Tucker J. Marion

1.8k total citations · 1 hit paper
56 papers, 1.2k citations indexed

About

Tucker J. Marion is a scholar working on Management of Technology and Innovation, Strategy and Management and Mechanical Engineering. According to data from OpenAlex, Tucker J. Marion has authored 56 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Management of Technology and Innovation, 21 papers in Strategy and Management and 18 papers in Mechanical Engineering. Recurrent topics in Tucker J. Marion's work include Innovation and Knowledge Management (19 papers), Product Development and Customization (18 papers) and Design Education and Practice (18 papers). Tucker J. Marion is often cited by papers focused on Innovation and Knowledge Management (19 papers), Product Development and Customization (18 papers) and Design Education and Practice (18 papers). Tucker J. Marion collaborates with scholars based in United States, Mexico and United Kingdom. Tucker J. Marion's co-authors include Sebastian K. Fixson, John H. Friar, Timothy W. Simpson, Gloria Barczak, Marc H. Meyer, Mohsen Moghaddam, Erik Jan Hultink, Denise Dunlap, Abe Zeid and Sagar Kamarthi and has published in prestigious journals such as Journal of Business Venturing, International Journal of Production Research and Information & Management.

In The Last Decade

Tucker J. Marion

51 papers receiving 1.1k citations

Hit Papers

The Transformation of the... 2020 2026 2022 2024 2020 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tucker J. Marion United States 21 462 433 261 204 167 56 1.2k
Stefano Magistretti Italy 18 420 0.9× 243 0.6× 132 0.5× 244 1.2× 138 0.8× 40 1.0k
Sebastian K. Fixson United States 16 681 1.5× 735 1.7× 210 0.8× 344 1.7× 273 1.6× 38 1.4k
Falk Uebernickel Switzerland 18 299 0.6× 228 0.5× 284 1.1× 123 0.6× 412 2.5× 127 1.4k
Eric Rebentisch United States 18 607 1.3× 383 0.9× 257 1.0× 95 0.5× 402 2.4× 85 1.4k
Preston G. Smith United States 13 328 0.7× 340 0.8× 146 0.6× 107 0.5× 212 1.3× 39 1.1k
Manuel E. Sosa United States 18 694 1.5× 946 2.2× 229 0.9× 555 2.7× 149 0.9× 42 2.0k
Kathrin M. Möslein Germany 18 396 0.9× 371 0.9× 180 0.7× 82 0.4× 135 0.8× 90 1.5k
Daniel Capaldo Amaral Brazil 15 475 1.0× 471 1.1× 254 1.0× 55 0.3× 327 2.0× 77 1.4k
David Baxter United Kingdom 19 272 0.6× 291 0.7× 241 0.9× 169 0.8× 108 0.6× 56 1.0k
Kathryn Cormican Ireland 20 521 1.1× 238 0.5× 93 0.4× 48 0.2× 231 1.4× 96 1.4k

Countries citing papers authored by Tucker J. Marion

Since Specialization
Citations

This map shows the geographic impact of Tucker J. Marion'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 Tucker J. Marion with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tucker J. Marion more than expected).

Fields of papers citing papers by Tucker J. Marion

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tucker J. Marion. 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 Tucker J. Marion. The network helps show where Tucker J. Marion may publish in the future.

