Emerging Science Journal (ESJ)
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Exploring the Nexus between Digital Economy and Green Growth: Insights from Emerging Economies
Get PDFThe digital economy creates new development space, opening high-speed and sustainable growth opportunities for Vietnam to become a leading country in the region in digital economic development and green growth. Thus, the article's objectives are to explore the key factors affecting the digital economy and their impacts on green growth. Based on the above goal, the authors used qualitative and quantitative methodologies to analyze the data, and the study used descriptive statistical methods, including assessing the mean value and standard deviation and utilizing a structural equation model using SPSS 20.0 and Amos from surveying a sample size of 250 persons related to management, economics, banks, research institutes, and universities in 10 provinces in Vietnam. The article's findings have five determinants influencing the digital economy and impacting the digital economy on green growth. Finally, the study's novelty helps policymakers and provincial managers apply research results to develop the digital economy and green growth. Mainly, many proposed solutions exist to realize the parallelism of the digital economy and the green economy; these policy recommendations pay more attention to investment in human resource quality, technological innovation, perfect digital policies, investment in digital infrastructure, and promote propaganda work to raise awareness of the entire society about the digital economy. Doi: 10.28991/ESJ-2024-08-04-022 Full Text: PD
SHAP-Instance Weighted and Anchor Explainable AI: Enhancing XGBoost for Financial Fraud Detection
Get PDFThis research aims to enhance financial fraud detection by integrating SHAP-Instance Weighting and Anchor Explainable AI with XGBoost, addressing challenges of class imbalance and model interpretability. The study extends SHAP values beyond feature importance to instance weighting, assigning higher weights to more influential instances. This focuses model learning on critical samples. It combines this with Anchor Explainable AI to generate interpretable if-then rules explaining model decisions. The approach is applied to a dataset of financial statements from the listed companies on the Stock Exchange of Thailand. The method significantly improves fraud detection performance, achieving perfect recall for fraudulent instances and substantial gains in accuracy while maintaining high precision. It effectively differentiates between non-fraudulent, fraudulent, and grey area cases. The generated rules provide transparent insights into model decisions, offering nuanced guidance for risk management and compliance. This research introduces instance weighting based on SHAP values as a novel concept in financial fraud detection. By simultaneously addressing class imbalance and interpretability, the integrated approach outperforms traditional methods and sets a new standard in the field. It provides a robust, explainable solution that reduces false positives and increases trust in fraud detection models. Doi: 10.28991/ESJ-2024-08-06-016 Full Text: PD
Topic Modeling: A Consistent Framework for Comparative Studies
Get PDFIn recent years, the field of Topic Modeling (TM) has grown in importance due to the increasing availability of digital text data. TM is an unsupervised learning technique that helps uncover latent semantic structures in large sets of documents, making it a valuable tool for finding relevant patterns. However, evaluating the performance of TM algorithms can be challenging as different metrics and datasets are often used, leading to inconsistent results. In addition, many current surveys of TM algorithms focus on a limited number of models and exclude state-of-the-art approaches. This paper has the objective of addressing these issues by presenting a comprehensive comparative study of five TM algorithms across three different benchmark datasets using five different metrics. We offer an updated survey of the latest TM approaches and evaluation metrics, providing a consistent framework for comparing different algorithms while introducing state-of-the art approaches that have been disregarded in the literature. The experiments, which primarily use Context Vectors (CV) Topic Coherence as an evaluation metric, show that Top2Vec is the best-performing model across all datasets, disrupting the tendency for Latent Dirichlet Allocation to be the best performer. Doi: 10.28991/ESJ-2024-08-01-09 Full Text: PD
Stimulation of Purchase Behavior Toward Biodegradable Bags: The Role of Green Skepticism
Get PDFToday, the habit of using light, durable, and disposable plastics that are poorly managed is one of the main reasons for environmental pollution, biodiversity loss, and climate change in Vietnam. Besides, due to the lack of consumption, most plastic companies in Vietnam refuse to switch their production to biodegradable plastic bags. The study is conducted to promote the purchase behavior of biodegradable plastic bags, which can reduce the consumption of non-degradable plastic in Vietnam. A non-probability sampling method was applied, with a sample size of 828 consumers who lived in Southeast Vietnam. SmartPLS software was applied to examine the hypotheses. The results show that attitudes, coping appraisal, and threat positively influence the purchase behavior of biodegradable plastic bags. Green skepticism negatively moderates the relationship between attitudes, coping appraisal, threat appraisal, and purchase intention toward biodegradable plastic bags. This study also added psychological factors, such as green skepticism, to fill the perception-behavior gap from previous studies and extend the protection-motivation theory. Some managerial implications will be proposed for plastic companies in Vietnam to switch their production toward biodegradable plastic bags. Besides, consumers will also be given guidance and encouragement to use these products through integrated marketing communication strategies. Doi: 10.28991/ESJ-2024-08-03-04 Full Text: PD
