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Type 2 Intuitionistic sets (IFS2) have been introduced by Atanassov (1999). They let experts assign membership and nonmembersip degrees in a wider area than it is in ordinary intuitionistic fuzzy sets. In this paper, we employ IFS2 sets for the development of IFS2 WASPAS method. WASPAS is a multicriteria method integrating simple additive weighting and weighted product methods. Single valued IFS2 sets have been used in the IFS2 WASPAS method. We illustrate the application of the proposed IFS2 WASPAS through a selection problem among communication firms.

Neutrosophic sets are an extension of intuitionistic fuzzy sets. Neutrosophic sets provided a new approach to uncertainty with their three components: Truth, Indeterminacy, and Falsity. The performance of law offices can be comparatively measured by multicriteria decision making methods. Linguistic assessments can be used in this process rather than exact numerical evaluations. In this paper, we used a neutrosophic analytic hierarchy process (AHP) for comparing the performances of law offices. The illustrative problem hierarchy includes four criteria and four alternatives are given.

Performance measurement in the service industry is a critical issue for identifying how well is the company working. In manufacturing companies, performance measurement primarily relies on capacity and the number of products produced without defects. How close is the final product to the targeted product is a tool for observing the effectiveness of production process. In the banking industry, the performance depends on revenue - cost analysis. Companies in service industry need to understand how successful their business goes; several techniques developed for measuring their performance. Most of those techniques need too many parameters to observe and prioritize for reflecting relative effects of individual criteria into the analysis. It is essential to specify each of them because more criteria mean more dimension and high accuracy. The criteria involved in law firms' performance measurement are uncertain, vague and collected at different periods. The purpose of this study is to observe longitudinal performance evaluations in law firms by using dynamic intuitionistic fuzzy sets.

Real options valuation is a financial technique for evaluating investments under conditions of uncertainty, particularly uncertainty associated with market variables such as future product demand or the future value of an asset. The real option value of the investment opportunity is what a value-maximizing firm would pay for the right to undertake the investment project with its inherent decision points. This paper proposes a fuzzy multicriteria R&D project selection methodology based on the hierarchical TOPSIS, which includes a fuzzy real options valuation model.

Since most of the companies prefer outsourcing for e-activities, the selection of e-service provider becomes a crucial issue for those companies. E-service evaluation is a complex problem in which many qualitative attributes must be considered. These kinds of attributes make the evaluation process hard and vague. Cost-benefit analyses applied to various areas are usually based on the data under certainty or risk. In case of uncertain, vague, and/or linguistic data, the fuzzy set theory can be used to handle the analysis. This paper presents the evaluation and selection process for e-service provider alternatives. Many main and sub-attributes are considered in the evaluation. The e-service providers are evaluated and prioritized using a fuzzy multi-attribute group decision-making method. This method first defines group consistency and inconsistency indices based on preferences to alternatives given by decision makers and construct a linear programming decision model based on the distance of each alternative to a fuzzy positive ideal solution which is unknown. Then the fuzzy positive ideal solution and the weights of attributes are estimated using the new decision model based on the group consistency and inconsistency indices. Finally, the distance of each alternative to the fuzzy positive ideal solution is calculated to determine the ranking order of all alternatives.

The theory of fuzzy logics founded by Zadeh in 1965 has been proven to be useful for dealing with uncertain and vague information. The grey theory that was first proposed by Deng (1982) avoids the inherent defects of conventional statistical methods and only requires a limited amount of data to estimate the behavior of unknown systems. In this paper, we use the fuzzy set theory and the grey theory to develop an efficient method to predict the cash flows of an investment. The cash flows obtained are used in present worth analysis to determine if the investment is acceptable. Illustrative examples are given.

In recognition of the importance of the ERP software selection and of the sizable risk that organizations take when they decide to buy this type of technology, this study proposed a systematic decision process for selecting a suitable ERP package. We are interested in two stages of decision-making: the identification of serious software candidates and the choice of the most appropriate ERP software package. To achieve this, we propose an integrated approach based on fuzzy logic, heuristic multi attribute utility and conjunctive methods. Finally, a case study is given to demonstrate the potential of the methodology.