网络广告运作的若干关键问题研究
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摘要
截止2012年底，中国网络广告市场规模突破750亿元，增长率达46.8%，随着网络广告的快速发展，广告主对网络广告和网络媒体对流量变现的需求日益增长，传统的网络广告运作模式越来越不适应大规模的网络广告交易，作为广告主和网络媒体之间的桥梁，广告网络改变了传统网络广告的运作模式，提高了网络广告市场的交易效率。
但是，广告网络也面临着广告运作中若干急需解决的关键问题，这些关键问题的解决将会有助于网络广告市场更好地发展。本文针对目前网络广告市场中急需解决的网络媒体资源整合与评价、网络广告点击欺诈、网络广告定价和网络广告投资四种关键热点问题进行了探索性和创新性研究，主要内容包括：
(1)网络媒体资源整合与评价研究。本文引入了22伯特兰价格博弈模型，研究了网络媒体资源的优化和整合。结果表明整合后的市场结构有利于广告主节约成本,广告网络可以实现规模经济和范围经济，网络媒体可以将流量变现，保持相对稳定的收入。构建了基于网络广告投放视角的网络媒体评价指标体系。应用区间数相离度和可能度偏差最大化多属性决策的方法，将精确型数据和区间型数据统一起来，建立了混合数据指标的评价模型，解决了网络广告的混合多属性指标决策问题。
(2)网络广告点击欺诈研究。建立了点击欺诈监管的基本博弈模型、广告网络受到广告主惩罚时的二级监管模型、存在多个网络媒体之间竞争情况下的监管模型。模型分析结果表明，通过加强对网络媒体的监督与控制，广告主实施对广告网络的惩罚，建立网络媒体之间的竞争机制，能有效地避免点击欺诈。基于双边道德风险视角，引入对网络媒体的罚金和点击欺诈的比例系数等参数，分析网络媒体的收益共享系数与罚金、欺诈比例系数的关系。模型均衡分析表明，最优收益共享系数与点击欺诈比例系数负相关，提高点击欺诈成本有利于制止点击欺诈。
(3)网络广告定价研究。基于风险规避的视角，建立了广告网络和网络媒体之间的两阶段收益定价模型。两阶段定价不仅使广告网络可以避免较高的广告成本支出，而且能够有效地制止点击欺诈和规避信息不对称性带来的风险，网络媒体则可以获得额外的收益。应用指数效用函数构建了CPM、CPC和CPA三种定价模型，并提出了一种新的定价转化规则，确定了合作双方对三种不同网络广告定价合约达成一致的条件，分析了点击率、行动率、风险态度等因素对三种定价模型的影响，并为广告网络和网络媒体在不同条件下指明了最优的广告定价模型。
(4)网络广告投资研究。应用最优化理论和方法构建基于门户网络广告和长尾网络广告单周期和两周期的投资决策模型，并通过模型分析求出单周期和两周期两类网络广告投资收益的最优条件。在两周期投资模型中引入广告学习因子和折现因子，当广告学习因子的数值越大，则对后期的投资与收益影响越大；后期相对于前期来说，数值越大，投资越小但收益越大；两周期收益与折现因子呈正向关系，折现因子越大，两周期收益越大；当的数值趋近于0时，两周期投资模型就退化为单周期投资模型。
本文对网络广告运作的若干关键问题研究的相关成果，对网络广告理论的进一步完善和未来网络广告市场的进一步发展具有积极的推动作用。
Up to Dec.2012, the market scale of online advertising in China has brokenthrough75billion and growth rate reached46.8%, respectively.With the rapiddevelopment of the internet, advertisers and online media’s demand to monetize thenetwork traffic has becoming more urgent, the traditional operation mode of onlineadvertising can’t adapt to large scale online advertising transactions. As the bridgebetween advertisers and online media, ads network has changed the operation mode oftraditional online advertising. However, the ads network itself also has many pressingcritical problems to be resolved. Based on the game theory and contract theory, theurgent and critical problems of online advertising which based on ads network has beenresearched. It provides decision-making support for the online advertising operation, themain contents include the following four aspects:
Firstly,22Bertrand price game model was introduced and integration ofnetwork media resources by ads network was analyzed. The result shows that optimizedand integrated advertising market structure is beneficial to every partner of the wholeonline advertising industry chain. Advertisers can save cost, ads network can achieveeconomies of scale and scope economy and network media can monetize its traffic,retaining relatively stable income. For choosing appropriate network media, theevaluation index system of network media based on the view of publishing onlineadvertising was built. The maximum deviation method based on deviation degree andpossibility degree of ulti-attribute decision-making were applied, integrated the precisedata and interval data and constructed an assessment model to solve the problem ofhybrid multi-attribute decision making.
