Emerging Science Journal (ESJ)
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An Empirical Analysis of Influencing Factors of Government Decision-Making on Public Crisis
Get PDFAs the times and the world are changing in an unprecedented way, public security issues have become increasingly linked, transnational, and diverse, causing huge impacts on the global economy and society, as well as posing great challenges to the government in dealing with public crisis decision-making. This study aims to determine the factors affecting the government's crisis decision-making and analyze the interrelationship among the factors affecting the government's crisis decision-making and the performance of its crisis decision-making. The questionnaire was developed and used to collect data from 400 samples of various groups, including government department personnel, scientific research institute practitioners, university lecturers, the public, and university students, both online and face-to-face. The structural equation model (SEM) is used to evaluate the structural relationships of the relevant variables, including the crisis decision-making body, crisis decision-making procedure, crisis decision-making performance, the decision environment, and value identification. It is found that the diversified decision-making subject and decision-making environment have a positive and significant impact on the public crisis decision-making process, value identification, and decision-making performance, respectively. This study has contributed to the following issues. Firstly, it developed new measurement tools and indicators for better evaluating the quality and effect of public crisis decision-making and exploring the influence of different factors on the crisis decision-making of the government. Secondly, it employed cross-industry and cross-cultural comparative research to find commonalities and differences and provide targeted recommendations. Doi: 10.28991/ESJ-2024-08-02-03 Full Text: PD
BSHPC: Improve Big Data Privacy Based on Blockchain and High-Performance Computing (HPC)
Get PDFThe vast expansion and sharp rise in data across many facets of society have made it increasingly difficult to manage big data effectively. Using traditional methods to ensure the security and privacy of users' data is no longer sufficient. In keeping with this worry, massive data storage is still crucial. High-Performance Computing (HPC) is examined to determine the need for handling blockchain issues and protecting large data in a decentralized manner that strives for resilience. This study proposes the Big Data Storage High-Performance Computing (BSHPC) approach, which addresses big data considerations in storage management to maintain accuracy and enables the usage of blockchain. The best storage management is the primary benefit of BSHPC, as only critical data is kept on the blockchain, and other data may be kept in an off-chain database using the interplanetary file system (IPFS). Furthermore, the network's node authentication in this strategy depends on trustworthy nodes. On HPC computers, data authenticity and provenance tracking would be guaranteed, and managing large data across blockchains would be more secure. The proposed method is simulated using the Python-MPI version, and the results confirm the effectiveness of the proposed method based on performance and transactions. Moreover, the proposed method is evaluated with another study in the literature on MEC-based sharing, and it proves its effectiveness. Doi: 10.28991/ESJ-2024-08-06-011 Full Text: PD
Enhancing Control Systems with Neural Network-Based Intelligent Controllers
Get PDFThe primary challenge faced by a neural controller in the dynamic model of a mobile robot lies in its ability to address the inherent complexity of the system dynamics. Given that mobile robots exhibit nonlinear movements and are subject to diverse environmental conditions, they contend with a challenging dynamic environment. The neural controllers must demonstrate the capability to continuously adapt and effectively learn to manage the variability present in the dynamic of the robot. This paper presents two intelligent controllers utilizing neural networks, showcasing their relevance in the field of robotics. The first controller, referred to as the neural PID (PIDN), integrates the traditional PID controller with a neural component. The second controller leverages the dynamic model of a differential robot to improve trajectory tracking, employing a parallel architecture that combines PID with neural networks (PID+NN). Our proposals adhere to a cascading structure, where the outer loop takes the lead in reducing position errors through a kinematic controller, while concurrently, the inner loop is employed to regulate linear and angular velocities through the proposed controllers. The controllers are validated in the CoppeliaSIM simulator, offering a realistic setting for evaluating the behavior of the chosen Pioneer 3-DX robot. To comprehensively assess controller performance, three strategies are examined: PIDN, PID+NN, and the conventional PID. Through a blend of qualitative and quantitative analyses, employing diverse performance metrics, the advantages of our proposed controllers become apparent. Doi: 10.28991/ESJ-2024-08-04-01 Full Text: PD
Risk Ordering Relation and Risk Control for P2P Lending Platforms: A Multi-Agent Systems (MAS) Approach
Get PDFIn the context of Peer-to-Peer (P2P) lending, risk controls are required, and they usually refer to a set of procedures and operations that aim to protect the integrity of data, particularly for accurate financial representation within the platform. Risk control procedures need to be in place to ensure accountability and fairness in risk and return trade-offs on federated platforms. This will foster trust among participants, especially when multiple fraud cases in the past, such as Enron, Madoff Investment Securities, and WorldCom, have accentuated the importance of a robust internal control mechanism in maintaining the credibility of the financial ecosystem. Stakeholders in the P2P lending industry are becoming increasingly concerned about the issue of trust, necessitating a re-evaluation of internal control frameworks to uphold objectivity and reliability. With the growth of the P2P lending industry as an alternative lending and borrowing platform