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As mobile devices have become a necessity in our daily lives, mobile advertising is also prevalent. Accordingly, it is critical for practitioners to understand how consumers visually attend to mobile advertisements. One popular way of doing so is via eye-tracking methodology. However, scant eye-tracking research exists in mobile settings due to technical challenges, e.g., cumbersome data annotation. To tackle these challenges, the authors propose an object-detection machine learning (ML) algorithm—You Only Look Once (YOLO) v3—to analyze eye-tracking videos automatically. Moreover, we extend the original YOLO v3 model by developing a novel algorithm to optimize the analysis of eye-tracking data collected from mobile devices. Through a lab experiment, we investigate how two types of ad elements (i.e., textual vs. pictorial) and shopping devices (i.e., mobile vs. PC) affect consumers' visual attention. Our findings suggest that (1) textual ad elements receive more attention than pictorial ones, and such differences are more pronounced in ads on mobile devices than those on PCs; and (2) mobile ads receive less attention than PC ads. Our findings provide managerial insights into developing effective digital advertising strategies to improve consumers' visual attention in online and mobile advertisements. [ABSTRACT FROM AUTHOR]

Although in-stream video advertising is common, its effects on advertisement (ad) information encoding remain unclear. We investigated the effects of in-stream video advertising by comparing two groups: those watching mid-roll (between the program) ads and those watching pre- and post-roll (before and after the program, respectively) ads. To elucidate how advertising content is encoded in the context of in-stream video advertising, we integrated two theoretical frameworks: the negative emotion–memory model (NEMM) and the limited capacity model of motivated–mediated message processing (LC4MP). We used electroencephalography (EEG) to assess negative emotions and bottom-up attention during advertisement viewing. The findings indicate that the first mid-roll ad induced negative emotions, but these feelings were attenuated during subsequent mid-rolls. In addition, negative emotions induced by mid-roll ads attenuated the role of bottom-up attention in the information encoding process. However, the pre- and post-roll ads were not accompanied by negative emotions; thus, bottom-up attention played a major role in the information encoding of these ads. The results also suggest that despite the negative emotions experienced during mid-rolls, such transient negative reactions did not affect purchase intention for the advertised products. [ABSTRACT FROM AUTHOR]

In realizing that consumers regularly straddle the work–life interface, some companies position their products according to their ability to address work and life needs together, then communicate this offering to consumers. Whether using a work–life positioning strategy is effective remains unclear , however. If this strategy signals work–life enrichment, it should increase consumers' interest, but only if the product demands few resources from consumers. If the product instead demands substantial resources, a work–life positioning might inadvertently trigger perceptions of work–life conflict and lower consumers' interest. To test these predictions, the authors partnered with three businesses to advertise their products, which impose varying resource demands, on social media using content that highlights the work–life interface or not. Analyses of ad click data support the predictions: Work–life ads are less effective than single-domain (work or life) ads if the advertising involves resource-demanding products, but they are more effective if it pertains to resource-undemanding products. Furthermore, the effects are stronger among consumer segments that experience more work–life conflict in general. With this initial application of work–life theory to a marketing context, this article offers relevant insights for both research and practice. [ABSTRACT FROM AUTHOR]

Although in-feed advertising is popular on mainstream platforms, academic research on it is limited. Platforms typically deliver organic content through two methods: subscription by users or recommendation by artificial intelligence. However, little is known about the ad performance between these two channels. This research examines how the performance of in-feed ads, in terms of click-through rates and conversion rates, differs between subscription and recommendation channels and whether these effects are mediated by ad intrusiveness and moderated by ad attributes. Two ad attributes are investigated: ad appeal (informational vs. emotional) and ad link (direct vs. indirect). Study 1 finds that the recommendation channel generates higher click-through rates but lower conversion rates than the subscription channel, and these effects are amplified by informational ad appeal and direct ad links. Study 2 explores channel differences, revealing that the recommendation channel yields less source credibility and content control, reducing consumer engagement with organic content. Studies 3 and 4 validate the mediating role of ad intrusiveness and rule out ad recognition as an alternative explanation. Study 5 uses eye-tracking technology to show that the recommendation channel has lower content engagement, lower ad intrusiveness, and greater ad interest. [ABSTRACT FROM AUTHOR]

The European Union's General Data Protection Regulation (GDPR), with its explicit consent requirement, may restrict the use of personal data and shake the foundations of online advertising. The ad industry has predicted drastic loss of revenue from GDPR compliance and has been seeking alternative ways of targeting. Taking advantage of an event created by an ad publisher's request for explicit consent from users with European Union IP addresses, the authors find that for a publisher that uses a pay-per-click model, has the capacity to leverage both user behavior and web page content information for advertising, and observes high consent rates, GDPR compliance leads to modest negative effects on ad performance, bid prices, and ad revenue. The changes in ad metrics can be explained by temporal variations in consent rates. The impact is most pronounced for travel and financial services advertisers and least pronounced for retail and consumer packaged goods advertisers. The authors further find that web page context can compensate for the loss of access to users' personal data, as the GDPR's negative impact is less pronounced when ads are posted on web pages presenting relevant content. The results suggest that publishers and advertisers should leverage targeting based on web page content after the GDPR's rollout. [ABSTRACT FROM AUTHOR]

