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https://doi.org/10.20867/thm.29.2.2

Mapping the research trends on social media in the hospitality sector from 2010 to 2020

Eunjung Kim orcid id orcid.org/0000-0003-2697-309X ; (Corresponding Author) Edith Cowan University School of Business and Law 270 Joondalup Drive, Joondalup WA 6027, Australia
Alexander Rolfe Best orcid id orcid.org/0000-0003-2097-2547 ; Edith Cowan University School of Business and Law 270 Joondalup Drive, Joondalup WA 6027, Australia
Kijung Choi ; William Angliss Institute Faculty of Higher Education 555 La Trobe Street, Melbourne, VIC 3000, Australia


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Sažetak

Purpose - This study undertakes a systematic review of the literature to gain insight into
existing studies on hospitality in social media and provide an update on current trends and
themes in scholarship.
Design - This study employs the systematic literature review to identify, evaluate, and
synthesize the existing literature.
Methodology - A total of 165 papers published between 2010–2020 were examined using
content analysis and Leximancer.
Approach - This review uses a hybrid review structure that incorporates structured reviews
and narrative elements supported by Leximancer analysis.
Findings - The review highlights the theories and methods used, research fields and
perspectives, and key research topics in the hospitality industry, showing a lack of engagement
with theories, the use of a dominant theoretical approach (eWOM), and the use of quantitative
research methods primarily to analyze content data. Changes in research trends are evident to
keep pace with increasing social media data and respond to the needs of different industries.
Originality - This study contributes by also identifying several research gaps and provide
future scholarly endeavors.

Ključne riječi

Social media Hospitality; Literature review; Research trend; Leximancer; Content analysis

Hrčak ID:

300907

URI

https://hrcak.srce.hr/300907

Datum izdavanja:

27.4.2023.

Posjeta: 487 *




INTRODUCTION

The importance of social media in the wider hospitality industry has evolved from novelty to necessity. The changing attitude toward social media within the industry is evidenced by growing scholarly attention on the technology, in both quantity and scope. Earlier works on social media use in the hospitality industry had focused on the potential of the “relatively new” technology and the eccentricities of its disruptive nature and capacity (Kasavana et al., 2010, p. 79). Understandings of social media in hospitality has since evolved to the point where studies are utilizing big data and analytical approaches (e.g., Jimenez- Marquez et al., 2019; Lamest & Brady, 2019). However, there is scope to better understand the breadth of the literature, and resultingly what actors are doing with social media within the hospitality industry. It is appropriate, therefore, to periodically review the hospitality literature pertaining to social media and provide an accurate assessment of current trends.

Key reviews of literature examining the use of social media in the hospitality and tourism industries have included: Lu and colleagues’ (2018) encapsulation of 105 works between 2004 and 2014, and a content analysis by Leung et al., (2013) of studies between 2007 and 2011, with both papers focusing on tourism and hospitality. Lu et al., (2018) reported that to the year 2014, the state of hospitality social media research was still developing as evidenced by several research gaps. Apparent gaps in the literature were also observed by Leung et al., (2013), who added that social media use presented strategic and competitive potential for tourism operators. These papers serve an adequate purpose in investigating the broad application of social media within the tourism and hospitality industries, however, given the evolution of social media in the second half of the 2010s, it is necessary to continue to update this knowledge. Further, it would benefit the hospitality industry to undertake a systematic review of literature on social media specifically within this sphere of knowledge.

It is key for scholarship to periodically update the consensus among the literature. This is especially true for the topic of social media, given it is a disruptive and rapidly evolving technology, which has maintained broad application and reach within the hospitality industry. Thus, this study aims to fulfil the need for current understandings to be presented by applying a systematic approach to collecting the literature and employing Leximancer to analyze the state of research, specifically over the decade from 2010 to 2020. Utilizing Leximancer allows for the identification of concepts within the selected literature, enhancing the information which the review can provide (Cretchley et al., 2010). By adopting a systematic approach, in this manner, this study provides the grounds for periodic comparative assessments of social media use in the hospitality to be undertaken, whilst also providing an update on the current trends and themes of the scholarship. Specifically, this review is differentiated by its intentions to provide both sound structured review data whilst also utilizing Leximancer to enable analysis of current and emergent research themes.

METHODS

To provide a comprehensive update on the research state of social media use in the hospitality sector, this study employs the systematic literature review methodology to identify, evaluate, and synthesize the existing literature (Okoli & Schabram, 2010). The systematic review is a widely used method of literature review, which allows for understanding of the breadth of research in a specific field (Tranfield et al., 2003) and provides reliable assessments of the relevant studies on a specific topic (Gough et al., 2017). This review specially adopts a hybrid-review structure (Paul & Criado, 2020), considering the incorporation of structured review and narrative elements supported by Leximancer analysis. After identifying the research purpose and goals of the review, a research protocol including the scope of the study, criteria, quality assessment and data extraction was developed as recommended by Okoli & Schabram (2010), leading to the search for the most necessary literature.

Data collection

Peer reviewed research papers on social media in the hospitality sector were identified and gathered from three online research databases including Science Direct, EBSCOHost, and Google Scholar. These three online research databases are recognized as the largest and most popular in searching for research papers in hospitality and tourism management (Buhalis & Law, 2008). Search strings were constructed using the following terms: ‘hotel’, ‘hospitality’, ‘social media’, ‘online review’, ‘user-generated content’, and ‘online social networking’. These terms appeared in the titles, keywords, or abstracts of the identified papers. The journals in which the papers were published were screened to confirm publications and ranking in the ABDC (Australian Business Deans Council) journal list. This assisted in the process to select high quality research papers within the scope of years from 2010 to 2020, at the time of the data collection. The ABDC ranking has been used at universities and business schools in Australia and New Zealand as a reference for journal quality, including across the areas of hospitality and marketing.

In addition, the direct relevance to the focus of this study was considered by reading the title, abstract and keywords of each article. To ensure the validity and avoid missing any relevant papers, the authors conducted the search independently between January and March 2021 and the final lists were combined using a Microsoft Excel database. The pool of 165 papers was selected for this study, with the exclusion criteria of duplication, in-press papers, commentaries, and book reviews. The collected papers were categorized by key information such as author(s), journal name, paper title, publication year, ABDC journal rankings, perspective (e.g., consumer, supply), methods and samples used in the research (e.g., method for collecting and analyzing data, range of industry sectors, type of social media), abstracts with key words, key measurement models/ frameworks and theories/approaches used.

Data analysis

The number of publications by year was recorded as cumulative frequency and analyzed under two phases (i.e., phase 1: 2010-2014, phase 2: 2015-2020). Journal titles and their ABDC journal ranking were coded and recorded as frequency and percentage. Key measurement models/frameworks and theories/approaches used were coded and classified as cited or applied for comparison. Samples used in the research were coded as frequency and/or percentage which were then classified under industry sectors, and social media applications. The number of perspectives (e.g., consumer, supply, or both) in each article was coded and analyzed in each year. The methods used were classified as detail of the methods (e.g., online survey, interview, observation etc.) and type of data (e.g., quantitative, qualitative, or both). The key data analysis was coded as frequency and classified under types of main data analysis methods reviewed in this study.

