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Reports and analyses the findings of recent research undertaken in five Scottish centres to assess hotel and catering workers′ attitudes to trade unions. Initially, reviews the reasons advanced in explaining low union density in the hotel and catering industry. These explanations formed the basis to the research project which are reported. The research fieldwork comprised interviews with hotel and catering workers in a variety of establishments across a range of industry sub‐sectors. Contrary to what would have been expected from a review of previous research, Scottish hotel and catering workers demonstrated positive views of trade unions and a high level of interest in union membership. In the light of such views, gives consideration to the reasons why hotel and catering workers remain largely non‐unionized in terms of employer hostility to trade unions and employee doubts about the potential for union success in the industry.

Purpose: The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to identify and analyse contemporary issues and challenges facing the hospitality industry, including trends, regulations, and Tech salutation.

Need for the study: The hospitality industry plays a significant role in the global economy with its diverse services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study will provide an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: The researchers used secondary data for the analysis of the chapter. The researchers reviewed journal papers, books, book chapters, government websites, handbooks, reports, internet, and official records for identification of issues and challenges in the hospitality industry.

Findings: The study identified several contemporary issues and challenges facing the hospitality industry, including the impact of technology and COVID-19 on operations and customer experience, changing consumer preferences for sustainable and ethical practices, labour shortages and retention issues, increasing competition, and changing regulatory environments.

Practical implications: The hospitality industry faces numerous contemporary issues and challenges that impact its sustainability and profitability. Industry stakeholders must understand and address these challenges to remain competitive and relevant in a rapidly changing global market. The findings of this study provide valuable insights into the contemporary issues and challenges facing the hospitality industry and suggest potential strategies for addressing these challenges.

This study aims to determine the barriers hindering the incorporation of blockchain technology (BCT) in two key service industries – hotel and health care – as well as to assess their readiness for implementing BCT after overcoming the barriers.

The barriers of this study are determined through two phases: a review of prior literature and obtaining expert opinions, which are then analyzed to identify specific barriers that are impeding the incorporation of BCT. Moreover, to generate a blockchain implementation reluctance index (BIRI), this study presents an interval-valued intuitionistic fuzzy set (IVIFS) that uses graph theory and matrix approach (GTMA). The permanent function in the GTMA approach is computed using the PERMAN algorithm. Finally, to compare the readiness of the hotel and health-care industries to adopt BCT, the BIRI values are plotted and evaluated.

The barriers identified by this study are listed under five major headings, namely, financial, operational, behavioral, technical and legal. This study revealed that the operational and technical barriers of BCT are critically hindering its widespread integration in hotel and health-care industries. Furthermore, on comparing the BIRI values of both industries, the result suggested that the hotel industry needs to work more on these barriers to effectively incorporate BCT. Besides the comparison, the BIRI values clearly indicate that both industries have to put a lot of effort into the mitigation of the barriers found by this study to successfully integrate BCT.

The experts’ opinions are used to evaluate the identified barriers, which raises the chance that the opinions are prejudiced based on the experts’ perspectives and ideologies. The sensitivity of decision-maker loads toward preference outcomes is not analyzed in this manuscript. Therefore, any recent sensitivity analysis may be considered a prospective field for future research. This study applies a multicriteria decision-making (MCDM) approach, IVIFS–GTMA, which limits the evaluation of the influence caused by individual barriers on the integration of BCT in the hotel and health-care industries. Henceforth, in future investigations, alternative MCDM methods may be used to analyze individual barriers.

According to the findings, if the hotel or health-care industry aims to incorporate BCT in its supply chain operations, it is recommended to emphasize more on the operational barriers along with the technical and behavioral barriers. The barriers mentioned in this manuscript can be used as guidance for developers in their development activities, such as scalability concerns, establishment costs, the 51% attack and the inefficient nature of BCT. Furthermore, they may address the potential users’ negative perceptions about security, privacy, trust and risk avoidance through creatively developed blockchain solutions to promote BCT implementation.

To the best of the author’s knowledge, this is the first study that identifies barriers toward BCT incorporation in the major service industries, i.e. hotel and health care. Moreover, this is the first study that compares the preparedness of the hotel and health-care industries to determine the industry that requires more work to implement BCT.

Promoting interns’ organizational socialization has become an urgent concern for the hotel industry. Building on career construction theory, this study aims to use a time-lagged design to investigate the interrelationships among perceived organizational support (POS), psychological capital and organizational socialization and their consequent effects on interns’ intention to stay in the hotel industry.

Panel data were obtained in three waves from hotel interns from 21 upscale hotels located in 13 cities in China with a time lag of 10 weeks (N = 369). The structural equation modeling was used for data analysis.

POS has a significantly positive effect on interns' psychological capital. Additionally, both POS and psychological capital contribute to the intention to stay in the hotel industry through the mediation of organizational socialization.

Hotels should communicate with interns more explicitly, provide assistance programs to alleviate uncertainty and reward interns on their excellent service performance to improve POS. Moreover, setting up psychological capital programs and empowering interns to be involved in task development is beneficial for enhancing psychological capital. Hotels should also consider mentoring as a socialization approach. Further, career planning and counseling programs should be provided for interns’ long-term hospitality career development.

A time-lagged research method is adopted to provide a new approach to improve interns’ intention to stay in the hotel industry from the interactionist perspective. This study enriches research about psychological capital, POS and organizational socialization.

