Trust Issues Research Articles

Listening to unheard voices: exploring salespeople’s perspectives on the value of corporate heritage

PurposeThis study aims to examine salespeople’s perspectives on the value of corporate heritage to relationship selling and the issue of trust in personal selling situations in the context of emerging markets.Design/methodology/approachAn interpretive approach was adopted, and 16 semi-structured interviews were conducted with senior salespeople in heritage institutions operating in Jordan.FindingsThis study reveals that corporate heritage is a valuable organizational resource for relationship selling. Reflecting the values of “trust” and “affinity,” corporate heritage confers trust to salespeople and their products in personal selling situations. Sales managers are advised to use corporate heritage to strengthen sales activities and empower salespeople.Originality/valueWhile previous research has explained the significance of corporate heritage to relationship marketing, the significance of corporate heritage to relationship selling and the issue of trust in personal selling situations remain unexplored. Jordan represents a context that has been largely neglected despite being typical of the corporate heritage phenomenon.

Towards intelligent and trustworthy task assignments for 5G-enabled industrial communication systems

With the unprecedented prevalence of IIoT and 5G technology, various applications supported by industrial communication systems have generated exponentially increased processing tasks, which makes task assignment inefficient due to insufficient workers. In this paper, an Intelligent and Trustworthy task assignment method based on Trust and Social relations (ITTS) is proposed for scenarios with many tasks and few workers. Specifically, ITTS first makes initial assignments based on trust and social influences, thereby transforming the complex large-scale industrial task assignment of the platform into the small-scale task assignment for each worker. Then, an intelligent Q-decision mechanism based on workers' social relation is proposed, which adopts the first-exploration-then-utilization principle to allocate tasks. Only when a worker cannot cope with the assigned tasks, it initiates dynamic worker recruitment, thus effectively solving the worker shortage problem as well as the cold start issue. More importantly, we consider trust and security issues, and evaluate the trust and social circles of workers by accumulating task feedback, to provide the platform a reference for worker recruitment, thereby creating a high-quality worker pool. Finally, extensive simulations demonstrate ITTS outperforms two benchmark methods by increasing task completion rates by 56.49%-61.53% and profit by 42.34%-47.19%.

The Concept of Public Trust-Based Leadership – An Outline

Abstract Objective The issue of trust in leading public organisations continues to inspire growing confidence among management researchers and practitioners. The characteristics and organisational behaviour of leaders are analysed from various angles. The subject of the research is one of the newer approaches, namely trustbased leadership (TBL). The aim of this paper is to identify characteristics and the roles of public trust-based leadership (PTBL). This is the type of leadership that most fully incorporates trust as the basis of organisational behaviour in vertical and horizontal relationships and consequently as organisational cooperation. Methodology The primary methods used in this article are a critical review of research on organisational trust, leadership and public trust contained in the academic literature and in surveys of trust in leadership conducted in recent years by consultancies and made available on line. Findings The study confirmed that an inalienable role of leaders is to shape their own organisational credibility in both internal and external relations. Achieving a high level of this credibility allows to earn trust. Value Added Demonstrating that a key differentiator of the trust-based leadership concept is that TBL is centring trust-based relationships throughout the entire organisation. Recommendations Further research on trust-based public leadership should support its presence in contemporary organisations.

Artificial Intelligence and Patient Autonomy in Obesity Treatment Decisions: An Empirical Study of the Challenges.

Background This study aims to explore the factors associated with artificial intelligence (AI) and patient autonomy in obesity treatment decision-making. Methodology A cross-sectional, online, descriptive survey design was adopted in this study. The survey instrument incorporated the Ideal Patient Autonomy Scale (IPAS) and other factors affecting patient autonomy in the AI-patient relationship. The study participants included 74 physicians, 55 dieticians, and 273 obese patients. Results Different views were expressed in the scales AI knows the best (μ = 2.95-3.15) and the patient should decide (μ = 2.95-3.16). Ethical concerns (μ = 3.24) and perceived privacy risks (μ = 3.58) were identified as having a more negative influence on patient autonomy compared to personal innovativeness (μ = 2.41) and trust (μ = 2.85). Physicians and dieticians expressed significantly higher trust in AI compared to patients (p < 0.05). Conclusions Patient autonomy in the AI-patient relationship is significantly affected by privacy, trust, and ethical issues. As trust is a multifaceted factor and AI is a novel technology in healthcare, it is essential to fully explore the various factors influencing trust and patient autonomy.

