Theory, Transformation, Practice and Exploration — A Review of An Introduction to Computational Advertising

Authors

  • Xin Gao South China University of Technology Author
  • Jinhai Zhang Wuhan Technology and Business University Author

DOI:

https://doi.org/10.63029/s4q7w409

Keywords:

Computational advertising, Digital advertising ecosystem, Algorithmic decision‐making, Human– machine collaboration, Value networks, Algorithmic governance

Abstract

This review offers a critical examination of An Introduction to Computational Advertising (in Chinese 计算广告学概论), edited in 2024 by Duan Chunlin, which presents a foundational framework for the emerging discipline of computational advertising in the era of data intelligence. Organised into four sections—Theoretical, Transformation, Practical and Exploratory—the book systematically constructs the conceptual boundaries of computational advertising, explains its algorithmic and technological infrastructure, and situates it within contemporary digital ecosystems shaped by platform mechanisms and human–machine collaboration. It provides valuable insights into user targeting, programmatic creativity, value optimisation and effect measurement, while also addressing frontier topics such as intelligent brand communication, metaverse media and algorithmic governance. This review evaluates the book’s contributions to disciplinary development, highlights its strengths in theoretical integration and contextual analysis, and identifies limitations related to empirical validation and international applicability. It concludes by suggesting directions for future research, including algorithmic fairness, model interpretability and interdisciplinary dialogue. This review highlights the contributions of the book to the field of computational advertising and its potential to inspire future scholarship and practice.

Author Biographies

  • Xin Gao, South China University of Technology

    Xin Gao is a doctoral candidate in Business Administration (Organizational Communication) at the School of Business Administration, South China University of Technology. His research focuses on computational advertising and advertising creativity. He has participated in several academic research projects and contributed to publications in related fields.

  • Jinhai Zhang, Wuhan Technology and Business University

    Professor Jinhai Zhang is Dean of the School of Literature and Law at Wuhan Technology and Business University and Chief Expert in Journalism and Communication. He formerly served as Professor and doctoral supervisor at the School of Journalism and Communication, Wuhan University; Director of the Media Development Research Center (a Ministry-of-Education Key Research Base in the Humanities and Social Sciences); and President of the China Advertising Education Association. Founder of the “Luojia School” of advertising studies, he is widely recognized as an influential scholar in China’s advertising academia and education. His honors include “Lifetime Contribution to the Development of Chinese Advertising Scholarship,” “Meritorious Figure in Chinese Advertising Education,” “Figure of Academic Contribution in Forty Years of Chinese Advertising,” and “Outstanding Achievement Figure in Forty Years of Chinese Advertising Education.” His research centers on advertising studies and media economics. He has led multiple projects funded by the National Social Science Fund of China, the Ministry of Education (general and major projects), and major projects of Hubei Province. He has authored more than twenty monographs and textbooks and published over one hundred high-level journal articles.

References

Akter, S., Bandara, R., Hani, U., Wamba, S.F., Foropon, C. & Papadopoulos, T. (2022) Algorithmic bias in machine learning–based marketing: A synthesis and research agenda. Journal of Business Research, 144, 201–216. doi:10.1016/j.jbusres.2022.01.083. DOI: https://doi.org/10.1016/j.jbusres.2022.01.083

Araujo, T., Copulsky, J.R., Hayes, J.L., Kim, S.J. & Srivastava, J. (2020) From purchasing exposure to fostering engagement: Brand–consumer experiences in the emerging computational advertising landscape. Journal of Advertising, 49(4), 428–445. doi:10.1080/00913367.2020.1795756. DOI: https://doi.org/10.1080/00913367.2020.1795756

Duan, C. & Cui, Y. (2024) Influence of computational advertising discipline development on sustainable innovation capability: An analysis of the chain mediating effects of organizational learning and knowledge sharing. Modern Communication (Journal of Communication University of China), 2024(3), 139–147.

Helberger, N., Huh, J., Milne, G., Strycharz, J. & Sundaram, H. (2020) Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising, 49(4), 377–393. DOI: https://doi.org/10.1080/00913367.2020.1811179

Huh, J. & Malthouse, E.C. (2020) Advancing computational advertising: Conceptualization of the field and future directions. Journal of Advertising, 49(4), 367–376. DOI: https://doi.org/10.1080/00913367.2020.1795759

Lissillour, R., Cui, Y., Guesmi, K., Chen, W. & Chen, Q. (2024) Value network and firm performance: the role of knowledge distance and environmental uncertainty. Journal of Knowledge Management, 28(1), 44–68. DOI: https://doi.org/10.1108/JKM-10-2022-0822

Thomas, V. & Liu-Thompkins, Y. (2024) Harnessing the strengths of computational advertising and experimental methods to enhance research design. Journal of Advertising, 53(5), 1–10. doi:10.1080/00913367.2024.2408002. DOI: https://doi.org/10.1080/00913367.2024.2408002

Wu, Z., Duan, C., Cui, Y. & Qin, R. (2023) Consumers’ attitudes toward low-carbon consumption based on a computational model: Evidence from China. Technological Forecasting and Social Change, 186, 122119. DOI: https://doi.org/10.1016/j.techfore.2022.122119

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Published

2025-11-08

How to Cite

Gao, X., & Zhang, J. . (2025). Theory, Transformation, Practice and Exploration — A Review of An Introduction to Computational Advertising. Management Research Quarterly, 2(2), 50-52. https://doi.org/10.63029/s4q7w409

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