نشریه مدیریت اطلاعات
سال هفتم شماره 1 (پیاپی 12، بهار و تابستان 1400)

Social commerce as a new paradigm of commerce has been considered for about a decade. The first attempt to apply this paradigm is to examine its acceptance process. In this research, social commerce acceptance studies have been reviewed with primary and secondary search strategies. The main purpose of this research is to examine the acceptance process from different perspectives and to analyze the research gap that paves the way for future research in this field. Survey perspectives include focus on acceptance steps, basic theories used, focus on value creation, extent of customer engagement, focus on innovation, type of media used, geographical focus, type of business transactions concerned, their influential factors, thematic focus and applied focus area, research methods used, data analysis tools and statistical samples. Accordingly, 203 articles were reviewed with two approaches: quantitative analysis and gap analysis. Quantitative analysis of studies showed that acceptance technology as the highest theories, social networks as most platforms, trust as the most widely used factor, Asia as most continental geographical focus, China and the United States as the most geographical focus of the country. Based on the gap analysis, service-oriented businesses, qualitative methods and modeling, focusing on e-commerce platforms and equipping them with social commerce constructs, and focusing on business-to-business transactions were identified as research gaps.

This study aimed to design a model for evaluating organizational infrastructures in providing electronic services by a business intelligence approach with a mixed method. In the qualitative section of the research, while the related texts and literature were studied, 10 semi-structured interviews were conducted by managers and senior experts who were active in the field of electronic services. The findings were analyzed using thematic analysis coding. In order to review and refine the codes using Delphi technique, the researcher obtained 135 codes in four stages. The validity of codes was estimated using Lawshe’s content validity (0.86) and the Kendall agreement coefficient (0.78). In the following, the data was classified in the form of 4 main themes based on business intelligence approach (technical, management, product, strategic), 20 sub-themes and 135 indicators and the considered model was designed. In the quantitative section, 270 specialists were selected using the census sampling method. The questionnaire validity was estimated using construct validity and its reliability was calculated using Cronbach's alpha coefficient (0.87). After data analysis in AMOS software, it was clear that the operating loads of all the sub-components are in good condition.

The aim of this study was to investigate the Triple Factors Bandura's Social-Cognitive Theory on users' interaction with Iranian academic digital Libraries. For this purpose, 384 people were selected as members of the research sample using two sampling methods (cluster random sampling and stratified random sampling) from the community of university users. The face and content validity of the questionnaires were evaluated using the opinions of experts and the construct validity was calculated using factor analysis. The reliability of the questionnaires was also confirmed using Cronbach's alpha method (0.948). In order to analyze the quantitative data related to the research question from descriptive and inferential statistics with the help of SPSS software. To test the qualitative date related to the research question, descriptive and inferential statistics were used applying SPSS software and for testing the model and hypotheses, Amos software was applied. The results of the research in the quantitative part showed that personal (cognitive) factors with a coefficient of 0.37, behavioral factors with a coefficient of 0.36 and environmental factors with a coefficient of 0.42 have an effect on the information retrieval interaction of university digital libraries. From the results of structural equation modelling, it was concluded that the intensity of personal (cognitive), behavioral and environmental factors in three dimensions of interaction in academic digital libraries are strong, and digital libraries need to pay more attention to these components in order to perform optimal information retrieval and develop interactive software.

In the age of technology and the increasing growth of information, managers face needs and challenges to maintain competitiveness, ignoring them will cause them to leave the competition scene. Accordingly, the purpose of this study is to identify and rank the information needs of managers in the field of research vice chancellor of Shahid Chamran University of Ahvaz in the research information management system. The present study is an applied studies in terms of purpose and is a qualitative research in terms of method. The research population included: vice chancellor and director of research, research assistants of faculties and principals who at the time of the research were a total of 20 people. The required data were collected with the help of in-depth semi-structured interviews and Delphi survey and for data analysis, qualitative data analysis method was used using content analysis method and SPSS software version 22. Findings of this study showed the information needs of the managers of the Vice Chancellor for Research in Shahid Chamran University of Ahvaz in the research information management system into six categories of information: "human and physical resources", "scientific products", "laboratory", "external environment information", "legal" and "Financial" are classified. "Scientific production information" is the first priority of identified needs. Also, the source of managers' information needs in printed sources is "written reports, written instructions" and non-printed sources "Internet and telephone". The "process challenges" in the research information management system are most important in meeting the information needs of the managers of the research department. Based on the selected coding, the information needs of the managers of the research department of Shahid Chamran University of Ahvaz were placed in six general categories. Research Information Management Managers have a variety of information needs.

