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Journal of Travel & Tourism Marketing

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The relevance of mobile tourism and informationtechnology: an analysis of recent trends andfuture research directions

Sai Liang, Markus Schuckert, Rob Law & Lorenzo Masiero

To cite this article: Sai Liang, Markus Schuckert, Rob Law & Lorenzo Masiero (2016):The relevance of mobile tourism and information technology: an analysis of recenttrends and future research directions, Journal of Travel & Tourism Marketing, DOI:10.1080/10548408.2016.1218403

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The relevance of mobile tourism and information technology: an analysis ofrecent trends and future research directionsSai Lianga, Markus Schuckert b, Rob Lawb and Lorenzo Masierob

aSchool of Management, Harbin Institute of Technology, 92 West Dazhi Street, Nangang District, 150001 Harbin, PR China; bSchool of Hotel& Tourism Management, The Hong Kong Polytechnic University, 17 Science Museum Road, TST-East, Kowloon, Hong Kong SAR

ABSTRACTAlthough there have been studies concerning information and communication technologiesadoption in the tourism industry, the research trends of mobile tourism (m-tourism) are stillnot very clear due to the short development time and emerging nature of the technologies. To fillthis gap, this study reviewed and analyzed articles related to online reviews of tourism andhospitality published in academic journals between 2002 and 2015. Through a keyword-drivensearch and content analysis, 92 articles are identified as relevant and classified into three topics.Our findings contribute to a better understanding of this promising research direction bypresenting the interesting classification methods used by relevant publications and their insights.This paper also discusses significant topical and methodological trends, and contributes to anoverall understanding of existing research and its limitations.

ARTICLE HISTORYReceived 26 June 2015Revised 2 June 2016Accepted 25 July 2016

KEYWORDSm-tourism; mobiletechnology; location-basedservices; applications;literature review; smarttourism

Introduction

As can be seen in recent developments in the tourismindustry and the focus of academic research, informa-tion and communication technology (ICT) and the inter-net have substantially changed the travel industry andtourism-related consumer behavior (Buhalis & Law,2008; Gretzel, Fesenmaier, & O’Leary, 2006; Lee & Hu,2005; Werthner & Klein, 1999). In addition, the impact ofthe internet and ICT is amplified when travelers areequipped with mobile technologies (Fesenmaier &Xiang, 2014; Gretzel, 2010; Lamsfus, Wang, Alzua-Sorzabal, & Xiang, 2014). The smartphone can be con-sidered a symbol of this technological superstorm; itsgrowing adoption and diffusion is driving the marketfor relevant software known as apps, short for applica-tions, (Kennedy-Eden & Gretzel, 2012). Today, smart-phones, apps, and mobile internet influence almostevery facet of everyday life, and travel and tourismhave seen dramatic changes (Kennedy-Eden & Gretzel,2012; Wang, Park, & Fesenmaier, 2012). With advancesin mobile technology, the emergence of wearables and“the internet of things” will accelerate the convergenceof mobile tourism (m-tourism) to create a social, local,and mobile technology for the travel industry. Thisinfluential combination of ICT and mobility in hospital-ity and tourism has attracted academic attention sincethe turn of the millennium (Beritelli & Schuppisser,

2006; Buhalis & Law, 2008; Gretzel et al., 2006; Lee &Hu, 2005; Tjostheim & Boge, 2001; Werthner & Klein,1999). Based on the time span involved, it is appropri-ate to conduct a review of recent research output onm-tourism in the fields of hospitality and tourism, bothfor the academic and practical value of such an exer-cise, and to indicate future research opportunities.

This article collects reviews and analyzes the aca-demic output in this field from the first relevant paperpublished in 2002 to the present. Despite its impact onthe industry and consumers, the role of m-tourism andits forms and applications in hospitality and tourismhave received limited attention. To fill the gap, thisstudy targets academic output related to m-tourism.

This study employs two approaches. First, all thescientific literature related to m-tourism is reviewed toproduce an overview of the topics that have emerged,the findings that have been made, the methods thathave been applied, and how the field has evolved interms of content. Second, the limitations of previousresearch and proposed directions for future research inthe field are analyzed, providing implications for bothresearchers and the industry. The purpose of this studyis to deliver easy access to an advanced understandingof the development of online review research in hospi-tality and tourism and an overall perspective of futureresearch efforts.

CONTACT Sai Liang tyliangsai@163.com PhD Candidate, School of Management, Harbin Institute of Technology, 92 West Dazhi Street, NangangDistrict, 150001 Harbin, PR China

JOURNAL OF TRAVEL & TOURISM MARKETING, 2016http://dx.doi.org/10.1080/10548408.2016.1218403

© 2016 Informa UK Limited, trading as Taylor & Francis Group

Methods

The methodological approach applied proceeds as fol-lows: identification of databases, identification of key-words, discussion of selected keywords, keyword searchand identification of relevant articles, discussion of rele-vant articles, and segmented content analysis of theselected articles.

In the first step, electronic databases are identifiedand selected. The downloading and data collectionwere conducted in December 2015, consulting thefour largest and most widely used electronic databases,the online search engines EBSCOhost, Google Scholar,Science Direct, and Scopus. Here, references are tracedto detect cross-citations in the articles (Law, Qi, &Buhalis, 2010). Second, keywords are identified anddiscussed. Based on the approach of Leung, Law, vanHoof, and Buhalis (2013), the following keywords arerecognized as relevant for this study: “mobile device”,“mobile technology”, “mobile application”, “apps”,“mobile service”, and “smartphone”. To narrow thefocus and ensure that the articles selected are relevantto the field of travel, tourism, and hospitality, keywordslike “tourism”, “travel”, “hotel”, “hospitality”, “destina-tion”, and “restaurant” are used to search for relevantarticles published in academic journals. This screeningprocess generated a relatively small number of papers,all of which are considered (Law, Leung, & Au, 2013;Schuckert, Liu, & Law, 2014). In the third step, fiveiteration loops of data retrieval and screening are per-formed, resulting in the identification of 92 relevantarticles published between 2002 and 2015. During thisscreening process, the abstract and keywords of eachpublication are analyzed to determine relevance to thefocus of this study. The authors then reviewed thearticles that have passed the selection process. To mini-mize any possibility of personal bias affecting the selec-tion of articles retrieved, a consensus among multipleauthors, all of whom are experienced researchers inelectronic (e)-commerce, have to be achieved (Lawet al., 2013).

In the fourth step, the content of the articles isanalyzed, examining the topical focus, the underlyingindustry or sector targeted, as well as the methodologyapplied, according to the analytical framework of Lineand Runyan (2012). Very few cases of mismatch areencountered during the grouping process. Here, acase-by-case in-depth discussion and analysis of everypaper is performed by the research team in order tosort out differences and reach an overall consensus.After the topical review, a methodological review isconducted analyzing and coding the sample source,the type of data, and the main analysis method used

in each study. The number of articles published in thesame issue of the journal is also documented.

In order to analyze the evolution of the work done,the method applied in each paper and the date of itspublication are used to segment the stream of literatureintroduced by Confente (2014).

