Excessive Trust Research Articles

Evolutionary Mechanism of Trust for Public–Private Partnership Projects with Public Participation

Trust plays a pivotal role in sustaining cooperative relationships and serves as the cornerstone of successful cooperation among participants in public–private partnership (PPP) projects. A decline in trust can result in unethical behavior, fractured relationships, and even project failure. Despite its critical importance, there is an insufficiency of research exploring the evolutionary dynamics of trust, particularly from the perspective of public participation. To address this, an evolutionary game model is constructed to analyze the evolution of behavioral strategies and identify their stable state from a dynamic perspective. The model examines the influence of trust levels and public participation on cooperation, revealing that trust asymmetry negatively impacts collaborative outcomes in PPP projects. There is an optimal trust level: trust positively influences cooperation up to a certain peak, beyond which excessive trust becomes detrimental and hinders cooperative outcomes. When trust levels are equal, the selection of behavioral strategies is influenced by the initial willingness of participants. A threshold exists for this initial willingness, above which cooperation is more likely to succeed. Additionally, public participation is found to significantly enhance cooperation. These conclusions advance the theoretical advancements of trust in PPP projects and offer valuable insights for policymakers and stakeholders in addressing trust-related challenges, thereby fostering sustainable collaboration.

Understanding online shopping fraud among Chinese elderly: Extending routine activity theory in the online context

Drawing from routine activity theory (RAT), this study explored the antecedents of older adults’ exposure to online shopping fraud and evaluated the moderators of the linkage between fraud exposure and victimization. Through a survey of 471 Chinese participants aged 55 and above, we found that older adults who engage in high-risk online behaviors, use insecure networks, frequently encounter promotional advertisements, and regularly shop on live-streaming platforms are at a heightened risk of fraud exposure. Following exposure, those exhibiting excessive trust in Internet platforms and a strong face-saving bias were more likely to incur monetary losses. Our research reframed RAT into a structured two-stage process, with fraud exposure leading to victimization, moderated by guardianship, and highlighted the critical role of cognitive biases among older adults. These findings offer valuable insights for developing effective safeguards to protect older people in the digital shopping landscape.

How Explainable Artificial Intelligence Can Increase or Decrease Clinicians' Trust in AI Applications in Health Care: Systematic Review.

Artificial intelligence (AI) has significant potential in clinical practice. However, its "black box" nature can lead clinicians to question its value. The challenge is to create sufficient trust for clinicians to feel comfortable using AI, but not so much that they defer to it even when it produces results that conflict with their clinical judgment in ways that lead to incorrect decisions. Explainable AI (XAI) aims to address this by providing explanations of how AI algorithms reach their conclusions. However, it remains unclear whether such explanations foster an appropriate degree of trust to ensure the optimal use of AI in clinical practice. This study aims to systematically review and synthesize empirical evidence on the impact of XAI on clinicians' trust in AI-driven clinical decision-making. A systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, searching PubMed and Web of Science databases. Studies were included if they empirically measured the impact of XAI on clinicians' trust using cognition- or affect-based measures. Out of 778 articles screened, 10 met the inclusion criteria. We assessed the risk of bias using standard tools appropriate to the methodology of each paper. The risk of bias in all papers was moderate or moderate to high. All included studies operationalized trust primarily through cognitive-based definitions, with 2 also incorporating affect-based measures. Out of these, 5 studies reported that XAI increased clinicians' trust compared with standard AI, particularly when the explanations were clear, concise, and relevant to clinical practice. In addition, 3 studies found no significant effect of XAI on trust, and the presence of explanations does not automatically improve trust. Notably, 2 studies highlighted that XAI could either enhance or diminish trust, depending on the complexity and coherence of the provided explanations. The majority of studies suggest that XAI has the potential to enhance clinicians' trust in recommendations generated by AI. However, complex or contradictory explanations can undermine this trust. More critically, trust in AI is not inherently beneficial, as AI recommendations are not infallible. These findings underscore the nuanced role of explanation quality and suggest that trust can be modulated through the careful design of XAI systems. Excessive trust in incorrect advice generated by AI can adversely impact clinical accuracy, just as can happen when correct advice is distrusted. Future research should focus on refining both cognitive and affect-based measures of trust and on developing strategies to achieve an appropriate balance in terms of trust, preventing both blind trust and undue skepticism. Optimizing trust in AI systems is essential for their effective integration into clinical practice.

