IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v176y2022ics0040162521008994.html
   My bibliography  Save this article

Requirement-driven evolution and strategy-enabled service design for new customized quick-response product order fulfillment process

Author

Listed:
  • Lee, Ching-Hung
  • Li, Li
  • Li, Fan
  • Chen, Chun-Hsien

Abstract

Under the digital transformation era, technologies such as Cyber-physical systems, the Internet of things, and Artificial Intelligence are increasingly mature, making it possible to transform from traditional factories to smart factories. During the transformation, building a communication channel between customer requirements and production capacity to realize customized order services with low volume and high-mix production is critical. This study proposes a novel requirement-driven and strategy-based model to achieve the quick response order placement and production configuration services through three phases, that is, (1) requirement-based service diagnosis, (2) design strategy generation, and (3) service system conceptualization and evaluation. Firstly, a statistical kano analysis method was proposed to mining customer requirements considering industry contexts. Then, TRIZ evolution trends were modified to design concepts for digital transformation based on key enterprise processes. Finally, a novel service development maturity model was constructed to evaluate the new digital system design. A comprehensive empirical case study of designing “Customized Product Order Fulfillment System” for the laptop production process is conducted to demonstrate this approach. The proposed novel requirement-driven and strategy-based model is expected to provide valuable insights for suggestions on technological trends and forecasting, future diverse and innovative applications in customized order fulfillment scenarios.

Suggested Citation

  • Lee, Ching-Hung & Li, Li & Li, Fan & Chen, Chun-Hsien, 2022. "Requirement-driven evolution and strategy-enabled service design for new customized quick-response product order fulfillment process," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
  • Handle: RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162521008994
    DOI: 10.1016/j.techfore.2021.121464
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521008994
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2021.121464?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. Lin, Shu-Ping & Yang, Chen-Lung & Chan, Ya-hui & Sheu, Chwen, 2010. "Refining Kano's 'quality attributes-satisfaction' model: A moderated regression approach," International Journal of Production Economics, Elsevier, vol. 126(2), pages 255-263, August.
    2. Karan Menon & Hannu Kärkkäinen & Thorsten Wuest, 2020. "Industrial internet platform provider and end-user perceptions of platform openness impacts," Industry and Innovation, Taylor & Francis Journals, vol. 27(4), pages 363-389, April.
    3. Fey,Victor & Rivin,Eugene, 2005. "Innovation on Demand," Cambridge Books, Cambridge University Press, number 9780521826204.
    4. Yixiang Wu & Jianxin Cheng, 2018. "Continuous Fuzzy Kano Model and Fuzzy AHP Model for Aesthetic Product Design: Case Study of an Electric Scooter," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-13, September.
    5. Hyejong Min & Junghwan Yun & Youngjung Geum, 2018. "Analyzing Dynamic Change in Customer Requirements: An Approach Using Review-Based Kano Analysis," Sustainability, MDPI, vol. 10(3), pages 1-17, March.
    6. Shwetank Avikal & Rohit Singh & Rashmi Rashmi, 2020. "QFD and Fuzzy Kano model based approach for classification of aesthetic attributes of SUV car profile," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 271-284, February.
    7. Sayid Albana, Abduh & Frein, Yannick & Hammami, Ramzi, 2018. "Effect of a lead time-dependent cost on lead time quotation, pricing, and capacity decisions in a stochastic make-to-order system with endogenous demand," International Journal of Production Economics, Elsevier, vol. 203(C), pages 83-95.
    8. Ashutosh Pandey & Rajendra Sahu, 2020. "Mapping heritage tourism service quality using the Kano model: a case study of Indian tourism," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 37(2), pages 264-283.
    9. H. C. Yadav & Rajeev Jain & A. R. Singh & P. K. Mishra, 2017. "Kano integrated robust design approach for aesthetical product design: a case study of a car profile," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1709-1727, October.
    10. Arash Shahin & Saeed Abedi & Mohammad Javad Ranjbar & Ahmad Kamali, 2017. "TRIZ and the Kano model: proposing an integrated approach for improving product quality according to customer needs," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 20(3), pages 392-404.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Peng Shao & Runhua Tan & Qingjin Peng & Wendan Yang & Fang Liu, 2023. "An Integrated Method to Acquire Technological Evolution Potential to Stimulate Innovative Product Design," Mathematics, MDPI, vol. 11(3), pages 1-24, January.

