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The Routledge Handbook of Hospitality Marketing
Dogan Gursoy
Mobile apps and hospitality marketing
Publication details
Lu Zhang
Published online on: 02 Oct 2017
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Mobile apps and
hospitality marketing
Lu Zhang
Mobile apps can be defined as application software designed to provide utilitarian values (e.g.,
information) and hedonic values (e.g., entertainment) on mobile devices such as smartphones
and tablets. These apps are either pre-​installed on devices during manufacture, or downloaded
by customers through software distribution platforms such as the App Store and Google Play
(Ho and Syu, 2010). As of June 2016, Google’s Google Play Store contained 2.2 million apps
and Apple’s App Store had 2 million available apps (Statista, 2016). The number of mobile app
downloads worldwide has increased dramatically in the past few years. In 2009, worldwide
mobile app downloads totaled approximately 2.52 billion and is expected to reach 268.69 billion in 2017 (Statista, 2016). The rapid growth of smartphones and mobile apps has changed
the ways in which consumers interact with a brand (Kim, Wang, and Malthouse, 2015) and has
provided marketers with another channel to reach out to their customers (Lin, Fang, and Hsu,
2014). More and more companies have welcomed mobile apps as a marketing tool that can be
used to attract new customers and increase brand loyalty among existing ones (Wang, Kim, and
Malthouse, 2016). As in all other services segments such as retailing, mobile apps have become
very popular in the hospitality industry. Restaurants’ branded apps allow customers to make
reservations using the app, which tends to perform better than traditional call reservations in
terms of hours, consistency, and record-​keeping accuracy (Kimes, 2011). Hotel groups such as
Marriott and Accor have been investing heavily in electronic assets to cement a digital presence that connects with customers in a meaningful way (Avery, Dev, and O’Connor, 2015). For
example, Marriott Mobile, together with, are considered as two of their fastest
growing booking channels (Marriott International, 2015). In 2015, the Marriott Mobile app
alone exceeded $1 billion in gross bookings. They were the first hotel company to offer mobile
check-​in and checkout services, and the first global hospitality company to offer Apple Pay as
another step that enables guests to engage more often with Marriott. Other major hotel companies such as IHG (InterContinental Hotel Group) and Hilton have their own mobile apps too.
See Table 42.1 for a summary of the mobile apps and functions of six major hotel companies.
As shown in Table 42.1, most hospitality companies’ mobile apps mainly focus on providing
basic utilitarian benefits to customers (e.g., easy booking). Judging by the number of reviews
and number of downloads, these apps have successfully reached a large group of consumers.
However, research has shown that only about one-​third of users continue to use an app one
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Table 42.1 Hotel mobile apps
Key figures
Customer ratings
(1–​5 stars)
• Booking
• Easy access to rewards
• Check-​in and checkout
• Chat with hotel
• Make requests for
• Mobile key
• Receive alert when room
is ready
• Generated $1 billion
in gross bookings
in 2015 (Marriott
International, 2015)
• 2.5 stars with
3498 ratings
on App Store
• 3.7 stars with
7907 ratings
on Google Play
• Booking
• Access special offers and
• Check-​in and checkout
• Receive alert when room
is ready
• 40% of digital visits
on mobile devices
• Over $1.2 billion
annual mobile
revenue in 2015,
up from less than
$50 million in 2010
• 27% downloads
growth (IHG, 2015)
• 4.5 stars with
5325 ratings
on App Store
• 4.1 stars with
11198 ratings
on Google Play
• Booking
• Digital key
• Check-​in and checkout
• Room selection
• Request amenities
• Access to special offers
• Request Uber rides
• Get recommendations
about local hotspots
• Business generated
from mobile app
is up nearly 150%
• Downloads exceeding 70,000 a week,
an increase of 200%
from 2015 (Skift,
• 4.5 stars with
11785 ratings
on App Store
• 4.5 stars with
19616 ratings
on Google Play
• Booking
• Explore local attractions
• Earn rewards
• Search for hotels
• Access verified guests
• 17% increase in
revenue for the first
quarter of 2016
compared to the
same period last year
because of direct
mobile booking
(Skift, 2016)
• 3.5 stars with
2334 ratings
on App Store
• 4.3 stars with
10274 ratings
on Google Play
• Booking
• Access TripAdvisor
• Check-​in
• Request Uber rides
• Wipolo: group all the
details about flights,
trains, hotels, etc.
