This paper investigates credit allocation policy making and its effect on economic development using bi-level programming. There are two challenging problems in bi-level credit allocation; at the first level government/public related institutes must allocate the credit strategically concerning sustainable development to regions and industrial sectors. At the second level, there are agent banks, which should allocate the credit tactically to individual applicants based on their own profitability and risk using their credit scoring models. There is a conflict of interest between these two stakeholders but the cooperation is inevitable. In this paper, a new bi-level programming formulation of the leader-follower game in association with sustainable development theory in the first level and data mining classifier at the second level is used to mathematically model the problem. The model is applied to a national development fund (NDF) as a government related organization and one of its agent banks. A new algorithm called Bi-level Genetic fuzzy apriori Algorithm (BGFAA) is introduced to solve the bilateral model. Experimental results are presented and compared with a unilateral policy making scenario by the leader. Findings show that although the objective functions of the leader are worse in the bilateral scenario but agent banks collaboration is attracted and guaranteed.

The movement of industrial societies towards implementation of information technology has begun and it has gained moment since early 90th and presently the speed of this movement is well obvious in less developed countries, including Iran. Internet Banking is one of the most tangible trends in today’s electronic commerce. It has direct relationship with the perception of the service qualities not only because of unique absorption of the internet, but also because of e-commerce, acceptance of internet services of banks by clients and the tendency for using such services. This paper investigates different factors influencing on acceptance of electronic banking in private banks versus public banks in a case study of two Iranian banks namely; Eqtesade Novin and Sepah using Technology Acceptance Model (TAM). Correlation test reveals that there was a positive and significant relationship between clients of private and public bank on five factors associated with TAM. In addition, structural equation method was used for investigation of relationships in offered model. In conclusion, all primary and secondary hypotheses for clients of private and public bank were confirmed.

Cash flow ratios help financial users get relevant information about financial resources for a given time. Cash flow ratios are now used more than the traditional ones because it is more effective and justified. Cash flow based ratios are especially surprising because they do not only play a significant role in the credit rating of evaluation, but also forecast the failure of a corporation. In this study, we perform an empirical investigation on a company named CMC. From the study, it is clear that the liquidity and solvency positions of the company were moderate whereas the company maintained low profitability. On the other hand, the efficiency and sufficiency ratios of the study give us a new look on financial judgement.

In precision manufacturing, especially in making of holes on the parts during drilling process for precision assembling of parts facing problems with burr formation. Drilling is one of the finishing operations in the production cycle, removal of burrs during drilling process is a time consuming and non-value added process to the manufacturing sector. In this paper, we developed an analytical models for thrust force, torque and burr size with variable clearance angle of drill bit geometry especially for Aluminium alloys used for automotive applications. An analytical model results were obtained by writing a code in MATLAB @ 2010 software for aluminium alloy series such as Al 6061, Al 2014 and Al 7075. In an economic front, de-veloped mathematical models are benefitted to reduce experimentation, these results reveal that at the beginning of the drilled hole due to indentation of chisel edge, more thrust and torque was identified, beyond that suddenly thrust force was lowered, cutting forces by the lip edges were increased from beginning of the process to progress of drilling process. The proposed model approach is helpful to the budding entrepreneurs in the related areas to select optimal combination of drilling parameters to attain multiple performance characteristics of responses especially in burr size to prevent the post finishing operations up to certain extent.

Cash flow models are one of the spotlights for evaluating a project. The actual data should be modeled then it could be used for the prediction process. In this paper, 996 airplane maintenance basis data are used as a database, and 119 similar data are chosen after clustering. The project is divided into 20 equal periods and first three periods are used for simulating the next point. The predicted data for each point is achieved by using of previous points from the beginning. The model is based on artificial neural network, and it is trained by three algorithms which are Genet-ic Algorithm (GA), Estimation of Distribution Algorithm (EDA), and hybrid GA-EDA method. Two dynamic ratios are used which are dividing the population into two halves, and the other is a ratio without dividing. The ratio would give a proportion to GA and EDA models in the hybrid algorithm, and then the hybrid algorithm could model the system more accurately. For each algorithm, three main errors are calculated which are mean absolute percentage error (MAPE), mean square error (MSE), and root means square error (RMSE). The best result is achieved for hybrid GA-EDA model without dividing the population and the MAPE, RMSE, and MSE values are %0.022, 28944.59 Dollars, and 837789503.79 Dollars, respectively.

