Abstract
D. Comm.
The South African vehicle industry is currently struggling to narrow the gap between the demand and supply for new vehicles. Customers are confronted with long waiting lists for some models, while producers are carrying high stock levels on other models. A possible explanation for this is the complex nature of the demand for vehicles, resulting in difficulty to analyze and forecast vehicle sales. The demand for large and luxury passenger vehicles is to a. large extent status-driven, while the demand for commercial vehicles and tractors can be seen as derived demand because they are being used in the production process. Motorcycles, on the other hand, can be seen as "inferior goods" due to their discomfort. Demand management suggests that managers must react proactively to changes in the market with the aid of strategic information systems. A key ingredient of information systems is econometric models. These models transform data into decision-relevant information. The availability and knowledge of these models are, however, very limited. Studies performed on the vehicle industry produced only a few broadly defined models. They analyze only the main categories and do not, for example, distinguish between small and large vehicles, while this mix of sales is important for the majority of stakeholders in the vehicle industry. If forecasts are made with these models, decisions will be based on inaccurate forecasts and scarce resources will be wasted. This study is executed against this background. It is an attempt to narrow this gap between demand and supply and to address the shortcomings of previous econometric models. The primary objective of the study is to compile and test an econometric model for each vehicle category in South Africa. The secondary objective is to investigate the use of econometric models in the strategic planning processes in the vehicle industry to gain a competitive advantage. In order to make conclusions and recommendations to the industry, the following steps were followed: All vehicle categories in South Africa were identified (small passenger cars, medium passenger cars, large passenger cars, light commercial vehicles, medium commercial vehicles, heavy commercial vehicles, tractors and motorcycles). A unique data base was compiled for each category of vehicle (prices of new vehicles, prices of second-hand vehicles and numbers sold). Economic and graphic analyses were performed on every category, investigating the determinants of the demand for that category of vehicle. An econometric model was estimated for each category of vehicle. These models were tested economically, statistically and econometrically to verify the soundness thereof. The uses of these models were illustrated ("what if" analyses and forecasting). The role of managers in the vehicle industry in the application of these models were investigated. It can be concluded from the results of the econometric models that consumer behaviour in the vehicle industry can be analysed and forecast quite accurately. It was proven from the results that the factors influencing the demand for the different categories of vehicles, and especially the extent to which these determinants influence demand, differ considerably among the categories. This emphasizes the importance of analyses of this nature where the determinants of demand are analyzed for each and every type of vehicle. This also emphasizes the risk managers take when decisions are based on models where all these categories are combined and only total vehicle demand is analyzed. The responsiveness of management depends to a large extent on the quality of the information systems in the company. The new approach, 'identified in this study, concentrates on the direct use of information systems, and more specifically econometric models, to establish a competitive advantage.