Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Irikefe, P. O.; Falahat, M.; Zainudin, A. D.; Motaghi, H.
In: Journal of Cleaner Production, vol. 574, 2026, ISSN: 09596526 (ISSN).
Abstract | Links | BibTeX | Tags: Digital readiness, Dynamic capabilities theory, Dynamic capability theory, Dynamics capability, Efficiency, Entrepreneurial leadership, Environmental management, Financial inclusion, Financial inclusions, Information use, Investments, Management efficiency, Resource allocation, Resource management, Resource management efficiency, Responsible Consumption and production (SDG 12), sustainable development, Triple Bottom Line, Triple-bottom-line sustainability
@article{irikefeEntrepreneurialLeadershipResource2026,
title = {Entrepreneurial leadership and resource management efficiency as necessary conditions for SME sustainability: A moderated mediation analysis of digital readiness and financial inclusion},
author = {P. O. Irikefe and M. Falahat and A. D. Zainudin and H. Motaghi},
url = {https://www.scopus.com/pages/publications/105046462855?origin=resultslist},
doi = {10.1016/j.jclepro.2026.149116},
issn = {09596526 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Journal of Cleaner Production},
volume = {574},
publisher = {Elsevier Ltd},
abstract = {Small and medium enterprises (SMEs) are central to employment and value creation, yet pressures from sustainability transition expose endemic financing frictions and uneven digital readiness (DR), particularly in emerging markets. This study examines how SME capabilities viz.: entrepreneurial leadership (EL) and resource management efficiency (RME) associate with triple-bottom-line (TBL) sustainability across economic (ECOS), environmental (ENVS), and social (SOCS) pillars, whether firm-level financial inclusion (FI) statistically mediates capability-to-TBL associations, and whether DR conditions these associations. Using survey data from 429 Malaysian SMEs, we apply a sequential analytics design: Partial Least Square-Structural Equation Modelling to test direct, mediated, and interaction effects; followed by Necessary Condition Analysis (NCA) and Importance-Performance Map Analysis in the bid to identify bottlenecks and practical priorities. Results show that EL is positively associated with ECOS, ENVS, and SOCS; whereas RME is strongly positively associated with ECOS and ENVS but is not significant for SOCS. FI is TBL pillar-asymmetric: it bolsters ENVS and SOCS but exhibits a negative effect on ECOS, and the mediated effects through FI mirror the pattern. DR significantly strengthens the FI to TBL pathways, yet conditional indirect effects indicate that high DR can neutralise FI's economic drag without reliably improving ECOS. NCA sharpens the conclusion: high ECOS is unattainable without RME, while high ENVS and SOCS require EL-RME-FI jointly; DR is not a robust necessity condition. Practically, SMEs should tighten efficiency routines first, mobilise leadership for adoption, channel finance through verified upgrading milestones and invest in DR only where it improves monitoring, traceability and compliance. Copyright © 2026. Published by Elsevier Ltd.},
keywords = {Digital readiness, Dynamic capabilities theory, Dynamic capability theory, Dynamics capability, Efficiency, Entrepreneurial leadership, Environmental management, Financial inclusion, Financial inclusions, Information use, Investments, Management efficiency, Resource allocation, Resource management, Resource management efficiency, Responsible Consumption and production (SDG 12), sustainable development, Triple Bottom Line, Triple-bottom-line sustainability},
pubstate = {published},
tppubtype = {article}
}
Small and medium enterprises (SMEs) are central to employment and value creation, yet pressures from sustainability transition expose endemic financing frictions and uneven digital readiness (DR), particularly in emerging markets. This study examines how SME capabilities viz.: entrepreneurial leadership (EL) and resource management efficiency (RME) associate with triple-bottom-line (TBL) sustainability across economic (ECOS), environmental (ENVS), and social (SOCS) pillars, whether firm-level financial inclusion (FI) statistically mediates capability-to-TBL associations, and whether DR conditions these associations. Using survey data from 429 Malaysian SMEs, we apply a sequential analytics design: Partial Least Square-Structural Equation Modelling to test direct, mediated, and interaction effects; followed by Necessary Condition Analysis (NCA) and Importance-Performance Map Analysis in the bid to identify bottlenecks and practical priorities. Results show that EL is positively associated with ECOS, ENVS, and SOCS; whereas RME is strongly positively associated with ECOS and ENVS but is not significant for SOCS. FI is TBL pillar-asymmetric: it bolsters ENVS and SOCS but exhibits a negative effect on ECOS, and the mediated effects through FI mirror the pattern. DR significantly strengthens the FI to TBL pathways, yet conditional indirect effects indicate that high DR can neutralise FI's economic drag without reliably improving ECOS. NCA sharpens the conclusion: high ECOS is unattainable without RME, while high ENVS and SOCS require EL-RME-FI jointly; DR is not a robust necessity condition. Practically, SMEs should tighten efficiency routines first, mobilise leadership for adoption, channel finance through verified upgrading milestones and invest in DR only where it improves monitoring, traceability and compliance. Copyright © 2026. Published by Elsevier Ltd.
