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Determining the optimal release time of movies: A study of movie and market characteristics
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2023 | Decision Support Systems | Citations: 0
Authors: Sharma, Megha; Basu, Sumanta; Chakraborty, Soumyakanti; Bose, Indranil

Abstract: The over-the-top (OTT) industry has witnessed remarkable growth in recent years ... Expand

Abstract: The over-the-top (OTT) industry has witnessed remarkable growth in recent years with a sharp increase in the number of subscribers, leading to increased competition among OTT platforms to acquire movie rights. Conse quently, the gap between the theatrical and OTT releases has been diminishing over the last few years. An early release of a movie on an OTT platform fetches a higher distribution fee for a movie distributor (MD), however, it reduces the MD’s revenue from the theatrical release. Therefore, it becomes critical for the MD to determine the optimal release time and distribution fee combination. In this paper, we analytically solve the MD’s decision problem and provide a detailed analysis of how the optimal release time varies with changes in platform characteristics such as the proportion of ad revenue and the platform’s risk profile, movie characteristics such as success factor and suitability for OTT, and market characteristics such as broadband penetration, piracy rate and customers’ preferences for viewing channels. We compare our results with the actual release times of 243 movies released during 2015–2022. We find that the optimal release time increases with ad revenue proportion, broadband penetration, and piracy rate, whereas the optimal fee reduces non-linearly with release time and depends on OTT’s risk profile. Our findings also indicate that the optimal release time reduces for movies that do not provide any additional utility for theater goers, and as customers’ preference towards OTT increases. Our work provides much-needed guidelines for professionals dealing with movie releases on OTTs. Collapse

Semantic filters: Amazon Prime Video

Topics: digital service Netflix Disney+ decision support system Hulu

Methods: parametric test mathematical model ANOVA paired t-test artificial neural network
Privacy Versioning for Competitive Advantage

2022 | International Conference on Information Systems | Citations: 0
Authors: Parra-Moyano, José; Mehta, Sameer

Abstract: There is increasing tension between the service quality improvements consumers ... Expand

Abstract: There is increasing tension between the service quality improvements consumers receive when they allow their data to be analyzed by a firm, and the costs they incur in terms of privacy sacrifices. This is motivating firms to explore new models to attract and retain a new generation of privacy-active customers (i.e., customers who act in order to protect their privacy). This paper sets the foundation to solve the mechanism design problem for a firm that offers a continuous set of menus allowing its customers to chose their optimal combination of privacy and price. The solution of the problem shows that the relationship between prices and the amount of data shared is non-monotonic. This is a surprising result that may contribute to a better understanding of the privacy paradox, as well as to help scholars and practitioners to push the known boundaries of privacy-based versioning. Collapse

Semantic filters: Amazon Prime Video

Topics: privacy competitive advantage information good digital service Amazon Prime Video

Methods: archival research literature study
The causal effect of subscription video streaming on DVD sales: Evidence from a natural experiment
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2022 | Decision Support Systems | Citations: 0
Authors: Yu, Yinan; Chen, Hailiang; Peng, Chih-Hung; Chau, Patrick Y.K.

Abstract: Subscription-based video streaming has recently become the main revenue driver i ... Expand

Abstract: Subscription-based video streaming has recently become the main revenue driver in the home entertainment industry. Whether and how it affects the sales of physical media, which was previously the industry’s largest revenue source for decades, is still not well understood. We answer this question using a natural experiment that occurred on October 1, 2015, when the content owner Epix switched its streaming partner from Netflix to Hulu. This event created an exogenous shock that significantly reduced the streaming availability of Epix’s content because of the difference in the market shares of the two streaming service providers at the time. This occurrence allows us to investigate the causal effect of subscription streaming on physical DVD sales. Our difference-indifferences analysis shows that the decline in the streaming availability of Epix’s content caused an increase of 36.07% in its monthly DVD sales during the 15 months after the event. We also find that the cannibalization between these two channels is much stronger for movies with higher level of content stickiness (e.g., more recent titles, and titles with a general audience (G) or parental guidance (PG) rating or belonging to the children/family genre). Our findings provide important implications for content owners on how to balance physical sales with revenues from streaming licenses. Collapse

Semantic filters: Amazon Prime Video

Topics: DVD digital service Netflix Hulu streaming service

Methods: experimental group natural experiment Internet Movie Database review longitudinal research robustness check
Amazon Prime Video Yesterday, Netflix Today: Explaining Subscribers' Switching Behavior from a Retrospective

2021 | European Conference On Information Systems | Citations: 0
Authors: Meier, Marco; Maier, Christian; Reis, Lea; Weitzel, Tim

Abstract: Video -on-demand (VoD) services attract millions of subscribers around the glo ... Expand

Abstract: Video -on-demand (VoD) services attract millions of subscribers around the globe. Despite their popularity, practice shows the interesting behavior of subscribers of VoD services switching regularly between different providers, such as Netflix or Amazon Prime Video. To sustain their revenues due to subscriptions, providers need to understand the reasons why subscribers switched to other VoD services. While existing research with a prospective point of view explains that users develop switching intentions between different services because of, for instance, dissatisfaction, there is scant research on their actual switching behavior from a retrospective. By analyzing interviews with 23 subscribers that switched VoD services, findings reveal five switching causes and three switching barriers that together explain switching behavior between VoD services. With that, the findings contribute to switching research by identifying switching causes and switching barriers, zooming in on causes of subscribers' dissatisfaction with VoD services, and studying switching behavior from a retrospective. Collapse

Semantic filters: Amazon Prime Video

Topics: digital service social influence Netflix Amazon Prime Video information system use

Methods: qualitative interview literature study qualitative coding mixed method personal interview

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Found 4 articles

Determining the optimal release time of movies: A study of movie and market characteristics

Privacy Versioning for Competitive Advantage

The causal effect of subscription video streaming on DVD sales: Evidence from a natural experiment

Amazon Prime Video Yesterday, Netflix Today: Explaining Subscribers' Switching Behavior from a Retrospective