Using an experimental tool that tracks viewers' real-time ad-skipping behavior, the current research tested when and why a highly arousing emotional appeal ad that induces a set of complex discrete emotions can reduce the ad-skipping rate on social media platforms such as YouTube. Across three experiments, we showed the following results. First, the ad-skipping rate of emotional appeal ads was lower among consumers who had the goal of watching emotional (versus informational) videos. Second, ad-elicited empathy mediated this effect. Third, the effects of the emotional appeal ad on ad-skipping behaviors were contingent upon consumers' predisposition to approach emotional experiences. Among consumers who were seeking emotional experiences, higher levels of empathy resulted in lower ad-skipping rates and longer ad-viewing duration when the emotional appeal of the ad matched with the emotional goal of video watching; in contrast, among consumers who were not seeking emotional experiences, the opposite effect was found. [ABSTRACT FROM AUTHOR]

Advertising to a consumer provides potentially useful information to the consumer and moves them along the purchase journey, and tracking the consumer's online activities enables an advertiser to infer the consumer's purchase journey state and target repeat ads accordingly. However, many consumers dislike being tracked, and, furthermore, repeat advertising may lead to ad wearout. The authors develop a model with consumers, an advertiser, and an ad network to investigate, under the preceding considerations, the impact of regulations that endow consumers with the choice to opt in to or out of online tracking. The authors find that, if ad effectiveness is intermediate, opting in to tracking decreases ad repetition; otherwise, opting in increases ad repetition. To make an opt-in decision, a consumer weighs the cost of ad wearout from repeat ads against the benefit of obtaining potentially relevant product information from them, and the consumer opts in to tracking if either ad effectiveness is intermediate or sensitivity to ad wearout is low. This opt-in pattern creates counterintuitive implications; for instance, higher ad effectiveness, even though it implies higher ad valuation for the advertiser, may reduce repeat ads and the ad network's profit. Under regulation that requires consumer consent for tracking, the results shed light on when and why consumers give such consent, and provide useful insights for practitioners and policy makers. [ABSTRACT FROM AUTHOR]

Sourcing algorithms are technologies used in online platforms to identify, screen, and inform potential applicants about job openings. The popularity of such technologies is rapidly increasing due to their pervasiveness in online advertising and beliefs that sourcing algorithms can decrease time to hire while improving the quality of new hires. What is little known, however, are their potential risks: sourcing algorithms could (intentionally or unintentionally) encode or exacerbate occupational demographic disparities, thereby hindering organizational diversity and/or decreasing the effectiveness of online hiring practices. Because sourcing algorithms identify and screen potential job applicants before they are made aware of employment opportunities, methods for evaluating discrimination in hiring which focus solely on job applicants (e.g., adverse impact ratio), may fail to detect the effects of discriminatory sourcing algorithms. Thus, we propose an expanded model of the employee hiring process to take into account the role of sourcing algorithms. Based on empirical approximations, we conducted a Monte Carlo simulation study to examine the magnitude and nature of sourcing algorithms' influence on hiring outcomes. Our findings suggest that sourcing algorithms could hinder the diversity of new hires while misleadingly suggesting positive diversity outcomes in personnel selection. We provide practical guidance for the use of sourcing algorithms and call for a systematic re‐examination of how to evaluate selection system fairness in the era of algorithmic recruitment. [ABSTRACT FROM AUTHOR]

Against the backdrop of calls for greater platform transparency, this exploratory article investigates Meta's 'Why Am I Seeing This Ad' (WAIST) feature, which is positioned as a consumer-level explanation of Meta's advertising model. Drawing on our own walkthroughs of Facebook and Instagram and data from the Australian Ad Observatory, we find the feature falls short in two ways. First, the explanations do not always align with how the system and its audience-building tools are sold to and used by advertisers. Second, the feature is focused narrowly on single ads and individual users, doing nothing to generate understanding of the patterns and sequences of targeted advertising in relation to other users or over time. We propose both platform practices and independent research strategies that could help to fill this gap between individual explanations, population-level patterns of targeted online advertising and the societal issues associated with it. [ABSTRACT FROM AUTHOR]

Sequential recommendation frames the recommendation task as a next‐item prediction problem, where the model is trained to predict the next item given a user behavior sequence. While recent research has made significant progress in developing advanced models for this task, there exists a notable gap in the exploration of subsequences and the predictability inherent in user behavior sequences. This oversight can lead models to recall inconsequential sequential patterns, adversely affecting recommendation quality. In this paper, we introduce a novel approach to augmenting sequential recommendation by integrating predictability awareness into subsequence modeling. Our method begins by discerning the predictability of target items; those easily predicted often align with the preceding subsequence, while those that are hard to predict typically indicate transitions to other subsequences. Leveraging this predictability information, we enhance the discovery of meaningful subsequences within individual user behavior sequences. Evaluation of four benchmark data sets using various state‐of‐the‐art sequential models illustrates the efficacy of our approach in enhancing recommendation performance. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

