基于互联网环境下的企业网络广告投资策略研究

摘要/Abstract

摘要： 随着网络广告的日益普及，选择投放合适的网络广告已经成为决定广告投放成功的关键，企业在进行网络广告投资决策时，面临着选择投资门户网络广告和长尾网络广告的困境。然而，目前并没有针对投放门户网络广告和长尾网络广告的理论和方法，因此需要投放门户网络广告和长尾网络广告的理论、方法和模型以有效指导企业广告投放的运作管理，为企业创造更高的价值。本文引进柯布-道格拉斯销售函数 S（a，q）=α-βa^-γq^-δ，尝试应用博弈论方法构建基于门户网络广告和长尾网络广告的非合作静态Nash投资模型、合作静态Nash投资模型和Stackelberg主从博弈投资决策模型，并通过模型均衡分析求出广告的投资小收益大的条件。与非合作的纳什均衡情况相比，Stackelberg主从博弈模型中，优先投资的网络广告投资小收益大，次后投资的网络广告投资大收益小。但总的投资和收益关系不确定。同其他三种投资情况相比，基于合作的投资策略比非合作和Stackelberg先后投资策略所获得的收益要大。同时，文中运用一个数值算例进一步验证了结论的有效性。解决了企业面临投资门户网络广告和长尾网络广告决策的困境，研究结论为企业投资网络广告提供理论依据和决策方法。

关键词: 门户网络广告, 长尾网络广告, 斯塔克伯格博弈, 纳什均衡

Abstract: With the increasing popularity of online advertising, the choice of appropriate online advertising has been the key of successful publishing. Enterprises are faced with dilemma when they select the investment between the portal online advertising and the long tail online advertising. Presently, however, there are no theories and methods aim to the portal online advertising and the long tail online advertising for publishing. Therefore, it is urgent to cry for the theories, methods, and models of online advertising publishing to instruct effectively the operation and management and create more value for enterprises. In this paper, Cobb-Douglas sales function S（a，q）=α-βa^-γq^-δ is introduced and non-cooperative static Nash investment model, cooperative static Nash investment model and Stackelberg investment model with game theory are built based on the portal online advertising and the long tail online advertising, through the analysis of model equilibrium to get the conditions that advertising investment gain big return from a small investment. In the condition of Stackelberg game model, the conditions are obtained that the long tail online advertising get big revenues from a small investment and the portal online advertising get big revenues from a small investment when they are successively invested respectively. Compared Stackelberg Equilibrium with non-cooperative Nash Equilibrium, the prior investment of online advertising gets big revenues from a small investment and subsequent investment gets small return from a big investment, and the relation of total investment and profits are uncertain. Compared with the non-cooperative online advertising investment model and Stackelberg game online advertising investment model, only the advertising investment based on cooperative Nash Equilibrium strategy can get the maximum profit. Furthermore, it verifies the validity of conclusion with a numerical example. The study conclusions solve dilemma for enterprises when they are faced with the investment between the portal online advertising and the long tail online advertising, it also provides enterprises a new theoretical basis and decision-making method for online advertising investment.

Key words: portal online advertising, long tail online advertising, Stackelberg game, Nash Equilibrium

中图分类号:

C931
F224

林宏伟, 邵培基. 基于互联网环境下的企业网络广告投资策略研究[J]. 中国管理科学, 2014, 22(2): 65-74.

LIN Hong-wei, SHAO Pei-ji. Study on Investment Strategies for Online Advertising Based on Internet Environment of Enterprise[J]. Chinese Journal of Management Science, 2014, 22(2): 65-74.

参考文献

[1] van der Wurff R, Bakker P, Picard R G. Economic growth and advertising expenditures in different media in different countries[J]. Journal of media Economics, 2008, 21(1):28-52.
[2] Gabszewicz J J, Laussel D, Sonnac N, Competition in the media and advertisingMarkets[J]. The Manchester School, 2006, 74(1):1-22.
[3] Naik P A, Raman K. Understanding the impact of synergy in ultimedia communications[J]. Journal of Marketing Research, 2003, 40(4):375-388.
[4] Berkowitz D, Allaway A, D'Souza D. The impact of differential lag effects on the allocation of advertising budgets across media[J]. Journal of Advertising Research, 2001, 41(2):27-36.
[5] Naik P A, Peter K. A hierarchical marketing communications model of online and offline media synergies[J]. Journal of Interactive Marketing, 2009, 23(4): 288-299.
[6] Soberman D. The complexity of media plan-ning today[J]. Journal of Brand Management, 2005, 12(6):420-429.
[7] Richard L. The paradox of ROI and decrea-sed spending in the ad industry[J]. American Journal of Business, 2009, 24(2):11-15.
[8] Danaher P J. Rust R T. Determining the optimal return on investment for an advertising campaign[J]. European Journal of Operational Research, 1996, 95(3):511-521.
[9] Leach D F, Reekie W D. A natural experiment of the effect of advertising on sales: The SASOL case[J]. Applied Economics, 1996, 28(9):1081-1091.
[10] Kennedy K, Kennedy B B. A small company's dilemma: Using search engi-nes effectively for corporate sales[J]. Management Research News, 2008, 31(10):737-745.
[11] Abrams Z, Keerthi S S, Mendelevitch O, et al. Ad delivery with budgeted advertisers: A comprehensive LP approach[J]. Journal of Electronic Commerce Research, 2008, 9(1):16-32.
[12] Özlük Ö, Cholette S. Allocating expenditures across keywords in search advertising[J]. Journal of Revenue and Pricing Management, 2007, 6(4):347-356.
[13] Muthukrishnan S, Pál M, Svitkina Z. Stochastic models for budget optimization in search-based advertising[J]. Algorithmica, 2010, 58(4):1022-1044.
[14] Zhao Lan, Nagurney A. A network equilb-brium framework for internet advertising: Models, qualitative analysis, and algorithms[J]. European Journal of Operational Research, 2008, 187(2):456-489.
[15] 曹文彬.企业网络广告的定价策略研究[J].中国管理科学, 2006, 14(1):94-99.
[16] Huang Zhimin, Li S X M. Co-op advertising models in manufacturerretailer supply chains: A game theory approach[J].European Journal of Operational Research, 2001, (135):527-544.
[17] 张庶萍, 张世英.基于微分对策的供应链合作广告决策研究[J].控制与决策, 2006, 21(2):153-157.
[18] 傅强, 曾顺秋.纵向合作广告的微分对策模型研究[J].系统工程理论与实践, 2007, (11):26-33.
[19] 罗卫, 张子刚, 欧阳明德.基于一个博弈论方法的简单供应链合作广告模型[J]. 系统工程理论与实践, 2004, (2):31-36.
[20] 梁樑, 余雁.供应链中制造商与代理商广告合作的博弈[J].系统工程理论方法应用, 2004, 13(6):490-494.
[21] 何建民, 刘赞.Internet环境下的网络广告投资渠道合作研究[J].合肥工业大学学报(自然科学版), 2008, 31(8):1241-1244.