مدل موجودی رضایت مشتری برای یکپارچه سازی زنجیره تامین
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|20615||2011||9 صفحه PDF||سفارش دهید||4939 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 38, Issue 1, January 2011, Pages 875–883
Customer relationship is increasingly influencing the performance of inventory management in a supply chain, and customer retention or migration directly affect the number of customer orders and demands as well as the inventory level. Therefore, the aim of this paper is to propose a customer satisfaction inventory (CSI) model that incorporates customer relationship management into an inventory model, where the probabilistic concepts of Markov chains of uncertainties in customer relationships of retention or migration are adopted. This enables us to determine both a CSI level for replenishing the inventory level to best fit future customer demand and a customer CSI value of the net profit or loss of an organization from a customer over its purchasing life against the inventory cost of an organization. The modeling and development of the proposed customer satisfaction inventory CSI model are discussed in this paper. Simulation and analysis are conducted for the proposed model, and satisfactory results are achieved, such that the proposed model can help to determine a CSI level that can fully meet orders and demand as well as minimizing inventory cost and maximizing CSI value.
Inventory management and customer relationship management are two co-related aspects in a supply chain, where customer relationship increasingly influences the performance of inventory management (Silver, 1981 and Swink et al., 2007). The tendency of a customer’s retention or migration can directly affect the number of customer orders and demands as well as the inventory level in a supply chain (Sramek et al., 2008 and Zhu and Thonemann, 2004). Information, including marketing strategy or sales demand etc. (Wang, Lau, & Lau, 2008) should also be shared within a supply chain. Among various expenditures in a supply chain, inventory costs generally account for the majority. Therefore, minimizing the inventory cost is a major objective in a supply chain, and it is widely accepted that keeping excessive stock is costly and ineffective (Aggawal, 1974). During the past few decades, various literatures and models have been published and proposed for effective inventory management (Axsater, 2006, Bartmann and Beckmann, 1992, Lewis, 1997, Lu et al., 2005, Pfohl et al., 1999, Watts et al., 1994, Xiong and Helo, 2006 and Yung et al., 2007), for example the Economic Order Quantity Model, RM-System, Newsvendor Problem, AHM Model, Bisection Method, etc. However, most of these inventory management models only account independently for various demand patterns, quantity discount, stockout costs, lead time variations, multi-stage/multi-item situations, etc., but few concepts or models are suggested for incorporating the customer relationship into the inventory management model. Therefore, in this paper, a customer satisfaction inventory CSI model is proposed for the supply chain. This is an integrated model that incorporates the probabilistic concepts of Markov chains of uncertainties in customer relationships of retention or migration into an inventory model, such that the customer loyalty towards a supply chain becomes a decision variable in the inventory management, and customer relationship management and inventory management can then be integrated in the supply chain. Supply chain integration can enhance the overall supply chain performance ( Fuentea et al., 2008, Lam et al., 2008 and Lam et al., 2009). More importantly, customer loyalty and retention play a vital role in a supply chain, as acquisition costs considerably exceed retention costs ( Bloomberg, 2001 and Dyche, 2002), and loyal customers with a long-standing relationship with the supply chain will make regular repeat purchases, thereby facilitating a gain in long-term profits ( Chan et al., 2008 and Ip et al., 2008). The Markov chains model is a probabilistic model accounting for the uncertainties in customer relationships. It uses probability and expected value to measure future relationships with an individual customer. The concepts of Markov chains are capable of modeling customer relationships and supporting business decision making for business growth, features that are in high demand in the disciplines of marketing and customer relationships (Bornnenberg, 1998, Chen et al., 2005 and Lu and Jiang, 2004). It has been claimed that the major advantages of the Markov chain model are its flexibility and sophistication (Isaacson and Madsen, 1976 and Puterman, 1994). Markov chains make use of a series of states of a system or process to identify all possible conditions; a Markov chains model of purchases states for a customer relationship (Pfeifer and Carraway, 2000) is shown in Fig. 1. It has a wide range of Markov properties, including reducibility, periodicity, recurrence, ergodicity, steady-state analysis, and limited distribution for precise prediction. Markov chains modeling can handle customer retention and customer migration situations, and can apply either to an existing customer or to a prospective customer. Therefore, by incorporating Markov chains into the inventory model, customer relationships of retention and migration can be analyzed and evaluated in the inventory management of the supply chain. Full-size image (16 K) Fig. 1. Markov chains model of purchasing states for customer relationship. Figure options The structure of this paper is as follows: in Section 2, the proposed customer satisfaction inventory CSI model is defined and modeled, and the assumptions and algorithms for the modeling are presented. In Section 3, a decision support system is developed to illustrate the effect of the proposed CSI model, datasets are collected and analyzed, and the empirical analysis results are presented afterward. Finally, a conclusion with further developments is given in Section 4.
نتیجه گیری انگلیسی
In this paper, a customer satisfaction inventory CSI model is proposed for inventory management in the supply chain. The conventional inventory model is improved to incorporate customer satisfaction, and utility functions of customer satisfaction inventory level (CSI level) and customer satisfaction inventory value (CSI value) are derived from the proposed model. The proposed model is an integrated model that incorporates the probabilistic concepts of Markov chains of uncertainties in relationships of customer retention or migration into an inventory model, and the customer relationship then becomes a decision variable in the inventory management as well as in the determination of CSI level and CSI value for a supply chain. From the simulation results and analysis of the developed decision support system, satisfactory results show that the proposed model can help to determine an inventory level that can fully meet customer orders as well as keeping inventory costs low. It can therefore be concluded that the proposed CSI model approach can provide new possibilities for inventory management in the supply chain. The model in this paper can be further improved in several aspects, for instance by adjusting and incorporating more factors such as distribution, transportation, and stockout costs to the model in order to determine the CSI level and CSI value of the proposed model and thereby attain a more accurate outcome. Further research should also be undertaken to investigate the optimization of the proposed model.