The impact of communication
channels on communication style
and information quality for hotel
CSUDH, Carson, California, USA
Cal State Pomona, Pomona, California, USA, and
California State University, Carson, California, USA
Purpose – The purpose of this study is to evaluate the impact of communication channels on
communication style and information quality as perceived by loyalty program members.
Design/methodology/approach – An online survey was utilized to collect data, and multivariate
analysis of variance was used to test the study hypothesis.
Findings – Study results indicated that the choice of a communication channel has a signicant
impact on the perceived communication style and information quality.
Research limitations/implications – The use of an online survey restricted the ability to
generalize ndings beyond those that use the internet. Replicating this study in other areas where
customers seek information outside of loyalty programs would provide valuable insight into the impact
of communication channels on communication style and perceived quality of communication.
Practical implications – Communication style and information quality have been shown to impact
customer loyalty. The results of this study indicate that the type of communication channel used
impacts style and information quality, and thereby loyalty.
Social implications – Executives should use these research ndings as a guide to how they should
structure and maintain relationships with their loyalty members.
Originality/value – This manuscript provides executives with a taxonomy of the tools and channels
available for communicating information to loyalty program members.
Keywords Customer loyalty, Perception, Loyalty programs, Information quality,
Communication channel, Communication style
Paper type Research paper
The service industry recognizes the fact that keeping their existing customers is just as
important as creating new ones, and loyalty marketing has become vital to its success
(Lam et al., 2004;Shoemaker and Lewis, 1999). Loyalty programs are popular marketing
relationship strategies developed to increase customer loyalty (Chai et al., 2015;
Shoemaker and Lewis, 1999), and have become products in and of themselves. Instead of
merely making members loyal to the end product or service, loyalty programs
The current issue and full text archive of this journal is available on Emerald Insight at:
Received 11 August 2015
Revised 2 December 2015
Accepted 2 December 2015
Journal of Hospitality and
Vol. 7 No. 1, 2016
themselves need to maintain member loyalty to survive (Namkung and Jang, 2009).
However, not all loyalty programs perform effectively (Barsky and Nash, 2006), and
many companies struggle due to unsuccessful loyalty programs (Nunes and Drèze,
2006). While there is no consensus regarding the factors that actually determine loyalty
(Agustin and Singh, 2005), Shoemaker’s Loyalty Circle (Shoemaker and Lewis, 1999)
posits that maintaining loyalty requires an equal and continuous balance of three
components: process, value and communication.
The internet has caused communication to play an increasingly important role in
the customer experience by acting as a catalyst for both company-created and
consumer-created efforts. In traditional marketing, one of the most successful
communication tools was the increased use of traditional viral marketing, more
commonly known as word-of-mouth. However, as technology and society evolved,
electronic word-of-mouth (eWOM) via social media has become an important
component of the marketing mix. Online travel forums have become an important outlet
for customers to share their experiences and advice with other travelers. This type of
communication is increasing rapidly and potentially could overshadow company-
created communication efforts (Berezan et al., 2015).
Berezan et al. (2015) found that the perceived information quality and communication
style of loyalty program members’ social networking interactions had a strong inuence
on their overall experience with the program, and emphasized the importance of
company-created and customer-created communication components in social media.
McCall and Voorhees (2010) also stressed the importance of future research on loyalty
programs to evaluate communication efforts that drive a sense of community in a
program. Online forums have the ability both to provide information and to foster a
sense of community among members by creating a social network. Although tangible
program attributes such as benets and rewards are easy to imitate,
communication-related aspects may be a way for programs to differentiate themselves
from the competition. Communication may both enhance the perceived benets and
invoke a sense of community through the quality of information and the communication
style. Therefore, for members of hotel loyalty programs, it is proposed that
communication has a signicant impact on program loyalty. (Is this needed?)
As technology advanced, different types of communication channels have been
utilized to reach out to consumers. Updated communication channels such as social
media are said to enhance a sense of community and thereby impact loyalty. Despite this
there is still a need for academic empirical research in this area (McCall and Voorhees,
2010) to examine the relationship of company-created and member-created
communication (both electronic and personal) and their dimensions (communication
style and information quality) on program loyalty. The purpose of this study is to
evaluate how company-created channels (program Web site and employees) and
member-created channels (traditional word-of-mouth and social media) impact program
members’ perceptions of communication style and information quality. Scant academic
research exists on communication style and information quality from company-created
and customer-created communication channels. Thus, this study contributes to the
literature on communication as it relates to loyalty. Further, studying these results will
assist marketers by investigating relationships between communication channels (and
dimensions of information quality and style) and antecedents of program loyalty for
hotel reward program members. The results reveal how marketers can impact program
loyalty more effectively through communication.
2. Literature review
2.1 Loyal customers and loyalty programs
Numerous studies emphasize the value of loyal customers. Petrick (2004) suggests that
loyal customers are more than just an immediate economic source; they also can act as
information channels that casually connect companies to potential customers such as
their friends, relatives and colleagues. Others suggest that loyal customers bring in new
customers through positive word-of-mouth and referrals, reducing the need for
advertising (Haywood, 1988;Kandampully, 1998;McAlexander et al., 2003;Reichheld
and Sasser, 1990;Rundle-Thiele and Mackay, 2001). In addition to making a purchase,
loyal customers express a preference for one company over others, praise the company,
say positive things about the company to others and recommend the company to others
(Zeithaml et al., 1996); potentially, the value of these actions can go far beyond purchase
behavior alone. Overall, retaining loyal customers has now become a must for success
and further, the ultimate goal for many businesses (Olsen et al., 2005).
