The DOI matches its Crossref record; 79 of the 81 references it cites were found in a registry or an index.
Trust in a specific technology: An investigation of its components and measures
Abstract
Trust plays an important role in many Information Systems (IS)-enabled situations. Most IS research employs trust as a measure of interpersonal or person-to-firm relations, such as trust in a Web vendor or a virtual team member. Although trust in other people is important, this article suggests that trust in the Information Technology (IT) itself also plays a role in shaping IT-related beliefs and behavior. To advance trust and technology research, this article presents a set of trust in technology construct definitions and measures. We also empirically examine these construct measures using tests of convergent, discriminant, and nomological validity. This study contributes to the literature by providing: (a) a framework that differentiates trust in technology from trust in people, (b) a theory-based set of definitions necessary for investigating different kinds of trust in technology, and (c) validated trust in technology measures useful to research and practice.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Trustworthiness judgments in humans or technology have different characteristics, yet they both are premised on the same underlying contextual conditions: risk, uncertainty and lack of control (McKnight et al. 2011).”
From Explaining Why the Computer Says No: Algorithmic Transparency Affects the Perceived Trustworthiness of Automated Decision‐Making (2023) · cites this paper as McKnight et al. 2011
In the citing paper
“Trust in technology has previously been seen in the light of the technology's functionality, ability to provide help and operational reliability and the technology provider's integrity, benevolence and competence-including privacy aspects (McKnight et al., 2011;Prakash and Das, 2020;Ta et al., 2020).”
From My Chatbot Companion - a Study of Human-Chatbot Relationships (2021) · cites this paper as McKnight et al., 2011
In the citing paper
“In the canonical models of trust formation, such (Giddens, 1990; Mayer et al., 1995; McKnight et al., 2011; Misztal, 1996) trust is described to have a number of different components. First, trust depends on the personal characteristics of the trustor, such as their propensity to trust, something which I do not discuss in this article. Second, trust is a factor of the perceived or actual char”
From Mediated trust: A theoretical framework to address the trustworthiness of technological trust mediators (2021) · cites this paper as McKnight et al., 2011
In the citing paper
“Nevertheless, trust is a complex concept and is built upon human users’ interaction and consequent assessment of the system from cognitive, emotional, and social dimensions [91-93].”
From Generative AI in medical practice: in-depth exploration of privacy and security challenges (2024) · cites this paper as [93]
In the citing paper
“Individual differences of users (e.g., gender, culture, age, and personality) are closely related to the propensity for or tendency toward technology users may manifest or develop (Gefen et al., 2008; McKnight et al. 2011).”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as McKnight et al. 2011
In the citing paper
“Proposition 6b. The greater the reliability an algorithm demonstrates, the higher the probability of building trust in AI algorithms over time.”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as McKnight et al., 2011
In the citing paper
“One important factor for initial trust is the user's propensity to trust, which, being tacit, bestows a positive impact on this starting phase and tends to remain stable over time (McKnight et al. 2011).”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as McKnight et al. 2011
In the citing paper
“Specific trust in people and trust in technology not only differ in terms of the nature of the object of dependence but also on important trusting beliefs.”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“Interpersonal trusting beliefs reflect judgments that the other party has suitable attributes and motives for performing as expected in a risky situation (Mayer et al. 1995), whereas technology-related trust necessarily reflects beliefs about a technology's characteristics rather than its motives (McKnight et al. 2011).”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“Most IS research nowadays employs a dualistic perspective on trust (see Table 1).First, trust in a specific person or organization (a moral and volitional agent) (Lankton et al. 2015;McKnight et al. 2011), such as trust in an e-vendor (Gefen et al. 2003) or virtual team members (Robert et al. 2009).”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“In contrast, individuals' trust in technology commonly concerns the technology's functionality (i.e., providing features needed to complete a task), its helpfulness (i.e., help functions will provide necessary advice), and its reliability (i.e., technology will consistently operate properly) (McKnight et al. 2011;Thatcher et al. 2010).”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“Trust plays a particularly important role in almost any ISenabled situation in which either uncertainty prevails or undesirable outcomes are possible (McKnight et al. 2011).”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“Specific trust in persons and technology can be further positioned in a nomological net of trust, comprising general trusting beliefs and institution-based trust as antecedents and trusting intentions as consequence of specific trust in persons or technology (McKnight et al. 2011;McKnight et al. 2002; see Fig. 1).”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“The trust literature suggests a causal ordering among trust constructs, such that an individual's general trusting beliefs in people or technology directly influences institutionbased trust and indirectly shapes trust in a specific person or technology (McKnight et al. 2011;McKnight and Chervany 2001).”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
In the citing paper
“In line with the view of institutions-based trust in technology being an antecedent to trust in a specific technology (McKnight et al. 2011), we argue, that the limited availability of large, high-quality data in certain areas, which constraints our ability to promote human well-being through AI in those areas, could lead society to perceive the entire class of AIbased systems as not beneficent (”
From Trustworthy artificial intelligence (2021) · cites this paper as McKnight et al. 2011
Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Tabachnick, B. G., & Fidell, L. S. (1983) · Cited by 79,882
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Significance tests and goodness of fit in the analysis of covariance structures.
