (D = 1.77; t(226) = 6.42, p < .0001, r = .28) compared to the near future condition (D = .91; t(226) =

3.34, p = .001, r = .14).

As participants were not required to indicate WTP for all car features, 47 of them did not indicate WTP for information on shape or/and color (15 for shape and 43 for color), leaving us a total of 181 data points. We used a base-10 logarithmic

transformation to adjust for excessive positive skew in the reported WTP values. For ease

of interpretation, however, all descriptive statistics are still presented in raw dollars. A

similar ANOVA conducted on the data produced a similar pattern of results. The main

effect of product feature was significant (F (1, 179) = 27.90, p < .0001, r = .26) such that

in general, participants indicated a higher WTP for information on shape (M = $210.27,

SD = 145.72) than on color (M = $130.52, SD = 122.50), suggesting that they considered

shape as a more essential high-level feature compared to color.

Again, this main effect was qualified by a significant two-way interaction (F (1,

179) = 4.87, p = .029, r = .10, see Figure 7). Planned comparisons showed that whereas

WTP for shape was fairly constant across the distant and near future conditions (Mdistant =

$221.44, SDdistant = 136.08 vs. Mnear = $199.30, SDnear = 154.43; t(179) = .62, p = .533), the WTP for color was much lower in the distant future condition, relative to the near future condition (Mdistant = $110.71, SDdistant = 106.17 vs. Mnear = $150.13, SDnear =

134.45; t(179) = -2.43, p = .016, r = .10). Put differently, the relative focus on shape

versus color increases over time as the difference between shape and color in WTP was

much greater in the distant future condition (D = $110.73; t(179) = 5.43, p < .0001, r =

.26) compared to the near future condition (D = $49.17; t(179) = 2.16, p = .032, r = .10).

Thus, using two different measures (self-reported focus of visualization and

WTP), this study established shape as a high-level feature and color as a low-level feature and that the relative weight placed on these two types of visual information changes as a function of temporal distance (with less weight placed on color relative to shape as temporal distance increases). In the subsequent experiments, we examine the

consequences that this shift in focus on shape versus color as a function of temporal

distance has for what people’s visual representations of distant versus near future “look”

like.

4.3. EXPERIMENT 2

To the extent that people focus on shape relative to color with increasing temporal

distance (as showed in Experiment 1), their visual representations of distant future events

should be characterized more by BW imagery – a mode of imagery that captures shape

but not color. By contrast, to the extent that people increasingly attend to color with

decreasing temporal distance, their visual representations of near future events should be

characterized more by color imagery. In Experiments 2abc, we manipulated whether people imagined distant versus near future events and assessed to what degree their visual representations were marked by BW versus color imagery. As an assessment of imagery, we provided participants with several versions of a picture that varied in color saturation level and asked them to indicate which picture best matched the image of the event they had created in their mind. We predicted that those imaging events occurring in the distant rather than near future would select images with lower saturation levels (and thus, characterized to a greater degree by BW rather than color imagery).

Experiment 2a

Method

Experiment 2a (N = 108, 59 females) utilized a one-way (temporal distance: distant vs. near) between-subjects design. We introduced the study as one designed to

examine how people imagine the future. We asked participants to imagine three different

scenarios (e.g., staying in a hotel for two nights, going to a theater to watch a movie,

going to a park for a picnic) as taking place a year from now (vs. a week from now). We

instructed them to “take a snapshot of the scene” in their mind, and then presented them

with three versions of the same photo, varying in color saturation level (low vs. medium

vs. high; see Figure 8).

As the saturation level decreases, images appear less colorful. As the saturation

level approaches 0% (as in our low saturation version of photos), images appear BW.

Participants then indicated which image most closely resembled what they had imagined.

We created two random scenario orders and counter-balanced these between-subjects.

Results and Discussion

We coded responses such that choices of low, medium, and high saturation pictures were given the values of -1, 0, and 1, respectively. We summed these item scores, creating a color index ranging from -3 to 3, with lower (vs. higher) scores indicating greater tendency to imagine the future in BW (vs. color). We included order as a factor in our analyses; the pattern of results was unchanged. Thus, the effect of order is not discussed further. As expected, when participants imagined the scenarios occurring in

distant future (M = .25, SD = 1.38) as compared to the near future (M = .84, SD = 1.29),

their visualization was significantly less colorful (F(1, 106) = 5.24, p = .02, r = .22).

Figure 9 plots the distribution of participants on the -3 to 3 color index. As can be seen, in the distant (near) future condition, the distribution populated more on the left (right) side of the scale, indicating a relative tendency to visualize the future in BW (color).

Although Experiment 2a provides initial evidence that people visualize the distant

relative to near future increasingly in BW relative to color, it is possible that the result

reflects methodological artifacts. For example, we manipulated temporal distance using a

between-subjects design, which may have introduced a shifting standard or response bias.

We also had participants imagine only three scenarios; a more robust sample might be

preferable. We thus attempted to replicate these findings in Experiment 2b using a

within-subject design and a larger set of scenarios.

Experiment 2b

Method

In Experiment 2b (N = 194, 86 females), participants were asked to imagine 50

scenarios (e.g., Please imagine that you are seeing a boy who is reading a book; see Table

6). These scenarios were divided into two blocks of 25 scenarios each. In the first block,

participants imagined the events taking place in the distant future (“five years from

today”), whereas in the second block, they imagined the events taking place in the near

future (“tomorrow”). Block order was counter-balanced between-subjects. After

visualizing each scenario, participants were shown four versions of a picture – varying

only in color saturation level – that depicted the imagined event. Again, the lowest

saturation level approached 0% saturation and appeared BW. Participants indicated

which picture best matched the image in their mind.

Results and Discussion

We coded responses using the values 1-4, such that the selections of images marked by increasing color saturation levels were given larger numbers. We then analyzed our data using multilevel modeling. That is, aggregating across all of the scenarios, we regressed participants’ image choice on temporal distance, statistically adjusting for the unique effects of each scenario and block order. Research suggests that multilevel or mixed modeling provides more precise and less biased effect size estimates relative to traditional analysis of variance approaches (Judd, Westfall, and Kenny 2012).

