Search Results (22)

The integration of blockchain technology into the Internet of Things (IoT) offers a decentralized paradigm for data integrity. However, the emergence of 51% attacks—driven by hashrate concentration—threatens the foundational trust of these resource-constrained networks. In resource-constrained IoT-enabled blockchain environments, mining-power asymmetry and limited governance capability may amplify the impact of strategic attacks. These characteristics motivate the need to analyze long-term adversarial behavior and governance effectiveness under repeated interactions. This paper develops a threshold-based analytical framework that integrates a single-stage decision model and a multi-stage discounted decision model to analyze 51% attack decisions and governance effects in asymmetric blockchain mining environments. We characterize the interaction between competing mining pools as a multi-stage game, integrating key parameters such as the discount factor of future utility and recovery penalty cycles. Our analysis demonstrates that a multi-stage framework creates a “long-term deterrent effect” where the net present value of potential future losses outweighs the immediate gains of hashrate abuse. analytical results indicate that the strategic threshold for launching an attack is highly sensitive to the duration of punitive measures and the accuracy of IoT-based anomaly detection. The results provide useful insights into the design of governance and incentive mechanisms for blockchain systems deployed in resource-constrained and heterogeneous environments. Full article

This study examines the conditional effects of trust on Generation Z’s environmental behaviour using a climate change risk perception framework within an input–output model. Climate change awareness initiates the process, while generalised trust (GT), institutional trust (IT), and community engagement mediate the relationship with environmental behaviour. Results show that individual trust plays a more significant role than institutional trust; however, their synergistic interaction is essential for developing climate change risk perceptions and community engagement. In low-trust contexts, community engagement emerges as a critical driver of positive environmental behaviour, underscoring the importance of trust alignment across individual and institutional levels. The findings underscore the need for strategies that address trust deficits and emphasise community-based engagement. Future research should explore the impact of cognitive biases, such as temporal discounting and status quo bias, to bridge the gap between awareness and action among Generation Z. Full article

The accelerating global demand for renewable heating, cooling and electricity, driven by climate change and rising living standards, presents both a challenge and an opportunity for sustainable energy transitions. This paper introduces the Initial-Aid Cashback (IAC) model, an innovative business model designed to finance renewable energy solutions, with a focus on space cooling, by leveraging citizen participation and collaborative financing mechanisms. The model incentivizes private investors through discounted energy prices, while system operators benefit from reduced upfront capital requirements and minimised financial risk. Through two case studies, an office building in Romania (small-scale case) and the application of the REGEN-BY-2 technology in a mixed housing–office area (large-scale case), the paper demonstrates the model’s potential to accelerate the adoption of renewable cooling technologies, enhance profitability for operators, and provide attractive returns for investors. The findings highlight the model’s adaptability to diverse stakeholder needs, its scalability, and its role in fostering the clean energy transition (CET). However, challenges such as the need for a minimum number of investors, legal complexities, and trust-building among stakeholders are identified as critical barriers to implementation. The paper concludes that the IAC model offers a promising pathway to integrate citizens and small investors into the CET, while emphasising the importance of supportive policies, clear governance structures, and practical testing to ensure its success. Full article

Generative AI (GenAI) now produces text, images, audio, and video that can be perceptually convincing at scale and at negligible marginal cost. While public debate often frames the associated harms as “deepfakes” or incremental extensions of misinformation and fraud, this view misses a broader socio-technical shift: GenAI enables synthetic realities—coherent, interactive, and potentially personalized information environments in which content, identity, and social interaction are jointly manufactured and mutually reinforcing. We argue that the most consequential risk is not merely the production of isolated synthetic artifacts, but the progressive erosion of shared epistemic ground and institutional verification practices as synthetic content, synthetic identity, and synthetic interaction become easy to generate and hard to audit. This paper (i) formalizes synthetic reality as a layered stack (content, identity, interaction, institutions), (ii) expands a taxonomy of GenAI harms spanning personal, economic, informational, and socio-technical risks, (iii) articulates the qualitative shifts introduced by GenAI (cost collapse, throughput, customization, micro-segmentation, provenance gaps, and trust erosion), and (iv) synthesizes recent risk realizations (2023–2025) into a compact case bank illustrating how these mechanisms manifest in fraud, elections, harassment, documentation, and supply-chain compromise. We then propose a mitigation stack that treats provenance infrastructure, platform governance, institutional workflow redesign, and public resilience as complementary rather than substitutable, and outline a research agenda focused on measuring epistemic security. We conclude with the Generative AI Paradox: as synthetic media becomes ubiquitous, societies may rationally discount digital evidence altogether, raising the cost of truth for everyday life and for democratic and economic institutions. Full article

