Most cited papers in Digital Transformation in Industry
What are the most cited papers in Digital Transformation in Industry?
The most cited paper in Digital Transformation in Industry is "Understanding digital transformation: A review and a research agenda" (Grégory Vial, 2019), with 6,975 citations. Next come "Digital transformation: A multidisciplinary reflection and research agenda" (5,424) and "A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems" (5,033).
Showing 50 of 100 papers. Every paper with more than 1,029 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Understanding digital transformation: A review and a research agenda Grégory Vial · The Journal of Strategic Information Systems | 10 Feb 2019 | 6,975 |
| 2 | Digital transformation: A multidisciplinary reflection and research agenda Peter C. Verhoef, Thijs Broekhuizen, Yakov Bart et al. · Journal of Business Research | 3 Nov 2019 | 5,424 |
| 3 | A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems Jay K. Lee, Behrad Bagheri, Hung-An Kao · Manufacturing Letters | 10 Dec 2014 | 5,033 |
| 4 | Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy Yogesh Kumar Dwivedi et al. · International Journal of Information Management | 27 Aug 2019 | 4,479 |
| 5 | Digital Twin in Industry: State-of-the-Art Fei Tao, He Zhang, Ang Liu et al. · IEEE Transactions on Industrial Informatics | Apr 2019 | 4,318 |
| 6 | Industry 4.0 Heiner Lasi, Peter Fettke, Hans-Georg Kemper et al. · Business & Information Systems Engineering | 19 Jun 2014 | 4,243 |
| 7 | Artificial Intelligence in Service Ming‐Hui Huang, Roland T. Rust · Journal of Service Research | 5 Feb 2018 | 3,516 |
| 8 | Digital Twin in manufacturing: A categorical literature review and classification Werner Kritzinger, Matthias Karner, Georg Traar et al. · IFAC-PapersOnLine | 2018 | 3,455 |
| 9 | Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems Michael W. Grieves, John Vickers | 16 Aug 2016 | 3,394 |
| 10 | Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal Karl Warner, Maximilian Wäger · Long Range Planning | 19 Dec 2018 | 3,368 |
| 11 | Big Data in Smart Farming – A review J. Wolfert, Lan Ge, C.N. Verdouw et al. · Agricultural Systems | 7 Feb 2017 | 3,328 |
| 12 | Industry 4.0: state of the art and future trends Li Da Xu, Eric Li Xu, Ling Li · International Journal of Production Research | 9 Mar 2018 | 3,210 |
| 13 | Industry 4.0: A survey on technologies, applications and open research issues Yang Lu · Journal of Industrial Information Integration | 17 Apr 2017 | 2,991 |
| 14 | Design Principles for Industrie 4.0 Scenarios Mario Hermann, Tobias Pentek, Boris Otto | 2016 | 2,970 |
| 15 | Industry 4.0 technologies: Implementation patterns in manufacturing companies Alejandro Germán Frank, Lucas Santos Dalenogare, Néstor Fabián Ayala · International Journal of Production Economics | 9 Jan 2019 | 2,902 |
| 16 | Intelligent Manufacturing in the Context of Industry 4.0: A Review Ray Y. Zhong, Xun William Xu, Eberhard Klotz et al. · Engineering | Oct 2017 | 2,894 |
| 17 | Digital twin-driven product design, manufacturing and service with big data Fei Tao, Jiangfeng Cheng, Qinglin Qi et al. · The International Journal of Advanced Manufacturing Technology | 16 Mar 2017 | 2,880 |
| 18 | Digital Twin: Enabling Technologies, Challenges and Open Research Aidan Fuller, Zhong Fan, Charles R. Day et al. · IEEE Access | 2020 | 2,846 |
| 19 | Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda Yanqing Duan, John Steven Edwards, Yogesh Kumar Dwivedi · International Journal of Information Management | 9 Feb 2019 | 2,586 |
| 20 | Industry 4.0 and Industry 5.0—Inception, conception and perception Xun William Xu, Yuqian Lu, Birgit Vogel‐Heuser et al. · Journal of Manufacturing Systems | Oct 2021 | 2,505 |
| 21 | Artificial Intelligence and Management: The Automation–Augmentation Paradox Sebastian Raisch, Sebastian Maximillian Krakowski · Academy of Management Review | 2021 | 2,475 |
| 22 | A Systematic Review of the Literature on Digital Transformation: Insights and Implications for Strategy and Organizational Change André Hanelt, René Bohnsack, David Marz et al. · Journal of Management Studies | 27 Sep 2020 | 2,450 |
| 23 | Characterising the Digital Twin: A systematic literature review David Jones, Chris M. Snider, Aydin Nassehi et al. · CIRP journal of manufacturing science and technology | 9 Mar 2020 | 2,353 |