Telegram is a cloud-based messenger with more than 500 million monthly active users. Telegram's features include the creation of supergroups, channels, bots, and secret chats that provide users with more capabilities than a messenger. Telegram is used as a social network in Iran; but it does not offer all the features of a social network, including finding a collection of users. Finding users is very useful for marketers to find the target audience. In this paper, a method in two parts is presented by users' communication graph. The first part is based on graphs and model groups based on the percentage of subscriptions with incoming users. The second section ranks the groups based on the number of managers. The data of this study includes information about 70 million users and 700,000 supergroups in Telegram. The information obtained has been crawled by the IdeKav System, and it is worth noting that this information has been obtained quite legally by the tool provided by Telegram to the public. In this article, the proposed method is evaluated based on popular groups in Telegram. Popular groups are groups in which a single topic is discussed. In this paper, the evaluation by popular Telegram groups has been done by two categories of validation and test, and the results of experimental experiments have shown the repetition of the results and the integrity of the proposed method. The proposed method with the aim of covering the whole graph in two parts has shown the effectiveness of the suggestions and reduction of forecasting error compared to the previous three studies.

Has been for a long time, effectiveness considered by organizations as a measure of achieving the goals of stakeholders. Now, audience are the key stakeholders of media and the measure of effectiveness is their goals. Therefore, in the world's top media, efficient models have been designed to evaluate effectiveness of programs from the audience's point of view. These models use social network data mining. Because social media data is accurate sources and without orientation of audience needs. The purpose of this study is to investigate the ability to use the Twitter user data in content effectiveness evaluating of the Islamic Republic of Iran Broadcasting. in previous research, interview tools or questionnaires have been used to collect data, which have problems such as gatekeeping and orientation. In this study, we investigated the ability to use Twitter data to effectiveness evaluate. This research has been done in two Steps. First step, based on in-depth expert interviews with 15 persons and thematic analysis method, we extracted a model for the content effectiveness evaluation. That include 5 main Component; Input, process, output, monitoring unit, research unit and 26 sub-components. In the second step, we mined Twitter user data about six series aired in 20 march to 20 December 2020, based on an unsupervised Clustering and analyzed by Rapid minder software and content analysis method. The results showed that both content analysis and Structural analysis methods can be used for content effectiveness evaluation. Also, Twitter data mining can be used in the precontent planning, the pre-production, distribution and feedback stages of the effectiveness evaluation model.

The purpose of this study is to meta- analysis studies in the field of the usability of library information storage and retrieval system based on the use of semantic web technologies. The method of the present study is qualitative based on the approach. This research has been done in two stages. In the first stage, to identify and evaluate the application of semantic web technologies in the library system; related information sources were identified and collected in Persian and Latin databases. The result of the first stage of the research is 125 related sources of information including: articles in journals, conferences, and dissertations English and Persian. In the second stage of the research, the content analysis of the texts obtained from the first stage based on three indicators of storage, search, and semantic retrieval has been done using MAXQDA software. The result of content analysis led to the identification of how semantic web technologies are used in the library system and their frequency of use. Content analysis of the texts showed that in the indexes of storage and semantic search, RDF technologies with 50%, Ontology with 25%, Linked Data with 20%, and SKOS with 4%; And in the Semantic Retrieval Index, Link Data technologies and FOAF. They are usable with 20% and 2%, respectively. In this study, the content analysis of texts led to a comprehensive view of the application of semantic web technologies in the organization and OPAC sections of the library system. Therefore, the use of semantic web technologies in the library system; Leads to the selection, display, reference, and semantic use of data and information resources of the internal and external library resources and increases the usability of the library system.

Business intelligence systems has become a vital part of organizations during the past several years. Pragmatically, there is limited research investigating the impact of using this system on coporate financial performance. The results of This researchs are also contradictory. This paper develops a model based on balance scorecard approach. The research data were collected from 82 private and public corporations that implemented BI system. The proposed relationships between constructs were tested by structural equition method. The results indicate that the financial performance of the organization does not improve directly through the acceptance of the business intelligence system. Indeed, system acceptance improves the performance of internal processes, customers, and organizational learning, and consequently indirectly improves financial performance. From practical viewpoint, the acceptance of this system makes achieving tangible financial benefits in terms of improving process performance, customer and learning. Therefore, financial performance is the last advantage of using this system.

