The purpose of this study is to analyze the characteristic of quality attributes of smart hotels by using a SERVQUAL-IPA model, focusing on Chinese, which has the most proactive approach for the adoption of smart hotel system. Toward this goal, six quality factors—tangibles, reliability, assurance, responsiveness, empathy, and playfulness—were extracted through factor analysis, and IPA was used to appraise the degree of importance and satisfaction for each quality attribute. As a result of the SERVQUAL-IPA model, quality attributes were categorized into four groups of 'keep up the good work,' 'possible overkill,' 'low priority,' and 'concentrate here.'. Furthermore, it was concluded that there is a need to focus on the following elements: ‘smart devices can assist customers in emergency situations’, ‘when the room control system identifies customer needs, the staff can provide prompt service’, ‘development and improvement of mobile applications that enable customers to control room amenities’, ‘regular maintenance for smart devices’, and ‘providing data-driven personalized recommendations through customer activity data analysis’.

본 연구는 코로나 팬데믹 이후 호텔전공 대학생들의 전공만족도가 취 업 준비 행동 간의 영향 관계를 검증하였다. 조사대상자 260명의 응답을 바탕으로 가설검정 결과 교과 만족, 인식 만족, 관계 만족이 모두 취업 준비 행동에 부분적으로 정(+)의 영향을 미치는 것으로 나타났다. 특히 인식 만족이 높을수록 직간접적 취업 준비 행동에 미치는 영향이 높았 다. 본 연구는 학문적으로는 인식 만족이 높을수록 취업 준비 행동에 높 은 영향 관계를 맺는 것에 주목하여 사회적 인식의 변화가 호텔산업 고 용시장의 구인난을 해결하는데 촉매 역할을 할 수 있음을 밝혔고, 실무 적으로는 다양하고 혁신적 교수법과 교과목 개발, 실무수업과 이론 수업 의 적절한 조합, 학생 맞춤형 상담과 취업지도, 커뮤니케이션 강화 등을 통해 호텔 전공학생의 전공만족도를 향상하고 이를 바탕으로 취업 준비 행동을 촉진 시킬 수 있음을 증명하였다.

This study examines the performance of a penalized neural network and the replication of a customer engagement survey scale with text information in the hotel industry. Although the empirical analysis shows highly accurate model performance only in the training sample, the results also clarify the issues of the engagement scale.

The study proposed a dual-path model to examine the relationship between customer perceived hotel innovativeness and customers’ interactivity, building the signaling theory. The model was tested with hotel customers from China. The findings suggest that customers’ perceived hotel innovativeness not only has a positive and direct impact on their interactivity, it also indirectly contributes to customers’ interactivity via two indirect paths, one featuring a cognitive-economic motivation pathway and the other featuring an affective-motivation pathway.

Based on the Anthropomorphism theory and the Computers Are Social Actors paradigm, this research adopts questionnaire method and explores the relationship between robot anthropomorphism, social presence, social cognition and consumer’ continued using intention. In addition, we select technology anxiety as the moderator to explore its boundary effect

The development of Information Communication Technologies (ICTs) has dramatically changed the way of hotel booking. The increasing number of online consumers provides abundant data for demand forcasting in revenue management. The current methods e.g. historical data analysis, normally focus on studying consumers’ behaviors and preferences in the hotel but may not be able to integrate that out of the hotel such as dining, travelling, shopping and entertaining, which will bring crucial references to the co-relationship between these consumption and the way of hotel booking. This research adopts a persona approach to infer consumers’ preference probability by using a variety of real-time data. Quantitative methods are employed. In order to predict the booking needs accurately, this research establish a Bayesian network on the online platform for life service that can be associated with various consumer behavior data. The results indicate that in the environment of uncertain demand, the algorithm is effective and applicable, which will help directors of hotel revenue management in accurate price planning and decision making.

