Consumer Privacy Research Articles

Does consumer privacy act influence firm performance in the retail industry? Evidence from a US state-level law change

In recent years, US states have introduced or passed consumer privacy laws. We explore the passage (June 28, 2018) and enforcement (January 1, 2020) of the California Consumer Privacy Act (CCPA) to ask whether such laws influence firm valuation. Based on organizational complexity and intangibility frameworks in the marketing literature, the law’s passage on June28,2018 did not have a meaningful stock market reaction in a sample of retail firms. Firms with higher intangibility or those with higher complexity and intangibility realized positive cumulative abnormal returns and Buy-and-Hold Abnormal Returns (BHAR). The findings are consistent after controlling for the text-based measures of privacy agreements, alternative measures of intangibility, and other robustness checks. Using the January 1, 2020, enforcement date, there were no meaningful changes in bounce rates and traffic from desktops or mobiles. The findings carry implications for policy makers, practitioners, and consumers.

Usability and Enforceability of Global Privacy Control

Web tracking by ad networks and other data-driven businesses is often privacy-invasive. Privacy laws, such as the California Consumer Privacy Act, aim to give people more control over their data. In particular, they provide a right to opt out from web tracking via privacy preference signals, notably Global Privacy Control (GPC). GPC holds the promise of enabling people to exercise their opt out rights on the web. Broad adoption of GPC hinges on its usability. In a usability survey we find that 94% of the participants would turn on GPC indicating a need for such efficient and effective opt out mechanism. 81% of the participants in our survey also have a correct understanding of what GPC does ensuring that their intent is accurately represented by their choice. The effectiveness of GPC is dependent on whether websites' GPC compliance can be enforced. A site's GPC compliance can be analyzed based on privacy flags, such as the US Privacy String, which is used on many sites to indicate the opt out status of a web user. Leveraging the US Privacy String for GPC purposes we implement a proof-of-concept browser extension that successfully and correctly analyzes sites' GPC compliance at a rate of 89%. We further implement a web crawler for our browser extension demonstrating that our analysis approach is scalable. We find that many sites do not respect GPC opt out signals despite being legally obligated to do so. Only 54/464 (12%) sites with a US Privacy String opt out users after having received a GPC signal.

A Qualitative Study on the Relationship of Personal Data with Consumer Privacy in Online Shopping

Bu araştırma müşteriler tarafından online alışverişte işletmelerle paylaşılan kişisel verilerin işletmelerce depolanmasının tüketici mahremiyeti endişesi ile ilişkisinin anlaşılması amacı ile yapılmıştır. Bu amaç doğrultusunda katılımcıların düşünce ve duyguların detaylı bir şekilde anlaşılması ve incelenmesi için nitel araştırma yöntemi olan görüşme tekniğinden yararlanılmıştır. Araştırmada amaçlı örnekleme yöntemi çerçevesinde online alışveriş yapan bireyler arasından evreni temsil edebilecek 20 kişilik bir örneklem seçilmiştir. 18 yaşından büyük, online alışveriş yapan 20 bireye yarı yapılandırılmış görüşme tekniği uygulanmıştır. 20 kişilik örneklemden elde edilen veriler MAXQDA 2020 Analiz Programı ile analizi yapılarak yorumlanmıştır. Elde edilen verilere göre, bireyler online alışverişte kişisel bilgilerinin korunduğuna inanmazken, online alışverişte kişisel bilgilerinin başkaları ile paylaşılmasına dair endişeleri olduğu ortaya çıkmıştır. Erkek ve kadın katılımcıların online alışverişte kişisel bilgilerinin başkaları ile paylaşılmasına dair endişe duyma oranlarının eşit çıkması, cinsiyet açısından bir farklılaşma olmadığını ortaya çıkarmıştır. Aynı zamanda katılımcıların online alışverişte kullandıkları kredi kartı bilgilerinin ele geçirilebileceği yönünde endişeli oldukları görülmüştür. Kadın katılımcılar için mahrem ürün “cinsel içerikli ürünler” ve “hijyenik pedler” iken, erkek katılımcılar için mahrem ürün “cinsel içerikli ürünler” dir. Erkek katılımcılar internetten mahrem olarak düşündükleri ürünleri satın almazken, kadın katılımcıların mahrem olarak düşündükleri ürünleri online alışverişte satın alacakları sonucuna ulaşılmıştır. Araştırma kapsamında elde edilen bulguların e-ticaret işletmelerine ve diğer işletmelere fayda sağlaması beklenmektedir.