Bentler, P. M., & Bonett, D. G. (1980) · Psychological Bulletin · doi:10.1037/0033-2909.88.3.588 · Cited by 20,015
An integrative model of organizational trust
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995) · The Academy of Management Review · doi:10.2307/258792 · Cited by 10,736
Trust: The Social Virtues and the Creation of Prosperity
Schneider, P. A., & Fukuyama, F. (1996) · Journal of Marketing · doi:10.2307/1251846 · Cited by 10,493
Flagged first, then by citations
2 of the 81 references couldn’t be matched to a known paper.
Research works printed but not linked: 8
- Berscheid E., Close Relationships
- 10.5465/amr.1998.926629 · DOI · Paper page
- Golembiewski R. T. and Mcconkie M. 1975. The centrality of interpersonal trust in group processes. In Theories of Group Processes G. L. Cooper Ed. John Wiley & Sons London 131--185. Golembiewski R. T. and Mcconkie M. 1975. The centrality of interpersonal trust in group processes. In Theories of Group Processes G. L. Cooper Ed. John Wiley & Sons London 131--185.
- 10.5555/2017317.2017325 · DOI
- Lewicki R. J., 1996, Organizations: Frontiers of Theory and Research
- 10.5465/amr.1995.9508080335 · DOI · Paper page
- Mcknight D. H., 2005, Trust in information technology. In The Blackwell Encyclopedia of Management, Management Information Systems, G. B. Davis, Ed., Blackwell, Malden, MA, 7, 329
- 10.5465/amr.1998.926622 · DOI · Paper page
Cited by
Sorted by citations
Items 901–999 of 999
Weissenfels, S., Kappler, K. E., Smolnik, S., & Menzel, M. (2022) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2022.496
van Bussel, M. V., Odekerken-Schröder, G., Ou, C., Swart, R., & Jacobs, M. (2022) · doi:10.2196/preprints.36535
Patnaik, P. (2022) · Advances in electronic government, digital divide, and regional development book series · doi:10.4018/978-1-7998-9710-1.ch006
Comparing AI and Human Feedback: The Role of Source in Feedback Perceptions
Nargesi, M. N. (2021) · doi:10.46569/20.500.12680/hd76s531w · Cited by 1
Meeting Strangers Online: Feature Models for Trustworthiness Assessment
Borchert, A., Ferreyra, N. E. D., & Heisel, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-14785-2_1
Wüest, R. S. A. S. (2022) · IADIS International Conference on e-Society (ES) · doi:10.33965/es_ml2022_202202l017
Gonzalez, J. C. (2022) · Open Access Victoria University of Wellington | Te Herenga Waka (Figshare) · doi:10.26686/wgtn.20579568 · Cited by 1
Identity Management for Cyber-Physical Systems
Preuveneers, D. (2022) · Springer eBooks · doi:10.1007/978-3-642-27739-9_1727-2
Koelmann, H., Müller, K., Niemann, M., & Riehle, D. M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-18253-2_7
What Drives Consumer’s Self-disclosure in Mobile Payment: An Investigate in China
Wu, S., Tan, G. W., & Aw, E. C. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-25274-7_12
Uporabljati ali ne uporabljati
Trkman, M. (2023) · Fakulteta za družbene vede eBooks · doi:10.51936/9789612950361 · Cited by 1
Study on the Discursive Strategies of Wired to Repair Trust in Blockchain
Su, Q. (2023) · Scientific and Social Research · doi:10.26689/ssr.v5i2.4727 · Cited by 1
Eapen, B. R., Baba, V. V., & Sohail, M. (2023) · Metamorphosis · doi:10.1177/09726225231157175
Building Trust-based Dynamic IT Capabilities: The Case of a State-owned Enterprise in South Africa
Mubaiwa, N., & Naidoo, R. (2023) · IST-Africa Conference (IST-Africa) · doi:10.23919/ist-africa60249.2023.10187790
