scholarly journals Privacy Concerns in Chatbot Interactions

Author(s):  
Carolin Ischen ◽  
Theo Araujo ◽  
Hilde Voorveld ◽  
Guda van Noort ◽  
Edith Smit

Chatbots are increasingly used in a commercial context to make product- or service-related recommendations. By doing so, they collect personal information of the user, similar to other online services. While privacy concerns in an online (website-) context are widely studied, research in the context of chatbot-interaction is lacking. This study investigates the extent to which chatbots with human-like cues influence perceptions of anthropomorphism (i.e., attribution of human like characteristics), privacy concerns, and consequently, information disclosure, attitudes and recommendation adherence. Findings show that a human-like chatbot leads to more information disclosure, and recommendation adherence mediated by higher perceived anthropomorphism and subsequently, lower privacy concerns in comparison to a machine-like chatbot. This result does not hold in comparison to a website; human-like chatbot and website were perceived as equally high in anthropomorphism. The results show the importance of both mediating concepts in regards to attitudinal and behavioral outcomes when interacting with chatbots.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jie Tang ◽  
Umair Akram ◽  
Wenjing Shi

PurposeMobile Applications (App) privacy has become a prominent social problem. Compared with privacy concerns, this study examines a relatively novel concept of privacy fatigue and explores its effect on the users’ intention to disclose their personal information via mobile Apps. In addition, the personality traits are proposed as antecedents that will induce the personal perception of privacy fatigue and privacy concerns differently.Design/methodology/approachData were collected from 426 respondents. Structure equation modeling was used to test the hypotheses.FindingsThe findings describe that App users’ intention toward personal information disclosure is determined by privacy fatigue and privacy concerns, but the former has a greater impact. With minor exceptions, the two factors are also influenced by different personality traits. Specifically, neuroticism has positive effects on privacy fatigue, but agreeableness and extraversion have presented the opposite results on the two variables.Practical implicationsThis research is very scarce to examine the joint effects of privacy fatigue, privacy concerns and personality traits on App users’ disclosing intention. In doing so, these results will be of benefit to App providers and platform managers and can be the basis for a variety of follow-up studies.Originality/valueWhile previous research just focuses on privacy concerns, this study explores the critical roles of privacy fatigue and opens up a new avenue of emotion-attitude analysis that can further increase the specificity and richness of users’ privacy research. Additionally, implications for personality traits as antecedents in the impact of App users’ privacy emotions and attitudes are discussed.


Author(s):  
Antonia Russo ◽  
Gianluca Lax ◽  
Baptiste Dromard ◽  
Menad Mezred

AbstractThe General Data Protection Regulation highlights the principle of data minimization, which means that only data required to successfully accomplish a given task should be processed. In this paper, we propose a Blockchain-based scheme that allows users to have control over the personal data revealed when accessing a service. The proposed solution does not rely on sophisticated cryptographic primitives, provides mechanisms for revoking the authorization to access a service and for guessing the identity of a user only in cases of need, and is compliant with the recent eIDAS Regulation. We prove that the proposed scheme is secure and reaches the expected goal, and we present an Ethereum-based implementation to show the effectiveness of the proposed solution.


2014 ◽  
Vol 10 (2) ◽  
pp. 23-44
Author(s):  
Hongwei “Chris” Yang

A paper survey of 489 Chinese college students was conducted in spring, 2012 to test a conceptual model of online information disclosure in social media. It shows that young Chinese SNS users' prior negative experience of online disclosure significantly increased their online privacy concerns and their perceived risk. Their online privacy concerns undermined their trust of online companies, marketers and laws to protect privacy and elevated their perceived risk. Their trust strongly predicted their intent to disclose the lifestyle and sensitive information. Their online privacy concerns only inhibited them from disclosing sensitive information in social media. However, their prior negative experience did not directly predict their intent of self-disclosure on SNS. Implications for academia and industry are discussed.


Author(s):  
Philipp K Masur ◽  
Sabine Trepte

Abstract Previous research has shown that people seldom experience privacy violations while using the Internet, such as unwanted and unknown sharing of personal information, credit card fraud, or identity theft. With this study, we ask whether individuals’ online privacy concerns increase and online information disclosure decreases if they experience such a worst-case scenario. Using representative data from a five-wave panel study (n = 745), we found that people who generally experience more privacy violations also have stronger privacy concerns (between-person differences). However, people who experienced more privacy violations than usual in the last 6 months were only slightly more concerned afterward and did not change their disclosure behavior afterward (within-person effects). The need for privacy moderated these processes. We untangle under which circumstances such experiences may be transformative, and discuss practical and conceptual consequences of how experiences translate into concerns, but not necessarily behaviors.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hamid Reza Nikkhah ◽  
Rajiv Sabherwal

PurposeIn this research, the authors focus on mobile cloud computing (MCC) collaboration apps that are multiplatform and send the users’ data to the cloud. Despite their benefits, MCC collaboration apps raise privacy concerns, as the users’ information is sent to the cloud where users lack direct control. This study aims to investigate why users disclose information to MCC apps despite privacy concerns and examine the effect of security and assurance mechanisms (i.e. privacy policies and ISO/IEC 27018 certification) on users’ perceptions and information disclosure. Based on three surveys conducted in 2016 (n = 515), 2017 (n = 505) and 2018 (n = 543), this study finds mixed results regarding the relationships among security, assurance mechanisms, utilitarian benefits and information disclosure.Design/methodology/approachThis study conducted three scenario-based surveys in the USA in 2016 (n = 515), 2017 (n = 505) and 2018 (n = 543).FindingsThis study finds mixed results of relationships among security, assurance mechanisms, utilitarian benefit and information disclosure.Originality/valueWith proliferation of MCC apps, the investigation of how users make privacy decision to disclose personal information to these apps is sparse. This study, for the first time, investigates whether the signals of assurance mechanism decrease users’ privacy concerns. This study also examines the interplay between security and privacy within information disclosure behavior. Finally, this study was conducted in 3 years to enhance the generalizability and robustness of findings.


