Emerging Science Journal (ESJ)
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Impact of Green Marketing Elements on Consumers: A Behavioral Approach
No full textThis research examines the factors influencing green purchasing behavior in the Vietnamese market, utilizing the Theory of Planned Behavior (TPB) as its foundation. Utilizing an online questionnaire survey of 596 Vietnamese consumers from December 2023 to February 2024, the research examines the influence of key factors, including green advertising, awareness of green products, environmental awareness, subjective norms, attitude toward green products, and green pricing on consumer purchase intentions and behaviors. The research utilized the technical of Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine and confirm the proposed hypotheses. The findings reveal that the most influential factor on consumer purchase intentions and behaviors is the attitude toward green products, highlighting the crucial role of consumer perceptions and values regarding environmentally friendly products. Furthermore, green advertising and awareness of green products also play a vital role in shaping consumer intentions. While subjective norms and green pricing also show an influence, they have a lesser impact. This study contributes both theoretically and practically by offering valuable insights for marketers and policymakers designing effective green marketing strategies that enhance consumer engagement and encourage the adoption of environmentally friendly products in Vietnam
A Study of the Effects of Knowledge Management on Enterprise Innovation Performance
No full textThis study aims to explore how knowledge management capability and enterprise innovation behavior jointly affect the innovation performance of manufacturing SMEs. Based on the background of the knowledge economy, we selected manufacturing SMEs with knowledge as their core competitiveness as the research object and constructed and optimized the theoretical model of “Knowledge Management Capability-Innovation Behavior-Innovation Performance”. Based on the research data from 400 manufacturing SMEs in China, the study adopts the empirical analysis method and examines the relationship between the variables through structural equation modeling. The results show that knowledge management capability has a significant positive impact on firms' innovation performance, while firms' innovation behavior mediates the relationship between knowledge management capability and innovation performance. The findings of this study not only validate the key role of knowledge management in enhancing the innovation capability of enterprises but also reveal the path mechanism for enterprises to realize knowledge transformation and innovation results by stimulating innovative behaviors. Compared with previous studies, this study systematically optimizes the construction of theoretical models and the analysis of mediating effects, enriches the research content in the field of knowledge management and innovation performance, and provides new theoretical support and empirical evidence for the knowledge management practice and innovation strategy formulation of manufacturing SMEs
Nonlinear and Heterogeneous Effect of Digitalization on Foreign Direct Investment: Evidence from Developing Countries
Get PDFThis study aims to clarify whether digitalization has a nonlinear and heterogeneous effect on foreign direct investment (FDI) inflows in developing countries. We employ data from the period 2002–2023 and apply various econometric methods, including System Generalized Method of Moments (S-GMM), Dynamic Panel Threshold Regression (DTPR), and Method of Moment Quantile Regression (MMQR), to address the research question. The findings report an inverted U-shaped relationship between digitalization and FDI. Specifically, the effect of digitalization on FDI changes across different levels of digitalization. Initially, digitalization positively affects FDI, but beyond a certain threshold, its impact turns negative. This indicates that the benefits of digitalization for FDI are not unlimited but may be constrained by the risks and costs associated with excessive digital infrastructure expansion. Additionally, the MMQR analysis shows a heterogeneous effect of digitalization on FDI. Digitalization has a stronger impact on FDI at lower quantiles. However, as a country's development level increases, the effectiveness of digitalization in attracting FDI gradually diminishes. Policymakers need to identify and maintain an optimal level of digitalization to promote FDI. This requires not only investment in digital infrastructure but also in supporting factors such as improved governance quality and the development of legal frameworks to ensure a stable and conducive economic environment for FDI. Moreover, flexible policies tailored to different country or regional groups are necessary to maximize the benefits of digitalization without triggering negative impacts on long-term economic development
A Multi-Dimensional Framework for Assessing the Societal Benefits of Collaborative R&I Projects Over Time
