Search Results (69)

Engineering contract management is a critical component of project management systems, serving as a key mechanism for ensuring successful project implementation. This study systematically analyzes 349 s-instance judicial cases related to construction engineering contract disputes in the Yangtze River Delta Economic Zone from 2017 to 2021, based on data obtained from the China Judgments Online database. The research identifies contractual risk characteristics across dimensions such as regional distribution, dispute terminology, legal citation patterns, and appellate role transitions. The key findings include the following: (1) Primary risks involve payment disputes, quality assurance failures, contractual validity issues, and schedule compliance challenges. (2) Litigation patterns reveal complex interdependencies between contracting parties and stakeholders, posing significant risk management challenges. (3) High second-instance modification rates stem from procedural irregularities, new evidence, improper legal application, and factual errors in initial trials. The study proposes stratified risk mitigation strategies, including governmental regulatory improvements and enterprise-level management optimizations. These findings offer valuable insights into advancing risk governance in construction contract administration, particularly through an enhanced understanding of dispute complexity and systemic vulnerabilities. Full article

This study explores how system-based and cognitive-based factors affect platform trust and its role in the actual use of PayLater services (buy now, pay later or BNPL) in Indonesia and Malaysia. PayLater, a fintech innovation, provides fast and convenient payment options through online platforms. By incorporating platform trust into the technology acceptance model (TAM), the research investigates whether borrowing intention acts as a mediator between platform trust and actual usage. Utilizing a quantitative approach with purposive sampling, data were gathered from 106 respondents in Indonesia and 169 in Malaysia, with 62 and 85 respondents meeting the criteria, respectively. Partial least squares (PLS) analysis indicates notable differences in how Indonesian and Malaysian users perceive platform trust, while the effect of platform trust on borrowing intention remains consistent across both nations. Borrowing intention emerges as a crucial factor influencing the actual use of PayLater services. The results offer important insights into the adoption of fintech services in emerging markets, highlighting the significance of platform trust in shaping user behavior. This research provides practical suggestions for fintech providers to improve platform trust and user engagement in cross-country scenarios. Full article

Objectives: The objective of this study is to quantify healthcare resource utilization, economic burden, and the multi-level medical security system for Spinal Muscular Atrophy (SMA) patients in Shaanxi Province, China, from a societal perspective using a survey. Methods: This observational study employed an online survey with a retrospective cross-sectional design in Shaanxi Province, China. The survey examined various aspects of SMA, including resource utilization, direct and indirect economic burdens, and co-payment mechanisms within a multi-level medical security system. Results: Following the inclusion of nusinersen in the National Reimbursement Drug List (NRDL) in 2022, the treatment rate for SMA patients increased significantly. After risdiplam was added to the NRDL in 2023, its use also saw a marked increase. Treatment costs varied by SMA type: Type 1 incurred the highest costs (RMB 300,000 or USD 41,000), followed by Type 2 (RMB 270,000 or USD 37,000), Type 3 (RMB 200,000 or USD 27,000), and Type 4 (RMB 80,000 or USD 11,000). The primary sources of costs were productivity losses due to primary caregivers (32.94%), nusinersen usage (29.29%), and risdiplam usage (17.33%). Out-of-pocket costs for SMA patients accounted for 29.29% of the total costs. In 2023, basic medical insurance covered 49% of direct costs and 32% of total costs. Patients still had to pay 25.73% of the total cost for the direct costs. Conclusions: Basic medical insurance is a critical foundation for patient security and plays a pivotal role in reimbursement. In contrast, commercial insurance has a relatively limited impact on covering the costs for SMA patients. These findings highlight the substantial healthcare burden faced by SMA patients under the current healthcare system in China. Full article