and the requirement of an autonomous P2P lending platform, complexity arises, and autonomous entities (i.e., MAS) working together to assess, monitor, and mitigate risks is the only solution for such complexities. The orchestration of MAS plays a pivotal role in facilitating and mitigating risks. This study aims to provide a process methodology for fostering collaborative dynamics within the P2P lending domain. A state diagram approach is presented, where state orders (SO), lending approvals, risk graphs, risk ordering relations, and risk bands (RB) are introduced for MAS to assume certain roles or tasks. For each task, controls for the segregation of duties are presented as well. Given the absence of proper autonomous systems for decision-making, robust internal control methods are necessary for controls to execute federated trust on lending platforms. Our approach will significantly improve investors' confidence meant to achieve this goal. Doi: 10.28991/ESJ-2024-08-04-024 Full Text: PD
Managerial Recommendations for Enhancing Green Consumption Behavior and Sustainable Consumption
Get PDFThe green consumerism movement is gaining steam in emerging nations with middle-income or higher populations, such as Vietnam, and is particularly well-liked in affluent countries. In addition, the importance of green consumerism is gaining significant traction, alongside efforts to promote ecologically friendly production and consumption. As the economy progressed, people's living standards improved, leading to a growing need for high-quality, safe products and services. This is particularly true for items that directly serve people and contribute to their everyday lives. Therefore, the article aims to evaluate the factors affecting green consumer behavior and sustainable consumption based on the structural equation model with the least squares method to test their hypotheses. The data were applied in the study through a survey of 360 consumers in 04 big cities in Vietnam. Research results showed that seven factors impact green consumption behavior, including (1) environmental awareness, (2) green product characteristics, (3) green marketing, (4) perceptions about green product prices, (5) social influence, (6) environmental policy, and (7) green consumption policy with significance 0.01. The finding explores green consumption behavior influencing sustainable consumption with a significance of 0.01. The practical implication helps managers, policymakers, and manufacturers consider applications to improve humanity and behavior green consumption in the global context of moving towards sustainable green development. The theory implication is to change behavior to improve greening production, reduce pollution and greenhouse emissions, and move towards sustainable development, bringing many practical economic and social benefits and intangible value for businesses. Simultaneously, the novelty of the study aids enterprises in staying abreast of this trend, enabling them to seize possibilities for fast growth, extend their market presence, and capitalize on governmental backing for businesses. Doi: 10.28991/ESJ-2024-08-06-07 Full Text: PD
Enterprise Innovation Decision-Making Towards Green and Sustainability from the Perspective of Cognitive Innovation
Get PDFAlthough numerous current studies on green consumption and sustainable enterprise development have been carried out, the majority of them examined the issues from customers' viewpoints. This study aims to explore the mechanism that shapes firm innovation decision-making in the context of green and sustainable development from the perspective of business awareness under the impact of customer expectations. The study conducted an online survey (via Google Forms) with the participation of 301 employees from different enterprises in the Mekong Delta, Vietnam. To restrict the common method biases, Cronbach's alpha was checked by using SPSS to ensure the reliability of the initial scales. Based on a deductive approach and testing hypotheses through evaluating the measurement model and structural model using SmartPLS software, the research results determined the mechanism of forming firm innovation decisions in this study via the impact of customer expectations as a stimulating factor leading to awareness of innovation. Customer expectations were positively associated with perceived marketing innovation. Perceived marketing innovation was not only positively associated with perceived process innovation but also related to firm innovation. Similarly, perceived process innovation was significantly positively associated with firm innovation. In alignment with research findings, significant practical and academic contributions were also proposed. Doi: 10.28991/ESJ-2024-08-06-013 Full Text: PD
Effect of Gadolinium Doping on the Structure of Ce₁₋ₓGdₓO₂₋₍ₓ/₂₎ Solid Solutions Prepared by Ionic Gelation Approach
Get PDFThe current research aims to present the structural characterization of Gd-doped ceria powders and ceramics, investigating the structural evolution resulting from cerium substitution with Gd across the entire composition range from 0 to 100 mol.% Gd2O3. Ce1-xGdxO2-x/2 powders with varying Gd contents (0 ≤ x ≤ 1) were synthesized using the ionic gelation method followed by thermal annealing. The resulting powders were subjected to high-temperature treatment to obtain ceramics. Characterization methods included X-ray diffraction (XRD) to identify phase composition and confirm the formation of Ce1-xGdxO2-x/2 solid solutions, infrared spectroscopy (IR) and scanning electron microscopy (SEM) for structural and morphological studies, and X-ray photoelectron spectroscopy (XPS) to evaluate the electronic structure. Comparative analysis of Gd-doped calcined powders and sintered pellets revealed the impact of thermal treatment on the structural features of the resulting solid solutions, elucidating the influence of gadolinium substitution. The novelty of this research lies in demonstrating the successful preparation of Ce1-xGdxO2-x/2 solid solutions via an alginate-mediated ion-exchange process and providing a detailed structural investigation over the entire range of dopant concentrations. This assessment highlights the feasibility for further research of these materials as suitable candidates for intermediate-temperature solid oxide fuel cells (IT-SOFCs) or catalyst applications.
