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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of System Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Soft System Methodology,Market Entry Strategies,Online Market,B2B Market
- چکیده:
- چکیده انگلیسی: The Internet is changing the transaction pattern of B2B markets. One of the major concerns of IT knowledge-based companies is how to take advantage of B2B online markets. These companies believe that the only possible strategy for entering these markets is to launch independent websites, and they are usually reluctant to enter these markets due to the requirements such as financial resources and skilled human resources. The literature showed that there were different strategies for entering these markets. This study aimed to identify the factors influencing the selection of B2B online market entry strategies in IT knowledge-based companies but given the complexity of choosing the right strategy, it is a complex and unstructured issue, with various stakeholders, both internal and external, involved. Therefore, due to this complexity and the strong role of the human factor in it, the methodology of soft systems methodology has been used. The results showed that the factors contributing to the selection of B2B online market entry strategies in IT knowledge-based companies included entry time, external beneficiaries' characteristics and needs, corporate resources, corporate control strategy, corporate IT capabilities, external beneficiaries' IT knowledge and motivation, and product.
- انتشار مقاله: 26-09-1398
- نویسندگان: Mohsen Karami,Abbas Ali Rastgar,Adel Azar,Davood Feiz,Mohammad Rahim Esfidani
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Information Technology Management
- نوع مقاله: Journal Article
- کلمات کلیدی: deep learning,Monetary Policy,Big data analytics,Now-casting
- چکیده:
- چکیده انگلیسی: The development of new technologies has confronted the entire domain of science and industry with issues of big data's scalability as well as its integration with the purpose of forecasting analytics in its life cycle. In predictive analytics, the forecast of near-future and recent past - or in other words, the now-casting - is the continuous study of real-time events and constantly updated where it considers eventuality. So, it is necessary to consider the highly data-driven technologies and to use new methods of analysis, like machine learning and visualization tools, with the ability of interaction and connection to different data resources with varieties of data regarding the type of big data aimed at reducing the risks of policy-making institution’s investment in the field of IT. The main scientific contribution of this article is presenting a new approach of policy-making for the now-casting of economic indicators in order to improve the performance of forecasting through the combination of deep nets and deep learning methods in the data and features representation. In this regard, a net under the title of P-V-L Deep: Predictive Variational Auto Encoders - Long Short-term Memory Deep Neural Network was designed in which the architecture of variational auto-encoder was used for unsupervised learning, data representation, and data reconstruction; moreover, long short-term memory was adopted in order to evaluate now-casting performance of deep nets in time-series of macro-econometric variations. Represented and reconstructed data in the generative network of variational auto-encoder to determine the performance of long-short-term memory in the forecasting of the economic indicators were compared to principal data of the net. The findings of the research argue that reconstructed data which are derived from variational auto-encoder embody shorter training time and outperform of prediction in long short-term memory compared to principal data.
- انتشار مقاله: 10-09-1398
- نویسندگان: Maryam Hajipour Sarduie,Mohammadali Afshar Kazemi,Mahmood Alborzi,Adel Azar,Ali Kermanshah
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Information Technology Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Good governance,organizational intelligence,Transparency,Intelligent governance,Policymaker organizations,Transparent intelligent governance
- چکیده:
- چکیده انگلیسی: The new paradigm of good governance has an emphasis on international transparency, and this in this study takes into account the actual impacts of organizational intelligence in policymaker organizations. This study primarily aims to design an intelligent model of transparent governance in policymaker organizations with the approach of good governance. The study is a fundamental research in terms of objectives. In the qualitative section, data collection was done through Delphi interview questions, and the statistical population was senior managers, specialists, and policymakers with targeted sampling. In the quantitative part, the population was mid-level managers and organizational intelligence experts. The random sampling method was via the Cochran formula, and 432 individuals were selected. Data gathering tools were interviews and researcher-made survey questionnaires. The content and face validity and Cronbach alpha reliability were employed. The data were analyzed by descriptive and inferential statistics, including factor analysis, regression, and structural equations. Model fit and Friedman test were employed. The findings indicated three dimensions in the proposed model design, including transparency, knowledge creation, and knowledge translation, along with six components, five subcomponents, and 23 indicators. The results suggested that there is a relatively strong and appropriate relationship between organizational intelligence and organizational transparency. Furthermore, sense-making had the highest correlation with organizational transparency. Also, the strongest predictor was the sense-making variable.