Background/Objectives: Diagnosis-related group (DRG)-based financing, a subcategory of case-based payment models, has been established as the primary reimbursement scheme in most high-income countries. Almost 40 years thereafter, the impact of the reform on gynecologic oncology funding and recompensation has not been clearly elucidated. This systematic review aims to address the scarce bibliographic data, consolidate the information regarding DRG-based systems in gynecologic oncology, evaluate the advantages and challenges of its implementation worldwide, and examine alternative and complementary recompensation schemes in this context. Methods: A stringent and comprehensive literature review of original articles using online databases (Google Scholar and Pubmed) yielded 173 potential results. Results: These were further assessed for relevance and eligibility and, finally, an in-depth investigation of 15 articles was conducted. We concluded that, despite the fact that DRG-based financing may be beneficial in most healthcare scenarios, the reimbursement scheme is challenged in the context of gynecologic oncology. Conclusions: An innovative approach comprising a combination of the values of case-based and value-based payment models would extend healthcare services beyond acute treatments and propose new perspectives in holistic healthcare provision in a financially sustainable environment. Full article

This study aims to describe and assess the impact of critical infrastructure (CI) cybersecurity issues on the sustainable development of smart cities. This study highlights the integration of PayTech systems into the broader CI landscape, highlighting their impact on maintaining economic stability and ensuring the smooth operation of city services. Key companies within smart regions, particularly those operating in the payment industries, are essential to maintaining the functionality of critical services. These companies facilitate the processing of services provided to citizens, enabling access to vital municipal services. As key players in the PayTech and online e-commerce sectors, they form a crucial part of modern critical infrastructure, operating within an ever-evolving digital environment. This study examines the recovery processes employed after cyberattacks, focusing on the differing perspectives of internal and external professionals. It identifies significant differences in the perceptions of recovery strategies among internal stakeholders, such as investor relations (IR) teams, reputation management (RM) experts, and Chief Information Security Officers (CISOs), who represent critical infrastructure companies. Additionally, it explores the roles of external auditors, who provide impartial emergency support and perform specialized recovery tasks. Importantly, this study underscores the current attitudes toward future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company’s internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors. Full article

Adopting advanced e-commerce practices is essential for enhancing user engagement and business performance, particularly in tourism. This study evaluates the e-commerce adoption of Kazakhstan’s tourism websites using an innovative Integrated Multi-Criteria Decision Analysis (IMCDA) methodology. Traditional evaluation methods overlook the interplay between website functionality, user experience, and strategic objectives. To address this gap, the IMCDA framework integrates qualitative and quantitative approaches by combining advanced Multi-Criteria Decision-Making (MCDM) techniques, including SPOTIS, ESP-COMET, RANCOM, and SITW, with content analysis and logistic regression. The study assessed 77 tourism websites, categorized into Online Travel Agencies (OTAs), Official Tourism Websites (OTWs), and Attraction Websites (AWs), based on 34 e-commerce features grouped into dimensions such as product information, functionality, reservations, payment systems, and customer relationship management (CRM). The findings reveal that OTAs significantly outperform OTWs and AWs in most dimensions, especially in online booking and CRM functionalities. At the same time, AWs lag in key e-commerce features like reservations and payment systems. This research highlights critical gaps in Kazakhstan’s tourism e-commerce ecosystem. It provides actionable recommendations, including enhancing CRM tools, integrating advanced booking systems, and leveraging collaborations with local financial technology providers like Kaspi Pay. The IMCDA framework offers a robust, adaptable evaluation model with practical implications for digital transformation and competitiveness in the tourism industry. This study contributes to advancing digital maturity in Kazakhstan’s tourism sector by addressing these gaps. It sets the foundation for future research to explore innovative strategies in e-commerce adoption across various regions and industries. Full article