Multiple-Stakeholder Perspectives on Accessibility Data and the Use of Socio-Technical Tools to Improve Sidewalk Accessibility

For people with disabilities, accessible pedestrian infrastructure can support independence, mobility, and improved quality of life. Yet, most pedestrian infrastructure presents barriers that impede movement. A major challenge for cities to improve pedestrian accessibility is the lack of reliable data on sidewalk accessibility. Little is known about the type of data needed for cities, as well as how different stakeholders perceive and use sidewalk data. Therefore, this study seeks to explore the perceptions of multiple stakeholders on the use, gathering, and application of sidewalk accessibility data. We conducted a series of workshops with 51 participants, including people with disabilities, caregivers, Americans with Disabilities Act (ADA) coordinators, and urban planners, to discuss sidewalk accessibility data and data collection tools. We used the socio-technological tool Project Sidewalk as an example. Participants identified various uses for the accessibility data such as route planning, barrier removal plans, and advocacy, and discussed issues of usability, trust, access, and accessibility of the data and tools. Our findings contribute to a better understanding of important factors that impact the use and application of accessibility data and how to implement accessibility data collection initiatives that utilize socio-technological approaches such as crowdsourcing.

Consumers’ attitude toward the source of biotechnology

Abstract Existing research based on labels, risks and benefits, and cultural differences has focused on consumers’ preferences for genetically modified (GM) food products. Limited attention has been paid to the attitudes toward the source who developed the biotechnology. Because there may be trust issues associated with large multinational firms that are often involved in the development of biotechnology, it remains an unexplored question whether consumers consider who produces the technology when forming opinions about food produced with biotechnology. This study investigates consumers’ attitude toward the source of biotechnology using a choice experiment with GM oranges. The study involved participants from three major orange-consuming countries (United States, Germany, and Spain). Results reveal that participants from all three countries were less willing to pay for GM oranges when the technology originated from multinational agribusiness corporations, compared to public universities and small companies. Further examining the effect of consumers’ perceptions, we found consumers’ perception of corporate distrust and environmental concern negatively influence their attitude toward the source of biotechnology, but their technology acceptance positively affects the attitude. By understanding consumers’ attitudes about the source of biotechnology and factors that may improve the consumer reactions, communication and promotion of new biotechnology food products to improve acceptance from existing and potential consumers are discussed.

AI and the quest for diversity and inclusion: a systematic literature review

AbstractThe pervasive presence and wide-ranging variety of artificial intelligence (AI) systems underscore the necessity for inclusivity and diversity in their design and implementation, to effectively address critical issues of fairness, trust, bias, and transparency. However, diversity and inclusion (D&amp;I) considerations are significantly neglected in AI systems design, development, and deployment. Ignoring D&amp;I in AI systems can cause digital redlining, discrimination, and algorithmic oppression, leading to AI systems being perceived as untrustworthy and unfair. Therefore, we conducted a systematic literature review (SLR) to identify the challenges and their corresponding solutions (guidelines/ strategies/ approaches/ practices) about D&amp;I in AI and about the applications of AI for D&amp;I practices. Through a rigorous search and selection, 48 relevant academic papers published from 2017 to 2022 were identified. By applying open coding on the extracted data from the selected papers, we identified 55 unique challenges and 33 unique solutions in addressing D&amp;I in AI. We also identified 24 unique challenges and 23 unique solutions for enhancing D&amp;I practices by AI. The result of our analysis and synthesis of the selected studies contributes to a deeper understanding of diversity and inclusion issues and considerations in the design, development and deployment of the AI ecosystem. The findings would play an important role in enhancing awareness and attracting the attention of researchers and practitioners in their quest to embed D&amp;I principles and practices in future AI systems. This study also identifies important gaps in the research literature that will inspire future direction for researchers.

