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Rapid technological changes, intense competition of enterprises, and globalization have transformed the phenomenon of financial distress and corporate bankruptcy into a major issue in financial and investment literature. Bankruptcy attracted the attention of financial sector activists, including investors, lenders, suppliers, business partners, and governments. Considering the role of intellectual capital in organizations, one can expect that companies with a richer intellectual capital are more intelligent in avoiding bankruptcy. The purpose of this research is to investigate the role of intellectual capital and its components (including human capital, structural capital, and customer capital) on firms’ probability of bankruptcy in Tehran Stock Exchange. For this purpose, the data of 147 firms from Tehran Stock Exchange that are selected by systematic elimination method were studied during time period of 1387 to 1393. In order to measure the intellectual capital, the PULIC model applied and to assess the probability of bankruptcy, conversion of Zscore results (from Altman Model) to the probability used. Also, to test hypotheses, multivariate regression models with hybrid data have been used. The results of the hypothesis test show that intellectual capital and its components have reverse (negative) and significant effects on the firms’ probability of bankruptcy in Tehran Stock Exchange.

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One of the most fundamental economic issues for holding companies is capital allocation. Typically, investors in selecting investment alternatives follow conflicting preferences and goals simultaneously. Therefore, developing a model based on available information can help decision makers to identify the most important competitive factors and focus their attention on the improvement of performance. However, several techniques have been introduced to determine the most important components. Analytical hierarchy process (AHP), a branch of multi criteria decision making (MCDM) methods, is a powerful tool for ranking a set of elements. Nevertheless, the AHP is disable to take into account the uncertainty involved in the process of decision making. On the other hand, intuitionistic fuzzy sets (IFS) are capable of handling the vagueness and ambiguity by using the scale of the pairwise comparisons represented by the IFS. The IFS-AHP (a combination of the IFS and AHP method) can lead to more precise description of the problem under consideration since the IFS is robust in describing complexity and uncertainty. Therefore, the IFS-AHP technique has much more advantages in comparison with the conventional AHP or fuzzy AHP. To demonstrate the potential application of the proposed approach, a real case study on ranking the critical factors influencing the Investment Options in the Holding Companies is illustrated. The results show that criterion C6 (Risk) with value of 0.1451 is the most important factor in Holding Companies.