University of QomSciences and Techniques of Information Management2476-665810320240922Design and Validation of a Model to Assess the Open Data Status of Iranian Government InstitutionsDesign and Validation of a Model to Assess the Open Data Status of Iranian Government Institutions740267510.22091/stim.2023.9255.1935FAMojtabaMazoochiAssistant Professor, Research Institute for Information and Communication Technology, Tehran, Iran0000-0001-9289-7940Mohammad HosseinKhaniPhD., Imam Sadeq University, Tehran, Iran.0000-0001-9289-7940MohammadMoradiPhD., Information Technology Engineering, Research Institute for Information and Communication Technology, Tehran, Iran0000-0002-3124-3289Journal Article20230318<strong>Purpose:</strong> Open data refers to non-confidential data that is made available without restrictions on use or distribution. Open government data is a tool for empowering citizens and giving them access to and permission to utilize data produced by the government sector. This enables individuals to use, store, redistribute, and integrate the data with other sources. Providing information as open data helps reduce corruption, fosters public trust, and contributes to the development of a democratic society. Open data offers significant opportunities for monitoring governance activities. Unfortunately, despite the importance of this issue and the existence of legal requirements, no reliable model has yet been developed to assess the open data status of Iranian government institutions. This study aims to design and validate a model for evaluating the open data status of these institutions, focusing on general axes to promote transparency within governmental organizations.
<strong>Method:</strong> The research method is applied in terms of purpose and utilizes a mixed data type, incorporating both qualitative and quantitative approaches. Three sources of information were utilized to identify the items for evaluating the open data index. Initially, the theoretical foundations and research conducted in this field were reviewed, and items suggested by experts were extracted. Subsequently, elites and scholars in the field were selected using purposive and snowball sampling methods, and in-depth semi-structured interviews were conducted with them until theoretical saturation regarding the items was achieved. The third source of information was Resolution No. 1 from the 16th session of the Executive Council of Information Technology in Iran. This resolution was proposed to enhance transparency and ensure citizens have free access to the open data of executive agencies. According to the resolution, all executive agencies are required to publish their data in twelve categories. After identifying and combining similar items and weighting them, the initial model was developed. To assess the validity of the items in the initial model, the Content Validity Index (CVI) was employed. Finally, structural equation modeling and related statistical tests were employed to validate the initial model, leading to its finalization.
<strong>Findings:</strong> A review of the three previously mentioned information sources used to identify open government data evaluation indicators resulted in the identification of 33 indicators categorized into four distinct dimensions: basic information, financial information, participation, and legal and functional systems. Following an examination of the validity and reliability of the initial model, 29 indicators within these four dimensions were approved for the evaluation of open government data. The results of the best-worst method used to prioritize dimensions based on their importance revealed that the dimensions of financial information, with a weight of 51.08%, are the most important, followed by the legal and functional system at 23.57%, participation at 18.42%, and basic information at 6.94%. These findings indicate the ranking of dimensions in the evaluation of open government data, from most to least important.
<strong>Conclusion:</strong> The findings of this study have the potential to enhance the accurate evaluation of open government data by focusing on the relevant indicators and dimensions. The findings can assist officials, researchers, and the general public in properly evaluating government organizations or institutions by taking into account the specified evaluation indicators. This approach will enable the positive impacts of open government data to be observed in society.
<strong>Purpose:</strong> Open data refers to non-confidential data that is made available without restrictions on use or distribution. Open government data is a tool for empowering citizens and giving them access to and permission to utilize data produced by the government sector. This enables individuals to use, store, redistribute, and integrate the data with other sources. Providing information as open data helps reduce corruption, fosters public trust, and contributes to the development of a democratic society. Open data offers significant opportunities for monitoring governance activities. Unfortunately, despite the importance of this issue and the existence of legal requirements, no reliable model has yet been developed to assess the open data status of Iranian government institutions. This study aims to design and validate a model for evaluating the open data status of these institutions, focusing on general axes to promote transparency within governmental organizations.
<strong>Method:</strong> The research method is applied in terms of purpose and utilizes a mixed data type, incorporating both qualitative and quantitative approaches. Three sources of information were utilized to identify the items for evaluating the open data index. Initially, the theoretical foundations and research conducted in this field were reviewed, and items suggested by experts were extracted. Subsequently, elites and scholars in the field were selected using purposive and snowball sampling methods, and in-depth semi-structured interviews were conducted with them until theoretical saturation regarding the items was achieved. The third source of information was Resolution No. 1 from the 16th session of the Executive Council of Information Technology in Iran. This resolution was proposed to enhance transparency and ensure citizens have free access to the open data of executive agencies. According to the resolution, all executive agencies are required to publish their data in twelve categories. After identifying and combining similar items and weighting them, the initial model was developed. To assess the validity of the items in the initial model, the Content Validity Index (CVI) was employed. Finally, structural equation modeling and related statistical tests were employed to validate the initial model, leading to its finalization.
<strong>Findings:</strong> A review of the three previously mentioned information sources used to identify open government data evaluation indicators resulted in the identification of 33 indicators categorized into four distinct dimensions: basic information, financial information, participation, and legal and functional systems. Following an examination of the validity and reliability of the initial model, 29 indicators within these four dimensions were approved for the evaluation of open government data. The results of the best-worst method used to prioritize dimensions based on their importance revealed that the dimensions of financial information, with a weight of 51.08%, are the most important, followed by the legal and functional system at 23.57%, participation at 18.42%, and basic information at 6.94%. These findings indicate the ranking of dimensions in the evaluation of open government data, from most to least important.
<strong>Conclusion:</strong> The findings of this study have the potential to enhance the accurate evaluation of open government data by focusing on the relevant indicators and dimensions. The findings can assist officials, researchers, and the general public in properly evaluating government organizations or institutions by taking into account the specified evaluation indicators. This approach will enable the positive impacts of open government data to be observed in society.
https://stim.qom.ac.ir/article_2675_30614832bbd98e7e2fb20746af92c22c.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Analysis of Factors Affecting Knowledge Sharing and Its Consequences in the SHAD Network as a Virtual Community of Practice Based on Chen and Hung's Model: A Case Study of Elementary School Teachers in Khorramabad CityAnalysis of Factors Affecting Knowledge Sharing and Its Consequences in the SHAD Network as a Virtual Community of Practice Based on Chen and Hung's Model: A Case Study of Elementary School Teachers in Khorramabad City4172273410.22091/stim.2024.9726.1984FAEhsanGeraeiAssociate Professor, Department of Knowledge and Information Science, Faculty of Literature and Humanities, Lorestan University, Khorramabad, Iran0000-0001-9484-1617ZahraKarimiPhD., Student, Department of Educational Sciences, Faculty of Educational Sciences and Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran.0009-0008-9519-451XRezvanShiriPhD., Student, Department of Educational Sciences, Faculty of Literature and Humanities, Lorestan University, Khorramabad, Iran.0000-0001-5638-5171Journal Article20230729<strong>Purpose</strong>: Knowledge sharing is a crucial process that adds value to organizational strategy.<br />It plays an essential role in facilitating the achievement of organizational goals, supporting organizational interests, sustaining success, fostering organizational learning, enhancing performance, creating a knowledge-based competitive advantage, and ultimately benefiting the community.<br />A collaborative community in the context of cyberspace is a virtual professional network that unites individuals with shared expertise in a specific field. This environment fosters knowledge sharing, enhances the professional skills of its members, provides advanced insights, and helps address career challenges. Accordingly, this study aims to analyze the factors influencing knowledge sharing and<br />its consequences within the Shad Network, a virtual collaborative community for elementary school teachers in Khorramabad city.
<strong>Method:</strong> This research is applied in terms of purpose and descriptive-correlational in terms of data collection and structural equation type. The conceptual framework of this study is based on the conceptual model presented in Chen and Hong's (2010) research. The research population includes 2208 elementary school teachers in Khorramabad city, of which 327 were selected as the research sample using the Krejci and Morgan table using stratified random sampling. Data collection was carried out using a questionnaire. Data analysis was carried out using SPSS and SmartPLS software.
<strong>Findings</strong>: Analysis of the demographic information of the respondents showed that 237 (72.48%) of the respondents were female and 90 (27.52%) of the respondents were male. In terms of educational qualifications, 199 (60.86%) had a bachelor's degree, 118 (36.08%) had a master's degree, 7 (2.14%) had a doctorate, and three (0.92%) had an associate's degree. The descriptive index analysis of the research variables showed that the average of each of the variables of reciprocity rule, interpersonal trust, self-efficacy in knowledge sharing, perceived relative advantage, knowledge donation behavior, knowledge collection behavior, perceived compatibility, knowledge use, and knowledge promotion are 4.268, 3.882, 4.104, 4.358, 4.336, 2.900, 4.084, 4, and 3.739, respectively. The results of the structural equations of the research showed that the variables of interpersonal trust (B=0.129); perceived relative advantage (B=0.152); self-efficacy in knowledge sharing (B=0.190), and reciprocity rule (B=0.251) have a significant effect on teachers' knowledge donation behavior. Also, the variable of perceived relative advantage (B=0.449) has a significant effect on knowledge collection behavior. Teachers' knowledge donation behavior has resulted in knowledge use (B=0.423). Also, three variables of knowledge collection behavior (B=0.197); knowledge use (B=0.363) and knowledge donation behavior (B=0.411) have a significant effect on the community promotion variable.
<strong>Conclusion</strong>: Considering the crucial role of primary school teachers in educating students, it is essential to plan for the optimal utilization of their specialized knowledge and experiences, as they represent a vital pillar of the education system. Additionally, it is recommended that the importance<br />of knowledge sharing be clearly communicated to teachers. By doing so, a culture of knowledge exchange will gradually be fostered among teachers. This means that educators will come to view knowledge sharing and acquisition as valuable and will be dedicated to it. Consequently, they will engage in exchanges driven by intrinsic motivation and utilize knowledge sharing as a tool for their own professional development. As a result, teachers will continuously strive to eliminate errors and obstacles, thereby enhancing their job productivity. Additionally, expert and specialist teachers can be requested to develop the necessary content in response to advancements in the educational landscape and current needs, sharing it on the Shad network. This will promote knowledge exchange among educators and contribute to the ongoing enhancement of the knowledge generated. Additionally, young and less experienced teachers can benefit from the accumulated knowledge of their more experienced counterparts without any restrictions related to time or location. In this context, the Shad Network will function as a knowledge management system or an educational knowledge repository.<strong>Purpose</strong>: Knowledge sharing is a crucial process that adds value to organizational strategy.<br />It plays an essential role in facilitating the achievement of organizational goals, supporting organizational interests, sustaining success, fostering organizational learning, enhancing performance, creating a knowledge-based competitive advantage, and ultimately benefiting the community.<br />A collaborative community in the context of cyberspace is a virtual professional network that unites individuals with shared expertise in a specific field. This environment fosters knowledge sharing, enhances the professional skills of its members, provides advanced insights, and helps address career challenges. Accordingly, this study aims to analyze the factors influencing knowledge sharing and<br />its consequences within the Shad Network, a virtual collaborative community for elementary school teachers in Khorramabad city.
<strong>Method:</strong> This research is applied in terms of purpose and descriptive-correlational in terms of data collection and structural equation type. The conceptual framework of this study is based on the conceptual model presented in Chen and Hong's (2010) research. The research population includes 2208 elementary school teachers in Khorramabad city, of which 327 were selected as the research sample using the Krejci and Morgan table using stratified random sampling. Data collection was carried out using a questionnaire. Data analysis was carried out using SPSS and SmartPLS software.
