Publication

@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}

}

@article{nokey,

title = {Interdependencies in Industry 4.0 Maturity: Fuzzy MCDA Analysis for Open Innovation in Developing Countries},

author = {Linda Salma Angreani and Faris Dzaudan Qadri and Annas Vijaya and Rana Manahil and Isabella Marquez Petrone and Nabilah and Ahmad Fauzi and Tasya Santi Rahmawati and Hendro Wicaksono},

url = {https://www.sciencedirect.com/science/article/pii/S2199853124001768},

doi = {https://doi.org/10.1016/j.joitmc.2024.100382},

isbn = {2199-8531},

year  = {2024},

date = {2024-09-25},

urldate = {2024-09-25},

journal = {Journal of Open Innovation: Technology, Market, and Complexity},

abstract = {The emergence of Industry 4.0 (I4.0) is reshaping industries worldwide, driven by rapid technological progress and the need for open innovation. This study focuses on understanding the interdependencies of driving factors of I4.0 maturity in developing countries using Fuzzy Multi-Criteria Decision Analysis (MCDA) methods. By analyzing Indonesia, Pakistan, and Venezuela, the research aims to foster open innovation and address the unique challenges these nations face in adopting I4.0 technologies. I4.0 maturity models are essential for evaluating current maturity levels and identifying areas for improvement. However, the complexity and interdependence of various factors—ranging from data science and technology to policy, governance, and open innovation dynamics, such as social open innovation and the role of SMEs—complicate this process. This study employs Fuzzy TOPSIS and Fuzzy DEMATEL to identify the critical factors influencing I4.0 maturity and analyze their interdependencies and prioritization. The results indicate that 'Data and Information' and 'Willingness to Change' are crucial across all countries, while strategic differences between large enterprises and SMEs highlight the need for tailored approaches. This research highlights the importance of continuous IT investment, digital leadership, collaborative ecosystems, and agile strategies in fostering open innovation and driving I4.0 adoption. This research contributes to the theoretical and practical understanding of I4.0 maturity, offering valuable insights for practitioners and academics to explore the dynamic interactions of I4.0 factors and their impact on operational efficiency.},

keywords = {industry 4.0, innovation management, multi criteria decision making, TOPSIS},

pubstate = {published},

tppubtype = {article}

}

@article{sukoco2023comparative,

title = {Comparative study of ASEAN research productivity},

author = {Badri Munir Sukoco and Rizky Ananda Putra and Humam Nur Muqaffi and Muhammad Vinka Lutfian and Hendro Wicaksono},

url = {https://journals.sagepub.com/doi/10.1177/21582440221145157},

doi = {https://doi.org/10.1177/21582440221145157},

year  = {2023},

date = {2023-01-03},

urldate = {2023-01-01},

journal = {Sage Open},

volume = {13},

number = {1},

pages = {21582440221145157},

publisher = {SAGE Publications Sage CA: Los Angeles, CA},

abstract = {Research productivity has become one of the main indicators used by higher education institutions (HEIs) as well as the country to support their innovation capability. This study purposely describes the research productivity among ASEAN countries, which is considered to be the world’s current economic hotspot. By using SciVal database to examine the literature over the last 10 years, we describe productivity, citation impact, and economic impact metrics. The findings indicate that Singapore is superior in terms of publication quality (citation) and patents while Malaysia is leading in terms of the number of scientific research. Interestingly, Indonesia’s scientific publication growth has the highest percentage. Furthermore, Engineering & Technology and Life Sciences & Medicine are the two major contributors to ASEAN research productivity. These subjects could be the major locomotives for ASEAN countries to use to sustain their competitiveness if the leaders can transform it into successful commercialization.

},

keywords = {innovation management, research management},

pubstate = {published},

tppubtype = {article}

}

@article{hamsal2023impact,

title = {The impact of environmental turbulence on business sustainability through organisational resilience and dynamic capabilities},

author = {Mohammad Hamsal and Mohammad Ichsan and Hendro Wicaksono},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {International Journal of Business Environment},

volume = {14},

number = {4},

pages = {417–439},

publisher = {Inderscience Publishers (IEL)},

keywords = {innovation management},

pubstate = {published},

tppubtype = {article}

}