- انتشار مقاله: 29-09-1398
- نویسندگان: Roya Sepehrnia,Mahmood Alborzi,Ali Kermanshah,Adel Azar,Rozita Sepehrnia
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Information Technology Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Policy-Making Institution,Big data analytics,Now-casting,Comprehensive model
- چکیده:
- چکیده انگلیسی: The ability of now-casting and eventuality is the most crucial and vital achievement of big data analytics in the area of policy-making. To recognize the trends and to render a real image of the current condition and alarming immediate indicators, the significance and the specific positions of big data in policy-making are undeniable. Moreover, the requirement for policy-making institutions to produce a structured model based on big data analytics for now-casting and eventuality of predictive policies is growing rapidly. The literature review demonstrates that a comprehensive model to assist policy-making institutions by providing all components and indicators in now-casting of predictive policies based on big data analytics is not devised yet. The presentation of the model is the main finding of this research. This research aims to provide a comprehensive model of now-casting and eventuality of predictive policies based on big data analytics for policy-making institutions. The research findings indicate that the dimensions of the comprehensive model include: the alignment of now-casting strategies and the big data analytics’ architecture, now-casting ecosystem, now-casting data resources, now-casting analytics, now-casting model and now-casting skill. The results of using the model were analyzed and the recommendations were presented.
- انتشار مقاله: 11-04-1398
- نویسندگان: Maryam Hajipour Sarduie,Mohammadali Afshar Kazemi,Mahmood Alborzi,Adel Azar,Ali Kermanshah
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Information Technology Management
- نوع مقاله: Journal Article
- کلمات کلیدی: fuzzy logic,Fuzzy Expert System,economic factors,Knowledge base,Technical Factors
- چکیده:
- چکیده انگلیسی: This article aims at designing a Fuzzy Expert System that helps select the appropriate industrial investment and prioritize the projects based on credible criteria and international standards in fuzzy environment to reduce the risk of adverse selection where possible. The main objectives of the research issue are optimizing decisions, increasing productivity and reducing investment risk that can ultimately lead to development.This article describes how to design and use fuzzy expert system and indicated the role of technical and economic criteria in selection of industrial projects. In this study, MATLAB (fuzzy inference module system) software was used to analyze the data, fuzzy inputs and outputs, establishment of rules and, ultimately, expert system output and their defuzzification, and the graphical interface. The existence of such a model in addition to helping to improve decision-making will help the development of industry and IndustrialadvancementIn order to validate this study, a case study was done and the comparison of the output of the proposed system with the experts’ opinions approved the validity of our system. The system helps to prioritize and select industrial projects and provides recommendations in more detailed.
- انتشار مقاله: 21-01-1396
- نویسندگان: Ali Rajabzadeh Ghatari,Ahmadreza Ghasemi,Adel Azar,Rohollah Hosseini
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Information Technology Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Data mining,Decision Tree,clustering,Human Resource Management,Knowledge discovery,personnel selection
- چکیده:
- چکیده انگلیسی: The success or failure of an organization has a direct relationship with how its human resources are employed and retained. It is the case that organizations keep large amounts of information and data on entrance evaluations and processes. This information, however, is often left unutilized. Data mining is considered a solution for analyzing these data. This paper is investigating educated and objective methods of data analysis. It follows statistical rules, data mining techniques, and the relationship between entrance evaluation scores and personal and professional variables. These factors are studied in order to determine the assignment and rank of potential employees. The database and personnel information of the a Commerce Bank of Iran (in years of 2005 and 2006) is studied and analyzed as a case study in order to identify the labor factors which are considered effective in job performance. The data mining technique that is used in this project serves as the decision-tree. Rules Derivation has been accomplished by the QUEST, CHAID, C5.0 and CART algorithms. The objective and the appropriate algorithms are determined based on seemingly “irrelevant” components, which the Commerce Bank Human Resources management experts described. Results indicated not taking into account the “performance assessment” variable as the objective. Also this project has identified the following from 26 variables have been investigated, five variables as the effective factors in employee promotion: examination score, interview score, degree, years of experience, and job location. The paper's results led in knowledge that can be practical.
