THE INFLUENCE OF BIG DATA ANALYTICS ON ORGANISATIONAL PERFORMANCE: A COMPARATIVE STUDY OF THE TECHNICAL UNIVERSITY OF KENYA AND STRATHMORE UNIVERSITY

Abstract

ABSTRACT This study investigated the influence of big data analytics on organisational performance of academic institutions in Kenya. The Technical University of Kenya (TUK) and Strathmore University (SU) provided the context for the study. They provided insights into the differences and/or similarities between the influence of big data analytics on organisational performance from the perspectives of private and public universities in Kenya. Previous studies on big data analytics have primarily focused on theorisation and formulation of expectations with positive aspects of big data analytics. However, within current literature the influence of big data analytics on organisational performance has received less attention. The specific objectives of the study were to: establish the characteristics of big data produced by the TUK and SU; investigate the techniques and tools used in big data analytics in the TUK and SU; examine the relationship between big data analytics and organisational performance of the TUK and SU; and propose strategies for enhancing the positive influence of big data analytics on organisational performance of TUK and SU. The study adopted convergent parallel mixed methods research design. Quantitative and qualitative data was collected using questionnaires and key informant interviews. The target population for the study was 22,050 respondents consisting of clients (students) as well as ICT staff, directors and managers from both TUK and SU. Information-oriented purposive sampling was used to select information-rich subjects. This gave TUK a sample size of 580 and 114 for SU. Quantitative data was analysed using Statistical Package for Social Sciences (SPSS) while the qualitative data was analysed using thematic analysis. This study established that five of the variables of organisational performance have a positive relationship with big data analytics in both institutions while two had a negative relationship in TUK. The variables with positive relationship were: innovativeness, creativeness, effectiveness, productiveness and efficiency. Whereas competiveness and profitability had a negative relationship in TUK, the same had a positive correlation in SU. The findings confirm that big data analytics support academic organisations to perform their functions better. The study recommends that academic institutions should develop strategies and policies on big data analytics to guide them on how to maximise its benefits. The findings can be used to enhance organisational performance of academic institutions by facilitating effective decision making as well as strategy formulation and execution. Keywords: big data analytics, organisational performance, academic institutions, Technical University of Kenya, Strathmore University, Kenya.