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Journal of Hospitality and Tourism Technology What do we know about social media and firms’ financial outcomes so far? Murat Kizildag, Mehmet Altin, Ozgur Ozdemir, Ilhan Demirer,

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Article information: To cite this document: Murat Kizildag, Mehmet Altin, Ozgur Ozdemir, Ilhan Demirer, (2017) "What do we know about social media and firms’ financial outcomes so far?", Journal of Hospitality and Tourism Technology, Vol. 8 Issue: 1, pp.39-54, https://doi.org/10.1108/JHTT-10-2016-0074 Permanent link to this document: https://doi.org/10.1108/JHTT-10-2016-0074 Downloaded on: 06 June 2017, At: 11:41 (PT) References: this document contains references to 26 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 70 times since 2017*

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What do we know about social media and firms’ financial outcomes so far? Murat Kizildag and Mehmet Altin Rosen College of Hospitality Management, University of Central Florida, Orlando, Florida, USA

Ozgur Ozdemir

Social media and firms

39 Received 19 October 2016 Revised 9 January 2017 25 January 2017 Accepted 25 January 2017

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Ozyegin University, Istanbul, Turkey, and

Ilhan Demirer Department of Hotel, Restaurant and Tourism Management, State University of New York at Plattsburgh, Plattsburgh, New York, USA

Abstract Purpose – This paper aims to understand the emergence, the revolution and the relevant knowledge of academic research concentrating on social media (SM) and hospitality and tourism firms’ financial performance. The authors not only identified the gaps and critical issues in research but also re-conceptualized profound directions for the future research in technology and finance in the hospitality and tourism field. Design/methodology/approach – This study adopted an in-depth review analysis to investigate and review previous scholarly papers published in hospitality, tourism and hospitality and tourism journals from January 2011 to the present. The authors thoroughly analyzed and reviewed peer-reviewed/refereed, blind-reviewed, full-length published articles and working papers within SM and hospitality firms’ financial performance. Editor notes, prefaces, research notes, industry articles, internet publications, conference preceding, books and book chapters were excluded. Findings – Having examined the empirical content of 26 peer-reviewed scholarly articles, the authors clearly observed that none of the papers went beyond analyzing the effect of SM on hotels’ revenue per available room, revenues, net profit, average daily rate, occupancy rates, net operating income, etc., and all papers ignored the analysis of many critical financial proxies. Research limitations/implications – This critique and review paper is limited to the relationship between SM and firms’ financial performance within the hospitality and tourism context. Practical implications – This review provides a blueprint to guide future research, facilitate knowledge accumulation and create a new understanding and awareness in practice as well as SM and financial performance research. Social implications – This paper complements and adds to previous work by demonstrating various aspects, evidences, findings and inferences regarding the association between online SM platforms and firms’ financial performance and by proposing rigorous abstract and specific future extensions to both practice and discipline-specific knowledge. Originality/value – There is an absence of the most updated review study of published papers on SM and hospitality and tourism firms’ financial performance. Although how SM contributes to firms’ financial performance is clear to academicians and industry professionals, no solid consensus or theoretical certainty about what the authors know and do not know has been achieved. Keywords Social media platforms, Financial performance, Financial performance proxies, Online social networking sites Paper type Research paper

Journal of Hospitality and Tourism Technology Vol. 8 No. 1, 2017 pp. 39-54 © Emerald Publishing Limited 1757-9880 DOI 10.1108/JHTT-10-2016-0074

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Introduction In recent years, the technological advances that have emerged since dot-com era in 1990s have shifted to collective, computer-mediated online platforms (i.e. Web 2.0, user-generated content and social networking mobile applications). These advances were the beginning of the social media (SM) phenomenon, which not only allows businesses to collectively gather consumer-based input, interaction, data, content-sharing and collaboration about their business functions but also lets companies to efficiently market their products, promote their brands and services, connect to the new and current customers, advance business functions and foster new business. The virtual nature of SM and its interactive online communications channels enable companies to create, share and/or exchange information and opinions that affect their business practices at the organization level. For instance, SM and its related technologies and pundits have given instantaneous and a broader customer access at a drastically reduced cost to organizations. This has tremendously helped businesses to reduce the cost of content creation, distribution and discovery methods. With the engagement of SM in this way, companies reached out to more customers with an efficient way in many organizational infrastructures and cultures, such as marketing efforts, delivering products and services, dealing with customer complaints and requests, organizational transparency, etc. In addition, companies have to restructure their organization environments and business processes and behaviors as a consequence of engaging in SM outlets. Besides their commercial activities, leadership mechanism, management practices and business collaborations with vendors and suppliers have to embrace this shift and change to succeed and uncover greater opportunities in the digital era. SM is a revolutionary trend that stems from the concepts of Web 2.0 and user-generated content (UGC). Thus, the power of SM phenomenon also stems from crowd-sourced Web 2.0 and UGC communities. The growth of UGC platforms (i.e. TripAdvisor, Yelp, etc). and social networking sites (i.e. Facebook, Instagram, Twitter, Pinterest, etc). and Web 2.0 outlets (i.e. Wikis, blogs, podcasts, etc). has enabled companies to tailor their production of goods and services, corporate marketing strategies and customer and public relations to meet specialized needs of targeted consumer groups. In short, aforementioned Web 2.0 and UGC mediums have changed companies’ internal organization structure by changing the way companies communicate with the world. In parallel to this, because information exchange and consumer communication are widely accessible through those Web 2.0 and UGC mediums, the quantitative inputs gathered from those outlets add value and support the financial and operational development of firms. Therefore, the degree to which various SM and online consumer networks are involved in firms’ core operations has drastically increased, resulting in a greater effect on firms’ financial and operational goals, strategies and outcomes. Accordingly, research on the associations between social media, social networking sites and firms’ financial outcomes has also increased at an unprecedented rate. Online consumer engagement through SM channels is especially critical for the hospitality and tourism industries because those service-oriented firms are highly information-sensitive. Also, several business practices (i.e. financial operations) of those companies are tightly associated with online consumer review portals, feedback-exchanging media outlets and consumer-generated electronic word-of-mouth (eWOM). For instance, SM applications in mobile phones facilitate the effective sharing of interactive information among consumers, and this shared information can reach millions very quickly. Additionally, the ubiquitous versatility of online and mobile social platforms is also critical for hospitality and tourism firms because the core of their business and revenue maximization practices is driven by people, specifically people’s opinions, preferences, feedback and travel decisions. Furthermore, hospitality and tourism firms’ financial