Richter, S.-L., & Resch, D. (2023) · Springer eBooks · doi:10.1007/978-3-031-32538-0_21
Evaluating Flexibility and Trust in Complex Decision Scenarios Using Decision Support SystemsPreprint
Reiners, S., Müller, L. S., Riehle, D. M., Becker, J., & Hertel, G. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4528603
Ologeanu‐Taddei, R., Guthrie, C. H., & Wamba, S. F. (2023) · Management international · doi:10.59876/a-4x1b-x300
Intelligent Virtual Assistants (IVAs): Trust and Zero Trust
Wylde, A. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-37963-5_8
Implications of the Instruments View of Computer Simulation
Alvarado, R. (2023) · Synthese Library/Synthese library · doi:10.1007/978-3-031-38647-3_7
Matlala, N. P. (2023) · Journal of Marketing and Consumer Behaviour in Emerging Markets · doi:10.7172/2449-6634.jmcbem.2023.2.3
An Empirical Investigation on Electronic Government Services Continuance and Trust
Ahmad, M. O., Ahmad, I., & Khan, I. S. (2023) · IEEE International Symposium on Technology and Society (ISTAS) · doi:10.1109/istas57930.2023.10306133
Samonte, M. J. C., Escarillo, J. G. M., Go, K., Landrito, N. B. A., & Randhawa, J. K. (2023) · International Conference on Information Management and Management Science (IMMS) · doi:10.1145/3625469.3625490
Political Trust, Accessibility and Privacy – Issues That Blockchain Can (Not) Solve?Preprint
Stanojević, A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4688056
von Kalckreuth, N., & Feufel, M. A. (2024) · medRxiv · doi:10.1101/2024.02.07.24302380
From Cash to Central Bank Digital Currency: Can Gen Z Adopt It?
Khoirunnisa, A. N., Azka, M. S. T., & Shofiatin, N. (2024) · East Java Economic Journal · doi:10.53572/ejavec.v8i1.122
Trust Transfer in the Adoption of Autonomous Last Mile ServicesPreprint
Wang, S., & Huang, Z. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4760812
How individuals perceive and process diagnostic device errors
Becker, M. Y., & Matt, C. (2024) · Journal of Decision System · doi:10.1080/12460125.2024.2354578
Hao, H., Lee, Y. W., Sharko, M., Li, Q., & Zhang, Y. (2024) · doi:10.2196/preprints.60862
Investigating Trust Perceptions Toward AI in Industrial Designers
Klimava, Y., Beltrão, G., & Paramonova, I. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-66594-3_20
A Vision to Enhance Trust Requirements for Peer Support Systems by Revisiting Trust Theories
Gheidar, Y., Lessard, L., & Yao, Y. (2024) · IEEE International Requirements Engineering Conference (RE) · doi:10.1109/re59067.2024.00052 · Cited by 1
Guiding Firms in Navigating Innovation: E-Learning as Driver to Enhance Trust in Technology
Ziegler, A., Peisl, T. C., & Brehm, J. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-71142-8_8
Trustful Trading in Shared Augmented Reality
Ritter, M., Liew, K., Wickramasinghe, Y. S., & Lukosch, S. (2024) · Symposium on Spatial User Interaction · doi:10.1145/3677386.3682086 · Cited by 1
Dao, H. M., Nguyen, L. H., Duong, L. D. D., & Nguyen, T. T. M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4975338
Digital Transformation and Organizational Performance: A Study of the Nigerian Immigration Service
Olota, O. O., Balogun, E. O., & Babawale, O. E. (2024) · Revista científica profundidad construyendo futuro · doi:10.22463/24221783.4519
Masciotra, V., & Boudrias, J. (2024) · Ad machina l avenir de l humain au travail · doi:10.1522/radm.no8.1840
Thirukketheeswaran, S., Meyer‐Waarden, L., & Kuhn, M. M. (2024) · Developments in marketing science: proceedings of the Academy of Marketing Science · doi:10.1007/978-3-031-76193-5_4
