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This paper proposes fuzzy multi-criteria decision-making approach integrated with fuzzy real option value theory. The applicability of the proposed method was shown on a real-world supermarket location selection problem. Based on the interviews with the experts, the evaluation criteria for retail location selection were identi¯ed. Then the network for fuzzy analytic network process (ANP) method was constructed. The fuzzy real option value for each alternative was calculated and used in the proposed approach as the representative of thē nancial dimension. Finally, the preference ranking of alternatives and the relative importance of the criteria were obtained. The signi¯cant contribution of the proposed approach is that it integrates the¯nancial dimension (FROV) of the location problem methodologically with the multi-criteria characteristic (FANP) of the problem. Another importance of this study is thē rst usage of real options valuation in the area of location selection science.

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In the process of fuzzy decision-making, ranking of fuzzy numbers is a necessity. The types of fuzzy numbers are triangular, trapezoidal, and L-R type. In the literature, there are many methods developed for ranking fuzzy numbers. These methods may produce different ranking results. Many of these methods necessitate graphical representations, complex and tedious calculations. The method developed in this paper has some advantages with respect to the other methods in both graphical representations and calculations. Applicability of the proposed method to multi-criteria decision-making methods, i.e. fuzzy scoring, fuzzy AHP and fuzzy TOPSIS methods, is shown in the paper.

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Knowledge management (KM) systems can provide businesses a wide range of advantages and efficiency improvements. Increasing competition forces companies to seek new ways to streamline their processes and manage their information and knowledge better, leading to increased demand for KM solutions. Considering various needs of organizations and diverse features of available KM alternatives, choosing the most suitable KM tool is an important decision for businesses. The contribution of this paper to the KM literature is a KM evaluation framework for decision makers to compare available KM products of different vendors by first identifying relevant evaluation criteria and then proposing a group decision making framework using the Interval Type-2 TOPSIS technique. This method has more flexibility in handling uncertainties compared to the Type-1 fuzzy sets and enables decision makers to effectively analyze, compare and select the most appropriate KM tools. The framework is also used in a case study for the sake of demonstrating its potential in businesses.

By 2050, the global population is estimated to rise to over 9 billion people, and the global food need is expected to ascend 50%. Moreover, by cause of climate change, agricultural production may decrease by 10%. Since cultivable land is constant, multi-layered farms are feasible alternatives to yield extra food from the unit land. Smart systems are logical options to assist production in these factory-like farms. When the amount of food grown per season is assessed, a single indoor hectare of a vertical farm could deliver yield equal to more than 30 hectares of land consuming 70% less water with nearly zero usage of pesticides. In this study, we evaluated technology selection for three vertical farm alternatives via MCDM methods. Even though commercial vertical farms are set up in several countries, area is still fresh and acquiring precise data is difficult. Therefore, we employed fuzzy logic as much as possible to overcome related uncertainties. WEDBA (Weighted Euclidean Distance Based Approximation) and MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) methods are employed to evaluate alternatives.