PERSONALITY TYPES AND CONSUMER PREFERENCES FOR MULTIPLE
CURRENCY USAGES: A STUDY OF THE RESTAURANT INDUSTRY
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of
Philosophy in the Graduate School of the Ohio State University
By
Hsin-Hui Hu, B.B.A., M.S.
****
The Ohio State University
2005
Dissertation Committee: Approved By:
H.G. Parsa, Ph. D.
R. Thomas George, Ed. D. Adviser
Kenneth R. Lord, Ph. D. College of Human Ecology
ii
ABSTRACT
The immense popularity of marketing promotions and loyalty programs has
resulted in the introduction of several new exchange media other than money. Therefore,
consumers are increasingly able to pay for goods and services in a combination of
currencies, not just in dollars. The current study examined the effects of personality
traits – need for cognition and self-monitoring – on consumers’ preferences of currency
usage in restaurant industry, and explored whether differences in restaurant segments
were related to consumers’ currency preferences. It also presented and tested the
conceptual model developed for this study.
An experimental design was applied to test seven hypotheses that reflected the
research question, whether individual differences and restaurant segments would
influence consumers’ preference of the currency usage. Total of 471 participants were
included in the study. Descriptive statistics and multinomial logistic regression was
performed with SPSS and STATA to analyze the data.
Results of the study indicated that the effects of self-monitoring and dining
companions are significantly related to consumers’ currency preferences while restaurant
segment and need for cognition have no significant impact on consumers’ currency
preferences. It showed that high self-monitors are less likely to prefer the currency of
points compared to dollars than low self-monitors. Moreover, consumers who dine alone
iii
are more likely to prefer to pay with points-only as opposed to dollars-only than
consumers who dine with the boss. Additionally, high self-monitors dining alone were
more likely to prefer to pay with combined-currency (dollars and points) or points-only
than low self-monitors. On the other hand, high-self monitors dining with a boss were
more likely to prefer to pay with dollars-only than to pay with dollars and points or
points-only.
The study identified the characteristics of consumers using the different currency
options in foodservice industry. By understanding the individual personality differences
of customers when using different currencies, restaurants could decide whether or not to
implement different currency prices based on their target markets.
iv
Dedicated to my loving family
v
ACKNOWLEDGEMENTS
This dissertation would not have been possible without the personal and
professional support of numerous people. I would like to express my gratitude to the
following people for their love, support, and patience over the last few years.
I would especially like to express my gratitude towards my advisor, Dr. H.G. Parsa,
for inspiring and encouraging me to pursue my doctoral degree. Not only was he readily
available for me, but Dr. Parsa was also to play a critical role in helping me survive the
doctoral program by providing whatever support he could. Throughout my doctoral work
he encouraged me to develop independent thinking and research skills. He continually
stimulated my analytical thinking and greatly assisted me with scientific writing. Dr.
Parsa is not only an advisor but also a friend and family to me. He has certainly become a
model for the type of researcher, teacher, and adviser I would like to become some day.
To the members of my committee, I am deeply grateful to Dr. R. Thomas George
for his support, guidance, and suggestions throughout my doctoral work. Dr. George
always read and responded to the drafts of each chapter of my work more quickly than I
could have hoped. His oral and written comments are always extremely perceptive,
helpful, and appropriate. I also extend my sincerest thanks to Dr. Kenneth Lord for his
generous time and commitment. Dr. Lord was always available to provide feedback on
this project and made valuable contributions. I admire his enthusiasm for research and
sincerely appreciate the considerable amount of time he spent helping with this study.
vi
I would like to express my thanks and appreciations to many other professors: Dr.
Wayne Johnson, Dr. Jay Kandampully, Dr. Timothy C. Brock, Dr. Neal F. Johnson, and
Dr. Xiaodong Liu in The Ohio State University; Dr. Jinlin Zhao and Professor Cheryl M.
Carter of Florida International University for their guidance, support and encouragement.
I also wish to thank Dr. Mohammed A. Rahman for his suggestions and support in
statistical techniques and research methods throughout my doctoral work. Special thanks
go to the chair, Dr. Hong, faculty and staff of the Department of Consumer Sciences for
their assistances and support during my doctoral work.
My graduate studies would not have been the same without the emotional and
social support from my friends and family. I am particularly thankful to my friends:
David Njite, Emma Lo, Ming-Tsung Huang, Jim Jao, Wei-Ching Lee, Shu-Fang Lin,
Howard Hsieh, Shin-I Liou, and Yi-Fang Lee. We not only studied, relaxed, and traveled
well together, but they were even willing to read some portions of this dissertation and
thus provided some very useful input. Their knowledge of computers was also extremely
helpful.
Most importantly, my parents contributed greatly for this dissertation. My family
has provided me with extraordinary encouragement and support through my academic
endeavor. I thank them for always being at my side, listening to me and giving me
support. I am grateful to my sisters, my brother, my grandmother and grandfather for all
their encouragement and unending enthusiastic support.
vii
VITA
August 30, 1976…………………….Born – Taipei, Taiwan
1999....................................................B.B.A. in Tourism, Ming Chuan University, Taipei, Taiwan
2001…………………………………M.S. in Hospitality and Tourism Management, Florida International University, Miami, FL
2002-2005…………………………..Graduate Student and Graduate Teaching Associate, Department of Consumer Sciences, College of Human Ecology, The Ohio State University, Columbus, OH
PUBLICATIONS
Research Publications
1. Parsa, H.G. and Hu, H.H. (2004). “Price-Ending Practices and Cultural Differences in the Food Service Industry: A Study of Taiwanese Restaurants,” Foodservice Technology. 4, 21–30.
2. Hu, H.H.; Zhao, J. and Carter, C. (2003). “Shipboard Employee Job Satisfaction in Major Cruise Lines,” FIU Hospitality Review. 21 (November), 10-21.
FIELD OF STUDY
Major Field: Human Ecology
Specialization: Hospitality Management, Consumer Behavior
viii
TABLE OF CONTENTS
Contents Page
Abstract ............................................................................................................................. ii
Dedication ........................................................................................................................ iv
Acknowledgments............................................................................................................. v
Vita.................................................................................................................................. vii
List of Tables ................................................................................................................... xi
List of Figures ................................................................................................................. xii
Chapters
1. INTRODUCTION ....................................................................................................... 1
Statement of the Problem.............................................................................. 4 Purpose of the Study ..................................................................................... 5 Definition of Terms....................................................................................... 6 Structure of the Study ................................................................................... 7
2. REVIEW OF LITERATURE ...................................................................................... 9
2.1 Sales Promotion ............................................................................................ 9 Consumer Benefits of Sales Promotions .................................................... 12 Consumer Response to Sales Promotions................................................... 16 The Effects of Sales Promotion on Purchase Intentions............................. 19 Price Perception and Sales Promotions....................................................... 20 Potential Traits and Influence on Consumer Purchase Behavior................ 21 Role of Price Promotion Framing ............................................................... 23 Sales Promotion in Hospitality Industry ..................................................... 27
2.2 Sales Promotion: The Usage of Currency................................................... 29 Currency Usage in Hospitality Industry ..................................................... 31
2.3 Personality Traits ........................................................................................ 35 Need for Cognition ..................................................................................... 36 Need for Cognition in Consumer Reactions of Price Promotion................ 37
ix
Self-Monitoring........................................................................................... 40 Self-Monitoring and Consumer Behavior................................................... 43 Impression Management............................................................................. 47 Self-Monitoring and Impression Management ........................................... 50
2.4 Conceptual Model....................................................................................... 54 Chapter Summary ....................................................................................... 56
3. METHODOLOGY .................................................................................................... 58
Experimental Design................................................................................... 58 The Sample Frame ...................................................................................... 61 Data Collection ........................................................................................... 62 Experimental Procedures ............................................................................ 62 Instrumentation ........................................................................................... 63
Independent Variables ...................................................................... 63 Dependent Variables......................................................................... 66
Data Analysis ............................................................................................ 67 Assumptions of Multinomial Logistic Regression ........................... 69 Interpretation of Multinomial Logistic Regression Model ............... 70
Chapter Summary ....................................................................................... 72
4. RESULTS .................................................................................................................. 74
Descriptive Statistics................................................................................... 74 Sample Characteristics...................................................................... 74 Currency Preference.......................................................................... 75 Restaurant Segments......................................................................... 76 Need for Cognition ........................................................................... 77 Self-Monitoring................................................................................. 78 Dining Companions .......................................................................... 79
Multinomial Logistic Regression Analysis................................................. 82 Summary of the Hypothesis Tests .............................................................. 94
5. CONCLUSIONS........................................................................................................ 97
Discussions and Summary .......................................................................... 97 Implications............................................................................................... 100 Limitations ................................................................................................ 102 Recommendations for Future Research .................................................... 103 Chapter Summary ..................................................................................... 104
x
6. POSTCRIPTS .......................................................................................................... 105 Restaurant Context.................................................................................... 106 Airline Context.......................................................................................... 109 Summary of the Results ............................................................................ 114
BIBLIOGRAPHY........................................................................................................... 115 APPENDIX A: Results of Multinomial Logistic Regression Analysis: 188 samples
included for Need for Cognition ........................................................... 129
APPENDIX B : Experiment Instruments ....................................................................... 134
APPENDIX C : Experiment Instruments for Postscript ................................................. 166
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LIST OF TABLES
Table Pages
2.1 Summary of Hotel Rewards Programs (continued) ............................................... 32
3.1 Experimental Design to assess Consumer Preferences for Currency Usage (continued) .............................................................................................................. 60
3.2 Measurement of Variables ..................................................................................... 68
4.1 Descriptive Statistics by the Type of Currency ..................................................... 81
4.2 Results of Multinomial Logistic Regression Analysis: Dollars and Points versus Dollars-only (continued)....................................................................................... 90
4.3 Results of Multinomial Logistic Regression Analysis: Points-only versus Dollars-only (continued)....................................................................................... 92
4.4 Summary of the Hypothesis Tests of Currency Preferences ................................. 96
6.1 Descriptive Statistics by the Type of Currency in Restaurant Context ............... 107
6.2 Results of Multinomial Logistic Regression Analysis for Restaurant Context ... 109
6.3 Descriptive Statistics by the Type of Currency in Airline Context ..................... 110
6.4 Results of Multinomial Logistic Regression Analysis for Airline Context......... 113
A.1 Results of Multinomial Logistic Regression Analysis: Dollars and Points versus Dollars-only (188 samples included for Need for Cognition) ................. 130
A.2 Results of Multinomial Logistic Regression Analysis: Points-only versus Dollars-only (188 samples included for Need for Cognition) ............................ 132
xii
LIST OF FIGURES
Figure Pages
2.1 The Effects of Need for Cognition, Self-Monitoring, Dining Companion, and Restaurant Segment on the Choice of Currency in the Restaurant Industry......... 55
4.1 Preferences for Three Types of Currencies ........................................................... 75
4.2 Currency Preferences in Three Restaurant Segments............................................ 77
4.3 Currency Preferences and Need for Cognition ...................................................... 78
4.4 Currency Preferences and High and Low Self-Monitoring ................................... 79
4.5 Currency Preferences for Companions Using Three Different Currency Types... 80
4.6 Currency Preferences of High Self-Monitors with Companions........................... 87
4.7 Currency Preferences of Low Self-Monitors with Companions............................ 88
4.8 Currency Preferences of High Self-Monitors with Three Restaurant Segments ... 88 4.9 Currency Preferences of Low Self-Monitors with Three Restaurant Segments.... 89 6.1 Currency Preferences in Restaurant Context ....................................................... 107
6.2 Currency Preferences for Need for Cognition in Restaurant Context ................. 108
6.3 Currency Preferences in Airline Context............................................................. 111
6.4 Currency Preferences for Need for Cognition in Airline Context ....................... 112
1
CHAPTER 1
INTRODUCTION
The immense popularity of marketing promotions and loyalty programs has
resulted in the introduction of several new exchange media other than money (Drèze and
Nunes, 2004). In 1985 American Airlines invented a new marketing idea called
frequent-flyer miles; they launched AAdvantage, the world's first mileage-based
frequent-flyer program. Airlines first introduced mileage schemes to build customer
loyalty. They also provided a vast marketing database, allowing airlines to track a
passenger's travel history and to focus advertising. Recently airlines have been selling
these mileages not only to credit-card companies but also to various business entities to
attract customers. However, almost 50% of miles are earned without even leaving the
ground. The biggest earners are credit-card spending and telephone calls, and services
such as car rentals, hotels, share-trading or refinancing a mortgage all offer extra
opportunities to top up consumers’ frequent miles (The Economist, 2002).
For example, the AAdvantage program provided by the American Airlines is
American's travel awards program. It was the original travel awards program, established
more than 20 years ago, and today is the world's largest program. AAdvantage members
earn miles each time they purchase an eligible published-fare ticket and fly on American
Airlines, American Connection, American Eagle or any of the more than 30 airline
2
partners. Members also earn bonus miles for flying on an eligible purchased-fare
Business Class or First Class ticket on American Airlines or any of its airline partners as
follows: an additional 25% of flight mileage flown in Business Class, or an additional
50% of flight mileage flown in First Class. In addition, members earn miles when staying
at AAdvantage hotel partners or when renting a car from a partner company. Currently
over 35 hotel partners representing more than 75 brands and all seven major car-rental
agencies are AAdvantage partners. Because not everyone is a frequent traveler, miles can
also be earned through non-travel-related partners including assorted financial and retail
partners. Miles can be redeemed for a variety of travel awards around the world on
American Airlines.
In the lodging industry, Hilton hotels also introduced a loyalty program called
Hilton Honors Club (HH club) (www.hhonors.hilton.com, 2005). The program of Hilton
Honors Club (HH club) offers a customer one qualifying stay accounting for two benefits
(they call this double dipping). The first benefit is that a qualifying-rate stay at one of the
affiliated hotels can earn 500 miles worth of frequent-flyer mileages of customer’s choice
from about 30 selected airlines. The second benefit is that every dollar a customer spends
earns 10 honor points. Those honor points can be used to receive various goods offered
by their reward site. The popular items on the reward site are mini disc players, MP3
players, cameras, camcorders, watches and computers. The points necessary to redeem
those items range widely from 45,000 to over 100,000 points. Another popular way to
benefit from those honor points is to either earn a 50% discount or to receive a free stay
at those participating hotels. For as few as 2,500 points, a member can benefit from the
50% discount for a weekend stay. And a free stay at one of those hotels starts at 10,000
3
points. Those points can also be used to obtain a free car rental, a vacation package of a
customer’s choice (Europe, Asia, Middle East, etc.), or a free three- to seven-day cruise
trip (either Carnival or Prince cruise) for as little as 185,000 points
(www.hhonors.hilton.com, 2005).
Various American Express Cards provide a program for cardholders to access free
rewards. For every dollar spent on the card, cardholders earn one point. Earned points can
be applied to a variety of services and products, many of which are travel related. There
is no yearly limit or expiration on points earned. Also, the Chase Ultimate Rewards
Platinum MasterCard, issued by Chase Bank, is designed for those who have very good
credit and plan to take advantage of the reward program offered. Through the reward
program, cardholders earn one point for every dollar spent on general purchases that may
be redeemed for gift certificates, brand-name merchandise, a variety of travel awards, or
cash rewards. Unused points do expire within three years and the maximum number of
points that may be earned per billing period must not exceed the cardholder's credit limit.
From frequent-flyer mileages to credit cards, consumers accumulate assets in
various novel currencies, which they then budget, save, trade, and spend just as they do
with money. Currently, some 100 million people around the world belong to at least one
such scheme (including one in three adults in the United States), collecting the nearly 500
billion miles distributed annually (The Economist, 2002). As of April 2002, the
cumulative number of unredeemed miles worldwide was estimated to be approximately
8.5 trillion, which at current redemption rates would take almost 23 years to clear (The
Economist, 2002). In 2000 alone, airlines issued 13 million free award tickets
(www.WebFlyer.com cited by Drèze and Nunes, 2004). Frequent-flyer miles or reward
4
points are treated almost like a second currency, but they are not freely tradable. The fine
print of all programs specifies that consumers cannot sell, buy or barter miles. However,
as with any controlled currency, there is a thriving black market. Brokers, such as Award
Traveller, will buy the miles at a discount. A direct consequence of the ubiquity of
rewards programs is that consumers are increasingly able to pay for goods and services in
a combination of currencies, not just in dollars (Drèze and Nunes, 2004). However, more
research is needed to understand consumer behaviors and responses to different
currencies.
STATEMENT OF THE PROBLEM
Several variables have the potential to affect consumer evaluation of different
currencies such as amount of payment, demographic characteristics, or personality traits.
Drèze and Nunes (2004) reported that consumers prefer one currency price over another
based on the amount of payment. Individual differences could be important moderators of
the consumer preferences of currency usage. It may be that certain consumers who are
contemplating spending reward points, dollars, or any mix of two currencies have
difficulty recalling or constructing a value for different amounts of either currency or
both. In addition, for certain consumers, the relevant information may be unavailable or
inaccessible. Despite the growing popularity of prices issued in more than one currency,
limited research has examined how consumers evaluate currency prices other than money.
Although various novel currencies have been introduced and applied at various business
5
entities to attract a customer, the restaurant business often does not utilize any currency
other than money except for credit cards. Thus, a need exists to expand our knowledge
and conceptualization of currency preferences to include consumer responses to different
currencies in the restaurant industry.
PURPOSE OF THE STUDY
The understanding of consumer behavior would be improved by the knowledge of
the consumers’ characteristics that relate to the different currency options. By
understanding the individual personality differences of customers when using different
currencies, restaurants could decide whether or not to implement different currency prices
based on their target markets. Thus, the purpose of this study is to explore whether
differences in currency usage are related to consumer behavior. This study is designed to
describe how two personality variables – need for cognition and self-monitoring – may
aid in understanding how individual differences can influence consumers’ preferences for
currency usage in the restaurant industry. In addition, it shows how the individual
difference variables of need for cognition and self-monitoring fit into an overall
conceptualization of currency preferences. Another purpose of the study is to determine
whether consumers’ currency preferences vary across restaurant segments.
6
DEFINITION OF TERMS
The operational definitions of the terms used in the present study follows:
Sales Promotion
Sales promotion is considered as an action-focused marketing event whose purpose
is to have a direct impact on the behavior of the firm's customers (Blattberg and Neslin,
1990).
Currency
A currency is a unit of exchange, facilitating the transfer of goods and services. It
is a form of money, where money is defined as a medium of exchange rather than e.g. a
store of value (Wikipedia, www.en.wikipedia.org/wiki/Currency, 2005).
Fine-Dining Restaurant
A fine-dining restaurant is defined as a restaurant offering high-quality foods with
high-quality service. Fine-dining restaurants are operationalized on menu price criteria of
an average guest check of $25 or higher (National Restaurant Association, 2004).
Casual-Dining Restaurant
A casual-dining restaurant is defined as a restaurant offer some table and bar
service such as coffee shops. Casual-dining restaurants are operationalized on menu price
criteria of an average guest check of $6 to $24 (National Restaurant Association, 2004).
Quick Service Restaurant
A quick-service restaurant is defined as a restaurant that offers a “limited menu
featuring food such as hamburgers, fries, hot dogs, chicken, tacos, burritos, gyros,
teriyaki bowl, various finger foods, and other items for the convenience of people on the
7
go.” Quick-service restaurants offer quality, speed, cleanliness, service, and value for the
customers (Walker, 2001). Quick-service restaurants are operationalized on limited menu
items, limited service with an average guest check of $5 or under (National Restaurant
Association, 2004).
Self-Monitoring
Self-Monitoring “is concerned with individual differences in the willingness or
ability to modify behavior in accordance with the norms of situational appropriateness”
(Miller and Thayer, 1988, p. 545).
Need for Cognition
Need for cognition refers to an individual’s tendency to engage in and enjoy
effortful cognitive endeavors (Cacioppo and Petty, 1982).
Dining Companion
Dining companion is operationally defined as the companion with whom one
shares the dining experience.
STRUCTURE OF THE STUDY
The structure of the study is presented as follows. Chapter 2, the literature review,
includes three sections. Section 2.1 provides an in-depth literature review on the concept
and theory of sales promotion from a consumer perspective. Section 2.2 discusses a
specific type of sales promotion – the usage of currency – and its relationship with
8
consumer behaviors and applications. Section 2.3 addresses the theoretical development
of the personality traits and consumer preferences for currency usage. Section 2.4
presents research hypotheses and a conceptual model based on the theory and related
research.
Chapter 3 presents the experimental and statistical methods used to test the
hypotheses. Two causal experimental designs are discussed. Multinomial logistic
regression is applied to analyze the data and test the hypotheses for the study.
Chapter 4 provides a descriptive profile of the sample as well as the results of
multinomial logistic regression. The summary of the hypothesis tests is also presented.
Chapter 5 presents a discussion of findings, conclusions, and implications of these
results. Limitations of the study and recommendations for future research are also
discussed.
9
CHAPTER 2
LITERATURE REVIEW
In this chapter, a literature review focuses on the impact of personality traits and
restaurant segments on consumer currency preferences. The literature review is organized
into three sections: sales promotion, sales promotion and the usage of currency, and
personality traits.
2.1 SALES PROMOTION
Sales promotions encompass all promotional activities other than advertising,
personal selling, or public relations. Blattberg and Neslin (1990) summarized various
definitions offered by several authors, and consider sales promotions as an action-focused
marketing event whose purpose is to have a direct impact on the behavior of the firm's
customers. Several important aspects of sales promotions should be highlighted to
complete the definition mentioned above. First, sales promotions involve some type of
inducement that provides an extra incentive to buy and represents the key element in a
promotional program (Schultz and Robinson, 1982). According to Strang (1983), this
incentive is added to the basic benefits provided by the brand. It temporarily alters the
perceived brand price or value. It is also considered as an acceleration tool designed to
speed up the selling process and maximize sales volume (Neslin et al., 1984). By offering
10
this extra incentive, sales-promotion techniques can motivate consumers to buy a larger
quantity of a brand or shorten the interpurchase time of the trade by inducing consumers
to take more immediate action (Laroche, et al., 2001). In essence, sales promotions are
used by nearly all consumer goods and services producers as temporary incentives
aimed at changing purchase behavior (Quelch, 1989).
