A Modelof Competitive Limit Pricing

This paper offers a new theory of limit pricing. Incumbents from different markets or regions "compete" against one another, with each attempting to price in a manner that deflects entry into the others' markets. An entrant is imperfectly informed as to the incumbents' respective investments in cost reduction and seeks to enter markets in which incumbents have high costs. In a focal equilibrium, the entrant uses a simple "comparison strategy," in which it enters only the highest-priced markets, and incumbents engage in limit-pricing behavior. The influence on pricing of the number of markets and the scope of entry is also reported. Throughout, the central feature of the analysis is that an incumbent's price affects its investment incentives, with lower prices being complementary to greater investment.     

Using R to teach econometrics

R, an open‐source programming environment for data analysis and graphics, has in only a decade grown to become a de‐facto standard for statistical analysis against which many popular commercial programs may be measured. The use of R for the teaching of econometric methods is appealing. It provides cutting‐edge statistical methods which are, by R's open‐source nature, available immediately. The software is stable, available at no cost, and exists for a number of platforms, including various flavours of Unix and Linux, Windows (9x/NT/2000), and the MacOS. Manuals are also available for download at no cost, and there is extensive on‐line information for the novice user. This review focuses on using R for teaching econometrics. Since R is an extremely powerful environment, this review should also be of interest to researchers. Copyright © 2002 John Wiley & Sons, Ltd.     

The impact of skewness in the hedging decision

The impact of skewness in the hedger's objective function is tested using a model of hedging derived from a third‐order Taylor Series approximation of expected utility. To determine the effect of price skewness upon hedging and speculation, analytical results are derived using an example of cotton storage. Findings suggest that when forward risk premiums and price skewness in the spot asset have opposite signs, speculation increases relative to the mean‐variance model. When the signs are identical, speculation will decrease, contradicting findings of mean‐variance models. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:503–520, 2006     

Investigating the Drivers of Consumer Acceptance and Response of SMS Advertising

This study tests five potential drivers underlying the acceptance of SMS advertising. After developing a scale to measure behavioral responses to SMS advertising, the relationships between the acceptance of SMS advertising, intention to receive SMS advertising and behavioral responses to SMS advertising are tested. A convenience sampling method was employed. Survey questionnaires were distributed across Western Australia. The return yielded 203 usable questionnaires from the respondents. Several factors emerge as significant drivers of acceptance of SMS advertising including utility of SMS advertisements, context of SMS advertisements and attitudes to advertising in general. Contrary to expectation, control over SMS advertisements did not emerge as a significant driver for acceptance of SMS advertising. Trust in advertisers and laws did not emerge as a significant driver of the acceptance of SMS advertising among Australian respondents. Advertisers who pursue consumer acceptance should strive to build utility and context considerations into their SMS campaigns. Future research opportunities include testing the drivers of SMS advertising to further investigate the impact of control and trust on acceptance of SMS advertising in other countries where the SMS advertising has not been explored yet.     

Comparing levels of resident empowerment among two culturally diverse resident populations in Oizumi,Gunma, Japan

While resident empowerment has been a central aspect of the sustainable tourism literature, difficulties of putting the concept into practice have been noted given the heterogeneous nature of communities. “Community” is often divided by kinship, age, gender and ethnicity, and such division may influence the perceptions of empowerment. The goal of this study was to better understand heterogeneous perceptions of empowerment by administering the Resident Empowerment through Tourism Scale within the community of Oizumi, Japan. Oizumi has the highest concentration of Brazilian immigrants in Japan, and the town has embraced “ethnic neighborhood tourism” centered on Brazilian culture as a strategy for economic development. Oizumi's demographic makeup allowed for testing differences in perceived empowerment between members of the dominant ethnic group (Japanese) and members of the ethnic minority group (Japanese Brazilians). Analysis of 650 completed questionnaires revealed that Brazilians felt more psychologically and socially empowered than Japanese residents, indicating a shift in the balance of power between the ethnic groups. Results also revealed that the political dimension of empowerment was rated relatively low among both groups, suggesting a general lack of opportunities to participate in the planning process. Implications for both practice and theory are presented.     

Navigating worlds of information: STEM literacy practices of experienced makers

Making as a design-centered learning activity has recently received significant attention in education. We use literacies—how individuals use representations to learn—to explore the STEM literacy practices of experienced designers and makers. Describing makers’ representational practices in STEM contexts can inform the design of literacy supports for young makers that can encourage their use of representations to connect STEM disciplines and design practices. We interviewed experienced makers to describe one literacy practice central to design: identifying, organizing, and integrating information. Makers enacted this practice within specific making processes—e.g., designing—with the purpose of sourcing and navigating information related to their chosen problems. The research supports efforts to bridge learning while making with learning in schools by positioning STEM literacies as central practices involved in the processes of designing and making.     

Examining the predictive validity of SUS-TAS with maximum parsimony in developing island countries

The Sustainable Tourism Attitude Scale (SUS-TAS) has been used as a tool to gauge the sentiment of local residents toward sustainable tourism development. This scale has been validated in cross-cultural settings by several scholars. In a like manner, in order to validate this scale, data were collected in the Cape Verde islands (off the coast of Africa) and the results showed (1) a parsimonious version of the 21-item SUS-TAS that facilitates the process of data collection without compromising its robustness and psychometric properties, (2) a validated second-order factor model, confirming that the seven factors of SUS-TAS can be loaded in two broader dimensions named “perceived tourism impacts” and “expected tourism sustainability”, (3) a SUS-TAS second-order factor model with validity in predicting residents’ support for sustainable tourism development, (4) that SUS-TAS can be interpreted by seven individual factors and/or as a global factor as indicated by the hierarchical measurement model and predictive validity. Methodological and theoretical interpretations are discussed and future refinement and applications are also offered.     

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.