Personalization Privacy Paradox Research Articles

INTEGRATING ADVANCED TECHNOLOGIES IN RETAIL: A CONCEPTUAL FRAMEWORK FOR ENHANCING CONSUMER EXPERIENCE AND TRUST

This study explores the integration of advanced technologies, such as Artificial Intelligence (AI), Augmented Reality (AR), and Big Data Analytics, in retail to enhance personalized consumer experiences while addressing privacy concerns. This research investigates the personalization-privacy paradox, where consumers value tailored recommendations but remain wary of data collection practices. Through a comprehensive literature review, this study developed a conceptual framework for responsibly integrating these technologies in retail. The framework illustrates how AI personalizes shopping experiences, AR enhances consumer engagement, and Big Data improves operational efficiency while also considering privacy issues. The key findings reveal that balancing personalized services with transparent data practices is essential for building consumer trust. This study emphasizes the importance of transparency and ethical data handling in mitigating privacy concerns and fostering a more consumer-centric retail environment. These insights contribute to retail strategies and provide practical guidance for leveraging cutting-edge technologies without compromising privacy, thereby highlighting the need for a balanced approach that maximizes the benefits of innovation while safeguarding consumer trust.

In smartness we trust: consumer experience, smart device personalization and privacy balance

PurposeDrawing on the personalization–privacy paradox and guided by means–end analysis, this study explores how consumers balance their concerns for privacy and the benefits of smart home device personalization and the role that trust plays in the process. More specifically, this study aims to investigate how perceptions of smart device personalization and privacy concerns are shaped by consumers’ experiences and the role of trust in the deliberation process.Design/methodology/approachIn-depth interviews were conducted across diverse demographic groups of smart device users to shed light on the balancing act between personalization and privacy.FindingsThe study found that product experience, ownership type, perceived value of convenience and control and quality of life via “smart things” are key motivators for product usage. The benefits of tailored recommendations and high relevance are balanced against the risks of echo chamber effects and loss of control. The results also show the role of active involvement in the privacy calculus and trust level. The study points to the significance of an ecosystem-based service/business model in gaining consumer confidence when they balance between personalization and privacy.Originality/valueAlthough many studies have explored trust, privacy concerns and personalization in an artificial intelligence (AI)-related context, few have addressed trust in the context of both smart devices and the personalization–privacy paradox. As such, this study adds to the existing literature by incorporating the concept of trust and addressing both privacy concerns and personalization in the AI context.

"Personalization Trends: Creating Tailored Customer Experiences" Dynamic Digital Solutions

The designing and producing in ways that resonate with customer preferences. Content and products that are personalized according to customer preferences can reduce customer fatigue and time in making choices, thereby decreasing their cognitive load. Despite its importance, the literature on personalized marketing remains fragmented due to the absence of a comprehensive review that consolidates the intellectual structure of the field. This study bridges this knowledge gap through a bibliometric review using performance analysis and science mapping. Through a comprehensive review of 383 publications, this study reveals the publication and citation trends, the most prolific authors, journals, and publications, and six major themes personalized recommendation, personalized relationship, personalization–privacy paradox, personalized advertising, personalization concept and discourse in marketing, and customer insights in personalized marketing) that characterize the body of knowledge of personalized marketing. The study concludes with future research directions as ways forward for personalized marketing, wherein a focus on new-age technologies involving artificial intelligence, big data, blockchain, internet of things, and wearables is encouraged to explore new ways to curate personalized experiences across online and offline channels.

Low-Fidelity Prototype of a Sensor-Dependent Interaction Platform: Formative Evaluation With Informal Caregivers of Older Adults With Cognitive Impairment.

Unobtrusive sensing technologies developed for monitoring deviant behaviors in older adult care require integration with an interaction platform to facilitate the flow of information between older adults and their caregivers. However, the continuous monitoring capabilities generate a considerable amount of data that must be interpreted, filtered, and personalized before being communicated to the informal caregivers based on their specific care needs and requirements. For the effective implementation of unobtrusive sensing solutions (USSs) in the care of older adults with cognitive impairment, we aimed to explore the expectations and preconditions regarding the implementation of USSs from the perspective of informal caregivers. Subsequently, we designed and evaluated a low-fidelity prototype of an interaction platform for its conceptual workflow and usability, incorporating persuasive system design features based on the needs and requirements of informal caregivers. Overall, 6 informal caregivers of older adults with cognitive impairment living alone participated in this qualitative interview study. We explored the expectation and preconditions regarding implementation through open-ended questions and conducted a formative evaluation (usability study with a think-aloud approach) to evaluate the conceptual workflow and used persuasive system design features in the interaction platform. Overall, a combination of inductive and thematic analyses was used to analyze the interviews. The results of this study present both positive and negative outcome expectations regarding the implementation of USSs, highlighting benefits such as objective decision-making and peace of mind and concerns about information overload and the potential substitution of human contact. Strategic information communication agreements between informal and formal caregivers were deemed crucial for the successful implementation of USSs in care. Overall, informal caregivers had a positive experience with the low-fidelity prototype of the interaction platform, particularly valuing the personalization feature. In conclusion, to achieve successful implementation, a holistic design approach is necessary, and equal consideration should be given to the personalization-privacy paradox to balance users' needs and privacy.