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successes and operational improvements are heavily dependent on consumers’ purchasing patterns, which have recently been shaped by a sharp rise in UGC information exchange among individuals. This is because the various dimensions of SM (i.e. Web 2.0 contents, UGCs, social networking sites, built-in mobile applications, etc). directly affect travel movements, consumer experiences, selections and behaviors, which are reflected in hospitality and tourism firms’ financial statements. Technology advances and adds various dimensions to the business world almost every day. As the management of hospitality and tourism companies observe, experience and adapt to the rapid growth and changes in SM technologies and platforms, academic research should constantly do the same. However, the academic findings and evidences often cannot follow the speed and constantly evolving, dynamic nature of SM technologies and their effect on firms’ financial structures. Therefore, it creates lack of collective consensus and theoretical certainty about what we know and do not know about the effect of SM on hospitality and tourism firms’ financial performance. One of the most critical ways to fill this vital gap is to address to synthesize what is known about SM and firms’ financial performance by creating a very clear collective portrait of the relevance of the research advancements, research focus and research stance emerged from the existing empirical and theoretical studies. This will help related academic research extend itself and develop new knowledge and practices that are aligned with these new advancements in SM technologies and platforms. As a result of these, we believe that we, as academicians, must supply an up-to-date, extensive, collective and systematic review and critique of the research origins and progress in terms of describing the relationship between SM and firms’ financial outcomes within the hospitality and tourism context. Additionally, there is an absence of the most updated review study of published papers on SM and hospitality and tourism firms’ financial performance. By conducting an in-depth article review and an extensive literature screening of various peer-reviewed hospitality and tourism journals, the overall objective and main purpose of this paper is to understand the emergence, the revolution and the relevant knowledge of academic research concentrating on SM and firms’ financial performance. In other words, we attempt to review and critique the empirical evidences and theoretical underpinnings in the SM and hospitality firms’ financial performance literature. In light of this, we aim to contribute and complement the existing body of knowledge by identifying the gaps and critical issues; generating innovative knowledge, profound directions and strategies; and re-conceptualizing the relevant findings, and what can be done to further technology and finance in the hospitality and tourism research field. We also attempt to add additional support and valuable extensions to contingency, administrative and systems theories by providing discussions on the changing interrelations of organizational functions, managements’ adaptation to technological changes in work environments and maintaining equilibrium through control of the employees and their changed working environments due to the advancements in SM technologies. We believe that our sample is the true representative of the population, reflecting the state of research on social media’s influence on firms’ financial performance. Methodological procedures This study adopted an in-depth review analysis to investigate and review previous scholarly papers published in hospitality, tourism and hospitality and tourism journals from January 2011 to the present time. During the data collection and paper identification processes, any non-social media and financial performance-related articles within hospitality and tourism context were removed from consideration. Only peer-reviewed/refereed, blind-reviewed, full-length published articles were thoroughly examined to confirm their appropriateness for

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our study. Editor notes, prefaces, research notes, industry articles, internet publications, conference preceding, books and book chapters were excluded. However, we included working papers because those are also peer-reviewed, full-length and online articles. If any study included more than one subject, then only the main area of focus was considered. We scanned and reviewed articles in hospitality and tourism journals through the EBSCO, JSTOR, Google Scholar, Emerald, Scopus, LexisNexis Academic, CAB Abstracts, ORCID, SSRN, ProQuest, ScienceDirect, Statista and Hospitality and Tourism Complete research databases and full-text collections. For each journal scanned, we searched for the keywords related but not limited to “social media”, “social media and financial performance”, “online reviews and hospitality firm performance”, “hotel sales and internet reviews”, “word of mouth and restaurant firm performance”, “social media and profit analysis in hospitality industry”, “online review sites and financial performance of hospitality firms” and “social networking sites and financial performance”. We excluded all the published articles that do not directly relate to research field SM and firms’ financial performance in the hospitality industry. When all the eliminations and screening processes were done, the final sample consisted of 26 articles: 24 journal articles and 2 published full-text working papers related to SM and firms’ financial performance in the hospitality and tourism context. Table I lists the article counts for each journal category. Social networking outlets and financial performance SM phenomenon significantly impacts firms’ financial success, structure and survival in global competitive markets. With the rise of SM usage, service-oriented, knowledge-based

