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

Gati, 2021, Differentially private data fusion and deep learning framework for cyber–physical–social systems: state-of-the-art and perspectives, Inf. Fusion, 76, 298, 10.1016/j.inffus.2021.04.017 Turel, 2019, The Digitization of the individual (DOTI), Inf. Syst. J. Leidner, 2021, The care theory of dignity amid personal data digitalization, MIS Q., 45, 343, 10.25300/MISQ/2021/15941 Cichy, 2021, Privacy concerns and data sharing in the internet of things: mixed methods evidence from connected cars, MIS Q., 45, 1863, 10.25300/MISQ/2021/14165 Jiang, 2020, It-enabled self-monitoring for chronic disease self-management: an interdisciplinary review, MIS Q., 44, 451, 10.25300/MISQ/2020/15108 Langheinrich, 2014, Quo vadis smart surveillance? How smart technologies combine and challenge democratic oversight, 151 Matt, 2019, The digitization of the individual: conceptual foundations and opportunities for research, Electron. Mark., 29, 315, 10.1007/s12525-019-00348-9 D'Arcy, 2009, User awareness of security countermeasures and its impact on information systems misuse: a deterrence approach, Inf. Syst. Res., 20, 79, 10.1287/isre.1070.0160 Dhir, 2019, Antecedents and consequences of social media fatigue, Int. J. Inf. Manag., 193, 10.1016/j.ijinfomgt.2019.05.021 Martin, 2016, An eye on your work: how empowerment affects the relationship between electronic surveillance and counterproductive work behaviours, Int. J. Hum. Resour. Manag., 27, 2635, 10.1080/09585192.2016.1225313 McNall, 2007, Effects of electronic monitoring types on perceptions of procedural justice, interpersonal justice, and privacy, J. Appl. Soc. Psychol., 37, 658, 10.1111/j.1559-1816.2007.00179.x Xiao, 2019, Exploring the antecedents of social network service fatigue: a socio-technical perspective, Ind. Manag. Data Syst., 119, 2006, 10.1108/IMDS-04-2019-0231 Dinev, 2008, Internet privacy concerns and beliefs about government surveillance – an empirical investigation, J. Strategic Inf. Syst., 17, 214, 10.1016/j.jsis.2007.09.002 Nelson, 2016, Health empowerment through activity trackers: an empirical smart wristband study, Comput. Hum. Behav., 62, 364, 10.1016/j.chb.2016.03.065 Shore, 2022, To share or not to share: extending protection motivation theory to understand data sharing with the police, Comput. Hum. Behav., 130, 10.1016/j.chb.2022.107188 Yost, 2018, Reactance to electronic surveillance: a test of antecedents and outcomes, J. Bus. Psychol., 34, 71, 10.1007/s10869-018-9532-2 Benlian, 2020, Mitigating the intrusive effects of smart home assistants by using anthropomorphic design features: a multimethod investigation, Inf. Syst. J., 30, 1010, 10.1111/isj.12243 Lanzing, 2018, Strongly recommended” revisiting decisional privacy to judge hypernudging in self-tracking technologies, Philos. Technol., 32, 549, 10.1007/s13347-018-0316-4 Suh, 2007, 966 West, 2019, Amazon: surveillance as a Service, Surveill. Soc., 17, 27, 10.24908/ss.v17i1/2.13008 Princi, 2020, I spy with my little sensor eye - effect of data-tracking and convenience on the intention to use smart technology, 10.24251/HICSS.2020.171 Calo, 2010, People can be so fake: a new dimension to privacy and technology scholarship, Penn State Law Rev., 114, 809 Lee, 2020, Home Iot resistance: extended privacy and vulnerability perspective, Telemat. Informat. Choi, 2017, Examining the effects of personalized app recommender systems on purchase intention: a self and social interaction perspective, J. Electron. Commerce Res., 18, 73 Gutierrez, 2019, Using privacy calculus theory to explore entrepreneurial directions in mobile location-based advertising: identifying intrusiveness as the critical risk factor, Comput. Hum. Behav., 95, 295, 10.1016/j.chb.2018.09.015 Tam, 2006, Understanding the impact of web personalization