Ganesh M.,JDA Software India Pvt. Ltd. |
Raghunathan S.,University of Texas at Dallas |
Rajendran C.,Indian Institute of Technology Madras
Decision Support Systems | Year: 2014
The literature on the value of information sharing within a supply chain is extensive. The bulk of the literature has focused on two-level supply chains that supply a single product. However, modern supply chains often have more than two levels and supply many products. Because many of these products are variants of the same base product, they tend to be substitutes and their demands correlated. Further, achieving supply-chain-wide information sharing in a multi-level supply chain is challenging because different firms may have different levels of incentives to share information. We analyze the value of information sharing using a comprehensive supply chain that has multiple levels, may have different degrees of information sharing, and supplies multiple products that may have different levels of substitutability and whose demands could be correlated to different degrees. Our analysis shows that substitution among the different products reduces the value of information sharing for all firms in the supply chain. The reduction is higher (i) for firms that are more upstream, (ii) when the degree of substitution is higher, (iii) when the number of substitutable products is higher, (iv) when the demands of products are more correlated, and (v) when the degree of information sharing is higher. Our results suggest that firms, especially those that are upstream in the supply chain, may face a significant risk of over-estimating the value of information sharing if they ignore substitution, demand correlation, and partial information sharing effects. © 2013 Published by Elsevier B.V.
Pazhani S.,Pennsylvania State University |
Ramkumar N.,JDA Software India Pvt. Ltd. |
Narendran T.T.,Indian Institute of Technology Madras |
Ganesh K.,McKinsey and Company
Journal of Industrial and Production Engineering | Year: 2013
Concerns over environmental degradation legislative requirements and growing business needs have fueled the growth of closed-loop supply chains (CLSCs). This paper addresses a bi-objective network design problem for multi-period, multi-product CLSC to minimize the total supply chain costs and to maximize the service efficiency of the warehouses and hybrid facilities. We develop a bi-objective mixed integer linear programming model to assist decisions in (1) location/ operating decisions for warehouses, hybrid facilities and manufacturing facilities and (2) production and distribution of products between stages in the supply chain. Goal programming models and compromise programming techniques are used to solve the problem. An application of the model is demonstrated using a case study from the literature. ©2013 Chinese Institute of Industrial Engineers.
Dulluri S.,JDA Software India Pvt. Ltd. |
Muthusamy G.,JDA Software India Pvt. Ltd.
International Journal of Information Systems and Supply Chain Management | Year: 2013
Service firms have become highly competitive in terms of providing the delivery. The delivery quality in terms of delivery commitments. Delivery commitments impact the customer in deciding for the service. Computing the delivery commitments in stochastic service systems is a real challenge. Delivery commitment forms a key parameter in formulating the service level agreements in B2B markets. In our current work we propose a queuing theoretic approach for computing the delivery commitments. The authors employ basic Probability theory to propose two bounds on delivery commitment time. Further, we investigate the effect of learning in service networks. They believe that their work can provide a simple and easy framework for quality analysis in stochastic service networks. Copyright © 2013, IGI Global.