IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v168y2022ics1366554522003209.html
   My bibliography  Save this article

Logistics, supply chain management and technology research: An analysis on the axis of technology mining

Author

Listed:
  • Yalcin, Haydar
  • Daim, Tugrul U.

Abstract

In this study, it is aimed to explore the technology research and development processes in the field of logistics and supply chain management according to scientific publications and patent data. For this purpose, important research focuses on the field were revealed, authors, institutions and countries leading the field were determined, and sub-technology areas for technologies in the field of logistics and supply chain management were determined by patent analysis. In our research, in which technology mining method was used, patent analysis and bibliometrics were handled together. Our research also aimed to determine the important research focuses for the field. Accordingly, with the pandemic, in scientific studies in the field of logistics and supply chain management, it has been seen that connected ecosystem components such as bitcoin, Internet of Things (IoT), and smart contracts stand out as open and relatively untouched areas. On the other hand, it has been observed that the USA, the United Kingdom, China and India have come to the fore as the leading countries in the field, and the tendency towards research on data flow and sharing has increased in patent analysis.

Suggested Citation

  • Yalcin, Haydar & Daim, Tugrul U., 2022. "Logistics, supply chain management and technology research: An analysis on the axis of technology mining," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:transe:v:168:y:2022:i:c:s1366554522003209
    DOI: 10.1016/j.tre.2022.102943
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554522003209
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2022.102943?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sven Winkelhaus & Eric H. Grosse, 2020. "Logistics 4.0: a systematic review towards a new logistics system," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 18-43, January.
    2. Haydar Yalcin & Tugrul Daim, 2021. "Mining research and invention activity for innovation trends: case of blockchain technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3775-3806, May.
    3. Shenle Pan & Damien Trentesaux & Duncan Mcfarlane & Benoit Montreuil & Eric Ballot & George Huang, 2021. "Digital interoperability in logistics and supply chain management: state-of-the-art and research avenues towards Physical Internet," Post-Print hal-03161524, HAL.
    4. Winkelhaus, S. & Grosse, E. H., 2020. "Logistics 4.0: a systematic review towards a new logistics system," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 118539, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Gao, Lidan & Porter, Alan L. & Wang, Jing & Fang, Shu & Zhang, Xian & Ma, Tingting & Wang, Wenping & Huang, Lu, 2013. "Technology life cycle analysis method based on patent documents," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 398-407.
    6. Zeba, Gordana & Dabić, Marina & Čičak, Mirjana & Daim, Tugrul & Yalcin, Haydar, 2021. "Technology mining: Artificial intelligence in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    7. Gunasekaran, Angappa & Ngai, Eric W.T., 2012. "The future of operations management: An outlook and analysis," International Journal of Production Economics, Elsevier, vol. 135(2), pages 687-701.
    8. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Verma, Pratima & Kumar, Vimal & Yalcin, Haydar & Daim, Tugrul, 2023. "Organizational architecture of strategic entrepreneurial firms for digital transformation: A bibliometric analysis," Technology in Society, Elsevier, vol. 75(C).
    2. Kumar, Devinder & Singh, Rajesh Kr & Mishra, Ruchi & Daim, Tugrul U., 2023. "Roadmap for integrating blockchain with Internet of Things (IoT) for sustainable and secured operations in logistics and supply chains: Decision making framework with case illustration," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    3. Yiwei Wu & Hongyu Zhang & Shuaian Wang & Lu Zhen, 2023. "Mathematical Optimization of Carbon Storage and Transport Problem for Carbon Capture, Use, and Storage Chain," Mathematics, MDPI, vol. 11(12), pages 1-14, June.
    4. Tomas Gabriel Bas & Paula Astudillo & Daniel Rojo & Angel Trigo, 2023. "Opinions Related to the Potential Application of Artificial Intelligence (AI) by the Responsible in Charge of the Administrative Management Related to the Logistics and Supply Chain of Medical Stock i," IJERPH, MDPI, vol. 20(6), pages 1-17, March.
