A Systems Dynamics Model for Mobile Industry Governance in the Context of the Kenyan Vision 2030

A Systems Dynamics Model for Mobile Industry Governance in the Context of the Kenyan Vision 2030

Amos O. Omamo (Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya), Anthony J. Rodriguez (Jaramogi Oginga Odinga University of Science & Technology, Bondo, Kenya) and Joseph Wafula Muliaro (Jomo Kenyatta University of Science and Technology, Nairobi, Kenya)
Copyright: © 2018 |Pages: 20
DOI: 10.4018/IJSDA.2018040105

Abstract

This article describes how Kenya has emerged in recent times as one of the fastest-growing telecom markets in the world. This article presents a system dynamics-integrated model of the Kenyan telecommunication sector—mobile telephony—that has been developed and calibrated to demonstrate the various interactions among system variables and the resultant impact on economic growth through simulations. The simulation result proves that the regulator, the Communications Authority of Kenya, should be the key entity to be governed. This modeling process started by delineating the mobile industry's system boundary. The interactions amongst the entities were then described. Based on a historical data analysis and the system archetypes identified, a system dynamics (SD) model was developed. The research tested the results of the model in a combination of scenarios, apart from several underlying feedback effects, it was found that mobile telephony and growth in gross domestic product (GDP) had strong positive correlation.
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Introduction

This study investigates mobile phone usage output on economic growth in Kenya. Inconsistent economic growth based on mobile service activity is a big concern in the developing as well as in the developed world. The econometric approach follows previous work by (Adrianaivo and Kpodar, 2011) and (Lee et al., 2009) on the impact of mobile penetration on GDP per capita growth. In Kenya, mobile telecommunication industry has witnessed a tremendous growth over the last few years, by June 2014 the total number of mobile subscriptions was recorded as 37.8 million up from 36.1 million (CAK, 2015). However, there is a wide variation in mobile diffusion as well as GDP growth across various counties in Kenya, raising questions of socio-economic disparities and how technology diffusion may help in the convergence of growth process among various counties. (Mindila et al., 2014), presents a systematic strategy of employing Information and Communication Technologies (ICTs) as interventions in the structural underpinnings of knowledge identification and management and models them within the system dynamic model. Empirical studies have found several factors such as per capita income, income inequality, population density, the age profile of the population, competition and regulatory structure to have a positive impact on mobile penetration (Yamakawa et al., 2013; Chakravarty, 2007). The relation between inequality and mobile penetration has been found to be mixed. In some studies, mobile penetration, was found to be negatively related to income inequality; whereas, it is positively related to inequality in the early stages of diffusion (Roeller & Waverman, 2001; Hytennin & Toivanen, 2011). In the developing country context, mobile phones serve dual purposes: one, as a consumption good for the rich and two, as a production good for the poor. Case studies from the Africa and Asia have shown the usefulness of mobiles as a production good (Jensen et al., 2007; Aker et al., 2008; Muto et al., 2008). For this reason, income inequality may influence the spread of mobile penetration in the early stages. Embracing the digital revolution requires good ICT governance. As highlighted by (Nair et al., 2005), for ICT to contribute to economic growth, a conducive legislative environment should be in place to support communication, commerce and trade in the digital medium. Although the impact of economic and demographic factors on mobile penetration has been established, there is not much clarity on the relationship between mobile phone penetration, economic growth and the extent to which this leads to convergence of growth process. The mobile industry of Kenya is, therefore, an exemplifying case for the phenomenon.

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