Since social media has become an essential tool in the contemporary hotel industry, companies are now building social media communities to engage customers online (Leung & Bai, 2013) and to maintain satisfaction, trust, commitment, loyalty, and brand relationship quality (Harrigan, Evers, Miles, & Daly, 2017). Despite global hotel companies’ increasing adoption of social media platforms to promote customer engagement, research in this area is still sparse (Harrigan et al., 2017; So, King, & Sparks, 2014). To fill this gap, the authors developed a theoretical model incorporating two antecedents (hotel brand experience and customer involvement to social media) and a consequence (brand relationship quality) of customer engagement (CE) in the context of hotel brand communities embedded in social media. Additionally, the authors included hotel brand reputation (HBR) in the model as another predictor of brand relationship quality (BRQ). This study obtained data from a panel survey consisting of the responses of hotel customers who had stayed at one of ten famous hotel brands in the U.S. within the past 12 months and were simultaneously followers of the hotel brand’s page on Facebook. The findings reveal that both antecedents (ISM and HBX) positively and significantly influence CE and that hotel brand experience (HBX) has a stronger impact on CE than ISM. The findings also demonstrate that CE has the strongest, positive effect on BRQ, followed by HBX and HBR. Furthermore, the findings indicate that the relationship between HBX and BRQ is partially and significantly mediated by CE. This research provides theoretical and practical contributions to the field. First, unlike previous studies, the current study utilized the concept of CE with hotel brand communities embedded in social media as a mediator between HBX and BRQ and found partial and significant mediation effects. Second, the study identified two new and crucial antecedents of CE with brand communities embedded in social media—customer brand experience and customer social media involvement. Third, this study found brand relationship quality as one of the primary outcomes of customer engagement with hotel brand communities in social media. Lastly, the findings confirm that social media-based brand communities (i.e., Facebook) are one tool companies can use to build long-lasting customer-brand relationships.

This is a cross-culture study looking into how organization’s customer orientation and empowerment influence hotel employees’ three types of OCBs (OCB-O, OCB-I and OCB-C). Using data collected from US and Australia employees, the study found that customer orientation was a significant predictor of employees’ three types of OCBs, while empowerment was only a significant predictor for employees’ OCB-C. Culture was found to moderate the proposed relationships, with stronger relationships observed in US than in Australia.

An increasing number of Internet users use hotel booking websites and online travel agencies to arrange trips and search for information related to their travels. This study investigates the impact of customer engagement on user perceptions of the quality and value of an online hotel-booking website, as well as whether such perceptions further influence user trust in online websites (eTrust) and result in behavioral intention of eLoyalty. The empirical results of structural equation modeling analysis of 400 questionnaire results collected in Taiwan reveal that customer engagement has a positive impact on perceived website quality (i.e., usability, ease of use, entertainment, and complementarity), which in turn influences perceived value. The results do not show a direct impact from customer engagement on perceived value. Finally, the results verify that eTrust mediates the relationship between consumers’ perceived website quality and behavioral intention of eLoyalty toward an online hotel-booking website; eTrust also mediates the relationship between consumers’ perceived value and behavioral intention of eLoyalty toward an online hotel-booking website. The findings provide both academic researchers and practitioners with a better understanding of customer engagement and facilitate development of more effective customer engagement strategies for online booking platforms.

