Research on Typical Models and Development Strategies of Mass Customization in China

doi:10.3901/JME.2025.10.512

Abstract

Abstract: Mass customization is revolutionarily different from the traditional production mode. On the one hand, it provides support for manufacturing enterprises to realize the synergy between economies of scope and economies of scale. On the other hand, it is not only influenced by technology-push and demand-pull factors, but also requires active government guidance due to problems such as innovation system failure and market failure. Drawing on the value co-creation theory, this study firstly constructs a framework for analyzing mass customization, and then distinguishes three typical mass customization models and analyzes relevant cases. Thirdly, it discusses the driving factors for mass customization from the perspectives of technology-push, demand-pull, and policy-promotion. Finally, countermeasure suggestions are provided for the development and popularization of the mass customization in China, aiming to promote the wide-based manufacturing transformation in China’s industrial sectors.

Key words: mass customization, value co-creation, technology-push, demand-pull, policy-promotion

CLC Number:

C93
TP399

JI Huanyong, MIAO Zhongzhen, WANG Pengjing, GAN Xiang, WANG Qiyue, ZANG Jiyuan. Research on Typical Models and Development Strategies of Mass Customization in China[J]. Journal of Mechanical Engineering, 2025, 61(10): 512-522.

References

[1] 周济. 以智能制造为主攻方向推进新型工业化[J]. 中国工业和信息化，2023(11)：40-44. ZHOU Ji. Promoting new industrialization with intelligent manufacturing as the main direction[J]. China Industry & Information Technology，2023(11)：40-44.
[2] 臧冀原，季桓永，黄庆学. 数智化赋能传统产业转型升级[J]. 中国科学院院刊，2024，39(7)：1183-1190. ZANG Jiyuan，JI Huanyong，HUANG Qingxue. Empowering traditional industries with digital intelligence for transformation and upgrading[J]. Bulletin of Chinese Academy of Sciences，2024，39(7)：1183-1190.
[3] 周济，李培根. 智能制造导论[M]. 北京：高等教育出版社，2024. ZHOU Ji，LI Peigen. Introduction to intelligent manufacturing[M]. Beijing：Higher Education Press，2024.
[4] 肖人彬. 大规模个性化定制：大规模个性化的新发展[J]. 计算机集成制造系统，2023，29(12)：4215-4226. XIAO Renbin. Massive personalized customization：New development of mass personalization[J]. Computer Integrated Manufacturing Systems，2023，29(12)：4215-4226.
[5] FRANK A G，MENDES G H S，AYALA N F，et al. Servitization and Industry 4.0 convergence in the digital transformation of product firms：A business model innovation perspective[J]. Technological Forecasting and Social Change，2019，141：341-351.
[6] 姚锡凡，马南峰，张存吉，等. 以人为本的智能制造：演进与展望[J]. 机械工程学报，2022，58(18)：2-15.YAO Xifan，MA Nanfeng，ZHANG Cunji，et al. Human-centric smart manufacturing：Evolution and outlook[J]. Journal of Mechanical Engineering，2022，58(18)：2-15.
[7] 马南峰，姚锡凡，陈飞翔，等. 面向工业5.0的人本智造[J]. 机械工程学报，2022，58 (18)：88-102.MA Nanfeng，YAO Xifan，CHEN Feixiang，et al. Human-centric smart manufacturing for industry 5.0[J]. Journal of Mechanical Engineering，2022，58(18)：88-102.
[8] HU S J. Evolving paradigms of manufacturing：From mass production to mass customization and personalization[J]. Procedia CIRP，2013(7)：3-8.
[9] JOST P J，SÜSSER T. Company-customer interaction in mass customization[J]. International Journal of Production Economics，2020，220：107454.
[10] GUNASEKARAN A，YUSUF Y Y，ADELEYE E O，et al. Agile manufacturing：An evolutionary review of practices[J]. International Journal of Production Research，2019，57(15-16)：5154-5174.
