3 research outputs found

    The stochastic lot-sizing problem with quantity discounts

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    This paper addresses the stochastic lot-sizing problem with quantity discounts. In particular, we examine the uncapacitated finite-period economic lot-sizing problem in which the parameters in each period are random and discrete. When an order is placed, a fixed cost is incurred and an all-unit quantity discount is awarded based on the quantity ordered. The lead time is zero and the order is delivered immediately. First we study the case with overstocks by which the excess inventory incurs a holding cost. The objective in this case is to minimize the expected total cost including ordering and holding costs. The stochastic dynamics is modeled with a scenario tree. We characterize properties of the optimal policy and propose a polynomial time algorithm with complexity O ( n 3 ) for single discount level, where n is the number of nodes in the scenario tree. We extend the results to cases allowing stockout and multi-discount levels. Numerical experiments are conducted to evaluate the performance of the algorithm and to gain the man- agement insights

    Nonlinear pricing for stochastic container leasing system

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    With the substantial upsurge of container traffic, the container leasing company thrives on the financial benefits and operational flexibility of leasing containers requested by shippers. In practice, container lease pricing problem is different from the consumer product pricing in consideration of the fair value of container, limited customer types and monopolistic supply market. In view of the durability of container and the diversified lease time and quantity, the pricing is a challenging task for the leasing company. This paper examines the monopolist’s nonlinear pricing problems in static and dynamic envi- ronments. In particular, the leasing company designs and commits a menu of price and hire quantity/time pairs to maximize the expected profit and in turn customers choose hire quantities/time to maximize their surpluses according to their hire preferences. In a static environment, closed-form solutions are obtained for different groups of customers with multiple types subject to capacity constraint. In a dynamic environment, we address two customer types and derive closed-form solutions for the problem of customers with hire time preference. Further, we show that the effect of the capacity constraint increases with time of the planning horizon when customers have the same hire time preference; while in the case with different hire time preferences, the capacity constraint has opposite effects on the low and high type customers. Last, the case of customers with hire quantity preference is discussed. We focus on the lease with alternative given sets of hire time and use dynamic programming to derive the numerical optimal hire time sequence

    Investigating the underlying social psychology of the innovation adoption in container trucking industry

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    Most extant literature in the transportation industry views innovation adoption as a rational choice process conducted on a cost-benefit calculation basis. This restricts our understanding of innovation decisions made by individuals embedded in a social-economic context. By investigating the underlying social psychology of the innovation adoption in the Chinese container trucking industry, this paper aims to answer the question as to ‘why trucking operators postpone adopting the cargo-truck matching system during its early stage’. In order to achieve the research objective, a mixed methods research framework is proposed. First, we conduct four in-depth interviews using semi-structured questionnaires to investigate the contextualized behavior of individuals, based on which three hypotheses are developed. Second, based on the data collected from an online questionnaire survey covering 282 trucking operators in Ningbo, the proposed empirical hypotheses are tested using a discrete choice model. We find that risk tolerance positively moderates influence of the status quo on the innovation adoption decision, whilst the effect on it of service-orientation is negative
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