Supply Chain and Sustainability Research: SCSR

An Impact of Marketing Strategies on University Students’ Online Shopping Behavior: A Case Study of Asia Eastern University of Science and Technology, Taiwan

YUCHI CHEN, Dhriwit Assawasirisilp — Tue, 07 Jan 2025 00:00:00 +0700

This research explores the influence of marketing strategies—namely product, price, distribution, and promotion—on university students' online shopping behavior. Focusing on students at Asia Eastern University of Science and Technology (AEUST), this study collected data through questionnaires distributed to a diverse sample of students. The analysis reveals that product strategy, particularly aspects such as product details, images, and brand diversity, is the most influential factor in shaping purchasing decisions. Subsequently, distribution strategies, such as the provision of free shipping and flexible delivery options, also significantly impact students' choices, making the overall shopping experience more appealing. While price strategies, including discounts and promotional offers, and promotional strategies play a role in the decision-making process, their effects are relatively less pronounced than those of product and distribution strategies. This study highlights the importance of understanding the unique preferences and behaviors of student consumers in the evolving e-commerce landscape. The findings provide valuable insights for e-commerce platforms targeting this demographic, suggesting that tailored marketing strategies can enhance engagement and drive sales among university students.

Research on Marketing Strategies of Decoration Design Company's Supply Chain

Yingying Quan — Tue, 07 Jan 2025 00:00:00 +0700

With the rapid development of China’s real estate industry and improved living standards among urban and rural residents, the demand for decoration design services has surged, driving the continuous growth of decoration design enterprises. However, fluctuations in the real estate market have intensified competition, presenting challenges to sustaining business development. Marketing management plays a crucial role in addressing these challenges, with a focus on formulating scientific marketing strategies to guide enterprise growth and ensure stability. This paper examines MS Decoration Design Company, leveraging literature review and field research to analyze its marketing strategy dilemmas. Key issues include ambiguous target customer groups, misalignment between product offerings and price positioning, insufficient brand awareness, limited marketing channels, and a lack of personalized services. These challenges highlight significant deficiencies in the company’s marketing strategy framework. To address these issues, this study applies SWOT analysis to propose targeted countermeasures. These include diversifying core business offerings, expanding market reach, optimizing the industrial ecological environment, and refining the company’s strategic focus. Recommendations emphasize clearly defining target customer groups, aligning product and price positioning, strengthening brand planning, enhancing channel development, and prioritizing personalized service delivery. By implementing these strategies, MS Decoration Design Company can improve its marketing approach, achieve sustainable development, and contribute to the broader growth of the decoration design industry.

Application of MATLAB-assisted Ridge Regression in Weight Reduction and Environmental Protection of Glass Bead Concrete

YAFENG HE, Baixiong DENG, MICHAEL A ALORIA, Xiaoye WEN, Zhongqin GENG — Tue, 07 Jan 2025 00:00:00 +0700

This study utilizes MATLAB to develop a Ridge regression prediction model, aimed at assessing the impact of incorporating vitrified microbead insulation sand into concrete on both weight reduction and environmental performance. Empirical findings indicate that substituting 20% of the manufactured sand with vitrified microbead insulation sand in C25 concrete reduces the concrete’s weight from 24.98 kg to 24.68 kg, achieving a 0.12% reduction. Concurrently, the compressive strength is significantly enhanced, increasing from 38.5 MPa to 40.3 MPa, indicating a notable improvement in material performance. The weight of the model-predicted concrete is 24.8873 kg, closely aligning with the actual experimental data, thereby affirming the accuracy and reliability of the Ridge regression model. The findings of this study provide robust scientific evidence supporting the lightweight design and sustainable application of concrete materials, highlighting the extensive potential of vitrified microbeads in construction engineering.

Global Green Logistics: Challenges and Opportunities in Vietnam's Sustainable Development

Eddie Hsu — Tue, 07 Jan 2025 00:00:00 +0700

The continuous intensification of global climate change makes it imperative for governments and companies to take effective measures to achieve carbon neutrality goals and reduce carbon emissions. As one of the main sources of carbon emissions in the global supply chain, the logistics industry is facing an urgent need for transformation. As a global manufacturing and exporting powerhouse, Viet Nam's logistics industry is facing the challenge of high carbon emissions and technological lag while promoting economic growth. This study aims to explore the problems faced by Viet Nam's logistics industry in terms of infrastructure, technology application, policy framework and finance, and propose short-, medium-term and long-term development strategies based on international experience to promote the green transformation of Viet Nam's logistics industry. The results of this study show that Viet Nam should strengthen infrastructure construction, promote policy and regulatory reforms, raise environmental awareness of enterprises and society, and actively introduce smart logistics technologies and green financial tools to achieve carbon neutrality. Finally, this study provides concrete policy recommendations aimed at assisting the Viet Nam government and enterprises to accelerate the sustainable development of the logistics industry.

Envisioning the Future of Supply Chain Transportation Management- Exploring Crowd Density Image Recognition with Deep Learning

EN-FU LI, Cheng-Chung Lee, Guan-Hong Chen — Tue, 07 Jan 2025 00:00:00 +0700

Over the past few decades, artificial intelligence (AI) technology has made significant progress, especially in image recognition and natural language processing. Deep learning, as a multi-level artificial neural network architecture, can automatically identify and learn data features through large amounts of data to achieve high-precision prediction and identification. This research aims to explore the practical application of deep learning in the field of image recognition, and designs an automated image recognition system, taking the identification of crowd density in a train carriage as an example. The system can accurately detect the number of passengers in each carriage, thereby optimizing urban rail transit strategies, ensuring even distribution of passengers and providing the best commuting experience. This technology also has important implications for supply chain management. Accurate people flow identification technology can improve resource utilization efficiency, optimize logistics resource allocation, and reduce transportation time and costs through real-time monitoring and prediction of people flow density. It can also improve demand forecasting and analyze historical data through deep learning algorithms to help companies predict demand more accurately and avoid excessive transportation and shared traffic. This technology enhances supply chain transparency and promotes sustainable development by monitoring the entire transportation process in real time. These applications can improve the operational efficiency of the transportation system and significantly improve the quality and efficiency of supply chain management, demonstrating the huge potential of deep learning technology in modern supply chain management.

A Review of Research on System Dynamics in Supply Chain Management

Chaozhe Jiang, Yanmin Shen, Yangyan Shi, Fang Xu, Yantong Jin — Tue, 07 Jan 2025 00:00:00 +0700

Based on the bibliometric method, this paper applies the text mining technology and draws the keyword cloud map and keyword co-occurrence network to deeply explore and comprehensively sort out the core application topics of system dynamics in supply chain management and its methodological system. It is found that system dynamics has important application value in many key areas such as inventory management, risk management, supply chain finance and green supply chain management. For each core application theme, this paper further extracts the keywords and constructs a co-occurrence network, which reveals the specific research directions, research methods and their interrelationships under each sub-theme in detail. In addition, in order to strengthen the empirical basis of the discussion, this paper cites several representative papers, analyses the simulations and numerical analyses carried out by these studies within the framework of system dynamics, and summarises the key parameters. Finally, based on the review and comprehensive analysis of the previous studies, this paper looks forward to future research trends, which will provide useful references for subsequent studies.