Multi-response permutation procedures for a priori classifications

An exact permutation test for analyzing and/or dredging multi-response data at the ordinal or higher levels is presented. The associated test statistic is based on the average distance (or any specified norm) between points within a priori disjoint subgroups of a finite population of points in an r-dimensional space (corresponding to r measured responses from each object in a finite population of objects). Alternative approximate tests based on the beta and normal distributions are provided. Two detailed examples utilizing actual social science data are considered, including comparisons of the approximate tests. An additional example describes the behavior of these tests under a variety of conditions, including extreme data configurations     

Confidence Bounds and Hypothesis Tests for Normal Distribution Coefficients of Variation

For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations.     

Multichannels Strategy Implementation: The Role of Channel Alignment Capabilities*

A firm's distribution channels represent a key portfolio of resources that can be leveraged for competitive advantage. One approach to this portfolio that has become increasingly important in recent years is multichannel distribution (MCD). While this strategy has important benefits in terms of market coverage and firm performance, the use of multiple channels seriously affects downstream channel roles such as service delivery, as the financial rewards to channel members and the services they offer are separated. A channel member who offers poor or no service can free‐ride on the services offered to the same customer from a different channel. We draw on agency theory to explain these negative consequences. Additionally, the resource‐based view of the firm along with capabilities theory provides two key means of alleviating these consequences: channel tracking capabilities and reward alignment capabilities. The study, conducted in an industry facing serious MCD issues (the outdoor sporting goods industry), used key informant data matched to secondary data. Our results show that managers can reap the performance rewards of MCD strategies while minimizing its negative consequences. In particular, monitoring practices such as frequent site visits and phone contact with customers develop the firm's channel tracking capabilities, allowing managers to better monitor downstream activities. This becomes particularly important as the complexity from having multiple channels increases. Likewise, reward alignment capabilities such as retail price maintenance agreements and cooperative advertising enable the manager to minimize conflict among channel participants by ensuring sufficient profitability for all channel members.     

Component selection norms for principal components regression

Multicollinearity or near exact linear dependence among the vectors of regressor variables in a multiple linear regression analysis can have important effects on the quality of least squares parameter estimates. One frequently suggested approach for these problems is principal components regression. This paper investigates alternative variable selection procedures and their implications for such an analysis.