Research On Delivery Time Compression Models Under BTO Mode

With fiercer competition and increasing demand for personality, instantaneous responsively ability has become the competition advantage. The focus of enterprises has moved from price, variety and quality to time-based competition. Besides, the production mode of the global manufacturing has transformed from mass-production to build-to-order (BTO). So it is necessary to study the effect of time compression model on cost under BTO mode and provide some theoretical instructions to BTO enterprises.Current order delivery time compression models are based on inventory. Combined with the empirical research on the domestic automobile industry and utilizing the combined method of theoretical models and empirical analysis, the paper studies on the order delivery time compression model under BTO mode, which can provide some theoretical instructions for domestic enterprises pursuing BTO mode. Firstly, the paper incorporates the customer waiting time in traditional delivery time compression model after deciding the scope of the customer waiting time when the enterprise transforms to BTO mode and tries to solve the time compression problem under BTO from the perspective of model analysis. The results show the real delivery time and reorder quantity should be decided on the customer waiting time. Secondly, based on the empirical research on the domestic automobile industry made by NSFC70332001 project team, the paper presents the basic model of practical order delivery and derives the three main consisting parts of order delivery time: order processing time, production time and distribution time. The comparative analysis on the three kinds of time by Grey Correlation Degree method shows that the order processing time is the primary time to be compressed. Lastly, the paper presents time compression quantity model considering the effect of time compression of the enterprise on the whole supply chain cost under BTO mode. The results show that risk equilibrium and reasonably controlling time to the optimum time compression quantity can both improve customer service level and decrease supply chain cost.