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Статті в журналах з теми "Personalization privacy paradox":
Karwatzki, Sabrina, Olga Dytynko, Manuel Trenz, and Daniel Veit. "Beyond the Personalization–Privacy Paradox: Privacy Valuation, Transparency Features, and Service Personalization." Journal of Management Information Systems 34, no. 2 (April 3, 2017): 369–400. http://dx.doi.org/10.1080/07421222.2017.1334467.
Aguirre, Elizabeth, Anne L. Roggeveen, Dhruv Grewal, and Martin Wetzels. "The personalization-privacy paradox: implications for new media." Journal of Consumer Marketing 33, no. 2 (March 21, 2016): 98–110. http://dx.doi.org/10.1108/jcm-06-2015-1458.
Cloarec, Julien. "The personalization–privacy paradox in the attention economy." Technological Forecasting and Social Change 161 (December 2020): 120299. http://dx.doi.org/10.1016/j.techfore.2020.120299.
Lee, Ae-Ri. "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." Sustainability 13, no. 19 (September 26, 2021): 10679. http://dx.doi.org/10.3390/su131910679.
Kaaniche, Nesrine, Maryline Laurent, and Sana Belguith. "Privacy enhancing technologies for solving the privacy-personalization paradox: Taxonomy and survey." Journal of Network and Computer Applications 171 (December 2020): 102807. http://dx.doi.org/10.1016/j.jnca.2020.102807.
Lei, Soey Sut Ieng, Irene Cheng Chu Chan, Jingyi Tang, and Shun Ye. "Will tourists take mobile travel advice? Examining the personalization-privacy paradox." Journal of Hospitality and Tourism Management 50 (March 2022): 288–97. http://dx.doi.org/10.1016/j.jhtm.2022.02.007.
Weinberger, Maor, and Dan Bouhnik. "Place Determinants for the Personalization-Privacy Tradeoff among Students." Issues in Informing Science and Information Technology 15 (2018): 079–95. http://dx.doi.org/10.28945/4019.
Guo, Xitong, Xiaofei Zhang, and Yongqiang Sun. "The privacy–personalization paradox in mHealth services acceptance of different age groups." Electronic Commerce Research and Applications 16 (March 2016): 55–65. http://dx.doi.org/10.1016/j.elerap.2015.11.001.
Kim, Yeong-Gug, and Eun-Ju Woo. "Privacy Concerns Within Personalization Based on the Internet of Things(IoT): A Perspective from the Privacy Paradox." Journal of Tourism Sciences 42, no. 7 (August 1, 2018): 71–84. http://dx.doi.org/10.17086/jts.2018.42.7.71.84.
Lee, Namyeon, and Ohbyung Kwon. "A privacy-aware feature selection method for solving the personalization–privacy paradox in mobile wellness healthcare services." Expert Systems with Applications 42, no. 5 (April 2015): 2764–71. http://dx.doi.org/10.1016/j.eswa.2014.11.031.
Дисертації з теми "Personalization privacy paradox":
Cloarec, Julien. "The Personalization-Privacy Paradox in the Attention Economy." Thesis, Toulouse 1, 2019. http://www.theses.fr/2019TOU10049.
