The Florida State University
DigiNole Commons Electronic Theses, Treatises and Dissertations
The Graduate School
4-30-2009
Three Essays on Consumer Co-production Michael David Giebelhausen Florida State University
Follow this and additional works at: http://diginole.lib.fsu.edu/etd Recommended Citation Giebelhausen, Michael David, "Three Essays on Consumer Co-production" (2009). Electronic Theses, Treatises and Dissertations. Paper 4319.
This Dissertation - Open Access is brought to you for free and open access by the The Graduate School at DigiNole Commons. It has been accepted for inclusion in Electronic Theses, Treatises and Dissertations by an authorized administrator of DigiNole Commons. For more information, please contact
[email protected].
FLORIDA STATE UNIVERSITY COLLEGE OF BUSINESS
THREE ESSAYS ON CONSUMER CO-PRODUCTION
By MICHAEL DAVID GIEBELHAUSEN
A Dissertation submitted to the Department of Marketing in partial fulfillment of the requirements for the degree of Doctor of Philosophy
Degree to be Awarded: Summer Semester, 2009
The members of the Committee approve the Dissertation of Michael Giebelhausen defended on April 30, 2009.
__________________________________ J. Joseph Cronin Professor Directing Dissertation ___________________________________ William Christiansen Outside Committee Member __________________________________ Charles Hofacker Committee Member __________________________________ Jeffery Smith Committee Member
Approved: _____________________________________ Michael Hartline, Chair, Department of Marketing
_____________________________________ Caryn Beck-Dudley, Dean, College of Business The Graduate School has verified and approved the above named committee members.
ii
I dedicate this dissertation to my family. Without your help and guidance along each step of the way, none of this would have been remotely possible.
iii
ACKNOWLEDGEMENTS
I would like to acknowledge all of the individuals who have helped and guided me during my preparations for a career in academia. First of all, special thanks go to my dissertation chair, Dr. Joe Cronin, who taught me what makes for a good dissertation. I would also like to thank the members of my committee, Dr. Jeff Smith, Dr. Charles Hofacker, and Dr. Bill Christiansen for their help and patience during this undertaking. Also worthy of acknowledgement are the many excellent professors here at Florida State University whose seminars provided me with exceptional training. Lastly, I must also express my gratitude to Dr. Mike Brady, Dr. Tom Novak, Dr. Donna Hoffman, and Dr. Mary Ann McGrath for helping open the doors to the career of my dreams.
iv
TABLE OF CONTENTS
List of Tables
vi
List of Figures
vii
Abstract
viii
1. CHAPTER 1: WHAT IS CO-PRODUCTION?
1
2. CHAPTER 2: PERCIEVED CONTROL VS. PERCIEVED VARIETY
10
3. CHAPTER 3: CUSTOMIZED PRODUCTS AS PERFOMANCE PLACEBOS
28
4. CHAPTER 4: CO-PRODUCTION AND COMMITMENT
43
5. CHAPTER 5: CONCLUSION
56
APPENDICES
66
A. MEASURES
66
B. TABLES
71
C. FIGURES
74
D. HUMAN SUBJECTS APPROVAL
86
REFERENCES
90
BIOGRAPHICAL SKETCH
100
v
LIST OF TABLES
2.1
Measurement Model Evaluation
71
2.2
Summary of Indirect Effects
71
3.1
Mediation Analysis Results
72
3.2
Mediation Analysis Results
72
4.1
ANCOVA Results
72
4.2
ANCOVA Results
73
4.3
Mediation Analysis Results
73
4.4
Mediation Analysis Results
73
vi
LIST OF FIGURES
1.1
Venn Diagram of Co-production Concepts
76
2.1
Conceptual Model
76
2.2
Pasta Configurator Stimulus, Level 1 of 5
77
2.3
Shoe Configurator Stimulus, Level 3 of 5
77
2.4
T-shirt Configurator Stimulus, Level 5 of 5
78
2.5
PLS Path Coefficients and t-values
79
2.6
PLS Path Coefficients and t-values
80
3.1
Exam Customization Stimulus, Performance Relevant
80
3.2
Exam Percent Scores by Placebo Condition
81
3.3
Study 3 Stimulus
81
4.1
Made41.com Stimulus
82
4.2
Study materials
82
4.3
Relational Information Processes Manipulation
83
4.5
Affective Commitment Outcomes
84
4.6
Calculative Commitment Outcomes
85
vii
ABSTRACT
Numerous terms have been used, often interchangeably, to describe the circumstances whereby consumers play a role in crafting the goods and services they ultimately consume. Chapter 1 answers the question “What is co-production?” by providing a review of the terminology relevant to this phenomenon. The perspectives of researchers hailing from a wide variety of disciplines are cited and summarized, providing a foundation for the three essays that follow. Chapter 2 (Essay 1) demonstrates that increasing product customizability leads to heightened perceptions regarding both personal control and the variety offered by the configuration interface. More interestingly, however, the results demonstrate that these perceptions exert opposing influences on two distinct behavioral intentions. While perceived control is found to increase intentions to create an original product and decrease intentions to replicate a familiar product, the exact opposite is true for perceptions of variety which promote product replication and discourages creativity. Mediation tests reveal two instances of a relatively rare form of “inconsistent mediation” whereby a null effect of the initial variable is completely accounted for by the positive influence of one intervening variable and the negative influence of another. These finding highlight the complexity surrounding consumers’ response to co-production opportunities and may help resolve an apparent conflict in the literature between those who argue in favor of less vs. more choice. In chapter 3, a second essay reports the results of three studies exploring the potential for customized products to induce placebo-like effects with regards to athletic, academic, and professional performance. For example, in study 3, when paired with information regarding the psychological effects of color, allowing students to customize the color of their exam resulted in significantly higher average scores (84% vs. 79%). All three studies point to increased confidence as the mechanism intervening between expectancies of customized products and individual performance. These findings viii
contribute to the very limited amount of research regarding placebo effects in marketing contexts and also further our understanding regarding how these effects operate. Additionally, the results suggest that an important driver of demand for customized products might be anticipated increases in felt confidence. The final essay of this dissertation, presented in chapter 4, examines the interaction between product performance and relational information processes in determining consumer commitment to the co-producing firm. The results demonstrate that, in terms of both affective and calculative commitment, relational information processes have the potential to completely counteract the effect of a negative outcome. Indeed, the results suggest that the greatest potential for building customer relationships may lie with individuals who have experienced a co-production failure. These findings highlight the need for firms to invest their resources in creating effective relational processes. This implication is especially relevant given research demonstrating that consumers may often co-produce products that perform worse than expected.
ix
CHAPTER 1
WHAT IS CO-PRODUCTION?
A wide variety of terms have been utilized in the academic literature to describe situations whereby individuals play a role in creating a product or service. Concepts such as co-creation, co-design, co-production, mass customization, personalization, selfdesign, and user-design are often evoked indiscriminately to describe identical phenomena. In the essays that follow this introduction, various terms are used as deemed appropriate for describing a particular circumstance under consideration. With regards to the title of this dissertation, however, co-production is the term that represents the best fit. Of all the definitions presented below, co-production’s is both inclusive enough to incorporate all three essays and also specific enough so as to not be rendered meaningless. An additional feature of this concept is that, as per the work of Etgar (2008), it has recently become one of the most thoroughly conceptualized. This introduction represents an attempt to answer the question posed by its title: “what is co-production” in a way that is different from Etgar (2008). In particular, this chapter strives to provide an accurate portrayal of the lexical landscape created by the academic literature surrounding this phenomenon. In order to accomplish this goal, it is also necessary to answer questions such as “what is co-creation” and “what is mass customization.” The tactic adopted in achieving this goal is to present and summarize the definitions offered by experts in the various domains occupying this conceptual space. It should be noted that a number of authors, most notably, Piller (2005), attempt to delineate between many of the terms discussed below. However, the attempt made by this chapter is somewhat unique in that it incorporates definitions from a wider range of conceptual domains including the manufacturing, services marketing, consumer psychology, marketing strategy, product design, and innovation literatures.