Decision support system (DSS) normally consists of a set of related computer programs and the data required to help with analysis and decision-making within an organization. Many software vendors claim their decision support, analytics or business intelligence applications may provide a competitive advantage by providing different facilities such as business intelligence tools, business performance management software, data mining tools, etc. This paper presents an empirical investigation to determine different DSS factors influencing on development of export activities on selected firms which are active in Tehran Stock Exchange. The study designs a questionnaire consists of 35 questions and distributes it among 211 randomly selected managers who were involved in export activities. Cronbach alpha has been calculated as 0.817, which is well above the minimum desirable level. Using principle component analysis, the study has detected five factors including internal resources, management approach, quality of data, efficiency of data and organizational approach, which influence the most on export activities.

Investment decisions are normally accomplished based on fundamental or technical methods. However, there are many cases where investors make their investment decisions based on their emotions. This study investigates the effects of various factors including biases representation, mental accounting and risk aversion when an investment decision is executed. In other words, the study examines the effects of emotional intelligence components on retail investors’ investment strategies on Tehran Stock Exchange (TSE). The proposed study selects a sample of 270 investors who had some experiences on TSE randomly and using a questionnaire based survey detected that there was a positive and meaningful relationship between emotional intelligence and investment decisions.

Free trade zones are important regions for development of business activities and detecting important factors for development of these regions plays essential role for development of economy. This paper presents an empirical investigation to determine the factors influencing the performance of the incentive polities of free trade zones in Iran. The study designs a questionnaire consists of 34 questions. Cronbach alpha is equal to 0.809, which is well above the minimum acceptable level. In addition, Bartlett & apos; s Test of Sphericity yields a Chi-Square value of 2392.31 with Sig. = 0.000. Using principal component analysis with rotation, the study has detected six important factors influencing on development of free trade zones including government support, financial capability, development strategy, product competition, infrastructure and consultation services.

This paper presents an empirical investigation to construct, to validate and to determine normalization factors associated with adolescents depression scale. The study is performed among 750 randomly selected guided and high school students, 364 male and 386 female, who live in city of Zanjan, Iran. Validity of Beck Depression Inventory (BDI), Validity of Simpson-Angus Scale (SAS) and divergence validity of the Coopersmith self- esteem coefficients are 0.72, 0.37 and -0.71, respectively. Result suggests that adolescents’ depression test is a reliable and valid tool for assessing depression, with utility in both research and clinical settings, counseling centers. In addition, the results of correlation test indicate there are some meaningful differences between depression levels of female and male students. In fact, our survey indicates that female students have more depression than male students do (F-value = 33.06, Sig. = 0.000). In addition, there are some meaningful differences between depression levels in various educational levels (F-value = 8.59, Sig. = 0.000). However, the study does not find sufficient evidence to believe there is any meaningful correlation between educational backgrounds and gender.

The designers often face the problem of choosing the best fitted material for a specific application from a huge array of available alternatives while simultaneously fulfilling all the given design requirements. For dealing with the material selection problems, a systematic and efficient approach is thus necessary. Selection of an optimal material from among various alternatives based on different conflicting subjective as well as objective attributes can be defined as a typical multi-criteria decision-making (MCDM) problem. The material selection problems for diverse engineering applications have already been solved by the past researchers employing different MCDM approaches. In this paper, the feasibility of Q-analysis technique as an MCDM tool is explored for arriving at the most appropriate decision regarding materials selection. Its applicability is demonstrated with the help of four illustrative examples and its capability to provide almost accurate material selection decisions is also validated.