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Experiential learning is considered to be a crucial factor in students' perceived learning outcomes. This study aims to explore the development of a mechanism in hospitality education and to analyze the learning outcomes (i.e. perceived quality, perceived value and learning satisfaction) using experiential learning (i.e. previous learning experience and personalized learning environment).

The course design consisted of two activities (instructing and learning activities) and three phases (before, during and after class) using the Moodle version 3.5 online platform as the educational and training site to sustain e-learning archives and activities. A longitudinal survey using a sample of 207 hospitality students in blended e-learning environment indicates positive relationships among the previously mentioned factors.

Results indicated that both previous learning experience and personalized learning environment have positive direct effects on perceived quality and perceived value, while both perceived quality and perceived value have positive direct effects on learning satisfaction. Furthermore, both perceived quality and perceived value mediate the relationship between previous learning experience and learning satisfaction, as well as the relationship between personalized learning environment and learning satisfaction.

These findings sustain the value of experiential learning, particularly the curriculum, student and faculty development in sustainable development education for hospitality.

The current study is designed to investigate the factors that foster the framing of destination competitiveness and establish the factors that drive the contribution of tourism innovations to economic growth in smart tourism destinations.

A four-year panel data were extracted from the World Economic Forum's travel and tourism competitiveness index and data were analysed using Poisson Pseudo Maximum Likelihood regression model.

The findings demonstrate that both the enabling environment and airport infrastructure significantly affect tourism's impact on the economy of the selected smart European tourism destinations. Conversely, human resources and general infrastructure display a negative correlation with tourism's contribution to the economy. However, no data in the sample support the idea that tourism policies, government prioritization or readiness of tourism information and communication technologies impact tourism's contribution to the economy. Additionally, the marginal effects indicate that improving the enabling environment and airport infrastructure can generate additional benefits for the economy through tourism.

The uniqueness of this study is the integration of smart tourism destinations with the measure of destination competitiveness to provide an empirical bridge that links tourism competitiveness to economic growth.

This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

As families engage in entrepreneurship, particularly in developing economies, women's engagement in such activities is subject to the traditional cultures, norms and values of the communities to which they belong. This paper aims to investigate how the socio-cultural context influences women's entrepreneurship as women engage in “family entrepreneuring”.

The study draws on an inductive qualitative approach to explore how multiple cultural, social and economic contexts encourage women's entrepreneurship and, thus, position them at the centre of family entrepreneuring within this community. Using snowballing techniques, we analyse narratives from 51 women entrepreneurs, generated through semi-structured interviews, to reveal key insights into the practice of family entrepreneuring.

The findings reveal the complex socio-cultural context within the “Adja” community, where polygamy, a traditional and cultural practice, enables the transfer of culturally and socially embedded informal knowledge. The study explains how women's entrepreneuring activities are supported by informal in-family apprenticeships, resulting in family members learning specific skills while also experiencing the feeling of belonging to the family. Showcasing the heterogeneity of contexts, particularly those found in Africa, this study challenges the normative view within the Global North and the dominance of the “heroic male” in entrepreneurship by showcasing how women (especially matriarchs) are significant actors in training other women, co-wives, daughters and relatives in family entrepreneuring.

Thus, this study contributes to the extant literature on family entrepreneuring by revealing an unusual case of women from polygamous families becoming the focal actors in family entrepreneuring activity and challenging the culturally ascribed gender roles to evolve into the breadwinners in their households, as well as focusing on how this process is driven by endogenous knowledge exchange.