<strong>Findings</strong>: Analysis of the demographic information of the respondents showed that 237 (72.48%) of the respondents were female and 90 (27.52%) of the respondents were male. In terms of educational qualifications, 199 (60.86%) had a bachelor's degree, 118 (36.08%) had a master's degree, 7 (2.14%) had a doctorate, and three (0.92%) had an associate's degree. The descriptive index analysis of the research variables showed that the average of each of the variables of reciprocity rule, interpersonal trust, self-efficacy in knowledge sharing, perceived relative advantage, knowledge donation behavior, knowledge collection behavior, perceived compatibility, knowledge use, and knowledge promotion are 4.268, 3.882, 4.104, 4.358, 4.336, 2.900, 4.084, 4, and 3.739, respectively. The results of the structural equations of the research showed that the variables of interpersonal trust (B=0.129); perceived relative advantage (B=0.152); self-efficacy in knowledge sharing (B=0.190), and reciprocity rule (B=0.251) have a significant effect on teachers' knowledge donation behavior. Also, the variable of perceived relative advantage (B=0.449) has a significant effect on knowledge collection behavior. Teachers' knowledge donation behavior has resulted in knowledge use (B=0.423). Also, three variables of knowledge collection behavior (B=0.197); knowledge use (B=0.363) and knowledge donation behavior (B=0.411) have a significant effect on the community promotion variable.
<strong>Conclusion</strong>: Considering the crucial role of primary school teachers in educating students, it is essential to plan for the optimal utilization of their specialized knowledge and experiences, as they represent a vital pillar of the education system. Additionally, it is recommended that the importance<br />of knowledge sharing be clearly communicated to teachers. By doing so, a culture of knowledge exchange will gradually be fostered among teachers. This means that educators will come to view knowledge sharing and acquisition as valuable and will be dedicated to it. Consequently, they will engage in exchanges driven by intrinsic motivation and utilize knowledge sharing as a tool for their own professional development. As a result, teachers will continuously strive to eliminate errors and obstacles, thereby enhancing their job productivity. Additionally, expert and specialist teachers can be requested to develop the necessary content in response to advancements in the educational landscape and current needs, sharing it on the Shad network. This will promote knowledge exchange among educators and contribute to the ongoing enhancement of the knowledge generated. Additionally, young and less experienced teachers can benefit from the accumulated knowledge of their more experienced counterparts without any restrictions related to time or location. In this context, the Shad Network will function as a knowledge management system or an educational knowledge repository.https://stim.qom.ac.ir/article_2734_ba07d53759410865b57e69051431b872.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Identifying the Levels of Commercialization of Knowledge in the Iranian Higher Education System and its ValidationIdentifying the Levels of Commercialization of Knowledge in the Iranian Higher Education System and its Validation73100264910.22091/stim.2023.9918.2008FAFereshtehAlizadehPhD., Student, Department of Higher Education Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran0000-0001-7305-0998AmirhooseinMahmoodiAssistant Professor, Department of Educational Management and Higher Education, Central Tehran Branch, Islamic Azad University, Tehran, Iran0000-0003-4741-0990MahdiMahmodiAssociate Professor, Department of Educational Sciences, Payam Noor University, Tehran, Iran.0000-0003-3529-0047Journal Article20230930<strong>Purpose: </strong>The aim of this study is to identify and prioritize the levels of knowledge commercialization within the Iranian higher education system and to validate these findings.
<strong>Method</strong>: The research method employed is an exploratory mixed-method approach. To gather information, a combination of library studies and the identification of an expert group was utilized. Sixteen individuals were interviewed using a semi-structured interview tool and the snowball sampling method, ultimately achieving theoretical saturation. After conducting the interviews, examples were identified and categorized using the content analysis method. Subsequently, the identified examples from the research community, specifically professors at the Islamic Azad University of Tehran, were prioritized and validated. The validity and reliability of the qualitative component were established through the triangulation method and the test-retest index. In the quantitative component, these were confirmed by subject matter experts, Cronbach's alpha, and factor loadings.
<strong>Findings: </strong>The findings were derived from both qualitative and quantitative components. In the qualitative segment, the levels of knowledge commercialization within the country's higher education system were assessed through interviews with a group of experts. The collected information was analyzed using content analysis, which identified six comprehensive themes: environmental factors, organizational structure, characteristics of intellectual creators, characteristics of created knowledge, characteristics of knowledge consumers, and types of knowledge. Additionally, the analysis revealed 25 organizing themes and 87 basic themes. Then, in the quantitative phase, data was collected using a questionnaire distributed among the research community, specifically professors at Islamic Azad University in Tehran. The data was prioritized based on factor loadings. The analysis revealed that the theme of intellectual characteristics of intellectual creators had a coefficient of 93.9%, while the theme of specialized knowledge had a coefficient of 94.9%. Both themes were identified as the top priorities within the levels of comprehensive and organizing themes.
<strong>Conclusion: </strong>The results of the study indicate the identification of the levels of commercialization within the Iranian higher education system. The calculated factor loadings highlight the importance of considering all levels of analysis. The order of prioritization derived from these loadings underscores the need to evaluate the contribution of each instance to the variable under study, particularly in light of limited resources and the necessity for effective management.<strong>Purpose: </strong>The aim of this study is to identify and prioritize the levels of knowledge commercialization within the Iranian higher education system and to validate these findings.
<strong>Method</strong>: The research method employed is an exploratory mixed-method approach. To gather information, a combination of library studies and the identification of an expert group was utilized. Sixteen individuals were interviewed using a semi-structured interview tool and the snowball sampling method, ultimately achieving theoretical saturation. After conducting the interviews, examples were identified and categorized using the content analysis method. Subsequently, the identified examples from the research community, specifically professors at the Islamic Azad University of Tehran, were prioritized and validated. The validity and reliability of the qualitative component were established through the triangulation method and the test-retest index. In the quantitative component, these were confirmed by subject matter experts, Cronbach's alpha, and factor loadings.
<strong>Findings: </strong>The findings were derived from both qualitative and quantitative components. In the qualitative segment, the levels of knowledge commercialization within the country's higher education system were assessed through interviews with a group of experts. The collected information was analyzed using content analysis, which identified six comprehensive themes: environmental factors, organizational structure, characteristics of intellectual creators, characteristics of created knowledge, characteristics of knowledge consumers, and types of knowledge. Additionally, the analysis revealed 25 organizing themes and 87 basic themes. Then, in the quantitative phase, data was collected using a questionnaire distributed among the research community, specifically professors at Islamic Azad University in Tehran. The data was prioritized based on factor loadings. The analysis revealed that the theme of intellectual characteristics of intellectual creators had a coefficient of 93.9%, while the theme of specialized knowledge had a coefficient of 94.9%. Both themes were identified as the top priorities within the levels of comprehensive and organizing themes.
<strong>Conclusion: </strong>The results of the study indicate the identification of the levels of commercialization within the Iranian higher education system. The calculated factor loadings highlight the importance of considering all levels of analysis. The order of prioritization derived from these loadings underscores the need to evaluate the contribution of each instance to the variable under study, particularly in light of limited resources and the necessity for effective management.https://stim.qom.ac.ir/article_2649_f738c4558b428e2ace0f84ec4cfa5dac.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Identifying the Components of Data Governance in the Organizational Context: Metasynthesis of TextsIdentifying the Components of Data Governance in the Organizational Context: Metasynthesis of Texts101130214110.22091/stim.2022.7660.1705FAFarahnazFatollahzadehPhD. Student, Department of Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, IranNadjlaHaririProfessor, Department of Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, Iran0000-0003-2320-7023ArmanSajedinejadAssistant Professor, Department of Industrial Engineering, Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran0000-0001-7705-6406FahimehBabalhavaejiAssociate Professor, Department of Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, Iran.0000-0002-0247-6614RoyaPournaghiAssistant Professor, Department of Knowledge and Information Science, Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran.0000-0003-0645-4866Journal Article20211226<strong>Purpose:</strong> Data governance describes the processes for defining data policies within an organization, the processes that specify how these policies will be implemented, and establishing an organizational structure that includes data governance councils and data stewards to monitor and ensure compliance between policies and data. Data governance is a multifaceted management program, with its primary objective being to treat data as a valuable organizational asset. This is accomplished by utilizing a comprehensive framework of policies, standards, processes, personnel, and technology that are essential for effective data management. Many organizations face challenges in establishing a successful and sustainable data governance program. The initial step in enhancing the organization’s performance is to ensure that the data governance program aligns with its goals and mission. What currently exists as data governance is an abstract concept, and this abstraction hinders its effective implementation. Therefore, it is essential to first establish a clear and effective definition based on existing literature to facilitate its implementation by identifying the various components of this concept.<br /><strong>Method: </strong>This study analyzed the content of texts in the field of data governance using the meta-synthesis method. The selection of information sources was conducted purposefully, based on their relevance to the research objectives. The studies were conducted between 2000 and 2021. A total of 68 articles and theses related to this field were selected by searching reputable databases, including Emerald, Scopus, Sage, ProQuest, Springer, Web of Science, and Google Scholar. Additionally, searches were conducted in the Persian section of the Iranian Scientific Information and Documents Center, the National Library and Documentation Center of Iran, the National Publications Information Database (Iran Mag), the Humanities Portal, the Noor Specialized Magazines Database (Noormags), the Academic Jihad Scientific Information Center, and the APEC libraries of various universities, <br />such as Tehran University, Allameh Tabatabaei University, Al-Zahra University, Tarbiat Modares University, and Kharazmi University. Ultimately, the articles were purposefully selected based on the Sandusky and Barroso model and were reviewed using qualitative content analysis.<br /><strong>Findings:</strong> The research findings identified five main components of data governance: “planning,” “organization and management,” “performance,” “execution,” and “evaluation.” Each of these main components has subcomponents, resulting in a total of 32 components for data governance identified through a meta-synthesis of texts. These components significantly contribute to the definition and implementation of data governance across various organizations. According to the findings of this research, data governance encompasses planning, organizing, managing, determining performance, implementing, monitoring, and evaluating data related to different organizations. Data governance should align with the organization's mission, strategy, norms, and culture to effectively manage data as a strategic asset. It should ensure quality control and safeguard access, management, monitoring, and maintenance, with the goal of enhancing the value of the company’s data and transforming it into a competitive advantage.<br /><strong>Conclusion:</strong> By using these components, each organization can design and implement a data governance program appropriate to its context. Organizations with different expertise and contexts can modify these components according to their context adapt them to their goals and strategies, and benefit from the benefits of data governance in their organization. Regarding the application of the main and secondary components derived from the current research, organizations need to pay attention to the importance of each of them. Organizations must consider the goals and strategies of the program to implement data governance and design principles to support the structure, culture, and goals.<strong>Purpose:</strong> Data governance describes the processes for defining data policies within an organization, the processes that specify how these policies will be implemented, and establishing an organizational structure that includes data governance councils and data stewards to monitor and ensure compliance between policies and data. Data governance is a multifaceted management program, with its primary objective being to treat data as a valuable organizational asset. This is accomplished by utilizing a comprehensive framework of policies, standards, processes, personnel, and technology that are essential for effective data management. Many organizations face challenges in establishing a successful and sustainable data governance program. The initial step in enhancing the organization’s performance is to ensure that the data governance program aligns with its goals and mission. What currently exists as data governance is an abstract concept, and this abstraction hinders its effective implementation. Therefore, it is essential to first establish a clear and effective definition based on existing literature to facilitate its implementation by identifying the various components of this concept.