1
DEFINITIONS
Co-creation 1
One interpretation of the term “co-creation” represents the most expansive concept presented in this list of definitions. This interpretation is associated with the increasingly popular Service-Dominant Logic (SDL) first presented by Vargo and Lusch (2004). According to Vargo and Lusch (2006, pg. 44), a fundamental proposition of the service dominant logic is that “the consumer is always a co-creator of value.” What they mean by this is that, in order for a product to provide any value, it must first be used in some way by a consumer. Thus, the value of every product ever used by anyone represents an act of co-creation. Interestingly, in their original 2004 article outlining their fundamental propositions, Vargo and Lusch used the term “co-production” as opposed to co-creation. However, they later amended this choice of terminology based on their view that the word co-production carried with it too much baggage associated with the goodsdominant logic they were attempting to refute (Lusch and Vargo 2006; Vargo and Lusch 2006). None the less, the original article remains highly cited, no doubt leading to situations where these terms are used interchangeably.
Co-creation 2
Adding to this confusion, a second conceptualization of co-creation is found in the literature. This conceptualization is more closely associated with the domains of mass customization and co-design (see below). In particular, “co-create” is often used as a verb in discussions of the circumstances whereby consumers customize products to their particular preferences (Piller 2005; Syam, Ruan, and Hess 2005). However, a review of the recent literature suggests that instances of the SDL conceptualization of co-creation are on the rise, while the term “co-creation” in discussions of mass customization is increasingly being replaced by the term “co-design.”
2
Co-design
Co-design is defined by Fiore, Lee, and Kunz (2004 pg. 835) as “a mass customization option where a product’s design is based on a customer’s selections from a range of design feature offerings.” Co-design is actively promoted as the correct terminology to use in discussions of mass customization. For example, Frank Piller, a noted expert on mass customization from the MIT Sloan School of Business, presents codesign as the genus of mass customization (see below). It is worthy to note that the term “value creation” also appears in this conceptualization. However, its use is well within the bounds of the SDL paradigm, as co-design would certainly represent a way that consumers create value. Additionally, “co-creation” also appears in the definition below, but is referenced in relation to the activities of manufactures rather than consumers. It may also be worthy to mention that, somewhat ironically, the title of Dr. Piller’s website is “Frank Piller’s Web Site on Mass Customization, Customer Co-creation & Open Innovation” (note the juxtaposition of “Customer Co-Creation” and “Mass Customization).
The genus of mass customization is customer co-design. Customers are integrated into value creation by defining, configuring, matching, or modifying an individual solution. Customization demands that the recipients of the customized goods transfer their needs and desires into a concrete product specification. Different to a do-it-yourself (DIY) setting (i.e. autonomous creation activities of consumers), this is done in a mode of interacting with the manufacturer who is responsible for providing the custom solution (“co-creation,” Ramirez 1999). Co-design activities are performed in an act of company-to-customer interaction and cooperation (Piller 2005, pg. 315).
3
Configurator The term “configurator” is unique from many in this list in that it references a specific type of tool or software (typically online) rather than a management strategy or consumer activity. The following description is offered by the International Configurator Database, an online academic resource for mass customization researchers, as representing a frequently cited definition of a configurator (http://www.configuratordatabase.com). (configurators) invite product purchasers to configure their own unique product by selecting from lists of options that have been predesigned by the mass customizer. For example, Dell Computer invites visitors to its website to “design your own computer” by making choices among lists of computer components on offer, such as monitors and disk drives (Von Hippel and Katz 2002, pg. 830).
Co-production Before it was confiscated (and later released) by the SDL paradigm, coproduction was commonly considered as an interaction of manufacturer and customer occurring prior to product creation (Tseng and Piller 2003). Alternatively, also prior to the emergence of SDL, Bendapudi and Leone (2003) opted for the term “co-production” in their research exploring activities ranging from making hotel reservations to entering measurements for custom-fit jeans. However, it seems likely that future consideration of co-production will be more consistent. In a recent issue of the Journal of the Academy of Marketing Science, Etgar (2008) undertakes the task of firmly establishing a conceptual model of co-production. In particular, he proposes a five-stage model of co-production consisting of: “1) the development of antecedent conditions, 2) development of motivations which prompt the consumer to engage in co-production, 3) calculation of the co-production cost-benefits, 4) activation when the consumer becomes engaged in the actual performance of the co-producing activities, 5) generation of outputs and evaluation of the results of the process” (Etgar 2008 pg. 99). What is especially worthy of note,
4
however, is that this most recent treatment posits that the term “co-production” only be used to describe cooperation formats between consumers and production partners that occur prior to product consumption. This requirement draws a firm line between coproduction and the service dominant logic interpretation of co-creation (formerly coproduction) which allows for continual co-production of value throughout the life of a product. Additionally, Etgar states that “one must recognize that co-production is an explicit result of decision making by consumers reflecting their own preferences” (Etgar 2008, p. 97). Etgar (2008, p. 98) further posits that “co-production encompasses all cooperation formats between consumers and production partners.” Based on the above, the working definition of co-production with regards to the research presented in this dissertation is as follows: All cooperation formats between consumers and production partners occurring prior to product consumption, whereby consumers make decisions designed to impact a product in a way that is reflective of their own preferences.
Customer Integration
Customer integration is a less specific construct than many of those appearing in this list. It is also an example of another term that has garnered additional attention since its inclusion within the SDL paradigm (Moeller 2008; Vargo 2008). Customer integration can be defined as “a mode of value creation in which customers are taking part in both operational and innovational value creating activities that used to be seen as the domain of the firm”(Piller 2009). The specific activities discussed in the literature range from bagging one’s own groceries to helping design products and advertising campaigns (i.e. crowdsourcing, Bonabeau 2009).
Mass customization
Of the terms listed, mass-customization is perhaps the most prevalent in both the academic literature and popular press. The term “mass-customization” was originally coined to describe a futuristic landscape where advanced manufacturing technologies
5
enable consumers to obtain products that are customized to their individual needs at prices comparable to mass-produced alternatives (Davis 1987). Perhaps in part due to the term’s original association with manufacturing, mass-customization seems to have become disassociated with circumstances other than those involving the “co-design” of manufactured physical goods. Indeed, some authors have gone so far to argue that the term mass-customization should not be applied to services settings (Kaplan and Haenlein 2006). While this assertion is debated (note the second definition below), it is consistent with the service literature’s apparent preference for the more general term of coproduction.
... a strategy that creates value by some form of company-customer interaction at the fabrication / assembly stage of the operations level to create customized products with production cost and monetary price similar to those of massproduced products (Kaplan and Haenlein 2006, pg. 168).
Mass customization refers to a customer co-design process of products and services which meet the needs of each individual customer with regard to certain product features. All operations are performed within a fixed solution space characterized by stable but still flexible and responsive processes. As a result, the costs associated with customization allow for a price level that does not imply a switch in an upper market segment (Piller 2005, pg. 315).
