Innovation Diffusion Associated with Informatics Capability Building in Civil Engineering Organizations

Authors

  • Jennifer K. Hughes Department of Advanced Computing, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA Author

Keywords:

Civil Engineering, Innovation Diffusion, Informatics Capability, Controlled Experiment, Software Engineering

Abstract

This paper examines the mechanisms of innovation diffusion within civil engineering organizations by focusing on informatics capability building. Traditional construction and engineering firms frequently encounter persistent barriers to digital transformation, driven by fragmented workflows, temporary project-based structures, and a cultural aversion to technological disruption. To investigate how informatics capabilities—specifically advanced computational design, parametric modeling, and data analytics—diffuse within these organizations, we conducted a rigorous controlled experiment involving 120 professional civil engineers across multiple design firms. The experimental group participated in a structured, peer-coached, and project-integrated capability-building program, whereas the control group relied on conventional self-paced online modules and passive software onboarding. Over a six-month monitoring period, we tracked individual skill acquisition, actual application on live projects, and subsequent peer-to-peer knowledge diffusion using social network analysis. The empirical results reveal that the structured, peer-supported intervention led to a statistically significant increase in both software proficiency and the rate of internal skill transmission compared to the control group. Network analysis demonstrated that trained peer coaches acted as critical catalysts, accelerating the diffusion of informatics practices to untrained colleagues by a substantial margin. These findings provide robust quantitative evidence that deliberate, network-centric capability building outperforms passive technology dissemination, offering a scalable blueprint for digital modernization in the civil engineering sector.

References

1. Walker, A. Blockchain and the Supply Chain. 2019. Available online: https://wpassets.porttechnology.org/wp-content/uploads/2020/03/25160842/CSUN.pdf (accessed on 12 January 2025).

2. Mvubu, M.; Naude, M.J. Digital transformation at third-party logistics providers: Challenges and best practices. J. Transp. Supply Chain Manag. 2024, 18, 1023.

3. Erickson, B.; Fausti, S.; Clay, D.; Clay, S. Knowledge, skills, and abilities in the precision agriculture workforce: An industry survey. Nat. Sci. Educ. 2018, 47, 1–11.

4. Gumbi, N.; Gumbi, L.; Twinomurinzi, H. Towards sustainable digital agriculture for smallholder farmers: A systematic literature review. Sustainability 2023, 15, 12530.

5. European Commission. Council Recommendation of 22 May 2018 on Key Competences for Lifelong Learning (Text with EEA Relevance), Official Journal of the European Union, 2018/C 189/01, 4.6.2018. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=oj:JOC_2018_189_R_0001 (accessed on 15 January 2026).

6. Delenclos, F.X.; Rasmussen, A.; Riedl, J. To Get Smart, Ports Go Digital. 2018. Available online: https://fightingmonarch.com/wp-content/uploads/2022/08/to-get-smart-ports-go-digital.pdf (accessed on 12 January 2025).

7. Katalin, T.G.; Rahoveanu, T.; Magdalena, M.; István, T. Sustainable new agricultural technology–economic aspects of precision crop protection. Procedia Econ. Financ. 2014, 8, 729–736.

8. European Commission. The European Green Deal, Communication from the Commission, COM(2019) 640 Final, Brussels, 11.12.2019 . Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640 (accessed on 15 January 2026).

9. General Assembly. Resolution Adopted by the General Assembly on 19 September 2016. A/RES/71/1. Available online: https://www.refworld.org/legal/resolution/unga/2016/en/112142 (accessed on 15 January 2026).

10. ITU. Digital Trends in Africa 2021. Available online: https://www.itu.int/hub/publication/d-ind-dig_trends_afr-01-2021/ (accessed on 15 January 2026).

11. UNICEF. Digital Mapping Analysis Sri Lanka, UNICES ROSA SBC—Digital Mapping 2025. Available online: https://clearinghouse.unicef.org/sites/ch/files/ch/teams-PD-C4D-Knowledge%20%20UNICEF-SAR%20Digital%20Mapping-SRI%20LANKA-2.0.pdf (accessed on 15 January 2026).

12. Mergel, I.; Edelmann, N.; Haug, N. Defining digital transformation: Results from expert interviews. Gov. Inf. Q. 2019, 36, 101385.

13. Rane, N.; Choudhary, S.; Rane, J. Artificial intelligence for enhancing resilience. J. Appl. Artif. Intell. 2024, 5, 1–33.

14. Magesa, M.; Jonathan, J.; Urassa, J. Digital Literacy of Smallholder Farmers in Tanzania. Sustainability 2023, 15, 13149.

15. Almeida, F. Challenges in the digital transformation of ports. Businesses 2023, 3, 548–568.

16. Berckmans, D. General introduction to precision livestock farming. Anim. Front. 2017, 7, 6–11.

17. Podstawka, M. The use of artificial intelligence in agriculture. In Ubezpieczenia W Rolnictwie—Materiały I Studia; OJS @ Academicon: Singapore, 2015; pp. 265–276.

18. González-Cancelas, N.; Palacios Calzada, J.P.C.; Vaca-Cabrero, J.; Camarero-Orive, A. Optimizing Sustainable Port Logistics in Spanish Ports with Emerging Technologies. Sustainability 2025, 17, 3392.

19. Jararweh, Y.; Fatima, S.; Jarrah, M.; AlZubi, S. Smart and sustainable agriculture: Fundamentals, enabling technologies, and future directions. Comput. Electr. Eng. 2023, 110, 108799.

20. Beltran-Peña, A.; Rosa, L.; D’Odorico, P. Global food self-sufficiency in the 21st century under sustainable intensification of agriculture. Environ. Res. Lett. 2020, 15, 095004.

21. Wang, T.; Jin, H.; Sieverding, H.L. Factors affecting farmer perceived challenges towards precision agriculture. Precis. Agric. 2023, 24, 2456–2478.

22. Monteiro, A.; Santos, S.; Gonçalves, P. Precision agriculture for crop and livestock farming—Brief review. Animals 2021, 11, 2345.

23. Tzanidakis, C.; Tzamaloukas, O.; Simitzis, P.; Panagakis, P. Precision livestock farming applications (PLF) for grazing animals. Agriculture 2023, 13, 288.

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Published

2026-01-25

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