2 resultados para Preference for variety
em Nottingham eTheses
Resumo:
Providing high levels of product variety and product customization is challenging for many companies. This paper presents a new classification of production and order fulfillment approaches available to manufacturing companies that offer high variety and/or product customization. Six categories of approaches are identified and described. An important emerging approach - open pipeline planning – is highlighted for high variety manufacturing environments. It allows a customer order to be fulfilled from anywhere in the system, enabling greater responsiveness in Build-to-Forecast systems. The links between the open pipeline approach, decoupling concepts and postponement strategies are discussed and the relevance of the approach to the volume automotive sector is highlighted. Results from a simulation study are presented illustrating the potential benefits when products can be reconfigured in an open pipeline system. The application of open pipeline concepts to different manufacturing domains is discussed and the operating characteristics of most relevance are highlighted. In addition to the automotive, sectors such as machinery and instrumentation, computer servers, telecommunications and electronic equipment may benefit from an open pipeline planning approach. When properly designed these systems can significantly enhance order fulfillment performance.
Resumo:
Electoral researchers are so much accustomed to analyzing the choice of the single most preferred party as the left-hand side variable of their models of electoral behavior that they often ignore revealed preference data. Drawing on random utility theory, their models predict electoral behavior at the extensive margin of choice. Since the seminal work of Luce and others on individual choice behavior, however, many social science disciplines (consumer research, labor market research, travel demand, etc.) have extended their inventory of observed preference data with, for instance, multiple paired comparisons, complete or incomplete rankings, and multiple ratings. Eliciting (voter) preferences using these procedures and applying appropriate choice models is known to considerably increase the efficiency of estimates of causal factors in models of (electoral) behavior. In this paper, we demonstrate the efficiency gain when adding additional preference information to first preferences, up to full ranking data. We do so for multi-party systems of different sizes. We use simulation studies as well as empirical data from the 1972 German election study. Comparing the practical considerations for using ranking and single preference data results in suggestions for choice of measurement instruments in different multi-candidate and multi-party settings.