    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. Li, Yan-Lai & Tang, Jia-Fu & Chin, Kwai-Sang & Jiang, Yu-Shi & Han, Yi & Pu, Yun, 2011. "Estimating the final priority ratings of engineering characteristics in mature-period product improvement by MDBA and AHP," International Journal of Production Economics, Elsevier, vol. 131(2), pages 575-586, June.
    2. Zhai, Yue & Hua, Guowei & Cheng, Meng & Cheng, T.C.E., 2023. "Production lead-time hedging and order allocation in an MTO supply chain," European Journal of Operational Research, Elsevier, vol. 311(3), pages 887-905.
    3. Xuan Gong & Yunchan Zhu & Rizwan Ali & Ruijin Guo, 2019. "Capturing Associations and Sustainable Competitiveness of Brands from Social Tags," Sustainability, MDPI, vol. 11(6), pages 1-20, March.
    4. Shi‐Woei Lin & Januardi, 2023. "Two‐stage pricing of perishable food supply chain with quality‐keeping and waste reduction efforts," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(3), pages 1749-1766, April.
    5. Amber Batwara & Vikram Sharma & Mohit Makkar & Antonio Giallanza, 2022. "An Empirical Investigation of Green Product Design and Development Strategies for Eco Industries Using Kano Model and Fuzzy AHP," Sustainability, MDPI, vol. 14(14), pages 1-35, July.
    6. Ramzi Hammami & Erfan Asgari & Yannick Frein & Imen Nouira, 2022. "Time- and price-based product differentiation in hybrid distribution with stockout-based substitution," Post-Print hal-03696900, HAL.
    7. Hammami, Ramzi & Frein, Yannick & Nouira, Imen & Albana, Abduh-Sayid, 2022. "On the interplay between local lead times, overall lead time, prices, and profits in decentralized supply chains," International Journal of Production Economics, Elsevier, vol. 243(C).
    8. Junegak Joung & Kiwook Jung & Sanghyun Ko & Kwangsoo Kim, 2018. "Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development," Sustainability, MDPI, vol. 11(1), pages 1-14, December.
    9. Ming-Tsang Lu & Hsi-Peng Lu & Chiao-Shan Chen, 2022. "Exploring the Key Priority Development Projects of Smart Transportation for Sustainability: Using Kano Model," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    10. Pablo Viveros & Enrico Zio & Christopher Nikulin & Raúl Stegmaier & Gloria Bravo, 2014. "Resolving equipment failure causes by root cause analysis and theory of inventive problem solving," Journal of Risk and Reliability, , vol. 228(1), pages 93-111, February.
    11. Peng Shao & Runhua Tan & Qingjin Peng & Wendan Yang & Fang Liu, 2023. "An Integrated Method to Acquire Technological Evolution Potential to Stimulate Innovative Product Design," Mathematics, MDPI, vol. 11(3), pages 1-24, January.
    12. Liu, Zhiqiang & Huang, Yanyi & Huang, Ying & Song, Yiping Amy & Kumar, Ajay, 2022. "How does one-sided versus two-sided customer orientation affect B2B platform’s innovation: Differential effects with top management team status," Journal of Business Research, Elsevier, vol. 141(C), pages 619-632.
    13. Hamid Reza Fazeli & Qingjin Peng, 2023. "Integrated approaches of BWM-QFD and FUCOM-QFD for improving weighting solution of design matrix," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1003-1020, March.
    14. Aijun Liu & Qiuyun Zhu & Xiaohui Ji & Hui Lu & Sang-Bing Tsai, 2018. "Novel Method for Perceiving Key Requirements of Customer Collaboration Low-Carbon Product Design," IJERPH, MDPI, vol. 15(7), pages 1-32, July.
    15. Jianguang Sun & Runhua Tan, 2012. "Method For Forecasting Di Based On Triz Technology System Evolution Theory," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-20.
    16. Hammami, Ramzi & Frein, Yannick & Albana, Abduh S., 2020. "Delivery time quotation and pricing in two-stage supply chains: Centralized decision-making with global and local managerial approaches," European Journal of Operational Research, Elsevier, vol. 286(1), pages 164-177.
    17. Hammami, Ramzi & Asgari, Erfan & Frein, Yannick & Nouira, Imen, 2022. "Time- and price-based product differentiation in hybrid distribution with stockout-based substitution," European Journal of Operational Research, Elsevier, vol. 300(3), pages 884-901.
    18. Nikolić, Vlastimir & Sajjadi, Shahin & Petković, Dalibor & Shamshirband, Shahaboddin & Ćojbašić, Žarko & Por, Lip Yee, 2016. "Design and state of art of innovative wind turbine systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 258-265.
    19. Don P. Clausing & Konstantinos V. Katsikopoulos, 2008. "Rationality in systems engineering: Beyond calculation or political action," Systems Engineering, John Wiley & Sons, vol. 11(4), pages 309-328, December.
    20. Chen, Li-Fei, 2012. "A novel approach to regression analysis for the classification of quality attributes in the Kano model: an empirical test in the food and beverage industry," Omega, Elsevier, vol. 40(5), pages 651-659.

    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:eee:tefoso:v:176:y:2022:i:c:s0040162521008994. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.