Michael Sony
Industrial and Manufacturing Engineering · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Industrial and Manufacturing Engineering — 30 citations into it; #2,376 of 2,521 by trust here, #2,480 by citations
- Management Information Systems — 10 citations into it
- Strategy and Management — 8 citations into it
- Management of Technology and Innovation — 7 citations into it
- Sociology and Political Science — 7 citations into it
Whom Michael Sony trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yang Lu
- Francisco Almada-Lobo
- Fulvio Castellacci
- David H. Autor
- A. Parasuraman
- Guy Standing
- Jiju Antony
- D. Harvey
- Shiyong Wang
Who trusts Michael Sony overall
Papers from Michael Sony's perspective
Ordered by how strongly the researchers Michael Sony trusts endorse each paper. Same corpus, a different order for every researcher.
- Common method biases in behavioral research: a critical review of the literature and recommended remedies. (Journal of Applied Psychology)
- From cloud computing to cloud manufacturing
- How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective
- Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal (International Journal of Production Research)
- Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors (European Journal of Information Systems)
- Implementing Smart Factory of Industrie 4.0: An Outlook (Int. J. Distributed Sens. Networks)
- Cyber Physical Systems: Design Challenges (IEEE International Symposium on Real-Time Distributed Computing)
- Human-machine-interaction in the industry 4.0 era (International Conference on Industrial Informatics)
- How Smart, Connected Products Are Transforming Competition
- Recent advances and trends in predictive manufacturing systems in big data environment