Video On Demand Service Providers Research Articles

Strategies to mitigate the cannibalization effect between subscription video-on-demand and transactional video-on-demand

Video-on-demand (VOD) service providers face the challenge of making strategic decisions regarding the allocation of movies to specific pricing plan libraries. This study delves into the cannibalization effect that occurs when a movie transitions from the transactional video-on-demand (TVOD) library to the subscription video-on-demand (SVOD) library. We conducted a comprehensive analysis using user purchasing and viewing data for 1541 movies offered by SK Broadband, South Korea's leading VOD service provider. Our analysis employed propensity score matching and difference-in-difference methodologies. The results of our initial analysis reveal that allocating movies to SVOD leads to an 192% increase in the number of views while simultaneously 52% decreasing TVOD sales. Additionally, we investigate the characteristics of movies that are particularly effective for SVOD servicing. To accomplish this, we scrutinized 236 movies available in SK Broadband's SVOD service using a cost-effectiveness analysis. Our second analysis demonstrates that certain categories of movies, including foreign films, non-G-rated movies, animations, and films not allowed as Download-To-Own (DTO), are more suitable for allocation to SVOD libraries. Furthermore, movies with lower box office viewership numbers exhibit greater success when allocated to SVOD. This study offers insights into the strategic considerations that VOD service providers should embrace, emphasizing a content feature-driven approach to managing pricing plan combinations.

A cultural levy or a digital streaming service tax: New film industry levies conflicting with the EU member states’s bilateral tax treaty obligations and OECD digital tax agreements?

This note highlights the obstacles that the film levy, as a form of financial contributions on video on demand (VoD) service providers under Article 13(2) of the 2018 EU Audiovisual Media Service Directive, may face in a cross-border context from an international tax perspective. In particular, the first obstacle is that the double tax treaties of member states exclude the possibility to levy income taxes on a foreign VoD service provider if it has no fixed and permanent presence, for example, an office, in the country. Second, the new global tax agreement on addressing the tax challenges of digitalization demands its parties (137 countries) to remove all unilateral domestic taxes on all digital services and all companies.

‘If you can’t beat them…’: AVMSD policy-making for Portuguese audiovisual production in the context of the small markets and of multistakeholderism

ABSTRACT The revision of the Audiovisual Media Services Directive (AVMSD) unlocked possibilities to legally frame the video-on-demand (VoD) services in Europe. This process put pressure on national systems and Member States. In Portugal, the initial governmental proposal for implementation did not contemplate a financial contribution from VoD to the national fund that supports Portuguese works. After a period of public consultation, the law included a 1% tax on those services’ revenues. Drawing on the Portuguese case, we discuss and critically analyse the policy-making process of the AVMSD implementation, assessing its outcomes and the perceptions of the stakeholders. Results indicate limitations and fragility of multistakeholderism. We argue that the smallness of Portuguese market is related to the State failing to implement an overarching policy concerning the cycle of film and TV production and to the fact that Portuguese cinema is now mostly left in the hands of VoD service providers.

Fragmentation and Audience Activity on Video-on-Demand Platform: Netflix and the ‘Binge-watching’


 
 
 One of digital transformation of television systems is an interactive service called video-on-demand (VOD). VOD provides full control to its users, by allowing viewers to enjoy, choose, store, and even download the desired audio-visual content anytime and through any electronic communication device. The presence of Netflix and other VOD service providers is transforming people's behavior patterns in watching television. People are beginning to switch to watching audiovisual content and episodes the same televisions or programs known as binge-watching through online streaming. This study focused on the concept of audiences’ activities based on Levy and Windahl’s typology model. The study also explored the motivation that was a part of uses and gratification theory. This new audience habit and motivation were explored by qualitative approach. The interview was conducted to the Netflix subscribers in Jakarta to discover the behavior activities and motivation of binge-watching. The thematic analysis was applied to analyze the process of fragmentation and audience activity that occurs in a very active new media society.
 
