Trust In Technology Research Articles

Is it all about fun? Self-service technology acceptance in Germany

ABSTRACT The introduction of self-service technology (SST), particularly self-checkout and self-scan services, has gained increasing attention from German retail. But to date, end-customer SST use has not developed extensively. The majority of German customers still prefer to use the traditional checkout service counter. The purpose of this paper is to explore how trust, fun, and usefulness can attract inexperienced prospective adopters and experienced customers to use SST. For this, our study investigated the intention to use an SST as a holistic system (self-scan and self-checkout) and considered trust in the SST technology for the first time. Also the interplay between fun and perceived usefulness has not been investigated before. The data were collected using an online questionnaire and in front of a German hypermarket that offers SST. The sample (n = 222) consists of both inexperienced and experienced customers. The data were analyzed using structural equation modeling in SmartPLS4. Results demonstrate fun is a decisive factor for a holistic SST system that incorporates the task of self-scanning and self-checkout. This also holds for trust and perceived usefulness. With regard to experienced and prospective users, the results show different effects in the importance of both groups. Fun is crucial for prospective users. For experienced users, benefits and trust become more important for long-term usage. Trust is an essential aspect for both user types. Managerial implications are discussed.

Artificial Intelligence Methods in Natural Language Processing: A Comprehensive Review

The rapid evolution of Artificial Intelligence (AI) since its inception in the mid-20th century has significantly influenced the field of Natural Language Processing (NLP), transforming it from a rule-based system to a dynamic and adaptive model capable of understanding the complexities of human language. This paper aims to offer a comprehensive review of the various applications and methodologies of AI in NLP, serving as a detailed guide for future research and practical applications. In the early sections, the paper elucidates the indispensable role of AI in NLP, highlighting its transition from symbolic reasoning to a focus on machine learning and deep learning, and its extensive applications in sectors such as healthcare, transportation, and finance. It emphasizes the symbiotic relationship between AI and NLP, facilitated by platforms like AllenNLP, which aid in the development of advanced language understanding models. Further, the paper explores specific AI techniques employed in NLP, including machine learning, Naive Bayes, and Support Vector Machines, and identifies pressing challenges and avenues for future research. It delves into the applications of AI in NLP, showcasing its transformative potential in tasks such as machine translation, facilitated by deep learning methods, and the development of chatbots and virtual assistants that have revolutionized human-technology interaction. The paper also highlights other fields impacted by AI techniques, including text summarization, sentiment analysis, and named entity recognition, emphasizing the efficiency and accuracy brought about by the integration of AI in these areas. In conclusion, the paper summarizes the remarkable advancements and persistent challenges in NLP, such as language ambiguity and contextual understanding, and underscores the need for diverse and representative labeled data for training. Looking forward, it identifies promising research avenues including Explainable AI, Few-shot and Zero-shot Learning, and the integration of NLP with other data modalities, aiming for a holistic understanding of multimodal data. The paper calls for enhanced robustness and security in NLP systems, especially in sensitive applications like content moderation and fake news detection, to foster trust and reliability in AI technologies. It advocates for continual learning in NLP models to adapt over time without losing previously acquired knowledge, paving the way for a future where AI and NLP work synergistically to understand and generate human language more effectively and efficiently.

My colleague is an AI! Trust differences between AI and human teammates

Purpose The purpose of this study was to investigate trust within human-AI teams. Trust is an essential mechanism for team success and effective human-AI collaboration. Design/methodology/approach In an online experiment, the authors investigated whether trust perceptions and behaviours are different when introducing a new AI teammate than when introducing a new human teammate. A between-subjects design was used. A total of 127 subjects were presented with a hypothetical team scenario and randomly assigned to one of two conditions: new AI or new human teammate. Findings As expected, perceived trustworthiness of the new team member and affective interpersonal trust were lower for an AI teammate than for a human teammate. No differences were found in cognitive interpersonal trust and trust behaviours. The findings suggest that humans can rationally trust an AI teammate when its competence and reliability are presumed, but the emotional aspect seems to be more difficult to develop. Originality/value This study contributes to human–AI teamwork research by connecting trust research in human-only teams with trust insights in human–AI collaborations through an integration of the existing literature on teamwork and on trust in intelligent technologies with the first empirical findings on trust towards AI teammates.

