ABSTRACT

Despite the growing popularity of online referral programs, a minimal amount is known regarding the theoretical foundations that drive the key actions associated with successful referrals. In this paper, we study which type of referral reward structure is most effective in maximizing word-of-mouth by conducting two randomized experiments in mobile gaming context. Specifically, we examine the effect of three incentive schemes: selfish reward (inviter gets all the reward), equal-split reward (50-50 split), and generous reward (invitee gets all the reward). Consistent across the two experiments, we find that pro-social referral incentive schemes, namely the equal-split and generous schemes, tend to dominate purely selfish schemes in creating WOM. Our mechanism-level analysis shows that both equal-split and generous schemes result in higher number of conversions by significantly increasing the invitee’s likelihood to accept referrals, which we further show that is partially due to selective and better targeted referrals. Our results contribute to the understanding of the optimal design of online referral programs and provide important implications for designing effective referral reward schemes in the digital world.

摘要

尽管在线推荐计划越来越受欢迎，但有关推动成功推荐相关关键行为的理论基础知之甚少。在本文中，我们通过在移动游戏环境中进行两次随机实验来研究哪种类型的推荐奖励结构最有效地扩大了口碑。具体来说，我们研究了三种激励方案的效果：自私的奖励（邀请者获得所有奖励），均等的奖励（50-50拆分）和慷慨的奖励（被邀请者获得所有奖励）。在这两个实验中一致，我们发现亲社会推荐激励计划，即均等和慷慨的计划，在创建WOM时倾向于主导纯粹自私的计划。我们的机制级分析表明，等分和慷慨的方案都会通过显着增加被邀请人接受推荐的可能性而导致更高的转换次数，这进一步表明，这部分是由于选择性和针对性更好的推荐。我们的结果有助于理解在线推荐计划的最佳设计，并为设计数字世界中的有效推荐奖励计划提供重要启示。