Journals in hospitality field International Journal of Contemporary Hospitality Management International Journal of Hospitality Management Tourism Management Journal of Business Research Cornell Hospitality Quarterly Tourism Economics Computer in Human Behavior Journal of Revenue and Pricing Management Marketing Intelligence & Planning International Journal of Information Management The Service Industries Journal Journal of Hospitality and Tourism Technology Journal of Travel Research Information and Communication Technologies in Tourism Service Science The Scholarly Commons. Cornell University University of Hertfordshire Business School Working Paper Collections Harvard Business School Working Paper Collections Table I. Classified list for journals reviewed

No. of articles

Journal classification and focus

5

Hospitality Administration & Management

4 2 1 1 1 1 1 1 1 1 1 1 1

Hospitality Administration & Management Tourism & Tourism Management Business & Management Hospitality Administration & Management Hospitality Administration & Management Travel & Hospitality Management Hospitality Administration & Management Marketing Information Management Service Management Technology Travel & Leisure Tourism & Technology

1 1 1

Service Management Hospitality Administration & Management Travel & Leisure

1

Hospitality Administration & Management

Notes: This table reports the breakdown of the journals, number of articles analyzed for each journal and the main focus and classification of the journals for 21 articles from January 2011 to December 2016; numerical figures in parentheses represent the number of papers reviewed from respective journal

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hospitality and tourism companies’ operations are democratized based on a new consumer culture and norms. This worldwide transformation in the travel, tourism and hospitality arenas has drawn researchers to empirically and theoretically investigate the effect of this knowledge-sharing culture on firms’ financial performance (Buhalis and Mamalakis, 2015; Xie et al., 2014).

Social media and firms

Web 2.0 and UGC platforms and financial performance in the lodging industry Advocates have been heavily focused on the relationship between several different online consumer review sites and UGC platforms and firms’ financial performance, as measured by various proxies, in the hotel and lodging industry. Viglia et al. (2016) examined the influence of eWOM on hotel occupancy rates by analyzing the online reviews and occupancy rates of 346 hotels in Rome, Italy. They collected data from online review sites regarding review scores, recommendation consistency and volume. The analysis indicated that the review score was the most significant factor in terms of impact on hotels’ occupancy rate. Their findings indicated that eWOM in the form of consumer ratings and volume had a significant impact on hotels’ financial performance via their effects on occupancy rates. Blal and Sturman’s (2014) paper also concentrated on eWOM but on hotel room sales and revenue per available room (RevPAR). They conclude that a high volume of comments does not apply to high-end hotel properties or perhaps to any hotel at all. Xie et al. (2014) analyzed the value of online consumer reviews and management response to hotel performance. They collected hotel review and management response data from TripAdvisor.com and matched those data with RevPAR data from hotels in five major hotel markets in the state of Texas, USA. They measured online consumer reviews using ratings, review volume and variation. The findings of the study were consistent with previous studies: consumer reviews had a positive impact on hotel performance. However, they also found that management responses had a negative impact on RevPAR. Additionally, Anderson (2012) analyzed the effect of SM on consumer purchasing decision and hotels’ financial performance. He found that the number of visits to TripAdvisor was increasing, while time spent per visit was decreasing due to the faster and more efficient search function. Anderson also measured the performance of hotels using ReviewsPro’s Global Review Index (GRI) and Smith Travel Research (STR) data. He estimated that a 1 per cent increase in GRI increases the average daily rate (ADR) by as much as 0.89 per cent and occupancy by as much as 0.54 per cent. Combining this effect shows that a 1 per cent increase in GRI increases RevPAR by 1.42 per cent. This analysis clearly indicates a performance increase due to higher and more positive SM activity. In the same token, Duverger (2013) investigates the effect of UGC on firm performance. Out of 138 properties in 13 different markets, the results demonstrate that UGC has a positive impact on market share via curvilinear relationship, especially in lower-tiered hotel properties as compared to the upper/luxury hotel segments. Additionally, the authors found it interesting that reviews, overall, have a negative impact on market share more frequently than they have a positive impact. Kim et al. (2015b) investigated how firm performance was affected by online customer reviews and firms’ responses to those reviews. The authors focused on four main factors: the relationship between overall rating and firm performance, number of online reviews and online performance, the association of the response to negative comments and firm performance and the links between variance (standard deviation) of online review ratings and hotel performance. Their findings show that the overall ratings and the response to negative comments were positively related to hotel performance (ADR and RevPAR). The number of reviews and the variation in ratings, as measured by standard deviation of the ratings, were found to be insignificant. Ye et al. (2009) focused on the same topic across Chinese hotels. Their findings were consisted with prior studies that online user reviews

