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Journals / Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji / 2025 / Cilt: 13 Sayı: 4

From Divergence to Alignment: Diagrammatic Thinking Across Industrial Design, Engineering, and Marketing

Farklılıktan Uyuma: Endüstriyel Tasarım, Mühendislik ve Pazarlama Disiplinlerinde Diyagramlarla Düşünme

Hüseyin Özkal Özsoy(MİMAR SİNAN GÜZEL SANATLAR ÜNİVERSİTESİ)0000-0001-5531-3539
Pages
1715–1727
Publication Date
2025-12-22
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings contribute to a deeper understanding of visual mediation as a critical factor in collaborative product development and propose strategies for aligning cognitive and visual frameworks to improve interdisciplinary communication and design outcomes.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In industrial product development, effective collaboration among designers, engineers, and marketers is crucial, yet is frequently challenged by fundamentally divergent mental models of how a product should function, appear, and succeed in the market.
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Key Findings & Data:Each discipline interprets and communicates design intent through distinct visual and cognitive frameworks, including conceptual sketches, technical schematics, customer journey maps, and market flows.
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Conclusion & Impact:The findings contribute to a deeper understanding of visual mediation as a critical factor in collaborative product development and propose strategies for aligning cognitive and visual frameworks to improve interdisciplinary communication and design outcomes.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Endüstriyel ürün geliştirme · Görsel düşünme · Zihinsel modeller

Abstract

In industrial product development, effective collaboration among designers, engineers, and marketers is crucial, yet is frequently challenged by fundamentally divergent mental models of how a product should function, appear, and succeed in the market. Each discipline interprets and communicates design intent through distinct visual and cognitive frameworks, including conceptual sketches, technical schematics, customer journey maps, and market flows. This article investigates how these disciplinary perspectives manifest in visual thinking practices and how shared diagramming tools function as mediators or points of friction within multidisciplinary teams. The study maps the interplay between mental models and representational practices by drawing on literature from design cognition, visual semiotics, systems thinking, and empirical observations from collaborative design settings. It further explores how misalignments impact decision-making, innovation, and project coherence. The findings contribute to a deeper understanding of visual mediation as a critical factor in collaborative product development and propose strategies for aligning cognitive and visual frameworks to improve interdisciplinary communication and design outcomes.

Özet

Endüstriyel ürün geliştirme sürecinde, tasarımcılar, mühendisler ve pazarlamacılar arasındaki etkili iş birliği büyük önem taşır; ancak bir ürünün nasıl çalışması, nasıl görünmesi ve pazarda nasıl başarılı olması gerektiğine dair kökten farklı zihinsel modeller nedeniyle bu iş birliği sıklıkla zorluklarla karşılaşır. Her disiplin, tasarım niyetini kavramsal eskizler, teknik şemalar, müşteri yolculuğu haritaları ve pazar akışları gibi kendine özgü görsel ve bilişsel çerçeveler aracılığıyla yorumlar ve aktarır. Bu makale, disiplinler arası bakış açılarını görsel düşünme pratiklerinde nasıl tezahür ettirdiğini ve paylaşılan diyagram araçlarının çok disiplinli ekipler içinde birer arabulucu mu yoksa sürtüşme noktası mı olduğunu araştırmaktadır. Çalışma, zihinsel modeller ile temsil pratikleri arasındaki etkileşimi tasarım bilişi, görsel göstergebilim, sistem düşüncesi ve iş birliğine dayalı tasarım ortamlarından elde edilen ampirik gözlemler ışığında haritalandırmaktadır. Ayrıca, bu uyumsuzlukların karar alma süreçleri, yenilikçilik ve proje bütünlüğü üzerindeki etkilerini incelemektedir. Bulgular, görsel aracılığın ortak ürün geliştirme süreçlerinde kritik bir faktör olarak daha derinlemesine anlaşılmasına katkı sağlamakta ve bilişsel ve görsel çerçevelerin hizalanmasına yönelik stratejiler önererek disiplinler arası iletişimi ve tasarım çıktılarının niteliğini artırmayı amaçlamaktadır.

