Do perceptions of time affect outbound-travel motivations and intention? An investigation among Chinese seniors

How people conceptualise time can play a critical role in their travel intention. However, relatively little research attention has been directed to the links between time perspective, outbound-travel motivation and outbound-travel intention. In this study, survey data from a sample of Chinese seniors were analysed to test hypotheses regarding these links. The results showed that present-time perspective and future-time perspective were directly related to travel motivation, and that the associations between present and future perspectives and travel intention were fully mediated by travel motivation. These findings not only highlight the relevance of time-perspective styles to travel research, but also have specific implications for tourism-destination marketers with senior audiences.     

Modifying and applying time and cost blocks: The case of E-Da theme park,Kaohsiung, Taiwan

The main purpose of this study is to modify and apply a management tool called time and cost blocks (TCB). The model was modified to adjust how the “benefit indicator” was measured and further enhanced by inclusion of visitor satisfaction scores and revisiting intention. Data collection was accomplished by means of a diary-type semi-structured questionnaire, which was administered in face-to-face interviews with 655 visitors of the E-Da World theme park in Kaohsiung, Taiwan. The results indicate that participation intensity (PI) and benefit indicator (BI) have a significant relationship with satisfaction and revisiting intention.     

Forecasting accuracy evaluation of tourist arrivals

This paper evaluates the use of several parametric and nonparametric forecasting techniques for predicting tourism demand in selected European countries. We find that no single model can provide the best forecasts for any of the countries in the short-, medium- and long-run. The results, which are tested for statistical significance, enable forecasters to choose the most suitable model (from those evaluated here) based on the country and horizon for forecasting tourism demand. Should a single model be of interest, then, across all selected countries and horizons the Recurrent Singular Spectrum Analysis model is found to be the most efficient based on lowest overall forecasting error. Neural Networks and ARFIMA are found to be the worst performing models.     

A management orientated approach to combination forecasting of tourism demand

Volatility, exponential smoothing, regression and Naïve 2 models are considered singly and in combination in terms of forecasting demand for international tourism. These models generate accurate predictions of tourism flows, but their prime utility is when combined with other models. Usually, models are combined by means of purely statistical criteria. We show that goal programming (GP) offers an alternative, flexible approach to model combination. GP offers planners a practical solution to tourism forecasting problems, since the method is more adaptable than conventional minimisation of prediction error, by permitting practitioners to prioritise a series of management related goals. Forecasters can focus on longer- and short-term goals, minimising forecast under- and over-estimation and/or concentrate on prediction errors in tourism flows at various times of the year.     

Moral economics

An adequate normative economics – one that is consistent with recent developments in our discipline (and in philosophy and psychology) and that resonates with widely held moral intuitions – will have to address the following challenges. First, utility cannot be both the basis of our predictions of economic behaviour and the evaluation of the outcomes of this behaviour. Second, we need to conceive of individual well-being and other desiderata in ways that are interpersonally comparable and that go beyond efficiency and fairness. Third, the representation of the economy as a ‘morality-free zone’ (requiring that contracts, including employment contracts, are complete) must give way to a recognition of the unaccountable exercise of power by private actors, even in a perfectly competitive equilibrium, and the way that this may violate democratic principles and limit the freedom and compromise the dignity of other actors. Fourth, the commitment to ‘liberal neutrality’ (thereby sidestepping the evaluation of preferences) and the related assumption of ‘unrestricted preferences’ in mechanism design and public policy must be abandoned, making room for a concern about the nature of our preferences and the ways that institutions shape our values.     

Evaluating portfolio Value-at-Risk using semi-parametric GARCH models

In this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes. Examining the within-sample VaRs of a set of given portfolios shows that the semi-parametric model performs uniformly well, while parametric models in several cases have unacceptable failure rates. Interestingly, distributional assumptions appear to have a much larger impact on the performance of the VaR estimates than the particular parametric specification chosen for the GARCH equations.     

Time varying country risk: an assessment of alternative modelling techniques

Three different techniques for the estimation of a time-varying beta are investigated: a bivariate GARCH model, the Schwert and Seguin approach, and the Kalman filter method. These approaches are applied to a set of monthly Morgan Stanley country index data over the period 1970 to 1995 and their relative performances compared. In-sample forecast tests of the performance of each of these methods for generating conditional beta suggest that the GARCH-based estimates of risk generate the lowest forecast error although these are not necessarily significantly less than those generated by the other techniques considered.     

Food beliefs and food supply chains: The impact of religion and religiosity in Israel

This paper demonstrates that religion and religiosity affect norms, which affect food consumption patterns and production. Heterogeneity and asymmetric information lead to multiple certification channels as well as multiple supply chains. Major supply chains may address multiple constituencies that are secular or less religious. Technological change affects norms and thus the food system. We obtain these results by analyzing the food systems for meat products in Israel where there are three religions – Jews, Muslims, and Christians – and people assign themselves three levels of religiosity – secular, conservative, and orthodox. Israel has multiple Kosher and Halal certifiers and several specialized supermarket chains for orthodox groups. Its main supermarket chains serve secular and some conservative segments. The immigration of secular Jews from Russia led to the proliferation of non-Kosher supply chains and products, and increased consumption of pork. New technologies and higher incomes led to emergence of fast food chains serving orthodox Jews that had previously tended to eat at home.     

Vertical differentiation via multi-tier geographical indications and the consumer perception of quality: The case of Chianti wines

We derive and estimate a model of demand for Geographical Indications allowing for subjective and heterogeneous quality perceptions, and study vertical differentiation based on multi-tier quality labels within the context of the strategy adopted by the Chianti Consortium. Quality perceptions and wine choices are elicited in an online experiment where the number of quality tiers is augmented incrementally in a between-subject design. The empirical model includes subjective quality perceptions as an (endogenous) explanatory variable, and unexplained heterogeneity in WTP for quality as a random parameter. We find that quality perceptions are endogenous to the labeling regime, and adding a high-quality label (Chianti Classico Gran Selezione) decreases the perceived quality of all other Chianti wines, but not the competitor wines. However, the market shared lost to perception restructuring is small compared to the benefits of increased vertical differentiation.