Personalization The term personalization is often used interchangeably, or in concert, with that of customization. For example, Goldsmith and Freiden (2004, pg. 228) state that “an emerging new strategic approach is termed “mass customization” or “personalization” whereby elements of the marketing mix are individualized for each customer.” Similarly, descriptions of personalization often bear a striking resemblance to those used to describe mass customization. For example, “with personalization, consumers can choose from various product attributes and a customized product is assembled based on their
6
preferences” (Moon, Chadee, and Tikoo 2008, pg. 31). However, others (see below) strongly oppose the mixing of these two terms. It seems that the debate hangs on the issue of whether or not consumer participation is required. For example, it is possible for someone to receive a personalized marketing message without any participation whatsoever on their part (i.e. amazon.com book recommendations). Personalization must not be mixed up with customization. While customization relates to changing, assembling or modifying product or service components according to customers' needs and desires, personalization involves intense communication and interaction between two parties, namely customer and supplier. Personalization in general is about selecting or filtering information objects for an individual by using information about the individual (the customer profile) and then negotiating the selection with the individual. Thus, personalization compares strongly to recommendation: From a large set of possibilities, customer specific recommendations are selected (Piller 2009).
Self-design / User-design
The terms user design and self design appear less frequently in the literature. When they do, the reason seems to be driven by a desire to specify the situation in which the user is doing the customizing. For example, Terwiesch and Ulrich (2005 pg. 68) define user design as “a particular form of product customization that allows the user to specify the properties of that product” (note that they italicize the word “user”). It is certainly possible that an individual could co-design a product intended for someone else to use. Furthermore, it seems that the use of the prefix “self” is appropriate for delineating the circumstances of interest to behavioral researchers (Schreier 2006).
7
Self-service technology
Another term related to the self is that of “self-service” technology (SST). This term, however, does not typically occupy the same literature as mass customization and related concepts. Research regarding SST tends to focus on technological advancements such as ATM’s and grocery store self checkout lines rather than those relating to product configuration (Meuter, Bitner, Ostrom, and Brown 2005). However, other research in this area has considered items such as photo kiosks to be examples of SSTs (Zhen, Nakata, Sivakumar, and Grewal 2007). It would certainly seem reasonable to argue that this technology, which allows consumers to specify the features of various photo related products, could also be classified as a “configurator” as per the above definition. Indeed, recent research suggests that the literature is in need of more specific classifications regarding self-service technologies (Cunningham, Young, and Gerlach 2009).
Summary
The Venn diagram presented in Figure 1.1 represents an attempt to create a graphical summary of the concepts presented above. In this diagram, the SDL interpretation of co-creation is seen as an overarching construct that encompasses all of the other definitions. In addition this legacy interpretation includes nearly all other activities that might be related to consumption. Co-production is the next largest circle due to its consideration of “all cooperation formats occurring between consumers and production partners.” Mass customization, and its related terms, can be considered as one particular type of co-production. The same can be said for self-service technologies that may or may not be related to product configuration. Personalization is considered to lie outside the circle of co-production based on the recognition that the execution of personalization does not necessarily require the consumer to be an active participant. However, the close association of this concept with both mass customization and coproduction warrants that the borders at least be touching. Lastly, while many examples of customer integration can be considered as representing both mass customization and co-
8
production (i.e. self-service technologies), other concepts associated with this term, such as crowdsourcing, seem to lie outside the boundary created by the stipulation that coproduction be considered as a precursor to consumption.
----------------------------------------------------
Insert figure 1.1 about here ----------------------------------------------------
Lastly, as a reminder, the working definition of co-production presented above is as follows: All cooperation formats between consumers and production partners occurring prior to product consumption whereby consumers make decisions designed to impact a product in a way that is reflective of their own preferences.
9
CHAPTER 2
EESSAY 1: PERCIEVED CONTROL VS. PERCIEVED VARIETY
Henry Ford wrote in his autobiography that “(a)ny customer can have a car painted any colour that he wants so long as it is black (Ford and Crowther 1922).” Today, a much different car buying experience allows Mini Cooper customers to pick from 372 interior and 319 exterior options (Schulz 2007). A few quick calculations revel that if someone were to pave over all of Martha’s Vineyard (approximately 100 square miles) with standard sized parking spaces, you could just squeeze in the “over 10,000,000 possible configurations” of Mini Cooper hardtops advertised as being attainable via the “Mini Configurator”(http://www.miniusa.com 2009). Finding a place to put all of the “seven trillion custom dress shirts” advertised as available from shirtsmyway.com would be an even more difficult task (http://www.shirtsmyway.com 2009). A single stack containing of all these shirts (assuming one inch per folded garment) would only be about 85 percent complete before it hit the sun. The interface allowing consumers access to such unprecedented variety is the product “configurator.” A configurator is defined as a piece of software that allows customers to adjust customizable goods and services to fit their individual needs (Franke and Piller 2003). As discussed in the introduction (i.e. chapter 1), these types of applications are often associated with mass-customization strategies. First coined by Davis in 1987, the term “mass customization” is derived from the combination of the terms “mass production” and “customization.” According to Franke and Schreier (2008 pg. 93) “(t)he core idea of mass customization is to provide a web-based user toolkit that allows the consumer to design a product which suits her individual preferences and is then produced for her.” Proponents of customization via configuration suggest that providing consumers with this capability results in a wide variety of positive outcomes
10
including product innovation, loyalty, and cost reductions (see Bendapudi and Leone 2003 for a review). The growing prevalence of product configuration opportunities seems to suggest that many firms have “bought in” to the benefits of mass customization proposed by both the popular press and academic literature. Indeed, some companies such as Nike, Dell Computers, and Lands End have experienced great success with their customizable product offerings. However, other well-known marketing organizations have had less luck with their entries into the mass customization milieu. Levis’ made to measure jeans, General Mills’ customized cereals, and Mattel’s custom Barbie dolls are just a few of the more publicized failures. Just as marketers are seemingly only beginning to understand the implications of allowing consumers a hand in creating products, so too are academic researchers. Burroughs and Mick (2004) point out that creative consumption, which they define as a departure from conventional consumption practice in a novel and functional way, has received little attention from consumer behavior researchers. This is perhaps in part due to the different conceptualizations of “creativity” found in the literature. For example, early research tended to conceptualize creativity as an individual difference variable (Barron and Harrington 1981). However, many distinct aspects of creativity have since been examined from a wide variety of disciplinary perspectives (see Runco 2004 for a review). As per the commonalities across these different approaches, Runco (2004) states that “originality is the most widely acknowledged requisite for creativity.” Of course, this statement might beg the question: “Well what then is originality?” In search of insights into how the numerous researchers studying creativity have understood originality, perhaps the most suitable reference is the humble dictionary. The Merriam-Webster dictionary defines “originality” as “the state of being original” and, correspondingly, “original” as 1) “not secondary, derivative, or imitative” and 2) “independent and creative in thought or action” (http://www.merriam-webster.com). With regards to the impact of customizability on creativity, particularly relevant insights can be gleaned from the recent work of Moreau and Dahl (2005). They find that constraining, rather than increasing, inputs available during a creative task increases the creativity of the resulting product. With regards to the mechanism, they point out that in the absence of constraints consumers can simply recall and replicate a solution to the task
11
at hand (Park and Smith 1989; Ward 1994). They also draw attention to the fact that individuals are reluctant to deviate from this “path of least resistance” because doing so requires both more cognitive effort as well as increased uncertainty regarding the result (Ward 1994). This insight that consumers may be better off with fewer choices is not unique to creative tasks. A growing body of research is examining a paradoxical phenomenon whereby the more products consumers have to choose from, the less satisfied they end up being with their selection (Chernev, Mick, and Johnson 2003; Sagi and Friedland 2007). The reason this represents a paradox is that it is generally assumed, by both marketers and consumers themselves, that more choice should enable increased satisfaction (Schwartz and Redmond 2005). Indeed, allowing consumers to access every conceivable configuration of a particular product is often seen as a key benefit of mass customization (Franke and Schreier 2008; Stefan, Kreuzer, Kuhn, and Stringfellow 2006; Wind and Rangaswamy 2001). No attempt to empirically reconcile these two perspectives with regards to customized products has yet to appear in the academic literature. Therefore, with respect to the above discussion, the stated goal of essay 1 is to provide insights into the effect of customizability on both creativity-related behavioral outcomes and customer satisfaction. In particular, this research focuses on the role played by two intervening variables resulting from product customizability: 1) perceived variety and 2) perceived control. The results, presented below, demonstrate that these mediators exert opposing influences on two distinct types of behaviors: 1) replication of a familiar product and 2) creative product configuration. Perceived variety is found to be negatively related to creative configuration, and positively associated with configuration designed to replicate a familiar product. However, the exact opposite is true for perceived control, which appears to promote creativity and discourage product replication. Additionally, the results suggest that creative behaviors contribute positively to anticipated satisfaction while behaviors designed to replicate a familiar product have no effect on this outcome variable. These findings provide valuable insights regarding the complexity surrounding the issue of customizability during product configuration and help explain conflicting recommendations relevant to this increasingly prevalent consumption phenomenon. Lastly, the results imply that organizations such as Mini Cooper and Shirts My Way are
12
taking the wrong approach in highlighting the extensive variety offered by their configuration interfaces and should instead attempt to independently promote perceptions of control.