Moray, R. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-8537-7_30
Identity Management for Cyber-Physical Systems
Preuveneers, D. (2025) · Springer eBooks · doi:10.1007/978-3-030-71522-9_1727
Eco-Anxiety and Insurance: Behavioral Experiments with Large Language ModelsPreprint
Vansteenberghe, É. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5054775
The Impact of Regulation on Blockchain and DeFiPreprint
Filippi, P. D. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5071991
The Model of Benevolence for Trust in Multi-agent System
Żurek, T., Wyner, A., & van Engers, T. (2025) · Smart innovation, systems and technologies · doi:10.1007/978-981-97-6469-3_2
Virtual Reality Applications for a Robo-Advisory System: Impact and Challenges
Yow, L. (2025) · The Journal of FinTech · doi:10.1142/s2705109925500038
Reducing Customer Complaints through Algorithm-Generated Feedback: Evidence from a Field Experiment
Deng, H., Zhuang, X., Du, M., Wang, L., & Wu, D. (2025) · Journal of Systems Science and Systems Engineering · doi:10.1007/s11518-025-5659-7
Bằng, N. V., Quốc, H. P., & Huy, K. T. (2025) · Tạp chí Kinh tế và Phát triển · doi:10.33301/jed.vi.2053
Who Uses Mobile Payment Apps in Developing Countries? Literacy, Education, and the Role of TrustPreprint
Hunter, S., Chai, A., Morgan, P., Deshpande, S., Westermann, S., & Rohde, N. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5258625
The effects of disclosing an algorithm’s inner workings and analytic thinking on algorithm reliance
Pinzger, A. (2025) · Journal of Management Control · doi:10.1007/s00187-025-00391-y
Designing for Trust: Integrating Self-referencing in Large Language Model-Based Health Coaching
Meywirth, S., Janson, A., & Söllner, M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93976-1_19 · Cited by 2
Factors Influencing Behavioral Intention to Use Automated Parking Systems in Bangkok
Tankongchamruskul, W., Chaiyasoonthorn, W., & Chaveesuk, S. (2025) · Springer proceedings in business and economics · doi:10.1007/978-981-96-4116-1_20
The Impact of Human-AI Collaboration on User Satisfaction: The Role of Trust
Chang, L., & Yao, Y. (2025) · doi:10.1109/ceeis65979.2025.00012 · Cited by 1
Cloarec, J., Meyer‐Waarden, L., Timmler, K., Thiele, S., Weiß, M., & Wiese, M. (2025) · Recherche et Applications en Marketing (French Edition) · doi:10.1177/07673701251347492
Trust in Voice Assistants: A Multidimensional Conceptualization Based on In-Home User InterviewsPreprint
Frehmann, K., Ziegele, M., Cruciger, R., Grobe, A.-K., & Bavaj, F. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5340213
From Innovation to Use: Configurational Pathways to High Fintech Use Across User Groups
Ryu, H.-S. (2025) · Sustainability · doi:10.3390/su17177762
Li, W., Yiğitcanlar, T., Nili, A., & Browne, W. N. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5492137
See, K., & Li, X. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5501125 · Cited by 1
Mosa, H., & Al-Haija, Q. S. A. (2025) · Springer eBooks · doi:10.1007/978-3-031-97007-8_1
Awad, B. K. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-5013-2_19
Vertrauenswürdige Künstliche Intelligenz
Schmid, U. (2025) · Springer eBooks · doi:10.1007/978-3-662-71567-3_10
Leveraging Large Language Models for Dataset Discovery
Chen, T., Schott, K., Mathiak, B., & Kern, D. (2025) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.1242