Since the Fourth Industrial Revolution was announced in 2015, relevant key technologies have recently merged and have extensively affected our society. To provide empirical insights into the future and address expected issues in the context of transportation, this study seeks to investigate how future road infrastructure technology will shift. Going over the mainstream future road infrastructure inspired by the strategy implemented in the Korean New Deal 2.0, we extract central keywords explaining what specific technologies and political directions will prevail globally. In particular, a specific morphological analyzer, Mecab-Ko, which is suitable for Korean is selected after comparing a variety of packages. Then, a specific text mining approach is employed to collect textual online sources (news articles, research articles, and reports) written in Korean while most studies gather information written in English. Using the term frequency-inverse document frequency (TF-IDF), 11 keywords were extracted from unstructured textual online sources. Topic modelling with latent Dirichlet allocation (LDA) is subsequently performed to classify them into four groups: an unmanned payment system, intelligent road infrastructure, connected automated driving road, and eco-friendly road. Based on these findings, we can take a glimpse into how the future road infrastructure in Korea will be reshaped. Evidently, a digitalized road without a human component is around the corner. Fully automated systems will soon become available, and the keyword sustainability will continue to receive critical attention in the transportation sector. Full article

The rapid expansion of non-face-to-face e-commerce services in the Korea has significantly increased the importance of personal identity proofing (PIP) for verifying users in online transactions, such as payments, refunds, membership registrations, and access to age-restricted products. Currently, personal identity proofing agencies (PIPAs) indiscriminately provide all of a user’s personal information to internet service providers (ISPs), leading to substantial privacy concerns and preventing users from selectively disclosing only the necessary information. The objective of this paper is to enhance the safety, convenience, and security of PIP services by proposing a method that empowers users to control the personal information they disclose while enabling digital identity integration for both online and offline applications. To achieve this, an extensive overview and analysis of the current PIP systems in Korea is presented, including methods. The strengths and weaknesses of these systems are critically examined, revealing limitations in privacy protection, user convenience, and security. Based on this analysis, a new method is proposed that introduces differentiated levels of PIP means according to authentication strength, allowing for the minimal necessary disclosure of personal information. The proposed method aims to improve the stability and reliability of the PIP service environment by addressing current privacy concerns and enhancing user control over personal information. This approach can be applied to e-commerce services in Korea and other countries facing similar challenges, contributing to the development of safer and more reliable online services. Full article

With the rapid rise in the gig economy driven by advancements in digital technology and financial technology, this study focuses on the work experiences and psychological perceptions of food delivery riders in platform-based employment. This study used a sample of food delivery riders from 19 cities in China (such as Shanghai, Beijing, Guangzhou, etc.) and multiple delivery platforms (such as Meituan, Ele.me) to collect data through a combination of online and offline questionnaires. The impact relationship between perceived fairness, organizational trust, and organizational identity of food delivery riders was examined through factor analysis, structural equation modeling, and mediation effect modeling. The results of the survey and statistical analysis indicate that fairness perception and its dimensions (distributive fairness, procedural fairness, and interactional fairness) significantly influence riders’ organizational identification, with organizational trust serving as a critical mediating factor. The integration of digital technology has substantially enhanced the operational efficiency of platform-based employment by enabling real-time tracking, transparent communication, and data-driven decision-making. Innovations in financial technology, such as digital payment systems and financial management tools, offer riders safer and more convenient compensation methods, thereby contributing to their financial stability and fostering trust in the platform. The establishment of trust alleviates the riders’ concerns regarding compensation stability and bolsters their optimistic attitudes toward accessing platform resources and meeting their needs. This study provides significant insights and recommendations for leveraging digital technology and financial technology to improve the relationship and operational efficiency between riders and platform enterprises. Full article

