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The Pennsylvania State University
The Graduate School
College of Health and Human Development
EXPLORING BUNDLING STRATEGIES FOR TOTAL REVENUE
MANAGEMENT
A Dissertation in
Hospitality Management
by
Myungekun Song
© 2018 Myungkeun Song
Submitted in Partial Fulfillment
of the Requirements
for the Degree of
Doctor of Philosophy
August 2018
ii
The dissertation of Myungkeun Song was reviewed and approved* by the following:
Breffni Noone
Associate Professor of Hospitality Management
Dissertation Advisor
Chair of Committee
Anna S. Mattila
Marriott Professor of Lodging Management
Professor-in-Charge Graduate Program
Hubert B. Van Hoof
Professor of Hospitality Management
Lisa E. Bolton
Professor of Marketing
*Signatures are on file in the Graduate School
iii
ABSTRACT
Revenue optimization efforts are centered upon driving revenue from a focal
product offering in the traditional revenue management setting. However, service firms
that apply revenue management usually have multiple ancillary products that have the
potential to make a significant revenue contribution. Therefore, revenue management
practitioners should develop strategies to drive revenue across all revenue streams to
effectively maximize total revenue. This concept, total revenue management, was
introduced in the early 2000’s, but the revenue management literature provides little
guidance in terms of actionable strategies for total revenue management implementation.
To address this gap, this dissertation explores effective bundling strategies for
maximizing total consumer spend at the online point of purchase. Study 1 found that a
mixed-non-leader bundle discount frame was more effective than an integrated mixed-
joint bundle discount frame when the non-leader product was hedonic in nature.
However, when the non-leader product was utilitarian in nature, there was no significant
difference in purchase intentions across the two bundle discount frames. Study 2 suggests
that standardized company-designed bundling may be more effective than customized
self-designed bundling when the non-leader product is hedonic in nature. However, when
the non-leader product is utilitarian in nature, customized self-designed bundling may be
the most effective approach. These findings provide revenue practitioners with firm
guidance on effective bundling practices for total revenue management.
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TABLE OF CONTENTS
List of Figures……………………………………………..……………………………vii
List of Tables……………………………………………...……………………………viii
Acknowledgements……………………………………………………………………...ix
CHAPTER 1. INTRODUCTION……………………..…………………………….…..1
CHAPTER 2. LITERATURE REVIEW……………………………………………….6
Overview………………………………………………………………………………...6
2.1 Product and Service Bundling………………………………………………………6
2.2 Bundle Discount Framing…………………………………………………………...8
2.3 Bundle Discount Frame and Ease of Justification………………………………....10
2.4 Consumption Nature and Ease of Justification…………………………………….13
2.5 Ease of Justification, Perceived Savings, and Purchase Intention…………………15
2.6 Customized Bundling……………………………………………………….……...18
2.7 Evaluation Modes………………………………………………………………….20
Summary of Hypotheses……………………………………………………………….23
CHAPTER 3. METHODS AND RESULTS………………………………………….25
Overview….……………………………………………………………………………25
3.1 Study Context……………………………………………………………………...25
3.2 Pre-test……………………………………………………………………………..26
3.2.1 Pre-test 1…………………………………………………………..……………26
3.2.1.1 Pre-test 1 Procedures………………………………………………………..26
3.2.1.2 Pre-test 1 Results……………………………………………………………28
3.2.2 Pre-test 2………………………………………………………………………..29
3.2.2.1 Pre-test 2 Procedures………………………………………………………..29
3.2.2.2 Pre-test 2 Results……………………………………………………………30
3.3 Study 1……………………………………………………………………………..31
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3.3.1 Procedures………………………………………………………………………31
3.3.2 Measures………………………………………………………………………..32
3.3.3 Results……………………………………………………………………...…...34
3.3.3.1 Sample Characteristics………………………………………………………34
3.3.3.2 Manipulation and Realism Checks……………………………...……….….36
3.3.3.3 Hypotheses Tests……………………………………………………………36
3.3.4 Discussion…………………………………………………………..……..……42
3.4 Study 2……………………………………………………………………….….…43
3.4.1 Procedures…………………………………...……………………………….....43
3.4.2 Measures………………………………..………………………………….…...44
3.4.3 Results………………………………………………………..………………...46
3.4.3.1 Sample Characteristics……………………………………………………...46
3.4.3.2 Manipulation and Realism Checks…………………………………………47
3.4.3.3 Hypotheses Tests……………………………………………………………49
3.4.4 Discussion…………………………………………………………..…………..53
CHAPTER 4. GENERAL DISCUSSION………………………..……………………55
4.1 Theoretical Implications…………………………………………………………...56
4.2 Managerial Implications…………………………………………………………...59
4.3 Limitations and Future Research Directions……………………………………….61
REFERENCES..........................................................................................................…...64
APPENDIX A: Study 1 Stimulus.....……………………………………………...……..75
APPENDIX A-1: Mixed-Non-Leader Frame & Hedonic Non-Leader Product
Condition…………………………………………………………....75
APPENDIX A-2: Mixed-Non-Leader Frame & Utilitarian Non-Leader Product
Condition……………………………………………………….…..76
APPENDIX A-3: Integrated Mixed-Joint & Hedonic Non-Leader Product Condition.77
APPENDIX A-4: Integrated Mixed-Joint & Utilitarian Non-Leader Product
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Condition…………………………………………………………..78
APPENDIX B: Study 2 Stimulus………………………………………………………..79
APPENDIX B-1: Company-Designed & Hedonic Non-Leader Product Condition….79
APPENDIX B-2: Company-Designed & Utilitarian Non-Leader Product Condition..80
APPENDIX B-3: Self-Designed Condition....……………..……………………..…...81
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LIST OF FIGURES
Figure 1 Conceptual Model for Study 1............................................................................18
Figure 2 Study 1: Mean Ratings for Ease of Justification by Experimental……………..38
Figure 3 Study 1: Mean Ratings for Perceived Savings by Experimental Condition……38
Figure 4 Study 1: Mean Ratings for Willingness to Purchase by Experimental
Condition……………………………………………………………..39
Figure 5 Study 2: Mean Ratings for Ease of Justification……………………………….52
Figure 6 Study 2: Mean Ratings for Willingness to Purchase…………………………...53
viii
LIST OF TABLES
Table 1 Scale Items………………………………………………………………………27
Table 2 Pre-Test 1: Means for Anticipated Price, Attractiveness, and Consumption
Nature by Non-Leader Product……………………………………..29
Table 3 Pre-Test 2: Means for Anticipated Price, Attractiveness, and Consumption
Nature by Non-Leader Product……………………………………..31
Table 4 Study 1: Scale Items…………………………………………………………….33
Table 5 Study 1: Sample Characteristics………………………………………………...35
Table 6 Study 1: Means for Ease of Justification, Perceived Savings, and Willingness to
Purchase by Experimental Condition………………………………….37
Table 7 Study 1: Result of Moderated Serial Mediation Analysis………………………41
Table 8 Study 2: Scale Items…………………………………………………………….46
Table 9 Study 2: Sample Characteristics………………………………………………...48
Table 10 Study 2: Means for Ease of Justification and Willingness to Purchase by
Experimental Condition………………………………………………51
Table 11. Study 2: MANOVA and univariate follow-up results………………………...52
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ACKNOWLEDGEMENTS
I would like to express my sincere appreciation to the many people who provided
support and direction toward the completion of this dissertation. This dissertation work
would not have been possible without their contributions and encouragement. First of all,
my deepest gratitude goes to my academic adviser and the committee chair, Dr. Breffni
Noone. Her insightful guidance was invaluable in conducting this dissertation. I
appreciate wholeheartedly, not only for her tremendous academic support, but also for
giving me so many wonderful opportunities. Dr. Noone, I will never forget the time I
spent with you here at Penn State. You made me a better educator as well as a better
researcher. It was truly my honor to have you as my academic adviser. I am so proud to
be your student. I will be missing you very much.
I would also like to express my sincere appreciation to Dr. Mattila, one of my
dissertation committee members. It was my honor to take your classes and work with
you. Also, I can’t thank you enough for all your help whenever I was struggling with my
research works including my dissertation. I sincerely appreciate your insightful guidance
and financial support for my research works. I will be missing you. And, Dr. Van Hoof
and Dr. Bolton, thank you very much for providing many invaluable insights and
suggestions that contributed to this dissertation. I really want to show my sincere respect
to you.
Further, special thanks to Dr. Quadri-Felitti for your endless support including
financial support. I could have not completed this dissertation without your support. Also,
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I would like to thank all the incredible faculty, staff members, and my friends at School
of Hospitality Management.
Finally, I would like to express my gratitude to my parents and sister for their
support and encouragement. I could not have completed my doctoral study without your
love and faith in me. I love you all so much.
1
CHAPTER 1. INTRODUCTION
Revenue management (RM) is a form of a capacity management in which demand
and supply are managed by manipulating price, time, and space to maximize revenue
(Kimes & Chase, 1998; Kimes & Renaghan, 2011; Kimes & Thompson, 2004, Kimes &
Wirtz, 2015; Song & Noone, 2017). RM is applicable to industries that have a relatively
fixed capacity, perishable inventory, a relatively high fixed, and low variable, cost
structure, and predictable but fluctuating demand (Wirtz & Kimes, 2007). RM has
traditionally been applied in the airline (Rose, 2016), hotel (Kimes, 2016), and rental car
(Li & Pang, 2017) industries. More recently, there has been a movement towards the
application of RM across a number of other tourism-related industries including the
restaurant (Kimes & Beard, 2013), spa (Kimes & Singh, 2009), and theme park (Heo &
Lee, 2009) industries.
Of the three levers of RM – price, time, and space - the focus of this research is
price. Specifically, this research examines potential approaches to driving ancillary
revenue in the context of traditional RM applications. In the traditional RM setting (i.e.,
airlines, hotels, rental car), revenue optimization efforts are centered upon driving
revenue from a focal product offering which is largely utilitarian in nature. For example,
the primary purpose of a seat on a plane is to provide the consumer with transportation
from one destination to another, while the fundamental purpose of a hotel guestroom is to
provide the consumer a place to sleep. However, in addition to a focal product, multiple
ancillary products exist that have the potential to make a significant revenue contribution
(e.g., airline lounge access and checked baggage revenues, hotel food and beverage and
2
spa revenues, and rental car GPS and insurance revenues). Thus, in order to effectively
maximize total revenue, revenue managers need to develop strategies to drive revenue
across all revenue streams. Reflecting this, the concept of total revenue management
(TRM) was introduced into the RM literature in the early 2000’s (Kimes, 2003). TRM
represents a strategic approach to RM wherein the focus is on total revenue optimization
rather than revenue optimization for the focal product alone. However, the RM literature
provides little guidance in terms of actionable strategies and tools for TRM
implementation. The current research seeks to address this gap in the literature by
exploring potential strategies to motivate consumer purchase of ancillary (add-on)
products when purchasing a focal product in the online environment.
Service firms within the traditional RM setting primarily leverage a standardized
bundling approach to drive consumer spend at the online point of purchase. However,
little is known about the impact of bundle discount frames on consumers’ reactions to
standardized bundles, or the potential role of customized bundling in driving revenue
performance. In Study 1, the author explores the effects of two different bundle discount
frames - mixed-non-leader and integrated mixed-joint - on purchase intentions. Within a
mixed-non-leader discount frame, a discount is provided on the add-on (non-leader)
product rather than the focal (leader) product, and the discount amount and the source of
the discount is explicitly identified (e.g., “Get a $10 discount on the airline lounge access
fee when you purchase an airline ticket/airline lounge access package”). In contrast, an
integrated mixed-joint discount frame simply highlights that the discount amount is on
the bundle itself (e.g., “Get a $10 discount when you purchase an airline ticket/airline
lounge access package”) (Gilbride, Guiltinan, & Urbany, 2008). Traditional RM
3
applications typically attach a best available rate (BAR) guarantee to focal products. In
this context, it is not meaningful to employ a bundle discount frame wherein a discount,
beyond the advertised BAR, is given on the focal product (Palamar & Edwards, 2007;
Rohlfs & Kimes, 2007). Thus, of the four bundle discount frames that service firms can
employ to frame bundle discounts (Gilbride et al., 2008), the two frames of interest in this
study are relevant in the traditional RM context. Further, while bundle discount frames
have been extensively studied in the literature (e.g., Guiltinan, 1987; Janiszewski &
Cunha, 2004; Khan and Dhar, 2010; Yadav, 1994, 1995), to the author’s knowledge this
is the first study to examine potential differences in consumer reaction to mixed-non-
leader and integrated mixed-joint frames.
Study 1 also seeks to advance the literature by exploring the mediating effects of
ease of justification and perceived savings on the bundle discount frame-purchase
intentions relationship. Rather than simply comparing differences in purchase intentions
across the two bundle discount frames of interest, the author suggests the underlying
mechanisms that may explain these differences. Finally, Study 1 incorporates
examination of the moderating effect of the consumption nature of non-leader product
within a bundle (utilitarian vs. hedonic) on the bundle discount framing-ease of
justification relationship. Khan and Dhar (2010) examined the effects of the consumption
nature of bundle components on purchase behavior in the context of a cross-category
bundle where the two components in the bundle were equivalent in terms of price and
centrality (i.e., both products were focal in nature). This study extends Khan and Dhar’s
(2010) work by examining the role of consumption nature in the bundle discount frame-
4
ease of justification relationship in the context of a tie-in bundle (i.e., focal and add-on
products).