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Cite This Article

Özsoy, H. Ö. (2025). From Divergence to Alignment: Diagrammatic Thinking Across Industrial Design, Engineering, and Marketing. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, Cilt: 13 Sayı: 4, 1715–1727. https://doi.org/10.29109/gujsc.1711966

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References (62)

  1. Nguyen M, and Mougenot C. A systematic review of empirical studies on multidisciplinary design collaboration: Findings, methods, and challenges. Des. Stud., vol. 81, p. 101120, Jul. 2022, doi: 10.1016/j.destud.2022.101120.
  2. Noble CH, and Kumar M. Exploring the Appeal of Product Design: A Grounded, Value-Based Model of Key Design Elements and Relationships. J. Prod. Innov. Manag., vol. 27, no. 5, pp. 640–657, 2010, doi: 10.1111/j.1540-5885.2010.00742.x.
  3. Pant P. Bridging the communication gap in industrial design engineering: a comprehensive framework for client, consultant designer, and end-user collaboration. 2023. (Accessed: May 08, 2025) https://lutpub.lut.fi/handle/10024/ 166607
  4. Moreno DP, Hernández AA, Yang MC, Otto KN, Otto KH, Linsey JS, Wood KL, Linden A. Fundamental studies in Design-by-Analogy: A focus on domain-knowledge experts and applications to transactional design problems. Des. Stud., vol. 35, no. 3, pp. 232–272, May 2014, doi: 10.1016/j.destud.2013.11.002.
  5. Edvardsson VJ, Wetter-Edman B, and Tronvoll B. Reshaping mental models - enabling innovation through service design. J. Serv. Manag., vol. 30, no. 1, pp. 75–104, 2019, doi: https://doi.org/10.1108/JOSM-08-2017-0186.
  6. Graell-Colas M. Exploring Visual Means for Communication and Collaboration in Multidisciplinary Teams, an Interpretation and Implementation for Design Education. Master's Thesis, The Ohio State University, 2009. (Accessed: May 08, 2025). https://etd.ohiolink.edu/acprod/odb_etd/etd/r/1501/10?clear=10&p10_accession_num=osu1230621313
  7. Wlazlak P, Eriksson Y, Johansson G, and Ahlin P., Visual representations for communication in geographically distributed new product development projects. J. Eng. Des., vol. 30, no. 8–9, pp. 385–403, 2019, doi: https://doi.org/10.1080/09544828.2019.1661362.
  8. Sokolava K. Basic Guidelines to Product Sketching. Hongkiat. (Accessed: May 08, 2025) https://www.hongkiat.com/blog/basic-guidelines-to-product-sketching/
  9. Steeg T. The Presentation of Systems Thinking in Support Materials for Secondary Design and Technology pupils: A review. Presented at the DATA International Research Conference, Loughborough University, 2003.
  10. Rantanen V. Marketing and Sales Funnel Implemented for a Market Research Bachelor’s thesis, Satakunta University of Applied Sciences, 2012. (Accessed: May 08, 2025) http://www.theseus.fi/handle/10024 /44953
  11. Kalay YE, Enhancing multi-disciplinary collaboration through semantically rich representation. Automation in Construction, vol. 10, no. 6, pp. 741–755, Aug. 2001, doi: 10.1016/S0926-5805(00)00091-1.
  12. Rituparna R, and Shinya U. Collaborative autoethnography: ‘self-reflection’ as a timely alternative research approach during the global pandemic. Qualitative Research Journal. Vol. 20, no. 4, pp. 383–392, Jul. 2020, doi: 10.1108/QRJ-06-2020-0054.
  13. Guang YM. Examining cross-disciplinary communication’s impact on multidisciplinary collaborations: implications for innovations. Information Communication Society. Vol. 19, no. 5, pp. 673–690, 2016, doi: https://doi.org/10.1080/1369118X.2016.1139611.
