The Impact of Supply Chain Risk Management on Financial Performance: Evidence from the Southeast Asian Manufacturing Sector
DOI:
https://doi.org/10.65875/abj02014555Keywords:
Supply Chain Risk Management, Manufacturing Industry, Financial Performance, Structural Equation ModelingAbstract
Supply chain risk management (SCRM) represents a fundamental priority for industrial enterprises, especially within Southeast Asian markets where heightened globalization and systemic volatility create formidable hurdles. Maintaining operational stability and securing superior financial results necessitates the integration of effective SCRM frameworks. Despite this necessity, scholarly evidence documenting the correlation between SCRM implementation and financial outcomes within this specific geographical context remains sparse. This investigation explores the influence exerted by supply chain risk management on the fiscal health of Southeast Asian manufacturing firms, offering a deeper understanding of how these practices bolster both profitability and organizational endurance. Quantitative research framework was adopted, drawing upon survey data harvested from 250 manufacturing entities operating throughout the region. Structural equation modeling (SEM) served as the primary analytical tool to evaluate the pathways between SCRM activities and key financial performance metrics, including return on assets (ROA) and net profit margins. Results indicate that proficient SCRM practices—specifically risk identification, comprehensive assessment, and proactive mitigation—yield substantial improvements in financial standing. Enterprises equipped with sophisticated SCRM systems demonstrated elevated profitability levels alongside a more robust capacity to withstand external disruptions. Mitigation strategies, most notably, emerged as the most significant driver of positive financial performance. Such findings underscore the critical requirement for adopting holistic SCRM protocols to optimize economic returns within the manufacturing industry.
References
Alhwaiti, Y., Khan, M., Asim, M., Siddiqi, M. H., Ishaq, M., & Alruwaili, M. (2025). Leveraging YOLO deep learning models to enhance plant disease identification. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-92143-0
Anwar, U. A. A., Rahayu, A., Wibowo, L. A., Sultan, M. A., Aspiranti, T., Furqon, C., & Rani,
A. M. (2025). Supply chain integration is the implementation of strategic management in improving business performance. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-00867-w
Barrionuevo, G. O., La Fé-Perdomo, I., & Ramos-Grez, J. A. (2025). Laser powder bed fusion dataset for relative density prediction of commercial metallic alloys. Scientific Data,
12(1). https://doi.org/10.1038/s41597-025-04576-x
Berta, K. K., & Tesfaye, M. (2025). Determinants of road construction project delay in the case of Woliso–Ambo road construction. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-86852-9
Bredt, B. H., Tripet, F., & Müller, P. (2025). Revealing complex mosquito behaviour: A review of current automated video tracking systems suitable for tracking mosquitoes in the field. Parasites and Vectors, 18(1). https://doi.org/10.1186/s13071-025-06666- 6
Chauhan, V., Gupta, L., & Dixit, J. (2025). Landslide susceptibility assessment for Uttarakhand, a Himalayan state of India, using multi-criteria decision making, bivariate, and machine learning models. Geoenvironmental Disasters, 12(1). https://doi.org/10.1186/s40677-024-00307-3
Cordero, J. M., & Mateos-Romero, L. (2025). Exploring the relationship between students´ experiences with online payment methods and financial competencies using a Bayesian nonparametric approach. Large-Scale Assessments in Education, 13(1). https://doi.org/10.1186/s40536-025-00239-w
Gao, R., Cui, S., Wang, Y., & Xu, W. (2025). Predicting financial distress in high-dimensional imbalanced datasets: A multi-heterogeneous self-paced ensemble learning framework. Financial Innovation, 11(1). https://doi.org/10.1186/s40854-024-00745-w
Geetha, S., Elakiya, E., Kanmani, R. S., & Das, M. K. (2025). High-performance fake review detection using pretrained DeBERTa optimized with Monarch Butterfly paradigm. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-89453-8
