13,882 research outputs found

    Evaluation of e-learning web sites using fuzzy axiomatic design based approach

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    High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

    Deriving consensus rankings via multicriteria decision making methodology

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    Purpose - This paper seeks to take a cautionary stance to the impact of the marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia. Design/methodology/approach - The ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4P's. Descriptive analysis is used to analyze best practice among the four marketing tactics. Findings - Outranking methods in consequence constitute a strong base on which to found the entire structure of the behavioral theory of benchmarking applied to development of marketing strategy. Research limitations/implications - This study looks only at a limited part of the puzzle of how consumer satisfaction translates into behavioral outcomes. Practical implications - The study provides managers with guidance on how to generate a rough outline of potential marketing activities that can be used to take advantage of capabilities and convert weaknesses and threats. Originality/value - The paper interestingly portrays the effective usage of multicriteria decision-making and ranking method to help marketing managers predict their marketing trends

    Overview and classification of coordination contracts within forward and reverse supply chains

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    Among coordination mechanisms, contracts are valuable tools used in both theory and practice to coordinate various supply chains. The focus of this paper is to present an overview of contracts and a classification of coordination contracts and contracting literature in the form of classification schemes. The two criteria used for contract classification, as resulted from contracting literature, are transfer payment contractual incentives and inventory risk sharing. The overview classification of the existing literature has as criteria the level of detail used in designing the coordination models with applicability on the forward and reverse supply chains.Coordination contracts; forward supply chain; reverse supply chain

    Optimization of the supplier selection process in prefabrication using BIM

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    Prefabrication offers substantial benefits including reduction in construction waste, material waste, energy use, labor demands, and delivery time, and an improvement in project constructability and cost certainty. As the material cost accounts for nearly 70% of the total cost of the prefabrication project, to select a suitable material supplier plays an important role in such a project. The purpose of this study is to present a method for supporting supplier selection of a prefabrication project. The proposed method consists of three parts. First, a list of assessment criteria was established to evaluate the suitability of supplier alternatives. Second, Building Information Modelling (BIM) was adopted to provide sufficient information about the project requirements and suppliers’ profiles, which facilitates the storage and sharing of information. Finally, the Analytic Hierarchy Process (AHP) was used to rank the importance of the assessment criteria and obtain the score of supplier alternatives. The suppliers were ranked based on the total scores. To illustrate how to use the proposed method, it was applied to a real prefabrication project. The proposed method facilitates the supplier selection process by providing sufficient information in an effective way and by improving the understanding of the project requirements

    Multi-agent knowledge integration mechanism using particle swarm optimization

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    This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.Ministry of Education, Science and Technology (Korea

    Uncertainty Models in Reverse Supply Chain: A Review

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    Reverse logistic has become an important topic for the organization due to growing environmental concern, government regulation, economic value, and sustainable competitiveness. Uncertainty is one of the key factors in the reverse supply chain that must be controlled; thus, the company could optimize the reverse supply chain function. This paper discusses progress in reverse logistic research. A total of 72 published articles were selected, analyzed, categorized and the research gaps were found among them. The study began by analyzed previous research articles in reverse logistic. In this stage, we also collected and reviewed journals discussing about the reverse supply chain. Meanwhile, the result of this stage shows that uncertainty factor has not been reviewed in detail. The most common theme as the background research in reverse logistic is environmental and economic aspect. Uncertainty in Close Loop Supply Chain is the most widely used approach, followed by the usage on reverse logistics, reverse supply chain and reverse Model. The most used approach and method on uncertainty are Mixed Integer Linear Programing, mixed integer nonlinear Programing, Robust Fuzzy Stochastic Programming, and Improved kriging-assisted robust optimization method. Customer demand, total cost, product returns are the most widely researched aspects. This paper may be useful for academicians, researchers and practitioners in learning on reverse logistic and reverse supply chain; therefore, close loop supply chain can be guidance for upcoming researches. Research opportunity based on this research combines total cost, quality return product, truck capacity, delivery route, remanufacturing capacity, and facility location got optimum function in uncertainty. The research method and approach for MINLP, IK-MRO and RSFP provide many opportunities for research. For theme and area in reverse logistic, close loop supply chain is the theme that provides the most research opportunities

    Decision support system in determining the location of new supermarket branches using the copras method

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    Supermarkets are one of the ideal and profitable retail business sectors to try because they are located in various urban and rural areas. This causes many people to be interested in setting up a supermarket. However, determining a strategic location is not easy and requires many strategic location considerations. The research objective is to develop a Decision Support System (DSS) to determine the location of new supermarket branches using the Complex Proportional Assessment (COPRAS) method, which is expected to be helpful for management and supermarket partners as a business strategy. The COPRAS method excels in calculating alternative utilities and selecting the best alternative. There are nine criteria (land rental price, distance to competitors, security, distance to education, warehouse distance, cleanliness, land area, building price, crowd) and five alternative locations (Juanda, Hos Cokroaminoto, Bayangkara, Batoro Katong, Sumoroto) are considered. This research created a web-based DSS that selects the best location for supermarket, with Juanda (A1) ranked first and scored 100, followed by Somoroto (location A5) with a score of 99.861, Bayangkara (A3) with a score of 97.099, Batoro Katong (A4) with a score of 91.293, and HOS Cokroaminoto (A2) with a score of 88.877. From the results of the COPRAS calculation, it can be concluded that Juanda is the best location to build a new supermarket branch location. This result provides a valuable tool for management and supermarket partners seeking to make informed decisions about branch expansion strategies

    A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators

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    The classical Analytical Hierarchy Process (AHP) has two limitations. Firstly, it disregards the aspect of uncertainty that usually embedded in the data or information expressed by human. Secondly, it ignores the aspect of interdependencies among attributes during aggregation. The application of fuzzy numbers aids in confronting the former issue whereas, the usage of Choquet Integral operator helps in dealing with the later issue. However, the application of fuzzy numbers into multi-attribute decision making (MADM) demands some additional steps and inputs from decision maker(s). Similarly, identification of monotone measure weights prior to employing Choquet Integral requires huge number of computational steps and amount of inputs from decision makers, especially with the increasing number of attributes. Therefore, this research proposed a MADM procedure which able to reduce the number of computational steps and amount of information required from the decision makers when dealing with these two aspects simultaneously. To attain primary goal of this research, five phases were executed. First, the concept of fuzzy set theory and its application in AHP were investigated. Second, an analysis on the aggregation operators was conducted. Third, the investigation was narrowed on Choquet Integral and its associate monotone measure. Subsequently, the proposed procedure was developed with the convergence of five major components namely Factor Analysis, Fuzzy-Linguistic Estimator, Choquet Integral, Mikhailov‘s Fuzzy AHP, and Simple Weighted Average. Finally, the feasibility of the proposed procedure was verified by solving a real MADM problem where the image of three stores located in Sabak Bernam, Selangor, Malaysia was analysed from the homemakers‘ perspective. This research has a potential in motivating more decision makers to simultaneously include uncertainties in human‘s data and interdependencies among attributes when solving any MADM problems
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