<br /><strong>Method: </strong>This study analyzed the content of texts in the field of data governance using the meta-synthesis method. The selection of information sources was conducted purposefully, based on their relevance to the research objectives. The studies were conducted between 2000 and 2021. A total of 68 articles and theses related to this field were selected by searching reputable databases, including Emerald, Scopus, Sage, ProQuest, Springer, Web of Science, and Google Scholar. Additionally, searches were conducted in the Persian section of the Iranian Scientific Information and Documents Center, the National Library and Documentation Center of Iran, the National Publications Information Database (Iran Mag), the Humanities Portal, the Noor Specialized Magazines Database (Noormags), the Academic Jihad Scientific Information Center, and the APEC libraries of various universities, <br />such as Tehran University, Allameh Tabatabaei University, Al-Zahra University, Tarbiat Modares University, and Kharazmi University. Ultimately, the articles were purposefully selected based on the Sandusky and Barroso model and were reviewed using qualitative content analysis.<br /><strong>Findings:</strong> The research findings identified five main components of data governance: “planning,” “organization and management,” “performance,” “execution,” and “evaluation.” Each of these main components has subcomponents, resulting in a total of 32 components for data governance identified through a meta-synthesis of texts. These components significantly contribute to the definition and implementation of data governance across various organizations. According to the findings of this research, data governance encompasses planning, organizing, managing, determining performance, implementing, monitoring, and evaluating data related to different organizations. Data governance should align with the organization's mission, strategy, norms, and culture to effectively manage data as a strategic asset. It should ensure quality control and safeguard access, management, monitoring, and maintenance, with the goal of enhancing the value of the company’s data and transforming it into a competitive advantage.<br /><strong>Conclusion:</strong> By using these components, each organization can design and implement a data governance program appropriate to its context. Organizations with different expertise and contexts can modify these components according to their context adapt them to their goals and strategies, and benefit from the benefits of data governance in their organization. Regarding the application of the main and secondary components derived from the current research, organizations need to pay attention to the importance of each of them. Organizations must consider the goals and strategies of the program to implement data governance and design principles to support the structure, culture, and goals.https://stim.qom.ac.ir/article_2141_76aa027f1fc4da86bcfea43ca3ed700c.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Developing a Structural Equation Model to Predict Health Knowledge of Users of the central Public library of Tehran Province Based on Sources of Health Information Acquisition and
the Mediating Role of Coping StylesDeveloping a Structural Equation Model to Predict Health Knowledge of Users of the central Public library of Tehran Province Based on Sources of Health Information Acquisition and
the Mediating Role of Coping Styles131152278610.22091/stim.2024.10032.2024FAMaryamGhanbari KhoshnoodPhD., Student, Department of Medical Library and Information Science, Faculty of Medical Management and Information Science, Isfahan University of Medical Sciences, Isfahan, Iran.0000-0002-2578-0918ZeinabSafaviPhD, Department of Knowledge and Information Science, Faculty of Educational Sciences and Psychology, Alzahra University, Tehran, Iran8755-0296-0003-0000RahmanEbrahimiPhD., Department of Knowledge and Information Science, Faculty of Educational Sciences and Psychology, Kharazmi University, Alborz, Iran0000-0001-7055-4541Journal Article20231028<strong>Purpose:</strong> Coping styles are considered as predictors of an individual's ability to obtain information related to health and personal care. More specifically, a person's coping style in accessing, accurately understanding, and utilizing health information sources significantly influences their knowledge and overall health status. The present study aimed to develop a structural equation model to predict the health knowledge of users at the Central Public Library of Tehran Province, based on health information sources and the mediating role of coping styles.
<strong>Method:</strong> The present study is applied in purpose and is of a survey type. The study population consists of users of the Central Public Library of Tehran Province. In accordance with the sample size determination in structural equation modeling methodology, the minimum sample size for this study was calculated to be 260. After confirming the validity of the "Health Knowledge" questionnaire with the input of five professors in information science and knowledge studies, its reliability was assessed through the participation of 30 individuals from the research community. The Cronbach's alpha coefficient was calculated to be 0.858. Out of 260 distributed questionnaires, 248 were returned<br />and utilized for data analysis. The data collection instruments included the Standard Coping Styles Questionnaire (Andler & Parker, 1994), the Standard Health Information Sources Questionnaire (Mousavi-Chalak & Riahi, 2017), and a researcher-developed Health Knowledge Questionnaire. SPSS software was employed to analyze the demographic characteristics of the research population and to present descriptive findings, while Smart PLS software and structural equation modeling were used to test the hypotheses.
<strong>Findings:</strong> The sources of health information acquisition of users of the Central Public Library of Tehran Province have a direct effect on their health knowledge. Therefore, the first hypothesis was approved. The coping styles of users of the Central Public Library of Tehran Province have a direct effect on their health knowledge, and thus the second hypothesis of the study was also confirmed. The main sources of health information for users of the Central Public Library of Tehran Province, in order of priority, are: doctors, nurses, and health professionals, visiting local health centers and clinics, free websites and electronic health resources, and electronic resources and books. In addition, the results showed that the participants in the study used the least to obtain health information from attending conferences and workshops, printed books, web-based social networks, and seeking help from librarians and information specialists.
<strong>Conclusion</strong>: According to the findings, doctors, nurses, and health professionals are the main sources of health information for users of the Central Public Library of Tehran Province. This indicates that users make informed decisions by consulting health professionals during crises and when the health of the community is at risk.
Given the geographical location of the Central Public Library of Tehran Province, which provides access to medical centers, and considering the educated community of library users in terms of their education and social status, it is reasonable to expect that they will seek assistance from health professionals to fulfill their health information needs. It is evident that, under such circumstances, the likelihood of utilizing librarians to access health information is minimal. Conducting a study similar to the present one in underserved areas underscores the significance of the library's geographic location in influencing users' engagement with health information resources. The findings of the current study can be utilized to enhance the health knowledge of public library users. By identifying the psychological characteristics of users and considering their coping styles and the most frequently used resources, we can provide adequate information through these resources and uncover the existing barriers that prevent users from accessing alternative sources of knowledge acquisition.<strong>Purpose:</strong> Coping styles are considered as predictors of an individual's ability to obtain information related to health and personal care. More specifically, a person's coping style in accessing, accurately understanding, and utilizing health information sources significantly influences their knowledge and overall health status. The present study aimed to develop a structural equation model to predict the health knowledge of users at the Central Public Library of Tehran Province, based on health information sources and the mediating role of coping styles.
<strong>Method:</strong> The present study is applied in purpose and is of a survey type. The study population consists of users of the Central Public Library of Tehran Province. In accordance with the sample size determination in structural equation modeling methodology, the minimum sample size for this study was calculated to be 260. After confirming the validity of the "Health Knowledge" questionnaire with the input of five professors in information science and knowledge studies, its reliability was assessed through the participation of 30 individuals from the research community. The Cronbach's alpha coefficient was calculated to be 0.858. Out of 260 distributed questionnaires, 248 were returned<br />and utilized for data analysis. The data collection instruments included the Standard Coping Styles Questionnaire (Andler & Parker, 1994), the Standard Health Information Sources Questionnaire (Mousavi-Chalak & Riahi, 2017), and a researcher-developed Health Knowledge Questionnaire. SPSS software was employed to analyze the demographic characteristics of the research population and to present descriptive findings, while Smart PLS software and structural equation modeling were used to test the hypotheses.
<strong>Findings:</strong> The sources of health information acquisition of users of the Central Public Library of Tehran Province have a direct effect on their health knowledge. Therefore, the first hypothesis was approved. The coping styles of users of the Central Public Library of Tehran Province have a direct effect on their health knowledge, and thus the second hypothesis of the study was also confirmed. The main sources of health information for users of the Central Public Library of Tehran Province, in order of priority, are: doctors, nurses, and health professionals, visiting local health centers and clinics, free websites and electronic health resources, and electronic resources and books. In addition, the results showed that the participants in the study used the least to obtain health information from attending conferences and workshops, printed books, web-based social networks, and seeking help from librarians and information specialists.
<strong>Conclusion</strong>: According to the findings, doctors, nurses, and health professionals are the main sources of health information for users of the Central Public Library of Tehran Province. This indicates that users make informed decisions by consulting health professionals during crises and when the health of the community is at risk.
Given the geographical location of the Central Public Library of Tehran Province, which provides access to medical centers, and considering the educated community of library users in terms of their education and social status, it is reasonable to expect that they will seek assistance from health professionals to fulfill their health information needs. It is evident that, under such circumstances, the likelihood of utilizing librarians to access health information is minimal. Conducting a study similar to the present one in underserved areas underscores the significance of the library's geographic location in influencing users' engagement with health information resources. The findings of the current study can be utilized to enhance the health knowledge of public library users. By identifying the psychological characteristics of users and considering their coping styles and the most frequently used resources, we can provide adequate information through these resources and uncover the existing barriers that prevent users from accessing alternative sources of knowledge acquisition.https://stim.qom.ac.ir/article_2786_f565af0b6e24c3e7a9f59d8e4b07f989.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Evaluation of the Websites of Specialized Journals
in the Field of Information Science and KnowledgeEvaluation of the Websites of Specialized Journals
in the Field of Information Science and Knowledge153172308410.22091/stim.2024.11239.2152FATaherehGholamiLecturer, Department of Knowledge and Information Science, University of Qom, Qom, Iran.0000-0002-2296-8018Journal Article20240824<strong>Purpose</strong>: The present study aims to examine the visual, structural, and content characteristics of the websites of Persian-language journals in the field of information science and knowledge in Iran. This study employs a survey research method with a descriptive approach to assess the status of websites belonging to specialized journals in the field of information science and knowledge in Iran.
<strong>Method</strong>: Data collection was conducted using a researcher-developed checklist tool divided into three sections: appearance criteria, structural criteria, and content criteria. The three-dimensional evaluation of the websites in question was conducted by the researcher, who directly referenced each journal's website and employed the observation method. Data analysis was performed using SPSS software.
<strong>Findings</strong>: The comparison of the three-dimensional features analyzed on the publications' websites revealed that they were in a desirable, acceptable, and satisfactory state, respectively, regarding their structural, content, and aesthetic components. The components of search links, including those found in general search engines, chat rooms, website advertisements, and the website's creation date, received the lowest scores among the structural elements. The lack of attention to the elements that facilitate searching within general search engines from the publication's website, the components that foster user interaction and incorporate their feedback into policymaking, and the factors related to building the audience's trust in the publication's credibility were significant weaknesses observed in the structural category of the publications' websites. In terms of content features, the lowest scores were attributed to the components of article titles in Arabic, article titles in other languages, and the acknowledgment of the sources of the website's content, all of which received no points. In the section on appearance features, items such as inserting a logo, noting title changes, and including a short title should also be considered. The lowest scores were attributed to the components of accompanying content, such as sound, video, images, photos, and charts, which were not present on any of the websites studied.