Ghoorah, U., Mariyani-Squire, E., & Zoha Amin, S. (2025). Relationships between financial transparency, trust, and performance: An examination of donors’ perceptions. Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-04640-2
Jiang, K., Chen, L., Li, J., & Du, X. (2025). The risk effects of corporate digitalization: Exacerbate or mitigate? Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-04628-y
Johari, M. F., Chiew, K. L., Hosen, A. R., Yong, K. S. C., Khan, A. S., Abbasi, I. A., & Grzonka, D. (2025). Key insights into recommended SMS spam detection datasets. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-92223-1
Lai, J. H. J., Ireland, P., Nguyen, D., Woodbury, A., & Pacey, V. (2025). The use and experience of the national disability insurance scheme for Australians with skeletal dysplasia: A mixed-methods study. Orphanet Journal of Rare Diseases, 20(1). https://doi.org/10.1186/s13023-025-03630-6
Lee, S., & Nguyen, T. T. (2025). Prioritizing public service investments and analyzing factors affecting willingness to pay for public services during the COVID-19 pandemic: A case study of rural areas in Chungnam Province, South Korea. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-00887-6
Li, T., Wang, Z., & Shi, P. (2025). Within-project and cross-project defect prediction based on model averaging. Scientific Reports, 15(1). https://doi.org/10.1038/s41598- 025-90832-4
Lin, B., & Xie, Y. (2025). How does digital finance drive energy transition? A green investment-based perspective. Financial Innovation, 11(1). https://doi.org/10.1186/s40854-025-00772-1
Lin, Y.-C., Padliansyah, R., Lu, Y.-H., & Liu, W.-R. (2025). Bankruptcy prediction: Integration of convolutional neural networks and explainable artificial intelligence techniques. International Journal of Accounting Information Systems, 56. https://doi.org/10.1016/j.accinf.2025.100744
Lu, K., & Shi, C. (2025). Why do travelers discontinue using integrated ride-hailing platforms? The role of perceived value and perceived risk. Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-04683-5
Martin-Melero, I., Gomez-Martinez, R., Medrano-Garcia, M. L., & Hernandez-Perlines, F. (2025). Comparison of sectorial and financial data for ESG scoring of mutual funds with machine learning. Financial Innovation, 11(1). https://doi.org/10.1186/s40854-024-00719-y
Miao, Z., Elizalde, B., Deshmukh, S., Kitzes, J., Wang, H., Dodhia, R., & Ferres, J. L. (2025). Multi-modal Language models in bioacoustics with zero-shot transfer: A case study. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-89153-3
Moreh, F., Hasan, Y., Rizvi, Z. H., Tomforde, S., & Wuttke, F. (2025). Hybrid neural network method for damage localization in structural health monitoring. Scientific Reports,
15(1). https://doi.org/10.1038/s41598-025-92396-9
Nazneen, A., Qazi, S., Ali, I. S., Saleem, I., Safdar, U., & Arafat, M. Y. (2025). Measuring the impact of intellectual capital on the firm’s financial performance: Evidence from Indian public sector companies. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-00827-4
Ogunbode, T. O., Esan, V. I., Ayegboyin, M. H., Ogunlaran, O. M., Sangoyomi, E. T., & Akande, J. A. (2025). Analysis of farmers’ perceptions on sustainable sweet orange farming in Nigeria amid climate change. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-90056-6
Phan, Q. H. (2025). Cost-Benefit Analysis of Renewable Energy Adoption in Small and Medium Enterprises (SMEs) in Indonesia. Advanced Business Journal, 1(1), 18-24.
Rajamony, R. K., Sridhar, K., Kalidasan, B., Mishra, R., Farade, R. A., Megalingam, A., Raj M, J. I., Nur-E-Alam, M., & Abedin, T. (2025). Cutting-edge cooling techniques for photovoltaic systems: A comprehensive review. Interactions, 246(1). https://doi.org/10.1007/s10751-025-02267-y
Roy, J. K., & Vasa, L. (2025). Financial technology and environmental, social, and governance in sustainable finance: A bibliometric and thematic content analysis. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-00934-2
Saiyed, S. A. H. I. L. A. L. I. (2025). Linking Corporate Social Responsibility and Self-Determination Theory: Driving Employee Motivation, Engagement, and Organizational Performance in India. Advanced Business Journal, 1(1), 32-46.