The success of the early frequent yer loyalty programs from the airline industry
inspired a crossover into a variety of other industries, including hotels, and loyalty
programs are now one of the most popular marketing strategies to retain customers
(McCall and Voorhees, 2010). Companies implement loyalty programs to reward
valuable customers, to generate information in order to better understand and serve the
customer, to manipulate consumer behavior and to defend against the competition
(O’Malley, 1998). Ultimately, these programs pursue value-added, interactive and
long-term-focused relationships by identifying, maintaining and increasing the
purchase behavior of the best customers (Meyer-Waarden, 2008;Verhoef, 2003)
ultimately avoiding unnecessary customer migration (Bahri-Ammari and Nussair,
2015). Loyalty programs have two main goals:
(1) to increase sales revenues by increasing purchase levels; and
(2) to maintain the current customer base by strengthening the bond between the
customer and the brand.
Companies benet by achieving these goals through increased sales and lower
marketing costs (Uncles et al., 2003).
Loyalty programs in themselves are no longer necessarily differentiators for
customer satisfaction. The prevalence of loyalty programs in the hotel industry means
that companies that do not offer such expected attributes may have dissatised
customers. Therefore, regardless of the program’s effectiveness, hotel companies may
need to maintain such programs to remain competitive (Ni et al., 2011). Furthermore,
programs need to differentiate by offering attributes considered valuable to program
members and at levels that meet or exceed customer expectations (Yoo and Kitterlin,
2012). Therefore, customized communication is vital to the success of target marketing
efforts. Through carefully managed company-created communication and better
awareness of customer-created communication, loyalty programs may more effectively
achieve their ultimate goal – program member loyalty (Allen and Wilburn, 2002).
2.2 Communication channels
This study evaluated both company-created and -managed (program web site and
employees) and customer-created and user-generated (traditional word-of-mouth
and social media) communication channels. Company-managed efforts such as
program web sites, social media efforts, direct e-mail campaigns and database-
marketing efforts are the norm. These efforts may also include personalized letters,
direct mail, web site interactions, other machine-mediated interactions and e-mail,
as well as in-person interactive dialogue between a company and its customers
throughout the pre-selling, consuming and post-consuming stages (Anderson and
Narus, 1990;Ball et al., 2004).
Customer-created communications include word-of-mouth (traditional and eWOM),
customer-to-customer (C2C) know-how exchange and online forums. As with traditional
word-of-mouth, eWOM has become a vital aspect of the marketing mix. eWOM is a form
of customer-created communication and is dened as:
[…] any positive or negative statement made by potential, actual, or former customers about a
product or company, which is made available to a multitude of people and institutions via the
Internet (Hennig-Thurau et al., 2004, p. 39).
C2C know-how exchange (von Hippel, 1988) is a component of eWOM by which
participants share their knowledge with the intent to optimize the service experience of
other customers (Hennig-Thurau et al., 2004;Racherla et al., 2013). C2C know-how
exchange also may impact the customer’s overall perceived value of the rm’s offering
signicantly (Kim and Lee, 2015;Gruen et al., 2006). Consumers increasingly rely on
these self-reports and reviews as part of the purchase decision-making process (Levy
et al., 2013). Overall, the communication channels evaluated in this study include
company web sites, employees, social media (eWOM, specically C2C knowledge
exchange and reviews/opinions) and personal word-of-mouth.
Parasuraman and Grewal (2000) explored how technology can inuence customer
responses on loyalty, satisfaction and perceived value. In determining better value, the
customers may place some importance on efciency (Meuter et al., 2000). In better value
theory, the customers feel that by using a particular product or service they are saving
time and money and that they are in charge (Dabholkar, 1996). Moreover, previous
studies found the importance of the usability level of technology on consumer behavior
(Luna et al., 2002;Muir and Moray, 1996). For example, it was found that the ease of
working through a web site such as that of a loyalty program can have an impact on
consumer attitudes (Luna et al., 2002). Usability is very important in identifying the key
elements of the quality of information involved (Ranganathan and Ganapathy, 2002)
and perceived online channel service quality (Montoya-Weiss et al., 2003). In summary,
customers will select the communication channel that they perceive as easier to use and
of better value to them than the other available channels. The choice of communication
channel will be impacted by how easy it is to use that particular channel (Davis, 1989);
elements such as clarity, usefulness, timeliness, friendliness and interactivity can be
vital in building the ease of use perception. The integration of variables such as
perceived usefulness (Rivera et al., 2015) in the communication style can affect the level
of customer satisfaction, attitude and ultimately the perception of better value to the
customer (Kim and Eom, 2002).
2.3 Communication style and information quality
Communication affects all aspects of the business relationship, especially trust,
satisfaction and loyalty (Ball et al. 2004). Effective relationship marketing
communication requires providing trustworthy information, providing service
information, fullling promises and providing information in case of service delivery
problems (Ndubisi and Chan, 2005). In the case of hotel loyalty programs, this
communication may include accurate and timely information regarding program
benets, promotion and regulations, as well as meeting expectations. Technological
advances in communication play an increasingly important role in the customer’s
experience by advancing both company-managed and customer-created
communication efforts. Ever-changing communication media, expanded customer
touch points and the expectations of accurate and customized information for instant
gratication directly impact the service industry’s ability to meet or beat the needs and
expectations of customers (Parasuraman and Colby, 2001;Ray et al., 2005).
In the early stages, communication builds awareness, develops customer preference,
convinces interested buyers and encourages potential buyers to make the purchase
decision. In later stages, communication involves keeping in touch with customers on a
regular basis, providing timely and accurate information and updates on services or
products and proactive communication in case of potential problems (Liu et al., 2015;
Ndubisi and Chan, 2005). Managing conict is also a vital aspect of communication. It is
the ability to avoid potential conicts, to solve manifest conicts before they create
problems and to discuss solutions openly when problems arise (Dwyer et al., 1987).
Ndubisi and Chan (2005) found a signicant relationship between conict handling and
customer loyalty. Good conict management can result in greater loyalty, “exit” or
“voice” (Rusbult et al., 1998), depending on the degree of prior satisfaction with the
relationship, the amount of the customer’s investment in the relationship and a
consideration of the alternatives. Improper or unresponsive handling of complaints can
be perceived as incompetent or opportunistic behavior and thereby will have a negative
impact on trust (Ganesan, 1994;Morgan and Hunt, 1994).