on user information processing and decision outcomes, MIS Q., 30, 865, 10.2307/25148757 Xu, 2012, Measuring mobile users' concerns for information privacy Xu, 2011, The personalization privacy paradox: an exploratory study of decision making process for location-aware marketing, Decis. Support Syst., 51, 42, 10.1016/j.dss.2010.11.017 Ibarra-Esquer, 2017, Tracking the evolution of the internet of things concept across different application domains, Sensors (Basel), 17, 1, 10.3390/s17061379 Li, 2019, Iot data feature extraction and intrusion detection system for smart cities based on deep migration learning, Int. J. Inf. Manag., 49, 533, 10.1016/j.ijinfomgt.2019.04.006 Ives, 2016, Enhancing customer service through the internet of things and digital data streams, MIS Q. Executive, 15, 279 Nelson, 2005, Antecedents of information and system quality: an empirical examination within the context of data warehousing, J. Manag. Inf. Syst., 21, 199, 10.1080/07421222.2005.11045823 Shin, 2014, A socio-technical framework for internet-of-things design: a human-centered design for the internet of things, Telemat. Inform., 31, 519, 10.1016/j.tele.2014.02.003 Vagts, 2012, User-centric protection and privacy in smart surveillance systems, 237 Harvey, 2020, The smart home: how consumers craft new service networks by combining heterogeneous smart domestic products, J. Service Res., 23, 504, 10.1177/1094670520929095 Yang, 2017, User Acceptance of smart home services: an extension of the theory of planned behavior, Ind. Manag. Data Syst., 117, 68, 10.1108/IMDS-01-2016-0017 2021 Mulcahy, 2019, Are households ready to engage with smart home technology?, J. Mark. Manag., 35, 1370, 10.1080/0267257X.2019.1680568 Chouk, 2019, Factors for and against resistance to smart services-role of consumer lifestyle and ecosystem related variables, J. Services Mark., 33, 449, 10.1108/JSM-01-2018-0046 Dong, 2017, Understanding usage of internet of things (Iot) systems in China, Inf. Technol. People, 30, 117, 10.1108/ITP-11-2015-0272 Hubert, 2019, The influence of acceptance and adoption drivers on smart home usage, Eur. J. Mark., 53, 1073, 10.1108/EJM-12-2016-0794 Khasawneh, 2022, Enhancing smart system platforms: factors affecting people's intentions toward smart homes in Jordan, Int. J. Technol. Hum. Interact. (IJTHI), 18, 1, 10.4018/IJTHI.293202 Nikou, 2019, Factors driving the adoption of smart home technology: an empirical assessment, Telemat. Inform., 45, 10.1016/j.tele.2019.101283 Park, 2017, Comprehensive approaches to user acceptance of internet of things in a smart home environment, IEEE Internet Things J., 4, 2342, 10.1109/JIOT.2017.2750765 Boer, 2019, Accepting the internet-of-things in our homes: the role of user skills, Telemat. Inform., 36, 147, 10.1016/j.tele.2018.12.004 Kim, 2017, A study on the adoption of Iot smart home service: using value-based adoption model, Total Qual. Manag. Bus. Excellence, 28, 1149, 10.1080/14783363.2017.1310708 Mamonov, 2021, Unlocking the smart home: exploring key factors affecting the smart lock adoption intention, Inf. Technol. People, 34, 835, 10.1108/ITP-07-2019-0357 Shin, 2018, Who will be smart home users? An analysis of adoption and diffusion of smart homes, Technol. Forecast. Soc. Change, 134, 246, 10.1016/j.techfore.2018.06.029 Wang, 2018, I want it anyway: consumer perceptions of smart home devices, J. Comput. Inf. Syst., 60, 437 Wunderlich, 2019, Adoption of sustainable technologies: a mixed-methods study of German households, MIS Q., 43, 673, 10.25300/MISQ/2019/12112 Lupton, 2016, The diverse domains of quantified selves: self-tracking modes and dataveillance, Econ. Soc., 45, 101, 10.1080/03085147.2016.1143726 Lee, 2017, Companionship with smart home devices: the impact of social connectedness and interaction types on perceived social support and companionship