Scenario and temporal distance were entered as within-subject (Level 1) variables, and participant and block order were entered as between-subjects (Level 2) variables. A programming error inadvertently led one scenario to be omitted during the experiment.

We thus included a total of 49 scenarios in our analysis. As expected, participants were more likely to select a low saturation picture when they imagined distant future (M =

3.10, SD = .82) as compared to near future events (M = 3.17, SD = .75; γ = -.03, SE =

.007, t(9309) = 4.63, p < .0001). These results replicate the results of Experiment 2a, suggesting that visual representations of the distant versus near future are relatively characterized by BW versus color imagery.

Experiment 2c

Although Experiments 2a and 2b support our focal hypothesis that temporal

distance influences the degree to which people’s visual representations are marked by

BW relative to color imagery, there are some potential alternative explanations. The relative absence of color in visual representations of the distant versus near future may

have resulted from impoverished representations that are caused by lower levels of

motivation and ease in the visualization process. We do not dismiss these as potential explanations. We suggest, however, that the effect of temporal distance on BW relative to

color imagery results from a distinct mechanism – i.e., a shift in the relative focus on

high-level relative to low-level visual features. To rule out these alternative explanations,

we conducted Experiment 2c to examine whether motivation and ease in visualizing

distant relative to near future events indeed affects whether visual representations are

marked by BW relative to color imagery. Second and more importantly, we tested

whether there would be an effect of temporal distance on mental imagery even after

controlling for these alternative mechanisms. This way, we could empirically assess to

what degree these alternative explanations account for the phenomenon we demonstrated

in our previous studies.

Method

Experiment 2c (N = 99, 41 females) was modeled after Experiment 2b. We

selected the first ten scenarios from the 50 scenarios used in Experiment 2b to shorten the

duration of the experiment. These ten scenarios were divided into two blocks of five

58 scenarios each. In the first block, participants imagined the events taking place in the distant future (“five years from today”), whereas in the second block, they imagined the events taking place in the near future (“tomorrow”). Block order was counter-balanced between-subjects. The assessment of visual representation was the same as in Experiment

2b. Importantly, after visualizing each scenario and indicating which of the four pictures best matched the image in their mind, participants reported their motivation and ease in visualizing the event by rating how much they agreed with each of the five statements

(see Table 7) on a seven-point scale (1 = Strongly disagree, 7 = Strongly agree).

Results and Discussion

We coded responses to the visualization task using the values 1-4, such that the selections of images marked by increasing color saturation levels were given larger numbers. We then analyzed our data using multilevel modeling as in Experiment 2b.

Analyses revealed the consistent pattern with Experiment 2b. Participants were more likely to select a low saturation picture when they imagined distant future (M = 2.80, SD

= 1.00) as compared to near future events (M = 3.00, SD = .92; γ = -.10, SE = .02, t(880.9)

= 4.44, p < .0001).

A principal axis factor analysis with varimax rotation was performed on ratings provided for the five items. Inspection of the eigenvalues and factor loadings suggested that two distinct factors underlie these items (see Table 1). Items 1, 2 and 5 loaded on the first factor which we interpreted as an index of perceived ease (Cronbach’s α = .86).

Items 3 and 4 loaded on the second factor which we interpreted as an index of motivation

(Cronbach’s α = .73). The average rating on the perceived ease index was higher in the

near future condition relative to the distant future condition (M distant = 5.69, SD distant =

1.29 vs. Mnear = 5.90, SDnear = 1.16; γ = -.11, SE = .02, t(880.9) = 4.64, p < .0001). The

average rating on the motivation index was also higher in the near future condition

compared to the distant future condition (Mdistant = 5.52, SDdistant = 1.24 vs. Mnear = 5.59,

SDnear = 1.23; γ = -.03, SE = .02, t(880.8) = 1.97, p = .05).

As a critical test, we included these two factors as covariates in our multilevel

modeling and found that temporal distance still affected participants’ picture choices (γ =

-.06, SE = .02, t(884.4) = 2.99, p = .003) even after we controlled for the effects of motivation (γ = -.09, SE = .02, t(881.9) = 4.21, p < .0001) and perceived ease (γ = -.06,

SE = .02, t(884.7) = 3.02, p = .003) in visualization. The fact that even after statistically adjusting for the effect of perceived ease and motivation, visual representations of distant relative to near future events were nevertheless characterized by BW relative to color imagery suggests that although temporal distance can impact visual representation via these alternative mechanisms, they cannot fully account for our proposed effect.

4.4. Experiment 3

Although Experiments 2a-2c provide the first direct evidence that people’s visualization of the distant (vs. near) future is increasingly characterized by BW (vs. color) imagery, they relied on methodology that requires participants to select a picture that best matches how they visualized an event. Although this matching methodology is commonly used to assess visual representations (Epley and Whitchurch 2008; Zell and

Balcetis 2012), it is possible that some methodological artifacts of the task produced our

results. For example, people may have selected more BW pictures not because they

imagined the events in BW, but because they imagined the event in different colors than

those presented in the target pictures. To address this concern, we attempted to replicate

these findings in Experiment 3 using a behavioral measure. That is, we asked participants

to imagine an event in the distant versus near future, and then provided participants with

several color pencils with which to complete a line-drawing that depicted the imagined

event. We would expect that those who imagined the event occurring in the distant versus

near future to use less color when completing the drawing.

Method

Experiment 3 (N = 159, 59 females) used a one-way (temporal distance: distant vs. near) between-subjects design. As in Experiments 2a-2c, we introduced our study as one designed to examine how people imagine the future. To strengthen the temporal distance manipulation, we first asked participants to imagine what they will be doing five years from today versus a week from today. To encourage elaboration, we asked participants to spend 60 seconds on writing in response to this prompt. When this time elapsed, the computer proceeded to the next task.

