JOURNAL ARTICLE

The Adoption of Blockchain Technology on Company's Internal Control System in Sales and Purchasing Cycle.

  • Published In: Journal of Emerging Technologies in Accounting, 2025, v. 22, n. 1. P. 65 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Lin, Yu-Cheng; Padliansyah, Roni; Wu, Pei-Pei 3 of 3

Abstract

This paper explores the use of blockchain technology to enhance internal control systems for fraud prevention within the sales and purchasing cycle. Despite existing internal controls, significant weaknesses persist in these systems, leading to issues such as poor performance, missing orders, underpricing, rebates, false charges, falsification of order information, late delivery, and order/performance shifting. Using the design science research approach (Hevner, March, Park, and Ram 2004), we propose a conceptual framework that allocates the verification, storage, and management of events to each authorized blockchain node, preventing tampering with verified data. By integrating blockchain's secure, traceable, and decentralized features with smart contracts, oracles, and the Internet of Things (IoT), our framework aims to automate workflows, track goods in real-time, and measure operational performance accurately. This approach enhances internal control systems, reduces audit workloads, and mitigates the risk of business fraud and misconduct. JEL Classifications: M42; M49. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Emerging Technologies in Accounting. 2025/03, Vol. 22, Issue 1, p65
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2025
  • ISSN:1554-1908
  • DOI:10.2308/JETA-2023-062
  • Accession Number:187394068
  • Copyright Statement:Copyright of Journal of Emerging Technologies in Accounting is the property of American Accounting Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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