Measuring agri-food supply chain performance and risk through a new analytical framework: a case study of New Zealand dairy

Many researchers and practitioners have long recognized the significance of measuring performance. Although general guidelines for measuring business performance are widely available, not appropriate measurement frameworks have been developed for measuring agri-food supply chain performance. Particularly, food quality and risk-related indicators have not been well integrated in existing performance measurement systems. Our research therefore addresses this knowledge gap by first providing an in-depth review on extant performance measurement systems and frameworks. It then develops an analytical framework by extending the Supply Chain Operations Reference (SCOR) model, which has been extensively implemented across non-food industries. The analytical framework is further validated by utilising a case study of 50 farmers and 10 dairy companies, operating in the New Zealand dairy industry. Our pilot testing and subsequent findings show that the individual metrics interlocked with the analytical framework are in-line with the key industrial practices adapted by the New Zealand dairy industry. In addition, the framework is flexible and scalable to evaluate and benchmark other agri-food supply chains — ranging from fresh products such as fruits and vegetables to processed foods such as canned fruits. The findings further show that the detailed information required for measuring the level-3 SCOR metrics is not easily available in the industry, as researchers need to access specific company records that may be confidential. Consequently, this study provides how agri-food supply chain managers can employ our new analytical framework in-conjunction with the SCOR model for a deeper understanding of the complicated performance measurement indicators applied in their agri-food production systems and relevant supply chains