Abstracts with keywords were qualitatively analyzed by Leximancer (version 4.5) to investigate key themes and concepts. Prior to the use of Leximancer, the data were arranged in Excel. In the first column, two phases (i.e., phase 1: 2010-2014, phase 2: 2015-2020) were recorded for comparison by year and abstracts with keywords were recorded in the second column. The Excel spreadsheet was uploaded in Leximancer and based on frequency occurrence of a concept, a concept map was produced to display the main themes and concepts visually. The larger colored circles represented the important themes and small gray nodes represented the concepts generated in each theme. In this analysis, Leximancer identified where each year phase was closely situated relative to the relevant dominant themes. Also, Insight Dashboard in Leximancer was used to compare the relative frequency and the strength of prominent concepts for each year phase. The relative frequency explains a conditional probability and the strength score is the reciprocal conditional probability (Leximancer, 2021). This approach highlighted the change of key research topics over time.

RESULTS

A total of 165 peer reviewed research articles on social media in the hospitality sector, published between 2010 and 2020, were included in the systematic review. Analysis of the reviewed articles was reported in terms of: (1) number of publications by year and journal; (2) theoretical base; (3) range of industry sectors and social media; (4) perspective of research; (5) research methods and data treatment (which represent the elements of structured review undertaken in this study); and (6) key themes and concepts (informed by Leximancer).

Number of publications by year and journal

From the initial year of collection in 2010 there was slow, but incremental, growth to fourteen total articles by 2012. Scholarship experienced significantly greater interest in 2013, in which seventeen articles were identified, more than doubling the scholarship, depicted in the cumulative frequency chart (see Figure 1). There was a considerable acceleration of publications at the midpoint of the decade (2015 to 2016), whereby 26 and 27 articles were identified, representing almost one third (32.1%) of all publications analyzed in this study. Interest remained steady (16 and 15 publications) for the next two years (2017 and 2018), before, again, growing slightly (20 and 22 publications) in the last two years (2019 and 2020) of the decade. As indicated in Figure 1, there are two observable phases for interest in the literature. These phases occurred prior to 2015, (Phase 1: 23.6 % of publications) (e.g., Blal et al., 2014; Bulchand-Gidumal et al., 2013; Cabiddu et al., 2014; Cantallops & Salvi, 2014; Chan & Guillet, 2011; Chaves et al., 2012; Gu & Ye, 2014; Kasavana et al., 2010; Kim et al, 2011; Kleinrichert et al., 2012; Levy et al., 2013; Liu et al., 2013; Mauri & Minazzi, 2013; Noone et al., 2011; Park & Allen, 2013; Sparks & Browning, 2011; Verma et al., 2012; Wei et al., 2013; Williams et al., 2010; Ye et al., 2011; Xie et al., 2011 etc.) and from 2015 (Phase 2: 76.4% of publications) (e.g., Albayrak et al., 2021; Amaro et al., 2016; Ayeh et al., 2016; Bigné et al., 2020; Buhalis & Sinarta, 2019; Casaló et al., 2015; Choi et al., 2016; Garrido-Moreno et al., 2018; Gavilan et al., 2018; Giglio et al., 2020; Hwang et al., 2018; Jung et al., 2018; Kim et al., 2015; Kim & Park, 2017; Leung & Tanford, 2016; Li & Ryan, 2020; Ma et al., 2018; Michopoulou & Moisa, 2019; Mkono & Tribe, 2017; Moro et al., 2019; Murphy & Chen, 2016; Neirotti et al., 2016; Phillips et al., 2015; Phillips et al., 2017; Qian et al., 2020; Su et al., 2015; Torres et al., 2015; Tung et al., 2018; Viglia et al., 2016; Yang, 2020; Yen & Tang, 2015, Zhao et al., 2019 etc.).

Table 1 depicts the distribution of articles by journal, and further segmenting this distribution by ABDC ranking. In compiling the 2019 version of the ABDC guide, a quality rating system was used along with four rating categories A*, A, B, and C. The greatest percentage (45%) of research was present in A-ranked journals, with the bulk of those sourced from three journals: International Journal of Contemporary Hospitality Management, Journal of Hospitality Marketing & Management, and Cornell Hospitality Quarterly. The next highest percentage (32%) of articles collected for this study were from A*-ranked journals with 73% of those articles published in either: International Journal of Hospitality Management, or Tourism Management. The remaining 24% of articles were collected from B and C-ranked journals, with the minority of articles (n=7), collected from two C-ranked journals. The bulk of B-ranked literature was published by the Journal of Hospitality and Tourism Technology, with 45%, there was a remainder of multiple journals from which one article was collected (shown in Table 1). The leading journal in each ranking, included ‘hospitality’ in the title.

Figure 1: Cumulative frequency of the 165 peer reviewed research papers examining social media in the hospitality sector by year published

image2.png

Table 1: Journal distribution and ABDC rankings of the 165 research papers on social media applications in the hospitality sector reviewed in this study

ABDC

Journal

ABDC ranking

1 Does not add to 100% due to rounding.

Theoretical base

Across the 165 papers identified in this systematic review, 102 papers evidently included at least one citation, discussion, or similar note of theories, models, frameworks, and approaches. There was a total of 135 occurrences of at least one mention of theories, models, frameworks, and approaches occurring within those 102 papers, and 55 instances where these were identified to have been specifically applied to the research as a theoretical base. There were 63 papers which, for various reasons (e.g., theoretical and review papers), did not evidently utilize, or explicitly mention a theoretical base. In some cases, however, multiple theoretical bases were utilized or mentioned in a single paper and these were included in the total count in Table 2.

Presented in Table 2 are the most apparent of the theoretical bases identified in the literature. Additionally, beyond the scope of Table 2, were 28 papers in which a theory, and 38 papers in which a model, framework, or approach was noted (or indeed applied as the theoretical base) at least once, however those 66 theoretical approaches were only identified on these singular occurrences. The eWOM approach (Litvin et al., 2008) was eight times more apparent than the next most evident theoretical basis; the uses and gratification (U&G) approach/theory (Katz et al., 1974; Stafford et al., 2004), which appeared in five papers, and was applied in three papers. The occurrence of eWOM in the literature aligned with the proclivity of social media being treated as an electronic form of communication, and as a source of data. The other theories, models, frameworks, and approaches of note in this review were: resource-based view theory (Grant, 1991), user generated content approach (Wright & Zdinak, 2008), motivation theory (Herzberg, 1968; Maslow, 1987), the technology acceptance model (Davis, 1989), grounded theory (Strauss, 1987), Herzberg’s two-factor theory (Herzberg, 1966), justice theory (Greenburg, 1987), social capital theory (Putnam, 1995), and the theory of planned behavior (Ajzen, 1988).