Participants were then asked to imagine meeting a new neighbor who just moved to the neighborhood in which they will be living five years from now (vs. are currently living). We asked participants to imagine that this new neighbor is planning a house-

warming party over the upcoming weekend and invites them to attend. She just finished

decorating her living room and describes her new living room as follows:

“My living room has a wooden floor, and the main area is covered by a

carpet. On the carpet, there are a sofa and a big sofa table. Beside this

sofa, there is a small side table with a lamp. Also, a big flower painting is

displayed above the sofa. In the backside of the room, there are a window

above a drawer and three small paintings near an arm chair.”

After providing this description, we asked participants to close their eyes and

imagine visiting their new neighbor’s house and seeing the living room five years from now (vs. this upcoming weekend). We then provided a line drawing of the room (see

Figure 10) and instructed them to color the drawing as they imagined it in their mind. We provided each participant with 10 color pencils. Five of these pencils were of grayscale

colors (light grey, 10% French grey, 50% warm grey, 70% French grey, and black),

whereas the other five pencils were of chromatic colors (red, yellow, green, blue, and violet). The dependent variable of interest was the use of grayscale versus chromatic colors.

Results and Discussion

We identified a total of 15 items that could be colored in the line drawing. A

research assistant blind to conditions and hypotheses counted the number of items that

were colored with grayscale pencils, colored with chromatic pencils, and left blank. First,

we found that the number of items left empty was not significantly different across

conditions (Mdistant = 8.02, SDdistant = 2.89 vs. Mnear = 7.30, SDnear = 3.45; F(1, 157) =

2.04, p = .15). We then analyzed the items colored using a 2 (temporal distance: distant vs. near) X 2 (pencil color: grayscale vs. chromatic) repeated-measure ANOVA with temporal distance as a between-subjects factor and pencil color as a within-subject factor.

The analysis revealed a significant main effect of pencil color (Mgrayscale = 3.09,

SDgrayscale = 2.19 vs. Mchromatic = 4.25, SD chromatic = 2.10; F(1, 157) = 26.39, p < .0001, r =

.26), suggesting that participants in general used more chromatic pencils than grayscale

pencils to color the line drawing picture. Critically, the interaction between temporal

distance and pencil color was also significant (F(1, 157) = 4.62, p = .03, r = .17). Planned

comparisons indicated that the tendency to use chromatic pencils was weaker in the

distant future condition (Mgrayscale = 3.15, SDgrayscale = 2.16 vs. Mchromatic = 3.83, SD

chromatic = 1.66; t(157) = 2.12, p = .04, r = .11) compared to the near future condition

(Mgrayscale = 3.03, SDgrayscale = 2.24 vs. Mchromatic = 4.67, SDchromatic = 2.41; t(157) =

5.14, p < .0001, r = .26). To capture the relative usage of grayscale (vs. chromatic) pencils, for each participant we computed the percentage of items colored by grayscale

(vs. chromatic) pencils. Consistently, the average percentage across participants was higher in the distant future condition (Mdistant = 43.28%, SDdistant = 18.12%) compared to

the near future condition (Mnear = 37.43%, SDnear = 20.07%; F(1, 157) = 3.71, p =

.056, r = .15). This finding – that participants re-produced their visual representations of distant relative to near future events using fewer colors – conceptually replicates

Experiment 2 using an alternative methodology.

4.5. EXPERIMENT 4

Although Experiments 2a, 2b, 2c, and 3 all support our focal hypothesis that

people increasingly visualize the distant future in BW and near future in color, they all

relied on methods that require introspection. Experiment 4 was designed to provide

evidence using a performance task that does not require such explicit introspection,

namely the Implicit Association Test (IAT; Greenwald, Nosek, and Banaji 2003). The

IAT uses reaction times to measure the strength of association between different

concepts. Stimuli in the IAT are presented in rapid succession and participants promptly

categorize these stimuli into one of two categories, which are mapped onto the same set

of response keys. People tend to respond more quickly when two cognitively associated

categories are both mapped onto the same key. Faster responses indicate that people

cognitively associate the two categories. We hypothesize that to the extent that people

tend to visualize the distant future in BW and near future in color, an association between the concepts of distant (vs. near) future and BW (vs. color) should be formed. As such, participants should be faster to categorize BW pictures and distant future-related concepts

(and color pictures and near future-related concepts) than BW pictures and near future-

related concepts (and color pictures and distant future-related concepts).

Method

The IAT (N = 159, 93 females) presented participants with stimuli relevant to the categories of distant versus near future and BW versus color. For the categories of distant versus near future, participants saw four words related to the concept of distant future

(later, future, delay, and long-term) and four words related to the concept of near future

(now, present, immediate, and short-term). For the categories of BW versus color,

participants saw six pictures, each presented in both BW and color (see Figure 11).

Instructions regarding the key and item assignments were presented at the beginning of each block. The first two blocks of the IAT were practice blocks: Block 1 required categorizing pictures as either “BW” or “color”, and Block 2 required categorizing words as either “distant” or “near.” Blocks 3 and 4 were combined critical blocks in which BW was paired with distant and color was paired with near (or vice versa, counter-balanced between-subjects). Specifically, responses for BW and distant were assigned to one key, whereas responses for color and near were assigned to the other key. Block 5 was another practice block, with the key pairings reversed from Block

1. Blocks 6 and 7 reversed the key assignments of Blocks 3 and 4 (i.e., color paired with distant and BW paired with near, or vice versa). Blocks 3 and 4 were identified as compatible blocks because the categorization task was consistent with our hypothesis, whereas Blocks 6 and 7 were identified as incompatible blocks because the categorization task was opposite to our hypothesis. To ensure that any effect was not dependent on the order of blocks, block order (compatible vs. incompatible blocks) was counterbalanced between-subjects. Participants were instructed to complete each trial as quickly and as accurately as they could.