An equilibrium analysis of blockchain integration strategies in the livestock meat supply chain considering consumers’ preference for quality trust

PurposeThis paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?Design/methodology/approachThis paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.FindingsThe results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.Originality/valueThis study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

РОЗВИТОК КРИТИЧНОГО МИСЛЕННЯ МАЙБУТНІХ ВЧИТЕЛІВ ІНФОРМАТИКИ ТА МАТЕМАТИКИ З ВИКОРИСТАННЯМ ЗАСОБІВ ШТУЧНОГО ІНТЕЛЕКТУ

The article examines the problems of developing critical thinking of future teachers of computer science and mathematics using artificial intelligence tools. The experience of domestic and foreign researchers regarding the use of artificial intelligence in education for the development of critical thinking, in particular, the United States of America, the Republic of Poland, and the Republic of Slovenia, was analyzed. The necessary components of critical thinking are defined: the use of logical thinking to analyze problems, make decisions and solve problems; obtaining, interpreting and using knowledge/facts/data in the process of solving problems; demonstration (manifestations) of creativity and non-standard thinking. In order to investigate the specifics of the application of critical thinking skills by future teachers of computer science and mathematics when working with artificial intelligence systems, a survey was conducted. The "Klochko Questionnaire: Peculiarities of using critical thinking skills by future teachers of computer science and mathematics when working with artificial intelligence systems" was created. The possibilities of using artificial intelligence tools in education have been clarified, in particular: analysis of educational data, creation of educational content, professional development, adaptive learning, and others.The results of the study showed that 92.2% of respondents use or plan to use artificial intelligence tools in the educational process. The vast majority of students studying to become computer science and mathematics teachers actively use artificial intelligence to solve various problems, applying critical thinking and developing their critical thinking skills. The development of critical thinking skills of future computer science and mathematics teachers is a necessary condition for their academic success, personal and professional development, competitiveness, preparation for future challenges, solving new problems, teaching students to think critically. The implementation of artificial intelligence tools for the development of critical thinking in future teachers may have certain risks, such as excessive trust in artificial intelligence and the reduction of the role of one's own experience, intuition, etc. It is important to note that the field of using artificial intelligence technologies in education is just beginning to develop and needs additional research, however, it has great potential for the development of critical thinking of future teachers.

A paper tiger in the fog of governance: Norway's riddle in biodiversity matters

AbstractEffective biodiversity protection is generally associated with a strict rule of law and democratic participation in environmental decision making. Norway's exceptional ranking in terms of governance, however, has failed to be a predictor of effective biodiversity protection. Through a systematic review of the main regulatory frameworks relevant to protecting biodiversity in Norway, this article analyses the misconceptions, perverse incentives and institutional bottlenecks that lie at the centre of the problem. The analysis finds three overarching barriers that regulatory frameworks have created to the effective protection and promotion of biodiversity in Norway, namely, a governance system based on diffuse legal obligations and responsibilities, excessive trust in private operators and considerable discretion to local entities. Accordingly, this article proposes three enabling factors, and related reform suggestions, for mitigating such barriers and domesticating earth system governance in biodiversity matters.

The price of (dis)trust – profiling believers of (dis)information in the Hungarian context

ABSTRACTTaking a person-centered approach – we explored different constellations of social-psychological characteristics associated with (dis)information belief in order to identify distinct subgroups whose (dis)information belief stems from different social or political motives. Hungarian participants (N = 296) judged the accuracy of fake and real news items with a political (pro/anti-government) and nonpolitical narrative. Two profiles of ‘fake news believers’ and two of ‘fake news non-believers’ emerged, with a high conspiracy mentality being the main marker of the former two. These two ‘fake news believers’ profiles were distinguishable: one exhibited extreme trust in the media and in politicians, and the other deep distrust. Our results suggest that not only political distrust, but also excessive trust can be associated with disinformation belief in less democratic social contexts.

The mediating role of E-trust in the relationships between E-service quality and E-Satisfaction on Gen Z users Shopee Apps

The aim of this study is to observe the effect of e-service quality on e-satisfaction mediated by e-trust in Shopee application users among generation Z. Excessive trust in users could be capable of growing the resulting sense of satisfaction. User satisfaction may be used by organizations to enhance quality and attract new users. This study is protected in the explanatory research category. Respondents in this look-at have been Shopee application users in Malang city. Identifying the type of samples in this observation used a purposive sampling approach with a sample size of 150 respondents. The record collection method makes use of a questionnaire, and the data are analyzed using PLS-SEM 3.3. The study's outcomes show that e-service quality has a significant impact on e-satisfaction. E-service quality has a significant impact on e-trust, and e-trust has a significant effect on e-satisfaction. e-trust can bridge the mediating position within the courtship between e-service quality and e-satisfaction. It's broadly hoped that the Shopee application can hold and grow user trust, mainly in Gen Z.
 Keywords: E-service quality; E-satisfaction; E-trust.

