User Confidence Research Articles

Customer Acceptance of Cheque Truncation and Electronic Clearing Services in Nepal

Efficient financial systems are vital to the economic integration of nations, with technological connectivity playing a pivotal role. In Nepal, despite the introduction of electronic cheque clearing (ECC) services in early 2012, skepticism persists among users. This study investigates the factors influencing the adoption of clearing services in Nepal, employing primary data collected using structured survey questionnaire. The research explores the relationship between independent factors such as Risk, Convenience, Trust, and Relative Advantages in determining usage patterns. With a sample size of 375 respondents, the descriptive and inferential analyses reveal a strong negative correlation between risk perception and clearing service adoption, while Trust, Convenience, and Relative Advantage exhibit robust positive relationships. Notably, convenience emerges as a key driver of adoption. The findings indicate the need for banks to mitigate risks and enhance user confidence, while also emphasizing the importance of leveraging convenience and relative advantages to promote adoption. This research offers valuable insights into the dynamics influencing the adoption of clearing services in Nepal, informing strategic interventions to boost confidence and increase usage in the financial ecosystem.

The role of automation etiquette and task-criticality on performance, workload, automation reliance, and user confidence

Previous research suggests good automation etiquette can yield positive effects on user performance, trust, automation reliance, and user confidence – especially in personified or anthropomorphized technologies. The current study examined the impact of automation etiquette and task-criticality in non-personified technology. The study used a computer-based automation task to examine good and bad automation etiquette models and different domain-based task-criticality levels (between-subjects) that contained various stages of automation (stage 2 and stage 3) and automation reliability levels (60% and 80%) (within-subjects). The study found that bad automation etiquette can increase automation bias and automation reliance which improved performance in the most capable automation condition (stage 3; 80% reliable) but also heightened user subjective workload and decreased user self-confidence. The study also demonstrated task-criticality can be successfully manipulated through domain and instructions. Overall, automation etiquette influenced performance and user confidence more in highly capable automation (stage 3) and in a low-criticality task domain.

Security analysis and evaluation of mobile banking applications in Nigeria

Rapid fintech adoption across the world is so ubiquitous. To facilitate more adoption in Nigeria, recently the Central Bank of Nigeria (CBN) introduced several policies that support cashless banking. Nowadays, Nigerian banks users could perform most of their daily transactions from any desired location using mobile banking applications. In the literature, there are insufficient studies that comprehensively evaluate the security strength or risks of these applications. Generally, insecure mobile banking applications could lead to financial fraud, violations of privacy, identity theft and eroded user confidence. Considering the situation, there is need to conduct research which comprehensively assess security of the applications. Consequently, in this paper we analyzed and evaluated the security of identified popular mobile banking applications in Nigeria. We conducted the analysis work using automated and manual static analysis methods. Then, we evaluated the security of the applications using multi-criteria decision-making technique. Our results revealed that most of the applications have several security challenges in form of vulnerabilities and insecure coding practices. Hence, our findings have shown the applications need further improvements for better security and safety.

The impact on users of an unfamiliar AED following a recent training experience: A randomized cross over simulation study

ObjectiveThis study examined the impact of prior familiarity with automated external defibrillator (AED) models on the time of defibrillation and the emotional experiences of laypersons. MethodsWe conducted a randomized cross over simulation study with 123 participants to assess their reactions to both familiar and unfamiliar AED models. The time to first defibrillation was measured using three different AED training models, two of which were previously unknown to the participants. Additionally, semi-structured interviews were held with the participants to gather further insights. ResultsParticipants took longer to initiate defibrillation with unfamiliar (M = 34 s) AEDs compared to familiar (M = 27 s) ones. This delay was accompanied by feelings of confusion, nervousness, and anxiety. Factors such as the design of the AED covers, electrodes, and buttons were identified as sources of confusion. Nonetheless, clear instructions and similarities between devices helped facilitate their use. ConclusionThe findings suggest that AED design and familiarity with different AED designs may affect performance by laypersons. To improve user confidence, it would be useful to familiarize users with a variety of AED models as part of training initiatives. Understanding the impact of AED familiarity on rescuer’s response can guide CPR training strategies and improve outcomes for OHCA. As more AED models become available to the public, the user-friendliness of AEDs may also be improved. It is beneficial for AED manufacturers to consider the results of research when developing new models.

