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Catering services play important role in the Spanish economy, accounting for 6.2% of GDP in 2021. To overcome the adverse economic impacts of COVID-19, catering services are considered one of the drivers to stimulate economic growth. Hence, the main aim of this paper is to analyse the sociodemographic profile of the family's main breadwinner who allocates most of his expenditure budget on different catering services before and during the pandemic caused by the COVID-19 in Spain.

The official Family Budget Survey in Spain was used. This offers information on expenditure by families in 2019 and 2020. CHAID multivariate analysis was employed. This has proved a valuable tool in predicting expenditure, as well as determining the cause–effect relationship of this expenditure.

Findings establish the main breadwinner's expenditure on catering services based on predictors such as “year” affected by the pandemic; “type of employment contract”; “gender”; and “age”. A gender “pub-gap” in consumption in bars and cafes has been revealed, and families with a male breadwinner, on a permanent contract, between the age of 40 and 60 spent the most on catering services.

This research presents a new interdisciplinary approach to family breadwinners as a company whose spend on catering is shaping the economic recovery and leading to new answers for hospitality management. Identified factors can lead to improved decision-making and contextualisation of economic models for food service providers in a post-pandemic future.

Short-term rentals (STRs) (like Airbnb) are reshaping social behaviour, notably in gastronomy, altering how people dine while travelling. This study delves into revenue management, examining the impact of seasonality and dining options near guests’ Airbnb. Machine Learning analysis of Airbnb data suggests owners enhance revenue strategies by adjusting prices seasonally, taking nearby food amenities into account.

This study analysed 220 Airbnb establishments from Madrid, Spain, using consistent monthly price data from Seetransparent and environment variables from MapInfo GIS. The Machine Learning algorithm calculated average prices, determined seasonal prices, applied factor analysis to categorise months and used cluster analysis to identify tourism-dwelling typologies with similar seasonal behaviour, considering nearby supermarkets/restaurants by factors such as proximity and availability of food options.

The findings reveal seasonal variations in three groups, using Machine Learning to improve revenue management: Group 1 has strong autumn-winter patterns and fewer restaurants; Group 2 shows higher spring seasonality, likely catering to tourists, and has more restaurants, while Group 3 has year-round stability, fewer supermarkets and active shops, potentially affecting local restaurant dynamics. Food establishments in these groups may need to adapt their strategies accordingly to capitalise on these seasonal trends.

Current literature lacks information on how seasonality, rental housing and proximity to amenities are interconnected. The originality of this study is to fill this gap by enhancing the STR price predictive model through a Machine Learning study. By examining seasonal trends, rental housing dynamics, and the proximity of supermarkets and restaurants to STR properties, the research enhances our understanding and predictions of STR price fluctuations, particularly in relation to the availability and demand for food options.

COVID-19, like many previous crises, proved once more that some hospitality and tourism organizations are more crises resilient than others. Despite increasing frequency and magnitude of crises, little is known about the features of crises resilient organizations and mitigation strategies they adopt. If the characteristics of such resiliency are identified, those strengths might be targeted. Hence, the purpose of this study is to identify characteristics of crises resilient organizations by analyzing the interface between different organizational characteristics, recovery strategies they adopted and impacts of COVID-19 on individual hospitality and tourism organizations.

A global sample of 202 respondents from 20 countries and four continents, representing different sectors of the hospitality and tourism industry, participated in the survey. Descriptive analysis and cluster analysis were used to rank the items and group hospitality and tourism organizations based on their crises resiliency.

Service quality, loyal customers, branding, high paid in capital, domestic market base, hygiene and safety image, information and communication technology adoption, product and market diversification and restructuring debts emerged as major characteristics and strategies of crises resilient organizations. Using cluster analysis, four different groups of organizations were identified. Based on the impacts of COVID-19 on these organizations, Cluster-1 emerged as significantly more crises resilient, whereas Cluster-4 organizations were significantly more vulnerable to crises. Their characteristics and mitigation strategies they adopted were discussed.

The paper not only identified features of crises resilient organizations and successful mitigation strategies but also measured their impact on various performance indicators. Future studies might use characteristics, mitigation strategies and performance indicators identified in this study.

Based on the findings, tourism organizations would focus on strengthening characteristics and implementing strategies that make crises resilient organizations. Public bodies and destination management would also set their decision criteria based on these findings to create a more resilient tourism industry.

This research not only identifies how hospitality and tourism organizations are affected by COVID-19 but also how these impacts change based on different organizational characteristics and strategies. Understanding which organizational characteristics affect the crises vulnerability of hospitality and tourism organizations might inform risk and crises management literature and structural design elements in tourism businesses, hence offer both theoretical and practical implications.

The research paper aims to study dissatisfaction of teleworking employees in Spain during the Covid-19 health pandemic in order to propose three models: sociodemographic profile of the teleworking dissatisfied employee; advantages and disadvantages for the teleworking dissatisfied employee and advantages for the teleworking dissatisfied employee.

This study uses official open data obtained from the Spanish National Statistical Institute (INE, 2022) through Decision Trees statistical multivariable models implementing Classification and Regression Trees and Recursive Partitioning and Regression Trees techniques to determine the variables that can influence the satisfaction or dissatisfaction of the subjects.

This investigation offers three models with two sociodemographic profiles of dissatisfied teleworking employee, who is a high/middle-level manager/employee around 45 years old, and she/he lives with the partner. Regarding the most important advantage of teleworking, employees consider “use/saving of time” and as disadvantage “worse organization and coordination of work”.

This research provides empirical evidence with inductive reasoning on understanding the challenges of teleworking dissatisfied employees in Spain not only in turbulent times but also in “normalcy” to improve overall teleworker well-being and accomplish company’s and organization’s long-term objectives for better productivity and effectivity. The study has high practical value due to the integral approach incorporating dissatisfaction as a driver that can trigger negative behaviours towards the organizations and that is seldom addressed in the literature. Additionally, this paper could provide some new ideas for accomplishing “Spain Digital 2025” and “Europe’s Digital Decade: 2030” plans on institutional level.

The purpose of this study is to present a holistic review of journal articles on value cocreation in the tourism and hospitality field. By distinguishing similarities and differences in the contexts of China and other regions, the authors identify targeted research directions.

This study collected 438 English articles and 31 Chinese articles on value cocreation in tourism and hospitality published in the Web of Science, Scopus and China National Knowledge Infrastructure online databases. After analyzing the study location of all articles in the sample, the authors identified 79 English-language articles that adopted China as the context of the study. The first data set included non-China-focused publications and the second data set included China-focused publications. A comparative bibliometric methodology was conducted.

The results indicate similarities and differences between the two data sets in terms of research methods, topics and future research directions. Seven major concepts were identified in the first data set: hospitality value cocreation; the value generation process; key stakeholders; outcome variables; the application of service-dominant logic; peer-to-peer accommodation and destination management. Four research focuses were identified in the second data set: the application of customer-dominant logic; the value generation process; resource integration and the cocreation experience.

This research contributes to the understanding of tourism and hospitality cocreation systems through literature analysis and encourages future research on the nexus of the Chinese and global contexts. This systematic investigation extends the concept of value cocreation by integrating its implementation process and value categories and further evaluates the consequences and benefits of value cocreation, which helps clarify how winners and losers can adjust their strategies accordingly.

The originality of this paper lies in the adopted comparative bibliometric analysis which comprehensively reviewed and compared the characteristics of value cocreation research across two contexts. In addition, the study dialectically assesses Chinese tourism cocreation phenomena and their impacts from a global perspective.