[11] HAEFNER N，WINCENT J，PARIDA V，et al. Artificial intelligence and innovation management：A review，framework，and research agenda[J]. Technological Forecasting and Social Change，2021，162：120392.
[12] RAJ A，DWIVEDI G，SHARMA A，et al. Barriers to the adoption of industry 4.0 technologies in the manufacturing sector：An inter-country comparative perspective[J]. International Journal of Production Economics，2020，224：107546.
[13] STORNELLI A，OZCAN S，SIMMS C. Advanced manufacturing technology adoption and innovation：A systematic literature review on barriers，enablers，and innovation types[J]. Research Policy，2021，50(6)：104229.
[14] CUGNO M，CASTAGNOLI R，BÜCHI G. Openness to Industry 4.0 and performance：The impact of barriers and incentives[J]. Technological Forecasting and Social Change，2021，168：120756.
[15] ZHOU Y，ZANG J Y，MIAO Z Z，et al. Upgrading pathways of intelligent manufacturing in China：Transitioning across technological paradigms[J]. Engineering，2019，5(4)：691-701.
[16] 周济. 提升制造业产业链水平加快建设现代产业体系[J]. 中国工业和信息化，2019(12)：38-41. ZHOU Ji. Improve the level of manufacturing industry chain and accelerate the construction of modern industrial system[J]. China Industry & Information Technology，2019(12)：38-41.
[17] 刘征驰，高翔宇，陈文武，等. 数字技术跃迁与企业全要素生产率—从自动化到智能化的比较分析[J]. 经济评论，2024(4)：73-89. LIU Zhengchi，GAO Xiangyu，CHEN Wenwu，et al. The transition of digital technology and the total factor productivity of enterprises：A comparative analysis from automation to intelligence[J]. Economic Review，2024(4)：73-89.
[18] 周源. 制造范式升级期共性使能技术扩散的影响因素分析与实证研究[J]. 中国软科学，2018(1)：19-32. ZHOU Yuan. Empirical study on influencing factors of generic enabling technologies’ diffusion during the period of manufacturing paradigm shift[J]. China Soft Science，2018(1)：19-32.
[19] XU G，ZHOU Y，JI H. How can government promote technology diffusion in manufacturing paradigm shift? Evidence from China[J]. IEEE Transactions on Engineering Management，2020，70(4)：1547-1559.
[20] 陈录城，鲁效平，盛国军，等. 大规模个性化定制研究综述[J]. 新型工业化，2023，13(10)：11-21. CHEN Lucheng，LU Xiaoping，SHENG Guojun，et al. A review of research on mass personalized customization[J]. The Journal of New Industrialization，2023，13(10)：11-21.
[21] 肖人彬，侯俊东，鲁效平，等. 大规模个性化定制的价值涌现原理—价值共创的新形态[J]. 南昌工程学院学报，2024，43(2)：1-8. XIAO Renbin，HOU Jundong，LU Xiaoping，et al. Value emergence principle of massive personalized customization：New form of value co-creation[J]. Journal of Nanchang Institute of Technology，2024，43(2)：1-8.
[22] TURNER F，MERLE A，GOTTELAND D. Enhancing consumer value of the co-design experience in mass customization[J]. Journal of Business Research，2020，117：473-483.
[23] ABBATE T，CODINI A P，AQUILANI B. Knowledge co-creation in open innovation digital platforms：Processes，tools and services[J]. Journal of Business & Industrial Marketing，2019，34(7)：1434-1447.
[24] 李树文，罗瑾琏，胡文安. 从价值交易走向价值共创：创新型企业的价值转型过程研究[J]. 管理世界，2022，38(3)：125-145.LI Shuwen，LUO Jinlian，HU Wenan. From value transaction to value co-creation：Research on the value transformation process of innovative enterprises[J]. Management World，2022，38(3)：125-145.
[25] DUANMU J L，BU M，PITTMAN R. Does market competition dampen environmental performance? Evidence from China[J]. Strategic Management Journal，2018，39(11)：3006-3030.
[26] WANG Y，MA H S，YANG J H，et al. Industry 4.0：A way from mass customization to mass personalization production[J]. Advances in Manufacturing，2017，5：311-320.