Results and Discussion

We analyzed IAT responses using the D-score algorithm with a 600 ms penalty

for incorrect responses (Greenwald, Nosek, and Banaji 2003). D-scores were calculated such that higher scores indicate greater strength of associations between the concepts of

BW and distant future (and color and near future) as compared to color and distant future

(and BW and near future). As predicted, people were faster during compatible blocks

(categorizing BW pictures with distant future, and color with near future) than during incompatible blocks (categorizing BW pictures with near future, and color with distant

future; Mcompatible = 821.13, SDcompatible = 811.45 vs. Mincompatible = 848.17, SDincompatible =

834.13), and this difference was statistically significant as the mean D-score significantly differed from zero (Md = .12, SDd = .53; t(158) = 2.88, p = .005, r = .22). That pairing

BW (vs. color) with distant (vs. near) future facilitated IAT performance suggests that

people indeed associate these two concepts.

That people cognitively associate BW (vs. color) imagery with the distant (vs. near) future is consistent with our hypothesis that people visualize the distant relative to

near future in BW relative to color. Importantly, this finding replicates Experiments 2a,

2b, 2c, and 3 using methodology that does not require introspection. Thus, the effect of

temporal distance on BW versus color imagery appears to be robust across diverse

methodologies.

4.6. EXPERIMENT 5

The results of Experiments 2-4 suggest that people’s visual representations of

distant versus near future events are relatively characterized by BW versus color. The

goal of Experiment 5 is to provide evidence for the proposed mechanism. We proposed

that it is a focus on the high-level versus low-level features of an event that leads people

to increasingly use BW versus color imagery as a function of temporal distance. As a test

of this mechanism, we directly manipulated participants’ attention to the high-level versus low-level features of an event by experimentally inducing high-level versus low- level construal. Manipulating people’s attention to these features via construal should have analogous effects on BW versus color imagery as manipulating temporal distance.

Method

Experiment 5 (N = 286, 112 females) was modeled after Experiment 2b. We informed participants that we were interested in understanding how people visualize events. We then asked them to imagine four scenarios (vacuuming the floor, brushing teeth, watering plants, and measuring a room). Critically, we manipulated attention to high-level versus low-level features by describing the scenarios in a manner that

highlighted their superordinate high-level ends (e.g., “Please imagine that you are watching a lady clean her house to show her cleanliness.”) versus their subordinate low-

level means (e.g., “Please imagine that you are watching a lady vacuum the floor in her

living room;” see Table 8). Previous research has shown that directing attention to these

“why” versus “how” aspects can induce high-level versus low-level construal,

respectively, which in turn impacts attention to the high-level versus low-level features of

events more broadly (Freitas, Gollwitzer, and Trope 2004; Fujita et al. 2006; Burgoon,

Henderson, and Markman 2013). We manipulated construal within-subject using a blocked design with block order counter-balanced between-subjects. In the first block, participants imagined two scenarios described in high-level terms, whereas in the second block, they imagined two scenarios described in low-level terms (or vice-versa). Scenario order (irrespective of condition) was held constant across all participants. After visualizing each scenario, participants were shown four versions of the same picture that depicted the imagined event with different color saturation levels and were asked to indicate the picture that best matched the image they had created in their minds. Again, the lowest saturation level approached 0% saturation and appeared BW.

Results and Discussion

As in Experiment 2b, we coded responses using the values 1-4, such that the selections of images marked by increasing color saturation levels were given larger numbers. As in Experiments 2b and 2c, we used multilevel modeling to analyze the data.

Aggregating across the four scenarios, we regressed participants’ picture choice on construal level, statistically adjusting for the unique effects of each scenario and block order. Scenario and construal were entered as within-subject (Level 1) variables, and participant and block order were entered as between-subjects (Level 2) variables. As predicted, participants were more likely to choose low saturation pictures when they were led to focus on the high-level “why” aspects (M = 2.97, SD = .82) rather than the low-

level “how” aspects (M = 3.07, SD = .76; γ = -.05, SE = .02, t(856.9)= 2.56, p = .01). This suggests that experimentally directing attention to the high-level versus low-level features led participants to imagine events increasingly in BW relative to color. These results provide evidence for our proposed mechanism that the effect of temporal distance on visual imagery is mediated by changes in attention to essential versus incidental features of events.

4.7. EXPERIMENT 6

In Experiments 6a and 6b, we sought to explore some of the implications of representing distant relative to near future events increasingly in BW rather than color for consumer behavior. Research suggests that marketing appeals that capture or “match” some feature of the recipient tend to produce greater attitude change (Cesario et al. 2008;

Katz 1960; Petty and Wegener 1998; Snyder and DeBono 1985). In the CLT literature, for example, research suggests that marketing materials concerning distant versus near future events were more effective when they directed attention to the high-level versus low-level features of those events, respectively (Fujita et al. 2008; Kim, Rao, and Lee

2009; Tsai and Thomas 2011). This presumably occurs because the high-level versus low-level messages highlight the very features that people naturally attend to when thinking about distant versus near future events. Such matching effects can lead to greater attitude change via misattributions of conceptual fluency (Kim et al. 2009) and via greater attention to and cognitive scrutiny of the appeals (Fujita et al. 2008). Thus, given that people tend to visualize distant versus near future events increasingly in BW rather

than color, communication appeals about distant versus near future events should be

more effective when accompanied by BW rather than color images.

Experiment 6a

Method

Experiment 6a (N = 140, 66 females) employed a 2 (temporal distance: distant vs. near) X 2 (imagery format: BW vs. color) between-subjects design. Adapting materials

used in previous research (Fujita et al., 2008), we told participants that we need their help

in testing the materials to be used in a fund-raiser for a wildlife conservation organization

(e.g., Save the Orcas Fund). Critically, to manipulate temporal distance, the fund-raising

event was described as taking place either a few years from now or a few days from now.

