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dissertation entitled

THE IMPORTANCE OF C CUSTOMER SATISFACTION AND
DELIGHT ON LOYALTY IN THE TOURISM
AND HOSPITALITY INDUSTRY

presented by

MI RAN KIM

has been accepted towards fulfillment
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PhD. degree in Community Agriculture Recreation and Resource Studies

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THE IMPORTANCE OF CUSTOMER SATISFACTION AND DELIGHT
ON LOYALTY IN THE TOURISM AND HOSPITALITY INDUSTRY
By

Mi Ran Kim

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY

Community, Agriculture, Recreation, and Resource Studies

2010

ABSTRACT
THE IMPORTANCE OF CUSTOMER SATISFACTION AND DELIGHT ON
LOYALTY IN THE TOURISM AND HOSPITALITY INDUSTRY
By
Mi Ran Kim

Customer satisfaction has been a focus of researchers and marketers as an
important antecedent of customer loyalty. Research has proven that satisfied customers
show loyalty by purchasing more products or services, recommending products to others,
and being less price sensitive (Anderson, Fomell, and Mazvancheryls, 2004; Homburg,
Koschate, and Hoyer, 2005). Recent studies propose customer delight as a new variable
of interest in satisfaction research and are anticipated to possibly produce greater
customer loyalty than satisfaction (Hicks, Page, Behe, Dennis, and Fernandez, 2005).
Like customer satisfaction, customer loyalty is also considered crucial to the success of a
business organization because loyal customers are less expensive to retain than to find
and develop new customers (Reichheld and Sasser, 1990). In recent years interest has
also grown in understanding the multi-phases of loyalty as a useful way to segment
customers with differential strategies (Knox and Walker, 2001; McMullan and Gilmore,
2002; Palmer, McMahon-Beanie, and Beggs, 2000).

The problem of this research is to examine the impact of customer satisfaction
and delight on loyalty by empirically testing a model. Furthermore, the study aims to
better understand four phases of loyalty development: cognitive, affective, conative, and
action loyalties. Data were collected from guests who stayed at a Midwestern resort

during a peak summer vacation time using an online and a paper survey (1,573 subjects

from an online survey, 87 subjects from a paper survey). The model was tested applying
structural equation modeling (SEM) to estimate the relationship between customer
satisfaction, delight, and loyalty in a tourism and hospitality context.

The findings support the proposed model and suggest that (1) customer
satisfaction has a direct and positive influence on cognitive and affective loyalty; (2)
customer delight has a direct and positive influence on cognitive and affective loyalty; (3)
customer satisfaction has a greater influence on cognitive loyalty than on customer
delight; (4) customer delight has a greater influence on affective loyalty than on customer
satisfaction; (5) cognitive and affective loyalties have a direct and positive influence on
conative loyalty; and (6) conative loyalty has a direct and positive influence on action
loyalty.

This study is one of few empirical studies on customer satisfaction, delight, and
loyalty and tests a more comprehensive model than previous research efforts. This study
will contribute to the body of knowledge on customer satisfaction, delight, and loyalty
and provide important theoretical and applied suggestions for the tourism and hospitality
industry. Future studies should replicate the findings and test the model with different
samples such as types of accommodations (e. g., business hotel, bed and breakfast), places
(e.g., other states, other countries), and service industries (e. g., restaurant, airline, cruise).
With attitudinal research, validating the accuracy of action loyalty or intended future
behaviors should be validated with actual measures of future returns to the business and

recommendations of the business to others.

DEDICATION

I would like to dedicate this dissertation to my beloved husband, Ki— Wan Park,
for his unconditional love and full support,
to my father, Kwaung—Ok Kim,
for his sacrificial love and support from heaven,
to my angel daughter, Yenna Park,
for being the joy and blessing of my life,

and to God for making all of this possible.

ACKNOWLEDGEMENTS

The long doctoral journey would not have been possible without support of many
people. I wish to express to them my sincere gratitude.

I am most appreciative of my two advisers, Dr. Christine A. Vogt and Dr. Bonnie
J. Knutson. They were always right there to listen and to give advice to me. They are my
forever mentors. Especially, I would like to give my deep appreciation to Dr. Christine A.
Vogt, committee chair, for her guidance, expertise, genuine caring, patience, and time.
She has profoundly shaped the research and writing of this study. She guided me during
every step of my Ph.D. journey and assigned priority to my success in the doctoral
program, providing the right balance of challenge and support. She is the best role model
for me. I am also extremely grateful for the tremendous support that I have received Since
the MS. program from my co-adviser, Dr. Bonnie J. Knutson. She has been motivating,
encouraging, caring, and enlightening, not only for myself, but also for my family. She is
the true motivator and mentor who inspired me to be the true marketer..When I stood
behind her, I became confident and strong to get through all my challenges during my
PhD. journey. I am forever grateful to her, my CMP (Cool Mother Professor).

My sincere appreciation is extended to my dissertation committee member and
Director of The School of Hospitality Business, Dr. Ronald F. Cichy. Without his sincere
support, guidance, expertise, and encouragement, I could not have completed my Ph.D.
journey successfully. He is The Leader to me and I will be The Follower. I am also very
grateful to the remaining members of my dissertation committee, Dr. Richard D. Paulsen
and Dr. Jeffrey A. Beck, for their academic support, expertise, encouragement, and time

in producing this work.

vi

I deeply thank Dr. Annette Rummel, president of Great Lakes Bay Regional
Convention & Visitors Bureau, Mrs. Judith Zehnder Keller, president of F rankenmuth
Bavarian Inn Lodge, Mr. Jim Engel, general manger of F rankenmuth Bavarian Inn Lodge,
and the guests of Frankenmuth Bavarian Inn Lodge for supporting me during this study.

My gratitude is also extended to Dr. Eun-Sil Lee who is my spiritual sister. Her
love, care, and support were a treasure. She also gave me many precious memories
during my Ph.D. study and made a place in my heart only she will ever occupy. I want
her to know how much I was influenced by her servant leadership as a good example for
God’s people. I would like to thank Julie Tkach. I call her my American sister. We
laughed, cried, prayed, and worked together through our Ph.D. lives. I could not have
completed this journey without Julie by my side. Especially, I am grateful for her help in
editing my dissertation paper. I hope our sistership goes on forever. My friends in the
prayers meeting, “Sisters of Lydia”, have my appreciation for their love, compassionate
fi'iendship, and prayers during my doctoral journey.

I express deep gratitude to my life partner, Ki-Wan Park for his full support, love,
and patience - it is my turn to return the favor now, and to my angel daughter, Yenna
Park, for being my joy and blessing all the time. Also I am greatly indebted to my
parents-in-law, Yong-Soo Park and Yong-Soon Choi, and my parents, Kwaung-Ok Kim
and Bok-Soon Kim, for their sacrificial support and unconditional love. Special thanks to
my sisters, sisters-in-law, brothers, brothers-in-law, nieces, and nephews. Thank you and
I love all of you.

Thank God! You were always with me, helped me, and blessed me. I praise Your

1181116.

vii

TABLE OF CONTENTS

LIST OF TABLES .............................................................................................................. x
LIST OF FIGURES .......................................................................................................... xii
CHAPTER 1 INTRODUCTION
Introduction of Constructs ................................................................................................. 1
Customer Satisfaction and Delight ..................................................................... 1
Customer Loyalty ............................................................................................... 2
Problem Statement ............................................................................................................. 3
Purpose of Study ................................................................................................................. 3
Conceptual Model and Hypotheses .................................................................................... 4
Delimitations ...................................................................................................................... 6
Definitions of Terms .......................................................................................................... 6

CHAPTER 2 LITERATURE REVIEW

Consumer Behavior ........................................................................................................... 8
Customer Satisfaction ...................................................................................................... 10
Customer Delight ............................................................................................................. 14
Customer Loyalty ............................................................................................................. l8
Affect and Cognition ........................................................................................................ 24
CHAPTER 3 RESEARCH DESIGN AND METHDOLOGY
Research Design ................................................................................................................ 29
Rationale for Research Method ........................................................................ 29
Sampling ........................................................................................................... 30
Pilot Study ........................................................................................................ 31
Data Collection ................................................................................................ 31
The Questionnaire ............................................................................................ 34
Survey Measurement ........................................................................................................ 34
Customer Satisfaction ...................................................................................... 34
Customer Delight ............................................................................................. 34
Cognitive Loyalty ............................................................................................ 35
Affective Loyalty ............................................................................................. 35
Conative Loyalty ............................................................................................... 36
Action Loyalty .................................................................................................. 36
Data Analysis .................................................................................................................... 38
CHAPTER 4 RESULTS
Preliminary Analyses ........................................................................................................ 40
Data Screening ................................................................................................. 40
Profile of Survey Respondents .......................................................................... 42
Traveling Characteristics of Survey Respondents ............................................ 42
Testing the Measurement Model ..................................................................................... 46
Confirmatory Factor Analysis ........................................................................... 46

viii

Assessment of Reliability and Validity ............................................................. 50

Testing the Structural Equation Model ............................................................................ 52
Multiple Squared Correlations .......................................................................... 56
Additional Analyses ......................................................................................................... 57
Additional Analysis with a Full Path Model .................................................... 57
Additional Analysis between New Guests and Repeat Guests ........................ 64
Additional Analysis between Loyalty Program Members and Non-Members 73
Summary .......................................................................................................................... 81
CHAPTER 5 DISCUSSION, IMPLICATIONS, AND CONCLUSION
Results of Hypotheses Testing and Discussion of the Findings ....................................... 82
Implications ....................................................................................................................... 86
Theoretical Implications ................................................................................... 86
Practical Implications ........................................................................................ 89
Limitations and Future Studies ......................................................................................... 94
Conclusion ........................................................................................................................ 95
APPENDICES .................................................................................................................. 97
BIBLIOGRAPHY .......................................................................................................... 108

ix

LIST OF TABLES

Table 1. Difference between Satisfaction and Delight .................................................... 18
Table 2. Four-Stage Loyalty Model ................................................................................. 22
Table 3. Types of Affective Responses ........................................................................... 25
Table 4. The Guest Profile of a Midwestern Resort ........................................................ 30
Table 5. Sampling Frame ................................................................................................. 30
Table 6. Data Collection .................................................................................................. 33
Table 7. Survey Measurement Items ................................................................................ 37
Table 8. Normality Test Results for Variables Included in the Proposed Model ............ 41
Table 9. Socio-Demographic Characteristics of Survey Respondents ............................. 43
Table 10. Travel Characteristics of Survey Respondents ................................................. 45
Table 11. The Recommended Goodness-Of-Fit Indices .................................................. 48
Table 12. Comparison of the Proposed and Modified Full Measurement Models ........... 49
Table 13. The Result of Confirmatory Factor Analysis for the Modified Measurement

Model 2 ............................................................................................................................ 51
Table 14. Discriminant Validity Matrix Local ................................................................. 52
Table 15. Results of Hypotheses Testing ......................................................................... 55
Table 16. Overall Fit Indices for the Hypothesized Structural Model .............................. 55
Table 17. The Results of the Proposed Model and the Full Path Model ......................... 61

Table 18. Socio-Demographic Characteristics of Survey Respondents between First-Time
Guests (or not Recent Guests in the Past 3 Years) and Repeat Guests ............................. 66

Table 19. Mean Difference in Satisfaction, Delight, Cognitive Loyalty, Affective Loyalty,
Conative Loyalty, and Action Loyalty between First-Time Guests (or not Recent Guests
in the Past 3 Years) and Repeat Guests ........................................................................... 67

Table 20. x2 Difference Tests ........................................................................................... 68

Table 21.. Comparison of Overall Fit Indices for Two Groups ......................................... 69

Table 22. Path Coefficients of the Hypothesized Models between the Groups of First-
Time Guests (or not Recent Guests in the Past 3 Years) ................................................. 70

Table 23. Socio-Demographic Characteristics of Survey Respondents between First-Time
Guests (or not Recent Guests in the Past 3 Years) and Repeat Guests ............................. 74

Table 24. Mean Difference in Satisfaction, Delight, Cognitive Loyalty, Affective Loyalty,
Conative Loyalty, and Action Loyalty between Loyalty Program Members and Loyalty

Program Non-Members ................................................................................................... 75
Table 25. x2 Difference Tests ........................................................................................... 76
Table 26. Comparison of Overall Fit Indices for Two Groups ......................................... 76
Table 27. Path Coefficients of the Hypothesized Models between the Groups of Loyalty

Program Members and Loyalty Program Non-Members ................................................ 78
Table 28. Summary of the Hypothesized Findings .......................................................... 81

Table 29. Comparison of Demographic Characteristics between On—line Survey
Respondents and Paper Suervey Respondents .................................................................. 97

Table 30. Compariosn of Demographic Characteristics betweem Respondents and Non-
Respondents ...................................................................................................................... 99

xi

LIST OF FIGURES

Figure 1. Proposed Research Model .................................................................................. 4
Figure 2. Overall Model of Consumer Behavior ............................................................... 9
Figure 3. The Expectation-Disconfinnation Theory ....................................................... 11
Figure 4. A Model of Dissatisfaction, Outrage, Satisfaction, and Delight ..................... 17
Figure 5. The Relationship between Affect and Cognition ............................................. 27
Figure 6. The Proposed Measurement Model ................................................................... 46
Figure 7. Results of Testing the Proposed Structural Model with Standardized Path

Coefficients and Squared Multiple Correlations .............................................................. 53
Figure 8. The Proposed Model ................................. . ........................................................ 58
Figure 9. The Full Path Model ......................................................................................... 59

Figure 10. Results of Testing the Proposed Structural Model with Standardized Path
Coefficients and Squared Multiple Correlations ............................................................... 62

Figure 11. Results of Testing the Full Path Structural Model with Standardized Path
Coefficients and Squared Multiple Correlations .............................................................. 63

Figure 12. Results of Testing the Structural Model with Standardized Path Coefficients
and Squared Multiple Correlations (A Group of First-Time Guests or not Recent Guests
in the Past 3 Years) .......................................................................................................... 71

Figure 13. Results of Testing the Structural Model with Standardized Path Coefficients
and Squared Multiple Correlations (A Group of Repeat Guests) .................................... 72

Figure 14. Results of Testing the Structural Model with Standardized Path Coefficients
and Squared Multiple Correlations (A Group of Loyalty Program Members) ................ 79

Figure 15. Results of Testing the Structural Model with Standardized Path Coefficients
and Squared Multiple Correlations (A Group of Loyalty Program Non-Members) ........ 80

Figure 16. Proposed Conceptual Model ........................................................................... 83

xii

CHAPTER 1

INTRODUCTION

This chapter includes the following sections: (1) Introduction of Constructs:
Customer Delight, Satisfaction, and Loyalty; (2) Problem Statement; (3) Purpose of
Study; (4) Proposed Research Model and Hypotheses; (5) Delimitations; and (6)
Definitions of Terms.

Introduction of Constructs
Customer Satisfaction and Delight

Customer satisfaction has been a dominant benchmark among marketers in
measuring their success as a fundamental factor to the well-being of individual customers
and to the profits of organizations supported through purchasing and patronization
(Oliver, 1997). Much literature demonstrates customer satisfaction is considered the main
antecedent of customer loyalty. Research has proven that satisfied customers Show
loyalty by purchasing more products or services, recommending products to others, and
being less price sensitive (Anderson, Fornell, and Mazvancheryls, 2004; Ajzen and
Driver, 1991; Chen and Gursoy, 2001; Homburg, Koschate, and Hoyer, 2005; Shoemaker
and Lewis, 1999; Yoon and Uysal, 2005).

Previous studies question whether satisfied customers are truly loyal (Johns and
Sasser, 1995; Skogland and Siguaw, 2004; Stewart, 1997) and some have also begun to
emphasize customer delight, which is beyond satisfaction, and may produce greater
loyalty or attractive attitudinal or behavioral states (Hicks, Page, Behe, Dennis, and
Fernandez, 2005; Schlossberg, 1990;). Customer delight can be the key to reaching

loyalty through offering the “wowing” experience for the customer (Oliver, Rust, and

Varki, 1997; Patterson, 1997; Torres and Kline, 2006) and delight can be an important
factor of profitability and competitive advantage, provided that particular service is not
easy to imitate, nor costly to implement (Oliver and Rust, 2000).

However, despite the wide acceptance of the customer delight concept, this idea
has not been given a clear theoretical foundation, measurement instruments, and
identification of antecedents and consequences of customer delight, nor has customer
delight been empirically related to customer satisfaction or loyalty.

Custom er Loyalty

Like customer satisfaction, customer loyalty is considered crucial to the success
of business organizations with the growing realization that it is much less expensive to
retain current customers than to find and develop new ones. Reichheld and Sasser (1990)
showed that a 5 percent improvement in customer retention can cause an increase in
profitability between 25 and 85 percent (in terms of net present value) depending on the
industry.

Academic research on customer loyalty has received considerable attention with
many studies exploring the linkage between customer loyalty and satisfaction. Some
loyalty studies have distinguished between the attitudinal and behavioral dimensions of
loyalty with a framework for understanding different phases of loyalty development
(Dick and Basu, 1994; Jacoby and Kyner, 1973; Knox and Walker, 2001; Oliver, 1997).
According to Jacoby and Kyner (1973), loyalty can be viewed as developing in three
phases: first, customers become loyal in a cognitive sense, then second, in an affective
sense, and third, in a conative manner. Oliver (1997) suggested a fourth phase, action

loyalty, which allows for completion of the loyalty framework.

The development of customer loyalty has become an important marketing strategy
for many years due to the benefits associated with retaining existing customers
(McMullan and Gilmore, 2002) and understanding the multi-phase processes of loyalty
for segmenting customers with differential strategies according to phases (Knox and
Walker, 2001; Palmer, McMahon-Beattie, and Beggs, 2000). However, there is little
empirical research to adequately explore the relationships between customer satisfaction,
delight, and loyalty, along with the four phases of a customer’s attitudinal and behavioral
states.

This research seeks to contribute to addressing this gap in the context of the
tourism and hospitality industry by empirically testing a conceptual framework to
understand more fully cognitive, affective, conative, and action loyalties.

Problem Statement

This study is aimed at understanding (1) how customer satisfaction and delight
influence loyalty, and (2) the existence of cognitive, affective, conative, and action
loyalties. These relationships will be in the context of the tourism and hospitality industry
with first time and repeat customers, as well as customers belonging (or not) to a paid
loyalty membership program.

Purpose of Study

This study is one of few empirical studies examining the relationships among
customer satisfaction, delight, and loyalty and offering a better understanding of the four
loyalty phases. This study also empirically tests a more comprehensive model than
previous research efforts. The findings of this study are expected to provide a deeper

understanding of customer satisfaction, delight, and loyalty for managers to more

effectively serve customers by better understanding loyalty creation and retention.

Additionally, this study is expected to contribute to the development of the body of

knowledge of customer satisfaction, delight, and loyalty studies.

Conceptual Model and Hypotheses

Based on these relationships, a model is proposed in Figure 1.

