JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT
Year:2016 | Volume:8 | Issue:2 |Papers Count:15

The security of information systems is one of the most important challenges for today's organizations. Although most organizations use security technologies, they concluded that technology is not enough by itself and the key threat to the organization security comes from employees who do not agree with the organization security policies. Therefore, the field of end users security behaviors in the organization has received serious attention. In accordance with recent studies, end users have different security perspectives which have weakened the monitoring of user's security behaviors. Using Q methodology, this research attempted to identify employees’ mental patterns regarding information security policies to lead employees with the security requirements of the organization. In this regard, by reviewing previous researches as well as evaluating and summing up the discourse space, Q statements were selected and ranked by 31 employees of petroleum products Distribution Company. Constantly, analysis statements and four mental patterns were identified and classified as assessors, committed, relatives and people who consider deterrence tools helpful in line with information security policies.

Effective and on time satisfaction of organizational requirements, implementation of KM projects and above all aligning KM with business strategies are the main concerns of executives which make the existence of KM strategic alignment roadmap necessary. In order to address challenges of aligning KM with critical business needs, this paper proposed a comprehensive road map of alignment with best practices and critical success factors of KM implementation. By applying survey approach, we investigated opinions of experts which were related to the KM alignment roadmap architecture and customization of roadmap factors. Then, by using evaluating research, the application of roadmap illustrated in Regional Electricity Company. Sampling method was purposeful (judgmental) which is a non-random method. Data were analyzed by descriptive and inferential statistics. The proposed roadmap had five levels with specific factors. Regional Electricity Company was in the second level of KM strategic alignment. By applying developed road map in Regional Electricity Company, current maturity of strategic aligning KM, strength and weak points of KM project were identified. Consequently, by considering the results of assessment, future strategies, focus and investment priorities of KM were extracted.

Knowledge sharing is perceived as a fundamental process of knowledge management. Individual's values are among the factors affecting knowledge sharing behavior that have not been investigated before. The developed research model investigated the impacts of individual motivation (Altruism and Reputation) on knowledge sharing behavior considering the moderating role of user's values. In order to test the research model, Idea City (known as Ideshahr) has been selected as one of the prosperous samples of Iranian virtual community with real knowledge sharing behaviors. As a quantitative research, survey method has been used. Structural Equation Modeling was applied to test the model. Based on data from 217 active users in Ideshahr, results showed that altruism and reputation had positive effects on knowledge sharing behavior. Moreover, it has been indicated that values of users had not moderated the relation between altruism/reputation and quality/quantity of knowledge sharing behavior.

This study seeks to identify the critical success factors of teams in the application-development project. To achieve this goal, a qualitative approach and content analysis was utilized. Semi-structured interviews with 14 developers and experts was performed for data collection. A systematic review of previous research shows that after 9 critical success factors. With the analysis interviews, the CSf's raised to 12, including user experience, strategy and project management, support and promotion, business models, planning and goal setting, financial and budgeting, marketing and customer needs, infrastructure, technical issues and design, contextual factors, teamwork and staffing. The results show that the customer experience, teamwork and contextual factors are core categories in the research paradigm model.

Social commerce has been introduced as a new approach to increase sales, number of customers and reduce marketing expenditures. This approach is a combination of business, communication between people, as well as communicative and informative technologies based on web 2.0 Its achievement originated from different factors relied on business, individuals, culture, and technology. These factors have been primarily identified on the basis of library researches and classified into six infrastructural groups including: technical, economical and human resources, cultural, rules governing the countries, style of management, and business. Then, it identified priority of the factors by using the fuzzy analytic hierarchy process (AHP). Innovation of this research was to extract a comprehensive list of factors and to prioritize them based on specific conditions in Iran.

This research attempted to evaluate Business Intelligence criteria accelerating further development of Core Banking System with creating meaningful analysis, decision support environment and optimizing the investments. By reviewing the related literature, Business Intelligence criteria were determined and the importance and priority of each criterion specified on the basis of questionnaire and doing Friedman and Binomial tests. This research presented an evaluation model based on the fuzzy multi-criteria decision making (Fuzzy TOPSIS) method. In the fuzzy-based method, weight of each criterion and results of assignable intelligence were described using linguistic terms, which can also be expressed as triangular fuzzy numbers. According to the findings, Risk Management System ranked as the first module with the largest distance from the negative ideal which indicated that this system had appropriate Business Intelligence capabilities to fortify decision support environment.