Exploring the Impact of Automation Bias and Complacency on Individual Criminal Responsibility for War Crimes

Abstract With advancing technology, complex decision-making in warfare, including targeting, is increasingly assisted by machines. Although involving humans in decision-making is often seen as a safeguard against machine errors, it does not always prevent them. Machines can make incorrect determinations or delay them when time is critical. In these cases, human operators, influenced by automation bias (excessive trust in machines’ determinations, despite the availability of contradicting or different information from other sources) or complacency (excessive trust in machines’ determinations, leading to reduced vigilance), may fail to recognize machine errors, potentially resulting in conduct amounting to a war crime. Considering the role of automation bias and complacency in the determination of the criminal responsibility of systems’ operators is crucial, especially, for understanding the accountability framework for war crimes involving autonomous weapon systems (AWS). By exploring how automation bias and complacency affect the determination of criminal responsibility for humans who operate AWS, this article offers insights for lawmakers at the national and international levels to understand complexities and effectively shape legislative responses with respect to criminal responsibility. This article also examines automation bias and complacency in psychology, their relevance in military operations employing AWS, and their potential to exonerate human operators from criminal responsibility. It concludes by advocating for legislative, organizational, and technical measures to counteract automation bias and complacency.

How does drivers’ trust in vehicle automation affect non-driving-related task engagement, vigilance, and initiative takeover performance after experiencing system failure?

Vehicle automation is a potentially highly advantageous concept in terms of reducing traffic accidents, e.g., due to distractions by non-driving related tasks (NDRTs) or decreased vigilance. The driver needs to have a thorough understanding of the vehicle automation system and a moderate level of trust in it for the advantages to be realized. System failures inherently adversely affect trust, however, a completely reliable system is unrealistic. In the present study, we explore how drivers’ trust in vehicle automation affects their NDRT engagement, vigilance, and initiative takeover performance after experiencing a system failure. In the induction experiment, seventy-seven participants were divided into three groups by their level of trust (distrust, appropriate trust, excessive trust) in the highly automated vehicle. All experienced five “hazardous events” in the formal experiment, the second of which was a system failure. Relevant results indicated that the system failure affected drivers differently depending on their levels of trust. Drivers’ NDRT engagement decreased after the system failure due to a decline in trust but increased during subsequent driving as trust recovered. Vigilance was higher in drivers who were distrustful, but the post-failure decrease in vigilance was higher compared to others. Drivers who were distrustful were more likely to initiatively take over the vehicle as evidenced by higher resulting acceleration upon encountering the hazards. The maximum resulting acceleration decreased with the sequence of hazardous events but increased with the level of risks. The findings of this work may be useful in terms of trust calibration processes, technological improvements to vehicle automation systems, and the promotion of automated vehicle usage.

The non-payments economy: 30 years later

The paper analyzes the reasons and consequences of the dominance of the non-payments economy in Russia in the 1990s. Arguing with a recent paper by A.B. Chubais “Non-payments in the Russian economy of the 1990s: An unforeseen institution” (Voprosy Ekonomiki, 2003, No. 7), the author puts forward his own arguments for the emergence, spread and contraction of the phenomenon of non-payments. According to his point of view the fundamental reason for developing the barter economy in Russia was the need for directors and managers of enterprises to obtain empirical information and knowledge about the new structure and possibilities of the Russian economy. The methodological miscalculations of the authors of the concept of market reforms of the 1990s, associated with excessive trust in neoclassical economic theory, in particular, in the neoclassical concept of the firm, have been discussed. A broader view of the activity and interaction of economic agents has been proposed. It takes into account the achievements of institutional, evolutionary, behavioral, and system economic theories. An analogy between the early 1990s and the early 2020s in terms of the formation of the data economy and, in the future, the knowledge economy has been drawn. On the basis of the conducted analysis general recommendations for economic theory, policy and practice have been formulated.