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have both negative and positive effects on online sales of hotel rooms based on many factors, such as hotel star ratings. Ye et al. (2011) carried on their empirical investigation and examined the effect of UGCs on hotel online booking in China. Even though their findings were slightly different than their previous study, the bottom line of the relationship was the same. Tuominen (2011) examined whether online word-of-mouth (online-WOM) affects a hotel’s bottom-line performance. He collected data on customer-generated content (online-WOM) from TripAdvisor for selected hotels in five northern European cities and one Saudi Arabian city: 520 hotels and 1,752 online reviews in total. Tuominen reported a considerable relationship between the number of reviews written on TripAdvisor and the ADR and RevPAR. He also noted a positive association between the review advantage score and ADR, RevPAR and occupancy level. In the same vein, the major contribution of Sparks and Browning’s (2011) paper to the existing body of literature was that even when the reviews were generally bad, booking intentions were relatively high in a positive frame compared to a negative frame. Parallel to above studies, Xie et al. (2016) hypothesized the interrelations among the volume of consumer-generated eWOM, managerial response to customer ratings and hotel financial performance. They collected 56,284 daily consumer reviews, of which 10,793 had attached managerial responses from TripAdvisor.com in five major hotel markets in Texas. They utilized total revenue available per room (TRevPAR) and RevPAR as two key hotel financial performance metrics. Their findings revealed that managerial response alone does not have a significant influence on hotel performance. The authors’ main inference was that positive feedback and the response on the part of managers to online consumer reviews positively moderates the effect of the volume of consumer reviews on hotel performance and increases TRevPAR and RevPAR. A study by Zhang et al. (2011) investigated the effect of consumer-generated eWOM on various types of hotels’ room rate performances and structures in New York City at the end of 2009. Within the scope of their investigation, the authors emphasized certain types of websites (i.e. TripAdvisor) on which online customer reviews and ratings were the most accessible and prevalent. Based on their regression estimations, they found that hotel class, as shown on online consumer portals, is the most important determinant of room price for hotels in New York City. Those hotels’ room prices are also tremendously affected by reviews and opinions on room quality and location. Ogut and Tas (2012) investigate how online customer ratings influence a hotel’s online sales and prices by making use of online booking platforms. All the information on the hotel star ratings, the region of the hotel in the city, the room price per night, the average customer rating, the number of hotel rooms and number of customer reviews were obtained from www.booking.com for the period from January 2009 through May 2009. The authors’ analyses revealed that higher customer ratings significantly increased the online sales of hotels. Contrary to their expectations, a higher star rating is not associated with an increase in sales. They also show that an improvement in customer ratings results in not only higher sales but also higher price for the hotel rooms. A further finding of the study is that the star ratings of hotels significantly affect the sensitivity of room prices to customer ratings. Noone et al. (2011) also worked on hotel room pricing and revenue management in correlation with SM technologies. They discussed many opportunities and issues as well as the future challenges within the context of SM dynamics and hotel revenue management practices such as pricing, discounts and customer demand to hotel products. Further, one of the most intriguing findings of Phillips et al.’s (2015) study is the relationship between the response rate to negative comments and hotel performance. The authors examined the influence of UGC, particularly online reviews, on financial performance among Swiss hotel firms. The authors used an artificial neural network to reveal the determinants of hotel performance.

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Second, the analysis was conducted using an aggregated data set, TrustYou (www.trustyou. com), which combines online reviews from 69 review and SM sites worldwide. Phillips et al. (2015) also documented that online reviews, together with traditional hotel characteristics, should be viewed as important determinants of hotel performance. In Anderson and Lawrence’s (2014) study, the main focus was firm reputation, as measured by ReviewPro’s GRI, which is used to analyze effect of social presence on hotel performance measures, such as revenue. In addition to firm reputation and performance, the authors also analyzed the moderating effect of heterogeneity on performance. Their findings confirm that higher online consumer review ratings have a positive relationship with RevPAR. Price elasticity of demand shows that a 1 per cent increase in reputation results in a 0.99 per cent increase in RevPAR. They also found that product heterogeneity, as measured by hotel type, moderates the relationship between reputation and performance. Overall results indicate that luxury and midscale hotels have less pricing power as compared to other types of hotels, which results in them using different strategies to maximize RevPAR. The articles cited above were specifically focused on the effect of UGC, Web 2.0 platforms and eWOM activities on various internal performance metrics of hotel and lodging enterprises. The effect of SM on lodging establishments’ financial performances (i.e. room pricing and revenues) is different when variant samples and various sources are examined at different time frames. Even though samples were different than each other, the consensus was that UGCs and Web 2.0 platforms have tremendous effect on various internal financial performance indicators, such as RevPAR, ADR, sales, room prices, room revenues, occupancy rates, room reservations, etc. Web 2.0 and UGC platforms and financial performance in the restaurant industry Online reviews and financial performance were also analyzed within the restaurant industry. Luca (2011) investigates the effects of consumer reviews on restaurant revenue. He collected reviews and ratings information from Yelp.com. Restaurant revenue data were collected from restaurants in Seattle from 2003 to 2009 through the Washington State Department of Revenue. The study used a regression discontinuity (RD) design to determine whether discontinuous changes in Yelp ratings were followed by discontinuous jumps in revenue. The results show that a one-star increase in ratings results in a 5-9.0 per cent increase in revenue for independent restaurants. Next, the study investigated the revenues of chain restaurants and found that the impact of a one-star increase in ratings was statistically insignificant and close to zero. This result is understandable in that more information about the quality of the product is already available for chain restaurants, but the results also indicate that as Yelp penetrates into the market, revenue shifts toward independent restaurants. Kim et al. (2016) investigated the impact of traditional restaurant attributes on the financial performance of restaurants, along with newly proposed determinants of restaurant performance: SM reviews (number of online reviews), a competitive ranking of the subject unit relative to competitive sets and an operational efficiency measure (i.e. guests served per hour of labor). Moreover, they also explore the potential moderating role of restaurant excellence certification in the relationship between firm performance and its determinants. As the sample of the study, Kim et al. (2016) use a chain restaurant company that operates more than 70 restaurants in 16 states of the USA. Financial performance data are provided by the companies such as TripAdvisor, Urbanspoon and Foursquare, as well as researchers’ surveys. The main independent variables of the study are the number of reviews, restaurant ranking and operational efficiency. The net sales, guest counts and average check act as proxies for the dependent variables. The findings of the study indicate that the number of reviews has a significantly positive effect on restaurant financial

