Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Designing a Lean Trust-building Model for E-government: An Empirical StudyinTehran Designing a Lean Trust-building Model for E-government: An Empirical StudyinTehran 232813 10.22034/aimj.2025.490256.1615 FA Roohallahً Noori Associate Prof., Department of Human Resource Management, Faculty of Management, Kharazmi University, Tehran, Iran Davari Irdmousi Davari Irdmousi MA., Department of Business Management, Faculty of Management, Kharazmi University, Tehran, Iran Somayeh Parvini MA., Department of Business Management, Faculty of Management, Kharazmi University, Tehran, Iran Journal Article 2024 11 23 This research aimed to examine the impact of trust-building on the performance of e-government in Tehran and to investigate and explain the key indicators affecting trust-building dimensions. Moreover, the study proposed strategies to enhance overall citizen participation and foster genuine trust in e-government in Tehran.This research was conducted using a descriptive-correlational method.To collect the necessary data,three questionnaires were employed:1.Deng's standard questionnaire for e-government performance,2.A researcher-made questionnaire adapted from Blengro and Carter, and 3. Morgan's questionnaire for trust-building. The questionnaire comprised 32 questions.The questionnaire items were structured into three dimensions of the independent variable, including government trust-building, electronic trust, and citizen trustworthiness, and one dimension of the dependent variable, e-government. The sample size was determined to be 388 using a stratified random sampling method with proportional allocation. Data analysis was conducted using SPSS and Amos software.The research findings indicated that the three dimensions of government trust-building, electronic trust,and citizen trustworthiness had a positive and significant impact on e-government performance. The fit indices of the proposed model, namely (Root Mean Square Error oApproximation: 0.41), (Goodness of Fit Index: 0.645), (Normalized Fit Index: 0.969),and (Comparative Fit Index: 0.900), confirmed the model, indicating that the research model had the capability to measure the main variables of the study.To foster trust ine-government, the primary focus should be on government trust-building, followed by electronic trust. Considering that each dimension ofthe research has specific indicators,creating conditions for improvement and development of these indicators will facilitate the enhancement of genuine trust in e-government. This research aimed to examine the impact of trust-building on the performance of e-government in Tehran and to investigate and explain the key indicators affecting trust-building dimensions. Moreover, the study proposed strategies to enhance overall citizen participation and foster genuine trust in e-government in Tehran.This research was conducted using a descriptive-correlational method.To collect the necessary data,three questionnaires were employed:1.Deng's standard questionnaire for e-government performance,2.A researcher-made questionnaire adapted from Blengro and Carter, and 3. Morgan's questionnaire for trust-building. The questionnaire comprised 32 questions.The questionnaire items were structured into three dimensions of the independent variable, including government trust-building, electronic trust, and citizen trustworthiness, and one dimension of the dependent variable, e-government. The sample size was determined to be 388 using a stratified random sampling method with proportional allocation. Data analysis was conducted using SPSS and Amos software.The research findings indicated that the three dimensions of government trust-building, electronic trust,and citizen trustworthiness had a positive and significant impact on e-government performance. The fit indices of the proposed model, namely (Root Mean Square Error oApproximation: 0.41), (Goodness of Fit Index: 0.645), (Normalized Fit Index: 0.969),and (Comparative Fit Index: 0.900), confirmed the model, indicating that the research model had the capability to measure the main variables of the study.To foster trust ine-government, the primary focus should be on government trust-building, followed by electronic trust. Considering that each dimension ofthe research has specific indicators,creating conditions for improvement and development of these indicators will facilitate the enhancement of genuine trust in e-government. Citizen trustworthiness Electronic trust E-Government Government trust-building Trust-Building https://www.aimj.ir/article_232813_ade3d7c0debc53da109dbf63213ec5e3.