Project 1: Value chain optimization models
Primary industries are core to the New Zealand economy, yet very underdeveloped in terms of analytics capacity. They are in critical need of smart services, to make them more efficient and effective, as well as being in need of significant capacity building with respect to human capacity to both use and develop analytics for decision making. This is particularly true in their value chains, where complexity and risk combine to make the use of solid analytical models more challenging. This project will work with the primary sector to both identify opportunities for gains and make recommendations for improvements.
The first goal of the research is to develop mixed-integer stochastic optimization models for optimizing value-chains under risk, applied to large-scale value chain optimization models in primary (and possibly manufacturing) industry. These models will then be used as benchmarks to test the outcomes of industrial organisation models that consider the equilibria that can be obtained with multiple self-interested parties acting in their own best interests. Such models can be used to investigate the strategic effects of different industry structures (e.g. vertical integrated co-operatives in contrast with competitive contractual arrangements) and how these might deviate in value from a perfectly coordinated supply chain.
The models developed in this project allow the comparison of optimization and equilibrium solutions under various assumptions about the risks faced by the companies. Such comparisons can be made in any competitive industry to inform companies how they might improve their risk-adjusted profits by changing their production plans and contracting arrangements. The study of equilibrium under risk is very new, and would make this research in primary industry value chains a world first.
Project 1 is led by Professor Tava Olsen from the University of Auckland Business School.