Bias of Investor Behavior in Making Investment Decisions in the Capital Market

Purpose: The long-term goal of this research is to find out the behavior of investors in making investment decisions in the capital market, while the specific target to be achieved is to know the biases of investor behavior in making investment decisions. Investment decision makers do not always behave in a way that is consistent with the assumptions made in accordance with the perception and understanding of the information received, but is strongly influenced by psychological factors. Research Methodology: This type of research is descriptive quantitative research. The survey was conducted on investors who are members of the group of young investors. The population of this study is all investors who actively trade in the Bali branch of the Indonesia Stock Exchange. By using a purposive sampling method, namely taking samples by adjusting the research criteria, namely investors who have made transactions in trading on the stock exchange for at least two years. Multiple regressions was used to test the hypotheses that were developed at a significance level of 0.05 percent. Results: Investors experience behavioral bias due to the influence of disposition and excessive trust. This circumstance will result in a reduction of their final wealth. The disposition effect influences decision making on investor behavior in the capital market. Investors have a tendency to realize less profits compared to the tendency to realize losses. Limitations: The results of this study may not apply to other excluded categories because this research is limited to investors who actively trade in the Bali branch of the Indonesia Stock Exchange. Contribution: Investors will be better off if they don't hold their shares for too long when the stock price declines and are not advised to sell profitable shares too quickly. Investor literacy should be improved by understanding information about company fundamentals.

Democratizing Finance: The “Citizen Fund”as an Institutional Proposal to Structurally Consider Non-Pecuniary Returns in Investment Decisions

An important element to explain the current multi-dimensional crises is the inability of capitalist institutions to consider non-pecuniary returns to investments (NPRI) in investment decisions. Orthodox economics highlights the creative force of the monetary profit motive, which translates into cultural habits and political decisions leading to overinvestment in harmful activities and underinvestment in desirable sectors. The flipside of this excessive trust in the monetary profit motive and markets is the weakening of the democratic institutions and the mistrust from the citizenry. Here, an archetype of a novel instrument for democratic finance is presented, to measure NPRIs, reconciling individual and collective action, harmonizing innovation, investment, and democracy.

BEPHAP: A Blockchain-based Efficient Privacy-Preserving Handover Authentication Protocol with key agreement for Internet of Vehicles

The Internet of Vehicles (IoV) can significantly improve transportation efficiency and ensure traffic safety. Authentication is regarded as the fundamental defense line against attacks in IoV. However, the state-of-the-art approaches suffer from several drawbacks, including bottlenecks of the single cloud server model, high computational overhead of operations, excessive trust in cloud servers and roadside units (RSUs), and leakage of vehicle trajectory privacy. This paper introduces BEPHAP, a Blockchain-based Efficient Privacy-preserving Handover Authentication Protocol with key agreement for internet of vehicles, to address these problems. BEPHAP achieves anonymous cross-domain mutual handover authentication with key agreement based on the tamper-proof blockchain, symmetric cryptography, and the chameleon hash function under a security model that cloud servers and RSUs may launch attacks. BEPHAP is particularly well suited for IoV since it allows vehicles to only perform lightweight cryptographic operations during authentication. BEPHAP also achieves data confidentiality, unlinkability, traceability, non-repudiation, non-frameability, and key escrow freeness. Formal verification based on ProVerif and formal security proofs based on the BAN logic indicates that BEPHAP is resistant to various typical attacks, such as man-in-the-middle attacks, impersonation attacks, and replay attacks. Performance analysis demonstrates that BEPHAP surpasses existing works in both computation and communication efficiencies. It is worth noting that BEPHAP reduces the computational cost of vehicles by 2 to 4 orders of magnitude compared to current schemes. And the message loss rate remains 0 at 5000 requests per second, which meets the requirement of IoV.

“Every Dog Has His Day”

This article proposes a competitive-evolving-committee proactive secret sharing. Every participant in the system has the opportunity to become a member of the holding committee and have sufficient anonymity. During the life cycle of serving as the holding committee members, they only send one message in the protocol without excessive interaction, and achieve receiver strong anonymity with a capability-based encryption scheme different from most public-key encryption schemes, at present named RiddleEncryption, which is also proposed in this paper. In RiddleEncryption the sender does not need to pay attention to the specific identity of the receiver but focuses on what kind of capability the receiver should have. Nobody can determine this kind of capability at the beginning of the system establishment. This article aims at depositing a secret in a distributed manner (e.g., blockchain) without excessive trust and to emphasize more anonymity and capability. The scheme can be used in the dynamic groups, authentication management, rights abuse prevention, and so on.

Cognitive and ethical reasons for the dissident movement in epidemiology

The article discusses several fundamental reasons for the emergence of such a significant phenomenon as the anti-vaccination movement. An attempt is made to classify these causes. The theory of the phases of the vaccination cycle by Robert Chen is presented. The theory of cognitive simplicity and the creation of illusory patterns to strengthen psychological control over a stressful situation was developed by Moscow anthropologist Alexandra Arkhipova. The decision to refuse vaccination is often accompanied by an inability to rank the risks and trust in pseudoscientific rumors. The level of distrust of citizens in government and healthcare, and, conversely, excessive trust in populist personalities, is also a significant reason for dissent in epidemiology. The article provides numerous examples from the history of smallpox, cholera and coronavirus epidemics. In conclusion, the article considers the problem of trust and mutual responsibility in society.

