True burden of drowning: compiling data to meet the new definition

The objective and aim of the study was to compile empirical data to quantify the underestimation of the true burden of drowning and to compare drowning rates using commonly reported codes compared with those revealed by use of the full range of drowning codes in ICD version 10. The authors reviewed mortality data (1999-2002) from Australia and the USA and compiled data to compare the burden of 'unintentional drowning' with that of 'all drowning'. In both Australia and the USA, drowning mortality is more than 35% higher when a full range of codes is examined. A more comprehensive representation of the drowning problem is needed to assist in strengthening prevention activities.     

Monday returns and asset pricing

The seasonal patterns observed on Monday stock returns are still unexplained by different asset pricing models. We attempt to fill this gap in the finance literature by using the Fama-French (Journal of Financial Economics 33:3–56, 1993) risk factors to explain the Monday seasonal. The results in the study show that Monday returns are explained by risk factors such as the market return, the size of the firms, and the book-to-market ratios of firms.     

Deriving joint space positioning maps from consumer preference ratings

Joint space multidimensional scaling maps are often utilized for positioning analyses and are estimated on survey samples of consumer preferences, choices, considerations, or intentions so as to provide a concise spatial depiction of the competitive landscape including relevant dimensions or attributes, competing brands, and consumers in the same joint space representation. Care has to be given concerning the underlying scale properties of such survey data so as not to distort the resulting joint space positioning map. We present a new joint space multidimensional scaling procedure for positioning analyses for displaying the structure in such survey data when such common ordered successive category measurement scales such as Likert, Edwards, semantic differential, etc., are employed. We present the technical details of this stochastic ordered preference multidimensional scaling vector model as well as the maximum likelihood estimation-based algorithm devised for parameter estimation. Favorable comparisons are made with several existent multidimensional scaling methods in representing the internal structure for such data in marketing positioning studies. An actual commercial positioning application concerning large sports utility vehicles consideration to buy judgments is presented with predictive validation comparisons with other multidimensional scaling joint space procedures.     

A two-stage technology foresight model with system dynamics simulation and its application in the Chinese ICT industry

Technology foresight is a process that identifies the critical technologies a country or industry needs to develop in order to shape a desired future. In this paper, a two-stage technology foresight approach is proposed. During the first stage, critical technologies are identified and evaluated by nationwide experts through Delphi surveys. In the second stage, a system dynamics simulation model is used to estimate how critical parameter values are likely to impact the attainment of foresight goals. A detailed illustration of this two-stage process is provided by a technology foresight case study in the Chinese information and communication technologies (ICT) industry. Because it was identified by the first-stage Delphi method as a critical technology, the diffusion of 4th generation wireless telecommunication technology (4G) was simulated, and experimentation was conducted. Suggestions are provided regarding how the Chinese information industry would need to expand the IP network infrastructure in order to support technology foresight goals under different scenarios.     

A sectoral approach to Okun’s Law

The study adds to the existing literature on the relationship between output and unemployment by using a sectoral specification of Okun’s Law to capture the differential sensitivity of the unemployment rate to output developments in the services and manufacturing sectors. Using quarterly data for the period between 2000 and 2012, we show that Malta’s unemployment rate has been more sensitive to output developments in the services sector than to those in the manufacturing sector. We use different equation specifications and the youth unemployment rate to show that the impact resulting from developments in the manufacturing sector occurs mainly via lay-offs while developments in the services sector affect the unemployment rate via the hiring of new entrants into the labour market.     

A review of: “EXPLOITING CYCLE TIME IN TECHNOLOGY MANAGEMENT”BY GERALD H. GAYNOR McGraw-Hill,Inc., New York, 1993, xvi + 349 pp. ISBN 0-07-023474-4. List $46.50.

Teaching engineering economy at the undergraduate level has changed little over the past century. In fact, it has become stagnant as its focus has turned toward financial mathematics and away from decision analysis. This is seen as a disservice to students who must eventually develop engineering economy studies. This paper provides motivation and suggestions to revitalize the curriculum, including teaching engineering economy in a decision-making context and integrating research advances into the curriculum. From these suggestions, a tested semester outline is presented. In the spirit of this special issue, it is hoped that these suggestions help move the teaching of engineering economy to the “next level” such that we can produce effective decision makers in the critical area of capital investment analysis.