Strategic Transformation Through Data Governance: Leveraging Key Performance Indicators (KPIs) in the Airline Industry

SeyyedAbdolHojjat  MoghadasNian,Mohammad  Rajol,Zahra  HosseinZadehShirazi

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Strategic Transformation Through Data Governance: Leveraging Key Performance Indicators (KPIs) in the Airline Industry

S. MoghadasNian,

M. Rajol,

Z. HosseinZadehShirazi

2026-02-22

https://doi.org/10.24108/preprints-3114557

This study explores the critical role of Key Performance Indicators (KPIs) in enhancing data governance within the airline industry. The primary objective is to identify, analyze, and evaluate the impact of specific KPIs on data quality, security, regulatory compliance, and overall data governance. Employing a mixed-methods approach, the research integrates both qualitative and quantitative methodologies. Data was collected through semi-structured interviews with industry experts and detailed case studies of leading airlines. Quantitative data on KPIs was obtained from performance reports, regulatory filings, and industry databases. Statistical analysis and comparative case study analysis were used to evaluate the data. The findings reveal that KPIs such as Data Accuracy Rate, Data Completeness, Data Consistency, Data Timeliness, and Compliance with Data Governance Standards significantly enhance data governance practices. Case studies illustrate how airlines successfully implementing KPI-driven data governance frameworks have achieved improved operational efficiency, regulatory compliance, and customer satisfaction. The study underscores the importance of strategic KPI management in transforming data governance from a compliance-centric function to a value-driving component of airline strategy. Recommendations for industry practitioners include adopting comprehensive data governance frameworks, investing in advanced analytical tools, establishing dedicated data governance teams, and promoting continuous training and awareness. Future research directions suggest exploring innovative data governance practices, integrating emerging technologies, and conducting longitudinal studies to assess the long-term impact of KPIs on data governance.

Ссылка для цитирования:

MoghadasNian S., Rajol M., HosseinZadehShirazi Z. 2026. Strategic Transformation Through Data Governance: Leveraging Key Performance Indicators (KPIs) in the Airline Industry. PREPRINTS.RU. https://doi.org/10.24108/preprints-3114557

Список литературы

1. Alhassan, I., Sammon, D., & Daly, M. (2016). Data governance activities: An analysis of the literature. Journal of Decision Systems, 25(1), 64-75. doi: 10.1080/12460125.2016.1187397

2. Alhassan, I., Sammon, D., & Daly, M. (2018). Data governance activities: A comparison between scientific and practice-oriented literature. Journal of Enterprise Information Management, 31(2), 338-356. doi: 10.1108/JEIM-01-2017-0007

3. Brous, P., Janssen, M., & Vilminko-Heikkinen, R. (2016). Coordinating decision-making in data management activities: A systematic review of data governance principles. In Proceedings of the International Conference on Electronic Government (pp. 63-73). doi: 10.1007/978-3-319-44421-5_9

4. Dahlberg, T., & Nokkala, T. (2015). A framework for the corporate governance of data – theoretical background and empirical evidence. Business, Management and Education, 13(2), 254-275. doi: 10.3846/BME.2015.254

5. Dingre, S. (2023). Exploration of Data Governance Frameworks, Roles, and Metrics for Success. Journal of Artificial Intelligence & Cloud Computing, 5(2), 195-210. doi: 10.47363/jaicc/2023(2)195

6. Kezar, A. J., & Eckel, P. D. (2004). Meeting today's governance challenges: A synthesis of the literature and examination of a future agenda for scholarship. Journal of Higher Education, 75(4), 371-399. doi: 10.1353/jhe.2004.0022

7. Khatri, V., & Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148-152. doi: 10.1145/1629175.1629210

8. Liaw, S. T., Pearce, C., Liyanage, H., Liaw, G. S. S., & de Lusignan, S. (2014). An integrated organisation-wide data quality management and information governance framework: Theoretical underpinnings. Informatics in Primary Care, 21(4), 123-135. doi: 10.14236/jhi.v21i4.87

