Publication

@article{yuniaristanto2024estimating,

title = {Estimating the market share of electric motorcycles: A system dynamics approach with the policy mix and sustainable life cycle costs},

author = {Yuniaristanto and Wahyudi Sutopo and Muhammad Hisjam and Hendro Wicaksono},

url = {https://www.sciencedirect.com/science/article/pii/S0301421524003653},

doi = {https://doi.org/10.1016/j.enpol.2024.114345},

year  = {2024},

date = {2024-12-01},

urldate = {2024-01-01},

journal = {Energy Policy},

volume = {195},

pages = {114345},

publisher = {Elsevier},

abstract = {Introducing electric vehicles is critical to maintaining air quality and reducing carbon emissions. The Indonesian government has issued several regulations to stimulate the diffusion of electric vehicles. This research attempts to forecast the electric vehicle market share, especially electric motorcycles, by involving the policy mix and sustainable life cycle costs. We propose a system dynamics approach that takes into account a policy mix including 0% down payment without credit interest subsidies, tax abolition, expansion of charging station network, and sustainable life cycle costs, i.e., total cost of ownership, social, and environment. The system dynamics model has four modules: the electric motorcycle cost, the conventional motorcycle cost, the economy module, and the consumer market. The simulation results show that the electric motorcycle market share will increase positively in 2021–2030, reaching 5.7% in 2030. Based on the scenario simulation results, providing more charging stations and vehicle tax abolition can significantly boost the market share of electric motorcycles in Indonesia. The study provides valuable insights for policymakers in formulating more appropriate policy instruments to promote electric vehicle diffusion in Indonesia.



},

keywords = {e-mobility, sustainability, system dynamics, technology adoption, transportation},

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{sutopo2024exploring,

title = {Exploring the determinants of intention to purchase electric motorcycles: the role of national culture in the UTAUT},

author = {Wahyudi Sutopo and Muhammad Hisjam and Hendro Wicaksono and others},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Transportation research part F: traffic psychology and behaviour},

volume = {100},

pages = {475–492},

publisher = {Pergamon},

keywords = {data science, sustainability, technology adoption},

pubstate = {published},

tppubtype = {article}

}

@article{thapaliya2024power,

title = {Power Consumption and Processing Time Estimation of CNC Machines Using Explainable Artificial Intelligence (XAI)},

author = {Suman Thapaliya and Omid Fatahi Valilai and Hendro Wicaksono},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Procedia Computer Science},

volume = {232},

pages = {861–870},

publisher = {Elsevier},

keywords = {energy management, explainable AI, machine learning, manufacturing},

pubstate = {published},

tppubtype = {article}

}

@article{habtemichael2024nft,

title = {NFT based Digital Twins for Tracing Value Added Creation in Manufacturing Supply Chains},

author = {Noah Habtemichael and Hendro Wicaksono and Omid Fatahi Valilai},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Procedia Computer Science},

volume = {232},

pages = {2841–2846},

publisher = {Elsevier},

keywords = {digital twins, supply chain management},

pubstate = {published},

tppubtype = {article}

}

@article{mechai2024causal,

title = {Causal Inference in Supply Chain Management: How Does Ever Given Accident at the Suez Canal Affect the Prices of Shipping Containers?},

author = {Nadhir Mechai and Hendro Wicaksono},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Procedia Computer Science},

volume = {232},

pages = {3173–3182},

publisher = {Elsevier},

keywords = {causal AI, causal inference},

pubstate = {published},

tppubtype = {article}

}

@article{wicaksono2024artificial,

title = {Artificial-intelligence-enabled dynamic demand response system for maximizing the use of renewable electricity in production processes},

author = {Hendro Wicaksono and Martin Trat and Atit Bashyal and Tina Boroukhian and Mine Felder and Mischa Ahrens and Janek Bender and Sebastian Groß and Daniel Steiner and Christoph July and others},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {The International Journal of Advanced Manufacturing Technology},

pages = {1–25},

publisher = {Springer London},

keywords = {demand response system, energy management, machine learning, manufacturing, ontologies},

