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Legal and Ethical Challenges of Online Behavioral Targeting in Advertising

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Legal and Ethical Challenges of Online Behavioral Targeting in Advertising

Abstract

Online behavioral targeting (OBT), the tracking of a consumer's online activities in order to develop a behavioral profile of the consumer, is a rapidly growing technique that enables advertisers to deliver relevant messages. While OBT provides many advantages to shoppers and advertisers alike, the practice has the technological potential to violate consumers’ privacy rights to a dangerous and unprecedented degree. Still, OBT is poorly understood by most consumers, is often nontransparent and deceptive, and in many cases does not even provide a reasonable chance to opt out. Due to OBT's relative newness, few laws, regulations, and policies, as well as in-depth ethical analyses of the practice, exist. Actions by the Federal Trade Commission (FTC), however, provide a notable exception. In a series of reports, in particular since 2009, the agency has engaged in dialogs with various stakeholders about OBT and the dangers it poses to consumers. Its efforts have also included legal enforcement activities. Within the context of these developments our article presents the evolution of the broader legal environment, including an ethical analysis of the FTC's efforts. Our objective is to shed light on the issue from a normative perspective and to assist online advertisers as well as regulators searching for guidelines and policies on how to use OBT in a responsible manner.
... Prior research suggests that consumer privacy subversion behavior can be overcome by organizational privacy-enhancing factors (Aguirre et al., 2015;Foxman & Kilcoyne, 1993;Martin & Murphy, 2017;Nill & Aalberts, 2014). Building on a justice-based perspective, research has noted that firms can increase consumers' perceived control over their information, thus increasing their willingness to share (Culnan & Bies, 2003;Etzioni, 2019;Schmidt et al., 2020). ...
... Research looking at individual dimensions of consumer privacy concerns (such as perceived lack of information control and a lack of firm trust) and their resulting levels in willingness to share their personal information, suggests that by controlling and manipulating these, organizations are able to reduce consumer privacy concern and subversion behavior, and increase consumer data sharing (e.g., Aguirre et al., 2015;Hong et al., 2019;Martin & Murphy, 2017;Nill & Aalberts, 2014). Similarly, studies looking at adapting organizational dimensions, that is, firm transparency, personalization of services through technical solutions (opt-in technology), or environmental dimensions, such as the display of a privacy notice), suggest that using these dimensions can reduce privacy concerns and subversion behavior, by allowing for greater perceived data control (Aguirre et al., 2015;Hong et al., 2019;Martin, 2015;Schmidt et al., 2020). ...
... Prior studies show that antecedents of consumer privacy concerns (such as perceived lack of information control and a lack of firm trust), impact on consumers' willingness to share their personal information. By controlling and manipulating antecedents of consumer privacy concerns, organizations are able to reduce consumer privacy concern and increase consumer data sharing (e.g., Aguirre et al., 2015;Foxman & Kilcoyne, 1993;Hong et al., 2019;Martin & Murphy, 2017;Nill & Aalberts, 2014 Dutton, 2017) has, thus far, only focused the impact of organizational care on employee commitment (Lilius et al., 2012), work-based anxiety (Kahn, 2001), satisfaction, and employee willingness to participate in organizational innovations (Carmeli et al., 2017;Lawrence & Maitlis, 2012 ...
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With an ever-increasing hunger for consumer data by firms, and despite many organizational efforts to reduce consumer privacy concerns, consumer subversion behavior towards information provision persists. Organizational privacy ethical care, an organizational behavior that goes beyond legislative action and moral codes, provides a new theory of how to overcome this issue. Across three studies, we develop and test theory which suggests an organizational ethic of care approach to privacy will have a positive impact on reducing consumer subversion behavior (i.e. increase consumers' willingness to share information and the accuracy of information they share). The correlational and causal results indicate that perceived organizational privacy ethical care is a positive driver of the amount and the accuracy of information consumers are willing to share with firms. The results also suggest partial support that this relationship is mediated through perceived information control and trust towards the organization. Thus, we provide some support for a better corporate approach to privacy, beyond previously suggested legislative and social responsibility standards, which allows for the reduction of consumer privacy concerns and subsequent subversion behaviors.