Table 2: Sample of theories, models, framework, and approaches featured in the 165 research papers on social media applications in the hospitality sector examined in this study

Theories, models, framework, and approaches

Appeared 1

Applied 2

Electronic word of mouth (eWOM) approach (Litvin et al., 2008)

40

32

Uses and gratification (U&G) approach/theory (Katz et al., 1974; Stafford et al., 2004)

5

3

Resource based view (RVB) theory (Grant, 1991)

4

3

User generated content (UGC) approach (Wright & Zdinak, 2008)

4

2

Motivation theory (Herzberg, 1968; Maslow, 1987)

3

3

Technology acceptance model (TAM) (Davis, 1989)

3

3

Grounded theory (Strauss, 1987)

2

1

Herzberg’s two-factor theory (Herzberg, 1966)

2

2

Justice theory (Greenburg, 1987)

2

2

Social capital theory (Putnam, 1995)

2

2

Theory of planned behavior (Ajzen, 1988)

2

2

Total

1353, 4

55 3

1 Cited, discussed or mentioned at least once in a paper but not evidently applied in the paper.

2 Applied, demonstrated, and explicitly researched through methods in the paper. Applied is a sub-group of Appeared.

3 Total < 165. A total of 63 papers neither cited nor applied specified theories, though some papers cited or applied more than one theory, model, or approach.

4 Total = 135 including an additional 66 theories or models, framework, and approaches appeared or were applied once, beyond the scope of this table.

Range of industry sectors and social media

The frequencies of industry sectors investigated in this study are shown in Table 3. As some papers investigated multiple sectors there were 177 instances of industry sectors examined in the literature. The most frequently investigated sector were hotels, featuring in 154 papers. This was exponentially more featured than the remaining industry sectors, which were: hospitality (n=12), tourism (n=7), restaurants (n=2), resorts (n=1), and airlines (n=1). Thus, within investigations of social media in hospitality, there was a clear focus on the hotel sector.

Table 3: Industry sectors in the 165 research papers on social media in hospitality examined in this study

Industry Sectors

Range of industry sectors

177 1

Hotel

154

Hospitality

12

Tourism

7

Restaurant

2

Resort

1

Airline

1

1 Total >165. Some papers covered multiple sectors.

Table 4 shows the social media applications which appeared in the literature examined in this study. Given that numerous studies investigated or utilized various social media applications, the frequency of which applications were mentioned exceeds the sample of 165 papers. The abundance of literature captured in this review necessitated that only applications appearing on multiple occasions were represented in Table 4, thus the omission of fifteen singularly appearing social media applications: Airbnb, Ciao.co.uk, Daodao.com, Google, Hotels.com, Hostelworld, Instagram, Makemytrip.com, Ozome, Sina Weibo, Tencent Weibo, Travelocity, TravelPost, TrustYou, and Venere.com. The most featured social media application was TripAdvisor, which was present in 26.7% of the literature. Facebook (12.5%), Twitter (4.9%), Booking.com (4.2%), Expedia (3.8%), and Yelp (3%) were the other significantly appearing social media applications. In 28 publications, though some form of social media appeared to be utilized in the research, specific applications were not identified within those studies. There were also 21 studies which did not appear to utilize, or discuss, specific social media applications (such as theoretical papers), though social media as a concept was still addressed. The nature of some of the studies included in this review necessitated a focus on fictitious social media, and this occurred in 19 studies.

Table 4: Social media applications used in the 165 research papers on the hospitality sector examined in this study

Social media applications Frequency % 2

TripAdvisor

71

26.8

Facebook

33

12.5

Undefined Social media 4

28

10.6

N/A 3

21

7.9

Fictitious Social media 5

19

7.2

Twitter

13

4.9

Booking.com

11

4.2

Expedia

10

3.8

Hotel websites

10

3.8

Yelp

8

3.0

Ctrip.com

3

1.1

Orbitz

3

1.1

Triavgo.com

3

1.1

Youku Wechat

3

1.1

Agoda

2

0.8

CouchSurfing

2

0.8

HolidayCheck

2

0.8

Instagram

2

0.8

Loyalty programs

2

0.8

Priceline

2

0.8

YouTube

2

0.8

Total 2651, 6

1 Total > 165. More than one social media application examined in most papers.

2 Does not add to 100% due to rounding.

3 Specific social media applications were not evident in certain studies.

4 Social media applications were used, but not explicitly identified.

5 Fictitious social media applications were constructed for the purpose of the study.

6 Various studies specifically identified one social media application, these 15 are unique from the remaining list.

Perspective of research

The breakdown of the two perspectives of the literature (consumer and supply), over time, is presented in Table 5. There was a somewhat greater proportion of consumer-focused literature (56%) than supply-focused literature (40.4%). There did not appear to be a clear trend in preference between perspectives over time though in 2016, scholarship that favored the consumer perspective was more than double. Six papers (3.6%) did not evidently focus on either perspective. One paper was found to have investigated both the consumer and supply perspectives, accounting for the total in this case being one greater (n=166) than total valid articles examined in the study. As for the foci of supply-oriented literature, researchers’ focus tended toward a supplier perspective on marketing (29 papers), customer relationship management (CRM) (18 papers), and sales performance (13 papers). The foci within the supply-oriented literature were excluded from the totals in Table 5 as some papers did not maintain a singular focus. Though social media marketing was the specific focus on just four occasions, it is possible that social media marketing was integrated in papers with the larger marketing focus, with the concept of social media marketing gaining attention as the decade progressed.

Table 5: Research Perspectives and focus areas of supply-oriented research from 165 research papers on social media in the hospitality industry