In Study 2, the author examines the differential effects of company-designed
bundling (i.e., standardized bundling) and self-designed bundling (i.e., customized
bundling) on purchase intentions. For the purpose of this study, company-designed
bundling refers to the practice wherein a company bundles a focal (leader) product with a
single add-on (non-leader) product, and offers this standardized bundle to all consumers.
In contrast, self-designed bundling refers to the practice wherein a company provides the
consumer a choice of two non-leader products (one utilitarian and one hedonic), such that
the consumer can combine the non-leader product of their choice with the leader product
to create a customized bundle. Prior literature suggests that customized bundling will
yield a more positive consumer response than standardized bundling (e.g., Coulter &
Coulter, 2002; Coelho & Henseler, 2012). However, it is proposed that this finding may
not always hold. Rather, drawing on the concept of separate versus joint evaluation
modes, the author seeks to extend the literature, by suggesting that the consumption
nature of the non-leader product in the bundle may influence the effects bundling
(standardized versus customized) on purchase intentions.
From a managerial standpoint, it is anticipated that the insights yielded from this
study will provide revenue managers with firm guidance on effective bundling practices.
In the context of traditional RM applications, revenue managers are tasked with driving
revenue from a range of ancillary products that vary in terms of their consumption nature
(utilitarian vs. hedonic). By exploring the role of ancillary products’ consumption nature
on consumers’ reactions to bundle discount frames and customized bundles, this research
5
provides guidance on the optimal bundle discount frame and customization approach to
match with the ancillary product on offer. In doing so, the goal is to maximize the
likelihood of successfully cross-selling ancillary products and maximize revenue from all
revenue-generating assets within the organization.
This dissertation is organized as follows. In Chapter 2, relevant literature in the
domains of bundling, bundle discount frames, and customization is reviewed. Hypotheses
relating to the roles of ease of justification, perceived savings, and the consumption
nature of non-leaders products in consumers’ behavioral response to bundle discount
frames and customization are presented. In Chapter 3, a description of the research
methodology employed in Study 1 and Study 2, and the empirical results of the studies,
are provided. Finally, in Chapter 4, the theoretical and practical implications of the
findings from Study 1 and Study 2 are discussed, and directions for future research are
identified.
6
CHAPTER 2. LITERATURE REVIEW
Overview
In this chapter, the theoretical framework for the author’s research hypotheses is
presented. First, the role, and types, of bundling for RM are discussed. The author then
outlines the four types of bundle discount frames available to service providers, and
discusses the relevance of two specific frames, mixed-non-leader and integrated mixed-
joint, to traditional RM applications. The literature relating to the potential mediating
roles of ease of justification and perceived savings in the bundle discount frame-purchase
intentions relationship is presented. In addition, the potential moderating role of the
consumption nature of the non-leader product within a bundle on the bundle discount
frame-ease of justification relationship is discussed. Finally, the potential effect of
customized (versus standardized) bundling on purchase intentions is explored, with a
focus on the consumption nature of the non-leader product on consumers’ reaction to
customized bundling.
2.1 Product and Service Bundling
Product or service bundling encompasses the parceling of two or more products
and/or services, usually at a discounted price, and can be effective in driving consumer
spend, and increasing capacity utilization, across a service firm’s multiple revenue
streams (Ng, Wirtz, & Lee, 1999). Bundling can be categorized as pure or mixed (Adams
& Yelles, 1976; Guiltinan, 1987; Schmalensee, 1984). Pure bundling entails selling
products or services only in a bundled form (e.g., all-inclusive hotels and resorts) while
7
mixed bundling, the focus of this study, enables consumers to either to purchase products
and services individually or purchase them together in a bundle (e.g., a hotel guest room
only, dinner only, or guestroom and dinner package). A primary objective of mixed
bundling is to cross-sell products and services (Guiltinan, 1987). It can entice consumers
who are already willing to purchase a focal product (e.g., airline seat) into buying
additional products and/or services (e.g., airline lounge access, checked baggage, travel
insurance, or in-flight meal) that they initially may not have been willing to buy.
Underlying mixed bundling is the concept of consumer surplus (Guiltinan, 1987).
When an individual’s reservation price (i.e., the maximum amount he or she is willing to
pay for a certain product) exceeds the actual price of a certain product, consumer surplus
is created. In contrast, when an individual’s reservation price is less than the actual price
of a certain product, negative utility will be created. Without a bundle, consumers will
only purchase the product whose reservation price exceeds or at least equals to the actual
price. By combining two or more products, marketers expect that consumer surplus from
the high-value product (i.e., reservation price exceeds the actual price of the product) is
transferred to the low-value products (i.e., reservation price is lower than the actual price
of the product) and covers the negative utility. In turn, consumers are more likely to
purchase all products in the bundle. In addition, a price discount, an inherent element of
bundling, increases the change of cross-selling by increasing the consumer surplus from a
high-value product and/or decreasing the negative utility from a low-value product
(Guiltinan, 1987).
8
2.2 Bundle Discount Framing
If we assume that two products, A and B are in a bundled format, four different
bundle discount framings can emerge (Gilbride et al., 2008).
Discount frame 1: Discount on product A
Discount frame 2: Discount on product B
Discount frame 3: Discount on both product A and B
Discount frame 4: Discount on the bundle itself.
Assuming that consumers are already willing to buy product A but not B, A is the leader
product, and B can be considered as the non-leader product. Giving a discount on A
constitutes a mixed-leader frame, and giving a discount on B constitutes a mixed-non-
leader frame. Giving a discount on both A and B represents a segregated mixed-joint
frame, and giving a discount on the bundle itself represents an integrated mixed-joint
frame (Gilbride et al., 2008). Among these four discount frames, only two frames –
mixed-non-leader and integrated mixed-joint frames – may be relevant to traditional RM
applications.
RM requires the use of variable pricing to balance supply and demand (Kimes &
Chase, 1998). During low demand periods, revenue managers use price discounts to
stimulate demand and increase capacity utilization, while during high demand periods,
revenue managers close out lower rates and focus on building average rate from existing
demand. In the hotel industry, for example, a hotel will publish a BAR which represents
the lowest unqualified rate available on any given day based on prevailing market
9
conditions. In other words, if a consumer does not qualify for a special rate such as an
AAA, AARP, government, or corporate rate, they will be quoted the BAR rate (Palamar
& Edwards, 2007). BAR pricing is designed to reduce confusion amongst consumers, and
to guarantee that the consumer is quoted the lowest available rate for products or services
they provide regardless of booking channel (e.g., company direct or third-party
distribution channel) (Rohlfs & Kimes, 2007; Noone & Mattila, 2009). Based on the
principle of BAR pricing, it is unlikely that a service firm would employ a bundling
strategy wherein a further discount, beyond the advertised BAR, is given on the leader
product. Thus, of the four mixed bundle discount frames (mixed-leader, mixed-non-
leader, mixed-joint, and integrated mixed-joint), the mixed-non-leader and integrated
mixed-joint discount frames which do not encompass a discount on the leader product
(e.g., the guest room in a hotel and the airline seat in an airline) are most relevant to
bundling for traditional RM applications.
According to Guiltinan (1987), the consumer surplus created from one product in
a given bundle will readily transfer to other products in the bundle. In other words, in a
two-product bundle, a discount on one product will have the same effect on the bundle
evaluation as an equivalent discount on the other product in the bundle. Thus, it should
not matter which product is discounted as long as a discount amount is equivalent.
However, a number of research studies suggest that discount framing does impact bundle
evaluation (Janiszewski & Cunha, 2004; Gilbride et al., 2008; Yadav, 1994, 1995). For
example, Yadav (1995) in the context of non-durable goods, demonstrated the superiority
of a mixed-leader frame over a mixed-non-leader frame, and suggested the weighted
average model to explain this result (i.e., consumers sequentially evaluate each product in
10
the bundle, starting with the focal product, and tend to anchor the evaluation of the
bundle to their initial evaluation). In contrast, others demonstrated the superiority of the
mixed-non-leader frame over the mixed-leader frame. For example, drawing on the value
function from prospect theory, Janiszewski and Cunha (2004) found, in the context of
non-durable goods, that a mixed-non-leader frame was preferred to a mixed-leader frame
(Tversky & Kahneman, 1991). Other researchers have also investigated consumer
reaction to integrated and segregated bundle discount frames. For example, Gilbride et al.
(2008) used transaction utility theory to explain their findings in relation to the superior
impact of an integrated mixed-joint frame (vs. segregate mixed-joint, and mixed-leader,
frames) on purchase choice (Thaler, 1985). Here, the author seeks to advance the
literature by examining consumer response to two bundle discount frames which hitherto
have not been compared: mixed-non-leader and integrated mixed-joint.
2.3 Bundle Discount Frame and Ease of Justification
The ability to justify a decision has been identified as one of the most important
aspects of consumer decision-making (Bettman. Luce, & Payne, 1998). Since consumers’
purchase decisions are often evaluated by others as well as oneself, the ease with which a
purchase can be justified constitutes an approach goal that affects consumers’ purchase
intention and decision satisfaction (Bettman et al., 1998). In other words, consumers’
decisions such as whether to buy a bundle, and which product among options to select,
are affected by the degree of ease with which they can justify their decision. Here, it is
proposed that, by virtue of enhanced information transparency, consumers will perceive
11
the purchase of a bundle with a mixed-non-leader frame as easier to justify than a bundle
with an integrated mixed-joint frame.
A key difference between mixed-non-leader and integrated mixed-joint frames is
the degree of savings information transparency associated with them. Information
transparency is defined as the degree of availability, accessibility, and visibility of
information (Zhu, 2002). It has been suggested that transparent information aids product
evaluation because useful information is more readily available to the consumer during
the evaluation process (Lynch and Ariely, 2000; Grewal, Hardestry, and Iyer, 2004).
Chaiken, Liberman, and Eagly (1989) advance the Heuristic – Systematic Model (HSM)
of information processing as a framework to understand the role of information
transparency in consumers’ evaluations. According to the HSM, individuals process
information systematically (i.e., comprehensive and analytic information processing
where the individual scrutinizes all information), and/or heuristically (i.e., simple
inferential information processing that includes minimal amount of information and
analysis). The HSM suggests that an individual is likely to employ a less effortful,
heuristic information processing mode as long as a heuristic cue is available. Chaiken et
al. (1989) suggest that information transparency can be a heuristic signal for persuasive
and credible information. Prior research supports the notion that information transparency
can influence message persuasiveness. For example, Lynch and Ariely (2000)
demonstrated, in the context of online shopping, that more transparent information can
lead to higher consumer welfare. In the same context, Grewal et al. (2004) demonstrated
that relatively more transparent price information can mitigate the negative effect of price
discrimination on perceptions of trust, price fairness, and repurchase intentions. Miao and
12
Mattila (2007) demonstrated that consumers feel more confident when evaluating
products when they have access to highly transparent information than when they have
access to information that is low in transparency. Moreover, Tanford, Baloglu, & Erdem
(2012) suggest that the benefits associated with transparent information are most salient
when the information is related to benefits such as a discount. In sum, these findings
suggest that information transparency, particularly in relation to saving information, is
positively associated with consumer’s evaluation of a product.
Here, it is proposed that the greater information transparency associated with a
mixed-non-leader frame (vs. integrated mixed-joint frame) will facilitate consumers’
evaluations of the discount given to bundle by reducing the cognitive effort required for
evaluation. With a mixed-non-leader frame information regarding the amount of the
discount and the source of discount is explicitly provided to consumers, while with an
integrated mixed-joint frame, the only information consumers are provided is the amount
of the discount in relation to the bundle as a whole. Drawing on the notion that
information transparency can provide a heuristic signal for persuasive and credible
information (Chaiken et al., 1989), it is suggested that the greater information
transparency associated with a mixed-non-leader frame (vs. integrated mixed-joint
frame), will enable consumers to more easily justify the purchase of a bundle. Further, it
is expected that the effect of bundle discount frame on ease of justification will be
moderated by consumption nature of the non-leader product.
13
2.4 Consumption Nature and Ease of Justification
The literature distinguishes two types of consumption value: utilitarian and
hedonic. Utilitarian consumption value is related to rationally-oriented benefit, practical
functionality, and instrumentality. In contrast, hedonic consumption value is related to
affective and sensory gratification, fun, and entertainment (e.g., Babin, Darden, &
Griffin, 1994; Batra & Ahtola, 1990; Drolet & Williams, 2007; Lim & Ang, 2008;
Okada, 2005; Voss, Spangenber, & Grohmann, 2003). Therefore, hedonic consumption
represents relatively more guilt-inducing consumption than utilitarian consumption
(Okada, 2005). Utilitarian consumption is more closely related to necessary choice, while
hedonic consumption is more closely related to discretionary choice (Okada, 2005).
Moreover, the outcome of utilitarian consumption is easier to quantify because it is
related to a task and functional outcome, whereas the outcome of hedonic consumption is
more difficult to quantify because it is related to a personal and experiential outcome
(Okada, 2005).
Because of the characteristics of hedonic consumption – guilt-inducing,
discretionary consumption with outcomes that are difficult to quantify – it is more
difficult to justify hedonic consumption than utilitarian consumption (Hsee, 1996; Khan
& Dhar, 2010; Okada, 2005). Consequently, consumers typically seek additional reasons
to justify hedonic consumption. For example, Kivetz and Simonson (2002) suggest that
the degree of effort that a consumer has to exert to obtain a hedonic product is positively
related to the perceived right to engage in hedonic consumption. Associating charity
donations with hedonic consumption can also help to justify that consumption
(Strahilevitz & Myers, 1998). Khan and Dhar (2010) suggest the use of a price discount
14
as a means of helping consumers to justify hedonic consumption in the context of cross-
category bundling. They define a heterogeneous bundle as the combination of two
products that differ in consumption nature (i.e., one utilitarian and one hedonic product)
and a homogeneous bundle as the combination of two products with a similar
consumption nature (i.e., both products are either utilitarian or hedonic). They found, in
the context of heterogeneous bundles, that a discount on the hedonic product led to higher
purchase intentions than a discount on the utilitarian product. The price discount on the
hedonic product reduced the difficulty in justifying hedonic consumption. Giving a
discount on the utilitarian product, on the other hand, did nothing to enable the consumer
to justify consumption of the hedonic product in the bundle, and therefore was less
effective in increasing purchase intention for the bundle. In the case of a homogeneous
bundle, giving a discount on one or other of the products in the bundle did not have a
significant effect on ease of justification.