Assesses the perceptions of service quality in China’s hotel industry, from the perspective of both international tourists and hotel managers. A questionnaire was used to survey a sample of 90 hotel managers and 270 international tourists who visited China and stayed at hotels in Beijing, Shanghai, and Guangzhou. A descriptive statistics analysis was used (paired t‐test and independent t‐test) to evaluate the service quality of China’s hotel industry from both the tourists’ and the managers’ perspectives, and to investigate the four gaps: between tourists’ expectations and their actual perceptions; between managers’ perceptions of tourists’ expectations and the actual expectations of tourists; between managers’ perceptions of a hotel’s service delivery and tourists’ actual perceptions of the service; and between managers’ perceptions of tourists’ expectations and managers’ perceptions of their hotel’s service delivery. The results showed that tourists’ perceptions of service quality provided in the hotel industry in China were consistently lower than their expectations and that managers overestimated the service delivery, compared to tourists’ perceptions of actual service quality, in the hotel industry in China. From the result of gap analysis, it might be concluded that Delivery Gap and Internal Evaluation Gap were the main reasons contributing to the service quality shortfalls in the hotel industry in China.

This study aims to explore the factors that affect the work attitudes of Generation Y towards the hotel industry in Macau from the perspective of senior management.

Using a purposeful sampling method, an in-depth interview with five executives in the hotel industry who are having a supervisory or managerial role from different departments and types of hotels was undertaken; the executives have a supervisory or managerial role from different departments and types of hotel.

The results reveal that attitudes of Generation Y lack the key aspects that potential staff should carry, but organizational culture and human resource management strategies, as well as external environment, can influence Generation Y’s work attitudes and loyalty. The findings also indicate that building Generation Y’s positive work attitudes and moderating the negatives are vital roles of human resource management strategy to maintain service performance.

A comprehensive Generation Y work-attitude framework is developed, and this study incorporates practitioner engagement in real-world practice, which impacts upon service performance in the hotel industry.

The purpose of this paper is twofold: first, to examine the extent to which hotel investments create jobs and, second, to compare whether investment in a particular hotel segment generates more or less jobs in the overall economy and in the tourism, leisure and hospitality industries.

The panel autoregressive distributed lag regression model was used to examine the effect of total hotel investments and hotel investments in economy-scale, midscale, luxury-scale and independent hotels on total employment and employment in the tourism, leisure and hospitality industries in the USA.

Hotel investments increase employment in both the overall economy and the tourism, leisure and hospitality industries. Midscale hotels make the highest contribution to employment in the overall economy. Economy-scale hotels make the highest contribution to employment in the overall tourism, leisure and hospitality industries.

The results support the postulations of growth pole theory. As hotel investment increases, not only does the hotel industry see gains in employment but also does related economic sectors see an increase. Midscale hotels have the greatest positive impact on local labor markets, which is consistent with the assertions of middle-out economics.

Community leaders should encourage the type of investment that benefits the broader area as much as possible by incentivizing the type of growth that is related to employment growth.

This study investigates the relations between hotel investment and employment from a theoretical and empirical perspective by providing objective claims inferred from statistical inferences.

In the prevailing COVID-19 pandemic, organizations now are expected to serve customers who are highly conscious of safety and sanitation. Among others, the hospitality industry is significantly and negatively influenced by this pandemic. Given the unique characteristics of services, using advanced technology is not enough to create a memorable experience without physical interaction between service providers and customers. Thus, this study aims to define the “new normal” for service customers and to explore the “new service design” for the hotel industry.

As most of the Southeast Asian countries heavily rely on the tourism industry, this study focuses on one of the emerging tourism destinations in this region, Malaysia. The data is collected through in-depth interviews with 17 potential national and international tourists.

The results suggest that considering the “new normal” for customers, there is an immediate need for the hotel industry to revamp their service design by mainly practicing disinfection and sanitation activities, re-designing overall infrastructure and introducing promotional offers.

This study is novel in its kind as it provides useful guidelines for both practitioners and academicians/researchers. Under this crucial time, very few research is conducted specifically focusing on the hotel industry and tourists’ behaviors amidst the COVID-19 pandemic. The study will provide in-depth knowledge about tourists’ expectations from the hotel services, especially in their own voices.

The purpose of this paper is to be limited to provide an overall economic structure linked with a particular hospitality industry by identifying the economic structure of relations between the two hotel industries and other industries within a particular state in the USA.

The analyses of output, labor income and employment multipliers from the input–output system were performed using the IMPLAN 3.0 software. The study attempted to compare the hotel/motel industry (industry code 411) and the accommodations industry (industry code 412) with the top ten industries and averages of each set of multipliers to estimate the relative importance and contribution of the two hotel industries to the economy of Texas. After this comparison, the aggregated input–output tables and multipliers were prepared to determine the economic inter-relationship between the two combined hotel industries (industry code 411 plus industry code 412) and the non-hotel industries, using the criteria of the NAICS (North American Industry Classification System).

The three findings of this study are summarized as follows. First, the two hotel industries impacted the state economy due to a high induced effect from output and a considerable direct, indirect and induced effect from labor income and employment, despite their relatively lower multipliers and the economic downturn in the state. Second, the hotel-related industry had a strong inter-dependent relationship with the finance and insurance-related industries. Finally, while the hotel industry generated more labor income and employment than did the other accommodations industry, it is interesting that the other accommodations industry created more output than did the hotel industry.

Other than limitations pertaining to assumptions of input-output model, an input-output analysis alone cannot become the best analytical method for decision-making. The study was a cross-sectional study with 2009 data and did not incorporate a time-series flow of the state economic structure over several decades. A study of the inter-relationship among varied states bordering the state could be worthwhile to identify the flow of inputs and outputs.

Despite a considerable number of research in measuring the economic impacts, this paper was of great significance, in that the economic impact of the hotel industry that has never been performed in a particular state of the USA was analyzed. Additionally, these quantified economic data and results should be helpful to future plans and policies associated with the hotel industry.

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy.

Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue.

All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues.

Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments.

It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.