Exploring Vulnerabilities and Attack Vectors Targeting Pacemaker Devices in Healthcare

This technical paper investigates the vulnerabilities and potential threats posed by emerging technologies, specifically Bluetoothenabled patient pacemakers. With the advancements in healthcare technology, pacemakers now utilize Bluetooth connectivity for real-time monitoring and data transmission, offering patients and healthcare providers an important convenience. However, this technology also introduces significant security risks, leaving these life-sustaining devices susceptible to malicious attacks. Through an in-depth analysis of existing research, real-life incidents, and vulnerabilities identified by experts in the field, this paper will underscore the critical vulnerabilities present in pacemaker systems. Examples, including findings from researchers such as Billy Rios, Jonathon Butts, and Marie Moe, demonstrate the potential severity of these vulnerabilities. From remote control manipulation to unauthorized access to sensitive medical data, the threats posed by these vulnerabilities are substantial and potentially life-threatening. Moreover, this paper outlines advanced mitigation strategies essential for protecting patient pacemakers against these security risks. Recommendations include end-to-end encryption, whitelist device pairing, intrusion detection systems, and regular firmware updates, highlight the collaborative efforts required from patients, healthcare providers, and manufacturers to mitigate these risks effectively. This paper’s findings underscore the urgent need for robust cybersecurity measures in the design, implementation, and maintenance of pacemaker systems. Addressing these vulnerabilities is key for ensuring patient safety, maintaining privacy, and building trust in healthcare technology. The implications of this research extend beyond pacemaker security, emphasizing the broader importance of cybersecurity in medical devices and the importance of ongoing research and regulatory initiatives to protect patient health.

From Cash to Central Bank Digital Currency: Can Gen Z Adopt It?

This study aims to examine the intention of youth in Indonesia to adopt Central Bank Digital Currency (CBDC). A sample of 285 respondents was analyzed using SEM-PLS and in-depth interviews. The results of the study found that involvement facilitation, institutional trust, and technology trust had a significant effect on youth's intention to use CBDC. These findings emphasize the importance of building trust in technology and institutions, as well as increasing public confidence in the ability of central banks to launch and regulate CBDC systems. Empirical evidence also shows that facilitation and literacy provided by the authorities need to be a significant focus in addressing potential barriers to technology use among the public. Furthermore, there are maximum literacy facilities and consultation given can increase public confidence in CBDC provider authorities to continue to develop technology to the fullest.

Blockchain technology and supply chain performance: The role of trust and relational capabilities

Blockchain technology (BCT) has become a focal point of attention within the field of supply chain management (SCM), characterized as a transformative and disruptive technology capable of instilling transparency and trust. While parallels between BCT and the internet have been drawn, its practical application in SCM remains in an early stage, resulting in a limited body of literature and a pronounced debate with divergent perspectives concerning its impact in this SCM domain. Drawing upon the Relational View (RV) and Dynamic Capabilities View (DCV), this study aims to address this debate by investigating the role of BCT in enhancing supply chain performance. The study utilizes semi-structured interviews with 31 industry experts, followed by thematic analysis, to unveil the underlying mechanisms through which BCT influences supply chain performance. Our findings underscore the pivotal role of trust, facilitated by BCT features, in enhancing SC performance, emphasizing the interdependence of trust in technology, platforms, and SC members. Moreover, our study uncovers the substantial influence of supply chain uncertainty on the association between BCT and trust, acknowledging its pertinence in the modern business landscape. Additionally, we present a conceptual model that elucidates the relationships among BCT, trust, relational capabilities, and supply chain performance. Our qualitative investigation suggests that trust, relational capabilities, and dynamic capabilities sequentially mediate the association between BCT and supply chain performance. This research, while reaffirming the applicability of the original RV model in the context of BCT, contributes to a nuanced perspective by identifying additional associations within the relational view. Specifically, we identify knowledge sharing, effective governance, and resource complementarity as mediating factors in the relationship between relation-specific assets and relational rent. Our study provides practical advice to managers and practitioners. It stresses the need to understand how BCT impacts supply chain performance and the crucial role of trust. We also recommend nurturing relational capabilities in supply chain networks and considering the context-specific benefits of BCT, especially in uncertain environments. This understanding enables informed decision-making to tackle challenges and leverage opportunities.