Secondly, a basic game theory model for click fraud monitoring was established,the model was extended to the two-echelon monitoring game model that the AdsNetwork would be punished by advertisers, and then further the two-echelon model wasextended into a regulation model when considering the competition among thepublishers. Analysis of Model shows that click fraud can be effectively prevented bymany ways including strengthening the supervision and control of network media, implementing punishment on Ad network by advertisers, reducing informationasymmetry, choosing the honest network media to publish advertising and building thecompetitive mechanism among network media. According to the perspective of doublemoral hazard, the proportional coefficient of fines and ratio of click fraud on networkmedia were introduced and the relationship between the revenue sharing coefficient andthe proportional coefficient of fines and ratio of click fraud on network media werediscussed. Analyzing on the equilibrium of the model shows that the optimal revenuesharing coefficient is negatively correlated with the ratio of click fraud, increasing thecost of click fraud is helpful to prevent click fraud.
Thirdly, based on the perspective of risk-averse, the two-stage revenue pricingmodel between the ads network and online media was built and Nash bargainingmethod was applied to determine the optimal two-stage pricing problem. The feasibleconditions of the implementation of the two-stage contract were identified and therelationship between the negotiation power and the first stage pricing was analyzed. Thestudy shows that two-stage pricing contract brings ads network and publishers moreflexible options. The two-stage pricing not only makes ads network (advertisers) avoidhigher advertising costs, but also effectively stops click fraud, avoids the risks ofasymmetry information and publishers will gain extra revenues. The three pricing modelthat CPM and CPC, CPM and CPA, CPC and CPA were constructed by usingexponential utility function. And then a new pricing conversion rule among CPM, CPCand CPA pricing contract was put forward. The conditions under which the partnerswould agree on the three different advertising pricing agreement were analyzed, and theinfluence of click-through rate, action rate and risk attitudes on three pricing modelwere analyzed, too. The results showed the optimal pricing model for the ads network(advertisers) and network media under different conditions.
Finally, by introducing Cobb-Douglas sales function and applying optimizationtheory and method, non-cooperative investment model, cooperative investment modeland dynamic two-stage investment model of single-period and two-period were buitbased on the portal online advertising and the long tail online advertising. The optimalinvestment revenue conditions were gained by analyzing model of single-period onlineadvertising investment and two-period online advertising investment. Learning effectsfactor and the discount factor were introduced into two-period investment model, the research results indicated that the bigger advertising learning effects factor resulted thebigger influence on later investment and revenue. Relative to the previous investment,increasing advertising learning effects factor, the later investment is smaller while therevenue is more. The two-period revenue is positive with discount factor, increasing thediscount factor, the more two-period revenue, when the values of learning effects factortends to be zero, two-period investment model will degenerate to a single-periodmodel.
The results of some critical problems on online advertising operation have apositive effect in further improving online advertising theory and further promotingonline advertising market development.
但是，广告网络也面临着广告运作中若干急需解决的关键问题，这些关键问题的解决将会有助于网络广告市场更好地发展。本文针对目前网络广告市场中急需解决的网络媒体资源整合与评价、网络广告点击欺诈、网络广告定价和网络广告投资四种关键热点问题进行了探索性和创新性研究，主要内容包括：
(1)网络媒体资源整合与评价研究。本文引入了22伯特兰价格博弈模型，研究了网络媒体资源的优化和整合。结果表明整合后的市场结构有利于广告主节约成本,广告网络可以实现规模经济和范围经济，网络媒体可以将流量变现，保持相对稳定的收入。构建了基于网络广告投放视角的网络媒体评价指标体系。应用区间数相离度和可能度偏差最大化多属性决策的方法，将精确型数据和区间型数据统一起来，建立了混合数据指标的评价模型，解决了网络广告的混合多属性指标决策问题。
(2)网络广告点击欺诈研究。建立了点击欺诈监管的基本博弈模型、广告网络受到广告主惩罚时的二级监管模型、存在多个网络媒体之间竞争情况下的监管模型。模型分析结果表明，通过加强对网络媒体的监督与控制，广告主实施对广告网络的惩罚，建立网络媒体之间的竞争机制，能有效地避免点击欺诈。基于双边道德风险视角，引入对网络媒体的罚金和点击欺诈的比例系数等参数，分析网络媒体的收益共享系数与罚金、欺诈比例系数的关系。模型均衡分析表明，最优收益共享系数与点击欺诈比例系数负相关，提高点击欺诈成本有利于制止点击欺诈。
(3)网络广告定价研究。基于风险规避的视角，建立了广告网络和网络媒体之间的两阶段收益定价模型。两阶段定价不仅使广告网络可以避免较高的广告成本支出，而且能够有效地制止点击欺诈和规避信息不对称性带来的风险，网络媒体则可以获得额外的收益。应用指数效用函数构建了CPM、CPC和CPA三种定价模型，并提出了一种新的定价转化规则，确定了合作双方对三种不同网络广告定价合约达成一致的条件，分析了点击率、行动率、风险态度等因素对三种定价模型的影响，并为广告网络和网络媒体在不同条件下指明了最优的广告定价模型。
(4)网络广告投资研究。应用最优化理论和方法构建基于门户网络广告和长尾网络广告单周期和两周期的投资决策模型，并通过模型分析求出单周期和两周期两类网络广告投资收益的最优条件。在两周期投资模型中引入广告学习因子和折现因子，当广告学习因子的数值越大，则对后期的投资与收益影响越大；后期相对于前期来说，数值越大，投资越小但收益越大；两周期收益与折现因子呈正向关系，折现因子越大，两周期收益越大；当的数值趋近于0时，两周期投资模型就退化为单周期投资模型。
本文对网络广告运作的若干关键问题研究的相关成果，对网络广告理论的进一步完善和未来网络广告市场的进一步发展具有积极的推动作用。
