30,022 research outputs found

    Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

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    The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment

    Problems of Evaluating Small Firms’ Quality as a Reason for Unfavourable Loan Conditions

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    The article substantiates the hypothesis that the profitability of small firms is above all determined by qualitative variables. In this respect a low standardization of goods and even more importantly, the high significance of governance structures play a crucial role rendering the quality of the firm’s human capital, the flexibility of its machinery but also externalities of business networks, an appropriate integration of the family into business affairs as examples of qualitative information which also bear a high degree of privacy. Whereas the literature suggests relational contracts as a way how qualitative and private information can be credibly conveyed to the lender, it is shown that even in the German housebank-dominated financial system borrower- lender relationships of the kind recommended by the literature are hardly to be found. Rather, German banks, too, respond to information gaps with unfavourable loan conditions. As an alternative specialized information intermediation is briefly discussed.Small firms financing, rationing, information

    Optimization of Evolutionary Neural Networks Using Hybrid Learning Algorithms

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    Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. Evolutionary algorithms are used to adapt the connection weights, network architecture and learning algorithms according to the problem environment. Even though evolutionary algorithms are well known as efficient global search algorithms, very often they miss the best local solutions in the complex solution space. In this paper, we propose a hybrid meta-heuristic learning approach combining evolutionary learning and local search methods (using 1st and 2nd order error information) to improve the learning and faster convergence obtained using a direct evolutionary approach. The proposed technique is tested on three different chaotic time series and the test results are compared with some popular neuro-fuzzy systems and a recently developed cutting angle method of global optimization. Empirical results reveal that the proposed technique is efficient in spite of the computational complexity

    The evaluation of E-business related technologies in the Railway Industry

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    For the purposes of this paper, e-business is defined as: "the performance, automisation and organisation of transactions, or chains of them, and the gathering and publishing of data, electronically over a communication protocol" Little research has been conducted either into how e-business technology can be successfully evaluated, or into the associated costs and benefits specifically related to the transportation and railway industries. Based upon a review of the current literature and a series of interviews held with railway operators, track managers and transportation customers from the Australian Fortune 100, the paper puts forward a framework for the evaluation of e-business investments within the railway industry. The research reported here is aimed at developing a flexible interface that enables the decision maker to assess and evaluate a wide variety of complex interacting variables. The proposed approach uses a variety of evaluation methods, as opposed to searching for a single "best" approach. Additionally, an attempt is being made to include the complex interaction between the implementation of the new technology and the changing organisational setting. A model is proposed using fuzzy logic to handle incomplete and uncertain knowledge; as well as to combine criteria within a conceptual model from which "real-worth" evaluations can be performed. This model provides a systematic approach to guide the decision maker in the deployment of e-business and emerging technologies in the industry. After discussing the main findings from a literature review on the use of evaluation frameworks in IT related projects, the paper deals with the proposed framework in detail. The use of empirical data, which was obtained transportation customers to help define the main framework factors, is also discussed. Finally, the paper summarises the main implications for rail freight of customers’s perceptions and stated needs in the e-business domain
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