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The purpose of this paper is to illustrate new methods of examining structural differences among segmented markets beyond comparing merely univariate variable mean scores, so as to help marketers and researchers gain better insights into segment differences for meaningful strategy development.

A comprehensive dataset covering various lodging market segments was constructed from Tripadvisor.com. The data then were sorted into lodging customer segments by star rating, type of operation, and level of price charged. Structural equation modeling with the −2 log‐likelihood difference test was conducted to illustrate how effectively the differences, if any, of market segments could be assessed in contrast to the traditional mean‐score comparison approach.

Guest satisfaction was influenced by the same performance variable to the same magnitude and direction across different lodging segments examined. Such stability in the amount of influence of performance on guest satisfaction was true even in the fact that the variable mean scores were significantly different across the market segments.

The traditional approach to examining segment differences via univariate mean scores could be one set of results, while the effect‐based difference assessments in this paper resulted in another. Developing marketing strategies based on the effect‐based segment differences, as illustrated in this paper, is considered more effective than the traditional mean‐based approach. One limitation of this paper could be use of a secondary dataset with limited scope of the model employed for an illustrative purpose. Another limitation is that the sample characteristics are unknown due to the nature of a secondary dataset. The examination of the market segments was also limited to those based on only three popular variables.

The paper is a fresh attempt to examine market segment differences through the effect of one variable on another. The paper advances the methods of hospitality and tourism research for examining segment differences beyond the traditional univariate mean‐based examination approach. The methodological illustration is applicable to a vast majority of different theoretical frameworks known in the hospitality and tourism field. Use of the assessment method illustrated in this paper also requires future market segmentation studies to rely more on theories than data.

The purpose of this paper is to analyze the implicit prices of hotel attributes in different time periods and different markets.

With data from the travel meta-search engine, this paper chose 3- to 5-star hotels in Beijing’s central business district and use hedonic price models.

The results suggest that the attributes with significant implicit prices differ in different time periods; the same attributes with different implicit prices in different time periods; the same attributes with different implicit prices in different market segments.

This study may help to explain the different findings on the relationship between the attributes and room rates of Chinese star-rated hotels in different time periods, and will be useful in both revenue optimization efforts and the design of new hotels projects.

The purpose of this paper is to assess the organisational readiness of small and medium scaled hotels to serve indigenous local cuisines and to segment the hotel properties for gastronomic tourism campaigning and destination marketing aims. The study also explores how the concept of organisational readiness relates to menu decision makers’ intentions, perceived benefits and organisational characteristics.

Organisational readiness was measured by three dimensions (culture, climate and capacity). Data were derived from a survey of primary menu decision makers from 187 hotels in Ghana. Using a combination of hierarchical and non-hierarchical (K-means) algorithms, the hotels were clustered into homogenous groups based on the original raw scores of hotel readiness indicators. The resultant cluster solution was then validated and profiled against relevant external variables.

Analyses reveal three clusters which distinguish hotels by the degree of readiness to serve indigenous local dishes. The resultant segments differ by hotel category (star rating) as well as by the job positions and perceptions of primary menu decision makers. Unexpectedly, lower class hotels displayed significantly greater levels of organisational readiness to serve indigenous cuisines than those in the higher class category.

The study demonstrates that organisational readiness is related to perceived benefits and intentions. Among others, the findings advance the understanding of organisational readiness in hotels in the context of menu decision-making. Given the need to embed new practices in a fast-changing hospitality environment, insights drawn could also serve as a basis for future research. Generalisability of empirical findings may be limited by the socio-economic context as well as the study’s focus on small and medium scaled hotels.

This paper supports hotel businesses in understanding the concept of organisational readiness and its relation to organisational characteristics and menu decision-making. By highlighting the different clusters of hotels, the findings accentuate the need for destination marketers and gastronomic tourism campaigners to target higher classed hotels and draw attention to the potential benefits of serving indigenous cuisines while addressing latent concerns. The results further underscore the role of organisational culture and the necessity for such campaign activities to be directed towards those with ample influence within the hierarchical structures of hotels.

