Along with the increased competition in production and service areas, many organizations attempt to provide their products at a lower price and higher quality. On the other hand, consideration of environmental criteria in the conventional supplier selection methodologies is required for companies trying to promote green supply chain management (GSCM). In this regard, a multi-criteria decision-making (MCDM) technique based on analytic hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) is used to evaluate and rate the suppliers. Then, considering the resource constraint, weight of criteria and a rank of suppliers are taken into account in a multi-objective mixed-integer linear programming (MOMILP) to determine the optimum order quantity of each supplier under uncertain conditions. To deal with the uncertain multi-objectiveness of the proposed model, a robust goal programming (RGP) approach based on Shannon entropy is applied. The offered methodology is applied to a real case study from a green service food manufacturing company in Iran in order to verify its applicability with a sensitivity analysis performed on different uncertainty levels. Furthermore, the threshold of robustness worthiness (TRW) is studied by applying different budgets of uncertainty for the green service food manufacturing company. Finally, a discussion and conclusion on the applicability of the methodology is provided, and an outlook to future research projects is given.

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M ost automobile manufacturers use franchised dealers to distribute their products and to perform sales-related and after-sales services. However, the link between dealers' service quality and manufacturer performance is not well understood. Some studies suggest that these services' quality affects product sales, repeat sales, and brand reputation. Others posit that dealer services are a commodity, and their quality may only affect sales in the extremes. We constructed data representing sales and service quality ratings of 1078 U.S. automobile dealerships over a year in five different car classes. We find that the quality of after-sales services positively influences sales of the brand in the dealer's region. Manufacturers whose dealers struggle with after-sales services take a hit in market share even in markets where they enjoy superior competitive status. We also find that sales-related services gain importance in highly competitive markets where the manufacturer has few dealers and competitors have many.

The balanced scorecard (BSC) is a strategic management method that links performance measurement to vision and strategies using a multidimensional set of financial and non-financial performance metrics. Although several studies have combined the BSC method with multi-criteria decision analysis methodologies, most of the research efforts do not consider the essentials of strategic and performance management in a systematic and holistic framework capable of handling imprecision and vagueness. The purpose of this study is to present a novel approach for structuring and prioritising the performance measures in the BSC method. The contribution of the proposed approach is fivefold: 1) we use the quality function deployment (QFD) technique to create a linkage between the BSC perspectives; 2) we use the analytic network process (ANP) technique to consider the interactions between the performance measures in each BSC perspective; 3) we integrate the QFD and the ANP techniques to help decision makers understand the relations between the performance measures in different perspectives and the correlations among the performance measures in the same perspective; 4) we handle the vagueness and ambiguity in decision makers' judgements with the fuzzy set theory; 5) we present a case study to demonstrate the applicability of the proposed approach and exhibit the efficacy of the procedures.

Security mechanisms are substantial to an e-business environment. While many security mechanisms have been developed to secure e-business processes (EBP) and networks, little attention is given to actual process of a systematic decision making. In most cases strongest security level available is selected. In many cases there are low risks and threats associated with the processes and the use of strong security wastes the available resources. In this paper the authors developed a practical multiple criteria decision making model based on the group fuzzy technique for order preference by similarity to ideal solution (GFTOPSIS) for choosing adequate security mechanism for e-business processes and making a trade-off between security and other important factors in the enterprise. Data was acquired from experts and implemented fuzzy approach. The authors differentiated four phases in the EBP. Each phase of the process which has specific security requirements thus we suggested the use of specified security mechanisms for each phase which improves the efficiency of the system.