The importance of personalization and customization of communication has been
illustrated by Allen and Wilburn (2002);Lemon et al. (2001) and Parasuraman et al.
(1991). Whatever the channel, customers now expect communication to be more
accessible, more accurate and more responsive than ever before. In services, customer
contact includes electronic and personal communication. Companies often measure
customer satisfaction with the communicative abilities of their customer contact
employees based on the following metrics: courtesy, professionalism, attentiveness,
knowledge, preparedness and thoroughness. Froehle (2006) evaluated the impact of
these service personnel characteristics on the customer experience according to
relationship-building characteristics and task-oriented characteristics in different
media environments. “Good” company-created communication has been dened as
“helpful, positive, timely, useful, easy, and pleasant”, with little effort required for the
customer to decode the communication and determine its utility (Ball et al., 2004).
Likewise, Berezan (2012) illustrates the importance of the communication dimensions of
communication style and information quality: “[Brand] customer service agents have
always been pleasant and friendly. My concern has been the amount of incorrect
information that [was] given out by these agents”, suggesting that positive
communication alone is not sufcient. Rather, a balance of information quality and style
is required to foster the antecedents of loyalty.
Measures for both communication style and information quality were based on how
the literature dened effective communication (Ball et al., 2004;Ganesan, 1994;Morgan
and Hunt, 1994;Ndubisi and Chan, 2005). Communication style dimensions for each
channel was examined based on participants’ agreement or disagreement with the
following descriptions: positive, personalized, customized, professional, interactive,
easy, pleasant, courteous, friendly, attentive and responsive. The information quality
dimension to be evaluated for each channel of communication included trustworthiness,
accuracy, clarity, helpfulness, usefulness, timeliness, continuity, proactivity,
accessibility and thoroughness.
2.4 Study hypothesis
The concept of the Loyalty Circle (Shoemaker, 2003;Shoemaker and Kapoor, 2008)
stresses that communication is just as important as the elements of value and process in
determining loyalty. However, technological advances increasingly cause
communication to play a more important role in the experience of customers by
advancing both company-managed and customer-created efforts (Fearis, 2012;Gupta,
2012;Parasuraman and Colby, 2001;Ray et al., 2005). Therefore, this study specically
examined the impact of communication channels and suggested the following
H1. The type of communication channel utilized has a signicant impact on loyalty
program members’ perception of communication style and information quality.
3.1 Data collection and survey instrument
The targeted sample for this study was active loyal members of hotel reward programs.
Loyal customers are described as those who have a preference, which results in an actual
behavior toward a product (Jacoby and Kyner, 1973). Thus, two criteria were used for
(1) subjects have a favorite hotel reward program; and
(2) subjects have stayed at a hotel at least twice in the past six months.
Subjects include members from all elite levels of hotel reward programs. Sampling was
performed by eRewards (ResearchNow), an online data collection agency with more
than six million qualied panel members. The nal sample for this study included a
total number of 541 participants.
An online survey was designed based on previous literature to collect data. The rst
three questions were screening pre-qualifying questions, ensuring that participants (a)
are of age, (b) have actively stayed in a hotel at least twice in the past six months and (c)
are members of a hotel reward program. The rst section asked participants where they
most often obtained information in regard to their hotel reward programs, which hotel
reward program(s) they belong to and what their favorite program is. The second
section asked respondents to rate the communication style and information quality
according to the communication channel from where they most often obtain their
information regarding their favorite hotel loyalty program. Demographic information
such as gender, marital status, education, employment, area of residence and income
were included in the nal section of the survey. For all scales, participants were asked to
rate how much they agreed or disagreed with each of the statements on a seven-point
Likert-type scale, anchored at “strongly disagree” and “strongly agree”.
3.2 Measurement validity and reliability
Communication style is composed of four sub-constructs (one for each communication
type: company web site, company employee, social media and personal word-of-mouth).
Each of these sub-constructs was initially composed of 11 items (positive, personalized,
customized, professional, interactive, easy, pleasant, courteous, friendly, attentive and
responsive). The following items were deleted due to their similarity in meaning to other
items: positive, personalized, easy, pleasant, courteous and responsive. After deleting
the same six items from the scale of each sub-construct, the construct “Communication
style” had high internal consistency (Cronbach’s
Information quality is also composed of four sub-constructs (one for each
communication type: company web site, company employee, social media and personal
word-of-mouth). Each of these sub-constructs was initially composed of the same ten
items (trustworthiness, accuracy, clarity, helpfulness, usefulness, timeliness, continuity,
proactivity, accessibility and thoroughness). Accurate, helpful, continuously provided
and proactively provided were removed due to their similar meanings to other items.
Easy to access was removed, as it was deemed by two experts that this is not a
dimension of information quality. After deleting the same ve items from the scale of
each sub-construct, the construct “Information quality” had high internal consistency
!0.957). Results of Cronbach’s alpha all exceeded the 0.8 level, indicating
an excellent level of internal consistency (Carmines and Zeller, 1979).
3.3 Data analysis method
Multivariate analysis of variance (MANOVA) was used to test the study hypothesis.
MANOVA is used to determine whether there are differences between independent
groups on the dependent variable. MANOVA is assumed to be relatively robust, but
assumptions include normal distribution, linear relationships among all pairs of
dependent variables, independence of observation and homogeneity of the covariance
matrices. All assumptions were met, and missing data were removed.
MANOVA was performed using communication style and information quality as the
dependent variables and communication channels as the independent variable.
Communication style included ve dimensions (customized, professional, interactive,
friendly, attentive), and information quality included ve dimensions as well
(trustworthy, clear, useful, timely and thorough). Communication channels included
four groups (company web site, company employee, social media and personal
word-of-mouth). Box’s M test of Equality of Covariance Matrices was observed to check
the homogeneity of variance. Although the test was signicant, indicating a signicant
difference among communication channels in the covariance matrices, this was not
much of a problem due to the moderately large sample size (n!541). Additionally, the
condence level was set at 0.001 to decrease the possibility of type 1 error.