While these incentives can be monetary or nonmonetary, most theoretical models
that have appeared in the marketing literature to date have focused on monetary
incentives. Various statistics show that sales promotions represent a significant part of a
firm’s marketing expenditures. A 1996 U.S. study reported that nearly 77% of the
advertising and promotions expenditure of consumer goods firms was on consumer and
trade promotions (Nielsen, 1996). Promotion spending reached over $288.3 billion in
2003, up 9.7% from the previous year in the U.S. The Promotion Marketing Association
(2003) reported that U.S. manufacturers spent almost twice as much of total 2003 budget
on consumer promotion (46%) than they did on consumer advertising (24.2%).
The promotional price is ‘‘packaged’’ and advertised in several ways (Kotler,
1994): (1) A limited-time “shelf-price” reduction: A lower price is offered for a limited
time to all consumers. The shelf-price discount is a reduction in a brand’s regular price. It
is displayed on the package and typically ranges from10 to 25% off the regular price for
grocery packaged goods. A shelf-price discount implies that all consumers who buy the
product at the time when the brand is on discount have the opportunity to buy it at a
lower price. Media advertising (e.g., television or newspaper) usually accompanies this
type of promotion (Kotler, 1994). (2) Free-Standing Insert (FSI) Coupons: A lower price
is offered to those consumers who present a coupon before the coupon’s expiry date
11
(Shimp, 1993). FSI coupons provide the firm with the option of charging a higher shelf
price while offering a lower price to those who choose to use the cents-off coupon when
one is available. Typically, a coupon is placed in a “free-standing insert” (FSI) in the
Sunday newspaper. No other media advertising usually accompanies this type of a price
promotion. (3) Mail-in Rebates: A lower price is offered to those consumers who send in
by mail a “proof of purchase.” Media advertising may or may not accompany this type of
price promotion. For example, automobile manufacturers typically advertise these rebates;
most packaged-goods rebates, however, are not advertised, except at the point of sale. (4)
Price Packs: A lower price is offered by means of an offer on the package –a peel-off
label which can be contemporaneously presented at the check-out counter or a coupon
that has to be cut out and presented on the next purchase occasion – or stored inside the
package. The non-peel-off on-package coupon is similar to the in-package coupon in
terms of when it can be redeemed, but it is different in that its existence is advertised on
the package (Raju et al., 1994). No media advertising usually accompanies a price-pack
promotion. (5) Electronic Coupons: These are coupons which are automatically generated
at the check-out counter based on what the consumer is buying. They are similar to
in-pack coupons in that they are good only for the next purchase, and their availability is
not known to the consumer at the point of purchase (Walsh, 1994).
Depending on how a sales promotion is presented, all contemporaneous
transactions may or may not happen at a single price. For example, in 1993 in the U.S.,
88% of all coupons were distributed through FSIs, making them the most popular
promotion vehicle. But only 1.8% of these coupons were redeemed, suggesting that a
large fraction of consumers was paying regular prices while a FSI coupon was available
12
(Walsh, 1994). By contrast, Engel et al. (1994) reported that coupons on product
packages had a redemption rate of 33% (among those buying the product), but only 3.8%
of coupons were package coupons. Coupons at the store shelf – which are like shelf-price
reductions – had a high redemption rate (among those buying the product), yet only 5%
of coupons were distributed at the store shelf. Finally, electronic coupons had a
redemption rate of 9%, but only 1% of all coupons were distributed electronically
(Whalen, 1994).
Consumer Benefits of Sales Promotions
According to Keller (1993), the benefits of sales promotion can be defined as the
perceived value attached to the sales-promotion experience, which can include both
promotion exposure (e.g., seeing a promotion on a product) and usage (e.g., redeeming a
coupon or buying a promoted product). This definition implies that consumers respond to
sales promotions because of the positive experience they provide, or, following
Holbrook’s (1994) definition, because of their customer value. Most analytical and
econometric models of sales promotions simply assume that monetary savings are the
only benefit motivating consumers to respond to sales promotions (Blattberg and Neslin,
1993). Behavioral research on sales promotions has tended to focus on the demographics
of deal-prone consumers (Blattberg et al. 1978; Narasimhan 1984; Bawa and Shoemaker,
1987) and on the identification of personal traits such as “coupon proneness,”
“value-consciousness,” or “market mavenism” (Mittal, 1994; Lichtenstein, Netemeyer,
and Burton, 1995). These studies offer a coherent portrait of the demographic and
psychographic characteristics of deal-prone consumers. However, because of their focus
13
on individual variables, these studies do not examine the nature, and the number, of the
specific consumer benefits of sales promotions. Yet, some robust empirical results
suggest that monetary savings cannot fully explain why and how consumers respond to
sales promotions. To account for these findings, researchers have advanced explanations
related to achievement motives (Darke and Freedman, 1995), self-perception (Schindler,
1992), and fairness perception (Thaler, 1985) or to price and quality inferences in
low-involvement processing (Inman, McAlister and Hoyer, 1990; Raghubir and Corfman,
1999). The contributions of the personality studies, the parsimony of the economic
perspective, and the existing work on the non-monetary benefits of sales promotions have
greatly contributed to our understanding of consumer response to sales promotion;
however, the extent of support for some of these explanations is limited.
An integrated study of the consumer benefits of sales promotions by Chandon,
Wansink, and Laurent (2000) provided a framework of the multiple consumer benefits of
a sales promotion. To develop a framework of the different consumer benefits of sales
promotions, Chandon, Wansink, and Laurent (2000) elaborated the literature on
consumer response to sales promotions, customer value, and hedonic consumption with
nine in-depth consumer interviews. The authors found that monetary and nonmonetary
promotions provide consumers with different levels of three hedonic benefits
(opportunities for value-expression, entertainment, and exploration), and three utilitarian
benefits (savings, higher product quality, and improved shopping convenience).
Utilitarian benefits are primarily instrumental, functional, and cognitive; they provide
customer value by being a means to an end. Hedonic benefits are non-instrumental,
experiential, and affective; they are appreciated for their own sake, without further
14
regards to their practical purposes (Hirschman and Holbrook, 1982). Hence, the benefits
of sales promotions can be classified as utilitarian when they help consumers maximize
the utility, efficiency, and economy of their shopping and buying, and as hedonic when
they provide intrinsic stimulation, fun, and self-esteem. On the one hand, buying a
promoted product can provide the moral satisfaction of behaving according to one’s
principles and values (e.g., being a good or a thrifty shopper)—an intrinsic or hedonic
benefit. On the other hand, buying a promoted product can be a means of increasing one’s
prestige and achieving higher social status or group affiliation (e.g., becoming a
recognized smart shopper or a market maven)—an extrinsic or utilitarian benefit
(Chandon, Wansink, and Laurent, 2000).
Chandon, Wansink, and Laurent (2000) further developed a benefit congruency
framework that predicts the types of product for which monetary and non-monetary
promotions are most effective. The fact that monetary and non-monetary promotions
provide different consumer benefits suggests that their effectiveness may depend on the
congruence or the match that these benefits have with the product, consumer, or purchase
occasion. According to most models of consumer choice (e.g., combinatorial models of
attitude formation or utility theory), consumers evaluate products on basis of the benefits
they provide, weighted by the importance of these benefits. The weighting of the benefits
varies across products, purchase occasions, and individuals (Meyer and Kahn, 1991;
Eagly and Chaiken, 1993). For low-involvement, repeat-purchase products, the weights
of some of these benefits may go down to zero, so that only a few benefits, the most
important ones, are considered in the purchase evaluation. For instance, Hoyer's (1984)
field study of laundry-detergent buyers in the US showed that a few product benefits such
15
as product performance, price, emotional attachment, or social norms account for 81% of
the benefits sought. Many studies have documented the varying importance of benefits
sought (e.g. Shavitt, 1990; Strahilevitz and Myers, 1998) but Leong’s (1993) study
provides some of the clearest evidence that although the same list of benefits accounted
for 86% of the benefits sought by Singaporean consumers, the weights of these benefits
were very different from the figures reported for US buyers. Interestingly, Leong found
that these weights varied more across product categories (e.g., laundry detergent vs.
shampoo) than across nationalities for the same category. Therefore, the utilitarian
benefits of a given choice alternative are given more weight when consumers make a
utilitarian purchase decision, and that hedonic benefits are given more weight when they
make a hedonic purchase decision. The varying importance of the benefits sought implies,
in turn, that the effectiveness of a sales promotion is higher when its benefits are
congruent with those sought for the purchase occasion. Simply stated, the
benefit-congruency principle proposes that sales promotions are more effective in
influencing brand choice when they provide the benefits that have the largest weight in
the evaluation of a purchase alternative (Chandon, Wansink, and Laurent, 2000).
In summary, sales promotions can provide consumers with an array of hedonic and
utilitarian benefits beyond monetary savings. Hedonic benefits include value expression,
entertainment, and exploration. Along with simple monetary savings, utilitarian benefits
also include product quality and shopping convenience. Moreover, non-monetary
promotions provide more hedonic benefits and fewer utilitarian benefits than monetary
promotions. All benefits, except quality, contribute to the overall evaluation of monetary
and non-monetary promotions. However, each type of promotion is primarily evaluated
16
based on the dominant benefits it provides. Finally, for high-equity brands, sales
promotions are more effective when they provide benefits that are congruent with those
provided by the product being promoted. Specifically, monetary promotions are more
effective for utilitarian products than for hedonic products. Conversely, non-monetary
promotions are relatively more effective for hedonic products than for utilitarian products
(Chandon, Wansink, and Laurent, 2000).
Consumer Response to Sales Promotions
Previous research in marketing and psychology has examined consumer response
to sales promotions using experimental methods and econometric analysis of secondary
data (e.g., Jain and Vilcassim, 1991; Kahn and Raju, 1999). Recently, researchers have
attempted to understand consumer response to sales promotions using theoretical models.
Helsen and Schmittlein’s study (1992) provided a better understanding of stockpiling
behavior. They defined stockpiling as loyal users buying more of the promoted brand, or
buying it earlier than when there is no promotion. As consumption rate is assumed to be
constant, it follows that promotion-induced stockpiling leads to loyal consumers being
subsidized. The authors note that this reduces the profitability of a promotional campaign.
Helsen and Schmittlein (1992) analyzed stockpiling using the framework developed in
Golabi (1985). Golabi considers the problem of a buyer purchasing a single item with no
transaction costs. The consumption rate is assumed to be constant, and future prices are
considered to be uncertain. However, the buyer assumed to know the probability
distribution of future prices. Golabi showed that under these assumptions, the optimal
purchasing policy is characterized by a set of critical prices. In other words, the observed
17
price in a period, when compared to the set of critical prices, can be used to arrive at
optimal procurement for that period. Expanding Golabi’s framework, Helsen and
Schmittlein (1992) examined the effect of deal frequency and deal magnitude on
stockpiling behavior and found that lower deal frequency leads to greater stockpiling.
The intuitive justification is that more frequent deals imply lesser need to stockpile on
any particular deal occasion.
Moreover, Assuncao and Meyer (1993) extended Golabi’s work on two critical
dimensions. First, they allowed consumption to be a function of price. In his model,
Golabi assumed a constant consumption rate. This assumption is quite appropriate in an
industrial buying context where quantity purchased is determined by engineering needs
and considerations. However, a consumer might want to adapt consumption by
substituting one product for another depending on prices. Also, Assuncao and Meyer
allowed future prices to follow a first-order stochastic process. Consequently, one can
examine purchasing behavior in situations where the consumer might believe that after a
promotion has been offered, it is less likely that a promotion will be offered in the very
next period. Assuncao and Meyer (1993) showed quite elegantly why a rational consumer
is likely to consume more if there is more stock at hand. The intuition is quite simple. A
more heavily stocked-up consumer has the capacity to wait longer for a good price deal.
Consequently, the price that the consumer expects to pay is also lower. Hence, the
consumer can indulge and consume more. Their results also explain why promotional
price elasticities are higher than regular price elasticities. Furthermore, as in Helsen and
Schmittlein’s study (1992), these authors also found that a higher discounting frequency
leads to lower price sensitivity and stockpiling.
18
A single supplier is an assumption in both Helsen and Schmittlein’s (1992) and
Assuncao and Meyer’ studies (1993). However, Krishna (1992) modeled situations where
the market consists of more than one brand, and the consumer has the option to choose
which brand to buy as well as how much to buy of the chosen brand – a scenario more
representative of today’s marketplace. Using the framework suggested in Raju,
Stinivasan and Lal (1990), Krishna (1992) assumed that the consumer’s brand-choice
decision is based on prices adjusted for quality. In other words, the consumer will choose
a brand that is lower priced once prices have been adjusted for quality differences
between the two brands. These quality-adjusted prices are referred to as “effective prices”.
Krishna (1992) showed why a consumer will purchase only one brand on any buying
occasion, and also that the entire information necessary to understand a consumer’s
buying decision is included in the probability distribution of the lowest realized effective
price. Recall that the consumer is assumed to compare effective prices and purchase the
brand with the lowest effective price to derive critical prices. The key implications in
Krishna’s study (1992) are derived using Monte Carlo simulations in a three-brand
market. In lines with Helsen and Schmittlein (1992) and Assuncao and Meyer (1993),
Krishna also found that higher discounting frequency leads to lower stockpiling. The
simulation results suggest that in markets with low brand loyalty and high promotional
frequency, one is not likely to observe a post-promotional dip mainly because off-deal
sales are lower, both before as well as after a promotion.
19
The Effects of Sales Promotion on Purchase Intentions
Shoemaker (1979) was one of the first to investigate the effects of promotions on
purchase behavior. He empirically showed that purchase acceleration was due to sales
promotion. His findings suggested that promotions were more apt to be associated with
increased quantity than with shorter interpurchase time. Then, Blattberg et al. (1981)
explained the dealing of storable products based on the idea of transferring
inventory-carrying costs from the retailer to the consumer. For four product classes, they
found statistically significant evidence of purchase acceleration in terms of both larger
quantities and shorter interpurchase times. Raju and Hastak (1983), who examined the
effect of a deal’s magnitude on the purchase behavior due to promotions, confirmed these
results. At the individual level, however, price promotions seemed to act as a disturbing
element, which inhibits negative thoughts that might arise about the brand. Also, Neslin
et al. (1984) expanded this empirical line of inquiry by developing an analytical
framework for studying purchase acceleration. Their main findings concern how coupons,
temporary price cuts, and featured price cuts were all associated with higher purchase
quantities.
In summary, there is a good deal of empirical support for an increase in purchase
quantity due to sales promotions in the consumer packaged-goods area, supporting the
concept of potential stockpiling (Helsen and Schmittlein, 1992). Also, as suggested by
Lichtenstein et al. (1990), deal-prone consumers tend to develop links between their
liking of specific price promotions and their inclination to buy products using these
20
promotions. Indeed, the notion of transaction utility dictates the behavior of the consumer.
It allows a particular psychological inducement (i.e., feeling good about using the
promotion) that plays the major role in directing the behavior.
Price Perception and Sales Promotions
Several recent studies tend to support the presence of mental processing engaged in
by the consumer at the initial stage of promotion use, particularly regarding the influence
of the promotion on the price perception of the purchase (Cheong, 1993; Folkes and
Wheat, 1995; Lichtenstein et al., 1998). Price-perception theories address the relationship
between objective price and consumers' judgments of the price (Sawyer et al., 1984).
Price promotions significantly affect consumers' price perception (Folkes and Wheat,
1995). Offering a product with a rebate results in higher perceptions as measured by the
most one would pay, expected price, fair price and reasonable price. This difference is
explained from a Mental Accounting perspective (Thaler, 1985).
Kalwani and Yim (1992) also explored the field of consumers' price expectations.
Their study proposes that consumers form expectations of prices and use them in
formulating their response to retail pricing. Their findings reveal that consumer reaction
depends not only on retail price, but also on the comparison they make with the
reservation price. In other words, consumers use the price they expect to pay for a brand
on a given purchase occasion as reference in forming price judgments. Therefore, even if
different processes have been hypothesized, there is a consensus on the existence of a
cognitive process. This process can be described as a cognitive evaluation, made by the
consumers, of the benefits of a price promotion.
21
Moreover, this idea is developed by Lichtenstein et al. (1998), who found
similarities between consumers with positive attitude toward private-label products and
consumers using price promotions, particularly regarding the mental calculation involved.
They describe these consumers as thoughtful shoppers who take pride in their
decision-making ability. These evaluations made by the consumers positively influence
the purchase intention of private-label products through the liking of these private labels.
Finally, certain promotional mechanisms such as coupons inherently require
searching costs (Schneider and Currim, 1991). Indeed, coupon users are used to engaging
in coupon searching and sorting (Bawa and Shoemaker, 1987). Particularly, the liking of
coupons seems correlated with specific behavior such as intensive use of weekly store
fliers containing coupons as well as information on sales (Lichtenstein et al., 1995).
Hence, using a coupon and identifying cents-off are thoughtful decisions and involve
information-search costs (Kahn and Schmittlein, 1992). Moreover, Kalwani and Yim
(1992) showed that consumers tend to use the last few purchase prices as a reference, as
well as readily available information from the environment concerning promotions. This
information is included circulars as well as other advertising information.
Potential Traits and Influence on Consumer Purchase Behavior
From managerial and academic perspectives, a tremendous effort has been made to
define the deal-prone consumer. The targeting of consumer deals, as well as the
understanding of consumer behavior would be improved by the knowledge of the
consumers’ characteristics that relate to deal purchasing in a product market. Mittal (1994)
presented a set of explanatory variables to capture the psychology of coupon-use
22
behaviors. His model regrouped demographic variables, lifestyles and self-perception
traits (busyness, financial wellness, and pride in homemaking). Particularly, he
underlined the fact that busy and well-off people were buying fewer promoted products
than their counterparts. He also reviewed some of the consumer shopping traits, such as
brand loyalty, store loyalty and comparison shopping. One of his main findings was that
coupon-redemption behavior and demographics were not linked in any way. This finding
contradicts previous findings (Blattberg et al., 1978; Narasimhan, 1984; Bawa and
Shoemaker, 1987). However, consumers' shopping traits do have a significant effect in
explaining coupon redemption.
Brand loyalty is probably the most studied individual-difference variable in the
promotional literature. Results are consistent in suggesting that brand loyalty negatively
affects deal or coupon attitude and use (Webster, 1965; Montgomery, 1971). Price et al.
(1988) included another personality trait in the study of coupon proneness, which is
market mavenism. The authors define market mavens as the people who possess
information about the products and places to shop, and who provide other consumers
with market information. These consumers are characterized by their expertise, in that
they plan their shopping trips and their expenses, and they are heavy users of coupons.
The results of this work indicate that this type of consumer is likely to engage in smart
shopping behaviors. Urbany et al. (1996) found a positive effect of market mavenism on
search behaviors and cognitive activities. An additional trait, which could significantly
influence promotion use, is variety seeking. In particular, when consumers seek variety,
they should like promotions that might help them discover new products (Narasimhan,
1984). Lichteinstein et al. (1990) were among the first to describe moderators of the
23
relationship between coupon proneness and coupon redemption behavior. They
developed a two-staged model in which a psychological level influenced the
coupon-responsive behavior rather than seeing it as isomorphic with the behavior.
Role of Price Promotion Framing
Research in the price-framing literature (Kahneman & Tversky, 1979; Thaler, 1985;
Thaler & Johnson, 1990) provides important insights into the process by which
consumers evaluate different deals and subsequently encode them in memory. Framing
effect refers to the finding that consumers respond differently to different descriptions of
the same decision question (Frisch, 1993). Framing of decision problems can affect
consumers’ judgments and, therefore, preferences (Kahneman and Tversky, 1979).
Folkes and Wheat (1995) found that framing via various types of promotions affects
consumers’ price perceptions.
According to Thaler (1985), people perform mental accounting on their
transactional gains or losses based on differential responses to such outcomes.
Considering the prospect theory which holds that an individual’s value function is
concave (risk-averse) over gains and convex (risk-seeking) in the loss domain, Thaler
showed that people psychologically segregate multiple gains but integrate losses.
Because a typical promotion represents a small gain relative to a larger loss (i.e., price
paid), using Thaler’s notion, in such cases individuals may either segregate the gain
(silver lining) or integrate it with the price and encode it as a reduced loss. However,
there is some evidence that shows that the key factor in “whether a consumer is going to
frame a given promotion as a gain or a reduced loss” seems to depend on the nature of
24
the promotion itself, that is, if it is monetary or nonmonetary. As Diamond and Campbell
(1989) explained, if the promotion is monetary and therefore in the same metric as the
item price, consumers are more likely to integrate it and subsequently encode it as a
reduced loss. However, if the promotion is nonmonetary (such as additional units of the
product), it obviously is in a different metric and therefore it will be encoded as a gain.
Furthermore, Diamond and Sanyal (1990) showed that consumers seem to prefer
promotions that are framed as gains to those that are described as reduced losses. In
particular, the authors find that in their experiments extra-product promotions that
involve giving an extra amount of the product (e.g., 49 cents worth of free soup) are
chosen over price promotions that give the same amount off as discount.
