Trust model to increase purchase intent among e-commerce consumers

• Main Authors: Abbass, S. M., Osman, S. E. F.
• Format: Article
• Published: Asian Research Publishing Network 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/73719/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962530361&partnerID=40&md5=51411ee74894a7eb506aca32e7b01b7c

This paper draws a comparison between proposed trust model and other online trust models, with special emphasis on eBay, as one of the best trusted sites in this field conducted by comparisons with similar sites in this paper, and it has been identified strengths and weaknesses that exist in the eBay site and a solutions for those problems has been proposed. Proposed model depends on a secured database by assurance key (AK), technically known as the AK-DB, which contains a unique number for each consumer can not possess other, and designed AK generation and verification system (AKGVS). The proposed AKs are intended to replace credit card numbers, as a tool for verification of consumer identity when conducting electronic transactions. After that capture a picture of the face of the consumer using a digital camera is stored digital image in the database (Image-DB) by his/her AK and then compared this data in a trusted third party (TTP) database equipped with technology Face Recognition (FR), where is verified by online verification (OV) system. After verifying the customer's AK and image, it is compared that data with the blacklist (BL) that have all of his/her data remnants precedent set by the TTP to make sure that the consumer has no previous offenses and then allow or not to allow him/ to practice e-commerce through the website. When allowed to practice E-Commerce in e-fulfillment of the terms of trade becomes (seller/buyer) to know each other, which, in turn, leads to increase the trust among them, and the formation of a secure e-community. Were generated AK system test and compare the results with the system used in the generation of credit cards results then were analyzed this data using the ANOVA statistical analysis to identify the results, the results proved that proposed model has made the best of these credit cards results, There is a significant difference and statistically significant (Sig. 0.000), then the proposed model assessing the same method adopted in the evaluation eBay model. Finally, proposed new e-payment mothed more secure and easy such as (Hassa service) or use of social networks such as (Twitter) in financial transactions.