The impact of relative residence times on the distribution of heavy drinkers in highly distinct environments

Alcohol consumption is a function of social dynamics, environmental contexts, individuals' preferences and family history. Empirical surveys have focused primarily on identification of risk factors for high-level drinking but have done little to clarify the underlying mechanisms at work. Also, there have been few attempts to apply nonlinear dynamics to the study of these mechanisms and processes at the population level. A simple framework where drinking is modeled as a socially contagious process in low- and high-risk connected environments is introduced. Individuals are classified as light, moderate (assumed mobile), and heavy drinkers. Moderate drinkers provide the link between both environments, that is, they are assumed to be the only individuals drinking in both settings. The focus here is on the effect of moderate drinkers, measured by the proportion of their time spent in “low-” versus “high-” risk drinking environments, on the distribution of drinkers.A simple model within our contact framework predicts that if the relative residence times of moderate drinkers are distributed randomly between low- and high-risk environments then the proportion of heavy drinkers is likely to be higher than expected. However, the full story even in a highly simplified setting is not so simple because “strong” local social mixing tends to increase high-risk drinking on its own. High levels of social interaction between light and moderate drinkers in low-risk environments can diminish the importance of the distribution of relative drinking times on the prevalence of heavy drinking.     

Profiling mobile TV adopters in college student populations of Korea

By profiling demographic characteristics, perceived general adoption attributes, perceived value-based adoption attributes, motivational needs, mass media use, and content interest, this exploratory study examines the nature of four categories of mobile TV adopters — current, potential, continuous non-, and discontinuous user groups. Despite the limited sample size (N = 214), there are some meaningful findings. First of all, the non-adoption rate of mobile TV of the continuous non-, and discontinuous user groups is higher than the adoption rate of the current and potential user groups. Less than half of the respondents (N = 34) who had used TV on a mobile device were unwilling to use it again in the next twelve months, and almost half of those (N = 102) did not have the intention of using it within the coming year. The results suggest that the discontinuous group seems to have been dissatisfied with the actual mobile TV use when compared with their expectations and evaluations, while the potential user group is more likely to have high expectations and positive evaluations before the adoption and use of mobile TV. All user groups were unwilling to pay the fee, despite the current and potential user groups perceiving the exceptional values. No differences were found in the personality trait of innovativeness and mass media use behaviors among the four groups.     

Decreasing Utility for Money and Optimal Corporate Debt Ratio

Increasing the ratio of debt capital to total capital increases leverage or sensitivity of equity earnings per share to changes in pretax earnings on composite capital. If (1) total capital needs, and (2) probabilistic pretax earnings on composite capital are held fixed while the debt ratio is increased, the result is an increased variability of after tax earnings per dollar of equity capital. With the “price” (variability) growing with still further increases in debt ratio, “nonuniform utility of money” concepts are helpful in revealing this growing variability as an “investor barrier” to still greater debt ratios.     

Building internal business scenarios based on real data from a performance measurement system

This paper presents a new methodology to build internal business scenarios from the data gathered by some key performance indicators (KPIs) defined within a performance measurement system. The application of the principal components analysis technique leads to the identification of latent relationships between KPIs that underlies some important business aspects. Further, this methodology allows to represent not only the temporal evolution of the organisation as a function of these business aspects but also the definition and determination of internal business scenarios, being therefore the source of meaningful managerial information. At the end of the paper, results of a practical application are presented and discussed, as well as their importance for the organisation from a decision making point of view.