The main goal of this study is prioritizing the Economic Data Management Integrated Framework’s criteria based on data management frameworks in knowledge-based enterprises, using the comparative methodology of multi-criteria decision making and fuzzy logic calculations in Expert Choice and MATLAB software environment. The statistical sample of the present study is composed of expert university professors in the field of study and specialists working in knowledge-based enterprises in Tehran or other similar positions. Finally, 300persons were selected using the non-probability sampling technique at 2020 winter. According to the fuzzy calculations of the prioritization of research criteria, one of the most important results of the present study is that: the most important criteria in the "Economic Data Architecture" cluster, was "Data Quality Model” with the hierarchical fuzzy weight of 0.096; and the most important criteria in the "Data Management Processes in Databases" cluster,were "Data Distribution Services factor" with the hierarchical fuzzy weight of 0.191; and "Data Access Protocol factor"with the hierarchical fuzzy weight of 0.120. on the other hand, the most important criteria in the "Economic Data Models" cluster, was "Conceptual Data Model"with hierarchical fuzzy weight of 0.123, since based on multi-criteria decision making technique and fuzzy logic calculations, they have the highest fuzzy rank.

Today, achieving sustainable growth and development is possible through the realizing knowledge-based economy. One of the key factors for success in this model is the identification and application of knowledge and innovation. Clusters are one of the tools for accelerating the growth and sustainable development of knowledge base. By providing a good platform for the production of tacit knowledge, clusters create the groundwork for innovation and technology creation, and thus realizing a knowledge-based economy. This article selects the information technology cluster and tries to explain the position of tacit knowledge and innovation in this cluster, examining the factors affecting the development of knowledge-based information technology, in addition to explain the relationship between clusters and knowledge-based economy. The countries studied in this article are thirteen European countries. For modeling, DOLS and FMOLS methods have been used for panel data. The indicators of research and development expenditures, education expenditures, exports of goods in the field of information and communication technology, as well as the number of firms active in the ICT cluster (as an ICT cluster index) are the indicators examined. The results of this study indicate that the important and influential indicators of knowledge-based economy have a positive and significant relationship with the index of clusters.

By using big data, companies can be accurately informed about future market trends and customer preferences. Accordingly, innovate in marketing activities. However, to take advantage of this new technology in marketing, elements and factors are needed. In this regard, the current study has identified the necessary Prerequisites for using big data to innovate in marketing activities. the methodology of current research is a qualitative method by getting interviews and using content analysis. The subjects were 18 experts in the fields of data science that were selected by purposeful sampling method. By analyzing the interviews, 6 main concepts and 17 sub-concepts were identified. The results showed that antecedents for using big data in marketing activities are data-driven culture, data-driven skills, data-driven systems creation, dynamic resources provision, data-driven marketing capabilities, and support and perception CEOs. The results of this study can be used to assess the readiness to use big data in the marketing activities of organizations to develop and improve products and services and better experience for their customers.

Given the increase in e-services and the need for IT-based decisions in businesses, IT governance in organizations, especially the banking industry, is a vital need. The present study has been proposed with the aim of designing the COBIT-TOGAF model for IT governance. In the qualitative section, while studying the literature, the guidance of managers and senior experts active in the field of banking information technology services was used. The proposed model for IT governance is based on COBIT 5 and TOGAF 9.1. The proposed model for IT governance is based on COBIT 5 and TOGAF 9.1. Data collection tool is a questionnaire, and research method is descriptive and survey also applied in terms of purpose. The statistical population of the current paper is 755 managers and employees of a private bank in Tehran province who were classified using Morgan table and random sampling method and 258 of them were selected as a statistical sample. Also, Cronbach's alpha of all questionnaire questions (34 questions) was equal to 0.95. Findings were performed using statistical methods and Fuzzy Analytical Hierarchical Process (FAHP). The results in SPSS 26 and Python, which are the main software in data analysis, show that the FAHP has the greatest effect on the variables of effectiveness and satisfaction with weights of 0.125 and 0.1666, and the criteria of efficiency and performance improvements with weights of 0.1112 and 0.090, respectively, are effective.