| 24 | The expected contribution of Industry 4.0 technologies for industrial performance Lucas Santos Dalenogare, Guilherme Brittes Benitez, Néstor Fabián Ayala et al. · International Journal of Production Economics | 20 Aug 2018 | 2,180 |
| 25 | Literature review of Industry 4.0 and related technologies Ercan Öztemel, Samet GÜRSEV · Journal of Intelligent Manufacturing | 24 Jul 2018 | 2,132 |
| 26 | Industry 4.0, digitization, and opportunities for sustainability Morteza Ghobakhloo · Journal of Cleaner Production | 27 Dec 2019 | 2,102 |
| 27 | Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal Yongxin Liao, Fernando Deschamps, Eduardo de Freitas Rocha Loures et al. · International Journal of Production Research | 28 Mar 2017 | 2,030 |
| 28 | Cyber-physical systems Ragunathan Raj Rajkumar, Insup Lee, Lui Sha et al. | 13 Jun 2010 | 1,983 |
| 29 | Opportunities of Sustainable Manufacturing in Industry 4.0 Tim Stock, Günther Seliger · Procedia CIRP | 2016 | 1,897 |
| 30 | Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment Jay K. Lee, Hung-An Kao, Shanhu Yang · Procedia CIRP | 2014 | 1,894 |
| 31 | Additive manufacturing and sustainability: an exploratory study of the advantages and challenges Simon James Ford, Mélanie Despeisse · Journal of Cleaner Production | 10 May 2016 | 1,883 |
| 32 | Digital Twin: Values, Challenges and Enablers From a Modeling Perspective Adil Rasheed, Omer San, Trond Kvamsdal · IEEE Access | 2020 | 1,879 |
| 33 | Review of digital twin about concepts, technologies, and industrial applications Mengnan Liu, Shuiliang Fang, Huiyue Dong et al. · Journal of Manufacturing Systems | 8 Jul 2020 | 1,877 |
| 34 | Industry 4.0 and the current status as well as future prospects on logistics Erik Hofmann, Marco Rüsch · Computers in Industry | 22 Apr 2017 | 1,852 |
| 35 | Industry 5.0: A survey on enabling technologies and potential applications Praveen Kumar Reddy Maddikunta, Quoc‐Viet Pham, B. Prabadevi et al. · Journal of Industrial Information Integration | 11 Aug 2021 | 1,850 |
| 36 | From cloud computing to cloud manufacturing Xun William Xu · Robotics and Computer-Integrated Manufacturing | 13 Aug 2011 | 1,782 |
| 37 | Data-driven smart manufacturing Fei Tao, Qinglin Qi, Ang Liu et al. · Journal of Manufacturing Systems | 17 Jan 2018 | 1,781 |
| 38 | A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 Dmitry Ivanov, Alexandre B. Dolgui · Production Planning & Control | 21 May 2020 | 1,748 |
| 39 | A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises Andreas Schumacher, Selim Erol, Wilfried Sihn · Procedia CIRP | 2016 | 1,733 |
| 40 | The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0 Martin Wollschlaeger, Thilo Sauter, Jürgen Jasperneite · IEEE Industrial Electronics Magazine | Mar 2017 | 1,729 |
| 41 | Deep learning for smart manufacturing: Methods and applications Jinjiang Wang, Yulin Ma, Laibin Zhang et al. · Journal of Manufacturing Systems | 8 Jan 2018 | 1,717 |
| 42 | Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison Qinglin Qi, Fei Tao · IEEE Access | 2018 | 1,695 |
| 43 | Cyber-physical systems in manufacturing László Monostori, Botond Kádár, Thomas Bauernhansl et al. · CIRP Annals | 2016 | 1,691 |
| 44 | Industry 5.0—A Human-Centric Solution Saeid Nahavandi · Sustainability | 13 Aug 2019 | 1,685 |
| 45 | A Review of the Roles of Digital Twin in CPS-based Production Systems Elisa Negri, Luca Fumagalli, Marco Macchi · Procedia Manufacturing | 2017 | 1,645 |
| 46 | Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues Yuqian Lu, Chao Liu, Kevin I‐Kai Wang et al. · Robotics and Computer-Integrated Manufacturing | 8 Aug 2019 | 1,614 |
| 47 | Enabling technologies and tools for digital twin Qinglin Qi, Fei Tao, Tianliang Hu et al. · Journal of Manufacturing Systems | 29 Oct 2019 | 1,557 |
| 48 | Implementing Smart Factory of Industrie 4.0: An Outlook Shiyong Wang, Jiafu Wan, Di Li et al. · International Journal of Distributed Sensor Networks | 2016 | 1,527 |
| 49 | Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry Thuy Duong Oesterreich, Frank Teuteberg · Computers in Industry | 5 Oct 2016 | 1,517 |
| 50 | Internet of things and supply chain management: a literature review Mohamed Ben‐Daya, Elkafi Hassini, Zied Bahroun · International Journal of Production Research | 16 Nov 2017 | 1,484 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.