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Designing a Conceptual Model of Blockchain-Based Digital Identityin International Businesses Designing a Conceptual Model of Blockchain-Based Digital Identityin International Businesses 232814 10.22034/aimj.2025.501055.1624 FA Hossein Rahimi Kolour Associate Prof., Department of Business Management, Faculty of Social Science, University of Mohaqheqh Ardabili, Ardabili, Iran 0000-0001-9166-1370 Mina Purhosein Roshan Ph.D. Candidate, Department of Business Management, Faculty of Social Science, University of Mohaqheqh Ardabili, Ardabil, Iran 0009-0008-6239-0522 Journal Article 2025 01 20 Given the security challenges and inefficiencies inherent in traditional identity verification systems within international trade, this study aims to design a conceptual model for blockchain-based digital identity in international business. This qualitative research collected data through semi-structured interviews with 12 experts in the fields of blockchain and international commerce. The data were analyzed using thematic analysis with the aid of MAXQDA software. The findings suggest that the application of blockchain in digital identity can contribute to transforming identity processes and international interactions through themes such as “data-driven and smart regulation,” “self-sovereign identity governance,” “autonomous identity management,” “process optimization and export facilitation,” “integration of systems and infrastructures,” and “trust-building and commercial transparency.”The resulting conceptual model offers an innovative solution for decentralized and secure digital identity management. Furthermore, it provides a robust foundation for technological policymaking, cross-border infrastructure design, and the development of e-commerce systems, ultimately contributing to the modernization and reliability of identity practices in the global business environment. Given the security challenges and inefficiencies inherent in traditional identity verification systems within international trade, this study aims to design a conceptual model for blockchain-based digital identity in international business. This qualitative research collected data through semi-structured interviews with 12 experts in the fields of blockchain and international commerce. The data were analyzed using thematic analysis with the aid of MAXQDA software. The findings suggest that the application of blockchain in digital identity can contribute to transforming identity processes and international interactions through themes such as “data-driven and smart regulation,” “self-sovereign identity governance,” “autonomous identity management,” “process optimization and export facilitation,” “integration of systems and infrastructures,” and “trust-building and commercial transparency.”The resulting conceptual model offers an innovative solution for decentralized and secure digital identity management. Furthermore, it provides a robust foundation for technological policymaking, cross-border infrastructure design, and the development of e-commerce systems, ultimately contributing to the modernization and reliability of identity practices in the global business environment. Digital identity Blockchain International business Innovation https://www.aimj.ir/article_232814_b7eea76c6a803c36b061e2aaba271351.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Innovations in Data Quality Management in the Oil and Gas Industry Innovations in Data Quality Management in the Oil and Gas Industry 232815 10.22034/aimj.2025.528978.1640 FA Alireza Shahraki Associate Prof., Department of Industrial Engineering, Faculty of Shahid Nikbakht Engineering, University of Sistan and Baluchestan, Zahedan, Iran 0000-0002-7809-8656 Farid Shahraki Moghadam MSc. Student, Department of Industrial Engineering, Faculty of Shahid Nikbakht Engineering, University of Sistan and Baluchestan, Zahedan, Iran Journal Article 2025 06 08 Data analytics offers a wide range of services to assist the oil and gas sector in developing reliable and secure processes. The information and data derived from these processes form the backbone of modern operations and business decisions. Data quality management in the oil and gas industry is crucial for ensuring operational efficiency, safety, and regulatory compliance. In an industry known for its complexity and scale, having high-quality data is vital for minimizing risks, maximizing productivity, and enabling informed decision-making. This study focuses on data quality management by examining the impact of innovative technologies such as big data analytics, machine learning, the Internet of Things (IoT), and blockchain, which play a significant role in addressing data quality challenges. To this end, a theoretical model was tested using partial least squares structural equation modeling (PLS-SEM) based on a sample of 319 companies operating in the oil and gas sector. The results indicate that big data analytics, machine learning, IoT, and blockchain have a positive and significant effect on data quality management in the oil and gas industry. This study contributes to the ongoing discourse on data quality management by providing a comprehensive analysis of current strategies and future directions, thereby enhancing the sustainability and competitiveness of oil and gas companies in a data-driven environment. Data analytics offers a wide range of services to assist the oil and gas sector in developing reliable and secure processes. The information and data derived from these processes form the backbone of modern operations and business decisions. Data quality management in the oil and gas industry is crucial for ensuring operational efficiency, safety, and