2.
Khosrojerdi, F.; Gagnon, S.; Valverde, R.
Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions Journal Article
In: Energies, vol. 18, no. 11, 2025, ISSN: 19961073 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Abstract | Links | BibTeX | Tags: Computer control systems, Condition, Electric power system control, Energy, Energy forecasting, Energy output, Maximum Power Point Tracking, MPPT, Photovoltaic arrays, Photovoltaic systems, Power, PSC, SDGs, Solar energy, Solar fuels, Solar heating, sustainable development, Sustainable energy development
@article{khosrojerdi_leveraging_2025,
title = {Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions},
author = {F. Khosrojerdi and S. Gagnon and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007798431&doi=10.3390%2Fen18112960&partnerID=40&md5=02986a1a6a4bcd62967f83e278b9edc6},
doi = {10.3390/en18112960},
issn = {19961073 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Energies},
volume = {18},
number = {11},
abstract = {In a photovoltaic (PV) system, shading caused by weather and environmental factors can significantly impact electricity production. For over a decade, artificial intelligence (AI) techniques have been applied to enhance energy production efficiency in the solar energy sector. This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. The findings highlight that AI contributes to the sustainable development of the solar power sector. Specifically, maximum power point tracking (MPPT) control systems, utilizing metaheuristic and computer-based algorithms, enable PV arrays to mitigate the impacts of shading effectively. The effect of shading on a PV module is also simulated using MATLAB R2018b. Using actual PV data from a solar power plant, power outputs are compared in two scenarios: (I) PV systems without a control system and (II) PV arrays equipped with MPPT boards. The System Advisor Model (SAM) is employed to calculate the monthly energy output of the case study. The results confirm that PV systems using MPPT technology generate significantly more monthly energy compared to those without MPPTs. © 2025 by the authors.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
keywords = {Computer control systems, Condition, Electric power system control, Energy, Energy forecasting, Energy output, Maximum Power Point Tracking, MPPT, Photovoltaic arrays, Photovoltaic systems, Power, PSC, SDGs, Solar energy, Solar fuels, Solar heating, sustainable development, Sustainable energy development},
pubstate = {published},
tppubtype = {article}
}
In a photovoltaic (PV) system, shading caused by weather and environmental factors can significantly impact electricity production. For over a decade, artificial intelligence (AI) techniques have been applied to enhance energy production efficiency in the solar energy sector. This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. The findings highlight that AI contributes to the sustainable development of the solar power sector. Specifically, maximum power point tracking (MPPT) control systems, utilizing metaheuristic and computer-based algorithms, enable PV arrays to mitigate the impacts of shading effectively. The effect of shading on a PV module is also simulated using MATLAB R2018b. Using actual PV data from a solar power plant, power outputs are compared in two scenarios: (I) PV systems without a control system and (II) PV arrays equipped with MPPT boards. The System Advisor Model (SAM) is employed to calculate the monthly energy output of the case study. The results confirm that PV systems using MPPT technology generate significantly more monthly energy compared to those without MPPTs. © 2025 by the authors.
3.
Falk, T. H.
