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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 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.

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.

The purpose of this paper is to broaden the perspective on how information and communication technology (ICT) relates to productivity by introducing a novel ICT variable: the share of ICT-schooled employees in firms, an intangible input often neglected or difficult to measure.

Based on a Cobb-Douglas production function specification, the association between the share of ICT-schooled employees and firm productivity is estimated by the use of unique comparable multi-linked firm-level data sets from statistical offices in six European countries for the period of 2001-2009.

There are indications that the share of ICT-schooled employees significantly and positively relates to productivity, and also that this relationship is generally more persistent than that of ICT intensity of firms, measured as the proportion of broadband internet-enabled employees. However, the strength of the association varies across countries and demonstrates that underlying factors, such as industry structure and institutional settings might be of importance too.

Data features and the way to access harmonised firm-level data across countries affect the choice of econometric approach and output variable.

The results emphasise the importance of specific ICT skills in firms independently of where in the organisation the employee works.

Studies on associations between employees with specific (higher) education based on formal credentials and productivity are rare. Even more uncommon is the cross-country setting with harmonised data including general ICT intensity of firms.

The purpose of this paper is to analyze the hedging efficiency (HE) of weather index insurances (WII) based on a whole-farm approach. The aim is to identify how different types of WII affect the economic performance risk of real farms in the light of the heterogeneity of farm operations and natural conditions.

Using historic simulation, the HE of various hedging strategies is computed for 20 farms in regions with moderate natural conditions. A priori defined “standardized” WII and hedge ratios as well as ex post “optimized” strategies are analyzed. The latter is identified through a risk programming approach that determines the strike level and hedge ratio that would have minimized the volatility of each farm’s historic total gross margins (TGMs) ex post.

(i) The correlations between the weather indexes and the yields of the farms’ main crop (wheat) do not provide useful insights regarding the whole-farm HE because farms’ performance risk is considerably affected by volatile factors other than wheat yield; (ii) Standardized WII are ill-suited to hedge performance risk for the majority of studied farms; (iii) A considerable positive whole-farm HE could have been obtained on average if farmers had been able to use the “optimized” risk management strategy. Using farm-specific information thus seems to be essential for identifying meaningful hedging strategies.

This study provides added value by analyzing the HE of WII for 20 German crop farms in “moderate” regions. The results show that exemplary tests of WII in extreme conditions provide no decision support for farmers in other regions.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Traditional agency theory assumes monitoring is good for the principal, but we investigate an unintended effect: diminishment of the agent’s preference for honesty. We hypothesize greater dishonest behavior in a monitored environment than in a non-monitored environment, when the agent has the opportunity to cheat outside the scope of monitoring. Relevant theories to explain such behavior are behavioral agency theory, where trust and reciprocity are thought to alter contractual outcomes, and the fraud-triangle theory, where the ability to rationalize deviant acts affects behavior. We utilize participants who have been acclimated to either a monitored or an unmonitored condition in an immediately preceding experiment and seamlessly continue that treatment. Within each of these conditions, participants perform a simple task with a performance-based monetary reward. Half self-report and can safely cheat, while the other half are verified; the difference between verified and self-reported scores is a proxy for dishonest reporting. As hypothesized, unmonitored individuals reciprocate with honest behavior, while monitored individuals tend toward dishonest behavior when the opportunity arises. Implications for fraud prevention are discussed.