This particular analysis is based on Berthon, Nairn,and Money’s (2003) paradigm funnel, a segmentationmethod which assigns the reviewed articles to cate-gories representing their primary purpose. Accordingto Nairn et al. (2007), level 1 of the funnel are articlesof empirical nature, while articles in level 2 addressanalytical methods and methodologies. The third levelcollects articles which are building and/or advancingtheories, whereas articles on level four compare anddiscuss ontological, epistemological, and methodicalperspectives related to mobile tourism. FollowingConfente (2014) and Breazeale (2009), a fifth level isused to collect articles which deliver a general perspec-tive and do not match any of the other levels.

In terms of chronology, it can be stated that thenumber of contributions is increasing. Based on thetrends revealed in other literature reviews, it seemsthat a peak can be expected during the next fewyears; however, the actual analysis shows that in thisresearch field, research on the topic of m-tourism isgaining in popularity and becoming more diverse(Figure 1); the number for 2015 is only a preliminaryfigure.

Topical review

As more and more customers and suppliers began toadopt ICTs for their purchase decisions and marketingstrategies, the application of emerging technologies inthe tourism industry, such as mobile and wireless tech-nology, also attracted the attention of researchers(Liang & Sun, 2014; Liu & Zhang, 2014; Zhong, Leung,Law, & Wu, 2013). Ninety-two relevant articles havebeen published in academic journals and can be classi-fied into several topical clusters. We discuss a widerange of topics in three research streams followingprevious classification methods which have been uti-lized in summarizing ICT adoption literatures (Buhalis &Law, 2008; Zhong et al., 2013). If a single paper focusedon more than one theme, the most obvious is used forclassification.

Table 1 shows the topical cluster results and alsopresents the specific nature and distribution of eachtopic. Most scholars prefer to investigate industrial con-tributions and business functions of mobile technologyin the tourism industry (47.8%), followed by the

2 S. LIANG ET AL.

relationship between mobile technology and customerbehavior, and customers’ motivation to apply mobiletechnology during travel (30.5%). Hospitality and tour-ism scholars have paid the least attention to technolo-gical innovation in the m-tourism context (21.7%).

Industry and business applications

As traditional electronic tourism intermediaries such asglobal distribution systems (GDSs) are gradually gainingacceptance by more and more travelers and travelagents, the internet has the potential to create newe-mediaries based on e-platforms such as mobiledevices, and the expected proliferation of these e-medi-aries will have a great impact on both traditionale-mediaries and future business models (Buhalis &Licata, 2002; Mistilis, Buhalis, & Gretzel, 2014). A com-mon topic in this cluster is the investigation of thestatus of m-tourism implementation, such as investigat-ing the research trends of mobile methodologies, suchas near-field communication (NFC) (Hannam, Butler, &Paris, 2014; Pesonen & Horster, 2012) as well as sum-marizing digital eras and past ICT adoption in the tour-ism industry (Buhalis & Law, 2008; Thakran & Verma,

2013; Zhong et al., 2013). Also, the contemporary pos-sibilities and challenges of such mobile technologiessuch as augmented reality and mobile recommendersystems (RSs) are summarized by such studies (Garau,2014; Gavalas, Konstantopoulos, Mastakas, & Pantziou,2014). The above mentioned studies mostly contributegeneral implications and understandings for both scho-lars and service providers facing the appearance anddevelopment of mobile technology in this industry.These implications and understandings are consideredto be necessary, especially due to the increase in boththe amount of mobile data and personal mobile deviceusage, and the widespread adoption of wireless localarea network (WLAN) solutions in recent years, whichpromotes the development of m-tourism (D’Ambra &Mistilis, 2009).

According to previous academic studies, the afore-mentioned technological innovation can have animpact on business functions in this industry(Kennedy-Eden & Gretzel, 2012; Marentakis & Emiris,2010; Mistilis et al., 2014). Thus several studies haveinvestigated the marketing implications of mobile tech-nology in the tourism industry and are mostly intendedto suggest diverse ways to utilize mobile technology asa marketing tool. For instance, Çeltek (2010) discussedthe marketing practice of mobile advergames and ana-lyzed the successful and weak areas of this emergingmobile technology as a marketing tool. Marentakis andEmiris (2010) pointed out that location-sensitive auctionapplications in the tourism industry can benefit auc-tioneers, mobile communications providers, and loca-tion-based service (LBS) providers by breaking downthe internet’s barriers and reducing communicationcosts; Pedrana (2014) investigated the business valueof LBSs and their effects on travel destinations. Latorre-Martínez, Iñíguez-Berrozpe, and Plumed-Lasarte (2014)discussed the use of image-focused social media (Flickr

Table 1. Topical clusters.Cluster Cluster description N %

Industry andbusinessapplications

The application of mobile technology inthe tourism industry and marketingimplications for service providers.

44 47.8%

Technologicalinnovation

The introduction of innovative mobile-related technology, devices, services,or applications and their effects onthe industry.

20 21.7%

Consumers anddemand

The impact of mobile technologyadoption on customer behavior; thestate of mobile device/technologyusage, preference, or acceptance andthe motivation of customers to utilizethese technologies while traveling.

28 30.5%

2 23

4

8

6

8

16 16

20

7

0

5

10

15

20

25

2002 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Figure 1. Number of articles per year.

JOURNAL OF TRAVEL & TOURISM MARKETING 3

and Instagram mainly) as marketing tools for tourismconsumption. Other marketing implications of mobiletechnologies or services, such as mobile hotel reserva-tion, social–local–mobile (SoLoMo) marketing, and NFCare also discussed in previous studies (Egger, 2013;Mistilis et al., 2014; Wang & Wang, 2010).

Apart from marketing functions, the influence ofdiverse mobile technologies on other aspects of thetourism industry have also been considered byresearchers. With the rapid growth in the number ofmobile device users and the emergence of many newapplications, our understanding of tourism travel andtraditional communication services is changed bymobile-related services (Dickinson et al., 2014; Foster,2009; Larsen, Urry, & Axhausen, 2007; White & White,2007). McCabe, Sharples, and Foster (2012) suggestedthat mobile and digital technologies are capable ofradically transforming city visit experiences, andNielsen and Liburd (2008) found that internet-basedneo-geography via mobile devices is an effective toolfor multilayered interpretation and dissemination tospecific visitor groups. In terms of virtual experience,various mobile applications have been found to haveeffects on categories ranging from verbal-based to ani-mated interactive experiences (Hyun, Lee, & Hu, 2009)and mobile tablet technology has also been utilized toevaluate the attractiveness of different nutrition label-ing formats for menus in the restaurant context (Yepes,2014). Others have also attempted to observe howmobile applications influence several areas in the tour-ism industry, such as tourism studies and monitoring(Ahas et al., 2007), tourism and city planning (Taha,2013), cultural heritage sites (Garau & Ilardi, 2014;Koukopoulos & Styliaras, 2013), sports tourism(Lamont & McKay, 2012; Lin et al., 2014), sustainablecultural contents and resources (Park & Kim, 2014),education and travel (Hsu & Lee, 2011; Etxeberria,Asensio, Vicent, & Cuenca, 2012), tourist guides, infor-mation acquisition and management planning(Albrecht, 2014; Blanco-Fernández, López-Nores, Pazos-Arias, García-Duque, & Martín-Vicente, 2011; Deliyiannis& Papaioannou, 2014; Fermoso, Mateos, Beato, &Berjón, 2015; Im, Yoon, & Lee, 2013; Kenteris, Gavalas,& Economou, 2011; Yang & Hwang, 2013), backpackerculture (Paris, 2012), and the traditional role of touristinformation centers (TICs) (Lyu & Hwang, 2015; Pan,2015).