The Internet of Senses for Healthcare 5.0: Enabling Technologies, Opportunities, and Challenges Journal Article
In: Healthcare in the Digital Age: Perspectives for Sustainable Innovation and Assessment, pp. 11–29, 2025, ISSN: 978-981961437-0 (ISBN); 978-981961436-3 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Enabling technologies, Environmental impact, Health care, Healthcare 5.0, Human sensing, Immersive, Medical applications, Medical informatics, Multisensory, Multisensory Immersive Reality, Olfaction, Sustainability, sustainable development, Technology challenges, Technology opportunities, User experience, User interfaces, Users' experiences, virtual reality
@article{falkInternetSensesHealthcare2025,
title = {The Internet of Senses for Healthcare 5.0: Enabling Technologies, Opportunities, and Challenges},
author = {T. H. Falk},
url = {https://www.scopus.com/pages/publications/105023337478?origin=resultslist},
doi = {10.1007/978-981-96-1437-0_2},
issn = {978-981961437-0 (ISBN); 978-981961436-3 (ISBN)},
year = {2025},
date = {2025-01-01},
journal = {Healthcare in the Digital Age: Perspectives for Sustainable Innovation and Assessment},
pages = {11–29},
publisher = {Springer Science+Business Media},
abstract = {Multisensory virtual reality immerses users in a virtual setting by stimulating all their senses. Coupled with artificial intelligence, next-generation communications, and human sensing technologies, the so-called Internet of Senses (IoS) will drive healthcare 5.0 applications for the betterment of humankind. Multisensory nature exposure experiences have already shown to reduce symptoms of anxiety. The integration of haptic technologies with olfactory stimuli could revolutionise remote medical applications, bringing specialised care to remote communities. Having this said, while the number of applications is numerous, we need to stop and think about the challenges that will arise, such as the environmental impact of developing and running these tools. Moreover, while these tools can increase accessibility to those that may have, for example, mobility issues, it can, on the other hand, limit usage for those with limited financial resources needed to run these tools. As such, do-it-yourself and/or open-source tools will be crucial to ensure equitable access worldwide. In this chapter, a description is given of the work done (and ongoing) by the author and his collaborators on how to enable healthcare 5.0 applications based on the IoS, how to better democratise them, and make them safer for users and the planet. © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.},
keywords = {Artificial intelligence, Enabling technologies, Environmental impact, Health care, Healthcare 5.0, Human sensing, Immersive, Medical applications, Medical informatics, Multisensory, Multisensory Immersive Reality, Olfaction, Sustainability, sustainable development, Technology challenges, Technology opportunities, User experience, User interfaces, Users' experiences, virtual reality},
pubstate = {published},
tppubtype = {article}
}
Multisensory virtual reality immerses users in a virtual setting by stimulating all their senses. Coupled with artificial intelligence, next-generation communications, and human sensing technologies, the so-called Internet of Senses (IoS) will drive healthcare 5.0 applications for the betterment of humankind. Multisensory nature exposure experiences have already shown to reduce symptoms of anxiety. The integration of haptic technologies with olfactory stimuli could revolutionise remote medical applications, bringing specialised care to remote communities. Having this said, while the number of applications is numerous, we need to stop and think about the challenges that will arise, such as the environmental impact of developing and running these tools. Moreover, while these tools can increase accessibility to those that may have, for example, mobility issues, it can, on the other hand, limit usage for those with limited financial resources needed to run these tools. As such, do-it-yourself and/or open-source tools will be crucial to ensure equitable access worldwide. In this chapter, a description is given of the work done (and ongoing) by the author and his collaborators on how to enable healthcare 5.0 applications based on the IoS, how to better democratise them, and make them safer for users and the planet. © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
4.
Khosrojerdi, F.; Gagnon, S.; Valverde, R.
Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions Journal Article
In: Energies, vol. 18, no. 11, 2025, ISSN: 19961073 (ISSN).
Abstract | Links | BibTeX | Tags: Computer control systems, Condition, Electric power system control, Energy, Energy forecasting, Energy output, Maximum Power Point Tracking, MPPT, Photovoltaic arrays, Photovoltaic systems, Power, PSC, SDGs, Solar energy, Solar fuels, Solar heating, sustainable development, Sustainable energy development
@article{khosrojerdiLeveragingAISustainable2025,
title = {Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions},
author = {F. Khosrojerdi and S. Gagnon and R. Valverde},
url = {https://www.scopus.com/pages/publications/105007798431?origin=resultslist},
doi = {10.3390/en18112960},
issn = {19961073 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Energies},
volume = {18},
number = {11},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {In a photovoltaic (PV) system, shading caused by weather and environmental factors can significantly impact electricity production. For over a decade, artificial intelligence (AI) techniques have been applied to enhance energy production efficiency in the solar energy sector. This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. The findings highlight that AI contributes to the sustainable development of the solar power sector. Specifically, maximum power point tracking (MPPT) control systems, utilizing metaheuristic and computer-based algorithms, enable PV arrays to mitigate the impacts of shading effectively. The effect of shading on a PV module is also simulated using MATLAB R2018b. Using actual PV data from a solar power plant, power outputs are compared in two scenarios: (I) PV systems without a control system and (II) PV arrays equipped with MPPT boards. The System Advisor Model (SAM) is employed to calculate the monthly energy output of the case study. The results confirm that PV systems using MPPT technology generate significantly more monthly energy compared to those without MPPTs. © 2025 by the authors.},
keywords = {Computer control systems, Condition, Electric power system control, Energy, Energy forecasting, Energy output, Maximum Power Point Tracking, MPPT, Photovoltaic arrays, Photovoltaic systems, Power, PSC, SDGs, Solar energy, Solar fuels, Solar heating, sustainable development, Sustainable energy development},
pubstate = {published},
tppubtype = {article}
}
In a photovoltaic (PV) system, shading caused by weather and environmental factors can significantly impact electricity production. For over a decade, artificial intelligence (AI) techniques have been applied to enhance energy production efficiency in the solar energy sector. This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. The findings highlight that AI contributes to the sustainable development of the solar power sector. Specifically, maximum power point tracking (MPPT) control systems, utilizing metaheuristic and computer-based algorithms, enable PV arrays to mitigate the impacts of shading effectively. The effect of shading on a PV module is also simulated using MATLAB R2018b. Using actual PV data from a solar power plant, power outputs are compared in two scenarios: (I) PV systems without a control system and (II) PV arrays equipped with MPPT boards. The System Advisor Model (SAM) is employed to calculate the monthly energy output of the case study. The results confirm that PV systems using MPPT technology generate significantly more monthly energy compared to those without MPPTs. © 2025 by the authors.