regulatory compliance. In an industry known for its complexity and scale, having high-quality data is vital for minimizing risks, maximizing productivity, and enabling informed decision-making. This study focuses on data quality management by examining the impact of innovative technologies such as big data analytics, machine learning, the Internet of Things (IoT), and blockchain, which play a significant role in addressing data quality challenges. To this end, a theoretical model was tested using partial least squares structural equation modeling (PLS-SEM) based on a sample of 319 companies operating in the oil and gas sector. The results indicate that big data analytics, machine learning, IoT, and blockchain have a positive and significant effect on data quality management in the oil and gas industry. This study contributes to the ongoing discourse on data quality management by providing a comprehensive analysis of current strategies and future directions, thereby enhancing the sustainability and competitiveness of oil and gas companies in a data-driven environment. Data quality management Oil and gas industry Internet of Things (IoT) Machine Learning Blockchain Big Data analytics https://www.aimj.ir/article_232815_1884f62528e2d1685ff193db508fadcc.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Standardization of Registering Alley and Street Names in Tehran in order to Organize Spatial Information Standardization of Registering Alley and Street Names in Tehran in order to Organize Spatial Information 232817 10.22034/aimj.2025.532980.1645 FA Seyed Mehdi Samaei Associate Prof., Iranian Research Institute for Information Science & Technology (IranDoc), Tehran, Iran Fariborz Doroudi Assistant Prof., Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran Journal Article 2025 07 08 The aim of the research is to standardize the registration of neighborhood and barzan names in Tehran to organize spatial information. The research method in this study is designed to identify and analyze the heterogeneity and dispersion of the registration of neighborhood and barzan names in Tehran qualitatively. This method includes collecting data in the field and using visual tools, as well as written recording. The target population consists of 7 districts of Tehran. Sampling was based on the Morgan and Krejci table, and the quantity of data collected was 384, which significantly represents the status of name registration in Tehran. Data collection was carried out using a multi-stage cluster method. In this method, several neighborhoods were selected from different districts of Tehran, and data were collected from each district. This approach allowed for the preparation of a diverse sample consistent with the statistical population of the status of name registration in different regions of Tehran. After clustering the data, information was extracted for the study in a non-random and purposeful manner. The percentage of data collected from region 6 was about 50%, and the remaining 50% was from regions 1, 2, 3, 7, 11, and 12. The research findings showed that Street signs in Iranian cities are written in Persian script, with their Latin equivalents also appearing on the sign. This practice dates back 150 years. Since then, there has been inconsistency in the way these names are transcribed into Latin characters. These inconsistencies are due to reasons such as the lack of a unified policy for transcribing names into Latin, the absence of a clear theoretical framework, and the ambiguity of Latin symbols for Persian letters. The diversity in the transcription of names is such that the Latin transcription differs from one region to another and from one street to another, and sometimes the Latin equivalent of a single name is written in two different ways on a single sign. There are also signs where a contradiction is observed on one side of the sign and in its Latin equivalent. In this study, various types of inconsistencies in the Latin transcription method of street names in the city of Tehran, from 8 districts and several neighborhoods in each district, and from among 384 examples and data according to the Morgan and Crysler table, were extracted, and then solutions were presented to standardize them. Obviously, the results of this study are not limited to Tehran and can be used to standardize the street signs of other Iranian cities. The aim of the research is to standardize the registration of neighborhood and barzan names in Tehran to organize spatial information. The research method in this study is designed to identify and analyze the heterogeneity and dispersion of the registration of neighborhood and barzan names in Tehran qualitatively. This method includes collecting data in the field and using visual tools, as well as written recording. The target population consists of 7 districts of Tehran. Sampling was based on the Morgan and Krejci table, and the quantity of data collected was 384, which significantly represents the status of name registration in Tehran. Data collection was carried out using a multi-stage cluster method. In this method, several neighborhoods were selected from different districts of Tehran, and data were collected