 

Customer
Satisfaction

 

 

 

Hlb+

H22 +

 

Customer
Delight

 

 

 

 

 

H2b +

Attitudinal Loyalty

ICognitive
Loyalty

       
  

H4a +

Loyalty

a Loyalty ‘

 

Conative 1
l
I

“ma:
Loyalty; ,

TAT

 

 
  

 

 

Figure 1. Proposed Research Model

The following hypotheses are proposed:

 

.-.,I.fLLo_ya.lty_}jjl:ii

 

** Darker lines indicate a stronger influence: H3a & H3b

Hypothesis 1: Customer satisfaction will have a direct positive influence on attitudinal

loyalty.

Hypothesis 1a: Customer satisfaction will have a direct positive influence on

 

cognitive loyalty.
Hypothesis 1b: Customer satisfaction will have a direct positive influence on
affective loyalty.
Hypothesis 2: Customer delight will have a direct positive influence on attitudinal
loyalty.
Hypothesis 2a: Customer delight will have a direct positive influence on
cognitive loyalty.
Hypothesis 2b: Customer delight will have a direct positive influence on
affective loyalty.
Hypothesis 3: Customer delight will have a greater influence on attitudinal loyalty in
comparison to satisfaction.
Hypothesis 3a: Customer delight will have a greater positive influence on
cognitive loyalty in comparison to satisfaction.
Hypothesis 3b: Customer delight will have a greater positive influence on
affective loyalty in comparison to satisfaction.
Hypothesis 4: Customer cognitive loyalty will have a direct positive influence on
conative loyalty.
Hypotheses 5: Customer affective loyalty will have a direct positive influence on
conative loyalty.
Hypothesis 6: Customer conative loyalty will have a direct positive influence on

action loyalty.

Delimitations

This study is delimited to the following:
1. All subjects were hotel guests in the Midwest who stayed in the months of July,
August, and September 2009.
2. Guests with email addresses were selected, which allowed this study to include guests
from the US, Canada, and other countries for an approximate sample size of 3,700
participants.
3. The participants included new guests and repeat guests who stayed at this hotel within
the last three years. Both current loyalty club members and non-members were included.
Definition of Terms

The following terms are defined to clarify their use in this study:
Action Loyalty: Loyalty to the action of rebuying the service or product (Dick and Basu,
1994; Oliver, 1997).
Affective Loyalty: Loyalty to the liking of the service or product (Dick and Basu, 1994;
Oliver, 1997).

Cognitive Loyalty: Loyalty to information such as price and features (Dick and Basu,

 

1994; Oliver, 1997).

 

Conative Loyalty: Loyalty to an intention to repurchase the service or product (Dick and
Basu, 1994; Oliver, 1997).

Customer Delight: A higher level of satisfaction that exceeds a customer’s expectations
as a combination of high pleasure (joy, elation) and high activation (surprise) (Oliver et

aL,1997)

Customer Loyalty: A deeply held commitment to rebuy or repatronize a preferred
product or service consistently in the future, despite situational influences and marketing
efforts having the potential to cause switching behavior (Oliver, 1997).

Customer Satisfaction: The customer’s fulfillment response to a product or service
feature, or to the product or service itself, which provides a pleasurable level of
consumption-related fulfillment, including levels of under- or over-fulfillment (Oliver,
1997)

Delight: A combination of high pleasure (joy, elation) and high activation or surprise as
one of the second level emotions (Plutchik, 1980; Russell, 1980; Watson and Tellegen,

1.985).

CHAPTER 2

LITERATURE REVIEW

The literature related to this study is reported in this chapter. For organizational
purposes, the literature is presented under the following topics: (1) Consumer Behavior;
(2) Customer Satisfaction; (3) Customer Delight; (4) Customer Loyalty; and (5) Affect
and Cognition.

Consumer Behavior

By the end of the 20th century, the study of consumer behavior became more
important than ever as a result of changing market forces such as increased competition,
changing consumer lifestyle, the greater influence of the consumer, and a changing
business orientation from a manufacturing focus to a marketing focus. Since then, the
need to understand consumers and their behavior has been a core topic around the globe
(Blackwell, Miniard, and Engel, 2001).

Consumer behavior is an applied science drawing from economics, psychology,
sociology, anthropology, statistics, and other disciplines (Hawkins, Mothersbaugh, and
Best, 2007; Peter and Olson, 2005). Consumer behavior is the study of individuals,
groups, or organizations and the processes they use to select, secure, use, and dispose of
products, services, experiences, or ideas to satisfy needs and the impacts that these
processes have on the consumer and society (Hawkins, Mothersbaugh, and Best, 2007).
Consumer behavior is also defined as the dynamic interaction of affect and cognition,
behavior, and the environment by which human beings conduct the exchange aspects of

their lives (Bennett, 1995). Consumer behavior is purposeful and goal oriented; products

and services are selected or rejected according to the extent to which they are perceived
as relevant to the needs and the lifestyle of a consumer (Peter and Olson, 2005).
According to an overall model of consumer behavior as shown in Figure 2, a consumer
builds up self-concepts and subsequent lifestyles based on a mixture of internal (mostly
psychological and physical) and external (mostly sociological and demographic)
influences. These self-concepts and lifestyles produce needs and desires, many of which
require consumption decisions to satisfy. As consumers come across relevant situations,
the consumer decision process is activated. This process and the experiences and
acquisitions it produces, in turn, influence the consumer’s self-concept and lifestyle by

affecting their internal and external characteristics (Hawkins et al., 2007).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1, Experiences and Acquisitions I ‘
External " . :geclsion :. .
Influences .1 , ., . rocess
-Cllltllre ' V 3; ‘ 3'71} ‘
-Subcu|ture j _ V,Srtuatrons .
i-Demographics ‘ ‘ . —Prohlcmi
-Socral Status _ -- g , Recognition-
.-ReferenceGroups 5 , p. 3
-Marketing Activities I Self-Cotillcept ' ,.,ri'rror_'maii§ii;zjfi .7
Ian Desires ': 3' Search
I Lifestyle 77¢ . . ,
i 7 i-Alternative" :
'I . l {Evaluatio'nand ._ '_
nterna selection" i '
Influences ’ IV ,
-Perception ' , . , . 7 V.
-Learning , * -Outlet Selection
~Memory and Purchase.
-Motives '_
-Personality ‘ . I :j
--Emo‘fions -P_ost-purch_a_se_ : .
.-Attitudes Experiences and Acquisitions » Processes »
1‘ l

 

Figure 2. Overall Model of Consumer Behavior (Adopted from Hawkins,
Mothersbaugh, and Best, 2007)

Customer Satisfaction

The importance of customer satisfaction as a core concept in marketing has led to
numerous studies over the past decades. The literature supports that satisfied customers
are willing to buy more products or services, recommend them to others, and are less
price sensitive (Homburg et al., 2005). Hence, satisfaction is an essential factor related to
a company’s future profit by increasing the customer retention rate (Anderson et al.,
2004)

Following the pioneering experimental study by Cardozo (1965), customer
satisfaction and product quality were emphasized by Olshavsky and Miller (1972) and
Anderson (1973). This approach suggested that expectations influence customer
satisfaction through perceived quality and disconfirmation. Following Olshavsky and
Miller (1972) and Anderson (1973), as shown in Figure 3, the expectation-
disconfirrnation theory was introduced by Oliver (1981), grounded by social psychology
(Weaver and Brickman, 1974), and influenced by organizational behavior (Ilgen, 1971).
The theory posits that customer satisfaction is believed to result from a process of
customers’ comparisons between their expectations and perceptions of performance and
that the confirmation or disconfirmation of those expectations predicts satisfaction.
Positive disconfirmation occurs when performance perceptions of customers exceed
expectations, which leads to satisfaction, whereas perceptions falling short of
expectations result in negative disconfirmation, which induces dissatisfaction. Since then,
this theory was used by researchers and industries with strong support (Tse and Wilton,

1988; Yi, 1990).

10

 

Expectations

 

 

 

    
   

Calculated Subjective

Disconfirmation Disconfirmation

.1
.2

 

 

 

Satisfaction/
Dissatisfaction

 

 

 

 

 

 

 

 

 

 

 

 

Performance
Outcomes

 

 

 

Figure 3. The Expectation-Disconfirmation Theory (Adopted from Oliver, 1997)
According to Churchill and Surprenant (1982), both expectations and perceptions
have been found to influence customer satisfaction and subjective disconfirmation under
various circumstances, and customer satisfaction is determined by the levels of prior
expectations, the levels of perceived performance, and the degree and direction of
disconfirmation. Many studies have tested the expectancy-disconfirmation theory,
resulting in different views about comparison standards for expectations and
interrelationships among the key variables (Anderson, 1973; Boulding, Kalra, Staelin,
and Zeitharnl, 1993; Cardozo, 1965; Churchill and Surprenant, 1982; Oliver, 1980;
Oliver and Swan, 1989; Olshavsky and Miller, 1972; Tse and Wilton, 1988; Yi, 1990).
Earlier studies focused on repurchase expectations as antecedents of satisfaction.

Specifically, Anderson and Sullivan (1993) emphasized the perceived quality at the post-

11

consumption stage based on utility-oriented framework. This approach considers
perceived quality as the utility resulting from consumption. Contrary to previous studies,
Anderson and Sullivan (1993) denied a direct effect of expectations on satisfaction.
Instead, they argued that expectations influence satisfaction through perceived quality
and disconfirmation. Overall, their model puts an emphasis on the role of perceived
quality in customer satisfaction. Since then, perceived quality and/or value have been
proposed as antecedents of satisfaction; satisfaction, then, mediates between quality
and/or value and behavioral intention (Cronin, Brady, and Hult, 2000; Fornell, Johnson,

Anderson, Cha, and Bryant, 1996; Patterson, 2004).

Despite extensive research in customer satisfaction, researchers have yet to
develop a consensual definition of customer satisfaction. Howard and Sheth (1969)
defined satisfaction as “the buyer’s cognitive state of being adequately or inadequately
rewarded for the sacrifice he has undergone” (p. 145), and Hunt (1977) offered
“satisfaction is not an emotion, it is the evaluation of an emotion, and as such, it becomes
a quasi-cognitive construct” (p. 459). Tse and Wilton (1988) classified satisfaction as
“the customer’s response to the evaluation of the perceived discrepancy between prior
expectations or some other norm of performance and the actual performance of the
product as perceived after its consumption” (p. 204). In contrast, Locke (1976)
summarized the volumes of research on job satisfaction to define satisfaction as “a
pleasurable or positive emotional state resulting from the appraisal of one’s job.”
Westbrook and Reilly (1983) described satisfaction as “an emotional response to the

experiences provided by, or associated with, particular products or services purchased, as

12

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well as the overall market place” (p. 256). Oliver (1997) defined satisfaction as the
customer’s fulfillment response.

Based on Oliver’s (1980) disconfirmation theory, satisfaction was primarily
understood as a cognitive state resulting from cognitive evaluations between expectations
and perceived performance which leads to satisfaction (Bigné, Andreu, and Gnoth, 2003;
Oliver and Swan, 1989). However, Oliver (1997) argued that both cognitive and
emotional antecedents must be modeled simultaneously in satisfaction modeling because
satisfaction is a hybrid of cognitions and emotions. Furthermore, Oliver (1997) also
demonstrated that positive emotions and negative emotions influence independently on a
customer’s satisfaction evaluation. Woodruff, Cadotte, and Jenkins (1983) supported that
satisfaction should be defined as the link between cognitive and emotional processes
because customer satisfaction is an emotional feeling in response to cognitive evaluation
through confirmation/disconfirrnation. Moreover, several other researchers suggested that
both cognitive and affective aspects of a product and service stimulus predict satisfaction
(Bigné et al., 2003; Mano and Oliver, 1993; Westbrook and Oliver, 1991; Wirtz, Mattila,
and Tan, 2000). Therefore, the need to understand satisfaction by incorporating both
cognitive and affective perspectives has been emphasized (Bi gné et al., 2003; Oliver et
al., 1997; Phillips and Baumgartner, 2002; Wirtz and Bateson, 1999; Wirtz et al., 2000).

In the tourism and hospitality industry, managers are trying to find ways to
increase customer satisfaction under the challenging environment of the expanding
sophistication of customers’ demands and market competition. Customer satisfaction is
also one of the most frequently examined topics by researchers. They have applied

satisfaction-related theories and methods in this area (Almanza, J affe, and Lin, 1994;

13

Barsky, 1992; Barsky and Labagh, 1992; Bigné et al., 2003; Danaher and Arweiler, 1996;
Getty and Thompson, 1995; Knutson, Stevens, Wullaert, Patton, and Yokoyama, 1991;
Oh and Jeong, 1996; Ryan and Cliff, 1997; Wirtz et al., 2000). Most lodging customer
studies have focused on measuring the level of customer satisfaction with individual
service attributes and customers’ wants and needs from the attribute (Cadotte and
Turgeon, 1988; Knutson, 1988; Lewis, 1983; Lewis and Pizarn, 1981; Nightingale, 1985;
Saleh and Ryan, 1991). Empirical evidence exists showing that tourists’ satisfaction is a
strong indicator of their intentions to revisit and recommend the destination to other
people (Beeho and Prentice, 1997; Bramwell, 1998; Juaneda, 1996; Kozak, 2001; Kozak
and Rimmington, 2000; Ross, 1993; Yau and Chan, 1990; Yoon and Uysal, 2005).

According to Yoon and Uysal (2005), satisfied tourists are more likely to return to
the same destination and are more willing to share their positive travel experience with
their fi'iends and relatives. Word-of-mouth (WOM) recommendations are especially
critical in tourism marketing because they are considered to be the most reliable, and thus
are one of the most sought-after information, sources for potential tourists (Yoon and
Uysal, 2005). In particular, in the tourism and hospitality industry, customers have more
opportunities to interact with a product and service provider during the consumption
experience. Therefore, understanding customers’ emotional needs becomes an important
aspect of understanding their satisfaction (Bigné et al., 2003).
Customer Delight

Customer satisfaction has been regarded as an important antecedent of loyalty for
many years, but recently, this idea has been challenged as research shows customer

satisfaction does not necessarily result in repurchase or loyalty (Johns and Sasser, 1995;

14

Stewart, 1997). Instead, researchers have begun to emphasize the importance of
delighting customers, which is more likely to indicate loyalty than satisfied customers
(Oliver et al., 1997; Paul, 2000). Delighting a customer can be considered a critical
competitive advantage (Hicks et al., 2005 ; Oliver et al., 1997; Williams and Anderson,
1999) because customer delight drives customer loyalty by retaining customers and
creating positive WOM (Johns and Sasser, 1995; Keiningham and Vavra, 2001; Maister,
1993; Oliver et al., 1997; Paul, 2000). Oliver et al.(l997) and Torres and Kline (2006)
suggested that the true way to increase loyalty, loyalty-driven profit, and improve
retention is not to satisfy customers, but to delight them by offering exceptional
personalized services while creating a customer preference towards a company.

Delight produces emotional bonds between customers and a company, product, or
service by “wowing” them, which may provide additional psychological benefits to the
customers (Berry, 1995; Hirschman and Holbrook, 1982; Oliver et al., 1997). Customer
delight is defined as a higher level of satisfaction achieved by exceeding a customer’s
expectations (Oliver et al., 1997) and is also considered to be one of the second level
emotions (Arnold, Goldston, Walsh, Reboussin, Daniel, Hickman, and Wood, 2005; Firm,
2005; Oliver et al., 1997; Russell, 1980; Watson and Tellegen, 1985). Emotions, in
general, consist of two dimensions: pleasure and arousal (Mano and Oliver, 1993; Mattila
and Wirtz, 2000; Russell and Pratt, 1980; Wirtz and Bateson, 1999). Pleasure refers to
the degree to which a person feels good, joyful, or happy in a situation, which arousal
refers to the extent to which a person feels stimulated and active (Bigné et al., 2003).
Mano and Oliver’s (1993) study showed a result of eight affects including high and low

non-specific activation and high, moderate, and low levels each of the positive and

15

negative affect. The most closely related affects are moderate arousal positive affect (e. g.
pleasure), high arousal positive affect (e. g. delight), and high non-specific arousal (e. g.
surprise).

Thus, delight is a combination of high pleasure (joy, elation) and high activation
(surprise) (Arnold et al., 2005; Firm, 2005 ; Oliver et al., 1997; Plutchik, 1980; Russell,
1980; Watson and Tellegen, 1985). Further, delight involves a stronger emotion and a
different physiological state than satisfaction and the occurring of delight is directly
related to positive affect during the consumer’s consumption experiences (Hicks et al.,
2005). Oliver et al. (1997) suggested that the experience of delight during the
consumption process may cause the customer to want and try for reoccurrences of this
affective state. Therefore, if delight is achieved, the customer will be more likely to
repurchase the product. Oliver et al. (1997) also argued that delight occurs when the
result is unanticipated and When high levels of performance initiate arousal, which leads
to pleasure, and ultimately delight. Delight is considered an ephemeral emotion.

Some studies posit that delight is not necessarily a combination of joy and
surprise. Instead, delight is described as a sense of relatedness between the customer and
the company that evokes feelings of joy (Kumar, Olshavsky, and King, 2001). Based on
this concept, customer delight and satisfaction are separate concepts although they are
correlated (Hicks et al., 2005; Oliver et al., 1997; Rust and Oliver, 1994; Westbrook and
Oliver, 1991). As shown in Figure 4, there are four different types of post purchase

response to a product or service: outrage/pain, dissatisfaction, satisfaction, and delight.

16

Experienced Performance
(Partially Affective)

Negative Positive

    

    
    
 
   
       
 

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Figure 4. A Model of Dissatisfaction, Outrage, Satisfaction, and Delight
(Adopted from Berman, 2005)

In this model, the major difference between satisfaction and delight is the element
of surprise, whereas there is a positive expected level of performance both in satisfaction
and delight (Berman, 2005). There are important differences between satisfaction and
delight as shown in Table 1. Satisfaction is more cognitive and based on perceptions,
while delight is more affective and emotional triggering feelings such as arousal, joy, and
pleasure. Satisfaction is also schema-based and results from a comparison between
expectation and performance, while delight is from a recreated schema, which needs out-
of-the-ordinary performance. Additionally, satisfaction has a weaker memory than

delight and it is based on fiilfilling the expected, while delight is based on fulfilling the

unexpected (Berman, 2005). Delight is also more likely to occur in situations where
customers are highly involved (Oliver et al., 1997).

Table 1. Differences between Satisfaction and Delight (Adapted from Berman, 2005)

 

 

 

Satisfaction Delight

-More cognitive -More affective

-Schema based -Recreated schema

-Weaker memory than delight —Stronger memory than satisfaction
-Based on fulfilling the ergiected -Based on fiilfilling the unexpected
Customer Loyalty

Customer loyalty is defined as a deeply held commitment to rebuy or repatronize
a preferred product or service consistently in the future, despite situational influences and
marketing efforts having the potential to cause switching behavior (Oliver, 1997).
Loyalty is desirable since it is much less expensive to retain current customers than to
find and develop new ones (Reichheld and Sasser, 1990). Furthermore, loyal customers
are more likely to act as free word-of-mouth (WOM) advertising agents that informally
bring networks of friends, relatives, and other potential customers to products and
services (Shoemaker and Lewis, 1999).

