Content uploaded by Kwabena G. Boakye
Author content
All content in this area was uploaded by Kwabena G. Boakye on Nov 21, 2017
Content may be subject to copyright.
www.asq.org 21
The Battle for Customer Loyalty:
An Examination of
Customer Loyalty in the
Goods and Services Domain
KWABENA G. BOAKYE, GEORGIA SOUTHERN UNIVERSITY
CHARLES BLANKSON, UNIVERSITY OF NORTH TEXAS
VICTOR R. PRYBUTOK, UNIVERSITY OF NORTH TEXAS
© 2017, ASQ
This research fills a gap in both quality management
and marketing literatures by examining how cus-
tomer co-production, experiential, and situational
variables in a nonpersonal setting influence loyalty
decisions toward products and services. Through an
empirical study, an interpersonal relationship theory
from social psychology, known as the investment
model (IM), is used to develop a better understand-
ing regarding the drivers of why customers stay loyal
with product and service firms. Self-reported data
from a sample of 221 college students who own an
automobile or live in an apartment were collected to
test the authors’ hypotheses. The results indicate that
customer satisfaction and the amount of investment
made by a customer positively influence their loyalty
toward a firm’s offering, while the quality avail-
ability of attractive alternatives negatively impacts
loyalty toward the firm’s offering. Furthermore, the
authors’ interpretation of the IM suggests that cus-
tomer satisfaction increases a customer’s loyalty
much more in a service offering compared with a
product offering. The authors, however, did not find
in their service/product offering comparison any dif-
ference between investment size, quality of attractive
alternatives, and loyalty. These findings provide a
much better insight in assessing the applicability of IM
in nonpersonal settings, providing information that
can help managers invest in resources that trigger
customer engagement and enhance loyalty levels.
Key words: customer experience, customer loyalty,
investment model, regression analysis, relationship
marketing
INTRODUCTION
Customer loyalty has and continues to garner increas-
ing attention from scholars and practitioners because
it occupies a central place in quality management and
service marketing (Evans 2015; Boakye et al. 2012;
Toufaily, Ricard, and Perrien 2013). Achieving cus-
tomer loyalty increasingly seems to require tailored
solutions that even top firms struggle to surmount
in determining the best actions to pursue (Snipes,
Loughman, and Fleck 2010; Wong and Sohal 2003).
To the firm, the financial impact of losing a customer
is colossal. For example, Accenture projects the cost of
winning back a customer after defection to be 50 to
100times the cost of retaining that customer.
Prior studies on customer loyalty have focused on
customers using cognitive judgment on product or ser-
vice attributes to make an informed decision to stay
loyal to a firm’s product or service (Panchapakesan, Sai,
and Rajendran 2015; Morgan and Hunt 1994). Though
these traditional models have long explained and pre-
dicted customer loyalty and behavior, there are recent
calls in the quality management and service marketing
literatures for firms to shift toward both co-production
and co-creation experience models where customers are
co-producers (Ebrahim et al. 2016; Pine and Gilmore
1998). Co-production results in value co-creation expe-
rience models where customers become genuinely,
creatively, and emotionally engaged in the shared pro-
duction of related goods and services (Vargo and Lusch
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
22 QMJ VOL. 24, NO. 4/© 2017, ASQ
In this study, the authors use two highly competi-
tive product sectors in the United States: automobile
ownership and apartment rentals. The U.S. automobile
industry contributes $500 billion to the economy and,
together with the automobile parts industry, the total
employment impact was more than 3.62 million jobs in
2012 (The Automotive Industry 2015; Hill et al. 2015).
At the same time, the U.S. apartment rental industry has
a 4.9 percent annual growth rate worth $165 billion,
employing 931,535 people in May 2015 and contribut-
ing $1.3 trillion to the U.S. economy (Apartment Rental
2015; Washington Multi-Family Housing Association
2015). The next section of the paper discusses the
theoretical background and research hypotheses. The
research methodology follows, followed by a data analy-
sis, as well as results, discussion, and conclusions. The
last section, managerial implications, is followed by
limitations and future research.
THEORETICAL BACKGROUND
AND RESEARCH HYPOTHESES
Investment Model
The IM (Rusbult 1980) is a theory in social psychology
that predicts commitment and persistence across many
types of relationships (for example, romantic relation-
ships, friendships, and relationships in organizational
settings). The model states that an individual’s com-
mitment is dependent upon the level of satisfaction
derived, the quality of attractive alternatives to the
relationship, and the investment size (that is, the mag-
nitude and importance of the resources invested in
a relationship) (Li, Browne, and Wetherbe 2006).
Basically, this theory captures both co-production and
co-creation aspects involving both parties in a relation-
ship with the aim of sustaining the relationship. This
study views dimensions of the IM as co-production
dimensions that customers engage themselves in, while
customer loyalty is viewed as the outcome value created
from the co-creation experience. Co-creation continues
to receive attention from service management and
marketing scholars (Black and Veloutsou 2017).
Concurring with the notion that the co-creation
process has to be understood and properly managed
2004). As a result, firms that provide such memorable
experiences for customers to feel engaged enhance their
competitive advantage on the market (Gentile, Spiller,
and Noci 2007) with higher profit margins and greater
market share, leading to higher loyalty returns.
Despite the pivotal role customer loyalty plays in the
quality management and service marketing strategy
formulation, findings across several studies differ (for
example, Liang and Wang 2008). The genesis of the
differences in findings may be a result of the impact
of context specificity in customer loyalty (Lewin,
Rajamma, and Paswan 2015; Aksoy 2013). Another
omission in the literature is the lack of studies com-
paring the examination of customer loyalty between a
tangible product and an intangible product (that is, a
service) in a single study (Scott, Peng, and Prybutok
2015). Examining these two contexts (service and
product) presents distinct marketing challenges for the-
ory surrounding customer loyalty and practice. These
lacunae are especially important in view of the chal-
lenges brought about by the characteristics of services.
This research seeks to contribute to the customer
loyalty literature by drawing on an interpersonal rela-
tionship theory from social psychology—the investment
model (IM) (Rusbult 1980)—in examining situa-
tional variables that customers use in their decisions to
remain loyal to a firm’s offering. The IM uses individual
experiences in a personal relationship to predict the
individual’s commitment level toward the relationships.
The use of the IM as the theoretical foundation for this
study is in line with Ketchen and Hults’ (2011) call for
the application of organization and psychology theories
to help describe, explain, and predict both organizational
management and marketing phenomena. Moreover, this
study tests the applicability of the IM in a nonpersonal
setting, particularly in two varying industries related to
tangible products and services. Thus, this paper attempts
to answer the following research questions:
1. Can the IM better identify the drivers of customer
consumption experience that enhance customer
decisions to stay loyal to firms’ products and services?
2. In view of the well-documented differences in prod-
uct and service characteristics, does a service or
product moderate the ability of the IM in predicting
loyalty among customers?