from each district. This approach allowed for the preparation of a diverse sample consistent with the statistical population of the status of name registration in different regions of Tehran. After clustering the data, information was extracted for the study in a non-random and purposeful manner. The percentage of data collected from region 6 was about 50%, and the remaining 50% was from regions 1, 2, 3, 7, 11, and 12. The research findings showed that Street signs in Iranian cities are written in Persian script, with their Latin equivalents also appearing on the sign. This practice dates back 150 years. Since then, there has been inconsistency in the way these names are transcribed into Latin characters. These inconsistencies are due to reasons such as the lack of a unified policy for transcribing names into Latin, the absence of a clear theoretical framework, and the ambiguity of Latin symbols for Persian letters. The diversity in the transcription of names is such that the Latin transcription differs from one region to another and from one street to another, and sometimes the Latin equivalent of a single name is written in two different ways on a single sign. There are also signs where a contradiction is observed on one side of the sign and in its Latin equivalent. In this study, various types of inconsistencies in the Latin transcription method of street names in the city of Tehran, from 8 districts and several neighborhoods in each district, and from among 384 examples and data according to the Morgan and Crysler table, were extracted, and then solutions were presented to standardize them. Obviously, the results of this study are not limited to Tehran and can be used to standardize the street signs of other Iranian cities. Linguistics Tehran Sign municipality Persian script Latin language https://www.aimj.ir/article_232817_63a3a67148d5d31c6af0ff6c67cd3ac2.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Developing a Conceptual Model for Policy Making of Governmental Support for the Iranian Publishing Sector Developing a Conceptual Model for Policy Making of Governmental Support for the Iranian Publishing Sector 232819 10.22034/aimj.2025.549806.1652 FA Ebrahim Heydari PhD Candidate, Department of Culture and Communication, Isf.C., Islamic Azad University, Isfahan, Iran 0009-0001-2747-0331 Mehrdad Sadeghi Assistant Prof., Department of Culture and Communication, Isf.C., Islamic Azad University, Isfahan, Iran 0000-0002-7712-1463 Ali Rashidpour Associate Prof., Department of Culture and Communication, Isf.C., Islamic Azad University, Isfahan, Iran 0000-0002-3275-4523 Journal Article 2025 09 28 The aim of this study is to develop a comprehensive model for government support policy in Iran's publishing industry. This study sought to discover and explain the dimensions, components, and internal relationships of the phenomenon of government support policy within the local context of the Iranian publishing industry, thereby providing a theoretical and practical framework for policymakers and stakeholders in this field. The research adopted a qualitative approach to answer the research questions, utilizing the Grounded Theory method. Rich data was collected through in-depth, semi-structured interviews with 15 experts and key actors in the Iranian publishing industry. The analysis of these interviews, through open, axial, and selective coding, led to the discovery of key concepts, categories, and dimensions that shaped the research's conceptual model. Furthermore, the components of the paradigmatic model—namely, phenomenon, causal conditions, contextual conditions, intervening conditions, strategies, and consequences—were used to analyze the key dimensions. The result of the open coding process was the identification and extraction of 680 initial codes/concepts. The results of the axial coding led to the organization of these initial concepts into the six main dimensions of the paradigmatic model, comprising a total of 166 broader concepts. The dimensions of this model are as follows: Phenomenon (29 concepts); Causal Conditions (32 concepts); Contextual Conditions (30 concepts); Intervening Conditions (16 concepts); Strategies (36 concepts); and Consequences (23 concepts). In the third and final step of coding, selective coding, the 166 axial concepts were organized into 20 broader and more abstract categories. Government support policy for the publishing industry in Iran has always been a challenge and has not been comprehensively addressed in academic research until now. The current research, with an encompassing perspective, seeks to develop the theoretical model for this type of policymaking. The present research developed and validated a comprehensive and indigenous model for government support policy in Iran's publishing industry. This model provides theoretical insights and can be used as a strategic tool for policymakers in formulating and implementing targeted and effective support programs. The aim of this study is to develop a comprehensive model for government support policy in Iran's publishing industry. This study sought to discover and explain the dimensions, components, and internal relationships of