Although loyalty has been researched in many different ways, loyalty has been
defined in two main approaches: behavioral loyalty and attitudinal loyalty (Dekimpe,
Steenkarnp, Mellens, and Vanden, 1997; Dick and Basu, 1994; Yi and La, 2004). In the
early loyalty studies, researchers mostly focused on the behavioral approach (Oliver,
1997). From the behavioral perspective, customer loyalty is defined as the non-random
purchase over time of one brand from a set of brands by a consumer using an evaluation
process (J acoby and Kyner, 1973; Newman and Werbal, 1973). Loyalty is also defined as

repeat purchase or patronage (Neal, 1999; Oliver, 1997) and as the proportion of times a

18

purchaser chooses the same product or service in a specific category compared to the
total number of purchases made by the purchaser in that category (Neal, 1999). In
measuring loyalty with a behavioral approach, a repurchase probability is used, which is
a long-term choice probability for a brand (Carpenter and Lehmann, 1985; Colombo,
Morrison, and Green, 1989; Dekimpe et al., 1997). Tellis (1988) measured loyalty as
repeat purchase frequency or relative volume of same brand purchasing. Furthermore,
Jacoby and Chestnut (1978) distinguished four kinds of loyalty: true focal brand loyalty
to the particular brand of interest, true multibrand loyalty which includes the focal brand,
nonloyal repeat purchasing of the focal brand, and happenstance purchasing of the focal
brand by a loyal or nonloyal buyer of another brand. Based on Jacoby and Chestnut’s
(1978) loyalty classification, Iwasaki and Havitz (1998) suggested three additional
components of behavioral loyalty: duration, frequency of purchases, and intensity.
Specifically, duration is the amount of time spent as a purchaser. Frequency is the
number of purchases over a certain period of time. Intensity is the number of hours one
devotes to using, participating in, or purchasing a product or service within a certain
period of time.

The criticism with the behavioral loyalty approach is that a repeat purchase is not
always the result of a psychological commitment to the brand, the intention may not lead
to action, and repeated buying behavior may not always reflect intentions (Yang and
Peterson, 2004). Additionally, there is no differentiation between customers who made

purchasing decisions with true brand preferences and those who purchased for

convenience or cost (Back, 2001). Day (1969) argued that measuring only the behavioral

19

aspects of loyalty can result in overestimating true loyalty, the commitment to a product
or service for as repurchasing behavior.

On the other hand, a number of researchers conceptualized loyalty based on an
attitudinal aspect begun by Guest (1944). According to this approach, loyalty was
considered a function of psychological processes (Jacoby and Chestnut, 1978), brand
preference, intentions, emotional commitment, strength of affection for a brand (Cronin
and Taylor, 1992; Iwasaki and Havitz, 1998), intention of word-of-mouth (WOM)
(Boulding et al., 1993), or willingness to pay a premium price (Zeithaml, Berry, and
Parasuraman, 1996). Therefore, loyal customers tend to Show special preference,
attachment, commitment, positive WOM, low switching to alternative brands, and
willingness to pay a premium price so that they contribute to higher profits (Yi and La,
2004). The criticism with the attitudinal loyalty concept lies in the lack of power in
predicting actual purchase behavior. Measuring attitudinal loyalty itself can not explain
the entirety of loyalty, and attitudinal loyalty should be combined with behavioral loyalty
to clarify true loyalty (Iwasaki and Havitz, 1998). Additionally, using both attitudinal and
behavioral aspects of loyalty provides a more influential explanation of loyalty (Assael,
1998)

Based on a review of attitudinal and behavioral loyalty approaches, Jacoby and
Chestnut (1978) viewed loyalty as a combination of attitudinal and behavioral aspects by
proposing that brand loyalty is repeat purchase behavior based on belief acquisition,
affect formation, and behavioral intention. Oliver (1999) and Zeithaml (2000) used both

attitudinal and behavioral measures to define and assess these variables. They suggested

that loyalty must consider both the behavioral and attitudinal perspectives. The use of

20

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both attitudinal and behavioral loyalty increases the predictive power of loyalty (Hunter,
1998; Pritchard and Howard, 1997). These two dimensions of loyalty approaches have
been applied and supported to understand customer loyalty better in many different fields
(Day, 1969; Jacoby and Kyner, 1973; Oliver, 1999; Pritchard and Howard, 1997; Yi and
La, 2004). Along with J acoby and Chestnut (1978), Dick and Basu (1994) suggested that
loyalty requires consistency across the cognitive, affective, and conative dimensions of
the consumer’s focal brand orientation.

Following Dick and Basu (1994), Oliver (1997, 1999) suggested the cognition-
affect-conation sequence of the loyalty-development process beginning from some
cognitive loyalty, followed by affective loyalty, to conative loyalty, and finally action
loyalty. He also described that loyalty formation is more likely to be an attitudinal
development process and customers may demonstrate different levels of loyalty in
different stages of this process. Table 2 presents the four phases of loyalty and their
corresponding antecedents, sustainers, and vulnerabilities as proposed by Dick and Basu
(1994) and Oliver (1997).

According to Oliver’s (1997) loyalty dimensionality, the first phase, cognitive
loyalty, is based on merely functional characteristics such as costs and benefits and is
focused on the product or service’s performance. It is the weakest state of loyalty since
this type of commitment is actually to costs and benefits and not to the brand itself
(Oliver, 1997). Therefore, consumers are likely to switch when they perceive alternative
offerings as being superior with respect to the cost-benefit ratio (Kalyanaram and Little,

1994; Sivakumar and Raj, 1997).

21

Table 2. Four-Stage Loyalty Model (Adapted from Oliver, 1997)

 

 

 

 

 

Identifying

Stage Maker Antecedents Sustainers Vulnerabilities

Cognitive Loyalty to Accessibility Cost Cost
information such Confidence Benefits Benefits
as price, features Centrality Quality Quality

Clarity

Affective Loyalty to liking: Emotions Satisfaction Dissatisfaction
“I buy it because I Moods Involvement Persuasion
like it.” Primary affect Liking, Preference Trial

Satisfaction Cognitive consistency

Conative Loyalty to an Switching Commitment Persuasion
intention: “I’m costs Cognitive consistency Trial
committed to Sunk costs
buying it.”

Action Loyalty to action Inertia Inertia Persuasion
inertia, the Sunk costs Sunk costs Trial
overcoming of
obstacles.

 

The second phase is affective loyalty, which is a favorable attitude toward a
specific brand or product. This loyalty is an enhanced liking for competitive brands,
which is conveyed through imagery and association used in competitive communications
(Oliver, 1999). Affective loyalty involves both the liking of the product or service and
experiencing satisfaction with the brand. Attitude is shown as a function of cognition
(expectancy disconfirmation) plus prior attitude, and plus satisfaction in later periods
(Oliver, 1999).

The third phase of loyalty development is conative loyalty which is behavioral
intention to repurchase and involves a deep brand-specific commitment (Harris and
Goode, 2004). Conative loyalty is stronger than affective loyalty but has vulnerabilities as
well (Evanschitzky and Wunderlich, 2006). Consumers are more likely to try alternative
offerings if they experience frequent service failure. Furthermore, although the consumer

is conatively loyal, he or she may consider alternative offerings (Oliver, 1999).

22

The last phase of loyalty is action loyalty, which is transformed into action (Kuhl,
1985) and includes habit and routinized response behavior. Action loyalty is a
commitment to the action of repurchasing. In this stage, intention is transformed into
action. Persuasion and trial can be tried by competitors but competitive offerings by
competitors are not considered as alternatives. This action control leads to a state of
readiness to act and to a desire to overcome obstacles to achieve the action (Oliver, 1999).

Many researchers have applied Oliver’s four-dimensional loyalty
conceptualization in developing loyalty dimensionality (Back, 2005; Back and Parks,
2003; Evanschitzky and Wunderlich, 2006; Harris and Goode, 2004; McMullan and
Gilmore, 2003; Oliver, 1999). For instance, Harris and Goode (2004) supported this
conceptualization by conducting an empirical test with two online service scenarios and
McMullan and Gilmore (2003) developed a 28-item scale to measure the four phases of
loyalty with an empirical test in the restaurant context. Back (2005) and Evanschitzky
and Wunderlich (2006) also confirmed Oliver’s (1999) conceptualization from their
empirical testing in the hotel and retail environment.

Some researchers suggested a different loyalty development sequence based on
Oliver’s loyalty development framework (Back, 2001; Jones and Taylor, 2007; Li and
Petrick, 2008; Rundle-Thiele, 2005). For example, following Breckler (1984), Beck
(2001) and Li and Petrick (2008) suggested that cognitive, affective, and conative loyalty
are not sequentially linked but all three aspects are independent factors of attitudinal
loyalty, which lead to action loyalty according to the tripartite model. Jones and Taylor
(2007) suggested a two-dimensional loyalty construct by combining attitudinal and

cognitive loyalty as one dimension and behavioral loyalty as the other dimension. Overall,

23

recent studies on loyalty have been broadening the concept, but there is still no consensus
on a loyalty development construct.

In tourist behavior research, return visitation has been used to assess tourists’
destination loyalty (Chen and Gursoy, 2001). Repeat visitation is a necessary component
of destination loyalty, as it generally tends to occur with brand loyalty. Destination
loyalty might also generate a lower sensitivity to prices offered by rival destinations
(Krishnamurthi and Papatla, 2003). Destination loyalty is defined by Chen and Gursoy
(2001) as the level of tourists’ perceptions of a destination as a recommendable place.
However, return visitation may not truly represent loyalty and a non-repeat visit behavior
may not represent lack of loyalty to a destination. For example, those who do not return
to a previously visited destination may remain loyal to that destination but simply want to
seek different travel experiences at new destinations.

Affect and Cognition

Cognition refers to people’s thoughts about an attitude object and encompasses
the content of one’s thoughts regarding beliefs in the statement of fact. Affect refers to
the specific quality of goodness or badness experienced as a feeling state and demarcates
positive or negative quality of a stimulus (Solvic, Finucane, Peters, and MacGregor,
2004; Zajonc, 1980). As shown in Table 3, there are four different kinds of affective
responses: emotions, specific feelings, moods, and evaluations (Peter and Olson, 2005).
Each type of affect involves positive or negative reactions. The four different kinds of
affect have different levels of physiological arousal and the intensity of feeling (Kroeber-

Riel, 1979).

24

Table 3. Types of Affective Responses (Adppted from Peter and Olson, 2005)

 

 

Level or Intensity or
Type of Affective Physiological Strength of Examples of Positive and
Responses Arousal Feeling Negative Affect
Higher arousal Stronger -Joy, love
Emotions -Fear, guilt, anger
I I -Warmth, satisfaction
Specific feelings -Disgust, sadness
-Alert, relaxed, calm
Moods -Blue, bored
-Like, good, favorable
Evaluations Lower arousal Weaker -Dislike, bad, unfavorable

 

There has been a long-standing theoretical issue in understanding the cognitive
and affective sequence and the interplay between cognition and affection is still
unresolved (Chebat and Michon, 2003; Lazarus, 1991; Solvic, 2000; Zajonc, 1980;
Zajonc and Markus, 1985). Lazarus (1982, 1984) posited that affect is connected to a
cognitive appraisal mechanism and affect needs cognition as a necessary precondition
because cognition is a prior element of affect. “Probably all mammals meet the minimal
cognitive requirements of emotion if one permits the concept of appraisal to include the
type of process described by ethnologists in which a fairly rigid, built-in response to
stimulus arrays differentiates danger fiom no-danger. An evaluative perception, hence,
appraisal, can operate at all levels of complexity, from the most primitive and inborn to
the most symbolic and experience-based.” (Lazarus, 1982, p. 1023).

In accordance with Lazarus’ (1982) statement, other theories of satisfaction and
loyalty based on the cognitive-affective sequence have been proposed (Bigné et al., 2003;
Fishbein and Ajzen, 1975; Oliver, 1997; Perez-Caro and Sanchez-Garcia, 2006). For
instance, Fishbein and Aj zen (1975) depicted that consumers form beliefs, formulate

likes and dislikes, and decide whether they wish to buy a product. Oliver (1997)

25

emphasized the importance of studying the cognitive-affective sequence as a cognitive
appraisal and then creating emotions or affect in behavior formation.

Zajonc (1980, 2000) emphasized the importance of affect in decision making as a
different approach to the cognitive and affective sequence. Affective reactions to stimuli
are often the very first reactions, occurring quickly and automatically and then leading
information processing and judgments about objects, activities, and other stimuli with a
direct and primary role in motivating behavior (Solvic, F inucane, Peters, and MacGregor,
2002; Zajonc, 1980, 2000). Further, Epstein (1994) argued that affect plays a central role
in what have come to be known as “dual-process theories” of thinking, knowing and
information processing. According to Epstein (1994), there are two basic modes of
thinking: experiential and rational. One of the main characteristics of the experiential
system is its affective basis. Although analysis is certainly important in some decision-
making circumstances, reliance on affect and emotion is a quicker, easier, and more
efficient way to navigate in a complex and uncertain world (Epstein, 1994; Slovic et al.,
2002). Some researchers support that affect is a direct and primary role in behavior
(LeDoux, 1996; Solvic, 1980; Slovic et al., 2002; Zajonc, 1980) and affective evaluation
can take place without conscious stimulus recognition (Kunst—Wilson and Zajonc, 1980).
Therefore, affect does not always need cognition but affect guides judgments and
decisions (Damasio, 1994; Lerner and Keltner, 2001; Loewenstin, Weber, Hsee, and
Welch, 2001; Zajonc, 1980; Zajonc and Markus, 1985) and representations of objects and
events in people’s minds are tagged to varying degrees with affect. In the process of

making a judgment or decision, people consult or refer to an affect pool containing all the

26

positive and negative tags associated with the representations consciously or
unconsciously (Tversky and Kahneman, 1974).

Zajonc (1980) argued that affect and cognition are separate and partially
independent systems and affect could be generated without a prior cognitive process,
although affect and cognition usually function conjointly. The neurophysiological
evidence (Armony, Servan-Schreiber, Cohen, and LeDoux, 1996; LeDoux, 1996)
suggests that affective processes and cognitive processes influence one another; affect
and cognition cannot be easily separated as pure affect or pure cognition. Peter and Olson
(2005) and Piaget (1981) described how affect and cognition are highly interdependent
involving different parts of the brain like affection and cognition are linked as two sides
of the same coin. Figure 5 shows how affect and cognition are related. Each system reacts
differently to aspects of environment and responds to the output of the other system

(Peter and Olson, 2005).

I Environment I

    
  
  

 

_....3
Cognitive System

I

 

 

 

 

 

 

Affective Cognitive Responses
Responses

—Knowledge
—Emotions -Meanings
-Feelings -Beliefs
-Moods ,
’-Evalnations

 

 

Figure 5. The Relationship between Affect and Cognition (Adopted from Peter and
Olson, 2005)

27

Given this relationship, in consumer behavior, understanding both affect and
cognition are important in developing marketing strategies for areas such as product
design, advertisement, and store layout (Peter and Olson, 2005). For example, as a
primary objective of marketing strategies, customer satisfaction consists of both affect
and cognition (Oliver, 1997) and brand image also includes affect (e. g., feelings and
emotions about the brand) and cognition (e. g., knowledge and beliefs about brand
attributes) (Dichter, 1985; Dobni and Zinkhan, 1990). Further, many studies have
explored the linkage between customer loyalty and satisfaction; most existing models of
customer loyalty are cognitively based and there is little research on the psychology

behind the development of customer loyalty (Mattila, 2001).

28

CHAPTER 3

RESEARCH DESIGN AND METHODOLOGY

This chapter discusses the research methodology that was used to answer the
proposed research hypotheses. This chapter is divided into three sections: (1) research
design including rational for research method, sampling, pilot study, and data collection
procedures; (2) survey measurement; and (3) data analysis.
Research Design
Rationale for Research Method

The main purpose of this study is to understand (1) how customer satisfaction and
delight influence loyalty, and (2) the relationships between cognitive, affective, conative,
and action loyalties. The survey research method is considered most appropriate over
other types of research methods in answering these research questions. Quantitative
methodology gives a broad, generalizable set of findings for this study by obtaining
responses from many people; a survey is good at examining relationships between factors
(Trochim, 2001). A popular resort in the Midwest was selected as it is located in one of
the most well-known tourist destinations in the state. As an independent hotel with 360
themed guestrooms, five indoor pools and three Whirlpools, a miniature golf course, a
large family fun center with over 100 video/arcade games, and several guest banquet and
convention spaces, this resort has a long standing club membership program.

Table 4 presents a profile summary of the population provided by the resort from
2003 to 2009. The population consisted of overnight hotel guests from a Midwestem

resort. Based on this profile of the population, a sample was selected to test the proposed

model.