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
www.asq.org 23
loyalty as both a highly desired outcome variable for
any business and a byproduct of the customer’s rela-
tionship experience with the firm’s offering. Besides,
customer loyalty has become paramount that finding
its antecedents is a major concern for firms. To that
end, the authors’ focus is on loyalty as an attitude. In
this study, loyalty refers to the tendency to feel psy-
chologically attached to or maintain a relationship
based on the quality of the customer’s experience level
toward the product or service (Gruen, Osmonbekov,
and Czaplewski 2006). The authors further conceive
loyalty to capture the overall experience of customers as
they co-create value during the service delivery.
Numerous studies have considered loyalty from the
firm’s perspective (Meyer-Waarden 2007; McDougall
and Levesque 2000). However, this study approaches
loyalty from the customer’s perspective by affording
marketers the opportunity to view the customer not
only as a co-producer but also with the intention of
understanding the activities that customers consider as
creating value (McColl-Kennedy et al. 2017).
Customer Satisfaction
Customer satisfaction is a key driver in increasing cus-
tomer loyalty and overall business performance, and
numerous studies in the quality management and ser-
vice marketing literatures corroborate this assertion
(Evans 2015; Heskett and Sasser 2010, 19-29). It is such
an important construct that it has received examination
in several other fields of discipline including tour-
ism (Li and Petrick 2008), construction management
(Bemelmans et al. 2011), organizational behavior (Liu,
Leach, and Bernhardt 2005), e-commerce (Chen 2012),
and so forth. The authors define customer satisfaction
as an overall attitude based on the customer’s unique
co-creation experience with the product purchase or
service usage (Fornell 1992). Besides, satisfaction is a
broader feeling and a reflection of contentment affected
by quality, price, and other personal factors. Not only
does satisfaction increase customer loyalty, but it also
prevents customer churn, lowers customer price sensi-
tivity, reduces operating costs, and enhances business
reputation (Fornell 1992).
Satisfaction from previous experiences and inter-
actions with products or services has the tendency to
as a strategy to create customer value, this study adds
to the discourse on how firms motivate customers
through the co-production process to create value
(Ostrom et al. 2010).
Relationships could either be between two people
or between a person and an object or an abstraction.
For example, information technology (IT) profession-
als who have relationships with their careers (that is, a
nonpersonal setting) could decide to stay in their rela-
tionship with their career if their expectations are met
or exceeded. Though their career (which is, virtually,
the other partner) is not human, there is an underlining
personal relationship that exists between them and their
career. Likewise, this same argument is what the authors
bring to bear in this study. That is, products and services
are not humans and do not have that personal touch or
feelings that human partners give in return. However,
a customer’s use of a product or service exhibits an
underlining relationship that exists and, thus, the con-
tinuous stay in the relationship will be contingent on the
customer’s assessment of his or her expectation being
met upon use of the service or product. To that extent,
the IM provides the theoretical justification for examin-
ing ways and processes through which value co-creation
from a customer loyalty point of view is enhanced with
tangible and intangible offerings. Unlike other allied
disciplines, such as psychology and management, review
of the literature shows few studies have applied the IM in
service marketing research (Ping 1993; Liu, Leach, and
Bernhardt 2005). This study operationalizes the IM in
the automobile and apartment rental service domains
within the U.S. marketplace. Due to the wide range of
tangible products and services available, the car owner-
ship and apartment service markets offer a fertile ground
for studying the stochastic process of loyalty to firm
offerings because of the stark differences between these
offerings and the challenges facing these domains in the
U.S. marketplace (McCloud and Dwyer 2011).
Customer Loyalty
Customer loyalty, a fundamental concept in both the
relationship marketing and management literature, is
key to understanding customer decisions to remain in
relationships with a product or service (Boakye et al
2012; Morgan and Hunt 1994). The authors consider
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
24 QMJ VOL. 24, NO. 4/© 2017, ASQ
are likely to be shaped by varying product characteris-
tics and service features from a variety of information
channels. In fact, a customer’s decision to remain loyal
to a product or service is a function of how attractive
the current product or service is, relative to its alter-
natives (Rusbult and Farrell 1983). Based on these
arguments, the authors hypothesize that:
• H2: Higher levels of quality of attractive alternatives
are associated with lower levels of customer loyalty.
Investment Size
The authors conceptualize investment size as a com-
bination of resources including time, emotional
involvement, effort, self-disclosure, and money
(Rusbult 1980). This variable encapsulates the cus-
tomer’s active participation in the production of a
needed product or service. Hence, the customer is seen
as a co-producer. Obviously, as co-producers, custom-
ers become heavily connected to the purchased product
or service and are not resigned to losing or abandoning
them at any point soon. On the other hand, customers
with low investments and little to no connection or
active participation in products or services have little to
lose should they decide to discontinue use.
In B2B settings, firms make specific investments in
business relationships with other firms to strengthen
relationships and create future expectations of loyalty
to their business partners (Rauyruen and Miller 2007).
These investments reflect a longer-term partnership and
an expectation of continuity to the partner (Ebers and
Semrau 2015). In this study, a customer’s investment
in a product or service indicates active participation
and loyalty, and suggests dependence on the product or
service for future interactions. Customers who observe
unique and experiential value with products and ser-
vices increase their level of investment in these product
and service offerings, making it difficult and challeng-
ing to switch to other products or services (van Triest et
al. 2009). Such active participation depicts the customer
engagement level and loyalty behaviors.
Investment levels increase with increasing sat-
isfaction and positive experience levels. Though
investment levels increase with increasing satisfac-
tion levels, there is also a possibility customers will
influence customers’ loyalty decisions. In fact, scholars
posit that a satisfied customer is also a loyal customer
(Jeon and Choi 2012; Szymanski and Henard 2001).
Although satisfaction may not always and necessarily
be the reason customers stay loyal to a product or ser-
vice (Oliver 1999; Jones and Sasser 1995), some studies
suggest that a satisfied customer is more likely to
remain loyal than a dissatisfied customer (McDougall
and Levesque 2000; Heskett and Sasser 2010, 19-29).
Therefore, the authors hypothesize that:
• H1: Higher levels of customer satisfaction are
associated with higher levels of customer loyalty.
Quality of Attractive
Alternatives
Alternatives are referred to in the services and consumer
marketing literature by a variety of terms, includ-
ing perceived attractiveness of alternatives (Colgate
and Lang 2001), competitive price perceptions (Varki
and Colgate 2001), or competitive influences (Kumar
2002), among others. Customers view alternatives to
a product or service from an image, service quality,
and reputation standpoint, expecting these alternatives
to be excellent and superior to the competing offer-
ing. Thus, consistent with prior research, the authors
conceptualize the quality of attractive alternatives as
any arrangement that differs from the status quo.
They therefore define quality of attractive alternatives
as positive perceptions toward a competing product or
service (Richard and Zhang 2012).
