Meiqian Li , Guowei Liu , Guofang Nan , Yinliang (Ricky) Tan
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引用次数: 0
Abstract
The rapid growth of illegal websites hosting pirated content has significantly reduced demand for legitimate media platforms, causing substantial economic losses to the media industry. Governmental departments must take measures to combat these illegal websites and restrict access to pirated content. This paper examines governmental enforcement against piracy on media platforms that offer consumer services under three revenue models: subscription, ad-based, and mixed. Our analysis yields the following key findings with critical managerial insights. First, under the subscription and mixed models, the optimal governmental enforcement levels lie within the piracy threat region where piracy exists in the market, but there is no demand for it, whereas under the ad-based model, the optimal governmental enforcement can allow the piracy to have a demand and even if no enforcement occurs. Second, optimal governmental enforcement exhibits a non-monotonic effect with respect to the quality of pirated content under each revenue model, which implies that the government does not necessarily strengthen its enforcement facing a higher quality of pirated content. Finally, the optimal governmental enforcement decreases as the consumer nuisance cost for advertisement increases under the ad-based model, whereas it presents a non-monotonic change under the mixed model. We further extend our main model to a duopoly platform setting and a situation of decreasing marginal efficiency of enforcement. The results demonstrate that the insights derived from our main model remain hold. These findings suggest that social planners should consider media platforms' revenue models and market conditions when formulating enforcement policies against piracy.
期刊介绍:
The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).