29

~~~~~

Table 4. The Guest Profile of a Midwestern resort

 

 

 

 

 

Data variable Number of % of Number of % of
from 2003 to February mailable mailable E-mailable E-mailable
2009 guests guests guests _guests
Total number of guests 130,370 100% 48,621 100%
F irst-time guests 102,959 73% 34,521 71%
Repeat guests 27,411 27% 14,100 29%
Sampling

The guests who stayed at the resort during the summer of 2009 in the months of

July, August, and September were the sample for this study. Table 5 shows the number of

guests who stayed at this resort, the number of e-mailed surveys, and the number of

mailed surveys in the months of July, August, and September 2009. The total sample size

was 3,709 (E-mailed surveys: 3,459 and mailed surveys: 250).

Table 5. Sampling Frame

 

 

 

 

 

Number of Total number

Total number of Number of E-mailed of surveys

guests stayed mailed surveys surveys distributed

July 2009 2,199 100 1,227 1,327

August 2009 2,750 125 1,537 1,662
September

2009 442 25 695 720

Total 5,391 250 3,459 3,709

 

Subjects were household travel parties of first-time guests and repeat guests who

stayed at this hotel one or more times within the last three years. Both current loyalty

club members and non-loyalty club members were included. Business travelers and

groups for events (e. g., weddings, reunions, meetings) were excluded in this study

because some of them might not be directly involved in the decision making of the choice

of hotel or in making the reservation. Instead their stay at this hotel might have been pre-

arranged by others.

30

Pilot Study

A pilot study (n=32) was conducted in June 2009 with faculty, administrators, and
graduate students at Michigan State University prior to the main survey to develop and
test a questionnaire instrument for this study. After this pilot study, the questionnaire
instrument was revised to facilitate easier reading and clearer wording. Reliability
(Cronbach’s alpha) for each measurement construct was also examined to clarify scale
items. The scales for “Customer satisfaction”, “Customer delight”, “Cognitive loyalty”,
“Affective loyalty”, “Conative loyalty”, and “Action loyalty” demonstrated acceptable
reliability ranging fi'om or = .71 to or = .96 (Nunnally and Bernstein, 1994).
Data Collection

Prior to data collection, a description of this study and the data collection
instruments were reviewed and approved by the Institutional Review Board (IRB) of
Michigan State University in May 2009. From July to September 2009, survey data were
collected through two different approaches: online surveys and paper surveys.
The Online Survey

The primary data collection was conducted via a self-administered online survey
using a web-based survey tool, Qualtrics, on a weekly basis. As Internet usage continues
to grow rapidly, online surveys offer several methodological and financial advantages
over the traditional paper survey (Couper, 2000). Advantages of online surveys include
faster response rate, case in sending reminders to participants, easier processing of data,
and less cost (Hewson, Yule, Laurent, and Vogel, 2003).

Each week, upon completing their stay at this hotel, the survey questionnaire was

emailed to them with an invitation letter from the general manager of the resort and a

31

1111'“ '81:

university professor. The first e-mail reminder was sent to those who had not yet
responded two weeks after the first survey questionnaire, and a second e—mail reminded
those who had not yet responded one week after the first reminder. The questionnaire
required approximately 15 to 20 minutes to complete. As shown in Table 6, a total of
3,459 surveys were sent via Qualtrics and the survey response rate was 50% (n=1,743).
The Paper Survey

A self-administered paper survey was also employed by mail in order to test for
biases that an online survey might cause and to ensure an appropriate sample size for
statistical power (i.e., the ability to detect and reject a poor model) in the SEM analysis
(Chin, 1998). Respondents were chosen based on a systematic random sampling method.
The main advantage of using systematic sampling over simple random sampling is the
assurance that the population will be evenly sampled over the population and simplicity
(Trochim, 2001).

The next week, after completing their stay at this hotel, a survey package was
mailed to them with an invitation letter by the general manager of the resort and a
university professor, a survey questionnaire, and a pre-paid return envelope. The first
mail reminder by a post-card was sent to those who had not yet responded two weeks
after the survey questionnaire, and a second mailing with a survey package, including an
invitation letter by the general manager of the resort and a university professor, a survey
questionnaire, and a pre-paid return envelope, reminded those who had not yet responded
one week after the first reminder. A total of 250 surveys were mailed and the survey

response rate was 38% (n=94).

32

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Before combining the two sets of data, demographic characteristics of participants
in these two data sets were compared. As shown in Appendix A, the average age of on-
line survey respondents was 48 years while that of paper survey respondents was 53 years.
There were no significant differences between the two sets of data with the demographic
characteristics such as gender, ethnicity, income, and number of people in the household.
The on—line survey respondents had more full- time employment and the paper survey
respondents had more Michigan residency.

Prior to analyzing the data after the two sets of data were combined, 177 data (170
from the online survey and 7 from the paper survey) were dropped because they were
found to be inappropriate for the analysis (e. g., incomplete data or guests whose primary
purpose of the stay were business or a group/bus tour). A total of 1,660 final data
(number of online surveys=1,573, number of paper surveys=87) were utilized for the
analysis.

Table 6. Data Collection

 

 

 

 

 

 

Online survey Paper survey Total
Number of surveys
distributed 3,459 250 3,709
Number of surveys
collected 1 ,743 94 1 ,837
Response rate 50% 38% 50%
Number of surveys
dropped a from data
analysis 170 7 177
Number of surveys used
for data analysis 1,573 87 1,660
R68ponse rate 46% 35% 45%

 

Note: a The incomplete data and guests whose primary purposes of their stay were
business or a group/bus tour were dropped.

33

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The Questionnaire

The questionnaire instrument consisted of six sections. The first section was
designed to understand guests’ recent stays at the resort and destination. The second
section measured guests’ planning, decision making, and hotel choice. The third section
asked about guests’ experiences during their recent stays at the resort. The fourth section
asked about guests’ satisfaction with their recent stay at the resort. The fifth section asked
about guests’ past experience with the resort, destination, and other hotels. The last
section asked for socio-demographic information.
Survey Measurement

The survey items for each construct were developed on the basis of previous
studies.
Customer Satisfaction

As shown in Table 7, customer satisfaction was measured with four items (Firm,
2005; Spreng, MacKenzie, and Olshavky, 1996). The response was given on a seven-
point Likert scale from 1 = strongly disagree to 7 = strongly agree with the following
questions: “Overall, this hotel was comfortable,” “Overall, this hotel was pleasing,”
“Overall, this hotel was satisfying,” and “Overall, this hotel was contenting.”
Customer Delight

Three items were previously used by F inn (2005) to measure customer delight and
five items were newly-developed based on the literature review. The response was given
on a seven—point Likert scale from 1 = strongly disagree to 7 = strongly agree with the
following questions: “I felt delighted at some time during my stay at this hotel,” “I felt

positively surprised at some time during my stay at this hotel,” “I felt overjoyed at some

34

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time during my stay at this hotel,” “I felt gleeful at some time during my stay at this
hotel,” “I felt elated at some time during my stay at this hotel,” “I felt grateful at some
time during my stay at this hotel,” “I felt pleased at some time during my stay at this
hotel,” and “The hotel had experiences/services which were unexpected and they
delighted_me.”
Cognitive Loyalty

The measurement items for cognitive loyalty were developed from Li and Petrick
(2008) and McMullan and Gilmore (2003) and presented five items on a seven-point
Likert scale fi'om 1 = strongly disagree to 7 = strongly agree. Items included “I believe
this hotel provides more benefits than other hotels of its type,” “I made the right choice of
hotel with this hotel,” “The hotel’s facilities are visually more appealing compared to
other hotels of its type,” “This hotel has better value for my money compared to other
hotel’s prices of its type,” and “This hotel provides me superior service quality compared
to other hotels of its type.”
A jfective Loyalty

Four of the measurement items for affective loyalty were developed from Li and
Petrick (2008) and McMullan and Gihnore (2003). One item was newly-developed on a
seven—point Likert scale from 1 = strongly disagree to 7 = strongly agree. Items included
“I feel happy when I stay at this hotel,” “I feel grateful to this hotel,” “I like this hotel
more than other hotels of its type,” “I love staying at this hotel,” and “Staying in this

hotel says a lot about who I am.”

35

C onative Loyalty

Six indicators were used to measure conative loyalty from the previous research
(Li and Petrick, 2008; McMullan and Gilmore, 2003). The items were on a seven-point
Likert scale from 1 = strongly disagree to 7 = strongly agree with the following
questions: “I consider myself to be highly loyal to this hotel,” “I intend to continue
staying at this hotel,” “I would change hotels if another hotel’s staff was more friendly,”
“I would try an alternative hotel if their loyalty program offered more benefits,” and “I
would try an alternative hotel if the alternative hotel offered increased facilities/services
to this hotel.”
Action Loyalty

Four indicators were used to measure action loyalty from the previous research
(Jones and Sasser, 1995; Shoemaker and Lewis, 1999). Items included “I will return to
this hotel in the next 6 months or less,” “in the next 7-12 months,” “in the next year
(more than 12 months from now),” and “I will recommend this hotel to others.” These

items were measured on a seven-point Likert scale from 1 = extremely unlikely to 7 =

quite likely.

36

Table 7. Survey Measurement Items

 

 

 

 

 

Measurement
Construct Scales Measurement Items
Satisfaction 7-point Likert scale Overall, this hotel was
Finn (2005); (1=Strong1y . Comfortable (Finn, 2005)
Spreng 3‘ 01- Disagree, 0 Satisfying to me (F inn, 2005)
(1996) 7=Strongly Agree) 0 Pleasing (Spreng et al., 1996)
Overall, I was content at this hotel. (Spreng et al.,
1996)
Delight 7-point Likert scale I felt at some time during my stay at this
Finn (2005); (1=Strongly hotel.
new items Disagree, - a -
7: Strongly Agree) - DelightZd (Firm, 2005)
0 Gleeful (Firm, 2005)
. Elated a (Firm, 2005)
0 Grateful (new item)
0 Overjoyed (new item)
0 Pleased (new item)
0 Positively surprised (new item)
This hotel had experiences/services which were
unexpected and they delighted me. (new item)
Cognitive 7-point Likert scale I made the right choice of hotel with this hotel.
Loyalty (l=Strongly (McMullan and Gilmore, 2003)
Li and Disagree, The hotel’s facilities are visually more appealing
Petrick 7=Strongly Agree) compared to other hotels of its type. (McMullan
(2008); and Gilmore, 2003)
McMullan This hotel has better value for my money
and Gilmore compared to other hotel’s prices of its type.
(2003) (McMullan and Gilmore, 2003)
I believe this hotel provides more benefits than
other hotels of its type. (Li and Petrick, 2008)
This hotel provides me superior service quality
compared to other hotels of its type. (Li and
Petrick, 2008)
Affective 7-point Likert scale I feel happy when I stay at this hotel. (Li and
Loyalty (1=Strongly Petrick, 2008)
Li and Disagree, I like this hotel more than other hotels of its type.
Petrick 7=Strongly Agree) (Li and Petrick, 2008)
(2008); I love staying at this hotel. (Li and Petrick, 2008)
McMullan Staying in this hotel says a lot about who I am.
and Gilmore (McMullan and Gilmore, 2003)
(2003); new I feel grateful to this hotel.(new item)
items ’

37

Table 7 (cont’d)

 

 

Conative 7-point Likert I intend to continue staying at this hotel. (Li and
Loyalty scale Petrick, 2008)
Li and (1=Strongly I consider myself to be highly loyal to this hotel.
Petrick Disagree, (McMullan and Gilmore, 2003)
(2008); 7=Strongly I would change hotels if another hotel’s staff was
McMullan Agree) more friendly. (McMullan and Gilmore, 2003)
and Gilmore I would try an alternative hotel if their loyalty
(2003) program offered more benefits. (McMullan and
Gilmore, 2003)
I would try an alternative hotel if the alternative
hotel offered increased facilities/services to this
hotel. (McMullan and Gilmore, 2003)
Action 7-point Likert I will return to this hotel in
$53212,“ :filExtremely o the next 6 months or less b (Jones and Sasser,
Sasser Unlikely, 7=Quite 1995, Shoemaker andbLewrs,1999)
(1995); Likely) o the next 7-12 months (Jones and Sasser, 1995;
Shoemaker Shoemaker and Lewis,1999)
figggims 0 the next year (more than 12 months fi'om now)

(Jones and Sasser, 1995; Shoemaker and
Lewis,1999)
I will recommend this hotel to others. (Jones and
Sasser, 1995; Shoemaker and Lewis,1999)

 

a : Modified items based on Finn’s measurement items (2005)

b .
: Modified items based on Jones and Sasser (1995), and Shoemaker and Lewrs (1999)

Data Analysis

Based on basic demographic information of all the hotel guests from July to

September 2009 given by the hotel, some characteristics (e.g., residency, number of

people in the household, membership, and average spent money during the stay at the

resort) of the respondents who returned completed surveys were compared to non-

respondents who failed to return a completed survey. As shown in Appendix B,

respondents and non-respondents had mostly similar demographic characteristics except

the percent of loyalty membership holders (Respondents: 50%, Non-Respondents: 26%).

38

Survey data were analyzed in two steps. First, preliminary statistics were obtained
using the Statistical Package for the Social Sciences (SPSS). For this study, SPSS 17.0
was used for the analysis. Descriptive statistics were obtained to determine the
distributional characteristics of each variable including the means, standard deviation,
skewness, and kurtosis. Second, structural equation modeling (SEM) was used to test the
proposed model and hypotheses. For this study, M-Plus 5.2 was utilized to complete the
analysis. In the SEM process, a confirmatory factor analysis (CFA) was first conducted
and then a measurement model fit was evaluated. CPA is useful in validating scales to
discover whether the measuring instrument appropriately measured the underlying
constructs prior to considering of the full model (Hair, Anderson, and Fornell, 1998).
Following the CF A, the data were used to estimate the hypothesized structural model in
evaluating the overall model fit and standardized solutions were used in reporting the

causal relationships between the exogenous and endogenous constructs.

39

CHAPTER 4

RESULTS

This chapter presents the findings on how customer satisfaction and delight
influence loyalty, and the relationships between cognitive, affective, conative, and action
loyalties. This chapter is divided into three sections: (1) the results of the preliminary
analyses, including data screening and profiles of survey respondents in terms of
demographic and traveling characteristics; (2) the results of tests conducted on the
measurement model including assessments of overall model fit, reliability, and validity;
and (3) the results associated with testing an integrated satisfaction, delight, and loyalty
model.

Preliminary Analyses

In this section, data screening procedures and descriptive statistics for the
variables are described.
Data Screening

Normality for each variable in the proposed model was examined to determine
whether the data met the normality assumption for the maximum likelihood estimation
(MLE). It is an important preliminary analysis step for subsequent SEM analyses to be
meaningful (Hair et al., 1998). The normality was assessed by evaluating the skewness
and kurtosis of each variable in the study. These tests indicated that all values for
univariate skewness and kurtosis were inside the acceptable range (-3 to 3 for skewness
and -10 to 10 for kurtosis) (Kline, 1998). Thus, the results of the normality test showed
no extreme departure from normality (skewness: from -2.17 to 0.55 and Kurtosis: from -

0.57 to 6.04) as shown in Table 8.

40

 
     

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Table 8. Normalitya Test Results for Variables Included in the Proposed Model.

 

 

 

 

 

 

 

Constructs Variable Names Skewnessb K u rt osisc
Customer SAT] (Comfortable) -2.15 5.53
Satisfaction SAT2 (Pleasing) -2.16 6.04
SAT3 (Satisfying) -2.06 4.90
SAT4 (Contengt) -2.17 5.36
Customer DEL] (Delighted) -1.41 2.17
Delight DEL2 (Gratefiil) -.81 .38
DEL3 (Elated) -.56 .13
DEL4 (Gleefiil) -.62 .15
DELS (Overjoyed) -.53 .06
DEL6 (Pleased) -2.08 5.06
DEL7 (Positively surprised) -.60 -.09
DEL8 (Unexpected and delighted) -.57 -.09
Cognitive COGl (More benefits) -1.16 1.55
Loyalty COG2 (Right choice) -1.94 4.43
COG3 (More appealing facilities) -1.18 1.55
COG4 (Better value) -.82 .35
COGS (Superior service quality) -.91 .60
Affective AFFl (Feel happy) -l.55 3.19
Loyalty AF F2 (Feel grateful) -.64 .19
AFF3 (Like) -.91 .57
AFF4 (Love staying) -1.21 1.42
AFF5 (Says a lot about who I am) -.48 -.22
Conative CON1(Consider myself to be highly loyal to this -.82 .23
Loyalty hotel)
CON2 (Intend to continue staying at this hotel) -1.33 1.80
CON3 (I would change hotels if another hotel’s -.13 -.48
staff was more friendly)
CON4 (I would try an alternative hotel if it was .51 -.49
less expensive than the lodge)
CONS (I would try an alternative hotel if their .19 -.57
loyalty program offered more benefits)
CON6 (I would try an alternative hotel if the .55 -.23
alternative hotel offered increased
facilities/services to the hotel)
Action ACTl (Likelihood to return to this hotel in the
Loyalty next 6 months or less) -1.21 2.32
ACT2 (Likelihood to return to this hotel in the
next 7-12 months) -1 .42 1.89
ACT3 (Likelihood to return to this hotel in the
next year (more than 12 months from now) -1.38 1.40
ACT4 (Likelihood to recommend this hotel to
others) -2.32 5.58

 

41

Table 8 (cont’d)

a . . . . b
Note: Normality was examrned in terms of skewness and kurtosrs. Skewness refers to
the symmetry of the distribution. Skewness with a value above 3 is conventionally

consrdered extremely skewed. Kurtosrs indicates a relative excess of cases in the tails of

a distribution relative to a normal distribution. A kurtosis value of 10 or below is a
conventional criterion indicating normal distribution in terms of its peakedness. A value
above 10 is considered extremely peaked.

Profile of Survey Respondents
Socio—Demogr_aphic Characteristics of Survey Respondents

Table 9 presents the respondents’ socio-demographic information. The majority
of the participants were female (69%) and the average age was 48 years. The majority of
participants (82 %) were European American/Middle Eastem/White. About 21% of
respondents had an annual household income between $50,000 and $74,999, followed by
those with an annual household income ranging between $75,000 and $99,999 (17%),
and between $100,000 and $149,999 (17%). The average number of people in a
household was three, the majority of respondents (58%) were employed full-time, and
13% of respondents were retired. The majority of respondents (69%) resided in Michigan,
followed by those living in Ohio (12%), Canada (7%), and other states (12%).
Traveling Characteristics of Survey Respondents