As previously noted, the focal or leader product in the context of traditional RM
applications is considered as largely utilitarian in nature because it provides functional
and necessary value (e.g., airline seat – transportation from the origin to the destination).
Therefore, when bundled with a non-leader product that is relatively hedonic in nature,
the bundle will be a heterogeneous bundle. In contrast, when the leader product is
bundled with a non-leader product that is relatively utilitarian in nature, the bundle will
be a homogeneous utilitarian bundle. In the case of a heterogeneous bundle (i.e., the non-
leader product is largely hedonic), a mixed-non-leader frame explicitly identifies that the
discount is on the non-leader product (e.g., $10 discount on airline lounge access). In
contrast, an integrated mixed-joint frame does not clearly state where discount comes
15
from (e.g., $10 discount on the package). In line with Khan and Dhar (2010), the author
expects that a mixed-non-leader frame will lead to higher ratings of ease of justification
than integrated mixed-joint frame when the non-leader product is hedonic. Further, given
that Khan and Dhar (2010) demonstrated that discounted product type (a discount on the
leader vs. a discount on the non-leader) does not have a differential effect on consumers’
perceptions of ease of justification for homogeneous bundles, the author proposes that the
bundle discount frame (mixed-non-leader frame vs. integrated mixed-joint frame) will
not have a significant impact on ease of justification when a non-leader product is
utilitarian.
H1: Consumption nature will moderate the relationship between bundle discount
frame and ease of justification. When the non-leader product is hedonic in nature,
a mixed-non-leader frame will lead to higher ratings for ease of justification than
an integrated mixed-joint frame. However, this gap in ease of justification ratings
between bundle discount frames (mixed-non-leader vs. integrated mixed-joint)
will not be as pronounced when the non-leader product is utilitarian in nature.
2.5 Ease of Justification, Perceived Savings, and Purchase Intention
Consumers, by virtue of their limited cognitive resources, generally desire to
minimize cognitive effort during decision making (March, 1978; Simon, 1955). Thus,
they tend to positively react to environments in which they can easily justify a given
decision (Bettman et al., 1998). Drawing on the concept of confirmation bias, it is
16
suggested here that the ease with which consumers can justify a product bundle will
positively impact their perceptions of the savings associated with that bundle.
Research in the domain of confirmation bias suggests that it is difficult to alter
consumers’ initial impressions about a given deal (e.g., Campbell & Warren, 2014;
Chernev, 2001; Klayman, 1995; Nakayama & Sutcliffe, 2005; Nickerson, 1998; Yin,
Mitra, & Zhang, 2016). Confirmation bias is defined as an individual’s tendency to seek,
and focus relatively more on, information that he thinks is supportive of his existing
beliefs. Individuals do not treat evidence supporting and opposing their existing beliefs
equally (Klayman, 1995). They either seek only supporting evidence, overweighting this
supporting evidence, or distort opposing evidence (Nickerson, 1998). This is likely due to
the fact that individuals are fundamentally limited to thinking of only one thing at a time,
and, once they focus on a particular hypothesis or belief, they continue to do so (Doherty
& Mynatt, 1986). Therefore, they collect information and evidence that can support their
beliefs instead of alternative beliefs (Doherty & Mynatt, 1986). The idea of confirmation
bias has been widely demonstrated in the literature. For example, Chernev (2001)
demonstrated that consumers evaluate common features in a manner that supports their
existing preferences. In the context of a choice task, positive common features were used
as evidence that supported already established preference. In contrast, negative common
features were discounted as evidence that opposed the established preference. In addition,
Yin et al. (2016) suggested confirmation bias as a theory that reconciles contradicting
findings in the context of consumer reactions to online reviews. They found that when
consumers’ initial impressions about a product were positive, the effect of positive
reviews on consumers’ subsequent evaluations of that product was more salient than the
17
effect of negative reviews. In contrast, when consumers’ initial impressions about a
product were negative, the effect of negative reviews on consumers’ subsequent
evaluation of that product was more salient than the effect of positive reviews.
Based on these findings, the author suggests that the initial impression that
consumers form about a deal, as a function of how easy they find it to justify the deal,
will affect their subsequent evaluation of the deal. If consumers perceive a deal as easy to
justify, they will perceive it as a fairly good deal. Subsequently, they will process
additional aspects of the deal, in particular the perceived savings associated with the deal,
in a manner that supports their initial belief about the deal. In other words, ease of
justification will be positively associated with the perceived savings associated with a
deal. Further, in line with previous research (e.g., Gonzalez, Esteva, Roggeveen, &
Grewal, 2016; Gupta & Cooper, 1992), the author expects that perceived savings will
positively affect willingness to purchase.
In sum, the author proposes that when the non-leader product within a bundle is
hedonic in nature, the higher ease of justification associated with a mixed-non-leader
frame (vs. an integrated mixed-joint) will drive higher perceptions of savings. This will
eventually yield a greater impact on consumers’ willingness to purchase for a mixed-non-
leader frame (vs. an integrated mixed-joint). In the case of a utilitarian non-leader
product, an insignificant difference in ease of justification between a mixed-non-leader
frame and an integrated mixed-joint frame will also lead to insignificant differences in
perceived savings and willingness to purchase between these two frames.
18
H2: There will be an indirect effect of bundle discount frame on willingness to
purchase through ease of justification and perceived savings. The serial
mediation effects will be more salient when the consumption nature of the non-
leader product in the bundle is hedonic (vs. utilitarian).
See Figure 1 for the conceptual model for Study 1.
Figure 1. Conceptual Model for Study 1
2.6 Customized Bundling
Over the past number of decades, there has been a growing recognition among
scholars and practitioners that product and service differentiation represents a source of
competitive advantage (Coelho & Henseler, 2012). One form of differentiation,
customization, represents the degree to which the firm’s offering is tailored to meet
heterogeneous consumers’ needs (Anderson, Fornell, & Rust, 1997), with the core goal of
Bundle
Discount Frame
Ease of
Justification
Perceived
Savings
Willingness
to Purchase
Consumption
Nature
19
customization being to design products and services that optimally satisfy the needs of a
given target market (Coelho & Henseler, 2012).
Several researchers have demonstrated the positive effects of customization on
consumer behavior. For example, Franke and his colleagues (2009) demonstrated that
product customization results in significantly higher purchase intentions, and a more
favorable attitude toward a given product than standard products because customization
more closely fits consumers’ preferences. In addition, Coelho and Henseler (2012)
showed that customization increases consumers’ perceived service quality, satisfaction,
and loyalty toward a service provider. Moreover, they demonstrated that customization
increases consumers’ trust toward providers, as customization represents a company’s
effort to reduce consumers’ uncertainty regarding a given product, and better satisfy
consumers’ heterogeneous needs. In a similar vein, Coulter and Coulter (2002) identified
seven significant predictors of trust, and demonstrated that customization was one of the
most powerful and durable builders of trust among the seven identified predictors.
Together, these findings suggest that consumers, in the context of product bundling, may
prefer customized bundles over standardized bundles. Based on the author’s expectation
of the general superiority of a mixed-non-leader bundle discount frame over an integrated
mixed-joint frame, the author focuses solely on a mixed-non-leader frame in the
following examination of customized (vs. standardized) bundling.
In the context of bundling, a service firm can simply choose and offer a single
non-leader product to cross-sell at the point of purchase with the leader product,
regardless of individual consumer’s needs. This represents a company-designed, or
standardized, bundle. In contrast, a service firm can provide a list of available non-leader
20
products from which consumers can choose a product to bundle with the leader product.
This represents a self-designed, or self-customized, bundle. In the case of self-designed
bundles, consumers participate in the bundle design process because they actually define
the elements of their bundled product. Prior research has demonstrated a positive
association between consumer participation and perceived control (e.g., Bateson, 1985;
Chan, Yim, and & Lam, 2010; Dabholkar, 2015), with perceived control, in turn,
positively influencing consumers’ evaluations of service experiences (Hui & Bateson,
1991; Noone, 2008; Noone, Wirtz, & Kimes, 2010). These findings suggest that a self-
designed bundle will be preferred over a company-designed bundle. However, the author
suggests that a self-designed bundle may not always be perceived as superior. Rather,
drawing on the concept of evaluation modes, it is proposed that the utilitarian versus
hedonic consumption value associated with the non-leader product in a bundle will
influence consumers’ reactions to self-designed (vs. company-designed) bundling.
2.7 Evaluation Modes
Evaluation mode refers to the distinction between evaluating a product in
isolation (i.e., separate evaluation mode) and evaluating it in the context of one or more
alternatives (i.e., joint evaluation mode) (Krüger, Mata, & Imhels, 2014). According to
evaluative theory, any evaluation represents one of these two modes (Hsee & Zhang,
2010). The situation wherein the consumer is presented a company-designed bundle,
comprising of a leader product and a single non-leader product, represents a separate
evaluation mode (i.e., the consumer has to evaluate only one non-leader product). In
21
contrast, with a self-designed bundle, consumers will be presented with multiple non-
leader products and must decide which product amongst those available they want to
include in their bundle. This situation represents a joint evaluation mode (i.e., the
consumer has to evaluate multiple non-leader products), where the non-leader products
will either be more utilitarian (e.g., travel insurance) or hedonic (e.g., airline lounge
access) in nature.
As previously mentioned, consumers find it relatively difficult to justify hedonic
consumption (vs. utilitarian consumption) because hedonic consumption is relatively
more guilt-inducing, discretionary, and its outcomes are more difficult to quantify, than
utilitarian consumption (Hsee, 1996; Khan & Dhar, 2010; Okada, 2005). Furthermore,
Okada (2005) demonstrated that consumers prefer hedonic consumption when it is
separately evaluated from, rather than jointly evaluated with, utilitarian consumption. In
other words, consumers find it more difficult to justify their hedonic consumption when it
is jointly evaluated with utilitarian consumption, which is relatively easy to justify, than
when hedonic consumption is evaluated alone. This is due to the contrast effect.
Consumers’ perceptions of an object are influenced by other objects in a comparison set.
For example, Thornton and Moore (1993) demonstrated that self-ratings of attractiveness
by men and women were influenced by the level of attractiveness of same-sex others in a
comparison set. When men and women were exposed to a highly attractive same-sex
person, their self-attractiveness ratings were lower than the self-attractiveness ratings of
those who were not. The high attractiveness of others highlighted the relatively lower
attractiveness of the individual when jointly evaluated. In a similar vein, Thornton and
Maurice (1997) demonstrated that women who were exposed to photos of models
22
typifying idealized thin physiques indicated lower self-esteem and higher self-
consciousness, social physique anxiety, and body dissatisfaction than women who were
not exposed to any photo. These findings suggest that, when consumers jointly evaluate
hedonic and utilitarian non-leader products during self-customization, the characteristics
of the relatively more utilitarian product will highlight the characteristics of the hedonic
non-leader products (i.e., discretionary, guilt-inducing, with difficult to quantify
outcomes) due to the contrast effect (Thornton & Moore, 1993). Thus, it is proposed that
consumers will be more likely to find it easier to justify the purchase of a self-customized
bundle that contains a utilitarian non-leader product rather than one with a hedonic non-
leader product. Consequently, they will be more willing to purchase a self-customized
bundle with a utilitarian non-leader product than one with a hedonic non-leader product.
In contrast, it is expected that, in a separate evaluation mode (company-designed
bundle), consumers will not demonstrate a preference for a utilitarian non-leader product
over a hedonic non-leader product. In the context of a separate evaluation mode, the
consumer has little information about other non-leader products that are available to
them, or even the existence of other options. Consumers construct justifications for the
decisions that they are motivated to make (Kunda, 1990). Thus, in the absence of an
explicit comparison against utilitarian non-leader products in the separate evaluation
mode, it is relatively easy for the consumer to justify purchasing a hedonic non-leader
product. Consequently, it is proposed that there will be no significant difference in ease
of justification across hedonic and utilitarian non-leader product bundles in a separate
evaluation mode. By extension, it is expected that willingness to purchase ratings will not
23
be significantly different between bundles with a hedonic non-leader product and those
with a utilitarian non-leader product. Hence, it is hypothesized:
H3a: For self-designed bundles, a bundle with a utilitarian non-leader product will
yield significantly higher ease of justification ratings than a bundle with a hedonic
non-leader product.
H3b: For company-designed bundles, there will be no significant difference in
ease of justification ratings between a bundle with a utilitarian non-leader product
and a bundle with a hedonic non-leader product.
H4a: For self-designed bundles, consumers will be more inclined to purchase a
bundle with a utilitarian non-leader product.
H4b: For company-designed bundles, there will be no significant difference in
willingness to purchase ratings between a bundle with a utilitarian non-leader
product and a bundle with a hedonic non-leader product.
