The Welfare Impact of Targeted Advertising Technologies

2022 | Information Systems Research | Citations: 3

Authors: Marotta, Veronica; Wu, Yue; Zhang, Kaifu; Acquisti, Alessandro

Abstract: We analyze the welfare implications of consumer data sharing, and restrictions t ... Expand

Abstract: We analyze the welfare implications of consumer data sharing, and restrictions to that sharing, in the context of online targeted advertising. Targeting technologies offer firms the ability to reach desired audiences through intermediary platforms. The platforms run auctions in real time to display ads on internet sites, leveraging consumers’ personal information collected online to personalize the ads. The online advertising industry posits that targeted advertising benefits advertising firms (that is, merchants who want to target ads to the desired consumers), consumers who see ads for preferred products, and the intermediary platforms that match consumers with firms. However, the claims that targeted advertising benefits all players involved have not been fully vetted in the literature. We develop an analytical model to analyze the economic and welfare implications of targeting technologies for those three players under alternative consumer information regimes. The regimes differ in the type and amount of consumer data available to the intermediary and to the advertising firms, and reflect the presence or absence of technological or regulatory restrictions to personal information flows. We find evidence of incentive misalignment among the players, as the intermediary prefers to share only a subset of consumer information with firms, whereas advertising firms prefer having complete information about the consumers. As such, a strategic intermediary with the ability to control which information is shared during the auction can have an incentive to use only the information that maximizes its payoff, overlooking the interests of both advertising firms and consumers. The information regimes that maximize consumer welfare vastly differ depending on consumers’ heterogeneity along two dimensions: a horizontal dimension, capturing consumer’s heterogeneity in product preferences; and a vertical dimension, capturing consumers’ heterogeneity in purchase power. Consumers prefer none of their personal information to be used for targeting only in limited circumstances. Otherwise, consumers are either indifferent or prefer only specific types of information to be used for targeting. Collapse

Topics: advertising management IS economics consumer surplus privacy marketing management

Methods: archival research mathematical model theory development

Theories: auction theory

Bidding on Keyword Auctions: Advertiser’s Perspective

2021 | International Conference on Information Systems | Citations: 0

Authors: Garg, Anurag; Cho, Soohyun; Aytug, Haldun

Abstract: We formulate an advertiser's bidding problem as a profit maximization problem i ... Expand

Abstract: We formulate an advertiser's bidding problem as a profit maximization problem in which the advertiser has to decide on how much to bid on each keyword subject to a budget, given that she can only observe her bid, her rank, the search frequency and the click frequency. We assume that the other advertisers' bids are i.i.d. random variables. We discuss how to determine a bid that will maximize expected profits when the search traffic for each keyword is generated by an independent Poisson process. We provide a formulation and discuss several properties of the problem. Collapse

Topics: advertising management online learning system marketing management real-time bidding search engine

Methods: computational algorithm stochastic model optimization model

Sustaining a Good Impression: Mechanisms for Selling Partitioned Impressions at Ad Exchanges

2020 | Information Systems Research | Citations: 0

Authors: Mehta, Sameer; Dawande, Milind; Janakiraman, Ganesh; Mookerjee, Vijay

Abstract: In the mobile advertising ecosystem, the role of ad exchanges to match advertise ... Expand

Abstract: In the mobile advertising ecosystem, the role of ad exchanges to match advertisers and publishers has grown significantly over the past few years. At a mobile ad exchange, impressions (i.e., opportunities to display ads) are sold to advertisers in real time through an auction mechanism. The traditional mechanism selects a single advertiser whose ad is displayed over the entire duration of an impression, that is, throughout the user’s visit. We argue that such a mechanism leads to an allocative inefficiency, as displaying only the winning ad throughout the lifetime of an impression precludes the exchange from exploiting the opportunity to obtain additional revenue from advertisers whose willingness to pay becomes higher during the lifetime of that impression. Our goal in this paper is to address this efficiency loss by offering mechanisms in which multiple ads can be displayed sequentially over the lifetime of the impression. We consider two plausible settings—one where each auction is individually rational for the advertisers and one where advertisers are better off relative to the traditional mechanism over the long run—and derive an optimal (i.e., revenue-maximizing for the ad exchange) mechanism for each setting. To efficiently compute the payment rule, the optimal mechanism for the former setting uses randomized payments. Under this mechanism, whereas the ad exchange always benefits relative to the traditional mechanism, the advertisers could either gain or lose—we demonstrate both these possibilities. The optimal mechanism for the latter setting is a “mutually beneficial” mechanism in that it guarantees a win–win for both the parties relative to the traditional mechanism, over the long run. Happily, for both the mechanisms, the allocation of ads and the payments from the advertisers are efficiently computable, thereby making them amenable to real-time bidding. Collapse

Topics: marketing management digital ad exchange mobile application IS economics economic surplus

Methods: descriptive statistic optimization model experiment hazard function

Understanding the Information-Based Transformation of Strategy and Society

2017 | Journal of Management Information Systems | Citations: 0

Authors: Clemons, Eric K.; Dewan, Rajiv M.; Kauffman, Robert J.; Weber, Thomas A.