the phenomenon of government support policy within the local context of the Iranian publishing industry, thereby providing a theoretical and practical framework for policymakers and stakeholders in this field. The research adopted a qualitative approach to answer the research questions, utilizing the Grounded Theory method. Rich data was collected through in-depth, semi-structured interviews with 15 experts and key actors in the Iranian publishing industry. The analysis of these interviews, through open, axial, and selective coding, led to the discovery of key concepts, categories, and dimensions that shaped the research's conceptual model. Furthermore, the components of the paradigmatic model—namely, phenomenon, causal conditions, contextual conditions, intervening conditions, strategies, and consequences—were used to analyze the key dimensions. The result of the open coding process was the identification and extraction of 680 initial codes/concepts. The results of the axial coding led to the organization of these initial concepts into the six main dimensions of the paradigmatic model, comprising a total of 166 broader concepts. The dimensions of this model are as follows: Phenomenon (29 concepts); Causal Conditions (32 concepts); Contextual Conditions (30 concepts); Intervening Conditions (16 concepts); Strategies (36 concepts); and Consequences (23 concepts). In the third and final step of coding, selective coding, the 166 axial concepts were organized into 20 broader and more abstract categories. Government support policy for the publishing industry in Iran has always been a challenge and has not been comprehensively addressed in academic research until now. The current research, with an encompassing perspective, seeks to develop the theoretical model for this type of policymaking. The present research developed and validated a comprehensive and indigenous model for government support policy in Iran's publishing industry. This model provides theoretical insights and can be used as a strategic tool for policymakers in formulating and implementing targeted and effective support programs. government support publishing industry Model development Grounded theory Iran https://www.aimj.ir/article_232819_7113d65efa98c24959da8aca2bc48738.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Applications of Artificial Intelligence in Electronic Archives: A Systematic Review Applications of Artificial Intelligence in Electronic Archives: A Systematic Review 233715 10.22034/aimj.2025.527993.1638 FA Farhad Shirani Assistant Prof., Department of Electronic Commerce, Iranian Research Institute for Information Science and Technology (IranDoc). Tehran, Iran Hanieh Hodaei MSc., Department of Business Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran Journal Article 2025 06 03 Today, the use of artificial intelligence in electronic archives has become a necessity, not just an optional option. With the increasing growth of data, the complexity of digital documents, and the need for fast and accurate access to information, artificial intelligence can play a key role in the optimization, maintenance, and exploitation of electronic archives. Artificial intelligence is increasingly integrated into electronic archives management and offers numerous benefits. This research was conducted to identify and introduce the most key applications of artificial intelligence in electronic archives. To achieve the research objective, the process outlined in the Cochrane Handbook for conducting a systematic review was used. initially, 160 works related to the topic of artificial intelligence and electronic archives were identified in databases. After removing duplicate works, 149 unique works remained. Then, the titles and abstracts of the articles were reviewed, and those that did not meet the research objective, namely "Investigating the application of artificial intelligence in electronic archives", were eliminated. At this stage, 120 works were selected from the databases. After this stage, the full text of the selected records was studied. To reduce bias, two researchers independently assessed the quality of the articles and low-quality articles were excluded. Finally, 30 works were selected as a sample for review. These works were then studied and the most key applications of artificial intelligence in electronic archives were extracted from their full text. A review of the collected articles showed that artificial intelligence tools and technologies can be used and utilized in six areas in electronic archives, including information discovery and monitoring, resource description and metadata generation, reference and research services, digital records storage and management, data security and protection, and improving efficiency and user experience. In the field of information exploration and monitoring, this technology can help with information search and retrieval, multilingual search, and improve recommendation systems. However, access to digital archival materials is still very complex for many reasons, such as privacy, data protection, sensitivity, national security, and copyright. Today, the use of artificial intelligence in electronic