Summary of Hypotheses
In this chapter, a number of hypotheses were presented regarding the nature of the
relationship between types of bundle discount frames (mixed-non-leader and integrated
mixed-joint) and consumers’ willingness to purchase. Based on the lower cognitive effort
associated with processing transparent (vs. non-transparent) information, it was proposed
that the purchase of a bundle with a mixed-non-leader frame will be perceived as easier
to justify than the purchase of a bundle with an integrated mixed-joint frame when the
24
non-leader product is hedonic nature. This gap is not expected to be significant when the
non-leader product is utilitarian in nature. In addition, based on confirmation bias theory,
and findings in the previous literature in relation to the positive relationship between
perceived savings and willingness to purchase, the author expects the indirect effect of
the type of bundle discount frame on willingness to purchase through ease of justification
and perceived savings will be more salient when the non-leader product is hedonic
nature.
In addition, two hypotheses were presented regarding the effect of bundle type
(self-designed vs. company-designed) on ease of justification and willingness to purchase
depending upon the consumption nature of the non-leader product in the bundle. Drawing
on the concept of evaluation mode, it was proposed that there would be no significant
difference in ease of justification and willingness to purchase ratings between company-
designed bundles that contain a hedonic non-leader product and those that contain a
utilitarian non-leader product. However, in the case of a self-designed bundle, it was
proposed that the consumer will find it significantly easier to justify the purchase of a
bundle with a utilitarian non-leader product than one with a hedonic non-leader product,
and consequently, willingness to purchase ratings will be higher for a bundle with a
utilitarian non-leader product.
25
CHAPTER 3. METHODS AND RESULTS
Overview
The current research is composed of two studies. Study 1 tests H1 and H2 by
examining a) the moderating role of the consumption nature of the non-leader product in
a bundle on the relationship between bundle discount frames (mixed-non-leader vs.
integrated mixed-joint) and ease of justification and b) the serial mediating role of ease of
justification and perceived savings on the relationship between bundle discount frames
and willingness to purchase. Study 2 tests H3 and H4 by examining the effect of bundle
type (self-designed vs. company-designed), and the consumption nature of the non-leader
product in a bundle, on ease of justification and purchase intentions. In the following
sections, the author describes the pre-tests conducted in advance of Studies 1 and 2,
followed by descriptions of the design of the studies including the stimuli, procedures and
measures employed, and the results of the hypotheses tests.
3.1 Study Context
The airline industry, which represents a traditional application of RM, was
selected as the context for this research. The focal product, a seat on an airplane, is
largely utilitarian in nature, thus fitting the examination of the bundle discount frames of
interest in this research. Additionally, the airline industry has multiple ancillary revenue
sources, that can be classified as relatively more hedonic (e.g., airline lounge access and
in-flight entertainment) or utilitarian (e.g., checked baggage and travel insurance) in
nature, allowing for the examination of the role of the consumption nature of the non-
26
leader product within a given bundle on consumer reaction to different types of bundle
discount frames, and customized (vs. standardized) bundles.
3.2 Pre-tests
Before Study 1 and Study 2 were conducted, the author conducted two pre-tests to
identify appropriate and comparable hedonic and utilitarian non-leader products in terms
of anticipated price and perceived attractiveness. Anticipated price was measured because
it has been widely demonstrated that price of a product affects consumers’ value and
quality perceptions and their purchase intention (e.g., Zeithmal, 1988). Perceived
attractiveness was also measured as it has been shown that the attractiveness of a product
may influence the ease with which consumers can justify product choice (Khan & Dhar,
2010), and approach behaviors (Bloch, 1995; Crilly, Moultrie, & Clarkson, 2004).
3.2.1 Pre-test 1
3.2.1.1 Pre-test 1 Procedures
The author included a total of seven non-leader products – checked-baggage,
airline lounge access, a seat with extended leg-room, travel insurance, in-flight
entertainment, a light-meal package, and on-board dining – in Pre-test 1. Participants
were randomly assigned to one of the seven non-leader products. In each condition,
participants were presented with a description, and a photograph, of a non-leader product,
and they were asked to rate the hedonic and utilitarian consumption nature of that product
27
using a single product, 7-point bipolar scale anchored by primarily utilitarian and
primarily hedonic (Khan & Dhar, 2010). Prior to completing this scale, participants were
provided with definitions of utilitarian (“a product is purchased for functional,
instrumental, and practical purposes) and hedonic (“a product is purchased for fun,
enjoyable experience, and entertainment purpose”) products. Participants were also asked
to specify the price they would anticipate paying for the product by using a sliding-scale
from $20 to $70. This price range was based on online search of major U.S. airlines’
website conducted in November 2017. Finally, participants were asked to rate the
attractiveness of the non-leader products using a 5-item, 7-point Likert scale anchored by
strongly disagree and strongly agree (Khan & Dhar, 2010; Cronbach’s α = 0.83). See
Table 1 for all scale items. Participants were recruited using Amazon Mechanical-Turk.
Table 1. Scale Products
Hedonic and utilitarian consumption nature (Khan and Dahr, 2010)
This checked-baggage service (the other six products) is ----- primarily utilitarian ~ primarily hedonic
Anticipated price
Please, rate your anticipated price for this checked-baggage service (the other six products) by using the
price scale from $20 to $70
Attractiveness
This checked-baggage service (the other six products) is attractive
This checked-baggage service (the other six products) can considerably improve the quality of my travel
experience.
Many other customers want to buy this checked-baggage service (the other six products).
This checked-baggage service (the other six products) fills a real need for me.
This checked-baggage service (the other six products) can give me real value
28
3.2.1.2 Pre-test 1 Results
A total of 70 individuals who passed simple attention checks were included in the
analyses, yielding an equal number of participants in each condition (n = 10 for each of
all seven conditions). The mean ratings for anticipated price, attractiveness, and
consumption nature by non-leader product are reported in Table 2. In terms of anticipated
price and attractiveness, four products – airline lounge access, on-board dining, checked-
baggage, and travel insurance – grouped together (Anticipated price: Mairline lounge access =
$32.47, Mon-board dining = $30.91, Mchecked-baggage = $31.00, Mtravel insurance = $34.53, p>0.4;
Attractiveness: Mairline lounge access = 4.57, Mon-board dining = 4.99, Mchecked-baggage = 4.55, Mtravel
insurance = 4.93, p>0.2). Another two products – a seat with extended leg-room and in-
flight entertainment – emerged as comparable on anticipated price and attractiveness
ratings (Anticipated price: Ma seat with extra legroom = $23.93, Min-flight entertainment =$21.53,
p>0.5; Attractiveness: Ma seat with extra legroom = 4.99, Min-flight entertainment = 5.34, p>0.1). The
final product - a light meal package - was rated significantly lower than the other six
products in terms of anticipated price (Mlight meal package = $14.04, p<0.05). Therefore, this
product was excluded from the further analysis.
In terms of the consumption nature of the products, two products among the set of
four comparable products – airline lounge access and on-board dining – were perceived
as relatively hedonic in nature (Mairline lounge access = 5.67, Mon-board dining = 5.00), and the
other two products – checked-baggage and travel insurance – were perceived as relatively
utilitarian in nature (Mchecked-baggage = 2.35, Mtravel insurance = 2.09). Both the seat with
extended leg-room and in-flight entertainment were perceived as relatively hedonic in
nature (Ma seat with extra legroom = 5.00, Min-flight entertainment =5.72). As a result, the four products
29
that were comparable in terms of anticipated price and attractiveness were selected for
further investigation in the second pre-test. Specifically, airline lounge access and on-
board dining were selected to represent products that are largely hedonic in nature, and
checked-baggage and travel insurance were selected to represent products that are largely
utilitarian in nature.
Table 2. Pre-Test 1: Means for Anticipated Price, Attractiveness, and Consumption
Nature by Non-Leader Product
Non-Leader Products
Means
Anticipated
Price Attractiveness
Consumption
Nature
Airline lounge access $32.47 4.57 5.67
On-board dining $30.91 4.99 5.00
Checked-baggage $31.00 4.55 2.35
Travel insurance $34.53 4.93 2.09
Light meal package $14.04 4.93 4.30
Extended-legroom $23.93 4.99 5.00
In-flight entertainment $21.53 5.34 5.72
3.2.2 Pre-test 2
3.2.2.1 Pre-test 2 Procedures
Pre-test 2 was conducted to ensure that the findings in relation to the four non-
leader products selected in Pre-test 1 held across a different sample of consumers. As
with Pre-test 1, participants were recruited using Amazon Mechanical-Turk, and were
randomly assigned to one of four non-leader products. The procedure and scales
employed in Pre-test 2 were identical to those used in Pre-test 1. The attractiveness scale
was reliable (Cronbach’s α = 0.89; Khan & Dhar, 2010).
30
3.2.2.2 Pre-test 2 Results
A total of 136 participants who passed simple attention checks were included in
the analysis, yielding an equal number of participants in each condition (n = 34 for each
of all four conditions). The mean ratings for anticipated price, attractiveness, and
consumption nature by non-leader product are reported in Table 3. In terms of anticipated
price, three products – airline lounge access, checked-baggage, and travel insurance –
were comparable (Mairline lounge access = $40.65, Mchecked-baggage = $35.74, and Mtravel insurance =
$42.84, p>0.1). The on-board dining was excluded from further analysis because the
anticipated price was not comparable with airline lounge access (Mon-board dining = $29.71,
Mairline lounge access = $40.65, p<0.05) and travel insurance (Mon-board dining = $29.71, Mairline
lounge access = $42.84, p<0.01). In terms of attractiveness, the three selected products were
comparable (Mairline lounge access = 4.62, Mchecked-baggage = 4.79, Mtravel insurance = 4.27, p>0.3).
In terms of the consumption nature of the products, airline lounge access was perceived
as significantly more hedonic than the other two products (Mairline lounge access = 6.16,
Mchecked-baggage = 1.97, p<0.0001; Mairline lounge access = 6.16, Mtravel insurance = 2.03, p<0.0001).
Based on the results of Pre-test 2, the author selected airline lounge access as the hedonic
non-leader product and checked-baggage and travel insurance as the utilitarian non-leader
product for Study 1.
31
Table 3. Pre-Test 2: Means for Anticipated Price, Attractiveness, and Consumption
Nature by Non-Leader Product
Non-Leader Products
Means
Anticipated Price Attractiveness
Consumption
Nature
Airline lounge access $40.65 4.62 6.16
Checked baggage $35.74 4.79 1.97
Travel insurance $42.84 4.27 2.03
On-board dining $29.71 5.07 5.55
3.3 Study 1
3.3.1 Procedures
To test H1 and H2, the author employed a 2 (bundle discount frame: mixed-
non-leader vs. integrated mixed-joint) x 2 (consumption nature of the non-leader product:
hedonic vs. utilitarian) between-subject experimental design. Participants were randomly
assigned to one of the four conditions. All participants were asked to imagine that they
planned to travel to a city located in the U.S. They were told that they decided to
purchase a round trip ticket, that the price of this round-trip ticket was $250, and that the
price included a regular economy seat for their flights to, and back from, the destination
city, as well as one carry-on personal product that could fit under the seat. Finally, they
were told that the airline company provided additional services for extra charges. For
participants who were assigned to the utilitarian (hedonic) condition, checked baggage
(airline lounge access) was shown as the non-leader product in the bundle. Participants
were informed that the regular price of the non-leader products was $35. This price was
based on market research, as well as the anticipated prices reported by participants in Pre-
tests 1 and 2. Participants who were assigned to the mixed-non-leader frame condition
(the integrated mixed-joint frame condition) were informed that they would receive a $10
32
discount on the $35 value of non-leader product (a $10 discount on the $285 total
package cost) if they purchased the package. See the stimuli in Appendix A. After
reading their assigned scenario, participants completed a questionnaire that contained
items used as manipulation checks, measures for the key variables, a realism check, and
demographic questions.
3.3.2 Measures
Willingness to purchase was measured using a 3-item, 7-point Likert scale
anchored by strongly disagree and strongly agree (Maxwell, 2002; Cronbach’s α = 0.97).
A 3-item, 7-point Likert scale anchored by strongly disagree and strongly agree was used
to measure ease of justification (Heitman et al., 2007; Cronbach’s α = 0.83). Perceived
savings were measured using a 2-item, 7-point Likert scale anchored by strongly disagree
and strongly agree (Gonzalez et al., 2016; r=0.75).
Level of complementarity was included as a control variable in the analyses.
Complementarity implies that the reservation price for one product is increased if the
other is purchased (Guiltinan, 1987). Thus, to control for the potential effects of
differences in the perceived level of complementarity of products across bundles on the
outcome variables of interested in the study, level of complementarity was measured
using a 3-item, 7-point Likert scale anchored by strongly disagree and strongly agree was
used (Sheng, Parker, & Nakamoto, 2007; Cronbach’s α =0.73).
The author used a single item, 7-point bipolar scale anchored by primarily
utilitarian (1) and primarily hedonic (7) to ensure that the manipulation for consumption
33
nature of the non-leader product was successful (Khan & Dhar, 2010). As in the pre-tests,
definitions of utilitarian and hedonic products were provided. In addition, to ensure that
the manipulation for bundle discount framing was successful, participants were asked to
indicate which product in the bundle was discounted. Finally, a single item measure was
used to assess the realism of the scenarios presented to the study’s participants (7-point
Likert scale, anchored by highly unrealistic and highly realistic). See Table 4 for all scale
products.