Samir, A. A., Elamir, A. H., Basyouni Helal, M., Goudy, Y., Elbarbary, K., El-Mezayen, M., Abo-Elenien, W., Abdelazim, E. H., Mabrouk, M. A., El-Tonbary, M. A., Ibrahim, S. Y., Abdelazem, I. E., Osama, O., Fathy, A. K., Lotfy, A., Marei, E. M., El-Saeed, M. M., Attallah, R. M., Salah, A. W., … Abdelsayed, K. (2025). Sociodemographic, lifestyle, and psychological factors as controllable predictors of academic self-efficacy after reforming a medical education system; the Egyptian Nationwide experience. BMC Medical Education, 25(1). https://doi.org/10.1186/s12909-025-06805-8
Sankova, M. V., Nikolenko, V. N., Litvinova, T. M., Volel, B. A., Oganesyan, M. V., Rizaeva,
N. A., Vovkogon, A. D., Sankov, S. V., Bulygin, K. V., Zharikova, T. S., Sankov, A. V., Panas, A., Pontes-Silva, A., & Zharikov, Y. O. (2025). Effects of the COVID-19 pandemic on the health of medical students transitioning from traditional education to distance learning: A prospective cohort. BMC Medical Education, 25(1). https://doi.org/10.1186/s12909-024-06407-w
Sibomana, O., Hakayuwa, C. M., Obianke, A., Gahire, H., Munyantore, J., & Chilala, M. M. (2025). Diagnostic accuracy of ECG smart chest patches versus PPG smartwatches for atrial fibrillation detection: A systematic review and meta-analysis. BMC Cardiovascular Disorders, 25(1). https://doi.org/10.1186/s12872-025-04582-2
Stephan, T., Paramana, P. P. D., Lin, C.-C., Agarwal, S., & Verma, R. (2025). Federated learning-driven IoT system for automated freshness monitoring in resource-constrained vending carts. Journal of Big Data, 12(1). https://doi.org/10.1186/s40537-025- 01063-3
Phattanaviroj, T., & Pattaradej, R. (2025). Green Supply Chain Management and Its Impact on Firm Competitiveness in Emerging Markets. Advanced Business Journal, 1(1), 1-10.
Vergil, H., Mursal, M., Kaplan, M., & Khan, A. U. I. (2025). The Causal Relationship between Public Investment in Renewable Energy and Climate Change Performance Index. International Journal of Energy Economics and Policy, 15(1), 121–130. https://doi.org/10.32479/ijeep.17308
Vijayan, S., & Chowdhary, C. L. (2025). A hybrid feature optimized CNN for rice crop disease prediction. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025- 92646-w
Wang, R. Z., Cummins, J. S., Syed, M., Stroev, N., Pastras, G., Sakellariou, J., Tsintzos, S., Askitopoulos, A., Veraldi, D., Calvanese Strinati, M., Gentilini, S., Pierangeli, D., Conti, C., & Berloff, N. G. (2025). Efficient computation using spatial-photonic Ising machines with low-rank and circulant matrix constraints. Communications Physics,
8(1). https://doi.org/10.1038/s42005-025-01987-5
Wang, Z. (2025). Application of CNN-based financial risk identification and management convolutional neural networks in financial risk. Systems and Soft Computing, 7. https://doi.org/10.1016/j.sasc.2025.200215
Wang, Z., Sun, Q., Zhang, X., Hu, Z., Chen, J., Zhong, C., & Li, H. (2025). CUGUV: A
Benchmark Dataset for Promoting Large-Scale Urban Village Mapping with Deep Learning Models. Scientific Data, 12(1). https://doi.org/10.1038/s41597-025- 04701-w
Warrenc, C., & Neary, B. (2025). A Marriage of Sun, Farmland, and Technology: How artificial intelligence (AI) can boost community support, financial returns, and performance of agrivoltaics projects. EPRI Journal, 1, 5–8.
Wei, D., Wang, Z., Qiu, M., Yu, J., Yu, J., Jin, Y., Sha, X., & Ouyang, K. (2025). Multiple objectives escaping bird search optimization and its application in stock market prediction based on a transformer model. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-88883-8
Zhang, S., Zhang, Q., Wang, M., Tang, X., Lu, X., & Huang, W. (2025). Key drivers of medical crowdfunding success: A comprehensive analysis of 84,712 projects. Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-024-04160-5
Zhou, Y., Xie, C., Wang, G.-J., Gong, J., & Zhu, Y. (2025). Forecasting cryptocurrency volatility: A novel framework based on the evolving multiscale graph neural network. Financial Innovation, 11(1). https://doi.org/10.1186/s40854-025-00768-x
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ming Sheng Fang (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.

