In the knowledge economy, human capital is a key factor in any organization to achieve a sustainable competitive advantage. Thus, selection of competent personnel is the most important function of human resource managers. However, because of a wide range of criteria and organizational factors that affect the process, personnel selection is often regarded as a complex problem that can be answered through multicriteria decision-making (MCDM) procedures. Despite the great importance of determining a comprehensive set of criteria, it has not gained enough attention in the literature. This study presents a competency framework with five criteria for choosing the best information technology (IT) expert from five alternatives. The stepwise weight assessment ratio analysis (SWARA) and grey additive ratio assessment (ARAS-G) methods are also used to derive the criteria weights and provide the final alternative, respectively. The results reveal that subject competency is the major criteria in IT personnel selection.
The construction industry is considered as one of the most dangerous industries in terms of occupational safety and has a high rate of occupational incidents and risks compared to other industries. Given the importance of identifying and assessing the occupational hazards in this industry, researchers have conducted numerous studies using statistical methods, multi-criteria decision-making methods, expert-based judgments, and so on. Although, these researchers have used linguistic variables, fuzzy sets and interval-valued intuitionistic fuzzy sets to overcome challenges such as uncertainty and ambiguity in the risk assessment conducted by experts; the previous models lack in efficiency if the experts are hesitant in their assessment. This leads to the inability to assign a specific membership degree to any risk. Therefore, in this research, it is tried to provide an improved approach to the Failure Mode and Effects Analysis (FMEA) method using an Multi-Criteria Decision-Making (MCDM) method based on the hesitant fuzzy set, which can effectively cope with the hesitance of the experts in the evaluation. Also, Stepwise Weight Assessment Ratio Analysis (SWARA) method is applied for risk factor weighing in the proposed approach. This model is applied to a construction industry case study to solve a realistic occupational risk assessment. Moreover, a comparison is made between the results of this model and those obtained by the conventional FMEA and some other aggregation operators. The results indicate that the newly developed approach is useful and flexible to address complex FMEA problems and can generate logical and reliable priority rankings for failure modes.
The financial performance is an indicator of financial stability, health and condition of any organisation. It could be utilised as a proper measure of the firm's credibility and its ability to pay off debts. Financial institutions use this measure to determine the lending policy and applicants' credits. This study proposes a model based on the CCSD weighing method and hybrid FCM-ARAS approach for clustering and evaluating the financial performance to enable banks to identify target groups and design appropriate and relevant policies. Based on previous studies and the views of senior financial managers of a public bank in Iran, eight economic criteria were evaluated. The presented method was used to assess the financial performance of 58 manufacturing companies applying for loans from a federal bank in Iran. However, the CCSD method was used to calculate criteria weights, and a hybrid FCM-ARAS approach was developed and applied to financial evaluation and clustering the companies. The use of the CCSD method can eliminate errors caused by subjective models and human judgments, and increase the accuracy of the assessment. In this study, the debt ratio and equity to total assets and ROA were identified as the main criteria to assess financial performance.
Given the high costs of construction and maintenance, an optimum design methodology is one of the most important steps towards the development of transportation infrastructure, especially freeways. However, the effects of different variables on the decision-making process to find an optimal variant have caused the choice to become a very difficult and professional task for decision makers. So, the current paper aims to determine the optimal variant route for Isfahan-Shiraz freeway through MADM approaches. First, evaluation indices for an optimal route variant are derived through literature review and expert panel assessment. Then, a dynamic fuzzy GRA method is used for weightings and optimal route selection. Bases on the results, the road longevity, views of NGOs and route integration are identified as the highest-weighted criteria in route variant prioritization. Further, Route 3 is defined as the priority for the optimal variant for Isfahan-Shiraz freeway, which is the main basis in practice.
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