Focusing the catastrophic illness debate.

Unlike other aspects of the American health experience, there is a current void of information on expensive illness experiences. This paper is designed to fill this void and prrsents an analysis of the incidence and cost of catastrophic illness in the United States. Catastrophic illness is defined as an illness episode for which a person incurs $5,000 or more of medical expenses in a calendar year. This information is used to provide a framework for focusing the debate about catastrophic and national health insurance.     

Determinants of Relationship Quality and Loyalty in Personalized Services

The study adopts a relationship perspective to examine and better understand customers' interactions with service firms' contact personnel, physical environment and customer environment and their influence on the relationship quality, that is trust and satisfaction, and consequently loyalty. The conceptual model, which integrates relational and evaluative perspectives, is validated in the Asian context of personalized service through findings from a survey of 325 respondents. The findings at the aggregate level indicate that while the physical environment is an important determinant of both trust and satisfaction in personalized service encounters, the customer environment influences only satisfaction but not trust. Service contact personnel's friendliness and knowledge of customers strongly influence relationship quality; while expertise, similarity and disclosure influence trust but not satisfaction. Both relationship trust and satisfaction were found to significantly influence loyalty to the service provider. At the disaggregate level, trust was found to be a stronger predictor of loyalty for high-end service providers while satisfaction was a stronger predictor of loyalty for low-end service providers. The implications for high-end and low-end service providers to enhance loyalty by strategically leveraging on key customer-firm antecedents of relationship trust and satisfaction are discussed.     

A toolkit for macrostructural regional forecasting: Methodological approaches and results of computations

This paper discusses the issues of developing a consistent system of forecast computations providing a long-term outlook for the Russian economy in both sectoral and regional contexts. Under special focus is the formation of regional development scenarios. Such scenarios are suggested to be based on the territorial pattern of investments into the national economy. Results of computations are presented for the period up to 2030 for two scenarios.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.