Crisis Of Trust Research Articles

The effect of disaggregated financial statements on potential nonprofit donors

PurposeThis study examines the effect that aggregated versus disaggregated financial statements has on a potential donor’s decision to donate to both large and small nonprofit organizations.Design/methodology/approachThis study utilizes 147 participants in a 2 × 2 design in which participants are placed in the role of potential donors.FindingsResults indicate that disaggregated financial statements increase the likelihood of donors donating. Findings suggest that trust serves as a mediating effect, as disaggregated information leads to increased organizational trust, which subsequently leads to an increased likelihood of donating.Research limitations/implicationsProviding participants with a fictitious scenario may not reflect true donor behavior. Participants also have no personal risk in deciding to donate because they are not actually making a financial donation.Practical implicationsOur results provide insight into the decision process of donors as this study suggests that disaggregated information leads to higher donations. As disaggregated information leads to higher trust, organizations are incentivized to provide disaggregated information because it increases the appearance of trustworthiness.Social implicationsFundraising campaigns can benefit from our findings. Nonprofit organizations should evaluate the impact on trust when considering best practices related to disaggregated information.Originality/valueThere is currently a trust crisis in America’s nonprofits, and this study aims to understand how the level of aggregation of financial statement information can increase trust and subsequent donor giving.

Social Trust in China

This article provides a comprehensive examination of social trust in China. It addresses ongoing debates about how much people trust, whether there is a trust crisis, and where trust comes from. Analyzing extensive harmonized data from the Chinese General Social Survey (2003–2021) and the World Values Survey (1990–2018) spanning three decades, we find that Chinese people have high levels of general trust in others; this high social trust has been largely stable over the last three decades; and political confidence and perceived fairness are two key drivers of trust. On the other hand, we see marked low trust toward several groups, such as strangers, businessmen, and religious individuals. Potential explanations are discussed. This study contributes to key trust debates and identifies novel trust patterns that can serve as valuable subjects for future research.

Exploring the Communication Impact of New Media Platforms Based on Pet-Based Short Videos

In recent years, pet short videos have attracted a large number of viewers as a popular topic, and as a result, have raised awareness of pets and stray animals. However, to shoot eye-catching video content, some creators abuse or abandon pets. These problems not only cause harm to the animals but also trigger a social crisis of trust, accompanied by ethical and legal issues. This paper explores the reasons for the popularity of pet-based short videos and the positive and negative impacts on the public and society of this issue. The study will adopt a case study research method to analyze the overall influence of pet bloggers by collecting relevant videos from short video platforms; meanwhile, popular videos and comments involving pet abuse and other incidents will be analyzed for content and public opinion. The final results of the study show that although pet short videos can effectively raise public concern about pets and stray animals, their negative ethical and social effects cannot be ignored, such as pet abuse and blind pet ownership, which hurt society. Future research should further focus on how to improve the ecology of short-form pet content thereby mitigating the negative social and animal impacts of pet-based short-form videos, thus enabling more positive impacts of video communication.

Investor behavior in crisis: a comparative study of fear-driven downtrends and confidence-led recoveries

PurposeThe purpose of this research is to investigate the differences between financial crises of fear and confidence and the differential behavior between downtrends and recovery.Design/methodology/approachFive national stock markets have been analyzed – the USA (SP500), China (Hang Seng), Spain (IBEX 35), Japan (Nikkei) and Germany (DAX) – through the evolution of three world economic crises: the mortgage bubble crisis of 2007 in the first place, with special attention to the bankruptcy of Lehman Brothers, which will be treated as an independent crisis process, and the crisis caused by COVID-19. The behavioral finance theory, with the support of the complexity theory in the field of risk management, will establish the different behavioral biases that explain the differences between the two types of crises, fear and confidence, when confronted with risk.FindingsEconomic crises resulting from a shocking event, addressed as crises of fear in this research, such as Lehman Brothers or COVID-19, are fast-moving; all the economies analyzed show a common pattern of evolution. The difference is found in the recovery periods in which the previous parallelism does not continue. Crisis events that arise from a social context, addressed as crises of trust in this research, follow similar patterns in their evolution; nonetheless, the start date presents higher variations than those originated by a shock. These crises also lack parallelism between fall and recovery.Practical implicationsUnderstanding crisis process patterns may help to prevent them and alleviate their effects when they occur.Originality/valueUnderstanding crisis process patterns may help to prevent them and alleviate their effects when they occur. This constitutes an original field of research.