Communicating a price promotion in different formats is similar to the framing of
purchase decision (Monroe, 1990). Different message formats, e.g.,” dollar off”,
“percentage off”, “2 for $” or “Buy1, get 1 at 1/2 price” illustrate direct reference to the
price differences (Raghubir, 1992). The role of deal semantics on subsequent consumer
evaluations has been investigated through several studies (e.g., Della Bitta et al., 1981;
Lichtenstein, Burton, and Karson, 1991; Grewal et al., 1996). These articles have
principally examined the issue of how different semantic cues (in price information)
appear differentially to communicate value to buyers. Lichtenstein, Burton, and Karson
(1991) found that a between-store price-comparison cue (“See elsewhere at $, Our price
$”) resulted in a less favorable attitude to the deal than a within-store comparison (Was $;
Now only $). Grewal et al. (1996) demonstrated how the consumer’s situation (i.e., being
in the store versus at home), as well as offered discount size moderate this semantic effect.
Das (1992) investigated how consumers perceive four economically equivalent deals
25
(which are all held constant at 25% discount level), for example, “25% off total when you
purchase 2,” “Buy 1, get 1 at price,” “Save $ on purchase of 2,” and “2 for $,” over eight
different product items. Results showed that deal semantics do indeed affect consumer
evaluations, and that this effect is larger for lower-priced products. Further, the author
reported that there is a significant interaction effect between certain types of semantic
cues and item price; for example, the savings (“Save $”) frame appears to be preferred for
higher-priced items.
Della Bitta et al. (1981) conducted an experiment to access consumer perceptions
of comparative price advertisements. Their study was designed to explore the effects of
different ways of presenting comparative price offers. Della Bitta et al. focused on the
comparative information to describe a sale such as describing a sale by dollar amount off
or percent off. The findings of their study indicated that presenting percent-off format
produced a nearly significant lower perception of value for the money than did presenting
dollar-amount-off format. Promotions presented in dollar amount off were more
positively evaluated than the percentage-off formats. Lichtensteien et. al. (1991)
examined the differential effects of two types of semantic cues: comparative prices (i.e.,
“see elsewhere $__, our price $__”) and past prices (i.e., “was $__, now only $__”) on
consumer perceptions. By using the actual newspaper advertisement that they modified
for the study, they learned that comparative prices in advertisements influenced a
consumer’s purchase intention more than past prices. Raghubir (1992) investigated the
26
effects of semantic cues on consumer evaluations of promotional deals, and found that “2
for $” and “Buy1, get 1 at 1/2 price” frames were most effective across price levels.
Moreover, “save $__” frame was particularly effective at a high price level, but not at not
low price levels.
Harlam et al. (1995) demonstrated that discounts presented in “together” format
(e.g. “buy X and Y together at $__”) produce highest purchase intent and those presented
in “separate” (e.g. “buy X at $__ and Y at $__ if you buy the bundle”) format produce the
lowest intent. Additionally, Chen et al. (1998) investigated how the framing of price
promotions influences consumers’ perceptions of these promotions and their purchase
intentions. They found no significant differences in consumer price perceptions as a
function of promotions framed as off-price sales or coupons. However, both promotional
frames resulted in lower price perceptions than did price perception for the item with
rebates. Because rebates generally involve a delay in receiving the price savings,
consumers may not integrate the savings into the price of the item. Thus, participants’
price perceptions for the item were similar to their perceptions of regular price. The
results also suggested that consumers evaluated a price reduction framed in dollar terms
and percentage terms differently for high-end and low-end products. For high-price
products, consumers perceive a price reduction framed in dollar terms as more significant
than the same price reduction framed in percentage terms. Oppositely, for low-price
products, consumers evaluate the price reduction framed in percentage terms more
positively than in dollar terms.
27
Sales Promotion in Hospitality Industry
Much of the academic research in sales promotion has focused on package goods;
however, there is a need to understand whether consumers’ response to coupons for
service purchases is similar to that of package-goods purchases. Hospitality services offer
consumers a combination of tangible and intangible attributes. The fact that hospitality
services contain both a tangible and an intangible component raises questions about how
consumers will respond to a particular sales-promotion tool.
Taylor and Long-Tolbert (2002) examined the influence of coupons on consumers’
quick-service restaurant (QSR) purchases. The high level of coupon activity evident in
the fast-food market is largely a function of intense competition. In the fast-food context,
patrons might perceive the risks associated with experimenting with unfamiliar QSR
alternatives to be high, especially if they ascribe importance to attributes such as food
quality or taste. As a result, it is unlikely that a large number of consumers will use a
coupon to try an unfamiliar service provider whose service or food quality is unknown.
Thus, a consumer who redeems a quick-service coupon during a promotion period would
be expected to have a high likelihood of making a repeat purchase once the promotion
concludes. The results of this study revealed that coupon redemption did not negatively
affect repeat purchase behavior. Also, consumers who redeemed the coupon were 7.5
times more likely to return to the QSR than non-redeemers. The coupon did not deter
repeat-purchase behavior, as has been found in some package-goods studies. Finally, the
greatest difference between consumers’ responses to coupons in package-goods
purchases and in QSR purchases was in the timing of subsequent purchases. The coupon
did not lengthen the repurchase time for QSRs following redemption, as it often does for
28
package goods. Coupon promotions are virtually a mainstay for QSRs. Consistent with
the findings in package-goods studies, fast-food consumers who have exhibited a strong
preference for a particular brand, as demonstrated through frequent prior purchases, are
most likely to take advantage of a coupon for that brand. This implies that consumers’
prior-purchase behavior provides a good indicator of the likelihood that consumers
respond to a coupon promotion.
In order to have better understanding of consumers’ responses to price promotions
in the service sector, Hu, Parsa, and Khan (2005) explored the role of discount formats
and various discount levels. They found that in service industries, high- and low-end
services are significantly different from each other in preference for type of discount
formats. Price reductions should be stated in dollar format for high-end services whereas
price reductions should be framed in percentage format for low-end services. Moreover,
consumers perceived discount levels differently depending for high- and low-end services.
Consumers perceive price reductions more strongly in high-end services than in low-end
services. In addition, consumers perceive quality attributes significantly lower in high
discount level (50%) for low-end services, compared to high-end services. For low-end
services, high discount level (50%) may lower consumers’ quality perceptions and may
not motivate their purchase intentions. Firms specializing in low-end services should not
place emphasis on large price reductions (50%) to avoid discounting consumers’
perceptions of quality and further affect their purchase intentions.
Furthermore, in high-end services, at low discount levels (5%) consumers prefer
price reductions in percentage format rather than dollar format. Therefore, firms that
provide high-end services should consider small price reductions and offer price
29
reductions in percentage format. Interestingly, consumers perceive discount formats
differently in different industries. In the restaurant industry, consumers prefer
percentage-discount format for fine-dining restaurants and dollar-discount format for
QSR. In the hotel industry, consumers prefer dollar-discount format over percentage
format overall. In addition, in the restaurant industry, consumers prefer percentage format
for low discount level (5%) in fine-dining restaurants and prefer dollar format for low
discount level (5%) in QSR. In the hotel industry, consumers prefer percentage-discount
format for low discount level (5%) in high-end hotels and prefer dollar-discount format
for high-discount level (40% and 50%) in low-end hotels.
2.2 SALES PROMOTION: THE USAGE OF CURRENCY
The pricing literature is replete with research that focuses on how consumers
respond to sales promotions when both the reference level and the change are expressed
in dollar terms (Nunes and Park, 2003). Yet many everyday exchanges involve a variety
of resources other than money (Donnenworth and Foa, 1974; Nunes and Park, 2003;
Drèze and Nunes, 2004).
Nunes and Park (2003) proposed a concept of incommensurate resources
addressing those individual carriers of wealth or welfare that are difficult to convert into a
single currency or common unit of measurement. In many respects, the notion of
incommensurate resources resembles the concept of compatibility. Previous work on
scale-compatibility biases suggests that the specific nature of a response scale tends to
focus people’s attention on compatible features of a stimulus (Slovic, Griffin and Tversky
1990; Shafir 1995). When two resources are delivered simultaneously, but in different
30
currencies, the marginal value of the nonmonetary, incremental benefit may be difficult
to evaluate in relation to the focal product or its price. Therefore, the value of the
premium may be less likely than a comparable discount to be viewed in a relative sense
and thus less likely to suffer from diminishing marginal returns (Nunes and Park, 2003).
In their study, Nunes and Park examine how consumers evaluate outcomes that involve
different currencies. The results of their study demonstrate that two different resources
(i.e., dollars and miles), which independently were perceived as equivalent, have different
effects when included as an incremental cost based on the currency of the primary
expense. As a result, the study shows that incommensurate resources can affect the
perceived value of an incremental benefit and incremental cost.
In extending the Nunes and Park work, Drèze and Nunes (2004) examined
consumers’ responses for the combined-currency price (dollars and miles). They make a
clear statement that the consumer does not value each unit in a currency equally. In other
words, each mile or dollar spent is not valued equally; the disutility of paying more
dollars and/or miles increases as the payment in that currency increases. By defining a
superior price as either lowering the psychological cost to the customer associated with a
particular revenue objective by the firm or raising the amount of revenue that can be
collected given a particular psychological cost, Drèze and Nunes (2004) showed that both
an interior solution can exist such that consumers prefer a combined-currency price and a
corner solution can also exist in which a price in one of the currencies dominates. Their
study indicates that consumers prefer the combined-currency prices to charges issued in a
single currency for payments in the “relatively low total cost” conditions. This implies
that consumers’ valuation for dollars increases more quickly than for miles as the amount
31
to be spent increases. In addition, the preference to pay primarily in dollars is at the low
end, and the preference to pay primarily in miles is at the high end. In the middle range,
combined-currency prices are most widely favored. Consequently, the evidence in the
Drèze and Nunes study (2004) illustrates how people often prefer to pay prices that
comprise payments in more than one currency. It also shows that consumers may favor
single-currency price because as the payment becomes larger in one currency, the
perceived cost of tracking transactions in more than one currency could become more
challenging.
Currency Usage in Hospitality Industry
Inspired by the airlines' success, most major hotel chains have developed
frequent-guest programs that reward customers for repeat business (McCleary and
Weaver, 1991). These programs aim to enhance the customer's sense of membership in a
unique club with benefits from this membership (e.g. free hotel rooms and gifts). Initially,
the hotel frequency programs were added perks for guests to garner free room nights and
other benefits during stays. These programs serve as a currency exchange to amass airline
frequent-flyer miles, hotel points and other kinds of rewards (Tepeci, 1999).
In a survey of its HHonors members, Hilton hotels learned that 19 percent of them
would not stay at a Hilton without such a membership program. Marriott also reported
that its FGP members spent two and a half times more at Marriott than they did before
joining the program (Seacord, 1996). McCleary and Weaver (1992) found that business
travelers who belonged to FGPs were willing to pay more than nonmembers for a hotel
room and FGP members were more likely to bring their families along to stay in the hotel.
32
Since it relaunched its frequent-guest program in 1993, ITT Sheraton's Club International
has more than doubled its membership base from 725,000 members to nearly 2 million.
The currency of Sheraton's program was changed from points to ClubMiles redeemable
for stays at Sheraton properties, car rentals with Avis, or frequent-flyer miles with its
eight airline partners. In addition, members visiting Sheraton's hotels in Las Vegas and
Tunica County can try the luck of the dice by exchanging ClubMiles for gaming chips.
Some chains offer more unusual rewards. Club Express, the frequent-guest program of
Renaissance Hotels and Resorts, allows its members to earn U.S. Savings Bonds.
Travelodge's Guest Rewards members garner long-distance calling cards for limited free
calling. Hyatt Hotels Corp.'s Gold Passport's program features check-cashing privileges.
The program's top award is a 10-night "Dreamscape" vacation, which includes airline
tickets for two, car rental and meals at any Hyatt hotel and resort (Bond, 1995). Table 1
presents a list of popular hotel rewards programs.
Continued
Table 2.1: Summary of Hotel Rewards Programs
Rewards Program Hotel
Best Western Gold Crown Club Best Western chain of hotels
Hilton HHonors
Hilton, Conrad DoubleTree Embassy Suites Hampton Inn Hilton Garden Inn Homewood Suites Scandic Hotels
33
Table 2.1 Continued
Howard Johnson SuperMiles
Howard Johnson chain of
hotels
Hyatt Gold Passport
Hyatt chain of hotels
Marriott Rewards
Marriott Hotels Resorts and Suites Courtyard by Marriott Fairfield Inn by Marriott Renaissance Hotels Resorts and Suites Marriott Conference Centers SpringHill Suites by Marriott Residence Inn TownePlace Suites by
Marriot
Priority Club
Inter-Continental Hotels and Resorts
Crowne Plaza Hotels and Resorts
Holiday Inn Holiday Inn Express Staybridge Suites
Starwood Preferred Guest
Westin Sheraton Four Points by Sheraton The Luxury Collection St. Regis and W Hotels
Travelodge Miles
Travelodge Travelodge Hotels Travelodge Inn Travelodge Suites and
Thriftlodge
Radisson Gold Rewards
Radisson Hotels worldwide
Wyndham by Request
Wyndham Hotels and Resorts
34
Although various novel currencies have been introduced and applied in the hotel
industry, restaurant business has not commonly used any currency other than money. In
the restaurant industry, the type of restaurant can be categorized into three segments
based on the level of service and the menu prices. According to the National Restaurant
Association, restaurants are categorized as: (1) high-end, fine-dining restaurants with
menu prices of $25 or higher; (2) mid-price, casual-dining restaurants with menu prices
ranging from $6 to $24; (3) quick-service restaurants (QSRs) with menu prices of $5 or
under. Based on the findings of Drèze and Nuness’ study (2004), consumers prefer one
currency price over another based on the amount of payment. The evidence in their study
indicates that the preference to pay primarily in dollars is at the low end, and the
preference to pay primarily in points is at the high end (miles are a type of
frequency-marketing device that could more generally be referred to as “points”);
however, in the middle range, combined-currency prices are most widely favored.
Although the distinctions in the menu prices of three restaurant segments are not
significant, the preference of currency usage may still be affected by different restaurant
segments. Thus, the next hypotheses:
H1: While dining out, consumers are more likely to pay with (a) single currency –
points- only – at high-end restaurants, (b) combined-currency – dollars and
points – at mid-priced restaurants, and (c) single currency – dollars- only – at
low price restaurants.
35
2.3 PERSONALITY TRAITS
The preferences of currency usage may be influenced not only by external but also
by internal factors such as personality traits of consumers. Interest in the relationship of
personality variables and consumer behavior has existed since the importance of
marketing was first recognized. Although the term “personality” has different meanings
to different people, one definition is that of a set of characteristics or traits that are
relatively enduring and differentiate one person from another (Guilford, 1959). An
advantage of the trait approach to personality is that traits can be objectively measured
with standard psychometric instruments and the resulting scores used to uncover
trait-performance relationships. Consumer behaviorists have attempted to link personality
traits and market behavior for the last 40 years on the assumption that this knowledge
would be useful in devising marketing strategy. This effort has often produced equivocal
results (Kassarjian and Sheffet, 1991). Some studies find strong relationships, some weak
ones, and some none at all.
Two personality variables have been used in the context of theoretical frameworks
and seem to offer a great deal of promise in understanding consumer behavior (Haugtvedt,
Petty, and Cacioppo, 1992). These personality variables – need for cognition (Cacioppo
and Petty, 1982) and self-monitoring (Snyder, 1974) – are useful for understanding
consumer behavior because they are closely linked with many theoretical frameworks.
36
Need for Cognition
Need-for-cognition is a well established and often-used individual-difference
construct investigated in over 100 empirical studies (Cacioppo et al., 1996). Need for
cognition refers to an individual’s tendency to engage in and enjoy effortful cognitive
endeavors (Cacioppo and Petty, 1982). The notion of such a disposition was first
researched by Cohen, Scotland, and Wolfe (1955), who suggested that individuals
differed in their “need to understand and make reasonable the experiential world” and
called this individual difference the need for cognition. Murphy (1947) described a
similar tendency as characterizing “thinkers,” for whom he suggested it was “fun to
think”. Research on need for cognition suggests that this characteristic is predictive of the
manner in which people deal with tasks and social information. Differences in need for
cognition represent differences in people’s chronic tendencies to engage in and enjoy
effortful thinking. Thus, the kinds of effects associated with need for cognition should
generally mirror the kinds of effects found for situational factors influencing motivation
to think (Cacioppo and Petty, 1982). Need for cognition is not conceptualized as a level
of intellectual ability, but rather as a relative proclivity to process information (Cacioppo
et al., 1996).
The need-for-cognition scale was formally developed and validated by Cacioppo
and Petty (1982), who suggested that it “taps individuals’ tendency to organize, abstract
and evaluate information”. Cacioppo and Petty (1982) argued that individuals who
possess high need for cognition are more highly motivated to think about the given
information than individuals with low need for cognition. In other words, individuals
with high need for cognition are viewed as cognitive spenders, report greater enjoyment
37
of complex tasks (Cacioppo and Petty, 1982, 1984) and are less likely to reduce their
efforts on cognitive tasks in situations where reduction of effort typically occurs (Petty et
al., 1985). Cognitive spenders have more dimensions available to interpret the
environment, are better able to process the large amounts of information conveyed in an
informationally complex message, and are less likely to suffer from information overload
than cognitive misers (Malhotra 1982). Also, in general, cognitive spenders are more
curious, enjoy mental activities, seek out additional stimulus information, differentiate
between strong and weak arguments, and recall more information from an event. In
contrast to cognitive spenders, low need-for-cognition individuals are viewed as cognitive
misers (Taylor, 1981), and they dislike effortful cognitive activities. Such individuals
prefer simple over complex tasks. Cognitive misers are likely to perform effortful
cognitive actions only when such actions are necessary for obtaining desired extrinsic
rewards (Cacioppo and Petty, 1984). In addition, cognitive misers are not characterized
as unable to differentiate cogent from hollow arguments, but rather they typically prefer
to avoid the effortful, cognitive work required to derive their attitudes based on the merits
of arguments presented (Haugtvedt, Petty, and Cacioppo, 1992).
Need for Cognition and Consumer Reactions to Price Promotions
In addition to its frequent use in psychological domains, need for cognition has
been applied in several consumer-behavior studies. Imman, Macalister, and Hoyer (1990)
were the first to examine the relationship between need for cognition and consumers’
reactions to promotion signals. The results of their study demonstrated that for cognitive
misers, promotion signal alone represents a sufficiently significant change in the choice
38
condition to induce a shift in choice behavior toward the promoted brand. For cognitive
spenders, however, a concomitant price cue is needed. This implies that cognitive misers
might employ less complex decision rules or heuristics than do cognitive spenders.
Moreover, Inman, Peter, and Raghubir (1997) examined whether an individual’s need for
cognition moderates the purchase-limit restriction effect. Consumers use restrictions as a
source of information to help them assess a promotion’s value. Folger (1992) suggested
that unavailability functions as a signal regarding the good, thereby making the good
more salient. Similarly, a restriction may act as a heuristic cue that signals deal value
(Inman, McAlister, and Hoyer, 1990) and may prompt consumers to allocate resources to
assess the offer. The results of their study indicated that promoting a brand with
restriction yields an increase in likelihood of purchase for cognitive misers, while
cognitive spenders are unaffected by a restriction. Restrictions appear to have a greater
influence on individuals who have a lower intrinsic preference of the cognitive demands
imposed by information processing.
Chatterjee and Basuroy (1998) investigated the role of need for cognition on
consumers’ reactions to price-matching offers. Cognitive misers are unlikely to devote
much thought to any situation. Hence they are more prone to use price-matching signals
as a heuristic to simplify choice. Cognitive spenders, on the other hand, are more likely to
consider both the competition as well as the collusion aspects of price-matching offers,
and base their choice on more substantive cues. Whereas cognitive spenders are
persuaded by price reduction, cognitive misers are persuaded by discount signals even
when the price of the promoted brands is not actually reduced (Imman, Macalister, and
Hoyer, 1990; Inman, Peter, and Raghubir, 1997). Burman and Biswas (2004) examined
39
the influence of need for cognition on consumer processing of reference prices. Their
study suggested that the cognitive spenders scrutinize the information more and therefore
enter the correction stage to either reject or discount an implausible reference price. On
the other hand, cognitive misers remain in the characterization stage due to their lack of
motivation to assess the information thoroughly and therefore will be more vulnerable to
implausible reference price claims. Hence, cognitive spenders respond favorably to the
plausible high reference-price condition as the savings are higher than in the plausible
low reference-price condition, but reflect greater discernment in the implausible reference
price condition and either disregard the price completely or discount it before making a
decision. Conversely, the attractiveness of the offer to the cognitive misers increases as
the reference price increases, and therefore the implausible reference price will be highly
effective simply because it indicates large savings.
Extending the preceding literature, one can state that currency usage is affected by
the need for cognition. Combined-currency price (e.g., dollars and points) requires
individuals to evaluate the value of each in a currency independently. When comparing
the combined currency to the single currency, individuals need to devote more thought to
combined-currency price than to a single-currency situation. Since need for cognition
appears to be a primary individual-difference variable identified as influencing
motivation to think, need for cognition should also influence individuals’ preference of
currency usage. Cognitive spenders are more likely to engage in and enjoy effortful
cognitive endeavors and prefer complex tasks over simple tasks. Hence, cognitive
spenders may prefer the combined currency compared to cognitive misers. Although
cognitive misers prefer simple to complex tasks, they are likely to perform effortful
40
cognitive actions only when such actions are necessary for obtaining desired extrinsic
rewards (Cacioppo and Petty, 1984). Average consumption by consumers is high at
high-end restaurants (as measured by the average guest check average), compared to the
spending at quick-service restaurants. Thus, cognitive spenders may prefer to use
combined currency at high-end restaurant to maximize their savings. To avoid the
complexity of dealing with two or more currencies, cognitive misers, in contrast, are most
likely to pay with a single currency while visiting restaurants of their choice. The choice
for mode of payment could also be affected by the type of restaurant since guest check
average differs significantly among the three types of restaurants.