Age-related differences in the social associative learning of trust information

Trust is a key component of social interaction. Older adults, however, often exhibit excessive trust relative to younger adults. One explanation is that older adults may learn to trust differently than younger adults. Here, we examine how younger (N = 33) and older adults (N = 30) learn to trust over time. Participants completed a classic iterative trust game with 3 partners. Younger and older adults shared similar amounts but differed in how they shared money. Compared to younger adults, older adults invested more with untrustworthy partners and less with trustworthy partners. As a group, older adults displayed less learning than younger adults. However, computational modeling suggests that this is not because older adults learn differently from positive and negative feedback than younger adults. Model-based fMRI analyses revealed several age- and learning-related differences in neural processing. Specifically, we found that older learners (N = 19), relative to older non-learners (N = 11), had greater reputation-related activity in metalizing/memory areas while making their decisions. Collectively, these findings suggest that older adult learners use social cues differently from non-learners.

Вплив особливостей розвитку покоління Y на становлення сучасного міжнародного ринку праці

The digitalization of society and of economic processes in general has significantly influenced the formation of the modern labor market, which has led to the emergence of new social needs and necessities for new specialists and new market niches. In the peresented publication, the features of the modern labor market are considered from the point of view of demographic windows and features of the perception of modern generations. Since the beginning of the twentieth century, six generations have been distinguished, at present three generations are most involved in labor relations. Representatives of generation X are used to relying primarily on themselves. The opportunity to be realized, to express this very independence is important for such people also regarding their careers. Representatives of generation X will be more willing to do work that gives space for creativity and breadth of thought. If you do not give them such an opportunity, then they lose interest. For such people, it is important to always have a choice, an open perspective. One of the most notable features of Generation Y is the dependence on knowledge, which they find not in books from libraries, but on Internet resources. This is a generation that loves to learn, because studying for millennials is something interesting and peculiar. What used to be learned exclusively from teachers and tutors becomes easily accessible to the «upsilons». This leads to another feature of this generation – excessive trust in the information provided by online services, especially when there is no censorship. For this generation, self-realization comes to the fore. This is not to say that they are not interested in the family, but career growth still remains in the first place. Generation Z is characterized by the absolute absence of a well-defined life position. Unlike all their predecessors, the «zetas» are not motivated by either money or any career growth. Moreover, they are completely dependent and have constant need of someone to point them out what they should do. They love to learn, quickly acquire new knowledge. Large amounts of information appear of no difficulty for them. «Zetas» are distinguished by their incredible multitasking and creativity. They love to find solutions in difficult situations and solve the most complex problems. Having identified the main features of generations, it can be noted that the formation of the modern labor market depends on many circumstances of the formation of the modern digital world. Thus, this process is significantly influenced by the digitalization strategy implemented by national governments to ensure the competitiveness of national economies. At this, too, a digital economy with a significant focus on inclusiveness can increase the influence of natural monopolies and promote concentration, which in the absence of effective and transparent institutions in society can lead to increased control on the part of the State and subordination of politics to the interests of the relevant elites.

Reliable, Possible, and Improbable About Student Years of Hryhorii Skovoroda

To this day the biography of young man Hryhorii Skovoroda is mostly a set of assumptions and conjectures than history about his life based on more or less authentic facts. Even the year of the philosopher’s birth is not as obvious as it is commonly supposed. Excessive trust in the specific work of Mykhailo Kovalynskyi about Skovoroda attempts to adjust those up to thinker’s time sources to much later information of Kovalynskyi’s work harm the critical study of Hryhoriy Savych’s biography. In this article on the basis of both well-known and new facts the established historiographical statements about the time of Skovoroda’s birth and education are revised or questioned. He could not start his studies at the Kyiv-Mohyla Academy before 1738/39 and completed them, most likely, no later than January 1750. It seems the gap in Hryhorii’s studying because of his singing in the court chapel lasted longer than scholars assumed before.

On the Analysis and Control of Audit Sampling Risk

Audit sampling technology is widely used in practical work due to its advantages of convenient and efficient efficiency, but it also has its disadvantages, producing audit sampling risk, which is divided into excessive trust risk and misuse risk. This paper borrows the accounts receivable data of Sichuan Star Electric Power Company, adopts the monetary unit sampling method to further understand and consider the audit sampling technology, and finally puts forward suggestions on the control means of audit sampling risk.