Social signals and green price tolerance: experimental evidence across product categories

Purpose This study examines how social signals shape consumers' Green Price Tolerance (GPT), defined as the switching threshold at which consumers stop choosing green products as price premiums increase, and whether effects vary across product categories. Design/methodology/approach A controlled behavioral experiment with a mixed between–within subjects design involved 360 participants and 1,800 observations across five product categories and four social signal conditions: no signal (control), peer signal, influencer/KOL signal, and rating signal. Data were analyzed using linear mixed-effects models in Stata 17. Findings Social signals significantly increased GPT, with rating signal producing the strongest effect, followed by influencer/KOL signal and peer signal. GPT also varied across product categories, indicating that category context shapes switching thresholds. Originality/value This study introduces Green Price Tolerance (GPT) as a behavioral construct that complements willingness to pay (WTP) by capturing switching thresholds rather than valuation outcomes. The findings extend social signaling research from preference formation to choice switching and provide experimental evidence on green choice behavior in an emerging market.