H2: While dining out, consumers with a high need for cognition are more likely to
prefer payment with combined currency than cognitive misers.
H3: While dining out, currency preferences of consumers with high and low need for
cognition are affected by the type of restaurant (high, mid and low priced).
Self-Monitoring
Since the time that Snyder (1974) developed the construct of self-monitoring, it has
been one of the most frequently employed individual-difference measures in the field of
personality and social psychology. The self-monitoring construct seems particularly
useful, because this trait reflects the degree to which individuals are influenced by
internal versus external cues. According to Snyder (1979, 1987), people differ in the
extent to which their behavior is susceptible to situational or interpersonal cues, as
opposed to inner states or dispositions. Individuals can be classified into two groups with
regard to their level of self-monitoring. Low self-monitoring individuals are especially
41
sensitive and responsive to inner dealings, attitudes, and beliefs. They view their behavior
to be influenced primarily by internal cues, such as personal beliefs and values. The
behaviors of low self-monitors reflect their feelings and attitudes without regard to
situational or interpersonal consequences of those behaviors (Snyder, 1979; Ajzen et. al.,
1982). Low self-monitors are conceived as thinking of themselves as “rather principled
beings” whose behavior flows from internal affective and personality dispositions and
who lack either the social skills or the perceptual sensitivity (or both) to mold their
behavior to situational demands (Snyder and Kendzierski, 1982).
In contrast, high self-monitors are much less sensitive to internal beliefs and values.
Instead, they view their behaviors as stemming primarily form a pragmatic view of what
external, situational cues define as socially appropriate action (Snyder, 1974). High
self-monitors are seen as being sensitive to cues as to the proper self-presentation in a
given situation and are highly capable of translating these perceptions into normatively
appropriate behavior. Thus, as originally conjectured by Snyder, at the fundamental core
of self-monitoring is unidimensional continuum ranging from a primary concern with
external sources of identity to an orientation toward internal sources of identity.
Studies of self-monitoring show that anticipated future interaction induce the
“situationally guided” high self-monitors to become even more attentive to situational
cues when deciding how to act while prompting low self-monitors to rely even less on
situational cues and more on personal thoughts and evaluations. Because high
self-monitors are easily deflected by situational influences and behave in anticipation of
consequences, their behaviors are likely to be inconsistent with their previous attitudes. In
contrast, low self-monitors, whose behaviors reflect their feelings and attitudes without
42
regard to situational or interpersonal consequences, could be expected to exhibit
substantial attitude-behavior correspondence (Shaffer, Ogden, and Wu, 1987). Moreover,
high self-monitors can be likened to consummate social pragmatists, willing and able to
project images designed to impress others. They seem to believe in the appearances they
create and to take stock in the fact that these appearances can and do become social
realities. By contrast, low self-monitors seem not only unwilling but also unable to carry
off appearances. They live as if put-on images are falsehoods, as if only those public
displays true to the privately experienced self are principled (Gangestad and Snyder,
2000).
Self-monitoring was first defined by Snyder (1974), who also developed a scale to
measure the construct. Items were chosen in the scale to describe (a) concern with social
appropriateness of one’s self-presentation, (b) attention to social comparison information
as cues to appropriate self-expression, (c) the ability to control and modify one’s
presentation and expressive behavior, (d) the use of this ability in particular situations,
and (e) the extent to which the respondent’s expressive behavior and self-presentation is
cross-situationally consistent or variable (Snyder, 1974). Studies on self-monitoring have
used multi-item self-report measures to identify people high and low in self-monitoring.
The most frequently used instruments are the 25-item, true-false, original
Self-Monitoring Scale (Snyder, 1974) and an 18-item refinement of this measure
(Gangestad and Snyder, 1985; Snyder and Gangestad, 1986). Although multiple content
domains are represented in these measures, expressive control figures prominently.
Indeed, a Self-Monitoring Scale item with one of the highest item-total correlations is “I
would probably make a good actor.” By any criterion, the theory of self-monitoring has
43
been a generative one. The self-monitoring construct has captured the interest of social
psychologists and personologists alike. Empirical tests of hypotheses spawned by
self-monitoring theory have accumulated into a very sizable literature. Several hundred
articles on self-monitoring have appeared since its inception, prompting claims that it “is
an important construct that promises social psychologists much in the way of explanatory
leverage” (Lennox and Wolfe, 1984) and that the Self-Monitoring Scale “is one of the
most popular measures to be introduced in recent years” (Briggs and Cheek, 1988).
Self-Monitoring and Consumer Behavior
There is a substantial body of empirical work on the link between self-monitoring
and consumer behavior (DeBono, 2000). Numerous studies indicate that the
self-monitoring construct appears reliably to identify individuals whose attitudes serve
either predominantly social-adjustive or value-expressive functions (DeBono, 1987;
Kristiansen and Zanna, 1991; Bazzini and Shaffer, 1995). As such, it represents a
valuable vehicle for examining questions related to attitude functions. High self-monitors,
as identified by their relatively high score on the self-monitoring scale (Snyder and
Grangestad, 1986), typically try to be the kind of person called for in each situation in
which they find themselves. They tend to be concerned about the image they project to
others in social situations, and they are generally adept at adjusting their
self-presentations to fit differing social and interpersonal considerations of
44
appropriateness. As a consequence of this orientation, high self-monitors often display
marked situational shifts in the images they project to others. In addition, they tend to
judge a product’s quality higher if it is advertised with an image orientation (DeBono and
Packer, 1991).
Low self-monitors, on the other hand, tend to be influenced by advertisements that
stress the performance of the product, in particular the extent to which it operates as
products of that type should. Such “hard-sell” advertisements often highlight the
durability of a product, the high quality of the material or ingredients in the product or, in
case of food products, the good taste of that product. Unlike their highly self-monitoring
counterparts, low self-monitors think more highly of these types of advertisements, are
wiling to pay more for products so advertised, and are more likely to try a product that is
marketed with a hard-sell approach (Snyder and DeBono, 1985). In addition, low
self-monitors rate the quality of products advertised with a quality orientation more
favorably than they would if these same products advertised with more of an image
orientation (DeBono and Packer, 1991). It appears then that low self-monitors’ concerns
with the consistency between what they purport to be and what they actually do is
paralleled by a concern with the consistency between what a product purports to be and
what it actually does. Empirical evidence has shown that high self-monitoring individuals
prefer brands in congruence with social situations while self-image congruence and
utilitarianism dominate the brand preference of low self-monitors (DeBono, 2000; Hogg,
45
Cox and Keeling, 2000). Also, high self-monitors respond more favorably to
status-oriented advertising claims while low self-monitors are more sensitive to the
quality and functional performance of products (Shavitt, Lowrey and Han, 1992; DeBono,
2000).
Shavitt et al. (1992) showed that high self-monitors tended to select social-identity
terms when describing products that could serve social purposes. When creating copy for
multiple-use products, high self-monitors gave social arguments for product purchase
(e.g., the product will make you look better), whereas low self-monitors preferred
utilitarian ones (e.g., the product will work better). Snyder (1987) has suggested that
self-monitoring affects consumer behavior because it is associated with interest in
maintaining a front through the use of props that convey an image of the self to other
people. This interest lends a chameleon-like quality to the high self-monitor who may
appear to be different people in different situations. High self-monitors, more than low
self-monitors, appear to be concerned with physical appearance and body image (Snyder
et al., 1985; Sullivan and Harnish, 1990), are aware of the messages that clothing and
other personal effects send, and can report behaviors that would produce certain
impressions (Snyder and Cantor, 1980). For example, clothing is often used for its
symbolic value (Solomon, 1983) and high self-monitors may be adept at manipulating
self-presentation through clothing. Some research shows that high self-monitoring
females are more likely than their low self-monitoring counterparts to be opinion leaders
in clothing selection and to use clothing to attain social approval (Davis and Lennon,
1985). Theoretically, these clothing choices would be driven by the item’s usefulness in
conveying messages appropriate for different social situations rather than being an
46
expression of private attitudes and feelings. The high self-monitor, more than low
self-monitor, could be expected to be able to describe what to do and wear to assume a
role that is different from the roles he or she usually plays.
Moreover, product and brand choice may reflect differences in concerns for
prestige and appearance among high and low self-monitors. Snyder (1987) reports that,
when high self-monitors were asked to judge the quality of either a sporty Pontiac Fiero
or a boxy Volkswagen Rabbit on the basis of car test report and photographs, they gave
more favorable quality ratings to the sporty car. Low self-monitors favored the functional
Volkswagen and seemed to believe that a flashy appearance could mask hidden flaws. In
addition, they tended to believe that generic products were as good as name-brand
products. Becherer and Richard (1978) indicated that self-monitoring acts as a
moderating variable that increases the ability of personality traits to predict brand choice.
The strongest moderating effect appeared among low self-monitors. The low
self-monitors’ personality traits, measured with a standard personality test (the California
Personality Inventory), predicted brand choice better than did high self-monitors’ traits.
These results were interpreted in the light of the low self-monitor’s tendency to remain
true to his or her internal self-image and not to exhibit situationally variable behavior to
the same degree as a high self-monitor.
Individuals’ preferences of payments (currency usage) may also be influenced by
self-monitoring. High self-monitors view their behaviors as stemming primarily from a
pragmatic view of what external and situational cues define as socially appropriate action
and use these cues as guidelines for monitoring their own verbal and nonverbal self
presentation (Snyder, 1979). Since combined-currency price is a signal of price discount,
47
high self-monitors may be less likely to use it. In contrast, high self-monitoring
individuals may be more likely to choose single currency to show their social status.
Even the nonmonetary currencies such as points or miles are a form of promotions; on
the other hand, they also deliver the images of loyal customers who are highly valued by
the organization. Hence, high self-monitors may prefer to use the single currency
compared to low self-monitors.
H4: While dining out, high self-monitoring consumers are more likely to pay with a
single currency than low self-monitoring consumers.
Impression Management
There are numerous ways in which to define impression management, yet at the
center of any of these is the recognition that people’s comprehension of a phenomenon
can be directed by others and their attempts to frame one’s perception (Fisk and Grove,
1996). Impression management refers to the process by which individuals attempt to
control the impressions others form of them. Because the impressions people make on
others have implications for how others perceive, evaluate, and treat them, as well as for
their own views of themselves, people sometimes behave in ways that will create certain
impressions in others’ eyes (Leary and Kowalski, 1990). Schlenker (1980) identifies
impression management as “the conscious or unconscious attempt to control images that
are real or imagined in social interactions”. Tedeschi (1981) stated that what people do
and say frequently represents attempts to create desired impressions on others. People are
fairly sensitive to the social significance of their conduct and behaviors and are motivated
to create desirable social identities in their interpersonal encounters (Tetlock and Mansted,
48
1985). Baumeister (1995) postulated that the self is an interpersonal tool; hence, people
become concerned with managing the impressions they create on others and fashion a
self that will bring them social approval and acceptance. Tedlock and Mansted, (1985)
conjectured that examples of impression management and strategic self-presentation are
ubiquitous in our society and range from our social gatherings and the cars we drive to
even the clothing we wear.
Ratner and Kahn (2002) indicated that individuals incorporate more variety in
hedonic choices (in food contexts in the present studies) to make a favorable impression
on others. Impression-management concerns lead people to choose variety: specifically,
they choose variety because they think it will convey a favorable image to others.
Moreover, previous research (Zimbardo, 1970; Diener,1980) has shown that individuals
adhere more to social norms about what constitutes appropriate behavior when their
behavior is identifiable than when it is anonymous. In laboratory experiments,
participants wearing name tags, who are referred to repeatedly by name, reveal personal
information about themselves to other participants, or have their behaviors known to the
other participants engage in more socially desirable behaviors. When anonymous,
people’s inhibitions against performing deviant behaviors are relaxed. Outside of the lab,
consumers have also been shown to act in more socially desirable ways when those
behaviors are identifiable rather than anonymous. For example, in one naturalistic study,
young consumers were more likely to steal Halloween candies when they were
anonymous than when they provided individuating information (Diener, et al., 1976).
49
Research on reference-group influences suggests that a crucial factor that
influences the salience of impression management concerns the nature of the salient
reference group (such as dining company). Bearden & Etzel (1982) found that consumer
purchases are not only a result of personal decision, but also an interaction of influence of
reference groups. These authors reported that the conspicuousness of a product is
positively related to its susceptibility to reference-group evaluation. Also, an individual’s
self-esteem can be enhanced through ownership and consumption of products typically
associated with an admired person or group or what we refer to as the aspiration group. In
a restaurant context, Stayman and Deshpande (1989) found that consumers’ menu
choices were affected by their dining companions, with menu items consistent with the
diner’s ethnic background more likely to be selected when dining with parents than with
business associates. Similarly, consumer preferences for currency usage may be affected
by the diner’s expectations of the attributions of those with whom s/he is dining; i.e., is
the use of “points” viewed as the mark of a “cheap” or a “smart” diner.
When points (either solely or in combination with dollar) are a signal of price
discount, paying with points may be viewed as a indicating that the diner is “cheap” when
dining with a higher-status recipient (e.g., boss). On the other hand, while dining with an
equal-status companion (e.g., friend), points (either solely or in combination with dollar)
may contribute to the conveyance of the impression of a “smart” diner who gets the most
for his/her money. When dining alone, impression management, which is relevant only in
a social-relations context, becomes unnecessary; the diner’s individual financial
motivations would face no competition from social demands, leaving him or her free to
reap the financial rewards of paying with points without regard to the impression it may
50
create. Hence, consumers may be less likely to pay with points (either solely or in
combination with dollar) while dining with a higher-status recipient than while dining
with an equal-status companion or alone.
H5: While dining out, currency preferences are affected by the dining context, such
that payment is more likely to occur with (a) dollars-only when dining with a
higher-status companion and (b) points-only when dining with an equal-status
companion or when dining alone.
Self-Monitoring and Impression Management
There are individual differences in the extent to which people are willing to adapt
their behavior to fit situational demands (e.g., Snyder 1987; Bearden, Netemeyer, and
Teel 1989). Snyder’s (1979) review of the literature reveals support for many predicted
differences between low and high scorers on the self-monitoring scale. In comparison to
low scorers, high scorers are more likely to adapt their behavior to the normative
requirements of particular situations, more likely to seek out information on what others
consider appropriate behavior, and less likely to rely on internalized standards as guides
to behavior. Overall, the behavior of high self-monitors appears to be primarily under the
control of impression-management concerns. This evidence suggests that the
self-monitoring variable should be useful in assessing the comparative validity of
impression management. Those effects mediated by impression management processes
should occur much more strongly among high self-monitors (Tetlock and Manstead,
1985).
51
Ratner and Kahn (2002) provided empirical support for the proposition that
individuals sometimes switch away from their favorites in order to make a favorable
impression on others. The finding indicated that the public/private difference is driven by
people’s desire to be evaluated favorably by others: an individual difference in desire to
alter one’s behavior to fit social situation influenced levels of variety seeking in predicted
ways, such that high-self monitors choose more variety than low-self monitors when
trying to make others think they made an interesting (rather than a rational) decision.
High self- monitors may seek variety in public to convey an image to others that they are
interesting and creative people. Low self- monitors, on the other hand, should be less
willing to change their behaviors simply to please or entertain others. However, if low
self- monitors are induced in public to make a thoughtful, rational decision, and they
believe that choosing to incorporate a varied set is a rational decision, they may be
induced to choose variety in public. Hence, if consumers feel pressure to choose variety
in public, then people will likely observe considerable variety in the consumer choices
made by others (Ratner and Kahn, 2002).
Njite and Parsa (2004) investigated the moderating role of self-monitoring on price
misrepresentation. The results of their study show that it is possible for individuals to
misrepresent price and purchase information in order to create favorable impressions
upon others. High self-monitoring individuals tended to misrepresent the information
more than low self-monitoring individuals. A deliberate concealment of a discount should
contribute to the conveyance of the impression of higher prestige, hence acceptance
within a desired perceived higher-status referent group. Due to their characteristics on the
self-monitoring scale, it is predicted that the high self-monitoring consumers are more
52
likely to conceal having purchased a product at a discount. However, the
misrepresentation is greater when communicating with a higher-status recipient as
compared to an equal-status group. Misrepresentation enables the communicator to be
identified more positively, having a prestige, and therefore to be affiliate with an aspired
higher-status group (Sengupta, et. al., 2002). On the other hand, low self-monitors are
less likely to conceal having purchased a product at a discount whether communicating
with a higher-status recipient or equal-status group.
Self-monitoring may yield different effects for different types of companions (e.g.,
friends and family versus someone the diner wants to impress like a date or the boss).
Since the effects mediated by impression-management processes should occur much
more strongly among high self-monitors, high self-monitors may be concerned that a
higher-status dining companion (e.g., boss) would perceive use of points (either solely or
in combination with dollars) as “cheap.” In contrast, there would be no basis for such an
effect to emerge if the diner were a low self-monitor or is s/he were dining alone:
H6: While dining out, currency preferences across dining contexts are moderated by
self-monitoring, such that high self-monitors are more likely than low
self-monitors to pay with dollars-only when dining with a high-status
companion.
Since points (either solely or in combination with dollars) could be a signal of price
discount, use of points at high-end restaurants may be viewed as a “smart” choice by
some, whereas use of points at quick-service restaurants may be viewed as a “cheap”
option. Since the guest average check at high-end restaurants is higher, paying with
points could save much more. Thus, points may be viewed as a “smart” choice at
53
high-end restaurants. However, at quick-service restaurants the average guest check is
much lower; paying with points may save only a few dollars. Therefore, points may be
considered as “cheap” option at quick-service restaurants. According to Snyder (1979),
high self-monitors view their behaviors as stemming primarily from a pragmatic view of
what external and situational cues define as socially appropriate action and use these cues
as guidelines for monitoring their own verbal and nonverbal self presentation. High
self-monitors may be concerned that use of points (either solely or in combination with
dollars) would be perceived as “smart” at high-end restaurants, whereas use of points
would be perceived as “cheap” at quick-service restaurants. However, there would be no
basis for such an effect to emerge for low self-monitors. Alternatively, restaurant type
may have an opposite effect. A high self-monitor at a fine-dining establishment may not
want to dilute the impression that s/he is sparing no cost to entertain a high-status
companion by paying with points. Taking such a person to a QSR, on the other hand,
may eliminate the possibility of any such impression from the moment the party enters a
QSR unit. Any “impression” from such a choice would focus more on efficient use of
time (e.g., a quick bite to eat and then back to work). Payment by points may be further
evidence of efficiency (efficient use of monetary resources). Which (if either) of these
outcomes may arise is an empirical question. In either case, the effects of self-monitoring
on currency preference may be moderated by the restaurant segments. Rather than stating
competing predictions, H7 takes the form of a non-directional moderating prediction:
H7: While dining out, currency preferences of high- and low-self-monitoring
consumers are affected by the type of restaurant (high, mid and low priced).
54
2.4 Conceptual Model
Figure 2.1 presents a proposed model, focused mainly on consumers’ currency
preferences. The proposed model incorporates the key variables discussed above such as
personality traits (need for cognition and self-monitoring), restaurant segments, and
dining companions. The present study retains the following hypotheses in the proposed
model. This study hypothesizes that restaurant segments affect consumers’ currency
preferences directly. Moreover, need for cognition has direct impact on currency
preference, and this relationship is also affected by restaurant segments. Furthermore,
self-monitoring also has direct impact on currency preference, and this relationship is
influenced by restaurant segments and dining companions.
55
Figure 2.1: The Effects of Need for Cognition, Self-Monitoring, Dining Companion, and Restaurant Segment on the Choice of Currency in the Restaurant Industry
Currency - $ - $ + Points - Points
Self-Monitoring - High - Low
H7
H1
H4
H2 H3
Need for Cognition - High - Low
Dining Companion - Boss - Friend - Alone
H5
H6
Restaurant Segment - High-end - Mid-price - QSR
55
56
Chapter Summary
This chapter provides an in-depth literature review on the concept and theory of
sales promotion from a consumer perspective, and discusses a specific type of sales
promotion – the usage of currency – and its relationship with consumer behaviors and
applications. Finally, it addresses the theoretical development of the personality traits and
consumer preferences for currency usage. Based on the theory and related research, seven
hypotheses were offered in the study. The experimental and statistical methods used to
test the hypotheses are presented in the next chapter.
Restaurant Types and Preference for Currency Usage:
H1: While dining out, consumers are more likely to pay with (a) single currency –
points - at high-end restaurants, (b) combined-currency- dollars and points –
at mid-priced restaurants, and (c) single currency – dollars - at low price
restaurants.
Personality Types and Preference for Currency Usage:
Need for Cognition:
H2: While dining out, consumers with a high need for cognition are more likely to
prefer payment with combined currency than cognitive misers.
H3: While dining out, currency preferences of consumers with high or low need for
cognition are affected by the type of restaurant (high, mid and low priced).
Self-Monitoring:
H4: While dining out, high self-monitoring consumers are more likely to pay with a
single currency than low self-monitoring consumers.
57
H5: While dining out, currency preferences are affected by the dining context, such
that payment is more likely to occur with (a) dollars-only when dining with a
higher-status companion and (b) points-only when dining with an equal-status
companion or when dining alone.
H6: While dining out, currency preferences across dining contexts are moderated by
self-monitoring, such that high self-monitors are more likely than low
self-monitors to pay with dollars-only when dining with a high-status
companion.
H7: While dining out, currency preferences of high and low self-monitoring
consumers are affected by the type of restaurant (high, mid and low priced).
