2025
Prasetyo, Moonita Limiany; Peranginangin, Randall Aginta; Martinovic, Nada; Ichsan, Mohammad; Wicaksono, Hendro
In: Journal of Open Innovation: Technology, Market, and Complexity, vol. 11, iss. 1, no. 100445, 2025.
Abstract | Links | BibTeX | Tags: artificial intelligence, industry 4.0, innovation management, project management
@article{nokey,
title = {Artificial Intelligence in Open Innovation Project Management: A Systematic Literature Review on Technologies, Applications, and Integration Requirements},
author = {Moonita Limiany Prasetyo and Randall Aginta Peranginangin and Nada Martinovic and Mohammad Ichsan and Hendro Wicaksono},
url = {https://www.sciencedirect.com/science/article/pii/S2199853124002397},
doi = {https://doi.org/10.1016/j.joitmc.2024.100445},
year = {2025},
date = {2025-03-01},
urldate = {2025-03-01},
journal = {Journal of Open Innovation: Technology, Market, and Complexity},
volume = {11},
number = {100445},
issue = {1},
abstract = {This study aims to provide insights to support organizations in building effective strategies for adopting Artificial Intelligence (AI) and improving project management processes. It focuses on open innovation projects. It employs a comprehensive and systematic literature review (SLR). A total of 365 publications have been chosen from a pool of 1265 papers in the IEEE and Scopus databases. The study develops a framework for literature synthesis guided by five research questions. Those questions address AI technologies, project management tasks, industries adopting AI, and requirements for successful adoption. The analysis reveals that Machine Learning is widely employed in project management, especially for predicting analytics, optimizing resources, and managing risks. AI improves open innovation project management by integrating diverse knowledge sources, enhancing collaboration, and providing strategic insights for decision-making. This study also found that AI adoption depends not only on technical infrastructure, integration with existing systems, and data readiness but also on leadership support, strategic alignment, financial resources, skills development, and organizational culture. The findings also highlight the importance of aligning AI initiatives with open innovation requirements, where collaboration, agility, and external knowledge integrations are crucial. The construction sector is at the forefront of adopting AI. This study fills a significant gap in previous research by identifying the technical and non-technical prerequisites for effectively incorporating AI into open innovation project management methodologies.},
keywords = {artificial intelligence, industry 4.0, innovation management, project management},
pubstate = {published},
tppubtype = {article}
}
This study aims to provide insights to support organizations in building effective strategies for adopting Artificial Intelligence (AI) and improving project management processes. It focuses on open innovation projects. It employs a comprehensive and systematic literature review (SLR). A total of 365 publications have been chosen from a pool of 1265 papers in the IEEE and Scopus databases. The study develops a framework for literature synthesis guided by five research questions. Those questions address AI technologies, project management tasks, industries adopting AI, and requirements for successful adoption. The analysis reveals that Machine Learning is widely employed in project management, especially for predicting analytics, optimizing resources, and managing risks. AI improves open innovation project management by integrating diverse knowledge sources, enhancing collaboration, and providing strategic insights for decision-making. This study also found that AI adoption depends not only on technical infrastructure, integration with existing systems, and data readiness but also on leadership support, strategic alignment, financial resources, skills development, and organizational culture. The findings also highlight the importance of aligning AI initiatives with open innovation requirements, where collaboration, agility, and external knowledge integrations are crucial. The construction sector is at the forefront of adopting AI. This study fills a significant gap in previous research by identifying the technical and non-technical prerequisites for effectively incorporating AI into open innovation project management methodologies.
2023
Sarafanov, Egor; Valilai, Omid Fatahi; Wicaksono, Hendro
Causal Analysis of Artificial Intelligence Adoption in Project Management Proceedings Article
In: Intelligent Systems Conference, pp. 245–264, Springer Nature Switzerland Cham 2023.
BibTeX | Tags: artificial intelligence, causal inference, data science, project management, technology adoption
@inproceedings{sarafanov2023causal,
title = {Causal Analysis of Artificial Intelligence Adoption in Project Management},
author = {Egor Sarafanov and Omid Fatahi Valilai and Hendro Wicaksono},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {Intelligent Systems Conference},
pages = {245–264},
organization = {Springer Nature Switzerland Cham},
keywords = {artificial intelligence, causal inference, data science, project management, technology adoption},
pubstate = {published},
tppubtype = {inproceedings}
}