{"id":7894,"date":"2026-06-15T10:46:55","date_gmt":"2026-06-15T02:46:55","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=7894"},"modified":"2026-06-19T19:20:55","modified_gmt":"2026-06-19T11:20:55","slug":"jase-202610-33-005","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202610-33-005","title":{"rendered":"Research on Market Competitive Advantage Evaluation of Innovation and Entrepreneurship Solutions Based on Multimodal Uncertainty Quantification"},"content":{"rendered":"\n
\n
\n

<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

\n

<\/i> Volume 33<\/a><\/p>\n<\/div>\n\n\n\n

\n
\n
\n
\n

Jun Zheng<\/i><\/a><\/p>\n\n\n\n

International Business School, Xi\u2019an Fanyi University, Xi\u2019an710105, China<\/p>\n<\/div>\n\n\n\n

\n

Received: November 19, 2025
Accepted: March 1, 2026
Publication Date: June 15, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Market Competitiveness Evaluation Model for Innovation and Entrepreneurship Solutions <\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:\u00a0 BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202610_33.005<\/a>\u00a0\u00a0<\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

<\/div>\n\n\n\n

Evaluating market competitive advantage requires the effective integration of multidimensional data such as user behavior, technological evolution, and policy dynamics that are typically dispersed across platforms and characterized by uncertainty. To address these challenges, this study proposes a multimodal uncertainty-based assessment framework for innovation and entrepreneurship solutions. Grounded in a theoretical model of market competitiveness, evaluation indicators are systematically classified and screened based on principles derived from industrial cluster theory and high-tech zone competitiveness theory, enabling a structured and theoretically consistent evaluation system. Using returning migrant worker entrepreneurship as a representative case, the proposed framework evaluates the effectiveness of government support across five dimensions: administration, finance, information, financial services, and support services. To enhance robustness and discrimination among indicators, a hybrid weighting strategy is developed by integrating subjective weights obtained via the G1 method with objective weights derived from maximum deviation optimization, forming a multimodal uncertainty-based combination weighting scheme. These weights are embedded within a fuzzy comprehensive evaluation model to capture ambiguity and heterogeneity in policy effectiveness. Experimental results indicate strong administrative support, with policy documentation achieving a score of 4 (“good”), while other policy-related indicators range from 3.4 to 3.5 (“moderate”), suggesting potential for further improvement. Comparative validation demonstrates that the proposed model achieves a low mean squared error of 0.0005, outperforming conventional SD- and EVA-based approaches and confirming its superior fitting accuracy and predictive reliability.<\/p>\n\n\n\n

Keywords: Innovation and entrepreneurship plan; Competitive advantage assessment; Multimodal uncertainty quantification; G1 method subjective weighting; Maximum deviation method<\/em><\/p>\n\n\n\n