Attractiveness of alternatives is intimately linked
to both product and/or service differentiation. Hence,
when product and service differentiation are dif-
ficult to match by competing firm offerings or are
nonexistent in the marketplace, customers are more
likely to remain loyal to the existing products or ser-
vices (Bendapudi and Berry 1997). Several studies have
established support for the direct but negative impact of
attractive alternatives on customer loyalty (Wu 2011;
Dagger, David, and Ng 2011). Moreover, customers, to
a larger extent, view attractive alternatives as a relative
advantage to remain loyal. As a result, customer per-
ceptions of attractive alternatives of a product or service
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
www.asq.org 25
volume of investment propels them not to switch
careers and remain committed and loyal to their cur-
rent career choice. These augments lead the authors
to state the following hypotheses:
• H3: Higher levels of customer satisfaction are asso-
ciated with higher levels of customer investment.
• H4: Higher levels of customer investment are
associated with higher levels of customer loyalty.
The type of offering (that is, product or service)
also has an impact on customer loyalty (Lewin,
Rajamm, and Paswan 2015; Wolak et al. 1998).
Products are tangible offerings that are physically
visible to the customer. In situations where cus-
tomers are not satisfied with the product—be its
features, characteristics, or usage—customers will
express dissatisfaction, leading to loyalty issues
(Osarenkhoe and Komunda 2013; Jose and
Buchanan 2013). On the other hand, when the prod-
uct provides the customer the desired satisfaction,
the customer is more likely to continue to use the
product or service. Services are intangible offer-
ings (Vargo and Lusch 2008; Sampson and Froehle
2006). However, a customer’s inability to feel,
touch, or physically see a service offering makes its
evaluation much more subtle than it would be for
tangible products (Kerin et al. 2003; Claycomb
and Martin 2001). To that end, loyalty levels
are higher in products than in services (Wolak
et al. 1998), since customers have physical
contact and interaction with the product. The
authors therefore hypothesize that type of offer-
ing (that is, product or service) will moderate
the relationship between variables of the IM
and customer loyalty (see Figure 1). Therefore:
• H5a: The type of offering positively moder-
ates the relationship between satisfaction
and customer loyalty.
• H5b: The type of offering positively moder-
ates the relationship between investment size
and customer loyalty.
• H5c: The type of offering negatively mod-
erates the relationship between quality of
attractive alternatives and customer loyalty.
continue to invest and remain loyal despite witness-
ing and encountering unpleasant product or service
experiences. In their study, Boles, Barksdale, and
Johnson (1997) posit that a patient shares some
significant investment when he or she reveals per-
sonal medical information to a physician as well as
spending time and money for treatment. The fact
that the patient has shared or continues to share his
or her personal health information with a physician
is an indication that the patient is investing in a
relationship with the physician because the current
treatment offered by the physician is either meeting
or exceeding their expectations. It is important to
note that good rapport, health progress, time, and
energy spent in adhering to the physician’s advice
will be lost should the patient decide to switch to
another physician.
Switching to a different physician will amount to
loss of investment in one’s health progress and years
of attachment with a physician. To prevent this loss
of many years of investment, the patient continues
to engage the physician for health services. Because
the specialized skills and competencies, which they
made significant investments to acquire, are only
applicable to their specific industry, the thought
of switching careers and subsequently losing that
Figure 1 Conceptual framework
Type of offering
(product/service)
Customer
satisfaction
Investment
size
Quality of
attractive
alternatives
Customer
loyalty
H1
H3
H4
H5a
H5b
H5c
H2
©2017, ASQ
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
26 QMJ VOL. 24, NO. 4/© 2017, ASQ
university in the southwestern part of the United States.
Although there is some concern about the use of college
students as surrogate customers and the validity and
generalizability of college student samples, students
are deemed appropriate for this study. As Mook (1983)
states, “representativeness of sample is of vital impor-
tance for certain purposes, such as survey research. For
other purposes, including drawing conclusions about
theory rather than about population, representativeness
is a trivial issue.” Moreover, Peterson and Merunka
(2013) claim that despite some widespread concerns
about college student samples for theory testing, not
a single study has offered convincing empirical evi-
dence regarding the negative consequences for research
conclusions drawn from them. A follow-up in-depth dis-
cussion with two managers at two local car dealers and
two managers of apartment complexes confirmed that
the sample was generally representative of their target
audience in the marketplace.
Six hundred questionnaires were distributed to a
convenience sample of students in four classes in a
business school. Out of the six hundred questionnaires,
221 complete and valid responses were received, yield-
ing a response rate of 36.8 percent. Respondents were
asked to respond to the scale items on a seven-point
Likert-type scale, ranging from 1 (strongly disagree)
to 7 (strongly agree). The first page of the question-
naire listed the contextualized IM constructs and their
items. The second page collected demographic infor-
mation. Instructors of the chosen classes awarded extra
credit for students’ participation. While 110 students
successfully completed the car survey, 111 students
completed the apartment renting survey, giving a total
of 221usable responses.
ANALYTICAL RESULTS
As shown in Table 1, males constitute a major com-
ponent of the sample for both apartment rentals
(55percent) and cars (54.5 percent). The dominant age
group in both study settings is the 18 to 25 age group
(that is, 73.9 percent in apartment rental and 72.7 per-
cent in car). This is followed by an equal representation
(21.6 percent for apartment rental and 21.8 percent for
car) in the 26 to 32 age group. Further, Table 1 reveals
METHODOLOGY
Research Design
and Measurement
A survey methodology was used to test the proposed
hypotheses. To appreciate the study and develop a better
understanding of the research context, two pilot tests
were conducted. The first pilot study involved a covert
observation technique at two automobile dealerships
and two apartment complexes in the Dallas-Fort Worth
(DFW) area of Texas. The authors complemented the
covert observation by engaging in unstructured face-to-
face interviews with four car sales managers and four
apartment managers in the DFW area. The manag-
ers discussed the target audiences, offerings’ attributes,
promotions and sales-inducing activities, and customer
service. In the second pilot study involving focus group
discussions with 45 senior class marketing students, the
authors observed that college students not only claim
to be conversant and knowledgeable about cars and
apartment rental offerings (Ahmed and Jabes 1995), but
apparently college students have also been the target of
car dealers’ and apartment complexes’ offerings and pro-
motions in recent months. Specifically, the pilot studies
were designed to ensure the appropriateness of the study
constructs in the context.
The findings from these pilot tests also allowed
for refinement of the questionnaire prior to the main
data collection. The authors measured their constructs
using multi-item scales contextualized from a variety of
extant studies (see Appendix), including: loyalty (Li and
Petrick 2008), customer satisfaction (Spreng, MacKenzie,
and Olshavsky 1996), quality of attractive alternatives
(Rusbult et al. 1998), and investment size (Iwasaki and
Havitz 2004; Jones, Mothersbaugh, and Beatty 2000). Type
of offering was coded as a dummy variable, with 1 denot-
ing a service offering and 0 denoting a product offering.
MAIN STUDY
Sample and Data Collection
In line with Seo, Yoon, and Vangelova (2016), the study
sample consisted of college students from a large public
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
www.asq.org 27
that most of the respondents were
Caucasian, followed by Hispanic,
Black/African American, and
Asian, in that order.