4.1 Sample prole
Table I shows the sample prole of the sample for this study. The majority of the sample
were over 55 years old (56.7 per cent), and approximately 20 per cent were between 45
and 54 years old. Nearly 11 per cent were in the age range between 35 and 44 years old
and less than 11 per cent were less than 35 years old. Thus, the majority of this sample
reects one of the most powerful markets in the USA – people above 50 years of age.
More than half of the sample was male, representing 52 per cent. The proportion of
females was 48.2 per cent. A large proportion of the sample either had a college degree
(43.6 per cent) or a post graduate degree (33.5 per cent). Slightly less than 20 per cent had
some college education. Almost 70 per cent of the sample was married, 17 per cent were
single and roughly 10 per cent were divorced or separated. Most of the sample traveled
for leisure representing more than 74 per cent, and about 24 per cent traveled for
4.2 Multivariate analysis of variance
Table II shows the summary of the multivariate main effect. A one-way MANOVA
revealed a statistically signicant main effect for communication channels on the
combined DVs, Wilks’
!0.74, F(30, 1,550) !5.52, p"0.001, with partial
Thus, the study hypothesis was supported. Given the signicance of the overall test,
follow-up analyses of variance (ANOVAs) were examined. Signicant univariate main
18–24 years 12 2.2
25–34 years 46 8.5
35–44 years 63 11.6
45–54 years 113 20.9
55–64 years 182 33.6
65 years and over 125 23.1
Male 280 51.8
Female 261 48.2
Less than high school 1 0.2
High school 22 4.1
Some college 101 18.7
College degree 236 43.6
Post-graduate degree 181 33.5
Married 377 69.7
Single 92 17.0
Separated/divorced 56 10.4
Widowed 16 3.0
Business 132 24.4
Leisure 402 74.3
Other 7 1.3
Total 541 100.0
effects for communication channels were obtained for both communication style and
information quality. Table III shows the summary of the univariate main effects.
All ve dimensions of communication style were inuenced by type of
communication channel as follows: customized, F(3, 537) !ó 21.89, p"0.005, partial
!0.11; professional, F(3, 537) !20.37, p"0.005, partial
!0.10; interactive, F(3,
537) !25.40, p"0.005, partial
!0.12; friendly, F(3, 537) !22.50, p"0.005, partial
!0.11; and attentive, F(3, 537) !20.95, p"0.005, partial
!0.11. Furthermore, all
ve dimensions of information quality were inuenced by type of communication
channel as follows: trustworthy, F(3, 537) !5.07, p"0.005, partial
!0.03; clear, F
(3, 537) !17.71, p"0.005, partial
!0.09; useful, F(3, 537) !3.95, p"0.005,
!0.02; timely, F(3, 537) !7.55, p"0.005, partial
!0.04; and thorough,
F(3, 537) !3.85, p"0.005, partial
The Levene’s statistics for the dependent variables, which had signicant univariate
ANOVAs were all non-signicant, meaning that the group variances were equal. Thus,
the Sheffé tests were employed for the post hoc tests to observe pairwise differences. The
condence level was cutoff at 0.005 since there were a total of ten signicant tests for the
post hoc tests. Table III shows the summary of the Sheffé post hoc tests. For
communication style, signicant mean differences in customized was obtained between
social media (M !4.13) and company web site (M !5.90), company employee (M !
5.25) and personal word-of-mouth (M !5.31); professional was obtained between
company web site (M !5.80) and company employee (M !5.10) and social media (M !
4.17); interactive was obtained between company web site (M !5.87) and company
employee (M !5.10) and social media (M !4.17)/between social media (M !4.17) and
Summary of one-way
Effect Value FSig.
Wilk’s Lambda 0.74 5.52 0.00* 0.09
Summary of follow-
up ANOVA tests
Dependent variables FSig.
Customized 21.89 0.00* 0.11
Professional 20.37 0.00* 0.10
Interactive 25.40 0.00* 0.12
Friendly 22.50 0.00* 0.11
Attentive 20.95 0.00* 0.11
Trustworthy 5.07 0.00* 0.03
Clear 17.71 0.00* 0.09
Useful 3.95 0.00* 0.02
Timely 7.55 0.00* 0.04
Thorough 3.85 0.01* 0.02
personal word-of-mouth (M !5.27); friendly was obtained between company web site
(M !5.77) and company employee (M !5.05) and social media (M !4.07) / between
social media (M !4.07) and personal word-of-mouth (M !5.18); attentive was obtained
between company web site (M !5.78) and company employee (M !5.05) and social
media (M !4.07).
For information quality, signicant mean differences in trustworthy was obtained
between company web site (M !5.25) and social media (M !4.30); clear was obtained
between social media (M !4.10) and company web site (M !5.79), company employee
(M !5.44) and personal word-of-mouth (M !5.45); timely was obtained between social
media (M !4.30) and company web site (M !5.43), company employee (M !5.41) and
personal word-of-mouth (M !5.61). There was no pairwise difference obtained for
useful and thorough. Table IV shows the summary of the descriptive statistics by the
dependent variables and the independent variables.
5. Implications and conclusion
Several important themes and observations emerged that are worthy of further
investigation and attention by those involved in communication for an organization.
