Effect of Big Data Analytics on Performance and Consumer Loyalty of Manufacturing Industries: An Empirical Research

Abstract

Big data has, as of late been perceived as one of the most significant domains of upcoming innovation. It has been fascinated numerous enterprises, since it can possibly explore organizations with high market worth. The paper investigates the types of market worth that organizations can make from big data analytics (BDA), the immediate effects it has on the economical performance of an industry, and the impacts of retail performance and consumer loyalty. According to the hypothesis upon resource-based view, investigation exhibits that the market value accomplished from interests in BDA prompts the interest as far as the economical performance (EP) of an industry. The survey is composed of two segments. The first segment, which was replied by all the industries, estimated the nearness or absence of BDA arrangements. We segregated the replies to this segment, and if the responders acknowledged certifiably, they were then approached to involve in the next segment of the poll. Out of the 300 finished questionnaires, 146 of the surveys were discovered appropriate to analyze our model, when our segregating questions in the first segment of the survey had been executed. The outcomes offer proof of the presence of a consumer loyalty (CL) intervention impact and of the absence of a retail performance (RP) impact. Hypothetical and pragmatic ramifications are conferred towards the last part of paper. BDA arrangements should be designed comprehensively to produce operational, organizational, structural and informational value. The outcomes of this research will assist in improving logical information at the junction of innovation and the board sciences. This study has some limitations that open up interesting opportunities for future research. First, this study has had a cross-sectional research design, in which all the measurement items were collected at the same point of time. A longitudinal study could extend this research by capturing the dynamics of the business value of big data analytics arrangements on different industry performances. Second, this research has employed one data collection method. Objective data from multiple sources could be used to further verify the proposed research model. This study has extended relevant theories in big data analytics arrangements by framing, in an original combination, four dimensions of the market worth of big data analytics arrangements on one outcome construct, that is, economical performance and the mediation variable of consumer loyalty.