The authors subjected their
data to two principal component
analyses, first with the IM con-
struct and second with customer
loyalty construct. They display in
Tables 2 and 3 the rotated factor
structure, percentage of variance
explained, and the alpha scores
for each factor obtained for IM
constructs (see Table 2) and
loyalty construct (see Table 3).
Acceptable internal consistency
scores above 0.75 were achieved
for all alpha scores.
They next subjected the data to confirmatory fac-
tor analysis (CFA) using SmartPLS 3.0 to ensure
convergent validity, discriminant validity, and com-
posite reliability (Ringle, Wendle, and Becker 2014).
Examination of the constructs’ loadings, composite
reliability (CR), and average variance extracted (AVE)
ensured convergent validity, with values higher than
the thresholds of 0.5 (Hair et al. 2006), 0.7 (Nunnally
1978), and 0.5 (Fornell and Larcker 1981), respectively.
Results of item reliability and convergent validity
analyses are shown in Table 4. A comparison of inter-
construct correlations (ϕ) and the square roots of AVEs
in Table 5 confirmed discriminant validity since the
correlations were below the square roots of AVEs for the
respective constructs. All these results revealed accept-
able levels of internal consistency, and convergent
and discriminant validity. The authors next averaged
scale items for each of the constructs and used them as
observation points in three sets of multiple regression
models to test the hypothesized relationships.
Because the model contains the interaction
effects of IM variables and type of offering, a mod-
erated regression analysis is appropriate for testing
the hypotheses (Jaccard, Wan, and Turrisi 1990). A
blockwise hierarchical approach is used to assess the
R-square change of the model and to also reduce the
possible multicollinearity produced by correlations
Table 1 Demographic profile of respondents
Measure Categories Apartment Rental Car
Frequency %Frequency %
Gender Male 61 55.0% 60 54.5%
Female 50 45.1% 50 45.5%
18-25 82 73.9% 80 72.7%
Age 26-32 24 21.6% 24 21.8%
33-39 32.7% 43.6%
40 and above 21.8% 21.9%
American Indian 21.8% 32.7%
Asian 76.3% 98.1%
Race Black/African American 16 14.4% 18 16.4%
Hispanic 24 21.6% 24 21.8%
Mixed Race 32.7% 21.9%
Caucasian 59 53.1% 54 49.1%
Total 111 100% 110 100%
Table 2 Rotated factor structure: Investment
model
Construct label Items 123
Satisfaction SAT1 0.893
SAT4 0.865
SAT3 0.807
SAT2 0.778
SAT5 0.746
Investment size IS2 0.841
IS1 0.841
IS3 0.715
IS4 0.644
Attractive
alternatives
QAA1 0.923
QAA2 0.906
QAA3 0.593
% of variance explained
(Total = 69.51%) 29.87 22.03 17.61
Cronbach’s Alpha 0.90 0.76 0.80
Table 3 Rotated factor structure: Investment
model
Construct label Items 1
Customer loyalty CL5 0.872
CL3 0.864
CL1 0.839
CL2 0.832
CL4 0.621
% of variance explained (Total = 65.77) 65.77
Cronbach’s Alpha 0.86
©2017, ASQ©2017, ASQ©2017, ASQ
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
28 QMJ VOL. 24, NO. 4/© 2017, ASQ
alternatives (β = −0.09; p<0.01) displayed a sig-
nificant negative effect. Hence, hypotheses H1, H2, and
H4 are supported. Regarding hypothesis3, the authors
regressed investment size (that is, dependent variable)
on customer satisfaction (that is, independent variable)
and found the satisfaction to have a positive and signifi-
cant effect (β = −0.50; p < 0.01). Moreover, customer
satisfaction accounted for about 25.3 percent of the vari-
ance in investment size. Based on this result, the authors
confirm support for H3. The addition of the interaction
terms in model 3 also increased the R-square value
significantly relative to model 2 (∆R2 = 0.01, p<0.01).
However, the authors found a significant moderating
impact of type of offering on the relationship between
satisfaction and customer loyalty (β=−0.11; p<0.05)
but not for investment size (β=0.04; p> 0.10) and
quality of attractive alternatives (β = −0.04; p > 0.10).
Thus, H5a is supported but not H5b and H5c.
To further facilitate these interpretations, the authors
plot the low- and high-level effects of the three IM
dimensions (that is, satisfaction, investment size, and
quality of attractive alternatives) on customer loyalty for
the moderating variable, type of offering (product or ser-
vice). Regarding the interplay of satisfaction and type of
offering, the results, as shown in Table 6, are in line with
the authors’ prediction that it would increase the level
of customer loyalty. Figure2a suggests that the effect of
customer satisfaction on loyalty is stronger for customers
with regard to services than products. Though customer
loyalty is higher in products than it is in services at low
satisfaction levels, the rate of change in loyalty sig-
nificantly increases for services than for products. As a
result, at high levels of satisfaction, customers attach
higher loyalty levels to services than
they attach to products. However,
this is not the case for customers
when it comes to investment size
and quality of attractive alterna-
tives. At lower levels of investment
(see Figure 2b) loyalty levels are
higher in products than they are
in services. Though loyalty levels
increase at high investments, the
rate of increase is not statistically
significant for either products or
among interaction terms (Zhou et al. 2007). Model 1
includes only the control variables. Model 2 adds the
three dimensions of IM and the moderating dummy
variable. Model 3 features all the interaction terms.
Moreover, the authors also checked the variance infla-
tion factors (VIF) associated with each regression
coefficient and found that the largest VIF was 2.91, so
multicollinearity was not a concern.
As shown in Table 6, model 1 shows the control
variables, with gender having a positive effect (β=0.88;
p < 0.01) on customer loyalty. In model 2, the main
effects and the moderator showed statistical significance
at the 0.01 level. While both satisfaction (β = 0.19;
p<.01) and investment size (β = 0.12; p < 0.01) had a
significant positive effect on customer loyalty, attractive
Table 4 Item reliability and convergent validity
Construct Items Loadings AVE CR
Customer satisfaction SAT1 0.894 0.717 0.926
SAT4 0.803
SAT3 0.866
SAT2 0.898
SAT5 0.763
Investment size IS1 0.822 0.605 0.857
IS2 0.830
IS3 0.580
IS4 0.851
Attractive
alternatives
QAA1 0.950 0.686 0.859
QAA2 0.953
QAA3 0.520
Customer loyalty CL1 0.857 0.655 0.903
CL2 0.863
CL3 0.863
CL4 0.575
CL5 0.849
Table 5 Evidence of discriminant validity
Constructs
Quality of
attractive
alternatives
Investment
size
Customer
satisfaction
Customer
loyalty
Quality of attractive
alternatives 0.829
Investment size −0.153 0.778
Customer satisfaction −0.181 0.488 0.846
Customer loyalty −0.446 0.532 0.521 0.809
Bolded diagonal elements are √AVE and the off-diagonal elements are
ϕ
estimates.
