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Research On The Pricing And Operation Strategies Of Chinese Network Literature Platforms

Posted on:2022-08-03Degree:MasterType:Thesis
Country:ChinaCandidate:Q G WangFull Text:PDF
GTID:2505306497491014Subject:Publishing Science
Abstract/Summary:PDF Full Text Request
The competition in Chinese network literature market has been increasingly intense.On the one hand,the scale of network literature market is limited,and the number of premium readers keeps steady.On the other hand,the free-of-charge network literature platforms have entered this market and compete against the incumbent with the business model of free reading and advertisement distribution,which enables them to take up higher market share.Analyzing the competition between the premium and freeof-charge network literature platform and clarifying their predominant pricing and operation strategies is advantageous for the researches on two sided market with the experiences form Chinese network literature market.The present paper has built four models,including monopoly premium network literature platform,monopoly free-ofcharge network literature platform,duopoly premium and free-of-charge network literature platforms with single-homing readers and duopoly platforms with multihoming readers.These models are used to explain the dominant pricing and operation strategies for premium and free-of-charge network literature platforms.The present paper has also conducted a numerical simulation to investigate the competition between premium and free-of-charge network literature platforms under different circumstances using parameters from the market reality.The simulation has enabled us to offer tentative suggestions for these network literature platforms on their pricing and operation strategies.The principal conclusions are listed as follows.Firstly,as for premium network literature platforms,they are intended to offer discounts to readers who have ever paid for reading since their entrance elasticity is relatively low.When readers are single-homing,the platforms tend to lower their prices for readers whose intra-group network externality is high.When readers are multihoming,however,the platforms will not lower their prices.Nevertheless,the income for writers will increase in both situations.Secondly,as for free-of-charge network literature platforms,they will not have incentives to reduce advertisement under most circumstances.The investment preference of exogenous advertisers has offered incentive for them to lower horizontal differences of their works from premium platforms.If the principal purposes of them are to increase advertisement amounts and profits,they are supposed to optimize the interaction between readers and writers moderately,or they may suffer from loss of profits.However,they should endeavor to optimize the interaction when their aims are to enhance the market share to ensure ROI for advertisers.Lastly,as for the optimization of the operation strategies for the two kinds of platforms,enhancing the intra-group network externality for readers has always been a predominant strategy in all situations.When readers are multi-homing,improving the user experiences for writers is not a dominant strategy since it may lead to the loss of profits,even though it is helpful to rise the market share and optimize the investment for advertisers.Nevertheless,improving the reading experience for readers has always been a dominant strategy for it is advantageous to rise advertisement amounts,market share and profits,but the marginal utility to improve this experience is decreasing.When readers are multi-homing,the free-of-charge platform is supposed to optimize the reading experience moderately and endeavor to rise the intra-group network externality for readers so as to attract advertisers.The premium network literature platforms should,however,spare no effort to optimize those experiences to augment their prices,market share and profits.
Keywords/Search Tags:Network Literature, Platform Economy, Pricing Strategy, Publishing Industry, Exogenous Advertisers
PDF Full Text Request
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