Journal of Information Technology Management
Year:2017 | Volume:9 | Issue:2 |Papers Count:11

Developments of recent decades shows that for reducing the financial and opportunities costs as well as increasing productivity, it is necessary to improve the quality of components and systems in organization. Information systems based on these rules should be considered and for improving their productivity, user’s satisfaction and effectiveness it is necessary to quality aspects of these systems are considered too. In this research a quality assurance system is developed to all parts of an information system from data gathering, data entry to indexing and dissemination of information for assuring of quality are included. This model based on continual improvement approach of Deming cycle will change all of its systems and processes so that each development in the system with considering current standards and quality guidelines are done.

Although trust relations among users in social media are the evidence of social influence, but the level of this impact depends on strength of trust among users. Therefore, in this paper we study the effect of trust relationships’ strength among users through the development of matrix factorization method. Matrix factorization is a method to predict the rate that user assign to the products. For this purpose, based on similarity factors the strength of trust relationship is measured, then this feature as an effective parameter was added to matrix factorization. The proposed model is applied on Epinions data set. The weight of trust relationships’ strength parameter is determined through the proposed model. Based on the results, by adding the strength of trust relationship the error rate is reduced. Furthermore, if the strength of trust between users is larger than 0.8, the error reduction will be more significant. Improving the results through more accurate estimation shows that this effect is set correctly.

Enterprise resource planning systems by facilitation and integration of organizations’ operations as well as leveraging the organization's operations and business activities has become an important competitive advantage for organizations. Although the appropriate choose of an ERP system can greatly contribute to the success of the organization, inappropriate selection of ERP also can lead to irreparable damages and costs. Therefore, in this study we have tried to use a multi-attribute decision-making model to evaluate and select the most appropriate ERP system. Since decision makers turn to “uncertain preferences” to evaluate the criteria and alternatives, applying Rough Set and the Gray Set theories in the context of multi-attribute decision-making models seems more logical and consistent. The findings indicate that the “total cost” a sub-criteria of product characteristics and “system technical capabilities” a sub-criteria of system requirements are the most significant criteria and the “A6” is the most significant alternative.

Viral marketing, relying on word of mouth principle is an advertising or a way to publish it on the Internet or mobile networks. The main objective of this article is to explore and prioritize important factors affecting viral marketing in the context of mobile applications. Meta-synthesis technique was used to explore the important factors affecting viral marketing and then using Fuzzy Delphi to determine the significance of the factors. The population of this study in the quantitative section was experts working in the field of viral marketing in the mobile application industry who have been selected by snowball sampling method. In the meantime, 30 experts were selected. The results of meta-synthesis method showed 26 important factors. By using Fuzzy Delphi, 12 factors including speed of message, attractiveness of message, ability to communicate with the product, morality, reliability of the source or validity, personality of the recipient, motivations of people, emotions of people, culture, brand reputation, brand strength as well as brand image were the most important factors.

This study was conducted in order to identity Qualitative factors affecting the production and distribution of information and knowledge in science and technology parks of Iran. The research was Applied Research in which, qualitative method was carried out. The population of the study was included of 10 managers of Knowledge-based Companies. The data was collected from the population using semi-structured and in-depth interviews. For data analysis, content analysis was used. Results of the qualitative factors affecting the production and distribution of information and knowledge in science and technology parks of Iran, led to extraction of 39 components which were classified in four categories: I) Foreign and domestic policy, II) Financial and economic support, III) Infrastructure barriers and IV) Cultural barriers. Results howed that overcoming the political, financial and economic, infrastructural and cultural barriers has undeniable impact on production and distribution of information and knowledge.

