Understanding design metrics: A theoretical model for application and evaluation

Authors

DOI:

https://doi.org/10.47909/awari.833

Keywords:

process metrification in design, user experience, object-oriented design metrics

Abstract

This article presented a theoretical study that aimed to identify applications of metrics in design. The study drew on established experiences from other fields that employed metric studies. It did so in order to propose an appropriate definition for the design discipline. The objective of this study was to conceptualize the phenomenon of design metrics. The scope was developed through a lexicographic analysis of international literature, using the OpenAlex database to map the range of possible metrics applicable to the design. Subsequently, we developed a theoretical framework based on a heuristic approach, employing artificial intelligence to initially identify relevant metric possibilities. Subsequently, clustering techniques were employed to map the associated disciplines and the contexts in which design was subject to quantification. The study identified three core application domains for design metrics. The initial aspect pertained to user experience, with concomitant extensions into the domain of customer behavior analysis. The second involved metrics applied to the development of systems and software, with a focus on improving the management of services and products. The third was directly connected to the second but emphasized the development of systems oriented toward physical objects or artifacts. The study proposed a theoretical model for design metrics, grounded in the tradition of graphic arts, which defined the key elements for its consolidation: the object of analysis, metric methodology, analytical variables, and mathematical application purposes.

Downloads

Download data is not yet available.

References

Albert, B., & Tullis, T. (2013). Measuring the user experience: Collecting, analyzing, and presenting usability metrics (2nd ed.). Morgan Kaufmann.

Alder, K. (2001). The measure of all things: The seven-year odyssey that transformed the world. Abacus.

Argyres, N., Bigelow, L., & Nickerson, J. A. (2013). Dominant designs, innovation shocks, and the follower's dilemma. Strategic Management Journal, 36(2), 216–234. https://doi.org/10.1002/smj.2207

Baba Gnanakumar, P., Ulaganathan, S., & Baby, M. K. (2024). Debunking Indian neo-banks' customer effort score and ESG values. ASEAN Journal on Science and Technology for Development, 41(2), Article 4. https://doi.org/10.61931/2224-9028.1565

Bangor, A., Kortum, P. T., & Miller, J. T. (2008). An empirical evaluation of the System Usability Scale. International Journal of Human–Computer Interaction, 24(6), 574–594. https://doi.org/10.1080/10447310802205776

Benavides, E. M. (2012). Metric design. In Advanced engineering design: An integrated approach (pp. 133–258). Woodhead Publishing. https://doi.org/10.1533/9780857095046.133

Briand, L., Morasca, S., & Basili, V. R. (1999). Defining and validating measures for object-based high-level design. IEEE Transactions on Software Engineering, 25(5), 722–743. https://doi.org/10.1109/32.815329

Brito e Abreu, F., & Melo, W. (1996). Evaluating the impact of object-oriented design on software quality. In Proceedings of the 3rd international software metrics symposium (pp. 90–99). https://doi.org/10.1109/METRIC.1996.492446

Cabrera, J. (2017). Modular design frameworks: A projects-based guide for UI/UX designers. Apress.

Chidamber, S. R., & Kemerer, C. F. (1994). A metrics suite for object-oriented design. IEEE Transactions on Software Engineering, 20(6), 476–493. https://doi.org/10.1109/32.295895

Farris, P., Bendle, N., Pfeifer, P., & Reibstein, D. (2010). Marketing metrics: The definitive guide to measuring marketing performance. Pearson Education.

Fenton, N. E. (1991). Software metrics: A rigorous approach. Chapman & Hall.

Frisch, R. (1933). Propagation problems and impulse problems in dynamic economics. In Economic essays in honour of Gustav Cassel (pp. 171–205). Allen & Unwin.

Gorbea Portal, S. (2005). Modelo teórico para el estudio métrico de la información documental. Trea.

Hadden, J., Tiwari, A., Roy, R., & Ruta, D. (2007). Computer assisted customer churn management: State-of-the-art and future trends. Computers & Operations Research, 34(10), 2902–2917. https://doi.org/10.1016/j.cor.2005.11.007

Hess, M. (2015). A metric test object informed by user requirements for better 3D recording of cultural heritage artefacts [Doctoral dissertation, University College London].

Hinton, A., & Lambert, W. M. (2022). Moving diversity, equity, and inclusion from opinion to evidence. Cell Reports Medicine, 3(4), 1–4. https://doi.org/10.1016/j.xcrm.2022.100619

Ismail, A. A. H. E., & Abdulkareem, A. M. (2024). Data-driven techniques for quantitative analysis of customer journey mapping in digital commerce. Emerging Trends in Machine Intelligence and Big Data, 16(4), 1–8.

Kantalainen, E. (2018). Conversion rate optimization with UI & UX design [Master’s thesis, University of York].

Kitchenham, B. A., & Linkman, S. J. (1990). Design metrics in practice. Information and Software Technology, 32(4), 304–310. https://doi.org/10.1016/0950-5849(90)90064-X

Kokubo, N., Yokoi, Y., Saitoh, Y., Murata, M., Maruo, K., Takebayashi, Y., Shinmei, I., Yoshimoto, S., & Horikoshi, M. (2018). A new device-aided cognitive function test, User eXperience-Trail Making Test (UX-TMT), sensitively detects neuropsychological performance in patients with dementia and Parkinson’s disease. BMC Psychiatry, 18(220), 1–10. https://doi.org/10.1186/s12888-018-1795-7

Kumar, V., & Reinartz, W. (2016). Creating enduring customer value. Journal of Marketing, 80(6), 36–68. https://doi.org/10.1509/jm.15.0414

Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96. https://doi.org/10.1509/jm.15.0420

Lima, E. L. (2017). Metric spaces (5th ed.). IMPA.