  14. Felten P. Visual Literacy. Change Mag. High. Learn., vol. 40, no. 6, pp. 60–64, Nov. 2008, doi: 10.3200/CHNG.40.6.60-64.
  15. Roberts JL, and Clare L. Meta-representational awareness in mild cognitive impairment: An interpretative phenomenological analysis. Aging Ment. Health, vol. 17, no. 3, pp. 300–309, 2012, doi: https://doi.org/10.1080/13 607863.2012.732033.
  16. Abbott V, and Zardini G. Functor String Diagrams: A Novel Approach to Flexible Diagrams for Applied Category Theory. 2024, arXiv. doi: 10.48550/ARXIV.2404.00249.
  17. Norman D. Some Observations on Mental Models. Mental Models, 1st ed., Psychology Press, 1983, pp. 7–14. doi: 10.4324/978131 5802725-2.
  18. Mumford MD. et al., Mental Models and Creative Problem-Solving: The Relationship of Objective and Subjective Model Attributes. Creativity Research Journal. Vol. 24, no. 4, pp. 311–330, Oct. 2012, doi: 10.1080/10400419.20 12.730008.
  19. Arnott D. Cognitive biases and decision support systems development: a design science approach. Information Systems Journal. Vol. 16, no. 1, pp. 55–78, 2006, doi: 10.1111/j.1365-2575.2006.00208.x.
  20. Overbeeke K, and Hummels C. Industrial Design, in The Encyclopedia of Human-Computer Interaction, vol. 6, Interaction Design Foundation, 2014. (Accessed: May 08, 2025). https://www.interaction-design.org/literature/ book/the-encyclopedia-of-human-computer-interaction-2nd-ed/industrial-design
  21. Anderson DM. Design for Manufacturability & Concurrent Engineering: How to Design for Low Cost, Design in High Quality, Design for Lean Manufacture, and Design Quickly for Fast Production. CIM Press, 2003.
  22. Luchs MG, Swan KS, and Creusen MEH. Perspective: A Review of Marketing Research on Product Design with Directions for Future Research. Journal of Product Innovation Management. Vol. 33, no. 3, pp. 320–341, 2016, doi: 10.1111/jpim.12276.
  23. Jones NA, Ross H, Lynam T, Perez P, and Leitch A. Mental Models: An Interdisciplinary Synthesis of Theory and Methods. Ecology and Sociology. Vol. 16, no. 1, 2011. (Accessed: May 08, 2025). https://www.jstor.org/stable /26268859
  24. Davison G, and Blackman D. The role of mental models in innovative teams. European Journal of Innovation Management. Vol. 8, no. 4, pp. 409–423, Jan. 2005, doi:10.1108/146010 60510627795.
  25. Badke-Schaub P, Neumann A, Lauche K, and Mohammed S. Mental models in design teams: a valid approach to performance in design collaboration?. CoDesign International Journal of CoCreation Des. Arts. Vol. 3, no. 1, pp. 5–20, 2007, doi: https://doi.org/10.1080/1571 0880601170768.
  26. Goldschmidt G. Serial Sketching: Visual Problem Solving in Designing. Cybernetic Systems. Vol. 23, no. 2, pp. 191–219, Mar. 1992, doi: 10.1080/01969729208927457.
  27. Sloman A. Diagrams in the Mind? Diagrammatic Representation and Reasoning, M. Anderson, B. Meyer, and P. Olivier, Eds., London: Springer, 2002, pp. 7–28. doi: 10.1007/978-1-4471-0109-3_1.
  28. Ensmenger N. The Multiple Meanings of a Flowchart. Information and Culture. Vol. 51, no. 3, pp. 321–351, Aug. 2016, doi: 10.7560/IC51302.
  29. Chan CS. Introduction of Design Cognition. In Style and Creativity in Design, Chan CS, Ed., Cham: Springer International Publishing, 2015, pp. 9–78. doi: 10.1007/978-3-319-14017-9_2.