Technological innovation

Continuous innovation improves mobile hardware, soft-ware, and network technology to provide additionalfunctions and for both tourists and service providers.

In recent decades, many mobile technologies and appli-cations have gained a powerful influence on variousaspects of the tourism industry and been pivotal forfuture technological innovation. Burgess, Sellitto, andKaranasios (2012) contribute to the evaluation ofm-tourism applications by presenting a model of infor-mation, communication, distribution, and transaction(ICDT) internet flows on mobile devices. With respectto website evaluation, one of the key areas of technol-ogy research, Stienmetz, Levy, and Boo (2013) examinethe factors influencing the overall usability of mobiledestination management organization (DMO) websites.Several studies also highlight the adoption of third-generation (3G) services (Hultkrantz, 2002), mobile tra-vel recommendation systems (Beritelli & Schuppisser,2006), positioning data (Ahas, Aasa, Roose, Mark, &Silm, 2008), and smartphone augmented reality (AR)applications (Yovcheva, Buhalis, & Gatzidis, 2012) inthis industry.

The largest proportion of studies in this area attemptto contribute to the debate about the improvementand innovation of m-tourism technology, such as elec-tronic tourist guides and mobile geospatial informationsystems (GISs) (Kenteris, Gavalas, & Economou, 2009;Reilly, Rodgers, Argue, Nunes, & Inkpen, 2006; Said,Omar, & Robert, 2009). Of all mobile-related services,technologies, and systems, recommender systemsattract the most research attention in this area.Several innovative novel recommendation systemswhich combine original engine with a mobile 3D GISarchitecture and/or allow the implementation of a loca-tion-aware front-end in the mobile device of the userare presented (Batet, Moreno, Sánchez, Isern, & Valls,2012; Noguera, Barranco, Segura, & Martínez, 2012).Related studies also contributed to the improvementof recommender systems by extending their notionthrough collaborative filtering techniques and employ-ing an innovative assessment method to investigate therelationship between contextual factors and item rat-ings (Baltrunas, Ludwig, Peer, & Ricci, 2012; Gavalas &Kenteris, 2011). The innovation of LBS is also discussed,and its design is improved by also considering both livebroadcast and online shopping (Yim, 2015).

Aiming to present and develop other innovativemobile technology, Tatsiopoulos and Boutsinas (2010)present an innovative mobile technology to serviceproviders in the tourism industry, a technology thatfacilitates tourists to share their experiences andexchange their knowledge transparently with others.Martín, De Ipiña, Lamsfus, and Alzua (2012) developan innovative platform to implement context-awaremobile services. Gil, Fraile, Ramos, Fez, and Guerri(2010) focus on the innovation of the topology of a

4 S. LIANG ET AL.

multimedia tourism service for mobile devices withbroadband, multicast, and/or broadcast access capabil-ities. Makkonen and Hokkanen (2013) focus on an inno-vative ICT application, a mobile game, and examine itsfunction in attracting tourists to Pielinen Museum inFinland. Ali and Frew (2014) aim to apply a newapproach to sustainable tourism (ST) development ofdestinations based on primary data obtained throughan online survey. To solve the problem of long waitingtimes at rides and in restaurants, a major aspect ofvisitor dissatisfaction, one study presents a new systemto mitigate suboptimal crowd distribution in real time(Brown, Kappes, & Marks, 2013).

Customers and demand

Due to the wide application of mobile technologies andtheir impact on various aspects of the tourism industry,many hospitality and tourism scholars have started totake an interest in observing customers’ usage, prefer-ences, and acceptance of mobile technology in order tounderstand their developmental status in the industry,and to investigate how these diverse technologies caninfluence customers’ travel behavior. A common topicin this area is investigation of customers’ usage ofmobile technology, mostly based on large-scale surveysor interviews (Radesky et al., 2014). For instance, con-sulting the suggestions of 2830 recent travelers, Verma,Stock, and McCarthy (2012) focus on customer prefer-ences for information searches and innovative mobileapps in the hospitality context. To provide manage-ment suggestions concerning operational strategies ofTICs, Lyu and Lee (2014) observe tourists’ heteroge-neous preferences for mobile internet devices by clas-sifying travelers according to whether they haveexperience of using TICs when traveling. Studies alsofocus on customers’ acceptance of photography viamobile devices and their perceptions of the fairness ofmobile services (Kwortnik & Han, 2011; Prideaux &Coghlan, 2010). With regard to mobile services, thepreference, acceptance, and adoption of such services,such as recommender systems, smartphone bookingservices (SBSs) and restaurant e-services are mainlyinvestigated based on primary data and empiricalmethods (Chang & Jang, 2014; Goh, Lee, Ang, & Chu,2010; Mozeik, Beldona, Cobanoglu, & Poorani, 2009; Tan& Hoe-Lian Goh, 2015). Also, Okazaki, Campo, Andreu,and Romero (2014) investigate the mixed interest tra-velers using mobile services to plan a trip, and segmentall travelers according to their planning behaviour.

The emergence and application of mobile services isgenerating a new set of mediators for tourists’ experi-ences and also rendering travel behavior inherently

dynamic and social (Lamsfus et al., 2014; Tussyadiah &Fesenmaier, 2009). Focusing on the effects of mobiletechnology and devices on tourists’ experiences andbehavior, scholars have carried out several empiricaland theoretical studies. Some pointed out that mobiledevices such as smartphones influence customerexperience by solving many information needs andhave implications for the development of mobile tech-nology in tourism (Tussyadiah, 2014; Wang, Xiang, &Fesenmaier, 2014a; Wang et al., 2012). Mobile technol-ogy and devices free customers from the need for adesktop device when they intend to seek the requiredinformation. This freedom gives customers the ability toselect how often, when, and where to create values,and allows service providers to provide information tocustomers more frequently (Anne Coussement &Teague, 2013; Dickinson et al., 2013).

Motivation, or the diverse driving factors of mobilemedia, is also a common theme that receives attentionin several studies. Using the structural equation model-ing method, Okazaki and Hirose (2009) evaluate howgender can influence customers’ habitual use of mobileinternet to seek information. The impact of personaltravel innovativeness and information privacy on theperception of potential value in location-based market-ing (LBM) services is examined by Beldona, Lin, and Yoo(2012). Using task-technology fit theories, the impact ofmotivations on consumer satisfaction has also beeninvestigated in the m-tourism shopping context (Kim,Chung, Lee, & Preis, 2015). Several scholars examine thedriving factors of customers’ acceptance of mobiledevices (Kim, Park, & Morrison, 2008; Morosan &DeFranco, 2014; Tussyadiah & Wang, 2014) and app-based mobile tour guides (AMTGs) (Lai, 2013; Peres,Correia, & Moital, 2011) for information seeking or activ-ity reservations. Additionally, the influence of custo-mers’ preferences (Kim, Ahn, & Chung, 2013) andmobile application usage (Wang, Xiang, & Fesenmaier,2014b) also attracts attention; several factors, such assystem quality, information quality, and interfacedesign, are shown to have effects on them.