On January 1, 2017, Philadelphia implemented a beverage excise tax. The study's objective was to determine whether beverage advertising expenditures and the number of beverage ads purchased changed in Philadelphia compared to Baltimore because of this tax. Monthly beverage ad expenditures and the number of beverage ads purchased by brand from January 2016 through December 2019 were obtained. Ads were coded as being for taxed or not taxed beverages and analyzed in 2023. The primary outcomes were quarterly taxed beverage ad expenditures and number of ads purchased. A controlled interrupted time series design on segmented linear regression models was used. Models (aggregated and stratified by internet, spot TV, and local radio) compared whether levels and trends in the outcomes changed from pre- to post-tax in Philadelphia compared to Baltimore. There were no significant differences in taxed beverage advertising expenditures between Philadelphia and Baltimore for trends pretax, at implementation, or post-tax. There were 0.13 (95% CI: −0.25, −0.003) fewer quarterly taxed beverage ads purchased per 100 households in Philadelphia versus Baltimore at baseline. Among internet advertising, there were 0.42 (95% CI: −0.77, −0.06) fewer quarterly taxed beverage ads purchased per 100 households in Philadelphia versus Baltimore immediately post-tax. For spot TV ads, the percentage of taxed beverages ads purchased per quarter was greater at baseline in Philadelphia by 28.0 percentage points (95% CI: 1.9, 54.1). This study found little evidence of changes in mass media advertising on the examined platforms between 2016 and 2019 due to the Philadelphia beverage tax. [ABSTRACT FROM AUTHOR]

The paper analysed cultural differences to explain ad engagement (AE) among Facebook users in India and Tanzania. It uses Hofstede's model and theory of planned behaviour to examine the differences in cultural values and AE between the two countries and to evaluate AE and its determinants. The paper used a cross-sectional descriptive design to collect data from 700 students from Indian and Tanzanian universities by using self-administered questionnaires. Data were analysed by using an independent sample t -test, Spearman's Rank correlation coefficient, Multi-group differences test, confirmatory factor analysis (CFA) and structural equation modelling (SEM) methods. These analyses were run in SPSS 20.0 and AMOS 24. The paper confirms cultural convergence for individualism and masculinity values, but significant differences in indulgence and uncertainty avoidance across India and Tanzania were observed. Also, significant differences in AE across the two countries were observed. Moreover, we found that attitude to Facebook advertising, subjective norms and perceived herd behaviour positively determines AE, while perceived intrusiveness determines AE negatively. Indulgence has an insignificant relationship with AE while other cultural values have a significant positive relationship. The paper adopted purposive sampling and limited the scope to Facebook, thus, the findings may lack generalisability to other social media platforms. Hence, multiple-platform ad engagement research is encouraged. The marketing implications from this paper include the development of AE strategies, designing culturally relevant ad content and themes and ad targeting. This paper contributes to the understanding of the relationship between cultural values and users' engagement with Facebook advertising. [ABSTRACT FROM AUTHOR]

In the digital era, online advertising fraud unfortunately undermines advertising and pricing cooperation in supply chains. In order to improve advertising effectiveness in a supply chain with a manufacturer and a retailer, this paper proposes three coordination mechanisms: cooperative advertising quality improvement (CQ), quality discount (QD) and a combination of the two (CQD). We derive the equilibrium advertising and pricing decisions in closed form under each mechanism. We show that improving advertising quality is always profitable for the two members, and that with QD included (either QD or CQD) can better coordinate the supply chain than CQ alone. However, the integration of a CQ and QD scheme is not always effective due to their interaction effects. Each mechanism can be achieved as an equilibrium strategy for supply chain members depending on their advertising effects. These insights offer theoretical evidence for the design of a supply chain coordination strategy. [ABSTRACT FROM AUTHOR]

Background: The frequency of health-related information seeking on the internet and social media platforms has increased remarkably. Thus, the ability to understand and select accurate health-related information online, known as EHealth literacy, is crucial for the population. Therefore, this study aimed to evaluate how eHealth literacy influences the critical analysis of oral health-related information obtained from the Internet and its influence on oral health-related behaviors. Methods: A cross-sectional online study was conducted with 418 Brazilian adults who responded to the eHEALS questionnaire, with questions regarding the influence of online information on oral health decisions. Socioeconomic and demographic characteristics were also collected. Results: The mean eHEALS score was 27.85 (± 8.13), with a range spanning from 8 to 40 points. Participants with higher eHEALS scores reported using social media platforms to seek for dentists and to acque information about symptoms, diagnoses, and treatments. Furthermore, this group tended not to disregard professional health recommendations based on Internet information and abstained from utilizing products promoted by digital influencers. In multivariate models, increased eHEALS scores were associated with reduced consumption of products endorsed by digital influencers. Conclusions: The findings from this study suggest that individuals with higher scores on the eHealth literacy questionnaire often conduct research on their health status and seek for health care providers on the Internet. Moreover, these individuals were less likely to be influenced by digital influencers. [ABSTRACT FROM AUTHOR]

Without considering the background to the changed reading behaviour, political demands and decisions regarding the development of reading culture and therefore the development of libraries remain undetermined. This essay attempts to determine the most important influencing factors and control variables in a tour d'horizon. Due to the deep roots of Western democracies in the reading culture, things get very political. But isn't it one of the librarians' tasks to reflect on these dependencies, to draw public attention to them, and adjust the services offered by their institutions? [ABSTRACT FROM AUTHOR]