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Total

%
Consumer Perspective 1

3

3

8

3

13

19

9

9

11

14

93

56

Supply Perspective 2 -3393

11

8

7

5

9

9

67

40.4
Branding -

-

-

2

-

-

2

1

-

1

- 6
Communication -

-

-

-

-

2

1

-

-

-

- 3
CSR -

-

-

-

-

-

-

1

-

1

- 1
Crisis Management -

-

-

-

-

2

-

-

-

-

- 2
CRM -

-

-

4

1

4

1

3

3

-

2

18

HRM -

-

-

-

-

1

1

-

-

-

2 4
Marketing

-

2

1

6

2

4

5

1

1

5

2

29

Organizational Perfor-

mance

-

-

-

-

-

1

-

-

-

2

2 5
Revenue Management

-

1

-

-

-

-

1

1

-

1

1

5
Sales Performance

-

1

-

-

2

3

1

2

2

1

1

13

Service Quality

-

-

1

3

-

-

-

-

-

-

-

4
Social Media Marketing

-

-

-

-

-

-

-

1

2

-

1

4
Sustainability

-

-

1

-

-

-

1

-

-

-

-

2
Not applicable

1

-

-

-

2

2

-

-

1

-

-

6 3.6
Total

2

6

6

17

8

26

27

16

15

20

23 3

166 1,

100%
3

1 Total is calculated via the number of papers: consumer, supply, or N/A, for each year and total.

2 Supply perspective foci are not included in the total, as more than one focus was present in some cases.

3 One paper focused on both consumers and supply perspective, thus adding one to total number of papers >165.

Research methods and data treatment

The research methods and modes of data analysis utilized in the 165 research papers are shown in Table 6. There was a clear tendency toward quantitative analysis (n=107, 64.8%) in the scholarship, with only 21.8% of papers (n=36) assuming a qualitative approach and the remaining 13.3% of papers (n=22) adopting a mixed methods approach. The quantitative preference of the literature is reflected in the key data analysis methods, with content analysis (n=39), regression analysis (n=35), descriptive analysis (n=32), structural equation modelling (SEM) (n=30), and analysis of variance (ANOVA) (n=23) among the most used data analysis methods. Qualitative studies also account for the prevalence of content analysis as a key method, and for the use of thematic analysis (n=12). Regarding the prevalence of content analysis, this is accounted for by the high frequency of content (n=72) as the main source of data. Other prevalent data sources were online surveys (n=56), interviews (n=23) and web crawling (n=17) also among the most employed data. Web crawling, along with text mining/analysis (n=3) reflect the data heavy nature of social media research and reflect the occurrence of sentiment analysis (n=8) and natural

language processing (n=8) among the data analysis methods. As with prior tables, the preponderance of data collected in this review necessitated that Table 6 present the most apparent methods, with some eleven other data collection methods, and 51 methods of data analysis employed across the scholarship.

Table 6: Research methods used, samples and perspectives in the 165 research papers on social media in hospitality

examined in this study

Category

Frequency

Methods used

Detail of the methods

207 1

Content

72

Online survey

56

Interview

23

Web crawling

17

Literature

8

Survey (other than online/unspecified)

7

Onsite survey

4

Participant observation

3

Observation

3

Text-mining/analysis

3

Other (single use methods)

8

Other (analysis of pre-existing/secondary data)

3

Type of data

165

Quantitative

107

Qualitative

36

Both (mixed methods)

22

Key data analysis 2

Data analysis methods

284 1

Content Analysis

39

Regression Analysis

35

Descriptive Analysis

32

Structural Equation Modelling (SEM)

30

Analysis of Variance (ANOVA)

23

Confirmatory Factor Analysis (CFA)

14

Thematic Analysis

12

Multivariate Analysis of Variance (MANOVA)

11

Sentiment Analysis

8

Natural Language Processing

8

Literature Review

7

Partial Least Squares (PLS)

6

Ordinary Least Squares (OLS)

4

Exploratory Factor Analysis (EFA)

4

Other methods

51

1 Total >165. Several papers used more than one method.

2 Some papers reported more than one sample.

Key themes and concepts

The five main themes and their connectivity rates were Hotel (100%), Social media (45%), Tourism data (15%), Sentiment (9%), and Factors (7%), in order of relative importance (see Figure 2). These were the main themes, including several relevant

concepts representing key research topics, in the abstracts with keywords, in the 165 research papers on social media in the hospitality sector examined in this study. Hotel was the most significant theme and mentioned 707 times in the 165 abstracts with keywords, which is unsurprising given Table 3 shows hotels as the most investigated within the hospitality sector. The Hotel theme included the relevant concepts of ‘online’, ‘reviews’, ‘customer’, ‘management’, ‘influence’, ‘satisfaction’, ‘value’, and ‘relationship’. Therefore, the concepts relevant to the Hotel theme suggest extant social media research of the hotel sector tends to focus on the possible impacts of customer satisfaction, relationships, and value on management decisions. Social media was the second theme, mentioned 538 times in the 165 abstracts with keywords. The relevant concepts to Social media as a theme were: ‘marketing’, ‘industry’, ‘managers’, ‘tourism’, and ‘Facebook’. This theme seemed to reflect the research topic about social media (especially, Facebook) study in tourism marketing industry. The third theme Tourism data was mentioned 369 times in the 165 abstracts with keywords. The concepts of ‘analysis’, ‘content’, ‘performance’, ‘model’, and ‘TripAdvisor’ were fairly related hence the analysis of tourism content (especially, from TripAdvisor) using a model, could be regarded as one of main research topics in the 165 research papers examined in this study. The fourth theme Sentiment was mentioned 152 times and contained the concepts of ‘positive’, ‘negative’, ‘travel’, ‘number’, and ‘higher’. This theme was apparent as the research topic in studies such as those regarding positive and/or negative travel experiences based on the higher number of reviews. The last theme, Factors, had relatively fewer relevant concepts such as ‘factors’ and ‘practices’. Therefore, it was possibly regarded as the research theme in terms of potential impact of factors related to the conduct of practices within the industry.

Figure 2: Key themes and concepts in the 165 research papers on social media in the hospitality sector examined in this

study

image3.jpeg

Through Insight Dashboard in Leximancer, two year phases (i.e., phase 1: 2010-2014, phase 2: 2015-2020) were compared according to the relative frequency and the strength of prominent concepts (see Table 7). In the phase 1 from 2010 to 2014, the concepts highly scored on the strength, such as ‘management’ (strength=33%, prominence score=1.7), ‘travel’ (strength=33%, prominence score=1.6), ‘information’ (strength=31%, prominence score=1.6), ‘factors’ (strength=30%, prominence score=1.5), ‘negative’ (strength=28%, prominence score=1.4), and ‘content’ (strength=26%, prominence score=1.3) could be considered as the most important concepts within 39 research papers published from 2010 to 2014. Research papers in this first phase tended to investigate factors and sentiment analysis of reviews in the management sector in the travel industry. By contrast, in phase 2 from 2015 to 2020, the concepts highly scored on the strength, such as ‘model’ (strength=96%, prominence score=1.2), ‘data’ (strength=89%, prominence score=1.1), ‘managers’ (strength=88%, prominence score=1.1), ‘TripAdvisor’ (strength=88%, prominence score=1.1), ‘paper’ (strength=87%, prominence score=1.1), and ‘findings’ (strength=87%, prominence score=1.1) could be considered as the most important concepts by 126 research papers published from 2015 to 2020. Interestingly, it appeared that research papers in this phase tended to use a specific model to analyze data collected from current popular social

media applications and identify a specific social media application used in their studies.

Table 7: Top 15 ranked concepts for each year phase

image4.png
  • 3.

    DISCUSSION

This literature review technique could allow authors to seek the value of emerging research in social media in the hospitality sector. It might be useful to make a future research agenda in this area.

In seeking further wide publications in high-ranking journals, journals in diverse fields and subject categories, not only within the hospitality field, but also tourism, events, marketing, media, leisure, information management, and sociology fields can be targeted. Doing so requires that researchers explore this topic whilst crossing disciplinary boundaries. Multiple research concepts, across diverse subject categories, are more likely to give a greater opportunity for the critical development of the research of social media in the hospitality sector, and collaboratively influence the growth of the relevant industries.

