E-learning websites evaluation and selection is extremely important for the establishment of ef-fective E-learning. The E-learning website selection has crucial importance for the educational sector. The selection of E-learning website problem is generally considered as a Multi-Criteria Decision Making (MCDM) problem which mainly consists of both qualitative and quantitative criteria. The development of an E-learning website mainly depends on the success of the E-learning website selection along with various alternatives. So, for the effective evaluation and se-lection of E-learning websites, a set of selection criteria should be obtained. This paper consists of two steps, the first step is the identification of E-learning website selection criteria, second step provides the linguistic variables against the selection criteria and then fuzzy set theory (FST) is adopted for the calculation of the priority weights of each selection criteria. To show the rela-tive importance of each selection criteria, they ranked according to their global weights.
This study develops an effective method to measure value chain performance and rank them based on qualitative criteria and to determine the ranking order of the various forms of performance under study. This approach integrates the advantage of grey systems theory and TOPSIS to evaluate and rank value chain performance. Grey-TOPSIS approach has been applied to measure and rank the value chain performance of various firms. The results indicate that the proposed model is useful to facilitate multi-criteria decision-making (MCDM) problem under the environment of uncertainty and vagueness. The model also provides an appropriate ranking order based on the available alternatives. The Grey-TOPSIS approach that will be useful to the managers to use for solving the similar type of decision-making problems in their firms in the future has been discussed. Even though, the problem of choosing a suitable performance option is often addressed in practice and research, very few studies are available in the literature of Grey-TOPSIS decision models. Also, Grey-TOPSIS model application in the tea processing firms is non-existence hence this study is the very first to apply this model in evaluating value chain performance in the tea processing firms.
Nowadays, selecting the most appropriate location for hub is one of the most significant issues not only in road, rail and air transportations, but also in maritime. Transshipment is the fastest growing segment of the marine container market; it increases traffic flow of marine container and scope of this type of marine carriage, accordingly. In this way, determining a movement loop for the voyages of a shipping company, probes identification of container hub ports by considering different operational factors including distance to the destinations. The focus of this paper is to locate the best location for container transshipment hub in southern seas of Iran. In this paper, an MCDM model is proposed for evaluating and selecting the marine container transshipment hub port. Finally, the utilization of the proposed model is demonstrated with a real case study of Iranian main ports. The results show that the MCDM model can be used to explain the evaluation and decision-making procedures of a proper marine container hub location selection.
The 20th century was the age of an industry-based as well as knowledge-based economy. In a knowledge-based economy, knowledge plays an essential role to produce wealth compared with other tangible and physical assets. The purpose of this research is to identify and rank different aspects of knowledge management based on the Hicks model using the fuzzy TOPSIS technique for one of the most prestigious universities in Iran. The proposed model considers four main criteria of knowledge including creation, distribution, storage, and application along with 17 sub-criteria. The Chi-square correlation test indicates a positive and meaningful correlation between four mentioned criteria and knowledge management implementation. Using the fuzzy TOPSIS technique, the results also indicate that “Need for new and updated information and knowledge” was selected as the most important sub-criterion and “Sharing or distribution of knowledge” was selected as the most important main criterion on Hicks model.