• Korean Management Science Review
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• v.33 no.1
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• pp.1-16
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• 2016

Drop-shipping is a commonly adopted online-order fulfillment strategy in the Internet age. In this practice, online retailers leverage the fulfillment capabilities of suppliers to fulfill orders. On the other hand, purchase dependence is a frequent phenomenon and is characterized by the purchase of certain items together due to their unknown interior associations. Although this concept has been significantly examined in the marketing field (e.g. market basket analysis), it has largely remained unaddressed in operations management. This paper develops an (R, T) model to address an environment in which unmet demand orders are partially lost and partially backordered when purchase dependence exists. The partial backorders are fulfilled by a drop-shipping option. Through computational analyses, this paper demonstrates the effect of both drop shipping on a partial backordering and purchase dependence. The results shows that more profit can be realized by utilizing a drop-shipping option under purchase dependence.

• Korean Management Science Review
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• v.32 no.1
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• pp.65-82
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• 2015

Purchase dependence is a frequent phenomenon in retail shops and is characterized by the purchase of certain items together due to their unknown interior associations. Although this concept has been significantly examined in the marketing field (e.g. market basket analysis), it has largely remained unaddressed in operations management. Since purchase dependence is an important factor in designing inventory replenishment policies, this paper demonstrates the means of applying it to the partial backordering inventory model. Through computational analyses, this paper compares the performance of inventory models that either consider or ignore purchase dependence; the results demonstrate that inventory models that ignore purchase dependence incur more average cost per unit time than the model that considers purchase dependence, and the impact of purchase dependence can increase in significance as the item set becomes more closely correlated with regard to order demand.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.83-100
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• 2014

Retail shops often experience purchase dependence in which some items are purchased together by customers due to their unknown interior associations. This paper develops an inventory model considering partial backordering under purchase dependence and compares the performance of the inventory model that ignores purchase dependence. Computational analyses show that purchase dependence should be incorporated as an important factor of inventory replenishment policy because the impact of purchase dependence can be more significant as the lost portion of the unmet demand orders increases and the item set is more correlated in terms of order demand.

• Industrial Engineering and Management Systems
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• v.14 no.3
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• pp.275-288
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• 2015

Purchase dependence is a frequent phenomenon in retail shops and is characterized by the purchase of certain items together due to their unknown interior associations. Although this concept has been significantly examined in the marketing field (e.g. market basket analysis), it has largely remained unaddressed in operations management. Since purchase dependence is an important factor in designing inventory replenishment policies, this paper demonstrates the means of applying it to the partial backordering inventory model. Through computational analyses, this paper compares the performance of inventory models that either consider or ignore purchase dependence; the results demonstrate that inventory models that ignore purchase dependence incur more average cost per unit time than the model that considers purchase dependence, and the impact of purchase dependence can increase in significance as the item set becomes more closely correlated with regard to order demand.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.26-32
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• 2007

This study deals with waiting-time dependent backordering rate during stock-out period in the EconomicProduction Quantity (EPQ) model. Assuming that the backordering rate follows an exponentially decreasingfunction of the waiting time, the backorder rate is developed under First-Come-First-Served (FCFS) andLast-Come-First-Served (LCFS) Policy. The mathematical models are developed based on differential equations.Through numerical examples, the validity of the developed models is illustrated.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.71-80
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• 1996

This paper presents a stochastic partial inventory model for the situation in which demand is deterministic, lead time follows normal distribution and backorder ratio during the stockout period decreases exponentially according to the length of backorder period. In this situation, an objective function is formulated to minimize the average annual cost, which is the sum of the ordering, carrying time-proportional backordering, quantity-proportional backordering and lost sales costs. And then the procedure of iterative solution method for the model is developed to find optimal reorder point and order quantity and numerical example to illustrate the proposed method is presented.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.127-136
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• 1998

This paper presents a stochastic partial backorder inventory model for the situation in which demand follows normal distribution and back order ratio during that stockout period decreases exponentially according to the length of backorder period. In the paper, an objective function is formulated to minimize the average annual cost, which is the sum of the ordering, carrying, time-proportional backordering, and lost sales cost. And then sensitivity analysis for various exponential backorder ratios and standard deviations of leadtime demand are presented. The inventory model in the paper is reduced to a backorder model and lost sales model, when backorder ratio is 1 and 0, respectively.