Driven by government subsidies and advertising revenue, air taxis present an innovative solution to alleviate traffic congestion and are poised for growth. However, at their current stage of development, air taxi companies primarily operate short-distance routes within cities and rarely offer intercity services. Moreover, as a new mode of transportation, air taxis experience low levels of consumer trust at present. This study, grounded in the Hotelling model, examines differentiated decision-making scenarios between two competing air taxi service providers. It systematically analyzes how service expansion (specifically, the introduction of intercity services) and advertising strategies affect pricing, market share, and profits. Furthermore, it explores optimal decision-making patterns under external disturbances, providing theoretical support for service providers formulating operational strategies. We constructed a differentiated decision-making game model to simulate competition between Service Provider 1 (which does not offer intercity services but may advertise) and Service Provider 2 (which advertises but may choose whether to offer intercity services). By comparing game equilibrium outcomes under different decision combinations, we identify threshold conditions for key variables (e.g., additional price for intercity services and the advertising discount coefficient). The model is further expanded to incorporate external disturbance factors, allowing for analysis of how such environments influence the profitability of each decision pattern. Research has revealed that 1. offering intercity services can increase a provider’s optimal price and market share, but only if the “additional price for intercity services exceeds the threshold”; 2. both providers choosing advertising services is the optimal strategy, but if the advertising discount coefficient exceeds a reasonable range, it will intensify vicious competition. Therefore, it must be controlled within the optimal threshold to avoid adverse effects; 3. under external disturbance conditions, service providers prefer models that do not involve intercity services, and the “both parties advertise (NTX)” combination is more optimal. If intercity services are necessary, disturbance risks must be carefully assessed, or flexible cost and operational strategies should be implemented to hedge against negative impacts. Full article

Traditional food markets are a key node of resilient food systems worldwide. However, improper food handling and limitations in market structures may result in foodborne disease. This study assessed the decision-making of consumers and vendors in traditional markets to identify opportunities to reduce foodborne contamination and exposure. A cross-sectional survey of 150 consumers and 150 vendors was conducted in Sidama, Ethiopia, in July–August 2022 to investigate practices, behavior drivers, and enabling environment factors relevant to food safety. Descriptive statistics were used to summarize demographics and behavior variables, and the Poverty Probability Index for socioeconomic status. Women consumers were the primary deciders for what food to buy. Of those surveyed, 26% of vendors and 19% of consumers lived below $3.20 USD/day. Consumers choose to purchase food based on price, food quality, vendor personality, and food safety (assessed using visual and sensory cues). Vendors were unconcerned about foodborne disease (73%) and attributed business success to food quality, their personality, and offering discounts. Salience and demand for food quality, as well as trusted relationships, could be leveraged as business incentives for vendors to adopt food safety practices and to increase consumers’ preference for safer food and ability to identify it. Full article

In this paper, I argue that there are several different circumstances in which it is rational for human agents not to trust artificial agents (such as ChatGPT). I claim that artificial agents cannot, in principle, be programmed with their own self (nor a simulation of their own self) and, consequently, cannot properly understand the indexicals ‘I’ and ‘me’. It also follows that they cannot take up a first-person point-of-view and that they cannot be conscious. They can understand that agent so-and-so (described in objective indexical-free terms) trusts or is entrusted but cannot know that they are that agent (if they are) and so cannot know that they are trusted or entrusted. Artificial agents cannot know what it means for it to have a normative expectation, nor what it means for it to be responsible for performing certain actions. Artificial agents lack all of the first-person properties that human agents possess, and which are epistemically important to human agents. Because of these limitations, and because artificial agents figure centrally in the trust relation defined in the Buechner–Tavani model of digital trust, there will be several different kinds of circumstances in which it would be rational for human agents not to trust artificial agents. I also examine the problem of moral luck, define a converse problem of moral luck, and argue that although each kind of problem of moral luck does not arise for artificial agents (since they cannot take up a first-person point-of-view), human agents should not trust artificial agents interacting with those human agents in moral luck and converse moral luck circumstances. Full article