Communication style and information quality have been shown to impact customer
loyalty (Ball et al., 2004;Ndubisi and Chan, 2005;van Riel et al., 2001). This study
suggests that the type of communication channel used by hotel loyalty program
members impacts their perception of communication style and information quality, and
thereby loyalty to the program (Ranganathan and Ganapathy, 2002). Marketing
managers should consider these research ndings when structuring and maintaining
relationships for their loyalty program members through the various communication
The results indicate that the choice of communication channel has a signicant
impact on perceived communication style and information quality, and their underlying
dimensions. For example, when using word-of-mouth as a communication channel,
information quality is perceived as trustworthy, clear, useful and thorough (Ball et al.,
2004;Racherla et al., 2013). Through the same channel, communication style is perceived
Company Company Social Personal
web site Employee Media WOM
M SD M SD M SD M SD
Customized 5.90 1.24 5.25 1.41 4.13 1.43 5.31 1.42
Professional 5.80 1.27 5.10 1.36 4.17 1.26 5.18 1.34
Interactive 5.87 1.19 5.10 1.35 4.10 1.49 5.27 1.30
Friendly 5.76 1.22 5.05 1.32 4.07 1.28 5.18 1.32
Attentive 5.78 1.22 5.00 1.33 4.23 1.33 5.14 1.28
Trustworthy 5.25 1.36 5.03 1.29 4.30 1.37 5.31 1.29
Clear 5.79 1.22 5.44 1.43 4.10 1.35 5.45 1.30
Useful 5.38 1.34 5.08 1.41 4.60 1.63 5.49 1.27
Timely 5.43 1.29 5.41 1.38 4.30 1.34 5.61 1.33
Thorough 5.26 1.38 5.37 1.35 4.43 1.45 5.39 1.34
as customized, professional, interactive, friendly and attentive (Parasuraman and Colby,
2001;Ray et al., 2005).
Under communication style, the “customized” variable showed signicant
differences among the four communication channels. While the program web site was
perceived to be the most customized (Parasuraman and Colby, 2001;Ray et al., 2005)
followed by personal word-of-mouth (Hennig-Thurau et al., 2004) and company
employee (Ball et al., 2004), social media was perceived as the least customized
communication channel when seeking information about loyalty programs. This may
be attributed to social media being a standard messaging platform for everyone (with
limited ltering capability), so it may not be able to satisfy everyone’s preferences
concurrently. In the same construct, the company web site was perceived to be the most
professional in communicating, followed by company employee interaction (Anderson
and Narus, 1990), word-of-mouth and social media. It is likely that the web site of a
loyalty program has more resources dedicated to the updates and maintenance, and the
company employees having more training when responding via chat, phone or e-mail.
For this study’s participants, social media is relatively in its infancy stage of acceptance
by an older age demographic. At the same time, the web site may be perceived as easy
to use and better value to the consumer, while social media may require extra effort and
energy, especially to the demographic over the age of 45, which made up more than 75
per cent of the survey participants. This is aligned with the Ease of Use Theory whereby
technology adoption needs to be effortless (Davis, 1989) and perceived to be easy to use
(Venkatesh and Davis, 1996). In this way, the customer perceives that they are receiving
better value (van Riel et al., 2001) and thus shows a higher level of satisfaction.
The company web site was deemed to be the most interactive and friendly channel
(Ball et al., 2004;Anderson and Narus, 1990), with social media perceived as the least
interactive and friendly. The participants in this survey prefer interacting through the
company web site, as this is a tool they may have gotten used to over time due to the ease
of use (Kim and Eom, 2002). Furthermore, company web sites provide a variety of
interactive options such as member account information, ofcial program information,
award availability and direct links to online reviews (social media). Social media,
however, does not score as high in interaction and friendliness in loyalty programs. This
means that any communication that is driven to the audience through the loyalty
program’s web site is considered more interactive and friendly (Anderson and Narus,
1990) than the rest of the communication channels. This is a surprising result,
considering that social media is largely a communication channel produced by the
customer for the customer. This may be attributed to the age distribution dynamic of the
participants, as they tend to be a more mature audience that may nd social media
channels to be a non-personal, non-friendly communication avenue for their needs and
preferences. A younger sample may produce different results in this situation.
Communication channels inuence all ve dimensions of information quality
(trustworthy, clear, useful, timely and thorough). Perhaps due to the nancial and
human resources devoted to web site management and updates, company web site
information quality meets the preferences of most consumers. This is well aligned with
the better value theory in which quality of information and service quality are two
highly sought attributes by customers when selecting their preferred channel of
communication (Athanassopoulos, 2000;Montoya-Weiss et al., 2003;Ranganathan and
Ganapathy, 2002). Social media is also considered trustworthy, likely because the
information is provided by fellow customers and without a business purpose (Racherla
et al., 2013). Program web site was perceived to provide the clearest information,
followed by company employees.
It is also interesting to observe that the timeliness of information provided through
social media is rated lower than personal word-of-mouth and program web site. This
may be attributed to the older demographic participants of the survey. Since social
media outlets are still relatively new to older participants, they may not check Facebook
or Twitter frequently and thus perceive the information posted as not current or
As opposed to Berezan (2012), the results of this study suggest that social media
platforms are not as prominent as other communication channels in positively
impacting perceived information quality and style. In fact, the most impactful channels
were company-created and managed channels û i.e. program web site and employees.
For management, this means that the customer rst seeks information through channels
in which the company has ownership and control of the content rather than outside
inuencers such as social media and personal word-of-mouth. This can be a very
powerful tool for organizations, since they now know that the customer trusts the
information posted on the web site more than any other channel disseminating
The ndings also revealed that more resources need to be devoted to social media if
the organization wants to utilize this particular channel for disseminating information.
Currently, loyalty members do not feel that is easy to use nor that it offers better value
than the other channels of delivering information such as the web site, employees or
word-of-mouth. Given the room for improvement in the social media experience for
program members, marketers have the opportunity to more effectively participate in
customer-created and managed social media platforms. Specically, resources should
be allocated on the basis of making the social media experience more friendly and
engaging to the end user when seeking information about their chosen hotel loyalty
Based on the current events, it is evident that the loyalty communication landscape is
in a state of ux. While company web sites have earned traction for ease of use and
better value both in terms of information quality and communication style, the other
communication channels such as social media outlets should not be ignored; they will
likely be the fastest catalyst and best ambassador for instant communication
information dissemination in the future. All of the major players in communication
channels such as the web site, the employees, word-of-mouth and social media will
always be jockeying for the rst position.
