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Disruptive technology identification of intelligent logistics robots in AIoT industry: Based on attributes and functions analysis

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  • Weifeng Jia
  • Shuo Wang
  • Yongping Xie
  • Zifeng Chen
  • Kaixin Gong

Abstract

This research constructs a disruptive technology identification framework based on attributes and functions and selects intelligent logistics robot technology for empirical analysis in the artificial intelligence & Internet of Things (AIoT) industry. We take the three attributes of technological novelty, breakthrough, and influence as measurement indicators to identify disruptive technologies and perform functional analysis of the technology to find potential markets for disruptive technologies. The research demonstrates that two‐dimensional code technology, sensing technology, intelligent control technology, artificial intelligence technology, and wireless communication technology are disruptive technologies in intelligent logistics robots. The future development directions of intelligent logistics robots include efficient, intelligent control operations, good human‐computer interaction, accurate safety obstacle avoidance, and accurate and efficient position detection. This research has put forward the future development direction of disruptive technology in AIoT and provided a reference for the R&D and manufacture of intelligent logistics robots.

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  • Weifeng Jia & Shuo Wang & Yongping Xie & Zifeng Chen & Kaixin Gong, 2022. "Disruptive technology identification of intelligent logistics robots in AIoT industry: Based on attributes and functions analysis," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 557-568, May.
    • Handle: RePEc:bla:srbeha:v:39:y:2022:i:3:p:557-568
    DOI: 10.1002/sres.2859
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    1. Janghyeok Yoon & Hyunseok Park & Kwangsoo Kim, 2013. "Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 313-331, January.
    2. Yang Lu, 2019. "Artificial intelligence: a survey on evolution, models, applications and future trends," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(1), pages 1-29, January.
    3. Sommarberg, Matti & Mäkinen, Saku J., 2019. "A method for anticipating the disruptive nature of digitalization in the machine-building industry," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 808-819.
    4. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    5. Momeni, Abdolreza & Rost, Katja, 2016. "Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 16-29.
    6. Hong Chen & Ling Li & Yong Chen, 2021. "Explore success factors that impact artificial intelligence adoption on telecom industry in China," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(1), pages 36-68, January.
    7. Kanchan Pradhan & Priyanka Chawla, 2020. "Medical Internet of things using machine learning algorithms for lung cancer detection," Journal of Management Analytics, Taylor & Francis Journals, vol. 7(4), pages 591-623, October.
    8. Yue Kang & Zhao Cai & Chee-Wee Tan & Qian Huang & Hefu Liu, 2020. "Natural language processing (NLP) in management research: A literature review," Journal of Management Analytics, Taylor & Francis Journals, vol. 7(2), pages 139-172, April.
    9. Li Da Xu, 2013. "Introduction: Systems Science in Industrial Sectors," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 211-213, May.
    10. Dixon, Tim & Eames, Malcolm & Britnell, Judith & Watson, Georgia Butina & Hunt, Miriam, 2014. "Urban retrofitting: Identifying disruptive and sustaining technologies using performative and foresight techniques," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 131-144.
    11. Janghyeok Yoon & Kwangsoo Kim, 2012. "Detecting signals of new technological opportunities using semantic patent analysis and outlier detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 445-461, February.
    12. Florian Egli & Nick Johnstone & Carlo Menon, 2015. "Identifying and inducing breakthrough inventions: An application related to climate change mitigation," OECD Science, Technology and Industry Working Papers 2015/4, OECD Publishing.
    13. Arthur, W. Brian, 2007. "The structure of invention," Research Policy, Elsevier, vol. 36(2), pages 274-287, March.
    14. Carlsen, H. & Dreborg, K.H. & Godman, M. & Hansson, S.O. & Johansson, L. & Wikman-Svahn, P., 2010. "Assessing socially disruptive technological change," Technology in Society, Elsevier, vol. 32(3), pages 209-218.
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    Cited by:

    1. Minhao Xiang & Dian Fu & Kun Lv, 2023. "Identifying and Predicting Trends of Disruptive Technologies: An Empirical Study Based on Text Mining and Time Series Forecasting," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    2. Li Da Xu, 2022. "Systems research on artificial intelligence," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 359-360, May.

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