Crowdsourcing for Industrial Innovations − Solutions and Challenges for SMEs

Christof Thim, André Ullrich ORCID Icon, Felix Eigelshoven, Norbert Gronau ORCID Icon, Ann-Carolin Ritter
JournalIndustrie 4.0 Management
Issue Volume 36, 2020, Edition 6, Pages 9-13
Open Accesshttps://doi.org/10.30844/I40M_20-6_S9-13
Bibliography Share Cite Download

Abstract

Innovation activity in the industrial environment is shifting towards product-service systems as a result of digitalisation. Small and medium-sized enterprises have so far focused their development activities strongly on product development. The switch to “smart” products and the coupling to services often requires personnel and financial resources that SMEs cannot provide. Crowdsourcing is one way of opening up the innovation process to external actors and realising cost and speed advantages. However, the integration of crowdsourcing elements faces several challenges. This article shows both the potentials and the barriers of crowdsourcing in the industrial environment.

Bibliography

[1] Leimeister, J. M.: Einführung in die Wirtschaftsinformatik. 12. Auflage. Berlin 2015.
[2] Leimeister, J. M.; Durward, D.; Zogaj, S.: Crowd Worker in Deutschland: Eine empirische Studie zum Arbeitsumfeld auf externen Crowdsourcing Plattformen. Studie der Hans- Böckler-Stiftung, Nr. 323. Düsseldorf 2016.
[3] Zogaj, S.; Bretschneider, U.; Leimeister, J. M.: Managing Crowdsourced Software Testing – A Case Study Based Insight on the Challenges of a Crowdsourcing Intermediary. Journal of Business Economics 84 (2014) 3, S. 375-405.
[4] Leimeister, J. M.; Zogaj, S.: Neue Arbeitsorganisation durch Crowdsourcing. Arbeitspapier der Hans-Böckler-Stiftung, Nr. 287. Düsseldorf 2013.
[5] Ullrich, A.; Vladova, G. 2016. Weighing the Pros and Cons of Engaging in Open Innovation. Technology Innovation Management Review, 6(4): 34-40. DOI: http://doi.org/10.22215/timreview/980.
[6] Teichmann, M.; Ullrich, A.; Wenz, J.; Gronau, N.: Herausforderungen und Handlungsempfehlungen betrieblicher Weiterbildungspraxis in Zeiten der Digitalisierung. HMD Praxis der Wirtschaftsinformatik 57 (2020), S. 512-527.
[7] Schmidt, F.: Arbeitsmärkte in der Plattformökonomie – Zur Funktionsweise und den Herausforderungen von Crowdwork und Gigwork. Bonn 2016.
[8] Ullrich, A.; Vladova, G.; Thim, C.; Gronau, N.: Organisatorischer Wandel und Akzeptanz in der Industrie 4.0-Fabrik – Vorgehen und Handlungsempfehlungen. In: Obermaier, R. (Hrsg): Handbuch Industrie 4.0 und Digitale Transformation. Berlin 2019.
[9] Kässi, O.; Lehdonvirta, V.: Online labour index: Measuring the online gig economy for policy and research. In: Technological Forecasting and Social Change 137 (2018), S. 241-248.

Your downloads

You might also be interested in

Audio-Immersive Learning in Continuing Vocational Education

Audio-Immersive Learning in Continuing Vocational Education

From linear audio playback to AI-supported conversational learning companions
Tim Beichter, Vanessa Hartmann, Katharina Hölzle ORCID Icon, Manuel Kaiser
Artificial intelligence is increasingly shaping continuing vocational education and training by enabling the personalization of individual learning experiences. At the same time, audio-based learning formats are attracting growing interest among learners because of their flexibility and suitability for workplace learning. However, a conceptual framework for AI-supported audio learning, as well as the potential of combining artificial intelligence with audio-based learning, has received little attention to date. This paper therefore presents a conceptual perspective on the design possibilities and educational potential of AI-supported audio learning formats.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 102-108 | DOI 10.30844/I4SE.26.5.12
Explaining AI in Industrial Production in an Accessible Way