• Easy access to rewards
• 40% of web visits are
from mobile devices
• 3 million app downloads (AccorHotels,
• 3.5 stars with
347 ratings on
App Store
• 4.1 stars with
18187 ratings
on Google Play
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Lu Zhang
month after first using it, and this number drops to just four percent after one year (Ding and
Chai, 2015). With such a high dropout rate, it is important for hospitality companies to truly
understand mobile apps and their impact on consumers. To help address this issue, this chapter
will discuss (1) the platform (i.e. the characteristics of mobile devices); (2) the type of mobile
apps and their basic functions; and (3) factors influencing consumers’ adoption of mobile apps.
Mobile devices
Compared with other devices such as desktop computers, mobile devices have a few unique
characteristics (Barnes, 2002; Gao, Rau, and Salvendy, 2009; Kannan, Chang, and Whinston,
2001), which will be discussed in the next sections.
Ubiquitous availability
Mobile devices are always “on” and connected. The fact that they are always available and
users carry them every day and everywhere changes the way we interact with mobile devices.
According to Weiser (1991), “The most profound technologies are those that disappear. They
weave themselves into the fabric of everyday life until they are indistinguishable from it” (p. 94).
Nowadays, people do not think of mobile devices as advanced technology. They are part of our
daily routine and simply a feature of the world we take for granted (Fano and Gershman, 2002).
An example of how mobile devices shape the way we act in the world is from the travel industry.
People use mobile devices for all types of activities before (e.g., booking hotel rooms), during (e.g.,
taking photos), and after (e.g., posting pictures on social media) their trips. Nearly every touch
point along the journey involves the usage of mobile devices.
Personal usage
While other traditional devices such as telephones and computers can usually be shared among
different users (e.g., family members, officemates, etc.), mobile devices are more personal
because they are usually carried and used by only one person and people tend to use them in
a personal context (Gong and Tarasewich, 2004). Different users have various levels of skills,
distinct usage habits, patterns, and preferences. Therefore, users are more likely to personalize
their mobile device so that it carries his or her personal identity and reflects individual preferences. Additionally, due to the nature of personal usage, mobile ads are often perceived as more
intrusive than traditional marketing techniques such as TV commercials and displayed ads on
Interactivity has historically been defined as any form of communication that replicates face-​to-​
face conversation (Rafaeli, 1988). Bucy (2004) suggested that interactivity consists of reciprocal
communication exchanges that involve some form of media, or information, and communication technology. Interactivity as a media feature comes in the form of different modalities
of information dissemination. While traditional mediums (e.g., newspapers) typically have two
modalities, text and pictures, new digital media interfaces offer a wide variety of modalities
that allow us to interact with several of our senses operating together, such as audio and video
(Sundar, 2008). Moreover, with the development of tablet and mobile technology, users are
often exposed to interactive modalities beyond just pointing and clicking, for example, dragging,
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Mobile apps and hospitality marketing
sliding, and flipping. Several studies have found that interactivity produces positive outcomes.
Basso et al. (2001) found that interactivity facilitates favorable judgments in online shopping
experiences. In addition, Stout, Villegas, and Kim (2001) found that interactive tools can boost
individuals’ willingness to interact when searching for health-​related information.
Context-​aware ability
Context-​aware computing refers to the ability to utilize contextual information such as location, display medium, and user profile in order to provide tailored functionality (Cheverst,
Davies, Mitchell, Friday, and Efstratiou, 2000). Two types of contextual information are usually
considered: personal information such as the consumer’s personal interests, and environmental
information such as the current location of the consumer. Given the context sensitivity of
mobile apps, they can recommend restaurants for lunch either based on customers’ previous
visits (i.e., personal information) or suggest places within 300 feet of users (i.e., environmental
Types of mobile apps
Having established the characteristics of the platform for which mobile apps are developed, the
discussion will now turn to the types of mobile apps currently on the market as well as the main
values provided. Bellman and colleagues (2011) differentiate between two types of apps: informational and game-​like apps. This chapter proposes a classification of four types of mobile apps
based upon two studies (Gupta, 2013; Zhao and Balagué, 2015): games and entertainment; utility;
discovery; and social network. Each type of mobile app provides a set of values that are unique to
customers. The notion of “value” is central to services marketing (Larivière, Joosten, Malthouse,
van Birgelen, Aksoy, Kunz, and Huang, 2013). It refers to the result of customers’ assessments in
weighing the bundle of benefits against the bundle of costs they expect to incur in evaluating,
obtaining, and using the product or service (Kotler, 2000). Understanding what values customers
intend to derive from mobile apps will help firms to create experiences that are engaging and
meaningful (Lariviere et al., 2013).
