The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
SUSTAINABLE INDUSTRIAL VALUE CREATION: BENEFITS AND CHALLENGES OF INDUSTRY 4.0
Abstract
The Industrial Internet of Things (IIoT) poses several implications on manufacturers in terms of economic, ecological, and social aspects referring to the Triple Bottom Line (TBL) of sustainable value creation. Due to its technical core, the current research focused on its technical fundamentals, whereas the economic discussion is still in its infancy. This paper aims at painting a comprehensive and structured picture of IIoT-related economic, ecological, and social benefits and challenges. For this purpose, we employ an exploratory multiple case study approach based on semi-structured expert interviews in 46 manufacturing companies from three leading German industries. Our study contributes to the sparse body of scientific IIoT literature by analysing the IIoT’s implications according to the TBL. We show that, in order to qualify for sustainable industrial value creation, the IIoT requires an extension of the established TBL by three further dimensions, i.e., technical integration, data and information, and public context.
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Cites
Case Study Research: Design and Methods
Chaiklin, H. (1991) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-199102000-00025 · Cited by 39,535
(1993) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(93)91697-o · Cited by 18,154
Theory Building From Cases: Opportunities And Challenges
Eisenhardt, K. M., & Graebner, M. E. (2007) · Academy of Management Journal · doi:10.5465/amj.2007.24160888 · Cited by 16,670
Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology
Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013) · Organizational Research Methods · doi:10.1177/1094428112452151 · Cited by 13,227
The Handbook of Social Psychology
Gravatt, A. E., Lindzey, G., & Aronson, F. (1969) · The Family Coordinator · doi:10.2307/582242 · Cited by 12,517
Corporate Social and Financial Performance: A Meta-Analysis
Orlitzky, M., Schmidt, F. L., & Rynes, S. L. (2003) · Organization Studies · doi:10.1177/0170840603024003910 · Cited by 7,641
Strategy and society: the link between competitive advantage and corporate social responsibility
(2007) · Strategic Direction · doi:10.1108/sd.2007.05623ead.006 · Cited by 7,410
Mixing Qualitative and Quantitative Methods: Triangulation in Action.
Jick, T. D. (1979) · Administrative Science Quarterly · doi:10.2307/2392366 · Cited by 7,103
Partnerships from cannibals with forks: The triple bottom line of 21st‐century business
Elkington, J. (1998) · Environmental Quality Management · doi:10.1002/tqem.3310080106 · Cited by 5,341
A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
Lee, J., Bagheri, B., & Kao, H.-A. (2015) · Manufacturing Letters · doi:10.1016/j.mfglet.2014.12.001 · Cited by 5,113
Cited by
Industry 4.0, digitization, and opportunities for sustainability
Ghobakhloo, M. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.119869 · Cited by 2,115
Horváth, D., & Szabó, R. Z. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.05.021 · Cited by 1,281
Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0
Müller, J. M., Buliga, O., & Voigt, K.-I. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2017.12.019 · Cited by 1,262
Self-citationLi, Y., Dai, J., & Cui, L. (2020) · International Journal of Production Economics · doi:10.1016/j.ijpe.2020.107777 · Cited by 922
Luthra, S., & Mangla, S. K. (2018) · Process Safety and Environmental Protection · doi:10.1016/j.psep.2018.04.018 · Cited by 909
Metadata
- Authors
- KIEL, D., MÜLLER, J. M., ARNOLD, C., & VOIGT, K.-I.
- Venue
- International Journal of Innovation Management
- Publisher
- World Scientific Pub Co Pte Ltd
- Published
- 2017-12
- Volume
- 21
- Issue
- 08
- Pages
- 1740015
- ISSN
- 1363-9196 (ISSN-L)
- 1757-5877
- OpenAlex
- W2772569019
- Cited by
- 769
- References
- 82
- FWCI
- 57.88
- Type
- journal article
- Language
- en
- Open access
- closed
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- KIEL, D., MÜLLER, J. M., ARNOLD, C., & VOIGT, K.-I. (2017). SUSTAINABLE INDUSTRIAL VALUE CREATION: BENEFITS AND CHALLENGES OF INDUSTRY 4.0. International Journal of Innovation Management. https://doi.org/10.1142/s1363919617400151
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
