Investigating the role of data-driven innovation and information quality on the adoption of blockchain technology on crowdfunding platforms

Abhishek Behl (), Brinda Sampat (), Vijay Pereira (), Nirma Sadamali Jayawardena () and Benjamin Laker ()
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Abhishek Behl: Management Development Institute
Brinda Sampat: NMIMS University
Vijay Pereira: NEOMA Business School
Nirma Sadamali Jayawardena: O P Jindal Global University
Benjamin Laker: University of Reading

Annals of Operations Research, 2024, vol. 333, issue 2, No 23, 1103-1132

Abstract: Abstract The purpose of this study is to investigate the role of data-driven innovation and information quality on the adoption of blockchain technology on crowdfunding platforms through adopting a mono method quantitativae approach. Micro-level theoretical perspectives have been less explored in studies of successful crowdfunding innovation than macro-level theoretical perspectives. Furthermore, crowdfunding platforms’ performance varies because of issues like trust, information asymmetry, and transparency of funds flow, among others. There is a solution to these issues in the form of Blockchain Technology (BCT). While BCT has been adopted and used by other businesses, its adoption and usefulness for crowdfunding platforms have not been studied. We investigate crowdfunding platform success using the “task-technology fit theory” and “resource-based view theory”. Authors collected primary level data from task owners of crowdfunding platforms to test the hypotheses. The proposed theoretical model is tested with a sample size of 314 business units, and the proposed hypotheses are tested using Warp PLS 7.0. We also control for the type of crowdfunding activities for our study. The study will help in understanding and improving the success of crowdfunding tasks on crowdfunding platforms. Additionally, it will contribute to TTF and RBV theory as well.

Keywords: Data driven innovation; Blockchain technology; Trust; Operational performance; Task technology fit theory; Resource bases view theory (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-023-05290-w

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