McGrath, W. (1989). What bibliometricians, scientometricians and informetricians study; a typology for definition and classification; topics for discussion. In: 2nd International conference on bibliometrics, scientometrics and informetrics, Ontario, 1989. The University of Western Ontario.

Meinel, C., Plattner, H., & Leifer, L. (2012). Design thinking research: Measuring performance in context. Springer.

Mkpojiogu, E. O. C., & Hashim, N. L. (2016). Understanding the relationship between Kano model’s customer satisfaction scores and self-stated requirements importance. SpringerPlus, 5(197), 1–22. https://doi.org/10.1186/s40064-016-1860-y

Moreno, J. L. (1934). Who shall survive? A new approach to the problem of human interrelations. Nervous and Mental Disease Publishing.

Nacke, O. (1979). Informetrie: eine neuer Name für eine neue Disziplin. Nachrichten für Documentation, 30(6), 219–226.

Nalimov, V. V., & Mul’chenko, Z. M. (1969). Naukometriya: Izucheniye razvitiya nauki kak informatsionnogo protsessa. Nauka.

O’Keeffe, M., & Cinnéide, M. Ó. (2003). A stochastic approach to automated design improvement. In Proceedings of the 2nd international conference on principles and practice of programming in Java (pp. 59–62). https://doi.org/10.5555/957289.957308

Palmer, J. W. (2002). Website usability, design, and performance metrics. Information Systems Research, 13(2), 151–167. https://doi.org/10.1287/isre.13.2.151.88

Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349. https://doi.org/10.1108/eb026482

Quah, T. S., & Thwin, M. M. T. (2003). Application of neural networks for software quality prediction using object-oriented metrics. In International conference on software maintenance (pp. 116–125). https://doi.org/10.1109/ICSM.2003.1235412

Rizzi, C., Campana, F., Bici, M., & Gherardini, F. (2021). Design tools and methods in industrial engineering II. In Proceedings of the second international conference on design tools and methods in industrial engineering, Rome, September 9–10. Springer.

Rombach, H. D. (1987). A controlled experiment on the impact of software structure on maintainability. IEEE Transactions on Software Engineering, 13(3), 344–354. https://doi.org/10.1109/TSE.1987.233165

Sasmito, G. W., Zulfiqar, L. O. M., & Nishom, M. (2019). Usability testing based on System Usability Scale and Net Promoter Score. In International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) (pp. 540–545). https://doi.org/10.1109/ISRITI48646.2019.9034666

Schramade, W. (2017). Investing in the UN Sustainable Development Goals: Opportunities for companies and investors. Journal of Applied Corporate Finance, 29(2), 87–99. https://doi.org/10.1111/jacf.12236

Schroth, S. (2025). Design a digital product that sells daily: The passive income blueprint for creators. Recorded Books.

Selby, R., & Hihn, J. (2006). Enabling early lifecycle predictive models of software systems. In Space 2006 conference proceedings. https://doi.org/10.2514/6.2006-7218

Shah, J. J., Kulkarni, S. V., & Vargas-Hernandez, N. (2000). Evaluation of idea generation methods for conceptual design: Effectiveness metrics and design of experiments. Journal of Mechanical Design, 122(4), 377–384. https://doi.org/10.1115/1.1315592

Shaik, A., Reddy, C. R. K., Manda, B., Prakashini, C., & Deepthi, K. (2010). An empirical validation of object-oriented design metrics in object-oriented systems. Journal of Emerging Trends in Engineering and Applied Sciences, 1(2).

Šperková, L., Škola, P., & Bruckner, T. (2015). Evaluation of e-Word-of-Mouth through Business Intelligence processes in banking domain. Journal of Intelligence Studies in Business, 5(2), 36–47. https://doi.org/10.37380/jisib.v5i2.129

Tague-Sutcliffe, J. (1992). An introduction to informetrics. Information Processing & Management, 28(1), 1–3. https://doi.org/10.1016/0306-4573(92)90087-G

Trialopa, E. F. (2022). Optimizing the customer service performance with using chatbot by utilizing bot accuracy, journey completion rate, and customer satisfaction score (CSAT). https://dspace.uii.ac.id/handle/123456789/42045

Xia, F. (1996). Module coupling: A design metric. In Proceedings 1996 Asia-Pacific software engineering conference (pp. 44–54). https://doi.org/10.1109/APSEC.1996.566739

Zage, W. M., & Zage, D. M. (1993). Evaluating design metrics on large-scale software. IEEE Software, 10(4), 75–81. https://doi.org/10.1109/52.219620

Downloads

Published

23-06-2025

How to Cite

Pinto, A. L., Monteiro Teixeira, J., & Lewis Velasco, J. (2025). Understanding design metrics: A theoretical model for application and evaluation. AWARI, 6, 1–10. https://doi.org/10.47909/awari.833

Issue

Section

Original article