Introduction Methods Results Discussion and Conclusions It is broadly recognised that chemsex is more prevalent among men who have sex with men, but little is known about chemsex in the context of commercial sexual encounters between men. This study investigates sex worker advertising characteristics and their advertised willingness to engage in chemsex with clients.Data were web scraped from the profiles of US‐based male sex workers (N = 3773) advertising services on an internet advertising platform in February 2021. This study describes the association between chemsex advertising and advertised age, race/ethnicity, sexual orientation, encounter type and COVID‐19 acknowledgement.28.5% of sex workers (n = 1077) advertised chemsex, 64.7% of whom were 25–34 years‐old (n = 697). The odds of chemsex advertising increased between ages 21–24 (aOR = 1.20, 95% CI 1.09–1.32) and declined among sex workers over 35 years‐old (aOR = 0.97, 95% CI 0.95–1.00). Sex workers advertising as bisexual were more likely to advertise chemsex than those identifying as gay (aOR = 1.38, 95% CI 1.18–1.63). Sex workers acknowledging COVID‐19 were less likely to advertise chemsex compared to those who did not (aOR = 0.65, 95% CI 0.48–0.89). Encounter type was associated with chemsex advertising among sex workers in this sample; sex workers not offering the “boyfriend experience” were more than 50% less likely to advertise chemsex than those who did offer the boyfriend experience (aOR = 0.47, 95% CI 0.36–0.61).Chemsex advertising in this population is likely influenced by multiple sociodemographic and occupational characteristics. Identifying sex workers likely to engage in chemsex based on advertising data could inform targeted education and harm‐reduction campaigns in this population. [ABSTRACT FROM AUTHOR]

Companies spend their social media advertising on several platforms, including Facebook, Instagram, TikTok, and Xiaohongshu. The proliferation of technology and the increasing accessibility for individuals to establish careers on social media platforms have led to the emergence of influencer marketing as a strategy that can foster consumer engagement within these platforms and perhaps impact brand loyalty. This study examines the effect of influencers marketing approach in the Malaysian context, taking into consideration the growing prominence of this phenomenon. This study utilized descriptive analysis to offer generalizable recommendations for companies regarding the effect of adopting the influencer marketing approach as a strategic method. The findings of this study provide valuable insights for companies seeking to develop their marketing strategies and promote consumer engagement to expand their market position. [ABSTRACT FROM AUTHOR]

Generation Z, being the generation to grow up in the digital era, evince some distinctive features and preferences that significantly shape their online shopping behavior. The study delves into various advertising appeals employed by E-commerce platforms and investigates their effectiveness in capturing the attention, interest, and loyalty of Generation Z consumers. The findings of this research aim to provide valuable insights for marketers and E-commerce businesses seeking to optimize their strategies for this influential consumer segment. The content is based on recent literature and on what are the views of Generation Z concerning the online advertising appeals. Technology and the internet being the integral part of the life of Generation Z, it represents a unique demographic with marked characteristics, preferences, and behaviors. Generation Z is quick to adopt and adapt to trends. E-commerce businesses must stay agile and responsive to emerging trends to remain relevant. Studying the impact of advertising appeals helps identify what resonates with this dynamic demographic, allowing businesses to adjust their strategies accordingly. In this study, we established that online advertising appeals don't have significant influence on purchase behavior of Generation Z although they improve the Customer experience and thereby brand loyalty. [ABSTRACT FROM AUTHOR]

This paper frames the choice of messenger in advertising content as a Bayesian persuasion problem and characterizes the optimal messenger choice. We propose a model of advertising content that focuses on messenger selection, where advertising can generate product-match signals for consumers. We consider advertising as a problem of Bayesian persuasion with costly information processing, where the type of communication messenger is costless to observe and determines the information structure consumers will face, thereby affecting their attention decisions. Messengers are classified as high type or low type based on their likelihood of generating positive signals about product match. Our findings highlight that the optimal choice of messengers depends on their signal elasticities and the firm's decision on whether to induce consumer attention. In particular, we find that when it is crucial to raise prices and high-type messengers overshadow the product match value by providing generally positive signals, a low-type messenger can effectively capture consumer attention and persuade them to pay a higher premium. This holds true even if high-type messengers can better grab consumers' attention by providing additional entertainment value or when some consumers are naive in belief updating. History: Antony Dukes served as the senior editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mksc.2022.0405. [ABSTRACT FROM AUTHOR]

Click-through rate (CTR) prediction aims to estimate the likelihood that a user will interact with an item. It has gained significant attention in areas such as online advertising and e-commerce. Existing studies have verified that feature interactions play a crucial role in CTR prediction, highlighting the need for efficient modeling of these interactions. However, most existing approaches in CTR prediction tend to overlook specific feature characteristics, relying instead on deep neural networks or advanced attention mechanisms to learn meaningful feature interactions. In real-world scenarios, features can be categorized into groups based on prior information, which motivates the explicit consideration of interactions between groups of features. For example, the unique context of an item often has a substantial correlation with a particular user, and a specific item often has a strong relationship with a particular user demographic. An efficient model, therefore, requires an appropriate inductive bias to learn these relationships. To address this issue, we present a Context-aware Cross Feature Attentive Network (CCFAN) that explicitly considers the relationship or association between items and users. We categorize input variables into four groups: user, item, user context, and item context, which allows learning significant interactions between (user)-(item context) and (item)-(user context) in an explicit way. These interactions are learned using a multi-head self-attention network that includes modules for user-item interaction and cross-feature interaction. To demonstrate the effectiveness of CCFAN, we conduct experiments on two public benchmark datasets, MovieLens1M and Frappe, and one real-world dataset from an educational service provider, WJTB. The experimental results show that CCFAN not only outperforms previous state-of-the-art CTR methods but also offers a high degree of explainability. [ABSTRACT FROM AUTHOR]

