Collaborations for Digital Transformation: Case Studies of Industry 4.0 in Brazil
Journal article
Rocha, C., Quandt, C., Deschamps, F., Philbin, S. and Cruzara, G. (2021). Collaborations for Digital Transformation: Case Studies of Industry 4.0 in Brazil. IEEE Transactions on Engineering Management. pp. 1-15. https://doi.org/10.1109/tem.2021.3061396
Authors | Rocha, C., Quandt, C., Deschamps, F., Philbin, S. and Cruzara, G. |
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Abstract | In today's digital age, many managers need to find new ways to manage collaborations where complementary partners co-create digital solutions. Collaborations with partners are at the center of digital projects, but managing these collaborations is challenging. This article objective is to investigate how research and development collaborations with scientific and business partners contribute to digital transformation. This has been achieved through an empirical investigation of three Brazilian manufacturers that are already on their journey toward digitalization. The research design involves multiple case studies and qualitative analysis, through data collection by interviews and questionnaires with participants from the tactical and strategic level followed by content analysis as well as nonparticipant observations. The findings indicate that the companies are at the early stage of building a digital ecosystem. However, they have already secured benefits from pursuing open innovation practices in the form of competitive advantage in operational processes. The results indicate that business success depends more on how (disruptive) technologies are developed and used by engaged people to add value to the enterprise, rather than simply adopting new technologies by themselves. Manufacturers need to act now to reshape their mindset, operational processes, and business models, respectively, enabling the understanding that: 1) organizational ecosystems are becoming more open and collaborative; 2) the value of data capture and analysis can be developed and used for data-driven learning, preventive and predictive capabilities, supporting decision-making; 3) customers' preferences need to be internalized to deliver customized experiences. |
Year | 2021 |
Journal | IEEE Transactions on Engineering Management |
Journal citation | pp. 1-15 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
ISSN | 0018-9391 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/tem.2021.3061396 |
Publication dates | |
Online | 17 Mar 2021 |
Publication process dates | |
Deposited | 19 Mar 2021 |
Accepted | 17 Feb 2021 |
Accepted author manuscript | License File Access Level Open |
Additional information | © 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Page range | 1-15 |
https://openresearch.lsbu.ac.uk/item/8w59z
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Accepted author manuscript
Article IEEE_Clear Version_Final File_v5.docx | ||
License: CC BY 4.0 | ||
File access level: Open |
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