Discursive Mechanisms of Constructing the “Existential Other” in the Relations of Trust Crisis between Russia and the West

Discursive Mechanisms of Constructing the “Existential Other” in the Relations of Trust Crisis between Russia and the West

High-Precision Heterogeneous Satellite Image Manipulation Localization: Feature Point Rules and Semantic Similarity Measurement

Misusing image tampering software makes it easier to manipulate satellite images, leading to a crisis of trust and security concerns in society. This study compares the inconsistencies between heterogeneous images to locate tampered areas and proposes a high-precision heterogeneous satellite image manipulation localization (HSIML) framework to distinguish tampered from real landcover changes, such as artificial constructions, and pseudo-changes, such as seasonal variations. The model operates at the patch level and comprises three modules: The heterogeneous image preprocessing module aligns heterogeneous images and filters noisy data. The feature point constraint module mitigates the effects of lighting and seasonal variations in the images by performing feature point matching, applying filtering rules to conduct an initial screening to identify candidate tampered patches. The semantic similarity measurement module designs a classification network to assess RS image feature saliency. It determines image consistency based on the similarity of semantic features and implements IML using predefined classification rules. Additionally, a dataset for IML is constructed based on satellite images. Extensive experiments compared with existing SOTA models demonstrate that our method achieved the highest F1 score in both localization accuracy and robustness tests and demonstrates the capability for handling large-scale areas.

Application of Topic Modelling Technology to the Analysis of Social Media Comments in the Context of State Identity Politics Research

In the situation of a shrinking field of public politics and a crisis of political trust, citizens may seek an alternative arena for presenting their own point of view. The social Internet space serves as a virtual projection of public contradictions and acts as an arena for the presentation and confrontation of political interests. At the same time, the increasing state presence in virtual space and the growing trust to online sources of information make social media an important channel for promoting certain patterns of political interpretations. The aim of this paper is to analyse the reactions of social media users to discover their attitudes towards the main narratives of contemporary identity politics of the Russian state. We used the Topic modelling method to study citizens’ reactions to various aspects of state identity politics. The total number of comments in the collected database is 8,023 (09/2022‑09/2023). In almost all the identified topics we can note the polarity of citizens’ opinions, examples of which are given in the article. However, there are a few topics where the users’ opinion is quite consolidated; for example, the image of the Crimean bridge on the cover of new textbooks was widely supported in comments, while the topic of traditional values, on the contrary, evokes negative feelings and shows “public tiredness”. Despite the limitations described in the conclusion of the article, the study demonstrates the high potential of applying the method of topic modelling to the analysis of the reactions of social media users.

Study on Audit Quality Management Optimization of M Accounting Firm

With the continuous development of market economy and the increasing prosperity of capital market in our country, accounting firms are taking on more and more important responsibilities as "gatekeepers" of capital market. Audit quality, as the core of accounting firm management, directly affects the stability and development of the financial market. The level of audit quality is directly related to investors' trust and dependence on financial reports, the reputation and business development of accounting firms, and influences corporate governance, financial market stability and government supervision. All along, the regulatory authorities pay more attention to the audit quality management of the firm. In the announcement disclosed by the China Securities Regulatory Commission, the firm will be punished for illegal behaviors every year. In recent years, the Ministry of Finance and the China Annotations Association will conduct practice quality supervision and inspection of the firm every year, the audit quality management of the firm still has defects. These problems may cause a crisis of trust in the public, which in turn affects the development of the entire industry. However, the current accounting firms do not pay enough attention to the audit quality management and the supervision is insufficient, and the audit quality becomes low. In order to promote the high-quality and sustainable development of the registered accounting industry, it is urgent to strengthen the audit quality management of accounting firms. Therefore, this paper takes M Accounting Firm as the case study object, analyzes and summarizes the existing problems in audit quality management of accounting firms found during the internship, finds out the causes of the problems, and puts forward targeted optimization suggestions, so as to strengthen the audit quality management of this accounting firm and promote its healthy and sustainable development.