This work introduces a novel cue that consumption advisers, like stylists and interior designers, can use to signal expertise: combinatory recommendations. In a combinatory recommendation, a person offers an opinion about compatibility among multiple products intended for joint usage. Across nine studies conducted in the lab and field, the authors find that offering a combinatory recommendation signals greater expertise (Study 1a, Study 2a) and, specifically, greater depth of knowledge (Study 1b), compared with other types of recommendations involving the same number of products. This effect does not depend on the helpfulness of the adviser (Study 2b) but is qualified by features of the recommendation itself (Study 3a) as well as the type of combination recommended (Study 3b). Importantly, the authors find this effect to have important downstream consequences, as the increased perceptions of expertise that follow a combinatory recommendation improve consumers' attitudes both toward products included in the recommendation and toward subsequent recommendations made by the adviser (Study 4, Study 5). The real-world persuasive value of combinatory recommendations is also tested in a field study (Study 6) that explores the effect of combinatory recommendations on click-through rates of Instagram advertisements. [ABSTRACT FROM AUTHOR]

This study aimed on the one hand to clarify the quality, authenticity, safety, and other issues related to products of the anabolic-androgenic steroid methandienone advertised on the Internet and personally imported to Japan and on the other hand to evaluate the use of two portable Raman spectrometers in identifying the active pharmaceutical ingredient (API). The study found that all n = 15 samples purchased from 14 websites were problematic regarding their package, labeling, and/or content. Specifically, one sample (6.7%) was confirmed falsified, twelve samples (80%) were found either to be falsified or unlicensed as pharmaceutical product, and two samples (13.3%) were received without information on the manufacturers' physical address or country of origin, with one sample (6.7%) having no labeling or other accompanying information at all. Both Raman spectrometers were able to identify the API in all samples as confirmed and quantified by ultra-high-performance liquid chromatography–Fourier transform mass spectrometry. Twelve samples contained on average less than 90% of the declared API content. By contacting national regulatory authorities in 44 countries, methandienone products were found to be approved in 1 country and not approved in 21 countries. To prevent health hazards and abuse, measures against the acquisition of anabolic-androgenic steroids from unknown sources are required. Portable Raman spectrometers may be suitable for the non-destructive and quick identification of methandienone in tablets. [ABSTRACT FROM AUTHOR]

In this paper we examine the nature of calls for the Ontario Problem Gambling Helpline from June 2021 to Jan 2023 to determine if the increased marketing of online and sports gambling has changed the nature of calls to the helpline. An interrupted time series model comparing the monthly calls before and after the expansion of online gambling and advertising (April 2023), found a significant effect. Calls related to the other games examined did not have a significant interrupted time series effect of from the expansion and advertising of online gambling. The results of this analysis clearly indicate an association between the expansion of legalized gambling and gambling advertising with the number of people who call the helpline for problem related to online gambling. [ABSTRACT FROM AUTHOR]

The aim of this paper is to optimize the allocation of multiple advertisements on a Web banner, where the price of an advertisement depends on the location at the banner. This problem can be defined as a two-dimensional single orthogonal knapsack problem with a location-based pixel-price model. A formulation is proposed in which the problem is specified as a 0–1 integer programming problem. As this problem is NP-complete, we mainly focus on a heuristic approach to solve the problem. We propose two new heuristic algorithms: the reactive GRASP algorithm and the partitioning left-justified algorithm. Next to that, we present an exact algorithm that is able to solve small problem instances in a reasonable time. These newly presented algorithms are compared with respect to efficiency and effectiveness to existing algorithms that solve the problem without a location-based pixel-price model. To test the quality of the algorithms, we have executed two experiments. The results of these experiments show that overall the reactive GRASP algorithm is the most effective algorithm, whereas the greedy stripping algorithm is the most efficient. [ABSTRACT FROM AUTHOR]

In 2022, Indonesian influencers have been accused of false advertising in promoting binary option applications through social media platforms such as Instagram and TikTok. Influencers use various promotional methods to promote brands, one of which is uploading content through social media platforms to be marketed to their followers. However, online advertising and consumer protection are subject to various legal issues that influencers must navigate to ensure compliance with relevant laws and regulations. Influencers must ensure that their advertisements are honest and undisputed. Influencers must ensure that the uploaded content is truthful and not misleading, and must be able to support any claims made in their content. Failure to do so may result in legal action from consumer protection commissions or government agencies including law enforcement officials. In this paper, a legal understanding of the process of using influencers can introduce legal requirements for influencers to comply with related regulations, official guidelines, and influencer agreements. Such explicit and/ or implicit provisions to be fulfilled in the influencer agreement for example representations and warranties for the authenticity of the content created by influencers. In this paper, this study will use a systematic method to solve research problems through qualitative method and data collection using a statutory approach, a conceptual approach, interpretation of the data collected, and drawing conclusions about the research data. The data in this paper analyzes legal issues regarding influencer responsibilities in digital marketing and consumer protection laws, oversight from regulatory bodies and law enforcement officials in supervising social media endorsements, and mandatory clauses in influencer agreements. The study highlights that while influencer marketing drives substantial economic activity, it also poses various legal challenges that must be addressed to protect consumer rights and maintain market integrity. Key legal issues shall include the need for clear disclosure of sponsored content and protection against misleading advertisements. [ABSTRACT FROM AUTHOR]