Thomaschewski, L., Tausch, A., Berretta, S., Vogel, O., & Kluge, A. (2025) · Zeitschrift für wirtschaftlichen Fabrikbetrieb · doi:10.1515/zwf-2025-1113
Merikko, J., Leppänen, L., & Mannila, L. (2025) · AI & Society · doi:10.1007/s00146-025-02699-8 · Cited by 2
Trust Design Framework in Blockchain-Enabled Supply Chains
Ostern, N., Simonet, J., & Obwegeser, N. (2025) · Springer eBooks · doi:10.1007/978-3-031-90210-9_16
The Influences of AI Locus of Causality and Trust in AI on the Adoption of AI Advice
Lee, K., Cho, W., & Woo, H. (2025) · Journal of Organizational Computing and Electronic Commerce · doi:10.1080/10919392.2025.2574195
Fang, C., Guo, F., & Belpaeme, T. (2025) · IEEE RO-MAN · doi:10.1109/ro-man63969.2025.11217721
Iglesias, P., Cameron, R., & Davison, C. (2025) · Asia Pacific Journal of Human Resources · doi:10.1111/1744-7941.70038
Towards Human-Centered Digital Health Interventions
Kostick, K. M., & Storch, E. A. (2025) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2025.10.004
Rahman, W. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5789189
Rahman, W. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5855384
Rebranding Loyalty: The Phygital Bridge of Ethical Brand Experiences
Alven, S. (2025) · International Journal of Commerce and Management Research Studies (IJCMRS) · doi:10.63090/ijcmrs/3049.1908.0018
Trust, Try, Buy, and Belong: How Does AI Create a Loyalty Loop in Hotels?
Wisker, Z. L., Myshkina, I., & Alani, N. H. S. (2025) · Tourism and Hospitality · doi:10.3390/tourhosp6050276 · Cited by 2
van Bussel, M. J. P., Odekerken‐Schröder, G., Ou, C., Swart, R., & Jacobs, M. (2022) · Figshare · doi:10.6084/m9.figshare.20277939
van Bussel, M. J. P., Odekerken‐Schröder, G., Ou, C., Swart, R., & Jacobs, M. (2022) · Figshare · doi:10.6084/m9.figshare.20277936
Designing Ethical Nudges: Aesthetic Principles for Trustworthy AI Marketing
Rose, N. (2025) · International Journal of Commerce and Management Research Studies (IJCMRS) · doi:10.63090/ijcmrs/3049.1908.0020
Evaluating user perceptions of trust in persuasive technology: A comparative study
Rahman, P., & Adaji, I. (2025) · International Conference on Information Technology for Social Good (GoodIT) · doi:10.1145/3748699.3749782 · Cited by 2
Conditions for the acceptance of advertising content generated by generative artificial intelligence
Sułkowski, Ł., & Kaczorowska–Spychalska, D. (2025) · Human Technology · doi:10.14254/1795-6889.2025.21-3.8
Research on Artificial Intelligence Technology Trust of University Teachers
Nie, Y., Cui, Y., & Lou, S. (2025) · International Conference on Implementing Generative AI into Telecommunication and Digital Innovation · doi:10.1145/3771792.3774393
Mesleki Gelişimde Çevrim içi Öğrenme Ortamlarına Yönelik Öğretmen Güveni Ölçeği Geliştirme Çalışması
Arslan, S., & Özkök, G. A. (2025) · Ondokuz Mayis Univ Egitim Fakultesi · doi:10.7822/omuefd.1664833
How can maritime automation and autonomy be safely implemented? A mixed-method topic model
Aalberg, A. L., & Kongsvik, T. (2026) · WMU Journal of Maritime Affairs · doi:10.1007/s13437-025-00401-9
Halal spas in Indonesia: design, privacy, certification, and booking intention
Ilyas, G. B., & Ilyas, M. F. G. B. (2026) · International Journal of Spa and Wellness · doi:10.1080/24721735.2026.2616169
Sim, M., & Kim, H. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6202730
AI-Driven Assessment of Project Management Tool Adoption,in Multinational Technology FirmsPreprint
