The computer does not always do it better! The effect of computer-automated reward calculations on consumer satisfaction with digital incentives for low-carbon behavior

Digital incentive tools encourage participants by recording and rewarding their daily low-carbon behavior on digital platforms, ultimately fostering a low-carbon lifestyle. This research explores the contextual factor affecting the effectiveness of rewards in digital incentive tools, specifically the impact of computer-automated calculation design (vs. self-calculation design) on satisfaction towards rewards. Through four controlled experiments focused on green commuting with American samples and one field experiment on clothing recycling with a Chinese sample, this research finds when participants notified of rewards, the computer-automated calculation design (vs. self-calculation design) reduces their satisfaction towards rewards. That is, when participants notified of potential rewards, presented computer-calculated outcomes automatically (rather than allowed to self- calculate their own rewards) would diminish their satisfaction towards rewards. This effect is mediated by the reduced salience of reward elements rather than decreased self-involvement. Furthermore, listing reward components can alleviate this negative impact. This research enhances the literature on extrinsic rewards and low- carbon behavior by identifying the design of automated reward calculations as a novel factor undermining reward effectiveness, and recommending practitioners to enhance participants’ perception of elements constituting the rewards. © 2024 Elsevier B.V.