58
CHAPTER 3
METHODOLOGY
This study was designed to explore the relationship between individual differences
(personality traits), restaurant segments, and consumers’ preference for currency usage. A
purpose of this study was to examine the effect of personality traits – need for cognition
and self-monitoring – on consumers’ preference for currency usage. The second purpose
of the study was to determine whether differences in restaurant segments were related to
consumers’ currency preferences. The chosen two experimental designs involve
measuring the dependent variable (currency preference) and blocking variables (need for
cognition and self-monitoring) and randomly assigning subjects to the independent
variables (restaurant type and dining context). Seven hypotheses are formulated to test
the research question, whether individual differences and restaurant segments would
influence consumers’ preference of the currency usage.
Experimental Design
The experimental method was chosen for this study because an experimental
design permits the inference of causation and allows the researcher to make a small
number of observations, but infer facts that would normally require an exhaustive set of
59
observations. Subjects are treated identically, except for the features that are different.
Thus observed differences in behavior can be unambiguously attributed to critical
differences among treatment conditions (Campbell and Stanley, 1963; Keppel, 1991).
Also, careful design helps the researcher to maximize the information gleaned from a
given number of experiments and minimize the number of studies required to validate (or
invalidate) a hypothesis. Although the survey method provides broad portraits of large
groups and large amounts of data at low cost, it is not able to test cause-and-effect
relationships. However, experiment design provides enough control to test cause/effect
relationships between variables by manipulating the independent variables and observing
the effect of the manipulation on the dependent variables (Keppel, 1991).
In order to examine the effect of personality traits and restaurant segments on
consumers’ preference for the currency usage, need for cognition (high vs low) and
self-monitoring (high vs. low) served as measured variables, with restaurant segments
(fine dining/causal dining/quick service restaurants) and dining context (boss/friend/alone)
as manipulated variables. Two 2 x 3 x 3 between-subject experimental designs are chosen:
(a). 2 Need for Cognition x 3 restaurant segments x 3 dining contexts and (b). 2
Self-Monitoring x 3 restaurant segments x 3 dining contexts, as depicted in the following
table:
60
Independent Variable Restaurant Segment Dining Companion
High Need for Cognition Fine-Dining Restaurant Boss Friend
Alone
Casual-Dining Restaurant Boss
Friend
Alone
Quick Service Restaurant Boss
Friend
Alone
Low Need for Cognition Fine-Dining Restaurant Boss Friend
Alone
Casual-Dining Restaurant Boss
Friend
Alone
Quick Service Restaurant Boss
Friend
Alone
High Self-Monitoring Fine-Dining Restaurant Boss Friend
Alone
Casual-Dining Restaurant Boss
Friend
Alone
Quick Service Restaurant Boss
Friend
Alone
Continued
Table3.1: Experimental Design to Assess Consumer Preferences for Currency Usage
61
Table 3.1 Continued
Independent Variable Restaurant Segment Dining Companion
Low Self-Monitoring Fine-Dining Restaurant Boss Friend
Alone
Casual-Dining Restaurant Boss
Friend
Alone
Quick Service Restaurant Boss
Friend
Alone
The Sample Frame
Population
The population targeted for this study was individuals over 18 years of age who
have experience with fine-dining, casual-dining, and quick-service restaurants. Students
in The Ohio State University were selected to represent the targeted population.
Sampling
The experiment employed a between-subjects design. It involved four independent
variables (need for cognition, self-monitoring, restaurant segment, and dining context)
and one dependent variable with three categories (dollars-only, dollars and points, and
points-only). According to Hosmer and Lemeshow (2000), the minimum number of cases
needed per independent variable is 10. Thus, the minimum number of subjects is180 ({2
x 3 x 3} x 10 = 180). In the present case, a convenience sample of 471 subjects was
selected from the target population, which exceeds the minimum requirements per cell. It
62
is a convenience sample and limitations of non-probabilistic sampling apply here. Also,
since the current study is more focused on tapping the basic psychological processes than
generalizations, a student sample is appropriate (Grewal, et al., 2000).
Data Collection
Several undergraduate classes offered at different class times during spring 2005
were used to collect the partial responses. The researcher's being physically present
during data collection offers many advantages: the researcher is better able to explain the
study, answer any questions immediately, administer the study protocol under controlled
conditions, and ensure that missing data are minimized. Another strategy of data
collection involved the use of “snowball” samples that rely on referrals from initial
subjects to generate more subjects and attempt to capture respondents who share
particular characteristics by asking those who meet the eligibility criteria to suggest
friends or neighbors who do as well (Atkinson and Flint, 2001). The defining feature of a
snowball sample is that it gathers individuals into a sample who have some acquaintance
with those who are already participating in the process.
Experimental Procedures
This study was conducted during class time starting at the beginning of the class.
Different undergraduate classes at different class time during an academic term were used
to collect responses over a period of two weeks. Direct administration was used in this
study for students enrolled in particular classes. The questionnaires were filled out in
class rooms with the researchers as the proctors. In phase I, all respondents were expected
63
to complete Snyder and Grangestad’s (1986) Self-Monitoring Scale and Cacioppo, Petty,
and Kao’s (1984) Need for Cognition Scale. Respondents were also required to answer a
series of questions related to their prior experiences in different currencies and
demographic information. In phase II, participants were asked to complete a
scenario-based, paper-and-pencil study in which they were asked to imagine that they
were paying for dinner with either dollars, reward points or the combination of two of
them. They were told to read a scenario in their booklet and to proceed through the
questions that follow at their own pace. Participants were subsequently instructed to
assume that they possess enough points and money to accommodate whichever pricing
option they prefer. Immediately following their reading of the presented scenario,
participants were asked to indicate on semantic-differential scales their preferences for
each of the three currencies (dollars-only, dollars and points, and points-only).
INSTRUMENTATION
Independent Variables
Need for Cognition
The Need for Cognition Scale (NCS), containing 18 statements on a five-point
scale, was used to measure the need for cognition measuring the tendency to engage in
and enjoy effortful cognitive activity (Cacioppo, Petty, and Kao, 1984). Need for
Cognition has been considered to be a rather stable individual difference that would
motivate individuals to elaborate issue-relevant arguments, regardless of topic or
situation. Cacioppo and Petty (1982) developed the Need for Cognition Scale by
generating a pool of opinion statements that appeared relevant to the hypothetical
64
construct. After removing ambiguous scale items, the remaining 45 items were tested on
groups assumed to differ in terms of their need for cognition. Statements that failed to
discriminate between these two groups were removed, resulting in the 34-item scale. An
abbreviated 18-item version of the scale (Cacioppo, Petty, and Kao, 1984) was chosen
because it was shown to tap the construct with comparable validity and greater efficiency
and ease of administration (Cacioppo, et al., 1996). This scale consists of 18
semantic-differential scales wherein subjects rate the extent to which various statements
are characteristic of themselves. Each item on this instrument was rated on a scale
ranging from 1 (not at all like me) to 5 (very much like me). Half of these items were
worded such that the endorsement indicated a greater need for cognition (e.g., “I usually
end up deliberating about issues even when they do not affect me personally”), whereas
the other half were worded such that the endorsement indicated a lesser need for
cognition (e.g., “I only think as hard as I have to”) (Appendix B). To calculate the
need-for-cognition scores, the nine items were reversed scored, and then all eighteen
items were summed. Respondents were split into high- and low-NFC groups based on a
median score split.
Self-monitoring
The personality trait of self-monitoring was assessed with a scale that is widely
used to measure the construct, Snyder’s (1987) Self-Monitoring Scale. The scale contains
18 true/false items scored in the direction of high self-monitoring so that higher scores
indicate higher self-monitoring (Appendix B). The scale was chosen because it has
greater internal consistency than the original 25 item SMS designed by Snder (1974).
65
Snyder constructed the revised scale from the earlier 25-item measure by choosing items
with at least a 0.15 correlation with the latent self-monitoring variable reflecting social
sergeancy, the tendency to be exhibitionistic and extroverted. The reported internal
consistency of the revised version of the Self-Monitoring Scale is approximately 0.70.
Lennox and Wolfe’s (1984) Revised Self-Monitoring Scale (RSMS) was not chosen
because it does not correlate with the original SMS scale and may be measuring a
different construct (Shuptrine, et al., 1990). Some researchers have argued against the use
of the SMS because of the presence of two or three factors (e.g. Wolfe, Lennox, and
Cutler, 1986; Briggs and Cheek, 1988; Lennox, 1988). However, Snyder and Gangestad
(1986) presented a strong argument that a single-person variable does exist and showed
that the full SMS consistently outperformed the factors in prior studies by Snyder. In
numerous studies by Snyder and various associates completed using the 25-item SMS,
the SMS had greater predictive ability than any of the subscales, as indicated by larger
F-values. In extensive validation, the SMS has demonstrated considerable internal
consistency, stability over time, and discriminant validity (Miller and Thayer, 1989).
Self-monitoring is traditionally viewed as a dichotomous trait and analyzed by dividing
respondents into high and low self-monitoring groups based on the self-monitoring score
of 10 (Larkin and Pines, 1994). Subjects with self-monitoring scores greater than or equal
to 10 were regarded as high self-monitors, and those with scores less than or equal to 9
were regarded as low self-monitors.
66
Restaurant Segments and Dining Companions
The study requires the participants to respond to one of the three restaurant
segments addressed by the hypotheses (fine-dining, casual-dining, quick-service
restaurants). Additionally, it requires subjects to experience one of the three dining
contexts (boss, friend, alone). Therefore, the development of scenarios involved three
levels of restaurant segments and three levels of dining contexts. Different occasions
were designed to include the different dining contexts in three types of restaurant
segments. In the scenarios, the subject was assumed to pay for herself / himself and the
person who is dining with her/ him. Therefore, the price in each scenario is for two
people. Also, price levels at the three restaurant segments were pretested on a student
sample.
Dependent Variables
The currency preference (dollars/points/dollars and points) is included as the
dependent variable. To assess participants’ preferences of currency usages,
semantic-differential scales anchored with disagree – agree; poor – good; do not prefer –
prefer; and unlikely to pay – likely to pay were used. Responses for these items range
from 1 to 7. These items are as follows:
Item 1: How likely that you agree to pay for this causal-dining experience with the
following choices?
Item 2: Paying for the causal-dining experience with the following choices is good
or bad?
67
Item 3: How do you prefer to pay for this causal-dining experience with the
following choices?
Item 4: How likely that you will pay for this causal-dining experience with the
following choices?
The currency preference is measured using 1 to 7 interval scale for each currency.
The responded scores of four questions for each currency were averaged, and the average
scores for three currencies were compared. The highest score among those three
currencies was considered as the currency that the respondent preferred.
The order of the three currencies (dollars-only, dollars and points, and points-only)
was counterbalanced across the items to avoid an order effect. Also, listing the three
currencies in varying orders required respondents to engage more attention and thought
while making their choices for currency preferences. The measurement of the selected
variables was described in Table 3.2.
DATA ANALYSIS
Analysis of the data is based on the hypotheses formulated from the research
question that motivated this research. The data collected from the participants are
analyzed using the Statistical Package for Social Sciences 12th version (SPSS) and
STATA 8th version. Multinomial Logistic regression was applied to analyze the data and
test the hypotheses for the study. Multinomial logistic regression is used to analyze
relationships between a non-metric dependent variable and metric or dichotomous
independent variables. It compares multiple groups through a combination of binary
68
Variables Measurement
Dependent Variables: Currency Preference:
(Dollars-only) 1 = Yes, 0 = No
Dollars and Points 1 = Yes, 0 = No
Points-only 1 = Yes, 0 = No
Independent Variables: Restaurant Segment
(Fine-Dining) 1 = Yes, 0 = No
Casual-Dining 1 = Yes, 0 = No
QSR 1 = Yes, 0 = No
Need for Cognition
(Low NFC) 1 = Yes, 0 = Other
High NFC 1 = Yes, 0 = Other
Self-Monitoring
(Low SEM) 1 = Yes, 0 = Other
High SEM 1 = Yes, 0 = Other
Companions
(Boss) 1 = Yes, 0 = No
Friend 1 = Yes, 0 = No
Alone 1 = Yes, 0 = No
Notea: The reference category is presented in parentheses
Table 3.2: Measurement of Variables logistic regressions, and allows researchers to analyze the dependent variable which is
categorical variable (discrete not continuous) with more than two possible values
(Hosmer and Lemeshow, 2000). The group comparisons are equivalent to the
comparisons for a dummy-coded dependent variable, with the group with the highest
numeric score used as the reference group. Multinomial logistic regression provides a set
69
of coefficients for each of the two comparisons. The coefficients for the reference group
are all zeros, similar to the coefficients for the reference group for a dummy-coded
variable. Thus, there are three equations, one for each of the groups defined by the
dependent variable. The three equations can be used to compute the probability that a
subject is a member of each of the three groups. A case is predicted to belong to the
group associated with the highest probability. Predicted group membership can be
compared to actual group membership to obtain a measure of classification accuracy
(Hosmer and Lemeshow, 2000).
Assumptions of Multinomial Logistic Regression
Multinomial logistic regression does not make any assumptions of normality,
linearity, and homogeneity of variance for the independent variables. Because it does not
impose these requirements, it is preferred to discriminant analysis when the data does not
satisfy these assumptions. The assumptions of multinomial logistic regression include:
Error terms are assumed to be independent (independent sampling).
Linearity: logistic regression does not require linear relationships between
the independents and the dependent, but it does assume a linear relationship
between the logit of the independents and the dependent.
No multicollinearity: to the extent that one independent is a linear function of
another independent, the problem of multicollinearity will occur in logistic
regression.
70
Expected dispersion: in logistic regression the expected variance of the
dependent can be compared to the observed variance, and discrepancies may
be considered under- or overdispersion (Wright, 1995).
The minimum number of cases per independent variable is 10, using a guideline
provided by Hosmer and Lemeshow (2000).
Interpretation of Multinomial Logistic Regression Model
There are several ways to interpret the multinomial logistic regression coefficients:
the effects on log odds; the effect on odds ratio; and the effect on probability.
The Effect on Log Odds
The logistic regression coefficients show the effects of the independent variables
on the predicted log odds of an event occurring. The logistic coefficients estimate the
additive change in the predicted log odds for a one-unit increase in the independent
variables, controlling for all other independent variables in the model. For categorical
independent variables, a unit change in the variable implies the difference between
membership in the indicator category and membership in the reference or omitted
category. In interpreting the logistic coefficient in terms of the effect on the log odds, the
threshold between negative and positive effect is 0 (Pampel, 2000). The logistic
coefficients estimate the marginal effects of the independent variables on the log odds of
falling into a particular category as opposed to a reference category (Liao, 1994). For
categorical independent variables, the logistic coefficient indicates the difference of logit
among the categories.
71
The Effect on Odds
The exponential of the logistic coefficient provides an estimate of the effect of the
independent variable on the odds of an event occurring. The exponentiated coefficient is
called the odds ratio and represents a multiplicative change in the odds for a one-unit
increase in the independent variable. For categorical independent variables, the
exponentiated coefficient is the odds ratio for those in the indicator category versus those
in the reference category. The exponential of a positive number is greater than 1, and the
odds ratio 1 corresponds to the logistic coefficient 0. An exponentiated coefficient greater
than 1 increases the odds and an exponentiated coefficient smaller than 1 decrease the
odds. The distance of an exponentiated coefficient from 1 in either direction indicates the
size of the effect on the odds for a one-unit change in the independent variable (Pampel,
2000). The exponentiated logistic coefficient is a single summary statistic for the
marginal effect of a given independent variable on the odds, controlling for other
independent variables (DeMaris, 1992). Interpreting the logistic coefficients in terms of
the effect on the odds of an event occurring is an easy and flexible way of interpretation.
The Effect on Probabilities
Based on the logistic coefficients, predicted probability for a given set of values of
the independent variables can be computed. Computing the event probability before and
after a unit change in ith explanatory variable provides the marginal effect of the
explanatory variable on the probability. However, the probability is a function of the
values of all explanatory variables in the model and the marginal effect on the probability
depends on a given set of values of the independent variables. The relationships between
72
the independent variables and the probability of an event occurring are nonlinear and
nonadditive (Liao, 1994; Pampel, 2000). Therefore, in contrast to marginal effect on log
odds, the marginal effect on the probability is not constant (DeMaris, 1992). It is not
possible to represent the marginal effect of a given predictor on the probability for all
cases using a single coefficient. Therefore, interpreting the logistic coefficient in terms of
the marginal effects on the probability is useful to examine a typical case. It is useful to
estimate the probability focusing on one or two interesting independent variables and
setting the values in other variables at their sample means (Liao, 1994). Predicted
probability in multiple-outcome models is more useful than those in binary-outcome
models. The probability represents a more general case because of the flexible number of
response categories (Liao, 1994). Predicted probability in multinomial model also
depends on a given set of values of the independent variables. Thus, predicted probability
is estimated focusing on a single independent variable and setting the value in other
variables at their sample means.
Chapter Summary
This chapter presents the two causal experimental designs and discusses statistical
methods used to test the hypotheses. The independent variables included in this study are
need-for-cognition and self-monitoring, restaurant segments and dining companions. The
dependent variable measures the preferences for three currency usages. The sample used
in the study included different undergraduate classes and snowball sample at The Ohio
State University. Multinomial logistic regression with SPSS and STATA is applied to
73
analyze the data and test the hypotheses for the study. Descriptive profiles of the sample
as well as the results of descriptive analysis and multinomial logistic regression are
discussed in the next chapter. The summary of the hypothesis tests is also presented in
chapter 4.
74
CHAPTER 4
RESULTS
In this chapter, descriptive analyses were used to identify the patterns explaining
consumers’ currency preferences. Frequencies were computed for the independent as
well as the dependent variables, the three currency categories. It also provides the results
of the hypothesis tests. The results from multinomial logistic regression analyses were
used to identity the consumers’ characteristics when using different currencies.
Descriptive Statistics
The respondent pool (n = 471) was recruited from different undergraduate classes
and snowball sample at The Ohio State University. Sample characteristics and the
frequencies for each of the independent and dependent variables are presented overall in
Table 4.1.
Sample Characteristics. In the sample, 43% of the respondents were female, and
about 57% were male. The majority of the respondents (82.1%) were 18-23 years old.
More than two-thirds of the respondents (72.4%) were employed. The mean of total
monthly spending was about $670 and the mean of monthly spending on food was about
$186.
75
The currency preferences for male subjects are similar to those for females. About
half of male (52.5%) and female (51.7%) preferred points-only. Subjects over 26 years
old had higher preference for points-only (73.0%) than those in other age groups. Also,
the preferences for points-only for employed respondents (55.4%) were higher than those
for unemployed respondents (43.1%). Interestingly, subjects with total spending under
$520 and spending in food under $100 had lower preference (41.9% and 41.2%,
respectively) for the points-only option than those in higher-expenditure groups.
Currency Preference. Dependent variables include three categories of currency
preferences: dollars-only, dollars and points, and points-only. Table 4.1 shows the
frequency of preference the type of currency. About 27% of the 471 cases preferred
dollars-only, 20.2% preferred combined-currency (dollars and points), and 51.8%
preferred points-only (Figure4.1).
0%
10%
20%
30%
40%50%
60%
Dollars Only Dollars &Points
Points Only
Figure 4.1: Preferences for Three Types of Currencies
76
Restaurant Segments. According to Figure 4.2, the patterns of currency preferences
were similar across in three restaurant segments (fine-dining, casual-dining, and
quick-service restaurant). Generally, more than half of the respondents preferred
points-only across three restaurant segments, and the respondents least preferred the
combined-currency: dollars and points.
In fine-dining restaurants, 51.8% of the respondents preferred points-only, 27.4%
of the respondents preferred dollars-only, and 20.7% preferred the combination of dollars
and points. Similarly, in casual-dining restaurants, 50.3% of the respondents preferred
points-only, 29.1% of the respondents preferred dollars-only, and 20.5% preferred the
combination of dollars and points. The respondents’ preferences for dollars-only were
slightly higher than in the other two restaurant segments. In quick-service restaurants, the
respondents’ preferences for points-only were slightly higher than fine-dining and
casual-dining restaurants, with 53.8% of the respondents preferring points-only, 26.9% of
the respondents preferring dollars-only, and 19.2% preferring a combination of dollars
and points. In summary, consumer preference across the three restaurant segments is
reasonably consistent.
77
0%
10%
20%
30%
40%
50%
60%
Fine-Dining Casual-Dining QSRDollars OnlyDollars & PointsPoints Only
Figure 4.2: Currency Preferences in Three Restaurant Segments
Need for Cognition. The mean score in this sample was 58.38, with scores ranging
from 18 to 99. Subjects were split into high and low need-for-cognition groups based on
the median (score of 58) split. According to Figure 4.3, the preferences for three types of
currencies for high need-for-cognition respondents are similar to those for low need for
cognition respondents. Among the high need-for-cognition, 52.8% preferred points-only,
28.1% preferred dollars-only, and 19.1% preferred the combination of dollars and points.
For low need-for-cognition respondents, 51.3% of the respondents preferred points-only,
27.5% preferred dollars-only, and 21.2% preferred the combination of dollars and points.
78
0%
10%
20%
30%
40%
50%
60%
High NFC Low NFC Dollars OnlyDollars & PointsPoints Only
Figure 4.3: Currency Preferences and Need for Cognition
Self-Monitoring. Consistent with past research on self-monitoring (see Larkin and
Pines, 1994), subjects with self-monitoring scores greater than or equal to 10 were
regarded as high self-monitors, and those with scores less than or equal to 9 were
regarded as low self-monitors. For self-monitoring, 31.3% of the high self-monitors and
24.1% of the low self-monitors prefer to pay with dollars-only. The preference for usage
of dollars-only was higher for high self-monitors than for low self-monitors (Figure 4.4).
