The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China

This thesis explores the factors that influence net benefits in the context of intelligent hanging systems for jeans and examines the relationship between user satisfaction and intention to use. Furthermore, it innovatively constructs a new conceptual model aimed at enhancing the net benefits of int...

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Main Author:	YARUI, HUO
Format:	Thesis
Language:	English
Published:	2023
Subjects:	TS Manufactures
Online Access:	http://ir.unimas.my/id/eprint/46010/1/PhD%20Thesis%20Huo%20Yarui%20FACA%20Final_19010082%28signed%29.pdf
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id	my-unimas-ir.46010
record_format	uketd_dc
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	TS Manufactures
spellingShingle	TS Manufactures YARUI, HUO The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China
description	This thesis explores the factors that influence net benefits in the context of intelligent hanging systems for jeans and examines the relationship between user satisfaction and intention to use. Furthermore, it innovatively constructs a new conceptual model aimed at enhancing the net benefits of intelligent hanging systems for jeans. Employing a mixed research methodology, qualitative research involved interviewing 20 participants, including factory managers and direct users of intelligent hanging systems, while quantitative research analyzed questionnaire responses from 2696 direct users of intelligent hanging systems. Qualitative research identified four core categories through three-level coding, which served as independent variables in quantitative research, mutually reinforcing each other and collectively validating the conceptual model of this study. The results reveal that the factors influencing net benefit production include information quality, system quality, service quality, perceived usefulness (independent variables), and user satisfaction and intention to use (mediating variables). Both user satisfaction and intention to use have a significant and positive influence on net benefits, supporting the ten research hypotheses. Consequently, the newly proposed conceptual model for the net benefits of intelligent hanging systems for jeans receives validation. Qualitative research identified four core categories through three-level coding, which served as independent variables in quantitative research, mutually reinforcing each other and collectively validating the conceptual model of this study. The results reveal that the factors influencing net benefit production include information quality, system quality, service quality, perceived usefulness (independent variables), and user satisfaction and intention to use (mediating variables). Both user satisfaction and intention to use have a significant and positive influence on net benefits, supporting the ten research hypotheses. Consequently, this study validates the newly proposed conceptual model for the net benefits of intelligent hanging systems for jeans. This thesis's theoretical contribution is the innovative construction and validation of a new conceptual model for net benefits, while also extending the DMSM theory in the field of jeans production. Additionally, the practical contribution of this study provides insights for jeans manufacturing enterprises to enhance net benefits, particularly in the adoption or efficient utilization of intelligent hanging systems. The findings will help enterprise managers better allocate resources and implement measures to improve net benefits. Furthermore, the output will assist policymakers in scientifically formulating and implementing intelligent production policies, as well as provide guidance for academia, future research endeavors, and improvement initiatives in the field of intelligent manufacturing.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	YARUI, HUO
author_facet	YARUI, HUO
author_sort	YARUI, HUO
title	The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China
title_short	The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China
title_full	The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China
title_fullStr	The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China
title_full_unstemmed	The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China
title_sort	new conceptual model for the net benefits improvement in the intelligent hanging production system for jeans in china
granting_institution	Universiti Malaysia Sarawak (UNIMAS)
granting_department	The Faculty of Applied and Creative Arts (FACA)
publishDate	2023
url	http://ir.unimas.my/id/eprint/46010/1/PhD%20Thesis%20Huo%20Yarui%20FACA%20Final_19010082%28signed%29.pdf
_version_	1811771585292402688
spelling	my-unimas-ir.460102024-09-24T00:54:11Z The New Conceptual Model for the Net Benefits Improvement in the Intelligent Hanging Production System for Jeans in China 2023-07-31 YARUI, HUO TS Manufactures This thesis explores the factors that influence net benefits in the context of intelligent hanging systems for jeans and examines the relationship between user satisfaction and intention to use. Furthermore, it innovatively constructs a new conceptual model aimed at enhancing the net benefits of intelligent hanging systems for jeans. Employing a mixed research methodology, qualitative research involved interviewing 20 participants, including factory managers and direct users of intelligent hanging systems, while quantitative research analyzed questionnaire responses from 2696 direct users of intelligent hanging systems. Qualitative research identified four core categories through three-level coding, which served as independent variables in quantitative research, mutually reinforcing each other and collectively validating the conceptual model of this study. The results reveal that the factors influencing net benefit production include information quality, system quality, service quality, perceived usefulness (independent variables), and user satisfaction and intention to use (mediating variables). Both user satisfaction and intention to use have a significant and positive influence on net benefits, supporting the ten research hypotheses. Consequently, the newly proposed conceptual model for the net benefits of intelligent hanging systems for jeans receives validation. Qualitative research identified four core categories through three-level coding, which served as independent variables in quantitative research, mutually reinforcing each other and collectively validating the conceptual model of this study. The results reveal that the factors influencing net benefit production include information quality, system quality, service quality, perceived usefulness (independent variables), and user satisfaction and intention to use (mediating variables). Both user satisfaction and intention to use have a significant and positive influence on net benefits, supporting the ten research hypotheses. Consequently, this study validates the newly proposed conceptual model for the net benefits of intelligent hanging systems for jeans. This thesis's theoretical contribution is the innovative construction and validation of a new conceptual model for net benefits, while also extending the DMSM theory in the field of jeans production. Additionally, the practical contribution of this study provides insights for jeans manufacturing enterprises to enhance net benefits, particularly in the adoption or efficient utilization of intelligent hanging systems. The findings will help enterprise managers better allocate resources and implement measures to improve net benefits. Furthermore, the output will assist policymakers in scientifically formulating and implementing intelligent production policies, as well as provide guidance for academia, future research endeavors, and improvement initiatives in the field of intelligent manufacturing. Lippincott Williams and Wilkins Ltd 2023-07 Thesis http://ir.unimas.my/id/eprint/46010/ http://ir.unimas.my/id/eprint/46010/1/PhD%20Thesis%20Huo%20Yarui%20FACA%20Final_19010082%28signed%29.pdf text en staffonly https://journals.lww.com/md-journal/fulltext/2023/07280/2023_international_conference_on_life,_health_and.34.aspx phd doctoral Universiti Malaysia Sarawak (UNIMAS) The Faculty of Applied and Creative Arts (FACA) Abulela, M. A. A., & Harwell, M. M. (2020). Data Analysis: Strengthening Inferences in Quantitative Education Studies Conducted by Novice Researchers. Educational Sciences: Theory and Practice, 20(1). https://doi.org/10.12738/jestp.2020.1.005 Aghion, P., Jones, B. F., & Jones, C. I. (2019). Artificial Intelligence and Economic Growth. In The Economics of Artificial Intelligence: An Agenda (Agrawal, A., Gans, J., & Goldfarb, A., 1nd ed.), pp. 237 – 282. Chicago: University of Chicago Press. Aguboshim, F. C. (2021). Adequacy of Sample Size in a Qualitative Case Study and the Dilemma of Data Saturation: A Narrative Review. World Journal of Advanced Research and Reviews, 