©2017, ASQ
©2017, ASQ
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
www.asq.org 29
loyal and committed customers. Unfortunately, the
examination of the differences in customer loyalty for
products and services is still an under-researched area
(Bruhn and Grund 2000).
This study relies on IM to determine situational vari-
ables that customers use in their decision-making process
to stay loyal to a firm’s offering. In doing so, this study tests
the applicability of the IM in a nonpersonal setting, partic-
ularly in two varying domains related to tangible products
and services. The IM theory captures both co-production
and co-creation variables that are needed to provide a
sustainable relationship for customers to remain loyal with
a firm’s offering. This study views these dimensions of the
IM as co- production dimensions that provide customers
that needed sense of engagement and customer loyalty as
the byproduct of the engagement experience. The authors’
findings offer insight from the customer’s perspective
involving factors that contribute to customer willingness
and desire to stay loyal to products or services. The positive
and significant effect of customer satisfaction on customer
loyalty corroborates prior research on this subject (Evans
2015; Heskett and Sasser 2010, 19-29). In fact, in their
services. Hence, the type of offering does not moderate the
relationship between investment size and customer loy-
alty. In Figure2c, the authors also show how customer
loyalty levels decrease for both products and services
when customers are faced with highly attractive alterna-
tives. It is interesting to note that, although loyalty levels
are lower for services than for products in high levels of
attractive alternatives, this difference in loyalty levels is
not statistically significantly different. Thus, the authors
conclude that the type of offering does not moderate the
relationship between quality of attractive alternatives and
customer loyalty.
DISCUSSION
That customer loyalty continues to receive growing
interest from quality management, operations, and
marketing scholars and practitioners (Evans 2015;
Toufaily, Ricard, and Perrien 2013; Boakye et al. 2012)
cannot be overemphasized. Firms are keen to align
their market and service operations with customer
demand-driven products and services in return for
Table 6 Results of hierarchical regression analysis for loyalty
as a function of investment model variables
Dependent Variable = Customer loyalty
Model 1 Model 2 Model 3
Std.
β
t-value Std.
β
t-value Std.
β
t-value
Control variables
Age 0.02 0.60 −0.01 −0.18 0.00 0.17
Gender 0.88** 27.60 0.67** 17.37 0.67** 17.60
Main effects
Offering (1=service, 0=product) −0.15** −4.10 −0.15** −4.22
Satisfaction 0.19** 5.80 0.11* 2.54
Attractive alternatives −0.09** −3.18 −0.50 −1.46
Investment size 0.12** 3.53 0.08* 2.05
Interaction effects
Satisfaction X Offering 0.11* 2.38
Attractive alternatives X Offering −0.04 −1.15
Investment size X Offering 0.04 0.87
F381.41** 195.44** 138.82**
R20.78 0.84 0.86**
∆R20.07** 0.01**
Std. error of est. 0.47 0.40 0.38
** p < 0.01; * p < 0.05
©2017, ASQ
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
30 QMJ VOL. 24, NO. 4/© 2017, ASQ
satisfaction to be positively related to loyalty of website use
and career, respectively. Satisfaction in relationship build-
ing is a harbinger for loyalty. Likewise, customers tend to
evaluate their satisfaction and experiences before making
an informed decision to either remain loyal or disloyal.
Worthy of note is that loyalty levels tend to increase any
time satisfaction levels increase, irrespective of the type of
offering (product and/or service). However, it is interesting
to note that the rate of loyalty levels increase for services
is more dramatic than for products based on the authors’
study. The authors found that customers have higher levels
of loyalty with products than services at lower levels of sat-
isfaction, but not at higher levels of satisfaction. At higher
levels of satisfaction, customers attach greater loyalty levels
to a service than to a product, as seen in Figure 2a.
As expected, customers who participate actively in
co-production and consumption are likely to be loyal
customers as a result of the memorable and unique experi-
ences they enjoy from such participation and engagement.
With such satisfying memorable and pleasant experiences,
customers are motivated to invest their resources (that is,
effort, time, money, and so on), thereby increasing their
level of investment. Further, when customers increase their
level of investment it is an indication of their satisfaction
with the offering, leading to a sense of attachment or
loyalty toward that particular offering. The results provide
such evidence, supporting the positive association between
investment size and customer loyalty to the type of offer-
ing. However, the authors did not find any difference in
the investment-loyalty relationship (see Figure 2b) for
either a product or a service. Though one would expect this
relationship to be more positive and significantly different
for products than for services, largely due to a product’s
physical attributes (such as quality performance, design,
reliability, and so on), which are tangible, the authors did
not find type of offering to influence this investment-loyalty
relationship in any shape or form.
The moderating effect of type of offering on the rela-
tionship between quality of attractive alternatives and
customer loyalty was significant. This result indicates the
ability of type of offering to strengthen the association
between quality of attractive alternatives and customer
loyalty. The finding implies that as quality of attrac-
tive alternatives increases (that is, when customers are
exposed to more alternatives of the offering), service
career commitment of IT professions study, they found
commitment to be primarily determined by satisfaction.
Their findings give further support to that assertion rela-
tive to the other dimensions in model 2. Moreover, the
result is not surprising, since Li and Petrick (2008) found
Figure 2 Customer loyalty and type of offering
interactions
Customer loyalty
0.8
0.6
0.4
0.2
0
−0.2
−0.4
−0.6
−0.8
−1
Low
Satisfaction
High
Product
Services
Customer loyalty
0.8
0.6
0.4
0.2
0
−0.2
−0.4
−0.6
−0.8
−1
Low
Investment
High
Product
Services
Customer loyalty
0.8
0.6
0.4
0.2
0
−0.2
−0.4
−0.6
−0.8
−1
Low
Attractive alternatives
High
Product
Services
Figure 2a
Figure 2b
Figure 2c
©2017, ASQ ©2017, ASQ ©2017, ASQ
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
www.asq.org 31
offering is based on customer experience and level of
engagement, management should endeavor to adapt
and provide quality product and service offerings and
features that will create a memorable and pleasant expe-
rience for consumers. Thus, for firms to build stronger
relationships with customers, product and service man-
agers should develop and implement experience-related
strategies that motivate customers to engage in a co-
productive experience for the co-creation of value.
Management should also work to have fewer prod-
uct returns, warranty repairs, and service recoveries,
since positive word-of-mouth from loyal customers
impacts referrals and makes new customer acquisi-
tion manageable. In addition, management must also
pay particular attention to feedback that is initiated
by loyal customers to make improvements in products
and services delivery, with the view of retaining loyal
customers and attracting new customers.