Although various theories, models, frameworks, and/or approaches have been utilized in several papers in this topic, around 40 % of papers did not evidently apply or mention a theoretical base. It might be partly explained that there are a number of exploratory studies which adopted thematic analysis and thus failed to adopt a theoretical viewpoint. This links with the prior ‘newness’ of the concept of social media, and its emergence in the industry where its usage requires identification prior to quantification. Indeed, this is reflected in this study’s distinction of phases and cumulative publication totals which suggest a maturing scholarship. The examination of research topics may be explained in a different way with other theoretical frameworks. It was indicated that application of appropriate theories tends to lead to substantial outcomes with respect to specific phenomenon.

Thus, a lack of engagement with theory in the reviewed research papers on this topic presents an opportunity for future research to extend a further understanding of social media in the hospitality sector. Research informed by various relevant theories would be better able to provide scholarly direction and enhance research design.

Our results showed that quantitative analysis (64.8%) was used extensively in the analysis of social media contents, consistent with the prevalence of quantitative research found in previous hospitality and tourism studies on social media trends (Lu et al., 2018). Employing the quantitative content analysis approach have been suggested as a logical assessment of social media content to eliminate researcher bias, however it tends to limit explanatory value within the theoretical discussion (Riffe et al., 2019). According to Khang et al. (2012), qualitative methods undertake to offer greater understanding of a phenomenon, and lead to new insights into social media. A balance of these methodological approaches is therefore encouraged for social media researchers in hospitality to contribute uncovered theoretical directions forward. The continued use of mixed-methods approaches could likewise assist here.

Interestingly, the data in phase 1, from 2010 to 2014, showed that the sentiment analysis in the management sector in the travel industry has been focused. The sentiment analysis of users’ comments has long been a research focus in the fields of information science and technology and commercial marketing management, as well as in online customer reviews. With textual information mining, the analysis of reviews could offer insight into customer needs, improve business processes and help companies establish themselves in the market. Better decision-making for consumers, companies, and other stakeholders would also increase customer satisfaction (Lin et al., 2021). Therefore, the use of text sentiment analysis methods is still an important analytical approach for online review data. However, it is essential to point out that online review data has flooded with major hospitality websites and social media nowadays, therefore, the researchers would need to consider how to effectively form the relevant methods and technologies for capturing and analyzing the important data resources for sentiment analysis. The data in phase 2, from 2015 to 2020, revealed an increasing pattern of research examining the effects of social media, based on a specific model to analyze data from a popular social media application (e.g., TripAdvisor, Facebook). This trend indicates that scholars have recognized and responded to a heightened level of complexity to understanding in the scholarship. Given considerable, and rapid, increases in volumes of available social media data, exploration of complex aspects such as the subjectivity of text reviews and various features in the dataset are required (Jimenez-Marquez et al., 2019) as is the application of a comprehensive model or framework for the advancement of research in this area (Lamest & Brady, 2019). It is also evident why more researchers tend to focus on one major social media application for in-depth investigation than before, thus providing a glimpse into how social media research in hospitality has evolved through these phases.

The studies encapsulated in this review were highly skewed toward the hotel sector. Further, review articles encapsulated in this systematic review such as Kasavana et al.’s (2010) investigation, which aimed to serve as a genesis paper on social media use in the hospitality sector, found use of social media was prominent among hotels. Hotels were again the focus of a review of social media in the hospitality sector with Cantallops & Salvi’s (2014) review of eWOM. Schuckert and colleagues (2015) sought to review trends of online reviews within the wider hospitality and tourism industries and found 60% of their sample literature focused on hotels. Hotels were overwhelmingly the focus of Aydin’s (2020) review of social media use in the hospitality industry, which focused on Turkish facilities, where over 80% of the sample social media accounts were from hotels. Therefore, hotels very much appear the focus of social media investigations within the hospitality of tourism industry, which is also reflected in this systematic review.

It could be explained, as the ubiquity of hotels in social media research within the hospitality industry, that even studies which did not take a deliberate view toward hotels, such as Buhalis & Sinarta (2019) who investigated real time social media use within tourism and hospitality, still investigated hotels within the wider sample. This was also true of Kandampully et al.’s (2018) review of customer experience management within hospitality, where hotels still featured, though not as the dominant focus. Indeed, for studies not to evidently focus on hotels required highly focused investigations, such as Mkono & Tribe’s (2017) study which adopted a netnographic approach from the consumer perspective and served to categorize the behaviors of social media users in the hospitality and tourism industry; likewise, the study by Ladkin & Buhalis (2016) who investigated social media as a recruitment tool in the hospitality industry was highly focused in its research aim.

Although there is a clear need for the hotel sector to be reflected in social media research within the hospitality industry, given its overwhelming presence, it would be advantageous for other sectors within the industry to be more prominently featured. Also, it may be interesting for future investigation to extend to various social media applications, beyond TripAdvisor and Facebook. The popularity of different applications likely varies in each country, and indeed, over time. This call should be heeded by scholars and practitioners to widen the focus of social media application across the breadth of hospitality industry. Such research is, however, dependent upon industry shifts, (especially in the face of the COVID-19 pandemic), and to see how the hospitality industry has adapted its social media use heading toward the upcoming decade.

Presented in Figure 3 are the future research areas on social media in the hospitality based on the discussion of this study.

Figure 3: Future research on social media in the hospitality

CONCLUSIONS AND LIMITATIONS

The systematic review has presented the current status of the literature on social media in the hospitality sector. This paper reviewed and found that (1) research interest has increased rapidly over the last half decade in A-ranked journals in the field of hospitality; (2) one dominant theoretical approach (eWOM) has been used and about 40% of the published research papers are not clearly on the basis of the theoretical framework; (3) quantitative research methods have been mostly used to analyze contents data; and (4) there are more opportunities to investigate a diverse range of industry sectors and specific social media applications from various research perspectives. This quantitative systematic review contributes to gain insight into existing hospitality studies on social media, identify several research gaps, and provide future scholarly endeavors to develop a more strategic research agenda that encourages a more collaborative and various approach with the aim of better understanding social media research within the hospitality industry. It is important to consider that this review has demonstrated the existence of two clear phases of scholarship on social media use in the hospitality sector between 2010 and 2020. This distinction was identifiable because this review specifically adopted a hybrid review approach to the systematic review and was thus able to map and explain the trends within scholarship. Dissimilar from extant reviews, the current study’s utilization of Leximancer enabled the authors scope for narrative explanation and informed commentary on the scholarship’s current and future trends. Significantly, this enabled this study to comment on the apparent shifting focus of the literature toward the end of the decade toward maturity demonstrated by heightened focus on employing and discussing models.

Limitations of this study include its scope, of ten years between 2010-2020, and though this was necessitated by the research design as to investigate this specific period of research, the investigation period is of specific importance to the hospitality industry as it predates the outbreak of the COVID-19 pandemic. COVID-19 has significantly impacted on the hospitality industry through the various restrictions on events, travel, and venues. Hence, there are likely trends among the utilization of social media within the hospitality industry which have emerged as a result of, or in response to, the pandemic.