This is an initial attempt to examine the application of the organisational readiness concept to menu decision-making in hotels and to explore the implications for segmentation purposes. Further analysis revealed the critical role of organisational culture on menu decision-making patterns. Thus, the paper applies an important element of organisational development theory to the hotel industry and represents a valuable contribution to the scant literature on indigenous cuisines in hotel food service contexts.

This study aims to examine the evolution of spatial–temporal patterns in China’s hotel industry from 1978 to 2018.

A database comprising over 140,000 hotels with more than 30 rooms was created. The exploratory spatial–temporal data analysis (ESTDA) method, based on space–time cube model, was used to explore and visualize the spatial–temporal pattern of hotels.

The Chinese hotel industry can be divided into two development stages, namely, a large hotel-dominant stage before 2000 and a small–medium-sized hotel-dominant stage after 2000. China’s prefecture-level cities were clustered into four tiers. The higher the tier, the earlier the city will initiate hotel development. The Chinese hotel industry has four continuous hotspots (the Yangtze River Delta, Pearl River Delta, Bohai Rim and Sichuan and Chongqing) and some temporary hotspots.

This study lacks quantitative investigation, which could show the underlying mechanism of the evolution of the Chinese hotel industry.

This study is the first to investigate China’s hotel evolution over 40 years by applying big data and the ESTDA method. The systematic and evolutionary exploration will enable hotel researchers to understand the spatial–temporal nature of hotel distribution better. Introducing the ESTDA method into tourism and hotel research also provides an additional tool to researchers. Hotel investors and operators, city and tourism planners and market regulators can learn from the evolution of location patterns to make better where and when decisions.

Market orientation and positioning have been widely recognized as organizational metrics linked to hotel performance. The purpose of this study is to offer the link among market orientation, positioning and hotel performance in Ghana’s (luxury) hotel sector. It also reports on the joint influence of market orientation and positioning on hotel performance in the same sector.

Three hypotheses were investigated on the link between market orientation and hotel performance, positioning and hotel performance, and the joint effect of market orientation and positioning on hotel performance. A survey of star-rated (luxury) hotels in the capital city of Ghana was used. One hundred and five responses were used in the analysis. Descriptive statistics, exploratory factor analysis and hierarchical regression were used to test the three hypotheses.

All hypotheses were accepted. Market orientation and positioning jointly affect hotel performance, and the study provides hotel managers with suggestions on how to enhance their performance via market orientation and positioning.

Market orientation, positioning, and performance measures focused on management perspectives without including perceptions of customers.

This study is one of the few attempts to systematically investigate the intertwined concepts of market orientation, positioning and performance in a developing economy hospitality context.

The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers.

Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms.

The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews.

The authors did not analyse data across demographic details because of access restriction policies of the websites.

Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously.

This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers.

This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.

This study aims to identify key factors influencing Chinese domestic travelers’ behaviors in hotel selection from a pool of budget hotel attribute-based factors and customer personal characteristics and determine the extent to which these factors impact on domestic Chinese travelers’ hotel selection preferences.

This study uses a discrete choice experimental design and a multinomial logit model to examine the key influential factors contributing to Chinese domestic travelers’ choice behavior to budget hotels. Both hotel attribute-based and personal trait factors were tested.

Results indicate that location, price and business functions were factors influencing guest choice behavior. For budget hotels, being located in the traditional central business districts and having a restaurant would leverage guest preference to stay. Among consumers’ personal characteristics, income, occupation, purpose of travel, personal attitude and past experience were found to be determinants of guest choice behavior.

This study contributes to the understanding of Chinese domestic travelers’ choice behaviors toward budget hotels and offers insights for industry practitioners to better design budget hotel products and service.

This research is the first that integrates hotel attributes with travelers’ characteristics and quantitatively evaluate the determinants affecting hotel choice behavior in China. The insights are of value academically to our understanding of cognitive mechanism underlying choice behavior.