10(03). Alam, M. K. (2021). A Systematic Qualitative Case Study: Questions, Data Collection, Nvivo Analysis and Saturation. Qualitative Research in Organizations and Management: An International Journal, 16(1). https://doi.org/10.1108/QROM-09-2019-1825 Alharahsheh, H. H., & Pius, A. (2020). A Review of Key Paradigms: Positivism VS Interpretivism. Global Academic Journal of Humanities and Social Science, 2(3), 39–43. https://doi.org/https://gajrc.com/gajhss Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411. https://doi.org/10.1037/0033-2909.103.3.411 Ang, S., & Straub, D. W. (1998). Production and Transaction Economies and IS Outsourcing: A study of the U.S. Banking Industry. MIS Quarterly: Management Information Systems, 22(4), 535–552. https://doi.org/10.2307/249554 Babazadeh, H., Alavidoost, M. H., Fazel Zarandi, M. H., & Sayyari, S. T. (2018). An Enhanced NSGA-II Algorithm for Fuzzy Bi-objective Assembly Line Balancing Problems. Computers and Industrial Engineering, 123, 189–208. https://doi.org/10.1016/j.cie.2018.06.014 Bai, J., Wang, X., & Wang, X. (2018). Application of Single Piece Flow Technology in Sample Clothing Enterprise. Wool Textile Journal, 46(9), 42–45. https://doi.org/10.19333/j.mfkj.2017100210905 Bai, M. (2023). Research on the Key Success Factors of Management Innovation in Tibetan Medicine Enterprises in the Qinghai-Tibet Plateau [Dissertation]. Northwest Minzu University. https://doi.org/10.27408/d.cnki.gxmzc.2023.000485 Balog, A. (2011). Testing a Multidimensional and Hierarchical Quality Assessment Model for Digital Libraries. Studies in Informatics & Control, 20(3), 233–246. https://doi.org/http://dx.doi.org/ Baron, R. M., & Kenny, D. A. (1986). The Moderator-mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037//0022-3514.51.6.1173 Bauschintana, S. & Qi, E. S. (2017). The Theory Frame of Discrete Manufacturing System Layout Optimization Based on Lean Design. Chinese Journal of Systems Science, 25(2), 88–91. https://doi.org/CNKI:SUN:XTBZ.0.2017-02-019 Baxter, P., & Jack, S. (2015). Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers. The Qualitative Report. https://doi.org/10.46743/2160-3715/2008.1573 Benitez, G. B., Ayala, N. F., & Frank, A. G. (2020). Industry 4.0 Innovation Ecosystems: An Evolutionary Perspective on Value Cocreation. International Journal of Production Economics, 228(10), 13. https://doi.org/10.1016/j.ijpe.2020.107735 Bi, N. (2022). Research on Intelligent Manufacturing Flow Shop Layout Considering AGV Path-planning. Ournal of Zhejiang University of Technology, 50(05), 568–573. https://doi.org/10.3969/j.issn.1006-4303.2022.05.015 Bihu, R. (2021). Questionnaire Survey Methodology in Educational and Social Science Studies. International Journal of Quantitative and Qualitative Research Methods, 9(3). Bing, M., Wen, K., & Zhou, F. (2017). Study on the Adoption Willingness and Influencing Factors of Farmers’ Livestock and Poultry Waste Resource Utilization Technology: Based on a Case Study of 462 Rural Households in Hunan. Journal of Hunan Agricultural University (Social Sciences), 18(4), 37–43. https://doi.org/10.13331/j.cnki.jhau(ss).2017.04.006 Blajeski, S., Smith, M. J., Harrington, M., Johnson, J., Ross, B., Weaver, A., Razzano, L. A., Pashka, N., Brown, A., Prestipino, J., Nelson, K., Lieberman, T., Jordan, N., Oulvey, E. A., Mueser, K. T., McGurk, S. R., Bell, M. D., & Smith, J. D. (2024). A Mixed-Methods Implementation Evaluation of Virtual Reality Job Interview Training in IPS Supported Employment. Psychiatric Services (Washington, D.C.), 75(3). https://doi.org/10.1176/appi.ps.20230023 Bollen, K. A., & Stine, R. (1990). Direct and Indirect Effects: Classical and Bootstrap Estimates of Variability. Sociological Methodology, 20, 115–140. https://doi.org/10.2307/271084 Borbála, P., Péter, P., Anna, M., Zsolt, D., & Katalin, F. (2021). The National Survey on Addiction Problems in Hungary 2019 (Nsaph): Methodology and Sample Description. Neuropsychopharmacologia Hungarica, 23(1). Børje, W., Michael, H., Moore, G., Peters, O., & Bernath, U. (2007). “The Theories and the Theorists : Why Theory is Important for Research .” EDEN Research Workshop, 5(3), 427–457. https://doi.org/www.cairn.info Bortolini, M., Faccio, M., Gamberi, M., & Pilati, F. (2017). Multi-objective Assembly Line Balancing Considering Component Picking and Ergonomic Risk. Computers and Industrial Engineering, 112, 348–367. https://doi.org/10.1016/j.cie.2017.08.029 Brown, A., & Danaher, P. A. (2019). CHE Principles: Facilitating Authentic and Dialogical Semi-Structured Interviews in Educational Research. International Journal Of Research And Method In Education, 42(1). https://doi.org/10.1080/1743727X.2017.1379987 Bryman, A., & Bell, E. (2011). Business Research Methods, 3rd ed., New York: In Oxford University press. Cai, Y., & Wang, Z. (2022). A study on Chinese Learners’ Willingness to Learn Live Online Courses Based on the Technology Acceptance Model. Language Teaching and Linguistic Studies, 5, 35–46. https://doi.org/10.3969/j.issn.0257-9448.2022.05.004 Cao, J., Ye, J., & Zhu, Q. (2023). National Document Information Resource Guarantee Platforms(NDIRGPs)user. Researches in Library Science , 9, 51–61. Cao, Y. (2020). SPSS-based Research on Multiple-choice Question. Statistics and Decision, 36(10), 55–58. https://doi.org/10.13546/j.cnki.tjyjc.2020.10.011 Cao, Z., Chu, J., Li, M., & Wang, X. (2021). A Study on the Impact of the Quality of Live Online Teaching Platform on the Learning Ability of University Students in the Information System Success Model-Chain-Mediating Effects of Knowledge Sharing and Satisfaction. Library and Information Service, 65(4), 61–72. https://doi.org/10.13266/j.issn.0252-3116.2021.04.007 Chang, H., Tian, Y., & Sha, S. (2014). Research on the User-acceptance of Library Information Push Service. Library Tribune, 34(11), 106–111. https://doi.org/10.3969/j.issn.1002-1167.2014.11.016 Chao, Y., & Sun, W. (2016). Balancing Assembly Line by Changing Cycle Time. Machine Design & Research, 32(4), 109–112. https://doi.org/10.13952/j.cnki.jofmdr.2016.0152 Chen, C., & Liu, Z. (2010). The Research Method of Case Study: An Overview of the Classics. Journal of Management Case Studies, 3(2), 175–182. https://doi.org/10.3969/j.issn.1674-1692.2010.02.007 Chen, C., Li, W., Chen, G., & Zhang, Y. (2022). An Empirical Study on Digital Train to Improve the Competency of Construction Team Leaders. Journal of Railway Science and Engineering, 19(2), 554–561. https://doi.org/10.19713/j.cnki.43-1423/u.T20210244 Chen, C., & You, Y. (2023). Defining Scope Conditions and Building Theory in Case-Oriented Research. Comparative Economic and Social Systems , 6, 150–158. https://doi.org/DOI: 10.3969/j.issn.1003-3947.2023.06.016 Chen, J. (2020). Research on Scheduling Management Informationization of Board-type Custom Furniture Enterprises [Dissertation]. Zhejiang Agriculture and Forestry University. Chen, J., He, T., Ma, H., & Lu, Y. (2024). A Study on the Willingness to Continuously Use Generative Artificial Intelligence Platforms - Taking ChatGPT as an Example. China CIO News, 04, 119–123. https://doi.org/DOI: 10.3969/j.issn.1001-2362.2024.04.032 Chen, J., Li, W., Huang, H., Gao, F., Gao, Y., & Jia, W. (2021). Architecture Design of Strategic Equipment Management Intelligent Platform. Metallurgical Industry Automation, 45(1), 8–13. https://doi.org/10.3969/j.issn.1000-7059.2021.01.002 Chen, J., Xu, Z., & Ma, Y. (2019). Analysis of Implementation Strategy of Intelligent Template Technology in Production Line Upgrading of Traditional Garment Enterprises. Jiangsu Textile , 6, 34-35,37. https://doi.org/DOI: 10.3969/j.issn.1005-6289.2019.06.012 Chen, J., Yang, L., Wang, K., Chen, W., & Yang, H. (2018). Scheduling Optimization of Flexible Assembly Production Line for Heavy Truck. IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association, 30(4), 23–31. Chen, J., Zhang, K., Zhou, Y., Liu, Y., Li, L., Chen, Z., & Yin, L. (2019). Exploring the Development of Research, Technology and Business of Machine Tool Domain in New-generation Information Technology Environment Based on Machine Learning. Sustainability (Switzerland), 11(12), 3316. https://doi.org/10.3390/SU11123316 Chen, L. (2018). Research on the Development Model of China’s Intelligent Manufacturing Industry——Based on the 4 Era of Industry. Technoeconomics & Management Research, 260(3), 109–113. https://doi.org/10.3969/j.issn.1004-292X.2018.03.020 Chen, R., Liang, C., Ye, C., & Jiang, L. (2018). A Multi-skilled Staff Scheduling Model for New Product R&D Project Portfolio Under Stochastic Turnover. Systems Engineering —Theory & Practice, 38(1), 164–176. https://doi.org/10.12011/1000-6788(2018)01-0164-13 Chen, W. (2014). Logistics Service Quality, Network Customer Satisfaction and Network Customer Loyalty: The Moderating Effect of Switching Costs. China Business and Market, 28(10), 44–51. https://doi.org/10.3969/j.issn.1007-8266.2014.10.006 Chen, X. (2000). Qualitative Research Methods and Social Science