[27] PALLANT J L，SANDS S，KARPEN I O. The 4Cs of mass customization in service industries：A customer lens[J]. Journal of Services Marketing，2020，34(4)：499-511.
[28] 杨青海，祁国宁. 大批量定制的机遇与挑战[J]. CAD/CAM与制造业信息化，2007(8)：18-21. YANG Qinghai，QI Guoning. Opportunities and challenges of mass customization[J]. Intelligent Manufacturing，2007(8)：18-21.
[29] ISMAIL H，REID I，MOONEY J，et al. How small and medium enterprises effectively participate in the mass customization game[J]. IEEE Transactions on Engineering Management，2007，54(1)：86-97.
[30] 杨青海，祁国宁. 大批量定制原理[J]. 机械工程学报，2007(11)：89-97. YANG Qinghai，QI Guoning. The principles of mass customization[J]. Journal of Mechanical Engineering，2007(11)：89-97.
[31] KUO T C. Mass customization and personalization software development：A case study eco-design product service system[J]. Journal of Intelligent Manufacturing，2013，24：1019-1031.
[32] BORTOLINI M，FERRARI E，GALIZIA F G，et al. An optimisation model for the dynamic management of cellular reconfigurable manufacturing systems under auxiliary module availability constraints[J]. Journal of Manufacturing Systems，2021，58：442-451.
[33] MOURTZIS D. Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era[J]. Logistics Research，2016，9：1-20.
[34] LACROIX R，SEIFERT R W，TIMONINA-FARKAS A. Benefiting from additive manufacturing for mass customization across the product life cycle[J]. Operations Research Perspectives，2021，8：100201.
[35] LV Y，XU X，WANG L. Smart manufacturing process and system automation–A critical review of the standards and envisioned scenarios[J]. Journal of Manufacturing Systems，2020，56：312-325.
[36] GUO L，CHEN S，ALLEN J K，et al. A framework for designing the customer-order decoupling point to facilitate mass customization[J]. Journal of Mechanical Design，2021，143(2)：022002.
[37] JAMES C D，MONDAL S. Optimization of decoupling point position using metaheuristic evolutionary algorithms for smart mass customization manufacturing[J]. Neural Computing and Applications，2021，33(17)：11125-11155.
[38] WANG Z，TAO X，ZENG X，et al. Design of customized garments towards sustainable fashion using 3D digital simulation and machine learning-supported human-product interactions[J]. International Journal of Computational Intelligence Systems，2023，16(1)：16.
[39] 肖人彬，林文广，赖荣燊，等. 数据驱动的产品大规模个性化设计研究[J]. 机械设计，2021，38(10)：1-14. XIAO Renbin，LIN Guangwen，LAI Rongshen，et al. Research on the data-driven product design for mass personalization[J]. Journal of Machine Design，2021，38(10)：1-14.
[40] MIASKIEWICZ T，KOZAR K A. Personas and user-centered design：How can personas benefit product design processes?[J]. Design Studies，2011，32(5)：417-430.
[41] TAO F，CHENG J，QI Q，et al. Digital twin-driven product design，manufacturing and service with big data[J]. The International Journal of Advanced Manufacturing Technology，2018，94：3563-3576.
[42] TSANG Y P，WU C H，LIN K Y，et al. Unlocking the power of big data analytics in new product development：An intelligent product design framework in the furniture industry[J]. Journal of Manufacturing Systems，2022，62：777-791.
[43] ZHENG P，XU X，CHEN C H. A data-driven cyber-physical approach for personalised smart，connected product co-development in a cloud-based environment[J]. Journal of Intelligent Manufacturing，2020，31(1)：3-18.