9. Lillie, T., & Eybers, S. (2018). Identifying the constructs and agile capabilities of data governance and data management: A review of the literature. In Proceedings of IDIA (pp. 8-19). doi: 10.1007/978-3-030-11235-6_20

10. Masayna, V., Koronios, A., & Gao, J. (2009). A framework for the development of the business case for the introduction of data quality program linked to corporate KPIs & governance. In Proceedings of the Fourth International Conference on Cooperation and Promotion of Information Resources in Science and Technology (pp. 56-63). doi: 10.1109/COINFO.2009.56

11. McCaig, M., & Rezania, D. (2021). A scoping review on data governance. Journal of Information Systems Education, 32(1), 1-12. doi: 10.2139/ssrn.3882450

12. Moghadasnian, S. (2022). Flight to excellence: A comprehensive guide to key performance indicators in the airline industry: Unlocking success through data-driven strategies and performance metrics. Aviation and Tourism Research and Innovation Center (ATRIC). Digital Publication. Tehran, Iran & Milan, Italy.

13. Moghadasnian, S. (2023). Strategica Aeronautica: Mastering KPI-driven leadership across the airline and tourism ecosystem: A comprehensive guide for executives: From analytic hierarchy process to zero-based budgeting, navigate the full spectrum of strategic decision-making metrics. Aviation and Tourism Research and Innovation Center (ATRIC). Digital Publication. Tehran, Iran & Milan, Italy.

14. Moktadir, M. A., Dwivedi, A., Rahman, A., Chiappetta Jabbour, C. J., Paul, S., Sultana, R., & Madaan, J. (2020). An investigation of key performance indicators for operational excellence towards sustainability in the leather products industry. Business Strategy and the Environment, 29(5), 2345-2359. doi: 10.1002/bse.2575

15. Nielsen, O. B. (2017). A comprehensive review of data governance literature. Journal of Decision Systems, 26(1), 85-102. doi: 10.1080/12460125.2016.1187397

16. Parra Riveros, H., Ospina López, D. Y., Amaya Rueda, I. Y., & Zambrano, L. (2023). Systematic review of the literature on data governance in healthcare institutions. In Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 1-12). doi: 10.46254/sa04.20230030

17. Pérez-Álvarez, J. M., Maté, A., Gómez-López, M. T., & Trujillo, J. (2018). Tactical business-process-decision support based on KPIs monitoring and validation. Computers in Industry, 100(1), 1-12. doi: 10.1016/j.compind.2018.08.001

18. Sharma, V., Mousavi, E., Gajjar, D., Madathil, K., Smith, C., & Matos, N. (2022). Regulatory framework around data governance and external benchmarking. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, 14(3), 1-12. doi: 10.1061/(ASCE)LA.1943-4170.0000526

19. Thongkruer, P., & Wanarat, S. (2020). Logistics service quality: Where we are and where we go in the context of airline industry. Management Research Review, 43(2), 139-159. doi: 10.1108/mrr-12-2019-0544

20. Tian, H., Presa-Reyes, M., Tao, Y., Wang, T., Pouyanfar, S., Miguel, A., Luis, S., Shyu, M. L., Chen, S. C., & Iyengar, S. S. (2021). Data analytics for air travel data: A survey and new perspectives. ACM Computing Surveys, 53(6), 1-36. doi: 10.1145/3469028

21. Weber, K., Otto, B., & Österle, H. (2009). One size does not fit all—a contingency approach to data governance. Journal of Data and Information Quality, 1(1), 1-27. doi: 10.1145/1515693.1515696

22. Wu, Y. (2023). Data governance and human rights: An algorithm discrimination literature review and bibliometric analysis. Journal of Humanities Arts and Social Science, 7(1), 18-33. doi: 10.26855/jhass.2023.01.018

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