pubstate = {published},

tppubtype = {article}

}

@article{angreani2024enhancing,

title = {Enhancing strategy for Industry 4.0 implementation through maturity models and standard reference architectures alignment},

author = {Linda Salma Angreani and Annas Vijaya and Hendro Wicaksono},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Journal of Manufacturing Technology Management},

publisher = {Emerald Publishing Limited},

keywords = {industry 4.0, multi criteria decision making},

pubstate = {published},

tppubtype = {article}

}

@article{nasrabadi2024shopping,

title = {Shopping marketplace analysis based on customer insights using social media analytics},

author = {Negar Nasrabadi and Hendro Wicaksono and Omid Fatahi Valilai},

url = {https://www.sciencedirect.com/science/article/pii/S2215016124003200},

doi = {https://doi.org/10.1016/j.mex.2024.102868},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {MethodsX},

volume = {13},

pages = {102868},

publisher = {Elsevier},

abstract = {Using the recent advances in data analytics, Companies can leverage sentiment analysis to identify trends and areas for improvement of their market strategy and operation planning. This analysis allows them to understand the sentiments expressed by customers and accurately predict customer behavior. Social media platforms have fundamentally altered the field of digital marketing. The findings of this research try to provide:

•

Potential implications for businesses aiming to optimize their product offerings and enhance customer satisfaction within specific cultural contexts.



•

A case study has been designed for understanding customers' perceptions and satisfaction levels toward various shops, including local ethnic stores and big chain stores.



The paper has conducted a literature review around main pillars like application of data analytics on social media, and sales strategies for establishing a marketplace using data analytics. Exploring the utilization of social media and customer feedback, the paper has proposed a conceptual model for creating insights for extraction of shopping experiences and factors used for customer purchasing decision making.},

keywords = {data science, sentiment analysis, text analytics},

pubstate = {published},

tppubtype = {article}

}

@article{rahmawati2024investment,

title = {Investment Decision-Making to Select Converted Electric Motorcycle Tests in Indonesia},

author = {Tasya Santi Rahmawati and Wahyudi Sutopo and Hendro Wicaksono},

url = {https://www.mdpi.com/2032-6653/15/8/334},

doi = {https://doi.org/10.3390/wevj15080334},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {World Electric Vehicle Journal},

volume = {15},

number = {8},

pages = {334},

publisher = {MDPI AG},

abstract = {The issue of carbon emissions can be addressed through environmentally friendly technological innovations, which contribute to the journey towards achieving net-zero emissions (NZE). The electrification of transportation by converting internal combustion engine (ICE) motorcycles to converted electric motorcycles (CEM) directly reduces the number of pollution sources from fossil-powered motors. In Indonesia, numerous government regulations support the commercialization of the CEM system, including the requirement for conversion workshops to be formal entities in the CEM process. Every CEM must pass a test to ensure its safety and suitability. Currently, the CEM testing process is conducted at only one location, making it inefficient and inaccessible. Therefore, most conversion workshops in Indonesia need to take investment steps in procuring CEM-type test tools. This research aims to determine the best alternative from several investment alternatives for CEM-type test tools. In selecting the investment, three criteria are considered: costs, operations, and specifications. By using the investment decision-making model, a hierarchical decision-making model is obtained, which is then processed using the analytical hierarchy process (AHP) and the technique for order of preference by similarity to the ideal solution (TOPSIS). Criteria are weighted to establish a priority order. The final step involves ranking the alternatives and selecting Investment 2 (INV2) as the best investment tool with a relative closeness value of 0.6279. Investment 2 has the shortest time process (40 min), the lowest electricity requirement, and the smallest dimensions. This research aims to provide recommendations for the best investment alternatives that can be purchased by the conversion workshops.