Methodology review

Table 2 summarizes the methodological analysis of ourintegration. The results show that 37% of scholars usequalitative methods and that diverse quantitative meth-ods are applied in 58.7% of studies. Four researchers docombine both quantitative and qualitative methods tosolve their research problems. Our findings suggest thatconceptual as well as descriptive methods are widelyutilized for m-tourism research which does not need touse data. Structural equation modeling based on

JOURNAL OF TRAVEL & TOURISM MARKETING 5

primary data is present in 13.1% of the literaturereviewed and we found that empirical methods arenot very common in these studies.

For journals publishing articles around mobile tour-ism, 22 are hospitality and tourism journals, and 26 arejournals from industries. Table 3 lists just the 15 journalswhich publish more than one related paper, including13 hospitality and tourism journals, and two non-hospi-tality and tourism journals. It shows that scholars in thisindustry usually submit their related research to theJournal of Travel Research, Journal of Hospitality andTourism Technology, Tourism Management, the Annalsof Tourism Research, and the Cornell HospitalityQuarterly. Our findings also indicate that the journalspublishing high-quality articles focus on this topic.

Evolutional analysis of the field

Based on previous literature using paradigm funnelmethod and its adaptation for this study, we classifyour articles into five levels: level 1 (empirical researchwhich made a contribution to the application of mobiletechnology or the usage of mobile devices in the tourismindustry or m-tourism articles based on primary or

secondary data); level 2 (studies focusing on selectingor combining different research methods to solveresearch problems); level 3 (research related to the appli-cation, implementation, and validation of a theory, orstudies which use a conceptual framework to analyzean m-tourism problem, and articles which introducemobile technologies and their application in the tourismindustry on a conceptual or descriptive level); level 4(articles attempting to utilize or generate a specific inno-vative research method or theory and those which inves-tigate how innovation in mobile technology caninfluence the tourism industry); level 5 (review papersand other integration papers). As Table 4 shows, level 1and level 3 attract the most attention from scholars(39.1% respectively). Articles in level 2 account for 9.8%of the total integration, and only four articles (5.5%) areclassified as level 4. Finally, 6.5% of the articles areclassified as level 5.

Level 1: empirical research

Thirty-six articles, which account for 39.1% of our inte-gration, are segmented in this funnel. The flourishingand influential application of mobile technology andthe usage of mobile devices in hospitality and tourismhave attracted academic attention on this level since2002 (Buhalis & Licata, 2002). Articles in this level aremostly interested in utilizing a quantitative or qualita-tive method and collecting primary or secondary datato solve problems relating to m-tourism.

Articles in this level tend to collect primary data byinterview, online survey, questionnaire, and focus groupas well as retrieving secondary data online. Accordingto our integration, primary data considered the mostdirect way to obtain information on the behavior ofcustomers attracts most scholars, and only three studiessolve their problems based on secondary data(Schuckert et al., 2014). Of 32 articles based on primarydata, 13 collect data by interviewing customers oranother target group. Some use questionnaires (10 arti-cles) and online surveys (eight articles) to obtain thenecessary data. Only two scholars attempt to collectdata using a focus group. In terms of sample sources,the origins of data in this level are diverse. Nine articlesobtain data from Asian regions, such as mainland China,Hong Kong, Macau, Taiwan, Japan, and Korea. Four usedata from European regions including Spain, Finland,and the United Kingdom (UK); two from Australia; tenfrom the United States (US); and 11 use internationalsources.

In this level, both quantitative and qualitative data ana-lysis methods are used by scholars, who mostly prefer toemploy quantitative methods to process data (69.4%).

Table 2. Methodological analysis.N %

MethodQuantitativeStructural equation modeling 12 13.1Descriptive statistics 8 8.7Empirical method (regression/factors/ANOVA) 7 7.6Experiment 4 4.3Quantitative content/Sentiment analysis 3 3.3Subtotal 34 37.0QualitativeDescriptive 31 33.7Conceptual 13 14.1Narrative analysis/Case study 10 10.9Subtotal 54 58.7Hybrid 4 4.3

ANOVA: analysis of variance.

Table 3. Titles of repeat contributions to journals.Name of Journal N %

Journal of Travel Research 9 15.0Journal of Hospitality and Tourism Technology 7 11.7Tourism Management 7 11.7Annals of Tourism Research 6 10.0Cornell Hospitality Quarterly 5 8.4Current Issues in Tourism 4 6.7Personal and Ubiquitous Computing 4 6.7e-Review of Tourism Research 3 5.0Journal of Vacation Marketing 3 5.0Asia Pacific Journal of Tourism Research 2 3.3Consumer Electronics, IEEE Transactions on 2 3.3International Journal of Hospitality Management 2 3.3International Journal of Tourism Research 2 3.3Journal of Sustainable Tourism 2 3.3Tourism Management Perspectives 2 3.3

6 S. LIANG ET AL.

Structural equation modeling is the quantitative methodmost commonly used by previous studies due to the pre-valence of primary data, followed by descriptive statisticalmethods and experiment. Other quantitative methods,such as sentiment analysis, regression, or factor analysisare all used in just a very few articles. Most of the qualitativeresearch articles use only a descriptivemethod, followedbya qualitative content analysis or projective method.

There are several research themes which can besummarized in this level. The most common theme is

customers and demand, in 22 papers in this level(60.7%). Focusing on this topic, scholars mostly investi-gate customers’ motivations to use or apply mobile-related technologies and applications. Ten scholarsobserve the contribution of mobile technologies tothe tourism industry or their business function. Onlyfour articles in the empirical level aim to investigatetechnological innovation.

The information and purpose of articles in level 1 aresummarized in Table 5.

Table 4. Articles divided according to levels of the paradigm funnel.Funnel level No. of articles % of articles Authors and data of articles

Level 1:EmpiricalObservation

36 39.1 Buhalis and Licata (2002); Reilly et al. (2006),Ahas et al. (2007), Kim et al. (2008),Nielsen & Liburd (2008), D’Ambra &Mistilis (2009), Mozeik et al. (2009),Okazaki & Hirose (2009), Goh et al. (2010),Prideaux & Coghlan (2010), Hsu & Lee(2011), Kwortnik & Han (2011), Peres et al.(2011), Beldona et al. (2012), Lamont &McKay (2012), Strielkowski, Riganti, & Jing(2012), Verma et al. (2012), Brown et al.(2013), Dickinson et al. (2013), Kim et al.(2013), Lai (2013), Makkonen & Hokkanen(2013), Stienmetz et al. (2013), Yang &Hwang (2013), Albrecht (2014), Chang &Jang (2014), Lyu & Lee (2014), Mistiliset al. (2014), Lin et al. (2014), Morosan &DeFranco (2014), Okazaki et al. (2014),Radesky et al. (2014), Tussyadiah & Wang(2014), Wang, Xiang, & Fesenmaier(2014a), Kim et al. (2015), Tan & Hoe-LianGoh (2015).

Level 2:Analytical methods

9 9.8 Beritelli & Schuppisser (2006), Ahas et al.(2008), Tussyadiah & Fesenmaier (2009),Çeltek (2010), Paris (2012), Wang et al.(2012), Yepes (2014), Lyu & Hwang (2015),Pan (2015).