Understanding Complex Relationships between Teachers and Parents

Collaborative relationships between school and families are increasingly put forward as a means to promote student success and persistence. This collaborative work sometimes creates tensions and misunderstandings (Ravn, 2005) that can exacerbate divisions of power and reproduce inequalities (e.g., Crozier, 2000; Lareau, 2011; Vincent 2000). The main purpose of this study is to identify the areas of tensions and inner contradictions that emerge in the teacher-parent relationships in order to guide them while engaging in individual and collective transformation processes. Relying on Hoover-Dempsey et al.’s proposed model (2010), we conducted in-depth interviews with volunteered elementary and secondary teachers. Salient findings are discussed in light of the cultural-historical activity theory (CHAT) (Engeström, 2015). These include mainly issues of trust versus control when it comes to choosing communication tools and issues related to the hierarchical status and power inside and outside the school when it comes to the redistribution of actions among the school community members. As a promising research and intervention avenue, the authors suggest to apply the Change Laboratory method (Virkkunen &amp; Newnham, 2013) anchored in CHAT and that uses mirror data to reflect upon and foster transformative processes, hence, relationships between teachers and parents.

WQCrowd: Secure blockchain-based crowdsourcing framework with multi-tier worker quality evaluation

Crowdsourcing platforms play a crucial role in promoting transparency and collaborative engagement among participants while aiming to reduce resource consumption and costs. To achieve this, these platforms incorporate mechanisms for monitoring and evaluating worker quality performance. However, significant challenges persist. Centralized systems present trust issues due to their vulnerability to single-point failures. Moreover, data manipulation by malicious actors undermine confidence in the evaluation process, and biased assessments and reward distribution may lead to reduced worker motivation. Addressing these concerns necessitates the development of a decentralized system that ensures trustworthiness, tamper-resistance, accountability, reliability, transparency, and security. This paper introduces a secure multi-tier worker quality evaluation crowdsourcing framework based on blockchain technology. WQCrowd utilizes smart contracts and adopts a three-tier model comprising the Identity, Worker Activity, and Reputation tiers. Additionally, an automated game-based worker evaluation method is incorporated, enhancing the precision of performance assessments. Through our Proof of Concept (PoC) analysis, we demonstrate that the utilization of the blockchain system effectively addresses security concerns, including trust, privacy, and accountability, prevalent in current worker performance evaluation systems. Furthermore, the implementation of the game-based automated system enables our proposed solution to make informed decisions regarding worker quality performance evaluation.

Predictors of Individual and Interpersonal Adjustment Among Non-offending Partners of Individuals With Histories of Sexual Offenses

Recent research indicates that the consequences of sexual offenses extend beyond target victims, including to non-offending partners of individuals with sexual offense histories. However, little research has focused on non-offending partners’ wellbeing and relationships with persons with sexual offense histories leading up to and following acts of sexual aggression. Non-offending partners may be secondary victims of their partners’ offenses in managing psychological difficulties (e.g., guilt, shame), social stigma and isolation, fear for their safety, or difficulties in their romantic relationships resulting from their partners’ sexual offenses, often with minimal supports. The current study examined key correlates of individual and interpersonal adjustment among 207 non-offending partners of individuals with histories of sexual offenses who were residing in Canada ( n = 36) or the United States ( n = 171). Findings indicate that positive changes due to the offense (i.e., improved finances), self-esteem, interpersonal adjustment, instrumental support, lower levels of acceptance, and humor positively predicted individual adjustment. Interpersonal adjustment was predicted by trust, intimacy, partner’s stress communication, and problem-focused and emotion-focused common dyadic coping. Findings highlight the need for services for non-offending partners, including interventions that address self-esteem and practical difficulties resulting from the offense, and couples therapy to address trust issues, intimacy concerns, and shared coping with stressors related to the offense.