Information Disclosure in the Era of Voice Technology

Whenever consumers interact with technological devices connected to the internet, they disclose information about themselves. The rapid diffusion of voice technology is shifting the way consumers interact with technological devices from typing or clicking to speaking. This article offers a comprehensive analysis of how this shift from manual to oral communication with technology affects information disclosure. The authors first consider verbal disclosure and provide a conceptual framework that explicates how voice technology can influence consumers’ propensity to reveal information about themselves through semantic content disclosed voluntarily. They then consider nonverbal disclosure and provide an analysis of how voice technology enables the collection of information revealed unintentionally through vocal paralanguage and ambient sound. The article offers testable propositions and poses open research questions that can serve as impetus for future research. In addition, it provides insights to marketers regarding how to navigate voice technology as a source of consumer information and to policy makers regarding how to better protect consumer privacy in interactions with voice technology.

Research on the impact of consumer privacy and intelligent personalization technology on purchase resistance

The main purpose of this study is to examine the impact of consumer privacy and intelligent personalization technology on purchase resistance using multidimensional development theory and the psychological contract violation model. From a holistic standpoint, this paper examines the internal mechanism of consumers’ resistance to personalized marketing, the different roles of situational factors and personal characteristics, and the stimulating factors of consumers’ psychological contract violation. The study concludes that psychological contract violation is the primary driver of consumer resistance to personalized marketing intent. The customization of perception, the enhancement of perception, and the legitimacy of the privacy policy are all negatively associated with the violation of psychological contracts with consumers. Personal innovation and online shopping experience are negatively correlated with consumers’ intention to resist personalized marketing; customization of perception has a significant direct effect on consumers’ resistance intention; There is no significant correlation between perceived improvement, privacy policy legitimacy, perceived privacy control, and consumers’ resistance intention. The contribution of this paper is to provide a new research perspective and theoretical explanation for a deeper understanding of consumers’ resistance to personalized marketing behavior.

Digital Marketing Business Strategy to MSME Performance in the Industrial Revolution 4.0 Era

This research examines how digital marketing helps SMEs in the industrial era 4.0. Seeing the phenomenon that is currently growing rapidly in the world of SMEs is very interesting and unique, the strategy for SMEs with technology needs to be studied in depth, hence the need for this research to use a qualitative descriptive method. This research examines the actors in the clothing business (distribution). This survey covers six owners and staff distribution. Observation, documentation, and participant in-depth analysis of data. Based on the results of research that has been interpreted with relevant previous research, that apparel SMEs in the industrial era 4.0 require conventional to digital growth strategies. Tokped, shopee, WhatsApp Business, and Instagram show that merchandise distortion has grown. Distortion works with small or independent bands with fans to create a selling environment. Distortion Merchandise band support pressure, goods and shipments, as well as buying and selling. On the other hand, Awesam is active in marketplaces and social media, from tokped, shopee, Lazada, Instagram, Tik Tok, and WhatsApp Business to the Awesam website which is at the top when it comes to "poor plain clothes". One account can publish two to five stories a day with interesting material. Consumer privacy hinders digital marketing. Most internet shopkeepers mark pictures or make product offers to all clients without the owner's consent. Customers sometimes get annoyed with the photos sent. The HR soft skills-technology balance is another issue to address.

