Michael A. Zaggl

414 total citations
33 papers, 264 citations indexed

About

Michael A. Zaggl is a scholar working on Computer Science Applications, Communication and Strategy and Management. According to data from OpenAlex, Michael A. Zaggl has authored 33 papers receiving a total of 264 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Science Applications, 11 papers in Communication and 8 papers in Strategy and Management. Recurrent topics in Michael A. Zaggl's work include Open Source Software Innovations (14 papers), Knowledge Management and Sharing (9 papers) and Innovation and Knowledge Management (6 papers). Michael A. Zaggl is often cited by papers focused on Open Source Software Innovations (14 papers), Knowledge Management and Sharing (9 papers) and Innovation and Knowledge Management (6 papers). Michael A. Zaggl collaborates with scholars based in Germany, Denmark and United States. Michael A. Zaggl's co-authors include Ann Majchrzak, Arvind Malhotra, Joern Block, Tim Schweisfurth, Christina Raasch, Matthias Meyer, Kathleen M. Carley, Cornelius Herstatt, Oliver Alexy and Jennifer L. Gibbs and has published in prestigious journals such as Strategic Management Journal, Research Policy and MIS Quarterly.

In The Last Decade

Michael A. Zaggl

29 papers receiving 249 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael A. Zaggl Germany 11 74 54 53 53 49 33 264
Matthias Stuermer Switzerland 7 106 1.4× 86 1.6× 26 0.5× 38 0.7× 31 0.6× 9 294
Elad Harison Israel 6 53 0.7× 97 1.8× 49 0.9× 39 0.7× 19 0.4× 22 237
Patrick Pollok Germany 7 174 2.4× 117 2.2× 27 0.5× 65 1.2× 48 1.0× 16 334
Sridhar S. Papagari United States 5 36 0.5× 150 2.8× 28 0.5× 64 1.2× 71 1.4× 7 322
Choong Kwon Lee South Korea 12 42 0.6× 62 1.1× 105 2.0× 104 2.0× 34 0.7× 28 340
John Prpić Canada 8 241 3.3× 35 0.6× 58 1.1× 81 1.5× 49 1.0× 21 397
Margaret T. O’Hara United States 8 57 0.8× 55 1.0× 39 0.7× 32 0.6× 33 0.7× 13 306
Gamel O. Wiredu Ghana 8 24 0.3× 40 0.7× 74 1.4× 80 1.5× 24 0.5× 18 266
Kari Liukkunen Finland 9 73 1.0× 54 1.0× 44 0.8× 30 0.6× 18 0.4× 32 332
Jeremy Hutchison‐Krupat United Kingdom 7 49 0.7× 113 2.1× 49 0.9× 18 0.3× 15 0.3× 14 258

Countries citing papers authored by Michael A. Zaggl

Since Specialization
Citations

This map shows the geographic impact of Michael A. Zaggl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael A. Zaggl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael A. Zaggl more than expected).

Fields of papers citing papers by Michael A. Zaggl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael A. Zaggl. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael A. Zaggl. The network helps show where Michael A. Zaggl may publish in the future.

Co-authorship network of co-authors of Michael A. Zaggl

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Zaggl. A scholar is included among the top collaborators of Michael A. Zaggl based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael A. Zaggl. Michael A. Zaggl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zaggl, Michael A., et al.. (2025). Success of mass customization toolkits: Product design typicality as boundary condition. Journal of Business Research. 200. 115669–115669.
2.
Zaggl, Michael A., et al.. (2025). Benefits for thee, not for me? mHealth engagement through the lens of privacy calculus theory and trust. Behaviour and Information Technology. 44(19). 4663–4683.
3.
Zaggl, Michael A. & Matthias M. Müller. (2024). Creativity reputation allocation in open and distributed innovation. Technovation. 138. 103117–103117. 2 indexed citations
4.
Zaggl, Michael A.. (2024). How Artifact-Based and Authority-Based Coordination Affect Propagation Costs in Open Source Software Development. MIS Quarterly. 49(2). 805–822. 1 indexed citations
5.
Zaggl, Michael A., et al.. (2024). The role of data science and data analytics for innovation: a literature review. RePEc: Research Papers in Economics. 7(4). 207–223. 2 indexed citations
6.
Schweisfurth, Tim, et al.. (2023). Distributed decision‐making in the shadow of hierarchy: How hierarchical similarity biases idea evaluation. Strategic Management Journal. 44(9). 2255–2282. 16 indexed citations
7.
Zaggl, Michael A., Arvind Malhotra, Oliver Alexy, & Ann Majchrzak. (2023). Governing crowdsourcing for unconstrained innovation problems. Strategic Management Journal. 44(11). 2783–2817. 11 indexed citations
8.
Lee, Jeong-Sik, Hyunwoo Park, & Michael A. Zaggl. (2022). When to Signal? Contingencies for Career-Motivated Contributions in Online Collaboration Communities. Journal of the Association for Information Systems. 23(6). 1386–1419. 4 indexed citations
9.
Zaggl, Michael A., et al.. (2022). Does Member Familiarity Help or Hinder Innovation? The Roles of Expertise and Dialogic Coordination. Academy of Management Proceedings. 2022(1). 2 indexed citations
10.
Zaggl, Michael A., et al.. (2022). Does Member Familiarity Help or Hinder Innovation? The Roles of Expertise and Dialogic Coordination. IEEE Transactions on Engineering Management. 71. 4006–4021. 4 indexed citations
11.
Lee, Jeongsik Jay, Hyunwoo Park, & Michael A. Zaggl. (2021). When to Signal? The Contextual Conditions for Career-Motivated User Contributions in Online Collaboration Communities. Proceedings of the ... Annual Hawaii International Conference on System Sciences. 1 indexed citations
12.
Zaggl, Michael A., Yao Sun, Ann Majchrzak, & Arvind Malhotra. (2021). Integrative Solutions in Online Crowdsourcing Innovation Challenges. Proceedings of the ... Annual Hawaii International Conference on System Sciences.
13.
Zaggl, Michael A., et al.. (2019). An Agent-Based Model of an Online Collaboration Community by using Fuzzy Logic. IFAC-PapersOnLine. 52(13). 665–670. 3 indexed citations
14.
Zaggl, Michael A., Tim Schweisfurth, & Cornelius Herstatt. (2019). The Dynamics of Openness and the Role of User Communities: A Case Study in the Ecosystem of Open Source Gaming Handhelds. IEEE Transactions on Engineering Management. 67(3). 712–723. 18 indexed citations
15.
Zaggl, Michael A., et al.. (2018). Hierarchical Distance and Idea Evaluation in Enterprise Crowdfunding. Journal of the Association for Information Systems. 4 indexed citations
16.
Zaggl, Michael A., et al.. (2018). The choice between uniqueness and conformity in mass customization. R and D Management. 49(2). 204–221. 21 indexed citations
17.
Reif, Julia A. M., Katharina G. Kugler, Felix C. Brodbeck, et al.. (2017). Modeling as the basis for innovation cycle management of PSS: Making use of interdisciplinary models. mediaTUM (Technical University of Munich). 1–6. 10 indexed citations
18.
Schweisfurth, Tim, et al.. (2017). Does similarity between evaluator and creator affect the evaluation of ideas?. Academy of Management Proceedings. 2017(1). 16758–16758. 6 indexed citations
19.
20.
Zaggl, Michael A.. (2013). Eleven mechanisms for the evolution of cooperation. Journal of Institutional Economics. 10(2). 197–230. 19 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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