International Journal of Information Technology & Decision Making

This study presents a new KEmeny Median Indicator Ranks Accordance (KEMIRA) method for determining criteria priority and selection criteria weights in the case of two separate groups of criteria for solving multiple criteria decision making (MCDM) problem. Kemeny median method is proposed to generalize experts' opinion. Medians are calculated applying three different measure functions. Criteria weights are calculated and alternatives ranking accomplished by solving optimization problem — minimization of ranks discrepancy function calculated for two groups of criteria. A numerical example for solving specific task of elite selection from security personnel is given to illustrate the proposed method.

Multicriteria Analytical SCOring Tool (MASCOT) is a decision-support tool based on spatial analysis that can score items (points, lines, and polygons) as a function of their Euclidian distance to other data (points, lines, polygons, rasters). MASCOT is integrated with ArcGIS 9.3.1 and makes it possible to achieve a complete workflow that may include data preparation and grouping of factors by theme, weighting, scoring, post-processing and decision-making. To achieve the weighting process, the Analytic Hierarchy Process (AHP) has been integrated. MASCOT was originally developed for the demining community, with the purpose of prioritizing clearance of mine hazards as a function of their distance to a set of predefined and measurable factors. We show here an example based on mine action data, but MASCOT is not limited to this community and many other application fields will benefit from it.

For multiple criteria decision problems, screening is a helpful process for reducing a larger set of alternatives to a smaller one containing the best alternatives so that decision makers (DMs) can concentrate on evaluating alternatives within a smaller set. This study proposes a graphical approach based on the extended case-based distance method to assist individual as well as group DMs in screening and observing the case distances between alternatives and selected cases. Benchmark cases can thus be examined. The screening results of all DMs and the collective group decisions can be simultaneously observed on the same plane. An individual DM can also examine his/her own screening results and those of the group to identify the differences between individual judgments and the group's collective opinions. An interactive screening procedure for group decisions is represented to provide flexibility so that DMs can check and adjust their preferences iteratively.

With the rapid development of the Internet, the online shopping market expands constantly. Inspired by fierce competition and complex and diverse consumer demand, personalized recommendation has become an effective marketing tool for e-commerce enterprises. However, the existing recommendation methods based on online consumer behavior or preferences are characterized by poor accuracy and low efficiency. The paper mainly conducts three studies, the study1 proves that seven online lifestyles, which are "Comfortable, Entertainment, Luxury, Tradition & Conservation, Rational, Fashion Sense, and Social Activities", affect Chinese consumers' purchase. However, the different online lifestyles have different effects on purchase, thus the response rates of recommending. The study2 proposes a new personalized recommendation method "online lifestyle tagging (OLT)" based on online lifestyle and user behavior tags to identify online lifestyles. In the study3, the efficiency of OLT is tested and verified using data collected from enterprises, it suggests that OLT has a significantly higher response rate than traditional behavior-based methods. This study demonstrates that OLT improves the accuracy and efficiency of personalized recommendation, and thus contributes to the theory of personalized recommendation and marketing methods based on lifestyle.

In pricing for European option Black–Scholes model has been widely used in various fields in which the model can be applied under appropriate conditions. In this paper, we discuss a binary option, which is popular in OTC (Over the Counter) market for hedging and speculation. In particular, asset-or-nothing option is basic for any other options but gives essential implications for constructing more complex option products. In addition to the primary role of the asset-or-nothing option, another availability of the option is considered by introducing fuzzy concept. Therefore, the uncertainty which an investor and intermediary usually have in their minds is incorporated in the pricing model. Thus, the model is described with fuzzy boundary conditions and applied to the conventional binary option, proposing more useful and actual pricing way of the option. This methodology with the analysis is examined, comparing with Monte Carlo simulations.