Research, Beijing: Education Science Press. Chen, X., & Liu, S. (2020). An Empirical Study on the Impact of Intelligent Manufacturing Transformation on Industrial Structure Upgrading. Statistics and Decision, 36(13), 121–124. https://doi.org/10.13546/j.cnki.tjyjc.2020.13.026 Chen, Y., & Yin, F. (2013). Network Education Training Users to Adopt Empirical Research. Technoeconomics & Management Research, 5, 15–19. https://doi.org/10.3969/j.issn.1004-292X.2013.05.005 Chen, Y., & Zhang, Z. (2018). Study on the Application of Warehouse Management System Equipped with RFID in the Panel Furniture Enterprises. China Forest Products Industry, 45(9), 55-57+62. https://doi.org/10.19531/j.issn1001-5299.201809014 Chen, Y., Cheng, C., & Li, J. (2018). Resource-constrained Assembly Line Balancing Problems with Multi-manned Workstations. Journal of Manufacturing Systems, 48, 107–119. https://doi.org/10.1016/j.jmsy.2018.07.001 Chen, Y., Zhang, Z., & Huang, L. (2021). Exploring the Mechanisms and Paths of Manufacturing Digital Enablement on Business Model Innovation. Chinese Journal of Management, 18(5), 731–740. https://doi.org/10.3969/j.issn.1672-884x.2021.05.011 Chen, Z., Wang, Z., Shi, W., & Tian, J. (2018). The Application of TRIZ and Lean Production in the Theory of Constraints. Machinery Design & Manufacture, 12, 68–71. https://doi.org/10.3969/j.issn.1001-3997.2018.12.017 Cheng, H., & Wang, J. (2017). A Review of Individual Users Oriented Research on Adoption Behavior of Cloud Services. Information and Documentation Services , 6, 68–73. https://doi.org/DOI: 10.3969/j.issn.1002-0314.2017.06.011 Cheng, Y., Sun, F., Zhang, Y., & Tao, F. (2019). Task Allocation in Manufacturing: A Review. In Journal of Industrial Information Integration, 15, 207–218. https://doi.org/10.1016/j.jii.2018.08.001 Cheng, Z. (2020). From the “Rhinoceros Wisdom” to See the Trend of Intelligent Garment Factories. China Fiber Inspection, 542(11), 108–111. https://doi.org/10.14162/j.cnki.11-4772/t.2020.11.029 Chi, I., & Xiao, X. (2020). Business Management Changes in the Digital Economy. Management World, 36(6), 135–152. https://doi.org/10.3969/j.issn.1002-5502.2020.06.011 Chi, R., & He, M. (2017). Influence Mechanism of Regional Brand on Enterprise Performance: Case of “Zhejiang Made.” Technology Economics, 36(8), 40–47. https://doi.org/10.3969/j.issn.1002-980X.2017.08.006 Chin, W. W., & Newsted, P. R. (1999). Structural Equation Modeling Analysis with Small Samples Using Partial Least Square. Statistical Strategies for Small Sample Research, 1(1), 307–341. Chu, K., & Wu, L. (2019). Application of Adaptive Genetic Algorithm in Mixed Flow Assembly Line Scheduling. Modern Manufacturing Engineering, 468(9), 37–40. https://doi.org/10.16731/j.cnki.1671-3133.2019.09.006 Chu, M., & Shang, Y. (2022). Diagnostic Study on the Antecedent Conditions of Intelligent Transformation and Upgrading of Manufacturing Industry. Journal of Liaoning University of Technology (Social Science Edition), 24(6), 25–29. https://doi.org/10.15916/j.issn1674-327x.2022.06.007 Chu, W. S., Kim, M. S., Jang, K. H., Song, J. H., Rodrigue, H., Chun, D. M., Cho, Y. T., Ko, S. H., Cho, K. J., Cha, S. W., Min, S., Jeong, S. H., Jeong, H., Lee, C. M., Chu, C. N., & Ahn, S. H. (2016). From Design for Manufacturing (DFM) to Manufacturing for Design (MFD) Via Hybrid Manufacturing and Intelligent Factory: A Review and Perspective of Paradigm Shift. International Journal of Precision Engineering and Manufacturing - Green Technology, 3(2), 209–222. https://doi.org/10.1007/s40684-016-0028-0 Chung, N., Lee, H., Lee, S. J., & Koo, C. (2015). The Influence of Tourism Website on Tourists’ Behavior to Determine Destination Selection: A Case Study of Creative Economy in Korea. Technological Forecasting and Social Change, 96, 130–143. https://doi.org/10.1016/j.techfore.2015.03.004 Çil, Z. A., Mete, S., Özceylan, E., & Ağpak, K. (2017). A Beam Search Approach for Solving Type II Robotic Parallel Assembly Line Balancing Problem. Applied Soft Computing, 61, 129–138. https://doi.org/10.1016/j.asoc.2017.07.062 Cole, R. (2023). Inter-Rater Reliability Methods in Qualitative Case Study Research. Sociological Methods and Research. https://doi.org/10.1177/00491241231156971 Comrey, A., & Lee, H. A. (1992). A First Course in Factor Anaysis. Hillsdale, NJ: Lawrence Eribaum Associates Publishers. Corley, K. G., & Gioia, D. A. (2011). Building Theory about Theory Building: What Constitutes a Theoretical Contribution? Academy of Management Review, 36(1), 12–32. https://doi.org/10.5465/amr.2009.0486 Creswell, J., & Plano, V. (2017). Designing and Conducting Mixed Methods Research - John W. Creswell, Vicki L. Plano Clark. In SAGE Publications. Cui, X. (2018). Computer Technology-aided Garment Sewing Line Optimization Design Research. Automation & Instrumentation, 2, 123–125. https://doi.org/10,14016/j.cnki,1001,9227,2018.02.123 Dai, X., Guo, K., & Liu, L. (2017). An Empirical Study on the Factors Influencing MOOC Learners’ Satisfaction--A Structural Equation Analysis Based on the Questionnaire of “Chinese University MOOC” Learners. Modern Distance Education, 2, 17–23. https://doi.org/10.13927/j.cnki.yuan.2017.0013 Dai, Y., & Zhang, X. (2021). Design of Sorting of Unloading Device for Garment Hanging System Based on PLC. HEILONGJIANG SCIENCE, 12(6), 7–9. https://doi.org/DOI: 10.3969/j.issn.1674-8646.2021.06.002 Dalton, D. R., Todor, W. D., Spendolini, M. J., Fielding, G. J., & Porter, L. W. (1980). Organization Structure and Performance: A Critical Review. Academy of Management Review, 5(1), 49–64. https://doi.org/10.5465/amr.1980.4288881 Davis, F. D. (1986). A Technology Acceptance Model for Empirically Testing New End-user Information Systems: Theory and Results [Dissertation]. Doctoral Dissertation, Massachusetts Institute of Technology. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly: Management Information Systems, 13(3), 319–340. https://doi.org/10.2307/249008 Davis, M. S. (1971). That’s Interesting!: Towards a Phenomenology of Sociology and a Sociology of Phenomenology. Philosophy of the Social Sciences, 1(2), 309–344. https://doi.org/10.1177/004839317100100211 Delice, Y., Aydoğan, E. K., Söylemez, I., & Özcan, U. (2018). An Ant Colony Optimisation Algorithm for Balancing Two-sided U-type Assembly Lines with Sequence-dependent Set-up Times. Sadhana - Academy Proceedings in Engineering Sciences, 43(12). https://doi.org/10.1007/s12046-018-0969-9 DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-year Update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748 DeLone, W. H., & McLean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/isre.3.1.60 Deng, C., Hu, R., Jiang, J., & Yin, G. (2021). Multi-objective Assembly Line Balancing Optimization Considering Worker Assignment. Modular Machine Tool & Automatic Manufacturing Technique, 568(6), 116-121+126. https://doi.org/10.13462/j.cnki.mmtamt.2021.06.027 Deng, C., & Legge, M. (2024). A Qualitative Case Study of Primary Classroom Teachers’ Perceived Value of Physical Education in New Zealand. Sport, Education and Society, 29(2). https://doi.org/10.1080/13573322.2022.2125948 Dey, M., Marti, L. & Jorm, A. F. (2019). The Swiss Youth Mental Health Literacy and Stigma Survey: Study methodology, Survey Questions/Vignettes, and Lessons Learned. European Journal of Psychiatry, 33(2). https://doi.org/10.1016/j.ejpsy.2018.12.001 Diaz C., J. L., & Ocampo-Martinez, C. (2019). Energy Efficiency in Discrete-Manufacturing Systems: Insights, Trends, and Control Strategies. In Journal of Manufacturing Systems, 52(Part A), 131–145. https://doi.org/10.1016/j.jmsy.2019.05.002 Ding, C., & Chen, Q. (2024). Digitalization of the German Economy: Strategic Evolution, Policies and Implementation Priorities, Progress, and Challenges. The Journal of Jiangsu Administration Institute, 02, 42–48. Ding, K., Lei, J., Zhang, F., Wang, Y., & Wang, C. (2020). Analyzing the Cyber-physical System–based Autonomous Collaborations Among Intelligent Manufacturing Resources in a Intelligent Shop Floor. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 234(3), 489–500. https://doi.org/10.1177/0954405419875340 Ding, K., Luo, D., & Zhang, X. (2022). Production Task Allocation and Prediction in a Intelligent Shop Floor Considering Equipment Layout. Manufacturing Automation, 44(7), 91–94. https://doi.org/10.3969/j.issn.1009-0134.2022.07.022 Dong, B., & Wang, Y. (2018). Creating Continuous Flow in the Production Line Based on Value Stream Mapping. Science Technology and Industry, 18(1), 112–116. https://doi.org/10.3969/j.issn.1671-1807.2018.01.020 Dong, J. (2021). Equilibrium Optimization Study of S Company’s T Product Line Based on Flexsim [Dissertation]. Hebei University of Engineering. https://doi.org/10.27104/d.cnki.ghbjy.2021.000526 Dong, M., Shao, T., & Li, S. (2016). Factor Analysis of Female College Students on Jean Consumption Demand. Journal of Beijing Institute of Clothing Technology, 36(3), 21–27. https://doi.org/10.16454/j.cnki.issn.1001-0564.2016.03.004 Dong, X. (2022). Research on Fast Fashion Trends Based on Text Semantic Mining and Time Series Clustering [Dissertation]. Donghua University. https://doi.org/10.27012/d.cnki.gdhuu.2022.001034 Dong, Y. (2023). Research on the Path for Small Farmers to Effectively Connect with the E-commerce Market under the Background of Digital Economy. Price:Theory & Practice, 7, 103–106. https://doi.org/DOI: 10.19851/j.cnki.CN11-1010/F.2023.07.181 Du, H. (2015). Information System Success Model and its Application in the Field of Digital Libraries. Researches in Library Science, 11, 30-33+39. https://doi.org/10.15941/j.cnki.issn1001-0424.2015.11.006 Du, J., Wang, S., & Liang, X. (2020). The Research of Multiple Uncertain Conditions in Production Line of M Company. Machinery Design & Manufacture, 7, 296–299. https://doi.org/10.3969/j.issn.1001-3997.2020.07.067 Du, J., Zheng, M., Dai, Y., & Li, Y. (2018). Action Coding for Operation Process of Garment Template. Journal of Textile Research, 39(9), 109–114. https://doi.org/10.13475/j.fzxb.20171010306 Du, Y., Chen, Z., & Liu, D. (2017). Research on Perception of Food Authenticity, Brand Image and Satisfaction in Rural Tourism——A Case Study of Yuanjiacun Village, Shanxi Province. Resource Development & Market, 33(1), 90–94. https://doi.org/10.3969/j.issn.1005-8141.2017.01.017 Eisenhardt, K. M. (1989). Building Theories from Case Study Research. Academy of Management Review, 14(4), 532–550. https://doi.org/10.5465/amr.1989.4308385 Fan, M. (2019). Research on Automatic Sample Generation of Women’s Fitted Jeans [Dissertation]. Zhejiang University of Technology. Fan, Y., Li, L., Zong, Q., Yang, L., & Li, B. (2023). Research on Application of Denim Fabric in Garment Design. Shandong Textile Economy , 11, 35–38. https://doi.org/DOI: 10.3969/j.issn.1673-0968.2023.11.009 Fang, A., Lu, M., & Liu, K. (2018). Empirical Study on Users’ Knowledge Purchase Intention for Virtual Community. Library and Information Service, 62(6), 105–115. https://doi.org/10.13266/j.issn.0252-3116.2018.06.013 Fang, L. (2016). High Quality and Low Discharge Processing Technology of Printing Jeans. Textile Dyeing and Finishing Journal, 38(14), 28–30. https://doi.org/10.3969/j.issn.1005-9350.2016.12.009 Fang, L., Li, D., Tang, H., & He, Q. (2017). Research and Realization of Real-time Monitoring System for Digital Factory Status. Modular Machine Tool & Automatic Manufacturing Technique, 12, 117-120+124. https://doi.org/10.13462/j.cnki.mmtamt.2017.12.029 Fang, W., Guo, Y., Huang, S., Liu, D., Cui, S., Liao, W., & Hong, D. (2021). Big Data Driven Intelligent Production Control of Discrete Manufacturing Process. Journal of Mechanical Engineering, 57(20), 277–291. https://doi.org/10.3901/JME.2021.20.277 Fang, Y. (2018). Analysis of Intelligent Manufacturing Technology and Standardization System Development. China Instrumentation, 324(3), 21–26. https://doi.org/CNKI:SUN:ZYQB.0.2018-03-006 Fatoki, O. (2021). Access to Finance and Performance of Small Firms in South Africa: The Moderating Effect of Financial Literacy. WSEAS Transactions on Business and Economics, 18. https://doi.org/10.37394/23207.2021.18.9 Fei, X., Shi, Y., & Yuan, Q. (2018). The Application and Prospect of the DeLone and McLean Model of IS Success. Modern Information, 38(11), 161-171+177. https://doi.org/10.3969/j.issn.1008-0821.2018.11.026 Feng, D., Wu, X., Ding, Y., Fan, J., He, X., & Wang, C. (2017). Research of Manufacturing Cell Formation Based on U-shaped Layout. Journal of Zhejiang University of Technology, 45(1), 88–93. https://doi.org/10.3969/j.issn.1006-4303.2017.01.018 Feng, R., Jiang, S., & Wan, Y. (2023). Analysis of the Development Strategies of Safety-oriented Intelligent Manufacturing in Major Countries/Regions of the World. World Sci-Tech R & D , 45(05), 543–554. https://doi.org/DOI: 10.16507/j.issn.1006-6055.2022.11.004 Feng, Y., Jiang, N., Li, B., Li, S., Wang, Y., & Wang, W. (2022). Pulsating Assembly Line Planning and Workshop Layout Design of Civil Aircraft Nose System. Aeronautical Manufacturing Technology, 65(10), 104–112. https://doi.org/10.16080/j.issn1671-833x.2022.10.104 Feng, Y., Zhang, T., & Chen, X. (2020). Multi Factor Production Cost Modeling Method for Intelligent Manufacturing. CIESC Journal, 71(3), 1111–1121. https://doi.org/10.11949/0438-1157.20191492 Fisel, J., Exner, Y., Stricker, N., & Lanza, G. (2019). Changeability and Flexibility of Assembly Line Balancing as a Multi-objective Optimization Problem. Journal of Manufacturing Systems, 53, 150–158. https://doi.org/10.1016/j.jmsy.2019.09.012 Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. In American Marketing Association, 18(1), 39–50. Fritz, M. S., & MacKinnon, D. P. (2007). Required Sample Size to Detect the Mediated Effect. Psychological Science, 18(3), 233–239. https://doi.org/10.1111/j.1467-9280.2007.01882.x Fu, Q. (2021). MES-oriented Research on Production Work Planning in the Assembly Plant of Company A [Dissertation]. Hebei University of Science and Technology. Gan, C., Xu, J., & Zhu, Y. (2018). An Empirical Study of Users’ Continuance Intention to Use Social Q&A Communities. Information Science, 36(2), 107–112. https://doi.org/10.13833/j.issn.1007-7634.2018.02.020 Gan, M. (2020). Overtime Compulsory Labor System and Innovation of Working Hours Enforcement. Social Science Research, 248(3), 102–108. https://doi.org/10.3969/j.issn.1000-4769.2020.03.011 Gan, Y., Hou, L., Xu, C., Zhang, W., Chen, D., & Fang, Y. (2019). Sequencing for Bus Mixed Model Assembly Line with Consideration of Product Switching. Computer Integrated Manufacturing Systems, 25(7), 1685–1694. https://doi.org/10.13196/j.cims.2019.07.009 Gan, Z. (2016). A Study of Consumer Behavior Using Online Travel Website Based on ELM Model. Chinese Journal of Management , 13(6), 889–898. https://doi.org/DOI: 10.3969/j.issn.1672-884x.2016.06.012 Gao, B., & Zhu, L. (2020). From World Factory to a Powerhouse of Industrial Internet of Things: Build New Competitive Advantage in the Era of Intelligent Manufacturing. Reform, 316(6), 30–43. https://kns.cnki.net/kcms/detail/50.1012.F.20200513.0852.002.html Gao, F. (2020). Introduction to the Integration of Hanging Systems and Information Systems in Custom Apparel Production. Industrial Innovation, 37(8), 124–125. Gao, J., Ma, Y., & Wu, B. (2012). The Application of Structural Equation Modeling in Tourism Research: A Review, Reflection and Examination. Tourism Tribune, 27(7), 98–111. Gao, K., & Sheng, Y. (2018). A Research on the Influencing Factors of Usage Intention of Regional Agricultural Products E-commerce Platforms. China Business and Market, 32(1), 67–74. https://doi.org/10.14089/j.cnki.cn11-3664/f.2018.01.008 Gao, P., Liu, W., & Xu, B. (2004). A Study of Enterprise ERP Implementation Based on Integrated TAM/TTF Model. Systems Engineering —Theory & Practice, 24(10), 74–79. https://doi.org/10.3321/j.issn:1000-6788.2004.10.013 Gao, S., & Liu, J. (2018). The Impact of Artificial Intelligence on Business Management Theory and Response. Studies in Science of Science, 36(11), 2004–2010. https://doi.org/10.16192/j.cnki.1003-2053.2018.11.010 Gao, X., & Meng, J. (2020). PDCA-based Risk Management of Green Supply Chain Partners in Dairy Industry. Economig Rfsearch Cuide, 22, 9-11+16. https://doi.org/10.3969/j.issn.1673-291X.2020.22.005 Gao, Y. (2022). How to Cultivate Students’ Thinking and Ability in Teaching (2): Qualitative and Quantitative Analysis. Mechanics in Engineering, 44(4), 941–946. https://doi.org/10.6052/1000-0879-22-250 Gao, Y. (2023). Diversity and Resistance:Identity of Male in Mass Culture and Fashion After the War. Decoration, 4, 54–65. https://doi.org/DOI: 10.3969/j.issn.0412-3662.2023.04.016 Gao, Z. (2022). Research on Production Line in a Powder Metallurgy Workshop Based on EM-Plant and Factory Layout Optimization. Powder Metallurgy Industry, 32(4), 89–100. https://doi.org/10.13228/j.boyuan.issn1006-6543.20210103 Gao, Z., Ye, S., Zhou, C., & Wang, H. (2022). Lean Improvement on Bogie Maintenance Process Based on Value Stream Mapping. Modern Manufacturing Engineering, 9, 113–122. https://doi.org/10.16731/j.cnki.1671-3133.2022.09.017 Ge, B., & Zhao, L. (2022). The Impact of CEO Turnover on State-Owned Enterprises to Overcome Structural Constraints and Achieve Strategic Renewal——Vertical Single Case Based on FAW Group. Chinese Journal of Management, 19(10), 1430–1441. https://doi.org/10.3969/j.issn.1672-884x.2022.10.002 Ge, C., Ji, C., Mi, N., Pan, R., & Gao, W. (2021). Intelligent Transformation Discussion of Spinning Enterprise Based on Manufacturing Execution System. Cotton Textile Technology, 49(10), 42–46. https://doi.org/10.3969/j.issn.1001-7415.2021.10.009 Ge, X., & Li, S. (2021). Research on Multi-objective Workshop Layout Optimization Based on Improved Genetic Algorithm. Modern Manufacturing Engineering, 3, 10-14+9. https://doi.org/10.16731/j.cnki.1671-3133.2021.03.002 Getnet Agazu, B., Ketemaw Dejenu, A., & Lemi Debela, K. (2022). A Comparative Review of Qualitative Research: A Guide to Design