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Although the role of human capital in the hospitality sector is critical, the industry faces challenges in attracting workers with a poor industry image frequently mentioned regarding labor shortages. This research paper attempts to investigate the factors influencing labor shortages by presenting the perspectives of employees and employers.

Precisely 232 rural hospitality industry employees (n = 128) and employers (n = 104) in Northern Italy were surveyed using a written close-ended online survey and a quantitative research design as part of a convenience sampling approach. For hypotheses testing, Spearman's rho was used.

A relationship between the shortage of professional workers and a variety of factors was found, including professional, digital, social and green skills, industry-intrinsic characteristics and symbolic image attributes of the industry. The findings show that some factors are more important for employees, while others are more significant for employers.

This study demonstrates several practical implications for the hospitality sector by addressing the under-researched stakeholder group of existing hospitality employees, e.g. improving working conditions, reduction of manual operations through digital technologies, realistic career planning, employer branding, identification of skill deficiencies and provision of specialized trainings.

Most research on labor shortages in the hospitality industry has focused on the perspective of either employees or employers. This study compares both perspectives, including the industry image, to gain a realistic picture of the relevant factors for a rural tourism destination in Northern Italy.

The purpose of this paper is to better understand the future of hotel chains by exploring the evolving expectations of guests, potential innovations, emerging opportunities, and likely future scenarios.

A literature review consisting of current events, industry reports, and recent trends is utilized to summarize and categorize the challenges and opportunities facing hotel chains.

The future of hotel chains will be driven by the convergence of an increasingly competitive landscape, along with a diverse evolving customer base seeking out unique and individualized experiences. In order to survive in the future hotel chains will have to: listen to and learn from guests incorporating big data insights, go beyond segments to provide personalized services, continuously develop the brand through signature experiences, utilize collaboration and open innovation to maintain an edge in technology and service, and through total revenue management generate ancillary revenues and maximize guest spend.

This paper provides a comprehensive set of recommendations to hotel chains highlighting opportunities related to: financing, revenue generation, personalization, and co-creation.

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

The COVID-19 pandemic, which appeared in China in late 2019, has affected the world psychologically, socially and economically in 2020. Tourism is one of the areas where the effects of COVID-19 have been felt most clearly. The study aims to determine the effect of negative problem orientation (NPO) and perceived risk related to the COVID-19 pandemic on travel and destination visit intention.

This study employed a convenience and probabilistic sampling method for collecting data from 531 respondents using an online questionnaire. Partial least square structural equation modeling (PLS-SEM) was used for testing research model.

According to the findings, NPO and perceived risk related to the pandemic were found to have direct and indirect effects on the travel behavior of tourists. The results of this research provide theoretical and practical implications for hospitality and travel businesses on topics such as the psychological effects of the pandemic and the travel behaviors of tourists.

It is estimated that the pandemic will also affect tourist behavior due to its effects on human psychology. For this reason, a study conducted in the context of tourist behavior theories is expected to contribute to the literature, managers and future of the tourism.

Due to population ageing, the European Union (EU) has adopted active ageing as a guiding principle in labour and retirement policies. Among the strategies for active ageing, age-friendly workplaces play a crucial role. This study compares age-friendly human resource (HR) practices in the Baltic and Nordic countries. The latter are pioneers in active ageing, and as the employment rate of older employees in the Baltics is like that in the Nordic countries, we may assume equally age-friendly workplaces in both regions.

We used the latest CRANET survey data (2021–2022) from 1,452 large firms in seven countries and constructed the fuzzy logic model on age-friendliness at the workplace.

Despite a high employment rate of older individuals in the Baltics, HR practices in these countries fall short of being age-friendly compared to their Nordic counterparts. Larger firms in the Nordic countries excel in every studied aspect, but deficiencies in the Baltics are primarily attributed to the absence of employer-provided health and pension schemes. The usage of early retirement is more frequent in the Nordic countries; however, its conceptualisation as an age-friendly HR practice deserves closer examination. Our findings suggest that the success of active ageing in employment has translated into age-friendly HR practices in larger organisations in the Nordics, but not in the Baltics. It is likely that high employment of older individuals in Estonia, Latvia and Lithuania is a result of the relative income poverty rate.

Our model represents one of the few attempts to utilise fuzzy logic methodology for studying human resource practices and their quantitative evaluation, especially concerning age-friendly workplaces.

This study aims to investigate the effects of economic policy uncertainty (EPU) on Italian hospitality sector. The investigation attempts to explain whether hotel performance drops when the perceived economic uncertainty increases in the period 2018–2022.

The study examines the impact of EPU on hotel performance in a sample of 661 Italian luxury hotels. To establish the relationship between EPU and hotel performance, we employ the generalized estimating equations (GEE) technique on 3,305 hotel-year observations.

The results show that EPU has a negative impact on hotel performance. More specifically, the analysis reveals that EPU is negatively and significantly related to the revenue per available room (REVPAR), average daily rate (ADR) and hotel occupancy (OCCR). We also look at the role of hotel brand chain affiliation and the moderating effect of conference space and hotel wellness services on the relationship between EPU and hotel performance.

