Multidimensional Trust Research Articles

Atypical dynamic trust learning in individuals with high autistic traits in a multi-round trust game with multiple trustworthiness cues

BackgroundUnderstanding the trust-building process, especially in contexts requiring the integration of multiple trustworthiness cues, is a fundamental aspect of social interactions among individuals with high autistic traits (ATs). It can offer valuable insights into the social functioning of these individuals. MethodParticipants with high and low ATs (N = 120; 30 in each group for two experiments) completed a 10-round trust game that embedded various trustworthiness cues, including reputation, advice (Experiment 1 = direct advice; Experiment 2 = social-emotional advice), and reciprocity. Linear mixed-effects models with investment rates as the dependent variable were used to analyze the data. ResultsMethodologically, the experimental results elucidated the fundamental characteristics of dynamic trust formation within the context of multidimensional trust information. Furthermore, High-AT individuals showed assigned less weight to reciprocity but relied heavily on reputation, and exhibited maladaptive advice-taking. Unlike low-AT individuals, high-AT individuals did not adaptively reduce reputational effect over rounds. ConclusionsOur findings highlight the unique challenges faced by individuals with high ATs when navigating complex social interactions.

How multifaceted trust influences travel intention amidst the COVID-19 pandemic: evidence from China

ABSTRACT Tourist trust is a crucial determinant of travel behavior amidst the COVID-19 pandemic. However, a thorough investigation of the multidimensional trust structure and the diverse impacts of each sub-dimension on travel behavior during COVID-19 is currently under-researched. To fill this gap, this study proposed a two-level, five-dimensional trust construct and further examined its impact on risk perception and travel intention. The moderating effect of travel motivation was also examined. Using data from 634 online survey participants in China, we conducted a hierarchical regression analysis and found that interpersonal, government, and enterprise trust are negatively associated with prospective tourists’ risk perception, which in turn increases travel intention. Moreover, high-level travel motivation enhances the negative influence of most multifaceted trust dimensions on risk perception while attenuating the negative influence of risk perception on travel intention. Our results have theoretical and managerial implications.

Adaptive multidimensional trust-based recommendation model for peer to peer applications

Abstract In today’s world, the widespread utilization of services such as Nearby Share, Near Field Communication (NFC), and Wi-Fi Direct for deploying various applications has significantly bolstered the demand for reliable and secure distributed ad-hoc peer-to-peer networks. Yet, ensuring the trustworthiness of participating nodes remains a significant challenge. Trust among nodes plays a pivotal role in collaborative network applications, especially in environments like Mobile Ad-hoc Networks and VANET (Vehicular Ad-hoc Networks). Evaluating the trustworthiness of nodes is essential for promptly identifying misleading entities, thereby preemptively preventing their involvement in ongoing transactions. Attributes or characteristics exhibited by nodes, such as honesty, selfishness, or malicious behavior, serve as key factors in trust computation. The effectiveness of trust evaluation directly influences the encouragement of honest nodes and the deterrence of malicious ones, thereby nurturing a healthy and competitive network ecosystem. Recognizing the dynamic nature of network environments, trust computation methods must be adaptable and diverse. The adaptive multidimensional trust (AMT) model introduced in this article goes beyond simple reputation assessment. It offers three distinct methods such as Direct Trust ( Direct Trust ) \left({{\rm{Direct}}}_{{\rm{Trust}}}) , multiple security parameters, identification of qualified recommenders, which got selected dynamically as per change in trust ratings of peers. AMT advocates for an incentive-driven approach to identify legitimate peers, monitoring gradual increases in their performance ratings, whereas, spikes in performance alert to potential colluding peers or nodes displaying erratic behavior. This article evaluates the effectiveness of the AMT through a case study focused on an E-commerce application. It scrutinizes the model’s performance across different percentages of malicious nodes within the network, providing a thorough analysis and discussion of the results based on the trust value of malicious and benign peers and efficiency by selecting genuine service for transaction.

