A mixture model approach is developed that simultaneously estimates the posterior membership probabilities of observations to a number of unobservable groups or latent classes, and the parameters of a generalized linear model which relates the observations, distributed according to some member...

This paper presents a conditional mixture, maximum likelihood methodology for performing clusterwise linear regression. This new methodology simultaneously estimates separate regression functions and membership in K clusters or groups. A review of related procedures is discussed with an...

Through the analysis of qualitative data, this research applies institutional theory and the resource-based perspective to examine why public accounting firms adopt women-friendly human resource management policies. The study reveals that 5 types of institutional pressures explain why...

This paper reviews recent work on macroeconomic management with varying organization of wage/price bargaining and degrees of credible monetary conservatism. The emerging literature synthesizes and extends theory and empirics on central bank independence (CBI) and coordinated wage/price...

We consider the bankruptcy law and workout practices in the United States and model bankruptcy as a strategic decision. We analyze a firm's choice between liquidation under Chapter 7, renegotiation of the debt contract in a workout, and reorganization under Chapter 11 of the bankruptcy code. Our...

This paper examines the impact of breastfeeding practices on the large regional differences in infant mortality in Germany around 1910. Breastfeeding is strongly negatively associated with infant mortality and remains so after controlling for public health measures and for demographic, economic,...

This paper discusses the issues in estimating the effects of marketing variables with linear models. When the variables are not directly observable, it is well known that direct regression yields biased estimates. Several researchers have recently suggested reverse regression as an alternative...

This paper presents a multidimensional scaling (MDS) methodology (vector model) for the spatial analysis of preference data that explicitly models the effects of unfamiliarity on evoked preferences. Our objective is to derive a joint space map of brand locations and consumer preference vectors...

Marketing researchers have long used brand switching analyses and Markov transition matrices to gain insights into managerial problems. Almost without exception, this work makes (inappropriate) inferences about individual consumers by analyzing household-level data. This paper presents a...

While conjoint analysis has been applied in a wide variety of different contexts in Marketing, most applications fail to explicitly consider retaliatory reactions from competitors. In this paper, a methodological extension is developed for conjoint analysis by explicitly modeling competition in...