and Implementation. In Qualitative Report (Vol. 27, Issue 8). https://doi.org/10.46743/2160-3715/2022.5748 Girod, S. J. G., & Whittington, R. (2017). Reconfiguration, Restructuring and Firm Performance: Dynamic Capabilities and Environmental Dynamism. Strategic Management Journal, 38(5), 1121–1133. https://doi.org/10.1002/smj.2543 Golafshani, N. (2003). Understanding Reliability and Validity in Qualitative Research. The Qualitative Report, 8(4), 597–607. https://doi.org/10.46743/2160-3715/2003.1870 Gong, G., Chiong, R., Deng, Q., & Gong, X. (2020). A Hybrid Artificial Bee Colony Algorithm for Flexible Job Shop Scheduling with Worker Flexibility. International Journal of Production Research, 58(14), 4406–4420. https://doi.org/10.1080/00207543.2019.1653504 Gong, S. (2019). The Design of Visual Effects of Hip Enhancement in the Styles of Straight Jeans. West Leather , 41(23), 49. Grenier, A. (2023). The Qualitative Embedded Case Study Method: Exploring and Refining Gerontological Concepts Via Qualitative Research with Older People. Journal of Aging Studies, 65. https://doi.org/10.1016/j.jaging.2023.101138 Grodach, C., & Gibson, C. (2019). Advancing Manufacturing?: Blinkered Visions in U.S. and Australian Urban Policy. Urban Policy and Research, 37(3). https://doi.org/10.1080/08111146.2018.1556633 Guan, X., Zhang, N., & Meng, Q. (2012). E-government Adoption Model for Public Based on Whole Process: An Empirical Research. Journal of Intelligence, 31(9), 191-196+201. https://doi.org/10.3969/j.issn.1002-1965.2012.09.036 Guo, H., Chen, D., Qu, T., Li, C., Huang, G., He, Z., Chen, M., & Zeng, Y. (2020). Lean Improvement of S Production Line Based on Value Stream. Computer Integrated Manufacturing Systems, 26(2), 320–330. https://doi.org/10.13196/j.cims.2020.02.005 Guo, L. (2018). Research on the Construction and Application of Cost Management System in China’s Electric Power Enterprises from the Perspective of Institutional Change [Dissertation]. Northeast University of Finance and Economics. Guo, L. (2020). Research on the Organization Model of Research Projects Oriented to the Transformation of Results [Dissertation]. Zhejiang University. https://doi.org/10.27461/d.cnki.gzjdx.2020.004573 Guo, L., & Cao, Y. (2018). Research on the Influencing Mechanism of College Students Learning Satisfaction with MOOCs. Journal of Higher Education, 39(12), 69–75. https://doi.org/CNKI:SUN:HIGH.0.2018-12-011 Guo, X. (2011). The Impact of Shopping Website Service Quality on Customer Satisfaction and Loyalty. Journal of Shanxi University of Finance and Economics, 33(S3), 120–121. https://doi.org/10.13781/j.cnki.1007-9556.2011.s3.152 Guo, X., & Chen, X. (2021). Data Enablement and Innovation of Chinese Manufacturing Enterprises: Frontier Analysis and Future Prospects. Science & Technology Progress and Policy, 38(15), 151–160. https://doi.org/10.6049/kjjbydc.2020110756 Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data Analysis, 5th ed., In New Jersey: Prentice Hall. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis, 7th ed. Prentice Hall, New Jersey. Technometrics, 15(3), 648. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equations Modeling (PLS-SEM). Sage Publications. Journal of Tourism Research, 6(2), 211-213. Halim, A. (2020). Pengaruh Pertumbuhan Usaha Mikro, Kecil Dan Menengah Terhadap Pertumbuhan Ekonomi Kabupaten Mamuju. Jurnal Ilmiah Ekonomi Pembangunan, 1(2). Hammersley, M. (2019). From Positivism to Post-Positivism: Progress or Digression? Teoria Polity⁃ki, 3, 175–188. Han, B., & Ji, X. (2020). The Method of Virtual Display for the Intelligent Production Line. Manufacturing Automation, 42(1), 136-138+156. https://doi.org/10.3969/j.issn.1009-0134.2020.01.027 Han, F., Liu, L., & Zhang, H. (2021). Optimization Design of Workshop Facility Layout Based on Improved SLP Algorithm. Machinery Design & Manufacture, 3, 297–300. https://doi.org/10.3969/j.issn.1001-3997.2021.03.068 Han, M., Tang, Y., & Zheng, D. (2021). Research on the Realistic Dilemma and Policy Support for the Intelligent Upgrading of China’s Manufacturing Industry. Journal of the Party School of CPC Ningbo Municipal Committee, 43(4), 110–116. https://doi.org/10.3969/j.issn.1008-4479.2021.04.012 Han, Y., Wu, J., Ma, J., & Wang, G. (2021). Evaluation on Intelligent Manufacturing Capability Based on Interval Number PROMETHEE Method. Modern Manufacturing Engineering, 3, 1–9. https://doi.org/10.16731/j.cnki.1671-3133.2021.03.001 Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium. Communication Monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360 He, C., & Hu, L. (2021). Trend and Theme Analysis of Library Function Research in China. JOURNAL OF QINGYUAN POLYTECHNIC , 14(3), 83–90. https://doi.org/DOI: 10.3969/j.issn.1674-4896.2021.03.016 He, W., Zhai, Y., & Wang, J. (2018). Green Science and Technology Innovation and Push Synergy Mechanism: Key Customer Perspective. Journal of Dalian University of Technology (Social Sciences), 39(3), 17–23. https://doi.org/10.19525/j.issn1008-407x.2018.03.003 He, X., Cui, L., Zhai, Y., Zhuang, X., & Wang, L. (2021). Real-time Data Acquisition and Analysis System of Automated Forging Production Line. Forging & Stamping Technology, 46(2), 14–18. https://doi.org/10.13330/j.issn.1000-3940.2021.02.003 Hennink, M., & Kaiser, B. N. (2022). Sample Sizes for Saturation in Qualitative Research: A Systematic Review of Empirical Tests. Social Science and Medicine, 292. https://doi.org/10.1016/j.socscimed.2021.114523 Hidayat, W., Widodo, S. A., & Syahrizal, T. (2023). The Statistical Thinking Skill and Adversity Quotient of English Pre-Service Teacher. International Journal of Evaluation and Research in Education, 12(1). https://doi.org/10.11591/ijere.v12i1.24302 Holtz, P., & Odağ, Ö. (2020). Popper was not a Positivist: Why Critical Rationalism Could be an Epistemology for Qualitative as well as Quantitative Social Scientific Research. Qualitative Research in Psychology, 17(4), 541–564. https://doi.org/10.1080/14780887.2018.1447622 Hong, H. (2018). Hermeneutics: Its History and Contemporary Development. Beijing: People’s University of China Press. Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6(1), 141–146. Hou, F., Wang, Y., Xu, X., & Su, Y. (2021). Operation Analysis of China Denim Industry in 2020. Cotton Textile Technology, 49(7), 76–79. https://doi.org/10.3969/j.issn.1001-7415.2021.07.019 Hou, P., Liao, Y., & Liu, F. (2021). Simulation Optimization of Brake Disc Flexible Manufacturing Line. Machine Tool & Hydraulics, 49(24), 165–171. https://doi.org/10.3969/j.issn.1001-3881.2021.24.032 Hu, B., & Chen, J. (2017). Optimal Task Allocation for Human-Machine Collaborative Manufacturing Systems. IEEE Robotics and Automation Letters, 2(4), 1933–1940. https://doi.org/10.1109/LRA.2017.2714981 Hu, B., Chen, X., & Zheng, Q. (2023). Research on Undergraduate Level Vocational Education:Review and Prospects——An Analysis Based on a Systematic Review Methodolody. Contemporary Vocational Education, 5, 4–13. https://doi.org/DOI: 10.3969/j.issn.1674-9154.2023.05.002 Hu, L. T., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118 Hu, M., & Li, F. (2018). Simulation and Optimization of the Crankshaft Production Line Based on “One-Piece Flow” Cell Production Mode. Modern Manufacturing Engineering, 450(3), 86–92. https://doi.org/10.16731/j.cnki.1671-3133.2018.03.016 Hu, R. (2020). From Intelligent Manufacturing to the Intelligent Economy and Society. Journal of Shanghai University of International Business and Economics, 27(5), 78–90. https://doi.org/10.16060/j.cnki.issn2095-8072.2020.05.006 Hua, C. (2020). Study on the Application of Indigo Dyeing Art in Jeans [Dissertation]. Wuhan Textile University. https://doi.org/10.27698/d.cnki.gwhxj.2020.000264 Huang, F., Zhuo, Z., & Wu, C. (2015). How do Life Insurers Satisfy Their Customers? —An Analysis of Determinants and Customer Segmentation. Insurance Studies, 9, 9–22. https://doi.org/10.13497/j.cnki.is.2015.09.002 Huang, K., & Yu, J. (2019). Study on the Optimization of the Air Condition Compressor Production Line. Manufacturing Technology & Machine Tool, 8, 82–86. https://doi.org/10.19287/j.cnki.1005-2402.2019.08.017 Huang, P., & Deng, Z. (2021). Analysis and Improvement of Production Line Balance Rate Based on Witness. Manufacturing Automation, 43(9), 50–55. https://doi.org/10.3969/j.issn.1009-0134.2021.09.011 Huang, P., Huang, W., & Ye, S. (2018). The Application of Value Stream Map Analysis in Improving Engine Production Line. Machinery Design & Manufacture, 3, 37-39+43. https://doi.org/10.3969/j.issn.1001-3997.2018.03.012 Huang, S., Guo, Y., Cha, S., Fang, W., & Wang, F. (2019). Review on Internet-of-manufacturing-things and Key Technologies for Discrete Workshop. Computer Integrated Manufacturing Systems, 25(2), 284–302. https://doi.org/10.13196/j.cims.2019.02.003 Huang, X., Jia, M., Long, T., Zhang, Y., Wang, C., & An, W. (2017). Analysis of the Investment Environment of DRC Mining Industry Based on SWOT Model. China Mining Magazine, 26(11), 96–102. Huang, Y., & Qi, E. (2015). Predicament and Way of China’s Manufacturing Industry Based on IE. Science of Science and Management of S.