Integration of AI Technology and ZPD: Pinpointing the Zone of Student Development to Promote Educational Innovation and Efficiency Improvement

In the era of rapid technological advancement, AI has profoundly penetrated various sectors of society, including education. This paper explores the positive impact of AI on students' Zone of Proximal Development (ZPD), aiming to assist teachers in making more accurate judgments regarding multiple students' ZPDs and thereby enhancing educational teaching. The findings reveal that AI technology, through its application in ZPD, can provide personalized learning resources and assistance to students, as well as offer teachers appropriate teaching content and strategies tailored to students' needs. However, in the actual teaching process, the application of ZPD to teaching still faces difficulties related to students' individualization, sensitive emotions, and trust crises. Based on this, this paper puts forward the following suggestions. Teachers need to be actively trained in AI to overcome potential resistance from older educators. At the same time, teachers should focus on identifying further technological advances in ZPD and related areas to maximize the benefits of AI in education.

How to Alleviate the Lack of Trust in Live Streaming: A Moderated Mediation Model of Immersive Technology

With the rapid growth of live streaming e-commerce, there have been frequent issues such as broadcasters’ misleading product promotions and artificial live streaming scenes that have created a crisis of trust for consumers. To solve the above problems, this study introduces immersive technology into live streaming and establishes a moderated mediation model with trust as the mediation and immersive technology as the moderator to investigate impact of technology on live streaming. The results further validate that broadcaster reputation and perceived value promote purchase intention and indirectly enhance it through trust. However, perceived value promotes purchase intention through trust only when the immersive technology is low and medium. This means that when immersive technology is medium and high, it will become the most important factor affecting trust in live streaming. The study offers insights into the impact of immersive technology on trust and advocates for its consideration in advancing the live streaming industry.

Sosialisasi Peningkatan Pengetahuan Keamanan Dalam Jual Beli Online

The increasing number of internet users makes Indonesia a very potential market for e-commerce. The growth of the middle class and the literacy rate of online buyers and sellers is also growing. E-commerce itself is not new, but its rise marks a new milestone for this industry in the country. Although it is growing quite rapidly, there is still one major problem that is preventing e-commerce in Indonesia from taking off, namely the problem of consumer trust in e-commerce sites. Consumers still do not trust the sales system with a non-physical buying and selling process, do not trust to provide credit card numbers to e-commerce services and are still afraid of fraud. However, this crisis of trust can actually be solved. One of the many ways is to use a payment service that has guaranteed security. Not all e-commerce can provide their own payment system, now there are many services that provide a secure payment system and are especially easy to apply to online stores. E-commerce players can use this payment system easily, quickly and which can improve the performance process in their online stores. However, the selection of services that provide a payment system must also be considered carefully. A secure payment system provider will provide a sense of security to prospective buyers, meaning that consumer trust must be built by e-commerce service providers so that consumers can be comfortable and do not encounter problems in making purchases and paying for products in the online stores provided.Security is important, the use of credit cards is widely highlighted because there are still many unpleasant incidents or fraud that occur due to the use of credit cards. Education on this security needs to be carried out continuously, because it will be related to consumer behavior.

A multi-dimensional hierarchical evaluation system for data quality in trustworthy AI

Recently, the widespread adoption of artificial intelligence (AI) has given rise to a significant trust crisis, stemming from the persistent emergence of issues in practical applications. As a crucial component of AI, data has a profound impact on the trustworthiness of AI. Nevertheless, researchers have struggled with the challenge of rationally assessing data quality, primarily due to the scarcity of versatile and effective evaluation methods. To address this trouble, a multi-dimensional hierarchical evaluation system (MDHES) is proposed to estimate the data quality. Initially, multiple key dimensions are devised to evaluate specific data conditions separately by the calculation of individual scores. Then, the strengths and weaknesses among various dimensions can be provided a clearer understanding. Furthermore, a comprehensive evaluation method, incorporating a fuzzy evaluation model, is developed to synthetically evaluate the data quality. Then, this evaluation method can achieve a dynamic balance, and meanwhile achieve a harmonious integration of subjectivity and objectivity criteria to ensure a more precise assessment result. Finally, rigorous experiment verification and comparison in both benchmark problems and real-world applications demonstrate the effectiveness of the proposed MDHES, which can accurately assess data quality to provide a strong data support for the development of trustworthy AI.