On the other hand, the preference for usage of points-only was higher for low
self-monitors than for high self-monitors. In the current sample, 54.8% of the low
self-monitors and 49.4% of the high self-monitors prefer to pay with points-only.
Moreover, 21.2% of the low self-monitors and 19.3% of the high self-monitors preferred
the combination of dollars and points.
79
0%
10%
20%
30%
40%
50%
60%
High SEM Low SEM Dollars OnlyDollars & PointsPoints Only
Figure 4.4: Currency Preferences and High and Low Self-Monitoring
Dining Companions. For companions, 46.1% of the respondents who dine with the
boss while 19.5% of the respondents who dine with a friend and 16.1% of the
respondents who dine alone preferred dollars-only. According to Figure 4.5, the
preferences for paying dollars-only while dining with the boss were higher than while
dining with a friend or alone. Also, the preferences for usage of the combination of
dollars and points while dining with a friend (23.5%) were higher than while dining with
the boss (18.0%) or while dining alone (19.4%). On the other hand, the preferences for
paying with points-only while dining alone (64.5%) were much higher than while dining
with the boss (35.9%), and slightly higher than while dining with a friend (57.0%).
80
0%
10%
20%
30%
40%
50%
60%
70%
Boss Friend Alone Dollars OnlyDollars & PointsPoints Only
Figure 4.5: Currency Preferences for Companions Using Three Different Currency Types
81
Table 4.1: Descriptive Statistics by the Type of Currency
Currency Preference Dollars-
Only Dollars & Points
Points- Only
Total Sample
Overall Currency Preference
n=129 (27.4%)
n=95 (20.2%)
n=244 (51.8%)
n = 471 (100%)
n (%) n (%) n (%) n (%) Demographic Variables
Gender Male 54 (27.0%) 41 (20.5%) 105 (52.5%) 200 (42.5%)
Female 77 (28.4%) 54 (19.9%) 140 (51.7%) 271 (57.5%)Age
18-20 27 (20.6%) 38 (29.0%) 66 (50.4%) 131 (27.7%) 21-23 79 (30.9%) 46 (18.0%) 131 (51.2%) 256 (54.4%) 24-26 18 (38.3%) 8 (17.0%) 21 (44.7%) 47 (10.0%)
26 or older 7 (18.9%) 3 (8.1%) 27 (73.0%) 37 (7.9%) Employment
Yes 91 (26.7%) 61 (17.9%) 189 (55.4%) 341 (72.4%) No 40 (30.8%) 34 (26.2%) 56 (43.1%) 130 (27.6%)
Monthly Spending Low (under $520) 42 (28.4%) 44 (29.7%) 62 (41.9%) 148 (31.4%)
Middle ($521-$770) 43 (28.3%) 23 (15.1%) 86 (56.6%) 152 (32.3%) High (over $770) 45 (26.5%) 28 (16.5%) 97 (57.1%) 170 (36.1%)
Food: Low (under $100) 24 (23.5%) 36 (35.3%) 42 (41.2%) 102 (21.7%)
Middle ($101-$200) 47 (30.9%) 25 (16.4%) 80 (52.6%) 152 (32.3%) High (over $200) 60 (27.6%) 34 (15.7%) 123 (56.7%) 217 (46.1%)
Independent Variables
Restaurant Segment Fine-Dining 45 (27.4%) 34 (20.7%) 85 (51.8%) 164 (34.8%)
Casual-Dining 44 (29.1%) 31 (20.5%) 76 (50.3%) 151 (32.1%) QSR 42 (26.9%) 30 (19.2%) 84 (53.8%) 156 (33.1%)
Need for Cognition High NFC 66 (28.1%) 45 (19.1%) 124 (52.8%) 235 (49.9%) Low NFC 65 (27.5%) 50 (21.2%) 121 (51.3%) 236 (50.1%)
Self-Monitoring High SEM 76 (31.3%) 47 (19.3%) 120 (49.4%) 243 (51.6%) Low SEM 55 (24.1%) 48 (21.1%) 125 (54.8%) 228 (48.4%)
Companions Boss 77 (46.1%) 30 (18.0%) 60 (35.9%) 167 (35.5%)
Friend 29 (19.5%) 35 (23.5%) 85 (57.0%) 149 (31.6%) Alone 25 (16.1%) 30 (19.4%) 100 (64.5%) 155 (32.9%)
82
Multinomial Logistic Regression Analysis
Personality types: need for cognition and self-monitoring, dining companions,
restaurant segments, and demographic variables related to the preference of currency
usage were examined using multinomial logistic regression analysis. Among the three
categories of currencies, the single currency dollars-only was the reference category for
the dependent variable. The likelihood of preference for each currency is compared with
the likelihood of preference of dollars-only. Table 4.2 and Table 4.3 present the results of
the multinomial logistic analysis of the demographic variables and the independent
variables associated with the preference for dollars-only, the combination of dollars and
points or points-only. Table 4.2 shows how the likelihood of preferring the
combined-currency (dollars and points) differs from the likelihood of preferring
dollars-only. And Table 4.3 shows the comparison of the likelihood of preferring
points-only with the likelihood of preferring dollars-only.
Demographic Variables
Gender, age and employment have no significant effect on currency preference
when comparing the preference for the combined-currency (dollars and points) to the
preference for dollars-only (Table 4.2). However, when comparing the preference for
points-only to the preference for dollars-only, the effect of age was positive and
significant at 0.1 level (p=.07 for age group of 21-23 years old and p=.06 for age group of
24-26 years old) (Table 4.3). The estimated odds for age group of 21-23 years old was
2.504 and for age group of 24-26 years old was 3.019, indicating that compared to the
21-23 years and 24-26 years old, over 26 years old were more likely to prefer points-only
as opposed to dollars-only.
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Employment had a positive effect on the probability of preferring points-only as
opposed to preferring dollars-only at 0.1 significant level (p=.08). The estimated odds for
employed respondents was 1.616 higher than for unemployed respondents (Table 4.3).
This suggests that employed respondents were 1.616 times more likely to prefer to pay
with points-only (as opposed to dollars-only) than unemployed respondents.
The effect of total monthly-spending was negative and significant at 0.05 level
(p=.05 for high monthly-spending) and at 0.1 level (p=.07 for mid-level monthly
-spending) when comparing the preference for points-only to the preference for
dollars-only (Table 4.3). For total monthly-spending, low monthly-spending was the
reference category. The estimated odds for high monthly-spending was .500 and for
mid-level monthly-spending was .482, indicating that compared to high and mid-level
monthly-spending respondents, those low in monthly spending were less likely to prefer
points-only as opposed to dollars-only.
In addition, the logistic coefficients for high monthly-spending for food and
mid-level monthly-spending for food were both positive and significant at 0.01 level
(p=.01 for high monthly-spending in food) and at 0.05 level (p=.02 for mid-level
monthly –spending in food) when comparing the preference for the combined currency
(dollars and points) to the preference for dollars-only (Table 4.2). The estimated odds for
high monthly-spending and mid-level monthly-spending in food were 3.111 and 3.252,
indicating that compared to respondents in high and mid rang in monthly-spending for
food, the low monthly-spending respondents were more likely to prefer the
combined-currency (dollars and points), as opposed to dollars-only.
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Independent Variables
For restaurant segments, fine-dining restaurant was the reference category. The
effect of restaurant segments was not significant when comparing the preference for the
combined-currency (dollars and points) to the preference for dollars-only and when
comparing the preference for points-only to the preference for dollars-only. Therefore,
hypotheses 1a, 1b, and 1c were not supported. However, the logistic coefficient for
casual-dining restaurant was negative and significant at 0.1 level (p=.07) when
comparing the preference for the combined currency (dollars and points) to the
preference for dollars-only (Table 4.2). The estimated odds for casual-dining restaurant
was .328. This suggests that respondents dining at fine-dining restaurant were .328 times
less likely to prefer to pay with the combined currency (dollars and points), as opposed to
dollars-only, than those dining at casual-dining restaurant.
The effect of need for cognition was first examined based on the median (score of
58) split into high and low need-for-cognition groups. The effect of need for cognition
was not significant at the 0.05 level when comparing the preference for the
combined-currency (dollars and points) to the preference for the dollars-only and when
comparing the preference for points-only to the preference for dollars-only. In addition,
to create a clear difference between the high and low need-for-cognition group, out of a
total sample of 471, subjects whose NFC score fell in the middle third of the distribution
were deleted from further analyses (see Inman et al., 1990; Petty and Cacioppo, 1986).
After dropping the middle third of the distribution, 188 subjects were included in the
analyses. The effect of need for cognition was still not significant when comparing the
preference for the combined-currency (dollars and points) to the preference for the
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dollars-only and when comparing the preference for points-only to the preference for
dollars-only (results presented in Appendix A). Thus, the results did not support
hypothesis 2. Furthermore, the interaction effect of need for cognition and restaurant
segments was also not significant. Hypothesis 3 was not supported.
The effect of self-monitoring was not significant when comparing the preference
for the combined-currency (dollars and points) to the preference for dollars-only.
Hypothesis 4 was not supported. However, self-monitoring was significant at 0.1 level
(p=.07) and had a positive effect on the probability of preferring paying points-only as
opposed to paying dollars-only. The estimated odds for high self-monitors was 2.448.
This suggests that low self-monitors were 2.448 times more likely to prefer to pay with
points-only (as opposed to dollars-only) than high self-monitors. In other words, high
self-monitors were less likely to prefer to pay with points-only (as opposed to pay with
dollars-only) than low self-monitors.
For companions, dining with the boss was the reference category. The logistic
coefficient for who dine with a friend was negative and significant at the 0.1 significance
level (p= .08) when comparing the preference for points-only to the preference for
dollars-only. The estimated odds for dining with a friend was 0.469. This suggests that
for who those dine with the boss were 0.469 times less likely to prefer to pay with
points-only (as opposed to dollars-only) than the respondents who dine with a friend.
Also, the logistic coefficient for who dine alone was negative and significant at the 0.05
significance level (p=.02) when comparing the preference for points-only to the
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preference for dollars-only. The estimated odds for dining alone was 0.4, indicating that
respondents that dine with the boss were 0.4 times less likely to prefer to pay with
points-only (as opposed to dollars-only) than the respondents who dine alone. Thus, the
results support hypothesis 5.
The interaction effect of self-monitoring and companions was marginally
significantly associated with currency preference. The logistic coefficient for high
self-monitors dining alone was negative and significant at the 0.05 significance level
(p=.02) when comparing the preference for the combined-currency (dollars and points) to
the preference for dollars-only. The estimated odds ratio for dining alone was .199. In
addition, the logistic coefficient for high self-monitors dining alone was negative and
significant at the 0.05 significance level (p=.01) when comparing the preference for
points-only to the preference for dollars-only. The estimated odds ratio was .217. These
suggest that high self-monitors dining alone were more likely to prefer to pay with
combined-currency (dollars and points) or points-only than low self-monitors (Figure 4.6
and 4.7). Thus, hypothesis 6 was supported.
Additionally, the interaction effect of self-monitoring and restaurant segment was
marginally significantly associated with currency preference. The logistic coefficient for
high self-monitors dining in fine-dining restaurant and quick-service restaurant were not
significant when comparing the preference for the combined-currency (dollars and points)
to the preference for dollars-only and when comparing the preference for points-only to
the preference for dollars-only. However, the logistic coefficient for interaction of
self-monitoring and casual-dining restaurant was positive and significant at 0.1 level
(p=.07) when comparing the preference for the combined currency (dollars and points) to
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the preference for dollars-only (Table 4.2). The estimated odds ratio was 3.629. This
suggests that low self-monitors dining in casual-dining restaurant were more likely to
prefer to pay with combined-currency (dollars and points) than high self-monitors (Figure
4.8 and 4.9). Therefore, Hypothesis 7 was partially supported.
0%
10%
20%
30%
40%
50%
60%
70%
Boss Friend Alone Dollars OnlyDollars and PointsPoints Only
Figure 4.6: Currency Preferences of High Self-Monitors with Companions
88
0%
10%
20%
30%
40%
50%
60%
70%
Boss Friend Alone Dollars OnlyDollars and PointsPoints Only
Figure 4.7: Currency Preferences of Low Self-Monitors with Companions
0%
10%
20%
30%
40%
50%
60%
Fine-Dining Casual-Dining QSR Dollars OnlyDollars & PointsPoints Only
Figure 4.8: Currency Preferences of High Self-Monitors with Three Restaurant Segments
89
0%
10%
20%
30%
40%
50%
60%
Fine-Dining Casual-Dining QSR Dollars OnlyDollars & PointsPoints Only
Figure 4.9: Currency Preferences of Low Self-Monitors with Three Restaurant Segments
90
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Continued Table 4.2: Results of Multinomial Logistic Regression Analysis: Dollars and Points
versus Dollars-only
Dollars + Points vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Demographic Variables Gender (omitted Male)
Female .039 .296 .896 1.039
Age (omitted 26 or older)
18-20 -1.258 .784 .108 .284 21-23 -.232 .756 .759 .793 24-26 -.229 .851 .788 .795
Employment (omitted Yes)
No -.025 .318 .938 .976
Total Monthly Spending (omitted Low: under $520)
High (over $770) -.188 .440 .668 .828 Middle ($521-$770) -.407 .512 .427 .666
Monthly Spending in Food (omitted Low: under $100)
High (over $200) 1.135** .447 .011 3.111 Middle ($101-$200) 1.179** .529 .026 3.252
Independent Variables
Restaurant Segment (omitted Fine-Dining)
Casual-Dining -1.115* .628 .076 .328 QSR -.407 .605 .501 .665
Need for Cognition (omitted Low NFC )
High NFC -.290 .497 .559 .748
Self-Monitoring (omitted Low SEM)
High SEM .194 .607 .749 1.215
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Table 4.2 Continued
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Dollars + Points vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Companions (omitted Boss )
Friend -.668 .514 .194 .513 Alone -.301 .509 .554 .740
Interactions
NFC*Casual-Dining .711 .713 .319 2.037 NFC*QSR -.040 .719 .955 .960
SEM*Casual-Dining 1.289* .712 .070 3.629 SEM*QSR .804 .710 .258 2.234
SEM* Friend -.642 .702 .360 .526 SEM*Alone -1.616** .742 .029 .199
Constant 1.295 1.952 .507
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∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Continued Table 4.3: Results of Multinomial Logistic Regression Analysis: Points-only versus
Dollars-only
Points-only vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Demographic Variables Gender (omitted Male)
Female -.056 .244 .819 .946
Age (omitted 26 or older)
18-20 .101 .545 .853 1.106 21-23 .918* .505 .069 2.504 24-26 1.105* .588 .060 3.019
Employment (omitted Yes)
No .480* .275 .081 1.616
Total Monthly Spending (omitted Low: under $520)
High (over $770) -.693** .359 .054 .500 Middle ($521-$770) -.730* .407 .073 .482
Monthly Spending in Food
(omitted Low: under $100) High (over $200) .231 .397 .560 1.260
Middle ($101-$200) .292 .443 .510 1.339
Independent Variables
Restaurant Segment (omitted Fine-Dining)
Casual-Dining -.466 .517 .367 .627 QSR .099 .490 .839 1.105
Need for Cognition (omitted Low NFC )
High NFC -.056 .412 .893 .946
Self-Monitoring (omitted Low SEM)
High SEM .895* .502 .074 2.448
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Table 4.3 Continued
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Points-only vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Companions (omitted Boss )
Friend -.756* .433 .081 .469 Alone -.915** .406 .024 .400
Interactions
NFC*Casual-Dining .384 .591 .516 1.468 NFC*QSR -.644 .585 .271 .525
SEM*Casual-Dining .309 .592 .601 1.363 SEM*QSR -.158 .585 .788 .854
SEM* Friend -.926 .580 .111 .396 SEM*Alone -1.527** .610 .012 .217
Constant 2.719 1.436 .058
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Summary of the Hypothesis Tests
Table 4.4 summarized the results of the research hypothesis testing regarding the
preferences for currency usages. Restaurant segments were not significantly related to the
preference for currency usages. Thus, the research hypothesis that while dining out,
consumers are more likely to pay with single currency (points only) at high-end
restaurants, to pay with the combined-currency (dollars and points) at mid-priced
restaurants, and to pay with single currency (dollars only) at low-price restaurants was
not supported. Though hypothesis 1 was not supported, casual-dining restaurant had a
negative impact on the probability of preferring paying the combined-currency (dollars
and points) as opposed to paying dollars-only.
Need for cognition was not significantly related to the preference for currency
usages. Thus, the research hypothesis that while dining out, consumers with a high need
for cognition are more likely to prefer payment with combined currency than cognitive
misers was not supported. Also, the interaction effect of need for cognition and restaurant
segments was not significant. Therefore, the research hypothesis that while dining out,
currency preferences of consumers with high or low need for cognition are affected by
the type of restaurant was not supported.
For self-monitoring, high self-monitors were less likely to prefer to pay with
points-only (as opposed to pay with dollars-only) than low self-monitors. Though the
research hypothesis that while dining out, high self-monitoring consumers are more likely
to pay with a single currency than low self-monitoring consumers was not supported,
self-monitoring had a positive effect on the probability of preferring paying points-only
as opposed to paying dollars-only.
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Dining companions had negative effect on the probability of preferring points-only
relative to preferring dollars-only. Thus, the research hypothesis that while dining out,
currency preferences are affected by the dining companions was supported. The
interaction effect of self-monitoring and dining companions was partially significantly
related to the preference for currency usages. High self-monitors dining alone were more
likely to prefer to pay with combined-currency (dollars and points) or points-only than
low self-monitors. This result supports the research hypothesis that while dining out,
currency preferences across social contexts are moderated by self-monitoring.
Finally, the interaction effect of self-monitoring and restaurant segment was
partially significantly related to the preference for currency usages. Low self-monitors
dining in casual-dining restaurant were more likely to prefer to pay with
combined-currency (dollars and points) than high self-monitors. This result supports the
research hypothesis that while dining out, currency preferences of consumers with high
or low need for cognition are affected by the type of restaurant (high, mid and low
priced).
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Research Hypotheses Model
Restaurant Types and Preference for Currency Usage:
H1: While dining out, consumers are more likely to pay with
(a) single currency – points - at high-end restaurants,
(b) combined-currency- dollars and points – at mid-priced
restaurants, and (c) single currency – dollars - at low price
restaurants.
Not supported
Personality Types and Preference for Currency Usage:
Need for Cognition:
H2: While dining out, consumers with a high need for
cognition are more likely to prefer payment with
combined currency than cognitive misers.
Not supported
H3: While dining out, currency preferences of consumers with
high or low need for cognition are affected by the type of
restaurant (high, mid and low priced).
Not supported
Self-Monitoring:
H4: While dining out, high self-monitoring consumers are more likely to pay with a single currency than low self-monitoring consumers.
Not supported
H5: While dining out, currency preferences are affected by the dining context, such that payment is more likely to occur with (a) dollars when dining with a higher-status companion and (b) points when dining with an equal-status companion or when dining alone.
Supported
H6: While dining out, currency preferences across dining contexts are moderated by self-monitoring, such that high self-monitors are more likely than low self-monitors to pay with dollars when dining with a high-status companion.
Supported
H7: While dining out, currency preferences of high and low self-monitoring consumers are affected by the type of restaurant (high, mid and low priced).
Supported
Table 4.4: Summary of the Hypothesis Tests of Currency Preferences
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CHAPTER 5
CONCLUSIONS
This chapter presents a discussion and a summary on the findings of the study. The
factors affecting the preference for currency usages are discussed. Implications for the
foodservices industry, the limitations of the study, and the directions for future research
are also addressed.
Discussions and Summary
The purpose of this study was to examine the effect of personality traits – need for
cognition and self-monitoring – on consumers’ preference for currency usage. A second
purpose of the study was to determine whether differences in restaurant segments were
related to consumers’ currency preferences. The independent variables included in this
study were the scores on need-for-cognition and self-monitoring scales, restaurant
segments and dining companions. The dependent variable measured the preferences for
three currency usages.
The sample used in the study included different undergraduate classes and
snowball sample at The Ohio State University. The study involved two phrases of data
collection. In phrase one, respondents were first asked to complete Snyder and
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Grangestad’s (1986) Self-Monitoring Scale and Cacioppo, Petty, and Kao’s (1984) Need
for Cognition Scale, to answer a series of questions related to their prior experiences in
different currencies and to provide demographic information. Participants were then
asked in phrase two to complete a scenario-based study in which they were asked to
indicate on semantic-differential scales their preferences for each of the three currencies
(dollars-only, dollars and points, and points-only).
The data collected from the participants were analyzed using SPSS and STATA
software packages. Multinomial logistic regression was performed to determine if need
for cognition, self-monitoring, restaurant segments, and dining companions would make
significant contribution to the currency preferences. There were several main findings
resulting from the data analysis. The overall results revealed that age, employment, total
monthly-spending, monthly-spending in food, self-monitoring, dining companions, and
the interaction of self-monitoring and dining companions affect consumer preferences for
currency usages.
First, age and employment have positive effects on the probability of preferring
points-only as opposed to preferring dollars-only. Consumers over 26 years old were
more likely to prefer points-only (as opposed to dollars-only) compared to consumers
21-23 years old and 24-26 years old. Moreover, employed consumers are more likely to
prefer to pay with points-only (as opposed to dollars-only) than unemployed consumers.
Furthermore, high and mid-level monthly-spending consumers are more likely to prefer
points-only as opposed to dollars-only. For high and mid-level monthly-spending
consumers, the currency of points is probably more attractive because of its nonmonetary
nature. Since their monthly spending is relatively high, high and mid-level
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monthly-spending consumers may use points first rather than dollars to take advantage of
greater flexibility of the dollars. However, low monthly food spending respondents are
more likely to prefer the combined-currency (dollars and points), as opposed to
dollars-only, than high and mid-monthly food spending respondents. People who would
like to spend more on food probably do not mind paying for food in restaurants with
dollars.