Although the authors relied on the literature and
obtained input from experts, this study has several
limitations. The first key limitation of this study is its
cross-sectional approach. Future longitudinal research
may be necessary to provide additional insights into dif-
ferent factors that capture other customer perspectives
for loyalty not captured in this study. Second, the focus
of the study allowed the authors to target a relatively
homogenous subpopulation of customers
—
college
students
—
limiting the generalizability of the authors’
results. Notwithstanding this limitation, college students
reflect a potential pool of future executives and salaried
customers (Peterson and Merunka 2013; Ahmed and
Jabes 1995) who have experience in the context in which
they were sampled. Still, to enhance generalization,
future researchers should engage other subpopulations
and the general public, and from different contexts.
Third, this research focused only on customers’ desire to
remain loyal in two nonpersonal settings. Future stud-
ies are needed to explore the linkages between variables
of the IM and customer loyalty across other nonper-
sonal settings to make it more generalizable. Fourth,
the research methodology relied heavily on self-reported
data. This may introduce common method variance
and instances of bias due to self-selection. To offer a
more comprehensive explanation of results, future stud-
ies should include qualitative interviews to explain how
customers approach loyalty decisions.
offerings tend to have lower loyalty levels than product
offerings, as illustrated in Figure2c. This result is not
surprising, since today’s market is dominated by services
(Vargo and Lusch 2004). The latter has been the catalyst
to the case whereby many firms offer similar services to
customers thereby giving customers a reason to switch
to other competing firms that offer better services in
satisfaction of their needs. This means managers must
provide service offerings that meet, delight, and awe cus-
tomers for customers to remain loyal.
CONCLUSION, LIMITATION,
AND FUTURE RESEARCH
The contemporary business environment is becoming
increasingly competitive, and customer loyalty is a key
requirement for firms seeking to compete and win in
such a setting. The authors’ study complements cus-
tomer loyalty research on components of the IM in
a nonpersonal setting. The results of this study have
implications for firms at large (both products and ser-
vices). Results show that customer satisfaction, attractive
alternatives, and investment size as situational variables
affect customers’ evaluations in making informed deci-
sions to remain loyal toward firms’ offerings. These
findings suggest customers assess their relationship expe-
riences and their engagement levels with the selling firm
to exhibit loyalty behaviors. However, the authors cau-
tion against generalizing their results to all services and
products, because this study only used a single indus-
try in both the product and service segments. Future
research should be conducted with a number of ser-
vice and product segments to ascertain the presence or
absence of the hypothesized relationships in the applica-
tion of the IM in a nonpersonal setting.
Moreover, the authors show how the dimensions of
this IM theory relates to or changes with customer loyalty
levels depending on a product or service offering. This
is important because such information helps managers
invest in resources that trigger customer engagement
and enhance loyalty levels. In addition, results from
this research show that a firm’s offering (product or
service) has a moderating effect on the relationship
between investment size and quality of attractive alterna-
tives on customer loyalty. Since loyalty toward a firm’s
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
32 QMJ VOL. 24, NO. 4/© 2017, ASQ
Evans, J. R. 2015. Modern analytics and the future of quality
and performance excellence. Quality Management Journal 22,
no.4:6-17.
Fornell, C., and D. F. Larcker. 1981. Evaluating structural equa-
tion models with unobservable variables and measurement error.
Journal of Marketing Research 18, no. 1:39-50.
Fornell, C. 1992. A national customer satisfaction barometer: The
Swedish experience. Journal of Marketing 56, no. 1:6-21.
Gentile, C., N. Spiller, and G. Noci. 2007. How to sustain the
customer experience: An overview of experience components
that co-create value with the customer. European Management
Journal 25, no. 5:395-410.
Gruen, T. W., T. Osmonbekov, and A. J. Czaplewski. 2006.
eWOM: The impact of customer-to-customer online know-how
exchange on customer value and loyalty. Journal of Business
Research 59, no. 4:449-456.
Hair, J. F., W. C. Black, B. J. Babin, R. E. Anderson, and R. L.
Tatham. 2006. Multivariate Data Analysis. Englewood Cliffs, NJ:
Prentice Hall.
Heskett, J. L., and W. E. Sasser Jr. 2010. Handbook of Service
Science, Part 1, The service profit chain: From satisfaction to own-
ership, P. P. Maglio, C. A. Kieliszewski, and J. S. Spohrer, eds.
New York, NY: Springer.
Hill, K., D. Maranger Menk, J. Cregger, and M. Schultz, 2015.
Contribution of the automotive industry to the economies of all
fifty states and the United States. Center for Automotive Research.
Available at: http://www.cargroup.org/?module=Newsandevent
=ViewandnewsID=113.
Iwasaki, Y., and M. E. Havitz. 2004. Examining relationships
between leisure involvement, psychological commitment and loyalty
to a recreation agency. Journal of Leisure Research 36, no. 1:45-72.
Jaccard, J., C. K. Wan, and R. Turrisi. 1990. The detection and
interpretation of interaction effects between continuous variables
in multiple regression. Multivariate Behavioral Research 25,
no.4:467-478.
Jeon, H., and B. Choi. 2012. The relationship between employee
satisfaction and customer satisfaction. Journal of Services
Marketing 26, no. 5:332-341.
Jones, T., and W. E. Sasser Jr. 1995. Why satisfied customers
defect. Harvard Business Review, no. 73:88-99.
Jones, M. A., D. L. Mothersbaugh, and S. E. Beatty. 2000.
Switching barriers and repurchase intentions in services. Journal
of Retailing 76, no. 2:259-274.
Jose, S., and F. Robert Buchanan. 2013. Marketing at the bottom
of the pyramid: Service quality sensitivity of captive microfinance
borrowers. Journal of Consumer Marketing 30, no. 7:573-582.
Kerin, R., E. N. Berkowitz, S. Hartley, and W. Rudelius. 2003.
Marketing, seventh edition. New York, NY: McGraw-Hill.
Ketchen, D. J., and G. T. M. Hult. 2011. Marketing and organi-
zation theory: Opportunities for synergy. Journal of the Academy
of Marketing Science 39, no. 4:481-483.
Kumar, P. 2002. The impact of performance, cost, and com-
petitive considerations on the relationship between satisfaction
and repurchase intent in business markets. Journal of Service
Research 5, no. 1:55-68.
Lewin, J., R. K. Rajamma, and A. K. Paswan. 2015. Customer
loyalty in entertainment venues: The reality TV genre. Journal of
Business Research 68, no. 3:616-622.
ACKNOWLEDGMENTS
The authors are grateful to the anonymous reviewers and the editor
for their valuable feedback to strengthen the paper. The lead author
wishes to acknowledge funding from the College of Business Admin-
istration at Georgia Southern University in support of this project.
REFERENCES
Ahmed, S. A., and J. Jabes. 1995. Job values of French speak-
ing business students in France and Canada: An overtime
study. International Journal of Commerce and Management 5,
no.1/2:109-129.
Aksoy, L. 2013. How do you measure what you can’t define? The
current state of loyalty measurement and management. Journal of
Service Management 24, no. 4:356-381.
Apartment rental in the U.S.: Market research report. 2015.
Available at: http://www.ibisworld.com/industry/default.
aspx?indid=1349.
