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The purpose of this paper is to provide a first evaluation of the effectiveness of the early bird discount on ski lift tickets by estimating the impact on hotel overnight stays of the Saas-Fee destination.

The difference-in-differences (DID) approach is used to compare winter sport destinations with and without the price reduction before and after the introduction of the price discount. The sample is composed of the 54 largest Swiss winter sport destinations for the seasons 2013/2014 and 2016/2017.

DID estimations show an increase in overnight stays of Swiss residents by 50 per cent as compared to the control group. Quantile regression estimations for the conditional upper part of the overnight stays distribution reveal a lower average treatment effect of 38 per cent. However, DID estimates for total overnight stays (domestic and foreign) are much smaller – about 17 per cent – indicating that the price reductions are not effective in attracting foreign visitors. Results are not sensitive when taking into account a large number of control variables (elevation, size and snow making capacity).

As tourists visiting winter sport destinations are interested in a mix of activities, lift ticket revenues or number of skier days should be used as an alternative outcome measure.

As positive effects on local tourism demand are mainly limited to Swiss tourists, such price strategies should be carefully considered. In the long term, the skiing market will stagnate or even shrink for several reasons (population ageing, climate change and changes in leisure preferences).

This paper provides a first quantitative evaluation of price discounts in tourism research. Knowledge about the discounts and consumers reactions to sales promotions are of great interest to marketing managers in today’s competitive ski market.

The purpose of this study is to provide a series of indicators to determine the limits to urban tourism growth, tourism gentrification and overtourism. The study addresses overtourism within the frame of urban liveability through a proxy analysis of tourism-relevant indicators for major European tourist cities.

Based on the various indicators, a composite overtourism indicator is derived. The following dimensions are considered for the composite indicator: total number of overnight stays per relevant tourist area in km²; number of museum visitors per population; average annual change in total nights between 2009 and 2017; and foreign nights per population.

Based on the results, Venice is the city with the highest degree of overtourism, followed by Florence, Seville and Lisbon. The remaining cities have a lower than average overtourism potential as indicated by the negative z-score.

This study and the composite overtourism indicators are only a starting point that can lead to further research in the field. Recommendations for further studies include the assessment of visitor flow and overtourism at different times of the year and to expand the study to other European urban destinations.

The paper suggests that policymakers should use these indicators when managing urban tourism development and monitoring visitor growth. Furthermore, they can be a starting point from which to assess the impact of tourism on the quality of life of local residents.

This study provides a starting point from which to assess the causes for social unrest tied to overtourism. If the city under study is found to have a lower than average overtourism potential, this indicates that there may be other social or psychological issues at play apart from sheer overcrowding.

To date, there has been no composite indicator that considered the different numerical aspects of overtourism altogether. This study provides a set of key indicators and a composite overtourism indicator to provide a preliminary appraisal of overtourism as a demand-side phenomenon with evidence from a range of established European urban destinations.

The purpose of this study is to provide new insights into the factors that influence cancellation behaviour with respect to hotel bookings. The data are based on individual bookings drawn from a hotel reservation system database comprising nine hotels.

The determinants of cancellation probability are estimated using a probit model with cluster adjusted standard errors at the hotel level. Separate estimates are provided for rooms booked offline, through online travel agencies and through traditional travel agencies.

Evidence based on 233,000 bookings shows that the overall cancellation rate is 8 per cent. Cancellation rates are highest for online bookings (17 per cent), followed by offline bookings (12 per cent) and travel agency bookings (4 per cent). Probit estimations show that the probability of cancelling a booking is significantly higher for early bookings, large groups that book offline, offline bookings during high seasons, bookings not involving children and bookings made by guests from specific countries (e.g. China and Russia). Among the factors, booking lead time and country of residence play the largest role, particularly for online bookings.

The analysis is based on individual-level booking data from one hotel chain in Finland, and therefore cannot be generalised for the total population of hotels in the country under observation.

The main contribution of this paper is a thorough investigation of the factors that influence cancellation behaviour at both the theoretical and empirical levels. Detailed and unique data from a hotel reservation system allow for new empirical insights into this behaviour.

This article examines the nature of service provision in the platform-based collaborative economy from the perspective of entrepreneurship theories. It departs from a knowledge gap about the individual and contextual determinants of service provision through digital platforms. By exploring these determinants for the service provision in two main sectors of the collaborative economy, transportation and accommodation, the study provides a first conceptual introduction of these activities and their nature for the existing entrepreneurship research.

The analysis is based upon Eurobarometer microdata (2018), covering 28 European countries with about 27,000 observations, and uses a seemingly unrelated Probit model.

The likelihood of service provision through platforms in the collaborative economy is highest for individuals aged 25–34 years but decreases continuously with age. Occupation, sex and population density of the place of residence are other relevant determinants. By contrast, the regulatory system and GDP per capita of the region are not relevant.

The findings illuminate the under-studied individual and contextual determinants related to individuals engaging with entrepreneurial activities in the collaborative economy. Future research should investigate the role of previous self-employment, skills and spatial context.

The collaborative economy is still a marginal sector in Europe that is likely to grow bigger. Particularly the young, highly educated entrepreneurial persons located in urban regions may spur this expected growth. Supporting policy measures aimed at this social stratum might foster digital entrepreneurship and contribute to growth in the digital economy.

By exploring the individual and contextual determinants for the service provision in the two main sectors of the platform-based collaborative economy, transportation and accommodation, the study provides a first conceptual introduction of these activities and their nature into existing entrepreneurship research.

