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Paper Type
Complete
Description
The goal of the current paper is to examine the impact of blockchain technology adoption on an organization’s business process innovation. Blockchain technology has been widely acknowledged for its usefulness in securing business transactions and benefits from decentralization and transparency. While blockchain implementation has notable advantages in a business process, such outcomes also rely on the nature of the business. Our research employed two theoretical concepts to measure blockchain adoption and its impact on an organization’s business process innovation: technological, organizational, and environmental (TOE) framework and task-technology fit. We specified hypotheses and tested them using survey responses. A total of 419 responses were collected and we analyzed them using partial least squares (PLS). Detailed results and discussions are addressed.
Paper Number
1734
Recommended Citation
Shin, Soo Il; Negash, Solomon; and Saeed, Khawaja, "Exploring the Impact of Blockchain and Distributed Ledger Technology Adoption on Business Process Innovation" (2023). AMCIS 2023 Proceedings. 37.
https://aisel.aisnet.org/amcis2023/sig_adit/sig_adit/37
Exploring the Impact of Blockchain and Distributed Ledger Technology Adoption on Business Process Innovation
The goal of the current paper is to examine the impact of blockchain technology adoption on an organization’s business process innovation. Blockchain technology has been widely acknowledged for its usefulness in securing business transactions and benefits from decentralization and transparency. While blockchain implementation has notable advantages in a business process, such outcomes also rely on the nature of the business. Our research employed two theoretical concepts to measure blockchain adoption and its impact on an organization’s business process innovation: technological, organizational, and environmental (TOE) framework and task-technology fit. We specified hypotheses and tested them using survey responses. A total of 419 responses were collected and we analyzed them using partial least squares (PLS). Detailed results and discussions are addressed.
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