Bemelmans, J., H. Voordijk, B. Vos, and J. Buter. 2011.
Assessing buyer-supplier relationship management: Multiple
case-study in the Dutch construction industry. Journal of
Construction Engineering and Management 138, no. 1:163-176.
Bendapudi, N., and L. L. Berry. 1997. Customers’ motivations
for maintaining relationships with service providers. Journal of
Retailing 73, no. 1:15-37.
Black, I., and C. Veloutsou. 2017. Working consumers:
Co-creation of brand identity, consumer identity, and brand com-
munity identity. Journal of Business Research 70:416-429.
Boakye, K. G., J. Kwon, C. Blankson, and V. R. Prybutok. 2012.
The attraction of the sizzle: A service investment model. Quality
Management Journal 19, no. 4:24-38.
Boles, J. S., H. C. Barksdale, and J. T. Johnson. 1997. Business
relationships: An examination of the effects of buyer-salesperson
relationships on customer retention and willingness to refer and
recommend. Journal of Business and Industrial Marketing 12,
no.3/4:253-264.
Bruhn, M., and M. A. Grund. 2000. Theory, development and
implementation of national customer satisfaction indices: The
Swiss Index of Customer Satisfaction (SWICS). Total Quality
Management 11, no. 7:1017-1028.
Chen, S. C. 2012. The customer satisfaction–loyalty relation in an
interactive e-service setting: The mediators. Journal of Retailing
and Consumer Services 19, no. 2:202-210.
Claycomb, C., and C. L. Martin. 2001. Building customer rela-
tionships: An inventory of service providers’ objectives and
practices. Marketing Intelligence & Planning 19, no. 6:385-399.
Colgate, M., and B. Lang. 2001. Switching barriers in consumer
markets: An investigation of the financial services industry.
Journal of Consumer Marketing 18, no. 4:332-347.
Dagger, T. S., M. E. David, and S. Ng. 2011. Do relationship
benefits and maintenance drive commitment and loyalty? Journal
of Services Marketing 25, no. 4:273-281.
Ebers, M., and T. Semrau. 2015. What drives the allocation
of specific investments between buyer and supplier? Journal of
Business Research 68, no. 2:415-424.
Ebrahim, R., A. Ghoneim, Z. Irani, and Y. Fan. 2016. A brand
preference and repurchase intention model: The role of consumer
experience. Journal of Marketing Management 9:1-30.
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
www.asq.org 33
Ringle, C. M., S. Wende, and J-M Becker. 2014. SmartPLS 3.0.
Hamburg: SmartPLS. Available at: http://www.smartpls.com.
Rusbult, C. E., J. M. Martz, and C. R. Agnew. 1998. The invest-
ment model scale: Measuring commitment level, satisfaction level,
quality of alternatives, and investment size. Personal Relationships
5, no. 4:357-391.
Rusbult, C. E., and D. Farrell. 1983. A longitudinal test of
the investment model: The impact on job satisfaction, job
commitment, and turnover of variations in rewards, costs, alter-
natives, and investments. Journal of Applied Psychology 68,
no.8:429-438.
Rusbult, C. E. 1980. Commitment and satisfaction in roman-
tic associations: A test of the investment model. Journal of
Experimental Social Psychology 16, no. 2:172-186.
Sampson, S. E., and C. M. Froehle. 2006. Foundations and
implications of a proposed unified services theory. Production
and Operations Management 15, no. 2:329-343.
Scott, R., X. Peng, and V. R. Prybutok. 2015. Contribution of
product and provider quality to cell phone industry quality.
Quality Management Journal 22, no. 2:33-47.
Seo, J. Y., S. Yoon, and M. Vangelova. 2016. Shopping plans,
buying motivations, and return policies: Impacts on prod-
uct returns and purchase likelihoods. Marketing Letters 27,
no.4:645-659.
Snipes, R. L., T. Loughman, and R. A. Fleck. 2010. The effects of
physicians’ feelings of empowerment and service quality percep-
tions on hospital recommendations. Quality Management Journal
17, no. 4:51-60.
Spreng, R. A., S. B. MacKenzie, and R. W. Olshavsky. 1996.
A reexamination of the determinants of customer satisfaction.
Journal of Marketing 60, no. 3:15-32.
Szymanski, D. M., and D. H. Henard. 2001. Customer satisfac-
tion: A meta-analysis of the empirical evidence. Journal of the
Academy of Marketing Science 29, no. 1:16-35.
The Automotive Industry in the United States. 2015. Available
at: http://selectusa.commerce.gov/industry-snapshots/
automotive-industry-united-states.
Toufaily, E., L. Ricard, and J. Perrien. 2013. Customer loyalty to
a commercial website: Descriptive meta-analysis of the empiri-
cal literature and proposal of an integrative model. Journal of
Business Research 66, no. 9:1436-1447.
van Triest, S., M. J. Bun, E. M. van Raaij, and M. J. Vernooij.
2009. The impact of customer-specific marketing expenses on
customer retention and customer profitability. Marketing Letters
20, no. 2:125-138.
Vargo, S. L., and R. F. Lusch. 2008. Why “service”? Journal of
the Academy of Marketing Science 36, no. 1:25-38.
Varki, S., and M. Colgate. 2001. The role of price perceptions in
an integrated model of behavioral intentions. Journal of Service
Research 3, no. 3:232-240.
Washington Multi-Family Housing Association. 2015. Apartment
industry contribution to U.S. economy. Available at: http://www.
wmfha.org/news/220775/Apartment-Industry-Contribution-to-
U.S.-Economy.htm.
Wolak, R., S. Kalafatis, and P. Harris. 1998. An investiga-
tion into four characteristics of services. Journal of Empirical
Generalizations in Marketing Science no. 2:22-42.
Liang, C. J., and W. H. Wang. 2008. Do loyal and more
involved customers reciprocate retailer’s relationship efforts?
Journal of Services Research 8, no. 1:63-90.
Li, D., G. J. Browne, and J. C. Wetherbe. 2006. Why do Internet
users stick with a specific site? A relationship perspective.
International Journal of Electronic Commerce 10, no. 4:105-141.
Li, X. R., and J. F. Petrick. 2008. Examining the antecedents of
brand loyalty from an investment model perspective. Journal of
Travel Research 47, no. 1:25-34.
Liu, A. H., M. P. Leach, and K. L. Bernhardt. 2005. Examining
customer value perceptions of organizational buyers when sourc-
ing from multiple vendors. Journal of Business Research 58,
no.5:559-568.
McCloud, L., and R. E. Dwyer. 2011. The fragile American:
Hardship and financial troubles in the 21st century. The
Sociological Quarterly 52, no. 1:13-35.
McColl-Kennedy, J. R., S. J. Hogan, L. Witell, and H. Snyder.
2017. Cocreative customer practices: Effects of health care
customer value cocreation practices on well-being. Journal of
Business Research, no. 70:55-66.
