On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining

Cha, Shih-Chao; Wang, Hao; Tan, Zhiyuan; Joung, Yuh-Jzer; Tseng, Yen-Chung; Yeh, Kuo-Hui

Abstract

Intelligence mining is one of the most promising technologies for effectively extracting intelligence (and knowledge) to enhance the quality of decision-making. In Taiwan, the government curtails underground economic activities and facilitates tax management via ubiquitous e-invoice information processing and intelligence mining for B2C transactions with management realized via privacy-preserved and robust consumer carriers. In this paper, we study the concept of carriers, a medium that facilitates the transfer of an e-invoice from a business to a consumer in a B2C transaction. Implementations of carriers not only depend on the underlying hardware, software, and network infrastructures that support their services, but also on consumers willingness to use them. In this paper, we review Taiwans Second Generation E-invoicing System, which is designed to promote the use of e-invoices in the consumer sector, and identify four problems that require further attention. These problems are: (1) no e-invoice data for immediate review; (2) limited readability of carriers by POS (Point of Sales); (3) lack of seamless integration into purchase behaviors; and (4) carrier traceability. We then discuss possible solutions to overcome these concerns, in hope of offering some insight into future mobile commerce based on e-invoice carriers in the cloud computing era.

Citation

Cha, S.-C., Wang, H., Tan, Z., Joung, Y.-J., Tseng, Y.-C., & Yeh, K.-H. (2020). On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(5), 641-652. https://doi.org/10.1109/tetci.2019.2938547

• Journal Article Type: Article
• Acceptance Date: Aug 18, 2019
• Online Publication Date: Jun 22, 2020
• Publication Date: 2020-10
• Deposit Date: Oct 21, 2019
• Publicly Available Date: Oct 22, 2019
• Journal: IEEE Transactions on Emerging Topics in Computational Intelligence
• Print ISSN: 2471-285X
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 4
• Issue: 5
• Pages: 641-652
• DOI: https://doi.org/10.1109/tetci.2019.2938547
• Public URL: http://researchrepository.napier.ac.uk/Output/2242196