Television Audiences can Learn and can Forget--Modeling the Audience”s Dynamic Decision Procedure
Television(TV)audience research can provide various accurate and reliable approaches to investigate TV ratings and viewer behavior.However,extant research ignores the issue of how the episodic nature of TV watching influences viewer behavior and program selection.The purpose of this paper is to elucidate the impact of an audience”s dynamic decisions under two interactive behaviors: learning behavior and forgetting behavior.Learning behavior refers to updating drama quality assessment using information,while forgetting behavior disturbs the use of information.Based on a deep exploration of viewing behavior in a longitudinal context,we construct an innovative methodology employing Bayesian rules to model the dynamic process,and test its performance by comparing with three benchmark models.Through empirical work of model calibration based on the people meter data from the Hong Kong TV industry,we show that the learning and forgetting behaviors are two important factors determining the fit and predictive ability of our model.Some managerial implications are then discussed in order to provide useful insights to guide advertiser and TV broadcaster decision-making.
decision processes dynamic learning forgetting Bayesian updating theory TV ratings
Lianlian Song Geoffrey Tso Hao Zhang Jianling Wang Wenlong Liu
Nanjing University of Aeronautics and Astronautics,Nanjing,China City University of Hong Kong,Hong Kong,China
国内会议
China Marketing International Conference 2017 (2017中国市场营销国际学术年会)
北京
英文
609-638
2017-07-14（万方平台首次上网日期，不代表论文的发表时间）