Enhancing recommendation acceptance: Resolving the personalization–privacy paradox in recommender systems: A privacy calculus perspective

The concept of recommendation acceptance intention (RAI) refers to the willingness of an individual to adopt and use recommender systems. However, contemporary recommender systems, relying solely on accuracy as an evaluation metric have demonstrated subpar performance. The evolving landscape requires the integration of multiple objectives, including relevance, diversity, novelty, and coverage. This study investigates the influence of distinct product organization formats (similar vs. related products) on consumer reactions, aiming to reduce privacy concerns while achieving objectives such as relevance and variety. Grounded in the privacy calculus theory and personalization–privacy paradox framework, this study asserts that organization formats prompt consumers to evaluate a recommender system, considering both privacy risks and personalization benefits. Findings from three experiments and one qualitative study indicate that a related product organization format effectively decreases consumer perceptions of privacy violation while enhancing their perceptions of variety compared to a similar product organization format. This result contributes to RAI and shapes consumer preferences for recommender systems. Moreover, this research distinguishes the mechanisms underlying the influence of organization formats on RAI in the context of different product types, such as durable goods and consumables. This distinction enhances implications for designing recommender systems in e-commerce.

Personalization in Marketing: Customizing the Customer Experience for Greater Engagement

In the realm of marketing, personalization refers to the strategic approach of designing and creating content and products that align with the specific preferences of individual customers. By tailoring offerings to customer preferences, businesses can effectively reduce customer fatigue and the time required for decision-making, ultimately alleviating cognitive load. Despite its significance, the existing body of literature on personalized marketing lacks a comprehensive review that consolidates the intellectual structure of the field. By thoroughly examining 383 publications, this study uncovers trends in publication and citation, identifies the most prolific authors, journals, and publications, and highlights six major themes that define the knowledge base of personalized marketing. These themes include personalized recommendations, personalized relationships, the personalization-privacy paradox, personalized advertising, the concept and discourse of personalization in marketing, and customer insights in personalized marketing. In conclusion, this study suggests future research directions for personalized marketing, emphasizing the exploration of new-age technologies such as artificial intelligence, big data, blockchain, the Internet of Things, and wearables. By leveraging these technologies, businesses can discover innovative methods to curate personalized experiences across both online and offline channels.

Tracking technologies in eHealth: Revisiting the personalization-privacy paradox through the transparency-control framework

Our research highlights the evolving landscape of online privacy, emphasizing the growing compliance pressure on tech companies and website owners due to GDPR regulations, particularly concerning cookie banners. The regulation of these banners for personalization underscores the trade-off known as the personalization-privacy paradox. Although recent studies emphasize the positive role of transparency and control in enhancing the digital experience, they often approached them in a static and isolated manner. We introduce a new approach to operationalizing transparency and control in our study within the context of Doctissimo, a well-known French health and wellness website recognized for aggregating user-generated health data and employing advertising trackers for marketing objectives. In Study 1, we examined banner transparency, demonstrating its positive effect on click-through intention via a preference for personalization over privacy. Study 2 focused on banner privacy controls and revealed that the impact of control was entirely mediated by the intrusion of information boundaries and the preference for personalization over privacy. This research contributes to the literature by investigating the personalization privacy paradox using an innovative operationalization within the transparency-control framework.

What influences users to provide explicit feedback? A case of food delivery recommenders