This paper analyses the link between educational qualification structure and information technology (IT) in the service production process. The analysis is based on 1996 cross‐sectional data for approximately 1,000 West German firms. The empirical evidence indicates that IT capital and high‐skilled labor are complements in the production process: firms with higher IT investment output ratios employ a larger fraction of high‐skilled workers at the expense of unskilled workers. To a lesser extent, the positive IT effect carries through for workers with vocational degrees including masters and technicians. Furthermore, we find that firms’ expectations of the future size of their high‐skilled workforce are positively related to their initial IT investment output ratio. To account for censoring in the employment variables, the empirical analysis uses Powell’s Censored Least Absolute Deviations estimators as well as standard Tobit estimators.

The purpose of this study is to understand how learners describe their experiences with short-term, introductory maker experiences and to test a method for assessing learners’ experiences authentic to short-term learning.

The authors collected written responses from participants at a two-day event, STEM Center Learning Days. Through an analysis of 707 unique instances of learner responses to participation in drop-in maker activities, they examined how participants describe their short-term learning experiences.

The authors found that although some activities appear to onlookers to create passive experiences for learners, these seemingly passive moments have a significant impact on learners. In addition, some learners described themselves as working in tandem with tools to make something work and other learners viewed the tools as working autonomously. They found that the assessment method allowed them to gain an understanding of how learners describe their experiences offering important implications for understanding short-term learning events.

The findings provide researchers studying short-term learning in its natural setting a new method to understand how learners make sense of their individual experience. Further, designers of short-term learning experiences may gain insights into their unique activities and indications of where additional guidance and scaffolds will improve small learning moments.

This chapter introduces the book by revolving around its core concept: digital citizenship. This introductory chapter on digital citizenship regimes in the postpandemics could be established by including several brief discussion points that gradually introduce and lead us comprehensively to the chapters of the book previously introduced. These discussion points are informative and attempt to introduce progressively to the key chapters of the book as follows: (1) Urban-Digital Citizenship Nexus; (2) Advancing Recent Literature on Citizenship; (3) Rescaling Nation-States: Pandemic Citizenship and Algorithmic Nations; (4) Beyond the Smart Cities; (5) Exploring Digital Citizenship Towards Technopolitical Dynamics; (6) Borderless and Pandemic Citizenship; and (7) In Summary: Towards Future Research and Policy Avenues in the Postpandemics.

Primary teaching trainees were given a 1‐week placement in environmental science centres, to learn about teaching children in non‐school contexts. The placements were mainly in the South West of England, and included both residential and day‐visit centres. Evaluation was through written and oral feedback from hosts and students, against a set of criteria. The article provides a rationale for such placements within a PGCE programme, describes how they operated in practice and analyses the feedback to make recommendations for future operation of the programme. It recommends provision of more documentation on placements at the planning stage, and proposes a more structured programme for working with children and materials development. The article makes recommendations for further research into the logistics of such placements, the impact of materials developed by trainees, their role and status during placement, and potential benefits of negotiating their own placements. It concludes by discussing the implications for placements more generally.

This study aims to explore various determinants of university attractiveness and its relationship with sustainable institutes. Further, the study examines the mediating role of perceived student support and sense of belongingness on the relationship between university attractiveness and sustainable institutes.

The data analysis was conducted with 637 responses from the students from private universities located in the northern region of India. Variance based partial least square structural equation modeling (PLS-SEM) was applied in the study to investigate the proposed conceptual model on sustainable higher institutions. Additionally, by applying PLS Predict, the predictive relevance of sustainable institutions with important and performing constructs was found out.

The results of this study indicate that university attractiveness plays a critical role in enhancing perceived student support, and it has a direct and significant impact on developing sustainable institutes. Further, students’ sense of belongingness is expressed as significant mediator between university attractiveness and sustainable institutes. The predictive relevance of the study was reported to be high. Most important indicators of university attractiveness were found to be teaching, research and publications, branding and promotion, and diversity in courses offered by the private universities.

The conceptual model under study can be investigated with a moderating effect of private and government universities in future. Additionally, the role of additional variables in online scenario under current pandemic situation can be assessed through the model used in this study. Future research can be done by using qualitative analysis through thematic analysis and sentiment analysis of students in higher education institutes.

The present study is the first to explore the mediating relationship of perceived student support and sense of belongingness with university attractiveness and sustainable institutes. The conceptual framework can prove to be important for education specialists, administrators of education institutes at university level and policymakers. The study offers effective ideas for policymakers to bring sustainability in education sector in near future especially in emerging economies and attain sustainable development goals.

Although microfinance had experienced rapid growth in most developing economies, multiple borrowing remains a growing concern for practitioners and researchers in recent years. Hence, the main purpose of the study is to evaluate the factors affecting multiple borrowing among microfinance clients.

The primary survey data of 400 microfinance clients from Bangladesh was collected to execute the research objective. Considering the types of dependent variable, this study employed logistics, probit, ordinary least squares (OLS) and Poisson regression techniques to analyze the data.

Among others, it was discovered that the expected (requested) loan amount is positively associated with multiple borrowing, while the level of training, small cattle farming business and marital status (widow/separated) exhibited negative effects under logistic regression. These results are robust with respect to the regression method, the specification and the definition of the outcome variable. Also, supply-side incentives (e.g. training) were found to partly influence the multiple-borrowing behavior of microfinance clients. These findings reiterate the contribution of both demand and supply-side factors to the multiple-borrowing behavior of clients. Consequently, policy implications and future research direction are advanced.

The authors have examined some individual-level characteristics as well as some supply-side incentives to better understand the underexplored issue of multiple-borrowing behavior among microfinance clients.