Though the effect of restaurant segment is not significant on the probability of
preferring points-only as opposed to dollars-only, consumers dining at fine-dining
restaurant are less likely to prefer to pay with the combined currency (dollars and points)
than the consumers dining at casual-dining restaurant. Moreover, need for cognition and
the interaction of need for cognition and restaurant segments have no significant impact
on consumer preferences for currency usage.
High self-monitors are less likely to prefer to pay with points-only (as opposed to
paying with dollars-only) than low self-monitors. For high self-monitors, the preferences
for currency usages are more likely influenced by the image delivered by the currency
than for low self-monitors. Even though the currency of points delivers image of a loyal
customer, it still communicates the image of price discount. Therefore, comparing to
dollars, high self-monitors are less likely to prefer the currency of points.
Companions have a negative effect on the probability of preferring points-only as
opposed to dollars-only. Consumers who dine with a friend or alone are more likely to
prefer to pay with points-only (as opposed to dollars-only) than consumers who dine with
the boss. This result indicates that dining companion is an important determinant of
preferring the currency of points. Since points are a signal of price discount, consumers
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do not want to make a cheap impression on the higher-status dining companion (e.g.,
boss) by using points for their dining experiences. On the other hand, if consumers dine
with a friend or alone, they are more likely to reap the financial rewards of paying with
points without regard to the impression it creates.
Finally, high self-monitors dining alone are more likely to prefer to pay with
combined-currency (dollars and points) or points-only than low self-monitors. The
interaction effect of self monitoring and companions is significantly associated with
currency preferences. High self-monitors dining alone are more likely to prefer to pay
with combined-currency (dollars and points) or points-only than low self-monitors. On
the other hand, high-self monitors dining with boss are more likely to prefer to pay with
dollars-only than to pay with dollars and points or points-only. Since the effects of
impression on companions occur much more strongly among high self-monitors,
consumers who are high self-monitors are more concerned that a higher-status dining
companion (e.g., boss) would perceive use of points as “cheap” than consumers who are
low self-monitors or dining alone. Additionally, low self-monitors dining in casual-dining
restaurant are more likely to prefer to pay with combined-currency (dollars and points)
than high self-monitors
Implications
This study extends our understanding of individual difference associated with
currency preference by examining the effects of self-monitoring, companions, and
restaurant segment on preferences for currency usages. Identifying the characteristics of
consumers using the different currency options is critical for the foodservice industry.
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Foodservice managers have to know their customers and remain close to the consumers
(Crawford-Welch, 1994). By understanding the individual personality differences of
customers when using different currencies, restaurants could decide whether or not to
implement different currency prices based on their target markets. Large restaurant chains
may specifically target different personality types with specific promotional programs to
meet their self-monitoring needs.
Dining companions play a major role in the preference of currency usage.
Restaurants could apply different currency prices based on the target customers and the
concepts of the restaurants. The results of this study suggest that consumers do not prefer
paying their dining experiences with points to avoid making a cheap impression on the
higher-status dining companion (e.g., boss). Therefore, it may not be a good idea to use
nonmonetary currency price for those restaurants that target business-oriented customers.
On the other hand, for family-oriented or casual-dining restaurants that attract consumers
to have fun with their companions of equal status or those on whom they do not need to
worry about the impression they make, combined currency (dollars and points) or
points-only may be considered as options for currency usages.
However, the combined currency prices or nonmonetary currency prices need not
be limited to a single restaurant unit but can be applied to the whole restaurant chain. By
implementing such a rewards program, the restaurants may keep more customers
patronizing their chains, increase customers’ loyalty, and further enhance restaurants’ the
long-term profitability.
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Limitations
Little prior research exists on exploring characteristics of consumers dealing with
the different currency options. This study takes the first step towards understanding
characteristics of consumers that influences their currency preferences. However, some
sampling and design characteristics may limit the generalizability of the results to the
larger population of consumers. The major limitations of this study include that the
findings from a student sample may not be the best choice to generalize to other
populations. While students frequently consume in low and mid-price restaurants and are
potential consumers for high-end restaurants, they are not representative of the larger
population. Since students tend to be in low income bracket and are more value oriented
than nonstudents, financial reward of paying with points without costing any money
seems most attractive for them. Also, the sample homogeneity might also have
contributed to the lack of some of the demographic effects.
Moreover, students may not have many experiences in high-end (fine-dining)
restaurants; they may differentiate three restaurant segments only based on the prices but
not other attributes. Therefore, the association between restaurant segments and currency
preferences might have been underestimated. Furthermore, the amount of payment across
the three restaurant segments is not significantly different; therefore, it could be a reason
why the differences in consumer preferences of three currency options across the three
restaurants are not significant.
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In addition, since not all participants completed the scenario-based questionnaires
under supervision, the researchers were not always available to answer questions and
make sure the questionnaires were being filled out properly. Also, the researchers could
not guarantee confidentiality for those subjects who gave their questionnaires to a student
to return to the researchers.
Recommendations for Future Research
Future research efforts could include replications using more representative
samples across all customer segments and more realistic designs allowing for higher
external validity. Also, these findings should be tested in field studies.
In addition, different exchange rates between different currencies may also
influence consumers’ currency preferences. Thus, idiosyncratic exchange rate or a
well-known exchange may be applied to compare the preference for currency usage.
Moreover, different combinations of two different currencies may also affect consumers’
preferences of the combined currency. For example, consumers’ perceptions of the
combined-currency price $70 and 700 points may be different with $59 and 810 points.
Thus, it would be interesting to compare consumers’ preferences for currency usage
including different combinations of two different currencies.
According to Drèze and Nuness (2004), consumers prefer one currency price over
another based on the amount of payment. Also, the results presented in postscript in
chapter 4 suggest that the effect of need for cognition may differ by different industry
104
contexts. The price range in different industries varies; therefore, different industries may
have different impacts on consumers’ currency preference. Different industries need to be
included in order to have a better understanding of consumers’ preference for currency
usage.
While concluding that the characteristics of consumers influence their currency
preferences, the question remains as to how different currency preferences affect
consumers spending behaviors. Results from previous studies in price promotion and
consumer purchase behavior consistently showed that price promotions increase sales and
affect consumer spending. Providing reward points as price promotions may not
guarantee increased profits; however, by providing different types of currencies, it is
possible to stimulate consumers’ amount of spending and further increase sales.
Therefore, an extension of this research would be examining whether differences in the
currency usage are related to consumer spending behaviors.
Chapter Summary
This chapter discusses the findings of the study, conclusions, and implications of
these results. Limitations of the study and recommendations for future research are also
discussed. Based on the results, the experiments are continued. As the extended study, the
dependent measure of currency preference was refined and uses different combinations of
three currencies instead of one option in the original study. Also, the independent
variables included in the extended study are need for cognition and three price levels
tested in two different industry contexts – restaurant context and airline context. Results
of the extended study will be discussed in chapter 6.
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CHAPTER 6
POSTSCRIPTS
Upon completing the original study, a follow up study was conducted with refined
instrument. The instrument was refined and tested in two different contexts: airline
context and restaurant context. The independent variables included in this study are only
need for cognition and three restaurant segments (fine-dining, causal-dining, and
quick-service restaurant) in restaurant context and three price levels of airline tickets
(high-priced, mid-priced, and low-priced ticket) in airline context.
To better understand the effect of need for cognition on consumer choice, a revised
study was conducted. A major objective of this follow up study is to increase complexity
of currency so that cognitive recourse will be in greater demand. In other words,
respondents have to use higher level of cognition in making complex choices. The
dependent measure - the currency preference was revised with 5 choices of dollars and
points combinations: 100% dollars-only, 75% of dollars and 25% of points, 50% of
dollars and 50% of points, 25% of dollars and 75% of points, and 100% points-only.
Respondents were asked to rank the options on a scale of 1 (most preferred) to 5 (least
preferred). The prices of combined-currency options were idiosyncratic price options
instead of rounded price options to stimulate respondents’ need for cognition.
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The respondents (n = 106) were recruited from different undergraduate classes
during spring 2005. The results from descriptive analyses and multinomial logistic
regression analyses for airline context and restaurant context were presented as follows
Restaurant Context
The frequency of preference the type of currency in restaurant context was
presented in Table 6.1. In fine-dining restaurants, 55.6% of the respondents preferred
points-only, 27.8% preferred the combined currency (dollars and points) and 16.7%
preferred dollars-only. Similarly, in casual-dining restaurants, 54.5% of the respondents
preferred points-only, 30.3% preferred the combined currency (dollars and points) and
15.2% preferred dollars-only. The respondents’ preferences for the combined currency
(dollars and points) were slightly higher in casual-dining segment than other two
restaurant segments. In quick-service restaurants, the respondents’ preferences for
dollars-only were higher than in fine-dining and casual-dining restaurants (Figure 6.1),
with 48.6% of the respondents preferring points-only, 21.6% preferring the combined
currency (dollars and points), and 29.7% preferring dollars-only.
Need for Cognition. Among the high need-for-cognition respondents, 54.7%
preferred points-only, 22.6% preferred the combined currency (dollars and points) and
22.6% preferred dollars-only. For low need-for-cognition respondents, 50.9% preferred
points-only, 30.2% preferred the combined currency (dollars and points) and 18.9%
preferred dollars-only. According to Figure 6.2, low need-for-cognition respondents had
higher preferences for the combined currency (dollars and points) than high
need-for-cognition respondents.
107
Table 6.1: Descriptive Statistics by the Type of Currency in Restaurant Context
0%10%20%30%40%50%60%70%80%
Fine-Dining Casual-Dining QSR Dollars OnlyDollars & PointsPoints Only
Figure 6.1: Currency Preferences in Restaurant Context
Currency Preference Dollars-
Only Dollars & Points
Points- Only
Total Sample
Overall Currency Preference
n=22 (20.8%)
n=28 (26.4%)
n=56 (52.8%)
n = 106 (100%)
n (%) n (%) n (%) n (%) Restaurant Segment
Fine-Dining 6 (16.7%) 10 (27.8%) 20 (55.6%) 36 (34.0%) Casual-Dining 5 (15.2%) 10 (30.3%) 18 (54.5%) 33 (31.1%)
QSR 11(29.7%) 8 (21.6%) 18 (48.6%) 37 (34.9%) Need for Cognition
High NFC 12 (22.6%) 12 (22.6%) 29 (54.7%) 53 (50.0%) Low NFC 10 (18.9%) 16 (30.2%) 27 (50.9%) 53 (50.0%)
108
0%10%20%30%40%
50%60%70%
High NFC Low NFC Dollars OnlyDollars & PointsPoints Only
Figure 6.2: Currency Preferences for Need for Cognition in Restaurant Context
Multinomial Logistic Regression Analysis
For restaurant segments, fine-dining restaurant was the reference category. The
effect of restaurant segments was not significant when comparing the preference for the
combined-currency (dollars and points) to the preference for dollars-only and when
comparing the preference for points-only to the preference for dollars-only.
Moreover, the effect of need for cognition was not significant when comparing the
preference for the combined-currency (dollars and points) to the preference for the
dollars-only and when comparing the preference for points-only to the preference for
dollars-only (Table 6.2).
109
Table 6.2: Results of Multinomial Logistic Regression Analysis for Restaurant Industry Airline Context
Table 6.3 shows the frequency of preference the type for currency in airline context.
For high-priced airline tickets, 72.2% of the respondents preferred points-only, 16.7%
preferred the combined currency (dollars and points), and 11.1% of the respondents
preferred dollars-only. For mid-priced airline tickets, 56.3% of the respondents preferred
points-only, 34.4% preferred the combination of dollars and points, and 9.4% of the
respondents preferred dollars-only. The tendency to prefer the combined currency
Dollars + Points vs. Dollars-only Variables (n=106) β S.E. Sig. Exp (β)
Restaurant Segment (omitted Fine-Dining)
Casual-Dining -.148 .698 .833 .863 QSR .666 .608 .273 1.947
Need for Cognition (omitted Low NFC )
High NFC .317 .518 .540 1.373
Constant .490 .798 .539 Points-only vs. Dollars-only
Variables (n=106) β S.E. Sig. Exp (β)
Restaurant Segment (omitted Fine-Dining)
Casual-Dining -.354 .770 .646 .702 QSR .722 .704 .305 2.058
Need for Cognition (omitted Low NFC )
High NFC .790 .599 .187 2.203 Constant -.384 .912 .674
110
(dollars and points) was higher compared to high-priced and low-priced airline tickets.
For low-priced airline tickets, the respondents’ preferences for dollars-only were higher
than at the other two price levels of airline tickets, with 55.3% of the respondents
preferring points-only, 26.3% preferring the combined currency (dollars and points), and
18.4% of the respondents preferring dollars-only. According to Figure 6.3, the patterns of
currency preferences were different in three levels of airline tickets (high-priced,
mid-priced, and low-priced). In summary, the tendency to prefer points-only decreased as
ticket prices decreased. The respondents’ preferences for the combined currency (dollars
and points) were higher for mid-priced tickets while the respondents’ preferences for
dollars-only were higher for low-priced tickets.
Table 6.3: Descriptive Statistics by the Type of Currency in Airline Context
Currency Preference Dollars-
Only Dollars & Points
Points- Only
Total Sample
Overall Currency Preference
n=14 (13.2%)
n=27 (25.5%)
n=65 (61.3%)
n = 106 (100%)
n (%) n (%) n (%) n (%) Airline Ticket High-Priced ($1,200) 4 (11.1%) 6 (16.7%) 26 (72.2%) 36 (34.0%)
Mid-Priced ($560) 3 (9.4%) 11 (34.4%) 18 (56.3%) 32 (30.2%) Low-Priced ($180) 7 (18.4%) 10 (26.3%) 21 (55.3%) 38 (35.8%)
Need for Cognition High NFC 9 (17.0%) 11 (20.8%) 33 (62.3%) 53 (50.0%) Low NFC 5 (9.4%) 16 (30.2%) 32 (60.4%) 53 (50.0%)
111
0%10%20%30%40%50%60%70%80%
High-Priced Mid-Priced Low-Priced Dollars OnlyDollars & PointsPoints Only
Figure 6.3: Currency Preferences in Airline Context
Need for Cognition. The mean score in this sample was 57.62, with scores ranging
from 34 to 87. Subjects were split into high and low need-for-cognition groups based on
the median (score of 55.5) split. Among the high need-for-cognition respondents, 62.3%
preferred points-only, 20.8% preferred the combined currency (dollars and points) and
17.0% preferred dollars-only. For low need-for-cognition respondents, 60.4%preferred
points-only, 30.2% preferred the combined currency (dollars and points) and 9.4%
preferred dollars-only. According to Figure 6.4, the preferences for the combined
currency (dollars and points) for low need-for-cognition respondents were higher than
those for high need for cognition respondents.
112
0%10%20%30%40%50%60%
70%
High NFC Low NFC Dollars OnlyDollars & PointsPoints Only
Figure 6.4: Currency Preferences for Need for Cognition in Airline Context Multinomial Logistic Regression Analysis
For price level of airline ticket, high-priced ticket was the reference category. The
effect of price level of airline ticket was not significant when comparing the preference
for the combined-currency (dollars and points) to the preference for dollars-only and
when comparing the preference for points-only to the preference for dollars-only.
However, in case of need for cognition, the effect of need for cognition was
positive and significant at 0.05 level (p=.04) when comparing the preference for the
combined-currency (dollars and points) to the preference for the dollars-only, but was not
significant when comparing the preference for points-only to the preference for
dollars-only (Table 6.4). The estimated odds for high need-for-cognition respondents was
4.139. This suggests that low need-for-cognition respondents were 4.139 times more
likely to prefer to pay with the combined-currency (dollars and points), as opposed to
113
dollars-only, than high need-for-cognition respondents. Since the sample size for the cell
of the interaction of price level of airline ticket and airline need for cognition was too
small, the interaction was not included in the analysis.
Table 6.4: Results of Multinomial Logistic Regression Analysis for Airline Context
Dollars + Points vs. Dollars-only Variables (n=106) β S.E. Sig. Exp (β)
Airline Ticket (omitted High-Priced)
Mid-Priced -1.222 .949 .198 .295 Low-Priced -.194 .836 .817 .824
Need for Cognition (omitted Low NFC )
High NFC 1.421** .712 .046 4.139
Constant .886 1.071 .408 Points-only vs. Dollars-only
Variables (n=106) β S.E. Sig. Exp (β)
Airline (omitted High-Priced)
Mid-Priced -.087 .840 .918 .917 Low-Priced .647 .705 .358 1.910
Need for Cognition (omitted Low NFC )
High NFC .700 .625 .263 2.015
Constant .905 .941 .408
114
Summary of the Results
Although the effects of restaurant segment and price level of airline ticket were not
significant in multinomial logistic regression, the patterns of consumers’ currency
preferences were different in three different price levels in descriptive analysis. The
tendency to prefer points-only decrease as lower amount of payment is involved.
Consumers’ preferences for the combined currency (dollars and points) are higher for
mid-priced level while the preferences for dollars-only are higher for low-priced level
compared to two other price levels.
In addition, the effect of need for cognition is significant when comparing the
preference for the combined-currency (dollars and points) to the preference for the
dollars-only in airline context, but was not significant in restaurant context. The reason
may be that there are larger amount of payments involved in airline context compared to
restaurant context. In airline context, low need-for-cognition consumers were more likely
to prefer to pay with the combined-currency (dollars and points), as opposed to
dollars-only, than high need-for-cognition consumers. Although the result is the opposite
the prediction of H2 in the original study, it still suggests that need for cognition is one of
the factor influencing consumers’ currency preference. Consumers’ need for cognition
may be stimulated when larger amount of payments are involved. The price range in
different industries varies; therefore, the effect of need for cognition may differ by
different industry contexts.
115
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APPENDIX A
Results of Multinomial Logistic Regression Analysis: 188 samples included for Need for Cognition
130
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Continued Table A.1: Results of Multinomial Logistic Regression Analysis: Dollars and Points
versus Dollars-only (188 samples included for Need for Cognition)
Dollars + Points vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Demographic Variables Gender (omitted Male)
Female -.180 .502 .720 .835
Age (omitted 26 or older)
18-20 -1.539 1.276 .228 .215 21-23 -.948 1.213 .434 .387 24-26 -.921 1.380 .504 .398
Employment (omitted Yes)
No -.090 .534 .866 .914
Total Monthly Spending (omitted Low: under $520)
High (over $770) 1.180 .789 .135 3.254 Middle ($521-$770) .070 .794 .929 1.073
Monthly Spending in Food (omitted Low: under $100)
High (over $200) .382 .769 .619 1.465 Middle ($101-$200) .605 .893 .498 1.831
Independent Variables
Restaurant Segment (omitted Fine-Dining)
Casual-Dining -1.256 1.074 .242 .285 QSR -.978 .998 .327 .376
Need for Cognition (omitted Low NFC )
High NFC -.354 .871 .685 .702
Self-Monitoring (omitted Low SEM )
High SEM .251 1.048 .811 1.285
131
Table A.1 Continued
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Dollars + Points vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Companions (omitted Boss )
Friend .004 .819 .996 1.004 Alone -.744 .883 .399 .475
Interactions
NFC*Casual-Dining .353 1.303 .786 1.423 NFC*QSR .671 1.210 .579 1.956
SEM*Casual-Dining 1.683 1.271 .185 5.383 SEM*QSR 1.206 1.155 .297 3.340
SEM* Friend -1.096 1.146 .339 .334 SEM*Alone -1.858 1.336 .164 .156
Constant 2.061 3.206 .520
132
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Continued Table A.2: Results of Multinomial Logistic Regression Analysis: Points-only versus
Dollars-only (188 samples included for Need for Cognition)
Points-only vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Demographic Variables Gender (omitted Male)
Female -.186 .413 .652 .830
Age (omitted 26 or older)
18-20 -.120 .803 .881 .887 21-23 .797 .709 .261 2.220 24-26 .860 .898 .338 2.363
Employment (omitted Yes)
No .445 .466 .339 1.561
Total Monthly Spending (omitted Low: under $520)
High (over $770) -.669 .638 .294 .512 Middle ($521-$770) -.391 .694 .574 .677
Monthly Spending in Food (omitted Low: under $100)
High (over $200) .388 .680 .568 1.474 Middle ($101-$200) .280 .760 .713 1.323
Independent Variables
Restaurant Segment (omitted Fine-Dining)
Casual-Dining .128 .857 .882 1.136 QSR .487 .791 .538 1.627
Need for Cognition (omitted Low NFC )
High NFC .228 .683 .738 1.257
Self-Monitoring (omitted Low SEM )
High SEM .897 .835 .283 2.453
133
Table A.2 Continued
∗, ∗∗, and ∗∗∗Significance levels at the .1, .05, and .01
Points-only vs. Dollars-only Variables (n=471) β S.E. Sig. Exp (β)
Companions (omitted Boss )
Friend -.277 .671 .680 .758 Alone -1.430** .747 .055 .239
Interactions
NFC*Casual-Dining -1.005 1.025 .327 .366 NFC*QSR -.600 .979 .540 .549
SEM*Casual-Dining .436 1.006 .664 1.547 SEM*QSR .154 .937 .869 1.167
SEM* Friend -1.045 .916 .254 .352 SEM*Alone -1.241 1.171 .289 .289
Constant 2.846 2.285 .213
134
APPENDIX B
EXPERIMENT INSTRUMENTS
135
INSTRUCTIONS:
o The statements below concern your personal reactions to a number of different situations.
o No two statements are exactly alike, so consider each statement carefully before answering.
o If a statement is TRUE or MOSTLY TRUE as applied to you, circle the "T" next to the question.
o If a statement is FALSE or NOT USUALLY TRUE as applied to you, circle the "F" next to the question.