To remain important and relevant, it is imperative that one must actively monitor
this space closely. Executives constantly need to keep abreast of developments as they
unfold and keep in mind the ease of use and better value theories as important to their
customers. Finally, one must provide unparalleled value (i.e. better value theory) to earn
customer loyalty and ultimately the Holy Grail, market share.
6. Study limitations and recommendations for future research
This study has some limitations that should be considered in future research. First, the
use of an online survey restricted the ability to generalize ndings beyond those that use
the internet. Therefore, it is not necessarily representative of all hotel loyalty program
members. Additionally, the use of an existing survey panel may result in inaccurate
responses, as participants are active survey respondents and may be motivated to
participate solely for the reward they are given from the data collection company. The
demographic prole of the study also presents some limitations. For example, nearly 56
per cent of participants were over 55 years of age, 34 per cent were between 35 and 54
and less than 12 per cent were under 34. Another demographic limitation to the study is
that the sample mainly consisted of leisure travelers (74 per cent).
Future research should consider segmenting according to the above-mentioned
demographic segments, as well as segmenting according to tier levels, average spent per
night, hotel class typically frequented and loyalty program brand. Furthermore,
replicating this study with a focus on business travelers or in other areas where
customers seek information outside of loyalty programs would provide valuable insight
into the impact of communication channels on communication style and perceived
quality of communication.
Agustin, C. and Singh, J. (2005), “Curvilinear effects of consumer loyalty determinants in relational
exchanges”, Journal of Marketing Research, Vol. 42 No. 1, pp. 96-108.
Allen, D.R. and Wilburn, M. (2002), Linking Customer and Employee Satisfaction to the Bottom
Line, American Society for Quality, Milwaukee, WI.
Anderson, J. and Narus, J. (1990), “A model of distributor rm and manufacturer rm working
partnerships”, Journal of Marketing, Vol. 54 No. 1, pp. 42-58.
Athanassopoulos, A.D. (2000), “Customer satisfaction cues to support market segmentation and
explain switching behavior”, Journal of Business Research, Vol. 47 No. 3, pp. 191-207.
Bahri-Ammari, N. and Nusssair, K. (2015), “Key factors for a successful implementation of a
customer relationship management technology in the Tunisian hotel sector”, Journal of
Hospitality and Tourism Technology, Vol. 6 No. 3, pp. 271-287.
Ball, D., Coelho, P. and Machas, A. (2004), “The role of communication and trust in explaining
customer loyalty: an extension to the ECSI model”, European Journal of Marketing, Vol. 38
Nos 9/10, pp. 1272-1293.
Barsky, J. and Nash, L. (2006), “Companies update loyalty programs, increase effectiveness”, Hotel
& Motel Management, Vol. 22 No. 11, pp. 28-29.
Berezan, O. (2012), “Self-image congruence with communication channels and its impact on
reward program loyalty”, Dissertation, UNLV Libraries, Las Vegas, NV.
Berezan, O., Raab, C., Tanford, S. and Kim, Y. (2015), “Evaluating loyalty constructs among hotel
reward program members using eWOM”, Journal of Hospitality & Tourism Research,
Vol. 39 No. 2, pp. 198-224.
Carmines, E.G. and Zeller, R.A. (1979), Reliability and Validity Assessment, Sage Publications,
Beverly Hills, CA.
Chai, J.C., Malhotra, N.K. and Dash, S. (2015), “The impact of relational bonding on intention and
loyalty: the mediating role of commitment foci in service relationships”, Journal of
Hospitality and Tourism Technology, Vol. 6 No. 3, pp. 203-227.
Dabholkar, P.A. (1996), “Consumer evaluations of new technology-based self-service options: an
investigation of alternative models of service quality”, International Journal of Research in
Marketing, Vol. 13 No. 1, pp. 29-51.
Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of
information technology”, MIS Quarterly, Vol. 13 No. 1, pp. 319-340.
Dwyer, F., Schurr, P. and Sejo, O. (1987), “Developing buyerûseller relationship”, Journal of
Marketing, Vol. 51 No. 2, pp. 11-27.
Fearis, B. (2012), “Only 11% of Brits book their holiday with high street agents”, available at:
Froehle, C.M. (2006), “Service personnel, technology, and their interaction in inuencing customer
satisfaction”, Decision Sciences, Vol. 37 No. 1, pp. 5-38.
Ganesan, S. (1994), “Determinants of long-term orientation in buyerûseller relationships”, Journal
of Marketing, Vol. 58 No. 2, pp. 1-19.
Gruen, T.W., Osmonbekov, T. and Czaplewski, A.J. (2006), “eWOM: the impact of
customer-to-customer online know-how exchange on customer value and loyalty”, Journal
of Business Research, Vol. 59 No. 4, pp. 449-456.
Gupta, R. (2012), “28Pc of all travel-related queries in the UK came from mobile devices by the end
of 2011”, available at: www.eyefortravel.com/mobile-and-technology/28pc-all-travel-
Haywood, K.M. (1988), “Repeat patronage: cultivating alliances with customers”, International
Journal of Hospitality Management, Vol. 7 No. 3, pp. 225-237.
Hennig-Thurau, T., Gwinner, K., Walsh, G. and Gremler, D. (2004), “Electronic word-of-mouth via
consumer-opinion platforms: what motivates consumers to articulate themselves on the
internet?”, Journal of Interactive Marketing, Vol. 18 No. 1, pp. 38-52.
Jacoby, J. and Kyner, D. (1973), “Brand loyalty verses repeat purchase behavior”, Journal of
Marketing Research, Vol. 10 No. 1, pp. 1-9.
Kandampully, J. (1998), “Service quality to service loyalty: a relationship which goes beyond
customer services”, Total Quality Management, Vol. 9 No. 6, pp. 431-443.
