Parviz Ahmadi; Seyed Hamid KhodadadHosseini; Asadollah Kordnaiej; Nabiollah Elyasi
Volume 21, Issue 1 , May 2017, , Pages 1-28
Abstract
Reviews have revealed that commercialization of science and technology in humanities has not had proper growth despite close relationship between economic development and development of financial sector. Therefore; lack of literature on commercialization in services point this study toward identifying ...
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Reviews have revealed that commercialization of science and technology in humanities has not had proper growth despite close relationship between economic development and development of financial sector. Therefore; lack of literature on commercialization in services point this study toward identifying commercialization processes of financial services. Research methodology in this study was qualitative and by using Triangulation. To identify basic concepts and commercialization phases, library research and semi-structured interviews with academic experts and industry specialists were used. Moreover, semi-structured questionnaires with an open-ended item were employed to sort the phases and extract the commercialization model. To analyze data at the first and the second phases; a combination of structural analysis and interpretation as well as the Interpretive Structural Modeling (ISM) were applied, respectively. Findings at the first phase included twelve steps: business strategies formulation, service ideas generation, screening, business analysis, project authorization, multi-tasking team formation, design of services and processes, design of service delivery system, sales and customer network training and empowering, pilot launch, full-scale launch, and service performance evaluation and improvement. The second phase also contained the prescription of the commercialization process model of innovative financial services in financial markets.
Parviz Ahmadi; mohamadreza amini; adel Azar
Volume 17, Issue 4 , January 2014, , Pages 65-95
Abstract
The necessity of restructuring university budgeting from program-based to performance-based budgeting (PBB) leads many studies to be conducted. Reviewing the literature, we observed that there is no mathematical model including Dual PBB Structure in University. The purpose of this paper is to construct ...
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The necessity of restructuring university budgeting from program-based to performance-based budgeting (PBB) leads many studies to be conducted. Reviewing the literature, we observed that there is no mathematical model including Dual PBB Structure in University. The purpose of this paper is to construct a PBB model for university so that the budget is allocated not only to plans based on their priorities, but also to faculties based on approved student per Capita by the Ministry of Sciences, Researches and Technology. Considering the various criteria in the university system and because of fuzzy and stochastic uncertainties in the problem parameters, two scenarios were analyzed. 1) Crisp Lower Bound Robust Fuzzy PBB (CLB-RFPPB) model 2) Fuzzy Lower Bound Robust Fuzzy PBB (FLB-RFPPB) model. A significant point in Both of them, is to use performance Indicators--calculated based on data envelopment analysis approach (DEA) regarding a basic model of input-oriented CCR— determined the importance coefficient for each educational groups in order to allocateing budget. In addition, the weights of Goals and the priority of each plan were determined using some paired comparison questionnaires completed by experts. The PBBGP model has 5 goals, 1142 constraints and 994 decision variables. The results of models solution- that are presented on two macro and Operational Levels- and simulation of Crisp and two RFPBB models, Demonstrate high level capabilities of RFPBB models in response to the uncertainty in the parameters of problem and also managing the level of decision risk
Parviz Ahmadi; Yasanallah Pourashraf
Volume 11, Issue 3 , October 2007, , Pages 29-58
Abstract
Customer statisfaction has received considerable attention in the marketing litrature and practice in the recent years. It affects several desirable outcomes like customer loyalty, word of mouth, promotion and purchase. Since such an increasing attention is given to customer satisfaction as a corporate ...
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Customer statisfaction has received considerable attention in the marketing litrature and practice in the recent years. It affects several desirable outcomes like customer loyalty, word of mouth, promotion and purchase. Since such an increasing attention is given to customer satisfaction as a corporate goal in addition to traditional financial measures of success, customer satisfaction must be translated into a number of measurable parameters directly linked to people,s job, i.e. the factors that people can understand and influence. This paper presents a customer statisfaction survey in commercial banks. A customer,s path to statisfaction model would display justice, perceived organizational support, similarity, liking, prior experiences, feedback and statisfaction as highly related.
Adel Azar; Amir Afsar; Parviz Ahmadi
Volume 10, Issue 4 , March 2007, , Pages 1-16
Abstract
Today, stock investment has become an important mean of national finance. Apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. In the past, long-term trading processes and many technical ...
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Today, stock investment has become an important mean of national finance. Apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. In the past, long-term trading processes and many technical analysis methods for stock market were put forward. However, stock market is a nonlinear system, due to the political, economical and psychological impact factors. Thus, it is difficult for us to use traditional analysis tools to make stock transaction decision. With the developmenting of nonlinear methods such as neural networks and fuzzy neural networks, we can now use these methods for stock price forecasting.
In this research, we presented three scenarios: 1) stock price forecasting with classical methods approach, 2) stock price forecasting with artificial intelligence methods approach, and 3) stock price forecasting with hybrid model. Therefore, first, we designed classical models such as exponential smoothing, trend analysis, and ARIMA, then artificial intelligent models such as neural networks and fuzzy neural networks were designed, next the third scenario i.e., hybrid model, was presented. Finally, the scenarios were measured. The experimental result showed that the hybrid model had more accuracy than the classical or artificial intelligent models.
The hybrid model enjoyed also such properties as fast convergence, high precision and strong function approximation ability, there fore, it is suitable for real stock price forecasting.
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Volume 5, Issue 1 , August 2001
