The product elimination function

Historically, major consideration given to product management has focused on research and development or the introductory stage of the product life cycle. The authors present an empirical study delineating the variables to be considered in the product elimination process. More specifically, the elimination process is evaluated under a situation of poor product performance despite a generally viable market. The basic objectives of the study were: to determine the significant variables in the product elimination process of the Small Appliance Industry; to determine the relative importance of the variables; to examine the interaction among variables. The data obtained through personal structured questionnaire interviews were analyzed and provided a ranking of twenty-six variables relevant to the elimination process. Moreover, the Johnson's Hierarchical Clustering Schemes was applied to determine the interaction among variables. The results indicate that profitability and financial variables are most significant in the elimination decision-process. Second, the primary clusters of importance are concerned with market share, market growth rate, consumer awareness, and competitive action.     

Reduced Form Auctions Revisited

This note uses the Theorem of the Alternative to prove new results on the implementability of general, asymmetric auctions, and to provide simpler proofs of known results for symmetric auctions. The tradeoff is that type spaces are taken to be finite.     

The demographic impact of AIDS in sub-Saharan Africa: short- and long-term projections

"This paper describes the methodology used to incorporate AIDS mortality in recently revised World Bank population projections....The paper first reviews different approaches for projecting AIDS and its demographic consequences. This is followed by a summary of an epidemiological model that simulates the spread of HIV used in this analysis, and a demographic model that translates mortality from AIDS into population outcomes. These models are then used in a set of simulations, from which the effect of current HIV prevalence on projected future mortality is extracted. Finally, the extracted equations linking current HIV prevalence with future mortality indicators are applied to sub-Saharan countries with a measurable level of current HIV prevalence."