An Empirical Examination of the Factors of Big Data Analytics Implementation in Supply Chain Management and Logistics

Numerous companies have effectively exploited Big Data Analytics (BDA) potential to enhance their effectiveness in the Big Data period. Given that big data application in logistics and supply chain management (SCM) is nevertheless in its early stages, assessments of BDA could differ from various viewpoints, producing certain difficulties in comprehending the significance and potential of big data. Based on past research on BDA and SCM, this work examines the factors that influence organizations' willingness to implement BDA in their everyday activities. This research divides potential elements into 4 groups: technical, firm, ecological, and supply chain issues. A framework consisting of direct factors like technical, firm, and mediators was presented based on the technology diffusion hypothesis. The experimental findings demonstrated that anticipated advantages and high-level management assistance might have a considerable impact on intended adoption. Furthermore, ecological variables like competitive adoption, administration legislation, and supply chain connection can greatly alter the direct connections between influencing causes and intended adoption.

I. Introduction

The rapid advancement of information technology has altered the competitive landscape in numerous businesses. Big data, which is defined by size, diversity, speed, and price, is a key component of numerous technological breakthroughs [1]. With the advancement of the big data era, big data analytics (BDA) has received adequate interest from scientists and professionals, who have realized the significant business potential big data may offer to a company. BDA is divided into 2 components: business analysis and big data [2]. The first type offers the details basis for BDA, whilst the latter relates to organizations' capability to employ data to acquire business knowledge. Several research studies have been conducted to study the process by which companies might employ BDA to enhance company effectiveness [3]. In practice, businesses have adopted BDA as a valuable instrument for precise advertising, predicting customer action, and managing user-generated materials.