No full textThis paper contributes to the ongoing discussion on assessing the actual societal benefits of collaborative research and innovation (R&I) projects, focusing specifically on Circular Bioeconomy (CBE) initiatives funded under European Interreg programs. Utilizing an abductive method aligned with a grounded theory approach, the study conducted a multiple case study of five cross-border CBE projects. Data from project leaders and secondary sources underwent inductive content analysis and were classified using the Triple Bottom Line (TBL) framework. Seven cross-cutting benefit categories emerged: capacity building, collaborative learning, community empowerment, networking, knowledge sharing, policy development, and sustainable business practices, identified as influencing results across TBL dimensions temporally. Findings reveal projects excel at generating short/medium-term outputs and outcomes strongly aligned with the social dimension, particularly through capacity building, collaborative learning, and knowledge sharing. Over time, long-term impacts demonstrate a more balanced distribution across all three TBL dimensions (social, environmental, and economic), indicating a trajectory towards broader benefits. Policy development and networking are emphasized as key drivers for achieving significant long-term, multi-dimensional impacts. This study introduces a novel, empirically grounded, multi-dimensional theoretical model. By inductively categorizing benefits and analyzing their temporal manifestation across TBL, it provides a practical framework for assessing comprehensive societal impact beyond conventional output metrics
Unleashing Effective Identification of ALS Based on Vowel Phonation: A Deep Learning Approach
No full textALS (Amyotrophic Lateral Sclerosis) is one of the fatal diseases across the world. Therefore, early detection can save patients suffering from ALS from life-threatening consequences. Typically, ALS can be identified based on different factors, and one such factor is voice analysis. Detection of ALS using sound signals is convenient and simpler than other methods, as it is a non-invasive approach, which makes the process faster and more efficient for detection. However, detection of ALS using traditional approaches is challenging, as it is a time-consuming process and heavy reliance on medical experts is needed. Therefore, AI-based models can be used for effective classification of ALS and non-ALS patients, as AI-based models possess the immense ability to examine vast amounts of data, including audio files, effectively. Owing to these factors, the proposed model focuses on employing an AI-based model for ALS classification based on vowel phonation /a/ and /i/. The process is carried out using the Minsk2020 dataset, where important features needed for the proposed model are extracted using MFCC (Mel-frequency cepstral coefficients) by removing the shakiness and jitteriness of the voice. The MFCC feature extraction technique extracts features based on the mel scale, as this reflects human auditory perception, thereby extracting features that are useful for classification. These extracted features are fed to CNN-LSTM (Convolutional Neural Network – Long Short Term Memory) with rapid dilatenet for classifying ALS and non-ALS patients accurately by identifying even the subtle changes in audio signals using maximizing the expansion/dilation rate and aid the context information for interpreting and analyzing the sound of vowels accurately and correctly without any loss of information. Finally, the efficacy of the proposed model is assessed using evaluation metrics. The proposed research work can assist medical professionals in detecting patients with ALS based on vowel phonation
Extending C-TAM-TPB: Dual-level Moderation of Perceived Web Security and Age in Digital Banking
No full textThis study examines the intention to adopt digital banking in Saudi Arabia by integrating the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). It includes Perceived Web Security (PWS) and Age as moderators, addressing trust and security perceptions across user segments in emerging markets. Data were collected from 353 digital banking users in Saudi Arabia using a cross-sectional quantitative design. The model was tested via Partial Least Squares Structural Equation Modeling (PLS-SEM), assessing measurement validity, path significance, moderation, and mediation effects. Predictive accuracy was evaluated with in-sample (R²) and out-of-sample (Q², PLS-Predict) indicators. The results confirmed the significance of core TAM variables—Perceived Ease of Use (PEU), Perceived Usefulness (PU), and Attitude Toward Use (ATU)—on Behavioral Intention (BI). Attitude was a strong predictor of BI, but Subjective Norms (SN) and Perceived Behavioral Control (PBC) were not significant. PWS moderated the ATU–BI relationship, enhancing intention under high security perception, but Age's dual-moderation effect was unsupported. Sequential mediation analysis validated that PEU and PU influence BI indirectly via ATU. This study enhances digital adoption research through a validated dual-level moderation model combining security perception and age. It refines TAM-TPB integration and offers practical insights for creating secure, user-centered digital banking systems tailored to specific cultures
Clustering and Network Analysis of Mobility Patterns as an Analysis Tool for Lean Project
