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This study aims to propose a consensus model that considers dynamic trust and the hesitation degree of the expert's evaluation, and the model can provide personalized adjustment advice to inconsistent experts.

The trust degree between experts will be affected by the decision-making environment or the behavior of other experts. Therefore, based on the psychological “similarity-attraction paradigm”, an adjustment method for the trust degree between experts is proposed. In addition, we proposed a method to measure the hesitation degree of the expert's evaluation under the multi-granular probabilistic linguistic environment. Based on the hesitation degree of evaluation and trust degree, a method for determining the importance degree of experts is proposed. In the feedback mechanism, we presented a personalized adjustment mechanism that can provide the personalized adjustment advice for inconsistent experts. The personalized adjustment advice is accepted readily by inconsistent experts and ensures that the collective consensus degree will increase after the adjustment.

The results show that the consensus model in this paper can solve the social network group decision-making problem, in which the trust degree among experts is dynamic changing. An illustrative example demonstrates the feasibility of the proposed model in this paper. Simulation experiments have confirmed the effectiveness of the model in promoting consensus.

The authors presented a novel dynamic trust consensus model based on the expert's hesitation degree and a personalized adjustment mechanism under the multi-granular probabilistic linguistic environment. The model can solve a variety of social network group decision-making problems.

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services.

A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, interval-valued intuitionistic fuzzy set (IVIFS) -was utilized to model the problem's uncertainty with analytic called IVIFS- hierarchy process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the fuzzy evaluation method (FEM) is followed for assessing the readiness score of indices in case studies.

The findings indicated that “Trust in government” is the most significant index affecting citizen's trust in e-Gov services while “Maintenance and support” has the least impact on user's intention to use e–Gov services.

The study contributes by introducing a unique research methodology that integrates three phases, including fuzzy Delphi, IVIFS AHP and fuzzy evaluation method. Moreover, the fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-valued intuitionistic fuzzy models the ambiguity of experts' judgments in an interval.

The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation.

The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies.

The purpose of this study is to investigate the impact of e-service quality and e-trust on customer e-satisfaction and, subsequently, on customer e-loyalty towards a website in the online shopping environment of Pakistan.

The research employed a quantitative approach and utilised structural equation modelling to investigate the relationship between e-service quality and e-trust on consumers’ e-satisfaction and e-loyalty. The data were collected from 250 individuals who actively use online shopping websites to purchase products in Pakistan.

The findings revealed that e-service quality and e-trust offered on e-commerce websites significantly impacted customer e-loyalty. However, it was found that both e-service quality and e-trust do not have a significant impact on customer e-satisfaction. In addition, the findings showed that customer e-satisfaction positively impacts e-loyalty.

Overall, these findings emphasise the importance of e-service quality, e-trust and customer e-satisfaction and their role in cultivating customer loyalty within the context of the online shopping environment in Pakistan.

This study contributes to the existing literature on online shopping in Pakistan by exploring the factors influencing consumer behaviour in this context. The findings add to the academic understanding of consumer behaviour and provide valuable insights for e-commerce businesses in Pakistan.

Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.

This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.

The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.

The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.

This study aims to propose an innovative model that integrates variables and examines the influence of internet usage expertise, perceived risk and attitude toward information control on privacy concerns (PC) and, consequently, in consumers’ willingness to disclose personal information online. The authors also propose to test the mediation role of trust between PCs and willingness to disclose information. Trust is not a predictor of PC but a causal mechanism – considering that the focus is to understand consumers’ attitudes and behavior regarding the virtual environment (not context-specific) (Martin, 2018).

The authors developed a survey questionnaire based on the constructs that compose the proposed model to collect data from 864 respondents. The survey questionnaire included the following scales: internet usage expertise from Ohanian (1990); perceived risk, attitude toward information control, trust and willingness to disclose personal information online from Malhotra et al. (2004); and PC from Castañeda and Montoro (2007). All items were measured on a Likert seven-point scale (1 = totally disagree; 7 = totally agree). To obtain Westin’s attitudinal categories toward privacy, respondents answered Westin’s three-item privacy index. For data analysis, the authors applied covariance-based structural equation modeling.

First, the proposed model explains the drivers of consumers’ disposition to provide personal information at a level that surpasses specific contexts (Martin, 2018), bringing the analysis to consumers’ level and considering their general perceptions toward data privacy. Second, the findings provide inputs to propose a better definition of Westin’s attitudinal categories toward privacy, which used to be defined only by individuals’ information privacy perception. Consumers’ perceptions about their abilities in using the internet, the risks, their beliefs toward information control and trust also help to delimitate and distinguish the fundamentalists, the pragmatics and the unconcerned.

Some limitations weigh the theoretical and practical implications of this study. The sample size of pragmatic and unconcerned respondents was substantially smaller than that of fundamentalists. It might be explained by applying Westin’s self-report index to classify the groups according to their score regarding PCs. Most individuals affirm having a great concern for their data privacy but still provide online information for the benefit of personalization – known as the privacy paradox (Zeng et al., 2021). It leads to another limitation of this research, given the lack of measures that classify respondents by considering their actual behavior toward privacy.

PC emerges as an important predictor of consumer trust and willingness to disclose their data online, and trust also influences this disposition. Managers need to implement actions that effectively reduce consumers’ concerns about privacy and increase their trust in the company – e.g. adopting a clear and transparent policy on how the data collected is stored, treated, protected and used to benefit the consumer. Regarding the perception of risk, if managers convince consumers that the data collected on the internet is protected, they tend to be less concerned about privacy.

