Barriers of big data analytics for smart cities development: a context of emerging economies
Shahbaz Khan
Abstract
Smart cities use Big Data Analytics (BDA) for efficient and effective utilisation of resources and the adoption of big data analytics faces several barriers. Therefore, the main purpose of this research is to investigate the key barriers towards the adoption of BDA in smart cities development. To fulfil this objective, initially, 13 barriers of BDA adoption is identified and then prioritise using Best Worst Method (BWM). The finding shows that data complexity, framework for BDA adoption, lack of technologies for BDA are the important barriers that hinder the incorporation of BDA in smart city development. The main contribution of this study is that it proposes a framework for the evaluation of the BDA adoption barrier related to smart city development. The proposed framework can be helpful for policy and decision-makers to analyse the barriers of BDA adoption in smart city design and development. This study is helpful in undertaking these barriers in an optimised manner for the accelerated development of smart cities.