FedER: Federated Learning through Experience Replay and privacy-preserving data synthesis

In the medical field, multi-center collaborations are often sought to yield more generalizable findings by leveraging the heterogeneity of patient and clinical data. However, recent privacy regulations hinder the possibility to share data, and consequently, to come up with machine learning-based solutions that support diagnosis and prognosis. Federated learning (FL) aims at sidestepping this limitation by bringing AI-based solutions to data owners and only sharing local AI models, or parts thereof, that need then to be aggregated. However, most of the existing federated learning solutions are still at their infancy and show several shortcomings, from the lack of a reliable and effective aggregation scheme able to retain the knowledge learned locally to weak privacy preservation as real data may be reconstructed from model updates. Furthermore, the majority of these approaches, especially those dealing with medical data, relies on a centralized distributed learning strategy that poses robustness, scalability and trust issues. In this paper we present a federated learning strategy, FedER, that, exploiting experience replay and generative adversarial concepts, effectively integrates features from local nodes, providing models able to generalize across multiple datasets while maintaining privacy. FedER is tested on two tasks — tuberculosis and melanoma classification — using multiple datasets in order to simulate realistic non-i.i.d. medical data scenarios. Results show that our approach achieves performance comparable to standard (non-federated) learning and significantly outperforms state-of-the-art federated methods. Remarkably, we also observe that FedER enables any node model to be used as a global federation model. Indeed, the experience replay strategy with privacy-preserving synthetic data allows all node models to converge to reach the same optimum without the need of a single shared model. Code is available at https://github.com/perceivelab/FedER.

LINGUISTIC FEATURES OF THE MODERN NEWSPAPER LANGUAGE: ANALYSIS AND RESEARCH

In contemporary high-choice media environments, the issue of media trust and its impact on people's media use has taken on new importance. At the same time, the extent to which people trust the news media and how much it matters for their use of different types of media is not clear. To lay the groundwork for future research, in this article we offer a focused review of how news media trust has been conceptualized and operationalized in previous research and research on the extent to which news media trust influences media use, and offer a theoretically derived framework for future research on news media trust and its influence on media use.

Privacy-preserving trust management method based on blockchain for cross-domain industrial IoT

The Industrial Internet of Things (IIOT) contains many devices from different autonomous domains (e.g., factories), which need to cooperate to complete complex manufacturing process. Devices from different domains collaborate with each other, which greatly raises trust concerns about device-to-device interactions. Existing trust management approaches may result in the risk of privacy leakage and low accuracy of trust evaluation. Thus, trust issues during interaction remain unsolved but imperative. In this paper, we propose a blockchain-based privacy-preserving trust management architecture PPTMA. Specifically, PPTMA adopts federated learning to train a task-specific trust model for different collaborative task. Our work is the first attempt to research the relationship between the weight calculation of trust metric and the change of context in the field of trust management. To preserve the privacy of devices, differential privacy (DP) is exploited during the trust evaluation process. In addition, a game theory-based incentive mechanism is proposed to encourage the IIOT device for actively and honestly submitting the trust data into the blockchain as so to promote the accuracy of trust computing. Finally, we also design a parallel consensus protocol (OPBFT) which realizes an assembly line to speed up the efficiency of the consensus process. The idea of consensus assembly line firstly proposed by us brings new opportunities for improving the consensus efficiency. Extensive experiments have been conducted to show the effectiveness and efficiency of the proposed method.

