Measuring performance of agri-food supply chains : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Supply Chain Management at Massey University, Palmerston North, New Zealand

Abstract

During the past two decades Supply Chain Management (SCM) has become a popular topic of business discussions. SCM presents a business philosophy of improving the long-term performance of individual companies and the supply chain (SC) as a whole and, as a result, attains or sustains a company's competitive position. The practical implementation of SCM has a number of constraints. The basic problems facing SCM are difficulties in adopting a SCM philosophy, the lack of general theory, difficulties of system thinking, and the unique characteristics of agribusiness SCs. Contemporary SCM theory is mainly descriptive and modern SCM research is predominately deductive. Research on SC performance measurement systems (PMSs) has not provided co-ordinated measurement of the bi-directional system flows (material, financial and informational). Available systems do not provide quantifiable measures for the network optimisation decision-making process. In this study an alternative approach to SCM problem resolution was developed. The three SC flows were integrated through the evaluation of their normalised performance measurements (NPMs). The NPM system was developed based on the primary concept that the performance of each SC flow within a SC may be uniformly measured using comparable sets of characteristics. This primary concept was then used as a basis to evaluate higher levels of system performance such as two-party contractual performance and then the performance of the total SC. Special attention was paid to the strategic level of SC analysis and optimisation. The suggested methodology was used to demonstrate how performance improvement of the SC as a whole is interrelated to the performance improvement of individual companies. Case evaluation of the proposed methodology allowed identification of the supply chain wave effect. This effect quantifies how the performance of one chain member affects the performance levels of other system participants. The application of game theory to the methodology indicated that a stable optimum SC strategy might be reached when business performances are balanced along the chain. The case study suggested that chain participants tend to move toward a stable optimum strategy over time. This research may be used as a prescriptive tool for a range of agri-food chain studies. Extended case evaluation is required to test the robustness of the suggested methods.