archives has become a necessity, not just an optional option. With the increasing growth of data, the complexity of digital documents, and the need for fast and accurate access to information, artificial intelligence can play a key role in the optimization, maintenance, and exploitation of electronic archives. Artificial intelligence is increasingly integrated into electronic archives management and offers numerous benefits. This research was conducted to identify and introduce the most key applications of artificial intelligence in electronic archives. To achieve the research objective, the process outlined in the Cochrane Handbook for conducting a systematic review was used. initially, 160 works related to the topic of artificial intelligence and electronic archives were identified in databases. After removing duplicate works, 149 unique works remained. Then, the titles and abstracts of the articles were reviewed, and those that did not meet the research objective, namely "Investigating the application of artificial intelligence in electronic archives", were eliminated. At this stage, 120 works were selected from the databases. After this stage, the full text of the selected records was studied. To reduce bias, two researchers independently assessed the quality of the articles and low-quality articles were excluded. Finally, 30 works were selected as a sample for review. These works were then studied and the most key applications of artificial intelligence in electronic archives were extracted from their full text. A review of the collected articles showed that artificial intelligence tools and technologies can be used and utilized in six areas in electronic archives, including information discovery and monitoring, resource description and metadata generation, reference and research services, digital records storage and management, data security and protection, and improving efficiency and user experience. In the field of information exploration and monitoring, this technology can help with information search and retrieval, multilingual search, and improve recommendation systems. However, access to digital archival materials is still very complex for many reasons, such as privacy, data protection, sensitivity, national security, and copyright. Artificial intelligence Electronic archives Information storage Access to Information https://www.aimj.ir/article_233715_16f1fd7274b97083b2edd116853d53cb.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 The Impact of Knowledge Sharing on the Relationship between Artificial Intelligence and Service Quality of Employees The Impact of Knowledge Sharing on the Relationship between Artificial Intelligence and Service Quality of Employees 233716 10.22034/aimj.2025.530930.1642 FA Seifallah Andayesh Assistant Prof., Department of knowledge and Information Science, Persian Gulf University, Bushehr, Iran 0000-0002-0095-4272 Journal Article 2025 06 27 The purpose of this study is to examine the impact of knowledge sharing on the relationship between artificial intelligence and the service quality of employees among librarians working in the libraries of medical universities in Tehran. This research is descriptive-survey in nature and applied in terms of purpose. The statistical population included all librarians working in the libraries of medical universities in Tehran (214 individuals). Using Cochran’s formula and standard statistical parameters, the sample size was determined as 137 librarians selected through stratified random sampling. For data collection, standardized questionnaires were employed: the artificial intelligence questionnaire developed by Chen et al. (2022) with 22 items, chosen due to its coherence, conciseness, and comprehensive coverage of AI dimensions; the knowledge sharing questionnaire developed by Damaj et al. (2016) with 12 items; and the service quality questionnaire developed by Parasuraman et al. (1985) with 22 items. The reliability of the instruments was confirmed using Cronbach’s alpha, and validity was established through convergent and discriminant validity. Data analysis was conducted using descriptive statistics such as frequency distribution, as well as inferential statistics through structural equation modeling (SEM) with Smart PLS software. The results showed that artificial intelligence has a positive and significant effect on employees’ service quality, and also positively influences knowledge sharing. Furthermore, knowledge sharing has a positive and significant impact on employees’ service quality. The results showed that knowledge sharing acts as a full mediator in the relationship between artificial intelligence and employees’ service quality. Therefore, this study contributes theoretically to the literature on artificial intelligence and knowledge management by demonstrating that knowledge mediation can bridge the gap between technology and the quality of human services. This research significantly contributes to the literature on artificial intelligence by highlighting research gaps in understanding the relationship between AI and service quality. The purpose of this study is to examine the impact of knowledge sharing on the