Search results

Studies show that internet has become a major force propelling growth in tourism sector in many countries. An appropriate diffusion of the information and communication technology (ICT) services can facilitate visibility of hotels and lodges on search sites and third-party booking websites and thus influence demand. It also helps leverage the use of social media for promotion and customer acquisition purposes. Recently, Myanmar, with impressive historical world heritage sites, is witnessing a tourist boom; more hotels are opening up and achieving competitive advantage by offering free internet connectivity to guests and locating their premises in the vicinity of an ICT infrastructure. The purpose of this paper is to investigate ICT readiness to support the lodging industry in Myanmar by focusing on one sub-index of the Network Readiness Index (NRI, a term heavily used by World Economic Forum). The paper focuses on the “Network Use” component of NRI, pertaining to the effect of the “quality of the Internet connection” available to lodges, and its association with the following dimensions: customer service: the availability of ICT services to guests, such as internet connectivity and availability of ATM in the vicinity; digital marketing: the use of social media, keeping records of guests and analyzing aggregate data to extract business insights; and business-to-business online booking: the use of online booking via major third-party intermediary websites like Expedia, Booking.com and Agoda.com.

Surveys were conducted in three major touristic cities in Myanmar: Bagan, Mandalay and the capital city, Nay Pyi Taw. A total of 101 valid questionnaires were used. Survey questions were centered around the following themes: internet connection problems, digital marketing activities, and online booking directly or via third party digital intermediary. The data are presented and interpreted by descriptive statistics and regression analysis.

Though, Myanmar is new to internet and commercial use of ICT, the awareness of the importance of leveraging social media and online booking for business development is surprisingly high in the lodging sector. On average, about 80 percent of surveyed hotels are present on the WWW through a dedicated hotel website. However, most websites lack an online booking capability. As a result, and due to a global trend, online booking through third-party intermediaries has become the dominant option for hotel booking arrangements in Myanmar. Agoda, founded in Bangkok in 2002, was found to be the number one choice for online booking intermediary in Myanmar, followed by Booking.com. Analysis of the logistic regression revealed that it was highly likely that areas around ATMs have better internet connectivity. As expected, it was also found that it is very unlikely that hotels reporting a problem in internet connectivity will be able to provide internet service to their guests. Despite the presence of problems in internet connectivity in Mandalay and Bagan cities, located away from the capital; most hotels in these cities resort to leveraging social media for promotion and customer/guest development. The analysis also revealed that cities located away from the capital are more aggressive in leverage online third-booking intermediaries.

While researchers were hoping for a higher participation rate in the survey, especially in the city of Mandalay, data collection was challenging, a number of hotels/lodges denied participation. This may have some implications on the generalization of results. However, over 70 and 45 percent of hotels/lodges in the capital city and the ancient city of Bagan, respectively, had participated in the survey.

Tourism has a great potential for growth in Myanmar. This research recommends ways to achieve and sustain competitive advantage for the lodging sector, which is vital for tourism.

Though a considerable research exists on tourism and the recent advances of the ICT sector in Myanmar, the country’s readiness for the actual usage of the internet for the development of tourism has not been specifically addressed. This paper explores this with compelling research findings useful for policy makers as well as players in the tourism sector.

Taiwan’s hotel industry was adversely impacted by the COVID-19 pandemic. This study aims to examine the effect of strategic choices by Taiwanese international tourist hotels before and during the pandemic environments.

A data envelopment analysis (DEA)-based Malmquist methodology is used in this study to provide a mechanism to assess Taiwanese hotel strategy performance. Changes in the productivity and performance of Taiwanese international tourist hotels were analyzed in the periods before and during the pandemic to uncover insights useful should a similar crisis occur in the future. Panel data were obtained from the annual report of international tourist hotels published by the Taiwan Tourism Bureau from 2017–2020. Two groups of hotels were analyzed in this study: city hotels and scenic hotels.

The findings of this study reveal that chain hotels tended to perform better than independent hotels in both city and scenic areas during the global pandemic. Specifically, the crisis caused a substantial decline in productivity and profitability for international tourist hotels in Taipei City during the COVID-19 period. Compared to city hotels, findings also indicate that most international tourist hotels in scenic areas were able to maintain better productivity, including larger-sized scenic hotels.

The DEA-based analysis provides unique and valuable insights for hotel firm leaders on how to better identify and make strategic choices when responding to future crises.