Level 3:Specific theories

36 39.1 Hultkrantz (2002), Larsen et al. (2007), White& White (2007), Foster (2009), Hyun et al.(2009), Kenteris et al. (2009), Said et al.(2009), Marentakis & Emiris (2010),Tatsiopoulos & Boutsinas (2010), Blanco-Fernández et al. (2011), Gavalas & Kenteris(2011), Kenteris et al. (2011), Batet et al.(2012), Etxeberria et al. (2012), Kennedy-Eden & Gretzel (2012), Martín et al. (2012),McCabe et al. (2012), Noguera et al.(2012), Yovcheva et al. (2012), AnneCoussement & Teague (2013), Egger(2013), Im et al. (2013), Koukopoulos &Styliaras (2013), Taha (2013), Deliyiannis &Papaioannou (2014), Dickinson et al.(2014), Garau (2014), Garau & Ilardi(2014), Lamsfus et al. (2014), Latorre-Martínez et al. (2014), Park & Kim (2014),Pedrana (2014), Tussyadiah (2014), Wang,Xiang, & Fesenmaier (2014b), Fermosoet al. (2015), Yim (2015).

Level 4:Cross assumption

5 5.5 Wang & Wang (2010), Gil et al. (2010),Baltrunas et al. (2012), Burgess et al.(2012), Ali & Frew (2014).

Overview 6 6.5 Buhalis & Law (2008), Pesonen & Horster(2012), Thakran & Verma (2013), Zhonget al. (2013), Gavalas et al. (2014),Hannam et al. (2014).

Sum 92 100

JOURNAL OF TRAVEL & TOURISM MARKETING 7

Table 5. Articles in level 1 of the funnel.Authors Year Purpose

Buhalis, D., Licata, M. C. 2002 Investigates and summarizes experts’ opinions on the future of both new andtraditional e-mediaries in the face of emerging and flourishing e-platformsincluding the internet, interactive digital television, and mobile devices.

Reilly, D., Rodgers, M., Argue, R., Nunes, M., Inkpen, K. 2006 Provides a mixed-media approach by combining paper-based maps with onlineguide resources to showcase existing limitations of mobile devices.

Ahas, R., Aasa, A., Mark, Ü., Pae, T., Kull, A. 2007 Based on a mobile positioning data set with anonymous roaming data and using asocial positioning method, this study analyzes the seasonality of foreign tourists’space consumption in Estonia.

Kim, D. Y., Park, J., Morrison, A. M. 2008 Examines the factors influencing tourist acceptance of mobile devices.Nielsen, N. C., Liburd, J. J. 2008 Explores the potential use of available geographic data in tourist mobile

communication.D’Ambra, J., Mistilis, N. 2009 Investigates how visitor information centers can meet tourists’ needs facing a

changing information infrastructure, and the main driving factors in thedevelopment of mobile wireless services.

Mozeik, C. K., Beldona, S., Cobanoglu, C., Poorani, A. 2009 Evaluates consumers’ acceptance of restaurant e-services regarding devicesincluding conventional lap-tops/desk devices, and mobile handhelds.

Okazaki, S., Hirose, M. 2009 Identifies the effect of satisfaction with PC Internet and with traditional media onthe habitual use of mobile internet.

Goh, D. H., Ang, R. P., Lee, C. S., Lee, C. K. 2010 Investigates tourists’ preference for selective mobile services according to a surveyas well as a focus group.

Prideaux, B., Coghlan, A. 2010 This study investigates the photographic habits, using mobile phones or cameras, ofvisitors to the Great Barrier Reef (Australia).

Hsu, L., Lee, S. N. 2011 Investigates tourists’ learning of English phrases using mobile phone technologybased on an experiment with 50 tourism students in Taiwan.

Kwortnik, R. J., Han, X. 2011 By comparing hotel services to mobile phone services, this study aims to investigatethe effect of guest perceptions of service fairness on their loyalty in a lodgingcontext.

Peres, R., Correia, A., Moital, M. 2011 Observes the factors which can influence tourists’ intention to use mobile electronictourist guides (METG) in order to understand tourists’ acceptance of innovativeinformation technologies.

Beldona, S., Lin, K., Yoo, J. 2012 Examines the impact of personal travel innovativeness, information privacy, and thetype of delivery method (pull versus push) on the perception of potential value inlocation-based marketing (LBM) services programs.

Lamont, M., McKay, J. 2012 Suggests how sports tourism research benefits from the sociological perspective ofpostmodernism by focusing on processes of mobile subjectivities.

Strielkowski, W., Riganti, P.; Jing, W. 2012 Assesses residents’, tourists’, and other stakeholders’ preferences for e-servicesbased on the results from 24 focus groups held in three European cities.

Verma, R., Stock, D., McCarthy, L. 2012 Summarizes internet search preferences and mobile device usage based onquestionnaires completed by 2830 recent travelers.

Brown, A., Kappes, J., Marks, J. 2013 A novel method is proposed to solve the problems of long waiting times at ridesand in restaurants by offering visitors well-timed incentives and information onmobile devices.

Dickinson,J. E., Filimonau, V., Cherrett, T., Davies, N., Norgate,S., Speed, C., Winstanley, C.

2013 Examines the role played by time in destination-based travel behavior andinvestigates the development of mobile technology by delivering uniquepersonalized information to users referenced to their current location in bothspace and time.

Kim, J., Ahn, K., Chung, N. 2013 Explores the factors which impact upon the intention of mobile device users andtheir perceptions of usage.

Lai, I. K. 2013 This study aims to identify antecedents and determinants affecting travelers’acceptance of an app-based mobile tour guide (AMTG).

Makkonen, T., Hokkanen, T. J. 2013 Tests the attraction of a mobile game which is one of the innovative informationand communication technology (ICT) applications used to encourage travelers tovisit Pielinen Museum in Lieksa, a peripheral town in Eastern Finland.

Stienmetz, J. L., Levy, S. E., Boo, S. 2013 Empirically investigates the usability of mobile destination marketing organizations ’(DMOs) websites.

Yang, W. S., Hwang, S. Y. 2013 Develops a cost-effective travel recommendation system to provide travelrecommendations based on tourists’ ratings.

Albrecht, J. N. 2014 Proposes the use of micro-mobility patterns as well as service blueprints in visitormanagement planning and identifies the potential of mobile GPS units to obtainmore detailed information.

Chang, E. S. C., Jang, J. Y. T. 2014 Investigates millennial mobile users’ adoption situation of smartphone bookingservices to purchase tourism products.

Lin, K. C., Chang, L. S., Tseng, C. M., Lin, H. H., Chen, Y. F.,Chao, C. L.

2014 Develops and introduces an APP for tourism promotion and energy expenditure (EE)monitor.

Lyu, S. O., Lee, H. 2014 Utilizes the stated preference choice method (SPCM) to provide implications to helptourism organizations develop feasible operational strategies for touristinformation centers (TICs).

Mistilis, N., Buhalis, D., Gretzel, U. 2014 Explores future e-destination marketing from Australian tourism stakeholdernetwork perspectives.

