추천자 인센티브와 피추천자 인센티브 설계에 대한 연구 = 피추천자 구매행동이 추천자에 미치는 네트워크 외부효과의 영향을 중심으로

국문 초록 (Abstract)

고객의 추천을 촉진하기 위한 인센티브는 점차 다양한 형태로 시도되고 있는데 최근에는 추천자와 더불어 피추천자에게도 인센티브를 제시하는 경우도 증가하고 있다. 그런데 피추천자의 구매는 마케터뿐만 아니라 추천자에게 득이 되기도 한다. 이에 따라 추천행동이 추천자, 피추천자, 마케터에게 야기하는 상호작용 효과를 염두에 두고 추천자 인센티브와 피추천자 인센티브를 종합적으로 고려하여 바람직한 추천 촉진 인센티브 방향을 모색해볼 필요성이 존재한다. 본 연구에서는 피추천자의 구매행동이 추천자의 효용을 직접 증가시키는 네트워크 외부효과가 존재하는 상황을 게임이론으로 모형화하여 적절한 추천자 인센티브와 피추천자 인센티브 구조를 모색하고 있다. 본 연구의 주요결과는 다음과 같다. (1) 피추천자 구매에 따른 추천자 효용 증대 외부효과가 클수록 추천자 인센티브와 피추천자 인센티브를 낮출 필요가 있다. (2) 피추천자 구매에 따른 추천자 효용증대 외부효과가 클수록 추천자 인센티브 비중을 낮추는 것이 바람직하다. (3) 명성이 낮은 (높은) 마케터일수록 피추천자 구매에 따른 추천자 효용증대 외부효과 증가에 따라 요구되는 추천자-피추천자 인센티브 감소폭이 커진다 (작아진다).

다국어 초록 (Multilingual Abstract)

As the importance of customer referral gets higher, more marketers are inclined to use diverse referral incentives to promote positive referrals. Furthermore some marketers use not only referrer incentives but also referree incentives to promote referrers` referral behavior. So one of the most urgent tasks in marketing field might be to answer the question what incentive system is optimal when marketers consider both referrer incentives and referree incentives. However there has been surprising lack of trial to answer the question. Despite the urgent need of trial to answer the question, there have been scarce trials to answer the question. In other words, most studies on referral incentives did not consider both referrer incentives and referree incentives. In this study, we try to find better incentive system for promoting referrals considering both referrer incentives and referree incentives. We use simple game theoretic modelling approach. We investigated two specific issues about the topic as following: (1) What level and structure of referrer incentive and referree incentive should the marketer provide when the referrer`s network externalities gets high (or low)?, (2) What structure of referrer and referree incentive should the marketer choose when the firm`s reputation level goes high (or low)? Our model is as follows. Here the referrer is a representative customer and the referree is a representative potential customer.Our game is of complete information setting. Stages of the game are as following. (Stage 1) Marketer sets price(p), referrer incentive(x) and referree incentive(y). (Stage 2) Referrer chooses his opitimal referring efforts level(a) based on the referrer incentive(x) which is handed over immediately.(Stage 3) Referree chooses his opitimal refer-verifying efforts level(b) based on the referree incentive(y) handed over immediately. Then, referree purchases proper quantity based on the marketer`s reputation, price level, and verification results. After that every player`s payoff gets realized. Our findings are as following. (1) As the level of referrer`s network externalities gets higher, the marketer had better decrease both referrer incentive and referree incentive., (2) As the level of referrer`s network externalities gets higher, the relative ratio of referrer incentive should be lowered in equilibrium., (3) Higher-reputation firm had better decrease incentives less than lower-reputation firm when the level of referrer`s network externalities gets higher. This study might be one of the incipient trials to investigate better incentive system for promoting referral behaviors considering not only referrer incentives but also referree incentives considering network externalities.

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