The personalization-privacy paradox operates as a continuous, tension-charged cycle. Although consumers expect and consider the value of personalization, marketers’ exploitation of consumers’ personal information to provide personalization raises privacy concerns. Consumers, then, form a reluctance to provide personal information for personalization. Some researchers have attempted to enlist IT solutions to address this issue (e.g., anonymizing techniques and peer-to-peer communication), but these solutions proved ineffective as they were too sophisticated for the average consumer. Consequently, the personalization-privacy paradox, which emerged with the advent of mobile technologies, must be more theoretically founded. To date, the information systems literature primarily explicates the issue by applying myriad micro-oriented theories (e.g., privacy calculus theory, game theory, and information boundary theory). The first chapter suggests that the personalization-privacy paradox should also be examined at a macro level—through the lens of the “attention economy.” Investigating the relationship among personalization, privacy, and attention, brings insights regarding the ecology of attention, choice architecture, and stylistic devices and suggests implications for research and practice. The second chapter builds on both social exchange and construal level theories to investigate the extent to which happiness drives the personalization–privacy trade-off decision, 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 is the strongest driver of willingness to disclose information in exchange for personalization, surpassing conventional privacy-related constructs (e.g., trust and risk beliefs). Based on social exchange theory and the engagement literature, the third chapter investigates the influence of SNS activity (i.e., collaborative engagement) on users’ willingness to disclose information for personalization (e.g., a form of engagement with SNS platforms). The model is tested using the same dataset as before (n = 649). The results show that happiness with the Internet increases SNS use frequency through SNS literacy, and trust beliefs (information collection concerns) positively (negatively) impact the strength of the indirect relationship between SNS use frequency and willingness to disclose information for personalization via SNS posting frequency. The fourth and last chapter examines the importance of empowering consumers regarding their privacy. While complex, it is necessary to keep on investigating the ambivalent effect of privacy controls because the trade-off between advertising effectiveness and consumer privacy is at the core of the platform economy, which revenues rely on advertising. The author conducted an online survey among French-speaking Facebook users (n = 227). Through a privacy calculus lens, the author adopted a within-subject design to test the effect of education on privacy controls on satisfaction with Facebook ads. The results show that education on privacy controls indirectly affect the satisfaction with Facebook ads via privacy concerns (negative), fairness (positive), and attention quality (positive)
Idberg, Lovisa, Sofia Orfanidou, and Oona Karppinen. "Privacy for sale! : An exploratory study of personalization privacy paradox in consumers’ response to personalized advertisements on social networking sites." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105022.
Hillqvist, Oliver, and Östergren Amanda Johnsson. "The personalization-privacy paradox: personalized ads on social media : Exploring invasive ads on social media, in relation to perceived usefulness, consumer privacy and trust." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-95893.
Toivonen, Elisa. "Surveillance? : The influence of information asymmetry on consumers’ perceptions of online personalization." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-22056.
Harrysson, Alexandra, and Julia Olsson. "Personalization paradox: the wish to be remembered and the right to be forgotten : A qualitative study of how companies balance being personal while protecting consumers’ right to privacy." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-387611.
Oliveira, Bruna Miyuki Kasuya de. "A disposição para revelar informações pessoais a sistemas de recomendação: um estudo experimental." reponame:Repositório Institucional do FGV, 2017. http://hdl.handle.net/10438/18712.
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A privacidade de informações na internet é uma das maiores preocupações advindas da ascensão da web 2.0. Entretanto, cada vez é mais comum a requisição e manejamento de dados pessoais por empresas que, por meio de Sistemas de Recomendação (SR), visam garantir aos usuários serviços ou produtos personalizados às suas necessidades. Porém, frequentemente os consumidores enfrentam um paradoxo de privacidade-personalização, pois precisam conceder informações, mas temem como elas serão utilizadas pelas empresas. O uso incoerente de tais dados pode dar ao indivíduo a sensação de que sua liberdade está sendo cerceada, levando-o a reagir de maneira diversa da intenção do sistema. Trata-se, efetivamente, de um efeito bumerangue, entendido como uma resposta oposta à ameaça de sua liberdade na web. Tendo em vista que a literatura de SI explora de maneira insuficiente os efeitos da percepção de intrusão na disposição em revelar informações, sobretudo por meio da teoria da reatância psicológica – de onde advém o efeito bumerangue – o objetivo desta pesquisa foi verificar como a percepção dos usuários sobre a intrusão do Sistema de Recomendação pode afetar a sua disposição em revelar suas informações. Foram realizados dois experimentos, sendo um nos Estados Unidos e outro no Brasil, com amostras válidas de 213 e 237 participantes, respectivamente. Para isto, foi desenvolvido um protótipo de Sistema de Recomendação Experimental na plataforma Qualtrics. As técnicas utilizadas para análise de dados foram a análise de variância de um fator (one-way ANOVA) e a análise de covariância (ANCOVA). Dentre os resultados obtidos, demonstrou-se o efeito bumerangue do SR, pois quanto maior o nível de intrusão do SR, menor a disposição para revelar suas informações; verificou-se a existência de apenas dois níveis de intrusão percebida pelo usuário; foi constatado o impacto das preocupações de privacidade na internet na relação entre percepção de intrusão e disposição em revelar suas informações, além da uniformidade no comportamento entre as duas amostras. Com base nos resultados, espera-se que desenvolvedores de SR e empresas que os utilizam evitem futuros efeitos bumerangue em suas recomendações, o que afugentaria um potencial cliente.