in smart homes, Comput. Hum. Behav., 922, 10.1016/j.chb.2017.06.031 O'Brolcháin, 2019, Privacy challenges in smart homes for people with dementia and people with intellectual disabilities, Ethics Inf. Technol., 21, 253, 10.1007/s10676-019-09507-0 Lee, 2016, Personalization–privacy paradox and consumer conflict with the use of location-based mobile commerce, Comput. Hum. Behav., 63, 453, 10.1016/j.chb.2016.05.056 Jenness, 2007, Taking a look at surveillance studies, Contemp. Sociol., 36, 2, 10.1177/009430610603600201 van Heek, 2017, The surveillance society: which factors form public acceptance of surveillance technologies?, 170 Wirth, 2019, Justification of mass surveillance: a quantitative study, 1337 Spitzmüller, 2006, Examining employee compliance with organizational surveillance and monitoring, J. Occup. Organ. Psychol., 79, 245, 10.1348/096317905X52607 Mani, 2019, Impact of privacy concerns on resistance to smart services: does the ‘Big brother effect’ matter?, J. Mark. Manag., 35, 1460, 10.1080/0267257X.2019.1667856 Pavlou, 2002, Institution-based trust in interorganizational exchange relationships: the role of online B2b marketplaces on trust formation, J. Strategic Inf. Syst., 11, 215, 10.1016/S0963-8687(02)00017-3 Paluch, 2019, Persuaded self-tracking with wearable technology: carrot or stick, J. Services Mark., 33, 436, 10.1108/JSM-03-2018-0091 Wright, 2010, Sorting out smart surveillance, Comput. Law Security Rev., 26, 343, 10.1016/j.clsr.2010.05.007 Oulasvirta, 2012, Long-term effects of ubiquitous surveillance in the home, 41 Lyon, 2014, Surveillance, snowden, and big data: capacities, consequences, critique, Big Data Soc., 1, 1, 10.1177/2053951714541861 Essen, 2008, The two facets of electronic care surveillance: an exploration of the views of older people who live with monitoring devices, Soc. Sci. Med., 67, 128, 10.1016/j.socscimed.2008.03.005 Sheng, 2008, An experimental study on ubiquitous commerce adoption: impact of personalization and privacy concerns, J. Assoc. Inf. Syst., 9, 344 Awad, 2006, The personalization privacy paradox: an empirical evaluation of information transparency and the willingness to be profiled online for personalization, MIS Q., 30, 13, 10.2307/25148715 Sutanto, 2013, Addressing the personalization-privacy paradox: an empirical assessment from a field experiment on smartphone users, MIS Q., 37, 1141, 10.25300/MISQ/2013/37.4.07 Lee, 2011, Personalisation–privacy paradox: the effects of personalisation and privacy assurance on customer responses to travel web sites, Tour. Manag., 32, 987, 10.1016/j.tourman.2010.08.011 Kehr, 2015, Blissfully ignorant: the effects of general privacy concerns, general institutional trust, and affect in the privacy calculus, Inf. Syst. J., 25, 607, 10.1111/isj.12062 Utz, 2009, The privacy paradox on social network sites revisited: the role of individual characteristics and group norms, Cyberpsychology, 3 Chen, 2019, Understanding consumers’ reactance of online personalized advertising: a new scheme of rational choice from a perspective of negative effects, Int. J. Inf. Manag., 53, 10.1016/j.ijinfomgt.2018.09.001 Ham, 2016, Exploring how consumers cope with online behavioral advertising, Int. J. Advert., 36, 632, 10.1080/02650487.2016.1239878 Guo, 2016, The privacy–personalization paradox in mhealth services acceptance of different age groups, Electron. Commer. Res. Appl., 16, 55, 10.1016/j.elerap.2015.11.001 Zeng, 2021, Does self-disclosure matter? A dynamic two-stage perspective for the personalization-privacy paradox, J. Bus. Res., 124, 667, 10.1016/j.jbusres.2020.02.006 Hong, 2013, Internet privacy concerns: an integrated conceptualization and four empirical studies, MIS Q., 37, 275, 10.25300/MISQ/2013/37.1.12 Malhotra, 2004, Internet users' information privacy concerns (Iuipc): the construct, the scale, and