درخت حوزه‌های تخصصی

This paper focuses on developing models to study influential factors on the inflation rate for a panel of available countries in the World Bank data base during 2008-2012 . For this purpose , Random effect log-linear and Ordinal logistic models are used for the analysis of continuous and categorical inflation rate variables . As the original inflation rate response to variables shows an apparent right skewness , the log transformation in the linear mixed effect model seems necessery . In the ordinal logistic mixed effect model , as a new approach , the inflation rate variable is categorized based on two threshols to increase model predictibality and precision . These two models consider the potential serial correlation between annual infltion rates and categories through introducing some latent random effect parameters . The results of both models show that money growth , GDP , oil price and income levels of the available countries are significant predictors with increasing effect on the next year inflation rate category . Using the categorical inflation response variable yields some superior results where government expenditure , exchange rate and capital formation are also detected as significant determinants of ordinal inflation variable . Also , the random effect variance is highly significant in both models which shows the necessery need for consideration of the potential association of inflation variables across time . JEL Classifications: E17, E27, E31, E37, E47

Development of E-banking has modified the structure of banking business and banking performance, efficiency, risk and challenges which have also been articulately recognized based on the international best practices. E-banking brazenly expedites and streamlines financial transactions via enhancing technology and expanding the bank services in comparison with conventional banking. Accordingly, online access to the banks’ products, financial statements, payment services and even credit scoring has considerably improved bank-customer relationships in the context of lending and borrowing practice, deposit composition, investment opportunities, trade finance options as well as account management diversification. The impact of recent E-banking developments on banking is statistically tested for the banking network of Iran using Dynamic Panel Data approach. Results indicate that the ratio of ATMs and Electronic Cards to bank assets positively and significantly influence profitability ratios. Meanwhile, the ratio of online branches and Pin Pads to the banks' assets negatively and significantly affects profitability although the transaction volumes have surged for the banks under study. JEL Classification: G21, G23, G32, F34 Keywords: E-Banking, Risks, Banks' Soundness Indicators

The present study tries to investigate the existing risks in the new product development process in the core banking field. Due to its use after production, new product development with the fewest errors and risks is always the subject of discussion and investigation among the researchers of this field. This study aims to investigate the most important risks existing in the new product development. The most important issue in this regard is that the market of manufactured products is increasingly competitive and the life-cycle of products is in decline due to environmental impacts. These factors force companies to follow such a process (new product development). Many techniques have been invented and applied in order to assess and manage the existing risks in different processes. Failure modes analysis technique and its resulted effects (FMEA) are considered as one of the most effective techniques that have been used for risk assessment of new product development in this study. Also, CORPAS-G method is used for prioritizing the detected risks. The purpose of this study is to identify the risks of new product and their priority for corrective measures to reduce the probable risks. Keywords: Risk assessment, Risk management, New product development, Core banking, FMEA, COPRAS-G GEL Classification: D24, D40, D61, D81, D92