Improving pneumonia diagnosis with high-accuracy CNN-Based chest X-ray image classification and integrated gradient

Pneumonia remains a significant global health challenge, contributing to high morbidity and mortality rates, particularly in vulnerable populations. Early and accurate diagnosis is critical for effective treatment, yet manual interpretation of chest X-rays can be time-consuming and prone to errors due to inter-observer variability. To address these challenges, this research focuses on automating pneumonia diagnosis by leveraging deep learning techniques. X-ray imaging, being a key diagnostic tool, is at the center of this study, where we aim to improve diagnostic accuracy using a carefully designed Convolutional Neural Network (CNN) architecture. Our model, trained on a curated dataset of 5,856 chest X-ray images, integrates the ’inception_v3′ layer for feature extraction with dense layers to build a high-performing binary classification tool. To further enhance model transparency and clinical utility, we incorporate Integrated Gradients (IG) for interpreting the model’s decision-making process. With 22.9 million trainable parameters, the proposed model achieves an accuracy of 97.23%. The integration of IG provides additional insights by identifying critical image regions that influence predictions, boosting user confidence in the system’s diagnostic recommendations. This research advances medical image analysis by presenting a reliable, interpretable CNN model for pneumonia detection, offering promising utility for clinical practice.

Data Security and Data Protection in Cloud Privacy Systems

In this modern world, the internet has become very influential in our daily lives. The Internet has many uses to solve various problems, one of which is full hardware storage, therefore the Internet provides software-based data, for example, cloud storage applications. The study aims to analyze and evaluate various data security techniques and protection methods used in the cloud computing framework, focusing on vulnerability identification, risk mitigation strategy assessment, and user security awareness improvement. In addition, this study aims to analyze data security techniques and data protection approaches applied to cloud systems. In addition, the study also assesses potential risks and mitigates security threats such as cyberattacks and data breaches. Using qualitative methodologies, the study investigated relevant literature, examined real-life cases of data breaches, and analyzed the effectiveness of security measures such as encryption and multi-factor authentication. The findings show that cloud systems remain vulnerable to cyber threats like DDoS attacks, credential theft, and data breaches due to inadequate security protocols. Key recommendations include adopting encryption, improved multi-factor authentication practices, and encouraging collaboration between cloud service providers and users to strengthen data security. The research contributes by proposing a comprehensive approach to improving data protection in cloud environments, ensuring a secure and resilient infrastructure for users. Implementing these findings will support the development of more secure cloud technologies and increase user confidence in data security practices. It is hoped that the study's results can provide recommendations to improve data security and data protection in cloud systems.

EyeWheel: Autonomous Wheelchair Mobility Through Eye Movement Control

This paper explores the advancements in assistive technology with gaze-controlled wheelchairs. These wheelchairs utilize eye-tracking sensors and intelligent algorithms to translate a user's gaze patterns into steering commands. This offers an intuitive control method for individuals with severe mobility limitations, such as those with ALS or quadriplegia. By simply looking in the desired direction, users can navigate their surroundings with improved independence and quality of life compared to traditional mobility aids. The paper highlights the benefits of smooth and precise control through eye movements. Additionally, it explores the integration of safety features like obstacle detection and customizable settings. These features contribute to enhanced user confidence and security, making gaze- controlled wheelchairs a transformative solution for individuals with diverse mobility needs. Keywords- eye-tracking, assistive technology, mobility impairment, gaze control, wheelchair navigation

Examining the Awareness of Mobile Money Users on Security Risks in Tanzania to Enhance Cybersecurity Literacy: A Case Study of Airtel Money

The proliferation of mobile money services in Tanzania has revolutionized financial inclusion, but it has also exposed users to increasing cyber threats. This study examines the level of cybersecurity awareness among mobile money users, focusing on Airtel as a case study, to identify gaps and opportunities for enhancing cybersecurity literacy. The research explores users’ exposure to formal training, the impact of Airtel’s educational materials, and users’ confidence in securing their accounts. Findings reveal a significant lack of formal training, with most users relying on Airtel’s security tips to develop cybersecurity knowledge. While these resources have improved user confidence, there is a demonstrated demand for structured workshops and comprehensive training programs. The study underscores the need for collaborative efforts between service providers, policymakers, and educational institutions to address these gaps. Enhancing cybersecurity literacy through accessible, interactive, and user-centred approaches is essential to fostering a secure mobile money ecosystem in Tanzania.

