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在口碑推荐过程中，相对于其他行为，推荐行为的互惠关系效应比较显著。而且，
推荐者进行口碑推荐时往往担心消耗被推荐者对自己的信任，这种担心将产生一定的
推荐风险成本。此外，相对于一般人而言，创新顾客更容易产生公平偏好效用。为了
突出推荐问题中明显存在的互惠关系效用、推荐风险成本以及创新顾客的公平偏好效
用，打破传统经济学对理性且纯粹自利假设的局限性，本论文以创新顾客为研究主体，
运用行为经济学和信息经济学的知识，将互惠、风险感知和公平引入效用理论模型，
构建以创新顾客为主要研究对象的口碑推荐激励模型，根据模型结果探讨企业应如何
设置推荐奖励，比较创新顾客与普通顾客的最优推荐奖励结果及其对企业净利润的不
同影响，分析互惠关系、公平偏好程度以及风险容忍度分别对口碑推荐激励机制的影
响，并借助 Mathematica、Matlab、Excel 等软件进行数值分析和案例分析以验证模型
结果
研究结果表明，第一，相比于普通顾客，企业为创新顾客设置的最优推荐奖励成
本更低，且顾客的创新贡献率越大，最优推荐奖励额度（奖励成本）越小。第二，企
业可结合创新顾客的特征来优化口碑推荐激励机制：对于互惠型创新顾客，创新顾客
与关系疏远被推荐者之间的互惠关系强度越大，最优推荐奖励额度越高；对于风险规
避型创新顾客，其风险容忍度越小，最优推荐奖励额度越高；对于公平偏好型创新顾
客，其公平偏好程度越小，最优推荐奖励额度越高。第三，考虑创新顾客在推荐过程
中的互惠效用，企业净利润随着强关系强度的增加而降低。第四，对于风险规避型创
新顾客，企业可通过以下两种方式增加自身净利润：①设置推荐奖励激发风险容忍度
适中的创新顾客的口碑推荐行为；②不设推荐奖励时则重点关注并引导高风险容忍度
的创新顾客进行推荐。第五，对于具有公平偏好的创新顾客，奖励高公平偏好型创新广东工业大学硕士学位论文
II
顾客的口碑推荐行为能够为企业带来更高的净利润。最终的结论为制定科学有效的创
新顾客的口碑推荐激励机制和最大化企业净利润提供一定的理论参考
关键词：创新顾客；口碑推荐激励；互惠关系；风险容忍度；公平偏好ABSTRACT
III
ABSTRACT
In the marketing environment which focuses on customer innovation and user
involvement, innovative customers tend to become opinion leaders, who have dramatic
effect on other potential customers. Enterprises gradually realize that innovative customer
recommendation behavior has become an important means of product or service promotion
and brand information transmission. Some enterprises have begun to use material rewards,
such as prizes and bonuses, to motivate innovative customers to make recommendations, but
have not yet regulated a scientific and effective referral reward program. The establishment
of an effective incentive mechanism, which not only attracts innovative customers to
recommend, but also helps to maximize the utility of enterprises.
In the process of recommendation, compared with other behaviors, the reciprocity
effect of recommendation behavior is significant. When referrers make recommendations,
they will worry about the trust crises from recipients, and the trust crises will cause risk costs.
In addition, innovative customers, compared with general people, who are more likely to
have fair preference utilities. In order to solve the problems caused by the reciprocal utility,
risk cost of recommendation and equity preference utility in recommendation process, and
break the assumption that people are rational and purely self-interested in traditional
economics, this paper takes innovative customer as the research subject, and applies the
knowledge of behavioral and information economics to construct three incentive models of
innovative customer recommendation. “Tie strength” , “risk tolerance”, “equity preference”
are respectively introduced into these threes incentive models based on behavioral
economics and information economics. According to the results of these models, we explore
that how enterprises reward innovative customer recommendations, and compare the
differences of model results between innovative customer and general customer. We also
respectively analyze that the impacts of tie strength, equity preference and risk tolerance on
incentive mechanism. Then we carry out two numerical analyses and a case analysis to
verify the model results with the help of MATHEMATICA, MATLAB and EXCEL.
The results show that, firstly, the optimal incentive cost of innovative customers
recommendation is lower than which of general customers, and the referral bonus (incentive
cost) decreases with the increase of rate of innovation contribution. Secondly, enterprises can
optimize the recommendation incentive mechanism in accordance with the characteristics of
innovative customers: for reciprocal innovative customers, the referral bonus increases with广东工业大学硕士学位论文
IV
the increase of tie strength between innovative customers and distant recipients; for risk
averse innovative customers, the referral bonus increases with the decrease of risk tolerance
of innovative customers; for innovative customers with equity preference, the referral bonus
increases with the decrease of equity preference of innovative customers. Thirdly, to
consider the reciprocal utility of innovative customer from recommendation, firm net income
decreases with the increase of close tie strength. Fourthly, for risk averse innovative
customers, firm net income can be increased through the following two ways: enterprises
should (1)set referral bonus to these innovative customers with moderate risk tolerance; (2)or
take innovative customers with high risk tolerance seriously and lead them to make
recommendation if enterprises do not set up referral bonus. Fifthly, the setting of referral
reward program for innovative customers with high equity preference, which can bring
higher firm net income. The conclusions provide theoretical references for the establishment
of scientific and effective incentive mechanism about innovative customer recommendation
and the maximization of firm net income.
Keyword: Innovative Customer; Recommendation Incentive Mechanism; Tie Strength; Risk
Tolerance; Equity Preference目 录
V
目 录
摘要.......I
ABSTRACT ... III
目录.....V
CONTENTS ... IX
第一章 绪论....1
1.1 研究背景与问题 ....... 1
1.2 研究意义 ....... 3
1.2.1 理论意义 ........ 3
1.2.2 实践意义 ........ 4
1.3 研究目标与内容 ....... 4
1.3.1 研究目标 ........ 4
1.3.2 研究内容 ........ 5
1.4 研究方法、思路与论文结构 ........... 6
1.4.1 研究方法 ........ 6
1.4.2 研究思路与技术路线6
1.4.3 论文结构 ........ 9
第二章 文献综述......10
2.1 相关概念的界定 .....
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