& T., 36(4), 85–94. Huang, Y., Yuan, X., Yu, K., & Gan, Z. (2022). Design and Simulation Optimization on Intelligent Forging Production Workshop for Engine Main Shaft Based on Plant Simulation. Forging & Stamping Technology, 47(7), 53-58+94. https://doi.org/10.13330/j.issn.1000-3940.2022.07.008 Huang, Z., Mo, B., & Wen, L. (2020). Garment Production Line Balance Based on Genetic Algorithm and Simulation. Journal of Textile Research, 41(7), 154–159. https://doi.org/10.13475/j.fzxb.20190707706 Hundleby, J. D., & Nunnally, J. (1968). Psychometric Theory. American Educational Research Journal, 5(3), 431. https://doi.org/10.2307/1161962 Jackson, D. L. (2003). Revisiting Sample Size and Number of Parameter Estimates: Some Support for the N:Q Hypothesis. Structural Equation Modeling, 10(1), 128–141. https://doi.org/10.1207/S15328007SEM1001_6 Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009). Reporting Practices in Confirmatory Factor Analysis: An Overview and Some Recommendations. Psychological Methods, 14(1), 6–23. https://doi.org/10.1037/a0014694 Jason, M., Hung, D. Q., & Ida, G. (2023). The Influence of Digitalisation on the Role of Quality Professionals and their Practices. Cogent Business and Management, 10(1). https://doi.org/10.1080/23311975.2022.2164162 Jayachandran, S., Biradavolu, M., & Cooper, J. (2023). Using Machine Learning and Qualitative Interviews to Design a Five-Question Survey Module for Women’s Agency. World Development, 161. https://doi.org/10.1016/j.worlddev.2022.106076 Jeschke, S., Brecher, C., Meisen, T., Özdemir, D., & Eschert, T. (2017). Industrial Internet of Things and Cyber Manufacturing Systems. Berlin: Springer Series in Wireless Technology. https://doi.org/10.1007/978-3-319-42559-7_1 Ji, Y., Han, M., & Zheng, D. (2018). Research on Intelligent Upgrading Path Selection of Manufacturing Enterprises——from the Perspective of Enterprise Entity. Reform of Economic System, 6, 89–95. Jiang, H., Duan, Q., Wang, Y., Zhang, P., & Huang, S. (2022). Design and Realization of MES System for Cord Fabric Twisting Workshop. Cotton Textile Technology, 50(10), 49–53. https://doi.org/10.3969/j.issn.1001-7415.2022.10.011 Jiang, Q. (2018). Research on JIT-oriented Flexible U-shaped Production Line Task Allocation Method and System [Dissertation]. Hefei University of Technology. Jiang, X. (2023). Fusion of Fashion Design and Artificial Intelligence. Social Sciences In Wuhan, 03, 89–90. Jiang, Y., Xie, G., & Zhou, R. (2017). Constructing Theoretical Model on Users’ Continuance Intention to Chinese Science Website. Science and Society, 7(2), 100-117+99. https://doi.org/10.19524/j.cnki.10-1009/g3.2017.02.100 Jiang, Z., Zhao, C., Li, H., Hu, P., & Huang, Y. (2017). Influencing Factors of Online Learners’ Satisfaction: A Comparative Study on Live Situation and Record Situation. Education Research, 23(4), 76–85. https://doi.org/10.13966/j.cnki.kfjyyj.2017.04.007 Jiao, Y., & Liu, Z. (2020). Digital Economy Empowers New Model of Intelligent Manufacturing - From Scale Production, Personalization to Moderate Scale Customization Innovation. Guizhou Social Sciences, 371(11), 148–154. https://doi.org/10.13713/j.cnki.cssci.2020.11.019 Jiao, Y., Deng, X., Li, L., Liu, W., Zhang, T., & Cao, N. (2023). Balancing and Collaborative Optimization of Bilateral U-shaped Assembly Lines Under Multiple Constraints. Journal of Jilin University (Engineering and Technology Edition), 53(7), 2053–2060. https://doi.org/10.13229/j.cnki.jdxbgxb20211050 Jiao, Y., Jin, H., Xing, X., Li, M., & Liu, X. (2021). Assembly Line Balance Research Methods, Literature and Development Review. In Concurrent Engineering Research and Applications, 29(2), 183–194. https://doi.org/10.1177/1063293X20987910 Jiao, Y., Li, M., Wang, Z., Jin, H., & Yang, Z. (2020). Random Double U-shaped Assembly Line Balancing Method Using Priority Value. Journal of Jilin University (Engineering and Technology Edition), 50(6), 2087–2093. https://doi.org/10.13229/j.cnki.jdxbgxb20190726 Jiao, Y., Li, Y., & Li, Z. (2021). Hot Point Change, Trend Analysis and Future Research Prospects in Product Line Research(1978～2019). Chinese Journal of Management, 18(7), 1095–1106. https://doi.org/10.3969/j.issn.1672-884x.2021.07.016 Jiao, Y., Xing, X., Zhu, C., Xu, L., & Zou, L. (2019). Modified Ranked Positional Weight Technique for Assembly Line Balance of Simple Line and U-shape. 10.11908/j.Issn.0253-374x.2019.01.019, 47(1), 143–148. https://doi.org/10.11908/j.issn.0253-374x.2019.01.019 Jiao, Y., Xu, L., Wang, Z., & Zhang, P. (2018). Balance Experiment and Analysis of Double U-shaped Assembly Line Based on Directed Network. Journal of Jilin University (Engineering and Technology Edition), 48(2), 454–459. https://doi.org/10.13229/j.cnki.jdxbgxb20170092 Jie, X., & Luo, Y. (2016). Research on the Characteristics of China’s New Manufacturing Industry and its Construction Path. Theory and Reform, 210(4), 184–188. https://doi.org/10.13553/j.cnki.llygg.2016.04.036 Jin, B. (2017). New Thinking on Industrial Transformation and Upgrading in the New Era of Globalization. China Small & Medium Enterprises, 261(8), 27–28. https://doi.org/10.3969/j.issn.1005-8400.2017.08.007 Jin, D., Cao, B., & Li, Y. (2019). Application of Digital Technology in Apparel Equipment. Tianjin Textile Science & Technology, 2, 19–21. https://doi.org/10.13518/j.cnki.tjtst.2019.02.006 Jin, X., Xu, F., & Bi, X. (2021). Investigation on the User Satisfaction of Knowledge Payment Platforms and Improvement Strategies. Information Studies:Theory & Application, 44(5), 146–152. https://doi.org/DOI: 10.16353/j.cnki.1000-7490.2021.05.022 Jin, Y., & Qi, W. (2021). Research on Automation Transformation Ideas and Key Technologies of Traditional Manual Production Line. Farm Machinery Using & Maintenance, 296(4), 49–50. https://doi.org/10.14031/j.cnki.njwx.2021.04.020 Jing, R., & Sun, X. (2021). Positivism Vs. Interpretivism: A Comparison and Insight of Two Classic Case Study Paradigms. Journal of Management World, 37(3), 198–216. https://doi.org/10.19744/j.cnki.11-1235/f.2021.0043 Jing, R., Cheng. S., & Yuan, D. (2020). Why Is Indigenous Management Research Important? Responses to Previous Questioning Views and Suggestions for Future Development. Foreign Economies & Management, 42(8), 3–16. https://doi.org/10.16538/j.cnki.fem.20200308.101 Jing, W., & Sun, P. (2019). Digital Economy Promotes High-quality Economic Development: A Theoretical Analysis Framework. Economist, 242(2), 66–73. https://doi.org/10.16158/j.cnki.51-1312/f.2019.02.008 Julio, R., Monzon, A., & Susilo, Y. O. (2024). Identifying Key Elements for User Satisfaction of Bike-Sharing Systems: a Combination of Direct and Indirect Evaluations. Transportation, 51(2). https://doi.org/10.1007/s11116-022-10335-3 Kalyaev, I. A. (2019). Priority of Scientific and Technological Development "The Transition to Advanced Digital, Intelligent Manufacturing Technologies, Robotic Systems, New Materials and Methods of Design, the Creation of Systems for Processing Large Amounts of Data, Machine l. Вестник Российской Академии Наук, 89(4), 348–350. https://doi.org/10.31857/s0869-5873894348-350 Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, B. H., & Noh, S. D. (2016). Smart Manufacturing: Past Research, Present Findings, and Future Directions. International Journal of Precision Engineering and Manufacturing - Green Technology, 3(1), 111–128. https://doi.org/10.1007/s40684-016-0015-5 Kang, J., Zhang, L., & Tan, C. (2022). Analysis of Optimal Design for Women’s High-waisted Jeans. Qingfang Gongye Yu Jishu, 51(5), 100–102. https://doi.org/DOI: 10.3969/j.issn.2095-0101.2022.05.030 Kettinger, W. J., & Lee, C. C. (1994). Perceived Service Quality and User Satisfaction with the Information Services Function. Decision Sciences, 25(5–6), 737–766. https://doi.org/10.1111/j.1540-5915.1994.tb01868.x Khojasteh, J. (2022). Review of A Beginner’s Guide to Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 29(5), 817–819. https://doi.org/10.1080/10705511.2022.2063128 Kilduff, M. (2006). Editor’s Comments: Publishing Theory. In Academy of Management Review, 31(2), 252–255. https://doi.org/10.5465/AMR.2006.20208678 Kisekka, V., & Giboney, J. S. (2018). The Effectiveness of Health Care Information Technologies: Evaluation of Trust, Security Beliefs, and Privacy as Determinants of Health Care Outcomes. 