Games and entertainment
Mobile apps are often used for satisfying individuals’ entertainment needs. Consumers intentionally seek playfulness while using their mobile devices by engaging in activities such as playing
games or watching YouTube videos. Popular game apps typically include casual games, which can
be described as “easy-​to-​play, short-​session games” (Bates, 2004, p. 10). They have an effortless
learning curve compared to hardcore video games and require lower commitment in terms of
time and resources (Speller, 2012). The growth of mobile devices/​apps is one of the main contributors of the popularity of casual gaming.
The second type of mobile app focuses on providing functions that facilitate tasks that consumers are currently performing. For instance, Google Maps is a map utility that can be used for
navigation purposes. Hotel mobile apps allow customers to enjoy their stay without directly
interacting with front desk clerks. Also, by using airlines’ mobile apps, consumers can purchase
tickets, check their flight status, and select seats.
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Lu Zhang
Table 42.2 Types of mobile app
Type of app
Value provided
Games and
Social network
Angry Birds, YouTube
Hedonic value –​escape and relax
Google Maps, Calculator
Yelp, TripAdvisor
Facebook, SnapChat
Utilitarian value –​facilitation
Utilitarian value –​information search
Both hedonic and
utilitarian –​ communication
This type of mobile app is usually used to find out about relevant events and conditions in
the immediate surroundings, society, and the world (Lariviere et al., 2013). It offers customers
the opportunity to search for information that is relevant in making purchasing decisions. For
example, Yelp can be used to find restaurants and TripAdvisor can be used to search for hotel
information. Customers can also use this type of mobile app to find out information about
local hotspots as well as read other customers’ evaluations of those places (i.e., online customer
Social network
From the user perspective, mobile apps for social networks are designed to allow users to stay
connected and be able to communicate with their friends at all times. Due to the ubiquitous
availability of mobile devices, apps such as Facebook and Twitter enable customers to share their
thoughts and experiences with other people anytime and anywhere (Lariviere et al., 2013).
Moreover, apps such as SnapChat and Vine take advantage of the built-​in camera of mobile
devices and offer customers greater flexibility in terms of the content (i.e., pictures and videos
in addition to text) they can share with others. See Table 42.2 for a summary of the four types
of mobile apps, examples, and values provided to users.
Consumers’ adoption of mobile apps
Consumers’ adoption and usage of a mobile app determines its success as a marketing tool
(Carroll, 2007; Chen, Hsu, and Wu, 2012; Picoto, Palma-​dos-​Reis, and Bélanger, 2010), because
adoption translates into bookings and revenue (Hu, 2011; Sangle and Awasthi, 2011). Consumers’
intention to adopt and use mobile apps has been extensively examined by prior research and
typically involves two theoretical frameworks: TAM (Technology Acceptance Model) and U&G
(Uses and Gratifications). Next, these two models will be introduced, together with research
related to mobile apps.
In 1989, Davis proposed the Technology Acceptance Model (TAM) to understand the psychological processes of information technology adoption and acceptance. Based on the theory
of reasoned action (Fishbein and Ajzen, 1975) and the theory of planned behavior (Ajzen, 1991),
TAM is one of the most widely accepted models in the area of technology adoption. The
original TAM focuses on two theoretical constructs, perceived usefulness (PU) and perceived
ease of use (PEOU), which are the fundamental determinants of system acceptance and use
(Davis, 1989). According to Davis (1989), perceived usefulness is defined as the degree to which
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Mobile apps and hospitality marketing
a person believes that using a particular system will enhance his or her job performance. Within
an organizational context, users believe that an application high in perceived usefulness is more
likely to produce a positive use-​performance relationship. On the other hand, perceived ease
of use refers to the degree to which a person believes that using a particular system would be
free of effort. An application perceived to be easier to use is more likely to be accepted by users.
Researchers further theorized that PU and PEOU will mediate the effect of external variables,
such as interface design, on behavioral intentions (Venkatesh and Bala, 2008). In addition, TAM
has gone through multiple waves of modifications. TAM2 was proposed by Venkatesh and Davis
(2000) and it incorporated additional theoretical constructs spanning social influence processes
(e.g., subjective norm) and cognitive instrumental processes (e.g., job relevance, output quality, and result demonstrability). Later, Venkatesh and Bala (2008) developed a more integrated
model –​TAM3 –​to present a complete network of the determinants of individuals’ IT adoption and use. Overall, TAM has been tested in different contexts, and has proven to be a robust
theoretical model (Wang, Chung, Park, McLaughlin, and Fulk, 2012).
The examination of consumers’ acceptance of mobile apps has been largely reliant on this
framework. For example, Kim,Yoon, and Han (2014) used TAM to investigate the antecedents of
mobile app usage among smartphone users. The results of their study indicated that four factors
have a significant influence on consumers’ attitudes towards app usage –​perceived informative
usefulness, perceived entertaining usefulness, perceived ease of use, and user review. Briz-​Ponce
and García-​Peñalvo (2015) examined mobile apps and TAM in the context of medical education
and included constructs such as PU, PEOU, social influence, facilitating conditions, self-​efficacy,
and anxiety.