Abstract: The world economy is undergoing dramatic changes, largely driven by the new avai ... Expand

Abstract: The world economy is undergoing dramatic changes, largely driven by the new availability of fine-grained information. Innovative ways of using data—large and small—have also prompted a rethinking of the boundaries for the combination and use of knowledge. The strategic design of information flows in the economy has the upside of higher economic rents and competitive advantage, as well as the downsides of wealth inequality and abuse of power. This has brought a wide range of regulatory challenges. To understand the nature of these sweeping changes, it is important to examine the new ways information is used, and how information flows can be leveraged to create competitive advantage and dampen competition. The analysis in this article examines four economic entities that produce and consume value, as well as three determinants for the modes of their operations. The economic entities includeconsumers, producers, markets, andsociety, whose interactions are determined byviability, networks, andagency. In this framework, we paint a picture of the transformation of information-based strategy in the future and suggest promising research opportunities. Collapse

Topics: marketing management IS economics economic surplus peer-to-peer model open source

Toward a Digital Attribution Model: Measuring the Impact of Display Advertising on Online Consumer Behavior

2016 | Management Information Systems Quarterly | Citations: 29

Authors: Ghose, Anindya; Todri-Adamopoulos, Vilma

Abstract: The increasing availability of individual-level data has raised the standards fo ... Expand

Abstract: The increasing availability of individual-level data has raised the standards for measurability and accountability in digital advertising. Using a massive individual-level data set, our paper captures the effectiveness of display advertising across a wide range of consumer behaviors. Two unique features of our data set that distinguish this paper from prior work are (1) the information on the actual viewability of impressions as on average 55% of the display ads are not rendered viewable and (2) the duration of exposure to the display advertisements, both at the individual-user level. Employing a quasi-experiment enabled by our setting, we use difference-in-differences and corresponding matching methods as well as instrumental variable techniques to control for unobservable and observable confounders. We empirically demonstrate that mere exposure to display advertising increases users’ propensity to search for the brand and the corresponding product; consumers engage both in active search exerting effort to gather information, and in passive search using information sources that arrive exogenously. We also find statistically and economically significant effects of display advertising on increasing consumers’ propensity to make a purchase. Furthermore, our findings reveal that the longer the duration of exposure to display advertising, the more likely the consumers are to engage in direct search behaviors (e.g., direct visits) rather than indirect ones (e.g., search engine inquiries). We also study the effects of various types of display advertising (e.g., prospecting, retargeting, affiliate targeting, video advertising, etc.) and the different goals they achieve. Our framework for evaluating display advertising effectiveness constitutes a stepping stone toward causally addressing the digital attribution problem. Collapse

Topics: marketing management banner advertising advertising management consumer behavior website

Methods: longitudinal research difference in differences quasi experiment robustness check propensity score method

Auto pricing Strategy for Real time bidding in advertising: A dynamic programming approach

2015 | International Conference on Information Systems | Citations: 0

Authors: Adikari, Shalinda; Dutta, Kaushik

Abstract: Unlike the traditional advertising practices, in the process of Real time biddin ... Expand

Abstract: Unlike the traditional advertising practices, in the process of Real time bidding (RTB), the impressions of a mobile application or a website are mapped to a particular advertiser through a real time auction, which triggers after an application is launched. As one of the key components of the RTB ecosystem, demand side platform (DSP) furnishes the advertisers a full pledge window to bid for available impressions. Due to fast growing market of mobile applications and websites, the selection of the most pertinent target audience to a particular advertiser, is not a simple human mediated process. Therefore, we propose an Auto Pricing Strategy (APS) approach to determine the applications to bid for and their respective bid prices from the advertisement agency perspective. We applied the APS on a real RTB bidding data and demonstrated how it outperforms the existing RTB approaches with a higher conversion rate for the same target spend. Collapse

Topics: mobile application Java advertising management price management mobile system

Methods: dynamic programming literature study computational algorithm optimization model mathematical model

Real Time Bidding in Online Digital Advertisement

2015 | DESRIST | Citations: 0

Authors: Adikari, Shalinda; Dutta, Kaushik

Abstract: Real time bidding (RTB) is becoming the key to target marketing where it could o ... Expand

Abstract: Real time bidding (RTB) is becoming the key to target marketing where it could optimize advertiser expectations drastically. Not like the conventional digital advertising, in the process of RTB, the impressions of a mobile application or a website are mapped to a particular advertiser through a bidding process which triggers and held for a few milliseconds after an application is launched. To carry out the bidding process a special platform called demand side platform (DSP) provides support to advertisers to bid for available impressions on their behalf. This process has turned into a complex mission as there are many applications/websites that have come into the market. Mapping them to advertisers’ target audience, and bidding appropriately for them is not a simple human mediated process. The complexity and the dynamic nature in the RTB process make it difficult to apply forecasting strategies effectively and efficiently. In this paper we propose an autonomous and a dynamic strategy for bidding decisions such as bidding price. We applied our proposed approach on a real RTB bidding data and demonstrated that our approach can achieve higher conversion rate with the target spend for a DSP. Collapse