Enhancing transparency in AI-powered customer engagement

This paper addresses the critical challenge of building consumer trust in AI-powered customer engagement by emphasising the necessity for transparency and accountability. Despite the potential of AI to revolutionise business operations and enhance customer experiences, widespread concerns about misinformation and the opacity of AI decision-making processes hinder trust. Surveys highlight a significant lack of awareness among consumers regarding their interactions with AI, alongside apprehensions about bias and fairness in AI algorithms. The paper advocates for the development of explainable AI models that are transparent and understandable to both consumers and organisational leaders, thereby mitigating potential biases and ensuring ethical use. It underscores the importance of organisational commitment to transparency practices beyond mere regulatory compliance, including fostering a culture of accountability, prioritising clear data policies and maintaining active engagement with stakeholders. By adopting a holistic approach to transparency and explainability, businesses can cultivate trust in AI technologies, bridging the gap between technological innovation and consumer acceptance, and paving the way for more ethical and effective AI-powered customer engagements.

A Conceptual Development of Digital Trade Adoption among Manufacturing Companies in China: A Technology Acceptance Model Approach

The proliferation of digital technologies has brought about transformative changes in various sectors, including manufacturing. In the context of China, a prominent manufacturing hub, the adoption of digital trade practices has emerged as a critical determinant of competitiveness and sustainability for manufacturing companies. This paper proposes a conceptual framework for understanding the factors influencing the adoption of digital trade among manufacturing firms in China, employing the Technology Acceptance Model (TAM) as a theoretical lens. Drawing upon extant literature and empirical insights, this conceptual paper identifies key constructs within the TAM framework, such as perceived usefulness, perceived ease of use, attitude toward digital trade, and behavioral intention, and adapts them to the specific context of digital trade adoption in the Chinese manufacturing sector. It explores how factors such as organizational readiness, technological infrastructure, government policies, and cultural factors influence the perceived usefulness and ease of use of digital trade platforms among manufacturing companies in China. Moreover, this paper extends the traditional TAM model by incorporating additional constructs such as trust in technology, perceived risk, and organizational innovativeness, which are deemed essential in understanding the complexities of digital trade adoption in a rapidly evolving technological landscape. It underscores the significance of trust-building mechanisms, risk mitigation strategies, and organizational culture in facilitating the successful implementation of digital trade initiatives within manufacturing enterprises in China. The proposed conceptual framework contributes to both theoretical and practical understandings of digital trade adoption by elucidating the interplay between technological factors, organizational dynamics, and contextual influences within the Chinese manufacturing context. By offering insights into the determinants of digital trade adoption and the mechanisms for enhancing acceptance and utilization of digital trade platforms, this paper aims to inform policymakers, industry practitioners, and scholars engaged in the promotion and facilitation of digital transformation within the manufacturing sector in China and beyond.

Bioelectrical impedance vector analysis as an indicator of malnutrition in children under five years with and without pneumonia in Mchinji District, Malawi: An exploratory mixed-methods analysis

Background Bioelectrical impedance vector analysis (BIVA) is a non-invasive approach to assessing body composition and cellular health, which may improve the assessment of nutritional status in sick children. We explored the reliability, clinical utility, and acceptability of BIVA, as an indicator of nutritional status for children under five years with and without pneumonia, in Malawi. Methods We conducted a parallel convergent mixed-methods exploratory study in Mchinji District Hospital, Malawi, in 2017. We recruited a convenience sample of children aged 0–59 months with clinical pneumonia, and without an acute illness. Children had duplicate anthropometric and BIVA measurements taken. BIVA measurements of phase angle were taken of the whole body, and trunk and arm segments. Reliability was assessed by comparing the variability in the two measures, and clinical utility by estimating the association between anthropometry and phase angle using linear regression. Focus group discussions with healthcare workers who had not previously used BIVA instrumentation were conducted to explore acceptability. Results A total of 52 children (24 with pneumonia and 28 healthy) were analysed. The reliability of sequential phase angle measurements was lower than anthropometric measurements, but trunk and arm segments performed better. The largest associations with phase angle were a negative relationship with weight-for-age z-score (WAZ) in children with pneumonia in the trunk segment, and a positive association with WAZ in the full body measurement in healthy children. Healthcare workers in focus group discussions expressed trust in BIVA technology and that it would enable more accurate diagnosis of malnutrition; however, they raised concerns about the sustainability and necessary resources to implement BIVA. Conclusions While healthcare workers were positive towards BIVA as a novel technology, implementation challenges should be expected. The differential direction of association between anthropometry and phase angle for children with pneumonia warrants further investigation.