Although various forms of explicit feedback such as ratings and reviews are important for recommenders, they are notoriously difficult to collect. However, beyond attributing these difficulties to user effort, we know surprisingly little about user motivations. Here, we provide a behavioral account of explicit feedback’s sparsity problem by modeling a range of constructs on the rating and review intentions of US food delivery platform users, using data collected from a structured survey (n = 796). Our model, combining the Technology Acceptance Model and Theory of Planned Behavior, revealed that standard industry practices for feedback collection appear misaligned with key psychological influences of behavioral intentions. Most notably, rating and review intentions were most influenced by subjective norms. This means that while most systems directly request feedback in user-to-provider relationships, eliciting them through social ties that manifest in user-to-user relationships is likely more effective. Secondly, our hypothesized dimensions of feedback’s perceived usefulness recorded insubstantial effect sizes on feedback intentions. These findings offered clues for practitioners to improve the connection between providing behaviors and recommendation benefits through contextualized messaging. In addition, perceived pressure and users’ high stated ability to provide feedback recorded insignificant effects, suggesting that frequent feedback requests may be ineffective. Lastly, privacy concerns recorded insignificant effects, hinting that the personalization-privacy paradox might not apply to preference information such as ratings and reviews. Our results provide a novel understanding of explicit feedback intentions to improve feedback collection in food delivery and beyond.

Reconciling the personalization–privacy paradox via DoctorBots: The roles of service robot acceptance model elements and technology anxiety

AbstractThe role of artificial intelligence (AI)‐based DoctorBots in improving healthcare and the medical industry is expected to increase significantly in the coming decades. However, contrary to the general view that AI can gradually replace human work, user acceptance of DoctorBots has become an obstacle to the development of AI medical diagnosis. Building on the service robot acceptance model (sRAM), this study investigates the potential of the functional, socioemotional, and relational elements of DoctorBots to reconcile the personalization–privacy paradox, thus enhancing user acceptance. Via two scenario‐based experiments with 398 participants, this study reveals that the negative influence of the personalization–privacy paradox on user acceptance is exacerbated when users' technology anxiety is high. In addition, an online survey of 400 DoctorBot users indicates that ease of use, subjective social norms, social presence, and rapport are effective in addressing both nonpersonalization (NPC) and privacy concerns (PVC). These findings suggest that the healthcare industry can leverage DoctorBots to implement self‐diagnosis. Specifically, DoctorBots' functional elements are effective in mitigating users' NPC, and their relational elements are effective in extenuating users' PVC.

Examining the failure of gamification in implementing innovation from the perspective of problematization in the retail sectors of emerging economies

Gamification is a strategy, methodology, or activity that has picked up pace over time and has been successfully deployed in organizations. Despite massive efforts to capture the success of the deployment of gamification in implementing innovation, its failure in this regard has hitherto been ignored. Until recently, it has been difficult to understand such failure from a contributing factor perspective. In bridging this gap, we conducted our study through the lens of problematization and social cognitive theory. We drew qualitative data from the field by recording the experiences and observations of stakeholders involved in attempting and failing to implement gamified projects in the retail industry. Our qualitative analysis was aimed at developing a signposting suited to help firms answer the fundamental question of “Why does gamification fail as an innovation strategy?” Our results highlighted four main factors that lead to the failure of gamified projects: a) self-efficacy, b) immersive dynamics, c) the personalization privacy paradox, and d) disengagement. Our study offers a conceptual framework suited to act as a guidebook for firms and consultants who wish to implement various gamified solutions at various stages. Further, we discuss the implications of our findings and propose future research perspectives.

MENGEKSPLORASI PARADOKS PRIVASI GEN-Z DALAM PERSONALISASI IKLAN DI MEDIA DIGITAL

The practice of disclosing personal information in accessing digital media is inevitable. In digital transaction consumers are required to fill personal data in which quite risky, while the nature of social media facilitate user to willingly share their daily life. This condition leads to the discussion of personalization-privacy paradox that put digital media user in a dilemmatic position. In one hand, they enjoy the relevancy of personalized offerings otherwise they worry about the risk of disclosing information as the result digital media algorithm. This study is aimed to capture the personalizationprivacy paradox faced by the gen Z as the true digital natives using survey method. As the result of the study, personalization-privacy paradox is a real issue faced by respondents. They actively calculate the risk and benefit of sharing their information in digital platform. Moreover, they also tend to be less cautious towards popular digital application as they already consider it as a safe platform.

Fintech and contactless payment: Help or hindrance? The role of invasion of privacy and information disclosure