Multidimensional Trust in Halal Logo of Food Products : A Study in Local Cultural Context

Multidimensional Trust in Halal Logo of Food Products : A Study in Local Cultural Context

A multi-dimensional trust attestation solution in 5G-IoT

The core missions of IoT are to sense data, transmit data and give feedback to the real world based on the calculation of the sensed data. The trust of sensing source data and transmission network is extremely important to IoT security. 5G-IoT with its low latency, wide connectivity and high-speed transmission extends the business scenarios of IoT, yet it also brings new challenges to trust proof solutions of IoT. Currently, there is a lack of efficient and reliable trust proof solutions for massive dynamically connected nodes, while the existing solutions have high computational complexity and can't adapt to time-sensitive services in 5G-IoT scenarios. In order to solve the above problems, this paper proposes an adaptive multi-dimensional trust proof solution. Firstly, the static and dynamic attributes of sensing nodes are metricized, and the historical interaction as well as the recommendation information are combined with the comprehensive metric of sensing nodes, and a multi-dimensional fine-grained trusted metric model is established in this paper. Then, based on the comprehensive metrics, the sensing nodes are logically grouped and assigned with service levels to achieve the screening and isolation of malicious nodes. At the same time, the proposed solution reduces the energy consumption of the metric process and optimizes the impact of real-time metrics on the interaction latency. Simulation experiments show that the solution can accurately and efficiently identify malicious nodes and effectively guarantee the safe and trustworthy operation of 5G-IoT nodes, while having a small impact on the latency of the 5G network.

Trust recovery tactics in financial services: the moderating role of service failure severity

PurposeGiven the fierce competition in financial services, service failure management and trust restoration tactics are becoming strategic priorities. Studies investigating trust restoration have increased over the years due to the significance of trust in services and the frequency of trust violations. Drawing on the sense-making and defensive approaches of attribution theory, this study aims to explore the effectiveness of various trust recovery tactics (e.g. apology, explanation, and investigation) in financial services considering the prevalence of service failure severity.Design/methodology/approachBased on a scenario-based survey, this study gathered data from 402 consumers of different banks in Pakistan. The study analyzed the data using ordinary least square regressions and structural equation modeling.FindingsThe study indicated that explanation is more effective in repairing character-competence and commitment-based trust, while investigation remained highly effective for inducing congruence-based trust. Interestingly, an apology was more effective for communication-based trust repairing, while context-based trust recovery was unaffected against all recovery tactics. Despite the prevalence of severe service failure, recovery actions proved fully effective for character-competence and commitment-based trust while partially effective for congruence-based trust recovery. This study also found that severe service failure undermines the effectiveness of recovery actions in repairing communication and context-based trust.Originality/valueThe study extends the literature on trust recovery by integrating sense-making and defensive attribution theory. The sense-making approach contributes to the existing knowledge on trust recovery by elucidating how consumers and service providers develop a shared understanding to facilitate the recovery mechanism of multidimensional trust in financial services.

Governance and trust in sustainability-based agri-food value chains. A comparative analysis of five cases in Germany

Value chains that generate an increased willingness to pay among consumers by offering enhanced levels of sustainability are widely discussed as an important strategy for creating new business opportunities and fostering food system transformation. Previous research has highlighted the importance of governance arrangements to secure the trust necessary for the establishment of sustainability-based value chains. However, how different coordination designs by private and public actors along the value chain affect trust formation is not well understood. To address this question, this paper combines the concepts of hybrid governance and multidimensional trust to guide a comparative analysis of five sustainability-based agri-food value chains in Germany as exemplary case studies. The findings show that different types of governance activities are necessary to build the capacity to address four different sources of trust: dispositional, affinitive, rational and procedural trust. Building trust capacities facilitates coordination of activities along the value chain and reliable delivery of sustainability-related value propositions. In all five cases, governance arrangements and building of trust capacities were geared towards increasing willingness to pay. Sustainability-based agri-food value chains have therefore limited potential to internalize the agri-food sector’s substantial negative externalities.

