• Industrial Engineering and Management Systems
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• 제8권2호
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• pp.72-79
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• 2009

The ultimate goal of inventory management is to decide the timing and the quantity of ordering in response to uncertain demands. Recently, some researchers have focused upon an impact of distortions in the information, e.g., customer order cancellation, on an economical inventory policy. The customer order cancellation is considered a kind of distortions in demands, because a demand that is eventually cancelled is equivalent to a phony demand. Also, there are some additional distortions in the inventory information. For instance, the procurement of suppliers may include some nonconforming items as a result of imperfect production and inspection by the suppliers, and/or damage in transit. The nonconforming item should be considered a kind of distortions in the inventory information, because the nonconforming item is equivalent to a phony stock. In this article, we consider an inventory model under the situation that customers can cancel their orders and the procurement of suppliers may include some nonconforming items. Then, we introduce the customer order reservation into the inventory model for the purpose of avoiding the costly backlogs, because the customer order reservation gives retailers a period to fulfill customer's requests. We formulate a periodic review (s, S) inventory model and investigate the economical operation under the situation mentioned above. Further, through the sensitivity analysis, we show the impact of these distortions and the effect of the customer order reservation on the inventory policy.

• Management Science and Financial Engineering
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• 제14권1호
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• pp.35-63
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• 2008

We discuss the problem of selecting profitable customer orders arriving at a company providing two classes of services. For an arriving customer order for the first class, the company 1) makes a decision whether to accept or reject it (admission control), or 2) decides a price of the order to offer to an arriving customer (pricing control). The customer order undergoing processing in the system may be cancelled owing to unavoidable circumstances with the customer. The second class of service is provided as a sideline, which prevents the server from being idle when all the customer orders for the first class are completed and delivered. This yields the sideline profit. We discuss both admission control and pricing control problems in an identical framework as well as examine the structure of the optimal policies maximizing the total expected present discounted net profit gained over an infinite planning horizon.

• 한국정보시스템학회지:정보시스템연구
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• 제30권2호
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• pp.105-126
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• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.207-223
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• 2013

Revenue management (RM) has been widely used to model products characterized as perishable. Classical RM model assumed that price is the sole factor in the model. Thus price adjustment becomes a crucial and costly factor in business. In this paper, an optimal pricing model is developed based on minimization of soft customer cost, one kind of price adjustment cost and is solved by Lagrange multiplier method. It is formed by expected discounted revenue/bid price integrating quantity-based RM and pricing-based RM. Quantity-based RM consists of two capacity models, namely, booking limit and overbooking. Booking limit, built by assuming uncertain customer arrival, decides the optimal capacity allocation for two market segments. Overbooking determines the level of accepted order exceeding capacity to anticipate probability of cancellation. Furthermore, pricing-based RM models occupancy/demand rate influenced by internal and competitor price changes. In this paper, a mathematical model based on game theoretic approach is developed for two conditions of deterministic and stochastic demand. Based on the equilibrium point, the best strategy for both hotels can be determined.

• 지능정보연구
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• 제17권2호
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• pp.61-75
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• 2011

시설물이나 토지, 도로, 방재 등 다방면에서 GIS의 효과성이 입증됨에 따라 최근 들어 상권이나 고객, 영업 관리 등에 GIS를 도입하여 시장분석 및 영업관리 역량을 강화하려는 민간 기업들이 증가하고 있다. 본 사례 연구에서는 날로 치열해지고 있는 통신시장의 경쟁환경 속에서 K사가 정교한 상권 및 고객 분석 역량을 확보하기 위해 GIS 영업정보 시스템을 구축 한 전 과정과 영업현장에서의 시스템 활용방안 등을 살펴보았다. 전사적으로 시스템을 오픈한 후 지사들로부터의 반응은 담당 관할구역에 대한 경쟁상황 파악 및 일/월 추세조회가 용이해 졌고, 왜곡되지 않은 실제 데이터를 제공받아 제한된 시간 내에 정확한 타겟 고객 선정이 가능해졌으며, 동별 시설분포와 같은 시설물 관련정보를 영업활동에 활용할 수 있어 매우 효과적이었다는 등이 주를 이루었다. 이와 같은 과정과 결과를 정리함으로써 향후 GIS 영업정보시스템 구축을 고려하고 있는 타 조직이나 기업들에게 의미 있는 가이드라인을 제시할 수 있기를 기대한다.