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Information Systems and e-Business Management

, Volume 17, Issue 2–4, pp 285–318 | Cite as

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

  • Abhishek Behl
  • Pankaj Dutta
  • Stefan Lessmann
  • Yogesh K. DwivediEmail author
  • Samarjit Kar
Original Article
  • 133 Downloads

Abstract

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future.

Keywords

Big data analytics Interpretive structural modelling Fuzzy MICMAC Analytical network process E-commerce Start-ups 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Abhishek Behl
    • 1
  • Pankaj Dutta
    • 1
  • Stefan Lessmann
    • 2
  • Yogesh K. Dwivedi
    • 3
    Email author
  • Samarjit Kar
    • 4
  1. 1.Shailesh J Mehta School of ManagementIndian Institute of Technology BombayPowai, MumbaiIndia
  2. 2.Chair of Information Systems, School of Business and EconomicsHumboldt-Universität zu BerlinBerlinGermany
  3. 3.School of ManagementSwansea UniversitySwanseaUK
  4. 4.Department of MathematicsNational Institute of Technology DurgapurDurgapurIndia

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