Dimensions of Industrial Openness

Understanding Openness and Its Implications for Sustainable Transformation

JournalIndustrie 4.0 Management
Issue Volume 39, 2023, Edition 6, Pages 42-45
Open Accesshttps://doi.org/10.30844/IM_23-6_42-45
Bibliography Share Cite Download

Abstract

The topic of Openness is of growing importance for industry, especially in Europe. However, the term Openness is used very differently. Openness includes several concepts, including Open Source Hardware, Open Source Software, Open Data, Open Standards, Open Innovation, Open Science and Open Education. The concepts address different dimensions of Openness, all based on some kind of participation and with the goal to create more transparency and accessibility. This article defines the concepts and provides a basic understanding of their importance for industry and for greater sustainability.

Keywords


Bibliography

[1] Schlagwein, D.; Conboy, K.; Feller, J.; Leimeister, J. M.; Morgan, L.: ‘Openness’ with and without Information Technology: A Framework and a Brief History. In: Journal of Information Technology 32 (2017) 4, pp. 297-305.
[2] Splitter, V.; Dobusch, L.; Von Krogh, G.; Whittington, R.; and Walgenbach, P.: Openness as Organizing Principle: Introduction to the Special Issue. In: Organization Studies 44 (2023) 1, pp. 7-27.
[3] Bonvoisin, J.: Implications of Open Source Design for Sustainability. In: Setchi, R.; Howlett, R. J.; Liu, Y.; Theobald, P. (eds): Sustainable Design and Manufacturing. Cham 2016, pp. 49-59.
[4] Lindman, J.; Nyman, L.; The Businesses of Open Data and Open Source: Some Key Similarities and Differences. In: Technology Innovation Management Review 4 (2014) 1: Open Source Business, pp. 12-17.
[5] CED. Open Standards, Open Source, and Open Innovation: Harnessing the Benefits of Openness. Digital Connections Council of the Committee for Economic Development(CED), 2006, pp. 119-176.
[6] Powell, A.: Democratizing Production through Open Source Knowledge: From Open Software to Open Hardware. In: Media, Culture & Society 34 (2012) 6, pp. 691-708.
[7] OKF. How to Open up Data. The Open Data Handbook by Open Knowledge Foundation (OKF). https://opendatahandbook.org/ guide/en/how-to-open-up-data/, accessed March 30, 2023.
[8] Hess, C.; Ostrom, E. (eds): Understanding Knowledge as a Commons: From Theory to Practice. Cambridge, MA 2007.
[9] OKF. Open Definition 2.1 – Open Definition – Defining Open in Open Data, Open Content and Open Knowledge. Open Knowdledge Foundation (OKF). URL: opendefinition.org/od/2.1/en/, accessed March 19, 2023.
[10] FSFE. Free Software – FSFE. FSFE – Free Software Foundation Europe. URL: fsfe.org/freesoftware/ freesoftware.html, accessed March 30, 2023.
[11] OSI. The Open Source Definition v1.9. Open Source Initiative (OSI). URL: opensource.org/osd/, accessed March 28, 2023.
[12] SPDX. SPDX License List | Software Package Data Exchange (SPDX) Version: 3.20. The Software Package Data Exchange (SPDX). URL: spdx.org/licenses/, accessed March 30, 2023.
[13] OSHWA. Open-Source-Hardware Definition 1.0. Open Source Hardware Association OSHWA. URL: www.oshwa.org/definition/, accessed March 31, 2023.
[14] ITU. Definition of “Open Standards.” International Telecommunication Union (ITU). URL: www.itu.int:443/ en/ITU-T/ipr/Pages/open.aspx, accessed March 30, 2023.
[15] OSGeo. Open Source and Open Standards – OSGeo Whitepaper. Open Source Geospatial Foundation Wiki. URL: wiki.osgeo.org/wiki/ Open_Source_and_Open_Standards, accessed March 19, 2023.
[16] Bogers, M.; Chesbrough, H.; Moedas, C.: Open Innovation: Research, Practices, and Policies. In: California Management Review 60 (2018) 2, pp. 5-16.
[17] Vicente-Saez, R.; Martinez-Fuentes, C.: Open Science Now: A Systematic Literature Review for an Integrated Definition. In: Journal of Business Research 88 (2018), pp. 428-436.
[18] Vrana, R.: Open Educational Resources (OER) as Means of Promotion of Open Education. Presented at the 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO) in Opatija, HR.
[19] Eisenmann, T. R.; Parker, G.; Van Alstyne, M. W.: Opening Platforms: How, When and Why?. In: SSRN Electronic Journal (2008).
[20] Broekhuizen, T. L. J.; Emrich, O.; Gijsenberg, M. J.; Broekhuis, M.; Donkers, B.; Sloot, L. M.: Digital Platform Openness: Drivers, Dimensions and Outcomes. In: Journal of Business Research 122 (2021), pp. 902-914. DOI: doi.org/10.1016/j.jbusres.2019.07.001.
[21] Scherer, A. G.; Voegtlin, C.: Corporate Governance for Responsible Innovation: Approaches to Corporate Governance and Their Implications for Sustainable Development. In: Academy of Management Perspectives 34 (2020) 2, pp. 182-208.
[22] Phonthanukitithaworn, C.; Srisathan, W. A.; Ketkaew, C.; Naruetharadhol, P.: Sustainable Development towards Openness SME Innovation: Taking Advantage of Intellectual Capital, Sustainable Initiatives, and Open Innovation. In: Sustainability 15 (2023) 3, p. 2126.