 

The characteristics of videos on demand for television programs and the determinants of their viewing patterns: Evidence from the Korean IPTV market

Korea's video-on-demand (VOD) market is led by pay TV service providers, especially internet protocol television (IPTV) service providers, and VODs for television programs (TV-VOD) represent the largest share of VOD in the country. TV-VOD is therefore of strategic importance to providers in terms of their current sales share and future growth. Focusing on the time-shift characteristics of TV-VOD and the serial complementarity of television programs, this study examines how various factors such as the characteristics of paid vs. free VOD services, and the average and variance of broadcast ratings affect VOD viewing patterns. An empirical analysis was conducted using data for TV-VODs of all television programs broadcast by major Korean broadcasters in 2015. The key findings are as follows: (1) There is an inverted-U shape relationship between broadcast ratings and TV-VOD views. This implies that there exists a positive window effect between the original broadcast and TV-VOD, with an exceptional substitution effect in segments with very high ratings. (2) Even if the average ratings are similar, there are more VOD views for programs that have a large fluctuation in ratings between episodes, mainly due to serial complementarity. (3) In terms of the distribution of VOD views over time, the initial concentration is higher in paid VOD packages and dramas, which implies that immediate decay appears for TV-VOD content because of subscriber preferences for novelty and the serial nature of drama shows. The study concludes with various implications for VOD service providers and policy makers.

AutoTune: Game-Based Adaptive Bitrate Streaming in Cloud-Based Hybrid VoD Systems

Hybrid peer-to-peer assisted cloud-based video-on-demand (VoD) systems augment cloud-based VoD systems with P2P networks to improve scalability and save bandwidth costs in the cloud. In these systems, the VoD service provider (e.g., NetFlix) relies on the cloud to deliver videos to users and pays for the cloud bandwidth consumption. The users can download videos from both the cloud and peers in the P2P network. It is important for the VoD service provider to i) minimize the cloud bandwidth consumption, and ii) guarantee users’ satisfaction (i.e., quality-of-experience). Though previous adaptive bitrate streaming (ABR) methods improve video playback smoothness, they cannot achieve these two goals simultaneously. To tackle this challenge, we propose AutoTune, a game-based adaptive bitrate streaming method. In AutoTune, we formulate the bitrate adaptation problem in ABR as a noncooperative Stackelberg game, where VoD service provider and the users are players. The VoD service provider acts as a leader and it decides the VoD service price for users with the objective of minimizing cloud bandwidth consumption while ensuring users’ participation. In response to the VoD service price, the users select video bitrates that lead to maximum utility (defined as a function of its satisfaction minus associated VoD service fee). Finally, the Stackelberg equilibrium is reached in which the cloud bandwidth consumption is minimized while users are satisfied with selected video bitrates. To enhance the performance of AutoTune, we further propose the reputation-based incentive scheme and the popularity-based cache management scheme. Experimental results from the PeerSim simulator and the PlanetLab real-world testbed show that compared to existing methods, AutoTune can provide high user satisfaction and save cloud bandwidth consumption. Also, the proposed enhancement schemes are effective in improving the performance of AutoTune.

Improved Quality Keyframe Selection Method for HD Video

With the widespread use of the Internet, services for providing large-capacity multimedia data such as video-on-demand (VOD) services and video uploading sites have greatly increased. VOD service providers want to be able to provide users with high-quality keyframes of high quality videos within a few minutes after the broadcast ends. However, existing keyframe extraction tends to select keyframes whose quality as a keyframe is insufficiently considered, and it takes a long computation time because it does not consider an HD class image. In this paper, we propose a keyframe selection method that flexibly applies multiple keyframe quality metrics and improves the computation time. The main procedure is as follows. After shot boundary detection is performed, the first frames are extracted as initial keyframes. The user sets evaluation metrics and priorities by considering the genre and attributes of the video. According to the evaluation metrics and the priority, the low-quality keyframe is selected as a replacement target. The replacement target keyframe is replaced with a high-quality frame in the shot. The proposed method was subjectively evaluated by 23 votes. Approximately 45% of the replaced keyframes were improved and about 18% of the replaced keyframes were adversely affected. Also, it took about 10 minutes to complete the summary of one hour video, which resulted in a reduction of more than 44.5% of the execution time.