PurposeThere is always a need to discover how a paradox between a customer’s desire for a more personalized experience and their privacy and security concerns would shape their intention to continue using contactless payment methods. However, personalization–privacy paradox has not been well-covered over the area of contactless payment. Therefore, this study aims to empirically examine the impact of personalization–privacy paradox on the customers’ continued intention (CIN) to use contactless payment.Design/methodology/approach – The empirical part of the current study was conducted in Saudi Arabia by collecting the primary data using online questionnaire from a convenience sample size of 297 actual users of contactless payment methods.FindingsBased on structural equation modeling, personalization and privacy invasion were approved to significantly impact perceived value of information disclosure (PVD). Strong causal associations were confirmed between perceived severity, structural assurance and response cost with privacy invasion. Finally, both PVD and privacy invasion significantly predict CIN.Research limitations/implicationsThere are other important factors (i.e. technology interactivity, technology readiness, social influence, trust, prior experience, etc.) were not tested in the current study. Therefore, future studies would pay more attention regarding the impact of these factors. The current study data were also collected using a convenience sample of actual users of contactless payment methods. Therefore, there is a concern regarding the generalizability of the current study results to other kind of customers who have not used contactless payment.Originality/valueThis study has integrated both personalization–privacy paradox and protection motivation theory in one model. The current study holds value in providing a new and complete picture of the inhibitors and enablers of customers’ CIN to use contactless payment, including new types of inhibitors. Furthermore, personalization–privacy paradox has not been fully examined over the related area of Fintech and contactless payment in general. Therefore, this study was able to extend the theoretical horizon personalization–privacy paradox to new area (i.e. contactless payment) and new cultural context (Saudi Arabia).

How does ad relevance affect consumers' attitudes toward personalized advertisements and social media platforms? The role of information co-ownership, vulnerability, and privacy cynicism

Consumers' responses to the use of their personal data for personalized advertising by platform providers are paradoxical. Drawing from psychological ownership theory and the collective information boundary, this study examines how the social relevance and personal relevance of ads impact consumers' attitudes toward advertisements and social media platforms. Basing on 350 responses, we confirm that perceptions of information co-ownership and feelings of vulnerability play a serial mediating role in the positive relationship between ad relevance and consumer attitudes. Specifically, ad relevance increases consumers' perceptions of social media platforms as co-owners of their personal information, which in turn reduces feelings of vulnerability and improves their attitudes toward personalized advertisements and social media platforms. Privacy cynicism negatively moderates the indirect effects of information co-ownership perceptions on two attitude variables mediated through feelings of vulnerability. Our research findings provide a new perspective on the personalization–privacy paradox and offer platform providers new insights into improving their personalized advertising performance and user–platform relationships.

Reconciling the Personalization-Privacy Paradox: Exploring Privacy Boundaries in Online Personalized Advertising

To reconcile the personalization-privacy paradox, we adopt the privacy as a state view and define privacy as a state of information boundary rule-following. We further identify five types of boundaries underlying some of the important implicit rules of maintaining privacy: communication channel, platform, device, temporal, and purpose boundaries. Using an online vignette survey, we investigated how each of these boundary types affected users’ privacy perceptions when they were subjected to personalized advertisements. Using fixed- and random-effects models, we investigated how violating different boundary rules leads to changes in perceived privacy. Our results show that all five boundary types are significant predictors of perceived privacy within individuals. The communication channel, device, and business versus private purpose are significant predictors of perceived privacy across the whole sample. Temporal boundaries and platform boundaries failed to achieve statistical significance when evaluated simultaneously with the other factors across the whole sample. This means that for each individual, observing the rules of these five boundary types leads to higher perceived privacy than not observing these conditions. Taken as a whole, observing communication channel, device, and business versus private purpose boundaries also leads to higher averages of perceived privacy across the whole sample. Theoretical and practical implications are discussed based on the results

AIoT-enabled smart surveillance for personal data digitalization: Contextual personalization-privacy paradox in smart home

Artificial intelligence of things technology provides smart surveillance capability for personal data digitalization. It will invade individuals’ information, physical, and social spaces and raise contextual privacy concerns while providing personalized services, which has not been explored in previous research. We theorize three types of smart surveillance and identify three subdimensions of contextual personalization and privacy concerns. Grounded in surveillance theory and personalization-privacy paradox, we examined the different trade-offs of contextual personalization and privacy concerns underlying the three types of smart surveillance on users’ behavioral intention in smart home context. The results also indicated that transparency can lessen the trade-off effects.

Personalization in personalized marketing: Trends and ways forward

AbstractIn marketing, personalization is the action of designing and producing in ways that resonate with customer preferences. Content and products that are personalized according to customer preferences can reduce customer fatigue and time in making choices, thereby decreasing their cognitive load. Despite its importance, the literature on personalized marketing remains fragmented due to the absence of a comprehensive review that consolidates the intellectual structure of the field. This study bridges this knowledge gap through a bibliometric review using performance analysis and science mapping. Through a comprehensive review of 383 publications, this study reveals the publication and citation trends, the most prolific authors, journals, and publications, and six major themes (i.e., personalized recommendation, personalized relationship, personalization–privacy paradox, personalized advertising, personalization concept and discourse in marketing, and customer insights in personalized marketing) that characterize the body of knowledge of personalized marketing. The study concludes with future research directions as ways forward for personalized marketing, wherein a focus on new‐age technologies involving artificial intelligence, big data, blockchain, internet of things, and wearables is encouraged to explore new ways to curate personalized experiences across online and offline channels.

