Grant, E. (2021) Big Data-Driven Innovation, Deep Learning-Assisted Smart Process Planning, and Product Decision-Making Information Systems in Sustainable Industry 4.0. Economics, Management, and Financial Markets, 16, 9-19. https://doi.org/10.22381/emfm16120211

has been cited by the following article:

• TITLE: Big Data Characteristics and Innovation Performance in Ghanaian Manufacturing Firms: The Role of the Big Data Team?

  AUTHORS: Samuel Kofi Otchere, Ennin Bernice Nyamewaa, Frank Hammond

  KEYWORDS: Big Data, Big Team, Innovation, Performance, Ghana

  JOURNAL NAME: Open Access Library Journal, Vol.9 No.2, February 24, 2022

  ABSTRACT: The study scrutinizes the connection between the big data characteristics and innovation performance in selected manufacturing firms in Ghana and the mediating role of the big data team in this relationship. This provides a new perspective to the ongoing debate on the big data innovation nexus globally. Using data from 43 accidentally selected manufacturing firms from Greater Accra in a structural equation model, the study confirms that big data characteristics positively influence innovation performance in manufacturing firms. However, velocity and volume are negatively associated with innovation performance in these firms. Finally, the sophistication and skill levels of the big data team positively mediate the connection amid big data characteristics and innovation performance. Therefore, management should prioritize the employment of a highly skilled big data team to benefit from all the characteristics of big data. Further, firms should consider the long-run big data analytics benefits over the initial cost of investment.