The purpose of the paper is to measure perceived performance of bilateral relationships in the chain. Therefore, quantitative data were collected from 270 chain members from 3 EU countries in 6 traditional food product categories. First, perceived performance of bilateral relationships was analysed which revealed a generally high perceived contribution of each chain member to its partners' performance. Second, cluster analysis was conducted resulting in 4 clusters: 1) Low performing chains; 2) Low perceived food manufacturer's (FM) performance by supplier (S) and customer (C); 3) High perceived FM performance by S and C; 4) High performing chains. Third, binary logistic regression was used to identify 7 relationship constructs that significantly predict cluster membership: trust, economic satisfaction, social satisfaction, dependency, coercive power, reputation, conflict and integration.
All Science Journal Classification (ASJC) codes
- Management Information Systems
- Computer Science Applications
- Computer Networks and Communications