Table 4. Study 1: Scale Items
Willingness to purchase (Maxwell, 2002)
The likelihood of me buying this airline ticket/checked baggage package (airline ticket/airline lounge
access package) is
My willingness to buying this airline ticket/checked baggage package (airline ticket/airline lounge access
package) is
The probability that I would consider buying this airline ticket/checked baggage package (airline
ticket/airline lounge access package) is
Perceived Savings (Gonzalez et al., 2016)
I would be saving a lot of money if I purchase this airline ticket/checked baggage package (airline
ticket/airline lounge access package)
This airline is selling airline ticket/checked baggage package (airline ticket/airline lounge access
package) at a considerable discount
Ease of justification (Heitmann et al., 2007)
I think it would be easy to justify buying this airline ticket/checked baggage package (airline
ticket/airline lounge access package)
I am able to see at first sight that this airline ticket/checked baggage package (airline ticket/airline lounge
access package) is attractive
In order to make a purchase decision for this airline ticket/checked baggage package (airline
ticket/airline lounge access package), it was not necessary to make any difficult trade-offs
Level of Complementarity (Sheng et al., 2007)
Airline ticket and checked baggage (airline lounge access) are highly complementary
Airline ticket checked baggage (airline lounge access) are very likely to be used together
Hedonic and utilitarian consumption nature (Khan and Dahr, 2010)
The checked baggage (airline lounge access) is ----- primarily utilitarian ~ primarily hedonic
Realism check
The situation described in the scenario was realistic.
34
3.3.3 Results
3.3.3.1 Sample Characteristics
A total of 200 participants were recruited via a 3rd party data collection
company, and 178 individuals who passed the attention checks were retained for the
analysis, yielding an approximately equal number of participants in each experimental
condition (n=44 for the mixed-non-leader/hedonic, and the mixed-non-leader/utilitarian
conditions; n=45 for the integrated mixed-joint/hedonic, and the integrated mixed-
joint/utilitarian conditions). Approximately, 47% (n=84) of the participants were male.
The average age of the participants was 44.49. The majority of participants had a college
degree or higher education (88.2%; n=157) and a full-time job (73.6%; n=131), with
79.2% (n=141) having a household income higher than $50,000. The majority of
participants (35.4%; n=63) had taken a flight 3 or 4 times for trip in the 24 months prior
to participating in the survey, with a further 44.3% (n=79) taking a flight more than 4
times. See Table 5 for the full characteristics of the sample.
35
Table 5. Study 1: Sample Characteristics
a last 24 months
Variable N %
Gender
Male 84 47.2
Female 94 52.8
Age
34 or under 58 32.58
35 – 50
51 – 69
70 or older
56
60
4
31.46
33.71
2.25
Education
Some High school or less 1 0.6
High School 20 11.2
College 101 56.7
Graduate school 56 31.5
Employment
Full-time 131 73.6
Part-time 15 8.4
Not currently employed 7 3.9
Retired 20 11.2
Student 3 1.7
Other 2 1.1
Household income
Less than $25,000 11 6.2
$25,000 to $49,999 26 14.6
$50,000 to $74,999 24 13.5
$75,000 to $99,999 33 18.5
$100,000 to $124,999 26 14.6
$125,000 to $ 149,999 22 12.4
$150,000 or more 36 20.2
Frequency of taking a flight for tripsa
1-2 times 36 20.2
3-4 times 63 35.4
5-6 times 20 11.2
More than 6 times 59 33.1
36
3.3.3.2 Manipulation and Realism Checks
For the consumption nature of the non-leader product manipulation, the
ratings were significantly higher in the hedonic condition than in the utilitarian condition
(Mhedonic = 5.02, Mutilitarian = 3.45, p<0.001). Thus, the manipulation for the consumption
nature of the non-leader product was successful. In terms of the bundle discount framing
manipulation, all participants in the mixed-non-leader frame condition correctly indicated
that the $10 discount was given on the non-leader product, and all participants in the
integrated mixed-joint frame condition correctly answered that $10 discount was given
on the bundle itself. Therefore, the bundle discount framing manipulation was successful.
All four scenarios were perceived as realistic (Mmixed-non-leader & hedonic = 5.34, Mmixed-non-
leader & utilitarian = 5.49, Mintegrated mixed-joint & hedonic = 5.71, Mintegrated-mixed-joint & utilitarian = 5.63).
3.3.3.3 Hypotheses Tests
The cell means for ease of justification, perceived savings, and willingness to
purchase are reported by experimental condition in Table 6. Consistent with expectations,
the cell means for ease of justification indicated that, when the consumption nature of the
non-leader product was hedonic, participants perceived the mixed-non-leader frame as
significantly easier to justify than the integrated mixed-joint frame (Mmixed-non-leader = 4.95,
Mintegrated mixed-joint= 3.47; p < 0.001). The gap in ease of justification was not significant
when the consumption nature of the non-leader product was utilitarian (Mmixed-non-leader =
5.03, Mintegrated mixed-joint = 4.57; p > 0.1). A similar pattern in cell means was present for
perceived savings and willingness to purchase. Participants perceived savings in the
37
mixed-non-leader frame as significantly greater than savings in the integrated mixed-joint
frame when the consumption nature of the non-leader product was hedonic (Mmixed-non-
leader = 4.20, Mintegrated mixed-joint= 2.68; p < 0.001). However, the gap in perceived savings
between the mixed-non-leader, and integrated mixed-joint, frames was not significant
when the non-leader product was utilitarian in nature (Mmixed-non-leader = 4.14, Mintegrated
mixed-joint= 3.69; p > 0.1). Finally, when the consumption nature of the non-leader product
was hedonic, a mixed-non-leader frame led to significantly higher ratings for willingness
to purchase than an integrated mixed-joint frame (Mmixed-non-leader = 4.54, Mintegrated mixed-
joint= 2.48; p < 0.001). But, the gap in willingness to purchase between the mixed-non-
leader and integrated mixed-joint frames was not significant when the non-leader product
was utilitarian in nature (Mmixed-non-leader = 4.68, Mintegrated mixed-joint= 4.27; p > 0.5).
Together, these results provide initial support for H1 and H2. These results are visualized
in Figure 2 to 4.
Table 6. Study 1: Means for Ease of Justification, Perceived Savings, and
Willingness to Purchase by Experimental Condition
Frame Consumption
Nature
Means
Ease of
justification
Perceived
savings
Willingness to
purchase
Mixed-non-
leader
Hedonic 4.95 4.20 4.54
Utilitarian 5.03 4.14 4.68
Integrated
mixed-joint
Hedonic 3.47 2.68 2.48
Utilitarian 4.57 3.69 4.27
38
Figure 2. Study 1: Mean Ratings for Ease of Justification by Experimental
Condition
Figure 3. Study 1: Mean Ratings for Perceived Savings by Experimental Condition
1
2
3
4
5
6
7
Hedonic Utilitarian
Mea
n R
atin
gs
for
Eas
e o
f Ju
stif
icat
ion
Consumption Nature of the Non-Leader Products
Mixed-non-leader Integrated mixed-joint
39
Figure 4. Study 1: Mean Ratings for Willingness to Purchase by Experimental
Condition
A customized PROCESS model macro in SPSS was employed to formally test
H1 and H2 (Hayes, 2017). This procedure used an ordinary-least squares path analysis to
estimate the coefficients in the model in order to determine the direct and indirect effects
of bundle discount frames on willingness to purchase. The author specified a bmatrix to
reflect the hypothesized mediating effects of ease of justification and perceived savings
on the bundle discount frame type-willingness to purchase relationship; a wmatrix to
incorporate the hypothesized moderating effect of consumption nature of the non-leader
product on the bundle discount frame type-ease of justification relationship; and, the level
of complementarity between two products in the bundle as a covariate. Bootstrapping
40
was implemented in these analyses to obtain bias-corrected 95% confidence intervals for
making statistical inference about specific and total indirect effects (see Preacher &
Hayes, 2008).
The results of the moderated serial mediation analysis are presented in Table
7. First, the results indicated that the interaction effect of bundle discount frame type and
the consumption nature of the non-leader product on ease of justification was significant
(β = 0.84, CI: 0.26, 1.42). This interaction effect is visualized in Figure 2. Specifically,
when the non-leader product was hedonic in nature, a mixed-non-leader frame led to
significantly higher ratings for ease of justification than an integrated mixed-joint frame
(Effect: -1.12, CI: -1.53, -0.70). Conversely, when a non-leader product was utilitarian in
nature, the gap in ease of justification between a mixed-non-leader and an integrated
mixed-joint frame was not significant (Effect: -0.28, CI: -0.69, 0.13). Thus, H1 was
supported.
The index of moderated serial mediation for the conditional indirect effect of
bundle discount frame type on willingness to purchase through ease of justification and
perceived savings was significant (Index = 0.32, CI = 0.09 to 0.62). When the non-leader
product was hedonic in nature, the serial mediating effects of ease of justification and
perceived savings on the bundle discount frame type-willingness to purchase relationship
were significant (Effect: -0.43, CI = -0.72 to -0.19). A mixed-non-leader frame led to
significantly higher ratings for willingness to purchase through higher ratings for ease of
justification and perceived savings when a non-leader product was hedonic in nature.
However, these serial mediation effects did not hold when a non-leader product was
utilitarian in nature (Effect: -0.11, CI: -0.29, 0.05). In other words, the gap in willingness
41
to purchase between the mixed-non-leader and integrated mixed-joint frames was no
longer significant when the non-leader product was utilitarian in nature. Thus, H2 was
supported.
Table 7. Study 1: Result of Moderated Serial Mediation Analysis
Ease of justification Perceived savings Willingness to
purchase
Coefficient 95% CI Coefficient 95% CI Coefficie
nt 95% CI
Constant 2.24 1.60,2.89 -0.08 -0.85,0.70 0.24 -0.52,1.00
Bundle frame type1 -1.12 -1.53,-0.70 -0.51 -0.88,-0.14
Consumption Nature2 0.08 -0.34,0.49
Interaction3 0.84 0.26,1.42
Ease of justification 0.77 0.59,0.94
Perceived savings 0.50 0.38,0.62
Complementarity 0.55 0.43,0.66 0.06 -0.12,0.25 0.46 0.31,0.61
R 0.69 0.64 0.75
R2 0.48 0.41 0.56
F 39.79 61.73 72.89
df1 (df2) 4 (173) 2 (175) 3 (174)
P <0.0001 <0.0001 <0.0001
Conditional effects4:
Nature Effect 95% CI
Hedonic -1.12 -1.53,-0.70
Utilitarian -0.28 -0.69,0.13
Indirect effects5:
Nature
Effect
-0.06
0.13
95% CI
-0.16,0.03
0.02,0.29 Hedonic -0.43 -0.72,-0.19
Utilitarian -0.11 -0.29,0.05
Index of moderated mediation
Index
0.32
95% CI
0.09,0.62
1Referece group: Mixed-non-leader frame 2Referece group: Hedonic 3Interaction: Perceived savings x Consumption nature of the non-leader product 4Interaction effect of bundle discount frame types and consumption nature on ease of justification 5Bundle discount frame -> Ease of justification -> Perceived savings -> Willingness to purchase
42
Finally, the control variable, the level of complementarity between the two
products in the bundle, had a significant effect on ease of justification (β = 0.55, CI: 0.43,
0.66) and willingness to purchase (β = 0.46, CI: 0.31, 0.61), but had an insignificant on
perceived savings (β = 0.06, CI: -0.12, 0.25).
3.3.4 Discussion
Consumer reaction to bundle discount frames has been widely studied (e.g.,
Guiltinan, 1987; Janiszewski & Cunha, 2004; Yadav, 1994, 1995). However, the two
bundle discount frames of interest in this study– mixed-non-leader and integrated mixed-
joint – have never been directly compared in the literature. Given the fact that these two
bundle discount frames are the most applicable to traditional RM applications, it is
important that the potential differential effects of these frames on consumers’ purchase
intentions is understood. It is also important to understand how the consumption nature of
the non-leader products promoted within a given bundle influences consumers’ reactions
to bundle discount frames. As expected, Study 1’s results demonstrated that a mixed-non-
leader frame was generally perceived as superior to an integrated mixed-joint frame in
terms of ease of justification when the non-leader product was hedonic (vs. utilitarian) in
nature. In other words, participants were likely to justify their decision to purchase a
hedonic non-leader product more easily when they were presented in a mixed-non-leader
discount frame than in an integrated mixed-joint frame. Consequently, participants
perceived higher savings, and were more willing to purchase a hedonic non-leader
product when a mixed-non-leader discount frame was presented. However, when the
non-leader product was utilitarian in nature, participants were likely to perceive mixed-
43
non-leader and integrated mixed-joint frames as equally easy to justify. Consequently,
perceived savings and willingness to purchase did not vary significantly across the two
bundle discount frames.
3.4 Study 2
3.4.1 Procedures
In Study 2, the focus was solely on mixed-non-leader bundle discount frames.
Specifically, Study 2 examined the role of customization, and further explored the impact
of the consumption nature of the non-leader product in a bundle, on consumers’ reactions
to bundling in the context of a mixed-non-leader bundle discount frame. Participants
were randomly assigned to one of three conditions. In the first condition, Company-
Designed-Utilitarian, participants were exposed to a company-designed bundle that
consisted of an airline ticket and travel insurance. In the second condition, Company-
Designed-Hedonic, participants were exposed to a company-designed bundle that
consisted of an airline ticket and airline lounge access. Finally, in the Self-Designed
condition, participants were exposed to a consumer self-designed bundle (i.e., customized
bundle) that consisted of an airline ticket and a choice between travel insurance.
(utilitarian non-leader product) and airline lounge access (hedonic non-leader product).
