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In the post-recession period, the business environment in developing countries is still relatively undesirable. Based on the reports published, the number of closed entrepreneurs are significantly more than the number of those newly established. These statistics also reflect that the development of entrepreneurship faces several challenges. However, a strategic management program must be accurately conducted to effectively control entrepreneurial challenges based on the limitation of time and financial resources. On the other hand, the program should provide an appropriate opportunity for competitiveness by producing better quality goods and services successfully marketed to consumers. The aim of this paper is to propose a robust model with a high potential for evaluation of entrepreneurial challenges in order to identify and control the most critical ones. To achieve the aim, the most critical parameters should be identified to prevent wasting the resources. Likewise, the analytical network process (ANP) method, a branch of multi-criteria decision making (MCDM) techniques, is a powerful tool that can consider all interrelationships and interdependencies between criteria. On the other hand, neutrosophic sets are among the most widespread approaches in coping with vagueness and unknown environment. The methodology employed in this paper uses a combination model based on ANP and neutrosophic sets using sustainable development indicators to prioritize the challenges of entrepreneurship. The results show that the proposed model has a high potential to provide a process for decision-making under a vague environment. [ABSTRACT FROM AUTHOR]

Nanotechnology plays a significant role in construction industry. The construction industry has been employed nanomaterials to improve the performance of construction components and the safety of the structure and to reduce the energy consuming and the cost of maintenance. In other words, nanotechnology has a substantial impact on the construction industry. Therefore, it is necessary to identify and evaluate the critical factors of the application of nanotechnology in construction in order to concentrate on the most critical factors. However, several techniques have been developed to prioritize the evaluation criteria. Analytical network process (ANP) technique, a branch of multi criteria decision making (MCDM) methods, is a powerful tool to rank a limited number of criteria. This technique takes into account both tangible and intangible criteria in the process of formulation of a decision making problem. This method is capable of handling all types of independence and dependence relationships. On the other hand, intuitionistic fuzzy set (IFS) is a well-known technique in considering the inherent uncertainty involved in the process of modelling a decision making problem. In this paper, a new model based on the IFS and ANP technique is proposed to evaluate the critical factors of the application of nanotechnology in the construction industry. The results demonstrate that the proposed model has a high potential for taking into account the uncertainty in the form of a three dimension function, including membership, non-membership, and non-determinacy. [ABSTRACT FROM AUTHOR]

The problem of handling equipment selection plays a significant role in the total cost of a mining project; so that it can affect the activity and continuity of the project and is a strategic problem. In this study, an integrated model based on two fuzzy multi-criteria decision making techniques for handling equipment selection is proposed. The proposed evaluation model is derived from group decision making, fuzzy set theory, analytical hierarchy process (AHP), and Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The fuzzy AHP (FAHP) method is utilized to calculate the relative importance of the evaluation criteria, then, fuzzy TOPSIS (FTOPSIS) is applied for evaluating the feasible handling equipment in order to select the best handling system among a pool of the possible alternatives. The model is applied for a real world case study to demonstrate the capability and effectiveness of the proposed model. To investigate the result sensitiveness to the changes of the criteria weights, a sensitivity analysis is finally conducted. [ABSTRACT FROM AUTHOR]

Brand extension is one of the most popular strategies in marketing. This is due to the fact that consumers usually take into account the brand first because it indirectly reflects the design, quality, and functions. According to the significant role of brand in creating benefit and diminishing risk for a new product, this study intended to develop a novel model for selecting the most appropriate strategy in brand extension. However, there are a number of criteria influencing the possible strategies, and they often are interdependent. Therefore, a multi-criteria decision making model based on Analytic Network Process and Additive Ratio Assessment methods has been developed to systematically clarify the interdependent relationships among the evaluation criteria of brand extension and then, scientifically evaluate the feasible strategies and rank the priorities of brand extension strategies. The results of the proposed model show that “Production cost” is the most important factor, followed by “Quality of parent brand” and “Perceived risk” while “Ice cream” is the highest satisfaction of brand extension. [ABSTRACT FROM PUBLISHER]

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives. [ABSTRACT FROM PUBLISHER]

Selection of the working strategy is a critical problem and it plays a significant role in the success of organization development. On the other hand, selecting the most appropriate working strategy among a pool of alternatives is a multi-criteria decision making (MCDM) problem. Since every working strategy has its benefits and costs and may bring a company different opportunities and risks, which kind of working strategy is the most appropriate for a company to accomplish is a sophisticated and complex decision with a high degree of uncertainty. Therefore, the current paper proposed an integrated evaluation model based on the analytic network process (ANP) and the complex proportional assessment (COPRAS), to help the decision makers or managers with the selection of proper working strategy in a fuzzy environment where the fuzziness and uncertainties are handled with linguistic terms parameterized by triangular fuzzy numbers (TFNs). In this paper fuzzy ANP (FANP) is utilized to take into account interdependence and dependencies and determine the importance weights of benefit, opportunities, cost and risk (BOCR) factors, and fuzzy COPRAS is applied to rank the alternatives. To show the potential application of the proposed model, a real world application is conducted to illustrate the use of the proposed model for the working strategy selection problem. The results show the capability and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Asset management, as a systematic process of operating, maintaining, and upgrading physical assets, is an important element of decision-making in heavy equipment management and operation. Maintenance strategy selection plays a significant role in mining design. However, the nature of maintenance strategy selection is a complex multi-criteria decision making (MCDM) problem including both tangible and intangible parameters which are often in conflicting with each other. As well as when decision makers are uncertain in determining and defining the ratings and the weights of alternatives and criteria respectively, fuzzy theory provides an appropriate tool to handle the existing uncertainties. In this paper, a new fuzzy MCDM method based on the concepts of COPRAS (COmplex PRoportional ASsessment) and AHP (Analytical Hierarchy Process) was proposed to evaluate the feasible maintenance strategy. The linguistic terms are employed to assess the ratings and weights. Fuzzy AHP is utilized to calculate the weights of the evaluation criteria; then, the rankings of alternatives are computed based on fuzzy sets theory and COPRAS. A real world case study is presented to illustrate a potential application of the proposed model. [ABSTRACT FROM AUTHOR]