Information privacy on internet is one of the biggest concerns that arise with web 2.0. However, it is increasingly common for companies that use Recommendation Systems (RS) the request and manage of personal data aiming to guarantee personalized services or products to the users. However, consumers often face a privacy-personalization paradox because they need to provide information, but fear how companies will use it. Incoherent use of such data can give to the individual the feeling that their freedom is being curtailed, causing reactions differently than the system’s intention. It is a boomerang effect, understood as an opposed response to the threat of its freedom on the web. Considering that the IS literature insufficiently explores the effects of the perception of intrusion on the willingness to disclose information, especially through the theory of psychological reactance – where the boomerang effect comes from – the objective of this research is to verify how the users' perception of the intrusion of the Recommendation System may affect your willingness to disclose your information. Two experiments were conducted in the United States and Brazil, with valid samples of 213 and 237 participants, respectively. A prototype of an Experimental Recommendation System (ERS) was developed on the Qualtrics platform. The techniques used for data analysis were the analysis of one-way variance (one-way ANOVA) and covariance analysis (ANCOVA). Among the results, the boomerang effect of RS was demonstrated, because the higher the level of SR intrusion, the less is the willingness to disclose its information. It was verified the existence of only two levels of intrusion perceived by the user. The impact of Internet privacy concerns on the relationship between perception of intrusion and willingness to disclose information was verified, as well as the behavioral indifference between the two samples. Based on the results, RS developers and companies that use them are expected to avoid future boomerang effects in their recommendations, which would scare away a potential customer.
LEE, YI-LIN, and 李宜霖. "Are You Worried about Personalized Service? An Empirical Study of the Personalization-Privacy Paradox." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/j7dcw9.
輔仁大學
企業管理學系管理學碩士班
105
Many websites today use personalized recommender systems to provide more attractive service to their customers. The conveniences provided by personalized services are often able to make the website more attractive to its users. In order to increase their competitiveness and customer loyalty, websites are prompted to collect more and more detailed information from its users. On the other hand, users today are also paying more and more attention on their privacy and personal information. They are worried that the website could steal, misuse or sell their information to a third party while expecting more benefit from personalization services, creating the problem of “The personalization-privacy paradox”. This research utilizes the privacy calculus theory to understand the relationship between personalization and privacy, how the users react when they run into the dilemma between privacy concern (perceived risk) and the benefit of personalization (perceived benefit), and how they perceive the value of personalization and influence their willingness to provide personal information. We use online survey to collect empirical data. The result of PLS analysis indicates that personalized service is positively affects perceived benefit. Information sensitivity and privacy concern both positively affects perceived risk. However, when customers are asked for data with low information sensitivity and low privacy concern, they are less likely to evaluate associated risks by performing a cost-benefit analysis. Perceived value is both influenced by perceived benefit and perceived risk and in term, affects customers’ willingness to provide personal information. We expect the findings from this study to provide some new findings for both researchers and developers of personalized recommender systems.
TrongDanh, Duong, and 楊重名. "The Personalization –Privacy Paradox: An Exploratory Study on the Intention to Disclose via Mobile Phone Applications." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/12594110200331268928.
國立成功大學
國際經營管理研究所
103
This study investigates the issue of consumer intention to disclose personal information via mobile applications. The study proposed a theoretical framework that were integrated protection motivation behavior on the basis of privacy calculus in order to explain an individual’s information disclosure behavior. Self-presentation, personalized services, perceived severity, importance of information transparency and perceived control were served as direct antecedents of perceived benefits and perceived risks. This study extends intention to disclose personal information literature by theoretically develop and empirically test the model within the current occurrence of disclosing personal information via mobile applications. Implications and future research are also discussed in this paper.
Частини книг з теми "Personalization privacy paradox":
Ku, Yi-Cheng, Peng-Yu Li, and Yi-Lin Lee. "Are You Worried About Personalized Service? An Empirical Study of the Personalization-Privacy Paradox." In HCI in Business, Government, and Organizations, 351–60. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91716-0_27.
Тези доповідей конференцій з теми "Personalization privacy paradox":
"Place Determinants for the Personalization-Privacy Tradeoff among Students." In InSITE 2018: Informing Science + IT Education Conferences: La Verne California. Informing Science Institute, 2018. http://dx.doi.org/10.28945/4069.