CONCEPTUAL REVIEW AND HYPOTHESES DEVELOPMENT
With regards to the behavioral outcomes resulting from perceived customizability, this paper takes the position that using a configurator to create an original product (henceforth referred to as creative configuration) and using a configurator to replicate a familiar product (henceforth “product replication”) represent two distinct types of behavior. To a certain extent, the argument is a semantic one. If, as discussed above, creativity implies originality and originality implies something “not secondary, derivative, or imitative” then it is untenable that a configuration behavior can be simultaneously both highly creative and highly replicative. Although this line of argument may be sufficient for hypothesizing a negative correlation, it does not address the alternative explanation that creation and replication simply represent opposite poles of some overarching construct. Insight into this issue, however, can again be gleaned from the work of Moreau and Dahl (2005), which demonstrates that, when consumers engage in a generative task, different cognitive processes operate depending on whether the individual is constructing a novel solution or retrieving a existing solution from memory. This demonstration, in a consumer context, that replication involves cognitive mechanisms distinct from those invoked during creation strongly suggests that it is improper to lump these behaviors under a single construct.
H1: Creative configuration and product replication represent two distinct, though negatively correlated, types of behavior.
For the purposes of this research “customizability” is defined simply as the extent to which a product’s attributes are able to be specified by the end user (i.e. consumer) prior to production. It is worth noting that there are a number of different ways in which
13
this variable might be manipulated. One manipulation is to increase the number of product attributes able to be specified by the consumer. Alternatively, a manipulation can be made regarding the number of choices available for any particular product attribute. Manipulations along either of these lines result in a finite, though potentially very large, set of attainable products. Other options for enabling customizability, however, result in an effectively infinite number of potential outcomes. For example, many configurators resemble a graphic design interface and provide the user with the ability to enter text, upload images, manipulate clip art, and so forth. Especially, in this latter case, the general level of perceived customizability, rather than any calculated assortment set size, is likely more appropriate for consideration as a causal variable. It is unlikely that consumers can fully comprehend the exponential increase in variety afforded by many product configuration interfaces even in cases where it is explicitly advertised, such as on the Mini Cooper and Shirts My Way web sites. Indeed, individuals are notoriously bad in situations involving numbers or math (Tversky and Kahneman 1974). More specifically, a number of researchers have demonstrated that the relationship between actual variety and perceived variety can be influenced by a number of factors including: consumer expectations, consumer expertise, the diversity of the assortment, and the shelf space occupied by the assortment (Kahn and Wansink 2004; Mogilner, Rudnick, and Iyengar 2008; Morales, Kahn, McAlister, and Broniarczyk 2005). The effect of actual variety on variety perceptions is undoubtedly complex and subject to a number of potential moderators. However, there is no reason to suspect that the positive relationship between actual variety and perceived variety consistently observed in the product assortment literature does not hold true in product configuration environments.
H2: There is a positive relationship between the extent to which a consumer can customize a product’s attributes during configuration (i.e. customizability) and their perceptions regarding the variety offered by the configuration interface.
14
As discussed in the introduction, it has been demonstrated that providing additional inputs discourages creative processing. One mechanism proposed is that when individuals have extensive options, they can imagine an existing product and replicate it rather than deviate from this “path of least resistance” by generating a creative product (Moreau and Dahl 2005). Additionally, researchers demonstrate that in product configuration environments, a large number of options decreases a consumer’s perceived self-efficacy, or confidence, with regards to the task at hand (Huffman and Kahn 1998). When an individual is less confident in their ability to create a successful solution, they are more likely to select an “off-the-shelf” version rather than create a custom solution (Dellaert and Stremersch 2005).
H3: There is a positive relationship between perceived variety and intentions to replicate a familiar product.
H4: There is a negative relationship between perceived variety and intentions to engage in creative product configuration.
The reason many findings regarding the effect of variety and constraints on consumption outcomes are seen as paradoxical is that, despite the apparent detrimental effects of too much choice, consumers consistently demonstrate a strong preference for extensive variety. One explanation for this preference for choice revolves around the finding that being able to choose engenders perceptions of control (Averill 1973; Botti, McGill, and Iyengar 2003; Skinner 1996). The desire for control is identified as a key driver of consumption and human behavior in general (see Hui and Bateson 1991 for a review). Correspondingly, this construct is subjected to extensive examination in the academic literature. In a review of research in this area, Skinner (1996) identifies over 100 terms relating to the construct of control, many related to the issue of choice. Thus, in the context of product configuration, it seems reasonable to assume that providing or limiting product customizability affects perceptions of control.
15
H5: There is a positive relationship between customizability and perceived control.
Insights into the effect of perceived control on consumer behavior during product configuration can be gleaned from recent research conducted by Burroughs and Mick (2004) regarding the relationship between Locus of Control (LOC) and consumer creativity. They find that individuals who generally believe events are under their control (i.e. having an internal LOC) demonstrate more creative responses to consumption problems. Jewell and Kidwell (2005) suggest that perceived control increases motivation to engage in deliberative processing; a type of processing related to the generation of creative outcomes (Runco 2004; Ward 2001). These finding are consistent with recent research involving the effect of empowerment on creativity in the psychology literature. For example, Smith and Troupe (2006) demonstrate that individuals primed to feel empowered engage in more abstract information processing. Of particular relevance to the context of creative configuration and product replication, is research demonstrating that people who feel empowered generate more creative ideas and are less influenced by salient examples (Galinsky, Magee, Gruenfeld, Whitson, and Liljenquist 2008). This suggests the following hypotheses:
H6: There is a negative relationship between perceived control and intentions to replicate a familiar product.
H7: There is a positive relationship between perceived control and intentions to engage in creative product configuration.