The findings of these studies help marketers to have a better understanding of how and why
people adopt mobile apps, given that advertising and app sales revenues are dependent upon
adoption and usage (Gerlich, Drumheller, Babb, and De’Armond, 2015). However, researchers
have argued that although TAM helps identify the antecedents of mobile app adoption, most of
the drivers identified only describe the app itself or the sponsor of the app (i.e., the firm) and fail
to explain how the app fits into the consumer’s life (Alnawas and Aburub, 2016). Additionally,
prior research that used TAM ignored the subsequent consumer behavior after adoption such as
consumer satisfaction and purchase intentions.
Given these two factors, a stream of research has studied consumers’ adoption of mobile
apps using the “Uses and Gratifications” theory (U&G) (Katz, Blumler, and Gurevitch, 1974).
U&G theory was developed to discuss the audience’s motives for media usage. It focuses on
the audience and their role in selecting a specific type of media, based on the assumption that
media users are driven by individual needs and gratification-​seeking motives (Blumler and Katz,
1974; Krcmar and Strizhakova, 2009). U&G theory has been applied to old media contexts
such as radio and television, as well as new media such as social network sites (Wei, Lin, Lu, and
Chuang, 2015) and mobile phones (Paragas, Clara, Main, and Rahman, 2011). Originally, Katz
et al. (1974) proposed four types of benefits that an audience can derive from media usage: cognitive benefits, social integrative benefits, personal integrative benefits, and hedonic benefits. In
terms of mobile applications, previous research studies identified a different set of motives for
downloading/​using mobile apps. For instance, Lewis, Brown, and Watkins (2014) explored the
relationship between “gratifications sought” and consumers’ attitudes and behavioral intention to
download mobile apps. Gratifications identified in their research included personal productivity,
entertainment/​enjoyment, personal enjoyment, self-​improvement, status, education, and communication/​interaction with others.
Additionally, Alnawas and Aburub (2016) found four interaction-​based benefits in the context of mobile apps: learning benefits (e.g., acquiring information to increase understanding/​
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Lu Zhang
knowledge of the environment), social integrative benefits (e.g., increase communication and
make users feel more a part of their community and better citizens), personal integrative benefits
(e.g., enhance the credibility, status, and confidence of the consumer), and hedonic benefits (e.g.,
enhance aesthetic or pleasurable experiences). Interestingly, only learning benefits and hedonic
benefits are found to generate purchase intentions in relation to mobile apps. Lin et al. (2014)
surveyed 441 mobile app users and found that social benefits, immediate access and mobility,
entertainment, self-​status seeking, pursuit of happiness, information seeking, and socializing were
the primary factors driving app users’ adopting behavior and addiction to apps. Moreover, previous research integrated the Theory of Planned Behavior, the Technology Acceptance Model, and
the Uses and Gratification Theory to predict young American consumers’ mobile app attitudes,
intent, and usage (Yang, 2013). The results indicated that perceived enjoyment, usefulness, ease
of use, perceived behavioral control, and subjective norms are significant predictors of users’
attitudes and intent to use mobile apps.
In addition to TAM and U&G theory, theoretical frameworks such as personalization versus privacy (Morosan and DeFranco, 2016; Nyheim, Xu, Zhang, and Mattila, 2015), signaling
theory and regulatory focus (Shen, 2015), and theory of consumption value (Peng, Chen, and
Wen, 2014) have also been employed to study users’ acceptance of mobile apps. For instance,
Morosan and DeFranco (2016) examined hotel guests’ intentions to use mobile apps via constructs such as personalization, privacy, personal innovativeness, and involvement. The results
of their study provided evidence that consumers’ personalization and privacy perceptions can
be used to predict how consumers participate in m-​commerce in hotels. Nyheim et al. (2015)
recruited 159 Millennials and asked them to use Starbucks’ apps for 30 days before completing a
survey.Their findings suggested that (1) advertising irritation is positively related to ad avoidance,
(2) perceived personalization has a negative impact on avoidance, and (3) privacy concern is not
a significant predictor of avoidance. Table 42.3 provides a summary of research related to mobile
apps, theories employed, and constructs/​factors examined.