2019 ◽  
Vol 28 (2) ◽  
pp. 161-181 ◽  
Author(s):  
Ibrahim M. Al-Jabri ◽  
Mustafa I. Eid ◽  
Amer Abed

Purpose Customer privacy and security are major concerns. Online firms worldwide collect customer data for various reasons. This study aims to investigate factors that motivate and hinder a customer’s willingness to disclose personal information (WTD) to online firms on e-commerce websites. Design/methodology/approach Based on an extensive literature review, three sets of factors have been identified. These sets of factors are privacy concern, perceived disclosure benefits and privacy assurances. It is hypothesized that privacy concerns negatively affect the disclosure of personal information, while the perceived benefits of disclosure have positive effects. Privacy assurances would positively affect information disclosure and attenuate the negative effect of privacy concerns on the disclosure of personal information. The authors gathered data from 253 online customers in Saudi Arabia. Findings The results indicate that perceived disclosure benefits and privacy concerns have a significant positive and negative relationship, respectively, with WTD online. Privacy assurances had neither a direct nor a moderating effect on information disclosure. Research limitations/implications The findings will inform online firms about the factors that prevent or motivate customers to disclose personal information. Originality/value The effect of privacy concerns and benefits on personal information disclosure are not fully understood in Saudi Arabia. This study reveals more insights into the specific factors that make online customers reluctant or motivated to disclose their personal information.


2020 ◽  
Author(s):  
Yuanyuan Dang ◽  
Shanshan Guo ◽  
Xitong Guo

BACKGROUND The mobile health (mHealth) provides a new opportunity for patients’ disease prediction and health self-management. At the same time, privacy problems in mHealth have brought forth significant attention concerning patients' online health information disclosure and hindered mHealth development. OBJECTIVE Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a national and linear decision-making process. However, people’s cognitive behavior processes are complex and mutual. In attempting to close this knowledge gap, we further optimize the information disclosure model of patients based on PCT by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proved to be a distinct and significant disclosure benefit of mHealth, was chosen to be the representative benefit of information disclosure in mHealth. METHODS From an individual perspective, a structural equation model with privacy concerns, health information disclosure intention in mHealth, and social support from mHealth has been examined. RESULTS 253 randomly selected participants provided validated questionnaire. The result indicated that perceived health information sensitivity positively enhances the privacy concern (0.505, p<0.01), and higher privacy concern levels will decrease the health information disclosure intention (-0.338, p<0.01). Various aspects of individual characters influence perceived health information sensitivity in different ways. The informational support has a negatively moderate on reduce the positive effect between perceived health information sensitivity and privacy concerns (-0.171, p<0.1) and will decrease the negative effect between privacy concerns and health information disclosure intention(-0.105, p<0.1). However, emotional support has no directly moderate effect on both privacy concerns and health information disclosure intention. CONCLUSIONS The results indicate that social support can be regarded as a disutility reducer, that is, on the one hand, it reduces the privacy concerns of patients; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderate effect of social support is partially supported. Informational support, one demission of social support, is significant, while the other demission, emotional support, is not significant in mHealth. Furthermore, the results are different among patients with different individual characteristics. This study also provides specific theoretical and practical implications to enhance the development of mHealth.


2010 ◽  
Vol 25 (2) ◽  
pp. 109-125 ◽  
Author(s):  
Hanna Krasnova ◽  
Sarah Spiekermann ◽  
Ksenia Koroleva ◽  
Thomas Hildebrand

On online social networks such as Facebook, massive self-disclosure by users has attracted the attention of Industry players and policymakers worldwide. Despite the Impressive scope of this phenomenon, very little Is understood about what motivates users to disclose personal Information. Integrating focus group results Into a theoretical privacy calculus framework, we develop and empirically test a Structural Equation Model of self-disclosure with 259 subjects. We find that users are primarily motivated to disclose Information because of the convenience of maintaining and developing relationships and platform enjoyment. Countervailing these benefits, privacy risks represent a critical barrier to information disclosure. However, users’ perception of risk can be mitigated by their trust in the network provider and availability of control options. Based on these findings, we offer recommendations for network providers.


Author(s):  
Bailing Liu ◽  
Paul A. Pavlou ◽  
Xiufeng Cheng

Companies face a trade-off between creating stronger privacy protection policies for consumers and employing more sophisticated data collection methods. Justice-driven privacy protection outlines a method to manage this trade-off. We built on the theoretical lens of justice theory to integrate justice provision with two key privacy protection features, negotiation and active-recommendation, and proposed an information technology (IT) solution to balance the trade-off between privacy protection and consumer data collection. In the context of mobile banking applications, we prototyped a theory-driven IT solution, referred to as negotiation, active-recommendation privacy policy application, which enables customer service agents to interact with and actively recommend personalized privacy policies to consumers. We benchmarked our solution through a field experiment relative to two conventional applications: an online privacy statement and a privacy policy with only a simple negotiation feature. The results showed that the proposed IT solution improved consumers’ perceived procedural justice, interactive justice, and distributive justice and increased their psychological comfort in using our application design and in turn reduced their privacy concerns, enhanced their privacy awareness, and increased their information disclosure intentions and actual disclosure behavior in practice. Our proposed design can provide consumers better privacy protection while ensuring that consumers voluntarily disclose personal information desirable for companies.


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