20(4), e107. https://doi.org/10.2196/jmir.9014 Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling. Journal of the American Statistical Association, 101(12). Kong, J., Yang, Y., Liao, Q., & Liu, J. (2024). Cross-disciplinary Learning Practice Research in Basic Education at Home and Abroad - Based on Systematic Literature Review Method. Modern Educational Technology, 34(06), 63-70. Krugh, M., & Mears, L. (2018). A Complementary Cyber-Human Systems framework for Industry 4.0 Cyber-Physical Systems. Manufacturing Letters, 15(Pt B), 89–92. https://doi.org/10.1016/j.mfglet.2018.01.003 Kuang, C., Li, G., & Xue, X. (2019). Research and Development of E Production Management System for Garment Industry. Wuxian Hulian Keji, 16(9), 46–49. https://doi.org/10.3969/j.issn.1672-6944.2019.09.021 Kuang, W., & Jia, Y. (2018). Behaviors and Habits of News Clients Users on the Basis of Technology Acceptance Model. Journal of Shenzhen University (Humanities & Social Sciences), 35(1), 95–102. https://doi.org/10.3969/j.issn.1000-260X.2018.01.011 Kucukkoc, I., & Zhang, D. Z. (2015). Balancing of Parallel U-shaped Assembly Lines. Computers and Operations Research, 64, 233–244. https://doi.org/10.1016/j.cor.2015.05.014 Kuhn, T. S. (1970). The Structure of Scientific Revolutions, 2nd enl. ed. Chicago: University of Chicago Press. Kumar, G., Banerjee, R., Kr Singh, D., Choubey, N., & Arnaw. (2020). Mathematics for Machine Learning. Journal of Mathematical Sciences & Computational Mathematics, 1(2). https://doi.org/10.15864/jmscm.1208 Kusiak, A. (2017). Smart Manufacturing Must Embrace Big Data. In Nature, 544(7648), 23–25. https://doi.org/10.1038/544023a Ladik, D. M., & Stewart, D. W. (2008). The contribution continuum. Journal of the Academy of Marketing Science, 36(2), 157–165. https://doi.org/10.1007/s11747-008-0087-z Lai, D., Liu, B., Hu, Y., & Liu, Y. (2020). Intelligent Manufacturing Capability Assessment and Diagnosis Based on Maturity Model. Management & Technology of SME, 22, 155–156. Lan, C. (2019). A Summary of Researches on Domestic Network Learning Anxiety. Journal of HeiLongJiang Vocational Institute of Ecological Engineering, 32(4), 89–91. https://doi.org/DOI: 10.3969/j.issn.1674-6341.2019.04.028 Lee, S.K., & Yu, J. H. (2012). Success Model of Project Management Information System in Construction. Automation in Construction, 25(25), 82－93. https://doi.org/10.1016/j.autcon.2012.04.015 Lei, F., & Wang, Y. (2022). Comparison of Innovation Modes of Manufacturing Industry Intelligent Transformation Between the US, Germany and Japan: based on the Perspective of National Innovation System. Asia-Pacific Economic Review, 232(3), 72–79. https://doi.org/10.16407/j.cnki.1000-6052.2022.03.001 Li, A., Zhao, Y., Zhang, J., & Liu, X. (2019). Multi-objective Assembly Line Balancing Optimization Method Considering Complexity of Assembly Relationship. Computer Integrated Manufacturing Systems, 25(7), 1665–1675. https://doi.org/10.13196/j.cims.2019.07.007 Li, B., Chai, X., & Hou, B. (2020). “New Infrastructure” Empowers Industrial Internet in Intelligent+ Era - Industrial Internet 2.0. China Economic & Trade Herald, 14, 31–34. https://doi.org/10.3969/j.issn.1007-9777.2020.21.009 Li, G., & Tang, Y. (2020). Construction of 3D Simulation Platform for Assembly Unit of Automatic Production Line. Experimental Technology and Management, 37(1), 141-144+148. https://doi.org/10.16791/j.cnki.sjg.2020.01.035 Li, H. (2019). Research on High Quality Technology of Knitted Jeans. Knitting Industries, 3, 48–51. Li, H., & Tang, X. (2017). The Analysis of the Relationship Between Stakeholder Orientation and Enterprise Performance: The Mediating Effect of Green Innovation. Science & Technology Progress and Policy, 34(9), 6–12. https://doi.org/10.6049/kjjbydc.2017GC0090 Li, H., Liu, R., & Qu, Z. (2020). Mathematical Models and Algorithms for Facility Layout Optimization of Production Line Using AGV Material Handling System. Industrial Engineering and Management, 25(5), 103–112. https://doi.org/10.19495/j.cnki.1007-5429.2020.05.013 Li, H., Liu, Y., & Li, B. (2022). Development and Change of Men’s Jeans in China from 1978 to 2021. Journal of Clothing Research, 7(6), 540–546. https://doi.org/DOI: 10.3969/j.issn.1671-7147.2022.06.011 Li, J., Guo, C., & Ming, J. (2021). Research on the Dynamic Evolution of Factors Influencing User Satisfaction to Mobile Library. Library Development, 3, 113-121+142. https://doi.org/10.19764/j.cnki.tsgjs.20201858 Li, J., Li ,B., & Li, Q. (2023). Analysis On the Development and Evolution of Denim Clothing in China. Journal of Zhejiang Textile & Fashion College , 22(4), 67–75. https://doi.org/DOI: 10.3969/j.issn.1674-2346.2023.04.011 Li, J., Li, Y., Song, H., & Yao, B. (2021). A Study on Sustainable Supply Chain Governance Path from the Perspective of Resources and Capabilities——Based on a Case Study of Lenovo’s Global Supply Chain. Management Review, 33(9), 326–339. https://doi.org/10.14120/j.cnki.cn11-5057/f.2021.09.029 Li, J., & Liu, Z. (2021). Analysis of the Impact on the Usage of University Library WeChat Public Platform Users in Emergencies. Journal of Library Science , 43(9), 67–76. https://doi.org/DOI: 10.3969/j.issn.1002-1884.2021.09.014 Li, J., Peng, Q., Li, F., Yang, Z., Du, G., & Liu, J. (2020). Application of Lean Production in Fine Blanking Workshop. Forging & Stamping Technology, 45(4), 202–207. https://doi.org/10.13330/j.issn.1000-3940.2020.04.030 Li, K., Liu, T., & Ruan, Y. (2022). Intelligent AGV Routing Scheduling with Applications in Semi-conductor Production. Computer Integrated Manufacturing Systems, 28(9), 2970–2980. https://doi.org/10.13196/j.cims.2022.09.026 Li, L. (2018). Research on the Equilibrium Problem of T Company Assembly Production Line Based on Multi-population Genetic Algorithm. Value Engineering, 37(1), 229–231. https://doi.org/10.14018/j.cnki.cn13-1085/n.2018.01.097 Li, L., Jin, C., Lin, T., & Zhu, Y. (2022). Modeling and Simulation of Production Logistics for Intelligent Shop Manufacturing System Based on EFSM. Journal of System Simulation, 1-14. https://doi.org/10.16182/j.issn1004731x.joss.22-0802 Li, L., Shi, X., & Liu, J. (2019). 40 Years of Manufacturing in China: Intelligentization Process and Outlook. China Soft Science, 337(1), 1-9+30. https://doi.org/10.3969/j.issn.1002-9753.2019.01.001 Li, M., Tang, Q., Zheng, Q., Xia, X., & Floudas, C. A. (2017). Rules-based Heuristic Approach for the U-shaped Assembly Line Balancing Problem. Applied Mathematical Modelling, 48, 423–439. https://doi.org/10.1016/j.apm.2016.12.031 Li, P., Zhang, P., & Zhang, Z. (2018). Application of Intelligent Template Technology in Production Line Optimization of Traditional Garment Enterprises. Shanghai Textile Science & Technology, 46(6), 22-24+34. https://doi.org/10.16549/j.cnki.issn.1001-2044.2018.06.006 Li, Q., & Guo, L. (2022). Empirical Research on User Satisfaction of Shaanxi Public Cultural Digital Platform. Hubei Agricultural Sciences , 61(4), 196–201. https://doi.org/DOI: 10.14088/j.cnki.issn0439-8114.2022.04.039 Li, R., Guan, H., & Wu, Z. (2018). Study on Design Innovative Management Mode in Chinese Furniture Manufacturing Enterprises. China Forest Products Industry, 45(1), 3–7. https://doi.org/10.19531/j.issn1001-5299.201801001 Li, S. (2021). Study on the Coupling Relationship between Higher Education Structure and Industrial Structure in Yangtze River Delta [Dissertation]. East China Normal University. Li, W., Hai, B., & Yi, W. (2020). Development and Application of Key Enabling Technologies for Intelligent Manufacturing. Manufacturing Technology & Machine Tool, 4, 26–29. https://doi.org/10.19287/j.cnki.1005-2402.2020.04.003 Li, W., Liu, Y., & Shen, C. (2018). The Transmutation of China’s Textile Enterprises from Traditional Manufacturing to Intelligent Manufacturing Since the Reform and Opening Up - taking the Construction of LS Textile Enterprises’ Intelligent Manufacturing Project as an Example. Enterprise Economy, 37(10), 61–69. https://doi.org/10.13529/j.cnki.enterprise.economy.2018.10.008 Li, W., Peng, L., & Zhang, D. (2019). Research on the Post Competency of Team Leader in Construction Project. Journal of Railway Science and Engineering, 16(10), 2636–2642. https://doi.org/10.19713/j.cnki.43-1423/u.2019.10.033 Li, W., Wang, L., & Chen, Y. (2022). Analysis of Taiwan’s Industrial Innovation Development Strategy Based on AHP-SWOT Model and Its Enlightenments to Fujian. Science and Technology Management Research, 42(18), 60–67. https://doi.org/10.3969/j.issn.1000-7695.2022.18.009 Li, W., Zhang, Z., & Mei, L. (2020). The Influencing Mechanism of Big Data Capability on Business Model Innovation Under the Background of Consumption Upgrading:A Case Study Based on Xiaomi and Netease Yanxuan. Journal of Management Case Studies , 13(1), 102–117. https://doi.org/DOI: 11.7511/JMCS20200107 Li, X. (2022). Evolution of Industrial Internet Policy in Main Developed Countries and its Enlightenment to China. Regional Economic Review, 58(4), 32–44. https://doi.org/10.14017/j.cnki.2095-5766.2022.0062 Li, X. (2019). Study on the Balance Problem of V205 Production Line of Company A [Dissertation]. Beijing Jiaotong University. Li, X., Du, B., Guo, S., & Xu, R. (2017). Production Scheduling Optimization Method for Textile Machinery Manufacturing Enterprise Based on Improved Bee Algorithm. Chinese Control Conference, 2805–2811. Li, X., Li, Q., & Yin, M. (2019). Customers’ Continued Intention in Using Group-buying APP ——Analysis and Demonstration of the ECM-Based Integration Approach. Journal of Dalian University of Technology (Social Sciences) , 40(4), 56–65. https://doi.org/DOI: 10.19525/j.issn1008-407x.2019.04.008 Li, X., Zhang, Z., & Chu, J. (2020). Research on the Construction of Garment Flexible Production Line Based on Intelligent Sewing Unit. Wool Textile Journal, 48(10), 77–80. https://doi.org/10.19333/j.mfkj.20200102104 Li, Y. (2017). Research and Practice of Talent Cultivating of “Team Leader” Typed Talents of Enterprises. Vocational and Technical Education, 38(32), 40–43. https://doi.org/10.3969/j.issn.1008-3219.2017.32.015 Li, Y. (2022). A Brief Discussion on the Innovative Application ofSashiko Embroidery on Jeans. Masterpieces of Nature, 3, 64–65. https://doi.org/DOI: 10.3969/j.issn.2095-7556.2022.03.027 Li, Y., & Li, P. (2021). Design and Research on Wireless Intelligent Monitoring System for Sewage Pipeline Leakage of Textile Mill. Microprocessors and Microsystems, 81(3), 1–8. 