a causal model, Inf. Syst. Res., 15, 336, 10.1287/isre.1040.0032 Smith, 1996, Information privacy: measuring individuals' concerns about organizational practices, MIS Q., 20, 167, 10.2307/249477 Degirmenci, 2020, Mobile users’ information privacy concerns and the role of app permission requests, Int. J. Inf. Manag., 50, 261, 10.1016/j.ijinfomgt.2019.05.010 Fan, 2020, Does role conflict influence discontinuous usage intentions? Privacy concerns, social media fatigue and self-esteem, Inf. Technol. People, 34, 1152, 10.1108/ITP-08-2019-0416 Kim, 2016, Web assurance seal services, trust and consumers’ concerns: an investigation of e-commerce transaction intentions across two nations, Eur. J. Inf. Syst., 25, 252, 10.1057/ejis.2015.16 Kim, 2018, Factors influencing willingness to provide personal information for personalized recommendations, Comput. Hum. Behav., 143, 10.1016/j.chb.2018.06.031 Mousavi, 2020, Effectiveness of privacy assurance mechanisms in users' privacy protection on social networking sites from the perspective of protection motivation theory, Decis. Support Syst., 135, 10.1016/j.dss.2020.113323 Zalmanson, 2022, The role of social cues and trust in users' private information disclosure, MIS Q., 46, 1109, 10.25300/MISQ/2022/16288 Zhang, 2022, Peer privacy concerns: conceptualization and measurement, MIS Q., 10.25300/MISQ/2022/14861 Knote, 2019, Towards solving the personalization-privacy paradox for smart personal assistants O'Brolchain, 2016, The convergence of virtual reality and social networks: threats to privacy and autonomy, Sci. Eng. Ethics, 22, 1, 10.1007/s11948-014-9621-1 Hong, 2014, A framework and guidelines for context-specific theorizing in information systems research, Inf. Syst. Res., 25, 111, 10.1287/isre.2013.0501 Xu, 2009, The role of push-pull technology in privacy calculus: the case of location-based services, J. Manag. Inf. Syst., 26, 135, 10.2753/MIS0742-1222260305 Xu, 2012, Research note—effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: a study of location-based services, Inf. Syst. Res., 23, 1342, 10.1287/isre.1120.0416 Dezhi, 2003, A framework for classifying personalization scheme used on e-commerce websites, 12 Gursoy, 2019, Consumers acceptance of artificially intelligent (Ai) device use in service delivery, Int. J. Inf. Manag., 49, 157, 10.1016/j.ijinfomgt.2019.03.008 Leino-Kilpi, 2001, Privacy: a review of the literature, Int. J. Nurs. Stud., 38, 663, 10.1016/S0020-7489(00)00111-5 Burgoon, 1982, Privacy and communication, Ann. Int. Commun. Assoc., 6, 206 Karwatzki, 2017, Beyond the personalization–privacy paradox: privacy valuation, transparency features, and service personalization, J. Manag. Inf. Syst., 34, 369, 10.1080/07421222.2017.1334467 Aguirre, 2015, Unraveling the personalization paradox: the effect of information collection and trust-building strategies on online advertisement effectiveness, J. Retail., 91, 34, 10.1016/j.jretai.2014.09.005 Li, 2013, Compressed sensing signal and data acquisition in wireless sensor networks and internet of things, IEEE Trans. Ind. Inform., 9, 2177, 10.1109/TII.2012.2189222 Haggerty, 2000, The surveillant assemblage, Br. J. Sociol., 51, 605, 10.1080/00071310020015280 Wang, 2019, Data fusion in cyber-physical-social systems: state-of-the-art and perspectives, Inf. Fusion, 42, 10.1016/j.inffus.2018.11.002 Hampapur, 2005, Smart video surveillance: exploring the concept of multiscale spatiotemporal tracking, IEEE Signal Process Mag., 22, 38, 10.1109/MSP.2005.1406476 Liang, 2014, Personalized content recommendation and user satisfaction: theoretical synthesis and empirical findings, J. Manag. Inf. Syst., 23, 45, 10.2753/MIS0742-1222230303 Junglas, 2006, The U-constructs: four information drives, Commun. Assoc. Inf. Syst., 17, 569 Featherman, 2003, Predicting E-services adoption: a perceived