Table 42.3 Research on users’ intention to adopt mobile apps
Author names
Alnawas and
Aburub (2016)
To examine the effects of
benefits generated from
interaction with mobile
apps on customer satisfaction and purchase
• Learning benefits
• Hedonic benefits
• Personal integrative benefits
• Social integrative benefits
• Consumer satisfaction
• Purchase intentions
• Perceived usefulness
• Perceived ease of use
• Social influence
• Facilitating conditions
• Self-​efficacy
• Anxiety
• Reliability
• Recommendation
• Attitude toward using
• Behavioral intention to use
the new technology
Briz-​Ponce and
To verify that TAM can be
used to measure and
explain the acceptance
of mobile apps within
medical education.
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Table 42.3 (Cont.)
Author names
Ding and Chai
To understand the emotional experiences and
influences on continued
usage of mobile apps.
• Disconfirmation
• Experiential benefits
• Instrumental benefits
• Identity benefits
• Social benefits
• Negative emotions
• Arousal
• Positive emotions
• Continuance intention
Expectancy disconfirmation
theory (EDT)
Brookshire, and
Chin (2016)
To explore factors
influencing consumers’
intention to
install a mobile
• Perceived security
• Application characteristics
• Positive reputation
• Familiarity
• Desensitization
• Consumer disposition to trust
• Consumer disposition to risk
• Perceived risk
• Consumer trust
• Perceived benefit
• Intent to install
A trust-​based
making model
Ho and Syu
To understand users’
motives for using mobile
apps and degree of
after use.
• Entertainment
• Instrumentality
• Informativity
• Sociability
• Mentality
• Trendiness
• Learning
Kang (2014)
To predict use
intention of mobile
• Performance expectancy
• Effort expectancy
• Social influence
• Entertainment motivation
• Social utility motivation
• Communication motivation
• Intention
UTAUT (the
Unified Theory
of Acceptance
and Use of
Kim, Yoon, and
Han (2014)
To identify
antecedents of
mobile app usage
among smartphone
• Perceived informative
• Perceived entertaining
• Perceived ease of use
• User review
• Attitude toward app usage
• Behavioral intention to use
mobile apps
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Table 42.3 (Cont.)
Author names
Kim, Wang, and
To examine the
effects of adopting and
using a mobile app on
subsequent purchases.
• Interactivity
• Stickiness
• Purchase behavior
Lewis, Brown,
and Watkins
To explore needs that consumers expect to fulfill
through apps and their
influence on consumers’
attitudes toward downloading apps.
• Personal productivity
• Entertainment/​enjoyment
• Personal enjoyment
• Self-​improvement
• Status
• Education
• Communication with others
Lin, Fang, and
Hsu (2014)
To identify user motives to
adopt and use a particular app.
• Social benefits
• Immediate access and
• Entertainment
• Self-​status seeking
• Pursuit of happiness
• Information seeking
• Socializing
• Attitude toward apps
• Addiction toward apps
Morosan and
To examine the roles of
personalization, privacy,
and involvement on
hotel guests’ intentions
to use mobile apps.
• General privacy concerns
• App-​related privacy concerns
• Personal innovativeness
• Perceived personalization
• Involvement
• Intentions
Nyheim, Xu,
Zhang, and
Mattila (2015)
To investigate Millennials’
perceptions of personalized smartphone app
advertising avoidance.
• Privacy concern
• Perceived personalization
• Ad irritation
• Ad avoidance
• Perceived control
Peng, Chen, and
Wen (2014)
To understand factors influencing app
adoption from the
perspectives of brand
relationship and consumption values.
• Brand attachment
• Brand identification
• Perceived value
• Quality value
• Acquisition value
• Efficiency value
• Emotion value
• Intention to use branded
Theory of consumption
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Mobile apps and hospitality marketing
Table 42.3 (Cont.)
Author names
Shen (2015)
To understand the effect
of product type and
message framing on
users’ adoption of
mobile apps.
• App type
• Perceived risk
• Message framing
• Mood
• Reputation source
• Product type
• Perceived usefulness
• Attitude toward apps
• Intention to use
Signaling theory
focus theory
Wang and Wang
To examine the adoption of mobile hotel
reservation services by
considering both gain
and loss elements influencing consumers’ value
• Information quality
• System quality
• Service quality
• Technological effort
• Perceived fee
• Perceived risk
• Perceived value
• Behavioral intention
Theory of consumption
Yang (2013)
To predict young
American consumers’
mobile app attitudes,
intent and use.
• Perceived usefulness
• Subjective norm
• Perceived control
• Ease of use
• Perceived enjoyment
• Perceived expressiveness
• Attitude toward mobile apps
• Intent to use mobile apps
U&G theory
AccorHotel, 2015. Powerful distribution and revenue management solutions. Available from: www.
distribution-​and-​revenue-​management.html. [15 October 2016].