With competition among hotel brands intensifying more than ever before, there has been a burgeoning interest in the hospitality industry on the topic of brand love. However, progress of brand love research in hotel context has been limited and investigation on antecedents of brand love has mainly focused on affective and relational aspects, while neglecting cognitive aspects of brand love. Therefore, the objective of this research was to illuminate the importance of brand love's cognitive aspect by identifying cognitive brand loyalty as a necessary component of brand love in hotel context. In addition, present research suggests that by inducing cognitive engagement among customers, hotel brands can attain cognitive brand loyalty from customers, which in turn derives brand love. To achieve the research objective, a questionnaire with items measuring brand love, cognitive brand loyalty and two aspects of cognitive engagement, cognitive attention and cognitive absorption, was distributed to 300 individuals through Amazon Mechanical Turk. Brand love was measured with scale adapted from Carroll and Ahuvia (2006), cognitive brand loyalty was measured using items introduced by Back and Parks (2003), and cognitive engagement elements were measured using items developed by So, King and Sparks (2014). In analyzing the data, structural equation modeling method was used. The findings of the study indicate that the effect of cognitive brand loyalty on brand love is significant and that the relationship between cognitive attention and cognitive brand loyalty is also positive and significant. However, the relationship between cognitive absorption and cognitive brand loyalty was positive only at a marginally significant level. As a result, the indirect effect of cognitive attention on brand love was positive and significant yet, the indirect effect of cognitive absorption on brand love was insignificant. This study enriches the brand love literature’s spectrum by illuminating the importance of brand love’s cognitive aspect. However, it is important to note that the focus is not necessarily on the cognitive processing or the standards, but on the cognitive engagement experience. In addition, because customers generally process information most heavily during the booking process, present research brings out managerial implications for hotel brands to direct more customers to their own brand website rather than the online-travel-agency( OTA) website. For instance, the results of present research illustrate that price discount or additional amenity are not enough to develop brand love. Rather, hotels should provide loyalty members who book directly through brand sites with more enjoyable, creative, and relevant to self-room shopping experience.

We aim to determine the level of Image Interactivity Technology which can create an optimal engagement on the online consumer’s experience while surfing on hotel websites. Our model includes three personal traits as moderating variables and will be tested through a mixed approach (i.e. experiment, interview and questionnaire).

Online review sites such as Booking.com or Tripadvisor are considered to be the most accessible and valuable feedback platform in the hospitality industry (Verma et al., 2012; Xiang & Gretzel, 2010; Yoo & Gretzel, 2008). To keep pace with customers’ use of social media, hotels have recently begun to use customer-generated content or online reviews to assist in decision-making (Chan & Guillet, 2011; Leung et al., 2013) since reviews can affect customer satisfaction and ultimately hotel sales and profitability (e.g. Ye et al., 2011; Zhang et al., 2011; Kim et al., 2016; Berezina et al., 2016;). However, limited research efforts have been made to understand customers’ satisfactory and unsatisfactory experiences by analysis of online reviews (Kim et al., 2016; Berezina et al., 2016; Rhee & Yang 2015 a;b; Levy et al., 2013; Li et al., 2013; Kim et al., 2015; 2016; Kwok & Xie, 2016). Furthermore, the effect of different service characteristics on hotel performance is expected to be assymetrical and non-linear (Mikulic & Prebežac, 2008; Füller et al. 2006; Kim et al., 2016; Zhang and Cole, 2016). The objective of this study is to analyse online reviews and determine whether different hotel service characteristics have assymetrical or symmetrical effects on hotel customer satisfaction. A total of 8.540 online customer reviews (from Booking.com) for 42 4 and 5 star hotels in Athens, Greece were analysed in terms of the overall score of the hotel and the individual service characteristics (cleanliness; location/access; personnel quality; installation quality; room quality; food quality; service process quality, and perceived value) for a 2-year period. Data was analyzed using penalty-reward analysis (Mikulic & Prebežac, 2008) and the three factor (satisfiers, dissatisfiers, hybrid) theory of customer satisfaction (Matzler & Sauerwein, 2002; Matzler et al., 2003). Results show that there are indeed asymmetric effects on customer satisfaction. The most powerful frustrators are cleanliness and perceived value and the highest impact dissatisfier is room quality, followed by installation quality and food quality. Only personnel quality and location/access are hybrid factors, meaning that they can have symmetric effects on customer satisfaction. Also, no characteristic was found to be a satisfier or delighter showing that delighting customers is very difficult. Results also differ according to reason for travel (leisure / business) and type of traveller (solo, groups, families, friends). The results of this study can serve as a guide for customizing hotel services for each type of customer. This can lead to higher customer satisfaction and higher perceived overall performance of hotels as expressed in online reviews. Also, higher review ratings can influence overall profits.

