Big Data and Citizen Feedback Analytics in Monitoring Public Service Performance

This paper focused on the impacts of big data and citizen feedback analytics on monitoring, evaluation, and the performance of the public services in nairobi county, kenya. The study aims and objectives were directed by the technology acceptance model (tam) and the degree to which it was intended to: (i) investigate the impact of big data analytics on the evidence-based decision-making; (ii) determine the impact of citizen feedback analytics on responsiveness and transparency; (iii) establish the role played by digital data integration in enhancing the overall performance; and (iv) the combined effects of analytics. The research had an important impact on the development of the field of digital governance and data-driven accountability in developing situations. The background stated the increasing use of digital governance tools in kenya but continued to point out frequent problems with integrating data, the use of feedback, and citizen trust. The problem statement highlighted that despite the investments in digital systems, public institutions are not able to convert analytics into practical performance insights. The descriptive and correlation design was embraced, which entailed 100 ict, m&e, administrative, and citizen respondents. The data were collected and analyzed using structured questionnaires and interviews and analyzed using spss (v.28) and nvivo (v.14). The theoretical model of the perceived usefulness and ease of use in relation to technology adoption was supported by the empirical literature in kenya, africa, and international literature. The results showed that both big data (r = 0.781) and analytics citizen feedback (r = 0.744) had a significant positive impact on service performance. The joint predictors had a total model explaining performance variance of 65.2 (r2 = 0.652). It was discussed that institutional readiness, digital literacy and governance culture are the factors of adoption. The paper has come up with the conclusion that analytics can improve transparency, responsiveness and efficiency. It suggested making digital analytics institutionalized in m&e policy, enhancing capacity building, enforcing data privacy, and increase citizen engagement portals as a means of making governance participatory.

big data, citizen feedback, monitoring and evaluation, public service performance, technology acceptance model, digital governance, kenya, accountability, transparency, data analytics.

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