The Effect of Audit Quality and Financial Performance on Audit Delay (Empirical Study on LQ45 Companies in 2021-2023)

The financial report is an information medium that is very useful for stakeholders. The financial statements owned by the company can be used for stakeholders to make decisions. Financial statements presented by companies must be audited because audited financial statements can increase the confidence of financial statement users. One of the important factors in financial statements is timeliness. Financial statements can be very useful if financial statements are presented on time, therefore the financial statements presented must be timely so that decision-making can also be taken appropriately. The purpose of this study is to see what factors can affect audit delays. Audit delay is the time difference between the closing date of the book and the date of signing the auditor's report. The sample in this study is companies with the LQ45 index, because LQ45 index companies are companies that have a healthy financial condition. Data will be taken from the Indonesia Stock Exchange website for 3 years. Data analysis will be carried out using SPSS by performing the Classical Assumption Test and the Multiple Linear Regression Test. The targeted output is journal publication in accredited national journals. Keywords: Audit Delay, Profitability, Leverage, Audit Quality

Influencia de los Delitos Cibernéticos Económicos en Perú

This article aimed to analyze the influence of economic cybercrimes in Peru during the year 2024, addressing the most common modalities, their economic impact, and deficiencies in the legal framework. Economic cybercrimes, such as phishing, identity theft, attacks on payment platforms, and e-commerce scams, have grown significantly in recent years, generating substantial economic losses and affecting user confidence in digital platforms. The methodology adopted was qualitative, with an exploratory and descriptive approach. For data collection, semi-structured interviews with criminal lawyers, prosecutors, and cybersecurity experts were used, along with the analysis of relevant court cases and the documentary review of official reports. The results showed a 26% increase in economic cybercrimes compared to the year 2023. Among the conclusions of the study, the urgent need to update the Peruvian legal framework to adapt to the new criminal modalities that arise with technological advances was highlighted. This analysis sought to provide a critical view on the incidence of economic cybercrimes in Peru.

Exploring Electronic Personal Health Record usage in Northern Italy: a cross-sectional study

Abstract Background The Electronic Personal Health Record (EPHR) is a patient-centered tool that enables citizens to manage their health information. The EPHR has been implemented worldwide, including in Italy, and holds immense potential, but it has shown a generalized underutilisation. Therefore, this paper aims to identify its fulfillment and the reasons behind its poor use, potentially uncovering the key to unlocking its benefits. Methods A survey was distributed on social media and in the waiting rooms of vaccination facilities in a Region of Italy. Multivariable regression models were conducted to detect a connection between the general population’s usage of the EPHR and specific independent variables. Results Of the 1634 respondents, 710 activated the EPHR, especially women, Italians, highly educated, unemployed, with good health but affected with chronic diseases. Amongst those who activated the EPHR, the multivariate analysis showed that the number of accesses to the platform was significantly associated with lower age (adjusted Odds Ratio (adjOR) 0.96 p = 0.015), higher level of education (adjOR 2.17 p = 0.029), unemployment (adjOR 5.61 p = 0.008) and considering the information on the EPHR complete (adjOR 3.83 p = 0.001). As age increases, the perceived ease of access to the EPHR decreases (adjOR=0.98 p = 0.049). Having a higher level of education (adjOR=0.41 p = 0.042), autonomy in reading health materials (adjOR=0.32 p = 0.043), and less self-confidence in filling out medical forms (adjOR=0.61 p = 0.033) were linked to a decrease in perceived ease of access. Conclusions The study showed that the EPHR is more utilised by specific categories of citizens, especially the young and those with higher education. More efforts should be made to increase access to the EPHR for the whole community by making it more intuitive and user-friendly. The present study provides valuable foundations to foster the implementation of a platform for sharing health data at a European level. Key messages • The Electronic Personal Health Record (EPHR) is underutilised despite its potential; it’s mainly accessed by young and highly educated individuals. • Efforts to increase EPHR usage must focus on improving accessibility and ease of access, as well as enhancing user confidence and autonomy in managing health information.

