Crude oil price forecasting based on internet concern using an extreme learning machine

The growing internet concern (IC) over the crude oil market and related events influences market trading, thus creating further instability within the oil market itself. We propose a modeling framework for analyzing the effects of IC on the oil market and for predicting the price volatility of crude oil’s futures market. This novel approach decomposes the original time series into intrinsic modes at different time scales using bivariate empirical mode decomposition (BEMD). The relationship between the oil price volatility and IC at an individual frequency is investigated. By utilizing decomposed intrinsic modes as specified characteristics, we also construct extreme learning machine (ELM) models with variant forecasting schemes. The experimental results illustrate that ELM models that incorporate intrinsic modes and IC outperform the baseline ELM and other benchmarks at distinct horizons. Having the power to improve the accuracy of baseline models, internet searching is a practical way of quantifying investor attention, which can help to predict short-run price fluctuations in the oil market.     

Identifying changes and trends in Hong Kong outbound tourism

Despite the numerous research endeavors aimed at investigating tourists’ preferences and motivations, it remains very difficult for practitioners to utilize the results of traditional association rule mining methods in tourism management. This research presents a new approach that extends the capability of the association rules technique to contrast targeted association rules with the aim of capturing the changes and trends in outbound tourism. Using datasets collected from five large-scale domestic tourism surveys of Hong Kong residents on outbound pleasure travel, both positive and negative contrasts are identified, thus enabling practitioners and policymakers to make appropriate decisions and develop more appropriate tourism products.     

A fuzzy comprehensive evaluation algorithm for analyzing electronic word-of-mouth

This study evaluates tourism experiences shared through electronic word-of-mouth (eWOM) across four Chinese attractions. The objective is to develop a framework for evaluating eWOM by constructing an indicator system and implementing an analytic hierarchy process with the use of a fuzzy comprehensive evaluation algorithm. This framework is achieved by mapping more than 6000 websites related to Chinese tourism attractions and filtering over 200,000 useful reviews to measure service performance. Results indicate that ecological–biological attractions failed to make tourists feel “very satisfied” in various aspects, such as overall evaluation, infrastructure, traffic, natural environment, and social environment. Overall, the study contributes by presenting a framework that can be adopted by tourism researchers and industry practitioners to understand tourist preferences and evaluate service performance to improve service quality.     

A contrast analysis of online hotel web service purchasers and browsers

Ever since the introduction of Internet technology to general business, websites have played an important role in the business and promotional efforts of hotels. However, the existing tourism and hospitality literature contains only a limited number of articles that examine the perceived importance of the different attributes of a hotel website. This paper reports a study that analyzed the different perceptions of specific hotel website attributes between online purchasers and browsers and between Western and Asian users. The empirical findings reveal a set of attributes that are the most important in developing effective hotel websites. The findings also indicate the necessity of designing English- and Chinese-language hotel websites differently, based on the significant differences in the responses obtained from these two groups of online users.     

To lead or to wait? An application to internationalization strategies under demand uncertainty

We examine the exports versus foreign direct investment (FDI) decision under demand uncertainty for an asymmetric cost duopoly. One of the firms can lead entry before demand realization or retain flexibility enjoying an informational advantage. When the time value of information is small and for sufficiently low investment costs, follow‐the‐leader behavior in FDI arises. Relatively high investment (fixed) costs result in follow‐the‐leader exporting behavior. When the time value of information becomes significant, the potential leader will opt for a wait‐and‐see strategy. For intermediate values of investment costs, the efficient firm invests, while the rival chooses to export.     

mLearning as a softer visitor management approach for sustainable tourism

With increased visitation to protected natural areas over the last four decades, there is a need for implementation of effective visitor management strategies at these sites to mitigate visitor impacts. This study explores the application of mobile learning (mLearning) in environmental interpretation and visitor education within the context of conservation and sustainable tourism. Specifically, it proposes a conceptual framework for mLearning as a visitor management tool for sustainable tourism. Current developments and innovations in mobile broadband networks, smartphone technology, and mobile software applications present opportunities for the utilization of such mobile-driven applications in interpretive programs to encourage free-choice learning and mindful visitor experiences. If effectively implemented, such interpretive programs and mLearning applications can affect visitor perceptions, attitudes, and future intentions toward conservation and environmental protection.     

The idea of a collaborative competition - a case study

This paper examines the idea of an online collaborative competition for solutions to environmental and social problems. It asks three basic questions: What is a collaborative competition? In what sense are collaborative competitions collaborative? And in view of the social and environmental goals of the competitions, are they a contribution to sustainability practice? Prepared by a conceptual analysis, partly drawing on the arguments for extended peer review in post-normal science, and based on the in-depth analysis of one collaborative competition, it is argued that the idea of a collaborative competition is innovative and suggestive; however, in practice there is only weak evidence for collaboration - the competitive element clearly prevails. The innovation, in practice, is a new way of making visible and thereby promoting social and environmental ideas. There is some evidence for collaborative spirit, but there is only limited evidence that arguments for extended peer review apply. The design of the online collaborative competition might not promote collaboration as well as it could. Therefore, the paper ends with a discussion of possibilities for changing the design of the competition.     

THE INFLUENCE OF FUNDAMENTALS ON EXCHANGE RATES: FINDINGS FROM ANALYSES OF NEWS EFFECTS

Abstract As we survey the literature of macroeconomic news in the foreign exchange market, we can by now look back on nearly 30 years of research. The first studies which analysed news effects on exchange rates were established in the early 1990s (see, for example, Dornbusch). Almost at the same time Meese and Rogoff published their influential paper, revealing the forecasting inferiority in exchange rates of structural models against the random walk. This finding has shocked the pillars of exchange rate economics and thus cast general suspicion on research focusing on fundamentals in this field. The eventual rising popularity of event studies can partly be attributed to the re‐establishment of the raison d’être of exchange rate economics. This work focuses on systematically surveying this literature with particular respect to its primary goal, i.e. shedding light on the analytical value of fundamental research. Thus, its major findings are, first, fundamental news does matter, whereas non‐fundamental news matters to a lesser degree. Second, news influences exchange rates via two separated channels, i.e. incorporating common information into prices directly or indirectly based upon order flow. Third, with a few exceptions the impact of fundamental news on exchange rates is fairly stable over time.     

The impact of the Asian financial crisis on Japanese demand for travel to Hong Kong: A study of various forecasting techniques

The Asian financial crisis has drawn worldwide attention because of its significant economic impact on local economics, especially on the economy of a tourism‐dependent destination. Unfortunately, there have been very few articles about the relationship of the Asian financial crisis and tourism demand forecasting. This relative lack of prior studies on the Asian financial crisis and tourism demand forecasting is particularly true in the context of Hong Kong. This article reports on a study that utilized officially published data to test the accuracy of forecasts of Japanese demand for travel to Hong Kong, measured in terms of the number of Japanese tourist arrivals. Seven commonly‐used tourism forecasting techniques were used to determine the forecasting accuracy. The quality of forecasting accuracy was measured in five dimensions. Experimental results indicated mixed results in terms of forecasting accuracy. Overall, artificial neural network outperformed other techniques in three of the five dimensions.