Linking blockchain technology and digital advertising: How blockchain technology can enhance digital advertising to be more effective, efficient, and trustworthy

Blockchain technology is often touted as a transformative solution for improving the current over-centralized systems in our economy, where all tangible and intangible assets are traded. Driven by computer science and engineering, blockchain technology is believed to decentralize the current system with its simple yet effective property of distributed ledger technology, which guarantees data transparency that can be seen by anyone in the network. With its robustness, blockchain technology can be applied to the centralized and multi-party-controlled current advertising ecosystem. Despite its potential, there is a lack of scientific discussion linking blockchain technology and advertising. In this essay, we examine the current challenges that render the measurement of advertising effects inefficient and untrustworthy in the advertising ecosystem. By focusing on such challenges as data transparency, consumer privacy, and ad fraud, we explain how blockchain technology can enhance the advertising system, making it more trustworthy from both technical and consumer standpoints.

Consumer Privacy Choices and (Un)Targeted Advertising Along the Purchase Journey

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.

A comparative analysis between General Data Protection Regulations and California Consumer Privacy Act

Data breach is a common phenomenon is these days. Entities holding the personal data are involved in providing data to marketing and other companies for their benefit. Consequently, the citizens suffer and pay the price of breaching. Various countries have adopted personal data protection laws in line with General Data Protection Regulations (GDPR). The California State has also made legislation to secure consumer rights in respect of personal data. This study made a comparison between General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA). After study, it has been identified that GDPR is a comprehensive document which can be used for providing security of personal data around the world. It has all the relevant clauses/ Articles that can be used accordingly. Furthermore, being dynamic in nature it has the capability to become adoptable to new changes/ technologies. However, there is a need to expend the scope of the study and conduct a comparative analysis on the basis of geographical boundaries. The future directions may include the study of laws relating to personal data protection of various developing countries in the context of the GDPR.

Navigating state data privacy laws: A guide for SEC-registered investment advisers

This paper focuses on prominent issues surrounding state data privacy laws, specifically looking at the California Consumer Privacy Act (CCPA), which was amended and expanded by the California Privacy Rights Act (CPRA), the Colorado Privacy Act (CPA) and the Virginia Consumer Data Privacy Act (VCDPA). Due to the lack of a comprehensive federal privacy law, state data privacy laws have recently raised several issues for Securities and Exchange Commission (SEC)-registered investment advisers as they try to navigate through new markets and new industry practices. As such, this paper addresses the similarities and differences between the CPRA, CPA and VCDPA. The paper also provides compliance guidance for investment advisers to address the varying obligation under these laws.

A novel distributed privacy‐preserving control and data collection method for IoT‐centric microgrids

AbstractThe privacy of electricity consumers has become one of the most critical subjects in designing smart meters and their proliferation. In this work, a multilayer architecture has been proposed for anonymous data collection from smart meters, which provides: (1) The anonymity of information for third‐party data consumers; (2) Secure communication to utility provider network for billing purposes; (3) Online control of data sharing for end‐users; (4) Low communication costs based on available Internet of things (IoT) communication protocols. The core elements of this architecture are, first, the digital twin equivalent of the cyber‐physical system and, second, the Tangle distributed ledger network with IOTA cryptocurrency. In this architecture, digital twin models are updated in real‐time by information received from trusted nodes of the Tangle distributed network anonymously. A small‐scale laboratory prototype based on this architecture has been developed using the dSPACE SCALEXIO real‐time simulator and open‐source software tools to prove the feasibility of the proposed solution. The numerical results confirm that after a few seconds of anomaly detection, the microgrid was fully stabilized around its operating point with less than 5% deviation during the transition time.

Decentralized Image Sharing and Copyright Protection using Blockchain

Social media has become an integral part of our lives as Platforms like Facebook, Twitter, Instagram are conceived as a means of direct consumer interaction. Here, the problem identified is that although, these mediums have been promising their consumers some major concerns like privacy and censorship resistance, the promise has not been kept. Keeping the profitability in mind, social media platforms are risking the privacy of consumers. Centralized nature of these mediums is the main reason behind these issues. So, the objective of the project is to build an application in a decentralized way so that consumers can communicate without censorship while protecting their privacy. Keywords—Censorship, Privacy, Centralized, Interaction, Decentralized, Consumers

Brazilian General Data Protection Law (LGPD) and California Consumer Privacy Act (CCPA)