risk facets perspective, Int. J. Hum. Comput. Stud., 59, 451, 10.1016/S1071-5819(03)00111-3 Hsu, 2016, An empirical examination of consumer adoption of internet of things services: network externalities and concern for information privacy perspectives, Comput. Hum. Behav., 62, 516, 10.1016/j.chb.2016.04.023 Zhang, 2019, Consumer experience and adoption intention of internet of things services: the impact of network externalities, J. Digit. Converg., 17, 177 Hong, 2020, What will be the possible barriers to consumers’ adoption of smart home services?, Telecomm. Policy, 44, 1, 10.1016/j.telpol.2019.101867 McLean, 2019, Hey Alexa … Examine the variables influencing the use of artificial intelligent in-home voice assistants, Comput. Hum. Behav., 28, 10.1016/j.chb.2019.05.009 Davis, 2020, Five processes in the platformisation of cultural production: amazon and its publishing ecosystem, Aust. Hum. Rev., 66 Foltz, 2020, Mobile users’ information privacy concerns instrument and Iot, Inf. Comput. Security, 28, 359, 10.1108/ICS-07-2019-0090 Monteiro, 2019, Synthetic knowing: the politics of the internet of things, MIS Q., 43, 167, 10.25300/MISQ/2019/13799 Lichy, 2017, Big data is watching you: opportunities and challenges from the perspective of young adult consumers in Russia, J. Mark. Manag., 33, 719, 10.1080/0267257X.2017.1313301 Sharron, 2016, The internet of things—evaluating the interplay of interoperability, industry standards and related ip licensing approaches, Licens. J., 36, 8 Lin, 2016, The moderate role of perceived surveillance for value perception in solomo services continuance Kim, 2019, Willingness to provide personal information: perspective of privacy calculus in Iot services, Comput. Hum. Behav., 92, 273, 10.1016/j.chb.2018.11.022 Lowry, 2018, Why security and privacy research lies at the centre of the information systems (is) artefact: proposing a bold research agenda, Eur. J. Inf. Syst., 26, 546, 10.1057/s41303-017-0066-x Solove, 2006, A taxonomy of privacy, Univ. PA. Law Rev., 154, 477, 10.2307/40041279 Guhr, 2020, Privacy concerns in the smart home context, SN Appl. Sci., 2, 1, 10.1007/s42452-020-2025-8 Crossler, 2019, Why Would I use location-protective settings on my smartphone? Motivating protective behaviors and the existence of the privacy knowledge–belief gap, Inf. Syst. Res., 30, 995, 10.1287/isre.2019.0846 Komninos, 2014, Survey in smart grid and smart home security: issues, challenges and countermeasures, IEEE Commun. Surveys Tutorials, 16, 1933, 10.1109/COMST.2014.2320093 Xu, 2011, Information privacy concerns: linking individual perceptions with institutional privacy assurances, J. Assoc. Inf. Syst., 12, 798 Chen, 2018, Does endowing a product with life make one feel more alive? The effect of product anthropomorphism on consumer vitality, J. Assoc. Consum. Res., 3, 503, 10.1086/698493 Aggarwal, 2011, When brands seem human, do humans act like brands? automatic behavioral priming effects of brand anthropomorphism, J. Consum. Res., 39, 307, 10.1086/662614 Venkatesh, 2003, User acceptance of information technology: toward a unified view, MIS Q., 27, 425, 10.2307/30036540 Tsai, 2019, Acceptance and resistance of telehealth: the perspective of dual-factor concepts in technology adoption, Int. J. Inf. Manag., 49, 34, 10.1016/j.ijinfomgt.2019.03.003 James, 2019, Using organismic integration theory to explore the associations between users' exercise motivations and fitness technology feature set use, MIS Q., 43, 287, 10.25300/MISQ/2019/14128 Hu, 2021, Can Ai artifacts influence human cognition? The effects of artificial autonomy in intelligent personal assistants, Int. J. Inf. Manag., 56, 1, 10.1016/j.ijinfomgt.2020.102250 Kummer, 2017, Technology-induced anxiety: manifestations, cultural influences, and its effect on the adoption of sensor-based technology in