Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/20050
Title: Investigating the impact of data and analytics strategy in performance of private firms in Sri Lanka
Authors: Wijayasiiriwardane, K. L.
Rajapakse, R. A. C. P.
Keywords: Big data
data and analytics strategy
firm performance
Issue Date: 2018
Publisher: Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka
Citation: Wijayasiiriwardane, K. L. and Rajapakse, R. A. C. P. (2018). Investigating the impact of data and analytics strategy in performance of private firms in Sri Lanka. Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka. p178.
Abstract: Big Data Analytics (BDA) is considered as a tool to explore new opportunities for an organization to be competitive in dynamic markets. It represents a set of technologies and algorithms to recognize important patterns such as new market opportunities and business propositions as well as to make effective predictions on market behaviors. Therefore, every organization put efforts to use their data, both structured and unstructured, strategically to be competitive. In other words, the performance of modern day firms is expected to have a close tie with the data and analytics strategy being used. However, there are no adequate research studies conducted to systematically evaluate the impact of the data and analytics strategy on the firm performance. In this research we intend to fill this research gap by systematically surveying the elements of the data and analytics strategies of key industry players in Sri Lanka and attempting to identify their relationships with the performance of respective companies. The performance will be evaluate under financial performance, customer retention and reach, growth in sales, growth in profit, return on investment, market performance etc. The research is designed as follows. We first did a comprehensive study on the existing literature about data and analytic strategy and, based on the resource-based theory and dynamic capability view, identified three main dimensions namely Big data analytics management capability, big data analytics talent capability, big data analytics technical capability and eleven sub-dimensions as capabilities to acquire for enhanced performance through data and analytics strategies. This theoretical model is planned to be validated through empirical data. Accordingly, we plan to collect data from managerial level users of a selected group of financial companies who are currently potential beneficiaries of big data capabilities through a questionnaire and subsequent open-ended interviews. The results will be then analyzed with respect to each sub-dimension to derive conclusions about the overall relationship between the data and analytics strategy and firm performance.
URI: http://repository.kln.ac.lk/handle/123456789/20050
Appears in Collections:IRSPAS 2018

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