Introduction: Advertising tools used by sex workers for solicitation and client screening have been identified as supporting occupational health and safety (OHS); however, sex work legislation continues to criminalize advertising by third parties. We explored how the criminalization of third-party advertising and online censorship shapes indoor sex workers' access to OHS measures such as client screening, and negotiation of prices and services, in addition to income security. Methods: As part of a community-based study in Vancouver, this analysis drew on 47 interviews (2017–2018) with indoor sex workers and third parties (e.g., managers, receptionists). Interview transcripts were coded by applying a collaboratively- developed framework drawing on structural determinants of OHS to explore multilevel risk and protective factors shaping sex work environments, including access to advertising. Results: Participants' narratives highlighted that most third parties provide support with online advertising on behalf of sex workers; however, criminalization limits potential safety and income security mechanisms. Third parties take on the financial and labour burdens of advertising and screening for indoor workers, particularly for racialized, im/migrant workers who might face language barriers. Sex work laws and online censorship severely restrict communication, and resulting vague advertisements undermine sex workers' OHS by limiting advance screening, and negotiation of prices, services, and use of PPE. Conclusions: Third-party criminalization, coupled with online censorship, hinders advertising, with related harms exacerbated for im/migrant sex workers who would otherwise benefit from the OHS measures offered through advertising. Policy Implications: Legislative reforms to decriminalize all aspects of the sex industry, including sex workers' right to third-party advertising, are urgently needed to increase OHS of sex workers. [ABSTRACT FROM AUTHOR]

The impact of online advertising, content marketing, and electronic word-of-mouth (e-WOM) on purchasing decisions in the Shopee Marketplace is investigated in this study. 200 Shopee users from Cirebon City and Regency are participating in the study. The study uses online surveys with random sampling approaches to gather primary data using quantitative descriptive research methods. Next, Structural Equation Modelling Partial Least Squares (SEM PLS) 3.2.9 is used to analyze the data. Eight out of ten hypotheses are supported or accepted, according to the statistical analysis results. The two hypotheses that are not supported are E-WOM> Customer Engagement and Content Marketing> Customer Engagement> Buying Decision. [ABSTRACT FROM AUTHOR]

Marketers are increasingly adopting drone videos to advertise their products and services in a novel and engaging manner. Despite this increasing adoption, academic research on the use of drone videos for product advertising is scarce. Particularly lacking is evidence of the efficacy of drone video ads in eliciting favorable viewer responses. This study seeks to fill this gap in the literature by developing a model in which exposure to a drone video ad enhances viewers' perceived presence and perceived novelty of the drone video ad. In turn, viewers' perceived presence and perceived novelty of the drone video ad are hypothesized to contribute to a favorable attitude toward the brand and greater intention to share the drone video ad on social media through a favorable attitude toward the drone video ad. To test the proposed model, a sample of viewers were directed to watch a drone video ad and answered questions about the drone video ad, the advertised brand, and their intention to share the drone video ad on social media. The findings contribute to the literature by documenting the effectiveness of drone video ads in eliciting favorable viewer responses and elucidating the theoretical mechanisms by which these responses are elicited. [ABSTRACT FROM AUTHOR]

Internet users often surf multiple websites as a bundle to fulfill their needs and 'pay' for the content by viewing ads. We study how such complementary websites choose advertising policies. Two forces distort the equilibrium away from the industry optimum and the efficient outcome. First, websites place too many ads (double marginalization). Second, given the total advertising volume at equilibrium, websites misallocate ads among themselves (misplacement). Competition in one market segment may eliminate double marginalization but exacerbate misplacement. Introducing micropayments removes misplacement, but the welfare consequences are ambiguous. Policymakers must thus be cautious when applying standard remedies to zero‐price markets. [ABSTRACT FROM AUTHOR]

I review models of consumer search and competition when product quality is uncertain and differs across firms. Although firms are vertically—and possibly also horizontally—differentiated, an appropriate symmetric price equilibrium with optimal consumer search can be neatly characterized. I propose a "random‐quality" framework that unifies these models and discuss their insights on the operation of consumer search markets, focusing on (i) online advertising and search through platforms, (ii) the welfare effects of entry in search markets, and (iii) the role of quality observability under search frictions. I suggest directions for further research on these and related topics. [ABSTRACT FROM AUTHOR]

User-generated videos (UGVs) are popular in the e-business context. Product-related information in UGVs greatly facilitates online transactions. This study aims to investigate the mechanism of audience information processing in online video scenarios. Drawing on elaboration likelihood model, this study proposed an antecedent model for the perceived helpfulness of video-based online reviews from the perspective of audiences' involvement. In addition, the features of the Danmu are acted as moderating variables, moderating the choice of route by influencing the audience's involvement. The results were obtained by an online survey. Results from partial least squares structural equation modeling (PLS-SEM) indicate that video content (i.e., media richness, perceived expertise, and emotional appeal) and video source (i.e., emotional trust, physical attractiveness, and vocal attractiveness) positively influence its perceived helpfulness and the features of Danmu (i.e., emotional intensity and content similarity) moderate the relationships both positively and negatively. This study provides theoretical contributions from several perspectives and practical implications to marketers. [ABSTRACT FROM AUTHOR]

Australia prohibits the sale of nicotine-vaping products unless prescribed by medical practitioners. Significant policy reforms were announced on the 28th of November 2023 including a ban on single-use disposable vapes with and without nicotine, and the removal of the personal importation scheme. Despite stringent regulations, loopholes exist such that e-cigarette vendors are getting around it, and online markets provide a route to do so. We discuss strategies used by vendors to covertly market e-cigarettes online through social media. In this perspective, we highlight three proposed policies to strengthen social media regulations that may be feasible to implement. Our proposed strategies to regulate e-cigarette product listings on social media involve implementing robust age verification measures, enhancing the system for flagging and reporting prohibited content, and developing a more effective system to identify and flag content related to e-cigarettes. [ABSTRACT FROM AUTHOR]

