Modern Research in Decision Making

Abstract Today, the dynamic and competitive business environment has made human resource development (HRD) a part of the strategic human resource management programs, and managers try to improve the competitiveness of the organization by developing employees. Therefore, the present study was conducted with the aim of formulating and prioritizing HRD strategies. This study is applied in terms of purpose, descriptive survey in nature, and mixed in terms of research method. In its qualitative phase, HRD strategies were formulated based on the SWOT matrix through in-depth interviews, and the indicators effective in prioritizing these strategies were determined. In the quantitative phase, the intensity of the effect and weight of the indicators were determined using the Fuzzy DANP technique, and the strategies were ranked using the Fuzzy GTMA technique. The statistical population of the study was managers and experts in the field of human resources of an insurance company, and sampling was carried out in a purposeful manner. The results of the research showed that the most important indicators affecting the selection of HRD strategies are: "the level of willingness, cooperation, and participation of employees in implementation", and "the amount of budget required". Also, based on the results of the fuzzy GTMA technique, the strategies of "generalizing in-service training to all levels of the organization", "strengthening the connection between HRD programs and the performance evaluation and promotion system of employees" and "strengthening creative and innovative thinking in employees and reducing their resistance to change" have a higher priority in this organization.

Abstract The production and circulation counterfeit drugs in the drug supply chain, especially in the field public health, is serious and vital challenge. Existing management systems in the supply chain are not able to guarantee the supply essential drugs patients. In order improve credibility medicines and reduce the problems the supply chain, it is suggested use the approach based blockchain technology. this research examines the performance the drug supply chain using blockchain technology ensure safety public health. Dynamic system method is used for implementation. The successful implementation blockchain technology requires a deeper understanding the complex dynamics the interaction system between its various components. The dynamic system approach can help analyze these complexities and identify the long-term effects changes in the supply chain. For this purpose, first, the desired data from the literature and interviews drug industry experts were collected, then modeling was done by defining variables, designing feedback loops and writing related mathematical equations. cause and effect diagrams were created as well as flow accumulation and simulation was performed period one year. The results the research show that among investigated indicators, the indicator increasing the detection rate and preventing fraud is particularly important because public health is directly affected by it. Other indicators, in order importance, include the balancing rate the pricing process, smart contracts, identity Digital coordination helps improve performance and strengthen trust in industry. In general, these indicators are used as a set of blockchain tools to improve transparency, security, efficiency and reduce fraud in the drug supply chain.

Abstract According to previous research, financial ratios have a high ability to predict the financial crisis of companies, but recently, research based on market variables and economic variables have attracted the attention of financial researchers. This research was first formed by examining the theory of asymmetry of financial information and since the stakeholders usually do not know the real financial conditions of the company before the occurrence of financial problems, it has predicted the financial crisis. The aim of this research is to be able to provide a more accurate model by using accounting variables, macroeconomic and market variables, so that stakeholders can make more confident decisions by relying on the predictive power of these models. In this research, using the data of 30 pharmaceutical companies admitted to the Tehran Stock Exchange in the period of 1397 to 1400, Based on the research results, the neural network model with selected variables of debt ratio, asset return, stock price, company size, consumer price index and GDP growth has the ability to predict the financial crisis. To predict the financial crisis of companies, it is possible to use the combination of accounting variables, macroeconomics and market variables, and also all the selected variables in the research affect the financial crisis.

Abstract Drug recycling is one of the issues that have recently been considered from various dimensions such as reducing environmental impacts, providing essential drugs, and developing a circular economy. In this regard, collecting the surplus drugs of citizens has become more important with the aim of recycling essential ones needed by patients and managing hazardous pharmaceutical wastes through reverse logistics. On the other hand, with reverse logistics management becoming more specialized, in order to focus more on their main activities and save costs, organizations are looking to hand over all or part of their activities to Third-Party Reverse Logistics Providers (3PRLP) and as a result, it has become a vital need for 3PRLPs to choose the appropriate operations strategy. In this research, with the aim of government-centered drug recycling management, the purchase and collection of citizens' surplus drugs has been assigned to 3PRLPs. Considering the three main beneficiaries, including the government, society and drug sellers and the goals of each, we have used the potential of the three tools of blockchain, cold chain logistics and cooperation among 3PRLPs to meet these goals and expectations, and have proposed an appropriate operations strategy for 3PRLPs. Based on the mathematical modeling of the research and the obtained objective function of 3PRLPs through the revenues received from the sale of the purchased drugs to the government, numerical results show that collaborative planning is better than non-cooperation, and on the other hand, the definition of the "drug essentiality" parameter will affect the final profit of 3PRLPs.

Abstract One of the fundamental challenges in Iran's banking system is the conflict of interest, which plays a critical role in public trust. This issue points to situations where individual personal interests are at odds with their duties and responsibilities. Without addressing the actors involved in conflicts of interest, achieving and controlling these conflicts cannot be assured. Therefore, this study employs content analysis, interviews with experts, and the identification of their desires and actions. Through the application of game theory and graph models, the equilibrium status among stakeholders such as banks, customers and borrowers, legislators and regulatory bodies, investors and market analysts, and consumer rights organizations has been identified. The equilibrium state among the actors was determined through interviews regarding their preferences and with the help of evolutionary path analysis, tracing the actors' movements from the current state to the equilibrium state. The study found that this equilibrium does not represent an ideal state for the community and policymakers, indicating a need for a shift in stakeholders' preferences. Through backward game analysis, it has been determined that legislators and regulatory bodies should strengthen oversight and transparency, and consumer rights organizations should initiate awareness campaigns and collaborate with lawmakers and supervisory bodies to enhance protective regulations, aiming to achieve an optimal state for the national economy. This research can assist the Islamic Consultative Assembly in developing more effective legislative strategies through a better understanding of the interactions between stakeholders.

Abstract In the fields of marketing, finance and economics, finding the factors that lead to the purchase decision is very important. In the decision-making process of individual investors in the capital market, various factors affect the desire and intention to buy stocks. The aim of the research was identify the main factors (categories) and sub-factors (components) and rank the factors affecting the desire to buy stocks by individual investors in the stock market. In the first stage, based on the qualitative research method and thematic analysis with the help of AtlasTI software, the factors affecting investors that create the intention to buy were identified. In the quantitative stage, using a survey strategy, the questionnaire required to assess the generalizability of the model was developed and distributed to the statistical population of the research and the analysis was carried out among 509 individual stock buyers in the Tehran stock market. In order to estimate the model, the structural equation modeling method and SPSS and AMOS software were used. According to the research results, 9 category groups were identified. Many components in the marketing factor subgroups (goods and services, brand and advertising) were introduced for the first time. Then, the factors ranked by Friedman's ranking test, The results indicated that the stock price trend, news and events, experiences, parallel market profitability and rumors were the 5 factors with the highest influential role.