Explaining AI in Industrial Production in an Accessible Way

Requirements for AI demonstrators to promote acceptance
Jennifer Link ORCID Icon, Markus Harlacher ORCID Icon, Colin Srebny, Sascha Stowasser ORCID Icon
Artificial intelligence (AI) offers a wide range of possibilities in industrial production, but it also presents challenges regarding employee acceptance. AI demonstrators are therefore of central importance, as they enable hands-on experience with AI. However, there has been a lack of systematically identified requirements for demonstrators that specifically promote acceptance and address negative emotions. Using a multi-stage research design, 69 requirements were identified, structured into functional requirements, quality requirements, and boundary conditions.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 6-14 | DOI 10.30844/I4SE.26.5.1
Work Design in the Use of Autonomous Systems

Work Design in the Use of Autonomous Systems

Addressing the shortage of skilled workers
Tim Jeske ORCID Icon, Sascha Stowasser ORCID Icon, Nicole Ottersböck, Sebastian Terstegen, Rasmus Adler ORCID Icon
Companies are increasingly challenged to address shortages of skilled workers while meeting rising demands for productivity, flexibility, and innovation. Because labor supply can only be expanded to a limited extent, there is a growing focus on designing work systems with productivity in mind. Autonomous systems offer significant potential in this regard. Their implementation requires not only technical adjustments but, above all, changes in organization, skills, and work design. This article analyzes empirically grounded change requirements in existing work systems as well as associated economic potential.
Industry 4.0 Science | Volume 42 | 2026 | Edition 5 | Pages 44-50 | DOI 10.30844/I4SE.26.5.5
Cooperation Routines of Complementors in Digital Ecosystems

Cooperation Routines of Complementors in Digital Ecosystems

A microfoundation of integrative dynamic capability
Christian Zabel ORCID Icon, Tahir Schmidt ORCID Icon
Complementors are central to value creation in digital ecosystems yet have limited leverage and must adapt through dynamic capabilities. Building on the Profiting From Innovation Framework, this study examines how integrative capabilities manifest for complementors through cooperative routines. Based on a systematic literature review of Scopus-indexed studies from 2020 to mid-2025 focusing on the microfoundation “orchestrating ecosystem actors”, we identify two routine clusters. Complementors cooperate with other complementors via partner sensing, scouting, coalitions, resource sharing, and risk allocation while protecting critical assets. They cooperate with platform owners via multichannel boundary spanning, quality signaling, governance compliance, boundary resource integration, and co-development, while facing the risk of owner entry. Research gaps concern the formalization of cooperation routines, taxonomy, and B2B contexts.
Industry 4.0 Science | Volume 42 | 2026 | Edition 4 | Pages 22-28 | DOI 10.30844/I4SE.26.4.3
Platform Adoption as a Dynamic Capability

Platform Adoption as a Dynamic Capability

How SMEs overcome barriers to adoption of B2B collaboration platforms
Nikolai Schäfer ORCID Icon, Marcel Hülsbeck ORCID Icon
Digital collaboration and innovation platforms offer SMEs significant potential to compensate for structural resource weaknesses and to participate in innovation ecosystems. Nevertheless, adoption in the B2B context remains low. This paper examines adoption barriers based on a systematic literature review using Teece’s dynamic capabilities approach. The analysis suggests that recurring obstacles can be structured along three dimensions: Sensing—lack of ecosystem awareness, absence of scanning routines; Seizing—IP concerns, governance uncertainty, adoption fatigue; Reconfiguring—closed-innovation culture, lack of absorptive capacity. Building on this, a practice-oriented capability-building framework is developed with recommendations for action.
Industry 4.0 Science | Volume 42 | 2026 | Edition 4 | Pages 42-48 | DOI 10.30844/I4SE.26.4.5
Industry 4.0—Progress and Digitalization in Limbo

Industry 4.0—Progress and Digitalization in Limbo

Status of sustainable transformation and digitalization in production engineering
Christian Donhauser ORCID Icon, Daniel Riepl
Digitalization projects help users represent complex processes more simply and efficiently. However, there are many obstacles to implementation. Reluctance to implement these projects is palpable. This affects, among others, employers and employees, who may fall behind economically by waiting or avoiding change. These observations can be traced back to an overarching research question: What barriers and systemic challenges hinder sustainable transformation within the context of Industry 4.0, particularly when considering human labor in production engineering? What questions are the affected stakeholders asking? The primary goal of this long-term research project is to define these questions decisively and in detail in order to develop a conceptual foundation that integrates research, teaching, and technological development and thus combines the potential of digital technologies with the experiential and practical knowledge of production workers.
Industry 4.0 Science | Volume 42 | 2026 | Edition 3 | Pages 56-60
Christoph Brocks