مطالب

The aim of the current research is to identify the futures of marketing in the banking industry with a focus on blockchain technology. The current research is applied in terms of direction and has a mixed methodology due to the use of qualitative and quantitative methods together. The theoretical population of the research was experts in banking marketing and digital financial technologies, especially blockchain, and the sampling method was done in a judgmental method. The sample size in this study was equal to 15 people. For data analysis, meta synthesis methods, Binominal's statistical test, developed Copras and root definitions tool were used. The tools of data collection in this research were interviews and questionnaires (expert evaluation and priority evaluation questionnaires). 47 drivers were extracted from meta synthesis and these drivers were classified into nine main drivers. The drivers of the research were screened in two stages using theory-based inference screening and Binominal's test, and 12 drivers were considered for prioritization using the Copras technique. The remaining drivers were evaluated using the Copras technique and three criteria of importance, degree of certainty and experts' expertise. The findings showed that the drivers of marketing researchers' interest in digital financial technologies and blockchain and the development of decentralized banking had the highest priority and were selected for scenario planning. Based on these two drivers, four scenarios of crypto bank, conservative banking, pioneer banking and traditional banking were developed. The research proposals were proposed based on the important drivers and the desired scenario (crypto bank).

This study examines trading strategies based on trading systems by analyzing the performance of 11 technical indicators. The data used for analysis were financial data of all firms listed on the Teh-ran Stock Exchange in the period from 2010 to 2020. Excluding the firms whose data were not available for the period under study, 135 firms were selected as the research sample. The results showed that the signals containing three indicators of moving average, exponential moving average, and relative strength over a weekly up to six-month period to buy or sell stocks (as a strategy) could be used more confidently compared to other indicators to achieve higher returns and profitability. As a result, investors can use the signals that these three indicators in weekly (EMA) and monthly (MA, RSI) periods and the quarterly (MA) and six-month (RSI, EMA) periods to determine buying and selling strategies with the lowest investment risks. It is also recommended that investors use a combination of these three indicators to invest, and extend their investment period over a longer period of time to bear less risk, and more returns.

Qualitative information security risk assessments are somewhat subjective and the high degree of subjectivity associated with the perception of risk means that management is often skeptical of risk analysis results, and is unwilling to make important decisions based on that. Besides, the process of information security risk assessment is quite complex and rife with uncertainty and without taken into account the uncertainty of information security risk assessment the results can be misleading. Therefore, in this paper, the Fuzzy Multi Criteria Group Decision Making (FMCGDM) model is proposed to address the above-mentioned problems. The focus group method used to identify risk parameters and the Delphi method is used to construct a hierarchy for risk parameters. The findings of this research would be useful for the information security department to become more capable in analyzing the InfoSec risks and reducing the consequences of subjective assessment. A case study involving an actual information security risk management project was presented to illustrate the use of the proposed model. Computational results demonstrated the efficiency and effectiveness of the presented model that can assist InfoSec risk analyst to better evaluate InfoSec risk.

The core goal of this study was to simulate the share and predict the current and non-current receivables in Shahr Bank using an agent-based approach. To this end, we employed the data related to the examined features in 11 bank branches aimed at determining the degree of importance of each of the factors affecting the repayment behavior of borrowers using the C5.0 algorithm, the decision tree method, and the simulation process in NetLogo software. We utilized the comparison of the repayment status of a sample of 100 customers over the past year (12 months ago) and at present aimed at assessing the simulated model. The estimation results of the simulation model, as well as the real findings, suggested that the number of type 1 customers (with active repayment status) has decreased during the last 12 months and the number of type 2 customers (with past due repayment status) has enhanced. If the economic recession conditions continue the same way, and considering the low effect of the recession conditions on the businesses of the bank''s customers in the next four years, then, the ratio of the bank''s current customers will decrease from about 89% to about 81%, while the ratio of the past-due customers of the bank will increase to more than double to about 13%. In the next step, we tried to simulate the future situation of the ratio and the share of the current bank customers'' claims in the next 4 years.

Organizational anomie (OA) is defined as the lack of law, as well as violations or weaknesses in the implementation of laws and norms in the organization, which can have detrimental effects on the performance of the organization and its members. The main focus of this study is to establish and validate an organizational anomie scale that can be employed to implement and operate this tool in field studies. The present research is applied-exploratory in terms of purpose and descriptive-survey in terms of method. To conduct this research, issues related to organizational anomie using factor analysis approach and content analysis method of scientific texts as well as from the perspective of qualified and experienced thinkers and experts and a researcher-made questionnaire on organizational anomie in COVID-19 pandemic are analyzed. it placed. Completed by experts and managers. The reliability coefficient of the test was calculated to be 0.85 using Cronbach's alpha test. Exploratory factor analysis of organizational questions revealed that the components of this questionnaire may explain more than 78.512 % of the desired variance. After one rotation of Varimax factors, the correlation between each item with each component was determined in the best situation and accordingly, twelve components were selected and extracted with the most weight: conflicting goals of the individual and organization, weakness in communication, standard selection ,ambiguity in goals, level of trustworthiness, negative attitude of employees towards themselves, feeling useless, understanding justice, weak control, common norms, organizational indifference, lack of socialization. According to the research findings, it can be concluded that organizational anomie is a multidimensional concept with many dimensions and components and cannot be studied with limited dimensions and components.