Table 10 presents the respondents’ travel information used for travel decision
making. Respondents indicated information used or marketing communications
influencing them to book the current stay at this hotel by (multiple responses allowed):
previous visit (57%), hotel membership holder (20%), fiiend or family member
recommended (17%), special package rate (17%), Internet web site or search engine
(16%), E-mail promotion, and newsletter offer (16%). Most of the respondents traveled

with their family members (86%) and friends (12%).

42

Table 9. Socio-Demographic Characteristics of SurveLRespondents

 

 

 

 

 

Camry Frequency %
Gender Female 1,132 69%
Male 507 31%
Total 1,639 a 100%
Age Mean:48 years old
19-24 years 25 2%
25-34 years 209 13%
35-44 years 446 28%
45-54 years 465 29%
55-64 years 306 19%
65-74 years 128 8%
75 years or older 34 2%
Total 1,613 a 100%
Race African American/Black 33 2%
American Indian 51 3%
Asian or Pacific Islander 11 1%
European American/Middle East/White 1,326 82%
Hispanic/Latino/Latina 12 1%
Other 178 l 1%
Total 1,61 1 a 100%
Employment Status Employed full-time 971 60%
Employed part-time 159 10%
Retired 204 9%
Self-employed 138 1 3%
Unemployed 68 4%
Other 71 4%
Total 1,61 1 a 100%
Income Less than $25,000 58 4%
$25,000-$34,999 90 6%
$35,000-$49,999 181 1 1%
$50,000-$74,999 343 22%
$75,000-$99,999 275 17%
$100,000-S 149,999 275 17%
$150,000-$199,999 71 5%
$200,000 or more 33 2%
I prefer not to respond 248 16%
Total 1,574 a 100%

 

43

Table 9 (cont’d)

 

 

Family Status Average total number of people in a 3
household
Average number of children in a
household (18 years or younger) 1
Average number of adults in a
household (19 years or older) 2
Primary Residence Michigan 1,137 70%
Ohio 200 12%
Canada 102 6%
Indiana 5 l 3%
Illinois 5 1 3%
Other 94 6%

 

a . .
Note: The value of “frequency" varies, due to questions not answered.

During their trip, their leisure activities were (multiple responses allowed):
explored F rankenmuth city or town (75%), shopped on Main Street Frankenmuth (72%),
went swimming in the resort’s pools or Whirlpools (71%), played in the resort’s game
rooms or indoor putt-putt golf (65%), shopped in Riverplace (63%), shopped in Birch
Run (50%), dined at a unique restaurant in the Bavarian Inn Lodge (49%), dined at the
resort on Main Street (48%), dined at Zehnder’s restaurant on Main Street (29%), and
dined at a unique restaurant outside of the resort (20%). Respondents were mostly
satisfied with the hotel’s location (Mean 6.66 on 1: very unsatisfied to 7: very satisfied),
friendliness of staff (6.43), hotel amenities (pool, game room, free nightly entertainment)
(6.42), room cleanliness (6.42), quality of food (6.30), room comfort (6.12), relationship

established between staff and customers (6.04), and value for money (5.68).

44

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Table 10. Travel Characteristics of Survey Respondents

 

 

 

Category Frequency %
Information or Previous visit 951 57%
marketing Hotel membership card holder 338 20%
communication to Friend or family member recommended 280 17%
book this recent Special package rate 27 5 17%
. a Internet web site or search engine 271 16%
stay at this resort E-mail promotion, newsletter offer 266 16%
Accompanied on Family members 1,424 86%
this recent stay at Friends 197 12%
this resort Alone 27 2%
Leisure activities Explored Frankenmuth city or town 1,248 75%
during this trip a Shopped-on Main Street Frankenmuth 1,201 72%
Went swrmmrng in the resort’s pools or
Whirlpools 1,192 71%
Played in the resort game rooms or
indoor putt-putt golf 1,093 65%
Shopped in Riverplace 1,058 63%
Shopped in Birch Run 838 50%
Dined at a unique restaurant in the
Bavarian Inn Lodge 810 49%
Dined at the resort on Main Street 797 48%
Dined at Zehnder’s restaurant on Main
Street 487 29%
Dined at a unique restaurant outside of
the resort 329 20%
Satisfaction with MEAN
this recent stay at Hotel location 6.66
this resort Friendliness of staff 6.43
(1: Very Hotel amenities (pool, game room, free
Unsatisfied to nightly entertainment) 6.42
7: Very Satisfied) Room cleanliness 6.42
Quality of food 6.30
Room comfort 6.12
Relationship established between staff
and customers 6.04
Value for money 5.68

 

Note: a multiple responses allowed.

45

Testing the Measurement Model
Confirmatory Factor Analysis: Model Specifications
The measurement model defines the relationships between observed variables and

the underlying constructs that the observed variables are presumed to measure.

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46

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Note: Satl: Comfortable, Sat2: Pleasing, Sat3: Satisfying, Sat4: Content; Dell: Delighted,
De12: Grateful, Del3: Elated, Del4: Gleeful, D6152 Overjoyed, Del6: Pleased, Del7:
Positively surprised, Del8: Unexpected and delighted; Cogl: More benefits, Cog2: Right
choice, Cog3: More appealing facilities, Cog4: Better value, Cog5: Superior service
quality; Affl: Feel happy, Aff2: Feel grateful, Aff3: Like, Aff4: Love staying, Aff5: Says
a lot about who I am; Conl: Consider myself to be highly loyal to this hotel, Con2:
Intend to continue staying at this hotel, Con3: I would change hotels if another hotel’s
staff was more friendly, Con4: I would try an alternative hotel if it was less expensive
than the lodge, Con5: I would try an alternative hotel if their loyalty program offered
more benefits, Con6: I would try an alternative hotel if the alternative hotel offered
increased facilities/services to the hotel; Actl: Likelihood to return to this hotel in the
next 6 months or less, Ath: Likelihood to return to this hotel in the next 7-12 months,
Act3: Likelihood to return to this hotel in the next year (more than 12 months from now),
Act4: Likelihood to recommend this hotel to others; Error Terms: el-e36.

A confirmatory factor analysis (CF A) was conducted to confirm the hypothesized
relationships between observed variables and their underlying constructs to assess the
degree to which the data fit the proposed measurement model. The measurement model
was estimated using the maximum likelihood method.

As shown in Figure 6, the proposed measurement model consists of six constructs
and 32 observed variables. Customer satisfaction is specified by four observed variables.
Customer delight is specified by eight observed variables. The cognitive loyalty and
affective loyalty are each specified by five observed variables. Conative loyalty is
specified by six variables. Action loyalty is specified by four observed variables.

The measurement model analyzed relationships among a set of observed variables
and latent variables by testing reliability and construct validity including convergent and
discriminant validity. Once the measurement model reached an acceptable level of fit, the
fill] hypothesized structural model was tested to determine its fit relative to the data being

tested. Model modification procedures were used to identify observed variables that had

low factor loadings, significant cross loadings, and large residuals using a standardized

47

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factor. For this study, five goodness-of-fit indices were selected (Browne and Cudeck,
1993; Garson, 2006; Kline, 1998; Steiger, 1989). As shown in Table 11, the goodness-of-
fit indices chosen for this study and the recommended range of good fit are presented.

The proposed measurement model was tested first and. was not acceptable with
the data (x2 (449)=7951.2, p<.001,CFI=.856, TLI=.841, RMSEA=.100, SRMR=.076) as
presented in Table 9. Thus, it was decided to modify the proposed model since CFI, TLI,

RMSEA, and SRMR did not fall within a range of acceptable values.

Table 11. The Recommended Goodness-Of-Fit Indices

 

 

Goodness-of-fit Indices Recommended Range
Used for the Study of Good Model Fit
. . . 2 ' ‘ -

o Chi-Square Statistics (x ) insrgnrficant p value (p>.01)
0 Comparative Fit Index (CPI) > .90
0 Tucker -Lewis Index (TLI) > .90
0 Root Mean Square Error of Approximation .

(RMSEA) <.08: A good fit
0 Standardized Root Mean Square Residual (SRMR) <.05: A good fit

 

2 . . . . . . 2
a x : There rs a problem of sample Size dependency. With rncreasrng sample Size, the x

value increases. For large sample sizes, the x2 statistic provides a highly sensitive
statistical test, but not a practical test of model fit (Bollen, 1989; Browne and Cudeck,
1993; Chung and Rensvold, 2002; Garson, 2006; Kline, 1998; Schermelleh-Engel,
Moosbrugger, and Miiller, 2003; Steiger, 1989).

The observed variables with low factor loadings were removed from the proposed

measurement (less than .50) (Kline, 1998). The CFA test results showed that modified

model 1 was a significantly better fit than the proposed model to the data (x2

(362)=5347.4, p<.001, CF I=.899, TLI=.887, RMSEA=.091, SRMR=.060). However, this

model still presented a poor fit since CFI, TLI, RMSEA, and SRMR results were not

48

within the acceptable ranges. Therefore, modified model 2 was suggested by deleting
several observed variables which had large residuals with other observed variables.

Finally, as shown in Table 12, modified mode12 showed a significant

improvement in chi-square (823.98) and a good fit to the data (12 (75)=823.98, p<.001,

CF I=.965, TLI=.951, RMSEA=.078, SRMR=.035). While CF I, TLI, RMSEA, and

SRMR results were within the recommended range for a model with good fit to the data,

2 . . . . . . . 2
x indicated a poor fit due to the large sample Size. With rncreasrng sample Size, the x

value increases and it leads to the problem that plausible models might be rejected,
although the discrepancy between the sample and the model-implied covariance matrix is

actually irrelevant (Bollen, 1.989; Cheung and Rensvold, 2002; Schermelleh-Engel,

2
Moosbrugger, and Miiller, 2003). JOreskog and SOrbom (1993) suggested that the x

statistic is not a formal test and it should not be focused on too much but rather viewed as
a descriptive goodness-of-fit index due to the problem of sample size (Bollen, 1989;
Schermelleh-Engel et al., 2003). Therefore, it was concluded that the modified model 2
was acceptable.

Table 12. Comparison of the Proposed and Modified Full Measurement Models

 

Model 112 Df CF] TLI RMSEA SRMR A 12
Initiai Model 7951.2 449 .856 .841 .100 .076

Modified

Modem 5347.4 362 .899 .887 .091 .060 2603.80

Modified

Modem 823.98 75 .965 .951 .078 .035 4523.42

 

49

 

 

[11111335

113131;.

'1“: r3"

» .LU

)

‘1

.5

@147

Assessment of Reliability and Validity

The modified measurement model 2 provided support for both validity and
reliability.
Reliabiligy: The reliability test was conducted using Cronbach’s alpha (or) and a
composite reliability, which indicates the internal consistency of the observed variables
measuring each factor. As shown in Table 11, Cronbach’s or of all six factors exceeded
the recommended .70 (Nunnally, 1978) except the cognitive loyalty construct (.61).
However it was considered to be minimally acceptable (Devillis, 1991). Composite
reliability was also conducted to measure true reliability because Cronbach's alpha (or)
may over- or under-estimate scale reliability (Raykov, 1998). The acceptable range for
composite reliability should be greater than .70 (Chin, 1998). All six factors were
acceptable at the recommended .70 level.
Convergent validity: Convergent validity refers to the degree of association between the
observed variables of a factor and is used to determine whether different observed
variables used to measure the factors are highly correlated. Convergent validity can be
examined by reviewing the results of a t-test for the factor loadings (Hatcher, 1994). As
displayed in Table 13, all factor loadings for the observed variables were statistically
significant with t-values ranging from 45.48 to 349.56 (p < .001) and standardized factor
loadings ranging from .69 to .97. Thus, it can be concluded that convergent validity was
supported.
Discriminant validly: Discriminant validity is the degree to which items differentiate
among constructs. The average variance extracted (AVE) for each of the constructs is

greater than their shared variance (Fomell and Larcker, 1981).

50

Table 13. The Result of Confirmatory Factor Analysis for the Modified

Measurement Model 2 (Reliability and Convergent Validity)

 

 

 

 

 

 

 

Variable Standardized t- Cronbach's Emmi"; c

Construct Name Loadinga value b AVE

Customer

Satisfaction SATl .83" 100.64 .95 .97 .91
SAT2 .97" 349.56
SAT3 .96" 307.36

Customer

Delight DELI .83" 80.34 .83 .91 .76
DEL2 .87 " 93.10
DEL3 .70" 48.22

Cognitive

Loyalty COG] .77 " 69.38 .61 .90 .82
COG2 .91 " 126.13

Affective

Loyalty AFFI .90" 110.18 .76 .90 .82
AFF2 .78 ” 68.40

Conative

Loyalty COM .87 " 116.77 .71 .90 .82
CON2 .94 " 164.47

Action

Loyalty ACTl .69" 45.48 .80 .90 .76
ACT2 .87 " 86.52
ACT3 .83" 74.20

 

Note: a Standardized loadings indicate relationships between observed variables and their

associated factors in order to examine convergent validity.

b
Composite Reliability = (Sum of standardized loadings) 2/ ((Sum of standardized

loadings)2 + Sum of indicator measurement error)

e Average Variance Extracted = Sum of squared standardized loadings/ (Sum of squared

standardized loadings + Sum of indicator measurement error)

.. Factor loadings are all significant at p < .001.

51

Table 14. Discriminant Validity Matrix
Customer Customer Cognitive Affective Conative Action
Satisfaction Delight Loyalty Loyalty Loyalty Loyalty

Customer

Satisfaction .91 a

Customer

Delight 50b .76

Cognitive

Loyalty .72 .59 .82

Affective

Loyalty .50 .59 .73 .82

Conative

Loyalty .46 .42 .69 .74 .82
Action

Loyalty .31 .31 .44 .47 .63 .76

 

a . .
Note: Average Variance Extracted for a given construct

The standardized correlation between constructs

Testing the Structural Equation Model

The proposed structural equation model is presented in Figure 7. The eight
hypotheses regarding the relationships among the factors were tested in the structural
equation model and the results of the hypotheses testing are presented in Table 15,
including the standardized path coefficients estimated by SEM and the results of the tests
of hypotheses. A path diagram is also presented in Figure 7. The path diagram shows
standardized path coefficients, representing the direction and strength of the direct
influence of one factor on another, and the squared multiple correlations indicating the

total variance in a factor explained by the factor(s). The results Show that the model fits

the data with all fit indices (112 (81)=730.85, p<.001, CFI=.971, TLI=.963, RMSEA=.070,

SRMR=.034) as shown in Table 15.

52

Action
Loyalty

12: .64

  

x2 (81)=730.85, p<.001,
CFI=.971, TLI=.963,
RMSEA=.070, SRMR=.034

Figure 7. Results of Testing the Proposed Structural Model with Standardized Path

Coefficients and Squared Multiple Correlations (R2: The Total Variance Explained
by the Direct Influence of One Factor on Another)

53

Seven of the eight hypotheses were supported, as shown in Figure 7. Customer
satisfaction had significant direct influences on cognitive and affective loyalty (support
for Hla and Hlb). The influence of customer satisfaction on cognitive loyalty (B = .69, p
< .001) was larger than that on affective loyalty (B = .35, p < .001). Customer delight had
a significant influence on cognitive and affective loyalty (support for H2a and H2b). The
influence of customer delight on affective loyalty (B = .51, p < .001) was larger than that
on cognitive loyalty (B = .28, p < .001). The influence of customer delight on cognitive
loyalty (B = .28, p < .001) was smaller than that of customer satisfaction on cognitive
loyalty (B = .69, p < .001) (did not support H3a). However, the influence of customer
delight on affective loyalty (B = .51, p < .001) was larger than that of customer

satisfaction on affective loyalty ([3 = .35, p < .001) (support H3b).

54

Table 15. Results of Hypotheses Testing

 

 

 

 

 

 

Standardize
d Path Hypotheses
Coefficient testing
Paths ([1) t-value P-value results
Customer Satisfaction 9
Cognitive Loyalty (Hla) .69 32.50 0.00 Supported
Customer Satisfaction 9
Affective Loyalty (Hlb) .35 11.95 0.00 Supported
Customer Delight 9
Cognitive Loyalty (H2a) .28 11.44 0.00 Supported
Customer Delight 9
Affective Loyalty (HZb) .51 17.66 0.00 Supported
Customer delight will
have a greater influence Customer Delight 9 Cognitive Not
on cognitive loyalty in Loyalty: .28 supported

comparison to satisfaction. Satisfaction 9 Cognitive Loyalty: .69
(H3a)

 

 

 

 

Customer delight will
have a greater influence Customer Delight 9 Affective
on affective loyalty in Loyalty: .51 Supported
comparison to satisfaction. Satisfaction 9 Affective Loyalty: .35

IH3b)
Cognitive Loyalty 9
Conative Loyalty (H4) .31 6.75 0.03 Supported
Affective Loyalty 9

_Conative Loyalty (H5) .59 13.02 0.00 Supported
Conative Loyalty 9
Action Loyalty (H6) .80 62.72 0.00 Supported

 

Cognitive and affective loyalty had significant influences on conative loyalty
(support for H4 and H5). The influence of affective loyalty on conative loyalty (I3 = .59, p
< .001) was larger than that of cognitive loyalty on conative loyalty ([3 = .31, p < .05).

Lastly, conative loyalty had significant influences on action loyalty (B = .80, p < .001)

 

 

(support for H6).
lable 16. Overall Fit Indices for the Hypothesized Structural Model
x2 Df CFl TLI RMSEA SRMR
imposed Model 730.85 81 .971 .963 .070 .034

 

55

 

1'1: III

AduhfiphhSquaredIGonndafions

As shown in Figure 7, 64 percent of variance in action loyalty was explained by
the influences of conative loyalty. Seventy-six percent of variance in conative loyalty was
explained by the influences of cognitive and affective loyalty. Customer satisfaction and
delight explained 82 percent of variance in cognitive loyalty and 63 percent in affective

loyalty.

56

Additional Analyses
Additional Analysis with a Full Path Model

In order to test complete or partial mediating effects among constructs and to
determine a better fitting model, a full path model was also tested by adding several paths
between antecedents and dependent variables as shown in Figure 8. The proposed model
is based on complete mediating effects of cognitive, affective, and conative loyalty. The
causal claims are grounded in previous studies of a sequential loyalty development
conceptualization with the mediating roles of each different phase of loyalty (Back, 2001 ,
2005; Back and Parks, 2003; Evanschitzky and Wunderlich, 2006; Harris and Goode,
2004; Oliver, 1999). Applying this framework in the tourism and hospitality context, this
study identified mediating effects between antecedents and dependent variables. In the
proposed model, cognitive and affective loyalty were used as mediator variables between
customer satisfaction and conative loyalty and also between customer delight and
conative loyalty. Conative loyalty was used as a mediator variable between cognitive
loyalty and action loyalty and between affective loyalty and action loyalty.

As shown in Figure 9, the full path model, a partial mediator model is less
restrictive. To this extent, customer satisfaction and delight could have direct effects on
the groups of conative and action loyalty. Cognitive and affective loyalty could also have
direct effects on action loyalty. Furthermore, this full path model shows cognitive,
affective, and conative loyalty as partial mediators. Therefore, the hill path model was
tested with this possibility although it was not hypothesized in the proposed model based

on some studies supporting that satisfaction has a direct impact on repeat purchase

57

intentions (Fornell, Johnson, Anderson, Cha, and Bryant, 1996; Yi, 1990) and brand

loyalty (Shoemaker and Lewis, 1999).

 

Customer
Satisfaction
Cognitive
Loyalty
Conative Action
loyalty Loyalty
Affective
loyalty
Cmtoiner
”eight

Figure 8. The Proposed Model

 
    
  

thmu
Sat'nfaction

Cognitive
Loyalty
Affective
Loyalty
Customer
Delight

Conative Action
Loyalty loyalty

Figure 9. The Full Path Model

The goodness-of-fit measures were compared to assess which of the two models

is better. As shown in the Table 17, both the proposed and full path models met the fit

59

criteria. The fit indices for the two models were very similar, showing that the two