Kim, E.B. and Eom, S.B. (2002), “Designing effective cyber store user interface”, Industrial
Management & Data Systems, Vol. 102 No. 5, pp. 241-251.
Lam, S.Y., Shankar, V., Erramilli, M.K. and Murthy, B. (2004), “Customer value, satisfaction,
loyalty, and switching costs: an illustration from a business-to-business service context”,
Journal of the Academy of Marketing Science, Vol. 32 No. 3, pp. 293-311.
Lemon, K.N., Rust, R.T. and Zeithaml, V.A. (2001), “What drives customer equity?”, Marketing
Management, Vol. 10 No. 1, pp. 20-25.
Levy, S.E., Duan, W. and Boo, S. (2013), “An analysis of one-star online reviews and responses in
the Washington, DC, lodging market”, Cornell Hospitality Quarterly, Vol. 54 No. 1, pp. 49-63.
Liu, B., Pennington-Gray, L. and Klemmer, L. (2015), “Using social media in hotel crisis
management: the case of bed bugs”, Journal of Hospitalty and Tourism Technology, Vol. 6
No. 2, pp. 102-112.
Luna, D., Perracchio, L.A. and de Juan, M.D. (2002), “Cross-cultural and cognitive aspects of
website navigation”, Journal of the Academy of Marketing Science, Vol. 30 No. 1,
McAlexander, J.H., Kim, S. and S.D. Roberts (2003), “Loyalty: the inuences of satisfaction and
brand community integration”, Journal of Marketing Theory and Practice, Vol. 11 No. 4,
McCall, M. and Voorhees, C. (2010), “The drivers of a loyalty program success: an organizing
framework and research agenda”, Cornell Hospitality Quarterly, Vol. 51 No. 1, pp. 35-52.
Meuter, M.L., Ostrom, A.L., Roundtree, R.I. and Bitner, M.J. (2000), “Self-service technologies:
understanding customer satisfaction with technology-based service encounters”, The
Journal of Marketing, Vol. 28 No. 1, pp. 50-64.
Meyer-Waarden, L. (2008), “The inuence of loyalty programme membership on customer
purchase behavior”, European Journal of Marketing, Vol. 42 Nos 1/2, pp. 87-114.
Montoya-Weiss, M.M., Voss, G.B. and Grewal, D. (2003), “Determinants of online channel use and
overall satisfaction with a relational, multichannel service provider”, Journal of the
Academy of Marketing Science, Vol. 31 No. 4, pp. 448-458.
Morgan, R. and Hunt, S. (1994), “The commitment–trust theory of relationship marketing”,
Journal of Marketing, Vol. 58 No. 1, pp. 20-38.
Muir, B.M. and Moray, N. (1996), “Trust in automation, part II: experimental studies of trust and
human intervention in a process control simulation”, Ergonomics, Vol. 39 No. 3, pp. 429-460.
Namkung, Y. and Jang, S. (2009), “The effects of interactional fairness on satisfaction and
behavioral intentions: mature versus non-mature customers”, International Journal of
Hospitality Management, Vol. 28 No. 3, pp. 397-405.
Ndubisi, N. and Chan, K. (2005), “Factorial and discriminant analyses of the underpinnings of
relationship marketing and customer satisfaction”, International Journal of Bank
Marketing, Vol. 23 No. 7, pp. 542-557.
Ni, S., Chan, W. and Shum, E. (2011), “A study of hotel frequent-guest programs: benets and
costs”, Journal of Vacation Marketing, Vol. 17 No. 4, pp. 315-327.
Nunes, J.C. and Dréze, X. (2006), “Your loyalty program is betraying you”, Harvard Business
Review, Vol. 84 No. 4, pp. 1-9.
Olsen, M.D., Chung, Y., Graf, N., Lee, K. and Madanoglu, M. (2005), “Branding: myth and reality in
the hotel industry”, Journal of Retail & Leisure Property, Vol. 4 No. 2, pp. 146-162.
O’Malley, L. (1998), “Can loyalty schemes really build loyalty?”, Marketing Intelligence and
Planning, Vol. 16 No. 1, pp. 47-55.
Parasuraman, A. and Colby, C.R. (2001), Techno-ready Marketing: How and Why Your Customers
Adopt Technology, The Free Press, New York, NY.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991), “Renement and reassessment of the
SERVQUAL scale”, Journal of Retailing, Vol. 67 No. 4, pp. 420-450.
Parasuraman, A. and Grewal, D. (2000), “The impact of technology on the quality-value-loyalty
chain: a research Agenda”, Journal of the Academy of Marketing Science, Vol. 28 No. 1,
Petrick, J.F. (2004), “Are loyal visitors desired visitors?”, Tourism Management, Vol. 25 No. 4,
Racherla, P., Connolly, D. and Christodoulidou, N. (2013), “What determines consumers’ ratings of
service providers? An exploratory study of online traveler reviews”, Journal of Hospitality
Marketing & Management, Vol. 22 No. 2.
Ranganathan, C. and Ganapathy, S. (2002), “Key dimensions of business-to-consumer web sites”,
Information & Management, Vol. 39 No. 6, pp. 457-465.
Ray, G., Muhanna, W.A. and Barney, J.B. (2005), “Information technology and the performance of
the customer service process: a resource-based analysis”, MIS Quarterly, Vol. 29 No. 4,
Reichheld, F.F. and Sasser, E.W. (1990), “Zero defections: quality comes to services”, Harvard
Business Review, Vol. 68 No. 5, pp. 105-116.
Rivera, M., Gregory, A. and Cobos, L. (2015), “Mobile application for the timeshare industry: the
inuence of technology experience, usefulness, and attitude on behavioral intentions”,
Journal of Hospitality and Tourism Technology, Vol. 6 No. 3, pp. 242-257.
Rundle-Thiele, S. and Mackay, M.M. (2001), “Assessing the performance of brand loyalty
measures”, Journal of Services Marketing, Vol. 15 No. 7, pp. 529-546.