A multi-dimensional trust model for misbehavior detection in vehicular ad hoc networks

Communication security is one of the focus issues of vehicular ad hoc networks (VANETs). Trust model is commonly used to identify malicious attackers or filter false messages in the network, which effectively guarantees secure communication between vehicles. Constrained by the distributed network architecture of VANETs, trust evaluation results may be biased due to uneven data distribution and lack of reference. By colluding with the partners, malicious vehicle launches imbalance attack and zigzag attack to bypass the detection of the trust model. To address these new intelligent attacks, we propose a multi-dimensional trust model (MDT) in this paper, which makes a combined evaluation of different trust attributes from vehicles. In MDT, data collection and trust calculation are deployed in vehicles and trust authority (TA), respectively. Since the model dynamically adjusts the corresponding weight coefficient according to the data fluctuations of each trust indicator by adopting entropy weight method and filters anomalous evaluation results by using the median absolute deviation (MAD) algorithm, it can effectively deal with complex and variable intelligent attacks. The legitimate identity of a vehicle will be revoked from the network by TA once its trust value is less than the threshold. We have conducted extensive experimental studies to evaluate the performance of MDT. The experimental results show that the MDT model can accurately and effectively calculate the global trust of vehicles and detect malicious attacks in the network under different scenarios and tests.

Antecedents and consequences of trust as a multidimensional construct. Cross-country analysis in the luxury retail sector

The objective of this study is to understand the role of the multidimensional trust of a luxury brand as an antecedent of consumer satisfaction and a consequence of reputation and familiarity, considering -in turn- that reputation and familiarity can be a consequence of the consumer’s cognitive and affective experiences. A cross-country analysis in the luxury retail sector was carried out. Association relationships between variables are tested by a model of structural equations. For this, a transnational analysis has been carried out in the luxury retail sector. A non-probabilistic sample was used in this study. 1058 people were interviewed, 608 consumers in Santiago (Chile) and 450 in Madrid (Spain). The key role played by the multidimensional trust of a luxury brand as an antecedent of satisfaction and consequence of reputation and familiarity is confirmed. When observing the reputation and familiarity of a luxury brand as a result of the cognitive and affective experiences of the consumer, differences between Chile and Spain have been discovered. Managers can not only use the brand’s own characteristics to differentiate themselves from the competition, but they can also do so through the multi-dimensional trust of the luxury brand.

The Impact of Trust-Building Mechanisms on Purchase Intention towards Metaverse Shopping: The Moderating Role of Age

Given the uncertainty of online transactions in metaverse shopping, the digital economy encourages building a trustworthy virtual environment. Based on media richness theory, this article examines how the perceived media richness of the metaverse helps engender multidimensional trust (i.e., cognitive trust and affective trust) and leads to purchase intention in the context of metaverse shopping. The proposed model is tested based on survey data from 332 consumers on an online scenario-based platform pertaining to metaverse initiatives. Structural equation modeling is used to examine the proposed research model. The empirical research findings show that the perceived media richness of the metaverse builds cognitive trust and affective trust, which in turn affects purchase intention towards metaverse shopping. Furthermore, we classify consumers into digital natives (DNs) and digital immigrants (DIs) based on chronological age and examine the different influences of the two dimensions of trust on purchase intention towards metaverse shopping between the two groups. We identify and address several knowledge gaps in the extant trust literature. We also discuss the theoretical and managerial implications and propose several suggestions for future research.

An Investigation of Pregnant Women's Attitudes Towards Childhood Vaccination and Trust in Health Services.

Vaccination of children is of great importance for their healthy growth and development. Several concerns that have been mentioned by families due to various reasons could affect vaccination acceptance. This study aims to investigate pregnant women's attitudes toward childhood vaccinations and trust in health services. This study was designed as a descriptive study. It was conducted in a city located in the eastern part of Turkey between March and May 2019. The sample was 193 volunteer pregnant women. Data were collected using the Socio-demographic Form, the Multidimensional Trust in Health-care System Scale, and the Public Attitude toward Vaccination Scale - Health Belief Model. A positive, statistically significant relationship was found between the Multidimensional Trust in Healthcare System Scale total mean score and Perceived Susceptibility, Perceived Severity, Perceived Benefits, and Health Responsibility (p < .01). In addition, education and income level, having social security, having had a vaccination or not, and knowing vaccines affected trusts in health services; having social security, having had vaccinations or not, and knowing vaccines affected health beliefs about vaccinations (p <0.05). This study found that knowing vaccines affects both trust in health services and health beliefs about vaccination. Therefore, community health nurses working in primary care should provide parents with accurate and effective information about vaccinations.