<strong>Conclusion</strong>: Websites serve as an effective tool for facilitating communication between publications and their audiences interested in education and research. In this study, we found that the websites examined are in a favorable condition regarding their structure and content, while their appearance is deemed acceptable. However, all three components reveal weaknesses that the publication's staff should address and rectify.<strong>Purpose</strong>: The present study aims to examine the visual, structural, and content characteristics of the websites of Persian-language journals in the field of information science and knowledge in Iran. This study employs a survey research method with a descriptive approach to assess the status of websites belonging to specialized journals in the field of information science and knowledge in Iran.
<strong>Method</strong>: Data collection was conducted using a researcher-developed checklist tool divided into three sections: appearance criteria, structural criteria, and content criteria. The three-dimensional evaluation of the websites in question was conducted by the researcher, who directly referenced each journal's website and employed the observation method. Data analysis was performed using SPSS software.
<strong>Findings</strong>: The comparison of the three-dimensional features analyzed on the publications' websites revealed that they were in a desirable, acceptable, and satisfactory state, respectively, regarding their structural, content, and aesthetic components. The components of search links, including those found in general search engines, chat rooms, website advertisements, and the website's creation date, received the lowest scores among the structural elements. The lack of attention to the elements that facilitate searching within general search engines from the publication's website, the components that foster user interaction and incorporate their feedback into policymaking, and the factors related to building the audience's trust in the publication's credibility were significant weaknesses observed in the structural category of the publications' websites. In terms of content features, the lowest scores were attributed to the components of article titles in Arabic, article titles in other languages, and the acknowledgment of the sources of the website's content, all of which received no points. In the section on appearance features, items such as inserting a logo, noting title changes, and including a short title should also be considered. The lowest scores were attributed to the components of accompanying content, such as sound, video, images, photos, and charts, which were not present on any of the websites studied.
<strong>Conclusion</strong>: Websites serve as an effective tool for facilitating communication between publications and their audiences interested in education and research. In this study, we found that the websites examined are in a favorable condition regarding their structure and content, while their appearance is deemed acceptable. However, all three components reveal weaknesses that the publication's staff should address and rectify.https://stim.qom.ac.ir/article_3084_3b0789b869f6e965dcd781fdb967d8cd.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Measuring the Concept of Responsible
Research and Innovation and its Role in Alleviating or Solving Societal IssuesMeasuring the Concept of Responsible
Research and Innovation and its Role in Alleviating or Solving Societal Issues173194295510.22091/stim.2024.10594.2085FAAkbarMohammadiAssistant Professor, Faculty of Commerce and Business, University of Tehran, Tehran, Iran.0000-0002-4621-8107SaharBabaeiAssistant Professor, Faculty of Governance, University of Tehran, Tehran, Iran0000-0002-1017-4181MohammadiRezaAttarpourAssistant Professor, Institute of Business Studies and Research, Tehran, Iran.0000-0001-6258-5786Journal Article20240407<strong>Purpose:</strong> Responsible research and innovation is a transparent and interactive process involving active participants in the fields of science, technology, and innovation. This process emphasizes moral acceptability, sustainability, and social desirability, holding all stakeholders accountable to one another. The goal is to institutionalize scientific and technological advancements within society and to address or mitigate societal challenges associated with these innovations. Given the growing complexity of social systems, the escalating nature of their problems and challenges, and the necessity for societies to address these issues, the role of research and innovation in tackling societal challenges is increasingly vital. In this context, the contributions of universities, research institutes, think tanks, and other scientific organizations are essential. Responsible research and innovation is a policy framework designed to align research and technological innovation with societal values. It engages various stakeholders in a multidimensional dialogue on key issues, including ethics, scientific education, open access to science, and social participation. Therefore, the aim of this study is to examine the evolution of the concept of responsible research and innovation and its effectiveness in addressing or mitigating societal problems.<br /><strong>Method</strong>: The present study is a comprehensive scientometric analysis in the field of innovation and responsible research. In the initial phase, the concept of research and innovation was examined using data from the Web of Science and an analysis of authoritative ISI articles published over the last three decades. In the next step, following the initial screening and identification of relevant articles based on their titles, abstracts, and content, the final articles were analyzed using an analytical process package called Bibliometrics in R software. This analytical process package is a tool for quantitative research in the field of scientometrics, designed for the statistical analysis of articles extracted from citation databases. These statistical analyses, which were also employed in the present study, focused on examining scientific collaborations among researchers, co-citations, and synergies between scientific activities. Finally, based on the qualitative assessment of the selected and screened articles, the results obtained were compared with those from the scientometric analysis, leading to the introduction of new concepts.<br /><strong>Findings</strong>: The analyses conducted in this study show that different groups are interdependent in terms of responsibility and the importance of being in tune between them is emphasized. In addition, basic concepts such as public participation, sustainability, ethics, governance, and responsible research and innovation are evolutionary concepts in this field of knowledge from literature. In this study, selected articles identified from different textual dimensions and the emergence of new concepts were analyzed, and finally, 33 concepts were identified in 8 different themes. Also, based on scientometric analysis and word occurrence analysis, 10 frequently used words were identified. Finally, a joint review identified and introduced 5 key concepts for this field. These 5 concepts include public participation, sustainability, ethics, governance, and responsible research and innovation.<br /><strong>Conclusion</strong>: This study showed that the literature on responsible research and innovation has grown and evolved with a significant trend in recent years. The findings of this study can provide a clear path for the evolution of the field of innovation and responsible research, both at the level of academic research and corporate experiences and also provide deep insights into the path of evolution of the field of research and innovation and its responsibility towards society. According to the results of the quantitative and scientometric analyses of this study, the emergence of concepts such as nanotechnology and synthetic biology indicates the scope of responsible research in technological sectors and indicates the transition of research paradigms towards ethics and sustainable development. These analyses also help to understand the historical origins, trends, and future directions of responsible research and innovation, and provide valuable guidance for politicians and individuals interested in promoting innovative planning and policies.<br /> <strong>Purpose:</strong> Responsible research and innovation is a transparent and interactive process involving active participants in the fields of science, technology, and innovation. This process emphasizes moral acceptability, sustainability, and social desirability, holding all stakeholders accountable to one another. The goal is to institutionalize scientific and technological advancements within society and to address or mitigate societal challenges associated with these innovations. Given the growing complexity of social systems, the escalating nature of their problems and challenges, and the necessity for societies to address these issues, the role of research and innovation in tackling societal challenges is increasingly vital. In this context, the contributions of universities, research institutes, think tanks, and other scientific organizations are essential. Responsible research and innovation is a policy framework designed to align research and technological innovation with societal values. It engages various stakeholders in a multidimensional dialogue on key issues, including ethics, scientific education, open access to science, and social participation. Therefore, the aim of this study is to examine the evolution of the concept of responsible research and innovation and its effectiveness in addressing or mitigating societal problems.<br /><strong>Method</strong>: The present study is a comprehensive scientometric analysis in the field of innovation and responsible research. In the initial phase, the concept of research and innovation was examined using data from the Web of Science and an analysis of authoritative ISI articles published over the last three decades. In the next step, following the initial screening and identification of relevant articles based on their titles, abstracts, and content, the final articles were analyzed using an analytical process package called Bibliometrics in R software. This analytical process package is a tool for quantitative research in the field of scientometrics, designed for the statistical analysis of articles extracted from citation databases. These statistical analyses, which were also employed in the present study, focused on examining scientific collaborations among researchers, co-citations, and synergies between scientific activities. Finally, based on the qualitative assessment of the selected and screened articles, the results obtained were compared with those from the scientometric analysis, leading to the introduction of new concepts.<br /><strong>Findings</strong>: The analyses conducted in this study show that different groups are interdependent in terms of responsibility and the importance of being in tune between them is emphasized. In addition, basic concepts such as public participation, sustainability, ethics, governance, and responsible research and innovation are evolutionary concepts in this field of knowledge from literature. In this study, selected articles identified from different textual dimensions and the emergence of new concepts were analyzed, and finally, 33 concepts were identified in 8 different themes. Also, based on scientometric analysis and word occurrence analysis, 10 frequently used words were identified. Finally, a joint review identified and introduced 5 key concepts for this field. These 5 concepts include public participation, sustainability, ethics, governance, and responsible research and innovation.<br /><strong>Conclusion</strong>: This study showed that the literature on responsible research and innovation has grown and evolved with a significant trend in recent years. The findings of this study can provide a clear path for the evolution of the field of innovation and responsible research, both at the level of academic research and corporate experiences and also provide deep insights into the path of evolution of the field of research and innovation and its responsibility towards society. According to the results of the quantitative and scientometric analyses of this study, the emergence of concepts such as nanotechnology and synthetic biology indicates the scope of responsible research in technological sectors and indicates the transition of research paradigms towards ethics and sustainable development. These analyses also help to understand the historical origins, trends, and future directions of responsible research and innovation, and provide valuable guidance for politicians and individuals interested in promoting innovative planning and policies.<br /> https://stim.qom.ac.ir/article_2955_1d492098ba72a77819818f424ee19d0b.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Identify the Effective Factors of
Improving Relevance in Information
Retrieval in Scientific Social NetworksIdentify the Effective Factors of
Improving Relevance in Information
Retrieval in Scientific Social Networks195220218210.22091/stim.2021.6132.1465FAMajidShirzadAssistant Professor, Department of Knowledge and Information Science, Payam Noor University, Tehran, Iran.0000-0002-4817-4355AfshinMousaviAssociate Professor, Department of Knowledge and Information Science, Payam Noor University, Tehran, Iran0000-0002-5614-1334SorayaZiaeiAssociate Professor, Department of Knowledge and Information Science, Payam Noor University, Tehran, Iran0000-0003-3134-1468FaramarzSohieliAssociate Professor, Department of Knowledge and Information Science, Payam Noor University, Tehran, Iran.0000-0003-2581-7052MariamSalamiAssociate Professor, Department of Knowledge and Information Science, Payam Noor University, Tehran, Iran0000-0002-1772-6751Journal Article20201029<strong>Purpose:</strong> The purpose of this study was to identify the factors affecting the improvement of relevance in information retrieval, as perceived by faculty members of the Department of Information Science and Knowledge in the Humanities and Medical Librarianship departments, within the scientific social networks of LinkedIn and ResearchGate.
<strong>Method: </strong>This research is applied in nature and was conducted using a survey methodology.<br />The study population sizes in the three departments—Humanities, Medical Librarianship, and Comprehensive Sciences—are 110, 102, and 207 individuals, respectively. Based on the Cochran formula, the sample sizes for statistical analysis are 86, 81, and 135 individuals, respectively, all of whom have utilized the scientific networks LinkedIn and ResearchGate. The selection of these two scientific networks was based on their higher number of referrals and the involvement of several experts. To assess the reliability of the questionnaire, Cronbach's alpha coefficient was employed. Additionally, the composite reliability method was utilized to evaluate the reliability of the constructs. To establish the validity of the questionnaire, input from various experts and specialists in management, library and information science, and sociology was considered. The extracted mean variance index was used to measure validity (credibility). The analysis of the structural model fit was conducted through confirmatory factor analysis and equation modeling, utilizing SmartPLS software.
<strong>Findings</strong><strong>: </strong>The results of the regression analysis indicate that among the research components, the presence of feedback, with a coefficient of 0.775, has the most significant impact on relevance and its enhancement in information retrieval within the LinkedIn database. Following the feedback variable, the variables of requests and questions, user characteristics, and database characteristics rank next, with coefficients of 0.515, 0.492, and 0.471, respectively. In the meantime, the information system does not demonstrate a significant effect. However, based on the results of the regression analysis, among the research components, the presence of feedback, with a coefficient of 0.812, has the most substantial impact on relevance and its enhancement in information retrieval within the ResearchGate database. Following the feedback variable, the variables of document characteristics, user characteristics, and requests and questions rank next, with coefficients of 0.726, 0.608, and 0.541, respectively. Overall, the information system and retrieval system do not exhibit a significant effect.
