Banking sector

The purpose of this paper is to examine the asymmetric effects of banking sector and stock market development on economic growth in Iran. For this purpose, Smooth Transition Regression (STR) model used based on seasonal time series data during 1989-2017. The results indicate that the impact of financial and banking development indices on economic growth is different for economic growth rates above and below 6%. Therefore, if the economic growth rate is higher than 6%, then we have a regression and when economic growth is lower than 6% will have another regression in order to effect of financial development of economic growth. In addition, results show that that the relationship between private sector credit and economic growth is much stronger than the relationship between stock market and economic growth.

This article investigates the financial convergence between Iran, OPEC & the Shanghai Organization trade groups, of which Iran is a member.  The analysis covers the period of 2005 to 2017.In order to examine the convergence dynamics of these financial markets; we have employed the Philips and Sul (2007) methodology, which uses a nonlinear time-varying factor model. This paper provides a comprehensive picture of the financial systems within Iran and its convergence clubs by testing the convergence of their money market with domestic credit to private sector by banks (% of GDP), deposit and lending interest rate, real interest rate, and capital market with Stocks traded, total value (% of GDP). The empirical findings show that money and stock markets of OPEC and the Shanghai group do not form a homogenous convergence club. Results show that Iran has convergence with some countries in OPEC and the Shanghai group in money and stock markets, which can be explained by their similar economic indicators in both markets. Furthermore, the convergence speed between Iran and the Shanghai countries is higher than that of Iran and OPEC countries, which proves that joint trade agreements are stronger reasons for convergence than the oil factor. Iran should implement further structural reforms in order to achieve greater financial convergence with its joined groups.

Networks are useful tools for presenting the relationships between financial institutions. During the previous years, many scholars have found that using single-layer networks cannot properly characterize and explain complex systems. The purpose of this research is to introduce a multiplex network in order to analyze, as accurately as possible, all aspects of communication between banks in capital market of Iran. In this article, each bank represents a node and three layers of return, trading volume and market Cap have been presented for analyzing the idea of multiplex networks. We have used the Granger causality method to determine the direction between nodes. For understanding the topology structure of these layers, different concepts have been used. The research findings show that the value layer topology has a significant similarity with the trading volume layer. Also according to the measure of centrality it can be seen that the centrality varies in different layers.

Banks play an important role in the growth and development of any economy. A profitable banking system enhances economic stability and efficiency to mitigate the impacts of sudden macroeconomic shocks. To be more efficient and profitable, banks need to recognize the factors underpinning their performance. Accrued liabilities are one of the factors that hinder the profitability of banks. There are several methods to assess banks' profitability with their own pros and cons. Among them, data envelopment analysis (DEA) has been recommended as one of the most common approaches to evaluate different efficiencies including cost efficiency, revenue efficiency, technical efficiency, and finally profitability. The availability of prices/weights of inputs and outputs provides financial managers with significant information for evaluating efficiencies and assists them in decision-making and strategy development processes. This study mainly aims to analyze banks' profitability by considering accrued liabilities resulting from undesirable factors, for which relevant data were collected from 33 branches of a commercial bank in Gilan province, Iran based on managerial and weak disposability. The results illustrated that only three branches were graded one in three dimensions of efficiency, namely technical, cost and revenue, and profitability. Besides, it was suggested that the lack of these efficiencies was not correlated with the branches' profitability.

Background & Purpose:  The job security has a direct impact on the employee’s motivation and effectiveness. Therefore, the main purpose of this study is investigating the effect of digital skills and competencies on job security in the banking sector. Methodology:  This survey is based on data from Maskan Bank in Iran, designing on a representative sample of 361 employees. The structural equation model using PLS software used to analyze research hypotheses designed from literature review. Findings:  Our findings show that digital skills and competencies positively correlated with job security. However, the digital skills have a stronger effect than digital competencies. Among all skills, computer skills and communication competencies had the strongest relation with job security. However, our findings also show that there is not significant correlation between content creation and data security competencies with job security, which needs further investigation. Conclusion:  Even though the impact of digital skills and competencies on employability has been studied previously, the relationship between these factors and job security not been considered. Thus, this research could be useful to develop body of knowledge in human computer interaction issues and mangers better understanding of information technology effects on employee’s perceived job security in workplace.

The present research examines the benefits of implementing knowledge management (KM) principles in the Jordanian banking sector to enhance performance. The study emphasizes the significance of Artificial Intelligence (AI) and how Jordanian banks utilize it to improve the quality of customer service they provide. This study targets managers at all levels and focuses on the Jordanian banking sector as its research environment. A questionnaire is created to gather information from a random sample to achieve the research's objectives. The study involves a sample of 250 managers. Additionally, the research adopts a descriptive methodology, and SPSS is used to analyze the data. The statistical findings provide robust evidence for the importance of performance expectations, social influence, and perceived risk in influencing consumer intentions. Marketers and decision-makers within the banking industry can leverage these insights to shape their long-term strategies for effectively utilizing and maximizing AI technology in the banking sector. Furthermore, by providing policymakers and practitioners of Jordanian commercial banks with insight into the variables influencing user satisfaction, the findings will help these complex institutions operate more effectively.