5.
Saini, H. K.; Rani, S.; Ouaissa, M.; Ouaissa, M.; Houda, Z. A. El; Moudoud, H.
CRC Press, 2025, ISBN: 978-100364032-5 (ISBN); 978-104107046-7 (ISBN), (Journal Abbreviation: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain. Pages: 283 Publication Title: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain.).
Abstract | Links | BibTeX | Tags: Case-studies, Computer forensics, Forensic Techniques, Internet of things, Machine data, Medical computing, Medical data, Medical practitioner, Network security, Next generation Internet, Patient data, Real-world, Security challenges, Security solutions, sustainable development
@book{sainiDigitalForensicsNextGeneration2025,
title = {Digital Forensics in Next-Generation Internet of Medical Things: Balancing Security and Sustainability},
author = {H. K. Saini and S. Rani and M. Ouaissa and M. Ouaissa and Z. A. El Houda and H. Moudoud},
url = {https://www.scopus.com/pages/publications/105024400792?origin=resultslist},
doi = {10.1201/9781003640325},
isbn = {978-100364032-5 (ISBN); 978-104107046-7 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {CRC Press},
series = {Digital Forensics in Next-Generation Internet of Medical Things: Balancing Security and Sustainability},
abstract = {This book provides a comprehensive exploration of the security challenges and solutions with digital sustainability in the rapidly evolving digital landscape of digital forensics. It explores the details of protecting Internet of Medical Things (IoMT) environments, where the medical data, patient data, and machine data are at high risk with the digital experiences. The book seeks to provide researchers, medical practitioners, and IT specialists with important information. It aims to set the stage for a future in which security and efficiency in IoMT smoothly blend through real-world case studies. Key themes cover IoMT-specific forensic techniques, the difficulties of striking a balance between environmental responsibility and security, and creative solutions that combine the two viewpoints. © 2026 selection and editorial matter, Hemant Kumar Saini, Sita Rani, Mariya Ouaissa, Mariyam Ouaissa, Zakaria Abou El Houda, and Hajar Moudoud. All rights reserved.},
note = {Journal Abbreviation: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain.
Pages: 283
Publication Title: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain.},
keywords = {Case-studies, Computer forensics, Forensic Techniques, Internet of things, Machine data, Medical computing, Medical data, Medical practitioner, Network security, Next generation Internet, Patient data, Real-world, Security challenges, Security solutions, sustainable development},
pubstate = {published},
tppubtype = {book}
}
This book provides a comprehensive exploration of the security challenges and solutions with digital sustainability in the rapidly evolving digital landscape of digital forensics. It explores the details of protecting Internet of Medical Things (IoMT) environments, where the medical data, patient data, and machine data are at high risk with the digital experiences. The book seeks to provide researchers, medical practitioners, and IT specialists with important information. It aims to set the stage for a future in which security and efficiency in IoMT smoothly blend through real-world case studies. Key themes cover IoMT-specific forensic techniques, the difficulties of striking a balance between environmental responsibility and security, and creative solutions that combine the two viewpoints. © 2026 selection and editorial matter, Hemant Kumar Saini, Sita Rani, Mariya Ouaissa, Mariyam Ouaissa, Zakaria Abou El Houda, and Hajar Moudoud. All rights reserved.