Failure mode and effect analysis (FMEA) is one of the risk analysis techniques recommended by international quality certification systems, such as ISO 9000, ISO/TS 16949, CE, and QS9000. Most current FMEA methods use the risk priority number (RPN) value to evaluate the risk of failure. The RPN value is the mathematical product of the three parameters of a failure mode that is rated between 1 and 10 in terms of its severity (S), occurrence (O), and detection (D), respectively. However, the RPN method has been found with three main drawbacks: (1) high duplicate RPN values, (2) failure to consider the ordered weights of S, O, and D, and (3) failure to consider the direct and indirect relationships between the failure modes and causes of failure. Therefore, this paper integrates the technique for order preference by similarity to ideal solution (TOPSIS) and the decision-making trial and evaluation laboratory (DEMATEL) approach to rank the risk of failure. A case of an inlet plate ring that has been drawn from a professional mechanical factory is presented to further illustrate the proposed approach. After comparing the result that was obtained from the proposed method with the conventional RPN and DEMATEL methods, it was found that the proposed method can resolve the abovementioned RPN ranking issues and give a more appropriate risk assessment than other listed approaches to provide valuable information for the decision makers.

In fuzzy decision-making environments, intuitionistic preference relation is highly useful in depicting uncertainty and vagueness of preference information provided by the decision maker. In the process of decision making with intuitionistic preference relation, the most crucial issue is how to derive the ranking of alternatives from intuitionistic preference relation. In this article, we investigate the ranking methods of alternatives on the basis of intuitionistic preference relation from various angles, which are based on the intuitionistic fuzzy ordered weighted averaging operator, the intuitionistic fuzzy ordered weighted geometric operator, the uncertain averaging operator, the uncertain geometric operator, the uncertain ordered weighted averaging operator, and the uncertain ordered weighted geometric operator, respectively, and study their desirable properties. Moreover, we give a numerical analysis of the developed ranking methods by a practical example, and finally discuss further research directions.

Due to ever-increasing trend in outsourcing information technology projects in today's competitive world, the risk management in information technology outsourcing (ITO) projects is a challenging issue. Hence, this paper reviews and extracts present corresponding risks by literature review to implement risk management in ITO. After reviewing a number of frameworks in the literatures related to prioritizing of extracted risk factors, a new framework is presented to determine the priority of them. Because of network structure of the proposed framework and multi-dimensional nature of the project risk, the fuzzy analytic network process (fuzzy ANP) is applied to prioritize risk factors. Also, since identifying and prioritizing of risk factors cannot necessarily meet the organization's needs related to the project risk, the ways to respond to these factors are evaluated. For this purpose, responses to the five highest ranked risk factors are considered. Prioritization of responses to these risk factors is done by applying fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) based on four criteria: quality, cost, time, and scope. Results, achieved from experts' judgment, show that the risk factor "Supplier's lack of expertise with an IT operation" is the most significant. Also, the best response for this factor, is "Review of monetary value and volume of suppliers' contracts prior to their selection" according to experts' point of view. In addition, a sensitivity analysis is carried out for validating the results.

The purpose of this paper is to develop an inclusion-based LINMAP (i.e., Linear Programming Technique for Multidimensional Analysis of Preference) method for multiple criteria decision analysis that is based on interval-valued Atanassov's intuitionistic fuzzy sets. Using the inclusion comparison possibility in the interval-valued Atanassov's intuitionistic fuzzy context, an inclusion-based index of interval-valued Atanassov's intuitionistic fuzzy numbers is proposed that considers positive and negative ideals. An inclusion-based consistency index and an inclusion-based inconsistency index to measure the concordance and discordance, respectively, between paired comparison judgments are suggested. An inclusion-based LINMAP model is constructed using a linear programming technique to determine the optimal criterion weights and obtain the corresponding comprehensive inclusion-based index for each alternative. Then, the priority order of the alternatives can be acquired according to the comprehensive inclusion-based indices. The feasibility of the proposed method is illustrated using a practical problem that relates to the selection of bridge construction methods. A comparative analysis of other relevant decision-making methods is conducted to validate the effectiveness of the developed methodology.