- انتشار مقاله: 11-10-1348
- نویسندگان: Adel Azar,Parviz Ahmadi,Mohammad Vahid Sebt
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Information Technology Management
- نوع مقاله: Journal Article
- کلمات کلیدی: Interpretive Structural Modeling,Calibration Diagram,Driver Power Dependence Matrix,Process Orientation
- چکیده:
- چکیده انگلیسی:
- انتشار مقاله: 11-10-1348
- نویسندگان: Adel Azar,Karim Bayat
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Finance and Managerial Accounting
- نوع مقاله: Journal Article
- کلمات کلیدی: valuation,Value Relevance,Net Financial Expenses,Residual Earnings
- چکیده:
- چکیده انگلیسی: Based on valuation model of residual earnings, we cannot use earnings and losses of balance sheet items recorded in fair value for valuation purposes, for the balance sheet provides a perfect estimate of such items’ value. The purpose of this study is to examine whether net financial expenses are related to the market price of stocks in Iran, because after initial recording of financial debts, no adjustments are done in historical cost regime. We expect to see an improvement in this relationship during severe fluctuations in the country’s economy. 35 companies were selected from firms listed in Tehran Stock Exchange and we a period of eleven years, 2005-2015 was studied. The statistical test for data analysis is regression testing. The results show that net financial expenses are value relevant and there is an increasing trend in value relevance of these expenses during imposing the sanctions. This trend is particularly strong from 2009 onwards
- انتشار مقاله: 14-08-1395
- نویسندگان: Hossein Etemadi,Adel Azar,Sasan Babaie
- مشاهده
- جایگاه : پژوهشی
- مجله: Environmental Energy and Economic Research
- نوع مقاله: Journal Article
- کلمات کلیدی: Green supply chain,Bayesian belief network model,medicine supply chain risks,interacting risks,Supply chain performance
- چکیده:
- چکیده انگلیسی: With the increase in environmental awareness, competitions and government policies, implementation of green supply chain management activities to sustain production and conserve resources is becoming more necessary for different organizations. However, it is difficult to successfully implement green supply chain (GSC) activities because of the risks involved. These risks alongside their resources disrupt the normal functioning of the GSC and affect its environmental and economic performance. The pharmaceutical industry in particular, is crucial to providing life-saving products and services to the society. The products and services provided in this industry, have several impacts on the environment in different ways. These include expired or unused medicines, inappropriate distribution by pharmacies or drug companies, disposal of surplus medicines in household sewage and improper disposal of pills or capsules by patients. This study represents a GSC risk network model that considers the interrelationships between risks in order to achieve an optimal level of performance measures defined in the supply chain by Bayesian Belief Networks (BBN). The model is empirically implemented through a case study conducted in Imam Reza hospital of Mashhad medicine supply chain involving structured and semi-structured interviews and workshop sessions with experts. This work uses a literature review and a causal map BBN approach in finalizing the risks and also uses the BBN inference system and scenario analysis for prioritization and analysis of the risks through the network under probability conditions. According to the findings, inefficient logistics network design, supplier quality issues and green raw material supply disruption are highly prioritized.
- انتشار مقاله: 21-10-1398
- نویسندگان: Mahdi Shakeri,Azim Zarei,Adel Azar,Morteza Maleki Minbash Razgah
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Performance,Banking industry,Agent-based modeling,Organizational ambidexterity
- چکیده:
- چکیده انگلیسی: Banks are the financial institutions that collect assets from various sources and allocate them to the sectors that require liquidity. Therefore, banks are an inherent element in the system of every country. As private banks enter financial markets, the demand for diverse banking services increases dramatically. Banks seek to use various techniques to improve their performance in attracting customers to increase their market share and profitability. In this regard, assessing the performance of banks is of utmost importance and has become a major activity of bank managers. With the constant changes in the modern world and incessant attempts of competitors to increase their market share by gaining competitive advantage, special attention should be paid to ambidexterity as a key strategy to increase competitive advantage and achieve high performance in dynamic business environments. The present study aimed to identify the ambidextrous factors affecting the performance of banks and present a model to assess the performance of an ambidextrous bank using an agent-based modeling approach. The main objective of the research is to achieve an applied model for managing the performance of the banking industry. The simulation model is processed using the agent-based modeling approach in AnyLogic software environment.
- انتشار مقاله: 01-05-1398
- نویسندگان: Farzaneh Jahanseir Khararoudi,Adel Azar,Tooraj Karimi
- مشاهده