Systematic review of the Health Literacy Questionnaire (HLQ) for global health literacy development

Abstract Background The Health Literacy Questionnaire (HLQ) is used to inform programs and policies in more than 80 countries. It is a key needs assessment in the Ophelia (Optimising Health Literacy and Access) process, a codesign process to build effective interventions. Ophelia is applied in the European Commission Joint Action on Cardiovascular Diseases and Diabetes initiative (25 projects/13 countries). Given growing demand, an Ophelia digital platform is being developed, and confirmation of robust HLQ psychometric evidence is needed for user confidence in the interpretation and use of HLQ scores in their contexts. This study is a review of the HLQ. Methods Developed in Australia in 2013, the HLQ measures nine health literacy domains and is translated to 40 languages. A March 2024 PRISMA systematic search (PROSPERO CRD42022361966) identified 257 articles, which were screened for evidence about internal structure and reliability. Results Across 15 countries/languages, 22 articles were included. Study samples included diverse groups, settings and contexts. Out of the 18 studies that used factor analysis, three used the Bayesian approach. All 15 classical factor analysis studies reported satisfactory fit indices in restricted 9-factor models (range CFI=0.841 to 0.995, TLI=0.826 to 0.969, RMSEA=0.048 to 0.084), except two required correlated residuals for acceptable fit indices. Factor loadings were significant except for five items across five studies (range .20 to .99). Three studies used Rasch modelling and found all domains had unidimensionality except for Domain 9 in one study. Most studies reported Cronbach’s alpha (range .57 to .95) across all domains, with only three studies reporting α<.7. Conclusions The HLQ has exceptional robust psychometric properties across cultures and languages, paving the way for users to have confidence in HLQ psychometric validity evidence on the upcoming Digital Ophelia platform to support scaling up of health literacy development. Key messages • The HLQ has robust psychometric properties across countries and languages. • The HLQ 9-domain profiles can inform intervention development for equitable health outcomes.

XAIEnsembleTL-IoV: A new eXplainable Artificial Intelligence ensemble transfer learning for zero-day botnet attack detection in the Internet of Vehicles

The Internet of Vehicles (IoV) is a network of interconnected vehicles that use modern communication technologies to communicate with each other and the surrounding infrastructure. The IoV is a novel network that experiences a continuous emergence and evolution of various forms of attacks. This research addresses the growing challenge of detecting zero-day botnet attacks within the IoV, a complex network that enhances real-time communication among vehicles and surrounding infrastructure to improve traffic management, safety, and driving experiences. Traditional machine learning-based intrusion detection systems (IDS) for IoV face two key limitations: the requirement for large labeled datasets and the “black box” issue, where the reasoning behind model decisions is not transparent, reducing user and stakeholder confidence. To solve these problems, this research proposes an eXplainable Artificial Intelligence (XAI) Ensemble Transfer Learning (TL) model specifically for detecting zero-day attacks in IoV. The proposed model integrates deep Shapley Additive Explanations (SHAP), providing transparency and making decisions understandable to cybersecurity professionals. Additionally, the model employs hybrid bidirectional long-short-term memory with autoencoders (BiLAE) to reduce the dimensionality of IoV network traffic, improving computational efficiency. It also uses Barnacle Mating Optimizer (BMO) to optimize the hyper-parameters of deep learning models such as ResNet, Inception, Inception ResNet, and MobileNet Convolution neural network-transfer learning architecture (CNN-TL), enhancing detection capabilities without needing vast amounts of labeled data. Experimental results showed that the model performed with an accuracy of 100 %, precision of 100 %, recall of 100 %, F1-score of 100 %, and Matthew Correlation Coefficient of 100 % in binary-class situations for internal vehicular (CAN) networks and achieved 99.88 % accuracy and similarly high metrics in multi-class scenarios for external vehicular networks(N-BaIoT). Compared to state-of-the-art techniques, the model proved to be more effective in detecting zero-day botnet attacks, reducing reliance on large datasets. Unlike traditional black-box models, the XAI component of the ensemble model offers insight into the decision-making process. It allows network administrators and security experts to understand how specific patterns in the data contribute to detection, making the system more transparent. The solution is highly adaptable and scalable for real-time application, designed to operate efficiently even on IoV gateway electronic control units with limited computational power.