Usual methods of segmentation have been designed, relying solely on the components ofRecency (R), Frequency (F) and Monetary (M) in which customers’ behavior changes over time are not considered. Accordingly, in order to achieve a desired segmentation method, this study aims to apply a set of statistical calculations, such as line slope and the derivative with respect to time and data mining methods such as K-means and Self-Organizing Maps (SOM) to define new parameters for studying the changes trending of customer purchasing behavior. The results show that considering the slope of the line of customer behavior changes (R, F, and M) and the higher value for recent behaviors of customers compared to that of their past behavior in customer segmentation would thereby increase the accuracy of predicting the future behavior and cause the customers of each section to become more homogeneous. Based on the suggested method, customers are categorized into four segments: best, spender, repeater and missed ones each of them are divided into two subcategories of ascending and descending segments, which leads to better and more accurate understanding of customers in different segments according to how of their purchasing behavior change. Finally, the characteristics of each segments and sub-segments are described and appropriate strategies are provided for managing its customers.

Identification and tracking scientific changes is critical for scientific policy makers. This research proposed a model for identification and tracking changes in Data Quality research area. We used cumulative citation network in order to find research communities and their changes during the time. The proposed model can be applied in other scientific disciplines. It can also shows all types of scientific changes including birth, growth, merging and death. In order to verify the model in Data Quality area, we selected all papers that is published between 1970 and 2009 that covers more than 7000 papers. It is shown that Data Quality research area is studied in different disciplines. According to the results, there is 82 percent correlation between number of citations and the growth of Data Quality communities that shows the importance of citation for community survival and growth.

In today's business environment companies are facing pressure to innovate and create new knowledge, that these issues have forced them to spend large sums on research and development, involving in high-risk investments, finding exclusive sources and even look for high-tech products with short life cycle. Coopetition strategy (competition and cooperation simultaneously) for companies that are seeking to innovate in order to compete in today's global market, is an essential strategy and provide many innovation opportunities for firms. In this study, the effects of collaboration in IT industry on innovation performance has been investigated in the implementation of the coopetition strategy. This study, is an applied research in terms of purpose, a descriptive survey in terms of data gathering and a correlational study considering relations between variables. The study population consists of Iranian companies operating in IT industry. Data were collected from 180 companies. The hypotheses were tested using structural equation modeling via WARP PLS3. The results showed that coopetition strategy and cooperation in industry has an impact on innovation performance. Also, coopetition strategy moderate the relationship between the cooperation in industry and innovation performance.

Netnograghy as a new approach in social networks and Internet communications analyzes customers' suggestions and opinions in the form of comments. Making use utilization of quantitative techniques in order to analyze, detect the meaning and recognize the signals of mainly incomplete opinions of customers is vital for managers. In this paper, firstly by the aid of grounded theory method, the meaning and important criterions of user comments in mobile shopping sites have been recognized and then these criterions have been graded based on decision making by experts and fuzzy preference relations with incomplete information. Analyze of users' comments proved six parameters: price, beauty, process speed, screen quality, battery as well as camera are significant, and among them, based on fuzzy relations with incomplete approach, beauty with value of 0.27563 is of utmost importance for users.

With increasing use of e-banking system in Iranian banking sector, ignoring the issue of fraud in the system will be very costly for banks and e-banking customers. Fraud in e-banking is due to some security problems (such as weakness in access control systems and inadequate internal control). So, identifying success factor in fraud prevention in e-banking can be useful for e-banking system developers to improve these systems security. In this paper we have tried to identify and rank these success factors for fraud prevention in e-banking systems. For this purpose, we first review the literature to find potential factors, then identified factors were weighted by using fuzzy group multi criteria decision-making model and experts' judgment. The results show that for elimination fraud in e-banking systems it is necessary to pay attention to technical, operational, strategic and financial factors respectively.

According to the complexity and differences between Iranian banks and other developed countries the appropriate actions to implement effective security management of information technology have not been taken. The aim of this study was to create a powerful model by selecting the appropriate security controls to protect information assets in the bank. In this model, at first the principle set for in ISO standard 27001, was extracted and then by further studies derived from best practices carried out in the world on the related subject from 2008 to 2016 using a qualitative descriptive method), points comply with information security management in the banking industry were added to it. With the study of Iranian banks in dealing with IT security management system and with help of action research tools, provisions which prevent the actual implementation of this standard was removed and finally a conceptual model with operating instructions and considering all the principles of information security management standard, as well as banking institutions focusing on the characteristics of Iran was proposed.