The purpose of this study posited that tourism companies and more especially hotels located in tourist destinations dependent on air transportation, need to commit more strongly to sustainability because of their greater distance from the main outbound markets. The research focused on determining whether hotels’ star rating, location, age and size influence their sustainability communication and on identifying the characteristics of the messages used in hotels’ sustainability communication.

To accomplish these objectives, a sequential mixed methods design with three interconnected phases was used, including quantitative data and content analysis.

Less than 10% of hotels located in a tourist destination strongly dependent on air transportation and peripheral to the main outbound markets actually communicate about sustainable practices on their websites. Communication practices are dependent on hotels’ star rating, location, size and age.

The study limitations are that it was conducted in only one destination and that the hotel websites’ layouts are heterogeneous, which means that the analysis and comparison of the relevant information is extremely challenging. In addition, the research only considered hotels or similar lodgings, leaving out other types of accommodation.

Hotels in tourist destinations dependent on air transportation need to adjust their sustainability communication in response to the trend among tourists toward greater consciousness about the environmental impacts of their individual tourism-related choices. Hotels also need to provide more accurate and detailed information on sustainable practices, with both affective and rational appeals that focus on tourists’ experiences.

The study was conducted in a destination dependent on air transportation and peripheral to the primary outbound markets.

This paper aims to employ data envelopment analysis (DEA) models to evaluate the efficiency level and the change of efficiency of the hotel industry in major Chinese cities from 2001 to 2011. The study also aims to investigate the determinants of this efficiency.

The DEA models were used to calibrate the scores of technical efficiency, pure technical efficiency and scale efficiency in each city, and the Malmquist productivity index was introduced to trace the efficiency change. Furthermore, the panel Tobit and linear regression models were applied to look into various factors contributing to efficiency scores.

The inefficiency of the hotel industry generally comes from the pure technical inefficiency. Moreover, the efficiency of the hotel industry has been considerably improved over the research period due to the change in technical efficiency. In addition, it was found that political hierarchy, degree of openness and level of tourism dependence help explain the cross-city differences in efficiency scores, whereas ownership structure dominantly contributes to the improvement of efficiency over time.

The benchmark analysis of efficiency is of great importance to cities with an unproductive hotel industry, as it helps them make critical adjustments towards the efficiency frontier.

This study represents one of the first studies to rigorously and systematically investigate the efficiency and efficiency change of the hotel industry in major Chinese cities and identify the possible factors explaining the efficiency score.

This case is written for those people who are interested in entrepreneurship, and to generate discussions on the Lean Start-up methodology, as well as other topics related to entrepreneurship and innovation.

It can be used with senior undergraduates, MBAs, EMBAs and senior executives.

In August 2011, Mars Ren and Gene Deng created a technology-based venture, Shanghai Tianhailu Network Information Technology Ltd. Filled with passion, they aspired to be the first “factory outlet” in China' hotel booking industry. To achieve this goal, they developed the Hotelvp app for mobile users. After 6:00 p.m. every day, users could book accommodation online in hotels above three-star standard for that same night at significant discounts. Hotels also benefited because they could sell their unsold room nights at the last minute and improve their revenue management. Ren and Deng were convinced that this win-win idea would take off. Unfortunately, it failed to fully satisfy either the users or the hotels. In spite of the founders' passion and energy, it was still acquired by a much more powerful player in the online sector, JD.com, in early 2014. This case is designed to stimulate in-depth discussions based on the question: What are the key obstacles when launching a startup and how to overcome them?

Through class discussion, it aims at teaching the student how to define and practice a start-up idea successfully by following the “Lean Start-up” methodology and/or take advantage of a practical tool, discovery-driven planning. Specifically, this case intends to teach students how: To identify and define a good start-up idea; To take actions based on the idea/opportunity, iterate and modify it along the way to create new start-ups, and finally lead the new start-ups to grow and succeed; To understand the key concepts, frameworks and theoretical logics of Lean Start-up methodology, and apply it in practice.

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