Who sells it best? How streamer personality and product type shape consumer purchase intentions for near-expiry products
Biyu Guan et al.
Abstract
Purpose Although there is potential to reduce waste and recover value for companies, consumer demand for near-expiry products (NEPs) remains low, even with initiatives like price discounts. However, little attention has been given to the role of emerging livestreaming. Based on risk perception theory, this study aims to examine how streamer personality and product type together influence consumer purchase intentions for NEPs. Design/methodology/approach Three experiments were conducted across different cultural contexts. Study 1 (N = 240, China) examined the interaction between streamer personality and product type on purchase intention for NEPs. Study 2A (N = 220, Britain) further investigated the mediating role of risk perception. Study 2B (N = 334, America) expanded on Study 2A by including a regular-product condition, thereby assessing whether the observed effects are specific to NEPs. Findings Results indicate that competent streamers heighten risk perception when promoting experience-type NEPs compared to search-type ones, thereby decreasing purchase intentions. Conversely, warm streamers lessen this risk gap, making experience-type NEPs more attractive to consumers. Practical implications Livestreaming can effectively promote NEPs when companies align the streamer’s personality with the product type, lowering risk perception, increasing purchase intent and supporting sustainable consumption. Originality/value This study advances research on NEPs by highlighting livestream commerce as a new driver. It develops a fit-based perspective, demonstrating that the match between streamer personality and product type acts as a diagnostic cue that influences risk perception, thereby expanding risk perception theory.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.