Background: Elderly drivers often face safety challenges due to age-related declines in cognitive, sensory, and motor functions. Advanced Driver Assistance Systems (ADAS) offer a potential solution by enhancing safety and mobility. Objectives and method: This systematic review investigates the factors influencing the perception and usage of ADAS among elderly drivers, focusing on perceived safety, usefulness, trust, and ease of use. Results: Older adults show a preference for Level 1 ADAS, which they perceive as safer. Although they acknowledge the usefulness of ADAS in supporting their autonomy, skepticism remains regarding higher-level systems, primarily due to concerns about reliability and invasiveness. Trust and ease of use are essential factors influencing their acceptance. The review identifies common themes and barriers to the adoption of these technologies and emphasizes the need for senior-friendly interfaces and targeted training. The findings indicate that addressing these issues can significantly improve the safety and mobility of elderly drivers. The successful adoption of ADAS among older adults depends on balancing safety, control, and ease of use, with gradual and supportive integration fostering greater acceptance and trust. Conclusions: This study outlines practical implications for stakeholders, emphasizing the need for user-friendly ADAS design, public awareness campaigns, government incentives, insurance discounts, and community training to enhance adoption among older drivers. Full article

Background: This paper examines the economic implications of market segmentation on consumer purchasing behavior with a particular emphasis on intertemporal pricing strategies in dynamic markets. Methods: In order to analyze optimal discount rates and the timing for price reductions for consumer segments, including loyal and deal-prone customers, a detailed mathematical model was developed. The model incorporates theories of consumer behavior and pricing elasticity to simulate market responses to price changes throughout a product’s lifecycle. Results: This research indicates that market segmentation enhances sales by targeting the distinct preferences of loyal consumers, who are less price-sensitive and who stabilize revenue streams, and deal-prone consumers, who respond to price reductions. Customizing pricing strategies for loyal consumers and deal-prone consumers increases sales volumes and optimizes profitability. Conclusions: This research improves our comprehension of market segmentation and dynamic pricing, providing a practical framework for businesses to create effective pricing strategies that can be promptly implemented. It emphasizes the significance of understanding consumer behavior and price sensitivity in the interest of revenue promotion. This study also emphasizes the social implications of equitable pricing practices, promoting the implementation of transparent and value-based strategies to promote market inclusivity and consumer trust. Full article

Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government which seeks to create a sustainable human-centric society by putting to work recent advances in technology. One of the key challenges in implementing Society 5.0 is providing trusted and secure services for everyone to use. Motivated by this challenge, this paper makes three contributions that we summarize as follows: Our first main contribution is to propose a novel blockchain and smart contract-based trust and reputation service design to reduce the uncertainty associated with buyer feedback in marketplaces that we expect to see in Society 5.0. Our second contribution is to extend Laplace’s Law of Succession in a way that provides a trust measure in a seller’s future performance in terms of their past reputation scores. Our third main contribution is to illustrate three applications of the proposed trust and reputation service. Here, we begin by discussing an application to a multi-segment marketplace, where a malicious seller may establish a stellar reputation by selling cheap items, only to use their excellent reputation score to defraud buyers in a different market segment. Next, we demonstrate how our trust and reputation service works in the context of sellers with time-varying performance due, say, to overcoming an initial learning curve. We provide a discounting scheme where older reputation scores are given less weight than more recent ones. Finally, we show how to predict trust and reputation far in the future, based on incomplete information. Extensive simulations have confirmed the accuracy of our analytical predictions. Full article

Food safety in developing countries has always been a concern, and deciding to purchase foods with a healthy label can be challenging. The goal of this study was to investigate the behavior of consumers for healthy foods by evaluating the factors influencing the prevalence of purchasing them despite having to pay a premium. Required data were collected in 2022 from 359 households in Mashhad, Iran, through an online questionnaire. A Generalized Poisson model was employed for analysis and the results indicate that the consumer’s field of study, the importance of food shape and size, the importance of food healthiness, the level of government supervision, practicing the 5Rs, awareness of the harmful effects of fast food on health (1% level) and variables of trust in a brand of healthy food, and the level of knowledge about the harmful effects of chemical fertilizers and toxins on human health (10% level) have a direct and significant relationship with consumers’ willingness to purchase more healthy foods for which they are willing to pay a premium. On the other hand, the relationship of some other factors, such as the importance of food price (1% level) and household size, household expenses, presence of individuals over 60 years old in the household, and the importance of food taste and flavor (5% level) became negative and significant. Therefore, to promote the consumption of foods with a healthy label for the purpose of reducing environmental issues and human health problems, it is recommended to produce and offer various healthy foods, create local markets, provide discounts and economic incentives to the public, and use attractive packaging with accurate and readable labels. Full article