Travel insurance, identified as a largely utilitarian product in the pre-tests, was used to
represent a utilitarian non-leader product in Study 2 to broaden the range of non-leader
products tested in this research. However, airline lounge access was retained as the
hedonic product as it emerged as the most appropriate hedonic non-leaser product form
44
Pre-test 2 in terms of both anticipated price and attractiveness. See the stimuli in
Appendix B. All participants were exposed to the same basic scenario as participants in
Study 1 (i.e., traveling to a city located in the U.S., with a price of $250 for a regular
economy seat). Participants were also informed that the airline provided additional
services at an extra charge. Participants then completed a questionnaire that contained
items used as manipulation checks, measures for the key variables of interest, a realism
check, and demographic questions.
3.4.2 Measures
The author used the same willingness to purchase (Maxwell, 2002; Cronbach’s
α=0.94) and ease of justification (Heitman et al., 2007; Cronbach’s α=0.88) scales as in
Study 1.
In the Company-Designed-Utilitarian, and the Company-Designed-Hedonic
conditions, participants rated willingness to purchase for the bundle that they were
exposed to in the same manner as in Study 1 (i.e., they rated the 3 willingness to book
items on 7-point scales anchored by strongly disagree and strongly agree). In the Self-
Designed condition, the goal was to tap into participants’ preferences between the
hedonic and utilitarian non-leader products presented to them. Thus, for each of the 3
willingness to book items, participants completed 7-point bipolar scales, with 7 indicating
a high preference for the utilitarian non-leader product and 1 indicating a high preference
for the hedonic non-leader product (See Table 8).
45
In the Company-Designed-Utilitarian, and Company-Designed-Hedonic
conditions, participants rated ease of justification for the bundle that they were exposed
to. In the Self-Designed condition, participants were asked to rate ease of justification for
both bundles on offer (airline ticket and airline lounge access, and airline ticket and travel
insurance). The order in which these scales (ease of justification for the bundle with the
hedonic non-leader product, and ease of justification for the bundle with the utilitarian
non-leader product) were presented to participants was randomized to control any
question order bias (Perreault, 1975).
In addition to these key variables, the author measured anticipated satisfaction
with the bundle purchase using a 4-item, 7-point bipolar scale anchored by not at all and
extremely (Botti & McGill, 2010; Cronbach’s α=0.93). Anticipated satisfaction was
measured to rule out the possibility that differences across the customized (Self-
Designed) and standardized (Company- Choice) conditions was simply a function of
differences in access to choice. See Table 8 for scale items.
To ensure that the manipulation for the consumption nature of the non-leader
product was successful, the single item, 7-point bipolar scale from Study 1 was used. In
addition, participants were asked to indicate how many options for the non-leader product
were presented to them to ensure that the Company-Designed versus Self-Designed
manipulation was successful. Finally, a single item measure from Study 1was used to
assess the realism of the scenarios presented to the study’s participants.
46
Table 8. Study 2: Scale Items
Willingness to purchase – Company-Designed conditions
(1 = strongly disagree; 7 = strongly agree)
The likelihood of me buying this airline ticket/checked baggage package (airline ticket/airline lounge
access package) is
My willingness to buying this airline ticket/checked baggage package (airline ticket/airline lounge
access package) is
The probability that I would consider buying this airline ticket/checked baggage package (airline
ticket/airline lounge access package) is
Willingness to Purchase – Self-Designed condition
(1 = Airline lounge access (high); 7 = Travel insurance (high))
The likelihood of me buying airline lounge access or travel insurance along with airline ticket is
My willingness to buy airline lounge access or travel insurance along with airline ticket is
The probability that I would consider buying airline lounge access or travel insurance along with airline
ticket is
Anticipated satisfaction
How much do you think you would like and enjoy this package?
How satisfied do you think you would be with this package?
How confident do you think you would like this package?
How good do you think you would feel about this package?
3.4.3 Results
3.4.3.1 Sample Characteristics
A total of 150 participants were recruited via a 3rd party data collection
company, and the 125 individuals who passed attention checks were retained for the
analysis, yielding an approximately equal number of participants in each experimental
condition (n=43 for the Company-Designed-Hedonic condition; n=40 for the Company-
Designed-Utilitarian condition; n=42 for the Self-Designed condition). In total, 42.4%
(n=53) of the participants were male. The average age of the participants was 38.75. The
majority of participants had a college degree or higher education (73.6%; n=92), and a
full-time job (60.8%, n=68), with 64.8% (n=81) having a household income higher than
47
$50,000. The majority of participants (53.6%; n=67) had taken a flight more than twice
for a trip in the 24 months prior to participating in the survey. See Table 9 for the full
characteristics of the sample.
3.4.3.2 Manipulation and Realism Checks
The ratings for the item measuring the consumption nature of the non-leader
product were significantly higher for the hedonic condition than the utilitarian condition
(Company-Designed: Mhedonic = 5.35, Mutilitarian = 2.82, p<0.001; Self-Designed: Mhedonic =
6.02, Mutilitarian = 2.05, p<0.001). Thus, the manipulation for the consumption nature of
the non-leader product was successful. In terms of the Company-Designed versus Self-
Designed manipulation, all participants in the Company-Designed condition correctly
indicated that one add-on option was provided, and all participants in the Self-Designed
condition correctly answered that more than one add-on option was provided. Therefore,
the Company-Designed versus Self-Designed manipulation was successful. All three
scenarios were perceived as realistic (Mcompany-designed-hedonic = 5.24, Mcompany-designed-utilitarian
= 5.29, Mself-designed = 5.71)
48
Table 9. Study 2: Sample Characteristics
a last 24 months
Variable N %
Gender
Male 53 42.4
Female 72 57.6
Age
34 or under 59 47.2
35 – 50
51 – 69
70 or older
36
25
5
28.8
20.0
4.0
Education
Some High school or less 0 0
High School 33 26.4
College 72 57.6
Graduate school 20 16.0
Employment
Full-time 76 60.8
Part-time 17 13.6
Not currently employed 12 9.6
Retired 10 8.0
Student 6 4.8
Other 4 3.2
Household income
Less than $25,000 14 11.2
$25,000 to $49,999 30 24.0
$50,000 to $74,999 37 29.6
$75,000 to $99,999 18 14.4
$100,000 to $124,999 8 6.4
$125,000 to $ 149,999 5 4.0
$150,000 or more 13 10.4
Frequency of taking a flight for tripsa
1-2 times 58 46.4
3-4 times 38 30.4
5-6 times 14 11.2
More than 6 times 15 12.0
49
3.4.3.3 Hypotheses Tests
Before conducting any hypotheses tests, a one-way ANOVA was employed to
test whether the customized and standardized conditions led to significant difference in
anticipated satisfaction ratings. There was no significant difference among three
conditions (Mcompany-designed&hedonic = 4.85, Mcompany-designed&utilitarian = 4.53, Mself-designed =
4.99, p>0.1. Therefore, the author could rule out the possibility that differences across the
customized and standardized conditions was simply a function of differences in access to
choice.
The cell means for ease of justification and willingness to purchase by
experimental condition are provided in Table 10. For the purpose of testing Hypotheses 3
and 4, the author separately analyzed the data in the Self-Designed and Company-
Designed conditions.
Self-Designed Condition
Ease of justification: Since each participant in the Self-Designed condition
rated ease of justification for both hedonic and utilitarian non-leader bundles, a one-way
repeated measures ANOVA was conducted to test H3a. The cell means for ease of
justification indicate that participants perceived the bundle with the utilitarian non-leader
product as easier to justify than the bundle with the hedonic non-leader product (Mhedonic
= 3.03, Mutilitarian = 5.29). The results of the repeated measures ANOVA revealed a
significant main effect of the consumption nature of the non-leader product on ease of
justification (F(1,41) = 49.09, p<0.0001). Thus, H3a was supported.
50
Willingness to purchase: Each participant in the Self-Designed condition rated
willingness to purchase on a bipolar scale (with 7 indicating a high preference for the
utilitarian non-leader product, and 1 indicating a high preference for the hedonic non-
leader product). As indicated in Table 10, the mean rating for willingness to purchase was
skewed towards the bundle with the utilitarian non-leader product (M = 5.48, standard
deviation = 1.5). In other words, participants indicated that they were more likely to
purchase a bundle with a utilitarian non-leader product than a bundle with a hedonic non-
leader product when provided both options to choose from. Thus, H4a was supported.
Company-Designed Conditions
A one-way MANOVA was employed to test H3b and H4b regarding the effect
of the consumption nature of the non-leader product on ease of justification and
willingness to purchase in the Company-Design conditions. MANOVA has the benefit of
controlling the experiment-wise error rate when some level of inter-correlation among
multiple dependent variables exists (Hair, Black, Babin, & Anderson, 2010).
The five assumptions underlying MANOVA were checked. First, there were
five outliers that exceeded the suggested Mahalanobis distance cutoff-point in the data
set, so those observations were excluded from further analysis. Second, a Box’s M test
was conducted to check homogeneity of covariance matrices assumption (p>0.1). Third,
in terms of the multi-collinearity assumption, the correlation between the two dependent
variables was 0.7. Box plot and scatter plots were used to test normality and linearity
51
assumption. The results of these assumption checks indicated that all assumptions were
satisfied.
As reported in Table 10, the cell means for ease of justification (Mhedonic =
4.62, Mutilitarian = 4.73) and willingness to purchase (Mhedonic = 3.90, Mutilitarian = 4.14)
provide initial support for H3b and H4b. A one-way MANOVA, with the consumption
nature of the non-leader product as an independent variable, was conducted on ease of
justification and willingness to purchase, along with follow-up univariate analyses. The
multivariate test results indicated an insignificant impact of the consumption nature of the
non-leader product on the multivariate dependent measure (F(2,80) = 0.28, p > 0.5). The
follow-up univariate test results indicated an insignificant impact of the consumption
nature of the non-leader product on both ease of justification (F(1,81) = 0.30, p > 0.5) and
willingness to purchase (F(1,81) = 0.56, p > 0.4) (See Table 11). Therefore, H3b and H4b
were supported. Figures 5 and 6 visualize the study’s findings in relation to H3a and H3b,
and H4a and H4b.
Table 10. Study 2: Means for Ease of Justification and Willingness to Purchase by
Experimental Condition
Frame Consumption
Nature
Means
Ease of
justification
Willingness to
purchase
Self-Designed Hedonic 3.03
5.481 Utilitarian 5.29
Company-
Designed
Hedonic 4.62 3.90
Utilitarian 4.73 4.14 1 7-point bipolar scale – 1: High willingness to purchase a hedonic non-leader product to
7: High willingness to purchase a utilitarian non-leader product
52
Table 11. Study 2: MANOVA and univariate follow-up results
Source Pillai’s
trace
(p-value)
Univariate follow-ups
Dependent variable Type
III SS
DF MS F p-value
Intercept 938.8
(p<0.001)
Ease of Justification 1807 1 1807 1839 p<0.001
Willingness to Purchase 1334 1 1334 632.9 P<0.001
Consumption
Nature1
0.28
(p>0.5)
Ease of Justification 0.29 1 0.29 0.30 p>0.5
Willingness to Purchase 1.18 1 1.18 0.56 p>0.4
Error - Ease of Justification 79.58 81 0.98
Willingness to Purchase 170.7 81 2.11
Total - Ease of Justification 1896 83
Willingness to Purchase 1516 83
Corrected
total
- Ease of Justification 79.88 82
Willingness to Purchase 171.9 82 1Referece group: Hedonic
Figure 5. Study 2: Mean Ratings for Ease of Justification
53
Figure 6. Study 2: Mean Ratings for Willingness to Purchase
3.4.4 Discussion
The positive effects of customization on consumers’ reactions including
perceived quality, satisfaction, and purchase intention have been widely demonstrated in
the literature (e.g., Coelho & Henseler, 2012; Coulter & Coulter, 2002; Franke et al.,
2009). However, the results from Study 2 suggest that this may not always be the case. In
this study, the self-designed bundle represented a customized bundle, while the company-
designed bundles represented standardized bundles. The results indicate that, when
participants were offered a self-designed bundle, which represents a situation where
consumers have to evaluate multiple non-leader products (i.e., a joint evaluation mode),
they were better able to justify the utilitarian non-leader product bundle than the hedonic
54
non-leader product bundle. Consequently, they were more likely to choose the utilitarian
non-leader product bundle. In contrast, when participants were offered a company-
designed bundle, which represents a situation where consumers have to evaluate only one
non-leader product (i.e., a separate evaluation mode), there was no significant difference
ease of justification or willingness to purchase across the utilitarian, and hedonic, non-
leader product bundles. In sum, these findings suggest that a customized bundle will be
more effective when promoting a utilitarian non-leader product. However, a standardized
company-designed bundle is more likely to encourage bundle purchase when promoting a
hedonic non-leader product.
55
CHAPTER 4. GENERAL DISCUSSION
Bundling is widely used by service providers as a strategy to cross-sell
products, and to encourage consumers who are already willing to purchase a focal
product to purchase additional products (Derdenger & Kumar, 2013; Janiszewski &
Cunha, 2004; Krüger et al., 2014; Mittelman, Andrade, Chattopadhyay, & Brendl, 2014;
Ng et al., 1999). In the context of TRM, therefore, bundling has the potential to play a
significant role in maximizing revenue across all of a firm’s revenue streams.
The overall goal of this research was to explore effective bundling strategies
for TRM. Prior research in the domain of bundling has examined consumers’ reactions to
different types of bundle discount frames (e.g., mixed-leader vs. mixed-non-leader,
mixed-leader vs. segregate mixed-joint vs. integrated mixed-joint). However, it provides
limited insight into the efficacy of the bundle discount frames that are relevant in a
traditional RM setting: mixed-non-leader, and integrated-mixed-joint, frames. Further,
the literature does not address the potential role that the consumption nature of the non-
leader product in the bundle plays in consumers’ reactions to bundle discount frames.