    5. Ghaffari, Mohsen & Aliahmadi, Alireza & Khalkhali, Abolfazl & Zakery, Amir & Daim, Tugrul U. & Yalcin, Haydar, 2023. "Topic-based technology mapping using patent data analysis: A case study of vehicle tires," Technological Forecasting and Social Change, Elsevier, vol. 193(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    2. Garza Ramos, Alejandro & Daim, Tugrul & Gaats, Lukas & Hutmacher, Dietmar W. & Hackenberger, David, 2022. "Technology roadmap for the development of a 3D cell culture workstation for a biomedical industry startup," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. Brauner, Philipp & Ziefle, Martina, 2022. "Beyond playful learning – Serious games for the human-centric digital transformation of production and a design process model," Technology in Society, Elsevier, vol. 71(C).
    5. Cannavacciuolo, Lorella & Ferraro, Giovanna & Ponsiglione, Cristina & Primario, Simonetta & Quinto, Ivana, 2023. "Technological innovation-enabling industry 4.0 paradigm: A systematic literature review," Technovation, Elsevier, vol. 124(C).
    6. Chung, Sai-Ho, 2021. "Applications of smart technologies in logistics and transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    7. Farajpour, Farnoush & Hassanzadeh, Alireza & Elahi, Shaban & Ghazanfari, Mehdi, 2022. "Digital supply chain blueprint via a systematic literature review," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    8. Menti, Federica & Romero, David & Jacobsen, Peter, 2023. "A technology assessment and implementation model for evaluating socio-cultural and technical factors for the successful deployment of Logistics 4.0 technologies," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    9. Kabadurmus, Ozgur & Kayikci, Yaşanur & Demir, Sercan & Koc, Basar, 2023. "A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    10. Cui, Huixia & Chen, Xiangyong & Guo, Ming & Jiao, Yang & Cao, Jinde & Qiu, Jianlong, 2023. "A distribution center location optimization model based on minimizing operating costs under uncertain demand with logistics node capacity scalability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    11. Ghaffari, Mohsen & Aliahmadi, Alireza & Khalkhali, Abolfazl & Zakery, Amir & Daim, Tugrul U. & Yalcin, Haydar, 2023. "Topic-based technology mapping using patent data analysis: A case study of vehicle tires," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    12. Anna Saniuk, 2022. "The Logistics 4.0 Implementation Supported by the Balanced Scorecard Method," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 198-207.
    13. Ranasinghe, Thilini & Grosse, Eric H. & Glock, Christoph H. & Jaber, Mohamad Y., 2024. "Never too late to learn: Unlocking the potential of aging workforce in manufacturing and service industries," International Journal of Production Economics, Elsevier, vol. 270(C).
    14. Behl, Abhishek & Sampat, Brinda & Gaur, Jighyasu & Pereira, Vijay & Laker, Benjamin & Shankar, Amit & Shi, Yangyan & Roohanifar, Mohammad, 2024. "Can gamification help green supply chain management firms achieve sustainable results in servitized ecosystem? An empirical investigation," Technovation, Elsevier, vol. 129(C).
    15. Naeini, Ali Bonyadi & Zamani, Mehdi & Daim, Tugrul U. & Sharma, Mahak & Yalcin, Haydar, 2022. "Conceptual structure and perspectives on “innovation management”: A bibliometric review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    16. Chen, Yi-Ting & Sun, Edward W. & Chang, Ming-Feng & Lin, Yi-Bing, 2021. "Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0," International Journal of Production Economics, Elsevier, vol. 238(C).
    17. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    18. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    19. June Young Lee & Sejung Ahn & Dohyun Kim, 2021. "Deep learning-based prediction of future growth potential of technologies," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-16, June.
    20. Guo, Chiquan & Wang, Yong J. & Metcalf, Ashley, 2014. "How to calibrate conventional market-oriented organizational culture in 21st century production-centered firms? A customer relationship perspective," International Journal of Production Economics, Elsevier, vol. 156(C), pages 235-245.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:168:y:2022:i:c:s1366554522003209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.