The issue of this work focuses on the critical analysis of the relevance of consumer personal data protection in the information society. The objective is to explain the relevance of the topic in light of the Brazilian General Data Protection Law and the California Consumer Privacy Act in the United States, in a micro-comparative approach. The literature review method was used, based on the theoretical-scientific construction through a comparison of the Brazilian and Californian legislation. To better understand the importance of protecting personal data today, the article discusses the global context of the knowledge society, the changes it has brought about in consumer relations, and then analyzes the Brazilian General Data Protection Law and the California Consumer Privacy Act. After studying both laws, it concludes that, considering the experience of the State of California and the growth of e-commerce in the country, it is up to Brazil to regulate the matter of protecting the consumer's personal data.

Guest editorial: Consumer privacy in the technological era

Guest editorial: Consumer privacy in the technological era

DER Forecast Using Privacy-Preserving Federated Learning

With the increasing penetration of distributed energy resources (DERs) in grid edge, including renewable generation, flexible loads, and storage, accurate prediction of distributed generation and consumption at the consumer level becomes important. However, DER prediction based on the transmission of customer-level data, either repeatedly or in large amounts, is not feasible due to privacy concerns. In this article, a distributed machine learning approach, federated learning (FL), is proposed to carry out DER forecasting using a network of Internet of Things (IoT) nodes, each of which transmits a model of the consumption and generation patterns without revealing consumer data. We consider a simulation study that includes 1000 DERs and show that our method leads to an accurate prediction of preserving consumer privacy, while still leading to an accurate forecast. We also evaluate grid-specific performance metrics, such as load swings and load curtailment, and show that our FL algorithm leads to satisfactory performance. Simulations are also performed on the Pecan street data set to demonstrate the validity of the proposed approach on real data.

Consent Verification Monitoring

Advances in personalization of digital services are driven by low-cost data collection and processing, in addition to the wide variety of third-party frameworks for authentication, storage, and marketing. New privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act, increasingly require organizations to explicitly state their data practices in privacy policies. When data practices change, a new version of the policy is released. This can occur a few times a year, when data collection or processing requirements are rapidly changing. Consent evolution raises specific challenges to ensuring GDPR compliance. We propose a formal consent framework to support organizations, data users, and data subjects in their understanding of policy evolution under a consent regime that supports both the retroactive and non-retroactive granting and withdrawal of consent. The contributions include (i) a formal framework to reason about data collection and access under multiple consent granting and revocation scenarios, (ii) a scripting language that implements the consent framework for encoding and executing different scenarios, (iii) five consent evolution use cases that illustrate how organizations would evolve their policies using this framework, and (iv) a scalability evaluation of the reasoning framework. The framework models are used to verify when user consent prevents or detects unauthorized data collection and access. The framework can be integrated into a runtime architecture to monitor policy violations as data practices evolve in real time. The framework was evaluated using the five use cases and a simulation to measure the framework scalability. The simulation results show that the approach is computationally scalable for use in runtime consent monitoring under a standard model of data collection and access and practice and policy evolution.

Optimizing Marketing Management Strategies Through IT Innovation: Big Data Integration for Better Consumer Understanding

