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Dive into the research topics where Samar K. Mukhopadhyay is active.

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Featured researches published by Samar K. Mukhopadhyay.


International Journal of Physical Distribution & Logistics Management | 2004

Reverse logistics in e‐business

Samar K. Mukhopadhyay; Robert Setoputro

In an Internet direct sales supply chain, the customers buy direct from the manufacturer sacrificing the benefit of physical inspection of the product. This increases the likelihood that customers will have some dissatisfaction with the product and would like to return it. A clearly explained and generous return policy, then, will be welcome by the customers and therefore will enhance demand. From the manufacturers point of view, this will increase revenue, but will also increase cost due to increased likelihood of return. This paper develops a profit‐maximization model to obtain optimal policies for price and the return policy in terms of certain market reaction parameters. It obtains jointly a number of managerial guidelines for using marketing and operational strategy variables to influence the reaction parameters so as to obtain the maximum benefit from the market. The paper mentions several future research possibilities.


International Journal of Physical Distribution & Logistics Management | 2006

The role of 4PL as the reverse logistics integrator

Samar K. Mukhopadhyay; Robert Setaputra

Purpose – An effective return policy is used as an important competitive weapon in the marketplace to substantially influence product sales. However, return policy is also seen as a problem for all parties in the supply chain due to the headache in processing returned merchandise. While retailers are efficient in selling, they do not usually have the expertise in handling the reverse flow. The purpose of this paper is to propose the use of a fourth party logistics (4PL) as a return service provider, and develops optimal decision policies for both the seller and the 4PL.Design/methodology/approach – A profit‐maximization model is presented to jointly obtain optimal policies for the seller and the 4PL through the use of Stackelberg like game theory, where the seller acts as the leader and the 4PL acts as the follower.Findings – Optimal values for the sellers and the 4PLs decisions are presented. Conditions under which profits for the seller and 4PL both increase are shown.Practical implications – This pap...


European Journal of Operational Research | 2007

A dynamic model for optimal design quality and return policies

Samar K. Mukhopadhyay; Robert Setaputra

Abstract A clearly explained and generous return policy has been established as a competitive weapon to enhance sales. From the firm’s point of view, a generous return policy will increase sales revenue, but will also increase cost due to increased likelihood of return. Design quality of the product has been used as a competitive weapon for a long time. This paper recognizes the relationship between design quality and price of the product, and the firm’s return policy. Quality level in the product would influence the amount of return directly. When the product quality is higher, the customer satisfaction rate will increase and the probability of return will decrease. We develop a profit-maximization model to jointly obtain optimal policies for the product quality level, price and the return policy over time. The model presented in this paper is dynamic in nature and considers the decisions as the product moves through the life cycle. We obtain a number of managerial guidelines for using marketing and operational strategy variables to obtain the maximum benefit from the market. We mention several future research possibilities.


Naval Research Logistics | 1995

Optimal timing schedules in earliness-tardiness single machine sequencing

Wlodzimierz Szwarc; Samar K. Mukhopadhyay

The article deals with a single machine earliness-tardiness scheduling model where idle times are permitted in job processing. Based on a cluster concept we develop properties of the model that lead to a very fast algorithm to find an optimal timing schedule for a given sequence of jobs. The performance of this algorithm is tested on 480 randomly generated problems involving 100, 200, 400 and 500 jobs. It takes less than two seconds to solve a 500 job problem on a PC.