Topics: Java advertising management mobile system mobile application programming language

Methods: dynamic programming longitudinal research autoregressive integrated moving average time series analysis computational algorithm

The Welfare and Allocative Impact of Targeted Advertising

2015 | International Conference on Information Systems | Citations: 0

Authors: Marotta, Veronica; Zhang, Kaifu; Acquisti, Alessandro

Abstract: We investigate the welfare implications and the allocative effects of different ... Expand

Abstract: We investigate the welfare implications and the allocative effects of different consumer data-handling regimes in online targeted advertising. We develop a three-players model that includes firms, consumers, and an intermediary - the ad exchange – and analyze three scenarios that differ in the type of consumers' data available during the targeting: a case in which only the horizontal information (consumers' brand preferences) is available; a case in which only vertical information (consumers' purchasing power) is available; a case in which both pieces of information are available. We find that there exist conditions under which the intermediary obtains the highest proportion of benefits from targeting and, in general, the intermediary's incentives regarding the type of consumer information to be used for targeting are misaligned with the incentives of firms and/or consumers. Furthermore, consumers' surplus from targeting is higher when only specific types of personal information are made available during the targeting process. Collapse

Topics: marketing management digital ad exchange advertising management IS economics consumer surplus

Methods: simulation economic model mathematical model literature study archival research

Theories: auction theory

Finding Similar Mobile Consumers with a Privacy-Friendly Geosocial Design

2015 | Information Systems Research | Citations: 0

Authors: Provost, Foster; Martens, David; Murray, Alan

Abstract: This paper focuses on finding the same and similar users based on location-visit ... Expand

Abstract: This paper focuses on finding the same and similar users based on location-visitation data in a mobile environment. We propose a new design that uses consumer-location data from mobile devices (smartphones, smart pads, laptops, etc.) to build a “geosimilarity network” among users. The geosimilarity network (GSN) could be used for a variety of analytics-driven applications, such as targeting advertisements to the same user on different devices or to users with similar tastes, and to improve online interactions by selecting users with similar tastes. The basic idea is that two devices are similar, and thereby connected in the GSN, when they share at least one visited location. They are more similar as they visit more shared locations and as the locations they share are visited by fewer people. This paper first introduces the main ideas and ties them to theory and related work. It next introduces a specific design for selecting entities with similar location distributions, the results of which are shown using real mobile location data across seven ad exchanges. We focus on two high-level questions: (1) Does geosimilarity allow us to find different entities corresponding to the same individual, for example, as seen through different bidding systems? And (2) do entities linked by similarities in local mobile behavior show similar interests, as measured by visits to particular publishers? The results show positive results for both. Specifically, for (1), even with the data sample’s limited observability, 70%–80% of the time the same individual is connected to herself in the GSN. For (2), the GSN neighbors of visitors to a wide variety of publishers are substantially more likely also to visit those same publishers. Highly similar GSN neighbors show very substantial lift. Collapse

Topics: mobile system advertising management mobile advertising mobile application marketing management

Methods: machine learning literature study digital trace data experiment

Understanding overbidding behavior in C2C auctions: an escalation theory perspective

2012 | European Journal of Information Systems | Citations: 10

Authors: Park, Sang Cheol; Keil, Mark; Kim, Jong UK; Bock, Gee-Woo

Abstract: With millions of online auctions per day, sites such as eBay have revolutionized ... Expand

Abstract: With millions of online auctions per day, sites such as eBay have revolutionized how consumers buy and sell goods. Despite the benefits associated with online consumer-to-consumer (C2C) auctions, there can be drawbacks. Consumers who purchase goods in online auctions may get caught up in auction fever, causing them to engage in overbidding, and sometimes leading to what has been referred to as the winner's curse. While several theoretical explanations have been proposed to explain overbidding behavior (OB), there has been little empirical work in this area. Drawing on escalation theory, this study develops and tests a model of the OB exhibited by individuals in online auction settings. Our model posits that certain escalation drivers such as sunk cost (SC), the completion effect (CE), and self-justification affect an individual's willingness to continue bidding (WCB) which, in turn, influences OB. Survey data collected from 250 online auction participants were used to test the model using partial least squares analysis. SC and CE were found to have significant impacts on OB that were either partially or fully mediated by WCB. We also found that competition intensity moderates the relationship between willingness to continue and OB such that when competition is more intense, the relationship becomes even stronger. The implications of these findings for both research and practice are discussed. Collapse

Topics: online auction marketing management real-time bidding accounting technology adoption

Methods: survey partial least squares regression data transformation factor analysis regression analysis method

Theories: escalation theory self justification theory prospect theory cognitive dissonance theory