Participants were then presented with a brief description about Orcas and the wildlife

charity:

“Orcas are large, stocky, heavy creatures easily recognized by their

distinctive jet-black, white, and grey markings. Save the Orcas Fund is an

initiative dedicated to raising money to help protect orcas (“killer

whales”). With the start of this fund-raising campaign in a few years (vs.

in a few days), Save the Orcas Fund hopes to raise enough money to help

orcas in a meaningful, long-lasting way.”

On the next page, we then presented a BW versus color picture of a group of orcas and asked participants to indicate how much (in US dollars) they would be willing to donate to the Save the Orcas Fund a few years (vs. days) from now. To facilitate the

misattribution of any conceptual fluency from the match between temporal distance and imagery format to their attitudes (e.g., Kim et al., 2009), we instructed participants to rely on their feelings to answer this question.

Results and Discussion

We used a base-10 logarithmic transformation to adjust for excessive positive skew in the reported amount of donation, while excluding one outlier who indicated an amount more than 3SD from the sample mean. We analyzed these data using a 2 X 2

between-subjects ANOVA. For ease of interpretation, all descriptive statistics are

presented in raw dollars. Analyses revealed a significant main effect of temporal distance

(F(1, 135) = 18.14, p < .0001, r = .34). Participants were willing to donate more in the

distant future (M = $20.11, SD = $23.83) as compared to the near future condition (M =

$7.42, SD = $10.50). Analyses also revealed a significant interaction between temporal

distance and imagery format (F(1, 135) = 6.61, p = .01, r = .22, see Figure 12). Even with

the inclusion of the one outlier, the interaction remained significant (F(1, 136) = 4.72, p =

.05, r = .18). Planned comparisons indicated that participants in the distant future

condition were willing to donate more when the message was accompanied by BW (MBW

= $26.86, SDBW = $29.38) relative to color imagery (Mco = $13.35, SDco = $13.36; t(135)

= 1.94, p = .05, r = .16). By contrast, participants in the near future condition indicated a marginally greater willingness to donate when the message was accompanied by color

(Mco = $9.34, SDco = $12.06) rather than BW imagery (MBW= $5.50, SDBW= $7.57; t(135)

= 1.71, p = .09, r = .15). These findings suggest that marketing appeals concerning distant

(vs. near) future events can be more effective when presented alongside imagery that is

BW (vs. color).

Experiment 6b

Experiment 6a showed that a match between imagery format and temporal distance increases the effectiveness of marketing appeals in charity donation domain.

Yet, one might question the robustness of the effect, given that the target of the marketing materials was a BW object (i.e., orcas). As such, the goal of Experiment 6b was to replicate Experiment 6a with a different object, as well as to test the robustness of the matching effect outside the charity donation domain.

Method

Experiment 6b (N = 147, 73 females) again used a 2 (temporal distance: distant vs. near) X 2 (imagery format: BW vs. color) between-subjects design. We introduced the study as one designed to examine how people imagine new products. We then provided information of a “flying hoverboard”:

“Flying hoverboards are items we have grown accustomed to seeing them in sci-fi

and futuristic movies like Back to the Future. However, flying hoverboards are

slowly shifting from the science fiction field to becoming reality. More and more

designers and startups are trying to come up with something similar to the flying

vehicle from Back to the Future.”

To manipulate temporal distance, we told participants that a company, HUVr

Tech, has finished developing a prototype of flying hoverboard and will unveil this new product five years from now versus tomorrow. We then asked participants to spend a minute visualizing what this flying hoverboard will look like. On the next screen, we presented a BW versus color picture of the flying hoverboard. We asked participants to indicate how much they would be willing to pay (in US dollars) to purchase this product and how much they liked it (1 = Not at all, 9 = Extremely).

Results and Discussion

We used a base-10 logarithmic transformation to adjust for excessive positive skew in the reported WTP values, and excluded one outlier who indicated an amount more than 3SD from the sample mean. We analyzed the data using a 2 X 2 between-

subjects ANOVA. For ease of interpretation, all descriptive statistics are presented in raw

dollars. Main effect of temporal distance or imagery format was not significant.

Importantly, however, analyses revealed a significant interaction between temporal

distance and imagery format (F(1, 142) = 6.26, p = .01, r = .21, see Figure 13). Even with

the inclusion of the one outlier, the interaction remained significant (F(1, 143) = 4.59, p

=.03, r = .18). Planned comparisons showed that participants in the distant future condition indicated a marginally higher WTP when the flying hoverboard was presented

in BW (MBW = $257.13, SDBW = $209.13) relative to color (Mco = $163.00, SDco =

$137.46; t(142) = 1.69, p = .09, r = .14). By contrast, participants in the near future

condition indicated a marginally higher WTP when the product was presented in color

(Mco = $274.26, SDco = $418.52) rather than in BW (MBW= $181.19, SDBW= $198.45; t(142) = 1.85, p = .065, r = .15).

The same ANOVA conducted on the product liking ratings revealed a consistent pattern of results. There were no significant main effects, but analyses did reveal a significant interaction between temporal distance and imagery format (F(1, 143) = 5.21, p

= .02, r = .19, see Figure 14). Planned comparisons suggested that participants in the distant future condition indicated a marginally higher liking for the flying hoverboard when it was presented in BW (MBW = 7.05, SDBW = 1.48) relative to color (Mco = 6.37,

SDco = 1.52; t(142) = 1.68, p = .10, r = .14). By contrast, participants in the near future condition indicated a marginally higher liking for the flying hoverboard when it was presented in color (Mco = 6.82, SDco = 1.70) compared to BW (MBW= 6.14, SDBW=1.99; t(142) = 1.77, p = .08, r = .15). Collectively, findings from Experiments 6a and 6b confirm that a match between temporal distance and imagery format enhances effectiveness of marketing appeals.

4.8. Summary and Managerial Implications

Our work provides initial evidence for the novel hypothesis that visualizations of distant (relative to near) future events are relatively characterized by BW (relative to color) imagery. Experiment 1 established that people treat shape as a high-level visual feature and color as a low-level visual feature of objects and events. More importantly, it showed that attention to color relative to shape decreases (or, put differently, attention to shape relative to color increases) as temporal distance to the future event increases.