It is surprising that women are often charged more for products and services marketed explicitly to them. This phenomenon, known as the pink tax, is a major issue that questions women's buying power. Nevertheless, it is not just limited to physical products – even online advertising can be subject to this type of gender-price discrimination. That is where our research comes in. We have developed a new methodology to measure what we call the digital marketing pink tax – the additional expense of delivering advertisements to female audiences. Analyzing data from Facebook advertising platforms across 187 countries and 40 territories shows this issue is systematic. Particularly, the digital marketing pink tax is prevalent in 79% of audiences across the world and 98% of audiences in highly developed countries. Therefore, advertisers incur a median cost of 30% more to display advertisements to women than men. In contrast, advertisers have to pay less digital marketing pink tax in less-developed countries (5%). Our research indicates that countries in the Middle East and Africa with a low Human Development Index (HDI) do not experience this phenomenon. Our comprehensive investigation of 24 industries reveals that advertisers must pay up to 64% of the digital marketing pink tax to target women in some industries. Our findings also suggest a connection between the digital marketing pink tax and the consumer pink tax – the extra charge placed on products marketed to women. Overall, our research sheds light on an important issue affecting women worldwide. Raising awareness of the digital marketing pink tax and advocating for better regulation. [ABSTRACT FROM AUTHOR]

Three decades ago, Karp, Vazirani, and Vazirani [Proceedings of the 22nd Annual ACM Symposium on Theory of Computing, 1990, pp. 352--358] defined the online matching problem and gave an optimal ... 0.632-competitive algorithm. Fifteen years later, Mehta et al. [J. ACM, 54 (2007), pp. 22:1--22:19] introduced the first generalization called AdWords driven by online advertising and obtained the optimal 1 1 e competitive ratio in the special case of small bids. It has been open ever since whether there is an algorithm for general bids better than the 0.5-competitive greedy algorithm. This paper presents a 0.5016-competitive algorithm for AdWords, answering this open question on the positive end. The algorithm builds on several ingredients, including a combination of the online primal dual framework and the configuration linear program of matching problems recently explored by Huang and Zhang [Proceedings of the 52nd ACM Symposium on Theory of Computing, 2020], a novel formulation of AdWords which we call the panorama view, and a generalization of the online correlated selection by Fahrbach et al. [Proceedings of the 61st Annual IEEE Symposium on Foundations of Computer Science, 2020], which we call the panoramic online correlated selection. [ABSTRACT FROM AUTHOR]

This article investigates digital and non-digital traces reused beyond the context of creation. A central idea of this article is that no (reused) dataset is perfect. Therefore, data quality assessment becomes essential to determine if a given dataset is "good enough" to be used to fulfill the users' goals. Biases, a possible source of discrimination, have become a relevant data challenge. Consequently, it is appropriate to analyze whether quality assessment indicators provide information on potential biases in the dataset. We use examples representing two opposing sides regarding data access to reflect on the relationship between quality and bias. First, the European Union open data portal fosters the democratization of data and expects users to manipulate the databases directly to perform their analyses. Second, online behavioral advertising systems offer individualized promotional services but do not share the datasets supporting their design. Quality assessment is socially constructed, as there is not a universal definition but a set of quality dimensions, which might change for each professional context. From the users' perspective, trust/credibility stands out as a relevant quality dimension in the two analyzed cases. Results show that quality indicators (whatever they are) provide limited information on potential biases. We suggest that data literacy is most needed among both open data users and clients of behavioral advertising systems. Notably, users must (be able to) understand the limitations of datasets for an optimal and bias-free interpretation of results and decision-making. [ABSTRACT FROM AUTHOR]

In today’s digital age, digital marketing has become an integral part of our daily lives. The internet, mobile applications, social media and other digital communication tools have become ubiquitous and are used by billions of people worldwide. This study aimed to investigate the factors that affect consumer purchase decisions in digital marketing. A set of self-administered questionnaires has been distributed to 166 respondents in Malaysia. The stimulus-organism-response (SOR) theory was employed in this study. The independent variables included in this study are email marketing, social media marketing, mobile marketing, online advertising, influencer marketing and trust plays as a moderating variable in the study. The findings of this study revealed that five out of eleven hypotheses were supported. Trust significantly showed a mediation effect on the relationship between mobile advertising and online advertising on purchase decisions. These findings contribute to Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure) by providing inputs on digital marketing’s effects, which can relate to the advancements in technology and innovation within the marketing sector. This research offers important insights for individuals, marketers and employers. Digital marketing is a powerful tool that can help businesses reach a larger audience, even with a limited budget. Utilising digital marketing tools like online advertising provides a valuable opportunity to strengthen online visibility, target the right audience, boost exposure and improve business outcomes. [ABSTRACT FROM AUTHOR]

Recruiting cisgender, heterosexual young men for research participation can be a difficult endeavour. This is more challenging with qualitative research studies that require substantial time commitment, or be of a sensitive nature, such as discussions of sex, intimacy, and emotion. These challenges can be amplified with the shift to online data collection procedures due to COVID-19. In this paper I reflect on the process of recruiting cisgender, heterosexual men for a qualitative study on sex and intimacy that relied solely on online advertising during the ongoing COVID-19 pandemic. I build on a critical men and masculinity (CMM) studies framework by considering a 'sex-as-dirty-work' approach which centres the uncomfortable practice of talking about and researching sex. I highlight the success of this approach that counters recommended best practice in getting men to participate. I conclude with a discussion of the implications of this approach, and suggestions for researchers. [ABSTRACT FROM AUTHOR]