  30. Martins MD, Martins IP, and Fitch WT. A novel approach to investigate recursion and iteration in visual hierarchical processing. Behav. Res. Methods, vol. 48, no. 4, pp. 1421–1442, Dec. 2016, doi: 10.3758/s13428-015-0657-1.
  31. Wynn DC, and Eckert CM. Perspectives on iteration in design and development. Research in Engineering Design. Vol. 28, no. 2, pp. 153–184, Apr. 2017, doi: 10.1007/s00163-016-0226-3.
  32. Gallagher CL. Sketching for Ideation: A Structured Approach for Increasing Divergent Thinking. in Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, in CHI EA ’17. New York, NY, USA: Association for Computing Machinery, May 2017, pp. 106–111. doi: 10.1145/3027063.3048424.
  33. Simmons CH, and Maguire DE. Manual of Engineering Drawing: Technical Product Specification and Documentation to British and International Standards. Butterworth-Heinemann, 2012.
  34. Baba Y, and Nobeoka K. Towards knowledge-based product development: the 3-D CAD model of knowledge creation. Research Policy. Vol. 26, no. 6, pp. 643–659, Feb. 1998, doi: 10.1016/S0048-7333(97)00040-1.
  35. Rishi B, and Popli S. Getting into the Customers' Shoes: Customer Journey Management. In Crafting Customer Experience Strategy, S. Popli and B. Rishi, Eds., Emerald Publishing Limited, 2021, pp. 21–45. doi: 10.1108/978-1-83909-710-220211002.
  36. Bradley C, Oliveira L, Birrell S, and Cain R. A new perspective on personas and customer journey maps: Proposing systemic UX. International Journal of Human-Computer Studies. Vol. 148, p. 102583, Apr. 2021, doi: 10.1016/j.ijhcs.2021.102583.
  37. Black LJ, and Andersen DF. Using Visual Representations as Boundary Objects to Resolve Conflict in Collaborative Model-Building Approaches. Systems Research and Behavioral Science. Vol. 29, no. 2, pp. 194–208, 2012, doi: 10.1002/sres.2106.
  38. Lucidchart, Customer Journey Map. (Accessed: May 08, 2025). https://lucidchart.com/blog/how-to-build-customer-journey-maps
  39. Dekkers R, Chang CM, and Kreutzfeldt J. The interface between ‘product design and engineering’ and manufacturing: A review of the literature and empirical evidence. Int. J. Prod. Econ. Vol. 144, no. 1, pp. 316–333, Jul. 2013, doi: 10.1016/j.ijpe.2013.02.020.
  40. King S, and Chang K. Understanding Industrial Design: Principles for UX and Interaction Design. O’Reilly Media, Inc., 2016.
  41. Pazarkaya İ, Yazar M, and Özdemir A. Eliptik Dişli Tasarımı, İmalatı, Analizi ve Eliptik Dişlilerin Endüstriyel Uygulamaları. Gazi Üniversitesi Fen Bilim. Derg. Part C Tasar. Ve Teknol., vol. 10, no. 3, Art. no. 3, Sep. 2022, doi: 10.29109/gujsc.1103492.
  42. Knotts TL, Jones SC, and Udell GG. Innovation Evaluation and Product Marketability. Market Management Journal. Vol. 19, no. 2, pp. 84–90, 2009.
  43. Vissers G, and Dankbaar B. Creativity in Multidisciplinary New Product Development Teams. Creativity and Innovation Management. Vol. 11, no. 1, pp. 31–42, 2002, doi: 10.1111/1467-8691.00234.
  44. Bennett LM, and Gadlin H. Collaboration and Team Science: From Theory to Practice. J. Investig. Med., vol. 60, no. 5, pp. 768–775, Jun. 2012, doi: 10.2310/JIM.0b013e3182 50871d.
  45. Ewenstein B, and Whyte J. Knowledge Practices in Design: The Role of Visual Representations as `Epistemic Objects’. Organ. Stud., vol. 30, no. 1, pp. 07–30, Jan. 2009, doi: 10.1177/0170840608083014.
  46. Harvey F. Heterogeneous distributed problem-solving involving visual objects as boundary objects. Front. Commun. Vol. 8, Jan. 2024, doi: 10.3389/fcomm.2023.1275695.