Building on this, we then reasoned that this relative shift in attention to shape versus

color would lead people to increasingly visualize distant relative to near future events in

BW versus color. Supporting this assertion, Experiments 2a-2c revealed that people report visualizing distant as compared to near future events in increasingly BW rather

than color imagery. Experiment 3 demonstrated that when asked to reproduce their visual representations in a coloring task, those who imagined the distant compared to near future were less likely to use color. Experiment 4 replicated these findings, demonstrating on a reaction time-based performance task that people associate the distant versus near future

with BW versus color, respectively. Experiment 5 provided evidence for our proposed

mechanism that this change in visual representations results from changes in attention to

high-level versus low-level features of the visualized event. Experiments 6a and 6b

explored the implications of these findings for marketing communications, demonstrating

greater willingness-to-pay and positive evaluations when messages about distant (vs.

near) future events are accompanied by BW (vs. color) images.

Experiments 1, 2c, and 5 are particularly note-worthy in that they not only

highlight construal level as the mechanism for the effect of temporal distance on BW

versus color imagery, but they also help address potential alternative explanations. One

might be tempted to dismiss our findings as merely demonstrating that distant relative to

near future representations are more impoverished and thus appear BW. Distant relative

to near future representations are more impoverished or degraded probably because

people have reduced motivation and ease in imagining events that are temporarily distant

and thus not immediately personally relevant (Petty and Cacioppo 1984; Petty, Cacioppo,

75 and Goldman 1981), or less emotionally intense (D’Argembeau and Van der Linden

2004; Van Boven, Kane, et al. 2010). We addressed these potential mechanisms by which temporal distance may impact visual representations in several ways. First, Experiment 5 manipulated construal level (rather than temporal distance) and showed that it had similar effect on BW versus color imagery. Because it held constant temporal distance and thus availability of information, amount of processing, and degree of emotionality, a mere impoverishment mechanism (based on the assumption of reduced motivation and ease in imagining distant future events) struggle to account for the observed effect. Second,

Experiment 2c explicitly measured motivation and ease of visualization and showed that the effect of temporal distance on BW versus color imagery still held after statistically adjusting for these factors. Third and most importantly, Experiment 1 provided evidence that people increasingly focus on shape relative to color when visualizing distant relative to near future events – a shift in attention that we suggest produces increasingly BW versus color imagery as visualized events become more temporally distant. Thus, although the abovementioned alternative mechanisms may partially account for the increasing absence of color in visual representations of the distant relative to near future,

Experiments 1, 2c, and 5 collectively suggested that our findings cannot simply be reduced to them.

Implications for Marketing and Consumer Behavior

This knowledge of how people see the future may have interesting implications for evaluation, judgment, and decision-making. As Experiments 6a and 6b demonstrate,

understanding how people literally see the future may have important implications for

persuasion and attitude change. Research on matching effects in persuasion suggests that

to the extent that there is a match or fit between a persuasive message and the message

recipient’s mental representation, persuasion is enhanced (Cesario et al. 2008; Fujita et al.

2008; Petty and Wegener 1998; Wheeler, Petty, and Bizer 2005). The present work

suggests that when attempting to change attitudes about temporally distant rather than near future events such as retirement, message appeals that leverage BW rather than color materials may be more effective. This implication may be particularly relevant for ongoing attempts to facilitate health promotion and disease prevention behaviors (Kreuter and Wray 2003; Noar, Benac, and Harris 2007). The benefits of many of these health promotion behaviors are not apparent until later in the future. Although counter-intuitive, to orient people to these distant future benefits, it may be more effective to present health communications in the context of BW rather than color images. We are currently conducting research to test these hypotheses.

Chapter 5: General Discussion

This dissertation work extends the existing CLT literature in a number of ways.

First, the present work is the first that suggests and establishes the interrelation between

color of imagery, psychological distance, and construal level. The first essay demonstrates that a basic component of visual imagery (presence or absence of color) can be an important antecedent variable that determines level of construal. It adds to a growing literature examining factors that lead people to construe events in higher vs.

lower-level terms beyond psychological distance, such as temperature (Ijzerman and

Semin 2010), darkness (Steidle, Werth, and Hanke 2011), visual perspective (Libby,

Shaeffer, and Eibach 2009), novelty (Förster, Liberman, and Shapira 2009), fluency

(Alter and Oppenheimer 2008), confidence (Wan and Rucker 2013), measurement unit

size (Maglio and Trope 2011), regulatory resource depletion (Agrawal and Wan 2009;

Bruyneel and DeWitte 2012; Schmeichel and Vohs 2009; Wan and Agrawal 2011) and

mood (Beukeboom and Semin 2006; Gasper and Clore 2002; Labroo and Patrick 2009).

Such factors are important to understand given the central role of construal level in

consumer information processing, evaluation, and decision-making (Trope et al. 2007).

More importantly, the second essay provides further evidence for the association

between that BW versus color imagery and construal level. This work shows this

association in the opposite causal direction – suggesting how temporal distance (and

corresponding high-level construal) evokes BW mental imagery, whereas temporal proximity (and corresponding low-level construal) evokes color mental imagery. Note that this finding not only provides additional evidence for this association, but also provides a functional account for why people associate these constructs in the first place.

That is, the association between BW versus color imagery and construal level may be the result of how people confront the challenges of visualizing the distant versus near future.

To our knowledge, the present findings are the first to provide insight on what distant versus near future events “look” like in the mind’s eye.

Second, this dissertation work may lead to the development of new experimental methodologies with which to manipulate and assess level of construal. Researchers looking to manipulating construal level could capitalize on the tendency for BW vs. color imagery to promote high-level and low-level construal, respectively. Results from

Experiment 3 in the first essay suggest that exposure to BW vs. color videos led people to construe subsequent unrelated materials in higher-level vs. lower-level terms. This indicates the possibility of developing materials that use BW vs. color stimulus to induce differences in construal level as procedural mindsets. Future research may pursue this possibility to expand the “toolbox” of procedures with which researchers can use to investigate further the role of construal level in consumer judgment and decision-making.