Reflections on governing Japan’s discharge of Fukushima nuclear-contaminated water: from the perspective of building a Maritime Community with a shared future

Since August 2023, Japan has discharged some eight rounds of Fukushima nuclear-contaminated water, totaling some 62,800 tons. Despite global criticism and domestic opposition, the Japanese government continues with this discharge plan, anticipating its continuance for decades. As distinct from conventional nuclear wastewater discharges from nuclear power plants, Japan’s recent discharges of Fukushima nuclear-contaminated water will release a significant number of radioactive nuclides into the ocean. It is foreseeable that the discharge of nuclear-contaminated water will adversely affect various sectors, including the marine environment, human health, the seafood trade, the maritime economy, and the international marine legal order. Currently, the governance of the Fukushima nuclear-contaminated water discharge faces three major dilemmas: insufficient participation by stakeholders, outdated regulations, and a crisis of trust. The concept of a titular Maritime Community with a Shared Future (MCSF) could address the discharge of Fukushima nuclear-contaminated water, incorporating diverse interests while also considering both current and future development. This paper argues that it is imperative to jointly engage in negotiation within the perspective of MCSF, to jointly build a governance mechanism and advance the update of rules, and to share data and information sustainably to manage the discharge of the Fukushima nuclear-contaminated water.

China’s Legal Practices Concerning Challenges of Artificial General Intelligence

The artificial general intelligence (AGI) industry, represented by ChatGPT, has impacted social order during its development, and also brought various risks and challenges, such as ethical concerns in science and technology, attribution of liability, intellectual property monopolies, data security, and algorithm manipulation. The development of AI is currently facing a crisis of trust. Therefore, the governance of the AGI industry must be prioritized, and the opportunity for the implementation of the Interim Administrative Measures for Generative Artificial Intelligence Services should be taken. It is necessary to enhance the norms for the supervision and management of scientific and technological ethics within the framework of the rule of law. Additionally, it is also essential to continuously improve the regulatory system for liability, balance the dual values of fair competition and innovation encouragement, and strengthen data-security protection systems in the field of AI. All of these will enable coordinated governance across multiple domains, stakeholders, systems, and tools.

How the crisis of trust in experts occurs on social media in China? Multiple-case analysis based on data mining

The importance of experts in the communication of scientific knowledge cannot be ignored, however, the crisis of trust in experts persists and is widening on social media in China. In this study, nine cases related to experts’ communication of scientific knowledge on Chinese social media Weibo during the period of 11 November 2022 to 22 January 2023 were selected based on the principles of high relevance, high discussion, and high visibility, and public comments on key post under the case were clustered and compared through data mining methods to understand what aspects of the public questioned the experts. The study found that the crisis of trust in experts on social media was the result of the combined effect of the experts, the media, and the public. Conflicting knowledge in expert systems, the perceived common-sense character of communicated knowledge, the lack of rigor and data-supported knowledge, the blurring of the boundaries between experts and administration and between experts and capital, and the dominance of instrumental rationality for experts could all affect public trust in experts. The media’s conscious or unconscious artistic processing of knowledge communicated by experts might mislead the public. The irrational emotion and populist tendencies of the public can amplify feelings of distrust towards experts. This study provides a theoretical and factual basis for understanding the mechanisms of the public’s behavior after receiving knowledge communicated by experts and for enhancing the effectiveness of science communication on social media.

Research on Credit Card Fraud Detection System Based on Federated Learning

With the rapid development of the mobile Internet, financial technology, especially artificial intelligence and blockchain technology, has profoundly changed our consumer behavior and the development model of the traditional financial industry. However, the accompanying risks are also being transmitted with unprecedented speed and complexity. Credit card fraud, as an important form of financial fraud, has caused huge economic losses and a crisis of trust for both financial institutions and consumers. Therefore, the establishment of an efficient and secure credit card fraud detection system has become an inevitable requirement for the continuous development of financial technology in the new era. The purpose of this paper is to study and develop a credit card fraud detection system based on federated learning, which can balance the positive and negative samples in credit card transaction data, protect the privacy of bank data, and effectively improve the accuracy and efficiency of fraud detection.