Extended reality in education and training: Enhancing trustworthiness

Extended reality (XR) technology, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), has the potential to revolutionize education by providing immersive and interactive learning experiences. However, to ensure successful implementation and adoption of XR in education, it is crucial to establish trust among all stakeholders. This paper presents a comprehensive framework for enhancing trust in XR technology in education and Training. The framework addresses key considerations such as transparency, privacy, ethical use, user training, research, collaboration, accessibility, continuous improvement, risk mitigation, and long-term sustainability. By implementing this framework, educational institutions can build a foundation of trust that fosters the effective integration of XR in education, leading to improved learning outcomes and engagement.

Decision-making styles and trust across farmers and bankers: Global survey results

Understanding in which contexts professionals come to trust their gut is critical both for human relations as well as for human–computer interaction. A prominent viewpoint promotes a deliberate trust development approach for professionals in all industries and at all levels of organizations (people use good thinking). The use of intuition has also been related to trust development. There is little empirical research that illuminates the circumstances under which intuitive decision making versus deliberative decision making influences trust. Lack of trust in technology and information systems has been suggested as a bottleneck in advancement. Through a survey we aimed to better understand the phenomenon of intuitive decision making of farmers and bankers. The main research purpose is to compare and contrast decision making styles of two environmentally different professions from a heterogeneous sample from different countries. Our results suggest that one’s sector plays a main role, when professionals determine if they can trust information and communication technologies (ICTs) in the workplace. We inform suggestions for practice and guide future research into this important area of managerial cognition and decision-making.

Transactive memory systems in superteams: the effect of an intelligent assistant in virtual teams

PurposeResearchers explore the impact of an intelligent assistant in virtual teams by applying the theoretical lens of a transactive memory system (TMS) to understand the relationships between trust in a specific technology, knowledge sharing and knowledge application.Design/methodology/approachAn online survey was administered to a Qualtrics-curated panel of individual, US-based virtual team members utilizing an intelligent assistant with team collaboration software. Partial least squares structural equation modeling (PLS-SEM) was utilized to examine the hypothesized relationships of interest.FindingsResults suggest that knowledge application is strongly influenced by trust in a specific technology and knowledge sharing. Additionally, a transactive memory system positively increases trust in the intelligent assistant, and similarly, trust in the intelligent assistant has a significant positive relationship with knowledge sharing.Originality/valueThe research model contributes to our understanding of the impact of an intelligent assistant in virtual teams. Although the transactive memory system construct has been explored in various contexts and models, few have explored the impact of an intelligent assistant and trust in a specific technology.

Understanding consumers’ adoption of e-pharmacy in Qatar: applying the unified theory of acceptance and use of technology

Purpose This study aims to investigate the factors influencing the adoption of online pharmacies in Qatar using the unified theory of acceptance and use of technology-2 (UTAUT-2) framework. Specifically, this study examines the impact of performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness of behavioral intention, which in turn affects the adoption of online pharmacies. Furthermore, this study explores the moderating role of word-of-mouth (WOM) recommendations on the relationship between behavioral intention and online pharmacy adaptation. Design/methodology/approach This study adopted a descriptive, quantitative approach to investigate the UTAUT-2 model in the context of consumers’ adoption of e-pharmacy in Qatar. Through convenience sampling, 455 responses were collected from regular customers accessing online pharmacy services. The data were analyzed using Smart-PLS 3.2 software to examine the hypothesized relationships. Findings The results showed that WOM recommendations significantly enhanced the relationship between behavioral intention and adopting online pharmacies in Qatar. This study identified the factors that may hinder or enable the adoption of online pharmacies, including performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness. Research limitations/implications This study contributes to the existing literature on technology acceptance by extending the UTAUT-2 model and recognizing three additional variables (perceived risk, technology trust and technology awareness). These need to be investigated against UTAUT-2 variables to detect the significance of their impact on adapting the e-health concept in Qatar. The potential for cultural change to accelerate the adoption of online pharmacies is highlighted. Future research should explore the role of moral and cultural factors in technology adoption. Practical implications The results underscore the economic and social significance of e-pharmacy adoption, particularly within the context of a developing country. Considering the positive intentions expressed by individuals toward e-pharmacy, it becomes crucial for managers and decision-makers to make strategic choices to address any challenges that may arise. Policymakers are encouraged to enhance their services and implement various development initiatives to expand e-pharmacy accessibility and availability. Originality/value This study builds upon previous research on e-commerce in the pharmaceutical industry and provides a comprehensive understanding of customers in developing countries. Extending the UTAUT-2 model and identifying additional variables contributes to the knowledge of e-health concepts in Qatar. The findings have practical implications for developing strategies to promote online pharmacy adoption in Qatar and other countries.