In addition, the second essay suggests the possibility of using BW vs. color imagery methodologically as a means of assessing construal level. Many current methods of assessing construal level are largely language-based. The most popular measure, for

example, is the Behavioral Identification Form, a questionnaire that assesses the extent to

which people prefer to describe actions verbally in terms of the abstract ends achieved

(“why” aspects) versus concrete means by which they are executed (“how” aspects;

Vallacher and Wegner 1989; see also, Burgoon et al. 2013). One common problem with

language-based measures, however, is that people might prefer one verbal description

over another due to reasons other than differences in construal level, such as a preference

for a specific phrasing or term. Many of these measures are also designed to assess

construal level as general mindsets, rather than to assess the construal of a specific event.

Assessing to what extent people imagine an event in BW versus color may address these measurement issues by assessing construal level non-linguistically and allow for assessments of subjective construal of specific events.

Third, understanding the relation between construal level and imagery may help us effectively influence consumers’ judgments and decisions. Research has demonstrated, for example, that high-level (vs. low-level) construal can enhance self-control (Fujita

2008; Fujita and Carnevale 2012). Other work has suggested that high-level (vs. low- level) construal can enhance the likelihood of finding more integrative win-win agreements in negotiation (Henderson and Trope 2009; Henderson, Trope, and Carnevale

2006), promote use of base-rates (Henderson et al. 2006; Ledgerwood, Wakslak, and

Wang 2010), and facilitate decision-making under information overload (Fukukura,

Ferguson, and Fujita 2013), among many other judgment and decision-making

phenomena (Trope et al. 2007). In all these cases, we should expect BW vs. color

imagery to have similar effects. Marketers seeking to leverage these effects may thus

consider using BW vs. color imagery as a psychological “nudge” (Thaler and Sunstein

2008).

Relating to the possibility that BW imagery enhances self-control, the second

essay further suggests interesting predictions: people who see temptations in their mind’s

eye in BW vs. color may be more likely to evidence successful self-control. Thus, when

presented with the stimulus “cake,” dieters who envision cake in BW rather than color

should be less tempted to engage in behavior that undermines their dieting goals.

Assessing how people visualize temptations may allow researchers to identify who is vulnerable to self-control failure, and to create interventions that target that vulnerability specifically (i.e., construing temptations in low-level rather than high-level terms).

Last but not least, one can suggest that this work is among the first to highlight the subjective experience of high-level vs. low-level construal. Although we know much about the antecedents and consequences of different levels of construal, less has been done to elaborate on the subjective experience of these psychological mindsets. The present work suggests part of this subjective experience entails seeing the world in BW when engaged in high-level construal, seeing it in color when engaged in low-level construal. Future work might further explore this assertion by extending this work beyond time to other dimensions of distance. The current work would suggest that people may perceive remote locations, socially distant others, and unlikely events more in BW, and may perceive close locations, socially near others, and likely events more in color.

Thus, whereas BW imagery may promote transcendence and the consideration of remote content more broadly, color imagery may promote immersion into the idiosyncracies of

direct experience. We look forward to further scientific inquiry exploring these possibilities.

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Appendix: Tables and Figures

Condition A Condition B (Compatible blocks precede incompatible (Incompatible blocks precede compatible blocks) blocks) Block Function Item Item Function Item Item Assigned Assigned Assigned Assigned To To To To Left-Key Right-Key Left-Key Right-Key 1 Practice BW Color Practice Color BW 2 Practice General Specific Practice General Specific 3 Compatible BW + Color + Incompatible Color + BW + General Specific General Specific 4 Compatible BW + Color + Incompatible Color + BW + General Specific General Specific 5 Practice Color BW Practice BW Color 6 Incompatible Color + BW + Compatible BW + Color + General Specific General Specific 7 Incompatible Color + BW + Compatible BW + Color + General Specific General Specific Table 1. Key assignments in IAT blocks

Study 2a Study 2b High vs. Low BW vs. Color Construal Imagery Groupings based on Groupings based on % grouped by % grouped by Detail Form Form Form leopard print vs. plain high heels vs. sneakers 88.24% vs. 92.75% vs. 1 (AC vs.BD) (AB vs.CD) 75.41% 82.86% spikes patent vs. plain flat shoes vs. sneakers 95.59% vs. 91.30% vs. 2 (AB vs.CD) (AC vs.BD) 86.89% 84.29% military print vs. plain high heel boots vs. sneakers 97.06% vs. 95.65% vs. 3 (AC vs.BD) (AB vs.CD) 91.80% 92.86% dot print vs. plain wedge heels vs. rain boots 95.59% vs. 97.10% vs. 4 (AC vs.BD) (AB vs.CD) 90.16% 88.57% tiger print vs. plain ankle boots vs. slippers 91.18% vs. 97.10% vs. 5 (AB vs.CD) (AC vs.BD) 83.61%. 85.71%. check print vs. plain combat boots vs. sneakers 95.59% vs. 97.10% vs. 6 (AB vs.CD) (AC vs.BD) 90.16% 87.14% Table 2. BW (vs. color) increases the tendency to categorize products based on high-level (low-level) features

Subscale and item p-value Positive .9905 Attentive .9279 Active .7892 Alert .4054 Determined .9762 Enthusiastic .6321 Excited .9013 Inspired .9653 Negative .4665 Afraid .4888 Scared .9458 Determined .9762 Jittery .9794 Irritable .2274 Hostile .3324 Guilty .6938 Nostalgia .9115 Table 3. The effect of color on responses to the PANAS items