Ajzen, I., 1991.The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2),
pp. 179–​211.
Alnawas, I. and Aburub, F., 2016. The effect of benefits generated from interacting with branded mobile
apps on consumer satisfaction and purchase intentions. Journal of Retailing and Consumer Services, 31,
pp. 313–​322.
Avery, J., Dev, C.S., and O’Connor, P., 2015. Accor: Strengthening the brand with digital marketing. Boston,
MA: Harvard Business School Publishing.
Barnes, S.J., 2002.The mobile commerce value chain: Analysis and future developments. International Journal
of Information Management, 22(2), pp. 91–​108.
Basso, A., Goldberg, D., Greenspan, S. and Weimer, D., 2001. First impressions: Emotional and cognitive
factors underlying judgments of trust e-​commerce. In Proceedings of the 3rd ACM Conference on Electronic
Commerce (pp. 137–​143). New York: ACM.
Bates, B., 2004. Game Design (Second ed.). Boston, MA: Thomson.
Bellman, S., Potter, R.F., Treleaven-​Hassard, S., Robinson, J.A. and Varan, D., 2011. The effectiveness of
branded mobile phone apps. Journal of Interactive Marketing, 25(4), pp. 191–​200.
Blumler, J.G. and Katz, E., 1974. The uses of mass communications: Current perspectives on gratifications research.
(Sage annual reviews of communication research,Volume III). Beverly Hills, CA: Sage.
Downloaded By: Lund University Libraries At: 21:37 24 Oct 2017; For: 9781315445526, chapter42, 10.4324/9781315445526.
Lu Zhang
Briz-​Ponce, L. and García-​Peñalvo, F.J., 2015. An empirical assessment of a technology acceptance model for
apps in medical education. Journal of Medical Systems, 39(11), pp. 1–​5.
Bucy, E.P., 2004. Interactivity in society: Locating an elusive concept. The Information Society, 20(5),
pp. 373–​383.
Carroll, J., 2007. July.Where to now? Generating visions for mBusiness from the drivers of use. In International
Conference on the Management of Mobile Business, 2007 (ICMB 2007). IEEE.
Chen, K.Y., Hsu, Y.L. and Wu, C.C., 2012. Mobile phone applications as innovative marketing tools for
hotels. International Journal of Organizational Innovation, 5(2), p. 116. Online at http://​search.proquest.
Cheverst, K., Davies, N., Mitchell, K., Friday, A. and Efstratiou, C., 2000, April. Developing a context-​aware
electronic tourist guide: Some issues and experiences. In Proceedings of the SIGCHI Conference on Human
Factors in Computing Systems (pp. 17–​24). ACM.
Davis, F.D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology.
MIS Quarterly, 13(3), pp. 319–​340.
Ding,Y. and Chai, K.H., 2015. Emotions and continued usage of mobile applications. Industrial Management
& Data Systems, 115(5), pp. 833–​852.
Fano, A. and Gershman, A., 2002. The future of business services in the age of ubiquitous computing.
Communications of the ACM, 45(12), pp. 83–​87.
Fishbein, M. and Ajzen, I., 1975. Belief, attitude, intention and behavior: An introduction to theory and research.
Reading, MA: Addison-​Wesley.
Gao, Q., Rau, P.L.P. and Salvendy, G., 2009. Perception of interactivity: Affects of four key variables in
mobile advertising. International Journal of Human-​Computer Interaction, 25(6), pp. 479–​505.
Gerlich, R.N., Drumheller, K., Babb, J. and De’Armond, D., 2015. App consumption: An exploratory analysis of the uses & gratifications of mobile apps. Academy of Marketing Studies Journal, 19(1),
pp. 69–​79.
Gong, J. and Tarasewich, P., 2004, November. Guidelines for handheld mobile device interface design. In
Proceedings of DSI 2004 Annual Meeting (pp. 3751–​3756).
Gupta, S., 2013, For mobile devices, think apps, not ads. Harvard Business Review, 91, pp. 70–​75.
Harris, M.A., Brookshire, R. and Chin, A.G., 2016. Identifying factors influencing consumers’ intent to
install mobile applications. International Journal of Information Management, 36(3), pp. 441–​450.
Ho, H.Y. and Syu, L.Y., 2010, August. Uses and gratifications of mobile application users. In International
Conference on Electronics and Information Engineering (ICEIE), 2010 (Vol. 1, pp. V1-​315–​V1-​318). IEEE.
Hu, Y., 2011. Linking perceived value, customer satisfaction, and purchase intention in e-​
settings. In Advances in Computer Science, Intelligent System and Environment (pp. 623–​
628). Berlin,
Heidelberg: Springer.
