Evaluating channel partner’s performance : impact of task environments on the relevance of measurement metrics

Purpose: The purpose of this paper is to develop a nuanced framework for evaluating a channel partner’s performance in distribution channel relationships. Given a channel partner’s task environment characteristics (high/low munificence, dynamism and complexity), the study examines which performance metrics (output, activity or capability) are most relevant for evaluating its performance levels effectively. Design/methodology/approach: The study adopts self-administered cross-sectional survey-based research design. Matched data were collected from 252 channel partners – manager relationship dyads. The latent change score (LCS) model within SEM framework provides mean paired-differences of the relevance ratings for each metrics. This was used to assess the empirical validity of the hypothesized relationships. Findings: The study demonstrates the importance of calibrating performance evaluation metrics to a channel partner’s task environment state, made possible by its holistic approach to performance evaluation. Based on an extensive analysis, it shows that no single metric is relevant within all environmental states; rather, it could be dysfunctional, a result that differs from vast majority of the literature. Research limitations/implications: Investigates individual linkages between task environment dimensions and performance metrics to provide a fuller understanding of these relationships. Also provides a theoretical framework to support further research on the topic. Practical implications: The study provides managerial guidelines (and extensive graphical analysis) for nuanced and dynamic evaluation of channel partners’ performance that can enable firms to identify and promote their most valuable channel partners and prevent the deterioration of others. Originality/value: First one to develop and empirically validate a nuanced framework for evaluating performance of exchange partners that operate under diverse task environment states.