Desai, P., Patel, S., Shah, B., & Patel, V. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6219012
Kim, T., Ling, T.-W., & Peng, W. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6259856
Influence of an Innovative HMI for Highly Automated Driving on Trust
Rauh, N., Günther-Gommlich, T., Maas, K.-A., Hollander, C., & Beggiato, M. (2026) · Advances in Science, Technology & Innovation/Advances in science, technology & innovation · doi:10.1007/978-3-032-03488-5_6
Ethical, legal and societal implications of Tactile Internet with Human-in-the-Loop
Kaesling, K., Engesser, S., Fairhurst, M. T., Jugov, T., Klös, V., Krzywinski, J., Lauber-Rönsberg, A., Neumann, N., Pannasch, S., Strufe, T., et al. (2026) · Elsevier eBooks · doi:10.1016/b978-0-44-330044-8.00037-3
CONFIGURING TRUST IN GENERATIVE AI: INTEGRATING TRUST THEORY AND USER SEGMENTATIONPreprint
Akhmedova, A., Marimón, F., Mas‐Machuca, M., & Amat‐Lefort, N. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6278331
Limberg, S. (2026) · Computers and Education Open · doi:10.1016/j.caeo.2026.100345 · Cited by 2
Design Thinking and AI: Facilitating HCAI Solutions
Böckle, M., Mohme, U., & Bick, M. (2026) · Springer eBooks · doi:10.1007/978-981-97-8440-0_73-2
Monod, E., Korotkova, N., Joyce, E., Pan, H. H., Meythaler, A., Khalil, S., & Gibbs, J. (2026) · Review of Managerial Science · doi:10.1007/s11846-026-01006-z
Han, E., Wang, P., Santoso, M., Rastogi, K., & Bailenson, J. N. (2026) · Computers in Human Behavior · doi:10.1016/j.chb.2026.108975
Jeon, Y. E., & Park, H. S. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2638543
Uzochukwu, B. S. C., Cherima, Y. J., Enebeli, U. U., Okeke, C. C., Uzochukwu, A. C., Omoha, A. R., Hassan, B. O., Eronu, E. M., Yusuf, S. M., & Uzochukwu, K. A. (2026) · Research Square · doi:10.21203/rs.3.rs-9066307/v1
Joshi, R., Bengler, K. J., & Augustyniak, J. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-19687-3_8
Wang, Y., & Xu, C. (2026) · International Journal of Public Health · doi:10.3389/ijph.2026.1609017
Zhang, B., & Jia, T. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6431880
Reconfiguring Intimacy With AI Companions
Wenxi, W. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-6623-4.ch003
LUO, X., & Matthes, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6480584
Ma, L., & Lyu, B. (2026) · Work · doi:10.1177/10519815261427711
Metadata
- Authors
- Mcknight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F.
- Affiliations
- Michigan State University (US)
- Clemson University (US)
- Washington State University (US)
- Venue
- ACM Transactions on Management Information Systems
- Published
- 2011-06
- Volume
- 2
- Issue
- 2
- Pages
- 1-25
- ISSN
- 2158-656X (ISSN-L)
- 2158-6578
- OpenAlex
- W2037881738
- Semantic Scholar
- 1581959e828d2701b72702264bca37ca7f408124
- Cited by
- 1,185
- References
- 81
- Citations by year
- 2026: 273 · 2025: 182 · 2024: 147 · 2023: 131 · 2022: 110 · 2021: 95 · 2020: 74 · 2019: 38 · 2018: 36 · 2017: 15 · 2016: 19 · 2015: 14 · 2014: 23 · 2013: 22 · 2012: 4
- FWCI
- 37.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Management Information Systems (publishedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- trust in technology, interpersonal trust, trust measurement, construct validity, convergent validity, discriminant validity, nomological network, technology adoption, information systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