Will tourists take mobile travel advice? Examining the personalization-privacy paradox

Recognizing the penetration of mobile devices and its transformational impact on travel behavior, tourism and hospitality businesses have been investing on various mobile initiatives to connect with travelers, hoping to influence their decision-making behaviors at different stages throughout the trip. One of these strategies is to provide personalized contents that are more attractive and persuasive. As research regarding the impact of mobile-driven personalization practices on travel behavior is limited, this study investigates the factors affecting travelers' adoption of personalized mobile travel advice. Based on personalization-privacy paradox and self-referencing effect, a 2 (self-reference: high vs. low) × 2 (relevance: high vs. low) between-subjects experiment was carried out. The results demonstrate the mechanism underlying the effects of personalization cues (self-reference and content relevance) on travelers’ intention to adopt personalized mobile travel advice. The competitive mediating roles of perceived personalization and privacy concern on the relationship between personalization cues and adoption intention are highlighted.

How AI chatbots have reshaped the frontline interface in China: examining the role of sales–service ambidexterity and the personalization–privacy paradox

PurposeThis study serves two purposes: (1) to evaluate the effects of organizational ambidexterity by examining how the balanced and the combined sales–service configurations of chatbots differ in their abilities to enhance customer experience and patronage and (2) to apply information boundary theory to assess the contingent role that chatbot sales–service ambidexterity can play in adapting to customers' personalization–privacy paradox.Design/methodology/approachAn online survey of artificial intelligence chatbots users was conducted, and a mixed-methods research design involving response surface analysis and polynomial regression was adopted to address the research aim.FindingsThe results of polynomial regressions on survey data from 507 online customers indicated that as the benefits of personalization decreased and the risk to privacy increased, the inherently negative (positive) effects of imbalanced (combined) chatbots' sales–service ambidexterity had an increasing (decreasing) influence on customer experience. Furthermore, customer experience fully mediated the association of chatbots' sales–service ambidexterity with customer patronage.Originality/valueFirst, this study enriches the literature on frontline ambidexterity and extends it to the setting of human–machine interaction. Second, the study contributes to the literature on the personalization–privacy paradox by demonstrating the importance of frontline ambidexterity for adapting to customer concerns. Third, the study examines the conduit between artificial intelligence (AI) chatbots' ambidexterity and sales performance, thereby helping to reconcile the previously inconsistent evidence regarding this relationship.

Investigating the Personalization–Privacy Paradox in Internet of Things (IoT) Based on Dual-Factor Theory: Moderating Effects of Type of IoT Service and User Value

Despite people’s concerns over privacy leakage in the Internet of Things (IoT), the needs for personalized IoT services are increasing, creating a conflicting phenomenon viewed as the personalization–privacy (P–P) paradox. This study proposes a research model that utilizes dual-factor theory to investigate the P–P paradox in IoT. It aims to analyze the impact of the dual factor—personalization and privacy concerns related to IoT services—on the intention to use IoT. Further, the model includes four-dimensional motivated innovativeness and previous privacy-invasion experience as key antecedents of the dual factor. Particularly, this study examines the moderating effects of the type of IoT service and user value on the relationship between dual factor and usage intention. Data were collected using a web-based survey. The results showed that personalization had a significant impact on the intention to use IoT, whereas privacy concerns did not. The effects of all antecedents except social innovativeness were significant. The P–P paradox phenomenon appeared differently depending on the type of IoT service and user value. This study contributes to gaining a better understanding of the factors that influence the increase in IoT usage in terms of both protecting and appropriately using personal information for IoT services.

The personalization–privacy paradox at the nexus of social exchange and construal level theories

AbstractMarketing personalization requires firms to collect information that they can use to personalize their products or services, which might raise consumer privacy concerns. Prior studies on construal level theory suggest that happier Internet users would likely take future rewards in social exchanges (e.g., personalization–privacy trade‐offs) into greater consideration. Building on both social exchange and construal level theories, this article investigates the extent to which happiness with the Internet drives the personalization–privacy paradox, as well as the moderating role of experience sharing frequency as a proxy for reciprocity. An online survey administered to a representative sample of French consumers (n = 649) largely confirms the predictions. Happiness with the Internet is the strongest driver of willingness to disclose information in exchange for personalization, surpassing conventional privacy‐related constructs (e.g., trust and risk beliefs). In line with social exchange theory, reciprocity has an important influence on online social exchanges too.