The main aim of the present research is to investigate the role of sense of calling (SOC) in the relationships between human resource practices (HRP), turnover intention (TI) and employee satisfaction (ES) in the hotel industry. Moreover, it also examines whether the relationships between these variables are different for city and resort hotel employees.

Quantitative research was employed to test the proposed hypotheses, and the survey technique was used to collect data. The participants of the research consist of 432 hotel employees who work in Antalya, Turkey. The hypotheses were tested using the partial least squares structural equation modeling (PLS–SEM) analyses.

The results of the analysis have shown that SOC significantly impacts the ES and TI, and HRP could be a new antecedent of SOC. On the other hand, while ES is positively affected by HRP, the SOC has a moderating role in the relationship between these variables.

Hotel authorities' understanding of the SOC’s role in employee attitudes and behavior would be a significant factor not only in retaining them but also in reducing employee turnover. They should consider increasing employees' SOC by focusing on HRP.

Besides being one of the few studies that have discussed SOC in the hospitality literature, the current study also contributes by examining the role of SOC in the relationships between HRP, ES and TI. It also adds value to the calling literature by revealing whether the relationship between these variables differs for city and resort hotel employees.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This study aims to assess how the provision of facilities management (FM) services influences customer satisfaction in hotels in secondary cities. This study focussed on customer satisfaction in relation to specific FM services such as cleaning, maintenance, security, internet/information technology and air conditioner servicing.

The study used a case study design. Simple random and purposive sampling methods were used to select the hotels and the respondents. The study used a survey based on the SERVQUAL model to collect data from 136 respondents. Six hotel managers were also interviewed.

There were disparities in customer satisfaction across the various hotel categories based on the assessment indicators used. Thus, customer satisfaction with FM services was not influenced by hotel ratings. On the calibre of staff handling FM activities, none of the hotels had a professional facilities manager. The hotel managers were in charge of FM activities, which affected the provision of FM services. Generally, customers in all the selected hotels were not satisfied with the quality of FM services. Specifically, the overall mean gap score was very low (−3.20), which meant that customers’ expectations far exceeded their perceptions, hence, their dissatisfaction. Tangible(s) of services were customers’ least appreciated (−1.04) dimension. This meant that hotels did not pay much attention to the physical (place) aspect of their FM activities. This should engage the attention of hospitality industry regulators and policymakers, given the current global health crisis caused by Covid-19 and its variance.

The study demonstrates customer satisfaction with FM services in hotels in secondary cities. Practically, hotels can become very competitive if they consider the findings of the study to provide effective customer-oriented FM services.

Photos are powerful tools to attract individuals’ attention and convey service experiences. Yet exactly how visual cues in a photo contribute to the perceptions of the staged servicescape, and how these perceptions inspire online booking/reservation behaviors, remains underexplored. Addressing the gap, this study aims to uncover (1) how perceptual information mediated by an online photo contributes to the formation of consumers' holistic perceptions of the service environment and (2) how such consumers' holistic perceptions further influence customers' online purchasing behaviors.

This research adopts an innovative crowdsourcing approach and refers to field data on consumers' online hotel booking behaviors to examine relationships among inferred servicescape dimensions, consumers' holistic perceptions of the mediated servicescape and their actual online booking/reservation behaviors (e.g. page-view and meta-click behaviors).

Confirmatory factor analysis and path analysis indicated that five mediated servicescape dimensions (i.e. color, lighting, furnishings, layout and style) contribute significantly to consumers' perceptions of the mediated servicescape (CPMS) and exert different impacts on CPMS. Connecting the crowdsourced rating and consumer behavioral data, CPMS is found to influence consumers' aggregated page-view and meta-click behavior, especially in the US market.

Building upon servicescape theory, the medium theory and the online booking literature, this research proposes a novel conceptual framework of CPMS to theorize the process by which visual cues in online photos contribute to CPMS and subsequent online purchase behaviors. Findings from this research extend Bitner's servicescape framework to mediated service contexts and provide practical implications for promoting service businesses.

This paper aims to examine the idea that an individual’s attitudes and beliefs toward change depend on the quality of the dyadic relationships formed through his/her ego network. Specifically, the focus of the research question is to test if an individual with high quality dyadic ties to others who have a favorable outlook on change will also have a favorable outlook on change.

The research sample consisted of 100 full-time hotel employees working in six city hotels located in Thessaloniki, Greece. To test the research question, three approaches were used including: a descriptive social network analysis (SNA), multiple regression and homophily testing based on Moran and Geary autocorrelations.