Mean number of segments (S.D.) BW Color Video 1 12.75 (6.96) 15.85 (8.61) Video 2 12.05 (8.34) 15.40 (14.53) Video 3 10.95 (6.64) 18.55 (6.06) Mean 11.92 (5.48) 16.60 (8.81) Table 4. BW (vs. color) increases the tendency to segment behavior in fewer, broader (vs. more, narrower) units

100

Behavior The original behavior and two interpretations % chose Commonality of it high-level (bold type indicates high-level interpretation) BW vs. Color 1. Making a list 85% vs.60% Getting organized vs. Writing things down 2. Reading 95% vs.70% Common Gaining knowledge vs. Following lines of print 3. Washing clothes 75% vs.45% Removing odors from clothes vs. Putting clothes into the machines 4. Eating 75% vs.65% Getting nutrition vs. Chewing and swallowing 5. Painting a room 95% vs.75% Making the rooms look nice vs. Applying brush strokes Uncommon 6. Chopping down a tree 65% vs.30% Getting firewood vs. Wielding an axe 7. Caring for houseplants 25% vs.10% Making the room look nice vs. Watering plants 8. Measuring a room for carpeting 90% vs.75% Getting ready to remodel vs. Using a yardstick Table 5. BW (vs. color) increases the tendency to interpret behaviors in high-level (vs. low-level) terms

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Block 1 Block 2 Order Activity Order Activity 1 a boy, reading a book 26 people, walking on a busy street 2 a girl, doing laundry 27 a group of people, playing bowling 3 a lady, cleaning house 28 boys, playing basketball 4 a guy, locking a door 29 a mother, shopping for groceries 5 people, voting 30 people, watching a movie in a theater 6 a boy, brushing his teeth 31 a girl, watching TV show 7 students, taking a test 32 a baby, sleeping 8 people, greeting each other 33 college students, listening to a lecture in a classroom 9 a couple, eating a dinner together 34 a man, lifting dumbbells 10 a grandfather, growing his garden 35 a father, grilling 11 a man, driving his car 36 a woman, jumping rope 12 a mother, talking to her child 37 a family, going on the rides 13 a man, pushing a doorbell 38 people, taking a picture 14 a girl, picking apples 39 a couple, getting married 15 a man, chopping down a tree 40 a family, playing in the ocean 16 a man, measuring a room for 41 a woman, counting money carpeting 17 a girl, painting a room 42 a man, sailing his boat 18 a girl, caring for her houseplants 43 a girl, playing with her dog 19 a young boy, climbing a tree 44 an elderly couple, walking in a park 20 a couple, cooking together 45 a family, having a picnic in a park 21 people, working in an office 46 a young girl, getting a flu shot 22 students, studying in a library 47 a woman, waiting at a bus stop 23 a girl, drinking coffee 48 a group of friends, drinking beer 24 a man, running 49 a young girl, talking on a phone 25 a mother, taking care of her baby 50 girls, shopping for shoes NOTE. Scenario no. 47 was not shown to participants due to programming error.

Table 6. Lists of the scenarios used in Experiment 2b

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Factor Loading Perceived Ease Motivation It was difficult to visualize the scene. (reverse .7058 .0888 coding) I could clearly visualize the scene. .8304 .2744 I was motivated in visualizing the scene. .2650 .6766 I put much effort in visualizing the scene. .1077 .6468 I was able to “see” the scene in my mind. .7896 .3174 Table 7. Factor analysis results

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Actions Scenarios Inducing High-level [vs. Low-level] Construal Vacuuming the floor Please imagine that you are watching a lady clean her house to show her cleanliness [vs. a lady vacuum the floor in her living room]. Brushing teeth Please imagine that you are watching a boy brush his teeth to prevent tooth decay [vs. a boy move a toothbrush around in his mouth]. Watering plants Please imagine that you are watching a grandfather care for his houseplants to make his garden look nice [vs. a grandfather water plants in his garden]. Measuring a room Please imagine that you are watching a man prepare for remodeling [vs. a man measure a room using a yard stick]. Table 8. List of the behaviors and their descriptions

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Words Pictures General Specific Black-and-White Color Category Exemplar

Electronics Digital Camera

Animal Poodle

Plant Tulip

Jewelry Ring

Furniture Sofa

Vehicle Convertible

Figure 1. Stimuli used in Experiment 1 (IAT)

105

Task Stimuli Task Stimuli 1 4

2 5

3 6

Figure 2. Stimuli used in Experiment 2

106

Figure 3. Stimuli used in Experiment 4

107

7.5

6.5

6 Primary Secondary 5.5 Importance (1 (1 9) to Importance 5

4.5 Black & White Color

Figure 4. BW (vs. color) increases the perceived importance of the primary (vs. secondary) feature

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Figure 5. Stimuli used in Experiment 5

109

7.0

6.5

6.0

5.5 Near Distant Focus (1~9)

5.0

4.5

4.0 Shape Color

Figure 6. Temporal distance moderates the focus on shape versus color

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250

200

150

Near Distant 100 WTP (dollars)

0 Shape Color

Figure 7. Temporal distance moderates WTP for information on shape versus color

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Figure 8. Measures used in Experiment 2a

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35%

30%

25%

20% NEAR 15% DISTANT

% of participants of % 10%

0% Color -3 -2 -1 0 1 2 3 Greater tendency Greater tendency to

to imagine in BW imagine in color

Figure 9. Effect of temporal distance on BW versus color imagery

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Figure 10. Line drawing used in Experiment 3

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Figure 11. Color version of stimuli used in Experiment 4 (IAT)

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20 Color 15 BW

10 Donation (dollars)

0 NEAR DISTANT

Figure 12. Temporal distance moderates the effectiveness of messages used BW versus color

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350

300

250

200 Color 150 BW WTP (dollars) 100

0 NEAR DISTNAT

Figure 13.Temporal distance moderates WTP for a new product presented in BW versus color

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8.0

7.5

7.0

6.5 Color BW Liking (1~9) 6.0

5.5

5.0 NEAR DISTANT

Figure 14. Temporal distance moderates liking for a new product presented in BW versus color

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