103734. https://doi.org/10.1016/j.micpro.2020.103734 Li, Y., Ding, S., He, Y., Liu, Y., Wang, F., & Kang, J. (2021). Layout Design and Optimization for Assembly Line System Based on Simulation. Manufacturing Technology & Machine Tool, 1, 51–55. https://doi.org/10.19287/j.cnki.1005-2402.2021.01.008 Li, Y., Du, J., Chen, J., Dai, Y., & Xun, P. (2019). Research Progress in Visual Intelligent Managementof Textile and Garment Production. Shanghai Textile Science & Technology, 47(2), 7-10+33. https://doi.org/10.16549/j.cnki.issn.1001-2044.2019.02.002 Li, Y., Li, M., Wang, D., & Zhong, C. (2017). The Research and Application of Management System for Lean Production Engine Assembly Line. Modular Machine Tool & Automatic Manufacturing Technique, 3, 154–157. https://doi.org/10.13462/j.cnki.mmtamt.2017.03.040 Li, Y., Song, D., & Wang, L. (2019). Group Distributed Manufacturing Process Resource Allocation Based on Chaos Genetic Algorithm. Control and Decision, 34(6), 1178–1186. https://doi.org/10.13195/j.kzyjc.2017.1526 Li, Z., & Li, Y. (2021). German’s Inter-agency Collaboration Mechanism and Experiences for Intelligent Manufacturing: An Case of the Future AM Project. Global Science, Technology and Economy, 36(11), 28–34. https://doi.org/10.3772/j.issn.1009-8623.2021.11.005 Liang, S., Zeng, G., & Lai, J. (2023). Research on the Influence Mechanism of Hotel Robot Use Behavior under the Background of Intelligent Technology Revolution. Tourism Forum , 16(1), 82–96. https://doi.org/DOI: 10.15962/j.cnki.tourismforum.202301008 Liang, X., Huang, L., & Jiang, J. (2017). Research on Antecedent Factors of Solvers’s Continuous Participation in Crowdsourcing Logistics. Journal of Business Economics, 7, 5–15. https://doi.org/10.14134/j.cnki.cn33-1336/f.2017.07.001 Liao, Z., Cong, M., Liu, D., & Meng, F. (2018). Using Simulation in Layout Verification of Solar Module Assembly Workshop. International Journal of Modeling, Simulation, and Scientific Computing, 9(2), 1–23. https://doi.org/10.1142/S1793962318500174 Lin, L., & Lu, W. (2019). The Impact of Digital Transformation on Management Reform of Manufacturing Enterprises: A Case Study Based on Kutesmart and Haier. Scientific Decision-Making, 258(1), 85–98. https://doi.org/10.3773/j.issn.1006-4885.2019.01.085 Lin, M., & Xie, S. (2020). An Exploration on the Critical Realism Approach of Educational Qualitative Research—— Also Discuss Interpretivism and Social Constructionism. International and Comparative Education, 42(10), 99–105. https://doi.org/10.3969/j.issn.1003-7667.2020.10.013 Lin, X. (2019). An Empirical Study of Factors Influencing Mobile Video APP Users’ Willingness to Continue Using [Dissertation]. Guangxi Normal University. Lin, S. C., Tseng, H. T., Shirazi, F., Hajli, N., & Tsai, P. T. (2023). Exploring Factors Influencing Impulse Buying In Live Streaming Shopping: a Stimulus-Organism-Response (SOR) Perspective. Asia Pacific Journal of Marketing and Logistics, 35(6). https://doi.org/10.1108/APJML-12-2021-0903 Lin, Z., Liu, A., & Sun, E. (2017). Design of Control Method for Hanger Enter-and-Out-Station in Garment Hanger System. Wool Textile Journal, 45(8), 75–79. https://doi.org/10.19333/j.mfkj.2016090040805 Liu, A. (2017). Research on the Controller of Intelligent Hanging Assembly Line System [Dissertation]. Donghua University. Liu, A., Tong, Z., & Sun, Y. (2017). Research on the Gain Adaptive Fuzzy Sliding Mode Control in Clothing Hanging Pipeline Ascension Arm Device. Wool Textile Journal, 45(7), 54–59. https://doi.org/10.19333/j.mfkj.2016080090706 Liu, C., Chen, Y., & Yu, S. (2015). On the Influence Factors of Index Design and Measurement Method of Organization Performance. Commercial Science Research, 22(6), 42–46. https://doi.org/DOI: 10.3969/j.issn.1008-2107.2015.06.010 Liu, D. (2018). Research on Standard Working Hours for Garment Sewing. Qingfang Gongye Yu Jishu, 47(4), 44-46+50. https://doi.org/10.3969/j.issn.2095-0101.2018.04.013 Liu, D. (2022). Study on the Improvement of Production Management of M Company Based on Lean Production Idea [Dissertation]. Jilin University. https://doi.org/10.27162/d.cnki.gjlin.2022.003377 Liu, D., & Zhao, Y. (2024). A New Prefac. Shanghai Textile Science & Technology, 52(05), 139. https://doi.org/10.16549/j.cnki.issn.1001-2044.2024.05.004 Liu, F., Zheng, S., Liu, Z., & Zhang, L. (2021). Research of Production Line Balance Based on IE and Integer Programming Theory. Modern Manufacturing Engineering, 6, 101–115. https://doi.org/10.16731/j.cnki.1671-3133.2021.06.017 Liu, H. (2020). Introduction to the Intelligent Production Technology of Clothing Based on Machine Recognition. Light and Textile Industry and Technology, 49(4), 58–59. Liu, H. (2022). An Empirical Study on the Influencing Factors of College Students’ Adoption of Large-scale Online Learning Behavior - Based on the Perspective of S-O-R and TAM. New Media Research , 8(19), 29-34+107. https://doi.org/DOI: 10.3969/j.issn.2096-0360.2022.19.008 Liu, H., & Li, Q. (2020). New Infrastructure Accelerates the Transformation and Upgrading of Manufacturing Industry. Contemporary Economic Management, 42(9), 26–31. https://doi.org/10.13253/j.cnki.ddjjgl.2020.09.004 Liu, H., & Yan, M. (2019). A Survey and Analysis of Intention to Use Intelligent Teaching Tools Based on the Integrated Technology Acceptance Model. Higher Education Forum, 12, 54–59. https://doi.org/10.3969/j.issn.1671-9719.2019.12.015 Liu, J., Ke, W., & Liu, C. (2019). Study on the Influence Factors on the Users’ Continuance Intention of Bike-sharing Based on TAM-ECM Model. Soft Science, 33(7), 116–121. https://doi.org/10.13956/j.ss.1001-8409.2019.07.19 Liu, J. & Li, J. (2024). Intelligent Manufacturing: Concept Evolution, System Deconstruction, and High-Quality Development. Reform, 02, 75–88. Liu, J., Wang, R., & Xie, N. (2022). Strategy and Policy Comparison of Chinese and German Manufacturing Digital Transformation. Decision & Information, 550(10), 52–63. https://doi.org/10.3969/j.issn.1002-8129.2022.10.007 Liu, J., Yuan, P., & Liu, C. (2021). Analysis of Pulling Material Supply Process and Electronic Kanban System Design. Manufacturing Automation, 43(3), 24–31. https://doi.org/10.3969/j.issn.1009-0134.2021.03.007 Liu, L., Su, X., & Cheng, D. (2018). The Study on the Influential Factors of Innovative Behavior in the Research Team of Colleges and Universities on the Communication Technology Platform——Cross-Layer Moderation Effect of Team Leader Support. Science & Technology Progress and Policy, 35(10), 138–144. https://doi.org/10.6049/kjjbydc.2017120126 Liu, L., Wang, S., & Fu, Y. (2022). Design of Lean Logistics System in Assembly Workshop in Discrete SME. Manufacturing Technology & Machine Tool, 3, 166–169. https://doi.org/10.19287/j.cnki.1005-2402.2022.03.029 Liu, L., Yan, Y., & Chen, M. (2018). Optimized Design of Hanging Production Line for Uniform Jacket. Wool Textile Journal, 46(7), 8–12. https://doi.org/10.19333/j.mfkj.2017080270705 Liu, M., & Zhang, P. (2021). A Study on the Demand and Satisfaction of Short Video User-Produced Content. Journalism & Communication, 28(8), 77–128. Liu, P. (2021). Study on the Improvement of Sensor Production Line Management in Company B from the Perspective of Value Stream Theory [Dissertation]. Southwestern University. https://doi.org/10.27684/d.cnki.gxndx.2021.004482 Liu, Q. (2020). Study on Architecture of Intelligent Manufacturing Theory. China Mechanical Engineering, 31(1), 24–36. https://doi.org/10.3969/j.issn.1004-132X.2020.01.004 Liu, Q., Jiang, N., & Dai, F. (2021). A Longitudinal Case Study of Evolution Mechanism of Functional Upgrade Modes Adopted by Leader Firms in NVC:from Technology Autonomy Perspective. Science & Technology Progress and Policy, 38(16), 1–10. https://doi.org/10.6049/kjjbydc.2020120682 Liu, Q., Wang, X., & Jiang, H. (2020). A Study on the Influencing Factors of Teachers’ Intention to Use Generated Learning Resources in Blended Teacher Training for Primary and Secondary School Teachers. Modern Distance Education , 6, 24–34. https://doi.org/DOI: 10.3969/j.issn.1001-8700.2020.06.004

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