Even though the SNA provided some valuable findings on the way structures and tie quality connected the participants, the results from the regression analysis and homophily testing indicated a lack of a positive relationship linking dyadic ties and behavioral intention toward change suggesting that dyadic ties do not influence behavioral intentions in a way that can be considered favorable to change.

Managers need to be aware that employees’ network relationship quality at the dyadic level is insufficient to create a supportive environment toward change. Therefore, dyadic ties significant contribution through SNA is the identification of power centers, influential people, interdepartmental links and interdependencies necessary to disseminate the change message and build sustainable momentum.

The limited number of prior empirical studies have thus far approached relationship quality as a concept composed of either emotional, psychological or technical features. This study differs by adopting the dimensions of tangibles, empathy, responsiveness, reliability and assurance existing in the TERRA model and by determining whether the dyadic tie quality positively impacts individual behavior toward change through the employment of a tripartite examination to strengthen the validation of similarities or differences in the results.

This study aims to use big data analysis and sheds light on key hotel features that play a role in the revisit intention of customers. In addition, this study endeavors to highlight hotel features for different customer segments.

This study uses a machine learning method and analyzes around 100,000 reviews of customers of 100 selected hotels around the world where they had indicated on Trip Advisor their intention to return to a particular hotel. The important features of the hotels are then extracted in terms of the 7Ps of the marketing mix. This study has then segmented customers intending to revisit hotels, based on the similarities in their reviews.

In total, 71 important hotel features are extracted using text analysis of comments. The most important features are the room, staff, food and accessibility. Also, customers are segmented into 15 groups, and key hotel features important for each segment are highlighted.

In this research, the number of repetitions of words was used to identify key hotel features, whereas sentence-based analysis or group analysis of adjacent words can be used.

This study highlights key hotel features that are crucial for customers’ revisit intention and identifies related market segments that can support managers in better designing their strategies and allocating their resources.

By using text mining analysis, this study identifies and classifies important hotel features that are crucial for the revisit intention of customers based on the 7Ps. Methodologically, the authors suggest a comprehensive method to describe the revisit intention of hotel customers based on customer reviews.

This study aims to use the voice of the customer (VoC) strategy to collect user-generated content (UGC) compare customer expectations with reality, make the necessary improvements for the business and create personalized strategies for each customer to maximize revenue, focus on hospitality industry in Vietnam market.

This study proposes a synthesis of techniques for a deep understanding of the VoC based on online reviews in the hospitality industry. First, 409,054 comments were collected from websites in the hospitality sector. Second, the data will be organized, stored, cleaned, analyzed and evaluated. Next, research using business intelligence (BI) solutions integrating three models, including net promoter score (NPS), graph model and latent Dirichlet allocation (LDA), based on natural language processing (NLP) technique, experiment on Vietnamese and English data to explore the multidimensional voice of customer’s row. Finally, a dashboard system will be implemented to visualize analysis results and recommendations on marketing strategies to improve product and service quality.

Experimental results allow analysts and managers to “listen to the customer’s voice” accurately and effectively, identify relationships between entities, topics of discussion in favor of positive and negative trends.

The novelty in this study is the integration of three models, including NPS, graph model and LDA. These models are combined based on the BI solution and NLP technique. The study also conducted experiments on both Vietnamese and English languages, which ensures more effective practical application.

Art hotels are increasingly providing an opportunity for creative artists to exhibit their artworks and collections within their premises. This research investigates how some hotels are transforming themselves into important cultural tourism centers. Specifically, its objectives are: (i) to better understand the extent to which travelers are aware about the existence of art hotels and to evaluate their level of interest in art-oriented initiatives; (ii) to determine which attributes and features of art hotels are appreciated by travelers; and (iii) to identify the type of travelers who are willing to stay in art hotels. The findings from a descriptive survey suggest that the incorporation of art into the hospitality industry can attract a diverse customer base and could result in a sustainable competitive advantage for hotels. This study identifies four types of travelers including: Art-Infused Travelers, Art-Seeking Travelers, Art-Indifferent Travelers, and Art-Blind Travelers. These prospective tourists were categorized according to their level of awareness and interest in art hotels and art-related experiences. In conclusion, this contribution implies that artification processes within the hospitality industry can add value to the cultural tourism market. Hence, it also advances future research avenues to academia.