Blockchain transparency in reducing second-hand luxury shopping uncertainty and the role of price consciousness
Source abstract
Abstract
Abstract This study explores consumer behavior and decision-making in the context of blockchain technology (BT) adoption within the second-hand luxury market. Specifically, it investigates how BT can reduce uncertainty and enhance transparency in second-hand luxury transactions based on a mental accounting theory approach. A partial least squares structural equation modeling analysis (N = 511) was conducted, focusing on consumers’ perceived quality of traceable information obtained through BT (i.e., product diagnosticity, informativeness, and trustworthiness) and their perceived risks in second-hand luxury online shopping (i.e., financial risk, social risk, time risk, contamination risk, performance risk). The findings confirm that the perceived quality of traceable information enhances blockchain transparency, reducing uncertainty in online second-hand luxury shopping. This leads consumers to perceive BT-enabled platforms as valuable, increasing their intention to adopt them. The study also examines the moderating effect of price consciousness on consumer perceptions of BT and decision-making. The results of the multi-group analysis confirm that consumers with lower price consciousness are more influenced by the diagnosticity provided by BT in terms of product transparency, while for consumers with higher price consciousness, trustworthiness emerges as a more significant factor. This research offers insights into the application of blockchain technology in the second-hand luxury market, particularly in enhancing transparency and consumer trust. It emphasizes the importance of retail strategies that communicate the advantages of BT and alleviate consumer risks associated with the online second-hand luxury market while recognizing consumers' varying levels of price consciousness.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Consumer Retail Behavior Studies · Technology Adoption and User Behaviour · Impact of AI and Big Data on Business and Society
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (45)
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