REFERENCES

industry. Journal of Hospitality Marketing & Management, 29(1), 1-21.https://doi.org/10.1080/19368623.2019.1588824

55(4), 365-375.https://doi.org/10.1177/1938965514533419

36(5), 563-582.https://doi.org/10.1080/10548408.2019.1592059

36 , 41-51.https://doi.org/10.1016/j.ijhm.2013.08.007

media websites?. Journal of Travel & Tourism Marketing, 28(4), 345-368.https://doi.org/10.1080/10548408.2011.571571

66, 53-61.https://doi.org/10.1016/j.tourman.2017.10.018

1(1), 68-82.https://doi.org/10.1108/17579881011023025

30(1-2), 3-22.https://doi.org/10.1080/10548408.2013.750919

55(4), 523-536.https://doi.org/10.1177/0047287514559033

positioning. International Journal of Information Management, 36(6), 1133-1143.https://doi.org/10.1016/j.ijinfomgt.2016.02.010

neural network analysis. Tourism Management, 50, 130-141.https://doi.org/10.1016/j.tourman.2015.01.028

Marketing, 32(59), 608-621.https://doi.org/10.1080/10548408.2014.933154

review. British Journal of Management, 14(3), 207-222.https://doi.org/10.1111/1467-8551.00375

22(2), 117-128.https://doi.org/10.1108/17542731011024246

e-word-of-mouth to hotel online bookings. Computers in Human Behavior, 27(2), 634-639.https://doi.org/10.1016/j.chb.2010.04.014 Yen, C.-L. A., & Tang, C.-H. H. (2015). Hotel attribute performance, eWOM motivations, and media choice. International Journal of Hospitality

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References

 

Albayrak, T., Caber, M., & Sigala, M. 2021 A quality measurement proposal for corporate social network sites: the case of hotel Facebook page. Current Issues in Tourism. 24(20):2955–2970. https://doi.org/10.1080/13683500.2020.1854199

 

Ajzen, I. 1988 Attitudes, personality, and behavior,. New York: Dorsey Press.;

 

Amaro, S., Duarte, P., & Henriques, C. 2016 Travelers’ use of social media: A clustering approach. Annals of Tourism Research. 59:1–15. https://doi. org/10.1016/j.annals.2016.03.007

 

Ayeh, J. K., Au, N., & Law, R. 2016 Investigating cross-national heterogeneity in the adoption of online hotel reviews. International Journal of Hospitality Management. 55:142–153. https://doi.org/10.1016/j.ijhm.2016.04.003

 

Aydin, G. 2020 Social media engagement and organic post effectiveness: A roadmap for increasing the effectiveness of social media use in hospitality industry. Journal of Hospitality Marketing & Management. 29(1):1–21. https://doi.org/10.1080/19368623.2019.1588824

 

Bigné, E., William, E., & Soria-Olivas, E. 2020 Similarity and consistency in hotel online ratings across platforms. Journal of Travel Research. 59(4):742–758. https://doi.org/10.1177/0047287519859705

 

Blal, I., & Sturman, M. C. 2014 The differential effects of the quality and quantity of online reviews on hotel room sales. Cornell Hospitality Quarterly. 55(4):365–375. https://doi.org/10.1177/1938965514533419

 

Buhalis, D., & Law, R. 2008 Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research. Tourism Management. 29(4):609–623. https://doi.org/10.1016/j.tourman.2008.01.005

 

Buhalis, D., & Sinarta, Y. 2019 Real-time co-creation and nowness service: lessons from tourism and hospitality. Journal of Travel & Tourism Marketing. 36(5):563–582. https://doi.org/10.1080/10548408.2019.1592059

 

Bulchand-Gidumal, J., Melián-González, S., & Lopez-Valcarcel, B. G. 2013 A social media analysis of the contribution of destinations to client satisfaction with hotels. International Journal of Hospitality Management. 35:44–47. https://doi.org/10.1016/j.ijhm.2013.05.003

 

Cabiddu, F., De Carlo, M., & Piccoli, G. 2014 Social media affordances: Enabling customer engagement. Annals of Tourism Research. 48:175–192. https://doi.org/10.1016/j.annals.2014.06.003

 

Cantallops, A.S., & Salvi, F. 2014 New consumer behavior: A review of research on eWOM and hotels. International Journal of Hospitality Management. 36:41–51. https://doi.org/10.1016/j.ijhm.2013.08.007

 

Casaló, L. V., Flavián, C., Guinalíu, M., & Ekinci, Y. 2015 Do online hotel rating schemes influence booking behaviors?. International Journal of Hospitality Management. 49:28–36. https://doi.org/10.1016/j.ijhm.2015.05.005

 

Chan, N. L., & Guillet, B. D. 2011 Investigation of social media marketing: how does the hotel industry in Hong Kong perform in marketing on social media websites?. Journal of Travel & Tourism Marketing. 28(4):345–368. https://doi.org/10.1080/10548408.2011.571571

 

Chaves, M. S., Gomes, R., & Pedron, C. 2012 Analysing reviews in the Web 2.0: Small and medium hotels in Portugal. Tourism management. 33(5):1286–1287. https://doi.org/10.1016/j.tourman.2011.11.007

 

Choi, E.-K., Fowler, D., Goh, B., & Yuan, J. 2016 Social media marketing: applying the uses and gratifications theory in the hotel industry. Journal of Hospitality Marketing & Management. 25(7):771–796. https://doi.org/10.1080/19368623.2016.1100102

 

Cretchley, J., Rooney, D., & Gallois, C. 2010 Mapping a 40-year history with Leximancer: Themes and concepts in the Journal of Cross-Cultural Psychology. Journal of Cross-Cultural Psychology. 41(3):318–328. https://doi.org/10.1177/0022022110366105

 

Davis, F. D. 1989 Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 13(3):319–340. https://doi. org/10.2307/249008

 

Garrido-Moreno, A., García-Morales, V. J., Lockett, N., & King, S. 2018 The missing link: Creating value with social media use in hotels. International Journal of Hospitality Management. 75:94–104. https://doi.org/10.1016/j.ijhm.2018.03.008

 

Gavilan, D., Avello, M., & Martinez-Navarro, G. 2018 The influence of online ratings and reviews on hotel booking consideration. Tourism management. 66:53–61. https://doi.org/10.1016/j.tourman.2017.10.018

 

Giglio, S., Pantano, E., Bilotta, E., & Melewar, T. 2020 Branding luxury hotels: Evidence from the analysis of consumers’“big”visual data on TripAdvisor.

 

Journal of Business research. 119:495–501. https://doi.org/10.1016/j.jbusres.2019.10.053 Gough, D., Oliver, S., & Thomas, J. 2017 An introduction to systematic reviews,. (London). Sage.