models had the same level of model fit (proposed model: x2 (81)=730.85, p<.001,
CFI=.971, TLI=.963, RMSEA=.070, SRMR=.034; competing model: x2 (75)=711.59,

2
p<.001, CFI=.972, TLI=.960, RMSEA=.072, SRMR=.033). The Chi-square (x )

difference test was also performed to assess whether there was a significant difference

between the two models (Bagozzi and Yi, 1988; JOreskog and SOrbom, 1993). The Chi-

2 . 2
square (x ) difference test between the proposed model and the full path model (A x =

19.267; A df = 6) supported that the full path model performed significantly better than
the proposed model. The results provided that customer satisfaction did not have a direct
effect on cognitive loyalty and action loyalty, whereas delight had a negative direct effect
on conative loyalty (I3 = - .10, p < .001) but a positively direct effect on action loyalty (B
= .08, p < .05). For cognitive and affective loyalty, there was no direct effect on action
loyalty. Therefore, this study showed that both cognitive and affective loyalty were
complete mediators between customer satisfaction and conative loyalty. Conative loyalty
also acted as a complete mediator between cognitive and action loyalty and between
affective loyalty and action loyalty. However, the result of the path between delight and
conative loyalty (negative effect of delight on conative loyalty) did not support the
previous studies showing a positive effect of delight on conative loyalty (Arnold et al.,
2005; Firm, 2005; Oliver et al., 1997). Therefore, these results suggest that the proposed

model was conceptually a better model than the full path model, although the competing

. . . . 2 .
model was statistically a better model resulting from the chi-square (x ) different test.

60

Table 17. The Results of the Proposed Model and Full Path Model

 

 

 

 

 

 

 

 

Path Proposed model Full Path model
Standardized Standardized
Path Path
Coeffiecient t- P- Coeffiecient t- P-
(0) value value ([1) value value
Customer Satisfaction9
Cognitive Loyalty .69 32.50 .000 .69 32.25 .000
Customer Satisfaction9
Affective Loyalty .35 11.95 .000 .40 15.65 .000
Customer Satisfaction9 Non-
Conative Loyalty Not tested -.07 -1.43 si g.
Customer Satisfaction9 Non-
Action Loyalty Not tested .04 .61 si g.
Customer Deli ght9
Cognitive Loyalty .28 11.44 .000 .28 11.64 .000
Customer Delight 9
Affective Loyalty .51 17.66 .000 .49 18.47 .000
Customer Delight 9
Conative Loyalty Not tested -.10 -3.30 .001
Customer Delight 9
Action Loyalty Not tested .08 2.12 .034
Cognitive Loyalty9
Conative Loyalty .31 6.75 .000 .32 3.48 .000
Cognitive Loyalty9 Non-
Action Lgyalty Not tested -.11 -.97 si g.
Affective Loyalty9
Conative Loyalty .59 13.02 .000 .72 11.71 .000
Affective Loyalty9 Non-
Action Loyalty Not tested .03 .29 sig.
Conative Loyalty9
Action Loyalty .80 62.72 .000 .79 14.35 .000
112611) 730.85 (81) 711.59 (75)
P value .000 .000
CFI .971 .972
TLI .963 .960
RMSEA .070 .072
SRMR .034 .033
R2 (Cognitive Loyalty) '82 '82
R2 (Affective Loyalty) '63 '68
R2 (Conative Loyalty) ‘76 '79
2 .64 .64

R (Action Loyalty)

 

61

 
    

Cognitive
loyalty

x2(81)=730.85,p<.001,
CFI=.971,TLI=.963,
RMSEA=.070, SRMR=.034

Figure 10. Results of Testing the Proposed Structural Model with Standardized
Path Coefficients and Squared Multiple Correlations

62

.ustomer
.tislaclion

    

Oil-Sig.

40H

Cognitive
Wally Non-Sig.

.32“ R =.79 on-Sig.

.71 Conative 79, Action
Loyalty ° Lola“!

 

Non-Sig. R2=.64
.08*
.ustomer
°ight
12(75F71159, p<.001,
=10" CFI=.972,TLI=.960,

RMSEA=.072, SRMR=.033

Figure 11. Results of Testing the Competing Structural Model with Standardized
Path Coefficients and Squared Multiple Correlations

63

Additional Analysis between F irst- Time Guests (or not Recent Guests in the Past 3
Years) and Repeat Guests

Based on the number of stays at the resort, respondents were divided into two
groups; first-time guests (or not recent guests in the past 3 years) and repeat guests. In
order to test the differences between these two groups, a two- group analysis was
conducted. Table 18 presents the respondents’ socio-demographic information for the
two groups. Most of the characteristics were similar between the two groups excluding
characteristics of employment status and primary residence. A group of first-time guests
(or not recent guests in the past 3 years) had a greater percentage of full-time
employment and a group of repeat guests had a greater percentage of primary residence
in Michigan.

Table 19 shows the means of customer satisfaction, delight, cognitive loyalty,
affective loyalty, conative loyalty, and action loyalty of the two groups. In order to
investigate whether the two groups have statistically significant differences, analysis of
variance (AN OVA) tests were performed. The mean differences in customer satisfaction
with three items were not statistically significant. Two items under delight, “delighted”
and “overjoyed,” were not statistically significant. However, an item under delight,
“positively surprised,” was statistically significant at p<0.05. One item under cognitive
loyalty, “I believe the hotel provides more benefits than other hotels of its type” was
statistically significant at p<0.05 and one item under cognitive loyalty, “The hotel’s
facilities are visually more appealing compared to other hotels of its type” was not

statistically significant. The mean differences in affective, conative, and action loyalty

64

were statistically significant at p<0.05 or p<0.001. The results showed that a group of

repeat guests had higher means of loyalty.

65

Table 18. Socio-Demographic Characteristics of Survey Respondents between First-
Time (or not recent guests in the past 3 years) and Repeat Guests

 

 

 

 

 

 

 

 

First-Time
Guests
(or Not Recent
Guests in the
Past 3 Years) Repeat Guests
Category (n=1,018) (n=640)
Frequency % Frequency %
Gender Female 672 3 1% 443 30%
Male 305 69% 189 70%
Total 977 100% 632 100%
Race African American/Black 20 2% 12 2%
American Indian 30 3% 21 3%
Asian or Pacific Islander 7 1% 4 1%
European American/Middle
East/White 801 83% 498 81%
Hispanic/Latino/Latina 8 1% 4 1%
Other 97 10% 78 13%
Total 963 100% 617 100%
Employment Employed full-time 604 63% 351 57%
Status Employed part-time 78 8% 75 12%
Retired 1 1 8 12% 50 8%
Self-employed 86 9% 82 13%
Unemployed 35 4% 33 5%
Other 40 4% 28 5%
Total 961 1 00% 619 100%
Income Less than $25,000 26 3% 30 5%
$25,000-$34,999 52 6% 36 6%
$35,000-$49,999 1 13 12% 64 1 1%
$50,000-$74,999 195 21 % 139 23%
$75,000-$99,999 174 18% 99 17%
$100,000-$149,999 162 17% l 10 18%
$150,000-$199,999 51 5% 19 3%
$200,000 or more 23 2% 6 1%
I prefer not to respond 149 16% 95 16%
Total 945 100% 598 100%
Primary Michigan 591 61% 448 73%
Residence Ohio 1 33 14% 5 1 8%
Canada 61 6% l 8 3%
Indiana 36 4% 34 6%
Illinois 41 3% 9 1%
Other 127 13% 54 9%
Total 989 1 00% 61 5 100%
Ag Mean 48 48

 

66

Table 19. Mean Difference in Satisfaction, Delight, Cognitive Loyalty, Affective
Loyalty, Conative Loyalty, and Action Loyalty between First-Time (or not recent
guests in the past 3 years) and Repeat Guests

First-Time Guests

 

 

 

 

 

 

(or Not Recent
Guests in the Past 3 Repeat
Years) Guests AN OVA
Constructs Variable Names (n=1,018) (n=640) (p)
Customer SATl (Comfortable) 6.1 a 6.1 Non. Sig.
Satisfaction SAT2 (Satisfying) 6.0 6.1 Non. Sig.
SAT3 (Content) 6.1 6.2 Non. Sig.
Customer DELl (Delighted) 5.7a 5.8 Non. Sig.
Delight DEL5 (Overjoyed) 4.8 5.0 Non. Sig.
DEL7 (Positively
surprised) 5. 1 4.8 .003
Cognitive COGl (More benefits) 5.6 a 5.8 .004
Loyalty COG2 (Right choice) 6.0 6.1 Non. Sig.
Affective AF F3 (Like) 5.4 a 5.6 .003
Loyalty AFF4 (Love staying) 5 .6 5.9 .000
AFFS (Says a lot about
who I am) 4.8 5.0 .001
Conative CON 1 (Consider myself
Loyalty to be highly loyal to this
hotel) 5 la 5.5 .000
CON2 (Intend to '
continue staying at this
hotel) 5. 5 5 .9 .000
Action ACTl (Likelihood to
Loyalty return to this hotel in the
next 6 months or less)
ACT2 (Likelihood to 33b 4.7 .000

return to this hotel in the
next 7-12 months)
ACT3 (Likelihood to 5.7 .000

return to this hotel in the 5'0
next year (more than 12
months from now) 5 5 .000

6.0

 

Note: a Scale: Range from 1: strongly disagree to 7: strongly agree
b
Scale: Range from 1: extremely unlikely to 7: quite likely

67

Hypothesized structural models of the two groups were also performed. The )8

difference test was used to test for the moderating effects on individual paths to examine

the groups’ differences in individual paths. Table 20 presents the 12 difference results for

path coefficients between groups. The x2 difference tests showed that the paths of

Customer Satisfaction --> Affective Loyalty, Customer Delight --> Cognitive Loyalty
and Affective Loyalty, Cognitive Loyalty --> Conative Loyalty, and Affective Loyalty

--> Conative Loyalty -

Table 20. 12 Difference Tests

 

 

 

 

 

 

 

 

Path Difference in 12

Customer Satisfaction 9 Cognitive Loyalty Non. Sig.
Customer Satisfaction 9 Affective Loyalty 8.26“
Customer Delight 9 Cognitive Loyalty 8.34“
Customer Delight 9 Affective Loyalty 8.29"
Cognitive Loyalty 9 Conative Loyalty 10.32"
Affective Loyalty 9 Conative Loyalty 8.61**
Conative Loyalty 9 Action Loyalty Non. Sig.

 

Note: “Significant at p<.001

As shown in the Table 21, both the groups of first-time guests (or not recent

guests in the past 3 years) and repeat guests met the fit criteria (first-time guests (or not

recent guests in the past 3 years): x2 (81)=454.82, p<.001, CF I=.969, TLI=.958,

RMSEA=.075, SRMR=.035; repeat guests: x2 (81)=232.92, p<.001, CFI=.976, TLI=.968,

RMSEA=.062, SRMR=.027).

68

Table 21. Comparison of Overall Fit Indices for Two Groups

 

 

 

if Df CFI TLI RMSEA SRMR
F irst-Time Guests
(or not recent guests in
the past 3 years) 454.82 81 .969 .958 .075 .035
Repeat Guests 232.92 81 .976 .968 .062 .027

 

As shown in Table 22, the results provided that customer delight has a greater
effect on cognitive loyalty and affective loyalty in the group of first-time guests (or not
recent guests in the past 3 years) (B = .35, I3 = .53) compared to the group of repeat guests
(B = .24, B = .41). Customer satisfaction has a greater effect on cognitive loyalty and
affective loyalty in the group of repeat guests ([3 = .68, B = .45) compared to the group of
first-time guests (or not recent guests in the past 3 years) ([3 = .63, B = .36). For cognitive
loyalty, there is no direct effect on conative loyalty in the group of first-time guests (or
not recent guests in the past 3 years) while cognitive loyalty has a positive effect on

conative loyalty in the group of repeat guests ([3 = .85).

69

Table 22. Path Coefficient of the Hypothesized Models between the Groups of First-
Time Guests (or not recent flests in the past 3 yea@ and Repeat Guests
First-Time Guests Repeat Guests

 

 

 

 

 

 

 

 

 

 

$1,018) (n=640)
Path Hypotheses Standardized Path Standardized Path
Coefficient ([3) Coefficient ([3)
Customer Satisfaction 9
Cognitive Loyalty Hla .63" .68**
Customer Satisfaction 9
Affective Loyalty Hlb .36** .45**
Customer Delight 9
Cognitive Loyalty H2a .35** .24"
Customer Delight 9
Affective Loyalty H2b .53** .41 **
Customer delight will
have a greater influence
on cognitive loyalty in
comparison to satisfaction. H3a Not Supported Not Supported
Customer delight will
have a greater influence
on affective loyalty in
comparison to satisfaction. H3b Supported Not Supported
Cognitive Loyalty 9
Conative Loyalty H4 Non-Sig. .33"
Affective Loyalty 9 H5
Conative Loyalty .85** .55**
Conative Loyalty 9 H6
Action Loyalty .78** .76**

 

7O

First-Time Guests
(or Not Recent Guests in the Past 3 Years)

. (n=1,018)

 

12 (81)-454.82, p<.001,
CFI=.969,TLI=.958,
RMSEA=.075,SRMR=.035

Figure 12. Results of Testing the Structural Model with Standardized Path
Coefficients and Squared Multiple Correlations (A Group of First-Time Guests (or
Not Recent Guests in the Past 3 Years)

71

Repeat Guests(n=640)

 
     
 

.mtomer
.alislaction

     
   

'76“ Action
loyalty

R2= .58

x2 (81)=232.92,p<.001,
CFI=.976,TLI=.968,
RMSEA=.062,SRMR=.027

Figure 13. Results of Testing the Structural Model with Standardized Path
Coefficients and Squared Multiple Correlations (A Group of Repeat Guests)

72

Additional Analysis between Loyalty Program Members and Loyalty Program Non-
Members

Respondents were divided into two groups; loyalty program members and loyalty
program non-members. In order to test the differences between these two groups, a two-
group analysis was conducted. Table 23 presents the respondents’ socio-demographic
information for the two groups. Most of the characteristics were similar between the
groups excluding characteristics of employment status and primary residence. The group
of loyalty program non-members had a greater percentage of full-time employment and a
group of loyalty program members had a greater percentage of primary residence in
Michigan.

Table 24 shows the means of customer satisfaction, delight, cognitive loyalty,
affective loyalty, conative loyalty, and action loyalty of these two groups. In order to
investigate whether the two groups have statistically significant differences, analysis of
variance (AN OVA) tests were performed. Table 25 shows that the mean differences in
customer satisfaction, cognitive, affective, conative, and action loyalty were statistically
significant at p<0.05 or p<0.001. The results showed that a group of loyalty program
members had higher means of customer satisfaction, cognitive, affective, conative, and
action loyalty. Two items under delight, “delighted” and “overjoyed,” were also
statistically significant at p<0.001. However, one item under delight, “positively

surprised,” was not statistically significant.

73

Table 23. Socio-Demographic Characteristics of Survey Respondents between

Loyalty Program Members and Loyalty Program Non-Members

 

Loyalty Program Loyalty Program

 

 

 

 

 

 

 

Members Non-Members
Category (n=815) (n=789y
Frequency % Frequency %
Gender Female 557 31% 544 70%
Male 250 69% 233 30%
Total 807 100% 777 1 00%
Race African American/Black 13 2% 19 3%
American Indian 27 3% 22 3%
Asian or Pacific Islander 5 1% 6 1%
European American/Middle
East/White 659 83% 622 82%
Hispanic/Latino/Latina 7 1% 4 1%
Other 87 1 1% 85 l 1%
Total 798 100% 1758 100%
Employment Employed full-time 455 5 8% 488 64%
Status Employed part-time 78 10% 72 9%
Retired 109 14% 88 12%
Self-employed 68 9% 64 8%
Unemployed 34 4% 31 4%
Other 46 6% 22 3%
Total 790 100% 765 100%
Income Less than $25,000 30 4% 24 3%
$25,000-$34,999 40 5% 47 6%
$35,000-$49,999 100 13% 75 10%
$50,000-$74,999 168 22% 162 22%
$75,000-$99,999 142 18% 126 17%
$100,000-$149,999 130 17% 141 19%
$150,000-$199,999 30 4% 40 5%
$200,000 or more 10 1% 19 3%
I prefer not to respond 131 17% 1 11 15%
Total 781 100% 745 100%
Primary Michigan 573 71% 466 60%
Residence Ohio 79 10% 105 14%
Canada 27 3% 52 7%
Indiana 40 5% 3 1 4%
Illinois 19 2% 31 3%
Other 77 9% 104 12%
Total 81 5 100% 789 100%
_A_ge Mean 48 47

 

74

Table 24. Mean Difference in Satisfaction, Delight, Cognitive Loyalty, Affective
Loyalty, Conative Loyalty, and Action Loyalty between Loyalty Program Members
and Loyalty Program Non-Members
Loyalty
Loyalty Program
Program Non-
Members Members AN OVA

 

 

 

 

 

 

Constructs Variable Names (n=815) (n=789) (p)
Customer SATl (Comfortable) 6 2 a 6.0 .004
Satisfaction SAT2 (Satisfying) 6 2 5.9 .000
SAT3 (Content) 6.3 6.0 .000
Customer DELI (Delighted) 5 9 a 5.6 .000
Delight DEL5 (Overjoyed) 5 1 4.7 .000
DEL7 (Positively surprised) 5'0 5.0 Non. Sig.
Cognitive COGl (More benefits) 5 9 a 5.5 .000
Loyalty COG2 (Right choice) 6 2 5.9 .000
Affective AFF3 (Like) 5 8 a 5.2 .000
Loyalty AFF4 (Love staying) 6 1 5.4 .000
AFFS (Says a lot about who I '
am) 5.2 4.5 .000
Conative CON1(Consider myself to be
Loyalty highly loyal to this hotel) 5 8 a 4.7 .000
CON2 (Intend to continue '
staying at this hotel) 6 1 5.2 .000
Action ACTl (Likelihood to return to
Loyalty this hotel in the next 6 months
or less) 5 0 b 3.3 .000

ACT2 (Likelihood to return to

this hotel in the next 7-12

months) 5 9 4.6 .000
ACT3 (Likelihood to return to '

this hotel in the next year

(more than 12 months from

now) 6 1 5.3 .000

 

Note: a Scale: Range from 1: strongly disagree to 7: strongly agree
b
Scale: Range from 1: extremely unlikely to 7: quite likely

Hypothesized structural models of the two groups were also performed. The x2

difference test was used to test for the moderating effects on individual paths to examine

75

the groups’ differences in individual paths. Table 25 presents the x2 difference results for

path coefficients between groups. The x2 difference tests showed that the paths of

Customer Delight --> Affective Loyalty, Cognitive Loyalty --> Conative Loyalty, and

Affective Loyalty --> Conative Loyalty.

Table 25. 12 Difference Tests

 

 

 

 

 

 

 

 

Path Difference in x2

Customer Satisfaction 9 Cognitive Loyalty Non. Sig.
Customer Satisfaction 9 Affective Loyalty Non. Sig.
Customer Delight 9 Cognitive Loyalty Non. Sig.
Customer Delight 9 Affective Loyalty 8.29"
Cognitive Loyalty 9 Conative Loyalty 9.65“
Affective Loyalty 9 Conative Loyalty 8.24M
Conative Loyalty 9 Action Loyalty Non. Sig

 

Note: "Significant at p<.001

As shown in the Table 26, both the groups of loyalty program members and
loyalty program non-members met the fit criteria (loyalty program members: )(2
(81)=730.85, p<.001, CFI=.971, TLI=.963, RMSEA=.070, SRMR=.034; loyalty program
non-members: x2 (81)=449.98, p<.001, CFI=.964, TLI=.953, RMSEA=.076,

SRMR=.038).

Table 26. Comparison of Overall Fit Indices for Two Groups
12 Df CFI TLI RMSEA SRMR

 

 

Loyalty Program

Members 730.85 81 .971 .963 .070 .034
Loyalty Program Non-

Members 449.98 81 .964 .953 .076 .038

 

The goodness-of-fit measures were compared to assess which of the two models

is better. As shown in the Table 25, both the proposed and competing models met the fit

76

criteria. The fit indices for two models were similar, showing that the two models had the

same level of model fit (proposed model: x2 (81)=730.85, p<.001, CF I=.971, TLI=.963,

RMSEA=.070, SRMR=.034; competing model: x2 (75)=711.59, p<.001, CF I=.972,

TLI=.960, RMSEA=.072, SRMR=.033).

As shown in Table 27, the results provided that customer delight has a greater
effect on cognitive loyalty and affective loyalty in the group of loyalty program non-
members (B = .33, B = .54) compared to the group of loyalty program members (B = .30,
B = .46). Customer satisfaction has a greater effect on affective loyalty in the group of
loyalty program members (B = .40) compared to the group of loyalty program non-
members (B = .36). Cognitive loyalty has a greater effect on conative loyalty in the group
of loyalty program non-members (B = .64) compared to the group of loyalty program
members (B = .31). Affective loyalty has a greater effect on conative loyalty in the groups
of loyalty program members ((B = .56) compared to the group of loyalty program non-

members (B = .35).

77

Table 27. Path Coefficients of the Hypothesized Models between the Groups of
Loyalty Program Members and Loyalty Prggam Non-Members

 

 

 

 

 

 

 

 

 

 

Loyalty Program Loyalty Program
Members Non-Members
(n=815) (n=789)

Path Hypotheses Standardized Path Standardized Path
Coefficrent (B) Coefficient (B)

Customer Satisfaction 9

Cognitive Loyalty Hla .63** .65"

Customer Satisfaction 9

Affective Loyalty Hlb .40** .36"

Customer Delight 9

Cognitive Loyalty H2a .30** .33“

Customer Delight 9

Affective Loyalty H2b .46“ .54"

Customer delight will have

a greater influence on

cognitive loyalty in

comparison to satisfaction. H3a Not Supported Not Supported

Customer delight will have

a greater influence on

affective loyalty in

comparison to satisfaction. H3b Supported Supported

Cognitive Loyalty 9 u ,H,

Conative Loyalty H4 '31 '64

Affective Loyalty 9

Conative Loyalty H5 .56** .35**

Table 27. (cont’d)

Conative Loyalty 9

Action Loyalty H6 .76** .56M

 

78

Loyalty Program Members (n=815)

 

x2(81)=730.85,p<.001,
CFI=.971,TLI=.963,
RMSEA=.070,SRMR=.034

Figure 14. Results of Testing the Structural Model with Standardized Path
Coefficients and Squared Multiple Correlations (A Group of Loyalty Program
Members)

79

Loyalty Program Non-Members (n=789)

