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ACOMS+ 및 학술지 리포지터리 설명회

  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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  • P-ISSN1738-3110
  • E-ISSN2093-7717
  • SCOPUS, ESCI

Impact of Big Data Analytics on Indian E-Tailing from SCM to TCS

Impact of Big Data Analytics on Indian E-Tailing from SCM to TCS

The Journal of Distribution Science(JDS) / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2024, v.22 no.8, pp.65-76
https://doi.org/10.15722/JDS.22.08.202408.65
BM Avinash
GM Divakar
Mouly Potluri Rajasekhara
B Megha

Abstract

Purpose: The study aims to recognize the relationship between big data analytics capabilities, big data analytics process, and perceived business performance from supply chain management to total customer satisfaction. Research design, data and methodology: The study followed a quantitative approach with a descriptive design. The data was collected from leading e-commerce companies in India using a structured questionnaire, and the data was coded and decoded using MS Excel, SPSS, and R language. It was further tested using Cronbach's alpha, KMO, and Bartlett's test for reliability and internal consistency. Results: The results showed that the big data analytics process acts as a robust mediator between big data analytics capabilities and perceived business performance. The 'direct, indirect and total effect of the model' and 'PLS-SEM model' showed that the big data analytics process directly impacts business performance. Conclusions: A complete indirect relationship exists between big data analytics capabilities and perceived business performance through the big data analytics process. The research contributesto e-commerce companies' understanding of the importance of big data analytics capabilities and processes.

keywords
Big Data Analytics, E-tailing, Big Data Analytics Capabilities, Big Data Analytics Process, Business Performance, Supply Chain Management (SCM), Total Customer Satisfaction (TCS)

The Journal of Distribution Science(JDS)