<strong>Conclusion: </strong>Based on the comprehensive research model, the effective factors identified in scientific social networks, such as the information system and retrieval system, can be regarded as a holistic framework for enhancing the relevance of information retrieval in these networks.<strong>Purpose:</strong> The purpose of this study was to identify the factors affecting the improvement of relevance in information retrieval, as perceived by faculty members of the Department of Information Science and Knowledge in the Humanities and Medical Librarianship departments, within the scientific social networks of LinkedIn and ResearchGate.
<strong>Method: </strong>This research is applied in nature and was conducted using a survey methodology.<br />The study population sizes in the three departments—Humanities, Medical Librarianship, and Comprehensive Sciences—are 110, 102, and 207 individuals, respectively. Based on the Cochran formula, the sample sizes for statistical analysis are 86, 81, and 135 individuals, respectively, all of whom have utilized the scientific networks LinkedIn and ResearchGate. The selection of these two scientific networks was based on their higher number of referrals and the involvement of several experts. To assess the reliability of the questionnaire, Cronbach's alpha coefficient was employed. Additionally, the composite reliability method was utilized to evaluate the reliability of the constructs. To establish the validity of the questionnaire, input from various experts and specialists in management, library and information science, and sociology was considered. The extracted mean variance index was used to measure validity (credibility). The analysis of the structural model fit was conducted through confirmatory factor analysis and equation modeling, utilizing SmartPLS software.
<strong>Findings</strong><strong>: </strong>The results of the regression analysis indicate that among the research components, the presence of feedback, with a coefficient of 0.775, has the most significant impact on relevance and its enhancement in information retrieval within the LinkedIn database. Following the feedback variable, the variables of requests and questions, user characteristics, and database characteristics rank next, with coefficients of 0.515, 0.492, and 0.471, respectively. In the meantime, the information system does not demonstrate a significant effect. However, based on the results of the regression analysis, among the research components, the presence of feedback, with a coefficient of 0.812, has the most substantial impact on relevance and its enhancement in information retrieval within the ResearchGate database. Following the feedback variable, the variables of document characteristics, user characteristics, and requests and questions rank next, with coefficients of 0.726, 0.608, and 0.541, respectively. Overall, the information system and retrieval system do not exhibit a significant effect.
<strong>Conclusion: </strong>Based on the comprehensive research model, the effective factors identified in scientific social networks, such as the information system and retrieval system, can be regarded as a holistic framework for enhancing the relevance of information retrieval in these networks.https://stim.qom.ac.ir/article_2182_0de1edbae10d2c4228b91e4ea2891b98.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Designing and Explaining a Model for Factors Affecting Technological Innovation Capabilities
(A Case Study: Iran Public Libraries Institution)Designing and Explaining a Model for Factors Affecting Technological Innovation Capabilities
(A Case Study: Iran Public Libraries Institution)221240205610.22091/stim.2021.6281.1488FAAbbasHosseinzadehPhD., Department of Knowledge and Information Science, Babol Branch, Islamic Azad University, Babol, Iran.SafiyehTahmasebi LimooniAssociate Professor, Department of Knowledge and Information Science, Babol Branch, Islamic Azad University, Babol, Iran0000-0002-1203-9303Seyed Ali AsgharRazaviAssociate Professor, Department of Knowledge and Information Science, Babol Branch, Islamic Azad University, Babol, Iran0000-0002-9386-1429Journal Article20201127<strong>Purpose:</strong> Developing technological capabilities is essential for the industrial progress of nations, and each country formulates strategies to enhance these capabilities based on its specific needs. Organizations must also engage in technological innovation to develop unique products and services that create market benefits. This is only achievable by relying on credible sources of knowledge. In this context, the current study aims to identify and explain the factors influencing technological innovation capabilities within the public library system of the country.<br /><strong>Method</strong>: This research is exploratory in purpose and fundamental in its intended audience. It employs a mixed-methods approach, utilizing both qualitative and quantitative data. In this methodology, qualitative data is collected and analyzed first, followed by the collection and analysis of quantitative data in the second stage. The statistical population for the qualitative component of the research consists of executive experts who possess a comprehensive understanding of the public library system in the country. The sampling method employed in this qualitative phase is purposive sampling. Consequently, individuals with expertise and experience in the operations, activities, and affairs of the public library system should be interviewed. After conducting 15 interviews, the researchers concluded that the information gathered had reached a saturation point, indicating that no further interviews were necessary. The statistical population for the quantitative phase of the study comprises all librarians in public libraries nationwide, totaling 6,171 individuals. Using the Cochran formula, the sample size was determined to be 362 participants. Considering an error margin of 0.05 percent and the potential non-return of some questionnaires, a total of 382 questionnaires were distributed. All questionnaires were subsequently collected and analyzed. The sampling method used in the quantitative phase was stratified random sampling. Each province of the country was treated as a distinct class, with the number of samples from each province determined by the number of employees in the public library institution located there. In the first phase of the research, which was qualitative, data were collected through semi-structured in-depth interviews. In the second phase, which was quantitative, a researcher-developed questionnaire was utilized. This questionnaire comprises 85 items and was designed based on the findings from the qualitative phase of the research. The validity of the research tools, specifically the interview and questionnaire, was assessed and confirmed using the content validity method. The reliability of the interviews was evaluated and confirmed through the test-retest method, yielding a coefficient of 0.87. Additionally, the reliability of the questionnaire was examined and confirmed using Cronbach's alpha, resulting in a coefficient of 0.948. To validate the qualitative data obtained from the interviews, thematic analysis was employed. For analyzing the quantitative data gathered from the questionnaires, confirmatory factor analysis was utilized.<br /><strong>Findings</strong>: Technological innovation capabilities are influenced by six key factors: education and learning, research and development, management, human resources, market analysis, and organizational structure. The management factor, with a factor loading of 0.951, has the most significant impact on technological innovation capabilities, while the education and learning factor, with a factor loading<br />of 0.794, has the least effect. Additionally, factors such as education and learning, research and development, management, human resources, market analysis, and organizational structure significantly influence the technological innovation capabilities of the country's public libraries. The proposed model also demonstrates a strong fit.<br /><strong>Conclusion:</strong> The results of the study indicate that six factors—education and learning, research<br />and development, management, human resources, market analysis, and organizational structure—significantly impact the technological innovation capabilities of public library institutions in the country. Research and development activities yield positive outcomes when supported by education and learning. Without adequate human resources, emerging technologies are unlikely to be embraced. If the organizational structure is designed to account for environmental changes, and market analysis is supported by feedback systems that address the needs of stakeholders, it will foster the development and enhancement of technological innovation capabilities. Therefore, the results of this study can assist managers in planning strategies to enhance and promote the technological innovation capabilities of employees in public library institutions. By identifying the key dimensions of these capabilities and improving them, organizations can create an environment conducive to employee growth, which ultimately contributes to the overall growth of the organization.<br /> <strong>Purpose:</strong> Developing technological capabilities is essential for the industrial progress of nations, and each country formulates strategies to enhance these capabilities based on its specific needs. Organizations must also engage in technological innovation to develop unique products and services that create market benefits. This is only achievable by relying on credible sources of knowledge. In this context, the current study aims to identify and explain the factors influencing technological innovation capabilities within the public library system of the country.<br /><strong>Method</strong>: This research is exploratory in purpose and fundamental in its intended audience. It employs a mixed-methods approach, utilizing both qualitative and quantitative data. In this methodology, qualitative data is collected and analyzed first, followed by the collection and analysis of quantitative data in the second stage. The statistical population for the qualitative component of the research consists of executive experts who possess a comprehensive understanding of the public library system in the country. The sampling method employed in this qualitative phase is purposive sampling. Consequently, individuals with expertise and experience in the operations, activities, and affairs of the public library system should be interviewed. After conducting 15 interviews, the researchers concluded that the information gathered had reached a saturation point, indicating that no further interviews were necessary. The statistical population for the quantitative phase of the study comprises all librarians in public libraries nationwide, totaling 6,171 individuals. Using the Cochran formula, the sample size was determined to be 362 participants. Considering an error margin of 0.05 percent and the potential non-return of some questionnaires, a total of 382 questionnaires were distributed. All questionnaires were subsequently collected and analyzed. The sampling method used in the quantitative phase was stratified random sampling. Each province of the country was treated as a distinct class, with the number of samples from each province determined by the number of employees in the public library institution located there. In the first phase of the research, which was qualitative, data were collected through semi-structured in-depth interviews. In the second phase, which was quantitative, a researcher-developed questionnaire was utilized. This questionnaire comprises 85 items and was designed based on the findings from the qualitative phase of the research. The validity of the research tools, specifically the interview and questionnaire, was assessed and confirmed using the content validity method. The reliability of the interviews was evaluated and confirmed through the test-retest method, yielding a coefficient of 0.87. Additionally, the reliability of the questionnaire was examined and confirmed using Cronbach's alpha, resulting in a coefficient of 0.948. To validate the qualitative data obtained from the interviews, thematic analysis was employed. For analyzing the quantitative data gathered from the questionnaires, confirmatory factor analysis was utilized.<br /><strong>Findings</strong>: Technological innovation capabilities are influenced by six key factors: education and learning, research and development, management, human resources, market analysis, and organizational structure. The management factor, with a factor loading of 0.951, has the most significant impact on technological innovation capabilities, while the education and learning factor, with a factor loading<br />of 0.794, has the least effect. Additionally, factors such as education and learning, research and development, management, human resources, market analysis, and organizational structure significantly influence the technological innovation capabilities of the country's public libraries. The proposed model also demonstrates a strong fit.<br /><strong>Conclusion:</strong> The results of the study indicate that six factors—education and learning, research<br />and development, management, human resources, market analysis, and organizational structure—significantly impact the technological innovation capabilities of public library institutions in the country. Research and development activities yield positive outcomes when supported by education and learning. Without adequate human resources, emerging technologies are unlikely to be embraced. If the organizational structure is designed to account for environmental changes, and market analysis is supported by feedback systems that address the needs of stakeholders, it will foster the development and enhancement of technological innovation capabilities. Therefore, the results of this study can assist managers in planning strategies to enhance and promote the technological innovation capabilities of employees in public library institutions. By identifying the key dimensions of these capabilities and improving them, organizations can create an environment conducive to employee growth, which ultimately contributes to the overall growth of the organization.<br /> https://stim.qom.ac.ir/article_2056_b0eac97bf703884cbcb10f6afc4c06a7.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Information Management in Investigating
the Role of Inflation and Exchange Rate on Foreign Direct Investment during 2003-2023Information Management in Investigating
the Role of Inflation and Exchange Rate on Foreign Direct Investment during 2003-2023241271310710.22091/stim.2024.11438.2168FAMohammadSharbatiPhD. Student, Department of Economics, Qeshm Branch, Islamic Azad University, Qeshm, Iran0000-0003-2370-5284Seyed YaqoubZeraatkishAssociate Professor, Department of Agricultural Economics, Faculty of Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran0000-0002-4180-8378MohammadMohebiAssociate Professor, Department of Economics, Faculty of Management and Economics, University of Hormozgan, Bandar Abbas, Iran0000-0001-6667-6941EbrahimNegahdariAssistant Professor, Department of Economics, Faculty of Humanities, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran0000-0002-0129-5096Journal Article20241010<strong>Purpose:</strong> The present study aims to investigate the impact of inflation and exchange rate fluctuations on the attraction of foreign direct investment (FDI) in Iran, utilizing the Copula modeling approach. This study aims to offer a fresh perspective on the intricate and nonlinear relationship between these economic variables and foreign investment in Iran. This study was conducted using data related to foreign direct investment, inflation rates, and exchange rates during the period from 2003 to 2023.
