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Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence

Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence
Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence
Mobile apps utilize the features of a mobile device to offer an ever-growing range of functionalities. This vast choice of functionalities is usually available for a small fee or for free. These apps access the user’s personal data, utilizing both the sensors on the device and big data from several sources. Nowadays, Artificial Intelligence (AI) is enhancing the ability to utilize more data and gain deeper insight. This increase in the access and utilization of personal information offers benefits but also challenges to trust. Using questionnaire data from Germany, this research explores the role of trust from the consumer’s perspective when purchasing mobile apps with enhanced AI. Models of trust from e-commerce are adapted to this specific context. A model is proposed and explored with quantitative methods. Structural Equation Modeling enables the relatively complex model to be tested and supported. Propensity to trust, institution-based trust, perceived sensitivity of personal information, and trust in the mobile app are found to impact the intention to use the mobile app with enhanced AI.
trust, information privacy, artificial intelligence, mobile commerce, mobile apps, big data
2673-6470
286-299
Zarifis, Alex
7622e840-ba78-4a4f-879b-6ba0f62363cc
Fu, Shixuan
d2d75a72-9d84-4af0-8073-db4383797ecc
Zarifis, Alex
7622e840-ba78-4a4f-879b-6ba0f62363cc
Fu, Shixuan
d2d75a72-9d84-4af0-8073-db4383797ecc

Zarifis, Alex and Fu, Shixuan (2023) Re-evaluating trust and privacy concern when purchasing a mobile app: Re-calibrating for the increasing role of Artificial Intelligence. digital, 3 (4), 286-299. (doi:10.3390/digital3040018).

Record type: Article

Abstract

Mobile apps utilize the features of a mobile device to offer an ever-growing range of functionalities. This vast choice of functionalities is usually available for a small fee or for free. These apps access the user’s personal data, utilizing both the sensors on the device and big data from several sources. Nowadays, Artificial Intelligence (AI) is enhancing the ability to utilize more data and gain deeper insight. This increase in the access and utilization of personal information offers benefits but also challenges to trust. Using questionnaire data from Germany, this research explores the role of trust from the consumer’s perspective when purchasing mobile apps with enhanced AI. Models of trust from e-commerce are adapted to this specific context. A model is proposed and explored with quantitative methods. Structural Equation Modeling enables the relatively complex model to be tested and supported. Propensity to trust, institution-based trust, perceived sensitivity of personal information, and trust in the mobile app are found to impact the intention to use the mobile app with enhanced AI.

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Re-evaluating trust and privacy concern when purchasing a mobile app Re-calibrating for the increasing role of Artificial Intelligence digital-03-00018-v2 - Version of Record
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Accepted/In Press date: 6 October 2023
Published date: 13 October 2023
Keywords: trust, information privacy, artificial intelligence, mobile commerce, mobile apps, big data

Identifiers

Local EPrints ID: 490174
URI: http://eprints.soton.ac.uk/id/eprint/490174
ISSN: 2673-6470
PURE UUID: 6eeebaa7-43af-447f-89e5-b57ad22cc17d
ORCID for Alex Zarifis: ORCID iD orcid.org/0000-0003-3103-4601

Catalogue record

Date deposited: 16 May 2024 16:39
Last modified: 06 Jun 2024 02:21

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Contributors

Author: Alex Zarifis ORCID iD
Author: Shixuan Fu

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