While an exploration of complex mechanisms and their impact on conceptually interesting behavioral intentions might be of great interest to consumer behavior researchers, more likely to be of interest to marketing practitioners are outcomes more closely related to purchase activities. Thus, it is worthwhile to extend the examination undertaken to the dependant variable of anticipated satisfaction. Furthermore, evaluating the potentially differing effects of creative configuration and product replication provides
16
insights as to how to resolve the apparent discrepancy between the positions of those who argue in favor of less or more choice. Practically speaking, replicating an existing product using a configuration interface is not much different from ordering that same product from a standard online storefront offering “off the shelf” products. One might even argue that the only real difference is the number of mouse clicks required to get the product into the shopping cart. To the extent that this is true, then research that examines the detrimental effect of variety on satisfaction and purchase intentions seems to be most applicable to the circumstances surrounding product replication. Extending this further implies a negative relationship between product replication and anticipated satisfaction. As mentioned above, research reveals an important paradox with regards to the relationship between satisfaction and the size of a choice set. The now classic study exploring this topic exposes consumers to either a large or small display of gourmet jams at a specialty food shop (Iyengar and Lepper 2000). Consumers seeing the large display are found more likely to visit the display and sample the jam, but these individuals purchase much less often and tend to be less satisfied with their selection. As is argued above, however, creative configuration represents a very different type of behavior and, thus, may have a very different effect on anticipated satisfaction. One insight comes from finding suggesting that creativity is both preceded and followed by increased levels of positive affect (Burroughs and Mick 2004; Hirt, Devers, and McCrea 2008). Being in a good mood has a number of positive outcomes, including those related to satisfaction (Oliver 1980). Thus, it is reasonable to make the following hypotheses.
H8: There is a negative relationship between product replication intentions and anticipated satisfaction.
H9: There is a positive relationship between creative configuration intentions and anticipated satisfaction.
17
Taken together, the hypotheses suggest the conceptual model identified in Figure 2.1. Viewing this model in its entirety provides some additional insights into the complexity surrounding product customizability. Specifically, the model implies that the mechanisms whereby customizability might affect product replication and creative configuration represent two instances of what has been described by Mackinnon, Fairchild and Fritz (2007) as “inconsistent mediation.” This type of mediation occurs when one mediated effect has a different sign than another mediated effect, thus potentially canceling out the impact of the initial variable on the outcome variable. Instances of this phenomenon, while relatively rare, have been demonstrated in the literature (Paulhus, Robbins, Trzesniewski, and Tracy 2004; Sheets and Braver 1999). The proposed model also adds an additional layer of interest as it includes dependant variables upon which these “inconsistent” mediation mechanisms can be predicted to exert opposite effects. An empirical demonstration of this result is an enticingly exotic outcome on its own accord. However, such a finding also provides substantial insights into the complexity surrounding the issue of customizability in product configuration environments.
----------------------------------------------------
Insert Figure 2.1 about here ----------------------------------------------------
METHOD
A sample of 106 undergraduate students from a large public university served as participants for this study. This represents a reasonable sampling frame as highly educated individuals of this age are generally assumed to have greater and more consistent abilities related to the technologies typically employed during product configuration (i.e. interactive websites). The study was hosted using an online laboratory designed for conducting behavioral research. Course extra-credit was used as the incentive for participation.
18
Over the course of the study, participants were exposed to a series of three online product configurator “screenshots” constructed for the purposes of this research (see Figures 2.2, 2.3, and 2.4 for sample stimuli). The product categories for the configurators (t-shirts, pasta, and athletic shoes) were chosen based on their relevance to the participant population and their relative prevalence in the International Configurator Database, a scientific database of over 500 web-based product configurators (www.configuratordatabase.com 2009). An additional goal was to construct configurators that represent the variety of different ways, as discussed above, in which customizability might be manipulated. For example, with regards to the pasta configurator, individuals viewed an online interface providing 4, 8, 12, 16, or 20 different ingredients in each of five fixed categories. For the athletic shoe configurator, customizability was manipulated by simultaneously adding both additional customizable features and the number of options available for that feature. The t-shirt configurator represented a graphic design type of customization interface. In this instance, customizability was adjusted by varying the number of colors, fonts, and graphics available as inputs into a user generated design. For each configurator, participants were randomly assigned to one of five levels of customizability.
-----------------------------------------------------------------------------
Insert Figure 2.2, 2.3, and 2.4 about here -----------------------------------------------------------------------------
One might describe the above data collection as representing a 3(customization interface) x 5(customizability level) mixed design. However, this description is potentially misleading. The design employed by this research was not intended to enable comparisons across the different customization interfaces. Indeed, these comparisons would only be reasonable given much tighter controls regarding the variation between the product configurator stimuli. While this might represent an interesting area for future research, the intention of the presented research was to explore the potential mechanisms whereby changes in customizability level affect specified behavioral outcomes related to product configuration. Additionally, it should be noted that there was no reason to
19
suspect that a particular level of customizability in one interface might be comparable to that same level in another. However, this was not a requirement of an analysis examining the correspondence between changes in customizability and changes in the proposed intervening and outcome variables. Regarding these intervening and outcome variables, a measure of perceived variety was adapted from Kahn and Wansink’s (2004) perceived variety scale (see Appendix for all scale items). Perceived control was evaluated via a scale consisting of items drawn from Mehrabian and Russell’s (1974) dominance scale and Glass and Singer’s (1972) helplessness scale; an approach commonly used in research examining control perceptions (Faranda 2001; Hui and Bateson 1991; Rompay, Galetzka, Pruyn, and Garcia 2008). Regarding the dependant variables of 1) behavioral intentions to replicate an existing product and 2) behavioral intentions to create an original product, however, the extant literature provided less explicit guidance. Behavioral intentions are very commonly evaluated using a question stem describing the behavior followed by a number of semantic differential items such as “unlikely / likely”, “improbable / probable”, “impossible / possible,” and so forth. Volume IV of the AMA Marketing Scales Handbook reports Cronbach’s alpha scores for 35 academic articles using this approach (Bruner, Hensel, and James 2005). Of those 35 articles, 28 report alphas of .90 or greater. All 35 report alphas of over .80. This suggests a large degree of redundancy in the items used to evaluate behavioral intentions. Thus, it appeared that, in this case, the question stem was more important than the items that follow it. This was especially true for the presented research as the behaviors of interest are more nuanced than say, the likelihood of buying a particular product. As a result, a slight modification of the standard behavioral intentions scale was deemed to be appropriate. Instead of a single description of each configuration behavior, four different descriptions were developed. For example, the measure of behavioral intentions to replicate a familiar product included items such as “I would replicate a product that I am familiar with” and “I would imitate a product similar to one that I had encountered before.” Each description was followed by a single “unlikely/likely” semantic differential scale. The hope was that these items would display a high degree of consistency,
20
indicating that each behavioral intention was accurately described and well understood by the participant (see below for item analysis).
