In this paper, we investigate how industrial buyers align their relationships with suppliers to the contextual characteristics of the purchase. We propose that patterns of purchasing strategy are evidenced, in part, by the alignment of three fundamental domains: the firm's strategic intent for a...

Clustering is a highly popular and widely used tool for identifying or constructing databased market segments. Over decades of applying cluster analytical procedures for the purpose of searching for homogeneous subgroups among consumers, questionable standards of utilization have emerged, e.g....

Understanding customer expectations is one of the keys to success for today's clothing manufacturers. Previous studies have explained how operational performance can be improved by a better understanding of customer-perceived values. This paper presents an analysis of data collected through a...

Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market research surveys. Covariate data associated with the judges are also often recorded. Such covariate data should be used in conjunction...

The dichotomy of development economics between market-driven and state-leddevelopment approaches has recently been complemented by a third strand whichfocus on knowledge and capabilities-based development models. Our paper aims tomake a first step towards a Comprehensive Neo-Schumpeterian theory...

This paper depicts a typology of regions, capturing the diversity of regional innovationsystems across the EU-10 (the enlargement member States). Following the RegionalInnovation Systems (RIS) literature, our research selects 21 variables related to theability of a region to generate and absorb...

In many regression applications, users are often faced with difficulties due to nonlinear relationships, heterogeneous subjects, or time series which are best represented by splines. In such applications, two or more regression functions are often necessary to best summarize the underlying...

This paper develops a maximum likelihood based method for simultaneously performing multidimensional scaling and cluster analysis on two-way dominance or profile data. This MULTICLUS procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of...

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...

This paper develops a maximum likelihood based methodology for simultaneously performing multidimensional unfolding and cluster analysis on two-way dominance or profile data. This new procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of...