Supply Chain Practice, Supply Chain Performance Indicators and Competitive Advantage of Australian Beef Enterprises: A Conceptual Framework

This research focuses on an Australian agribusiness supply chain, the Australian Beef Supply Chain. The definition of the Australian Beef Supply Chain is the chain or sequence of all activities from the breeding property to the domestic or overseas consumers. The beef sector in Australia is undergoing rapid change because of globalisation, a highly competitive beef market (local and export), quicker production cycle and delivery times and consequently reduced inventories, a general speed-up of the rate of change in the business environment, the trend toward more outsourcing of activities, and the rapid development of IT. In this business environment, advanced supply chain systems have the potential to provide significant contributions to Australian beef industry performance. A conceptual framework of the research project has been proposed. There are three elements of conceptual framework. Firstly, supply chain practice of Australian beef industry consists of five sub-elements such as strategic supplier partnerships, customer relationships, information sharing, information quality and a lean system. Moreover, there is an antecedent of cooperative behaviour such as trust and commitment influencing supply chain practice and supply chain performance indicators. Secondly, supply chain performance indicators include four sub-elements such as flexibility, efficiency, food quality and responsiveness. Finally, the competitive advantage framework of the Australian beef enterprises consists of price, quality, export sales growth and time to market. As a further step of the research after developing the conceptual framework, the research project focuses the analysis on how the antecedents of the sub-elements of supply chain practice affect supply chain performance in Australian beef enterprises, how trust and commitment in trading partners affect supply chain performance, how attributes such as flexibility, efficiency, food quality and responsiveness influence the sub-elements of competitive advantage. The research project leads on to further work on how Australian beef enterprises measure their supply chain performance and what the major difficulties are arising when implementing supply chain management in the Australian beef industry and what kind of changes can be made to beef supply chains to enhance their performance.Agribusiness,

The Sinking of the schooner Sofia and How It\u27s Crew Utilized Adaptive Leadership to Survive

This is the historical account of the tall ship, or schooner, Sofia that sank on February 23, 1982, off the North Island of New Zealand, between Cape Reinga and North Cape. Of the 17 crew members on board, 16 of them made it into the life rafts. They were rescued by the Russian trawler Vasili Perov more than five days later. How the crew managed to survive in the life rafts is further examined through the adaptive leadership framework by Ronald Heifetz, Alexander Grashow, and Marty Linsky. Through this examination, the Sofia’s survival leadership is compared and contrasted to the Grafton and Invercauld, shipwrecks that stranded survivors on New Zealand’s Auckland Islands at the same time; each ship’s survival group unaware of the other

A hands-on approach to teaching system identification using first order plus dead time (FOPDT) modelling of step response data

This paper describes three step response-based system identification methods of increasing complexity, together with a range of exercises that will enhance student understanding of this area in an engaging and practical way. For illustration purposes and practicality, it is assumed that the model to be identified is of the first order plus dead time (FOPDT) type. The first method uses a popular graphical technique, which is easy to understand and apply, but inaccurate when the response data is not ideal. The second uses the Nelder-Mead simplex method, which is a more powerful technique and has the added benefit of introducing undergraduate students to the concepts of numerical optimisation. The third uses an integral equation (IE) algorithm. The latter two methods, which can be readily extended to other model structures and input types, are also demonstrated using experimental data obtained from a tank level control system