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performance – net sales, guest counts and average check. Moreover, the study finds that restaurant rankings significantly contribute to the prediction of restaurant performance. The analyses also show that having an excellence certificate moderates the relationship between the number of online reviews and restaurants’ financial performance. Aforementioned studies particularly focused on restaurant firms’ financial behavior when they engage in SM activities. It is clear from the findings, results and observations that restaurants’ financial success is impacted by the reviews online (i.e. Yelp). The association between SM technologies and financial performance of the restaurant firms also has influences on restaurant employee turnovers and labor structure. Thus, besides financial performance, those studies also shed a light on efficiency measures of restaurants’ business functions. Built-in SM portals, mobile applications and firm performance Some attention is paid to the impact of SM portals, activities, environments and practices on firms’ financial performance. Makki et al. (2016) investigated the effect of a last-minute discounting strategy on hotels’ profitability performance. The focus of this paper is the relationship between a last-minute hotel-booking mobile app – HotelTonight – and the ADR, occupancy and net operating income (NOI) from top Florida destinations. The findings were aligned with previous findings: there is a positive relationship between ADR and NOI. The analysis also showed a significant and positive relationship between hotels’ use of HotelTonight and occupancy rate. Furthermore, the results indicate that using HotelTonight improves hotels’ NOI. Kim et al. (2015a) examine the relationship between SM activity and the financial value of restaurant firms. Authors measured restaurant firms’ value with Tobin’s q. They also utilized the restaurant social media (RSM) index score to show the levels of participation in SM sentiment tracking, competitive comparisons and the levels of engagement among restaurant brands (Twitter, Facebook, Klout analytics and Social Insights). In addition to the main independent variables, this study used several control variables: size, leverage, short-term profitability, dividend payout per share and firm growth. The findings of the study support a positive and linear relationship between restaurant firms’ SM activity and firm value. Inversini and Masiero (2014) analyzed the use of SM and online travel agencies’ (OTAs) room sales patterns. They investigated the importance of SM and OTAs in online sales. The authors collected data from 97 hotels in Switzerland, using a questionnaire that included questions about how important the hoteliers find SM and OTAs, as well as other factors related to the selection of the platforms. The findings of the study indicate that there is a direct, positive relationship between the importance of OTAs for hoteliers and the importance of SM in terms of online sales. The results also indicate that the functionality of booking technology and the effectiveness of marketing and resources are significant factors that impact the use of social media. Furthermore, the popularity and importance of the platform were the two factors that positively impacted the use of OTAs in online sales. Using a SM marketing theory, Wu (2016) studied the effects of the emerging SM environment on organizational strategy and performance from a resource-based viewpoint. The author used qualitative methods to gather research constructs and variables and used quantitative methods to develop models with which to measure SM variables. Using confirmatory factor analysis (CFA) and path analysis, the study findings indicated that SM strategy had a significant, positive impact on firm performance. Buhalis and Mamalakis (2015) focused on social media’s return on investment (ROI) and performance evaluation in the hotel industry. They assessed the effectiveness of various SM) channels in terms of ROI. The authors used Google Analytics for Web analytics, such as the number of visits, traffic sources and conversion rates. The authors used WebHotelier for reservation and analytics

