Economic Analysis of Reward Advertising

Guo, Hong; Zhao, Xuying; Lin, Hongwei; De, Liu

doi:10.1111/poms.13015

Cited by 33 publications

(17 citation statements)

References 31 publications

(59 reference statements)

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“…Turner et al (2011) study the in-game ad-scheduling problem. Guo et al (2019b) and Sheng et al (2020) study the structure of "rewarded" advertising where players are incentivized to watch ads for in-game rewards. Generally, these rewards come in the form of virtual currencies whose value is fixed by the game designer.…”

Section: Related Workmentioning

confidence: 99%

Optimizing for Strategy Diversity in the Design of Video Games

Hanguir¹,

Ma²,

Ryan³

2021

Preprint

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We consider the problem of designing video games (modeled here by choosing the structure of a linear program solved by players) so that players with different resources play diverse strategies. In particular, game designers hope to avoid scenarios where players use the same "weapons" or "tactics" even as they progress through the game. We model this design question as a choice over the constraint matrix A and cost vector c that seeks to maximize the number of possible supports of unique optimal solutions (what we call loadouts) of Linear Programs max{c x | Ax ≤ b, x ≥ 0} with nonnegative data considered over all resource vectors b.We provide an upper bound on the optimal number of loadouts and provide a family of constructions that have an asymptotically optimal number of loadouts. The upper bound is based on a connection between our problem and the study of triangulations of point sets arising from polyhedral combinatorics, and specifically the combinatorics of the cyclic polytope. Our asymptotically optimal construction also draws inspiration from the properties of the cyclic polytope. Our construction provides practical guidance to game designers seeking to offer a diversity of play for their plays.

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Section: Related Workmentioning

confidence: 99%

Optimizing for Strategy Diversity in the Design of Video Games

Hanguir¹,

Ma²,

Ryan³

2021

Preprint

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“…In [19], a Wi-Fi network provider allows users to either directly pay or watch ads to access the Wi-Fi network. In [20], an app developer offers virtual items, and each app user will either pay or watch ads to obtain them in the equilibrium. In these studies, the fee-based and ad-based services are always substitutes, and each user chooses between these two options.…”

Section: B Related Work 1) Provision Of Fee-based and Ad-based Servicesmentioning

confidence: 99%

“…Therefore, our work studies a novel structure, and derives new insights for the joint provision of fee-based and ad-based services. Furthermore, our work considers the operator's capacity for providing the service and the advertising's wear-out effect, which were not considered in [19] and [20].…”

Section: B Related Work 1) Provision Of Fee-based and Ad-based Servicesmentioning

confidence: 99%

Monetizing Mobile Data via Data Rewards

Wei

Berry

2020

IEEE J. Select. Areas Commun.

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Most mobile network operators generate revenues by directly charging users for data plan subscriptions. Some operators now also offer users data rewards to incentivize them to watch mobile ads, which enables the operators to collect payments from advertisers and create new revenue streams.In this work, we analyze and compare two data rewarding schemes: a Subscription-Aware Rewarding (SAR) scheme and a Subscription-Unaware Rewarding (SUR) scheme. Under the SAR scheme, only the subscribers of the operators' data plans are eligible for the rewards; under the SUR scheme, all users are eligible for the rewards (e.g., the users who do not subscribe to the data plans can still get SIM cards and receive data rewards by watching ads). We model the interactions among an operator, users, and advertisers by a two-stage Stackelberg game, and characterize their equilibrium strategies under both the SAR and SUR schemes. We show that the SAR scheme can lead to more subscriptions and a higher operator revenue from the data market, while the SUR scheme can lead to better ad viewership and a higher operator revenue from the ad market. We further show that the operator's optimal choice between the two schemes is sensitive to the users' data consumption utility function and the operator's network capacity. We provide some counter-intuitive insights. For example, when each user has a logarithmic utility function, the operator should apply the SUR scheme (i.e., reward both subscribers and non-subscribers) if and only if it has a small network capacity.

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“…For the theoretical model, the existing research on in-App advertising is relatively few. Guo et al explore the mechanism of reward advertising in game Apps, and find that only when the marginal revenue of advertising is rapidly decreasing should the number of ads per user be limited [43]. Oh et al propose a new bargaining model (the improved apex game) which analyzes the revenue sharing mechanism of platform and App, and explore the appropriate revenue distribution between platform and App [44].…”

Section: Online Advertisingmentioning

confidence: 99%

Considering In-App Advertising Mode, Platform-App Channel Coordination by a Sustainable Cooperative Advertising Mechanism

Liu

2019

Sustainability

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Regardless of the platform or Apps the number of users is a prerequisite for monetization. Considering in-App advertising, through the optimal control theory, this paper establishes a dynamic advertising strategy model of one platform and n Apps under the decentralized and integrated systems. For each system, the model is constrained by the states dynamics of the number of the platform’s users and App’s users. Our research has obtained some management insights and findings as follows. Firstly, Apps don’t have to worry about the negative effects of in-App advertising caused by other Apps when making advertising decisions. Interestingly, the platform will use the advertising subsidy policy to limit the delivery density of in-App advertising. Specifically, the higher the negative impact of in-App advertising caused by App i, the lower the advertising subsidies provided to App i. Additionally, when determining the advertising subsidy rate, the platform will also comprehensively consider the profitability of Apps and the costs and benefits of in-App advertising. Secondly, our proposed sustainable cooperative advertising mechanism can simultaneously coordinate the Platform-App channel and implement the optimal integrated objective. Finally, we theoretically prove that under some mild conditions, the mechanism can both improve the profits of the platform and n Apps.

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Economic Analysis of Reward Advertising

Cited by 33 publications

References 31 publications

Optimizing for Strategy Diversity in the Design of Video Games

Optimizing for Strategy Diversity in the Design of Video Games

Monetizing Mobile Data via Data Rewards

Considering In-App Advertising Mode, Platform-App Channel Coordination by a Sustainable Cooperative Advertising Mechanism

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