relationship between artificial intelligence and the service quality of employees among librarians working in the libraries of medical universities in Tehran. This research is descriptive-survey in nature and applied in terms of purpose. The statistical population included all librarians working in the libraries of medical universities in Tehran (214 individuals). Using Cochran’s formula and standard statistical parameters, the sample size was determined as 137 librarians selected through stratified random sampling. For data collection, standardized questionnaires were employed: the artificial intelligence questionnaire developed by Chen et al. (2022) with 22 items, chosen due to its coherence, conciseness, and comprehensive coverage of AI dimensions; the knowledge sharing questionnaire developed by Damaj et al. (2016) with 12 items; and the service quality questionnaire developed by Parasuraman et al. (1985) with 22 items. The reliability of the instruments was confirmed using Cronbach’s alpha, and validity was established through convergent and discriminant validity. Data analysis was conducted using descriptive statistics such as frequency distribution, as well as inferential statistics through structural equation modeling (SEM) with Smart PLS software. The results showed that artificial intelligence has a positive and significant effect on employees’ service quality, and also positively influences knowledge sharing. Furthermore, knowledge sharing has a positive and significant impact on employees’ service quality. The results showed that knowledge sharing acts as a full mediator in the relationship between artificial intelligence and employees’ service quality. Therefore, this study contributes theoretically to the literature on artificial intelligence and knowledge management by demonstrating that knowledge mediation can bridge the gap between technology and the quality of human services. This research significantly contributes to the literature on artificial intelligence by highlighting research gaps in understanding the relationship between AI and service quality. Artificial intelligence Service Quality knowledge sharing Academic librarians https://www.aimj.ir/article_233716_3a15d42805a2b2bc57ecaaf590fd98e0.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 The Mediating Role of Accounting Information Systems on the Relationship between Digital Technology and Strategic Performance of Electronic Companies The Mediating Role of Accounting Information Systems on the Relationship between Digital Technology and Strategic Performance of Electronic Companies 235310 10.22034/aimj.2025.553463.1657 FA Ali Ebrahimi Kordlar Associate Prof., Department of Accounting and Auditing, Faculty of Accounting and Financial Sciences, College of Management, University of Tehran, Tehran, Iran 0000-0003-4627-9388 Yahya Seyed Talebi MSc. Student, Department of Accounting and Auditing, Faculty of Accounting and Financial Sciences, College of Management, University of Tehran, Tehran, Iran Journal Article 2025 10 15 This study aimed to investigate the mediating role of accounting information systems in the relationship between digital technology and strategic performance and the moderating role of digital innovation in electronic companies. The importance of the subject stems from the fact that organizations in the era of digital transformation need to use new technologies and integrate them with information systems and innovative processes to achieve sustainable strategic performance. The research method is applied in terms of purpose and descriptive-analytical and survey in terms of implementation. The required data were collected using a standard questionnaire consisting of four main constructs. The statistical population includes companies active in the field of electronics and similar industries accepted on the Tehran Stock Exchange. Structural equation modeling based on the partial least square method was used to analyze the data. The research findings showed that digital technology does not have a significant direct effect on strategic performance and its role is more apparent in the form of an enabling and indirect factor. In contrast, accounting information systems played an effective role as a mediating variable in transmitting the effect of digital technology on strategic performance and significantly strengthened this relationship. The results also showed that digital innovation in the research population does not have a significant moderating role in this relationship, although it can act as an independent path to improve strategic performance. Overall, the results of the study indicate that investment in digital technology leads to improved strategic performance when it is accompanied by the development of accounting information systems and the application of digital innovations in business processes and models. This study aimed to investigate the mediating role of accounting information systems in the relationship between digital technology and strategic performance and the moderating role of digital innovation in electronic companies. The importance of the subject stems from the fact that organizations in the era of digital