German and Australian hospitals, Inf. Manag., 54, 73, 10.1016/j.im.2016.04.002 Warkentin, 2017, Shared benefits and information privacy what determines smart meter technology adoption, J. Assoc. Inf. Syst., 18, 758 Armstrong, 1977, Estimating nonresponse bias in mail surveys, J. Mark. Res., 14, 396, 10.1177/002224377701400320 Liang, 2007, Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management, MIS Q., 31, 59, 10.2307/25148781 Lynn, 2012, Lateral collinearity and misleading results in variance-based sem: an illustration and recommendations, J. Assoc. Inf. Syst., 13, 546 Lohmoller, 1988, The PLS program system: latent variables path analysis with partial least squares estimation, Multivariate Behav. Res., 23, 125, 10.1207/s15327906mbr2301_7 Becker, 2012, Hierarchical latent variable models in pls-sem: guidelines for using reflective-formative type models, Long Range Plann., 45, 359, 10.1016/j.lrp.2012.10.001 Hou, 2019, The involvement paradox: the role of cognitive absorption in mobile instant messaging user satisfaction, Ind. Manag. Data Syst., 119, 881, 10.1108/IMDS-06-2018-0245 Zhang, 2020, How social-media-enabled co-creation between customers and the firm drives business value? The perspective of organizational learning and social capital, Inf. Manag., 57, 10.1016/j.im.2019.103200 Straub, 2004, Validation guidelines for is positivist research, Commun. Assoc. Inf. Syst., 13, 380 Chin, 1997, Advancing the theory of adaptive structuration: the development of a scale to measure faithfulness of appropriation, Inf. Syst. Res., 8, 342, 10.1287/isre.8.4.342 Fornell, 1981, Evaluating structural equation models with unobservable variables and measurement error, J. Mark. Res., 18, 39, 10.1177/002224378101800104 Henseler, 2016, Using PLS path modeling in new technology research: updated guidelines, Ind. Manag. Data Syst., 116, 2, 10.1108/IMDS-09-2015-0382 Chin, 2003, A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study, Inf. Syst. Res., 14, 189, 10.1287/isre.14.2.189.16018 Gerbing, 1984, On the meaning of within-factor correlated measurement errors, J. Consum. Res., 11, 572, 10.1086/208993 Law, 1998, Toward a taxonomy of multidimensional constructs, Acad. Manag. Rev., 23, 741, 10.2307/259060 Petter, 2007, Specifying formative constructs in information systems research, MIS Q., 31, 623, 10.2307/25148814 Xu, 2008, Combining empirical experimentation and modeling techniques: a design research approach for personalized mobile advertising applications, Decis. Support Syst., 44, 710, 10.1016/j.dss.2007.10.002 Bagozzi, 1982 Aiken, 1991 Hayes, 2013 Wang, 2021, Role stressors, job satisfaction, and employee creativity: the cross-level moderating role of social media use within teams, Inf. Manag., 58, 1, 10.1016/j.im.2020.103317 Edwards, 2007, Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis, Psychol. Methods, 12, 1, 10.1037/1082-989X.12.1.1 Morosan, 2016, Modeling guests’ intentions to use mobile apps in hotels: the roles of personalization, privacy, and involvement, Int. J. Contemp. Hosp. Manag., 28, 1968, 10.1108/IJCHM-07-2015-0349 Banks, 2021, Good robots, bad robots: morally valenced behavior effects on perceived mind, morality, and trust, Int. J. Soc. Robot., 2021, 10.1007/s12369-020-00692-3 Kim, 2019, Smart homes as product-service systems: two focal areas for developing competitive smart home appliances, Serv. Sci., 11, 292, 10.1287/serv.2019.0248 Kininmonth, 2018, Privacy concerns and acceptance of government surveillance in Australia Galluccio, 2011, Context privacy in the internet of things, 61 Kolkowska, 2015, Privacy Dimensions in design of smart home systems for elderly people Padyab, 2018, Exploring the dimensions of individual privacy concerns in relation to the internet of things use situations, Digit. Policy, Regul. Govern., 20, 528, 10.1108/DPRG-05-2018-0023