Doi: 10.28991/ESJ-2024-08-05-01
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Enhancing Supply Chain Resilience through Artificial Intelligence: A Strategic Framework for Executives
Get PDFIn today's contemporary turbulent business environment, marked by disruptions ranging from natural disasters to global pandemic, supply chain resilience is crucial. This research addresses the pressing need to understand challenges faced by Indian supply chain executives by adopting AI-driven solutions for enhancing resilience. Analyzing data from 300 executives using ANOVA and t-tests reveals critical patterns in encountered barriers. Simultaneously, the study aims to fill gaps in existing literature by developing a strategic framework for executives. Using Structured Equation Modeling (SEM), it outlines best practices for integrating AI into supply chain operations, offering nuanced insights into strategic considerations and organizational barriers influencing AI adoption decisions. The research identifies a gap in comprehensive studies on challenges and decision-making factors specific to Indian executives adopting AI for supply chain resilience. By addressing this gap, the study enriches global discourse on AI in supply chain management and provides targeted guidance to Indian executives navigating AI-enabled operations. Ultimately, the research aims to empower executives with actionable insights to effectively leverage AI, enabling them to fortify supply chain resilience amidst India's evolving business dynamics.JEL Code: O32, M15, L23, L25, Q55. Doi: 10.28991/ESJ-2024-08-04-013 Full Text: PD
Unraveling the Myths of Rural vs. Urban Academic Achievement Drivers
Get PDFThe generalized migration of individuals from rural to urban areas is a global phenomenon that entails many divides, education being one of them. However, there is a lack of understanding regarding whether the factors driving higher academic achievement (AA) differ between urban and rural students. This study uses data from almost every student in Portugal who took the Portuguese and/or mathematics high school national exams. By applying OLS, the aim is to identify the AA drivers and compare these drivers between urban and rural areas. Among the key findings, variables related to academic background emerged as the strongest predictors of AA, regardless of the environment. Additionally, ICT access is insignificant in urban and rural areas, while socio-economic status does not significantly impact AA amongst rural students. These findings highlight the need for tailored interventions that address the unique challenges faced by students in different areas, with a particular focus on enhancing academic support structures to improve educational outcomes. To the best of our knowledge, this study is the first to utilize data encompassing virtually every student in an entire country to compare and understand the differences in the determinants of AA between urban and rural areas. Doi: 10.28991/ESJ-2024-08-06-010 Full Text: PD
Enhancing Efficiency: The Impact of Cloud Computing Adoption on Small and Medium Enterprises Performance
Get PDFThis study investigated the factors influencing cloud computing adoption (CCA) and its impact on organizational performance (OP) among SMEs employees in Bahrain. The study used an online survey approach, which includes Likert scale questions to assess attitudes and views, multiple-choice questions for categorical data, and open-ended questions to obtain qualitative insights. The target audience comprises 300-350 small and medium-sized enterprises (SMEs) in Bahrain currently utilizing cloud computing technology, and 314 useful responses were received. A mixed two-step sampling technique was initiated by convenience sampling. Then, snowball sampling was used to guarantee the inclusion of various SME categories, thus ensuring representativeness. The measurements are derived from validated instruments used in academic research, with the questionnaire incorporating elements adapted from the studies conducted. Participants' responses to the Likert scale are analyzed using SmartPLS 4 to understand their perspectives. Full collinearity was used to assess common method bias, and VIF values below 3.3 indicated no bias. The measuring model's validity and reliability were evaluated by loadings, AVE, CR, and discriminant validity tests (HTMT), which ensured all constructs fulfilled thresholds. Path coefficients, standard errors, t-values, and p-values were used to evaluate the structural model using 10,000-sample bootstrapping. The research findings indicate that both Perceived Ease of Use (PEU) and Perceived Usefulness (PU) have a substantial impact on Cloud Computing Adoption (CCA), which in turn improves the performance of Bahraini SMEs. PEU and PU directly impact CCA while indirectly improving Organizational Performance (OP) by increasing cloud computing usage. These findings emphasize the importance of user-friendly and beneficial cloud solutions in increasing cloud computing adoption and enhancing business outcomes for SMEs. Doi: 10.28991/ESJ-2024-08-06-017 Full Text: PD