The dynamic business environment, the fusion of Information Technology (IT) innovation with marketing management strategies has emerged as a crucial element for success amidst heightened competition. As markets evolve and consumer behaviors shift, enterprises are compelled to adapt swiftly, employing innovative tools and methodologies to gain insights and maintain relevance. Within this context, the integration of Big Data analytics emerges as a transformative catalyst, offering unprecedented opportunities to comprehend consumer preferences and optimize marketing endeavors. The convergence of IT and marketing management signifies a paradigm shift in how businesses conceive and execute their strategies. Historically, marketing decisions relied heavily on intuition, market research, and limited data samples. However, the digital revolution has ushered in an era characterized by the generation and collection of vast amounts of data at an unprecedented pace. This proliferation of data presents both challenges and opportunities for marketers. While the sheer volume and complexity of data can be overwhelming, harnessing this reservoir of data can unlock invaluable insights into consumer behavior, preferences, and trends. The integration of Big Data into marketing management strategies has revolutionized consumer understanding and value creation. By leveraging vast amounts of consumer data, businesses can extract valuable insights to gain a competitive advantage and enhance consumer engagement. However, this integration also presents challenges, including concerns regarding data privacy and security. At the forefront of this data-driven revolution lies Big Data analytics—a multidisciplinary field utilizing advanced computational techniques to analyze large and diverse datasets. Unlike traditional analytics approaches, Big Data analytics excels in processing massive volumes of structured and unstructured data with agility and efficiency. By harnessing distributed computing, machine learning algorithms, and cloud infrastructure, organizations can extract actionable intelligence from previously unwieldy datasets. The integration of Big Data analytics into marketing management holds immense promise for unlocking new avenues of consumer understanding. By aggregating and analyzing disparate data sources, marketers can gain comprehensive insights into consumer preferences, behaviors, and sentiments, enabling more targeted and effective marketing strategies. Moreover, Big Data analytics empowers marketers to anticipate and respond to emerging trends and market shifts with unprecedented agility, ensuring a competitive edge in fast-paced industries. However, realizing the full potential of Big Data integration in marketing management requires more than technological prowess—it demands a strategic shift in organizational mindset and culture. Embracing a data-driven approach necessitates breaking down silos between departments, fostering cross-functional collaboration, and promoting a culture of experimentation and innovation. Additionally, it requires a commitment to ethical data practices to safeguard consumer privacy and data security throughout the data lifecycle.

The effects of personal information on competition: Consumer privacy and partial price discrimination

This article studies the effects of consumer information on the intensity of competition. In a two dimensional duopoly model of horizontal product differentiation, firms use consumer information to price discriminate. I contrast a full privacy and a no privacy benchmark with intermediate regimes in which the firms can profile consumers only partially. I show that with partial privacy firms are always better-off with price discrimination: the relationship between information and profits is hump-shaped. In particular, competing firms prefer to target consumers with partial but asymmetric information about preferences. Instead, consumers prefer either no or full privacy in aggregate, but the effects of information on individual surplus are ambiguous: there are always winners and losers. Finally, I study the information acquisition incentives of the firms when there is an external data seller. When this upstream data broker holds partially informative data, an exclusive allocation arises. Instead, when data is fully informative, each competitor acquires consumer data but on a different dimension. These findings are relevant for the strategic decisions of firms active in digital markets and contribute to the policy debate surrounding privacy, exclusive access to data and competition.

Advertising strategies of competing firms considering consumer privacy concerns

AbstractTargeted advertising based on consumers' purchase history is the most prevalent choice for firms; however, its effectiveness is affected by an increase in consumer privacy concerns. We established a two‐period game model to analyze firms' equilibrium advertising strategies, pricing strategies, and profits when a segment of consumers is unwilling to provide their purchase information owing to privacy concerns. Based on the equilibrium results, some valuable managerial insights are suggested for competing firms. Firms should consider the proportion of privacy‐sensitive consumers and advertising costs when developing advertising strategies. Targeted advertising is not an optimal choice invariably.

Consumer privacy concerns in entrepreneurial contexts: Evidence from an online experiment

AbstractThe causal link between customer privacy concerns and organizational nature—specifically, entrepreneurial startups versus mature enterprises—remains unexplored. Using an online experiment, this study examines whether consumers' privacy concerns differ between these two types of organizations. Drawing on protection motivation theory, the study investigates whether customers' privacy concerns are stronger toward entrepreneurial startups than toward mature firms when both declare privacy protection. It further explores whether consumer participation in designing privacy protection mechanisms differently affects consumers' privacy concerns toward start‐ups versus mature firms. The empirical results of an online experiment using a sample of 373 college students support the study hypotheses that (i) for unilateral privacy protection declarations, consumers' privacy concerns are higher toward entrepreneurial startups, and (ii) when consumers are invited to participate in designing privacy protection mechanisms, consumers' privacy concerns toward entrepreneurial startups significantly decrease. Our findings complement the literature on consumer privacy defensive behaviors by highlighting that consumer privacy concerns are associated with the organizational nature and privacy protection initiatives.