A Systematic Roadmap on Privacy, Security, Trust, Identity Management, and Resilience: Wireless Sensor Networks and Internet of Things Architectures

As everything around us will be linked to the net in many ways via the Internet of Things (IoTs) and compared to the standard Internet, new forms of problems and complications can arise. Huge IoTs experiments are currently under way, most of which concern its sight, supporting technology, software, or facilities. Recently, a limited studies have comprehensively defined the security requirements such as privacy concerns, security, and trusting in the IoTs that are deemed special to the future net, these terms need to be discussed and addressed via numerous scholars and research groups as well. This article surveyed through 102 references from popular literature databases to explore the features\ properties that define the distinctive IoT relating to forthcoming privacy, security and trust issues. Then created security requirements that were triggered by the mentioned properties. This article examined the privacy, security, trust and resilience components of the three most popular IoT architectures in consideration of the requirements as well. Also, this survey contributed to the state-of-the-art security issues for embedded devices in Internet of Things world including provide a comparative table of well-known secure routing protocols and their countermeasures to well-known attacks on Open Systems Interconnection (OSI) structure of Wireless Sensor Networks (WSNs) within Internet of Things world. Finally, this survey identifies a number of study gaps that will serve as the foundation for future research.

Transforming the nature of trust between banks and young clients: from traditional to digital banking

PurposeThis study aims to explore how the shift from traditional to digital banking transforms the nature of trust between banks and their younger clients (aged 18–35) from the perspective of bank employees.Design/methodology/approachQualitative semi-structured interviews with representatives of Ukrainian classical banks and neobanks were conducted. The interviews were analysed using the theoretical approach of institution-based and social network-based trust to identify the key distinctions between the nature of trust in traditional and digital banking.FindingsThe employees of the banks reported that digitalization processes have helped to mitigate trust issues; as a result, their banks have not experienced any difficulties in this regard among young people. Furthermore, social networks, particularly social approval, were found to be significant factors for establishing trust in digital banking among young people.Research limitations/implicationsThe results of this study could assist bank managers in adapting their strategies for cultivating trust among younger clients and aiding international law regulators and government institutions in preventing unintended circumstances in financial services. These contributions were shaped by the study’s limitations, including its focus on only two concepts of trust building: institution-based and social network-based, as well as its specific Ukrainian context.Originality/valueThis study highlights social approval as a valuable constituent of the trust-building process that influences trust in institutions. Furthermore, while gaining social approval – particularly through digital platforms – can promote trust-building among young people, this “easy way” may have negative societal consequences by endorsing unscrupulous institutions.

A98Lessons learned from hyperkalaemia simulation: improving policy &amp;amp;amp; practice

Following an investigation where ten times the amount of prescribed insulin was given to a patient during the administration of treatment for hyperkalaemia, learning needs were identified. It was from this incident outcome that the aim for this project arose. Create a hypokalaemia simulation that can be delivered trust wide with only one facilitator. The simulation was run on the medical wards that the staff were familiar with to allow us to identify policies and process gaps as well as learning needs. The simulation only required two registered nurses and with the debriefing session usually took around 40 minutes. This limits the impact on busy wards allowing for safe staffing levels to be maintained. Simulation incident forms were completed for each session to highlight and raise awareness of identified learning points to both ward managers and local governance leads. The first error that impacted the simulation was the spelling effecting the access to treatment guidelines contained within a Trust policy. The Trust we work for is proud to be multinational, and we found that the majority of our colleagues that have received education oversees used the more widely recognized spelling in Europe of hyperkalemia. This was escalated and the second spelling was added as a keyword, after this change the problem was not repeated in subsequent simulations. It led to further reviews of Trust policies and has driven a change in keywords within the policy portfolio. The second and third errors were around lack policy and treatment flowchart awareness and poor knowledge on how to navigate the intranet to find policies. Although the participants in the simulation left with a good awareness of the policy and practices accessing the policy and flowchart during the session, it had become apparent that this was a wider Trust issue. Therefore, communication posters were made to highlight the policy and treatment flowchart for hyperkalaemia. Using a QR code staff could play a short video showing how to access the Trust policies from the intranet page after the sessions. Future plans include collaboratively using simulation to test systems and highlight learning points for other incidents or errors that arise throughout the Trust. Also, we look to utilize Dynamic QR codes [1] that allow for the content connect to the QR code to be updated without the poster having to be reprinted and laminated allowing for a live document. Authors confirm that all relevant ethical standards for research conduct and dissemination have been met. The submitting author confirms that relevant ethical approval was granted, if applicable.