The hotel industry vs. online travel agencies: forever foe? The rise of Online Travel Agency (OTA) conglomerates such as Expedia and Priceline has forced the hotel industry to find ways of working with, or avoiding, an increasingly powerful channel for room distribution, and an increasingly relevant set of brands for consumers (Zhang, Denizci Guillet, & Kucukusta, 2015; Lee, Denizci Guillet, & Law, 2013). Although strategizing how to work with different electronic distribution channels has been studied, very few of them have addressed hoteliers‘ perceptions of OTAs, and how OTAs are affecting the industry. In this exploratory research, we sought to investigate the state of current and possible future relationships between OTAs and the hotel industry, from the perspective of diverse hoteliers in the U.S. Using a grounded theory method (Charmaz, 2014; Corbin, Strauss, & Strauss, 2014) that advises to maximize variety to increase the chances of finding new distinctions through a method of ‗constant comparison‘ between data sources, we interviewed eight highly accomplished hotel industry professionals in the U.S., mostly executives, across a variety of roles. Two of our informants were owners/operators of a large hotel management group (Interviewees 1 and 2), one was a former C-level executive at a major hotel brand (Interviewee 3), one was a senior executive at a midlevel regional hotel brand (Interviewee 4), one was the owner/operator to two family-run independent hotels (Interviewee 5), one was the owner of an independent, luxury hotel online services provider (Interviewee 6), one was the manager of a mid-level major brand hotel (Interviewee 7), and one was the owner of a hotel real estate investment company (Interviewee 8). The interviews were semi-structured on: the influence of OTAs on their business, and the hotel industry in general and current strategies for working with, or competing against, OTAs. The interviewees were guaranteed full anonymity, and the resulting 60-75 minute conversations were fully transcribed. Based on the grounded theory design, we followed gradual phases of data analysis: a preliminary open coding phase where concepts are associated with a line-by-line reading of transcripts; a focused coding phase where a limited number of concepts are chosen for further analysis; and an ‗axial‘ coding phase where concepts are systematically related to each other. During the open coding phase, this study‘s authors individually did initial code generation. They then came together to select the primary themes that emerged during focused coding, and worked together to relate the chosen themes to each other, and to key contextual variables such as industry role, hotel size, and hotel category. The impact of OTAs The first consistent perception of OTAs from every corner of the hotel industry is that they ―are not going away‖ (Interviewees 1, 2, 3, 4, 5, 7, 8). The interviewees noted that OTAs first came into the picture post 9-11 when the market was down. Back then, hoteliers ―signed up for OTAs without thinking about any future impacts‖ (Interviewee 5), and ―did not anticipate how disruptive they were going to be, because the original OTA model was to sell distressed or unusable inventory‖ (Interviewee 1). The negative perceptions of OTAs were widespread, with the use of terms such as ―necessary evils‖, ―evil empires‖, and ―Frankenstein‖ (Interviewees 4 and 5). The hotel industry ―sold its soul‖ to OTAs (Interviewee 1), we [hoteliers] are idiots‖ (Interviewee 8) and ―we hate them all.‖ (Interviewee 5). The interviewees expressed that OTAs have had an unexpectedly significant and negative impact on the hotel industry and their business, ―dramatically changing the landscape of hotel business‖ (Interviewee 8). With a marketing budget far larger than that of many hotels, OTAs have successfully convinced consumers to book on their websites for speed, convenience, choice, and loyalty points, and made them believe – incorrectly, according to the interviewees – that they can get the cheapest rates there. The negative view of OTAs has led to a predominantly zero-sum view of the hotel- OTA relationship. OTAs have consolidated to develop a large network of suppliers, and they have been taking more direct business away from hotels, according to the interviewees. As such, the main impact of OTAs on the interviewees‘ hotel bookings was increasing costs due to commission fees to the OTAs, which ―drive up the customer acquisition cost, [which is why] profit hasn‘t gone up in proportion to the revenue increase‖ over the years (Interviewee 6). All but one interviewee mentioned the term ―rate parity,‖ whereby hotels and OTAs have to offer the same room rates on their respective websites. Nonetheless, one interviewee expressed discontent about OTAs‘ practices of rate parity, because hoteliers have ―no clue what they‘re selling [my inventory] for, especially when hotels are packaged with other travel products‖ (Interviewee 5). To minimize this negative financial impact, hotels try to increase direct bookings as much as possible from their members by offering extra features such as mobile check-in, or better rates available only to them. This ‗closed group‘ offering is also practiced by OTAs through which their loyalty program members can also be offered more favorable pricing or terms. The interviewees mentioned that the impact of OTAs is larger for independent than for chain hotels because independent hotels have no ―big distribution channel, and it‘s a way for [them] to be visible‖ (Interviewee 8). However, OTAs are more expensive for independent than for chain hotels, as the latter can leverage their large size to negotiate better terms with OTAs. The OTA commission rates at the interviewees‘ hotels ranged between 6% and 28%, with the highest rate being for independent hotels. Four interviewees pointed