An empirical study on acceptance of video on demand services in Indian market

The purpose of this study is to devise a suitable business model to exploit the opportunities in the Indian video on demand (VOD) service provider industry. To achieve the desired purpose, the researcher approached the respondents to find out their expectation and perceptions of service quality in VOD services experiences based on the dimensions of the SERVQUAL model. A quantitative research had been carried out for the purpose and this involved some quantitative analyses with the use of statistical tools (descriptive and inferential). The data obtained from the respondents using the VOD services of the services offered by the VOD service providers are in the quantifiable terms so that the required objectives, which were framed for the study, can be achieved statistically with the help of SPSS software version 20.0 for the analysis of the quantifiable data.

Dynamic Strategy Selection based on Evidence Theory. Application on a P2P-VoD system

Peer-to-Peer Video-on-Demand (VoD) systems are rising as a new dominant way to distribute video content over IP networks. While many works addressed the broad area of P2P communications, few work has been focused onto the resource allocation in P2P streaming systems, where the real-time constraint adds another dimension to the problem. Most work on P2P resource allocation solve the problem with static rules strategies are not robust when they are facing to the content demand (popularity) trends. In this paper, we use a dynamic approach, which automatically selects the best strategy on a given time period. With the proposed P2P resource allocation method, a VoD service provider can combine any number of resource allocation strategies and formulate different performance objectives that meet its requirements. As part of our effort to develop algorithms that can be effectively deployed by broadband operators, we developed a full-scale emulator for P2P streaming that can support up to 10,000 peers. The P2P streaming emulator includes a VoD request generators, along with a SuperNode (with backend DataBase) that tracks and allocates network resources. In this paper the goal is to use a low complexity learning approach to enhance the performance of a P2P-VoD system based on evidence theory. The proposed approach is compared to both static and dynamic solutions. The obtained results show that the proposed approach allows to reduce the complexity of selecting resource allocation strategies, while maintaining a low rejection rate.

Analysis and Detection of Fake Views in Online Video Services

Online video-on-demand(VoD) services invariably maintain a view count for each video they serve, and it has become an important currency for various stakeholders, from viewers, to content owners, advertizers, and the online service providers themselves. There is often significant financial incentive to use a robot (or a botnet) to artificially create fake views. How can we detect fake views? Can we detect them (and stop them) efficiently? What is the extent of fake views with current VoD service providers? These are the questions we study in this article. We develop some algorithms and show that they are quite effective for this problem.

Pushing Server Bandwidth Consumption to the Limit: Modeling and Analysis of Peer-Assisted VoD

Recent years have witnessed video-on-demand (VoD) as an efficient means for providing reliable streaming service for Internet users. It is known that peer-assisted VoD systems, such as NetFlix and PPlive, generally incur a lower deployment cost in terms of server bandwidth consumption. However, some fundamental issues still need to be further clarified, particularly for VoD service providers. In particular, how far can we push peer-assisted VoD forward, and at the scale of VoD systems, the maximum reduction of server bandwidth consumption that can be achieved with peer-assisted approaches. In this paper, we provide extensive model analysis to understand the minimum server bandwidth consumption for peer-assisted VoD systems. We first propose a basic model that can optimally schedule user demands at given snapshots. Our model analysis reveals the optimal performance bound and shows that the existing peer-assisted protocols are still far from being optimal. How to push the server bandwidth consumption to the limit remains a big challenge in VoD system design. To approach the optimal bandwidth consumption in real deployment, we further extend our model to a realistic case to capture the peer dynamic across continuous time-slots. The simulation result indicates that the optimal load scheduling problem is still achievable through a dynamic programming algorithm. Its design principle further motivates a fast priority-based algorithm that achieves near-optimal performance. These proposed algorithms can significantly reduce the bandwidth consumption of dedicated VoD servers.

