International Journal of Industrial Engineering & Production Research

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Service Oriented Enterprises (SOEs) are subject to constant change and variation. In this paper, the changes are considered from an economic perspective based on service culture notion. Once a change is implemented, the costs of some member services may increase, whereas the costs of some other services may reduce. We construct a game theoretic model trying to capture the possible conflicting interests of different parties in a SOE. Three incentive mechanisms are applied to the model. The first incentive mechanism shares the utility equally among the services involved in the change the second utility-sharing rule is based on the Nash’s bargaining solution, which accommodates the possible biased interdependencies inside the network and the third rule, based on the Harsanyi’s modified Shapley value, takes into account the possible coalition formation among the network parties. Since the three rules are analytically solvable, the principles of utility sharing can be implemented, for instance, as ex-ante contracts.

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Assessment and selection of suppliers are two most important tasks in the purchasing part in supply chain management. Supplier selection can be considered to be a single or multi-objective problem. From another point of view, it can be a single or multi-sourcing problem. In this paper, an integrated AHP and Fuzzy TOPSIS model is proposed to solve the supplier selection problem. This model makes the decision-maker to be able to solve this problem with different criteria and different weight for each criterion with respect to the purchasing strategy. Finally, the proposed model is illustrated by an example.

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  Response time is one of the critical web service quality dimensions. It refers to how long it takes that a web service responds to request of a user. In order to manage the response time, pricing schemes can work as an efficient access control mechanism. In this paper, we study competition between two providers offering functionally same web services where there is a monopoly service provider. The monopoly offers a service that is complementary to their services. Each provider needs to decide a service level (L or H) and a corresponding price for the selected service level to meet the service level guarantee. We construct a Stackelberg game and benefit from queuing theory concept to propose a model that can examine strategic choices of the providers .

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  This article investigates integrated production-inventory models with backorder. A single supplier and a single buyer are considered and shortage as backorder is allowed for the buyer. The proposed models determine optimal order quantity, optimal backorder quantity and optimal number of deliveries on the joint total cost for both buyer and supplier. Two cases are discussed: single-setup-single-delivery (SSSD) case and single-setup-multiple-deliveries (SSMD) case. Two algorithms are applied for optimizing SSMD case: Gradient search and particle swarm optimization (PSO) algorithms. Finally, numerical example and sensitivity analysis are provided to compare the total cost of the SSSD and SSMD cases and effectiveness of the considered algorithms. Findings show that the policy of frequent shipments in small lot sizes results in less total cost than single shipment policy .

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  Multiple criteria decision making (MCDM) problem is one of the famous different kinds of decision making problems. In more cases in real situations, determining the exact values for MCDM problems is difficult or impossible. So, the values of alternatives with respect to the criteria or / and the values of criteria weights, are considered as fuzzy values (fuzzy numbers). In such conditions, the conventional crisp approaches for solving MCDM problems tend to be less effective for dealing with the imprecise or vagueness nature of the linguistic assessments. In this situation, the fuzzy MCDM methods are applied for solving MCDM problems. In this paper, we propose a fuzzy TOPSIS (for Order Preference by Similarity to Ideal Solution) method based on left and right scores for fuzzy MCDM problems. To show the applicability of the proposed method, two numerical examples are presented. As a result, our proposed method is precise, easy use and practical for solving MCDM problem with fuzzy data. Moreover, the proposed method considers the decision makers (DMs) preference in the decision making process. It seems that the proposed fuzzy TOPSIS method is flexible and easy to use and has a low computational volume .

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This article develops an integrated JIT lot-splitting model for a single supplier and a single buyer. In this model we consider reduction of setup time, and the optimal lot size are obtained due to reduced setup time in the context of joint optimization for both buyer and supplier, under deterministic condition with a single product. Two cases are discussed: Single Delivery (SD) case, and Multiple Delivery (MD) case. These two cases are investigated before and after setup time reduction. The proposed model determines the optimal order quantity (Q*), optimal rate of setup reduction (R*), and the optimal number of deliveries (N*) -just for multiple deliveries case- on the joint total cost for both buyer and supplier. For optimizing our model two algorithm including Gradient Search and Particle Swarm Optimization (PSO), which is a population-based search algorithm, are applied. Finally numerical example and sensitivity analysis are provided to compare the aggregate total cost for two cases and effectiveness of the considered algorithm. The results show that which policy for lot-sizing is leading to less total cost.

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Abstract Customer Lifetime Value (CLV) is known as an important concept in marketing and management of organizations to increase the captured profitability. Total value that a customer produces during his/her lifetime is named customer lifetime value. The generated value can be calculated through different methods. Each method considers different parameters. Due to the industry, firm, business or product, the parameters of CLV may vary. Companies use CLV to segment customers, analyze churn probability, allocate resources or formulate strategies related to each segment. In this article we review most presented models of calculating CLV. The aim of this survey is to gather CLV formulations of past 3 decades, which include Net Present Value (NPV), Markov chain model, probability model, RFM, survival analysis and so on.

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Data mining is a powerful tool for firms to extract knowledge from their customers’ transaction data. One of the useful applications of data mining is segmentation. Segmentation is an effective tool for managers to make right marketing strategies for right customer segments. In this study we have segmented retailers of a hygienic manufacture. Nowadays all manufactures do understand that for staying in the competitive market, they should set up an effective relationship with their retailers. We have proposed a LRFMP (relationship Length, Recency, Frequency, Monetary, and Potential) model for retailer segmentation. Ten retailer clusters have been obtained by applying K-means algorithm with K-optimum according Davies-Bouldin index on LRFMP variables. We have analyzed obtained clusters by weighted sum of LRFMP values, which the weight of each variable calculated by Analytic Hierarchy Process (AHP) technique. In addition we have analyzed each cluster in order to formulate segment-specific marketing actions for retailers. The results of this research can help marketing managers to gain deep insights about retailers.