transformation need to use new technologies and integrate them with information systems and innovative processes to achieve sustainable strategic performance. The research method is applied in terms of purpose and descriptive-analytical and survey in terms of implementation. The required data were collected using a standard questionnaire consisting of four main constructs. The statistical population includes companies active in the field of electronics and similar industries accepted on the Tehran Stock Exchange. Structural equation modeling based on the partial least square method was used to analyze the data. The research findings showed that digital technology does not have a significant direct effect on strategic performance and its role is more apparent in the form of an enabling and indirect factor. In contrast, accounting information systems played an effective role as a mediating variable in transmitting the effect of digital technology on strategic performance and significantly strengthened this relationship. The results also showed that digital innovation in the research population does not have a significant moderating role in this relationship, although it can act as an independent path to improve strategic performance. Overall, the results of the study indicate that investment in digital technology leads to improved strategic performance when it is accompanied by the development of accounting information systems and the application of digital innovations in business processes and models. Digital Technology Strategic Performance accounting information systems Digital innovation https://www.aimj.ir/article_235310_7eafa59c166a0f0a974c8d03c0e8331d.pdf
Iranian Journal of Information Management 1735-8418 10 2 2025 02 19 Designing a Structural Model of Smart Intellectual Capital in Medical Universities Designing a Structural Model of Smart Intellectual Capital in Medical Universities 235497 10.22034/aimj.2025.510464.1629 FA Fateme Sohrabi PhD Candidate, Department of Management, Aliabad Katul Branch, Islamic Azad University, Aliabad Katul, Iran Roohalla Samiee Assistant Prof., Department of Management, Aliabad Katul Branch, Islamic Azad University, Aliabad Katul, Iran Alireza Mazidi Assistant Prof., Department of Management, Aliabad Katul Branch, Islamic Azad University, Aliabad Katul, Iran Journal Article 2025 03 04 Nowadays, considering the dynamic and complex conditions facing organizations, intellectual capital is becoming an important asset for organizations. The aim of this research was to design a structural model of intelligent intellectual capital in medical universities. This research was conducted in a descriptive and mixed exploratory manner. In the qualitative part, in order to identify the components, interviews were conducted with 10 academic experts in the field of management who were selected using a purposeful judgment method. In the quantitative part, the statistical population was 140 managers (senior, middle, operational) of the units of the University of Medical Sciences in Region One of the country, and the sample size was determined as 103 people based on the Krejci and Morgan table and by simple random sampling method. The findings of the qualitative part show that this model has 22 components in 5 dimensions (causal, contextual, intervening factors, strategies and actions, and consequences). Also, the findings of the quantitative section show that causal factors have an impact of 0.880 on intelligent intellectual capital, and intelligent intellectual capital, contextual and interfering factors have an impact of 0.371, 0.326 and 0.345 on strategies and actions, and strategies and actions also have an impact of 0.563 on outcomes. Nowadays, considering the dynamic and complex conditions facing organizations, intellectual capital is becoming an important asset for organizations. The aim of this research was to design a structural model of intelligent intellectual capital in medical universities. This research was conducted in a descriptive and mixed exploratory manner. In the qualitative part, in order to identify the components, interviews were conducted with 10 academic experts in the field of management who were selected using a purposeful judgment method. In the quantitative part, the statistical population was 140 managers (senior, middle, operational) of the units of the University of Medical Sciences in Region One of the country, and the sample size was determined as 103 people based on the Krejci and Morgan table and by simple random sampling method. The findings of the qualitative part show that this model has 22 components in 5 dimensions (causal, contextual, intervening factors, strategies and actions, and consequences). Also, the findings of the quantitative section show that causal factors have an impact of 0.880 on intelligent intellectual capital, and intelligent intellectual capital, contextual and interfering factors have an impact of 0.371, 0.326 and 0.345 on strategies and actions, and strategies and actions also have an impact of 0.563 on outcomes. intellectual capital SMART university Medical Sciences https://www.aimj.ir/article_235497_3a97b6f6db2b1ca75880f7f2a1ba01ee.pdf