Financial performance evaluation is very important in a highly competitive business environment. Accordingly, an accurate and appropriate performance evaluation is critical. Financial performance indicators reflect the competitiveness of a company and they must be carefully identified in the evaluation process. Generally, accounting measures are used for performance evaluation. However, these measures are not sufficient for performance evaluation in the today’s competitive economy. Therefore, value based measures have recently been introduced to express the company value. In this study, a hybrid approach is proposed for financial performance evaluation of automotive companies of Tehran stock exchange (TSE). For this purpose, a hierarchical financial performance evaluation model is structured based on the accounting measures and economic value measures. In this approach Fuzzy Analytic Hierarchy Process (FAHP) is applied to determine weights of criteria. Then the companies are ranked by using Fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje (in Serbian), Fuzzy Additive Ratio Assessment (ARAS-F) and Fuzzy Complex Proportional Assessment (Fuzzy COPRAS), simultaneously. Also results of three outranking methods are combined by using the mean ranks. The results represented the highest importance of economic value measures than accounting measures in financial performance evaluation of companies. Six companies were ranked applying the proposed approach.
Multi Criteria Decision Making (MCDM) is an advanced field of Operation Research; recently MCDM methods are efficient and common tools for performance evaluation in many areas such as finance and economy. The aim of this study is to show one of applications of mathematics in real word. This study with considering value based measures and accounting based measures simultaneously, provided a hybrid approach of MCDM methods in fuzzy environment for financial performance evaluation of automotive and parts manufacturing industry of Tehran stock exchange (TSE).for this purpose Fuzzy analytic hierarchy process (FAHP) is applied to determine the relative important of each criterion, then The companies are ranked according their financial performance by using fuzzy additive ratio assessment (Fuzzy ARAS) method. The finding of this study showed effective of this approach in evaluating financial performance.
In order to compete in the global environment, a manufacturing company has to keep developing new technologies. Selection of a right technology is a critical stage in a successful technology transfer process. However, technology selection is a complex multi-dimensional problem including both qualitative and quantitative factors, such as human resources, operational and financial dimensions, which may be in conflict and may also be uncertain. In addition, interdependent relationships exist among various dimensions as well as criteria of technology selection. The identified problems could be solved by combining multiple criteria decision making (MCDM) methods of different nature and fuzzy set theory. The objective of the current paper is to develop a complex approach to evaluate technologies and to rank their appropriateness for a company. A hybrid model is proposed, based on Fuzzy Analytic Network Process (FANP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). A real-life case study is presented to validate the proposed model.
Knowledge-Based Business Fuzzy Logic Incubators Centers of Iran North RegionIn today's globalized economy, companies are facing ever increasing competitive pressures. A commonly adopted strategy for remaining competitive is to commercialize Products. Commercialization activities play an important role in bringing to market new t Products is the knowledge based companies. The goal of the current Research is the show Effective factors on Commercialization of Products in Knowledge-Based Business. The sample of this study is all managers of knowledge based companies in development centers which established in the northern regions of Iran. The data are collected by questionnaire with the reliability coefficient 86% of the sample. Data analyzed by using fuzzy hypothesis testing approach. The results of this work provide
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