The main purpose of this study was to propose a model for assessing the effectiveness of web-based marketing in Iran's airline industry. Thence in the first step after identifying the components of the model on the basis of literature review and opinions of experts in the field of marketing and sales related to airline industry, the final components of the model were extracted. In the second step, the Dematel method has been used to determine the existing relations between criteria. In the following, we utilized the ANP to determine the weight of each criterion with regard to the existing dependency and feedback between criteria as the third step. Finally in the last step of this research three reputable Iranian Companies in the airline industry were ranked by the use of VICTOR method. The results obtained by Dematel method indicated the internal and external communications between criteria of the assessing effectiveness of web-based marketing model. Meanwhile, the results of ANP suggested that “Reliability” was in the first place in terms of weight and importance among all criteria of the model. Result of VICOR showed that Mahan Company had the minimum distance to the ideal level.

The utilization of 3G and 4G is rapidly increasing and also cellphone users are briskly changing their consumption behavior, using preferences and shopping manner. Accordingly, cellphone manufacturers should create an accurate insight of their target market and provide a “special offer” to their target consumers. In order to reach a correct understanding of the target market, consumption behavior and lifestyle of the submarkets we found the appropriate number of community clusters after criticizing the traditional methods and introducing market segmentation techniques which were based on neural networks. By utilizing the fuzzy Delphi technique, variables of target market segmentation were found. Finally, the obtained clusters and segmentations of the market were refined by using the techniques of K-means and aggregation (Agglomerative). The population of this research included the consumers of mobile in Tehran with a sample of 130 specimens after collecting data through questionnaires, results demonstrated that the Tehran cellphone market was comprised of 5 Clusters, each one are capable of implementing marketing strategy and marketing mix separately with taking into account the competitive advantages of ICT companies to maximize their demand and margin.

Internet entrepreneurs methods for identification and use of knowledge, skills and insights related to their business, have major impacts on creation and effective management of such businesses. Due to the diversity of learning methods used by internet entrepreneurs, this article intended to identify and prioritize them. In order to do so, semi-structured interviews were conducted with 10 successful internet entrepreneurs and by means of coding method, conventional learning methods for internet entrepreneurs were identified. Then, by distribution and using Friedman analysis of 376 questionnaires, superior learning methods were prioritized. Findings of this study indicated four major sources of learning as follows: learning from teaching – publications, learning from work – task, learning from social-human interaction, and learning from imitation – benchmarking. Furthermore, learning methods prioritization results showed that observation and imitation of best websites, reading websites content, personal thoughts and initiatives of problem solutions are three main methods of learning for Iranian entrepreneurs.

Nowadays, banks require new devices such as recommender systems to attract and preserve customers. Unlike most recommender systems in which the given recommendation is based on similarities between the preferences of users, this research has employed the classification techniques where customer’s past interests is considered as the most important feature to provide proper banking services for them. In this research, four classifiers including MLP, SVM, KNN, and Naïve Bayes have been used. Firstly, the data set which was related to the services used by different bank customers was pre-processed and four different classification methods were trained by using it. Then, their validations were assessed by the 10-fold cross validation and the best method was selected. Lastly, the final recommender system which was a combination of four classification methods including Naïve Bayes with performance P=%85.4, 5-nn with P=%83.3, MLP with P=%81.4, and MLP with P=%92.6 respectively proposed for recommendation of four banking services including the internet, mobile, internet transfer and paying on the phone is.

Nowadays, researches are faced with large volumes of data. Since a considerable amount of them are unstructured, they cannot be processed naturally. Hence two main challenges in this field are high dimensional of features space and bulk of available data. In this research, a feature selection method based on target features is propose to handle the curse of dimensionality. Moreover, to address the huge volume of data some of prototype selection approaches are utilized. The proposed method in this paper has three essential steps that each step improves the previous ones. Although, the proposed method reached significant results in each phase separately, its best performance obtained via the last phase in terms of classification accuracy rate. To evaluate the performance of the proposed method, it has been compared with three-layer algorithm. The results revealed that the proposed method had significantly better results than the three-layer algorithm in average.