IT’s a matter of trust: Literature reviews and analyses of human trust in information technology

Trust is one of the most important constructs for understanding the adoption of information technologies (IT). In this paper, we review and analyze two literatures on the construct of human trust in IT artifacts and in the entities that source, operate, and govern IT. The first literature review focuses on defining of the construct of trust across a range of disciplines. Our analysis of this literature identified 13 assumptions about the nature of trust. The assumptions illustrate the complexities of human trust. The second literature review focused on 214 empirical studies of the construct of trust published in the AIS Senior Scholars’ Basket of Eight journals. We analyze this literature to identify IS scholar’s most common assessments of trust from qualitative studies and most common measures of trust from quantitative studies. As a cumulative body of knowledge, IS scholars have deeply examined the multidimensional aspect of trust by examining different types of trust, including affective trust, cognitive trust, institutional trust, instrumental trust, intrinsic trust, knowledge-based trust, relational trust, swift trust, disposition to trust, trusting beliefs, and more. IS scholars have also extensively examined the assumption that trust is dynamic, as evidenced by the many qualitative papers that examined trust as a process. Our review also finds that IS scholars have conducted extensive research examining trust in Web2 technologies, which are characterized by centralized applications and centralized governance. While the IS scholarly community has established a substantial tradition around the construct of trust, there is still interesting work to be done. With recent releases of open generative AI and with the rise of Web3 technologies like blockchains that purport to be “trustless,” the construct of trust in IT needs to be re-examined in these emerging contexts. We also encourage more research on trust in bi-directional relationships, on the limits of transitive trust, and on the construct of distrust.

Developing AI for Weather Prediction

The question of how professional and lay communities develop trust in new technologies, and automation in particular, has been a matter of lively debate. As a charismatic technology, artificial intelligence (A.I.) has been a common topic of these debates. This paper presents a case study of how the discourses and principles of ethics of technology development—specifically, of A.I.— were mobilized to form trust among actors in the fields of computer science, risk communication, and weather forecasting. My analysis draws on sociology of expertise and the literature on ethics of A.I. to ask: how emerging networks of expertise use ethics to overcome mistrust in technology? And, what role does the institutionalization of those networks play in the process of trust formation? I situate this discussion on the NSF Institute for Research on Trustworthy A.I. The Institute is positioned as a mediating organization with the goal of increasing trust in this technology primarily the weather forecasting community, but also among the public. I show that first, to better understand how scientific and professional fields react to increased automation it is crucial to unpack the historical backdrop of how the professional identity of those experts has been shaped by a relationship with computer-supported modeling. To this end, I situate the discussion in the long-standing tensions between computer modelling and tacit knowledge in weather forecasting. Second, I argue that the means of establishing trust in A.I. propagated by the actors in the paper, which pair norms of explainability to sensitivity to professional intuitions and domain-specific conventions, rely on a series of “mutual orientations” (Edwards, 1996). I mobilize the concept of “mutual orientations” to describe the work of tailoring the ethics of A.I. to the specific requirements of weather sciences, but also to the vision of a national strategy of investment in this technology.