Development of the bank of russia’s fast payment system in modern conditions

The financial market development in Russia and in the world is currently characterized by a number of processes such as emergence of a large number of new products and new formats implementation for their provision, expansion of the geography of financial institutions presence, national boundaries erasure in acquisition and provision of financial services, sales channels improvement for financial products and services, including remote ones, using modern information technologies. The article studies issues related to the current state and prospects of the fast payment system (hereinafter referred to as FPS) development considering the synergetic impact of payment services digitalization and sanctions restrictions. It analyzes the changes taking place in the FPS service in recent years, focusing on innovative business models, new functions implementation, technological transformations, as well as regulatory and risk aspects. The study pays special attention to the financial technology impact on development and functioning of the system as a key element of the payment industry. The potential of FPS in the context of ensuring the Russian payment infrastructure security represents an important direction for strengthening user confidence and system sustainability. The paper considers a number of promising areas for further development of FPSs, including their applicability to cross-border payments.

The Effect Of E-Service Quality And E-Trust On Buying Interest In Shopee Pay Users In The Millennial Generation

The use of e-wallet is increasing as online transactions increase in Indonesia. This research is an explanatory study that aims to find out the influence of E-service quality and E-trust on the interest of using ShopeePay when shopping online among Millennials in DKI Jakarta. The population of this study is the entire Generation of Millennials in DKI Jakarta who have used ShopeePay at least three times when making online transactions and the number is unknown. Sampling technique used is purposive sampling techniques on condition samples are Millennial Generation, live in the territory of DKI Jakarta and have used ShoppePay at least 3 times. Data collected through the spread of the google form questionnaire to the Millennial Generation. Data analysis using SmartPLS 3.0 Partial Least Squares Structural Equation Modeling (PLS-SEM). Research results show that E-Service Quality and E-Trust have a positive and significant influence on purchasing interest using ShopeePay on the millennial generation in DKI Jakarta. According to research results, 92.9% of Millennial Generation interest in using ShoppePay is influenced by E-Service Quality and E-Trust. The findings confirm that it is important for e-wallet service providers to focus on improving the quality of electronic services and building user confidence to boost purchasing interest.

Pengaruh Audit Fee, Audit Tenure, dan Audit Delay Terhadap Kualitas Audit dengan Komite Audit Sebagai Variabel Moderasi

This research related to audit quality aims to prevent violations and misstatements in financial reports. Audit quality can help to maintain the level of confidence of financial report users in the validity and accuracy of financial reports that have been audited and published by the auditor. This research uses descriptive quantitative research methods because it presents an overview of the relationships and objectives of the variables studied. The results of this research state that audit fees contribute to audit quality in food and beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange (BEI) for the 2020 - 2022 period.

The Influence of Thoracic Ultrasound on the Clinical Practice of Pulmonologists in Portugal.