Customer
Satisfaction R2: 85
.65**
Cognitive
.36" War,
one
'73 67 Conative '75“ Action
' loyalty loyalty
.33** ~35”

Afl'ective R2: .93 R2: .56
Loyalty
.54**
Customer 2
ll =.70
x2(81H49.98,p<.001,

CFI=.964, TLI=.953,
RMSEA=.076, SRMR=.038

Figure 15. Results of Testing the Structural Model with Standardized Path
Coefficients and Squared Multiple Correlations (A Group of Loyalty Program Non-
Members)

Summary

This chapter presented the results on the customer satisfaction, delight, and
loyalty model testing including six hypotheses tests summarized in Table 28.
Additionally, this chapter showed the results of the groups’ differences (e. g., First-time
guests vs. Repeat guests, Loyalty program members vs. Loyalty program non-members).
The next chapter discusses the results and implication of the study, as well as,
opportunities for future research and limitations of this study. The results are presented
with current literature perspectives and the theoretical contributions of the study are
discussed including managerial implications.
Table 28. Summary of the Hypothesized Finding

Hypothesis Findings
Customer satisfaction will have a direct positive influence on

 

 

 

 

 

Hla cognitive loyalty. Supported

Customer satisfaction will have a direct positive influence on Su o rt e d
Hlb affective loyalty. pp

Customer delight Will have a direct posrtlve influence on cognitive Supported
H2a loyalty.

Customer delight will have a direct positive influence on affective S

upported

H2b loyalty.

Customer delight will have a greater influence on cognitive Not
H3a loyalty in comparison to satisfaction. supported

Customer delight will have a greater influence on affective loyalty

. . . . Supported
H3b 1n comparison to satlsfactron.

Cogmtlve loyalty Will have a direct positive influence on conative Supported
H4 loyalty.

Affective loyalty Will have a dlrect posmve 1nfluence on conative Supported
H5 loyalty.

Conative loyalty Wlll have a direct posrtive 1nfluence on action Supported

H6 loyalty.

 

81

CHAPTER 5

DISCUSSION, IMPLICATIONS, AND CONCLUSIONS

The purpose of this study was to examine the impact of customer satisfaction and
delight on loyalty by empirically testing a model. Furthermore, the study aimed to better
understand four phases of loyalty development: cognitive, affective, conative, and action
loyalties. The subjects of this study were 1,660 (1,573 from an online survey, 87 from a
paper survey) guests who stayed at a Midwestern resort hotel, during the summer of 2009
in the months of July, August, and September. All subjects completed either an online or
paper survey instrument consisting of six sections and the respondents’ demographic data
and traveling characteristics. To answer the research questions, structural equation
modeling (SEM) was conducted to explore the relationships between customer
satisfaction, delight, and loyalty in a tourism and hospitality context. The Statistical
Package for the Social Science (SPSS) was also used for all descriptive analyses
including the frequency distributions.

This chapter consists of four sections: (1) summary of the important findings of
this study and discusses the findings; (2) the theoretical and practical implications of the
study are presented; (3) directions for fiiture research and limitations of the study; and (4)
conclusion with final comments.

Results of Hypotheses Testing and Discussion of the Findings
As presented in Figure 16, the conceptual model of this study was proposed to

examine relationships among the constructs with six hypotheses.

82

 

Customer delight will have a greater positive influence
H— on cognitive loyalty in comparison to satisfaction.

Customer H33
Salutation

la

Cognitive
Hlb level!

H4

Conative H6 Action
10W loyalty
H2a
Affective
..
Customer
Customer delight w111 have a greater posutuve mfluencc

on affective loyalty in comparison to satisfaction.

 

 

 

 

 

 

 

 

 

Figure 16. Proposed Conceptual Model

83

Hypotheses 1a & 1 b: Customer satisfaction will have a direct positive influence on
cognitive and affective loyalty.

The hypotheses regarding the direct influence of customer satisfaction on
cognitive loyalty (Hla) and affective loyalty (Hlb) were supported. These findings
provide empirical evidence in support of previous studies that noted the positive
relationship between customer satisfaction and attitudinal loyalty (Cronin and Taylor,
1992; Yi, 1990; Zeithaml et al., 1996). Specifically, this finding shows that satisfaction
influences positively cognitive and affective loyalty directly. These findings also indicate
that respondents had a higher cognitive loyalty (B = .69) than affective loyalty (B = .35).

Hypotheses 2a & 2b: Customer delight will have a direct positive influence on
cognitive and affective loyalty.

Hypotheses 2a and 2b were supported with the direct influence of customer
delight on cognitive loyalty (H2a) and affective loyalty (H2b). This finding broadens the
conceptualization of customer delight-related loyalty by providing empirical evidence
and supports the literature review suggesting the important role of customer delight as a
pivotal driver of loyalty (Hicks et al., 2005; Kumar et al., 2006; Oliver et al., 1997;
Patterson, 1997; Rust and Oliver, 1994; Westbrook and Oliver, 1991; Williams and
Anderson, 1999). However, in the context of tourism and hospitality, empirical research
of the relationship between delight and loyalty has not been studied much and remains in
its infancy. Therefore, the current study constitutes one of the grounding steps toward
investigating this relationship. The strength of the direct influence of customer delight on

affective loyalty was higher ([3 = .51) than on cognitive loyalty (B = .28).

84

Hypotheses 3a & 3b: Customer delight will have a greater influence on cognitive &
affective loyalty in comparison to satisfaction.

Hypothesis 3a was not supported. Customer delight had a weaker influence on
cognitive loyalty (B = .28) in comparison to the influence of satisfaction on cognitive
loyalty (B = .69). This finding challenges the proposition that customer delight is more
likely to show loyalty than satisfied customers (Oliver et al., 1997; Paul, 2000).
Hypothesis 3b was supported. This finding indicates that customer delight had a greater
influence on affective loyalty (B = .51) in comparison to the influence of satisfaction on
affective loyalty (B = .35). This finding provides empirical evidence in support of
previous studies that delight is a stronger emotion than satisfaction and can be
discriminated as a different psychological state than satisfaction (Mano, 1991; Watson
and Tellegen, 1985), and delight is directly related to positive affect (Hicks et al., 2005;
Oliver et al., 1997).

Hypotheses 4 & 5: Cognitive loyalty and affective loyalty will have a direct positive
influence on conative loyalty.

Hypotheses 4 and 5 were supported. Both cognitive and affective loyalty had
significant and positive direct influence on conative loyalty. This finding suggests that
both cognitive and affective loyalty directly contribute to conative loyalty, and thus
supports the findings of previous loyalty studies which emphasized that cognitive and
affective loyalty influence conative loyalty positively either directly or indirectly (Harris
and Goode, 2004; McMullan and Gilmore, 2003; Oliver, 1997, 1999). This study
proposes a new conceptual model of loyalty development as cognitive and affective
loyalty directly influence conative loyalty. Affective loyalty had a stronger direct

influence on conative loyalty (B = .59) in comparison to cognitive loyalty (B = .31).

85

Hypothesis 6: C onative loyalty will have a direct positive influence on action loyalty.

Hypothesis 6 was supported. Conative loyalty was found to have significant and
positive direct influences on action loyalty (B = .80). This result supports a model of
attitude-behavior linkage, which is theoretically grounded as attitudinal loyalty leads to
behavioral loyalty (Ajzen, 1991; Breckler, 1984; Dick and Basu, 1994). This finding also
indicates that there is a strong relationship between conative loyalty and action loyalty (B
= .80), and 64 percent of the variance in action loyalty was explained by the influences of
conative loyalty.
Implications

The findings of this study have both theoretical and practical implications. This
section presents the theoretical contributions of this study to existing tourism and
hospitality literature, and its practical implications for tourism and hospitality marketers.
Theoretical Implications

The present study has several theoretical implications for consumer behavior
research. First, this study is one of few empirical studies on customer satisfaction, delight,
and loyalty and provides a foundation for researchers in the understanding of the
relationships between customer satisfaction, delight, and loyalty. In particular, this study
extends support for the conceptualization of customer satisfaction and delight as distinct
constructs (Hicks et al., 2005; Oliver et al., 1997; Rust and OliVer, 1994; Westbrook and
Oliver, 1991). This study also shows that both customer satisfaction and delight are
important antecedents of loyalty; particularly, customer satisfaction and delight have
direct significant relationships with cognitive and affective loyalty. Furthermore, the

strength of the impact of customer delight on affective loyalty has greater influence than

86

that of customer delight on cognitive loyalty, while the strength of the impact of customer
satisfaction on cognitive loyalty is greater than that on affective loyalty.

Second, the findings of this study provide new insights by integrating customer
satisfaction and delight concepts together in an effort to better explain customer loyalty.
A number of researchers have previously highlighted the importance of customer delight
(Hicks et al., 2005; Kumar et al., 2006; Oliver et al., 1997; Patterson, 1997; Rust and
Oliver, 1994; Westbrook and Oliver, 1991; Williams and Anderson, 1999). In particular,
understanding a customer’s emotional experience becomes critical in the tourism and
hospitality industry area because there are many interactions with customers and staff
during the consumption process in a service environment. Additionally, it is suggested
that a mere customer satisfaction approach may be not enough in understanding customer
loyalty (Hicks et al., 2005; Oliver et al., 1997 ; Williams and Anderson, 1999). Although
researchers agree on the importance of emotional factors, such as customer delight being
related to loyalty, there have been few empirical studies linking delight and loyalty.
Therefore, this study extends support for the importance of customer delight as one of the
primary antecedents of customer loyalty by empirically proving that customer delight
directly leads to loyalty. Specifically, the present study showed that customer delight has
a direct positive influence on cognitive and affective loyalty and customer delight has a
greater impact on affective loyalty, in comparison to satisfaction.

A‘third theoretical implication of this study is its contribution to extend the
existing literature on the customer loyalty formation process by attempting a new
conceptualization of the loyalty dimension. Most earlier studies on the conceptualization

of the loyalty dimension originated from Dick and Basu (1994) and Oliver (1997, 1999)

87

which suggested that loyalty formation starts from cognitive loyalty, followed by
affective loyalty, to conative loyalty, and ultimately to action loyalty (Oliver, 1997, 1999).
Based on Oliver’s (1997, 1999) loyalty dimensions, many researchers have supported
Oliver’s four loyalty dimensions model by empirically testing the model and developing
the measurement scales (Harris and Goode, 2004; Knox and Walker, 2001; McMullan
and Gilmore, 2003; Tsaur, Chiu, and Huang, 2002). Meanwhile, other researchers
challenged the cognitive-affective-conative loyalty sequences and proposed four unique
phases of loyalty development (Back, 2001; Jones and Taylor, 2007; Li and Petrick,
2008). For example, Back (2001) and Li and Petrick (2008) suggested that the three
attitudinal loyalty dimensions of cognitive, affective, and conative loyalty are not a
sequential formation process but are independent concepts. Furthermore, this present
study proposes a new conceptualization of loyalty development: the two loyalty
dimensions, cognitive and affective loyalty, are independent and inter-relational
components of attitudinal loyalty. This conceptualization is grounded in the psychology
literature with cognition and affection as separate and independent concepts (Peter and
Olson, 2005; Piaget, 1981; Stevens, 1970). This conceptualization was also empirically
supported from the testing of the proposed model. Furthermore, this study is meaningful
as one of a few empirical studies distinguishing the different impacts of cognitive and
affective loyalty on conative loyalty. Additionally, while many researchers have focused
on the cognitive aspects of loyalty, this study supports that affective loyalty is more likely
to enhance conative loyalty than cognitive loyalty.

Last, this study extends the existing literature on the link of customer satisfaction

and loyalty by providing empirical support. There are many studies that emphasize the

88

importance of customer satisfaction on loyalty (Aj zen and Driver, 1991; Chen and
Gursoy, 2001; Shoemaker and Lewis, 1999; Yoon and Uysal, 2005) while some studies
found customer satisfaction does not always have a significant influence on loyalty
(Jones and Sasser, 1995; Stewart, 1997). However, the finding of this study reinforces the
traditional view that there is a statistically strong and critical relationship between
customer satisfaction and loyalty, and that customer satisfaction is one of main
antecedents of loyalty (Mittal and Karnakura, 2001). Specifically, this study provides the
ability to understand satisfaction from both cognitive and affective perspectives although
satisfaction was focused on a more cognitive perspective in the previous studies. Based
on Oliver’s (1980) disconfirmation theory, satisfaction was primarily understood as a
cognitive state resulting from cognitive evaluations between expectations and perceived
performance which then leads to satisfaction (Bigné et al., 2003; Oliver and Swan, 1989)
and satisfaction also has a direct effect on cognitive loyalty (Back, 2005; Back and Parks,
2003; Firm; 2005, Oliver, 1997). However, in recent studies, the need to understand
satisfaction incorporating both cognitive and affective perspectives has been increased
(Bigné et al., 2003; Mano and Oliver, 1993; Oliver, 1993; Oliver et al., 1997; Westbrook
and Oliver, 1991; Wirtz and Bateson, 1999; Wirtz et al., 2000). Therefore, this study is
meaningful to support satisfaction as an important antecedent, not only of cognitive
loyalty, but of affective loyalty.
Practical Implications

Tourism and hospitality managers are facing a dynamic and competitive market

environment as customers are becoming more sophisticated. To give better service and

89

increase customer loyalty, this study provides several practical implications for tourism
and hospitality managers.

First, this study shows that managers need to understand the importance of not
only customer satisfaction but also delight in directly driving customer loyalty. Managers
have mostly focused on improving customer satisfaction to increase customer loyalty.
Now, achieving mere customer satisfaction is not enough to get customers’ attention and
gain loyalty among other competitors; the changes in the tourism and hospitality industry
demand more than customer satisfaction-style management. Therefore, being
knowledgeable about customer delight can be a valuable motivator for managers in
developing marketing strategy. They need to take steps to ensure the generation of both
customer satisfaction and delight, which can provide stronger influences in the creation
of customer loyalty.

As a good example of generating customer delight, Disney is known for having
created one of the most popular and memorable destinations in the world. They are an
expert in the tourism and hospitality industry and they worked to recreate that experience
nationally by opening retail stores some years ago. Now they are remodeling those stores
to create a whole new level of experience by spending around $1 million per store. They
are redesigning the stores from a kid’s perspective for “the best 30 minutes of a child’s
day.” For instance, Disney is creating new activities using technology such as
interactivity with film clips of a child’s own choosing, karaoke contests, and live chats
with Disney Channel stars via satellite. Through these unique customer experiences, the
customers have the opportunities to see and feel something different every time they

come into the store.

90

As an another example in the tourism and hospitality industry, and on the other
end of the cost spectrum, Doubletree hotel has created a delightful service by greeting
guests at check-in with a “sweet treat” of a complimentary, warm chocolate chip cookie.
This small touch can create delightful memories without much cost.

One of the biggest concerns about customer delight is the effect of raising the bar
of customer’s expectations about future performances, making it more difficult for
marketers to reliably create customer delight in the future (Arnold et al., 2005; Rust and
Oliver and Rust, 2000). Therefore, as a second implication of this study, managers need
to understand that the key to successfully applying deli ght-generating strategies lies in the
selective usage of the concept and in creating differentiated and personalized services so
that the competitors are not able to easily copy the delight program. As a good example
of accomplishing deli ght-generating strategies, the front-line personnel, those who are
mostly in contact with customers, can be a critical source to deliver delight effectively
through good relationships with customers. However, in today’s labor market, keeping
dedicated personnel is becoming more challenging (Keiningham and Vavra, 2001).
Furthermore, long-term relationships with customers can provide more opportunities to
exceed the customer’s expectations and “wowing” them by building emotional bonds
(Zeithaml and Bitner, 2003). In the process of developing loyal relationships, these
delighting elements can provide additional psychological benefits to the customers. For
example, in his book, “Hug Your Customers,” Mitchell (2003) suggests many examples
of the physical and psychological benefits of hugs for customers. Hence, training,

motivating, empowering, and rewarding service staff should be emphasized as a critical

91

marketing strategy to evoke delightfiil experiences for customers and ultimately to
provide a tool in the creation of customer loyalty.

Third, web-based social media such as customer blogs, review sites, and
discussion boards would allow managers to apply marketing communication strategies
and to create customer delight. Web-based social media can play a vital role, not just as a
marketing channel, but as conversational marketing by transforming customers from
content customers to content producers and building customer relationships (Knutson,
2010). Additionally, e-mail marketing can also be a powerful direct-to-customer
distribution and marketing tool which allows companies to engage customers in
personalized and mutually beneficial interactive relationships and sells the experience
more efficiently.

Fourth, this study suggests that adding the four different phases of loyalty
development to measure customer loyalty can be a good tool for managers to understand
the loyalty of customers. To increase customer loyalty, companies must know and
understand the key needs and wants that are important to their customers, recognizing
that customers are not all the same, nor are their concerns and expectations (Keiningham
and Vavra, 2001). Companies need to gather as much information as possible about the
customers; thoroughly knowing and understanding customers is essential before a
company can create delight for customers. Additionally, understanding customer’s
emotional connections with products and services can have the potential to generate a