<strong>Method:</strong> The data were collected from reliable domestic and international sources and subsequently analyzed using the Copula method, which enables the modeling of complex dependencies between variables. In this context, 25 types of copula functions, including Clayton and Joe-Frank rotational functions, were employed to analyze the dependence among inflation, exchange rates, and foreign direct investment. The parameters of these functions were estimated and evaluated using Bayesian methods and Markov Chain Monte Carlo (MCMC) simulations.
<strong>Findings:</strong> The results of this study indicate that the relationship between inflation and exchange rates in relation to foreign direct investment (FDI) attraction is asymmetric and nonlinear. Furthermore, an increase in inflation is associated with a significant decrease in foreign investment. Additionally, fluctuations in exchange rates, as an economic risk factor, negatively impact foreign investors' decision-making and have diminished their willingness to invest in Iran. The results of copula modeling indicated that the Clayton function most effectively models the relationship between inflation and foreign direct investment (FDI) attraction, while the Joe-Frank rotational function is more appropriate for analyzing the relationship between exchange rates and FDI. Evaluation criteria include maximum likelihood, the Akaike Information Criterion (AIC), and the minimum root-mean-square error (RMSE), which indicate the accuracy of these functions in modeling the data under investigation.
<strong>Conclusion:</strong> The results indicate that inflation and the exchange rate have a significant negative impact on attracting foreign direct investment in Iran. High inflation, as a destabilizing factor, diminishes the appeal of investment, while exchange rate fluctuations, viewed as a significant economic risk, pose a barrier to foreign investors' entry. Copula analysis further emphasizes the asymmetric and intricate dependencies among these variables. As a result, Iranian economic policymakers can create a more favorable environment for attracting foreign investment by effectively managing the inflation rate and stabilizing the exchange rate. Future studies should consider shorter time periods and additional factors, such as interest rates and political stability, to gain a more accurate understanding of how these elements influence foreign investment attraction.
<strong>Purpose:</strong> The present study aims to investigate the impact of inflation and exchange rate fluctuations on the attraction of foreign direct investment (FDI) in Iran, utilizing the Copula modeling approach. This study aims to offer a fresh perspective on the intricate and nonlinear relationship between these economic variables and foreign investment in Iran. This study was conducted using data related to foreign direct investment, inflation rates, and exchange rates during the period from 2003 to 2023.
<strong>Method:</strong> The data were collected from reliable domestic and international sources and subsequently analyzed using the Copula method, which enables the modeling of complex dependencies between variables. In this context, 25 types of copula functions, including Clayton and Joe-Frank rotational functions, were employed to analyze the dependence among inflation, exchange rates, and foreign direct investment. The parameters of these functions were estimated and evaluated using Bayesian methods and Markov Chain Monte Carlo (MCMC) simulations.
<strong>Findings:</strong> The results of this study indicate that the relationship between inflation and exchange rates in relation to foreign direct investment (FDI) attraction is asymmetric and nonlinear. Furthermore, an increase in inflation is associated with a significant decrease in foreign investment. Additionally, fluctuations in exchange rates, as an economic risk factor, negatively impact foreign investors' decision-making and have diminished their willingness to invest in Iran. The results of copula modeling indicated that the Clayton function most effectively models the relationship between inflation and foreign direct investment (FDI) attraction, while the Joe-Frank rotational function is more appropriate for analyzing the relationship between exchange rates and FDI. Evaluation criteria include maximum likelihood, the Akaike Information Criterion (AIC), and the minimum root-mean-square error (RMSE), which indicate the accuracy of these functions in modeling the data under investigation.
<strong>Conclusion:</strong> The results indicate that inflation and the exchange rate have a significant negative impact on attracting foreign direct investment in Iran. High inflation, as a destabilizing factor, diminishes the appeal of investment, while exchange rate fluctuations, viewed as a significant economic risk, pose a barrier to foreign investors' entry. Copula analysis further emphasizes the asymmetric and intricate dependencies among these variables. As a result, Iranian economic policymakers can create a more favorable environment for attracting foreign investment by effectively managing the inflation rate and stabilizing the exchange rate. Future studies should consider shorter time periods and additional factors, such as interest rates and political stability, to gain a more accurate understanding of how these elements influence foreign investment attraction.
https://stim.qom.ac.ir/article_3107_4f049c76abf8076ef7ea5b05226f5eb6.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Organizational Governance from the Clarivate PerspectiveOrganizational Governance from the Clarivate Perspective273298267410.22091/stim.2024.10093.2037FAAliShabaniAssistant Professor, Department of Knowledge and Information Science, Faculty of Management, University of Tehran, Tehran, Iran.0000-0001-7323-4332AliSharafiPhD., Department of Knowledge and Information Science, Faculty of Management, University of Tehran, Tehran, Iran0000-0002-3366-5995Journal Article20231121<strong>Purpose:</strong> Organizational governance encompasses the structures, processes, and methodologies employed by an organization to communicate, direct, organize, and control its activities. Serving as a mechanism for knowledge integration and sharing, organizational governance establishes channels for disseminating knowledge, fostering cooperation among members, and empowering individuals to create, acquire, and share knowledge. It involves leveraging appropriate technologies for storing, transferring, and sharing knowledge, along with continuous monitoring and evaluation of knowledge management processes. Building an organizational culture rooted in trust and knowledge sharing is essential, especially when individuals are willing to share their knowledge. Essentially, organizational governance plays a pivotal role in enhancing organizational excellence at all levels of the organization. It contributes to heightened productivity, efficiency, and effectiveness by promoting better organization, facilitating accurate communication, improving risk management, and providing enhanced access to human and financial resources through the application of effective governance methods. Successful organizational governance necessitates informed policy-making, and a thorough analysis of research in this domain can drive progress. Therefore, the purpose of this research is to analyze the trends in published scientific literature on organizational governance within the Clarivate Database.<br /><strong>Method:</strong> This applied research utilizes a descriptive method and a scientometric approach to analyze the trends in scientific publications on organizational governance within the Web of Science reference database. The statistical population comprises 249 scientific outputs published between 1981 and 2021 in the Clarivate Database. To assess publication and citation patterns concerning governance indicators—such as responsibility, political stability, effectiveness, supervisory quality, rule of law, and corruption control—global governance indicators are referenced. VOSviewer and Excel software are utilized for data analysis.<br /><strong>Findings:</strong> Analysis reveals an upward trend in scientific outputs related to organizational governance from 1981 to 2021, with a predominant focus on economics, public administration, and government. Notable authors include Philatoto, Leiblein, and Jackson, while countries such as the United States, England, Canada, Germany, the Netherlands, and China, along with universities<br />like Stanford, the University of Illinois, the University of Arizona, the University of Georgia,<br />the University of Copenhagen, and Harvard University, are at the forefront of publishing outputs<br />on organizational governance. Top-performing countries in governance indicators include the Netherlands, Canada, Germany, the United Kingdom, Taiwan, France, the United States, Spain, Italy, and China. Co-authorship, co-referencing, and scientific collaboration are relatively limited and dispersed, with countries such as the United States, England, Malaysia, and Brazil exhibiting higher levels of interaction. Key topics in organizational governance include governance, management, innovation, systems, organizational and corporate performance, trust, networks, information technology, and collaboration. The study concludes that innovation and technology, particularly in effective<br />e-governance, play a crucial role in enhancing transparency, improving information accessibility,<br />and boosting overall organizational performance. They enhance management processes, including reporting and control, while fostering new channels for communication and collaboration among organizational members, resulting in accelerated progress.<br />The facilitation of governance processes has been shown to correlate with increased productivity, efficiency, and effectiveness. Notably, the research indicates a negative relationship between the number of documents and governance indicators, suggesting that fluctuations in scientific publication output influence corresponding changes in governance indicators. However, a strong positive correlation exists between citation rates and governance indicators across countries. This highlights the reciprocal relationship between scientific production and citation rates on governance indicators. It emphasizes that countries with strong governance performance often experience higher rates of publication and citation of scientific outputs.<br /><strong>Conclusion:</strong> In conclusion, analyzing scientific outputs in organizational governance can inform effective scientific policies, reveal new subject areas and research gaps, outline research directions, promote the generation of new knowledge, and encourage further research initiatives. Additionally, it fosters the anticipation of future scientific developments, identifies influential contributors in the scientific community, establishes improved connections and collaborations across various fields, and promotes overall scientific advancement in the area of organizational governance.<br /> <strong>Purpose:</strong> Organizational governance encompasses the structures, processes, and methodologies employed by an organization to communicate, direct, organize, and control its activities. Serving as a mechanism for knowledge integration and sharing, organizational governance establishes channels for disseminating knowledge, fostering cooperation among members, and empowering individuals to create, acquire, and share knowledge. It involves leveraging appropriate technologies for storing, transferring, and sharing knowledge, along with continuous monitoring and evaluation of knowledge management processes. Building an organizational culture rooted in trust and knowledge sharing is essential, especially when individuals are willing to share their knowledge. Essentially, organizational governance plays a pivotal role in enhancing organizational excellence at all levels of the organization. It contributes to heightened productivity, efficiency, and effectiveness by promoting better organization, facilitating accurate communication, improving risk management, and providing enhanced access to human and financial resources through the application of effective governance methods. Successful organizational governance necessitates informed policy-making, and a thorough analysis of research in this domain can drive progress. Therefore, the purpose of this research is to analyze the trends in published scientific literature on organizational governance within the Clarivate Database.<br /><strong>Method:</strong> This applied research utilizes a descriptive method and a scientometric approach to analyze the trends in scientific publications on organizational governance within the Web of Science reference database. The statistical population comprises 249 scientific outputs published between 1981 and 2021 in the Clarivate Database. To assess publication and citation patterns concerning governance indicators—such as responsibility, political stability, effectiveness, supervisory quality, rule of law, and corruption control—global governance indicators are referenced. VOSviewer and Excel software are utilized for data analysis.<br /><strong>Findings:</strong> Analysis reveals an upward trend in scientific outputs related to organizational governance from 1981 to 2021, with a predominant focus on economics, public administration, and government. Notable authors include Philatoto, Leiblein, and Jackson, while countries such as the United States, England, Canada, Germany, the Netherlands, and China, along with universities<br />like Stanford, the University of Illinois, the University of Arizona, the University of Georgia,<br />the University of Copenhagen, and Harvard University, are at the forefront of publishing outputs<br />on organizational governance. Top-performing countries in governance indicators include the Netherlands, Canada, Germany, the United Kingdom, Taiwan, France, the United States, Spain, Italy, and China. Co-authorship, co-referencing, and scientific collaboration are relatively limited and dispersed, with countries such as the United States, England, Malaysia, and Brazil exhibiting higher levels of interaction. Key topics in organizational governance include governance, management, innovation, systems, organizational and corporate performance, trust, networks, information technology, and collaboration. The study concludes that innovation and technology, particularly in effective<br />e-governance, play a crucial role in enhancing transparency, improving information accessibility,<br />and boosting overall organizational performance. They enhance management processes, including reporting and control, while fostering new channels for communication and collaboration among organizational members, resulting in accelerated progress.