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This study investigates how the value propositions in interdependent digital and analogue markets differ from each other. For this purpose, we conducted a content analysis and comparative case-study of four Dutch journalistic platforms that operate in markets for print and online advertising and paying audiences (subscriptions or memberships). First, we find that in digital (online) markets the value propositions on both market sides are more fused than in analogue markets. Second, we find that this is the reason for online platforms that serve the paying audiences, to offer advertising-free content. This suggests that there is not always a mutual dependency of the two market-sides as platform scholars assume, but that there may be a tension arising from interdependency, where some users may actually be attracted to the absence of the other market-side (advertising) and indirect network effect exploitation. [ABSTRACT FROM AUTHOR]

This article explores the use of generative AI (GenAI) in marketing content creation. It emphasizes the importance of high-quality content in marketing and explains how GenAI can revolutionize the content creation process. The article discusses the trade-offs between content quality and quantity and how GenAI can overcome these trade-offs. It provides examples of how GenAI can efficiently create more content and improve decision-making in marketing. The article also discusses the challenges and opportunities of using GenAI in marketing, including the need for personalized content distribution and unbiased training data. It concludes by highlighting the potential for GenAI to improve product design and search engine marketing. [Extracted from the article]

There are growing concerns about the commercialisation of childhood and the consequences of marketing to children, including marketing's negative effects and increasingly sophisticated and potentially deceptive online tactics that permeate the contemporary media environment. Children and young people are prolific users of video-sharing platforms (VSP) such as TikTok and YouTube, yet little is known about children's advertising literacy within these contexts. Therefore, this paper answers recent calls for a deeper understanding of children's advertising literacy in light of their increasingly digital lifestyles. A combination of qualitative, participatory creative methods were used with children aged 9–11 from the UK. Findings show that despite their negative perceptions of online advertising, children place a level of trust in video-sharing platforms, based on a misconception that the commercialisation of content is always disclosed. This is concerning because children may prefer and pay more attention to content that they believe to be genuine. [ABSTRACT FROM AUTHOR]

YouTube unboxing videos have become a popular genre among youth, and hosts often receive financial or other incentives for showcasing products. Although sponsored relationships must be explicitly disclosed per legal regulations, not all videos comply. This study assesses US tweens' reactions to unboxing videos with varying cues of a sponsored relationship between the host and product manufacturer, using a 3 (sponsored; non-sponsored; sponsorship unaddressed cue) x 2 (advertising training; no advertising training) randomized experimental design. The sample consisted of 215 tweens between ages 8–13 years. Half of the participants were randomly assigned to watch an advertising literacy training video before the unboxing video. Tweens detect a higher selling intent within the sponsored video (relative to the non-sponsored video), only after viewing the advertising literacy training video. The training video enhances the positive relationship between perceived informative intent and purchase intention, while weakening the positive relationship between perceived selling intent and purchase intention. Findings suggest tweens may have a unique mental schema for unboxing-style online videos which is a hybrid of informational and advertisement. Brief training videos could be used on video streaming platforms to develop and cue tweens' advertising literacy. Children's advertising literacy develops with age, but identifying native forms of online advertising is especially difficult. Tweens need cues to apply advertising literacy skills. Displaying sponsorship disclosures has shown mixed success at activating their advertising knowledge in online advertising contexts. Tweens differentiate selling intent between sponsored and non-sponsored unboxing videos only after prior training. The training does not help them detect selling intent in videos without sponsorship disclosures, or reduce tweens' perceptions of the informative intent of sponsored content. Embedding advertising literacy training videos within YouTube could help counter vulnerability to native advertising. Advertising literacy training content may need to closely match persuasive tactics within sponsored content, as tweens did not generalize concepts from the training video. [ABSTRACT FROM AUTHOR]

This article explores the presence of harmful content on social media platforms and why users are drawn to it. The authors argue that the advertising-based business model of these platforms can create incentives for displaying harmful content. They propose a model that suggests advertising-driven platforms may prioritize user engagement over the potential harm caused by the content. However, subscription-based platforms are less likely to display harmful content as it decreases users' willingness to pay. The article also presents findings from a field experiment that showed a decrease in engagement and ad impressions when toxic content was removed. It cautions against assuming that increased engagement always leads to improved welfare and highlights the complex policy implications of reducing harmful content on social media platforms. [Extracted from the article]

A differential game model has been utilised in this paper to analyse the dynamic strategic problems of online advertising in a two-echelon supply chain. First, the level of spillover effects has been introduced to examine the impact of different types of online advertising. Second, based on the improved Lanchester model, a dynamic investment decision model for online advertising has been developed. The results of the simulation describe the market share, online advertising investment amount and profit changes over time. Finally, by using the Rubinstein bargaining model, a proposal for a distribution mechanism is developed to achieve the coordination of a two-echelon supply chain system under strategic alliances. We find that: (1) The e-retailer's use of position-fixed online advertising is inversely proportional to the spillover effect. (2) When the two e-retailers are in a symmetrical position, the manufacturer is better off by choosing the e-retailer to form the strategic alliance; when in an asymmetric position, a manufacturer is expected to choose to not give e-retailer subsidies to maximise the supply chain profits. (3) The party with a stronger negotiation ability may bear more losses even though it may gain more profits. [ABSTRACT FROM AUTHOR]

Copyright of Computer und Recht is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Computer und Recht is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)