Focusing on sustainable fashion brands’ effective price promotion, this experimental study developed two sets of stimuli, ‘discount’ and ‘disclosure’ strategies, and tested consumers’ evaluations of price fairness, product attractiveness, quality, and brand trust based on each strategy. Subsequently, this study compared consumers’ evaluations of the discount and disclosure strategies. An analysis of 961 Korean samples revealed that a high discount rate increased price fairness and product attractiveness, and the highly promotion-focused consumers were more likely to perceive product attractiveness and quality when positive framing was presented. In the disclosure strategy, the reference point effect was prominent; when the conventional markup rate was provided, consumers showed greater price fairness, product attractiveness, and brand trust. Furthermore, it was noteworthy that disclosing conventional markup along with the firm’s markup showed the same price fairness perceptions as that of a high markup rate. Built on reference point and regulatory focus fit, this study empirically proved the effectiveness of the price promotions of sustainable fashion brands to whom quality and trustworthiness are greatly important, extending the academic originality of this study. Practically, effective use of price promotion strategies can help fashion management handle inventory problems in a sustainable way without massive investment in technologies. Full article

The aim of the research was to analyze consumer behavior regarding changes in the place where the food was purchased during the COVID-19 pandemic. An analysis of the relationship between sociodemographic characteristics and changes in the frequency of food purchases in specified retail outlets was presented. Different consumer reactions to the threats and restrictions that resulted from the COVID-19 pandemic were found. Gender had a statistically significant impact on the changes in the place of purchase in the case of supermarkets and discount stores. Women were reported to be more cautious about the risks associated with shopping in supermarkets and discount stores. Age had a statistically significant impact on the frequency of grocery shopping in small local/rural stores, in medium-sized self-service stores, in supermarkets and in discount stores. Among the group of respondents aged 46 and over, greater trust in larger commercial units was observed. Education had a statistically significant impact on the frequency of shopping for groceries only in supermarkets. In turn, the place of residence had a statistically significant impact on the change in the frequency of making purchases in medium-sized self-service stores and discount stores. The results of our own research are not unambiguous, but they indicate certain tendencies in the perception of health safety when shopping among various social groups. Full article

A single sensor is prone to decline recognition accuracy in the face of a complex environment, while the existing multi-sensor evidence theory fusion methods do not comprehensively consider the impact of evidence conflict and fuzziness. In this paper, a new evidence weight combination and probability allocation method is proposed, which calculated the degree of evidence fuzziness through the maximum entropy principle, and also considered the impact of evidence conflict on fusing results. The two impact factors were combined to calculate the trusted discount and reallocate the probability function. Finally, Dempster’s combination rule was used to fuse every piece of evidence. On this basis, experiments were first conducted to prove that the existing weight combination methods produce results contrary to common sense when handling high-conflicting and high-clarity evidence, and then comparative experiments were conducted to prove the effectiveness of the proposed evidence weight combination and probability allocation method. Moreover, it was verified, on the PAMAP2 data set, that the proposed method can obtain higher fusing accuracy and more reliable fusing results in all kinds of behavior recognition. Compared with the traditional methods and the existing improved methods, the weight allocation method proposed in this paper dynamically adjusts the weight of fuzziness and conflict in the fusing process and improves the fusing accuracy by about 3.3% and 1.7% respectively which solved the limitations of the existing weight combination methods. Full article

This study aimed to identify the current experiences with and future preferences for payment and reimbursement models for high-priced hospital therapies in the Netherlands, where the main barriers lie and assess how policy structures facilitate these models. A questionnaire was sent out to Dutch stakeholders (in)directly involved in payment and reimbursement agreements. The survey contained statements assessed with Likert scales, rankings and open questions. The results were analyzed using descriptive statistics. Thirty-nine stakeholders (out of 100) (in)directly involved with reimbursement decision-making completed the survey. Our inquiry showed that currently financial-based reimbursement models are applied most, especially discounts were perceived best due to their simplicity. For the future, outcome-based reimbursement models were preferred, particularly pay-for-outcome models. The main stated challenge for implementation was generating evidence in practice. According to the respondents, upfront payments are currently implemented most often, whereas delayed payment models are preferred to be applied more frequently in the future. Particularly payment-at-outcome-achieved models are preferred; however, they were stated as administratively challenging to arrange. The respondents were moderately satisfied with the payment and reimbursement system in the Netherlands, arguing that the transparency of the final agreements and mutual trust could be improved. These insights can provide stakeholders with future direction when negotiating and implementing innovative reimbursement and payment models. Attention should be paid to the main barriers that are currently perceived as hindering a more frequent implementation of the preferred models and how national policy structures can facilitate a successful implementation. Full article