Internet of things readiness model for higher learning institutions in Kenya

Abstract

The Internet of Things (IoT) has been an effective tool in enhancing access to information in learning environments to assist Higher Learning Institutions (HLIs) in improving the quality of education. There have been many successful implementations of IoT in educational sectors in developed countries. However, an exploration of previous studies on the usage of IoT shows that only a few studies have investigated IoT readiness within developing countries. The increase in the number of students, lack of enough physical infrastructure, lack of equity, and low funding has led to poor quality of education in Kenya. Therefore, the objective of this research is to analyse factors influencing IoT readiness and to propose a readiness model for Higher Learning Institutions in Kenya. The model is developed through the Softwareas- a-Service (SaaS), and Tripod Readiness and Technology Readiness Index (TRI) models. Thirteen hypotheses are employed for the proposed model to test the impact of the readiness factors on the implementation of IoT by HLIs. A survey is conducted to examine the influence of the identified readiness factors on the implementation of IoT. A total of 181 respondents from three top Information and Communications Technology (ICT) learning institutions participated in the study. The collected data is analysed using the Partial Least Squares (PLS) method based on Structural Equation Modelling (SEM) and the Importance Performance Matrix (IPMA) is used to extract critical IoT readiness factors. The outcomes show that Relative Advantage, Simplicity, Compatibility, Top Management Support, IT Infrastructure, Competitor Pressure, Optimism and Insecurity had an impact on the implementation of IoT by HLIs. However, Experienceability, Partner Pressure, and Discomfort had no impact on IoT readiness. The outcome of this research shows that TRI influences technological, organizational, and environmental readiness on IoT readiness and attitude towards IoT. Moreover, both organizational and people factors are significant for IoT readiness in HLIs. The study offers an instrument and an IoT Readiness Model for implementing IoT in Kenyan HLIs.