Morosan, C., DeFranco, A. 2014 Examines the manner in which system beliefs (i.e. usefulness, ease of use),subjective norms, and facilitating conditions influence club members’ attitudesand intentions to use mobile devices

(Continued )

8 S. LIANG ET AL.

Level 2: analytical methods

The articles in this level represent 9.8% of the total; theymainly focus on the selection of research methods orthe comparability of results obtained from mixed meth-ods (Table 6). Several studies in this level utilize bothqualitative and quantitative methods. Beritelli andSchuppisser (2006) summarizes seven areas of qualita-tive and quantitative research methods to exploremobile travel recommendation systems and presentsthe limitations of their application in a real-life environ-ment. Combining qualitative and quantitative contentanalysis is common in the studies in this level(Tussyadiah & Fesenmaier, 2009; Wang et al., 2012).For example, Wang et al. (2012) examine mediationmechanisms of smartphones on tourists’ experienceby combining and comparing the results from qualita-tive and quantitative content analysis methods. Mixedquantitative analysis methods are also widely used byscholars, who focus on m-tourism studies due to theneed to decide whether the quantitative method theyselected is suitable (Ahas et al., 2008; Lyu & Hwang,2015; Pan, 2015; Paris, 2012; Yepes, 2014). For instance,Lyu and Hwang (2015) develop empirical models and

compare the results of ordinary least squares (OLS) andTobit model estimations in order to choose a moreappropriate empirical method to examine the impactsof recent rapid changes caused by the wide usage ofmobile devices in the information communicationenvironment. Others in this level use mixed qualitativemethods. Çeltek (2010) observes the marketing practiceof mobile advergames in the tourism industry usingstrengths, weaknesses, opportunities, and threats(SWOT) analysis and qualitative content analysis.

In terms of the data type of the nine articles in thislevel, five utilize secondary data, and four use primarydata. Two papers obtain their primary data throughonline surveys, and only one scholar uses question-naires or adapts the type of interview. Data samplesare mostly taken from international sources. Just onearticle collects data, from Korea, Switzerland, and theUS. In terms of research theme, five articles in this levelcan be summarized as focusing on industry and busi-ness applications to investigate how m-tourism tech-nologies can have effects on the tourism industry.Another four articles focus on technological innovationas well as customers and demand.

Table5. (Continued).

Authors Year Purpose

Okazaki, S., Campo, S., Andreu, L., Romero, J. 2014 Classifies Spanish tourists into different segments and analyzes the differences intheir mobile internet services usage.

Radesky, J. S., Kistin, C. J., Zuckerman, B., Nitzberg, K., Gross,J., Kaplan-Sanoff, M., Augustyn, M., Silverstein, M.

2014 Examines the usage of mobile devices by caregivers and children for the purpose ofcaregiver–child interaction during meals in fast-food restaurants.

Tussyadiah, I. P., Wang, D. 2014 Explores the factors that drive tourists’ inclination to adopt push recommendationsfrom mobile devices.

Wang, D., Xiang, Z., Fesenmaier, D. R. 2014 Analyzes the factors driving the use of smartphones using qualitative methods.Kim, M. J., Chung, N., Lee, C. K., Preis, M. W. 2015 Investigates the impact of motivations (value, enjoyment, time saving, and mobility)

on consumer satisfaction by applying contingency and task-technology fittheories in the m-tourism shopping context.

Tan, E. M., Hoe-Lian Goh, D. 2015 This study aims to find out the users’ preference for social media information bymultiple contexts and tasks.

Table 6. Articles in level 2 of the funnel.Authors Year Purpose

Beritelli, P., Schuppisser, M. 2006 Tests pilot acceptability, usability, and market potential of mobile travel recommendation systems based ona trial case of St. Moritz, Switzerland.

Ahas, R., Aasa, A., Roose, A., Mark, Ü.,Silm, S.

2008 Introduces the applicability of passive mobile positioning data in studying tourism.

Tussyadiah, I. P., Fesenmaier, D. R. 2009 This study aims to observe the function of online travel videos as mediators of tourist experiences.Çeltek, E. 2010 Focuses on mobile advergame practices in the tourism industry, this paper provides an understanding of

the qualities and potentials of the mobile advergame as an advertising and marketing tool.Paris, C. M. 2012 Using a mixed-analysis method, this paper examines potential cultural divergence of flashpackers, who

represent an emerging subculture in backpacker culture, and the application of mobile technology in thisculture.

Wang, D., Park, S., Fesenmaier, D. R. 2012 Investigates travelers’ usage of smartphones (and associated applications) to explore mediation mechanismsof smartphones.

Yepes, M. F. 2014 Examines the effects of five different menu nutrition labeling formats for attractiveness, perceived influence,and actual influence on students’ food choices using mobile tablet technology.

Lyu, S. O., Hwang, J. 2015 Presents implications for TICs on how to respond to new demands for travel information due to the usageof mobile devices.

Pan, B. 2015 Explores the clickthrough rates (CTRs) of several published clickthrough reports and investigates the CTRs ofwebpages of DMOs in different ranks of different properties (web, image, and mobile searches) on asearch engine.

JOURNAL OF TRAVEL & TOURISM MARKETING 9

Level 3: specific theory

As mobile technology and mobile devices are emergingtechnologies, only limited numbers of persons areaccustomed to using them when traveling. The limita-tion of data may lead to large numbers of conceptual,descriptive, and theoretical articles emerging. There arethus quite a large proportion of studies in level 3, whichaccount for 39.1% of the integration (Table 7). Wesummarize articles in this level as those related totheoretical generative mechanisms or the applicationof a specific theory, such as adaptive structuration the-ory (Wang, Xiang, & Fesenmaier, 2014b). Conceptualarticles or studies which have made a contribution tothe introduction of a specific mobile technology and itsapplication in the tourism industry based on descriptivemethods and without data are also integrated in thislevel.

The conceptual and theoretical articles are mostlydistributed in the topic of industry and business appli-cations (58.8%). Four papers investigate the effect ofmobile applications on travelers’ behavior and experi-ence, thus falling into the area of customers anddemand. Technological innovation is the focus of fourother papers, which use specific theories or conceptualframeworks.

Level 4: core assumptions

There are four articles in this level, which account for5.5% of our integrations (Table 8). Articles in this levelmainly focus on explaining particular conceptual orontological issues. One of them proposes and tests anew research model to examine the effect of custo-mers’ value perceptions on intention to adopt mobilehotel reservation (MHR) services (Wang & Wang, 2010).Burgess et al. (2012) develop a new theoretical modelof ICDT internet flows on mobile devices, and Ali andFrew (2014) treat ICT as an innovative approach for STdevelopment of destinations.

Level 5: overview articles

Five articles are assigned to this level, not only reviewpapers related to m-tourism but also papers whoseresearch purpose is to summarize or integrate previousresearch on the development of m-tourism services,application, or technology (6.5%) (Table 9). Two papersin the funnel are review papers which analyze theliterature on ICT based on English and Chinese aca-demic sources (Buhalis & Law, 2008; Zhong et al.,2013). The others are mostly intended to review orsummarize the development process or the progress

of a specific research direction in m-tourism. Forinstance, Pesonen and Horster (2012) and Hannamet al. (2014) integrate previous research concerningNFC technology and mobile methodologies. Thakranand Verma (2013) comprehensively categorize thetime between the 1960s and the present into fourdigital eras and present development trends in onlinedistribution channels for the hospitality and tourismindustry.

Discussion and implications

With the flourishing and influential application ofe-commerce and e-platforms, there is no doubt thatmore and more mobile technologies, devices, applica-tions, and services will emerge and be applied in thehospitality and tourism industry. Hospitality and tour-ism scholars will pay more attention to this directionand carry out more studies. It is therefore necessary toutilize an innovative method to summarize previousstudies in order to more conveniently provide research-ers and marketers with a deeper understanding ofmobile technology and its application in this industry.Future studies can be easily integrated into the presentintegration.