Thoracic ultrasound (TUS) has garnered increased recognition, both in aiding pleural procedures and as a complement to physical examination. Operator ability is essential to obtain reliable findings. This study aimed to inquire pulmonology specialists and residents about their confidence with the technique and to determine future needs. A self-administered online survey, including a total of 24 questions, was sent to pulmonology specialists and residents registered as members of the Portuguese Pulmonology Society. Participation was pseudoanonymized and voluntary. One hundred fourteen valid answers were obtained. Most responders had prior TUS training. The primary method for knowledge consolidation was unsupervised practice. The majority had an ultrasound machine available in their daily practice; only 17% performed TUS more than 3 times per week. Overall confidence in TUS usage for diagnostic purposes (median: 7/10), disease monitoring (median: 7/10), and invasive procedures (median: 8/10) were high. There was a significant relation between higher levels of confidence and regularly attending TUS courses and performing TUS more than 3 times per week. The main reasons cited as preventing regular use of TUS were the availability/cost of courses and the availability/cost of equipment. Regular TUS training and utilization are essential to boost user's confidence degree. Its use is already a regular feature in the daily practice of pulmonologists in Portugal, but further and better structured training is required to meet the needs of clinicians. The inclusion of mandatory TUS training in residency programs should be considered in the future.

An energy analysis methodology for residential heat pump retrofits

The government has targets to upscale domestic heat pump retrofit as part of the strategy to decarbonise heat. There are significant barriers to uptake including installation cost together with a lack of expertise in predicting and reporting energy and carbon performance. As a result, end user confidence in heat pumps can be low. This paper presents analysis of two monitored domestic properties using high resolution data. The aim is to develop reliable prediction and in-use diagnostic tools to improve transparency and reliability of heat pump performance. This paper focuses on a method drawn from theory as set out in CIBSE TM41, and shows how real building heat loss coefficients can be determined from regression analysis over different time frame resolutions. Practical application This research aims to provide residential heat pump retrofit providers with cost effective methods for assessing the suitability of dwellings to accept heat pump retrofit solutions, and to extend these techniques for the effective monitoring and performance evaluation of heat pumps post installation.

Acceptance of artificial intelligence: key factors, challenges, and implementation strategies

This research paper investigates the key factors influencing AI acceptance, focusing on elements such as technological readiness, perceived usefulness, and ease of use, along with the organizational and societal impacts. It identifies the significant obstacles to AI adoption, including ethical concerns, data privacy issues, and the potential for job displacement. The study also explores the importance of trust and transparency in promoting AI acceptance, highlighting the necessity for explainable AI (XAI) to build user confidence. Strategies for enhancing AI acceptance are examined, emphasizing the need for robust regulatory frameworks, ongoing education, and skill development to mitigate resistance and boost user engagement. The research stresses the importance of a user-centric approach in AI system design and implementation, taking into account end-user needs and concerns. Additionally, it underscores the value of collaboration between industry, academia, and policymakers in fostering an environment conducive to AI innovation and acceptance. By offering a thorough analysis of the factors affecting AI acceptance and the associated challenges, this paper provides valuable insights and actionable strategies for stakeholders aiming to navigate the complex landscape of AI integration effectively.

THE INFLUENCE OF AUDITOR ETHICS ON AUDIT QUALITY IN PINRANG DISTRICT INSPECTORATE OFFICE

Audit quality is defined as the probability of an Auditor determining and reporting fraud that occurs in the client's accounting system. The higher the audit quality produced by the auditor, the higher the confidence of information users in using financial reports. This research aims to determine the influence of auditor ethics on audit quality at inspectorate offices. This type of research is quantitative research in the form of a questionnaire with uses an exploratory approach using data collection techniques, namely primary in the form of questionnaires and secondary data obtained indirectly which is tested using descriptive statistical analysis tests, validity tests, reliability tests, classical assumption tests, hypothesis tests. The results of this research show that: (1) Auditor integrity partially influences audit quality, this is proven by a significant value of 0.033, which is <0.05. (2) Objectivity partially influences audit quality, this is proven by a significant value of 0.000 where <0.05. (3) Partial competency has no effect on audit quality, this is proven by a significant value of 0.449, which is > 0.05. (4) Auditor confidentiality does not partially influence audit quality, this is proven by a significant value of 0.179, which is > 0.05. (5) The auditor's professional behavior partially influences audit quality, this is proven by a significant value of 0.000, where <0.05. Integrity (X1), Objectivity (X2), Competence (X3), Creativity (X4) and Professional Behavior (X5) simultaneously influence audit quality, this is proven by the F valuecount 47,563 > Ftable2.53 and a significant value of 0.000 <0.05.