SLA-based Multi-dimensional Trust Model for Fog Computing Environments

SLA-based Multi-dimensional Trust Model for Fog Computing Environments

A Trust Scale for Human-Robot Interaction: Translation, Adaptation, and Validation of a Human Computer Trust Scale

Recently there has been an increasing demand for technologies (automated and intelligent machines) that brings benefits to organizations and society. Similar to the widespread use of personal computers in the past, today’s needs are towards facilitating human-machine technology appropriation, especially in highly risky and regulated industries like robotics, manufacturing, automation, military, finance, or healthcare. In this context, trust can be used as a critical element to instruct how human-machine interaction should occur. Considering the context-dependency and multidimensional trust, this study seeks to find a way to measure the effects of perceived trust in a collaborative robot (cobot), regardless of its literal credibility as a real person. This article aims at translating, adapting, and validating a Human-Computer Trust Scale (HCTM) in human-robot interaction (HRI) context and its application to cobots. The Human-Robot Interaction Trust Scale (HRITS) involved 239 participants and included eleven items. The 2nd order CFA with a general factor called “trust” have proven to be empirically robust ( CFI = .94 ; TLI = .93 ; SRMR = .04 ; and RMSEA = .05 ) [ CR = .84 ; AVE = .58 , and MaxR H = .92 ]; results indicated a good measurement of the general factor trust, and the model satisfied the criteria for measure trust. An analysis of the differences in perceptions of trust by gender was conducted using a t -test. This analysis showed that statistical differences by gender exist ( p = .04 ). This study’s results allowed for a better understanding of trust in HRI, specifically regarding cobots. The validation of a Portuguese scale for trust assessment in HRI can give a valuable contribution to designing collaborative environments between humans and robots.

A novel multidimensional trust evaluation and fusion mechanism in fog-based Internet of Things

With the fast advancement of IoT, it has gained more attention from industry and academia. However, because diverse security attacks result in the lack of trust between IoT edge devices and the network, a proper trust mechanism is necessary. To address the issue, a novel trust management approach is proposed in this work. In particular, we have proposed a multidimensional trust evaluation mechanism to comprehensively evaluate the trustworthiness of IoT edge devices, with diverse opinions formed by different network entities after observing. Next, a novel trust fusion scheme named JSDM-AHP that integrates the objective Jensen–Shannon divergence measure (JSDM) and analytic hierarchy process (AHP) is developed to fuse diverse decision factors. Theoretical analysis and simulation results show that the proposed trust strategy has high computation-efficiency, scalability, resilience, robustness, and outperforms all the other compered methods in reliability. Furthermore, with the proposed security approach, diverse cyber attacks such as flooding attacks, random attacks, conflicting behavior attacks, on–off attacks, and recommendation attacks can well be defended against, reflecting the high security of the method.

Trust towards Human vs. Automated Agents: Using a Multidimensional Trust Questionnaire to Assess The Role of Performance, Utility, Purpose, and Transparency

In various domains, humans are supported by automated systems. Earlier research has suggested that trust in automated agents differs from trust in other humans. The present studies aimed at taking a multi-dimensional look at effects on trust towards automation and humans. To this end, we conducted two studies to empirically validate a multi-dimensional trust questionnaire to assess performance, utility, purpose, and transparency subdimensions of trust (Study 1, N = 160) and to study experimental effects of support agent (i.e., human vs. decision support system) and failure experience (i.e., none vs. one; Study 2, N = 181). The expected factor structure was confirmed. Moreover, the results showed that being supported by a human mostly impacted the performance subscale. In sum, the findings illustrate the importance to study trust not only uni-dimensionally but to consider different subdimensions, particularly as a single-item trust measurement was mostly correlated to performance and utility subscales.