<br />The facilitation of governance processes has been shown to correlate with increased productivity, efficiency, and effectiveness. Notably, the research indicates a negative relationship between the number of documents and governance indicators, suggesting that fluctuations in scientific publication output influence corresponding changes in governance indicators. However, a strong positive correlation exists between citation rates and governance indicators across countries. This highlights the reciprocal relationship between scientific production and citation rates on governance indicators. It emphasizes that countries with strong governance performance often experience higher rates of publication and citation of scientific outputs.<br /><strong>Conclusion:</strong> In conclusion, analyzing scientific outputs in organizational governance can inform effective scientific policies, reveal new subject areas and research gaps, outline research directions, promote the generation of new knowledge, and encourage further research initiatives. Additionally, it fosters the anticipation of future scientific developments, identifies influential contributors in the scientific community, establishes improved connections and collaborations across various fields, and promotes overall scientific advancement in the area of organizational governance.<br /> https://stim.qom.ac.ir/article_2674_5edaa3f7b703415baa7361784c7b985a.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Investigating the Topic Trend of Profit Management in Asian Countries in the Scopus Database with a Scientometric ApproachInvestigating the Topic Trend of Profit Management in Asian Countries in the Scopus Database with a Scientometric Approach299324334110.22091/stim.2024.10629.2088FAMohammad JavadZare BahnamiriAssociate Professor, Department of Accounting, Faculty of Economic and Administrative Sciences, University of Qom, Qom, Iran0000-0003-3992-8810SamiraBalavarMS, Department of Accounting, Faculty of Economic and Administrative Sciences, University of Qom, Qom, Iran0009-0006-6157-0252HadisehHeidariPh.D. Candidate in knowledge and Information science, Al-Zahra University, Tehran, Iran.0000-0001-5242-4348Journal Article20240417<strong>Purpose:</strong> Scientometric studies offer insights into the production, dissemination, and application of scientific knowledge, enabling managers at various research and executive levels to make informed decisions in their respective fields. The aim of this research is to analyze and review studies indexed in the Scopus database that pertain to profit management in Asian countries.<br /><strong>Methods:</strong> This research is an applied study conducted using documentary methods and scientometric techniques. The research community comprises 1,465 scientific publications indexed in the field of profit management. The time frame of the study spans 25 years, from 1998 to 2023, focusing on researchers in this field who are registered in the Scopus database.<br /><strong>Findings:</strong> The highest growth trend in scientific productions occurred during the period from 2022 to 2023, while the lowest growth trend was observed from 1998 to 2014, during which fewer than 100 degrees were produced. Following that, from 2015 to 2023, scientific production exhibited <br />a positive trend, increasing from 100 to 337 degrees. The majority of scientific publications were released during the years 2022 to 2023. In the following analysis, the growth rate of scientific productions was examined. According to this survey, although scientific productions were limited in the early years, it has experienced significant growth. The highest growth rate was recorded in 2001 at 4.0%, while the lowest growth rate occurred in 2000, with a decline of -1.0% due to a lack of degree production. According to ten highly cited articles on profit management, the total number of citations for scientific productions related to this field in the Scopus database during the review period was 27,002. On average, each article received approximately 11.59 citations.<br />The highest change rate of 471 citations in 2010 is attributed to the study by Jian et al. (2010), which focused on support through related party transactions. The article Private and Public Ownership and Earnings Management: Evidence from Chinese Listed Companies by Ding et al. (2007) has the lowest citation rate, with only 287 citations. Among the total of 6,470 authors in the field of earnings management listed in Scopus from 1998 to 2023, Wang, with 30 documents, Salehi, with 23 documents, and Li, with 22 documents, are the most frequently cited authors. In terms of countries, China leads with 775 documents, followed by Indonesia with 267 documents and Malaysia with 261 documents. The most productive journal in this field is the Asia Pacific Journal of Accounting and Economics, which has published 45 documents. Additionally, the University of Uttara Malaysia is<br />the most prolific institution, contributing 68 papers. The emerging issues surrounding earnings management research from 2014 to 2016 have been addressed in topics such as income, which has a link strength of 215, shareholders with a link strength of 116, and listed companies with a link strength of 123. Additionally, issues related to profit management, with a link strength of 2,264, corporate governance with a link strength of 706, and real profit management with a link strength of 508 have been examined during the period from 2018 to 2019. Furthermore, topics such as financial reporting quality with a link strength of 82, company performance with a link strength of 80, and audit costs with a link strength of 55 have emerged as significant areas of interest for researchers in recent years. According to high-frequency word analysis, the clustering of research keywords consists of eight interwoven keyword clusters.<br /><strong>Conclusion:</strong> In any case, considering the significance of the subject and the limited number of studies conducted in this field, it is essential to focus more attention on this area. This focus aligns with the goals of preventing and uncovering profit management issues. An analysis of journals, universities, and the most cited authors indicates that future collaborative efforts among researchers are necessary in this domain. In order to benefit from the findings of such research, scholars in the field of accounting, like their counterparts in other disciplines, should prioritize scientometric studies. This approach will help establish a coherent framework for understanding the current state<br />of accounting research and enhance the quality of published accounting articles. Based on this, suggestions have been presented to complete this research and expand scientific studies in the field of accounting knowledge, specifically focusing on the subject area of profit and reviewing related research.<br /> <strong>Purpose:</strong> Scientometric studies offer insights into the production, dissemination, and application of scientific knowledge, enabling managers at various research and executive levels to make informed decisions in their respective fields. The aim of this research is to analyze and review studies indexed in the Scopus database that pertain to profit management in Asian countries.<br /><strong>Methods:</strong> This research is an applied study conducted using documentary methods and scientometric techniques. The research community comprises 1,465 scientific publications indexed in the field of profit management. The time frame of the study spans 25 years, from 1998 to 2023, focusing on researchers in this field who are registered in the Scopus database.<br /><strong>Findings:</strong> The highest growth trend in scientific productions occurred during the period from 2022 to 2023, while the lowest growth trend was observed from 1998 to 2014, during which fewer than 100 degrees were produced. Following that, from 2015 to 2023, scientific production exhibited <br />a positive trend, increasing from 100 to 337 degrees. The majority of scientific publications were released during the years 2022 to 2023. In the following analysis, the growth rate of scientific productions was examined. According to this survey, although scientific productions were limited in the early years, it has experienced significant growth. The highest growth rate was recorded in 2001 at 4.0%, while the lowest growth rate occurred in 2000, with a decline of -1.0% due to a lack of degree production. According to ten highly cited articles on profit management, the total number of citations for scientific productions related to this field in the Scopus database during the review period was 27,002. On average, each article received approximately 11.59 citations.<br />The highest change rate of 471 citations in 2010 is attributed to the study by Jian et al. (2010), which focused on support through related party transactions. The article Private and Public Ownership and Earnings Management: Evidence from Chinese Listed Companies by Ding et al. (2007) has the lowest citation rate, with only 287 citations. Among the total of 6,470 authors in the field of earnings management listed in Scopus from 1998 to 2023, Wang, with 30 documents, Salehi, with 23 documents, and Li, with 22 documents, are the most frequently cited authors. In terms of countries, China leads with 775 documents, followed by Indonesia with 267 documents and Malaysia with 261 documents. The most productive journal in this field is the Asia Pacific Journal of Accounting and Economics, which has published 45 documents. Additionally, the University of Uttara Malaysia is<br />the most prolific institution, contributing 68 papers. The emerging issues surrounding earnings management research from 2014 to 2016 have been addressed in topics such as income, which has a link strength of 215, shareholders with a link strength of 116, and listed companies with a link strength of 123. Additionally, issues related to profit management, with a link strength of 2,264, corporate governance with a link strength of 706, and real profit management with a link strength of 508 have been examined during the period from 2018 to 2019. Furthermore, topics such as financial reporting quality with a link strength of 82, company performance with a link strength of 80, and audit costs with a link strength of 55 have emerged as significant areas of interest for researchers in recent years. According to high-frequency word analysis, the clustering of research keywords consists of eight interwoven keyword clusters.<br /><strong>Conclusion:</strong> In any case, considering the significance of the subject and the limited number of studies conducted in this field, it is essential to focus more attention on this area. This focus aligns with the goals of preventing and uncovering profit management issues. An analysis of journals, universities, and the most cited authors indicates that future collaborative efforts among researchers are necessary in this domain. In order to benefit from the findings of such research, scholars in the field of accounting, like their counterparts in other disciplines, should prioritize scientometric studies. This approach will help establish a coherent framework for understanding the current state<br />of accounting research and enhance the quality of published accounting articles. Based on this, suggestions have been presented to complete this research and expand scientific studies in the field of accounting knowledge, specifically focusing on the subject area of profit and reviewing related research.<br /> https://stim.qom.ac.ir/article_3341_f17e48521c0afcb2b1cf08e4911aa5ab.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Identifying Crime Prediction Strategies in
Schools Using the Internet of Things (IOT)Identifying Crime Prediction Strategies in
Schools Using the Internet of Things (IOT)325350330910.22091/stim.2025.10372.2063FASamanAbdollahiAssistant Professor, Department of Law, Naragh Branch, Islamic Azad University, Naragh, Iran.0000-0003-2153-5306Journal Article20240202<strong>Purpose:</strong> The establishment and implementation of information and communication technology (ICT) in combating crime have made some societies more modern and innovative in crime detection. Accordingly, societies equipped with modern capabilities have greater opportunities. To enhance identification and intervention in this area, it is essential to propose a system that utilizes social tools from the Internet of Things to support the identification of criminals and the prediction of crime in the real world. One of the most critical areas for implementing the Internet of Things (IoT) to predict crimes is within schools. Students represent both the most vital and vulnerable components of the educational system and the national capital of any country. Therefore, it is essential to leverage modern technologies for crime prediction in schools. The purpose of this study is to investigate the role of the Internet of Things in predicting crimes in schools.
<strong>Method</strong>: This article is focused on its purpose and employs quantitative methods and surveys for implementation. The statistical population for this research consists of experts and criminologists in Tehran in 2023. The sample size was determined using the formula for an indefinite population. In a pilot study involving 30 questionnaires, the variance of the original sample was found to be 0.32. Ultimately, 157 individuals were selected as the sample using a simple random sampling method. The instrument used in this research is a researcher-developed questionnaire focused on the Internet of Things in schools, specifically regarding crime prediction. The data collected were analyzed using statistical inference tests and structural equation modeling.
<strong>Findings</strong>: The structural relationship analysis revealed that the direct effect of "Internet of Things capabilities" on crime prediction, with a coefficient of 0.81, indicates that these capabilities can significantly contribute to predicting crime in schools. In second place, the "Internet of Things applicability in identifying crime patterns, with a coefficient of 0.63, significantly influences crime prediction in schools. Finally, the "Internet of Things functional requirements in schools, with a coefficient of 0.52, also impacts crime prediction in educational settings. Overall, these modeling results align with the inferential findings from testing the hypotheses.