The paradigm funnel is a method we are employingin the evolutional analysis of the field part to summar-ize how previous m-tourism studies analyze theirresearch problems. This technique represents an effec-tive way for researchers to both understand previousresearch trends and summarize future related studiesinto a present integration.

The paradigm funnel in the present study suggeststhat the majority of studies focus on solving problemsvia empirical observation and data integration (level 1),as well as conceptual frameworks or theory (level 3)when data are not sufficient or it is difficult to obtainthem. We also summarize the research trends of articlesin level 1 and level 3 and present the data types,sample sources, and research methods of the articlesin level 1 which are based on data. By reading articles inlevel 1, researchers and marketers can convenientlyunderstand the trends of empirical studies in thisresearch direction. Researchers can also decide theresearch theme, sample source, data type, and researchmethod of their future studies according to the pre-vious integration. Articles in level 3 seem to be morecritical for researchers who are interested in this direc-tion. With an understanding of the development ofmobile technologies and customers’acceptance ofthem, it is easier to start a new research project byemploying data to test theories or conceptual frame-works. One can also follow descriptive studies intended

10 S. LIANG ET AL.

Table 7. Articles in level 3 of the funnel.Authors Year Purpose

Hultkrantz, L. 2002 Provides institutional frameworks to explore the role of 3G services in future touristconsumption.

Larsen, J., Urry, J., Axhausen, K. W. 2007 Analyzes various transformations of tourism caused by “time–space compressing”technologies and the mobilities of labor markets, higher education, family life,migration, and diasporic movement.

White, N. R., White, P. B. 2007 Defines “home” and “away” in relation to the regular contact made possible by mobilecommunication services.

Foster, M. D. 2009 Analyzes how camera-phones, within the broader context of cell phone (keitai) culture inJapan, alter the way tourist sites and events are experienced, recorded, and shared.

Hyun, M. Y., Lee, S., Hu, C. 2009 Conceptualizes virtual tourism in the mobile context and explores the typology of virtualexperience through two dimensions: vividness and interactivity.

Kenteris, M., Gavalas, D., Economou, D. 2009 Presents the design and implementation issues of a mobile tourism research prototype.Robert, L. 2009 Mobile city-tourism-based case to improve the effectiveness of data storage and data

access by tourists.Marentakis, C., Emiris, D. 2010 Proposes a conceptual architecture for the development of an auction business-to-

consumer marketplace which has a number of stakeholders beyond sellers, likeauctioneers and mobile communications providers.

Tatsiopoulos, C., Boutsinas, B. 2010 Introduces an innovative technology to automatically exchange the knowledge ofpotential tourists with other users who have the same or similar interests and make useof it via mobile devices.

Blanco-Fernández, Y., López-Nores, M., Pazos-Arias, J.J., García-Duque, J., Martín-Vicente, M.

2011 Introduces an interactive application (TripFromTV+) that provides tailor-made touristpackages, to help viewers to decide what to do and what to visit during a trip.

Kenteris, M., Gavalas, D., Economou, D. 2011 Examines a mobile application enhancing the tourism experience by applying a tool,allowing for the adaptation of personalized web content, transferred to a mobileapplication hosted at users’ mobile device.

Gavalas, D., Kenteris, M. 2011 Extends the traditional notion of travel recommender systems by both applyingcollaborative filtering techniques and considering contextual information.

Batet, M., Moreno, A., Sánchez, D., Isern, D., Valls, A. 2012 Presents a novel recommendation system, Turist@, to address the issue of how to providepersonalized recommendations of cultural and leisure activities for tourists at thedestination.

Etxeberria, A. I., Asensio, M., Vicent, N., Cuenca, J. M. 2012 Discusses two main uses for mobile devices, which are augmented reality (AR) andgeocaching games involving global positioning system (GPS) equipment.

Kennedy-Eden, H., Gretzel, U. 2012 Provides a conceptual framework for understanding differences and similarities of theclassifications of mobile applications (apps) in tourism to present insights into appdevelopment trends.

Martín, D., de Ipiña, D. L., Lamsfus, C., Alzua, A. 2012 Suggests an innovative Cloud-based platform which contains several wizards in order tofacilitate management of context data by non-technical users to ease the developmentof context-aware mobile services.

McCabe, S., Sharples, M., Foster, C. 2012 Conceptually analyzes the effect of scenario-based design on tourism destinationstakeholders.

Noguera, J. M., Barranco, M. J., Segura, R. J.,Martínez, L.

2012 Presents a novel mobile recommendation system which combines a hybridrecommendation engine and a mobile 3D geographic information system (GIS)architecture.

Yovcheva, Z., Buhalis, D., Gatzidis, C. 2012 Provides an investigation of current smartphone AR applications, outlining tourism-relateddomain-specific design challenges in developing a better understanding of the designspace for smartphone context-aware AR applications for tourists.

Coussement, A. M., Teague, T. J. 2013 Conceptualizes a framework to argue that mobile customers are starting to change thedynamics of the relationship between the hospitality entity and the customer throughuse of the internet and migrating to the present use of mobile technology.

Egger, R. 2013 Introduces the benefit and future applications of near-field communication (NFC), which iscurrently considered one of the most promising mobile technologies in the tourismindustry.

Im, D., Yoon, H., Lee, J. 2013 Analyzes and compares popular apps which contain information on the unique resourcesthat the regions have, such as scenery, biology, history, culture, and narratives.

Koukopoulos, D., Styliaras, G. 2013 Presents a trustworthy commercial multimedia guiding system in smartphones for cultureand heritage sites and attractions.

Taha, D. S. 2013 Describes the influence of social networks on tourism and city planning through the pastdecade and pinpoints its contributions and constraints.

Deliyiannis, I., Papaioannou, G. 2014 A new open framework is developed to improve visitors’ experience and present targetedinformation in a personalized audiovisual interactive manner on mobile devices.

Dickinson, J. E., Ghali, K., Cherrett, T., Speed, C., Davies,N., Norgate, S.

2014 Reviews the usage of smartphone app functionalities by domestic tourism travel domain,then examines the mediator effect of smartphone on tourism travel.

Garau, C. 2014 Discusses the actual possibilities, challenges, as well as benefits of AR in the field ofcultural heritage.

Garau, C., Ilardi, E. 2014 Simulates a prototype by allowing uses to obtain tourist paths both online and on mobiledevices to provide audio–video content to create a tour of the local heritage.

Lamsfus, C., Wang, D., Alzua-Sorzabal, A., Xiang, Z. 2014 This article proposes a conceptual framework for the structural and fundamental propertiesof context and provides implications for the design of mobile systems.

Latorre-Martínez, M. P., Iñíguez-Berrozpe, T., Plumed-Lasarte, M.

2014 Analyzes how image-focused social media (Flickr and Instagram mainly) perform a marketstudy of tourism consumption.

(Continued )

JOURNAL OF TRAVEL & TOURISM MARKETING 11

to introduce new m-tourism technology by investigat-ing customers’ acceptance of and preference for tech-nology or how its emergence and application impactsupon the tourism industry.

Studies in level 2 and level 4 pay more attention tothe selection, combination, and innovation of researchmethods, and thus can help researchers to understandmainstream and innovative research methods in thisdirection, and to select more appropriate methods intheir own future study. Review studies (level 5) repre-sent an effective way for scholars and marketers toobtain a preliminary understanding of this researchdirection since these articles summarize the researchtrends of a specific direction.