Similarly, it does not address the potential impact of the consumption nature of the non-
leader product in the bundle on consumer response to customized (vs. standardized)
bundling. Thus, this research sought to address these gaps in the literature, and provide
revenue managers with insights to guide their TRM efforts.
56
4.1 Theoretical Implications
This research extends the literature in a number of ways. First, it examined the
role of different bundle discount frames in driving consumers’ purchase intentions. The
two bundle discount frames of interest in this research – mixed-non-leader and integrated
mixed-joint – are pertinent to bundling for TRM but have not previously been directly
compared in the literature. Second, this research probed the impact of bundle discount
frames on ease of justification, and the role of the consumption nature of the non-leader
product within a bundle in the discount frames–ease of consumption justification
relationship. A key difference between the two bundle discount frames studied in this
research is the amount of discount information provided to the consumer. The relatively
more transparent discount information associated with the mixed-non-leader frame
allows consumers to justify the purchase of a given bundle more easily than an integrated
mixed-joint frame. The more transparent information provided by the mixed-non-leader
frame is a heuristic cue for persuasive and credible information (Chaiken et al., 1989).
This transparency is key when the non-leader product is hedonic in nature. Consumers
seek reasons to justify their purchase decisions (Shafir, Simonson, & Tversky, 1993).
When a purchase decision is difficult to justify, consumers have to actively seek
additional reasons to justify their decisions. However, when a purchase decision is
relatively easy to justify, consumers are less involved in additional justification processes
(Shafir et al., 1993). Given that hedonic consumption is more difficult to justify than
utilitarian consumption (Hsee, 1996; Okada, 2005), consumers are more sensitive to
additional reasons such as price discount information with hedonic (vs. utilitarian)
consumption to help them to justify their purchase. Thus, extending the work of Khan
57
and Dhar (2010), this research suggests in the context of tie-in bundling, that a mixed-
non-leader bundle discount frame, by virtue of information transparency, will drive
higher ease of justification ratings when the non-leader product is hedonic in nature.
Third, this research advances the literature by demonstrating the mediating
roles of ease of justification and perceived savings on the relationship between bundle
discount frames and purchase intentions when the non-leader product in a given bundle is
hedonic in nature. As previously mentioned, a mixed-non-leader bundle discount frame is
likely to be easier to justify than an integrated mixed-joint frame with hedonic non-leader
products. Once consumers form their first impression of a product based on its
justifiability, this first impression influences subsequent evaluations of the perceived
savings associated with that product. Prior research has widely examined confirmation
bias, a type of cognitive bias in the information processing (e.g., Campbell & Warren,
2014; Chernev, 2001; Klayman, 1995; Nakayama & Sutcliffe, 2005; Nickerson, 1998;
Yin et al., 2016). Once consumers form an impression of a product, they tend to process
other aspects of the product in a way that supports this first impression. They seek, and
overweight, supporting evidence. The notion of confirmation bias was supported by the
findings of this research, with a positive relationship between ease of justification and
perceived savings observed when the non-leader product was hedonic in nature. Thus,
this research supported an indirect effect of bundle discount frame on willingness to
purchase through ease of justification and perceived savings when the non-leader product
was hedonic nature. This research also suggests that, when the non-leader product is
utilitarian in nature, the two bundle discount frames under examination do not have a
significantly different impact on ease of justification. In the absence of the need for
58
additional reasons to justify the purchase of a bundle a utilitarian non-leader product, the
bundle discount frame did not produce a differential effect on ease of justification, and
consequently, perceived saving and willingness to purchase did not vary significantly
across the two bundle discount frames.
Fourth, this research extends the literature in terms of consumers’ response to
bundle customization. Prior research suggests that customized bundling may be preferred
over standardized bundling (e.g., Bateson, 1985; Coulter & Coulter, 2002; Coelho &
Henseler, 2012). However, the findings of Study 2 suggest that this may not necessarily
be the case. Rather, the findings support the idea that, by virtue of differences in
evaluation modes across self-designed and company-designed bundles, coupled with the
consumption nature of the non-leader product within a given bundle, self-designed
bundling may work best when the non-leader product is utilitarian in nature. With self-
designed bundling, consumers have to evaluate multiple non-leader products (i.e., joint
evaluation mode). In this context, consumers’ evaluations of a product are influenced by
the other products in the comparison set. Thus, due to the contrast effect (Thornton &
Maurice, 1997; Thornton & Moore, 1993), the purchase of a bundle with a utilitarian
non-leader product will be easier to justify than the purchase of a bundle with a hedonic
non-leader product. In contrast, with company-designed bundling, consumers have to
evaluate only one single non-leader product (i.e., separate evaluation mode). They do not
have information about the other products so they construct justifications for the
decisions that they are motivated to make (Kunda, 1990). Thus, when the non-leader
product within a bundle is hedonic in nature, the findings of this research suggest that
59
company-designed bundle will drive higher ratings for ease of justification and
willingness to purchase than a self-designed bundle.
4.2 Managerial Implications
This research provides a number of insights for RM practitioners regarding the
deployment of bundling strategies for TRM. The first step in the development of
bundling strategies is to make a decision regarding what ancillary products to promote.
Several factors may drive this decision. For example, a firm may choose to focus on
ancillary products that yield a high contribution margin, such that flow through to the
bottom line is maximized. Alternatively, the goal may be to push sales for new ancillary
products, or drive demand for revenue-generating assets that are being under-utilized
(e.g., hotel food and beverage facilities). Once, the decision has been made regarding
what to promote, the findings of this research suggest that management should next
classify those ancillary products targeted for promotion in bundles by consumption
nature. Products tend to be comprised of both utilitarian and hedonic components, so the
focus here should be on classifying ancillary products based on the relative strength of
their consumption nature. For example, access to an airline lounge can be considered
relatively more hedonic than utilitarian in nature, while a grab and go breakfast at a hotel
can be considered primarily utilitarian in nature.
Once products have been classified by consumption nature, the next decision
is how to present the discount on the bundle. The findings of this research suggest that
the choice of bundle discount frame (mixed-non-leader vs. integrated mixed-joint) should
60
be guided by the consumption nature of the ancillary product. Specifically, a mixed-non-
leader frame (vs. an integrated mixed-joint frame) may yield a greater volume of
purchase activity when the consumption nature of the ancillary product is largely
hedonic. In this instance, consumers will likely perceive that, by virtue of greater
information transparency, the discount in the mixed-non-leader frame is easier to justify,
and by extension will yield higher perceptions of savings on the bundle. In contrast, the
choice of bundle discount frame may be less critical when the consumption nature of the
ancillary product is largely utilitarian. In this context, consumers are not seeking
additional reasons to justify their purchase, thus information regarding which product in
the bundle is discounted becomes less important. Consumers are likely to perceive both
bundle discount frames (mixed-non-leader and integrated mixed-joint) as equivalent in
terms of ease of justification, yielding little differences in perceived savings and
willingness to purchase across the two types of frames.
In terms of the choice regarding pursuit of customized (vs. standardized)
bundling, again practitioners should be guided by the consumption nature of the ancillary
product. The findings of this research suggest that self-designed bundling is more
effective when promoting utilitarian, rather than hedonic, ancillary products. When
presented with a choice between a utilitarian and a hedonic ancillary product, the
purchase of a utilitarian product is easier to justify. In contrast, research findings indicate
that company-designed bundles will work equally effectively for the promotion of
utilitarian and hedonic ancillary products.
61
4.3 Limitations and Future Research Directions
As with any single piece of research, the findings of this research should be
interpreted with caution for several reasons. First, the author employed a controlled
experimental design for both Study 1 and Study 2. This approach allowed the author to
test precise predictions derived from theory while holding all else constant (Calder,
Phillips, & Tybout, 1981). To simulate reality as accurately as possible, stimuli were
presented to participants in a manner that mimicked the user experience of an individual
airline webpage, with participants’ scores on the realism check suggesting that the
scenarios were perceived as realistic. However, a limitation of experimental design is that
it often lacks external validity, limiting generalizability across populations and settings.
Additional research employing a field study that examines actual choice behavior is also
needed to complement the findings of this research. Further, by their nature, controlled
experimental conditions limit the amount of information that the participant can use to
evaluate a given scenario. Consequently, high correlation may be observed among related
constructs of interest. I observed a relatively high correlation between two variables -
ease of justification and willingness to purchase - in Study 1. Therefore, the serial
mediating effects observed in Study 1 should be interpreted with caution. Further
research is merited to probe these relationships.
This research was conducted in an airline context, with three airline-related
non-leader products represented: airline lounge access (hedonic non-leader product), and
checked-baggage and travel insurance (utilitarian non-leader products). Future research
utilizing different contexts and related non-leader products (e.g., hotels, with hotel stay-
related non-leader products) is needed to assess the robustness of the findings across
62
different RM contexts. On a related note, this research focused on bundles that either
included one leader product and one non-leader product (Study 1 and Company-Designed
in Study 2), or one leader product and a choice between two non-leader products (Self-
Designed in Study 2). In reality, a service firm may bundle more than two products.
Thus, further research is required to assess how consumers evaluate multiple hedonic and
utilitarian non-leader options simultaneously. Prior research has demonstrated that too
many options can create choice overload, and negatively affect consumers’ responses
(Chernev, Bockenholt, & Goodman, 2015; Iyengar & Lepper, 2000; Scheibehenne,
Greifeneder, & Todd, 2010). Thus, examination of how consumers simultaneously assess
multiple hedonic and utilitarian non-leader options should incorporate consideration of
choice set size.
The prices associated with the non-leader products in both studies were relatively
low in comparison to the price of the focal product (e.g., $35 for airline lounge access
versus $250 for an airline ticket). Research is merited to investigate whether the study’s
findings would hold when price differences between leader and non-leader products is
less significant (e.g., hotel room rate and a spa treatment). Examination of the impact of
prices differences across bundles (by virtue of the price differences associated with
different ancillary products) on consumer response to bundle discount frames is also
warranted. On a related note, participants in this research were presented with ancillary
products which were comparable in terms of attractiveness. It would be interesting to
probe the potential role of variability in the perceived attractiveness of non-leader
products on consumer response to bundle discount frames and customized bundles. In
this research, the focus was on the moderating effect of the consumption nature of non-
63
leader items on consumer reactions to bundle discount frames and degree of
customization. Future research should encompass other potential moderators. For
example, familiarity with the non-leader product may affect the ease with which the
consumer justifies different bundle discount frames and customized bundle offerings
(Raju, 1977). Product familiarity is directly related with evaluation process. Consumers
who are familiar with the product, they can evaluate the product more easily, and this will
positively affect the confidence in the evaluation process (Raju, 1977). Therefore, it is
highly likely that familiarity affects ease of justification. This is particularly important
when promoting a new non-leader product because a new item is typically less familiar to
consumers compared to existing products.
64
REFERENCES
Adams, W. J., & Yellen, J. L. (1976). Commodity bundling and the burden of monopoly.
Quarterly Journal of Economics, 90(3), 475-498.
Anderson, E. W., Fornell, C., & Rust, R. T. (1997). Customer satisfaction, productivity,
and profitability: Differences between goods and services. Marketing
science, 16(2), 129-145.
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic
and utilitarian shopping value. Journal of consumer research, 20(4), 644-656.
Bateson, J. E. (1985). Perceived control and the service encounter. The service
encounter: Managing employee/customer interaction in service businesses, 67-82.
Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources of
consumer attitudes. Marketing letters, 2(2), 159-170.
Bettman, J. R., Luce, M. F., & Payne, J. W. (1998). Constructive consumer choice
processes. Journal of consumer research, 25(3), 187-217.
Bloch, P. H. (1995). Seeking the ideal form: Product design and consumer response. The
Journal of Marketing, 16-29.
Botti, S., & McGill, A. L. (2010). The locus of choice: Personal causality and satisfaction
with hedonic and utilitarian decisions. Journal of Consumer Research, 37(6), 1065-
1078.
65
Campbell, M. C., & Warren, C. (2014). The progress bias in goal pursuit: When one step
forward seems larger than one step back. Journal of consumer research, 41(5),
1316-1331.
Chernev, A. (2001). The impact of common features on consumer preferences: A case of
confirmatory reasoning. Journal of Consumer Research, 27(4), 475-488.
Chernev, A., Böckenholt, U., & Goodman, J. (2015). Choice overload: A conceptual
review and meta-analysis. Journal of Consumer Psychology, 25(2), 333-358.
Chaiken, S., Liberman, A., & Eagly, A. H. (1989). Heuristic and Systematic Information
Processing within and beyond the Persuasion Context. In J. S. Uleman, & J. A.
Bargh (Eds.), Unintended Thought (pp. 212-252). New York: Guilford.
Chan, K. W., Yim, C. K., & Lam, S. S. (2010). Is customer participation in value creation
a double-edged sword? Evidence from professional financial services across
cultures. Journal of marketing, 74(3), 48-64.
Chen, A., Peng, N., & Hung, K. P. (2015). Strategic management of salespeople when
promoting new products: Moderating effects of sales-related organizational
psychological climate. European Journal of Marketing, 49(9/10), 1616-1644.
Coulter, K. S., & Coulter, R. A. (2002). Determinants of trust in a service provider: the
moderating role of length of relationship. Journal of services marketing, 16(1), 35-
50.
Coelho, P. S., & Henseler, J. (2012). Creating customer loyalty through service
customization. European Journal of Marketing, 46(3/4), 331-356.
66
Crilly, N., Moultrie, J., & Clarkson, P. J. (2004). Seeing things: consumer response to the
visual domain in product design. Design studies, 25(6), 547-577.
