IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v6y2025i2d10.1007_s43069-025-00463-8.html
   My bibliography  Save this article

Adoption and Impact of Quick Response Manufacturing Across Industry Sector

Author

Listed:
  • N. Nelfiyanti

    (Universitas Muhammadiyah Jakarta)

  • Ahmad Shah Hizam Md Yasir

    (Faculty of Resilience)

  • Nik Mohamed

    (Universiti Malaysia Pahang Al-Sultan Abdullah)

  • M. F. A. Ahmad

    (Universiti Malaysia Pahang Al-Sultan Abdullah)

Abstract

Quick response manufacturing (QRM) is a strategic manufacturing approach aimed at reducing production cycle times to enhance operational efficiency and competitiveness. Industries today face persistent challenges, such as delayed product deliveries, high operating costs, and inefficiencies that hinder productivity and quality. While numerous studies have highlighted the theoretical benefits of QRM, there remains a lack of consolidated evidence on its practical impact across multiple industry sectors. Specifically, there is limited comparative analysis that synthesizes QRM outcomes in diverse contexts, such as precision manufacturing, textiles, and small and medium industries (SMI). This research gap hinders a broader understanding of QRM’s cross-sector applicability and its tangible contributions to production performance. To address this gap, this study evaluates the adoption and impact of QRM across various industry sectors through a comprehensive literature review, analyzing 70 academic articles and industry reports. The research focuses on three critical areas: (1) efficiency in production and delivery, (2) cost reduction, and (3) enhancement of product quality and quantity. Data was sourced from peer-reviewed academic journals, industry case studies, and relevant research reports. The findings reveal that QRM significantly improves on-time delivery by 45% and reduces production backlog by 50%. Additionally, QRM lowers warehousing and inventory costs by 35% and minimizes production downtime costs by 40%. Product quality and quantity improvements include a 30% reduction in defects and a 25% increase in output. This study fills the existing research gap by providing a sector-spanning evaluation of QRM’s effectiveness and concludes that QRM is a highly effective strategy for optimizing manufacturing efficiency, enhancing supply chain operations, and reducing operational costs. It offers valuable insights for industry stakeholders seeking data-driven justifications for adopting QRM, especially in environments where responsiveness and efficiency are critical for competitiveness.

