Exploring the application of the Delphi method as a forecasting tool in Information Systems and Technologies research

The Delphi method has been used widely in clarifying decision-making based on the opinions of experts in all research areas. This study focuses on Information Systems and Information Technology (IS/IT) research area. Its aim is to explore the use of the Delphi method in topics related to IS/IT as a forecasting tool. A sizeable amount of research has been examined about IS/IT using the Delphi method. This work proposes a guideline for applying the Delphi method in IS/IT studies based on a literature review of high impact IS/IT papers that apply Delphi with a view to answering forecasting questions. This guideline defines the most relevant aspects which should be considered when applying this method. Previously, the authors conducted a literature review of 2502 articles from different research topics to obtain evidence about the diffusion of the Delphi method in IS/IT compared to other areas.     

A Mixed Duopoly With Switching Costs

We examine the effects of switching costs in a two‐period Hotelling‐type model where a profit‐maximising private firm competes with a welfare‐maximising public firm. We show that, in contrast with the case in which both firms are private, where switching costs raise prices in both periods, in the mixed duopoly they raise prices in the second period but reduce them in the first period. Moreover, the first‐period price reduction is of such magnitude that switching costs reduce firms’ profits and raise consumer welfare. We also find that switching costs affect the consequences of privatisation in favour of firms and against consumers.     

On the observational implications of taste-based discrimination in racial profiling

This paper contributes to a growing literature that attempts to determine whether disparities in police stops and searches of potential criminals of different races stem from taste-based discrimination. The key challenge in making this evaluation is that police officers have more information than the econometrician and thus racial disparities in police behavior may result from these unobservable factors rather than discrimination. We develop a general equilibrium model of police and potential criminal behavior that encompasses key models in the literature. We highlight the assumptions needed for existing methods of detecting racial discrimination to hold. In particular, we show that when there are increasing costs to search, existing tests for discrimination can give incorrect results. Given the potential importance of these costs, we then propose some alternate methods for detecting racial bias in police behavior.     

A Critical Review of Homo Economicus from Five Approaches

Neoclassical economics is based on and structured around the notion of homo economicus. The theory of consumer choice, the theory of the firm, industrial organization, and welfare theorems all require the assumption that agents act in accordance with the scheme of individualistic rational optimization. In this context, our contribution is threefold. First, we delimit the notion of homo economicus according to five characteristics or dimensions. Second, we critically review this anthropological scheme from five distinct approaches, namely, behavioral economics, institutional economics, political economy, economic anthropology, and ecological economics. Third, we conclude that the scheme of homo economicus is clearly inadequate and deficient. However, despite its inadequacies, it remains one of the fundamental pillars of the neoclassical paradigm in economics, which allows us to discuss why we have not yet overcome this paradigm.     

Tourism Demand Forecasting with Neural Network Models: Different Ways of Treating Information

This paper aims to compare the performance of three different artificial neural network techniques for tourist demand forecasting: a multi‐layer perceptron, a radial basis function and an Elman network. We find that multi‐layer perceptron and radial basis function models outperform Elman networks. We repeated the experiment assuming different topologies regarding the number of lags used for concatenation so as to evaluate the effect of the memory on the forecasting results. We find that for higher memories, the forecasting performance obtained for longer horizons improves, suggesting the importance of increasing the dimensionality for long‐term forecasting. Copyright © 2014 John Wiley & Sons, Ltd.