<strong>Conclusion</strong>: By using the Internet of Things in environmental design and maintenance, we can enhance local safety and environmental control, identify crime patterns, increase police awareness of criminal activity, conduct crime analysis, and utilize artificial intelligence algorithms. This approach enables us to accurately predict the occurrence of crimes in specific locations and take proactive measures to prevent them. Therefore, specialized systems and infrastructures for the development of the Internet of Things (IoT) in schools and other critical and sensitive locations should be utilized effectively, and appropriate platforms should be established to support their development. Therefore, planners, policymakers, and criminologists can leverage real data to significantly manage crime prevention processes in schools, thereby reducing the incidence of crime as the infrastructure develops.<strong>Purpose:</strong> The establishment and implementation of information and communication technology (ICT) in combating crime have made some societies more modern and innovative in crime detection. Accordingly, societies equipped with modern capabilities have greater opportunities. To enhance identification and intervention in this area, it is essential to propose a system that utilizes social tools from the Internet of Things to support the identification of criminals and the prediction of crime in the real world. One of the most critical areas for implementing the Internet of Things (IoT) to predict crimes is within schools. Students represent both the most vital and vulnerable components of the educational system and the national capital of any country. Therefore, it is essential to leverage modern technologies for crime prediction in schools. The purpose of this study is to investigate the role of the Internet of Things in predicting crimes in schools.
<strong>Method</strong>: This article is focused on its purpose and employs quantitative methods and surveys for implementation. The statistical population for this research consists of experts and criminologists in Tehran in 2023. The sample size was determined using the formula for an indefinite population. In a pilot study involving 30 questionnaires, the variance of the original sample was found to be 0.32. Ultimately, 157 individuals were selected as the sample using a simple random sampling method. The instrument used in this research is a researcher-developed questionnaire focused on the Internet of Things in schools, specifically regarding crime prediction. The data collected were analyzed using statistical inference tests and structural equation modeling.
<strong>Findings</strong>: The structural relationship analysis revealed that the direct effect of "Internet of Things capabilities" on crime prediction, with a coefficient of 0.81, indicates that these capabilities can significantly contribute to predicting crime in schools. In second place, the "Internet of Things applicability in identifying crime patterns, with a coefficient of 0.63, significantly influences crime prediction in schools. Finally, the "Internet of Things functional requirements in schools, with a coefficient of 0.52, also impacts crime prediction in educational settings. Overall, these modeling results align with the inferential findings from testing the hypotheses.
<strong>Conclusion</strong>: By using the Internet of Things in environmental design and maintenance, we can enhance local safety and environmental control, identify crime patterns, increase police awareness of criminal activity, conduct crime analysis, and utilize artificial intelligence algorithms. This approach enables us to accurately predict the occurrence of crimes in specific locations and take proactive measures to prevent them. Therefore, specialized systems and infrastructures for the development of the Internet of Things (IoT) in schools and other critical and sensitive locations should be utilized effectively, and appropriate platforms should be established to support their development. Therefore, planners, policymakers, and criminologists can leverage real data to significantly manage crime prevention processes in schools, thereby reducing the incidence of crime as the infrastructure develops.https://stim.qom.ac.ir/article_3309_878307e8fb90cd14ba35187f83eb034c.pdfUniversity of QomSciences and Techniques of Information Management2476-665810320240922Investigating the Impact Information and Communication Technology and Misery Index on Poverty with Panel DataInvestigating the Impact Information and Communication Technology and Misery Index on Poverty with Panel Data351372253010.22091/stim.2023.9709.1982FAHassanAma Bandeh GharaeiAssistant Professor, Department of Economics, Payam Noor University, Tehran, Iran0000-0002-3542-1740AbulfazlYavari HhalilAbabAssistant Professor, Faculty of Computer Engineering and Information Technology, Payam Noor University, Tehran, Iran0000-0002-8329-4256Seyed MohammadSeyediPhD Student, Department of Economics, Faculty of Administrative and Economic Sciences, Ferdowsi University of Mashhad, Mashhad, Iran0002-8106-4449HamedMokhtari TorshiziPhD Student, Department of Economics, Faculty of Administrative and Economic Sciences, Ferdowsi University of Mashhad, Mashhad, IranJournal Article20230724<strong>Purpose:</strong> Poverty is a complex issue with social and economic dimensions, recognized by international organizations such as the World Health Organization, the International Labour Organization, and the Food and Agriculture Organization (FAO). These organizations actively work to reduce and eradicate poverty. Amartya Sen's capability approach suggests measuring poverty as a deprivation of basic capabilities rather than merely focusing on income. In the context of technological advancements, particularly in information and communication technology (ICT), there is significant potential for ICT to contribute to poverty reduction. Information and Communication Technology (ICT) can improve access to health information, government services, employment opportunities, education, and support for economically disadvantaged individuals. Understanding the relationship between poverty and ICT is essential.
<strong>Method:</strong> This research aims to explore the impact of information and communication technology (ICT) and economic variables on poverty. It utilizes a combination of data to examine the correlation between ICT and macroeconomic factors. The analysis involves studying time series observations across various sectors using a fixed effects model with pooled data. The model is evaluated using the Lagrange coefficient test developed by Brosh and Pagan. The model incorporates the penetration rate of mobile technology as a proxy for information and communication technology (ICT), along with macroeconomic variables such as inflation and unemployment, which together constitute the misery index. Additionally, per capita income is regarded as a macroeconomic variable that influences poverty. The model can be expressed as follows: P=F (ICT, MI, PI). The poverty indicator is denoted by the symbol P, while the information and communication technology variable is represented by Fava ICT. The misery index, which incorporates variables such as inflation and unemployment, is denoted as MI. The macroeconomic variable representing per capita income is symbolized as PI. The study focuses on a statistical population of 36 countries selected for their similarities in economic, political, and social characteristics. The selected countries ensure comparability and control for potential confounding factors. The study covers the years 2000 to 2021, allowing for an analysis of long-term trends and relationships among poverty, information and communication technology, macroeconomic variables, and per capita income in these countries.
<strong>Finding:</strong> The significant levels of all variables in the model indicate that false regression is not a concern. This suggests that the observed relationships in the analysis are statistically meaningful and not merely due to chance. The F-Limer test confirms the appropriateness of using panel data by indicating the presence of a panel structure within the dataset. This allows for the consideration of both cross-sectional and time-series dimensions. The Hausman test supports the use of random effects in the model, indicating that unobserved individual-specific effects do not significantly influence<br />the estimated coefficients. The analysis results confirm the existence of a relationship between information and communication technology, the misery index, per capita income, and poverty levels. Specifically, the misery index and information technology demonstrate the most significant impact and are statistically significant. These findings underscore the importance of addressing economic distress, promoting technological advancements, and enhancing income levels as potential strategies for poverty reduction. It is important to note that the specific magnitudes and significance levels of the effects may vary depending on the statistical techniques and model specifications used in the analysis.
<strong>Conclusion:</strong> Governments can play a crucial role in alleviating poverty by investing in information and communication technology (ICT) infrastructure and creating an environment that encourages private sector participation. Allocating and securing financial resources is essential for supporting the development and implementation of ICT initiatives. Policy-making should be informed by comprehensive research and analysis to identify the specific needs and priorities of each country. This approach will lead to the development of effective policies that align with goals for poverty reduction and socioeconomic development. Additionally, the establishment of laws and regulations can guide the implementation of ICT initiatives, ensuring their effectiveness and sustainability. Regular evaluations and assessments are essential for monitoring progress and impact, allowing for necessary adjustments. It is unfortunate that some countries, including those that are economically and socially close to Iran, may depend on imitation and replication instead of adopting comprehensive approaches to ICT development. Governments should acknowledge their distinct contexts and challenges, formulating customized strategies to effectively leverage the potential of Information and Communication Technology (ICT) in poverty alleviation and sustainable development.<strong>Purpose:</strong> Poverty is a complex issue with social and economic dimensions, recognized by international organizations such as the World Health Organization, the International Labour Organization, and the Food and Agriculture Organization (FAO). These organizations actively work to reduce and eradicate poverty. Amartya Sen's capability approach suggests measuring poverty as a deprivation of basic capabilities rather than merely focusing on income. In the context of technological advancements, particularly in information and communication technology (ICT), there is significant potential for ICT to contribute to poverty reduction. Information and Communication Technology (ICT) can improve access to health information, government services, employment opportunities, education, and support for economically disadvantaged individuals. Understanding the relationship between poverty and ICT is essential.
<strong>Method:</strong> This research aims to explore the impact of information and communication technology (ICT) and economic variables on poverty. It utilizes a combination of data to examine the correlation between ICT and macroeconomic factors. The analysis involves studying time series observations across various sectors using a fixed effects model with pooled data. The model is evaluated using the Lagrange coefficient test developed by Brosh and Pagan. The model incorporates the penetration rate of mobile technology as a proxy for information and communication technology (ICT), along with macroeconomic variables such as inflation and unemployment, which together constitute the misery index. Additionally, per capita income is regarded as a macroeconomic variable that influences poverty. The model can be expressed as follows: P=F (ICT, MI, PI). The poverty indicator is denoted by the symbol P, while the information and communication technology variable is represented by Fava ICT. The misery index, which incorporates variables such as inflation and unemployment, is denoted as MI. The macroeconomic variable representing per capita income is symbolized as PI. The study focuses on a statistical population of 36 countries selected for their similarities in economic, political, and social characteristics. The selected countries ensure comparability and control for potential confounding factors. The study covers the years 2000 to 2021, allowing for an analysis of long-term trends and relationships among poverty, information and communication technology, macroeconomic variables, and per capita income in these countries.
<strong>Finding:</strong> The significant levels of all variables in the model indicate that false regression is not a concern. This suggests that the observed relationships in the analysis are statistically meaningful and not merely due to chance. The F-Limer test confirms the appropriateness of using panel data by indicating the presence of a panel structure within the dataset. This allows for the consideration of both cross-sectional and time-series dimensions. The Hausman test supports the use of random effects in the model, indicating that unobserved individual-specific effects do not significantly influence<br />the estimated coefficients. The analysis results confirm the existence of a relationship between information and communication technology, the misery index, per capita income, and poverty levels. Specifically, the misery index and information technology demonstrate the most significant impact and are statistically significant. These findings underscore the importance of addressing economic distress, promoting technological advancements, and enhancing income levels as potential strategies for poverty reduction. It is important to note that the specific magnitudes and significance levels of the effects may vary depending on the statistical techniques and model specifications used in the analysis.
<strong>Conclusion:</strong> Governments can play a crucial role in alleviating poverty by investing in information and communication technology (ICT) infrastructure and creating an environment that encourages private sector participation. Allocating and securing financial resources is essential for supporting the development and implementation of ICT initiatives. Policy-making should be informed by comprehensive research and analysis to identify the specific needs and priorities of each country. This approach will lead to the development of effective policies that align with goals for poverty reduction and socioeconomic development. Additionally, the establishment of laws and regulations can guide the implementation of ICT initiatives, ensuring their effectiveness and sustainability. Regular evaluations and assessments are essential for monitoring progress and impact, allowing for necessary adjustments. It is unfortunate that some countries, including those that are economically and socially close to Iran, may depend on imitation and replication instead of adopting comprehensive approaches to ICT development. Governments should acknowledge their distinct contexts and challenges, formulating customized strategies to effectively leverage the potential of Information and Communication Technology (ICT) in poverty alleviation and sustainable development.https://stim.qom.ac.ir/article_2530_1c8dd3702a7628a6261467e3a5670f32.pdf