Lead Time Strategies Based On Customer Choice Behavior

This paper studies how a firm determines lead time strategies to maximize his own profit in a circumstance where the market demand depends on both lead time and price. We divide customers into time-sensitive customer and price-sensitive customer based on customer "s comprehensive sensitive coefficient on lead time and price. Through adopting utility function to describe customer choice behavior, three quotation strategies, namely, single fast, single slow, as well as hybrid quotation strategy, are proposed based on different practice.Firstly, we found a basic model without constraints and select the most profitable strategy through profit comparison. The results reveal that, as customers are lead time sensitive, the fast quotation strategy is best. However, as customers are price sensitive, the best strategy depends on the utility discount coefficient. Numerical analysis further reveals the influence of relevant parameters on the decisions.Secondly, taking into account that the real market usually exist both types of customers, we introduce the heterogeneous customer scale factor into the model. The results reveal that, as the weighted comprehensive sensitive coefficient on lead time and price is positive, the fast quotation strategy is always better than the slow one, however, as the coefficient is negative, the best strategy depends on the utility discount coefficient and the heterogeneous customer scale factor as well. The firm need consider these two parameters comprehensively to make a decision. Numerical analysis further reveals the influence of relevant parameters on the decisions.Finally, taking into account that overcapacity or shortages are widely existed, we introduce the capacity constraints into the model. The results reveal that, as customers are lead time sensitive, the fast quotation strategy depends on capacity. However, as customers are price sensitive, the best strategy depends on three factors including the utility discount coefficient, unit capacity consumption ratio and the capacity. The firm need comprehensively consider these three parameters to make a decision. Numerical analysis further reveals the influence of relevant parameters on the decisions.