 

Grant, R. M. 1991 The resource-based theory of competitive advantage: implications for strategy formulation”. California Management Review. 33(3):114–135. https://doi.org/10.2307/41166664

 

Greenburg, J. 1987 A taxonomy of organizational justice theories. Academy of Management Review. 12(1):9–22. https://doi.org/10.5465/amr.1987.4306437

 

Gu, B., & Ye, Q. 2014 First step in social media: Measuring the influence of online management responses on customer satisfaction. Production and Operations Management. 23(4):570–582. https://doi.org/10.1111/poms.12043

 

Herzberg, F. 1966 Work and the nature of man,. New York: The World Publishing Company.;

 

Herzberg, F. 1968 One more time: how do you motivate employees?. Harvard Business Review. 46(19):53–62

 

Hwang, J., Park, S., & Woo, M. 2018 Understanding user experiences of online travel review websites for hotel booking behaviours: An investigation of a dual motivation theory. Asia Pacific Journal of Tourism Research. 23(4):359–372. https://doi.org/10.1080/10941665.2018.1444648

 

Jimenez-Marquez, J. L., Gonzalez-Carrasco, I., Lopez-Cuadrado, J. L., & Ruiz-Mezcua, B. 2019 Towards a big data framework for analyzing social media content. International Journal of Information Management. 44:1–12. https://doi.org/10.1016/j.ijinfomgt.2018.09.003

 

Jung, T. H., Dieck, M. C. T., & Chung, N. 2018 Determinants of hotel social media continued usage. International Journal of Contemporary Hospitality Management. 30(2):1152–1171. https://doi.org/10.1108/IJCHM-02-2017-0068

 

Kandampully, J., Zhang, T. C., & Jaakkola, E. 2018 Customer experience management in hospitality. International Journal of Contemporary Hospitality Management. 30(1):21–56. https://doi.org/10.1108/IJCHM-10-2015-0549

 

Kasavana, M. L., Nusair, K., & Teodosic, K. 2010 Online social networking: redefining the human web. Journal of Hospitality and Tourism Technology. 1(1):68–82. https://doi.org/10.1108/17579881011023025

 

Katz, E., Blumler, J. G., & Gurevitch, M. 1974 Utilization of mass communication by the individual. In Blumler, J. G., & Katz, E. (Eds.), , editor. The uses of mass communication. p. 19–32. Sage Publications.;

 

Khang, H., Ki, E-J., & Ye, L. 2012 Social media research in advertising, communication, marketing, and public relations, 1997–2010. Journalism & Mass Communication Quarterly. 89(2):279–298. https://doi.org/10.1177/1077699012439853

 

Kim, E. E. K., Mattila, A. S., & Baloglu, S. 2011 Effects of gender and expertise on consumers’ motivation to read online hotel reviews. Cornell Hospitality Quarterly. 52(4):399–406. https://doi.org/10.1177/1938965510394357

 

Kim, W. G., Lim, H, & Brymer, R. A. 2015 The effectiveness of managing social media on hotel performance. International Journal of Hospitality Management. 44:165–171. https://doi.org/10.1016/j.ijhm.2014.10.014

 

Kim, W. G., & Park, S. A. 2017 Social media review rating versus traditional customer satisfaction. International Journal of Contemporary Hospitality Management. 29(2):784–802. https://doi.org/10.1108/IJCHM-11-2015-0627

 

Kleinrichert, D., Ergul, M., Johnson, C., & Uydaci, M. 2012 Boutique hotels: Technology, social media and green practices. Journal of Hospitality and Tourism Technology. 3(3):211–225. https://doi.org/10.1108/17579881211264495

 

Ladkin, A., & Buhalis, D. 2016 Online and social media recruitment. International Journal of Contemporary Hospitality Management. 28(2):327–345. https://doi.org/10.1108/IJCHM-05-2014-0218

 

Lamest, M., & Brady, M. 2019 Data-focused managerial challenges within the hotel sector. Tourism Review. 74(1):104–115. https://doi.org/10.1108/TR-03–2017

 

Leung, D., Law, R., van Hoof, H., & Buhalis, D. 2013 Social media in tourism and hospitality: A literature review. Journal of Travel & Tourism Marketing. 3012:3–22. https://doi.org/10.1080/10548408.2013.750919

 

Leung, X. Y., & Tanford, S. 2016 What drives Facebook fans to “like” hotel pages: A comparison of three competing models. Journal of Hospitality Marketing & Management. 25(3):314–345. https://doi.org/10.1080/19368623.2015.1014125

 

Levy, S. E., Duan, W., & Boo, S. 2013 An analysis of one-star online reviews and responses in the Washington, DC, lodging market. Cornell Hospitality Quarterly. 54(1):49–63. https://doi.org/10.1177/1938965512464513

 

Leximancer 2021 Leximancer User Guide. Retrieved March 2, 2021, from. https://doc.leximancer.com/doc/LeximancerManual.pdf

 

Li, F. S., & Ryan, C. 2020 Western guest experiences of a Pyongyang international hotel, North Korea: Satisfaction under conditions of constrained choice.

 

Lin, X. M., Ho, C. H., Xia, L. T., & Zhao, R. Y. 2021 Sentiment analysis of low-carbon travel APP user comments based on deep learning. Sustainable Energy Technologies and Assessments. 44:https://doi.org/10.1016/j.seta.2021.101014

 

Litvin, S. W., Goldsmith, R.E., & Pan, B. 2008 Electronic word-of-mouth in hospitality and tourism management. Tourism Management. 29(3):458–468. https://doi.org/10.1016/j.tourman.2007.05.011

 

Liu, S., Law, R., Rong, J., Li, G., & Hall, J. 2013 Analyzing changes in hotel customers’ expectations by trip mode. International Journal of Hospitality Management. 34:359–371. https://doi.org/10.1016/j.ijhm.2012.11.011

 

Lu, Y., Chen, Z., & Law, R. 2018 Mapping the progress of social media research in hospitality and tourism management from 2004 to 2014. Journal of Travel & Tourism Marketing. 35(2):102–118. https://doi.org/10.1080/10548408.2017.1350249

 

Ma, Y., Xiang, Z., Du, Q., & Fan, W. 2018 Effects of user-provided photos on hotel review helpfulness: An analytical approach with deep leaning.

 

International Journal of Hospitality Management. 71:p. 120–131. https://doi.org/10.1016/j.ijhm.2017.12.008

 

Maslow, A. H. 1967 A theory of meta motivation: the biological rooting of the value-life. Journal of Humanistic Psychology. 7(2):93–127. https://doi.org/10.1177/002216786700700201

 

Mauri, A. G., & Minazzi, R. 2013 Web reviews influence on expectations and purchasing intentions of hotel potential customers. International Journal of Hospitality Management. 34:99–107. https://doi.org/10.1016/j.ijhm.2013.02.012

 

Michopoulou, E., & Moisa, D. G. 2019 Hotel social media metrics: The ROI dilemma. International Journal of Hospitality Management. 76:308–315. https://doi.org/10.1016/j.ijhm.2018.05.019

 

Mkono, M., & Tribe, J. 2017 Beyond reviewing: Uncovering the multiple roles of tourism social media users. Journal of Travel Research. 56(3):287–298. https://doi.org/10.1177/0047287516636236

 

Moro, S., Ramos, P., Esmerado, J., & Jalali, S. M. J. 2019 Can we trace back hotel online reviews’ characteristics using gamification features?.