A UTAUT-Based Framework for Analyzing Users’ Intention to Adopt Artificial Intelligence in Human Resource Recruitment: A Case Study of Thailand

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education, and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This study focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It utilized the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thailand recruitment practices. The study explores the factors influencing users’ intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literature and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in the Bangkok metropolitan area supplied comprehensive responses. The study reveals that several factors, including perceived value, perceived autonomy, effort expectancy, and facilitating conditions, significantly impact the intention to adopt AI for recruitment. While social influence and trust in AI technology do not have a direct influence on intention, social influence directly affects perceived value. Trust in AI technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations, and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

New Challenges of Learning Accounting With Artificial Intelligence: The Role of Innovation and Trust in Technology

<p style="text-align:justify">Online learning has become increasingly popular, making the learning process more attractive. One of the most popular learning media is artificial intelligence (AI). However, students do not accept this technology at all. Therefore, this study examined the factors influencing accounting students' acceptance of AI in learning. The survey was conducted with 147 higher-education students who use AI as a learning medium. The data were analyzed using SmartPLS 4.0 with the partial least square approach. The results showed that perceived usefulness influenced behavioral intention to use and satisfaction. However, perceived ease of use was only significant for satisfaction. Similarly, perceived confidence must be consistent with intention. Although it may influence perceived usefulness, other constructs, such as AI quality and personal innovativeness, can increase students' perceptions of the benefits and convenience of adopting AI in learning. Thus, this study contributes to the development of the technology acceptance model (TAM) and the information systems success model and is helpful to scholars, especially in applying AI in learning. They need to pay attention to the quality of AI, such as the accuracy of the information produced. Thus, the need to control the information from the AI only serves as a reference without requiring you to trust it completely.</p>

The moral, the political and social licence in digitally‐driven family policy and intervention: Parents negotiating experiential knowledge and ‘other’ families

AbstractThe article provides a conceptually informed empirical critique of the pursuit of social licence as a warrant for data linkage and predictive analytics in the field of family policy intervention. It draws on research focusing on parental views of digitally‐driven family governance in the United Kingdom. We identify the notion of consensus that undergirds the concept of social licence that acts to obscure inequalities and silence conflict, and to reframe digital surveillance and prediction as a moral rather than political issue. Using focus group and individual interview material, we show how parents assert professional or lay experiential knowledges in making judgements about the legitimacy of and trust in operational data technologies, involving struggles between positionings as parents like ‘us’ and ‘other’ parents. We demonstrate how parents have different leverages from these unequal and morally charged social locations. Inevitably, the application of social licence in the domain of digital family policy and intervention is fractured by entrenched social divisions and inequalities.

International Perception and Local Pride in Smart City Development: The Case of Hong Kong

Abstract Local citizens’ perceptions of their own cities are often neglected when assessing cities’ performance. Using the perceived international image and collective pride in Hong Kong as the entry point, this article aims to discover the relationship between citizens’ trust in public authorities and urban technologies. Four angles of investigation are developed: the impact of cities’ promotion of their international image on local pride; the attitudinal and demographic characteristics of proud citizens; the linkage of local pride with public trust, and digital trust. This article uses data from a Hong Kong-based territory-wide survey in 2021 to conduct the analysis. The result suggests that public trust is an elemental factor having a positive relationship with collective pride and digital trust in Hong Kong. This article also identifies the group of citizens with the least pride. Regaining the citizen's trust is the best remedy for facilitating smart city development.

How deep is your trust? A comparative user requirements’ analysis of automation in medical and mobility technologies

In a changing world full of innovative technologies, trust and trust requirements are increasingly important for designing user-centred systems and ensuring their long-term implementation. In this study, we explored and compared the requirements of future users to build trust in the two contexts of medical and mobility technology by considering Ambient Assisted Living technologies (AAL) and Shared Autonomous Vehicles (SAV). We conducted an online survey study with N = 143 participants. The results show significant differences in the evaluation of individual trust requirements in the two contexts about data sharing, data privacy and security as well as customization. Using a cluster analysis, we identified distinct user groups and trust personalities in both contexts (medicine and mobility). The clusters differ in terms of innovation openness and risk readiness, initial trust, and presence of chronic illness. Correlation analyses revealed significant relationships between people’s initial perceived trust in technology in the two contexts and their assessment of trust requirements, as well as their behavioural intentions to use SAV or AAL systems. Our findings indicate that trust requirements are context-specific and influenced by individual characteristics. This knowledge can be used to inform developers and distributors of technologies to design, build, and manage systems that meet the needs of future users.