ANALYSIS AND RESULTS
Partial Least Squares (PLS), sometimes called Projection to Latent structures, via SmartPLS 2.0 is used to test the hypotheses specified above. PLS has a number of characteristics that make it particularly well suited for analyzing the data collected in this study. For example, with regards to mediation testing, a number of researchers present arguments regarding the superiority of latent variable approaches (Frazier, Tix, and Barron 2004; Iacobucci, Saldanha, and Deng 2007). Additionally, the two potential instances of “inconsistent mediation” discussed above are not well suited for being tested by the common, though increasingly controversial, indirect method popularized by Barron and Kenny (1986) where “step 1” entails demonstrating a significant relationship between the initial and outcome variable. Indeed under the circumstances where the initial effect is canceled out by opposing mechanisms, an indirect approach to evaluating mediation is infeasible. However, this does not represent a particularly troublesome limitation as direct tests of mediation (e.g. the Sobel test), which evaluate mediation via a product of path coefficients, are increasingly being presented as a superior approach (see MacKinnon, Lockwood, Hoffman, West, and Sheets 2002 for a review). Furthermore, PLS is a particularly appropriate method for conducting these types of mediation tests. The reason is that PLS’s use of bootstrapping to develop confidence intervals effectively deals with the key weakness of approaches such as the Sobel test: i.e. sensitivity to nonnormal distributions (Chin 1998; Efron 1988). Indeed, bootstrapping in general is growing increasingly popular as a method for evaluating mediating effects (Preacher and Hayes 2008; Shrout and Bolger 2002). Aside from considerations relating to mediation testing, PLS offers a number of other benefits for this analysis. For one, it provides the ability to examine the convergent and discriminant validity of the evaluated constructs via the method outlined by Fornell
21
and Larker (1981). Another useful feature is that, unlike other latent variable techniques, PLS permits the use of nominal data and constructs indicated by single items (e.g. the five levels of customizability manipulated in this study). Additionally, it is argued that PLS is superior for testing complex relationships such as those implied by the above model (Fornell and Bookstein 1982). Furthermore, it is demonstrated that PLS is robust to multicollinearity among independent variables (opposed to covariance-based structural equation modeling) (Fornell and Bookstein 1982). To the extent that perceptions of variety and perceptions of control are correlated, this represents a useful feature. Lastly, with PLS and its associated bootstrapping, independence of observations is not required (Lohmoller 1989); another desirable feature given the nature of our data collection.
Model Evaluation
PLS was used to estimate a path model (see Figure 2.5) representing the effects hypothesized above. To provide confidence intervals regarding the resulting path coefficients, a bootstrap sample equal to the number of configurator evaluation instances in the dataset (315) was replicated 1000 times. It should also be noted that three participants failed to complete the study in its entirety; this being the reason that the number of cases did not equal 318 (i.e. 3 interfaces x 106 participants). The measurement model demonstrated (see Table 2.1) acceptable convergent validity with all of the constructs having composite reliabilities (CR) of over .90. Correspondingly, average variance extracted (AVE) values exceeded the .70 level at which point the variance due to the construct becomes greater than that due to measurement error. Additionally, discriminant validity, as per Fornell and Larker’s (1981) guidelines, was evidenced by AVE values which, for all constructs, exceeded shared variance between the construct and all other variables in the model. This analysis also represented a successful test of H1 which proposed that creative configuration and product replication represent two distinct, though negatively correlated, types of behavior. In summary, this preliminary analysis provided support that the measures included in the conceptual model (see Figure 2.1) are of sufficient quality so as to allow for an examination of potential causal relationships. Equally important, they point to the
22
fact that creative configuration and product replication warrant being considered as separate constructs.
-----------------------------------------------------------------------------
Insert Table 2.1 about here -----------------------------------------------------------------------------
With regards to the evaluation of the structural model, supportive of H2 and H5, the results from the path analysis indicated that increasing customizability, as per the experimental manipulation, resulted in both increased perceptions regarding the variety offered by the configuration interface (β = .399, t = 9.041, p < .001) and increased perceptions of control (β = .223, t = 4.004, p < .001). Support was also found for H7 as the effect of perceived control on creative configuration intentions was positive and significant (β = .248, t = 4.54, p < .001). As predicted by H6, the effect of perceived control on product replication intentions was, alternatively, negative and significant (β = -.266, t = 4.295, p < .001). As predicted, perceptions of variety had the exact opposite effect. Per H4, the relationship between of perceived variety and creative configuration intentions was negative and significant (β = -.150, t =2.325, p = .020). As per H3, the relationship between perceived variety and replication intentions was positive and significant (β = .260, t = 4.008, p < .001). Hypotheses 9, regarding the positive impact creative intentions on anticipated satisfaction, was supported by a significant positive relationship between these two variables (β = .172, t = 2.231, p = .026). Hypotheses 8, regarding the negative impact of replication intentions on anticipated satisfaction, however, was not supported. Rather there was an insignificant relationship between these two variables (β = .104, t = 1.318, p =.188). However, the fact that creative configuration intentions and product replication intention differ with regards to their impact on anticipated satisfaction provides further evidence that these two behaviors warrant separate consideration (i.e. H1). In summary, support was found for all but one of the effects hypothesized above. The exception was insignificant relationship between product replication on anticipated satisfaction, a relationship hypothesized (H8) to be negative and significant.
23
--------------------------------------------------------------------
Insert Figure 2.5 about here --------------------------------------------------------------------
Mediation of a Null Effect
The results presented in Table 2.1 demonstrate that, in product configuration environments, replicating a familiar product and creating a new product are distinct activities that are negatively correlated. The results also suggest that perceived control and perceived variety mediate the relationship between customizability and both of these variables. However, a more formal test is needed. What makes this test somewhat unique is that the mediating effects are opposite of one another. Perceived control is positively associated with creative configuration and negatively associated with product replication. Conversely, perceived variety is positively related to creative configuration and negatively related to product replication. These circumstances, as described by MacKinnon et al.(2007) allow for the full mediation of a null effect. To see if this is indeed the case, PLS is used to fit a model (see Figure 2.6) demonstrating the effect of the experimental manipulation on the outcome variables. Consistent with the opposing effects of perceived variety and perceived control, the direct effect of customizability on both creative configuration intentions (β = .045, t =.559, p = .577) and product replication intentions (β = .058, t =.759, p = .448) is small and statistically insignificant. Thus, the groundwork was laid for a demonstration of two instances of the mediation of a null effect.
--------------------------------------------------------------------
Insert Figure 2.6 about here --------------------------------------------------------------------
A series of Sobel tests (see Table 2.2), confirms the presence of mediation. The null effect of customizability on creative configuration intentions is accounted for by a negative mediating effect through perceived variety (z= 2.26, p =.024) and a positive
24
mediating effect through perceived control (z= 3.08, p = .002). Alternatively, the null effect of customizability on product replication intentions, is explained by a positive mediating effect through perceived variety (z= 3.63, p < .001) and a negative mediating effect through perceived control (z= 2.99, p = .003). Thus, the conceptual model (Figure 2.1) does indeed represent two instances of mediation of a null effect. The fact that, choice evokes these opposing mediators helps explain the discrepancy between recommendations of more versus less choice found in the literature. Under circumstances when the control mechanism is more salient, one might expect increased satisfaction. However, when perceived variety is the dominant mediator, decreased satisfaction seems more likely.
