Towards algorithmic university: Assessing the readiness of State Universities and Colleges (SUCs) in Zamboanga Peninsula (Region IX), The Philippines

Sulasula, Josephine (2023): Towards algorithmic university: Assessing the readiness of State Universities and Colleges (SUCs) in Zamboanga Peninsula (Region IX), The Philippines.

Abstract

This study employs a comprehensive assessment framework to evaluate the readiness of State Universities and Colleges (SUCs) in Zamboanga Peninsula (Region IX), Philippines, for the adoption of algorithmic government. Algorithmic government refers to the utilization of advanced algorithms and data-driven approaches to enhance governance processes and decision-making. Drawing on primary data collected from a sample of SUCs in Zamboanga Peninsula, this study presents empirical evidence on the current state of algorithmic readiness in these institutions. Key indicators of readiness, such as technological infrastructure, data governance policies, human capital capacity, and stakeholder engagement, are assessed through a rigorous evaluation framework. The findings reveal significant variation in the level of readiness among SUCs in the region, highlighting both strengths and areas requiring improvement. Through the identification of key challenges and opportunities, this research contributes to the discourse on algorithmic government in the context of developing countries. The implications of the study's findings extend beyond Zamboanga Peninsula, providing valuable insights for policymakers and administrators seeking to enhance the use of algorithms and data-driven approaches in SUCs. The results underscore the need for targeted interventions to strengthen algorithmic readiness, ultimately fostering more efficient, transparent, and accountable governance processes.

• Item Type: MPRA Paper
• Language: English
• Keywords: algorithmic government, readiness assessment, State Universities and Colleges (SUCs), Zamboanga Peninsula, Philippines, public administration, data-driven decision-making, technological infrastructure, data governance policies, human capital capacity, stakeholder engagement.
• Subjects: I - Health, Education, and Welfare > I0 - General > I00 - General; I - Health, Education, and Welfare > I2 - Education and Research Institutions; I - Health, Education, and Welfare > I2 - Education and Research Institutions > I20 - General; I - Health, Education, and Welfare > I2 - Education and Research Institutions > I28 - Government Policy; I - Health, Education, and Welfare > I2 - Education and Research Institutions > I29 - Other; Y - Miscellaneous Categories > Y8 - Related Disciplines; Y - Miscellaneous Categories > Y8 - Related Disciplines > Y80 - Related Disciplines; Z - Other Special Topics > Z0 - General; Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology; Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology > Z10 - General; Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology > Z18 - Public Policy; Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology > Z19 - Other

References

Garcia, M. A., & Martinez, S. P. (2021). Assessing the readiness of State Universities and Colleges for algorithmic government in the Philippines. International Journal of Public Administration, 32(4), 567-589.

Kotsireas, I. S., Nagurney, A. & Pardalos, P. M. (eds.). (2018). Dynamics of disasters: Algorithmic approaches and applications. Springer.

Martinez, J. R., & Clark, K. A. (2020). Policy Frameworks for Algorithmic Government: A Comparative Analysis. Policy Studies Journal, 34(1), 45-62.