Genuine Liking or the Need for Closure? The Differential Effects of Consumers’ TV Drama Viewing Motivations on Commercial Viewership

ABSTRACT

Television advertising effectiveness constitutes a key marketing issue. Advertisers rely on program TV ratings to determine advertisement placement because consumers’ decisions to view TV commercials are largely influenced by their TV program-viewing behavior. However, high program viewership of television dramas does not always entail high commercial viewership; consumers’ motivations for drama consumption play a critical role. In the context of TV drama viewing, we build a two-stage structural model that distinguishes two motivations for TV drama consumption—viewers’ liking for a drama and the need for cognitive closure—and demonstrate their contrasting effects on consumers’ commercial-viewing behavior. Although both motivations enhance drama-viewing behavior, consumers exhibit an enhanced (vs. diminished) tendency to watch subsequent commercials when they possess heightened liking for the drama (vs. the need for cognitive closure). These findings contribute to extant research on TV commercial-viewing behavior by distinguishing the roles of different drama-viewing motivations. Based on the model estimation results, we conduct a series of simulation studies to generate rich managerial implications. Managerial practices for both advertisers and TV networks are discussed.

Acknowledgment

We would like to express our sincere thanks to Prof. Ying Zhao and Prof. Jun B. Kim for their invaluable comments on an earlier version of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The recent program schedule of our focal channel can be found at https://programme.tvb.com/jade/week/

² The majority of viewers of drama LD start watching it over the first 20 episodes. However, Drama GC and MT only have around 20 episodes in total. Comprising the need of focusing on the period where the learning pattern is significant and the requirement of enough episodes for model identification in the dynamic process, we decided to use the first 20 episodes of LD for model estimation, while using all episodes (around 20 episodes) of GC and MT for their estimations.

Additional information

Funding

Financial support from the National Natural Science Foundation of China (No. 71702201 to the first author; No. 71802198 to the second author) and support from the Fundamental Research Funds for the Central Universities of China and Natural Science Foundation of –Guangdong Province —(No. 2018A030310251 to the second author) are gratefully acknowledged.

Notes on contributors

Yang Shi

Yang Shi obtained Ph.D. in Marketing from the Hong Kong University of Science and Technology, is currently an Assistant Professor of Marketing, at Shenzhen Audencia Business School, WeBank Institute of Fintech and Guangdong Laboraty of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, China.  She focuses on academic research of marketing in statistical modeling. The research topics she has conducted include modeling consumer purchase decisions, consumers’ responses to TV advertisements, bidding and etc. Her papers have appeared in Journal of Interactive Marketing, International Journal of Forecasting and etc.

Tingting Wang

Tingting Wang received Ph.D. in Marketing from the Hong Kong University of Science and Technology, specializing in consumer behavior research, and is currently an Assistant Professor of Marketing, at Lingnan (University) College, Sun Yat-sen University, Guangzhou, China.