Items True False 1 I find it hard to imitate the behavior of other people. T F 2 At parties and social gatherings, I do not attempt to do or say
things that others will like. T F
3 I can only argue for ideas which I already believe. T F 4 I can make impromptu speeches even on topics about which I
have almost no information. T F
5 I guess I put on a show to impress or entertain others. T F 6 I would probably make a good actor. T F 7 In a group of people I am rarely the center of attention. T F 8 In different situations and with different people, I often act like
very different persons. T F
9 I am not particularly good at making other people like me. True False 10 I'm not always the person I appear to be. T F 11 I would not change my opinions (or the way I do things) in order
to please someone or win their favor. T F
12 I have considered being an entertainer. T F 13 I have never been good at games like charades or
improvisational acting. T F
14 I have trouble changing my behavior to suit different people and different situations. T F
15 At a party I let others keep the jokes and stories going. T F 16 I feel a bit awkward in public and do not show up quite as well
as I should. T F
17 I can look anyone in the eye and tell a lie with a straight face (if for a right end). T F
18 I may deceive people by being friendly when I really dislike them. T F
136
INSTRUCTIONS:
o For each of the statements below, please indicate to what extent the statement is characteristic of you.
- If the statement is extremely uncharacteristic of you (not at all like you) please circle a “1”
- If the statement is extremely characteristic of you (very much like you) please circle“5”
- If a statement is neither extremely uncharacteristic nor extremely characteristic of you; then please use the number in the middle of the scale that describes the best fit.
Items Not at all Very much Like me Like me
1 I would prefer complex to simple problems 1 2 3 4 5 2 I like to have the responsibility of handling a
situation that requires a lot of thinking 1 2 3 4 5
3 Thinking is not my idea of fun 1 2 3 4 5 4 I would rather do something that requires
little thought than something that is sure to challenge my thinking abilities
1 2 3 4 5
5 I try to anticipate and avoid situations where there is likely chance I will have to think in depth about something
1 2 3 4 5
6 I find satisfaction in deliberating hard and for long hours
1 2 3 4 5
7 I only think as hard as I have to 1 2 3 4 5 8 I prefer to think about small, daily projects
to long-term ones 1 2 3 4 5
9 I like tasks that require little thought once I’ve learned them.
1 2 3 4 5
10 The idea of relying on thought to make my way to the top appeals to me 1 2 3 4 5
11 I really enjoy a task that involves coming up with new solutions to problems 1 2 3 4 5
12 Learning new ways to think doesn’t excite me very much 1 2 3 4 5
13 I prefer my life to be filled with puzzles that I must solve 1 2 3 4 5
14 The notion of thinking abstractly is appealing to me 1 2 3 4 5
15 I would prefer a task that is intellectual, difficult, an important to one that is somewhat important but does not require much thought.
1 2 3 4 5
137
Items Not at all Very much
Like me Like me 16 I feel relief rather than satisfaction after
completing a task that required a lot of mental effort
1 2 3 4 5
17 It’s enough for me that something gets the job done; I don’t care how or why it works 1 2 3 4 5
18 I usually end up deliberating about issues even when they do not affect me personally 1 2 3 4 5
138
Please answer the following questions
1. Gender: Male_________ Female ________
2. Age: Under 18______ 18 to 20______ 21 to 23______ 24 to 26______ 26 or older______
3. Are you currently employed? Yes______ No______
4. What is your estimate monthly spending for the following items? Rent______ Food______ Entertainment______
5. Are you familiar with the frequent-flier miles programs? Unfamiliar Familiar
1 2 3 4 5 6 7
6. Are you knowledgeable about the frequent-flier program? Not Knowledgeable Knowledgeable
1 2 3 4 5 6 7
7. Do you have a frequent-flier account? Yes______ No______
8. Are you experienced in redeeming frequent-flier miles? Inexperienced Experienced
1 2 3 4 5 6 7
139
TREATMENT A
Fine-Dining Restaurant Dining with the Boss
140
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You have worked with an upscale department store in the upper- Midwest part of the United States. You have been ranked as one of the top-performing managers of your company for two years in a row. And you are expecting to get a promotion soon. You report to the regional manager, who in turn reports to the vice-president. Your regional manager called yesterday to alert you that the vice-president will be in town to visit your market. He is on his way from San Francisco to Boston and stopping over for only one day. The vice-president reports directly to the president of the company. His visit is very important to you and your anticipated promotion. You know the vice-president enjoys good food and wine, and you want to take him to the BEST fine dining restaurant in town. From your past experience, you expect the restaurant bill would be around $150 for the two of you.
141
This fine dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($150).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this fine-dining experience with the following choices?
Very Unlikely Very Likely $150 1 2 3 4 5 6 7 $75 + 750 points 1 2 3 4 5 6 7 1500 points 1 2 3 4 5 6 7
2. Paying for this fine-dining experience with the following choices is -
Poor Choice Excellent Choice $75 + 750 points 1 2 3 4 5 6 7 $150 1 2 3 4 5 6 7 1500 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this fine-dining experience with the following choices?
Least Prefer Most Prefer 1500 points 1 2 3 4 5 6 7 $75 + 750 points 1 2 3 4 5 6 7 $150 1 2 3 4 5 6 7
4. How likely that you will pay for this fine-dining experience with the following choices?
Very Unlikely Very Likely $75 + 750 points 1 2 3 4 5 6 7 $150 1 2 3 4 5 6 7 1500 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
142
TREATMENT B
Fine-Dining Restaurant Dining with a Friend
143
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You and your best friend from high school are going to graduate from college next week. You both are very excited. It is like a dream come true. After the graduation, your Best Friend will be leaving town to join a major corporation in Boston, and you will be heading west to Los Angeles to work with a major consumer corporation. You may not see each other for a while as you both pursue careers at the opposite ends of the country. It will be a long time before you both have a dinner together. So you have decided to take your Best Friend to dinner to celebrate your graduation and beginning of new careers for both of you. You know that s/he enjoys dining at the BEST fine-dining restaurants in town. You want to take her/him to her/his favorite restaurant which also happens to be your favorite one too. From your past experience, you know that the restaurant bill would be around $150 for the two of you.
144
This fine dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few years, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($150).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this fine-dining experience with the following choices?
Very Unlikely Very Likely $150 1 2 3 4 5 6 7 $75 + 750 points 1 2 3 4 5 6 7 1500 points 1 2 3 4 5 6 7
2. Paying for this fine-dining experience with the following choices is -
Poor Choice Excellent Choice $75 + 750 points 1 2 3 4 5 6 7 $150 1 2 3 4 5 6 7 1500 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this fine-dining experience with the following choices?
Least Prefer Most Prefer 1500 points 1 2 3 4 5 6 7 $75 + 750 points 1 2 3 4 5 6 7 $150 1 2 3 4 5 6 7
4. How likely that you will pay for this fine-dining experience with the following choices?
Very Unlikely Very Likely $75 + 750 points 1 2 3 4 5 6 7 $150 1 2 3 4 5 6 7 1500 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
145
TREATMENT C
Fine-Dining Restaurant Dining Alone
146
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You opened your mail yesterday. You were pleasantly
surprised and delighted to learn that you were selected as the “Outstanding Student of the Year” from your college. You will receive the award during the university graduation ceremonies. To celebrate this accomplishment, you want to take one of your friends to dinner to a fine-dining restaurant in town. You made the reservation for 2 people for 6 pm. You arrived early and were waiting for your friend. You ordered your favorite drink while waiting. Around 6:10pm, you receive a call from you friend and s/he sounds very upset. S/he has to take her/his father to the emergency room right away. S/he is unable to join you for dinner. Since you are already at the restaurant, have a reservation and ordered the drinks already, you have decided to order the meal anyway. From your past experience, you know that the restaurant bill would be around $70 for one person.
147
This fine dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($70).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this fine-dining experience with the following choices?
Very Unlikely Very Likely $70 1 2 3 4 5 6 7 $35 + 350 points 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
2. Paying for this fine-dining experience with the following choices is -
Poor Choice Excellent Choice $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this fine-dining experience with the following choices?
Least Prefer Most Prefer 700 points 1 2 3 4 5 6 7 $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7
4. How likely that you will pay for this fine-dining experience with the following choices?
Very Unlikely Very Likely $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
148
TREATMENT D
Causal-Dining Restaurant Dining with the Boss
149
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation o
o
o
o
You are the general manager of an upscale department store in upper-Midwest part of the United States. The district manager of your company is in town for his market inspection and also visits your market. He has been extremely busy working all day. He spent the whole day in reviewing sales reports, financial reports and personnel documents in your market and meeting with the managers in your unit. So your district manager is looking for someplace to relax and also wants to get to know the town. He doesn’t want to dress for the evening and wants a casual atmosphere so that everyone is at ease and comfortable. You know he enjoys good food more than a fancy place. So, you want to take him to a popular causal-dining restaurant in town to welcome him. From your past experience, you know that the restaurant bill would be around $70 for the two of you.
150
This casual dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($70).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this causal-dining experience with the following choices?
Very Unlikely Very Likely $70 1 2 3 4 5 6 7 $35 + 350 points 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
2. Paying for this causal-dining experience with the following choices is -
Poor Choice Excellent Choice $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this causal-dining experience with the following choices?
Least Prefer Most Prefer 700 points 1 2 3 4 5 6 7 $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7
4. How likely that you will pay for this causal-dining experience with the following choices?
Very Unlikely Very Likely $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
151
TREATMENT E
Causal-Dining Restaurant Dining with a Friend
152
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You and your best friend from high school are going to graduate from college next week. You both are very excited. It is like a dream come true. After the graduation, your Best Friend will be leaving town to join a major corporation in Boston. And you will be heading west to Los Angeles to work with a major consumer corporation. You may not see each other for a while as you both pursue careers at the opposite ends of the country. It will be a long time before you both have a dinner together. So you have decided to take your Best Friend to a casual dinner to catch up on old time stories. You want a relaxed atmosphere with a few drinks. You want to take her/him to your favorite ‘hang out’ restaurant. From your past experience, you know that the restaurant bill would be around $70 for the two of you.
153
This casual dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($70).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this causal-dining experience with the following choices?
Very Unlikely Very Likely $70 1 2 3 4 5 6 7 $35 + 350 points 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
2. Paying for this causal-dining experience with the following choices is -
Poor Choice Excellent Choice $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this causal-dining experience with the following choices?
Least Prefer Most Prefer 700 points 1 2 3 4 5 6 7 $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7
4. How likely that you will pay for this causal-dining experience with the following choices?
Very Unlikely Very Likely $35 + 350 points 1 2 3 4 5 6 7 $70 1 2 3 4 5 6 7 700 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
154
TREATMENT F
Casual-Dining Restaurant Dining Alone
155
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You opened your mail yesterday. You were
pleasantly surprised and delighted to learn that you were selected as the “Outstanding Student of the Year” from your college. You will receive the award during the university graduation ceremonies. To share this news, you want to take one of your friends to dinner to a casual-dining restaurant in town. S/he was supposed to meet you at the restaurant around 6.00pm. You arrived early and were waiting for your friend. You ordered your favorite drink while you were waiting. Around 6:10pm, you receive a call from you friend and s/he sounds very upset. S/he has a family emergency and s/he has to take care of it right away. So s/he is unable to join you for dinner. Since you are already at the restaurant and ordered the drinks already, you have decided to order the meal anyway. From your past experience, you know that the restaurant bill would be around $30 for one person.
156
This casual dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($30).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this causal-dining experience with the following choices?
Very Unlikely Very Likely $30 1 2 3 4 5 6 7 $15 + 150 points 1 2 3 4 5 6 7 300 points 1 2 3 4 5 6 7
2. Paying for this causal-dining experience with the following choices is -
Poor Choice Excellent Choice $15 + 150 points 1 2 3 4 5 6 7 $30 1 2 3 4 5 6 7 300 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this causal-dining experience with the following choices?
Least Prefer Most Prefer 300 points 1 2 3 4 5 6 7 $15 + 150 points 1 2 3 4 5 6 7 $30 1 2 3 4 5 6 7
4. How likely that you will pay for this causal-dining experience with the following choices?
Very Unlikely Very Likely $15 + 150 points 1 2 3 4 5 6 7 $30 1 2 3 4 5 6 7 300 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
157
TREATMENT G
Quick Service Restaurant
Dining with the Boss
158
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You and your boss just finished a meeting with a client.
It was a long presentation, and you both are tired. It is lunch time, and both of you are very hungry. You have another major presentation tomorrow with a new client, and you and your boss still have a lot to discuss about the presentation and strategies. Since there is so much work to be done, you don’t want take too long for lunch. So you both have agreed to go to the soup-and-sandwich deli located in the first floor of the corporate office. As a frequent customer, you know that the lunch would cost around $14 for the two of you.
159
This quick service restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($14).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this experience in quick service restaurant with the following choices?
Very Unlikely Very Likely $14 1 2 3 4 5 6 7 $7 + 70 points 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
2. Paying for this experience in quick service restaurant with the following choices is -
Poor Choice Excellent Choice $7 + 70 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this experience in quick service restaurant with the following choices?
Least Prefer Most Prefer 140 points 1 2 3 4 5 6 7 $7 + 700 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7
4. How likely that you will pay for this experience in quick service restaurant with the following choices?
Very Unlikely Very Likely $7 + 70 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
160
TREATMENT H
Quick Service Restaurant Dining with a Friend
161
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
o
You and your friend are taking a course together. It
is a senior-level course. You and your friend are working at your apartment on a class project for that course which is due at 5:00 this afternoon. It is lunch time and both of you are hungry. You both agree to take a quick break and don’t want to waste too much time. It is your turn to buy the lunch as your friend paid for it yesterday. To save time, you decide to go to a quick service restaurant located a block from your apartment. You know that the bill for lunch would be around $14 for the two of you.
162
This quick service restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($14).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this experience in quick service restaurant with the following choices?
Very Unlikely Very Likely $14 1 2 3 4 5 6 7 $7 + 70 points 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
2. Paying for this experience in quick service restaurant with the following choices is -
Poor Choice Excellent Choice $7 + 70 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this experience in quick service restaurant with the following choices?
Least Prefer Most Prefer 140 points 1 2 3 4 5 6 7 $7 + 700 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7
4. How likely that you will pay for this experience in quick service restaurant with the following choices?
Very Unlikely Very Likely $7 + 70 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
163
TREATMENT I
Quick Service Restaurant Dining Alone
164
Dear Participant,
o We are seeking your true reactions to a situation that you might actually experience
in daily life.
o After reading the scenario, please respond to the questions in a natural manner
--the way you believe you would actually react.
Please imagine yourself in the following situation
You and your friend are taking a course together. It is a senior level course. You and your friend have decided to work at your apartment on a class project for that course which is due at 5:00 this afternoon. He is supposed to meet you around 2:00 pm. You have been working on this project all morning. It is lunch time and you are little hungry. So you want to take a little break and eat lunch quickly before your friend arrives. To save time, you decide to go to a quick service restaurant located a block from your apartment. You know that the lunch would cost around $6.
165
This quick service restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected abundant points over the past few visits, and you have sufficient cash too. So tonight you have 3 CHOICES while paying for your dinner ($6).
The exchange rate: $10 = 100 points
Please answer the following questions
1. How likely that you agree to pay for this experience in quick service restaurant with the following choices?
Very Unlikely Very Likely $14 1 2 3 4 5 6 7 $7 + 70 points 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
2. Paying for this experience in quick service restaurant with the following choices is -
Poor Choice Excellent Choice $7 + 70 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
3. How do you prefer to pay for this experience in quick service restaurant with the following choices?
Least Prefer Most Prefer 140 points 1 2 3 4 5 6 7 $7 + 700 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7
4. How likely that you will pay for this experience in quick service restaurant with the following choices?
Very Unlikely Very Likely $7 + 70 points 1 2 3 4 5 6 7 $14 1 2 3 4 5 6 7 140 points 1 2 3 4 5 6 7
5. Please briefly explain the rational behind your choice.
____________________________________________________________________
____________________________________________________________________
166
APPENDIX C
EXPERIMENT INSTRUMENTS FOR POSTSCRIPT
167
AIRLINE CONTEXT
TREATMENT A
High-Priced Airline Ticket
168
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience in
daily life.
o After reading the scenario, please respond to the questions in a natural manner --
the way you believe you would actually react.
Please imagine yourself in the following situation How would you like to pay for the airline ticket? [Exchange rate: $10 = 500 miles] Please rank the following 5 options on a scale of 1 to 5:
1 = most preferred 5 = least preferred
$1,200
$860 +
17,000miles
$600 +
30,000miles
$240 +
48,000miles
60,000 miles
_______
_______
_______
_______
_______
You are on the phone with an airline, securing a roundtrip ticket to visit your uncle whom you really like and admire. Since it is not an
advance purchase, you must pay full price for the ticket. The price of the ticket is $1,200.
You have a frequent flier account with this particular airline. You have 60,500 miles in your frequent flier account, and you have
sufficient cash too.
169
AIRLINE CONTEXT
TREATMENT B
Mid-Priced Airline Ticket
170
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience in
daily life.
o After reading the scenario, please respond to the questions in a natural manner --
the way you believe you would actually react.
Please imagine yourself in the following situation How would you like to pay for the airline ticket? [Exchange rate: $10 = 500 miles] Please rank the following 5 options on a scale of 1 to 5:
1 = most preferred 5 = least preferred
$560
$420 +
7000miles
$280 +
14,000miles
$140 +
21,000miles
28,000 miles
_______
_______
_______
_______
_______
You are on the phone with an airline, securing a roundtrip ticket to visit your uncle whom you really like and admire. Since it is not an advance purchase, you must pay full price for the ticket. The price
of the ticket is $560.
You have a frequent flier account with this particular airline. You have 28,500 miles in your frequent flier account, and you have
sufficient cash too.
171
AIRLINE CONTEXT
TREATMENT C
Low-Priced Airline Ticket
172
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience in
daily life.
o After reading the scenario, please respond to the questions in a natural manner --
the way you believe you would actually react.
Please imagine yourself in the following situation
How would you like to pay for the airline ticket? [Exchange rate: $10 = 500 miles] Please rank the following 5 options on a scale of 1 to 5:
1 = most preferred 5 = least preferred
$180
$135 +
2250miles
$90 +
4,500miles
$45 +
6,750miles
9,000 miles
_______
_______
_______
_______
_______
You are on the phone with an airline, securing a roundtrip ticket to visit your uncle whom you really like and admire. Since it is not an advance purchase, you must pay full price for the ticket. The price
of the ticket is $180.
You have a frequent flier account with this particular airline. You have 9,500 miles in your frequent flier account, and you have
sufficient cash too.
173
RESTAURANT CONTEXT
TREATMENT A
Fine-Dining Restaurant
174
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience in
daily life.
o After reading the scenario, please respond to the questions in a natural manne r--
the way you believe you would actually react.
Please imagine yourself in the following situation
How would you prefer to pay?
[Exchange rate: $10 = 500 points] Please rank the following 5 options on a scale of 1 to 5:
1 = most preferred 5 = least preferred
$68
$52 +
800 points
$34 +
1,700 points
$18 +
2,500 points
3,400 points
_______
_______
_______
_______
_______
You are a member of the student association. It is the end of the quarter. As usual, the association holds a party at a fine dining
restaurant for all members to celebrate this year’s achievements. Everyone gets a separate check to pay his/her meal. Your bill for
the meal in this fine dining restaurant is $68.
This fine dining restaurant has a loyal customer reward program for customers to accumulate points at each visit. As a frequent guest, you have collected 3,500 points in your account over the
past few years, and you have sufficient cash too.
175
RESTAURANT CONTEXT
TREATMENT B
Casual-Dining Restaurant
176
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience in
daily life.
o After reading the scenario, please respond to the questions in a natural
manner--the way you believe you would actually react.
Please imagine yourself in the following situation How would you prefer to pay?
[Exchange rate: $10 = 500 points] Please rank the following 5 options on a scale of 1 to 5:
1 = most preferred 5 = least preferred
$32
$24 +
600points
$16 +
800points
$8 +
1,200 points
1,600 points _______
_______
_______
_______
_______
You are a member of the student association. It is the end of the
quarter. As usual, the association holds a party at a casual dining restaurant for all members to celebrate this year’s
achievements. Everyone gets a separate check to pay his/her meal. Your bill for the meal in this casual dining restaurant is $32.
This casual dining restaurant has a loyal customer reward
program for customers to accumulate points at each visit. As a frequent guest, you have collected 1,700 points in your account
over the past few years, and you have sufficient cash too.
177
RESTAURANT CONTEXT
TREATMENT C
Quick-Service Restaurant
178
Dear Participant, o We are seeking your true reactions to a situation that you might actually experience in
daily life.
o After reading the scenario, please respond to the questions in a natural
manner--the way you believe you would actually react.
Please imagine yourself in the following situation
How would you prefer to pay?
[Exchange rate: $10 = 500 points] Please rank the following 5 options on a scale of 1 to 5:
1 = most preferred 5 = least preferred
$6
$4 +
100points
$3 +
150points
$2 +
200points
300 points
_______
_______
_______
_______
_______
You are a member of the student association. It is the end of the
quarter. As usual, the association holds a party at a quick service restaurant for all members to celebrate this year’s achievements.
Everyone gets a separate check to pay his/her meal. Your bill for the meal at this quick service restaurant is $6.
This quick service restaurant has a loyal customer reward
program for customers to accumulate points at each visit. As a frequent guest, you have collected 400 points in your account over
the past few years, and you have sufficient cash too.
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