----------------------------------------------------
Insert Table 2.2 about here ----------------------------------------------------
DISCUSSION
As discussed above, proponents of mass customization view putting the customer in control as an obvious path towards maximizing satisfaction (Gilmore and Pine 2000; Wind and Rangaswamy 2001). However, consumer decision making researchers might suggest that allowing consumers to configure a product simply adds to the overwhelming number of choices already present in the market place and likely to engender dissatisfaction (Chernev 2006; Iyengar and Lepper 2000; Schwartz 2006). Empirically reconciling these two viewpoints, however, has yet to be attempted. The findings provide a number of insights into the increasingly important issue of how much customizability to provide to consumers engaging in product configuration. Perhaps not surprisingly, customizability is found to result in increased perceptions regarding both the variety offered by the configuration interface and an individual’s control over the resulting outcome. However, the results also suggest that perceptions of control still play a key role in determining consumer behavior within product configuration environments. In particular, it is demonstrated that the mechanisms of
25
perceived control and perceived variety completely counteract one another with regards to two distinct (though negatively correlated) behavioral outcomes: creative configuration and replication of a familiar product. It is noted that the combination of these mechanisms comprise a unique, and conceptually interesting type of mediation whereby a null effect of the initial variable (in this case an experimental manipulation of customizability) is fully mediated by a positive and negative effect. This contributes to our understanding of this phenomenon, and indicates that future research not considering both of theses mechanisms may yield inconsistent results. Additionally, identifying creative configuration and product replication as two distinct behaviors provides the key for reconciling competing recommendations regarding whether to provide consumers with more or less choice during product configuration (i.e. customizability). Product replication intentions, the results indicate, have no impact on anticipated satisfaction. Creative configuration intentions, on the other hand, are found to have a positive influence on anticipated satisfaction. Thus, as per the conceptual model (Figure 2.1), the only route from product customizability to anticipated satisfaction is that which follows a path through perceived control and creative configuration intentions. Alternatively, as per the results, the path through perceived variety only increases product replication intentions which have no impact on anticipated satisfaction. Thus, increasing customizability will only increase a consumer’s anticipated satisfaction if it evokes perceptions of control to a greater extent than perceptions of variety and, therefore, engenders creativity rather than replication. The managerial implication resulting from this finding is that marketers should strive to promote perceptions of control and downplay the variety offered by the configuration interface. This is undoubtedly not a trivial task given the close relationship between variety and control. However, it remains a very relevant recommendation as a review of the mass customization landscape indicates that, very often, marketers are doing just the opposite.
FUTURE RESEARCH
Perhaps the key managerial implication resulting from this study is that marketers should strive to promote control, rather than variety, in co-production environments.
26
However, future research is needed to confirm this insight. An experiment where different levels of customizability are crossed with stimuli designed to promote either control or variety provides more justification for this recommendation and represents a replication of the this study. In particular, one strategy is to take high and low customizability versions of one of the configurators presented above and precede it with advertising promoting either control or variety. The effect of these manipulations on perceived variety, perceived control, creative configuration intentions, product replication intentions, and anticipated satisfaction can then be tested with an ANOVA. Additionally, the above conceptual model (i.e. Figure 2.1) provides a foundation for a number of theory orientated projects. In particular, the understanding of consumers’ responses to customizability could be expanded by exploring the potential mediators intervening between the constructs represented in the model. For example, the literature suggests that positive affect may explain the link between creativity intentions and anticipated satisfaction. This is worthy of empirical demonstration. As with any research, replication across a wider variety of configurators would be beneficial. This may be particularly true in this case as this model represents two instances of “inconsistent” mediation whereby a null effect is completely accounted for by the positive influence of one intervening variable and the negative influence of another. Additionally, this model may extend to a number of other domains where the concept of customizability may be applicable.
27
CHAPTER 3
ESSAY 2: CUSTOMIZED PRODUCTS AS PERFOMANCE PLACEBOS
The presented research began as an in-depth interview study designed to explore consumer’s thoughts and feelings regarding mass customized athletic equipment. As discussed previously, “mass customization” is a term used to describe the circumstances whereby, at price points comparable to mass produced products, consumers are able to customize a product to fit their unique needs. As the study progressed, one particularly interesting facet regarding customized athletic equipment emerged. Not surprisingly, the athlete participants associated the ability to alter various features of their equipment as leading to improved athletic performance. What was surprising, however, was that this effect was equally attributed to product characteristic which, ostensibly, should have no impact on performance (i.e. changing the colors). The participants’ comments seemed to suggest a psychological mechanism related to increased confidence. A review of the literature confirmed these circumstances to be indicative of a possible placebo effect. In the medical literature, a “placebo,” is described as “a substance or procedure that has no inherent power to produce an effect that is sought or expected” (Stewart-Williams and Podd 2004). A “placebo effect” occurs when that placebo produces the sought or expected effect none-the-less. The literature review also suggests that the phenomenon of placebo effects in marketing contexts had only recently begun to be considered. In fact, a 2005 special issue of the Journal of Marketing Research comprises the bulk of the research in this area. Additionally, appearing in that issue is a call for future research to examine confidence as a potential mechanism via which product expectations might result in improved performance (Shiv, Carmon, and Ariely 2005b). Inspired by the above qualitative insights and literature review, a follow up study was designed to empirically test whether demand for customized products might indeed
28
be driven by an expectation of improved performance operating via increased confidence. In study 3, this effect was observed in a real world setting when allowing students to customize the color of their exam, resulted in higher scores among individuals primed to expect an increase in test-taking performance. The combined results of these studies strongly suggest that placebo effects should receive more consideration by both marketing academics and practitioners. Additionally, these findings provide support that felt confidence mediates the relationship between expectancies of customized products and actual improvements in performance.
CONCEPTUAL REVIEW
Flying Elephants
For the uninitiated, the 1941 Walt Disney film Dumbo, is about a young elephant of the same name who, due to his extraordinarily large ears, is endowed with the capability to fly. Though he is initially skeptical of his abilities, a group of crows “use psychology” to convince Dumbo that a magic feather (conveniently sourced from one of their tails), will make him able to fly. Human beings also have many extraordinary abilities of which we are skeptical. Most commonly cited in studies of placebo effects is the documented capacity of the mind to effect a physiological response (White, Tursky, and Schwartz 1985). Most typically, this is demonstrated when a group of doctors convince a patient that a magic pill (actually a placebo containing nothing more magical than sugar) will make them feel better. More formally, a placebo effect is described to occur when “expectation changes the actor’s response to a situation, resulting in expectancy confirmation” (1992). Despite the apparent recognition by cartoonists of placebo effects in contexts outside of the medical field, academic researchers have only recently begun to examine this phenomenon in other areas of inquiry. Indeed, a 2005 special issue of the Journal of Marketing Research seems to comprise the bulk of the academic literature relevant to marketing researchers. Perhaps most groundbreaking in this volume is the work of Shiv, Carmon, and Ariely (2005a, hereafter SCA) that demonstrates how both a product’s price
29
and associated advertising claims can influence consumers in a placebo-like manner. The nascent stage of research in this area, however, is evidenced by a search on Business Source Complete, using the key terms “placebo” and “consumer,” which returns a total of seventeen academic articles. Of those seventeen not represented in the JMR special issue, three are related to medical studies, one is from the psychology literature, two deal with subliminal self-help tapes, and one is a review of SCA’s 2005 article. As per the research of SCA, it might be noted that in two of their three studies, only negative placebo effects were observed. That is, discounting the price of an energy drink was found to be associated with decreased performance on a series of puzzles. Individuals in the regular price condition perform no better than control subjects not exposed to the placebo. In their third study, however, a positive placebo effect is evoked by exposing participants to strong advertising claims regarding the ability of the energy drink to boost mental alertness. Positive placebos are the type more often associated with the placebo effect and correspondingly, the topic of the presented research.