  47. Fruchter R. Conceptual, Collaborative Building Design Through Shared Graphics. IEEE Intell. Syst. Vol. 11, no. 03, pp. 33–41, May 1996, doi: 10.1109/64.506752.
  48. Avdiji H, Elikan D, Missonier S, and Pigneur Y. Designing Tools for Collectively Solving Ill-Structured Problems. Hawaii Int. Conf. Syst. Sci. 2018 HICSS-51, Jan. 2018, https://aisel.aisnet.org/hicss-51/cl/processes_and_technologies_for_team/3
  49. Kurpınar G, Çevik A, and Kurpınar Y. Investigating the Use of Immersive Virtual Reality in Professional Architectural Design Process,” Gazi Üniversitesi Fen Bilim. Derg. Part C Tasar. Ve Teknol. Vol. 13, no. 1, Art. no. 1, Mar. 2025, doi: 10.29109/gujsc. 1572568.
  50. Watson BW. Towards an Understanding of Human Behaviour for Design Action. PhD. Thesis, Loughborough University, 2011.
  51. Self JA. The Use of Design Tools in Industrial Design Practice. PhD. Thesis, Kingston University, London, 2012. https://www.researchgate.net/publication/289674998_The_Use_of_Design_Tools_in_Industrial_Design_Practice
  52. Michalek JJ, Feinberg FM, and Papalambros PY. Linking Marketing and Engineering Product Design Decisions via Analytical Target Cascading. Journal of Product Innovation Management. Vol. 22, no. 1, pp. 42–62, 2005, doi: 10.1111/j.0737-6782.2005.00102.x.
  53. Ainsworth S. DeFT: A conceptual framework for learning with multiple representations. Learning and Instruction. Vol. 16, pp. 183–198, Jun. 2006, doi: 10.1016/j.learninstruc. 2006.03.001.
  54. Gergle D, Kraut DE, and Fussell SR. Language Efficiency and Visual Technology: Minimizing Collaborative Effort with Visual Information. Journal of Language and Social Psychology. Vol. 23, no. 4, pp. 491–517, Dec. 2004, doi: 10.1177/0261927X04269589.
  55. Cotter A. Moving and being moved through time: Autoethnographic Reflections on first-person research and its development over 30 years. Counselling and Psychotherapy Research. Vol. 17, no. 2, pp. 104–112, 2017, doi: 10.1002/capr.12098.
  56. Ellis G. So, What Are Cognitive Biases?. In Cognitive Biases in Visualizations, Ellis G. Ed., Cham: Springer International Publishing, 2018, pp. 1–10. doi: 10.1007/978-3-319-95831-6_1.
  57. Braun J. Reflective Journaling on a Systems Approach to Vehicle Design. ASEE Annual Conference & Exposition, Vancouver, BC: American Society for Engineering Education, 2011, p. 22.1231.1-22.1231.13. doi: 10.18260 /1-2--18630.
  58. Lucidchart. (Accessed: May 13, 2025). https://www.lucidchart.com/pages/landing
  59. Hellweger S, and Wang X. What is User Experience Really: towards a UX Conceptual Framework, Mar. 06, 2015, arXiv: arXiv:1503.01850. doi: 10.48550/arXiv.1503. 01850.
  60. Tally RT. Introduction: Mapping Narratives. In Literary Cartographies: Spatiality, Representation, and Narrative, Tally RT. Ed., New York: Palgrave Macmillan US, 2014, pp. 1–12. doi: 10.1057/9781137449375_1.
  61. Graell-Colas M. Exploring Visual Means for Communication and Collaboration in Multidisciplinary Teams, an Interpretation and Implementation for Design Education. Master's Thesis, The Ohio State University, 2009. (Accessed: May 08, 2025). https://etd.ohiolink.edu/acprod/odb_etd/etd/r/1501/10?clear=10&p10_accession_num=osu1230621313
  62. Lucidchart, Customer Journey Map. (Accessed: May 08, 2025). https://lucidchart.com/blog/how-to-build-customer-journey-maps