out that hotel location and service/price level influence the degree to which OTAs are utilized. That is, OTAs‘ booking volume is higher at resorts, and at hotels at or near airports with a high guest turnover. OTAs‘ booking volume is also higher for hotels with limited service (economy or budget hotels) than those with higher levels of service/price (luxury or upper scale hotels). The former, as compared to the latter, are akin to ―soap on a shelf‖ (Interviewee 8) because they are not distinctive in the consumer‘s mind, and consumers who choose to stay at the former are typically price-elastic. Although the majority of bookings at major chain hotels are still generated by direct bookings, what concerns the hoteliers most is that the percentage of bookings by OTAs has been ―growing at a double-digit rate for many years‖ (Interviewee 3). This makes the interviewees feel that ―OTAs take customers away‖ from their hotels (Interviewee 8). Strategic response of the hotel industry Although all the interviewees acknowledged and worried about the negative financial impact of OTAs, the only consistent strategy for coping with OTAs was to divert bookings to more cost-effective channels such as direct booking, or ―limit visibility over premium dates as much as possible‖ (Interviewee 8). They responded that they use or have to use most or all major OTAs (e.g., Expedia, Priceline), simply because these are prevalent and most familiar to consumers today. The response to the perceived OTA threat varied, depending on the respondent‘s role in the hotel industry. The REIT investor (Interviewee 8) and the major brand executive (Interviewee 3) displayed the purest zero-sum view of the relationship. The REIT investor believed the best response is to strengthen the bargaining position of hotels and win back lost revenue, expressing that hotels are ―letting other people take all this money…we‘re stupid.‖ From the major brand perspective, the best response was consolidation (getting bigger) to have better leverage in complex OTA negotiations, and to have more capital for marketing campaigns and technology development. For the more ―independent‖ respondents there was more scope to react by working with OTAs at some level. The single hotel manager and the independent hotel owner both used the metaphor of ―playing the game‖ to survive in the new era: ―You‘d better play ball with them if you want a presence online‖ (Interviewee 5). For an independent hotel, ―Expedia is my franchise website‖ (Interviewee 7) because OTAs are ―doing things that I could never do as an independent‖ (Interviewee 5). In particular, they emphasized the necessity to understand and master the digital marketing landscape of social media, review sites, search engine optimization, daily deal sites, and a good online presence on their own websites, expressing ―You gotta fish where the fish are‖ (Interviewee 4). Independent and small hotels do suffer from higher OTA commissions, but can also work in their favor in terms of preferred placement in hotel searches and referrals from OTAs. The technology service company‘s, (Interviewee 6) key strategic response was to gain control over customer data, because customer email addresses are particularly important for ―retargeting and email marketing to get guests back for zero costs‖ but is difficult to obtain when receiving bookings from OTAs. Some interviewees were able to see other potential strategic responses that were promising, but not yet pursued widely. One example was ‗bundling‘ products and services along with hotel rooms in new ways (Interviewees 1, 2, 4, 5, 6), similar to Airbnb‘s recent pivoting of offerings. Recognizing that part of the success of OTAs comes from customer convenience, some interviewees thought that innovations such as eliminating check-in (Interviewee 4) would help hotels cope with the new pressures. The regional hotel chain executive and the hotel management company owners perceived that changes to the physical product offered by hotels were needed to compete with Internet providers, especially Airbnb, saying that hotels need to ―rethink the long hallway‖ and the ―300 square-foot rooms‖ (Interviewee 4). This same executive saw significant barriers to innovation in the hotel industry. ―We [hotel industry] are definitely trying…but we are capital heavy, labor heavy, slow to innovate‖ (Interviewee 4). Discussion Our exploratory findings suggest that hoteliers, across a variety of hotel industry roles, had an almost uniformly profoundly negative, zero-sum view of the OTA relationship. While not dismissing the very real concerns and profitability pressures of the hotel industry, we are concerned that these perceptions may lead hotel industry players to not pursue or develop the relationship between them and OTAs in more mutually beneficial ways. The strategy of choice right now is to simply compete directly with OTAs, which is not a strategy that has necessarily worked for other traditional industries when digital intermediaries have entered their space, especially highly fragmented ones with many service providers such as the media and retail industries (Grossman, 2016). This view of the relationship does explain the relative lack of innovation about how to maximize the benefits of this relationship for both sides. In contrast to the zero-sum view, we would point to an alternative theory such as coopetition (Brandenburger & Nalebuff, 2011). The theory of co-opetition points to two simultaneous processes: the cooperation required to ‗create the pie‘, or create value for all parties; and the competition to ‗divide up the pie‘ or capture the value created. Success in co-opetition comes from ‗changing the game‘ by developing new partnerships with four related parties: customers, suppliers, competitors, and complementors that offer ancillary services. In our data, we saw some tentative