Your downloads


Potentials: Innovation

You might also be interested in

MAKI—A Digital Assistant for Practice-Based Learning

MAKI—A Digital Assistant for Practice-Based Learning

Why every factory is a learning factory
Olaf Resch ORCID Icon
With the help of digital assistants, academic teaching is possible in any factory. In order to achieve the best learning effects, however, the interests of all stakeholders must be taken into account. The factory wishes to deploy its employees quickly and productively, the learners desire a positive learning experience, and the educators want to illustrate abstract concepts in a meaningful and practical way. The only way to combine all of these perspectives is via a well-thought-out educational concept and highly functioning technology.
Industry 4.0 Science | Volume 42 | 2026 | Edition 2 | Pages 70-77
Serious Gaming and the Energy Transition

Serious Gaming and the Energy Transition

Collaborative knowledge generation and interactive understanding of complex interrelationships
Janine Gondolf ORCID Icon, Gert Mehlmann, Jörn Hartung, Bernd Schweinshaut, Anne Bauer
Conveying the complexity and multifaceted nature of the energy transition to a broad audience is a challenge. This article demonstrates how interactive serious games on a multitouch table can help make connections tangible and comprehensible. The games and the table were used in various conversational contexts. These are presented here in three case vignettes based on participant observation of the different applications, as well as situated and shared reflection. The vignettes demonstrate how interaction can trigger epistemic processes, enable shifts in perspective, and foster collective thinking, all of which are necessary for shaping the future of society as a whole.
Industry 4.0 Science | Volume 42 | 2026 | Edition 2 | Pages 62-69
Industrial Transformation via a Machining Learning Factory

Industrial Transformation via a Machining Learning Factory

A learning module to foster competencies for a sustainability-driven transformation
Oskay Ozen ORCID Icon, Victoria Breidling ORCID Icon, Stefan Seyfried ORCID Icon, Matthias Weigold
Sustainability-enhancing transformation processes are necessary in all sectors if we are to remain within planetary boundaries. This also applies to the industrial sector as a significant emitter of greenhouse gases. Employees need new competencies to master this complex task of industrial transformation. These range from CO2 equivalents accounting to the development and evaluation of transformation scenarios, including technical measures. The learning module developed here addresses these competency requirements and uses the example of the ETA factory to show how a competency-oriented learning module for industrial transformation can be structured. It essentially comprises four phases: data collection and CO2 equivalents accounting, cause analysis, development of measures and evaluation of measures.
Industry 4.0 Science | Volume 42 | Edition 2 | Pages 38-47 | DOI 10.30844/I4SE.26.2.38
Data Quality and Domain Expertise for Resilient AI Deployment

Data Quality and Domain Expertise for Resilient AI Deployment

Integrating anomaly and label error detection in industry
Pavlos Rath-Manakidis, Henry Huick, Erdi Ünal, Björn Krämer ORCID Icon, Laurenz Wiskott ORCID Icon
AI implementation transforms work and worker-technology relationships in industrial quality control. This paper explores how approaches to data quality and model transparency support ethical AI deployment, fostering worker agency, trust, and sustainable work design in automatic surface inspection systems (ASIS). Recurring problems like data inefficiency, variable model confidence, and limited AI expertise point to key challenges of human-centered AI: user trust, agency and responsible data management. A solution co-developed with an ASIS supplier demonstrates that the challenges extend beyond the purely technical, underscoring the value of AI design that augments human capabilities. Technical solutions such as anomaly, label error, and domain drift detection are proposed to enhance data quality and model reliability. The insights emphasize the following generalizable strategies for resilient AI integration: understanding user-reported problems through a human-AI interaction lens, ...
Industry 4.0 Science | Volume 42 | Edition 1 | Pages 128-135 | DOI 10.30844/I4SE.26.1.120
Digital Competence Lab (DCL) for Speech Therapy

Digital Competence Lab (DCL) for Speech Therapy

Designing a learning platform to advance digital skills
Anika Thurmann ORCID Icon, Antonia Weirich ORCID Icon, Kerstin Bilda, Fiona Dörr ORCID Icon, Lars Tönges ORCID Icon
The digital transformation of healthcare results in lasting changes in speech therapy. Smart technologies and artificial intelligence (AI) are creating new opportunities to ensure therapy quality, address care bottlenecks, and actively involve patients in exercise processes. At the same time, these developments are expanding the role of speech therapists, who increasingly use digital systems as supportive tools in addition to their core therapeutic tasks. Based on a feasibility study of the AI-supported application ISi-Speech-Sprechen in a real-world setting of complex Parkinson's therapy (PKT), this article outlines the key challenges associated with implementing smart technologies.
Industry 4.0 Science | Volume 42 | 2026 | Edition 1 | Pages 110-118 | DOI 10.30844/I4SE.26.1.102
AI Skills for Responsible Use

AI Skills for Responsible Use

Realistic learning environments, critical thinking, and role design in teams
Valentin Langholf ORCID Icon, Niklas Obermann ORCID Icon, Uta Wilkens ORCID Icon, Marco Kuhnke, Michael Prüfer
Artificial intelligence (AI) is changing the world of work. But how can work teams learn to use AI support in a way that delivers speed advantages and ensures consistently high quality? One possible approach is to test it in a workplace-like simulation. Trying it out under realistic conditions shows the role that critical thinking plays.
Industry 4.0 Science | Volume 42 | Edition 1 | Pages 100-107 | DOI 10.30844/I4SE.26.1.92