The results suggest different aspects influencing the willingness to disclose personal information online, including different responses considering consumers’ PCs. Through their policies and legislation, the authors understand that governments must be attentive to this aspect, establishing regulations that protect consumers’ data in the virtual environment. In addition to regulatory policies, education campaigns can be carried out for both consumers and managers to raise the discussion about privacy and the availability of information in the online environment, demonstrating the importance of protecting personal data to benefit the government, consumers and organizations.

Although there is increasing research on consumers’ privacy, studies have not considered their attitudinal classifications – high, moderate and low concern – as moderators of willingness to disclose information online. Researchers have also increased attention to the antecedents of PCs and disclosure of information but overlooked possible mechanisms that explain the relationship between them.

The current body of empirical research regarding the impact of trust in the cybersecurity commitment of institutions on digital payment usage has focused solely on a macro-level analysis, overlooking the intricate dynamics between institutions' cybersecurity commitments and the trust levels of digital payment users. In light of this limitation, this study aims to offer a more comprehensive understanding of this complex relationship.

A case study was conducted on digital payment users in India through the critical realist lens. To gather data, interviews and focus group discussions were conducted with digital payment users from various regions of the country.

The citizen-centric outcomes of the national cybersecurity commitment (performance and responsiveness) are the most prominent and impactful trust indicators. These outcomes play a crucial role in shaping digital payment users' perception and trust in the cybersecurity commitment of public institutions. Individuals' value positions also influence trust judgments, as it is essential to recognize the value tensions that may arise due to security implementation and their congruence with citizens' values.

The findings of this study have significant implications for policymakers. They are potentially an artifact of the security and perception of digital payment users and the cultural uniqueness of digital payment users in India.

The study proposes a holistic understanding of the relationship between institutions' cybersecurity commitments and the trust levels of digital payment users. It offers a qualitative evaluation of how digital payment users perceive and construe efficient information security management implemented by public institutions.

The relationship between trust, accountability and procedural justice is studied via research into British credit unions (CUs) following regulatory reform to remedy problems exposed by the 2007–2008 global financial crisis.

Interviews at 13 case studies of different types and sizes of credit unions in Glasgow, Scotland, are examined using template analysis and abductive theorizing to understand the effects of disproportionate reforms on small credit unions.

Smaller credit unions found three regulatory changes – namely dual regulators, increased minimum reserves and introduction of the Senior Managers and Certification Regime – excessive. Excessive change generated distrust in regulators. Regulators' insufficient attention to procedural justice contributed to this distrust.

Linkage of multidimensional confluent trust to a multilevel system of accountability provides an original way of understanding how indiscriminate attempts at trust repair damage some elements of trust in formal regulatory systems. Recognition of the need for procedural justice to enable smaller credit unions to articulate their extant checks and potential exemption from formal regulations provides another valuable contribution. The explanation of the abductive logic employed is also original.

Gripped by the COVID-19 pandemic, the airline industry has faced many restrictions. Based on the determining factor of repurchase intention, this research paper addresses the roles of brand engagement (BE) and consumer trust during the pandemic.

A number of 439 out of 500 questionnaires, which were distributed among the Iranian airlines' customers, were completed and returned (an 87% response rate). SmartPLS 3 was used to carry out the confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) in order to validate the research hypotheses.

The results show that during the COVID-19 pandemic, BE had a significant effect on customer purchase intention. In addition, BE boosted customer trust and thereby increased repurchase intention. Perceived risks of COVID-19 moderated these relationships. The findings also show that airline customers are highly sensitive to various perceived risks and were especially so during the COVID-19 pandemic. These perceived risks have major impacts on customers' intention to reuse the services of airline companies. High levels of perceived risk decrease customer trust, BE and repurchase intention rates, and vice versa.

This paper provides authorities and decision-makers of the air transport industry with several practical recommendations based on the research findings. As the results confirmed, there is a worthwhile relationship between BE and customer trust; regarding the both direct and indirect benefits of customer trust for for-profit firms and the huge importance of trust in creating competitive advantages, different airline companies need to implement various strategies to engage customers with their brand names, and thereby institutionalize trust in their customers' minds during the pandemic. Since customer trust was also found to improve repurchase intention rates significantly, authorities of the airline industry must take actions to reduce feelings of mistrust and risk among consumers and increase customer trust during COVID-19.

This paper is the first to explore the effect of BE on airline customers' repurchase intentions during the COVID-19 pandemic. It has produced practical suggestions to employees and activists of the air transport industry regarding the use of BE as a tool to restore customer trust during and after the COVID-19 epidemic. This research focuses on the airline industry, which is particularly interesting given the industry's intensely competitive environment and the dramatic effect of COVID-19 on the industry.

This study investigates the factors that influence citizens trust in public leaders [i.e. presidents, members of parliament (MPs) and local government leaders (LGs)] in 34 countries in Africa between 2019 and 2021.

Individual-level data with a sample size of 48,084 was obtained from the Afro-Barometer round 8 survey only and analyzed using multivariate binary logistic regression.

Several important and intriguing observations were made from this analysis: (1) the performance of public leaders influences citizens trust in their leaders; (2) the perceived corruption of public leaders and civil servants and the level of corruption influence citizens trust in public leaders; (3) perceived neighborhood problems (i.e. fear of violence, fear of terrorism and service delivery) influence citizens trust in their public leaders and (4) the socio-demographic characteristics of citizens (i.e. age, religion, education, location, employment and political party affiliation) influence citizens trust in their public leaders.

This study is exceptional in two ways: (1) it examines and compares citizens trust in public leaders across different levels, i.e. presidents, MPs and LGs in Africa and (2) it examines and compares the factors influencing citizens trust in public leaders in Africa comparatively.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.