Results provide new evidence for academics to critically evaluate the behavior of luxury hotels under uncertain economic conditions. The investigation offers valuable information also for government, tourism policymakers, tourist hotel owners, hoteliers and tourism managers in their decision-making.

This study provides strategic implications for practitioners and operators in hospitality industry to evaluate the factors ensuring hotel profitability in periods of EPU.

This paper provides interesting insights into the characteristics and practices of profitable hotels in Italy. Few econometric studies empirically explored the effects of EPU in the hospitality field so far and no prior study investigated this topic in the Italian hospitality sector. Therefore, this paper tries to close an important gap in the existing literature improving the understanding of EPU in the Italian hospitality industry.

This paper aims to explore the existence of convergence in non-monetary working conditions in Europe resorting to widely used definitions of this phenomenon and composite indexes of job quality.

The analysis relies on composite indexes, widely used in previous literature, for 207 regions in six different areas of job quality drawing on the microdata of the European Working Conditions Survey from 1995 to 2015. This study assesses the occurrence of convergence both in terms of dispersion of job quality outcomes (sigma-convergence) and, especially, regarding the existence of a catch-up process (beta-convergence).

This study finds evidence of both types of convergences in all the domains, with the exception of skills and discretion and prospects dimensions according to the sigma-convergence approach. The results do not suggest substantial differences between the 15 European Union countries before the 2004 enlargement and the new Member States and are robust to a wide range of changes in the sample and different econometric specifications.

Tot he best of the authors’ knowledge, this paper represents the first rigorous and systematic attempt of addressing the existence of convergence in non-monetary working conditions, applying formal and widely accepted definitions of this phenomenon. It contributes to our knowledge on this topic providing strong evidence of convergence in job quality. Those results can be of interest for scholars in Economics and other Social Sciences.

The ripple effect (i.e. disruption propagation in networks) belongs to one of the central pillars in supply chain resilience and viability research, constituting a type of systemic disruption. A considerable body of knowledge has been developed for the last two decades to examine the ripple effect triggered by instantaneous disruptions, e.g. earthquakes or factory fires. In contrast, far less research has been devoted to study the ripple effect under long-term disruptions, such as in the wake of the COVID-19 pandemic.

This study qualitatively analyses secondary data on the ripple effects incurred in automotive and electronics supply chains. Through the analysis of five distinct case studies illustrating operational practices used by companies to cope with the ripple effect, we uncover a disruption propagation mechanism through the supply chains during the semiconductor shortage in 2020–2022.

Applying a theory elaboration approach, we sequence the triggers for the ripple effects induced by the semiconductor shortage. Second, the measures to mitigate the ripple effect employed by automotive and electronics companies are delineated with a cost-effectiveness analysis. Finally, the results are summarised and generalised into a causal loop diagram providing a more complete conceptualisation of long-term disruption propagation.

The results add to the academic discourse on appropriate mitigation strategies. They can help build scenarios for simulation and analytical models to inform decision-making as well as incorporate systemic risks from ripple effects into a normal operations mode. In addition, the findings provide practical recommendations for implementing short- and long-term measures during long-term disruptions.

The purpose of this study is to investigate the robotic restaurant experience of travellers around the world and understand the components of robotic restaurant experience.

Travellers who had experienced a robotic restaurant were purposefully selected as a sample group for the study. As the robotic restaurants are limited around the world, multiple case study method has been chosen to gather richer data. A user-generated content technique which is a form of qualitative case study method has been benefited to gather data from travellers’ reviews.

The results reveal a model of components of robotic restaurant experience that include six main themes: attraction for kids, robotic system, memorable experience, ambience related attributes, food related attributes (economic value and gastronomic aspects) and deficiencies (in robotic system, in ambience related attributes and in food related attributes).

This paper is one of the first to investigate the robotic restaurant experience of travellers around the world. Moreover, it contributes to the research on restaurant experience and offers a model of components of the robotic restaurant experience.

This paper aims to present the findings from a European study on the digital skills gaps in tourism and hospitality companies.

Mixed methods research was adopted. The sample includes 1,668 respondents (1,404 survey respondents and 264 interviewees) in 5 tourism sectors (accommodation establishments, tour operators and travel agents, food and beverage, visitor attractions and destination management organisations) in 8 European countries (UK, Italy, Ireland, Spain, Hungary, Germany, the Netherlands and Bulgaria).

The most important future digital skills include online marketing and communication skills, social media skills, MS Office skills, operating systems use skills and skills to monitor online reviews. The largest gaps between the current and the future skill levels were identified for artificial intelligence and robotics skills and augmented reality and virtual reality skills, but these skills, together with computer programming skills, were considered also as the least important digital skills. Three clusters were identified on the basis of their reported gaps between the current level and the future needs of digital skills. The country of registration, sector and size shape respondents’ answers regarding the current and future skills levels and the skills gap between them.

The paper discusses the digital skills gap of tourism and hospitality employees and identifies the most important digital skills they would need in the future.