The South African preferential procurement policy emerged from the demand for transparency, fair competition, value-for-money, standardised and benchmark pricing, and regulation of public procurement arrangements in the construction industry. The policy aims to address historical inequalities, support economic growth, and foster sustainable development. The effectiveness of the preferential procurement policy in South Africa is affected by the inhibiting factors of its implementation system. Given this, this study assesses the factors inhibiting preferential procurement policy implementation in the South African construction industry. This study reviewed the extant literature from online databases as a secondary data source to identify and understand the factors inhibiting procurement policy implementation. A quantitative research design using a closed-ended survey questionnaire surveyed 31 identified inhibiting factors affecting procurement policy implementation from the literature review. One hundred sixty-seven (167) questionnaires were retrieved from two hundred (200) distributed, representing an 83.5 per cent response rate, distributed through Google Forms to the respondents in Northwest Province, South Africa. The reliability of the data collection instrument was determined using Bartlett’s sphericity, Cronbach’s alpha, and Kaiser–Meyer–Olkin tests. The exploratory factor analysis findings established eight components from the 31 identified inhibiting factors affecting procurement policy implementation, which are the absence of due diligence in procurement screening, corruption and political interference in procurement systems, an ineffective regulatory framework supporting public procurement policy, discrepancies in award of contracts and the absence of dispute resolution, ambiguity in procurement selection criteria, poor enforcement mechanisms, cost discrepancies in advance payment, and excessive bureaucracy in procurement documentation. This study’s practical implications provide an understanding of establishing and prioritising procurement selection criteria, such as project requalification requirements, cost performance requirements, technology integration in the prequalification process, and contract change order requirements, which would improve procurement systems in the South African construction industry. Full article

Aimed at advancing the reform of the Paid Use of Residential Land, this study investigates the willingness to pay among farmers and its underlying factors. Based on a Logistic Regression analysis of a micro-survey of 450 pieces of data from the Sichuan Province in 2023, we evaluated the effects of three factors, namely individual, regional and cultural forces. Further, Random Forest analysis and SHAP value interpretation refined our insights into these effects. Firstly, the research reveals a significant willingness to pay, with 83.6% of sample farmers being ready to participate in the reform, and 53.1% of them preferring online payment (the funds are mostly expected to be used for village infrastructure improvements). Secondly, the study implies that Individual Force is the most impactful factor, followed by regional and cultural forces. Thirdly, the three factors show different effects on farmers’ willingness to pay from different income groups, i.e., villagers with poorer infrastructure and lower clarity of homestead policy systems tend to be against the reform, whereas farmers with strong urban identity and collective pride support it. Based on these findings, efforts should be made to increase the publicity of Paid Use of Residential Land. Moreover, we should clarify the reform policies, accelerate the development of the online payment platform, use the funds for village infrastructure improvements, and advocate for care-based fee measures for disadvantaged groups. Full article

Peer-to-peer lending, a novel element of Internet finance that links lenders and borrowers via online platforms, has generated large profits for investors. However, borrowers’ missed payments have negatively impacted the industry’s sustainable growth. It is imperative to create a system that can correctly predict loan defaults to lessen the damage brought on by defaulters. The goal of this study is to fill the gap in the literature by exploring the feasibility of developing prediction models for P2P loan defaults without relying heavily on personal data while also focusing on identifying key variables influencing borrowers’ repayment capacity through systematic feature selection and exploratory data analysis. Given this, this study aims to create a computational model that aids lenders in determining the approval or rejection of a loan application, relying on the financial data provided by applicants. The selected dataset, sourced from an open database, contains 8578 transaction records and includes 14 attributes related to financial information, with no personal data included. A loan dataset is first subjected to an in-depth exploratory data analysis to find behaviors connected to loan defaults. Subsequently, diverse and noteworthy machine learning classification algorithms, including Random Forest, Support Vector Machine, Decision Tree, Logistic Regression, Naïve Bayes, and XGBoost, were employed to build models capable of discerning borrowers who repay their loans from those who do not. Our findings indicate that borrowers who fail to comply with their lenders’ credit policies, pay elevated interest rates, and possess low FICO ratings are at a higher likelihood of defaulting. Furthermore, elevated risk is observed among clients who obtain loans for small businesses. All classification models, including XGBoost and Random Forest, successfully developed and performed satisfactorily and achieved an accuracy of over 80%. When the decision threshold is set to 0.4, the best performance for predicting loan defaulters is achieved using logistic regression, which accurately identifies 83% of the defaulted loans, with a recall of 83%, precision of 21% and f1 score of 33%. Full article