recognition of co-opetition possibilities in each of these four categories. For new customer relationships, we saw some desire by hoteliers to improve customer convenience and value, beyond simply increasing loyalty rewards. Some hoteliers recognized that OTAs have succeeded in part because of the consumer convenience and value proposition is a superior one. For new supplier relationships, there is limited recognition that new kinds of hotel products might be needed, supplied by non-traditional sources as in the Airbnb case, or by construction partners when building new hotels. Hotels have traditionally worked with complementors by bundling rooms with various travel services such as gaming or meals, but OTAs and Airbnb now offer similar services, making it difficult for hoteliers to differentiate themselves. Thus, there is an opportunity for hoteliers to creatively rethink their relationship with complementors, which none of our respondents mentioned. Despite the negative perceptions, our respondents reported some possibilities for new relationships with their OTA competitors, by using digital marketing techniques to their own advantage. To take an example, instead of having a booking war against OTAs, Red Lion Hotels strategically decided it would partner with Expedia in 2016. When customers see Red Lion hotel rates on Expedia sites, they see both a loyalty member rate, which is lower, and a non-member rate. Even if they are not part of Red Lion‘s loyalty program, customers can still book the loyalty rate and are then automatically enrolled as Red Lion members – thus enjoying member benefits while at the same time also earning points with Expedia. To complete the enrollment, the customer‘s email address is then sent to Red Lion ―which is a big deal because the online travel agencies don‘t normally share such information with partners‖ (Schaal, 2016b, p. 1). Looking across all four categories of new co-opetition relationships, however, we see little evidence of coordinated, systematic strategies for pursuing them in the hotel industry. For the hotel industry to respond to the rise of today‘s OTAs, and the other technology companies that might enter the industry in the future, we suggest that hotels will need to transcend their negative, zero-sum views of the OTA relationship and actively experiment with new co-opetition relationships. In addition, the hotel industry should also continue to improve the effectiveness of its traditional responses to OTAs, including their loyalty programs and brand loyalty initiatives. Several interviewees acknowledged that consumer behavior is changing and consumers today are not as brand loyal at they used to be. Research results echo the same phenomenon. For example, Wollan, Davis, De Angelis, and Quiring (2017) found that 71% of 25,426 respondents in 33 countries said ‗loyalty programs do not engender loyalty‘; 77% ‗retract their loyalty more quickly than they did three years ago‘; and 61% said they ‗switched one brand to another in the last year.‘ Decreasing brand loyalty is also apparent for hotels. MBLM (2017) found that consumers have the least ‗brand intimacy‘ (emotional bond with a brand) with hotel brands compared to those of other industries such as automotive and retail. Similarly, Oracle Hospitality (2017) found that 58.7% of survey participants (8,000 in Australia, Brazil, Mexico, France, Germany, Japan, U.K. and U.S.) stated that they do not belong to any hotel program. The Global Traveler Study (2014) also found the diminishing meaning of ‗loyalty to one hotel,‘ as 66% of their 4,618 respondents in the U.S., U.K., Germany and China are members of 1-4 hotel loyalty programs, while 15% are members of 5 or more programs. Despite the decreasing numbers and the questioned value of such programs, hoteliers are still trying to make consumers loyal to their own brand by enticing them to join their loyalty program. This effort is to increase direct bookings and compete with OTAs by offering ‗member-only‘ incentives such as member discounts, or additional perks such as free late check-outs, free meals, or free upgrades. However, these incentives may exacerbate the already increasing costs for hoteliers, particularly if they are attracting consumers who are price sensitive and would not book directly unless they get something back. While the interviewees mentioned their efforts to increase direct bookings through loyalty programs, none referred to the cost of those programs. Given the changing consumer behavior toward becoming less loyal to brands, it stands to reason for hoteliers to re-consider their loyalty programs. Conclusion Hoteliers are fighting intermediation and trying to push direct bookings. This is nothing new for them since they have been doing it with traditional travel agencies for years. Yet, bookings with traditional agencies remain strong, and OTA bookings continue to grow. It seems that it might be time for hoteliers to quit fighting intermediation, and embrace the ―good‖ that it can bring by adopting a co-opetition mindset, while also creatively thinking about brand loyalty programs and what they might bring to that mindset – if anything. In the zero-sum perception of OTAs, however, we found little space for innovative thinking about how to create new offerings through new partnerships, or loyalty programs. While existing OTAs, and emerging OTAs such as Airbnb, are personalizing services for customers, offering new services that are bundled with rooms, and new products with a new population of room suppliers, the hotel industry‘s response is to simply copy what the OTAs are doing and apply it to their own online bookings. We urge the hotel industry to move beyond this response, and be equally creative in finding new co-opetition opportunities that speak to the traditional strengths of the hospitality industry and its experienced professionals.

