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Aim: First, tlris study aims to identify and review tire primary studies in liich user psychological needs liave been applied to solve problems related to time field of Information Technology; tlmerm, it tries to provide a suitable framework for researchers atmd designers of IT prodmmct by classifying these stmrdies arid investigating the contexts of U-Ser needs applicatioim. Methodology: Haviimg a qualitative approaclm. time research carried out a Systematic Mappitmg Shidy (SMS) based otr time 5-step fraimmework presented by Peterseim et al. (2008). Irm total, 1152 researclm with filll access were identified witlmout army time liirmit, by searclmiimg valid domestic aimd foreign scieimtific databases. Finally, 'a group of 45 shrdies was selected through selectiorm criteria. Then, time' selected researches, were classified based oim time obtained criteria and were analyzed using quaimt'itative coimtent aimalysis aimd descriptive statistics. Findings: hr time last two decades, time applicatioim of user' psyclmological imeeds for solviimg probleimms related to a wide range of IT products lmas growmm iimcreasiirgly iim time fonmm o'f using wellkimowim tlmeories. or exp'loitiimg time components of imeeds (witlmout referring to a specific theory)٠or as a general concept. Time review of primary studies shows tlmree thematic contexts, for applyiimg psychological needs: 1) user experience design 2) aimalysis of product quality aspects aimd 3) aimalysis of user behavior. Conclusion: The review of the literature background of these three contexts and mapping them with the classification criteria of selected researches (time, type of product, application of needs, and methodology) has clarified the boundaries and characteristics of these three thematic contexts as a mind map for researchers. Finally, by analyzing these criteria, especially the application of needs in the field of IT, suggestions are presented for firture studies. [ABSTRACT FROM AUTHOR]

These days, every business is trying to achieve its competitive goals. In other words, if one business uses the most modern analytical technologies optimally, it will certainly boost its success level at an exponential rate. The Islamic Republic News Agency (IRNA) is one such mass media industry that, according to its need, uses the benefits information technology (IT) provides it with. News flows, surveys, human resource management, warehouse management, software are key parts of the agency’s news penetration criteria. There is little software that focuses on analytical solutions for running the business optimally. This paper, among available text mining methods, intends to present the most important keywords of news texts based on weighing of words and their correlations, news classification, news sentiments, news trends in order to provide insights and patterns for future scholars and practitioners in the field. This approach will help news agencies maintain their competitive edge as well as predict and react to the market of news search and provision in a timely context-based manner. [ABSTRACT FROM AUTHOR]

Full-text articles are mostly provided in electronic formats, but it still remains a challenge to find deeply related works beyond the keywords and abstract contexts. Identification of related scientific articles based on keywords and abstracts help researchers to find desired and informative content, but it requires the utilization of variety of text analytics (mining) methods to address the need. This study investigates information systems (IS) articles to cluster and evaluate the domain of knowledge of recent Information Systems publications using text clustering methods and then to predict the exact clusters of knowledge of new articles using classification methods. This categorization and predictive learning approach help the scholars and practitioners to find the most relevant articles for their researches and practical endeavors through an automated mechanism. Articles have been collected from the Scopus repository. The dataset has been narrowed to specific areas of recent information systems research. Different text analytics methods such as text normalization, natural language processing (NLP) and clustering algorithms have been applied and the results for each cluster are evaluated by extensive analysis of identified clusters based on their terms frequency and key phrases. Afterwards, different classification algorithms are applied to learn the current clustering and to predict the major subject focus of a newly published article based on the abstract approximation to the previously learned domains of information systems knowledge. The prediction approach helps the scholars identifying the usability of many articles for further research. [ABSTRACT FROM AUTHOR]

Flipped classroom is a relatively new model in education that primarily focuses on learner-centered instructions. In other words, the model allows both management and teachers to build a more active and dynamic learning environment on the campus. The current paper tries to document the implementation of the flipped classroom model in two big data courses. Here, the course contents have been curated from a couple of websites with different contents including videos and short books as well as reports. The mixed-method approach was applied while analyzing the student perceptions in demographically two different groups. It was found that students of both groups responded positively to the flipped classroom, with each focusing on their specific goals. Consequently, the first group focused on the academic achievement whereas the second group with managerial jobs focused on solving problems in their workplaces. Students of both groups, although preferred TED talks and documentaries, they were opposed to university-like videos and O'Reilly short books and reports. Meanwhile, the use of English language contents turned out to be both a challenge and an opportunity for students. [ABSTRACT FROM AUTHOR]

An ever-increasing use of Internet has greatly been affecting the importance of e-commerce websites. As such, analyzing those websites and discovering customers' purchasing power, the present study tends to propose a framework and an appropriate structure to make the websites more flexible and highly functional. Such an efficient and effective framework facilitates customers' purchasing capacities. In this framework, different techniques and methods including the genetic algorithm, neural networks, and collaborative filtering are utilized. The pre- and post-execution data show that the proposed framework changes the website structure based on the two criteria, i.e., sales conversion rate and average pre-purchase page views and finally leading to improved website usability. [ABSTRACT FROM AUTHOR]

Information technology has played a remarkably important role in developing the contemporary educational system. It not only provides easy access to enormous stores of information but also increases students' scientific efficiency. However, the availability of this technology has also led to increased plagiarism. This study attempted to explore how access to Internet technology contributes to plagiarism problems from the perspective of university students in Iran. A qualitative method to semistructured interviews with 20 students suggested important themes: uncertainty avoidance, tendency to use shortcuts to progress, symbolic certification, social learning and modeling of faculty members as mentors, and plagiarism in the name of justice. Survey data from 180 university students suggest that the personality characteristic of conscientiousness had a negative effect on using information technology to commit plagiarism. [ABSTRACT FROM AUTHOR]

Abstract: Data mining techniques, extracting patterns from large databases have become widespread in business. Using these techniques, various rules may be obtained and only a small number of these rules may be selected for implementation due, at least in part, to limitations of budget and resources. Evaluating and ranking the interestingness or usefulness of association rules is important in data mining. This paper proposes a new integrated data envelopment analysis (DEA) model which is able to find most efficient association rule by solving only one mixed integer linear programming (MILP). Then, utilizing this model, a new method for prioritizing association rules by considering multiple criteria is proposed. As an advantage, the proposed method is computationally more efficient than previous works. Using an example of market basket analysis, applicability of our DEA based method for measuring the efficiency of association rules with multiple criteria is illustrated. [Copyright &y& Elsevier]

Since the web is always developing, and users' needs are constantly changing, organisations in recent decades have increasingly focused on developing information and communication technologies (ICTs). To introduce new e-services to their customers, they have largely invested in web development and promotional activities. The present study, therefore, describes a novel approach for evaluating and improving website link structure by using web usage mining, as well as assessing the usage pattern of an Iranian organisation. Analysing this pattern, the visited paths are illustrated and the website is modelled as a directed graph. On the basis of graph theory definitions, some measures are introduced and applied to evaluate website usability and link structures. Finally, a ranking improvement strategy is proposed and findings are discussed. [ABSTRACT FROM AUTHOR]