Co-authorship network of co-authors of Tucker J. Marion

This figure shows the co-authorship network connecting the top 25 collaborators of Tucker J. Marion. A scholar is included among the top collaborators of Tucker J. Marion 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 Tucker J. Marion. Tucker J. Marion 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.
Marion, Tucker J., et al.. (2025). Integrating AI into the Front End of New Product Development. Research-Technology Management. 68(2). 10–22.
2.
Yuan, Chenxi, et al.. (2024). DCG-GAN: design concept generation with generative adversarial networks. Design Science. 10. 5 indexed citations
3.
Piller, Frank T., et al.. (2024). Generative AI, Innovation, and Trust. The Journal of Applied Behavioral Science. 60(4). 613–622. 8 indexed citations
4.
Yuan, Chenxi, et al.. (2023). ARE GENERATIVE ADVERSARIAL NETWORKS CAPABLE OF GENERATING NOVEL AND DIVERSE DESIGN CONCEPTS? AN EXPERIMENTAL ANALYSIS OF PERFORMANCE. Proceedings of the Design Society. 3. 633–644. 9 indexed citations
5.
Koskinen, Kari, et al.. (2023). Tethered Architectures in Cyber-Physical System Development: The Case of Tesla's Autopilot System. SSRN Electronic Journal. 1 indexed citations
6.
Han, Yi, et al.. (2023). EXTRACTING LATENT NEEDS FROM ONLINE REVIEWS THROUGH DEEP LEARNING BASED LANGUAGE MODEL. Proceedings of the Design Society. 3. 1855–1864. 5 indexed citations
7.
Moghaddam, Mohsen, et al.. (2023). Special Issue: Emerging Technologies and Methods for Early-Stage Product Design and Development. Journal of Mechanical Design. 145(4). 5 indexed citations
9.
Marion, Tucker J., David M. Cannon, Tahira Reid, & Anna‐Maria R. McGowan. (2021). A CONCEPTUAL MODEL FOR INTEGRATING DESIGN THINKING AND LEAN STARTUP METHODS INTO THE INNOVATION PROCESS. Proceedings of the Design Society. 1. 31–40. 1 indexed citations
10.
Seidel, Victor P., Tucker J. Marion, & Sebastian K. Fixson. (2020). Innovating How to Learn Design Thinking, Making, and Innovation: Incorporating Multiple Modes in Teaching the Innovation Process. INFORMS Transactions on Education. 20(2). 73–84. 17 indexed citations
11.
Marion, Tucker J. & Sebastian K. Fixson. (2020). The Transformation of the Innovation Process: How Digital Tools are Changing Work, Collaboration, and Organizations in New Product Development*. Journal of Product Innovation Management. 38(1). 192–215. 218 indexed citations breakdown →
12.
Marion, Tucker J. & Sebastian K. Fixson. (2019). The Influence of Collaborative Information Technology Tool Usage on NPD. Proceedings of the ... International Conference on Engineering Design. 1(1). 219–228. 2 indexed citations
13.
Marion, Tucker J. & Marc H. Meyer. (2018). Organizing to Achieve Modular Architecture Across Different Products. IEEE Transactions on Engineering Management. 65(3). 404–416. 5 indexed citations
14.
Marion, Tucker J. & Sebastian K. Fixson. (2018). The Innovation Navigator. University of Toronto Press eBooks. 7 indexed citations
15.
Marion, Tucker J., Mike Reid, Erik Jan Hultink, & Gloria Barczak. (2016). The Influence of Collaborative IT Tools on NPD. Research-Technology Management. 59(2). 47–54. 20 indexed citations
16.
Marion, Tucker J. & John H. Friar. (2012). Managing Global Outsourcing to Enhance Lean Innovation: Outsourcing Techniques Used by Smaller Firms Can Help Larger Firms Keep R&D Lean While Maintaining Innovation Efficiency. Research-Technology Management. 55(5). 44.
17.
Marion, Tucker J., et al.. (2009). Moving New Venture New Product Development from Information Push to Pull Using Web 2.0. 287–296. 7 indexed citations
18.
Marion, Tucker J.. (2009). A Framework for Balancing Efficiency and Effectiveness in Innovative Product Design. 369–378. 3 indexed citations
19.
Alizon, Fabrice, Tucker J. Marion, Steven B. Shooter, & Timothy W. Simpson. (2007). Tools for the Platform Designer’S Toolbox. Guidelines for a Decision Support Method Adapted to NPD Processes. 2 indexed citations
20.
Marion, Tucker J., et al.. (2006). Two Methodologies for Identifying Product Platform Elements Within an Existing Set of Products. 811–821. 15 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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