Personalizing banner ads or embedding ads with specific data signals or triggers, such as – personal characteristics, past behaviours, etc. is believed to improve customer response or Click Through Rate (CTR) since, embedding ads with viewers/recipients’ personal data or characteristics make ads more appealing and relevant to users (Lambrecht & Tucker, 2013). However, evidence also exists in literature that personalization can be ineffective as the usage of customers’ personal data can trigger off privacy concerns causing them to ignore such ads (van Doorn & Hoekstra, 2013). Investigations exploring suitability and effectiveness of ad personalization report that factors such as advertised product, data used for personalizing may influence the effectiveness of personalized ads (De Keyzer, Dens, & De Pelsmacker, 2015; Goldfarb & Tucker, 2011; van Doorn & Hoekstra, 2013). In this research we examine the impact of personalization triggers (PTs) on click through rate (CTR) of online banner ads across cultures. CTR data for 1345 unique ad copies (personalized) of an international hotel group screened in Japan and Middle East countries was used for this study. Data analyses revealed significant impact of PTs on CTRs. Analyses further revealed that – 1) usage of past purchase data impacts the CTR negatively, implying that customers respond negatively to ads showing hotel properties that they have previously visited/stayed in; 2) usage of search history data has a significant positive impact on CTR, suggesting that customers respond favourably towards ads showing hotel properties in destinations revealed from their search history. Interestingly, culture specific data such as local language elicit different responses in different cultures. While in Japan, language personalised ads i.e., ads in Japanese language fared poorly (negative impact on CTR) as compared to ads in English language (positive impact on CTR); in the Middle East it was the ads in English language that fared poorly (negative impact on CTR) compared to ads in Arabic. These results strongly suggest that the knowledge of PTs influence CTR and combining them with the right creative elements would help advertisers in improving customer engagement with ads, have a positive impact on CTR and even improve customer conversion. This would imply better returns for the resources spent on digital advertising. Findings from the study are true and reflective of the PTs (membership, brand affinity, destination, language) used in the ad campaign under study and limited to the cultures investigated. Future studies exploring other PTs in online hotel ads would help marketers in making a more informed decision while selecting data signals or PTs for personalizing digital banner ads for hotel brands.