Global Perspectives on Management Consulting Competitiveness: Analyzing Knowledge Brokers' Components
Get PDFBridging a significant gap in knowledge broker research, this study addresses the challenges and difficulties in demystifying the roles and components of Knowledge Brokers (KBs) within the management consulting context. Despite their recognized importance, the specific functions, and components of KBs in this specific sector context, known for its intensive use of knowledge, have been unexplored. This study aims to narrow the research gap by identifying key components of KB that enable the knowledge brokerage process in management consulting. Utilizing a mixed methods approach with Structural Equation Modeling (SEM) and data collection from various geographies from global perspectives, the research offers an in-depth understanding of KBs in management consulting. The research findings confirm Interpersonal Skills and Cognitive Ability, along with sub-components like Interactive Skill, Motivational Skill, Hybrid & Anomalous, Neutrality, Professional Competence and Experiential Knowledge, as critical to KBs. The findings offer original contributions to theoretical implications by narrowing the research gaps within this specific context. On the practical front, this study provides strategic insights for organizations to significantly enhance sustainable innovation by integrating external knowledge into organizational decision-making processes, which could be extendable to other industries. Furthermore, it suggests the potential to evolve traditional knowledge brokerage into technology-driven platforms and enhance the innovation ecosystem. Finally, the research findings offer the foundations for future studies on similar professional and knowledge-intensive settings, contextual influences of KBs, and the interrelationships among KB components. Doi: 10.28991/ESJ-2024-08-03-014 Full Text: PD
Relationship between Emotional Intelligence, Social Skills, and Anxiety: A Quantitative Systematic Review
Get PDFIntroduction: Emotional intelligence allows us to manage, regulate, and recognize our emotions and those of others, also allowing us to face and solve problems by choosing to provide an appropriate response to the situation experienced by a subject. Social skills are the behaviors that an individual emits in the interpersonal context through their feelings, rights, and opinions, seeking to resolve conflict situations immediately, minimizing the likelihood of experiencing them in the future. Anxiety appears in the individual when he perceives certain situations as threatening or dangerous, hindering his ability to provide an adequate response, being excessive, uncontrollable, or lasting, and this is classified as a mental disorder. Objective: The objective of this study is to describe the relationship between emotional intelligence, social skills, and anxiety. Methods: A quantitative methodology has been employed, basing the study on a systematic review of previous research using the Scopus, Scielo, Redalyc, and Google Scholar repositories. Findings: An initial sample of 1722 articles was obtained, which passed through inclusion and exclusion criteria, resulting in 73 articles. Novelty:The contribution of this study lies in understanding that low anxiety levels lead to better performance of emotional intelligence and social skills. This situation allows people to resolve conflicts that arise in the daily lives of individuals. Doi: 10.28991/ESJ-2024-08-06-025 Full Text: PD
Revealing the Effect of Big Data Capabilities on Efficiency-Based Business Model Innovation
Get PDFObjectives: Business model innovation is significant for corporation performance. Unclear or poorly designed business models can only achieve moderate or insignificant results in terms of performance. Under the view of innovation theory, multiple factors affect the efficiency-based business model innovation. Big data capabilities, knowledge creation, and Institutional environment are proposed. Methods: With the collection from 513 pig farming enterprises in China, this research analyzes the relationships among big data capabilities, knowledge creation, institutional environment, and efficiency-based business model innovation by SMART-PLS. Findings: As a result, big data capabilities have a positive impact on efficiency-based business model innovation. Big data capabilities have a positive impact on knowledge creation. Knowledge creation has a positive impact on efficient business model innovation, which is supported. Knowledge creation mediates between big data capabilities and efficient business model innovation, which is supported. The impact of institutional environment regulation knowledge creation on efficient business model innovation. Novelty:This research has theoretical and practical contributions. This study implies the theory of innovation to the practice. And it also enriches the literature and research on business model innovation. Doi: 10.28991/ESJ-2024-08-04-016 Full Text: PD