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analysis, such as the number of referral visits, the number of bookings and revenues from referral sources. Finally, the authors used Facebook for social network analysis, such as post-analysis, page likes and engagement rates. ROI is calculated as follows: [(Gain of investment-Cost of investment)/Cost of Investment]. Their findings showed that if actual sales are higher than the forecasted sales, this difference can be attributed to SM return approach, which showed an increase in revenue of 134.61 per cent. The authors concluded that this can be partially attributed to the contributions of the TripAdvisor and HolidayCheck referral websites. Separating these earlier and extended examination periods showed an ROI of 65.6 per cent. In a recent paper, Neirotti et al. (2016) investigated the role of SM in the Italian hotel industry. More precisely, they focus on understanding the extent to which hotel firms utilize SM tools and how online customer reviews affect a hotel’s bottom-line performance. Neirotti et al. (2016) randomly picked 240 hotel firms from AIDA, an Italian database for financial and operational data. Online reviews were collected from TripAdvisor. The main independent variable of the investigation is online visibility, which is constructed based on three sub-constructs: the number of reviews, the online rating and the dispersion of the online ratings. Three performance indicators are used as the dependent variables of the study: revenue growth, gross profit margin difference and net profit margin difference. The study finds that consumer online ratings matter the most in term of achieving online visibility and their effect exceeds that of the number of online reviews. E-marketing efforts using SM are another emerging line of research within the hospitality and tourism context. Tsiotsou and Vlachopoulou (2011) examine the inter-relation between market orientation and e-marketing, as well as their impact on company performance in the tourism industry. The authors argued that firms’ market orientation and e-marketing efforts have direct and indirect effects on tourism services performance. Tourism service performance has also been categorized using three attributes: service productivity, service quality and net profit. The results demonstrate that market orientation has significantly positive and direct effects on both tourism performance and e-marketing. Taken all together, the body knowledge related to built-in SM portals and mobile applications suggested positive and direct influences on hospitality firms’ financial performance and success. Therefore, the main inference is that SM is the new platform for doing business and managements need to embrace the change in new policies and business functions due to constantly advancing SM best practices at a very high speed (Table II). Concluding remarks Knowing what has been achieved in SM and financial performance research in the near past can help us better predict and plan for future research developments. Therefore, this study summarizes and reviews the literature from January 2011 to December 2016 in regard to the effect of social networking sites and SM outlets on hospitality and tourism firms’ financial performance and outcomes. We provide a detailed abstract concerning the main focus, the results and findings, the discussions and the contributions of each article written over the specified time frame. We aimed to provide extensive research results, findings, evidence and the overall outlook regarding the association between SM and hospitality and tourism companies’ financial performance. In this light, we reviewed a total of 26 peer-reviewed scholarly publications from several research databases such as EBSCO. The majority of the articles were published in top-tier hospitality and tourism management and administration journals. Some of the articles in regard to SM and financial performance within the hospitality and tourism research context were published in second-tier hospitality, leisure, tourism and travel journals. However, some others were published in non-hospitality journals, such as the Journal of Business Research, Marketing Intelligence & Planning and the

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The differential effects of the quality and quantity of online reviews on hotel room sales

The influence of recent hotel amenities and green practices on guests’ price premium and revisit intention The impact of online reviews on hotel booking intentions and perception of trust The impact of online user reviews on hotel room sales The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings Social media meets hotel revenue management: Opportunities, issues and unanswered questions Determinants of hotel room price: An exploration of travelers’ hierarchy of accommodation needs

Blal and Sturman (2014)

Kim et al. (2016b)

Understanding the effects of market orientation and e-marketing on service performance The influence of internet customer reviews on the online sales and prices in hotel industry

The effectiveness of managing social media on hotel performance

Tsiotsou and Vlachopoulou (2011)

Kim et al. (2015b)

Ogut and Tas (2012)

The influence of TripAdvisor consumer-generated travel reviews on hotel performance

Tuominen (2011)

Zhang et al. (2011)

Noone et al. (2011)

Ye et al. (2011)

Ye et al. (2009)

Sparks et al. (2011)

Effects of managerial response on consumer eWOM and hotel performance: Evidence from TripAdvisor

Xie et al. (2016)

Table II. Summary of published academic studies

Title of the study

International Journal of Hospitality Management

The Service Industries Journal

Marketing Intelligence & Planning

University of Hertfordshire Business School Working Paper Collections

Journal of Revenue and Pricing Management International Journal of Contemporary Hospitality Management

International Journal of Hospitality Management Computers in Human Behavior

Tourism Management

Tourism Economics

Cornell Hospitality Quarterly

International Journal of Contemporary Hospitality Management

Journal published

Managerial communication through eWOM on social media and financial performance of various lodging establishments The effect of TripAdvisor scores (eWOM), the number of reviews on lodging sales performance, and the moderating effect of the hotel segment on these relationships The influence of hotels’ salient attributes on customers’ overall online evaluation, revisit intention, and hotel performance Factors that influence whether prospective tourists would book hotel rooms online The impact of online WOM on Chinese hotel bookings at the organization level The impact of online user-generated reviews on Chinese hotel online booking performance The effect of social media on hotel’s revenue and pricing Online ratings of travelers through online consumer sites (i.e. TripAdvisor) and hotel room price performance The impact of customer generated content (eWOM) on hotel performance (i.e. ADR, RevPAR and occupancy) Market orientation, e-marketing, and their influence on tourism services performance Online customer ratings (available at www.booking.com) and star ratings and their association with online hotel prices and sales Online customer reviews and ratings in the hotel industry and their effect on ADR and RevPAR. Dealing with negative online reviews to enhance financial performance (continued)