European Journal of Marketing | 1998

Interfaces for resolving marketing, manufacturing and design conflicts

Samar K. Mukhopadhyay; Anil V. Gupta

Marketing‐manufacturing interface is becoming an increasingly important research area, as the firms unable to reduce inter‐departmental conflict find their global competitiveness compromised. Due to inevitable interaction of marketing and manufacturing with design engineering in conflict and resolution, there is a need to increase the scope of the research area of manufacturing‐marketing interface to include design (engineering) and establish appropriate interfaces between each pair of these domains. Some firms are practising concurrent engineering to minimise the conflict between design and manufacturing departments. Several interface variables can be used to resolve inter‐departmental conflict. A firm’s decision to pursue a particular interface requires commitment, investment and change in culture. What type of interface should a firm choose? This paper introduces a conceptual framework to resolve this dilemma. Specifically, the contribution of this paper is at least threefold. First, it characterises the possible conflicts that can arise due to interaction between the three functional areas – marketing, manufacturing, and design. Design is recognised as a separate function in its own right. Second, it identifies and describes possible variables that can be utilised as interfaces to resolve conflicts. Third, it establishes a methodology to develop a framework to assess inter‐departmental conflict and identify an optimal mix of interface variables to resolve all possible conflicts. The paper concludes with an actual case study involving a global marketing‐manufacturing company and provides an application of this framework and methodology.


Operations Research Letters | 1996

Decomposition of the single machine total tardiness problem

Wlodzimierz Szwarc; Samar K. Mukhopadhyay

The paper deals with the single machine total tardiness problem. It develops a new decomposition rule and presents a special and very fast branch and bound algorithm based on pure decomposition. This algorithm is tested on 2400 problems whose sizes vary from 100 to 150 jobs.


Operations Research | 1997

A Differential Game Theoretic Model for Duopolistic Competition on Design Quality

Samar K. Mukhopadhyay; Panagiotis Kouvelis

In this paper we propose a differential game theoretic model to analyze the design quality and pricing decisions for a product over the product life cycle. The market is represented as a duopoly where our product competes against a similar product marketed by our competition. The duopolistic competition is modeled as a two-player nonzero sum noncooperative game. The resulting control theoretic model is solved under certain functional assumptions to describe the Nash equilibrium strategies of the two competitors. Finally, observations made on an extensive set of numerical experimentations over a variety of model parameters are summarized into a set of relevant managerial guidelines on developing design quality and pricing strategies.


Iie Transactions | 1999

Modeling the design quality competition for durable products

Panagiotis Kouvelis; Samar K. Mukhopadhyay

In this paper we model the design quality competition in durable product markets. We use a duopolistic non-cooperative game theoretic framework. Each firm controls the design quality level and the price of its product. The resulting control theoretic model is solved under certain functional assumptions to describe the Nash equilibrium design quality and pricing strategies of the two competitors. We compare open and closed loop design quality and pricing strategies. We use an extensive set of numerical experiments to investigate the effects of various parameters of the model on the optimal policies. We conclude with a brief summary of our results and some useful managerial insights derived from the model.


International Journal of Quality & Reliability Management | 1995

Optimal process variance under Taguchi loss

Samar K. Mukhopadhyay; Debopam Chakraborty

Most research on the process control charts concentrates on the economic design of its parameters. Reduction of variance as a control decision has not been researched. Presents a model for optimal decision on variance reduction and includes the rejection losses of the non‐conforming units increasing due to increased variance, Taguchi loss of the conforming units, and the cost of reducing variance. Optimal policies are derived analytically for uniform distribution and numerically for normal distribution. Applications of the model to the area of machine replacement and global manufacturing are suggested.


International Journal of Logistics Systems and Management | 2010

A framework for research in reverse logistics

Robert Setaputra; Samar K. Mukhopadhyay

In recent years, there have been growing interests from both academicians and practitioners to study the topic of reverse logistics. We attempt to develop a research framework in the area of reverse logistics by dividing it into six research categories. We categorise these areas, provide an extensive literature survey, and show the basic research premises and scope of each of these areas. This research will help future researchers in reverse logistics to focus their work to the appropriate field. This research will also help practitioners working on reverse logistics to find managerial guidelines in making specific decisions.

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Dive into the Samar K. Mukhopadhyay's collaboration.

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Xiaohang Yue

University of Wisconsin–Milwaukee

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Xiaowei Zhu

West Chester University of Pennsylvania

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Robert Setaputra

Shippensburg University of Pennsylvania

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Wlodzimierz Szwarc

University of Wisconsin–Milwaukee

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Ziping Wang

Morgan State University

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Panagiotis Kouvelis

Washington University in St. Louis

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Sanjoy Ghose

University of Wisconsin–Milwaukee

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Xuemei Su

California State University

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