Rusbult, C., Martz, J. and Agnew, C. (1998), “The investment model scale: measuring commitment
level, satisfaction level, quality of alternatives, and investment size”, Personal
Relationships, Vol. 5 No. 1, pp. 357-391.
Shoemaker, S. (2003), “The future of pricing”, Journal of Revenue and Pricing Management, Vol. 2
No. 3, pp. 271-279.
Shoemaker, S. and Kapoor, C. (2008), “Relationship and loyalty marketing”, in Oh, H. (Ed.),
Handbook of Hospitality Marketing Management, Elsevier, New York, NY, pp. 119-152.
Shoemaker, S. and Lewis, R.C. (1999), “Customer loyalty: the future of hospitality marketing”,
Hospitality Management, Vol. 18 No. 1, pp. 345-370.
Uncles, M.D., Dowling, G.R. and Hammond, K. (2003), “Customer loyalty and customer loyalty
programs”, Journal of Consumer Marketing, Vol. 20 No. 4, pp. 294-316.
van Riel, A.C., Liljander, V. and Jurriens, P. (2001), “Exploring consumer evaluations of e-services:
a portal site”, International Journal of Service Industry Management, Vol. 12 No. 4,
Venkatesh, V. and Davis, F.D. (1996), “A model of the antecedents of perceived ease of use:
development and test”, Decision Sciences, Vol. 27 No. 3, pp. 451-481.
Verhoef, P.C. (2003), “Understanding the effect of customer relationship management efforts on
customer retention and customer share development”, Journal of Marketing, Vol. 7 No. 1,
von Hippel, E. (1988), The Sources of Innovation, Oxford University Press, New York, NY.
Yoo, M. and Kitterlin, M. (2012), “Maintaining your loyal customers during hard times: an
observation from the gaming industry”, FIU Hospitality Review, Vol. 30 No. 1, pp. 112-130.
Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996), “The behavioral consequences of service
quality”, Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
Adams, D.A., Nelson, R.R. and Todd, P.A. (1992), “Perceived usefulness, ease of use, and usage of
information technology: a replication”, MIS Quarterly, Vol. 16 No. 2, pp. 227-247.
Agarwal, R. and Karahanna, E. (2000), “Time ies when you’re having fun: cognitive absorption
and beliefs about information technology usage 1”, MIS Quarterly, Vol. 24 No. 4,
Antonios, J. (2011), “Understanding the effects of customer education on customer loyalty”,
Business Leadership Review, Vol. VIII No. 1, pp. 1-15.
Aubert, B., Khoury, G. and Jaber, R. (2005), “Enhancing customer relationships through customer
education: an exploratory study”, in Chapelet, B. and Awajan, A. (Eds), Proceedings of the
First International Conference on E-business and E-learning, Amman, pp. 194-201.
Bearden, W.O., Hardesty, D.M. and Rose, R.L. (2001), “Consumer self-condence: renements in
conceptualization and measurement”, Journal of Consumer Research, Vol. 28 No. 1,
Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989), “User acceptance of computer technology: a
comparison of two theoretical models”, Management Science, Vol. 35 No. 8, pp. 982-1003.
Flavián, C., Guinalíu, M. and Gurrea, R. (2006), “The role played by perceived usability,
satisfaction and consumer trust on website loyalty”, Information & Management, Vol. 43
No. 1, pp. 1-14.
Koufaris, M., Kambil, A. and LaBarbera, P.A. (2001), “Consumer behavior in web-based
commerce: an empirical study”, International Journal of Electronic Commerce, Vol. 6 No. 1,
Lemon, K.N., White, T.B. and Winer, R.S. (2002), “Dynamic customer relationship management:
incorporating future consideration into service retention decision”, Journal of Marketing,
Vol. 66 No. 1, pp. 1-14.
Mayock, P. (2012), “Wyndham ‘opening doors’ for franchisees”, available at: www.hotelnewsnow.
Strauss, J., el-Ansary, A. and Frost, R. (2003), E-marketing, Prentice Hall, Upper Saddle, NJ.
Venkatesh, V. (2000), “Determinants of perceived ease of use: integrating control, intrinsic
motivation, and emotion into the technology acceptance model”, Information Systems
Research, Vol. 11 No. 4, pp. 342-365.
About the authors
Dr Orie Berezan is an Assistant Professor of Marketing at California State University, Dominguez
Hills. His research interests are customer loyalty, reward programs and social networking in the
Dr Michelle Yoo is an Assistant Professor at The Collins College of Hospitality Management in
California State Polytechnic University Pomona (Cal Poly Pomona). Dr Yoo’s research interest
areas include strategic marketing, customer relationship marketing and database marketing in
the hospitality industry.
Dr Natasa Christodoulidou is the Director of the Hospitality Technology Research Institute at
California State University Dominguez Hills (CSUDH). She is an Associate Professor in the
Management and Marketing Department at CSUDH where she teaches for the undergraduate and
the MBA programs. She holds a PhD from the University of Nevada Las Vegas (UNLV), an MBA
from the University of Wisconsin-Milwaukee (UWM) and a Master’s of Accounting and a BSc
from Arizona State University (ASU). Her research interests are in the areas of Hospitality
Technology, Electronic Commerce, Electronic Distribution and E-marketing. Her research has
appeared in numerous academic and professional journals. Dr Christodoulidou presents regularly
at academic and professional industry conferences around the world. She currently serves as
Program co-chair for the 2015 Decision Sciences Institute (DSI) Annual Meeting, and Vice
President and 2016 Program Chair for the Western Decision Sciences Institute (WDSI). Currently
Dr Christodoulidou is investigating the impact of mobile technologies and social media for
airlines, hotels and online travel agencies (OTAs). Her speaking engagements recently have
included Cyprus, Dubai, France, Los Angeles, San Francisco, Long Beach, Las Vegas, Boston,
Dallas and others. Natasa Christodoulidou is the corresponding author and can be contacted at:
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