[44] 肖人彬，程贤福，陈诚，等. 基于公理设计和设计关联矩阵的产品平台设计新方法[J]. 机械工程学报，2012，48(11)：94-103. XIAO Renbin，CHENG Xianfu，CHEN Cheng，et al. New approach to product platform design based on axiomatic design and design relationship matrix[J]. Journal of Mechanical Engineering，2012，48(11)：94-103.
[45] WANG Y，TSENG M M. A Naïve Bayes approach to map customer requirements to product variants[J]. Journal of Intelligent Manufacturing，2015，26(3)：501-509.
[46] JIANG Z，WEN H，HAN F，et al. Data-driven generative design for mass customization：A case study[J]. Advanced Engineering Informatics，2022，54：101786.
[47] ZHOU J，ZHOU Y H，WANG B C，et al. Human-cyber- physical systems (HCPSs) in the context of new- generation intelligent manufacturing[J]. Engineering，2019，5(4)：624-636.
[48] 臧冀原，王柏村，孟柳，等. 智能制造的三个基本范式：从数字化制造、“互联网+”制造到新一代智能制造[J]. 中国工程科学，2018，20(4)：13-18. ZANG Jiyuan，WANG Baicun，MENG Liu，et al. Brief analysis on three basic paradigms of intelligent manufacturing[J]. Strategic Study of CAE，2018，20(4)：13-18.
[49] 王柏村，臧冀原，屈贤明，等. 基于人—信息—物理系统(HCPS)的新一代智能制造研究[J]. 中国工程科学，2018，20(4)：29-34. WANG Baicun，ZANG Jiyuan，QU Xianming，et al. Research on new-generation intelligent manufacturing based on human-cyber-physical systems[J]. Strategic Study of CAE，2018，20(4)：29-34.
[50] KUSIA A. Open manufacturing：A design-for-resilience approach[J]. International Journal of Production Research，2020，58(15)：4647-4658.
[51] CHERUBINI A，PASSAMA R，CROSNIER A，et al. Collaborative manufacturing with physical human-robot interaction[J]. Robotics and Computer-Integrated Manufacturing，2016，40：1-13.
[52] NEGAHBAN A，SMITH J S. Simulation for manufacturing system design and operation：Literature review and analysis[J]. Journal of Manufacturing Systems，2014，33(2)：241-261.
[53] YELLES-CHAOUCHE A R，GUREVSKY E，BRAHIMI N，et al. Reconfigurable manufacturing systems from an optimisation perspective：A focused review of literature[J]. International Journal of Production Research，2021，59(21)：6400-6418.
[54] AHELEROFF S，MOSTASHIRI N，XU X，et al. Mass personalisation as a service in industry 4.0：A resilient response case study[J]. Advanced Engineering Informatics，2021，50：101438.
[55] 林文广，赖荣燊，肖人彬. 面向大规模个性化生产的韧性制造系统[J]. 科技导报，2021，39(22)：75-84. LIN Wenguang，LAI Rongshen，XIAO Renbin. Resilient manufacturing systems for mass personalization[J]. Science & Technology Review，2021，39(22)：75-84.
[56] RAMMER C，FERNÁNDEZ G P，CZARNITZKI D. Artificial intelligence and industrial innovation：Evidence from German firm-level data[J]. Research Policy，2022，51(7)：104555.
[57] LEE I，LEE K. The internet of things(IoT)：Applications，investments，and challenges for enterprises[J]. Business Horizons，2015，58(4)：431-440.
[58] CAVALCANTE I M，FRAZZON E M，FORCELLINI F A，et al. A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing[J]. International Journal of Information Management，2019，49：86-97.
[59] PAPAZOGLOU M E，SPANOS Y E. Bridging distant technological domains：A longitudinal study of the determinants of breadth of innovation diffusion[J]. Research Policy，2018，47(9)：1713-1728.
[60] BUHR H，FUNK R J，OWEN-SMITH J. The authenticity premium：Balancing conformity and innovation in high technology industries[J]. Research Policy，2021，50：104085.
[61] 万君，苗仲桢，季桓永，等. 最优区分视角下企业信号传递对技术创新扩散的影响[J]. 科技进步与对策，2023，40(10)：58-66. WAN Jun，MIAO Zhongzhen，JI Huanyong，et al. The influence of firms signals on technological innovation diffusion from the perspective of optimal distinctiveness[J]. Science & Technology Progress and Policy，2023，40(10)：58-66.