McDougall, G. H., and T. Levesque. 2000. Customer satisfaction
with services: Putting perceived value into the equation. Journal of
Services Marketing 14, no. 5:392-410.
Meyer-Waarden, L. 2007. The effects of loyalty programs on cus-
tomer lifetime duration and share of wallet. Journal of Retailing
83, no. 2:223-236.
Mook, D. G. 1983. In defense of external invalidity. American
Psychologist 38, no. 4:379-387.
Morgan, R. M., and S. D. Hunt. 1994. The commitment-trust theory
of relationship marketing. Journal of Marketing 58, no.3:20-38.
Nunnally, J. C. 1978. Psychometric theory. New York: McGraw-Hill.
Oliver, R. L. 1999. Whence consumer loyalty? Journal of
Marketing, no. 63:33-44.
Osarenkhoe, A., and M. B. Komunda. 2013. Redress for cus-
tomer dissatisfaction and its impact on customer satisfaction
and customer loyalty. Journal of Marketing Development and
Competitiveness 7, no. 2:102-114.
Ostrom, A. L., M. J. Bitner, S. W. Brown, K. A. Burkhard, M.
Goul, V. Smith-Daniels, and E. Rabinovich. 2010. Moving for-
ward and making a difference: Research priorities for the science
of service. Journal of Service Research 13, no. 1:4–36.
Panchapakesan, P., L. P. Sai, and C. Rajendran. 2015. Customer
satisfaction in Indian hospitals: Moderators and mediators.
Quality Management Journal 22, no. 1:10-29.
Peterson, R. A., and D. R. Merunka. 2013. Convenience samples
of college students and research reproducibility. Journal of
Business Research 67, no. 5:1035-1041.
Pine, B. J., and J. H. Gilmore. 1998. Welcome to the experience
economy. Harvard Business Review 76:97-105.
Ping, R. A. 1993. The effect of satisfaction and structural con-
straints on retailer exiting, voice, loyalty, opportunism, and
neglect. Journal of Retailing 69, no. 3:320-352.
Rauyruen, P., and K. E. Miller. 2007. Relationship quality as a
predictor of B2B customer loyalty. Journal of Business Research
60, no. 1:21-31.
Richard, J. E., and A. Zhang. 2012. Corporate image, loyalty,
and commitment in the consumer travel industry. Journal of
Marketing Management 28, no. 5-6:568-593.
The Battle for Customer Loyalty: An Examination of Customer Loyalty in the Goods and Services Domain
34 QMJ VOL. 24, NO. 4/© 2017, ASQ
Wu, L. 2011. Satisfaction, inertia, and customer loyalty in the
varying levels of the zone of tolerance and alternative attractive-
ness. Journal of Services Marketing 25, no. 5:310–322.
Zhou, K. Z., J. R. Brown, C. S. Dev, and S. Agarwal. 2007. The
effects of customer and competitor orientations on performance in
global markets: A contingency analysis. Journal of International
Business Studies 38, no. 2:303-319.
BIOGRAPHIES
Kwabena G. Boakye is an assistant professor in the Department
of Logistics and Supply Chain Management at Georgia Southern
University. He holds a bachelor’s degree from Kwame Nkrumah
University of Science and Technology, Ghana, a master’s degree
from the University of Idaho, and a doctorate from the University
of North Texas. Boakye is an ASQ Certified Six Sigma Black Belt
(CSSBB) and Green Belt (CSSGB). His research focuses on quality
and service operations, service experience and value-driven cus-
tomer behavior, and IT post-adoption. His works have appeared in
Operations Management Research, Quality Management Journal,
Thunderbird International Business Review, Journal of Retailing
and Consumer Services, Computers in Human Behavior, Journal of
Computer and Information Systems, International Journal of Quality
and Reliability Management, and others. He can be reached by
email at kboakye@georgiasouthern.edu.
Charles Blankson is an associate professor of marketing in the
Department of Marketing and Logistics, College of Business,
University of North Texas in Denton, TX. Blankson has a doctor-
ate from Kingston University in the United Kingdom. His research
interests include strategic marketing— positioning and brand
management, advertising, services marketing, small business
marketing, and international/multicultural marketing. He has
published in the Journal of Advertising Research, European
Journal of Marketing, Journal of Business Research, Industrial
Marketing Management, Journal of Public Policy & Marketing,
International Journal of Advertising, Psychology & Marketing,
Journal of Product and Brand Management, International Small
Business Journal, Journal of Services Marketing, and others.
Victor R. Prybutok is a Regents professor of decision sciences in
the Information Technology and Decision Sciences Department
and associate dean for graduate programs and research in the
College of Business at the University of North Texas. He received
his bachelor’s degree, two master’s degrees, and a doctorate
from Drexel University. Prybutok is an ASQ Certified Quality
Engineer (CQE), Quality Auditor (CQA), Manager of Quality/
Organizational Excellence (CMQ/OE), and an accredited pro-
fessional statistician by the American Statistical Association.
Prybutok has authored more than 160 journal articles, several
book chapters, and more than 180 conference presentations in
information systems measurement, quality control, risk assess-
ment, and applied statistics.
APPENDIX: QUESTIONNAIRE ITEMS
Customer Satisfaction (adapted from Spreng, MacKenzie, and Olshavsky 1996)
SAT1 I feel satisfied with my – (apartment/automobile)
SAT2 My (apartment/automobile) is much better than others
SAT3 My (apartment/automobile) is close to ideal
SAT4 My (apartment/automobile) makes me very happy
SAT5 My (apartment/automobile) does a good job fulfill my security needs
Quality of Attractive Alternatives (adapted from Rusbult, Martz, and Agnew 1998)
AA1: Compared to my current (apartment/automobile), other possible (apartment/automobile) alternatives are
attractive to me
AA2: Compared to my current (apartment/automobile), other possible (apartment/automobile) are close to ideal
AA3: I would do fine if I were not living/owning my current (apartment/automobile)
Investment Size (adapted from Iwasaki and Havitz 2004; Jones, Mothersbaugh, and Beatty 2000)
IS1: I have invested a great deal of money in my (apartment/automobile)
IS2: I have invested a great deal of effort in living in apartment/purchasing automobile
IS3: Many aspects of my life is linked with my (apartment/automobile)
IS4: I have invested a great deal of time in my (apartment/automobile)
Customer Loyalty (adapted from Li and Petrick 2008)
CL1: I am loyal to my (apartment/automobile)
CL2: I feel very attached to my (apartment/automobile)
CL3: I would feel upset if I were to lose my (apartment/automobile) in the near future
CL4: It is unlikely I will have a different (apartment/automobile) within the next year
CL5: I am oriented toward the long-term future of my (apartment/automobile)
CopyrightofQualityManagementJournalisthepropertyofAmericanSocietyforQuality,
Inc.anditscontentmaynotbecopiedoremailedtomultiplesitesorpostedtoalistserv
withoutthecopyrightholder'sexpresswrittenpermission.However,usersmayprint,
download,oremailarticlesforindividualuse.