Primary focus and main argument(s) of the study

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Author(s) and year of publication

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The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis Are customers’ reviews creating value in the hospitality industry? Exploring the moderating effects of market positioning

Phillips et al. (2015)

The influence of online reputation and product heterogeneity on service firm financial performance

Social media return on investment and performance evaluation in the hotel industry context

Curvilinear Effects of User-Generated Content on Hotels’ Market Share: A Dynamic Panel-Data Analysis Effects of social media on firm value for US restaurant companies

Anderson and Lawrence (2014)

Buhalis and Mamalakis (2015)

Duverger (2013)

Luca (2011)

Reviews, Reputation, and Revenue: The Case of Yelp.com

The impact of social media on lodging performance

Anderson (2012)

Kim et al. (2015a)

The impact of social media reviews on restaurant performance: The moderating role of excellence certificate

Kim et al. (2016)

Neirotti et al. (2016)

Title of the study

Author(s) and year of publication

Harvard Business School NOM Unit Working Paper

International Journal of Hospitality Management

Journal of Travel Research

Information and Communication Technologies in Tourism

The Scholarly Commons. Cornell University Service Science

International Journal of Hospitality Management

International Journal of Information Management

Tourism Management

Journal published

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Examination of the effect of user generated content (eWOW) on Swiss hotel industry through artificial neural networks The role of user generated content in hotel revenue growth, gross profit margin and net profit margin. Distribution of value generated via online visibility with other distributors Traditional determinants of restaurant performance, association between online reviews and restaurant performance, and moderating effect of excellence certificate in the relationship between online reviews and restaurant performance Effect of social media on consumers’ purchase decision and hotels’ performance The influence of firm reputation as measured by ReviewPro’s Global Review Index (GRI) on hotel performance measures such as revenue, demand, and supply Effectiveness of various Social Media (SM) channels and Return on Investment (ROI) on those channels The effect of User Generated Content (UGC) on firm performance and their non-linear and dynamic relationship The relationship between social media activity of restaurant firms and value of firms (Tobin’s q) The study employed regression discontinuity design to investigate effect of consumer reviews on restaurant demand (continued)

Primary focus and main argument(s) of the study

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Table II.

Selling rooms online: The use of social media and online travel agents

The influence of e-word-of-mouth on hotel occupancy rate The performance impact of social media in the chain store industry The business value of online consumer reviews and management response to hotel performance

Inversini and Masiero (2014)

Viglia et al. (2016)

International Journal of Contemporary Hospitality Management

International Journal of Contemporary Hospitality Management Journal of Business Research

International Journal of Contemporary Hospitality Management

Journal of Hospitality and Tourism Technology

Journal published

The study investigates last minute discounting strategy’s effect on property performance The relationship among the functionality of booking technology, effectiveness, social media, and rooms sales. OTAs’ utilization of social media for room sales performance Online review scores from eWOM sites and the patterns of hotel occupancy rates Social media strategy and firm’s financial performance The impact of online customer reviews and hotel performance (RevPAR)

Primary focus and main argument(s) of the study

Notes: This table details the content of the existing published academic articles in regard to the association of social networking sites, social media and firms’ financial performance from January 2011 to December 2016; this table is compiled by the authors

Xie et al. (2014)

Wu (2016)

HotelTonight usage and hotel profitability

Makki et al. (2016)

Table II.