[62] STUMMER C，KIESLING E，GÜNTHER M，et al. Innovation diffusion of repeat purchase products in a competitive market：An agent-based simulation approach[J]. European Journal of Operational Research，2015，245(1)，157-167.
[63] KACHE F，SEURING S. Challenges and opportunities of digital information at the intersection of big data analytics and supply chain management[J]. International Journal of Operations & Production Management，2017，37(1)：10-36.
[64] VIAL G. Understanding digital transformation：A review and a research agenda[J]. Managing Digital Transformation，2021：13-66.
[65] BLICHFELDT H，FAULLANT R. Performance effects of digital technology adoption and product & service innovation–A process-industry perspective[J]. Technovation，2021，105：102275.
[66] LIBONI L B，CEZARINO L O，JABBOUR C J C，et al. Smart industry and the pathways to HRM 4.0：Implications for SCM[J]. Supply Chain Management：An International Journal，2019，24(1)：124-146.
[67] LASHITEW A A. When businesses go digital：The role of CEO attributes in technology adoption and utilization during the COVID-19 pandemic[J]. Technological Forecasting and Social Change，2023，189：122324.
[68] DALENOGARE L S，BENITEZ G B，AYALA N F，et al. The expected contribution of Industry 4.0 technologies for industrial performance[J]. International Journal of Production Economics，2018，204：383-394.
[69] GEBAUER H，FLEISCH E，LAMPRECHT C，et al. Growth paths for overcoming the digitalization paradox[J]. Business Horizons，2020，63(3)：313-323.
[70] JI H，MIAO Z，WAN J，et al. Digital transformation and financial performance：The moderating role of entrepreneurs’ social capital[J]. Technology Analysis & Strategic Management，2024，36(8)：1978-1995.
[71] VON GRAEVENITZ G，GRAHAM S J H，MYERS A F. Distance (still) hampers diffusion of innovations[J]. Regional Studies，2022，56(2)：227-241.
[72] VERDOLINI E，GALEOTTI M. At home and abroad：An empirical analysis of innovation and diffusion in energy technologies[J]. Journal of Environmental Economics and Management，2011，61(2)：119-134.
[73] ANTONIOLI D，DI BERARDINO C，ONESTI G. Specialization and KIBS in the Euro area：A vertically integrated sector perspective[J]. International Review of Applied Economics，2020，34(2)：267-290.
[74] WEN J，QUALLS W J，ZENG D. To explore or exploit：The influence of inter-firm R&D network diversity and structural holes on innovation outcomes[J]. Technovation，2021，100：102178.
[75] DE SILVA M，HOWELLS J，MEYER M. Innovation intermediaries and collaboration：Knowledge-based practices and internal value creation[J]. Research Policy，2018，47(1)：70-87.
[76] WOOLTHUIS R K，LANKHUIZEN M，GILSING V. A system failure framework for innovation policy design[J]. Technovation，2005，25(6)：609-619.
[77] HUGUENIN A，JEANNERAT H. Creating change through pilot and demonstration projects：Towards a valuation policy approach[J]. Research Policy，2017，46(3)：624-635.
[78] 周楠，杨珍，赵晓旭，等. 京津冀区域科技创新政策协同演变：2011—2021年[J]. 中国科技论坛，2023(8)：27-38. ZHOU Nan，YANG Zhen，ZHAO Xiaoxu，et al. The evolution of regional science and technology innovation policy synergy in Beijing-Tianjin-Hebei region：2011—2021[J]. Forum on Science and Technology in China，2023(8)：27-38.
[79] HOWELL S T. Joint ventures and technology adoption：A Chinese industrial policy that backfired[J]. Research Policy，2018，47(8)：1448-1462.
[80] GAO Y，HU Y，LIU X，et al. Can public R&D subsidy facilitate firms’ exploratory innovation? The heterogeneous effects between central and local subsidy programs[J]. Research Policy，2021，50(4)：104221.