... One dominant targeting technology is online behavior tracking, which embeds third-party cookie files on users' browsers and tracks individual users' online behaviors. Advertisers analyze the tracking data to accurately identify individuals' interests and then deliver the most relevant ad messages to each individual (Ham 2017;Nill and Aalberts 2014). Consequently, consumers' video-advertising experiences could be elevated by serving relevant ad messages to individuals, inducing them to be highly involved in ad messages (Ham 2017;Ham and Nelson 2016). ...
... Our study aimed to examine the potential benefit of using an ad-choice option in mid-roll video advertising that significantly interrupts users' video-watching experience. We also attempted to test the moderation role of ad involvement on the effect of ad choice, given the fact that most digital advertising is now being delivered using behavior-tracking technology, which increases consumers' ad involvement (Ham 2017;Nill and Aalberts 2014). We employed ideas from PRT and ELM to discern the mechanism underlying the proposed relationships. ...
... The targeted advertising of mobile users is achieved by online behavioral targeting (OBT), which is a technique that precisely delivers customized information to mobile users. OBT first collects users' online behaviors, such as web page visits, keyword searching, and shopping records (Li and Nill, 2020), then recommended personalized advertisements based on OBT's algorithm will be delivered to specified mobile users as a result of their behavioral records (Nill and Aalberts, 2014). For example, TikTok collects and analyses users' interactive behaviors, such as video 'likes' and 'shares', followed accounts, comments, and created content, then its recommendation system will deliver short new videos based on interactions (TikTok, 2020). ...
... Nill and Aalberts (2014) define BTA as a technology that serves consumers with more precise advertisements by tracking and analyzing users' browsing history. The data collected by BTA providers typically includes the visit history of the website, keyword searches, online shopping records, geographic location, and video watching records (Nill and Aalberts, 2014). Halkola (2017) argues that BTA is more effective in influencing users' purchasing decisions than traditional advertisements when online shopping, and consumers' click-through rate is enhanced via the combination of behavioral and contextual targeting . ...
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The study investigates the antecedents that affect consumers’ acceptance of behavioral targeting advertising (BTA) services by extending technology acceptance Model 2 (TAM2) with perceived risk. A two-stage PLS-SEM-artificial-neural-network (ANN) predictive analytic approach was adopted to analyze the collected data, of which PLS-SEM was first applied to test the hypotheses, followed by the ANN technique to detect the nonlinear effect on the model. A total of 475 usable self-administered questionnaires were collected, and the results showed that only the relationship between the image and perceived usefulness (PU) was not supported. As per Model B, the ranking of subjective norms (SN) and PU between the PLS-SEM and ANN model does not match each other, implying that hidden attributes may exist in affecting the role of SN and PU under the practical context of which the relationship between variables may not fully be explained by a linear perspective. The finding is beneficial for advertising practitioners and software developers who wish to optimize BTA results. Theoretically, the study extends TAM2 in the context of advertising, which is a neglected research area. Methodologically, the study is the first to apply TAM2 using the hybrid PLS-SEM-ANN in the context of advertising.
... Findings have also been largely inconsistent, suggesting chatbot advertising can lead to both positive and negative consumer evaluations and behaviors; some consumers appreciate the various benefits of personalized content, but others are more conscious of risks associated with disclosing personal information. For instance, consumers have shown to like advertising that uses detailed personal information (White et al. 2008;Zarouali et al. 2019) because of the efficiency associated with being able to easily find the right products and services (Nill and Aalberts 2014;Tucker 2014). Furthermore chatbots' personalized products and services increase brand loyalty (Ho, Hancock, and Miner 2018;Milfeld and Haley 2022). ...