Title of the study

50

Author(s) and year of publication

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International Journal of Information Management. Our findings from the in-depth review analysis indicated interesting results about the effect of SM usage on hospitality firms’ financial performance. One of the most intriguing findings is that we observed that advocates have mostly focused on the effects of the UGC SM outlets (i.e. TripAdvisor, Urbanspoon, Foursquare, Yelp, HotelTonight, etc). and social platforms with Web 2.0 concept (i.e. Facebook and Twitter) on different types of hospitality and tourism firms’ financial performance that mostly concentrates on internal operations. For instance, the effect of online reviews, customer perceptions and guest satisfaction scores gathered from different SM outlets on hospitality firms’ net profit, NOI, RevPAR, TRevPAR, sales volume, occupancy rates, revenue margins, ADR is the most common and main focus in previously published research within this field. Having examined the empirical content of all the articles, we additionally found that authors widely investigated the financial performance of hospitality and tourism firms (especially lodging and restaurant establishments through eWOM spread over various SM and UGC channels, i.e. Yelp, TripAdvior, etc.). Finally, some of the research was inclined to examine the versatility of different type of hotel firms’ financial performance (i.e. room prices, discounts, occupancy rates) depending on customer usage of online booking sites for room reservations. Take all together, our main inference is that individual results of each paper we analyzed and the particular influences of different SM channels on firms’ financial performance depend on the different company operations, size, business orientation, culture, financial structure and geographical location. In other words, even though the effect of SM is different to various types of hospitality and tourism firms, it apparently plays an important role in firms’ financial outcomes both positively and negatively. Our reviews provide a blueprint to guide future research, facilitate knowledge accumulation and create a new understanding and awareness in SM and financial performance research based on the gaps and issues we observed. Gaps identified and future research directions One benefit of critical review studies is that those papers can engender innovative, previously unconsidered, research endeavors; add new insights and knowledge to perennial issues and gaps; and allow for multiple new mental constructions via deeper reasoning. The existing evidence has helped us in understanding the foundations and interactions of SM and hospitality and tourism firms’ financial performance. However, although how SM contributes to firms’ financial performance is clear to academicians and industry professionals, no solid consensus or theoretical certainty about what we know and do not know has been collectively achieved. This uncertainty mostly stems from the constantly evolving, dynamic nature of SM and its technological components. Thus, this creates a vital gap in academic research. The relevance of these advancements is restricted to a certain research focus and stance in the empirical and theoretical studies we reviewed. A prudent way to address this gap is to synthesize what is known about SM and firms’ financial performance by creating a very clear portrait of new research ideas, propositions and development for the future agenda. Systematically forming analytical practices with immediate data and knowledge will support future research opportunities and build new methods for use in the future. Across the papers we analyzed, we noticed that the SM phenomenon and its relationship to firms’ financial structures and outcomes are not fully examined in all their aspects. Thus, research designs and ideas are somewhat restricted, and the evidence presented in those papers is isolated from many essential measures and key points. In other words, the academic research field of SM and financial performance is devoid of new perspectives. For instance, existing papers concentrate upon property-level analysis rather than corporate-level analysis, especially when financial performance measures are

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considered. We clearly observed that none of the papers went beyond analyzing the effect of SM on hotels’ RevPAR, revenues, net profit, ADR, occupancy rates, NOI, etc., and all papers ignored the analysis of many critical financial proxies. SM is not only an indispensable phenomenon for hospitality and tourism establishments but also for corporations. Corporations tailor their goods and standardize their services based on consumer feedback so that they can generate additional revenues, earnings and cash flows. If SM affects individual properties’ revenue and earnings, it must impact earnings at the corporate level as well. Thus, it is of utmost importance for academic studies to examine the effect of this phenomenon on various financial proxies and items in various financial statements at the corporate level, such as stock returns, dividend payouts based on the level of retained earnings, earning price per share, cash inflows, etc. In line with this, considering the cost of implementing SM at both the single-establishment and corporate levels in comparison to financial performance, as seen on various financial statements could be a logical extension for future research attempts. However, one of the most important potential problem and constraint of quantitatively examining the effect of SM technologies and platforms on corporate-level financial performance and/or structure (i.e. SM practices and firm’s equity value) is to face with limited data, which stem from the limited number of publicly traded hospitality and tourism firms. This will most likely create data-selection biases and possibly the findings will have general validity and reliability issues when researchers try to extend their research in this field. Apart from this, under a broad definition of SM, the papers we reviewed captured and investigated various online review sites and UGC platforms (i.e. TripAdvisor, Booking.com, Foursquare, Urbanspoon, TrustYou.com, ReviewPro, etc). within the hospitality and tourism industry. In most papers, the authors attempted to understand the relationship between eWOM and firms’ financial performance. Because only two papers examined Twitter and Facebook and only one paper focused on Yelp in the context of the hospitality and tourism industry, the analyses, experiments and understanding are insufficient, and the findings and arguments remain unresolved. Thus, it is difficult to believe that the link between consumer feedback and reviews submitted via multiple SM channels and financial performance is actually understood. This is one of the important areas that must be explored with a deeper focus in the future. Samples are mostly composed of various lodging and hotel companies and/or establishments. The rapid development of SM and financial performance studies over the past decade has reduced the importance of understanding historical patterns and predicting future trends in other major sub-sectors, such as the restaurant industry. Our review shows that there are only two published papers with a sample of restaurant firms and one paper focused on OTAs’ sales performance in relation to SM. We believe that understanding how the various characteristics of consumer feedback moderate that feedback’s effect on performance in other service-based industries is vital to producing non-monotonic results for the industry. As an example, the effect of SM can be examined in establishments and/or corporations that must set their prices dynamically to optimize financial returns due to capacity constraints, volatile customer demand and high seasonality impact (i.e. airline industry). Today, the SM phenomenon and hospitality and tourism firms’ core business functions are interdependent so as academic research in this field. Hence, according to the gaps and issues identified above, three major challenges for future research in this regard are identified: one, determining how to integrate various scopes of SM in evaluating firms’ financial performance at both the single-establishment and corporate levels; second, determining what aspects of financial performance and outcomes are tied to the SM

phenomenon and various social media platforms in other hospitality and tourism industries; and third, widening the main focus of the current research in hospitality and tourism field in line with the seminal papers published in mainstream technology and business research journals. References Anderson, C. (2012), “The impact of social media on lodging performance”, The Scholarly Commons, Vol. 12, Cornell University, pp. 6-11.

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Corresponding author Murat Kizildag can be contacted at: [email protected]

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