higher level of satisfaction, delight, and ultimately, loyalty for the company. Hence, by
measuring customer satisfaction, emotions including customer delight, and the four

different phases of loyalty, managers can utilize the information to understand individual

92

customer’s preferences to offer personalized services with deep emotional experiences
and they can design, target, and apply a marketing strategy based on their satisfaction,
emotions, and different loyalty stages. As a result, the companies can be differentiated
from other competitors and attract more business over competitors.

Fifih, this study can provide important knowledge and a tool for managers to
segment customers according to their loyalty stage. Customers who are at different
phases of customer loyalty may need differentiated strategies applied to them (Knox and
Walker, 2001; McMullan and Gilmore, 2008). Specifically, the finding that affective
loyalty has greater impact on conative loyalty, in comparison to cognitive loyalty, can be
considered by marketers in the planning and implementation of loyalty programs. The
importance of customers’ positive emotions is not a new finding, but managers seem to
have been slow to apply this into practice. Emotions can be at the heart of a marketing
strategy, as these findings have shown. Therefore, managers need to understand which
products and services can drive more customers to affective loyalty. As an example, the
loyalty program is becoming a more important long-term marketing strategy for customer
loyalty because retaining existing customers costs less than acquiring a new customer.
However, most of the present loyalty programs offer points or savings as the key benefit
and managers are not aware of a customer’s emotion when they develop or implement the
loyalty program even though customers are looking for personalized loyalty rewards and
benefits. To offer the right type of rewards and benefits which can be found in specially
designed personalized loyalty programs, managers need to have enough individual
member preference information including the understanding of customers’ emotions.

Therefore, this study suggests that marketers need to develop a loyalty program not only

93

to reward loyal customers but also to effectively enhance affective loyalty, which is
strongly related to conative loyalty and action loyalty either directly or indirectly.
Limitations and Future Studies

Although this study provides several theoretical and practical implications for the
tourism and hospitality industries, there are several limitations and recommendations for
further research. First, the model presented in this study fits the sample and the data well.
To be generalized to other populations, the theoretical structure can be tested with
different samples such as types of accommodations (e. g., business hotel, bed and
breakfast), places (e.g., other states, other countries), and service industries (e.g.,
restaurant, airline, cruise).

A second limitation of this study relates to the action loyalty items in the survey.
The items in measuring action loyalty may not be accurate in the likelihood to
return/recommend to stay at this hotel. The respondents may respond inaccurately or just
guess their willingness to return/recommend to visit this hotel. Thus, future research
might need to consider measuring actual stays with the hotel studied and their
recommendation of this hotel to validate the accuracy of action loyalty.

Third, although the model fits the data reasonably well with encouraging results,
the discriminant validity of some latent variables in this study was relatively low. This
was due to the high correlations among constructs. Future study is needed to conduct
additional research on measurement scale improvement and discriminant validity,
including further investigation of the relationship between the scale and the measures of
the constructs. The scale could be also tested with another data set. Therefore, future

research might enhance the model measures by improving the discriminant validity.

94

Finally, future research could benefit from pursuing other factors, which can be
incorporated into the model. For example, socio-demographics, such as gender, might be
different for customer satisfaction, delight, and loyalty. Particularly, for hi gh-
involvement products and services, there is a significant difference in customer
satisfaction and loyalty by gender (Mittal and Kamakura, 2001). Additionally, future
research would also need to consider differentiating various customer segments (i.e.,
male vs. female) and research methodologies (i.e., online vs. paper surveys) in the
conceptual model developed in this study.

Conclusion

This study aimed to test the impact of customer satisfaction and delight on loyalty
in the context of tourism and hospitality. The findings from this study demonstrate that
cognitive and affective loyalty are directly influenced by customer satisfaction and
delight, conative loyalty is directly influenced by cognitive and affective loyalty, and
action loyalty is directly influenced by conative loyalty. The results of this study have
both theoretical and practical value in that they fill gaps in previous tourism and
hospitality research on customer satisfaction, delight, and loyalty. Furthermore, the
results suggest a new conceptualization of the loyalty dimension. This study also
provides important information on emotional factors such as customer delight and
affective loyalty which are critical concepts related to loyalty. Future research, based on
this study, should (1) replicate this study with a probabilistic survey sample, (2) validate
the accuracy of action loyalty by measuring actual future return/recommendation, (3)
improve measurement scales, and (4) extend this model by incorporating other possible

factors that may influence customer satisfaction, delight, and loyalty.

95

APPENDICES

96

Table 29. Comparison of Demographic Characteristics between On-line Survey

Appendix A

Respondents and Paper Survey Respondents

 

 

 

 

 

 

 

Group

On-line Survey Paper Survey Difference

Characteristics Respondents Respondents Tests
Frequency % Frequency %

Number of data 1 ,5 73 87
Gender Non. Sig.
Female 1,072 69% 60 70%
Male 481 31% 26 30%
Total 1,553 100% 86 100%
Ethnicity Non. Sing
Afiican American/Black 30 2% 3 4%
American Indian 5 l 3% 0 0%
Asian or Pacific Islander 1 1 1% 0 0%
European
American/Middle
East/White 1 ,246 82% 80 94%
Hispanic/Latino/Latina 12 1% 0 0%
Other 176 12% 2 2%
Total 1,526 100% 85 100%
Income Non. Sig.
Less than $25,000 52 4% 6 7%
$25,000-$34,999 83 6% 7 8%
$35,000—$49,999 161 l 1% 20 24%
$50,000-$74,999 327 22% 16 19%
$75,000-$99,999 267 18% 8 10%
$100,000-$149,999 268 18% 7 8%
$150,000-$199,999 70 5% 1 1%
$200,000 or more 33 2% 19 23%
I prefer not to respond 229 15% 0 0%
Total 1,490 100% 84 100%
Employment status .014
Employed full-time 931 67% 40 46%
Employed part-time 15 1% 9 10%
Self-employed 130 9% 8 9%
Retired 179 13% 25 29%
Unemployed 67 5% 1 1%
Other 67 5% 4 5%
Total 1,574 100% 87 100%

 

97

Table 29 (cont’d)

 

 

 

Residency:
MI
OH 1,085 69% 67 76%
CANADA 189 12% 8 9%
IN 1 10 7% 2 2%
IL 47 3% 2 2%
Other (e.g., FL, NY, PA) 47 3% 0 0%
94 6% 9 10%
Total
1,572 100% 88 100%
Average age 48 53
Average number of 3 3
people in the household Adults: 2 Adults: 2
Children: 1 Children: 1

 

98

Appendix B

Table 30. Comparison of Demographic Characteristics between Respondents and

Non-Respondents

 

 

 

 

 

 

Characteristics Respondents Non-Respondents
Frequency % Frequency %
Number of data 1,660 31% 3,731 69%
Residency:
MI 1,137 70% 2,537 68%
OH 200 12% 410 11%
CANADA 102 6% 262 7%
IN 51 3% 149 4%
IL 51 3% 1 12 3%
Other (e. g., FL, NY, PA) 94 6% 260 7%
Total 1,635 100% 3,731 100%
Loyalty membership holder 815 50% 970 26%
Average money spent during the
stay at the resort $264 $259
Average number of people in the 3 3
household Adults: 2 Adults: 2
Children: 1 Children: 1

 

99

Appendix C

A Survey Questionnaire

Bavarian Inn Lodge Guest Survey

  
   
    
  

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Thank you for accepting our invitation to participate in this important research.
We are surveying recent overnight hotel guests.

 

This first section asks about your recent visit to the Bavarian Inn Lodge and
Frankenmuth.

1. On this recent stay, did you consider staying at any other hotel, motel, bed & breakfast, or
campggound in the Frankenmuth area other than Bavarian Inn Lodge? Please select one.

El Yes (If yes, which one(s)?) El No
2. On this recent stay, did you consider staying at any other destination other than F ' “
for this vacation? Please select one.

Cl Yes (If yes, which one(s)?) El No

3. Are you currently a member of the Bavarian Inn Lodge loyalty progzam called the
“Bavarian Inn Perks Club”? Please select one.

1] Yes D No, I have never been a member
El Not sure El No, but I was a member in the past

100

4. Are you currently a member of any other hotel. motel, bed & breakfast, or campground loyalty
progzam that you could have used in the F rankenmuth area? Please select one.

[1 Yes D No, I have never been a member

I] Not sure El No, but I was a member in the past

 

 

This second section asks about your planning, decision making, and hotel choice.

 

 

5. What was the primag pumose of your recent stay at the Bavarian Inn Lodge? Please select one.
C] Business Cl Group/ Bus tour [I Leisure

6. How did you make a hotel choice or reservation for your recent stay at the Bavarian Inn
Lodge? Please select one.
D Self-arranged (continue to #7) l] Pre-arranged by others (skip to #9)

7. Please indicate the importance of the followirLgyaspects of the Bavarian Inn Lodge when you
selected this hotel for your recent stay. Please select one for each item.

 

 

Very Very
Unimportant Neutral Important
Friendliness of staff 1 2 3 5 6 7
Hotel amenities (pool, game room,
free nightly entertainment) 1 2 3 4 5 6 7
Hotel location 1 2 3 4 5 6 7
Quality of food 1 2 3 4 5 6 7
Relationships established between 1 2 3 4 5 6 7
staff and customers
Room cleanliness 1 2 3 4 5 6 7
Room comfort 1 2 3 4 5 6 7
Value for money 1 2 3 4 5 6 7

8. What influenced you to book your recent stay at the Bavarian Inn Lodge?
Please select all that apply.

[:1 AAA membership [3 Internet web site or search engine

[:1 Billboard [:1 Meeting organizer

[j Brochure [1 Newspaper/Magazine

D Bus tour [1 Previous visit

[1 Department of Transportation road sign [3 Special package rate

[:1 E-mail promotion, newsletters offer [:1 Travel agent

[3 Friend or family member recommended [3 TV/Radio

[1 Highway welcome centers [:1 Visitors Center or Chamber of
Commerce

[3 Hotel gift certificate [3 Walk-in

[:1 Hotel membership card holder [:1 Other (please, specify)

(Perks Club)

 

101

 

 

This third section asks about your experiences during your recent stay
at the Bavarian Inn Lodge.

 

 

9. Who stayed with you on your recent stay at the Bavarian Inn Lodge? Please select all that

apply.
El Alone D Family members: (please select all that
apply)
[3 Business acquaintances El Children [1 Parents
D Clubs organized group Cl Grandchildren D Siblings
[3 Friends El Grandparents El Spouse
[:1 Others (please specify) Cl Other family members

10. What leisure activities did you do during your trip which included the Bavarian Inn Lodge?
Please select all that apply.

 

[I

Attended a festival, event, or activity
Dined at a unique restaurant in the
Bavarian Inn Lodge

Dined at the Bavarian Inn restaurant on
Main Street

Dined at Zehnder’s restaurant on Main
Street

Cl

C]

Shopped in Riverplace
Shopped on Main Street Frankenmuth

Toured or drove for pleasure

Visited a historic site

[I Dined at a unique restaurant outside of I] Visited a local museum
the Bavarian Inn Lodge
[3 Explored F rankenmuth city or town [3 Visited/Shopped Farmer’s market or

Pick-your-own

[j Participated in outdoor recreation (i.e., E] Visited a local or county park (e.g.,
bike, golf, boat, swim and beach sport fields, trails)
activities, fish etc.)

[:1 Played in Bavarian Inn Lodge game [3 Went swimming in Bavarian Inn
rooms or indoor putt-putt golf Lodge’s pools or Whirlpools

[j Shopped in Birch Rm [:1 Other (please specijy)

11. If you could describe your recent stay at the Bavarian Inn Lodge by an emotion or feeling.
what would that emotion or feeling be? Please type in the blank below.

 

102

12. Please indicate the extent to which each of the following statements accurately describes aa
emotion or feeling you h’ad during your recent stay at the Bavarian Inn Lodge. Please select one
for each item.

 

 

 

I felt at some time_during my stay Strongly Strongly
at the Lodge. Disagree Neutral Agree
Delighted 1 2 3 4 5 6 7

Grateful l 2 3 4 5 6 7

Elated 1 2 3 4 5 6 7

Gleeful l 2 3 4 5 6 7

Overjoyed l 2 3 4 5 6 7

Pleased l 2 3 4 5 6 7

Positively surprised I 2 3 4 5 6 7

The Bavarian Inn Lodge had

experiences/ services which were unexpected

and they delighted me. 1 2 3 4 5 6 7

 

 

This fourth section asks about your satisfaction with your recent stay at the Bavarian Inn
Lodge and future planning with the Lodje.

 

 

13. Please indicate the extent to which each of the following aspects accurately describes your
satisfaction with your recent stay at the Bavarian Inn Lodge. Please select one for each item.

 

 

Didn’t
Very Very apply to
Unsatisfied Neutral Satisfied my stay
Friendliness of staff 1 2 3 4 5 6 7 [3
Hotel amenities ool, ame
room, free nightly) enteftainment) 1 2 3 4 5 6 7 D
Hotel location 1 2 3 4 5 6 7 [1
Quality of food 1 2 3 4 5 6 7 El
R l i n i li
b... 1 2 a 4 s . 7 a
Room cleanliness 1 2 3 4 5 6 7 El
Room comfort 1 2 3 4 5 6 7 [:1
Value for money 1 2 3 4 5 6 7 E]

14. Please indicate the extent to which each of the following statements accurately describes your
overall satisfaction with your recent stay at the Bavarian Inn Lodge. Please select one for each
item.

 

 

 

Strongly Strongly
Overall, Bavarian Inn Lodge was . Disagree Neutral Agree
Comfortable l 2 3 4 5 6 7
Pleasing l 2 3 4 5 6 7
Satisfying to me 1 2 3 4 5 6 7
Overall, I was content at the Lodge. 1 2 3 4 5 6 7

103

15. Please indicate the extent to which each of the following statements accurately describes your
thoughts about the Bavarian Inn Lodge. Please select one for each item.

 

 

 

 

 

Strongly Strongly
Disagree Neutral Agree
I believe the Lodge provides more benefits 1 2 3 4 5 6 7
than other hotels of its type.
I made the right chorce of hotel With the 1 2 3 4 5 6 7
Lodge.
The Lodge’s farcilities are visually more
appealing compared to other hotels of its 1 2 3 4 5 6 7
type.

The Lodge has better value for my money
compared to other hotel’s prices of its type.
The Lodge provides me superior service 1 2 3 4 5 6 7
gualigy compared to other hotels of its type.

16. Please indicate the extent to which each of the following statements accurately describes your
emotion or feeling with the Bavarian Inn Lodge compare to other hotels of its type. Please select
one for each item.

 

 

 

 

Strongly Strongly
Disagree Neutral Agree
I feel happy when I stay at the Lodge. 1 2 3 4 5 6 7
I feel gateful to the Lodge. 1 2 3 4 5 6 7
I 11.3 the Lodge more than other hotels 1 2 3 4 5 6 7
of rts type.
I love staying at the Lodge. 1 2 3 4 5 6 7
Staying in the Lodge says a lot about
who I am. 1 2 3 4 5 6 7

17. Please indicate the likelihood to return to stay at the Bavarian Inn Lodge?
Please select one for each item.

 

Extremely Quite
I will return to the Lodge in . Unlikely Neutral Likely
the next 6 months or less 1 2 3 4 5 6 7
the next 7-12 months 1 2 3 4 5 6 7
the next year (more than 12 months from now) 1 2 3 4 5 6 7

18. Please indicate the seasonal likelihood to return to stay at the Bavarian Inn Lodge?
Please select one for each item.

 

Extremely Quite
I will return to the Lodge in . Unlikely Neutral Likely
Spring (March, April, May) 1 2 3 4 5 6 7
Summer (June, July, August) 1 2 3 4 5 6 7
Fall (September, October, November) 1 2 3 4 5 6 7
Winter (December, January, February) 1 2 3 4 5 6 7

104

19. Please indicate the likelihood to recommend the Bavarian Inn Lodge to others. Please select
one.

 

Extremely Quite
Unlikely Neutral Likely
I will recommend the Lodge to others. 1 2 3 4 5 6 7

20. Please indicate the extent to which each of the following statements accurately describes your
intention toward staying at the Bavarian Inn Lodge. Please select one for each item.

 

 

 

 

 

 

 

Strongly Strongly
Disagree Neutral Agree
. .
I consrder myself to be highly loyal to 1 2 3 4 5 6 7
the Lodge.
I intend to continue staflng at the 1 2 3 4 5 6 7
Lodge.
I would change hotels if another hotel’s
staff was more friendly. 1 2 3 4 5 6 7
I would try an alternative hotel if it was
less expensive than the Lodge. 1 2 3 4 5 6 7
I would try an altematrve hotel if their 1 2 3 4 5 6 7

 

loyalty program offered more benefits.
I would try an altemtive hotel if the
alternative hotel offered increased 1 2 3 4 5 6 7
facilities/ services to the Lodge.

 

 

This fifth section asks about your past experience with Bavarian Inn Lodge,
Frankenmuth, and other hotels.

 

 

21. In the past three ways, how many times have you stayed at other hotels. motels, bed &
breakfasts, or campgrounds in the Frankenmuth area? Please select one.

El 0 times (skip to #26) El 4-6 times II] 10-12 times

C] 1-3 times [3 7-9 times Cl More than 12 times

 

 

22. Approximately, what was the month and year of your last gay before this recent stay in the
mnkenmuth area? Please type in the month and year below.
Month Year

 

 

23. In the past three years excluding this recent stay, how many times have you stayed at the
Bavarian Inn Lodge? Please select one.

El 0 times (skip to #26) El 4-6 times El 10-12 times

[:1 1-3 times El 7-9 times [3 More than 12 times

24. Approximately, what was the month and year of your last stay before this recent stay at the
Bavarian Inn Lodge during the past three years? Please type in the month and year below.
Month Year

 

 

25. In the past three years, how many times have you recommended the Bavarian Inn Lodge to
others? Please select one.

El 0 times El 4-6 times 1] 10-12 times

C] 1-3 times [1 7-9 times El More than 12 times

 

105

 

 

The final section of this survey asks for descriptive information about you and your
household. This information will be held in the strictest confidence and will only be used
for statistic purposes.

 

 

26. Are you? Please select a response. El Male [3 Female

27. In which year were you born? Please type a number.
My birth year

 

28. In which US. state or foreign country is your primary residence located? Please type it.
Location of primary residence

 

29. What is the postal code of your primary residence? Please type the numbers.
Postal code
30. How many children and adults live in your household including yourself? Please type a whole
number in each field below. Enter “0” if none.
Total number of people in your household (including yourself)
Number of children (18 years or younger)
Number of adults (19 years or older, including yourself)

 

31. Which one of the following best describes your ethnicity or race? Please select one.

C] African American/ Black El European American/ Middle East/White
E] American Indian El Hispanic/ Latino/ Latina
El Asian or Pacific Islander [3 Other (please specijy)

 

32. Which employment status best describes you at the time you visited Bavarian Inn Lodge?
Please select one.

[I] Employed full-time D Retired l3 Unemployed

El Employed part-time Cl Self-employed El Other (please specify)

33. Which income category best describes your total annual household income before aw in
2008? Please select one.

D Less than $25,000 El $50,000- $74,999 Cl $150,000-$199,999
El $25,000- $34,999 El $75,000 - $99,999 [1 $200,000 or more
Cl $35,000- $49,999 D $100,000-$149,999 El I prefer not to respond.

Thank you for completing this survey.

To enter a chance to win one grand prize of a Bavarian Inn Lodge stay, please fill out the contact
information on the drawing ticket.

Everyone who completed this survey and sends us back this survey will receive $20, $40, $5 0,
and half ofl your second chicken vouchers by email.

106

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107

 

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