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In this article, the authors examine the effect of regulatory focus and privacy concerns on consumers’ responses to highly personalized chatbot advertising. Findings from two experimental studies indicate that predominantly promotion-focused consumers are more receptive and respond more favorably to highly personalized chatbot advertising because they attend more to benefits they may gain from disclosing personal information. In contrast, consumers who are predominantly prevention focused are more attentive to the risks involved and feel unfavorably toward highly personalized chatbot advertising. In addition, consumers who are highly concerned about privacy disdain highly personalized ads, regardless of regulatory focus. Risk-benefit perceptions are shown to mediate interactions of ad personalization, regulatory focus, and privacy concerns.
...  Individual cultural values (Liu, Marchewka, & Ku, 2004)  Personality traits (Junglas, Johnson, & Spitzmüller, 2008)  Demographic characteristics (Cho, Rivera-Sánchez, & Lim, 2009;Malhotra, Kim, & Agarwal, 2004)  Personal expertise in using the internet (Singh & Hill, 2003)  Length, frequency, and sophistication in internet usage (Bellman, Johnson, Kobrin, & Lohse, 2004)  Nature and sensitivity of the information collected (Yang and Wang, 2009)  Self-efficacy and psychological need for privacy (Yao, Rice, & Wallis, 2007)  Familiarity with the data collection policies of firms (Van Slyke, Shim, Johnson, & Jiang, 2006)  Perceived vulnerability (Dinev & Hart, 2004)  Prior negative experience (Li, 2011)  Privacy disposition (Li, 2014)  Perceived severity of privacy breach (Mohamed & Ahmad, 2012)  Identity theft (Saunders & Zucker, 1999)  Social awareness about issues involving internet usage (Dinev & Hart, 2005)  Information disclosure practices of firms (Casadesus-Masanell & Hervas-Drane, 2015)  Ethics and privacy practices of firms (Culnan & Williams, 2009) Privacy concerns could lead to many consequences such as trust deficit (Naqvi & Al-Shihi, 2014), security threats (Wu, Huang, Yen, & Popova, 2012), unwillingness to provide personal information (Nam, Song, Park, & Ik, 2006), providing only limited and anonymous, or false personal information (Dinev & Hart, 2006), reduced usage intentions (Milne & Boza, 1999), legal and ethical challenges for firms (Nill and Aalberts, 2014), adoption of privacy protection technologies , and other consequences related to adverse customer reactions such as refusal to purchase, negative word of mouth, switchover intentions, and complaints (Thambusamy, Church, Nemati, & Barrick, 2010), which affect the profitability of the firm. ...
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This paper examined the formation of litigation intentions among e-commerce customers under the privacy breach due to the influence of antecedents such as vulnerability, social risk, privacy dispositions, effectiveness privacy policy, awareness of data management and moderators like privacy control beliefs, efficacy in coping and litigation complexity. A structural equation modelling analysis revealed that reasons for privacy breach perceptions are customer dispositions about privacy, anticipated vulnerability due to privacy breach, and social risk related to personal information disclosure. The control beliefs and coping skills of customers under privacy threat positively moderates litigation intentions. Similarly, the task complexity of litigation significantly reduces litigation intentions.
... That is, information is collected about the individual consumer's internet activities in order to get a broad picture. Once analyzed, the collected information enables advertisers to deliver relevant and targeted messages (Nill & Aalberts, 2014). This practice is becoming a mainstream marketing practice as the industry claims that it enhances ad effectiveness (Aalberts et al., 2016;Aguirre et al., 2015). ...
... Interaction with algorithms is becoming a common part of consumers' experience with digital media. To boost consumer engagement, digital platforms (e.g., Facebook, Google, and Netflix) increasingly use online behavioral targeting (OBT)-the practice of delivering relevant, personalized messages to consumers based on the analysis of their online behaviors and sometimes other available metrics such as demographics and geographic data (Boerman et al., 2017;Nill & Aalberts, 2014). Essential to this practice is using machine learning algorithms to monitor consumers and make inferences about their characteristics and preferences, subjecting consumers to the algorithms' "gaze," an act involving not only seeing but also interpreting (Lacan, 1977). ...
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