Strategic Development of a Knitting Small Medium Enterprise Using Swot and QSPM Analysis
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Micro, Small, and Medium Enterprises (MSMEs) play a vital role in Indonesia’s economic development. However, knitting-based MSMEs continue to face various challenges, including limited digital marketing capabilities, fluctuating revenues, increasing competition, and rapidly changing fashion trends. This study aimed to formulate and prioritize business development strategies for a knitting MSME in Kampoeng Radjoet Binongjati, Bandung, using SWOT analysis and the Quantitative Strategic Planning Matrix (QSPM). Internal factors were identified using the Feasibility Model for SMEs, which covers supply chain, production, value proposition, marketing, and performance dimensions, while external factors were analyzed using the PESTEL framework. These frameworks were applied to provide a structured and theoretically grounded approach to factor identification, addressing a common limitation in previous MSME-focused SWOT studies that relied on ad hoc factor selection. The Internal Factor Analysis Summary (IFAS) results showed a strength score of 3.102 and a weakness score of 3.559, while the External Factor Analysis Summary (EFAS) results indicated an opportunity score of 3.503 and a threat score of 2.623. The business was positioned in the Weakness–Opportunity (WO) quadrant with coordinates of (−0.457; +0.880), indicating a turnaround strategy orientation. The QSPM analysis identified the optimization of social media and e-commerce platform performance as the priority strategy, with a Total Attractiveness Score (TAS) of 11.54. This study demonstrates that applying the Feasibility Model for SMEs as a structured basis for identifying internal factors can enhance the analytical rigor of SWOT-QSPM analysis in the context of creative industry MSMEs.
Abd Rahman, A., Singhry, H. B., Hanafiah, M. H., & Abdul, M. (2017). Influence of perceived benefits and traceability system on the readiness for Halal Assurance System implementation among food manufacturers. Food Control, 73, 1318–1326.
Ayoub, H. S., & Sopuru, J. C. (2026). Reconfiguring strategic capabilities in the digital era: How AI-enabled dynamic capability, data-driven culture, and organizational learning shape firm performance. Sustainability, 18(3), 1157.
Benzaghta, M. A., et al. (2021). SWOT analysis applications: An integrative literature review. Journal of Global Business Insights, 6(1), 55–73.
Chumaidiyah, E., Fauzia, P. M., & Abdulbasah Kamil, A. (2024). Enhancement of SME feasibility through the integration of BMC, functional organization, and SCM. Cogent Business & Management.
Cong, L. W., Liang, T., Zhang, X., & Zhu, W. (2025). Textual factors: A scalable, interpretable, and data-driven approach to analyzing unstructured information. Management Science, 71(12), 10727–10739.
David, F. R., David, F. R., & David, M. E. (2020). Strategic management: A competitive advantage approach (17th ed.). Pearson.
Denaro, N., Merlano, M. C., & Russi, E. G. (2016). Follow-up in head and neck cancer: Do more does it mean do better? A systematic review and our proposal based on our experience. Clinical and Experimental Otorhinolaryngology, 9(4), 287–297.
Dong, L., Jiang, P., & Xu, F. (2023). Impact of traceability technology adoption in food supply chain networks. Management Science, 69(3), 1518–1535.
Fairfield, T., & Charman, A. E. (2017). Explicit Bayesian analysis for process tracing: Guidelines, opportunities, and caveats. Political Analysis, 25(3), 363–380.
Gürel, M., & Tat, M. (2021). SWOT analysis: A theoretical review. Journal of International Social Research, 15(82), 1–8.
Hasan, M. M., & Shehun, M. T. F. (2022). Implementing sustainable supply chain practices in global apparel retail: A systematic review of current trends. ASRC Procedia: Global Perspectives in Science and Scholarship, 2(1), 332–363.
Katadata Insight Center. (2024). Preferensi konsumen terhadap produk lokal Indonesia 2024. Katadata.
Kay, A., & Baker, P. (2015). What can causal process tracing offer to policy studies? A review of the literature. Policy Studies Journal, 43(1), 1–21.
Lievens, F., & Sackett, P. R. (2017). The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures. Journal of Applied Psychology, 102(1), 43.
Lobo, C. A., Marinho, A., Santos Pereira, C., Azevedo, M., & Moreira, F. (2025). The role of leadership and strategic alliances in innovation and digital transformation for sustainable entrepreneurial ecosystems: A comprehensive analysis of the existing literature. Sustainability, 17(13), 6182.
Miric, M., Jia, N., & Huang, K. G. (2023). Using supervised machine learning for large-scale classification in management research: The case for identifying artificial intelligence patents. Strategic Management Journal, 44(2), 491–519.
Perera, M. (2022). The PESTEL analysis framework: A comprehensive review. International Journal of Management Studies, 11(2), 78–89.
Rangkuti, F. (2021). Analisis SWOT: Teknik membedah kasus bisnis. Gramedia Pustaka Utama.
Sepasgozar, S. M. E., & Davis, S. (2018). Construction technology adoption cube: An investigation on process, factors, barriers, drivers and decision makers using NVivo and AHP analysis. Buildings, 8(6), 74.
Seyi-Lande, O. B., Arowogbadamu, A. A.-G., & Oziri, S. T. (2022). Cross-functional key performance indicator frameworks for driving organizational alignment and sustainable business growth. International Journal of Multidisciplinary Futuristic Development, 1(2), 1–18.
Statista. (2024). Indonesia fashion market outlook 2024. Statista.
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