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. Dwivedi () and Samarjit Kar
Additional contact information
Abhishek Behl: Indian Institute of Technology Bombay
Pankaj Dutta: Indian Institute of Technology Bombay
Stefan Lessmann: Humboldt-Universität zu Berlin
Yogesh K. Dwivedi: Swansea University
Samarjit Kar: National Institute of Technology Durgapur

Information Systems and e-Business Management, 2019, vol. 17, issue 2, No 4, 285-318

Abstract: 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 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://link.springer.com/10.1007/s10257-019-00452-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infsem:v:17:y:2019:i:2:d:10.1007_s10257-019-00452-5

Ordering information: This journal article can be ordered from
http://www.springer. ... ystems/journal/10257

DOI: 10.1007/s10257-019-00452-5

Access Statistics for this article

Information Systems and e-Business Management is currently edited by Jörg Becker and Michael J. Shaw

More articles in Information Systems and e-Business Management from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().