6.
Khosrojerdi, F.; Gagnon, S.; Valverde, R.
Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions Journal Article
In: Energies, vol. 18, no. 11, 2025, ISSN: 19961073 (ISSN).
Abstract | Links | BibTeX | Tags: Computer control systems, Condition, Electric power system control, Energy, Energy forecasting, Energy output, Maximum Power Point Tracking, MPPT, Photovoltaic arrays, Photovoltaic systems, Power, PSC, SDGs, Solar energy, Solar fuels, Solar heating, sustainable development, Sustainable energy development
@article{khosrojerdiLeveragingAISustainable2025a,
title = {Leveraging AI for Sustainable Energy Development in Solar Power Plants Operating Under Shading Conditions},
author = {F. Khosrojerdi and S. Gagnon and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007798431&doi=10.3390%2Fen18112960&partnerID=40&md5=02986a1a6a4bcd62967f83e278b9edc6},
doi = {10.3390/en18112960},
issn = {19961073 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Energies},
volume = {18},
number = {11},
abstract = {In a photovoltaic (PV) system, shading caused by weather and environmental factors can significantly impact electricity production. For over a decade, artificial intelligence (AI) techniques have been applied to enhance energy production efficiency in the solar energy sector. This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. The findings highlight that AI contributes to the sustainable development of the solar power sector. Specifically, maximum power point tracking (MPPT) control systems, utilizing metaheuristic and computer-based algorithms, enable PV arrays to mitigate the impacts of shading effectively. The effect of shading on a PV module is also simulated using MATLAB R2018b. Using actual PV data from a solar power plant, power outputs are compared in two scenarios: (I) PV systems without a control system and (II) PV arrays equipped with MPPT boards. The System Advisor Model (SAM) is employed to calculate the monthly energy output of the case study. The results confirm that PV systems using MPPT technology generate significantly more monthly energy compared to those without MPPTs. © 2025 by the authors.},
keywords = {Computer control systems, Condition, Electric power system control, Energy, Energy forecasting, Energy output, Maximum Power Point Tracking, MPPT, Photovoltaic arrays, Photovoltaic systems, Power, PSC, SDGs, Solar energy, Solar fuels, Solar heating, sustainable development, Sustainable energy development},
pubstate = {published},
tppubtype = {article}
}
In a photovoltaic (PV) system, shading caused by weather and environmental factors can significantly impact electricity production. For over a decade, artificial intelligence (AI) techniques have been applied to enhance energy production efficiency in the solar energy sector. This paper demonstrates how AI-based control systems can improve energy output in a solar power plant under shading conditions. The findings highlight that AI contributes to the sustainable development of the solar power sector. Specifically, maximum power point tracking (MPPT) control systems, utilizing metaheuristic and computer-based algorithms, enable PV arrays to mitigate the impacts of shading effectively. The effect of shading on a PV module is also simulated using MATLAB R2018b. Using actual PV data from a solar power plant, power outputs are compared in two scenarios: (I) PV systems without a control system and (II) PV arrays equipped with MPPT boards. The System Advisor Model (SAM) is employed to calculate the monthly energy output of the case study. The results confirm that PV systems using MPPT technology generate significantly more monthly energy compared to those without MPPTs. © 2025 by the authors.
7.
Masuda, Y.; Taylor, J.; Gagnon, S.; Raisinghani, M.; Jain, R.; Jacobson, I.
IS LEADERSHIP EDUCATION FOR SUSTAINABLE INNOVATION AND DIGITAL TRANSFORMATION: EFFECTIVENESS AND CHALLENGES Proceedings Article
In: Proc. AIS SIGED Int. Conf. Inf. Syst. Educ. Res., ICISER, Association for Information Systems, 2024.