Trust in the Healthcare System and Social Coronavirus Anxiety; A Study in the Turkish Society

Purpose: The aim of this research is to determine the level of trust in the healthcare system and coronavirus anxiety of the Turkish society during the COVID-19 pandemic. Methods: To obtain the data; "Multidimensional Trust in Health-Care Systems Scale (MTHCSS)" and "Coronavirus Anxiety Scale (CAS)" were used. The research was carried out using the online questionnaire between August-September 2020, with the participation of 1185 people. Two-Sample Independent T-Test, One-Way Analysis of Variance (ANOVA) and correlation analysis were used in the analysis of the data. Results: It was determined that the mean scale scores of the participants the MTHCSS was high (59.06±13.76) and the mean score of the CAS was (1.86±3.30) low. Analyses carried out; showed that there are significant statistical differences between gender, presence of chronic disease, working status and compliance with the measures taken, trust in the healthcare system and coronavirus anxiety (p&amp;lt; 0.05). In Addition, the correlation analysis performed showed that there is a weak negative relationship between trust in the healthcare system and social Coronavirus anxiety. Conclusion: The results showed that the Turkish society trusts their healthcare system. This makes think that the struggle given under the pandemic conditions is well managed by the Turkish healthcare system.

Retraction Note to : Secure routing scheme with multi-dimensional trust evaluation for wireless sensor network

Retraction Note to : Secure routing scheme with multi-dimensional trust evaluation for wireless sensor network

Intuitionistic fuzzy social network hybrid MCDM model for an assessment of digital reforms of manufacturing industry in China

• A new intuitionistic fuzzy aggregation method is proposed, called the IF hybrid average and geometric operator. • A multi-dimensional trust propagation model is built to reflect decision makers’ social relationships. • A social network MCDM model is proposed under an IFS environment. • The MCDM model is used to evaluate the effects of digital reform in the communication equipment manufacturing enterprises in China. • The influence of the parameters in the proposed method on the result is considered to ensure the robustness. Digital reform requires enterprises to use digital technology to create a deep integration between their production, management, and operational processes, and generate a data chain for the entire process, thereby meeting the personalized requirements and expectations of customers. The achievements of digital reform in manufacturing enterprises need to be evaluated scientifically, which can help the enterprises adjust their development strategies for a digital reform in a timely manner. We therefore propose a multi-criteria model based on a social network for assessing a digital reform under an intuitionistic fuzzy environment, wherein an intuitionistic fuzzy hybrid average and geometric operator is proposed to aggregate evaluation information more effectively than with existing methods. In addition, because the trust relationships between experts can affect their decisions, a social network is introduced to determine the weights assigned to these experts. Finally, a case study of four manufacturing enterprises is presented to verify the effectiveness of the proposed method.

Auto-Adaptive Trust Measurement Model Based on Multidimensional Decision-Making Attributes for Internet of Vehicles

As an important branch and application of the Internet of Things (IoT), the Internet of Vehicles (IoV) has the characteristics of wide distribution and dynamic connection. The current research on trust measurement and management in IoV, to some degree, solved vehicles reliability and QoS issues, but these models still have some drawbacks, like insufficient adaptability to the dynamic changes of the context. Therefore, this paper proposes an adaptive trust measurement model for IoV based on multidimensional decision-making attributes. The model not only takes full advantage of the central static trust management role of the local organization but also implements a distributed self-governing mechanism to tackle the dynamic trust management issues. In the process of trust management, the model allows vehicles to handle the trust evaluation according to the service preferences, and vehicles can select some or all of the attributes from the multidimensional trust decision attribute list. For the recommendation trust evaluation, vehicles can select those vehicles which have similar service preferences from the vehicle candidate list. When computing the recommendation trust, the recommendation trust dispersion model is used to handle evaluation bias problems. The method of information entropy is introduced to tackle the weight adaptation problem when computing comprehensive trust evaluation. The simulation results and analysis show that the model can detect and recognize the malicious vehicles in the network and mitigate the risk that malicious vehicles provide the service to normal vehicles.

Arbitration chambers and trust in technology provider: Impacts of trust in technology intermediated dispute resolution proceedings

Trust is an essential element in building relationships between different parties and contexts. Online dispute resolutions rely on temporary relationships to be successful, making trust a crucial component of such contexts. Yet, online environments are not free of suspicion. This study presents and tests a technology acceptance model based on multidimensional trust and security assurances offered by providers and developers of the environments and applications used in online arbitrations and dispute resolution procedures. The data, collected in an online survey and analyzed using structural equation modeling, show that structural assurance is an essential determinant of trust in digital technologies. Also, beliefs that service providers are benevolent towards the users positively affect their attitude towards the future use of online digital technologies and services in ADR proceedings.