We also summarize the research themes andresearch methods of our integration and combinethese classification methods with the aforementionedparadigm funnel segmentation to open a different the-oretical and practical perspective. Scholars and practi-tioners can conveniently attain a better understandingof the effect of diverse mobile applications on variousaspects of the hospitality and tourism industry, innova-tive mobile technologies, the relationship between theadoption of mobile technology and customer behavior,the usage situation, and the motivation for customersto employ mobile technologies based on differentmethodologies by combining our topical classificationmethod and the paradigm funnel method. Future

Table7. (Continued).

Authors Year Purpose

Park, M. K., Kim, J. Y. 2014 Discusses the values of developing smartphone apps based on GIS to connect sustainablecultural contents and resources with public art.

Pedrana, M. 2014 Investigates the definition of location-based services (LBSs) and their effect on business ingeneral and tourism destinations in particular. This study also observes how LBS may beuseful for all tourism services.

Tussyadiah, I. P. 2014 Reviews the literature on different disciplines relevant to tourism and utilizes the processof designing for mobile-mediated tourism experiences as a case. This paper presents atheoretical framework for the practice of experience design.

Wang, D., Xiang, Z., Fesenmaier, D. R. 2014 Based on adaptive structuration theory, this study builds a conceptual framework toidentify spillover effects of smartphone use in everyday life into travel.

Fermoso, A. M., Mateos, M., Beato, M. E., Berjón, R. 2015 Introduces a mobile tourism application working as a tourist guide for citizens to combineweb of data with open data from a public institution.

Yim, J. 2015 Discusses a new design of an LBS system for local area tourism which has the ability tointegrate information around live broadcast and online shopping.

Table 8. Articles in level 4 of the funnel.Authors Year Purpose

Gil, A., Fraile, F., Ramos, M., Fez, I.,Guerri, J. C.

2010 Presents the topology of a multimedia tourism service that targets mobile devices equipped with broadbandand either multicast or broadcast access capabilities.

Wang, H. Y., Wang, S. H. 2010 Presents a new research model capturing both gain and loss elements influencing the effect of individual valueperceptions on behavioral intention to adopt mobile hotel reservation (MHR) services.

Baltrunas, L., Ludwig, B., Peer, S.,& Ricci, F.

2012 Applies a new approach which simulates contextual situations to more easily capture data regarding how thecontext influences user ratings for assessing and modeling the relationship between contextual factors anditem ratings.

Burgess, S., Sellitto, C., Karanasios, S. 2012 This article theoretically classifies online m-tourism applications according to Angehrn’s four virtual “spaces” toassess mobile applications according to information attributes.

Ali, A., J. Frew, A. 2014 Conceptualizes ICT as an innovative approach to solving some of the ailments of ST.

Table 9. Articles in level 5 of the funnel.Authors Year Purpose

Buhalis, D., Law, R. 2008 Reviews articles on e-tourism published in the past 20 years, analyzes future development trends of e-tourism, and demonstrates critical changes that will affect the structure of the tourism industry.

Pesonen, J., Horster, E. 2012 Reviews research on near-field communication (NFC) technology and segments them into differenttopics. This paper also reviews current and potential applications of NFC in tourism based on existingcase studies.

Thakran, K., Verma, R. 2013 Summarizes four digital eras in the travel and tourism domain since the 1960s and presents some of theimportant upcoming trends in online distribution channels for the hospitality and tourism industry.

Zhong, L., Leung, D., Law, R., Wu, B. 2013 Integrates Chinese-language literature focusing on e-tourism in the past 17 years, presenting the researchtrends and authors’ contributions to this literature.

Gavalas, D., Konstantopoulos, C.,Mastakas, K., Pantziou, G.

2014 Reviews the state-of-the-art in the field, proposing a classification of mobile tourism recommendersystems (RSs) and providing insights into their services offered.

Hannam, K., Butler, G., Paris, C. M. 2014 Presents a conceptual overview of tourism mobilities and examines mobile methodologies for tourismresearch.

12 S. LIANG ET AL.

studies can build upon the present study by adding andsummarizing future relevant articles into our integra-tion by deciding on the classification of articles and addthem to the corresponding table. Also, researchers canapply this innovative method to other topics and direc-tions in the hospitality and tourism industry.

Conclusions and limitations

This paper reviews 92 articles related to m-tourismpublished between 2002 and 2015 using the paradigmfunnel method, which classifies articles into differentfunnels and then summarizes the research trends ofeach funnel. This study will help researchers and practi-tioners to understand the research trends of bothempirical and conceptual studies. By reading articlesin level 3, scholars can easily identify conceptual andtheoretical research trends, and then carry out theirstudy on the basis of relevant theory and conceptualframeworks. When they need to select a suitableresearch method, they can simply consult the articlesin level 2 and level 4. Integration in level 1 will also havean effect on the process of obtaining and generatingdata. This study is also useful for practitioners in thetourism industry; it can help them understand clearlythe development of diverse mobile technologies,devices, applications, and services as well as their appli-cation to and effect on the tourism industry, thus pro-viding useful guidance on how to face these changes.

Mobile tourism is an emerging field and will gainacademic attention with the increasing number ofapplications and variety of mobile-related devices(smartphones, glasses, or other wearables), technology,and services in this industry. However, there are alsosome limitations in present articles while several pro-mising research trends can be presented to furtherresearch.

First, a very large proportion of studies are usingdescriptive methods and are based on researchers’ sub-jective judgment, especially regarding themes concern-ing the application and innovation of mobiletechnology. Many studies concentrate on the introduc-tion of a new technology, device, or service relating tomobile tourism and are rather descriptive, but mayprovide insights into related technologies from amacroscopic perspective. However, those studies deli-ver a subjective assessment rather than empirical data.In addition, most of the studies show a limited knowl-edge of computer language and/or programdevelopment.

Second, work related to conceptual frameworks aswell as work on related theories around mobile technol-ogy application shows a lack of consumer-related studies.

Especially the appropriate data collection seems to be achallenge since many innovations did not disseminateenough to be widely promoted, accepted, and used bycustomers. However, much theoretical and conceptualresearch is needed to explore the influence of consumerbehavior, marketers, and/or the industry.

Finally, in all empirical studies in our analysis the mostcommon methods to collect data are primary data collec-tion via interview, questionnaire, online survey, and/orfocus group. The use of secondary data sources seemslimited and the proposed use of large and interdisciplin-ary data sets (“big data”) has not taken place yet as wellas consumer-centric studies, panel tests, or the analysis ofprocesses, data collection, and analysis methods found inneighboring disciplines like software engineering orlogistics. The focus on booking behavior and satisfactionof customers booking online with those who book viamobile devices as well as how the design of apps canaffect the satisfaction of customers booking via smart-phones may be another interesting area.

The main limitation of this paper is the fact thatthere are only 92 related papers in our integration,which is a rather small sample. This is because m-tour-ism is a relatively new phenomenon. However, we areconfident that there will be more publications in thefuture. Also, we only focused on English-language arti-cles, neglecting articles in other languages and chaptersin books and conference proceedings. Further studiescan carry out more comprehensive investigations andcombine their articles with our integration.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by a grant from the The Hong KongPolytechnic University [Grant Number 1-ZE3K].

ORCIDMarkus Schuckert http://orcid.org/0000-0003-1912-8672

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