IHG, 2015. Annual report and form 20-​F 2015. Available from:​files/​reports/​ar2015/​
index.html. [10 October 2016].
Kang, S., 2014. Factors influencing intention of mobile application use. International Journal of Mobile
Communications, 12(4), pp. 360–​379.
Kannan, P.K., Chang, A.M. and Whinston, A.B., 2001, January. Wireless commerce: Marketing issues and possibilities. In Proceedings of the 34th Annual Hawaii International Conference on System Sciences, 2001. IEEE.
Katz, E., Blumler, J.G. and Gurevitch, M., 1974. The uses and gratifications approach to mass communication.
Beverly Hills: Sage.
Kim, S.J., Wang, R.J.H. and Malthouse, E.C., 2015. The effects of adopting and using a brand’s mobile
application on customers’ subsequent purchase behavior. Journal of Interactive Marketing, 31, pp. 28–​41.
Kim, S.C.,Yoon, D. and Han, E.K., 2014. Antecedents of mobile app usage among smartphone users. Journal
of Marketing Communications, 22(6), pp. 1–​18.
Kimes, S.E., 2011. Customer perceptions of electronic ordering. Cornell Hospitality Report, 11(9), pp. 4–​18.
Kotler, P., 2000. Marketing management: The millennium edition. International edition. London: Prentice Hall.
Krcmar, M. and Strizhakova, Y., 2009. Uses and gratifications as media choice. In T. Hartman (ed.), Media
choice: A theoretical and empirical overview (pp. 53–​69). New York: Routledge.
Larivière, B., Joosten, H., Malthouse, E.C., van Birgelen, M., Aksoy, P., Kunz, W.H. and Huang, M.H., 2013.
Value fusion: The blending of consumer and firm value in the distinct context of mobile technologies
and social media. Journal of Service Management, 24(3), pp. 268–​293.
Lewis, R., Brown, K. and Watkins, B., 2014, January. Identifying gratifications sought that drive positive attitudes toward mobile apps and intent to download mobile apps: Using gender as a moderating variable.
In American Academy of Advertising. Conference. Proceedings, p. 70.
Downloaded By: Lund University Libraries At: 21:37 24 Oct 2017; For: 9781315445526, chapter42, 10.4324/9781315445526.
Mobile apps and hospitality marketing
Lin, Y.H., Fang, C.H. and Hsu, C.L., 2014. Determining uses and gratifications for mobile phone apps. In
Future Information Technology (pp. 661–​668). Berlin, Heidelberg: Springer.
Morosan, C. and DeFranco, A., 2016. Modeling guests’ intentions to use mobile apps in hotels: The roles
of personalization, privacy, and involvement. International Journal of Contemporary Hospitality Management,
28(9), pp. 1968–​1991.
Marriott International, 2015. Annual report. Available from: http://​​downloads/​
MAR/​0 x0x884644/​9 34434D3-​0 551-​4 E9D-​9 4EF-​687390A5AE6F/​2015_​AR.pdf. [10 October
Nyheim, P., Xu, S., Zhang, L. and Mattila, A.S., 2015. Predictors of avoidance towards personalization of
restaurant smartphone advertising: A study from the Millennials’ perspective. Journal of Hospitality and
Tourism Technology, 6(2), pp. 145–​159.
Paragas, F., Clara, D.Y., Main, L.T. and Rahman, N.B., 2010. Mobile telephony uses and gratifications among
elderly Singaporeans. Media Asia, 37(4), p. 215.
Peng, K.F., Chen, Y. and Wen, K.W., 2014. Brand relationship, consumption values and branded app adoption. Industrial Management & Data Systems,114(8), pp. 1131–​1143.
Picoto, W.N., Palma-​dos-​Reis, A. and Bélanger, F., 2010, June. How does mobile business create value
for firms? In 2010 Ninth International Conference on Mobile Business and 2010 Ninth Global Mobility
Roundtable (ICMB-​GMR), (pp. 9–​16). IEEE.
Rafaeli, S., 1988. From new media to communication. Sage Annual Review of Communication Research:
Advancing Communication Science, 16, pp. 110–​134.
Sangle, P.S. and Awasthi, P., 2011. Consumer’s expectations from mobile CRM services: A banking context.
Business Process Management Journal, 17(6), pp. 898–​918.
Shen, G.C.C., 2015. Users’ adoption of mobile applications: Product type and message framing’s moderating
effect. Journal of Business Research, 68(11), pp. 2317–​2321.
Skift, 2016. Hotel CEOs won’t back down when it comes to pushing direct bookings. Available
from: https://​​2016/​05/​16/​hotel-​ceos-​wont-​back-​down-​when-​it-​comes-​to-​pushing-​direct-​
bookings/​. [15 October 2016].