Birds of a Different Feather
Various topics in the academic literature bear a number of similarities to placebo effects. Of these, self-fulfilling prophecies are perhaps the most closely related. The selffulfilling prophecy is described by Merton (1957) as “a false definition of the situation evoking a new behavior which makes the originally false conception come true.” The distinction between self-fulfilling prophecy and placebo effects is that the former is a false belief that sets in motion behaviors that cause, rather than enable, the outcome to be realized. In the Dumbo example, a self-fulfilling prophesy is the appropriate description if Dumbo had not originally been capable of flying (as he was), but his belief in the magic feather caused him to embark on an ear strength training regimen that later gave him this ability. Self-deception is a related phenomenon that, unlike placebo effects, receives some attention in the marketing literature (Deighton 1992; Deighton 1984; Sujan, Bettman, and Sujan 1986). This phenomenon is different in that it does not require that actual changes result from a false belief. Rather, self-deception requires only a change in individual’s
30
perceptions. A key moderator of the self-deception effect is the subjectivity of the situation being evaluated (Hoch 2002; Hoch and Ha 1986). For unambiguous outcomes, it becomes difficult to deceive oneself into accepting that a false belief is true. Whether or not one can fly, for example, represents an outcome that is particularly unreceptive to self-deception. Humans (and indeed other animals) are quick to infer causal relationships where none exist. Perhaps the most famous example from the academic literature is B.F Skinner’s (Skinner 1948) Journal of Experimental Psychology Article entitled “Superstition in the Pigeon.” Skinner observes that a food pellet, dropped into the pigeon’s pen at regular intervals encouraged the pigeons to increase the frequency of the behavior they were performing when the reward first appeared. The more the pigeon’s performed this particular behavior, the more likely it is that it coincides with the next regularly awarded treat. Over time, this lead to the development what can be called a superstitious ritual. For example, one of Skinner’s pigeons is conditioned to repeatedly turn counter-clockwise circles, while others repeatedly execute unusual head movements. Superstitions bear a closer resemblance to self-deception as opposed to placebo effects or self-fulfilling prophecies. The difference is that placebo effects and self-fulfilling prophesies actually cause some outcome to occur. Superstitions, on the other hand, can be considered expectancies that have no effect (i.e. the food pellet is going to keep appearing at the same rate no matter what the pigeon does). Driven in large part by a desire to control uncontrollable outcomes, humans are quick to form superstitions ranging from picking lottery numbers to picking which lucky shirt to wear while attending a sporting event (Keinan 2002; Matute 1995; Ono 1987).
Expectancy Effects
The mechanism by which placebo effects operate is an individual’s expectancy that a particular outcome will result (Kirsch 2004; Kirsch and Harrington 1997; StewartWilliams and Podd 2004b). However, how these expectancies translate into actual outcomes is dependant on the outcome itself. In medical studies, various brain functions are often cited as the intervening variable (Borsook and Becerra 2005). For marketing
31
outcomes, the particulars of how expectancies operate are less understood. In a rejoinder to their empirical paper, SCA suggest that future research examine the mechanisms by which marketing induced expectancy translate into placebo-like outcomes (Shiv, Carmon, and Ariely 2005b). One potential intervening variable suggested by SCA is an individual’s level of felt anxiety or confidence. While they are not alone in suggesting this possibility, confidence as a placebo mechanism has yet to be empirically tested (Stewart-Williams and Podd 2004). The presented research, as discussed below, is well suited to address this gap in the literature.
STUDY 1: Qualitative Pretest
As mentioned in the introduction, the genesis for this essay came from an in-depth interview study examining athlete’s thoughts and feelings regarding mass customized athletic equipment. As the study progressed, one particularly interesting insight began to emerge. A significant percentage of the participants expressed the viewpoint that being able to customize various cosmetic features of their equipment helps their on-field performance. When questioned as to why this would be the case, participants’ comments suggest the presence of some psychological mechanism mediating the relationship. That an athlete’s performance is improved by allowing them to customize the color of their shoes seemed like a phenomenon worthy of more exploration. Thus, the qualitative study suggests an approach designed to focus more narrowly on the circumstances and mechanisms whereby cosmetic customization might generate a placebo-like effect with regards to individual performance. A few of the quotes motivating this shift in direction are presented below.
Customization allows you to feel like you’re involved…feel like, I guess, more confident. And I think that confidence, in my opinion, is the key to all sports. – Matt
32
(Customization) takes it to a new level where it almost makes you feel like a pro, like that the company is willing to give you that option to make it yours.…By allowing you to just tweak little things on it and make it yours, it’s kind of giving you part of that hero, or part of that attitude, I guess. (What do you mean by “that attitude”?) I don’t know, of being thought of that way, of being the star, of being someone who is worthy (of custom equipment). – Leticia
I think it’s more of a mental thing because the top athletes have the customized products. It feels like you have to have that level of customization. Whether it be tailored to your body or, you know, a special kind of suit. – Leah
As far as performance, I mean obviously (customization) is not really giving you any on the field boost, but I think it’s more of a confidence thing. – Bobby
STUDY 2: Demonstration in Consumer Settings
In study 1, participant comments point to confidence as potential outcome of customization that can result in increased performance. In retrospect, this finding is not surprising. A review of the literature reveals that the domain of sport is rich with anecdotes of superstitious behavior, occasionally studied in the context of placebo effects (Schippers and Van Lange 2006). A potential weakness of study 1 is that the context of athletic achievement might be considered as being on the fringes of mainstream consumer behavior. For study 2, the domain of individual performance under consideration is that of a job interview. The associated customized product is a custom-fit business suit. The goal of study 3 is to provide an empirical test regarding whether expected performance is related to purchase intentions for customized products via the mechanism of anticipated confidence. A sample of 112 undergraduate marketing students completed a survey preceded by a short hypothetical scenario describing a shopping trip associated with an upcoming interview. The survey was hosted in an online laboratory designed for conducting behavioral research. Course extra credit was offered as an incentive for participation.
33
H1: As suggested by study 1, anticipated confidence mediates the relationship between performance expectations and intentions to acquire customized products.
Stimulus and Procedure
Custom tailored clothing is certainly not a new product category. However, recent advances such as 3-D body scanning technologies make the mass-customization of clothing a reality. However, it is certainly possible that not all the participants in this study were aware of these new technologies. Thus, in order to minimize variation regarding knowledge of custom clothing, prior to accessing the survey, participants view a short video clip of a news program describing body scanning technologies related to mass customized clothing. After viewing this video, participants are asked to read a short survey regarding a hypothetical shopping trip for a suit to wear at an interview the following month. In the scenario, after selecting a suit, the participants are informed by a salesperson that the store is running a special where they can receive a custom fit suit for the same price. All they have to do is get a body scan and a custom fit suit will be delivered to them within the week. A picture of the body scanner featured in the news clip is placed to the left of the scenario (see Figure 3.1).
----------------------------------------------------
Insert Figure 3.1 about here ----------------------------------------------------
Measures
The dependent variable for this study is a single item asking individuals whether they want to keep the suit they had originally selected or opt for the customized version suggested by the salesperson. Expectancies regarding the effect of a customized suit on interview performance is measured using two agree/disagree nine point items: 1) Wearing a custom tailored business suit will help me perform better during my interview
34
and 2) Wearing a custom tailored business suit will help me do a good job during my interview. A measure of confidence is also included (see Appendix A for all scale items). All of the scales exhibit Cronbach’s alphas greater than .90.
Analysis and Results
A mediation analysis was conducted following the procedure described by Barron and Kenny (1986) (see Table 3.1). Step 1 examines the relationship between expectancies regarding the effect of a customized suit on interview performance (hereafter performance expectancies) and the measure regarding whether the individual would opt for the custom fit version of the suit they had selected (hereafter product choice) (see Table 3.1). A linear regression finds the effect of performance expectancies on product choice to be positive and significant (β =.414, t(1,118) = 4.947, p < .001). In the next step, the regression estimating the effect of performance expectancies on anticipated confidence is also significant (β =.717, t(1,118) = 11.161, p < .001). Similarly significant is the effect of anticipated confidence on product choice (β =.518, t(1,118) = 6.583, p < .001). In the final step, the relationship between performance expectancies and product choice becomes insignificant (β =.088, t(1,117) = .782, p = .436), while the relationship between confidence and choice remains highly significant (β =.455, t(1,117) = .436, p < .001) indicating full mediation. A Sobel test of the indirect path is also highly significant (z= 3.016, p