A study of user behavior in online VoD services

A big portion of Internet traffic nowadays is video. A good understanding of user behavior in online Video-on-Demand (VoD) systems can help us design, configure and manage video content distribution. With the help of a major VoD service provider, we conducted a detailed study of user behavior watching streamed videos over the Internet. We engineered the video player at the client side to collect user behavior reports for over 540 million sessions. In order to isolate the possible effect of session quality of experience (QoE) on user behavior, we use only the sessions with perfect QoE, and leave out those sessions with QoE impairments (such as freezes). Our main finding is that users spend a lot of time browsing: viewing part of one video after another, and only occasionally (around 20% of the time) watching a video to its completion. We consider seek (jump to a new position of the video) as a special form of browsing – repeating partial viewing of the same video. Our analysis leads to a user behavior model in which a user transitions through a random number of short views before a longer view, and repeats the process a random number of times. This model can be considered an extension, and a more detailed alternative to the closed queueing network formulation introduced by Wu et al. (2009) [1]. As an application of our user behavior model, we use it to measure video popularity. We study the similarity of our approach to subjective evaluation and simple view count based metric, and conclude our approach gives results closer to subjective evaluation.

BitTorrent-like P2P approaches for VoD: A comparative study

The enormous popularity of Video on Demand (VoD) has attracted substantial research attention into the effective use of peer-to-peer (P2P) architectures to provide solutions at large-scale. In particular, the high efficiency of BitTorrent has inspired many P2P protocols for VoD. However, these protocols use different approaches to adapt the design of Bittorrent to VoD, and in most cases their performance has been evaluated separately and in limited scenarios. As a consequence, the research community still lacks a clear understanding of how these protocols compare against each other and how well each of them would work in real world conditions, where, for instance, peers have heterogeneous bandwidths, may freeride or may be located behind NAT/firewall.In this paper, we propose a simulation based methodology which aims at putting forward a common base for comparing the performance of these different protocols under a wide range of conditions. We show that, despite their considerable differences: (i) existing BitTorrent-like VoD approaches all share some characteristics, such as that their bandwidth reciprocity based methods to incentivize cooperation do not always yield an optimal overall performance. Furthermore, we demonstrate that (ii) in these protocols there is a trade-off between QoS and resilience to freeriding and malicious attacks. We also discover that, (iii) when peers doing streaming coexist with peers doing traditional file transfer, the latter actually benefit from this coexistence, at the expenses of the former. Finally, we show that (iv) early departures of peers from the system do not significantly affect the QoS delivered, while jumping to a different position in the file has a bigger negative impact. Overall, our findings provide important implications for both VoD service providers and future system designers. On the one hand, our results can guide VoD service providers in selecting the most appropriate protocol for a given environment. On the other hand, exposing the flaws of current approaches will help researchers in improving them and/or designing better ones.

Predictive connectionist approach for VoD bandwidth management

This paper describes a step-by-step improvement process of a predictive connectionist module applied in the context of Video on Demand Service Providers (VDSP) applications. The aim at the end is to provide a methodology based on estimation to right size bandwidth usage. The improvement methodology [G. Gomes, Un Modèle Connexioniste pour la Prédiction e l’Optimization de la Bande Passante: Approche Basée sur la Nature Autosimulaire du Trafic Vidéo IP, doctorat thesis presented at Université d’Evry – Val d’Essonne, France (2004)] consists of three phases named examples-based level, modular solution and HVS (Heuristic for Variable Selection) [Y. Bennani, M. Yacoub, Features selection and architecture optimization in connectionist systems, International Journal of Neural Systems 10(5) (2000) 379–395]. In the first phase the “sliding and overlaying” technique is used for enabling the Predictive Connectionist Module (PCM) to be aware of dynamic input. In the second phase a new connectionist network is added to the first one so that the proactive function with prediction could be achieved through a modular architecture. Finally, the HVS method is used in the third phase for identifying optimized connectionist models with higher accuracy. Simulations results are provided which cover learning, prediction and evaluation phases.