Get PDFThe study aims to optimize internal logistics processes by applying Lean philosophy and data science tools, with a primary focus on qualifying processes to determine their value-added contribution within the logistics context. Utilizing a novel two-step methodology, the research first employs a modified DBSCAN algorithm to analyze indoor positioning data and categorize activities. This is followed by multi-layer network modeling to understand processes and create a framework that enables the reduction of idle activities through optimization algorithms. A real warehouse case study, using a UWB-based Indoor Positioning System (IPS) to track forklifts, demonstrates the method's effectiveness in identifying non-value-added activities. The results reveal specific opportunities for reducing idle, enhancing resource utilization, and improving operational efficiency. This innovative combination of advanced data analysis techniques and Lean principles provides a comprehensive framework for logistics optimization, significantly enhancing process efficiency through optimized task scheduling and resource allocation. Doi: 10.28991/ESJ-2025-09-01-013 Full Text: PD
Innovative Chemical Engineering Education: Social Media-Enhanced Project-Based Learning Approaches
Get PDFThis study investigates the integration of social media platforms, specifically YouTube and TikTok, as educational tools in Project-Based Learning (PBL) within chemical engineering courses, with a particularly focus on Unit Operations. The research involved seventy-eight students from the Universidad Técnica Particular de Loja across two consecutive semesters (April-August 2022 and October 2022-February 2023). Students were tasked with creating educational videos to communicate complex engineering concepts. YouTube was utilized for longer, detailed explanations, while TikTok was employed for short, engaging content. The results demonstrate the effectiveness of this method in enhancing student engagement and comprehension of both theoretical and practical concepts. Instructors observed substantial improvements in student creativity and digital literacy. Quantitative data, such as average course scores, and qualitative feedback from instructors highlight both the strengths and challenges of leveraging social media as a learning tool. A project evaluation rubric was developed to assess performance across several dimensions, including content mastery, practical application, creativity, and engagement. The study concludes that the combination of PBL with social media platforms creates a dynamic, interactive learning environment that cultivates essential skills for future engineers. However, it also identifies areas for refinement, particularly in terms of effective communication through digital media formats. Doi: 10.28991/ESJ-2024-SIED1-021 Full Text: PD
The Impact of Interactive Behaviour on Service Quality: The Role of Relationship Quality, External Environment
No full textThis study explores the impact of interactive behaviour, relationship quality, and the external environment on the quality of urban public services, as well as their mechanisms of action. Correlation analysis (CA) was used to assess the relationships between variables, while a structural equation modelling (SEM) analysed the complex links among interactive behaviour, relationship quality, public service quality, and the external environment. Additionally, principal component analysis (PCA) and K-Means clustering techniques were applied to reveal intrinsic relationships between variables. The findings indicate that interactive behaviour indirectly enhances public service quality by improving relationship quality, with the external environment playing a significant moderating role in this process. The model fit indices (CFI, RMSEA, chi-square statistics) confirmed the model’s interpretability and consistency with the data. The innovation of this study lies in the integration of PCA and K-Means clustering into the SEM model, providing a more comprehensive framework for analysing variable relationships. This research offers a theoretical foundation and practical guidance for policymakers seeking to optimize public service management strategies, government departments aiming to strengthen cooperation, and scholars working to deepen related research
Enhancing Students' Conjecturing Skills Through RBL-STEM with Antimagic Coloring and Geometric Transformation in Batik Design
Get PDFStudents' conjecturing refers to the process wherein students make educated guesses or hypotheses about a problem, situation, or concept based on their prior knowledge, observations, and reasoning skills. It is an essential aspect of problem-solving and critical thinking skills. This research aims to enhance students' conjecturing thinking skills by implementing RBL-STEM using the (a,d)-edge antimagic coloring technique and geometric transformation to develop Batik motifs. A mixed methods approach was used, combining quantitative and qualitative analyses. Using an independent sample t-test, the quantitative analysis examined differences in conjecturing skills between the experimental and control classes. Qualitative analysis, through in-depth interviews, provided a triangulation of the quantitative findings. The results indicated a significant improvement in the students' conjecturing skills after the implementation of RBL-STEM. Statistical analysis at a confidence level of 5% showed a t statistic with Sig. (2-tailed) = 0.036 < 0.05, confirming the rejection of H0. The novelty of the study lies in integrating the (a,d)-edge antimagic coloring technique and geometric transformation into classroom research with STEM activities. These findings suggest that RBL-STEM has the potential to improve students' conjecturing abilities, particularly in the development of batik motifs rooted in local wisdom. Doi: 10.28991/ESJ-2025-09-02-019 Full Text: PD