Over the past years, online payments or cloud-based payments have significantly increased around the globe. Cloud-based payment systems (CBPS) are more involved in the payment process due to their convenience and flexibility. Although CBPS offers obvious benefits, their adoption rates among Australian users are comparatively lower compared to those in other countries. People are dissatisfied with current payment methods or are unaware of the advantages of CBPS. Using the technology acceptance model (TAM) with perceived ease of use and perceived usefulness, a qualitative research method was applied through semi-structured interviews to collect data from 20 consumers in Australia. The findings pointed out an appreciation for security features such as two-factor authentication and cutting-edge technologies. The banks were trusted by Australians, but a lack of education and additional fees on digital payment platforms were sources of concern. In the context of CBPS, it was observed that electronic devices were easy to use and proved to be useful. Service providers need to improve security measures and implement innovative technologies to enhance user privacy and prevent fraudulent activities. Overall, Australians expressed satisfaction with their banks; however, there are opportunities for enhancement, particularly in bolstering security measures and providing education on emerging payments options. Full article

Although self-service facilities (SSFs) have been used on a large scale worldwide, they can be easily contaminated by microorganisms from the hands of their sequential users. This research aimed to study the prevalence and antimicrobial susceptibility/resistance of bacteria contaminating SSFs in Sakaka, Aljouf, Saudi Arabia. We randomly swabbed the surfaces of 200 SSFs, then used the suitable culture media, standard microbiological methods, and the MicroScan WalkAway Microbiology System, including the identification/antimicrobial susceptibility testing-combo panels. A high SSFs’ bacterial contamination load was detected (78.00%). Ninety percent of the samples collected in the afternoon, during the maximum workload of the SSFs, yielded bacterial growth (p < 0.001 *). Most of the contaminated SSFs were supermarket payment machines, self-pumping equipment at gas stations (p = 0.004 *), online banking service machines (p = 0.026 *), and barcode scanners in supermarkets. In the antiseptic-deficient areas, 55.1% of the contaminated SSFs were detected (p = 0.008 *). Fifty percent of the contaminated SSFs were not decontaminated. The most common bacterial contaminants were Escherichia coli (70 isolates), Klebsiella pneumoniae (66 isolates), Staphylococcus epidermidis (34 isolates), methicillin-resistant Staphylococcus aureus (18 isolates), and methicillin-sensitive Staphylococcus aureus (14 isolates), representing 31.53%, 29.73%, 15.32%, 8.11%, and 6.31% of the isolates, respectively. Variable degrees of reduced sensitivity to some antimicrobials were detected among the bacterial isolates. The SSFs represent potential risks for the exchange of antimicrobial-resistant bacteria between the out-hospital environment and the hospitals through the hands of the public. As technology and science advance, there is an urgent need to deploy creative and automated techniques for decontaminating SSFs and make use of recent advancements in materials science for producing antibacterial surfaces. Full article

In recent decades, online platforms that use Web 3.0 have tremendously expanded their goods, services, and values to numerous applications thanks to its inherent advantages of convenience, service speed, connectivity, etc. Although online commerce and other relevant platforms have clear merits, offline-based commerce and payments are indispensable and should be activated continuously, because offline systems have intrinsic value for people. With the theme of benefiting all humankind, we propose a new adaptive benefit platform, called BeneWinD, which is endowed with strengths of online and offline platforms. Furthermore, a new currency for integrated benefits, the win–win digital currency, is used in the proposed platform. Essentially, the proposed platform with a distributed virtual emotion foundation aims to provide a wide scope of benefits to both parties, the seller and consumer, in online and offline settings. We primarily introduce features, applicable scenarios, and services of the proposed platform. Different from previous systems and perspectives, BeneWinD can be combined with Web 3.0 because it deliberates based on the decentralized or distributed virtual emotion foundation, and the virtual emotion feature and the detected virtual emotion information with anonymity are open to everyone who wants to participate in the platform. It follows that the BeneWinD platform can be connected to the linked virtual emotion data block or win–win digital currency. Furthermore, crucial research challenges and issues are addressed in order to make great contributions to improve the development of the platform. Full article