},

keywords = {e-mobility, multi criteria decision making, technology adoption, TOPSIS, transportation},

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},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Sage Open},

volume = {13},

number = {1},

pages = {21582440221145157},

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

keywords = {innovation management, research management},

pubstate = {published},

tppubtype = {article}

}

@article{almais2023principal,

title = {Principal Component Analysis-Based Data Clustering for Labeling of Level Damage Sector in Post-Natural Disasters},

author = {Agung Teguh Wibowo Almais and Adi Susilo and Agus Naba and Moechammad Sarosa and Cahyo Crysdian and Imam Tazi and Mokhamad Amin Hariyadi and Muhammad Aziz Muslim and Puspa Miladin Nuraida Safitri Abdul Basid and Yunifa Miftachul Arif and others},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {IEEE Access},

publisher = {IEEE},

keywords = {data science, machine learning},

pubstate = {published},

tppubtype = {article}

}

@article{caraveo2023rating,

title = {Rating ESG key performance indicators in the airline industry},

author = {Alan Francisco Caraveo Gomez Llanos and Annas Vijaya and Hendro Wicaksono},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Environment, Development and Sustainability},

pages = {1–25},

publisher = {Springer Netherlands},

keywords = {ESG, multi criteria decision making, sustainability},

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}

}

@article{angreani2023identifying,

title = {Identifying Essential Driving Factors of Industry 4.0 Maturity Models Using Fuzzy MCDM Methods},

author = {Linda Salma Angreani and Annas Vijaya and Hendro Wicaksono},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Procedia CIRP},

volume = {120},

pages = {1582–1587},

publisher = {Elsevier},

keywords = {industry 4.0, multi criteria decision making},

pubstate = {published},

tppubtype = {article}

}

@article{pidikiti2023ontology,

title = {An Ontology Model to Facilitate the Semantic Interoperability in Assessing the Circular Economy Performance of the Automotive Industry},

author = {Vamsi Sai Pidikiti and Annas Vijaya and Omid Fatahi Valilai and Hendro Wicaksono},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Procedia CIRP},

volume = {120},

pages = {1351–1356},

publisher = {Elsevier},

keywords = {circular economy, ontologies, semantic web, sustainability},

pubstate = {published},

tppubtype = {article}

}

@article{lobo2022implementation,

title = {Implementation of Blockchain Technology to Enhance Last Mile Delivery Models with Sustainability Perspectives},

author = {Carol Riona Lobo and Hendro Wicaksono and Omid Fatahi Valilai},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {IFAC-PapersOnLine},

volume = {55},

number = {10},

pages = {3304–3309},

publisher = {Elsevier},

keywords = {blockchain, logistics},

pubstate = {published},

tppubtype = {article}

}

@article{wicaksono2022production,

title = {Production Planning and Control: Theories and Best Practices},

author = {Hendro Wicaksono},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

publisher = {OSF Preprints},

keywords = {data science, manufacturing},

pubstate = {published},

tppubtype = {article}

}

@article{istiqomah2022optimizing,

title = {Optimizing Electric Motorcycle-Charging Station Locations for Easy Accessibility and Public Benefit: A Case Study in Surakarta},

author = {Silvi Istiqomah and Wahyudi Sutopo and Muhammad Hisjam and Hendro Wicaksono},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {World Electr. Veh. J.},

volume = {13},

number = {12},

pages = {232},

keywords = {operation research, sustainability, transportation},

pubstate = {published},

tppubtype = {article}

}

@article{wicaksono2021accelerating,

title = {Accelerating Energy Transition to Green Electricity through Artificial Intelligence},

author = {Hendro Wicaksono},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

publisher = {OSF Preprints},

keywords = {artificial intelligence, energy management, machine learning, ontologies, semantic web, sustainability},

pubstate = {published},

tppubtype = {article}

}

@article{fritz2021automatic,

title = {Automatic information extraction from text-based requirements},

author = {Simon Fritz and Vethiga Srikanthan and Ryan Arbai and Chenwei Sun and Jivka Ovtcharova and Hendro Wicaksono},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Int. J. Knowl. Eng},

volume = {7},

number = {1},

pages = {8–13},

keywords = {machine learning, natural language processing},

pubstate = {published},

tppubtype = {article}

}

@article{farooq2021advancing,

title = {Advancing on the analysis of causes and consequences of green skepticism},

author = {Yousuf Farooq and Hendro Wicaksono},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Journal of Cleaner Production},

volume = {320},

pages = {128927},

publisher = {Elsevier},

keywords = {data science, sustainability},

pubstate = {published},

tppubtype = {article}

}