Issues of trust in money and the monetary system

Subject. The article deals with two main confidence issues, i.e. economic agents’ choosing the bearer of the institution of money and assessment of confidence in the monetary unit. Objectives. The purpose is to perform a comprehensive study of the main problems of trust in money in economic relations, to assess the elements of trust that lie in the way of economic agents' choice of forms of money, and to characterize our approach to the assessment of trust. Methods. The study rests on the methodology of the new institutional economic theory, using methods of comparative, logical, and statistical analysis. Results. We revealed a five-level hierarchical structure of trust in money that demonstrates the formation of trust in the monetary unit through the trust in the State, that is, the arrangement of the national monetary system and the reputation of monetary organizations, as well as through the trust in the functions they perform. We unveiled indicators of trust that are under the influence of endogenous and exogenous political, institutional, economic, functional, and socio-psychological factors, and that are subject to quantitative assessment. Conclusions. Trust in the institution of money is characterized by dependence on the designated endogenous and exogenous factors, which include the identified indicators of trust assessment, and which influence an individual's choice of a certain form of money. According to our own approach, it is advisable to evaluate trust in terms of its presence or absence, which, in turn, can be determined through the presence of a doubt factor in respondents.

Ethical Dilemmas in the Use of Artificial Intelligence in Breast Cancer Diagnosis and Treatment (Addressing Issues of Bias, Transferability, and Patient Trust in Breast Cancer AI)

Breast cancer care is becoming one of the main areas of development of artificial intelligence (AI), with applications including screening and diagnosis, risk calculation, disease progression, clinical decision support, management planning, and precision medicine. This paper will review the ethical, legal, and social implications of these developments, including the values embedded in algorithms, evaluation of results, issues of bias, data ownership, confidentiality, and consent, as well as legal, moral, and professional responsibilities. Additionally, we also need to consider the potential impact on patients, including trust in healthcare, as well as explaining the reasons why AI is being implemented quickly. Resolving this challenge requires the involvement of professionals, governments and regulators, health care providers, and patients, regarding the imposition of conditions on implementation, and preventive monitoring systems to ensure development does not move too quickly ahead of evaluation and discussion.

Towards secure and resilient unmanned aerial vehicles swarm network based on blockchain

AbstractBlockchain, as an emerging technology, has found diverse applications in solving trust issues in multi‐party cooperation. The field of Unmanned Aerial Vehicle (UAV) swarm networks is no exception, as UAVs are susceptible to attacks from malicious counterparts due to limited computing and storage resources. In this paper, the authors present an adaptive networking mechanism for UAVs based on blockchain technology, which incorporates three key technologies. Utilizing Global Unique Identifier (GUID) and block storage, UAVs can achieve rapid identity authentication and efficient swarm switching. By evaluating node participation in block consensus, malicious nodes within the UAV swarm can be accurately identified. Additionally, routing learning based on node security attributes and link quality ensures secure and efficient data transmission. Simulation test results demonstrate the practicality and applicability of the proposed blockchain‐based adaptive networking mechanism for UAV swarm networks.

Prerequisites of Good Cooperation between Teachers and School Psychologists: A Qualitative Analysis

The aim of this study was to determine what kinds of factors play a role in the formation of relationships and cooperation between teachers and school psychologists in Czech schools and the ways in which these factors operate. We used a qualitative methodological design with data collection conducted in the form of semi-structured interviews with eight teachers and ten school psychologists. Subsequent analysis was performed using the grounded theory method. The results indicated the central importance of how a given teacher views the school psychologist, which further determines which factors will influence the degree to which the psychologist is accepted. The following factors were shown to be important in the relationship between a psychologist and a teacher’s neutral attitude toward them: the characteristics of the teacher and the psychologist, the role of school management, the role of school focus and the degree to which the psychologist’s role is understood. The discrepancy between the actual role of the school psychologist and how their role is perceived by the teachers can be a source of issues in cooperation and trust between the two.