Bio-Mechatronics Development of Robotic Exoskeleton System With Mobile-Prismatic Joint Mechanism for Passive Hand Wearable-Rehabilitation
Get PDFThe World Health Organization (WHO) estimates that 15 million people are affected by stroke each year, causing deterioration of the upper limb, which is reflected in 70-80% of them, decreasing the performance of daily activities and quality of life, mainly affecting hand functions. Thus, the purpose of this study is to present a high-quality alternative to recover muscle tone and mobility, consisting of a hand-exoskeleton for passive rehabilitation. It covers a motion protocol for each finger and pressure sensors to give a safety pressure range during the gripping function. The bio-design method covers standards (ISO 13485 and VDI 2206) based on biomechanic and anthropometric fundamentals, where Fusion 360 was used for mechanical development and electrical-electronic circuit schematics. The prototyping process was based on 3D printing using polylactic acid (PLA); also, the actuators were servomotors DS3218, the pressure sensors were RP-C7.6-LT, and the microcontroller was Arduino Nano. The system has been validated by the Institute of Research in Biomedical Sciences (INICIB) at the Ricardo Palma University, where the novelty of this work lies in the introduction of a new mobile-prismatic joint mechanism. In conclusion, favorable results were achieved regarding the complete flexion and extension of the fingers (91.6% acceptance rate, tested in 100 subjects), so the next step proposes that the wearable device will be used in the Physical Medicine and Rehabilitation Departments of Medical Centers. Doi: 10.28991/ESJ-2024-08-06-02 Full Text: PD
Assessing the Impact of Innovation Processes on Electronic Systems Technology Adoption
Get PDFObjectives: This study aims to explore the adoption of electronic health records (EHRs) in the Australian private healthcare sector by integrating three prominent innovation models, namely the Technology Acceptance Model (TAM), the Diffusion of Innovation (DOI) model, and the Technology-Organization-Environment (TOE) framework. The objective of the study is to understand how these combined models might better inform the EHR adoption process and identify the key factors influencing successful implementation. Methods/Analysis: An exploratory qualitative research design employing a phenomenological approach was utilized to investigate the research. Data were collected through semi-structured interviews with senior managers at a private hospital in South-East Queensland. Purposive sampling was employed to select participants, ensuring representation from key decision-makers involved in the EHRs planning process. Thematic analysis, guided by the reflexive thematic analysis (RTA) approach of Braun and Clarke, was used to analyze the data and derive insights into the factors influencing EHRs adoption. Findings: Key findings indicate that perceived usefulness and job relevance (from TAM), innovation attributes and communication channels (from DOI), and technological, organizational, and environmental contexts (from TOE) are critical elements for successful EHRs implementation. The study also highlights the importance of user engagement, comprehensive training, leadership support, and financial resources. Novelty/Improvement: This study offers a novel contribution by integrating the TAM, DOI, and TOE models to provide a more holistic understanding of EHRs adoption in the private healthcare sector. It also introduces the concept of time as a critical innovation artefact, highlighting its significance in the adoption process. Doi: 10.28991/ESJ-2024-08-05-02 Full Text: PD
Optimizing Injection Molding for Propellers with Soft Computing, Fuzzy Evaluation, and Taguchi Method
Get PDFThis research explores multi-objective optimization in injection molding with a focus on identifying the optimal configuration for the moldability index in aviation propeller manufacturing. The study employs the Taguchi method and fuzzy analytic hierarchy process (FAHP) combined with the Technique for the Order Performance by Similarity to the Ideal Solution (TOPSIS) to systematically evaluate diverse objectives. The investigation specifically addresses two prevalent defects”shrinkage rate and sink mark”that impact the final quality of injection-molded components. Polypropylene is chosen as the injection material, and critical process parameters encompass melt temperature, mold temperature, filling time, cooling time, and pressure holding time. The Taguchi L25 orthogonal array is selected, considering the number of levels and parameters, and Finite Element Analysis (FEA) is applied to enhance precision in results. To validate both simulation outcomes and the proposed optimization methodology, Artificial Neural Network (ANN) analysis is conducted for the chosen component. The Fuzzy-TOPSIS method, in conjunction with ANN, is employed to ascertain the optimal levels of the selected parameters. The margin of error between the chosen optimization methods is found to be less than one percent, underscoring their suitability for injection molding optimization. The efficacy of the selected optimization method has been corroborated in prior research. Ultimately, employing the fuzzy-TOPSIS optimization method yields a minimum shrinkage value of 16.34% and a sink mark value of 0.0516 mm. Similarly, utilizing the ANN optimization method results in minimum values of 16.42% for shrinkage and 0.0519 mm for the sink mark. Doi: 10.28991/ESJ-2024-08-05-025 Full Text: PD