 

International Journal of Information Management. 44:p. 88–95. https://doi.org/10.1016/j.ijinfomgt.2018.09.015

 

Murphy, H. C., & Chen, M.-M. 2016 Online information sources used in hotel bookings: Examining relevance and recall. Journal of Travel Research. 55(4):523–536. https://doi.org/10.1177/0047287514559033

 

Neirotti, P., Raguseo, E., & Paolucci, E. 2016 Are customers’ reviews creating value in the hospitality industry? Exploring the moderating effects of market positioning. International Journal of Information Management. 36(6):1133–1143. https://doi.org/10.1016/j.ijinfomgt.2016.02.010

 

Noone, B. M., McGuire, K. A., & Rohlfs, K. V. 2011 Social media meets hotel revenue management: Opportunities, issues and unanswered questions.

 

Journal of Revenue and Pricing Management. 10(4):p. 293–305. https://doi.org/10.1057/rpm.2011.12

 

Okoli, C., & Schabram, K. 2010 A guide to conducting a systematic literature review of information systems research. Sprouts: Working Papers on Information Systems. 10(26):1–49. http://sprouts.aisnet.org/10-26

 

Park, S.-Y., & Allen, J. P. 2013 Responding to online reviews: Problem solving and engagement in hotels. Cornell Hospitality Quarterly. 54(1):64–73. https://doi.org/10.1177/1938965512463118

 

Paul, J., & Criado, A.R. 2020 The art of writing literature review: What do we know and what do we need to know?. International Business Review. 29:https://doi.org/10.1016/j.ibusrev.2020.101717

 

Phillips, P., Zigan, K., Silva, M. M. S., & Schegg, R. 2015 The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis. Tourism Management. 50:130–141. https://doi.org/10.1016/j.tourman.2015.01.028

 

Phillips, P., Barnes, S., Zigan, K., & Schegg, R. 2017 Understanding the impact of online reviews on hotel performance: an empirical analysis. Journal of Travel Research. 56(2):235–249. https://doi.org/10.1177/0047287516636481

 

Putnam, R. D. 1995 Tuning in, tuning out: the strange disappearance of social capital in America. PS: Political Sciences and Politics. 28(4):664–683. https://doi.org/10.2307/420517

 

Qian, J., Law, R., Wei, J., Shen, H., & Sun, Y. 2020 Hotels’ self-positioned image versus customers’ perceived image: a case study of a boutique luxury hotel in Hong Kong. Tourism Review. 76(1):198–211. https://doi.org/10.1108/TR-02-2019-0078

 

Riffe, D., Lacy, S., Watson, B.R., & Fico, F. 2019 Analyzing media messages: Using quantitative content analysis in research,. (New Yor). Routledge. Schuckert,. M., Liu, X., & Law, R. 2015 Hospitality and tourism online reviews: Recent trends and future directions. Journal of Travel & Tourism Marketing. 32(59):608–621. https://doi.org/10.1080/10548408.2014.933154

 

Sparks, B. A., & Browning, V. 2011 The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management. 32(6):1310–1323. https://doi.org/10.1016/j.tourman.2010.12.011

 

Stafford, T. F., Stafford, M. R., & Schkade, L. L. 2004 Determining uses and gratifications for the internet. Decision Sciences. 35(2):259–288. https://doi. org/10.1111/j.00117315.2004.02524.x

 

Strauss, A. L. 1987 Qualitative analysis for social scientists,. Cambridge University Press.;

 

Su, N., Mariadoss, B. J., & Reynolds, D. 2015 Friendship on social networking sites: Improving relationships between hotel brands and consumers.

 

International Journal of Hospitality Management. 51:p. 76–86. https://doi.org/10.1016/j.ijhm.2015.08.009

 

Torres, E. N., Singh, D., & Robertson-Ring, A. 2015 Consumer reviews and the creation of booking transaction value: Lessons from the hotel industry.

 

International Journal of Hospitality Management. 50:p. 77–83. https://doi.org/10.1016/j.ijhm.2015.07.012

 

Tranfield, D., Denyer, D., & Smart, P. 2003 Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British Journal of Management. 14(3):207–222. https://doi.org/10.1111/1467-8551.00375

 

Tung, V. W. S., & Au, N. 2018 Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management. 30(7):2680–2697. https://doi.org/10.1108/IJCHM-06-2017-0322

 

Verma, R., Stock, D., & McCarthy, L. 2012 Customer preferences for online, social media, and mobile innovations in the hospitality industry. Cornell Hospitality Quarterly. 53(3):183–186. https://doi.org/10.1177/1938965512445161

 

Viglia, G., Minazzi, R., & Buhalis, D. 2016 The influence of e-word-of-mouth on hotel occupancy rate. International Journal of Contemporary Hospitality Management. 28(9):2035–2051. https://doi.org/10.1108/IJCHM-05-2015-0238

 

Wei, W., Miao, L., & Huang, Z. J. 2013 Customer engagement behaviors and hotel responses. International Journal of Hospitality Management. 33:316–330. https://doi.org/10.1016/j.ijhm.2012.10.002

 

Williams, R., van der Wiele, T., van Iwaarden, J., & Eldridge, S. 2010 The importance of user‐generated content: the case of hotels. The TQM Journal. 22(2):117–128. https://doi.org/10.1108/17542731011024246

 

Wright, S., & Zdinak, J. 2008 New communication behaviors in a Web 2.0 world – changes, challenges and opportunities in the era of the information revolution. Retrieved January 13, 2021, from. https://bit.ly/3DXqGs0

 

Yang, F. X. 2020 Social media friending in building coworker guanxi: A study in the hotel industry. International Journal of Hospitality Management. 84:https://doi.org/10.1016/j.ijhm.2018.10.020

 

Ye, Q., Law, R., Gu, B., & Chen, W. 2011 The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human Behavior. 27(2):634–639. https://doi.org/10.1016/j.chb.2010.04.014 Yen, C.-L. A., & Tang, C.-H. H. , editor. 2015 Hotel attribute performance, eWOM motivations, and media choice. International Journal of Hospitality.

 

 

Xie, H. J., Miao, L., Kuo, P.-J., & Lee, B.-Y. 2011 Consumers’ responses to ambivalent online hotel reviews: The role of perceived source credibility and pre-decisional disposition. International Journal of Hospitality Management. 30(1):178–183. https://doi.org/10.1016/j.ijhm.2010.04.008

 

Zhao, Y., Xu, X., & Wang, M. 2019 Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews. International Journal of Hospitality Management. 76:111–121. https://doi.org/10.1016/j.ijhm.2018.03.017Please cite this article as:.

 

Kim, E., Best, A.R. & Choi, K. 2023 Mapping the Research Trends on Social Media in the Hospitality Sector from 2010 to 2020. Tourism and Hospitality Management. 29(2):169–183. https://doi.org/10.20867/thm.29.2.2


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