Noor, A. F. Mohamed; Moghavvemi, S.; Tajudeen, F. P.; Motaghi, H.; Salehi, A. Cybersecurity Readiness: A Review via Dynamic Capabilities Article d'actes Dans: M., Myers; R.A., Alias; W.F., Boh (Ed.): Pac. Asia Conf. Inf. Syst., Association for Information Systems, 2025, ISBN: 26896354 (ISSN). @inproceedings{mohamed_noor_cybersecurity_2025,
title = {Cybersecurity Readiness: A Review via Dynamic Capabilities},
author = {A. F. Mohamed Noor and S. Moghavvemi and F. P. Tajudeen and H. Motaghi and A. Salehi},
editor = {Myers M. and Alias R.A. and Boh W.F.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105029273577&partnerID=40&md5=2d20002e3605f51d6e87bd24f7af0cc0},
isbn = {26896354 (ISSN)},
year = {2025},
date = {2025-01-01},
booktitle = {Pac. Asia Conf. Inf. Syst.},
publisher = {Association for Information Systems},
abstract = {Understanding the factors influencing cybersecurity readiness is crucial for strategic investment in cyber capabilities. However, there is a gap in applying Dynamic Capabilities (DC) theory, which focuses on organizational agility in adapting to changing environments. This study fills this gap by using DC theory to analyze and categorize existing literature, offering a framework to classify cybersecurity readiness factors across different stages. This approach enhances our understanding of how organizations maintain a competitive edge amidst evolving cyber threats. The study addresses the following research question: What are the key factors influencing cybersecurity readiness in organizations, as discussed in literature from 2014 to 2023? Utilizing a thematic review with Atlas.ti 23, it examines literature from 2014 to 2023, providing a broad perspective on relevant factors. By applying DC theory, this research offers valuable insights for academics, organizations, and policymakers, aiding in strategy development and informed policymaking. © 2025, Association for Information Systems. All rights reserved.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Understanding the factors influencing cybersecurity readiness is crucial for strategic investment in cyber capabilities. However, there is a gap in applying Dynamic Capabilities (DC) theory, which focuses on organizational agility in adapting to changing environments. This study fills this gap by using DC theory to analyze and categorize existing literature, offering a framework to classify cybersecurity readiness factors across different stages. This approach enhances our understanding of how organizations maintain a competitive edge amidst evolving cyber threats. The study addresses the following research question: What are the key factors influencing cybersecurity readiness in organizations, as discussed in literature from 2014 to 2023? Utilizing a thematic review with Atlas.ti 23, it examines literature from 2014 to 2023, providing a broad perspective on relevant factors. By applying DC theory, this research offers valuable insights for academics, organizations, and policymakers, aiding in strategy development and informed policymaking. © 2025, Association for Information Systems. All rights reserved. |
Nosrati, S.; Motaghi, H. The AI Complacency Model: Integrating Bounded Rationality and Information Processing Article d'actes Dans: Am. Conf. Inf. Syst., AMCIS, p. 4590–4599, Association for Information Systems, 2025, ISBN: 979-833132774-3 (ISBN). @inproceedings{nosrati_ai_2025,
title = {The AI Complacency Model: Integrating Bounded Rationality and Information Processing},
author = {S. Nosrati and H. Motaghi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105025349267&partnerID=40&md5=14d676bedd3ea18921ed24a830889a8b},
isbn = {979-833132774-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Am. Conf. Inf. Syst., AMCIS},
volume = {7},
pages = {4590–4599},
publisher = {Association for Information Systems},
abstract = {This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved. |
Nosratabadi, S.; Bahrami, P.; Motaghi, H.; Yusof, M.; Kharuddin, A. F. How Do Human Capital Empowerments Constitute the Organizational Performance? Article de journal Dans: Lecture Notes in Networks and Systems, vol. 487, p. 467–481, 2023, ISSN: 23673370, (ISBN: 9783031080838). @article{nosratabadi_how_2023,
title = {How Do Human Capital Empowerments Constitute the Organizational Performance?},
author = {S. Nosratabadi and P. Bahrami and H. Motaghi and M. Yusof and A. F. Kharuddin},
editor = {Hamdan A. Alareeni B.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135086416&doi=10.1007%2f978-3-031-08084-5_34&partnerID=40&md5=79b9b99499ef514ac67bc2b3abe8a0a5},
doi = {10.1007/978-3-031-08084-5_34},
issn = {23673370},
year = {2023},
date = {2023-01-01},
journal = {Lecture Notes in Networks and Systems},
volume = {487},
pages = {467–481},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Much research has proven the effect of human capital on the organizational performance; the present study demonstrates how this causal relationship take place in the reality. In other words, in this research, first, organizational factors that cause human capital to flourish and be empowered are identified, and then their effects on the factors that shape the performance of an organization are identified. Hence, the main objective of this study was to examine the impact of the organizational factors empowering human capital on the organizational performance enablers. To do so, a questionnaire is administrated and Linear regression analysis using SPSS 22.0 applied for data analysis. According to the results, human capital empowerment factors have a statistically significant impact on the performance enablers. Finding disclosed that an effective performance evaluation system and effective leadership, which empower human capital in the organization, have a positive significant effect on the organizational performance. The findings indicate that organizations with an effective performance appraisal system and effective leadership not only provide a platform in which human capital is identified and grown, but also improve the factors that shape the performance of an organization. This research contributes to the literature on human resources, human capital, organizational management, and ultimately organizational performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
note = {ISBN: 9783031080838},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Much research has proven the effect of human capital on the organizational performance; the present study demonstrates how this causal relationship take place in the reality. In other words, in this research, first, organizational factors that cause human capital to flourish and be empowered are identified, and then their effects on the factors that shape the performance of an organization are identified. Hence, the main objective of this study was to examine the impact of the organizational factors empowering human capital on the organizational performance enablers. To do so, a questionnaire is administrated and Linear regression analysis using SPSS 22.0 applied for data analysis. According to the results, human capital empowerment factors have a statistically significant impact on the performance enablers. Finding disclosed that an effective performance evaluation system and effective leadership, which empower human capital in the organization, have a positive significant effect on the organizational performance. The findings indicate that organizations with an effective performance appraisal system and effective leadership not only provide a platform in which human capital is identified and grown, but also improve the factors that shape the performance of an organization. This research contributes to the literature on human resources, human capital, organizational management, and ultimately organizational performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