Up to Dec.2012, the market scale of online advertising in China has brokenthrough75billion and growth rate reached46.8%, respectively.With the rapiddevelopment of the internet, advertisers and online media’s demand to monetize thenetwork traffic has becoming more urgent, the traditional operation mode of onlineadvertising can’t adapt to large scale online advertising transactions. As the bridgebetween advertisers and online media, ads network has changed the operation mode oftraditional online advertising. However, the ads network itself also has many pressingcritical problems to be resolved. Based on the game theory and contract theory, theurgent and critical problems of online advertising which based on ads network has beenresearched. It provides decision-making support for the online advertising operation, themain contents include the following four aspects:
Firstly,22Bertrand price game model was introduced and integration ofnetwork media resources by ads network was analyzed. The result shows that optimizedand integrated advertising market structure is beneficial to every partner of the wholeonline advertising industry chain. Advertisers can save cost, ads network can achieveeconomies of scale and scope economy and network media can monetize its traffic,retaining relatively stable income. For choosing appropriate network media, theevaluation index system of network media based on the view of publishing onlineadvertising was built. The maximum deviation method based on deviation degree andpossibility degree of ulti-attribute decision-making were applied, integrated the precisedata and interval data and constructed an assessment model to solve the problem ofhybrid multi-attribute decision making.
Secondly, a basic game theory model for click fraud monitoring was established,the model was extended to the two-echelon monitoring game model that the AdsNetwork would be punished by advertisers, and then further the two-echelon model wasextended into a regulation model when considering the competition among thepublishers. Analysis of Model shows that click fraud can be effectively prevented bymany ways including strengthening the supervision and control of network media, implementing punishment on Ad network by advertisers, reducing informationasymmetry, choosing the honest network media to publish advertising and building thecompetitive mechanism among network media. According to the perspective of doublemoral hazard, the proportional coefficient of fines and ratio of click fraud on networkmedia were introduced and the relationship between the revenue sharing coefficient andthe proportional coefficient of fines and ratio of click fraud on network media werediscussed. Analyzing on the equilibrium of the model shows that the optimal revenuesharing coefficient is negatively correlated with the ratio of click fraud, increasing thecost of click fraud is helpful to prevent click fraud.
Thirdly, based on the perspective of risk-averse, the two-stage revenue pricingmodel between the ads network and online media was built and Nash bargainingmethod was applied to determine the optimal two-stage pricing problem. The feasibleconditions of the implementation of the two-stage contract were identified and therelationship between the negotiation power and the first stage pricing was analyzed. Thestudy shows that two-stage pricing contract brings ads network and publishers moreflexible options. The two-stage pricing not only makes ads network (advertisers) avoidhigher advertising costs, but also effectively stops click fraud, avoids the risks ofasymmetry information and publishers will gain extra revenues. The three pricing modelthat CPM and CPC, CPM and CPA, CPC and CPA were constructed by usingexponential utility function. And then a new pricing conversion rule among CPM, CPCand CPA pricing contract was put forward. The conditions under which the partnerswould agree on the three different advertising pricing agreement were analyzed, and theinfluence of click-through rate, action rate and risk attitudes on three pricing modelwere analyzed, too. The results showed the optimal pricing model for the ads network(advertisers) and network media under different conditions.
Finally, by introducing Cobb-Douglas sales function and applying optimizationtheory and method, non-cooperative investment model, cooperative investment modeland dynamic two-stage investment model of single-period and two-period were buitbased on the portal online advertising and the long tail online advertising. The optimalinvestment revenue conditions were gained by analyzing model of single-period onlineadvertising investment and two-period online advertising investment. Learning effectsfactor and the discount factor were introduced into two-period investment model, the research results indicated that the bigger advertising learning effects factor resulted thebigger influence on later investment and revenue. Relative to the previous investment,increasing advertising learning effects factor, the later investment is smaller while therevenue is more. The two-period revenue is positive with discount factor, increasing thediscount factor, the more two-period revenue, when the values of learning effects factortends to be zero, two-period investment model will degenerate to a single-periodmodel.
The results of some critical problems on online advertising operation have apositive effect in further improving online advertising theory and further promotingonline advertising market development.
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