Expectations of Katowice residents regarding the program assumptions of the European city of science Katowice 2024 in the field of medical and health sciences - questionnaire survey results

IntroductionScientific literacy has been the subject of studies for several decades, but there is much less interest in the social perception of science, traceability of key areas of scientific activity and social expectations regarding science. Proper recognition of such issues can significantly contribute to a better understanding of the causes of the crisis of trust in science and help to find an effective and socially acceptable solution to mitigate it. Our study was aimed at identifying and systematizing the public needs and expectations towards medical and health sciences, based on the example of the population of Katowice.Materials and methodsThe study was carried out using a mixed, qualitative-quantitative methodology. Based on the conclusions of the in-depth interviews, a questionnaire was constructed to check the level of awareness of residents of Katowice obtaining the title of the European City of Science 2024 and the respondents’ opinion on the development of medical and health sciences. 400 inhabitants of the city and/or people associated with it through their work or education took part in the questionnaire survey.ResultsOnly 7.8% of respondents had in-depth knowledge about the European City of Science 2024 project, with further 28.8% declaring some level of general knowledge of the issue. Study participants associated medical and health sciences with health promotion and clinical specialties (43% and 33,5% respectively). In terms of further development of medical and health sciences in Katowice study participants prioritized mainly development of research in chronic and lifestyle-related diseases (51%) and the need of development of prevention and health promotion (46.3%) as well as clinical medicine (32.8%). The inhabitants of the city recognize the resources of the city and the region in the field of medical sciences and health sciences as large and with high development potential.ConclusionsThe events organized as part of the European City of Science 2024 should become a good opportunity to promote and disseminate knowledge about the achievements and development potential of the City and the Region in the field of medical and health sciences.

Design of knowledge transaction protection mechanism in the open innovation community based on blockchain technology

Open innovation communities (OICs) are important for the development of modern enterprises. However, there are still many safety hazards and trust crises on community platforms. This paper proposes an approach that combines blockchain technology and an OIC, as blockchain technology provides a direction for solving trust and security problems in community platform transactions. Moreover, the design of smart contracts can ensure the implementation of transactions and improve their reliability. In this study, the participants in an OIC and three types of infringement problems were analyzed. The Byzantine Fault Tolerant (BFT) algorithm was applied to design the logic of smart contracts and the coupling between idea platforms and the blockchain. The protection mechanism of an OIC was established based on blockchain smart contract supervision to provide a better knowledge co-creation environment for OICs.

Research and application of tourism management in the IoT industry under the background of sustainable blockchain

In the contemporary era, there is a heightened awareness of the significance of a spiritual life, and travel is a popular choice for many. The Internet is driving rapid diversification in people's travel choices. At the same time, the traditional tourism industry's Tourism Management (TM) model, which has been in place for decades, is no longer able to satisfy people's diversified choices for tourism. This is due to a number of factors, including the trust crisis caused by asymmetric information, the outdated nature of the TM model, and the insecure personal information that is shared between intermediaries. This paper discusses the application of sustainable blockchain technology in tourism management and sets up a tourism management system based on blockchain and the Internet of Things. It takes 20 scenic spots as examples to study the application of the TM model. This paper evaluates the TM model from four key aspects: tourist satisfaction, tourism infrastructure completeness, tourism consumption level and tourism service content richness. It compares the results with those of the traditional TM system. The experimental results are clear: tourist satisfaction at scenic spots 5, 10 and 15 in the sustainable blockchain TM mode is 68 %, 87 % and 71 % respectively, which is higher than that in the traditional TM mode. In the context of sustainable blockchain, the TM mode is the optimal approach for serving tourists and enhancing their travel experience. This study also assists Chinese tourism business operators in recognizing the potential impact of blockchain technology on the development of the tourism industry. They can then formulate strategies at an early stage to cope with the information technology changes in the era of the digital economy.

The decline of populism? Crisis of trust and parties of political alternative in modern Italy

The decline of populism? Crisis of trust and parties of political alternative in modern Italy