Suggested Citation

  • N. Nelfiyanti & Ahmad Shah Hizam Md Yasir & Nik Mohamed & M. F. A. Ahmad, 2025. "Adoption and Impact of Quick Response Manufacturing Across Industry Sector," SN Operations Research Forum, Springer, vol. 6(2), pages 1-32, June.
    • Handle: RePEc:spr:snopef:v:6:y:2025:i:2:d:10.1007_s43069-025-00463-8
    DOI: 10.1007/s43069-025-00463-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-025-00463-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s43069-025-00463-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ying Wei & Frank Y. Chen & Mark Lee & Houmin Yan & Kenneth Kong & Chi Ho Ng, 2010. "Divide and Conquer: From MTO to ATO/MTO," International Handbooks on Information Systems, in: T. C. Edwin Cheng & Tsan-Ming Choi (ed.), Innovative Quick Response Programs in Logistics and Supply Chain Management, pages 331-354, Springer.
    2. Gérard P. Cachon & Robert Swinney, 2011. "The Value of Fast Fashion: Quick Response, Enhanced Design, and Strategic Consumer Behavior," Management Science, INFORMS, vol. 57(4), pages 778-795, April.
    3. Mandyam Srinivasan & S. Viswanathan, 2010. "Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems," IISE Transactions, Taylor & Francis Journals, vol. 42(6), pages 379-391.
    4. Maico Roris Severino & Moacir Godinho Filho, 2019. "POLCA system for supply chain management: simulation in the automotive industry," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1271-1289, March.
    5. Fernandes, Nuno Octavio & do Carmo-Silva, Silvio, 2006. "Generic POLCA--A production and materials flow control mechanism for quick response manufacturing," International Journal of Production Economics, Elsevier, vol. 104(1), pages 74-84, November.
    6. Choi, Tsan-Ming & Sethi, Suresh, 2010. "Innovative quick response programs: A review," International Journal of Production Economics, Elsevier, vol. 127(1), pages 1-12, September.
    7. Godinho Filho, Moacir & Marchesini, Antonio Gilberto & Riezebos, Jan & Vandaele, Nico & Ganga, Gilberto Miller Devós, 2017. "The application of Quick Response Manufacturing practices in Brazil, Europe, and the USA: An exploratory study," International Journal of Production Economics, Elsevier, vol. 193(C), pages 437-448.
    8. Hau-Ling Chan & Bin Shen & Yajun Cai, 2018. "Quick response strategy with cleaner technology in a supply chain: coordination and win-win situation analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3397-3408, May.
    9. Moacir Godinho Filho & Antonio Gilberto Marchesini & Jan Riezebos & Nico Vandaele & Gilberto Miller Devós Ganga, 2017. "The extent of knowledge of Quick Response Manufacturing principles: an exploratory transnational study," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 4891-4911, September.
    10. Sanjay Bhasin, 2024. "Constituent performance management ingredients necessary to gauge the performance of a lean manufacturing organisation," International Journal of Business Performance Management, Inderscience Enterprises Ltd, vol. 25(3), pages 345-368.
    11. Wanzhu Wang & Qazi Salman Khalid & Muhammad Abas & Hao Li & Shakir Azim & Abdur Rehman Babar & Waqas Saleem & Razaullah Khan, 2021. "Implementation of POLCA Integrated QRM Framework for Optimized Production Performance—A Case Study," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    12. Yang, Daojian & Qi, Ershi & Li, Yajiao, 2015. "Quick response and supply chain structure with strategic consumers," Omega, Elsevier, vol. 52(C), pages 1-14.
    13. Anbesh Jamwal & Ankur Aggarwal & Sumit Gupta & Parul Sharma, 2019. "A study on the barriers to lean manufacturing implementation for small-scale industries in Himachal region (India)," International Journal of Intelligent Enterprise, Inderscience Enterprises Ltd, vol. 6(2/3/4), pages 393-407.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Jian & Duan, Yongrui, 2020. "Pricing, ordering, and quick response for online sellers in the presence of consumer disappointment aversion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    2. Dong, Junfeng & Wu, Desheng Dash, 2019. "Two-period pricing and quick response with strategic customers," International Journal of Production Economics, Elsevier, vol. 215(C), pages 165-173.
    3. Choi, Tsan-Ming & Chen, Yue & Chung, Sai Ho, 2019. "Online-offline fashion franchising supply chains without channel conflicts: Choices on postponement and contracts," International Journal of Production Economics, Elsevier, vol. 215(C), pages 174-184.
    4. Qiu, Ruozhen & Sun, Yue & Zhou, Hongcheng & Sun, Minghe, 2023. "Dynamic pricing and quick response of a retailer in the presence of strategic consumers: A distributionally robust optimization approach," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1270-1298.
    5. Matthias Thürer & Nuno O. Fernandes & Mark Stevenson & Cristovao Silva & Silvio Carmo-Silva, 2019. "POLC-A: an assessment of POLCA’s authorization element," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2435-2447, August.
    6. Chen Tian & Tiaojun Xiao, 2017. "Profit of a Supply Chain versus its Decentralization in the Presence of Strategic Customers," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1647-1670, November.
    7. Yanan Song & Xiaobo Zhao, 2017. "A newsvendor problem with boundedly rational strategic customers," International Journal of Production Research, Taylor & Francis Journals, vol. 55(1), pages 228-243, January.
    8. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    9. Yang, Daojian & Qi, Ershi & Li, Yajiao, 2015. "Quick response and supply chain structure with strategic consumers," Omega, Elsevier, vol. 52(C), pages 1-14.
    10. Ye, Taofeng & Sun, Hao, 2016. "Price-setting newsvendor with strategic consumers," Omega, Elsevier, vol. 63(C), pages 103-110.
    11. Wang, Hua & Dong, Dayong & Guan, Zhenzhong & Bai, Chunguang, 2021. "The impact of quantity commitment with disappointment-averse and elation-seeking consumers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    12. Fernando José Gómez Paredes & Moacir Godinho Filho & Matthias Thürer & Nuno O. Fernandes & Charbel José Chiappeta Jabbour, 2022. "Factors for choosing production control systems in make-to-order shops: a systematic literature review," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 639-674, March.
    13. Shuyun Ren & Hau-Ling Chan & Pratibha Ram, 2017. "A Comparative Study on Fashion Demand Forecasting Models with Multiple Sources of Uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 335-355, October.
    14. Choi, Tsan-Ming, 2020. "Internet based elastic logistics platforms for fashion quick response systems in the digital era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    15. Feng Yang & Junjun Kong & Minyue Jin, 2019. "Two-Period Pricing with Selling Effort in the Presence of Strategic Customers," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(03), pages 1-21, June.
    16. Khouja, Moutaz & Christou, Eliana & Stylianou, Antonis, 2020. "A heuristic approach to in-season capacity allocation in a multi-product newsvendor model," Omega, Elsevier, vol. 95(C).
    17. repec:ers:journl:v:xxiv:y:2021:i:3b:p:47-60 is not listed on IDEAS
    18. Tsan-Ming Choi, 2018. "Impacts of retailer’s risk averse behaviors on quick response fashion supply chain systems," Annals of Operations Research, Springer, vol. 268(1), pages 239-257, September.
    19. Hubert Pun & Gregory D. DeYong, 2017. "Competing with Copycats When Customers Are Strategic," Manufacturing & Service Operations Management, INFORMS, vol. 19(3), pages 403-418, July.
    20. Shi, Xiutian & Shen, Bin, 2019. "Product upgrading or not: R&D tax credit, consumer switch and information updating," International Journal of Production Economics, Elsevier, vol. 213(C), pages 13-22.
    21. Serel, Doğan A., 2012. "Multi-item quick response system with budget constraint," International Journal of Production Economics, Elsevier, vol. 137(2), pages 235-249.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:snopef:v:6:y:2025:i:2:d:10.1007_s43069-025-00463-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.