Speller III, T.H., 2012. The business and dynamics of free-​to-​play social-​casual game apps (Doctoral dissertation,
Massachusetts Institute of Technology). Available from: http://​​handle/​1721.1/​70824.
[15 October 2016].
Statista, 2016. Number of mobile app downloads worldwide from 2009 to 2017 (in millions). Available
from:​statistics/​266488/​forecast-​of-​mobile-​app-​downloads/​. [15 October 2016].
Stout, P.A., Villegas, J. and Kim, H., 2001. Enhancing learning through use of interactive tools on health-​
related websites. Health Education Research,16(6), pp. 721–​733.
Sundar, S.S., 2008.The MAIN model: A heuristic approach to understanding technology effects on credibility. In M.J. Metzger and A.J. Flanagin (eds.), Digital media, youth, and credibility.The John D. and Catherine
T. MacArthur Foundation Series on Digital Media and Learning (pp. 73–​100). Cambridge, MA: The
MIT Press.
Venkatesh, V. and Bala, H., 2008. Technology acceptance model 3 and a research agenda on interventions.
Decision Sciences, 39(2), pp. 273–​315.
Venkatesh,V. and Davis, F.D., 2000. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), pp. 186–​204.
Wang, B., Kim, S. and Malthouse, E.C., 2016. Branded apps and mobile platforms as new tools for advertising. The new advertising: Branding, content, and consumer relationships in the data-​driven social media era. Santa
Barbara, CA: ABC-​CLIO.
Wang, H., Chung, J.E., Park, N., McLaughlin, M.L. and Fulk, J., 2012. Understanding online community
participation: A technology acceptance perspective. Communication Research, 39(6), 781–​801.
Wang, H.Y. and Wang, S.H., 2010. Predicting mobile hotel reservation adoption: Insight from a perceived
value standpoint. International Journal of Hospitality Management, 29(4), pp. 598–​608.
Wei, H.L., Lin, K.Y., Lu, H.P. and Chuang, I.H., 2015. Understanding the intentions of users to
‘stick’ to social networking sites: A case study in Taiwan. Behaviour & Information Technology, 34(2),
pp. 151–​162.
Weiser, M., 1991. The computer for the 21st century. Scientific American, 265(3), pp. 94–​104.
Yang, H.C., 2013. Bon appétit for apps: Young american consumers’ acceptance of mobile applications.
Journal of Computer Information Systems, 53(3), pp. 85–​96.
Zhao, Z. and Balagué, C., 2015. Designing branded mobile apps: Fundamentals and recommendations.
Business Horizons, 58(3), pp. 305–​315.
Downloaded By: Lund University Libraries At: 21:37 24 Oct 2017; For: 9781315445526, chapter42, 10.4324/9781315445526.
Lu Zhang
Further reading
Ask, J., Johnson, C., Drego, V.L., Harteveldt, H.H., Mulpuru, S. and Wiramihardja, L. 2011. Mobile is not
just another channel. Forrest Research. Available from:​report/​Mobile+Is+Not+Jus
t+Another+Channel/​-​/​E-​RES58676 [15 October 2016]. (Explaining the unique attributes of mobile
phones and how marketers can leverage them to create new experiences for consumers.)
Furner, C.P., Racherla, P. and Babb, J.S., 2014. Mobile app stickiness (MASS) and mobile interactivity: A
conceptual model. The Marketing Review, 14(2), pp. 163–​188. (A discussion on how app features affect
consumers’ perceptions of interactivity.)
King,W.R. and He, J., 2006. A meta-​analysis of the technology acceptance model. Information & Management,
43(6), pp. 740–​755. (A detailed analysis of research using the TAM model.)
Krum, C., 2010. Mobile marketing: Finding your customers no matter where they are. Indianapolis, IN: Pearson
Education. (A comprehensive guide for marketers on how to integrate mobile marketing with their
existing on-​and offline marketing campaigns.)
McQuail, D., 1985. Gratifications research and media theory: four models or one. In K.E. Rosengren, L.A.
Wenner, and Palmer, P. (eds.), Media gratification research: Current perspectives (pp. 149–​167). Beverly Hills,
CA: Sage. (An introduction to U&G theory.)
Sundar, S.S., Jia, H., Waddell, T.F. and Huang,Y., 2015. Toward a theory of interactive media effects (TIME).
In S. Sundart (ed.), The handbook of the psychology of communication technology (pp. 47–​86). Chichester, UK:
John Wiley & Sons, Ltd. (Explaining how interface features affect user psychology.)
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