Dabholkar, P. A. (2015). How to improve perceived service quality by increasing
customer participation. In Proceedings of the 1990 academy of marketing science
(AMS) annual conference (pp. 483-487). Springer, Cham.
Derdenger, T., & Kumar, V. (2013). The dynamic effects of bundling as a product
strategy. Marketing Science, 32(6), 827-859.
Doherty, M. E., & Mynatt, C. R. (1986). The magical number one. In D. Moates & R.
Butrick (Eds.), Inference Ohio University Interdisciplinary Conference 86 (pp.
221-230).
Drolet, A., Williams, P., & Lau-Gesk, L. (2007). Age-related differences in responses to
affective vs. rational ads for hedonic vs. utilitarian products. Marketing
letters, 18(4), 211-221.
Franke, N., Keinz, P., & Steger, C. J. (2009). Testing the value of customization: when
do customers really prefer products tailored to their preferences?. Journal of
Marketing, 73(5), 103-121.
Gilbride, T. J., Guiltinan, J. P., & Urbany, J. E. (2008). Framing effects in mixed price
bundling. Marketing Letters, 19(2), 125-139.
González, E. M., Esteva, E., Roggeveen, A. L., & Grewal, D. (2016). Amount off versus
percentage off—when does it matter?. Journal of Business Research, 69(3), 1022-
1027.
67
Grewal, D., Hardesty, D. M., & Iyer, G. R. (2004). The effects of buyer identification and
purchase timing on consumers’ perceptions of trust, price fairness, and repurchase
intentions. Journal of Interactive Marketing, 18(4), 87-98.
Guiltinan, J. P. (1987). The price bundling of services: A normative framework. Journal
of Marketing, 51(2), 74-85.
Gupta, S., & Cooper, L. G. (1992). The discounting of discounts and promotion
thresholds. Journal of consumer research, 19(3), 401-411.
Hair, J. F. (2010). Black, WC, Babin, BJ, & Anderson, RE (2010). Multivariate data
analysis, 7. Prentice Hall, Englewood Cliffs, NJ
Hayes, A. F. 2017. Introduction to mediation, moderation, and conditional process
analysis: A regression-based approach. New York, NY: Guilford Publications.
Heitmann, M., Lehmann, D. R., & Herrmann, A. (2007). Choice goal attainment and
decision and consumption satisfaction. Journal of marketing research, 44(2), 234-
250.
Heo, C. Y., & Lee, S. (2009). Application of revenue management practices to the theme
park industry. International Journal of Hospitality Management, 28(3), 446-453.
Hsee, C. K. (1996). Elastic justification: How unjustifiable factors influence
judgments. Organizational Behavior and Human Decision Processes, 66(1), 122-
129.
68
Hitt, L. M., & Chen, P. Y. (2005). Bundling with customer self-selection: A simple
approach to bundling low-marginal-cost goods. Management Science, 51(10),
1481-1493.
Hsee, C. K., & Zhang, J. (2010). General evaluability theory. Perspectives on
Psychological Science, 5(4), 343-355.
Hui, M. K., & Bateson, J. E. (1991). Perceived control and the effects of crowding and
consumer choice on the service experience. Journal of consumer research, 18(2),
174-184.
Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too
much of a good thing?. Journal of personality and social psychology, 79(6), 995.
Janiszewski, C., & Cunha, M. (2004). The influence of price discount framing on the
evaluation of a product bundle. Journal of Consumer Research, 30(4), 534-546.
Khan, U., & Dhar, R. (2010). Price-framing effects on the purchase of hedonic and
utilitarian bundles. Journal of Marketing Research, 47(6), 1090-1099.
Kimes, S. E. (2003). Revenue management: A retrospective. Cornell Hospitality
Quarterly, 44(5/6), 131.
Kimes, S. E. (2016). The evolution of hotel revenue management. Journal of Revenue
and Pricing Management, 15(3-4), 247-251.
Kimes, S. E., & Beard, J. (2013). The future of restaurant revenue management. Journal
of Revenue and Pricing Management, 12(5), 464-469
69
Kimes, S. E., & Chase, R.B.(1998) The strategic levers of yield management, Journal of
Service Research, 1 (2), 156-166.
Kimes, S. E., & Renaghan, L. M. (2011). The role of space in revenue management.
Revenue Management Theories and Issues, Practical Pricing Perspective.
Houndmills: Macmillan Publishers Limited, 17-28
Kimes, S. E., & Singh, S. (2009). Spa revenue management. Cornell Hospitality
Quarterly, 50(1), 82-95
Kimes, S. E., & Thompson, G. M. (2004). Restaurant revenue management at Chevys:
Determining the best table mix. Decision Sciences, 35(3), 371-392.
Kimes, S. E., & Wirtz, J. (2015). Revenue management: Advanced strategies and tools to
enhance firm profitability. Foundations and Trends in Marketing, 8(1), 1-68
Kivetz, R., & Simonson, I. (2002). Earning the right to indulge: Effort as a determinant of
customer preferences toward frequency program rewards. Journal of Marketing
Research, 39(2), 155-170.
Klayman, J. (1995). Varieties of confirmation bias. In Psychology of learning and
motivation (Vol. 32, pp. 385-418). Academic Press.
Krüger, T., Mata, A., & Ihmels, M. (2014). The Presenter's Paradox Revisited: An
Evaluation Mode Account. Journal of Consumer Research, 41(4), 1127-1136.
Kunda, Z. (1990). The case for motivated reasoning. Psychological bulletin, 108(3), 480.
70
Li, D., & Pang, Z. (2017). Dynamic booking control for car rental revenue management:
A decomposition approach. European Journal of Operational Research, 256(3),
850-867.
Lim, E. A. C., & Ang, S. H. (2008). Hedonic vs. utilitarian consumption: A cross-cultural
perspective based on cultural conditioning. Journal of business research, 61(3),
225-232.
Lynch Jr, J. G., & Ariely, D. (2000). Wine online: Search costs affect competition on
price, quality, and distribution. Marketing science, 19(1), 83-103.
March, J. G. (1978). Bounded rationality, ambiguity, and the engineering of choice. The
Bell Journal of Economics, 587-608.
Maxwell, S. (2002). Rule-based price fairness and its effect on willingness to
purchase. Journal of economic psychology, 23(2), 191-212.
Miao, L., & Mattila, A. S. (2007). How and how much to reveal? The effects of price
transparency on consumers' price perceptions. Journal of Hospitality & Tourism
Research, 31(4), 530-545.
Mittelman, M., Andrade, E. B., Chattopadhyay, A., & Brendl, C. M. (2014). The offer
framing effect: choosing single versus bundled offerings affects variety
seeking. Journal of Consumer Research, 41(4), 953-964.
Nakayama, M., & Sutcliffe, N. G. (2005). Exploratory analysis on the halo effect of
strategic goals on IOS effectiveness evaluation. Information &
Management, 42(2), 275-288.
71
Ng, I. C., Wirtz, J., & Sheang Lee, K. (1999). The strategic role of unused service
capacity. International Journal of Service Industry Management, 10(2), 211-244.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many
guises. Review of general psychology, 2(2), 175-220.
Noone, B. M. (2008). Customer perceived control and the moderating effect of restaurant
type on evaluations of restaurant employee performance. International Journal of
Hospitality Management, 27, 23-29
Noone, B. M., & Mattila, A. S. (2009). Hotel revenue management and the Internet: The
effect of price presentation strategies on customers’ willingness to
book. International Journal of Hospitality Management, 28(2), 272-279.
Noone, B. M., Wirtz, J., & Kimes, S. E. (2010). The effect of perceived control on
consumer responses to service encounter pace: A revenue management
perspective. Cornell Hospitality Quarterly, 53(4), 295-307
Okada, E. M. (2005). Justification effects on consumer choice of hedonic and utilitarian
goods. Journal of marketing research, 42(1), 43-53.
Palamar, J., & Edwards, V. (2007). Dynamic pricing: Friend or foe. USA: BTE Tourism
Training and Consulting, Buckhiester Management, 1-14.
Perreault, W. D. (1975). Controlling order-effect bias. The Public Opinion
Quarterly, 39(4), 544-551.
72
Preacher, K. J., Hayes, A. F. 2008. Asymptotic and resampling strategies for assessing
and comparing indirect effects in multiple mediator models. Behavior Research
Methods, 40(3), 879-891.
Raju, P. S. (1977). Product familiarity, brand name, and price influences on product
evaluation. ACR North American Advances.
Rohlfs, K. V., & Kimes, S. E. (2007). Customers' perceptions of best available hotel
rates. Cornell Hotel and Restaurant Administration Quarterly, 48(2), 151-162.
Rose, P. (2016). A lifetime in airline revenue management. Journal of Revenue and
Pricing Management, 15, 197-202
Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). Can there ever be too many
options? A meta-analytic review of choice overload. Journal of Consumer
Research, 37(3), 409-425.
Schmalensee, R. (1984). Gaussian demand and commodity bundling. Journal of business,
S211-S230.
Shafir, E., Simonson, I., & Tversky, A. (1993). Reason-based choice. Cognition, 49(1),
11-36.
Sheng, S., Parker, A. M., & Nakamoto, K. (2007). The effects of price discount and
product complementarity on consumer evaluations of bundle components. Journal
of Marketing Theory and Practice, 15(1), 53-64.
Simon, H. A. (1955). A behavioral model of rational choice. The quarterly journal of
economics, 69(1), 99-118.
73
Song, M., & Noone, B. M. (2017). The moderating effect of perceived spatial crowding
on the relationship between perceived service encounter pace and customer
satisfaction. International Journal of Hospitality Management, 65, 37-46.
Strahilevitz, M., & Myers, J. G. (1998). Donations to charity as purchase incentives: How
well they work may depend on what you are trying to sell. Journal of consumer
research, 24(4), 434-446.
Tanford, S., Baloglu, S., & Erdem, M. (2012). Travel packaging on the Internet: The
impact of pricing information and perceived value on consumer choice. Journal of
Travel Research, 51(1), 68-80.
Thaler, R. (1985). Mental accounting and consumer choice. Marketing science, 4(3), 199-
214.
Thornton, B., & Maurice, J. (1997). Physique contrast effect: Adverse impact of idealized
body images for women. Sex Roles, 37(5-6), 433-439.
Thornton, B., & Moore, S. (1993). Physical attractiveness contrast effect: Implications
for self-esteem and evaluations of the social self. Personality and Social
Psychology Bulletin, 19(4), 474-480.
Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-
dependent model. The quarterly journal of economics, 106(4), 1039-1061.
Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the hedonic and
utilitarian dimensions of consumer attitude. Journal of marketing research, 40(3),
310-320.
74
Wirtz, J., & Kimes, S. E. (2007). The moderating role of familiarity in fairness
perceptions of revenue management pricing. Journal of Service Research, 9(3),
229-240.
Yadav, M. S. (1994). How buyers evaluate product bundles: A model of anchoring and
adjustment. Journal of Consumer Research, 21(2), 342-353.
Yadav, M. S. (1995). Bundle evaluation in different market segments: The effects of
discount framing and buyers' preference heterogeneity. Journal of the Academy of
Marketing Science, 23(3), 206-215.
Yin, D., Mitra, S., & Zhang, H. (2016). Research note—When do consumers value
positive vs. negative reviews? An empirical investigation of confirmation bias in
online word of mouth. Information Systems Research, 27(1), 131-144.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end
model and synthesis of evidence. The Journal of marketing, 2-22.
Zhu, K. (2002). Information transparency in electronic marketplaces: Why data
transparency may hinder the adoption of B2B exchanges. Electronic
markets, 12(2), 92-99.
75
APPENDIX A-1. Study 1 Stimulus: Mixed-Non-Leader Frame & Hedonic Non-
Leader Product Condition
76
APPENDIX A-2. Study 1 Stimulus: Mixed-Non-Leader Frame & Utilitarian Non-
Leader Product Condition
77
APPENDIX A-3. Study 1 Stimulus: Integrated Mixed-Joint Frame & Hedonic Non-
Leader Product Condition
78
APPENDIX A-4. Study 1 Stimulus: Integrated Mixed-Joint Frame & Utilitarian
Non-Leader Product Condition
79
APPENDIX B-1. Study 2 Stimulus: Company-Designed & Hedonic Non-Leader
Product Condition
80
APPENDIX B-2. Study 2 Stimulus: Company-Designed & Utilitarian Non-Leader
Product Condition
81
APPENDIX B-3. Study 2 Stimulus: Self-Designed Condition
VITA
MyungKeun Song
EDUCATION
2018 The Pennsylvania State University, School of Hospitality Management
Ph.D. in Hospitality Management
2013 Cornell University, School of Hotel Administration
Master of Management in Hospitality
2013 University of Nevada, Las Vegas, College of Hotel Administration
B.S. Hospitality Management
HONORS AND AWARDS
Small Project Grant, The Pennsylvania State University, 2016
Dean’s Honor List, University of Nevada, Las Vegas, 2004, 2005
Best Performance in Speech Contest, Minister of Culture and Tourism Award, 2000
REFEREED JOURNAL ARTICLES
Song, M., & Noone, B. M. (2017). The moderating effect of perceived spatial crowding
on the relationship between perceived service encounter pace and customer satisfaction.
International Journal of Hospitality Management. 65, 37-46
Song, M., Noone, B. M., & Mattila, A. S. (In press). A tale of two cultures: Consumer
reactance and willingness to book fenced rates. Journal of Travel Research.
Song, M., Noone, B. M., & Han. J. R. An examination of the role of booking lead time in
consumers’ reactions to online scarcity messages (Under review in International Journal
of Hospitality Management).