Corporate social responsibility (CSR) communication is generally regarded as good and necessary to inform stakeholders of a company’s CSR deeds. However, research has recently uncovered the practice of “greenhushing” within the context of the hospitality industry (Coles, Warren, Borden, & Dinan, 2017; Font, Elgammal, & Lamond, 2017). Greenhushing means that companies de-emphasize green credentials and CSR activities. Going on holidays is an indulgent act that might result from people feeling they have earned some luxury, including behaving lavishly in terms of resource consumption and responsible behavior. Thus, curtailing this indulgent, irresponsible guest behavior without compromising a guest’s holiday experience is a key challenge for hotels. This paper explores whether the assumption that customers do not want to hear about CSR communication while on holiday is true from the customers’ side and what type of communication achieves to curtail unethical behavioral intentions. Based on 594 usable responses from an online survey, we undertake a moderation analysis with a multi-categorical antecedent variable (different communication stimuli), pro-environmental identity as a moderator and behavioral intentions for “unethical” behavior as a dependent variable using PROCESS 3.0 for SPSS (Hayes, 2018). The results provide partial support for our theoretical predictions.

The hotel industry has been reaching their existing and prospecting customers via emails throughout a customer’s journey, from pre-arrival information/promotions to post-stay emails for the reviews (Huang, 2016). In different from other email marketing campaigns containing pure promotional materials for acquiring customers, post-stay e-mails can be used to send personalized messages and build an emotional connection with customers by thanking and rewarding their stays. As an increasing number of customers open and read emails via mobile devices on the move (Jordan, 2015), effectively designed post-stay emails with persuasive messages can be a powerful communicating method keeping customers in the lines of dialog with the brands. However, there is lack of studies on how the post-stay email marketing campaign works to retain customers. This study aimed to identify post-stay email features that affect customers’ intention to revisit the same hotel brand depending on their levels of involvement in choosing hotels for leisure purpose. Grounded on the Elaboration Likelihood Model (ELM) (Petty & Cacioppo, 1986), this study identified what causes “motivation” to process a post-stay email and which email features can be more effectively positioned to persuade consumers with different elaboration levels. This study developed hypotheses regarding the effects of email features on attitude and intention to revisit the hotel brands. A total of 189 responses was determined to be usable in this study. Using Path Analysis, this study tested multivariate regression model with direct effect of email features on attitude and indirect effects of email features on intention to revisit the hotel brand. In addition, this study tested a moderating effect of leisure involvement on the hypothesized paths. The results showed that consumers with a low level of leisure involvement tended to be influenced by financial and interactivity features on their attitude towards the hotel brand while personalization features yielded favorable attitude towards the hotel brand for consumers with a high level of leisure involvement. Attitude towards the hotel brand was a significant predictor of behavioral intention to revisit the hotel brand that sends post-stay emails in this study. Industry professionals and researchers can utilize this study to better design their e-mails as customer retention strategies. The email features analyzed in this study can be strategically included in the post-stay e-mail according to their target market. The initiative can assist in reinforcing or persuading their guests to revisit the hotel brand and build stronger customer relationships.

This study examines the impact of emotional intelligence on the complaint handling process and outcome in the Chinese hotel setting. The results of the study indicate that the TARP model can be applied to China's hotel environment; “network evaluation” has become an important factor in assessing the severity of complaints. Besides, the negotiation and communication methods need to be adaptive in the context of Chinese consumer culture, and the complaints in the hotel environment should be handled immediately. Compared with the negative cases, the frequency of emotional intelligence application in positive cases is higher in every aspect of the TARP model. For the first time, the qualitative case study method is applied to similar research topics, and the application of various dimensions of emotional intelligence in hotel complaint handling process is thoroughly explored. This study not only has theoretical contributions but also serves as a reference for hotels to formulate a high-quality complaint handling standard operating procedure