Abstract | Links | BibTeX | Tags: Data quality, Digital Innovation, Digital innovations, Digital transformation, Education computing, Enterprise Architecture, Human resource management, Information systems, IS Community, IS leadership, Knowledge management, Leadership education, Rapid growth, Sustainability, sustainable development, Value creation, Workers'
@inproceedings{masuda_is_2024,
title = {IS LEADERSHIP EDUCATION FOR SUSTAINABLE INNOVATION AND DIGITAL TRANSFORMATION: EFFECTIVENESS AND CHALLENGES},
author = {Y. Masuda and J. Taylor and S. Gagnon and M. Raisinghani and R. Jain and I. Jacobson},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105010296891&partnerID=40&md5=73b27057e28ff407e1a59116e34be23c},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. AIS SIGED Int. Conf. Inf. Syst. Educ. Res., ICISER},
publisher = {Association for Information Systems},
abstract = {The rapid growth of AI is enabling new capabilities for organizations in knowledge management and requiring new worker capabilities in value creation. New generative AI capabilities can facilitate improved data quality and better worker support. However, best practices for effective and safe use of generative AI are still being established. Scholars must continue to develop their curriculum and pedagogy to prepare students for these new challenges. This panel focuses on educating members for Sustainable Leadership positions in IS within the context of Digital Innovation and Transformation, utilizing the framework that encompasses Digital Strategy and Enterprise Architecture. © 2024 ICISER. All Rights Reserved.},
keywords = {Data quality, Digital Innovation, Digital innovations, Digital transformation, Education computing, Enterprise Architecture, Human resource management, Information systems, IS Community, IS leadership, Knowledge management, Leadership education, Rapid growth, Sustainability, sustainable development, Value creation, Workers'},
pubstate = {published},
tppubtype = {inproceedings}
}
The rapid growth of AI is enabling new capabilities for organizations in knowledge management and requiring new worker capabilities in value creation. New generative AI capabilities can facilitate improved data quality and better worker support. However, best practices for effective and safe use of generative AI are still being established. Scholars must continue to develop their curriculum and pedagogy to prepare students for these new challenges. This panel focuses on educating members for Sustainable Leadership positions in IS within the context of Digital Innovation and Transformation, utilizing the framework that encompasses Digital Strategy and Enterprise Architecture. © 2024 ICISER. All Rights Reserved.
8.
Masuda, Y.; Taylor, J.; Gagnon, S.; Raisinghani, M.; Jain, R.; Jacobson, I.
IS LEADERSHIP EDUCATION FOR SUSTAINABLE INNOVATION AND DIGITAL TRANSFORMATION: EFFECTIVENESS AND CHALLENGES Proceedings Article
In: Proc. AIS SIGED Int. Conf. Inf. Syst. Educ. Res., ICISER, Association for Information Systems, 2024.
Abstract | Links | BibTeX | Tags: Data quality, Digital Innovation, Digital innovations, Digital transformation, Education computing, Enterprise Architecture, Human resource management, Information systems, IS Community, IS leadership, Knowledge management, Leadership education, Rapid growth, Sustainability, sustainable development, Value creation, Workers'
@inproceedings{masudaLEADERSHIPEDUCATIONSUSTAINABLE2024,
title = {IS LEADERSHIP EDUCATION FOR SUSTAINABLE INNOVATION AND DIGITAL TRANSFORMATION: EFFECTIVENESS AND CHALLENGES},
author = {Y. Masuda and J. Taylor and S. Gagnon and M. Raisinghani and R. Jain and I. Jacobson},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105010296891&partnerID=40&md5=73b27057e28ff407e1a59116e34be23c},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. AIS SIGED Int. Conf. Inf. Syst. Educ. Res., ICISER},
publisher = {Association for Information Systems},
abstract = {The rapid growth of AI is enabling new capabilities for organizations in knowledge management and requiring new worker capabilities in value creation. New generative AI capabilities can facilitate improved data quality and better worker support. However, best practices for effective and safe use of generative AI are still being established. Scholars must continue to develop their curriculum and pedagogy to prepare students for these new challenges. This panel focuses on educating members for Sustainable Leadership positions in IS within the context of Digital Innovation and Transformation, utilizing the framework that encompasses Digital Strategy and Enterprise Architecture. © 2024 ICISER. All Rights Reserved.},
keywords = {Data quality, Digital Innovation, Digital innovations, Digital transformation, Education computing, Enterprise Architecture, Human resource management, Information systems, IS Community, IS leadership, Knowledge management, Leadership education, Rapid growth, Sustainability, sustainable development, Value creation, Workers'},
pubstate = {published},
tppubtype = {inproceedings}
}
The rapid growth of AI is enabling new capabilities for organizations in knowledge management and requiring new worker capabilities in value creation. New generative AI capabilities can facilitate improved data quality and better worker support. However, best practices for effective and safe use of generative AI are still being established. Scholars must continue to develop their curriculum and pedagogy to prepare students for these new challenges. This panel focuses on educating members for Sustainable Leadership positions in IS within the context of Digital Innovation and Transformation, utilizing the framework that encompasses Digital Strategy and Enterprise Architecture. © 2024 ICISER. All Rights Reserved.