<\/div>\n\n\n\n
\n
\n
\n
    \n
  1. [1] J. Shi and X. Zhao, (2023) \u201cAnti-leakage method of network sensitive information data based on homomorphic encryption” Journal of Intelligent Systems 32(1): 20220281. DOI: 10.1515\/jisys-2022-0281.<\/li>\n
  2. [2] S. Kurma, T. A. Lestari, K. Singh, A. Paul, and S. Mumtaz, (2024) “Active RIS in digital twin-based URLLC IoT networks: Fully-connected versus sub-connected?” IEEE Transactions on Wireless Communications 23(9): 12354-12367. DOI: 10.1109\/TWC.2024.3391663.<\/li>\n
  3. [3] T. J. Silverman, M. G. Deceglie, I. Repins, M. Owen-Bellini, J. J. Berry, J. S. Stein, and L. T. Schelhas, (2025) “Durability research is pivotal for perovskite photovoltaics” Nature Energy 10(8): 934-940. DOI: 10.1038\/s41560-025-01786-w.<\/li>\n
  4. [4] H. Shi, T. Li, F. Yang, and L. Qiao, (2024) “Modeling Uncertainties Associated with Single-Valued Neutrosophic Multi-Attribute Decision-Making for Performance Evaluation of Risk Investment in Small and Medium-Sized High-Technology Venture Enterprises” Neutrosophic Sets and Systems 75(1): 17.<\/li>\n
  5. [5] V. Tatar, (2025) “Evaluation of Barriers to Digital Transformation in Maritime Logistics Based on A Spherical Fuzzy Multi-Criteria Decision-Making Framework” Verimlilik Dergisi (PRODUCTIVITY FOR LOGISTICS): 29-44. DOI: 10.51551\/verimlilik.1526042.<\/li>\n
  6. [6] X. Xing, (2025) “Licensing models for green technology patent pools-should free licences, FRAND licences, or compulsory licences be used?”:<\/li>\n
  7. [7] M. M. Thottoli. “Technology enabled Business Plan for the course entrepreneurship creativity and innovation”. In: International Conference on Environmental, Social, and Governance (ICESG 2024). Atlantis Press. 2025, 292-302. DOI: 10.2991\/978-2-38476-358-0_22.<\/li>\n
  8. [8] L. Ren and Z. Liu, (2025) “Quality Evaluation Model of Innovation and Entrepreneurship Education Based on Fuzzy” International Journal of High Speed Electronics and Systems 34(04): 2540265. DOI: 10.1142\/S0129156425402657.<\/li>\n
  9. [9] M. K. Akg\u00fcn and S. Soyg\u00fcder, (2025) “A hybrid decision-making framework for evaluating mHealth app quality: integrating fuzzy BWM with the weighted Heronian mean” International Journal of Fuzzy Systems: 1-41. DOI: 10.1007\/s40815-025-02093-y.<\/li>\n
  10. [10] D. Somaya and J. You, (2024) “Scalability, venture capital availability, and unicorns: Evidence from the valuation and timing of IPOs” Journal of Business Venturing 39(1): 106345. DOI: 10.1016\/j.jbusvent.2023.106345.<\/li>\n
  11. [11] J. Woehler and C. Ernst, (2023) “The importance of marketing mix planning and customer orientation for venture capital-financed startups: impacts on valuation, performance, and survival” Journal of Research in Marketing and Entrepreneurship 25(1): 1-25. DOI: 10.1108\/JRME-08-2021-0098.<\/li>\n
  12. [12] N. Sinha and S. Biswas, (2024) “Social entrepreneurship and philanthropic venture capital financing” Business Strategy & Development 7(3): e70011. DOI: 10.1002\/bsd2.70011.<\/li>\n
  13. [13] A. Giakoumelou, A. Salvi, O. Kvasova, and I. Rizomyliotis, (2025) “The start-up’s roadmap to private equity financing: substituting discounts with a premium in valuation for growth” International Journal of Entrepreneurial Behavior & Research 31(2-3): 479-497. DOI: 10.1108\/IJEBR-02-2022-0197.<\/li>\n
  14. [14] Y. Yang, J.-Q. Yang, R. Bao, D.-C. Zhan, H. Zhu, X.-R. Gao, H. Xiong, and J. Yang, (2021) “Corporate relative valuation using heterogeneous multi-modal graph neural network” IEEE Transactions on Knowledge and Data Engineering 35(1): 211-224. DOI: 10.1109\/TKDE.2021.3080293.<\/li>\n
  15. [15] Y. Xu, J. F. Yeung, A. P. Chan, D. W. Chan, S. Q. Wang, and Y. Ke, (2010) “Developing a risk assessment model for PPP projects in China-A fuzzy synthetic evaluation approach” Automation in construction 19(7): 929-943. DOI: 10.1016\/j.autcon.2010.06.006.<\/li>\n
  16. [16] L. Liu, (2025) “An intelligent assessment method for innovative entrepreneurial ecosystems fusing deep representation learning and causal inference” Journal of Computational Methods in Sciences and Engineering: 14727978251348633. DOI: 10.1177\/14727978251348633.<\/li>\n
  17. [17] M. Kellekci, U. Cebeci, and O. Dogan, (2025) “Prioritizing Early-Stage Start-Up Investment Alternatives Under Uncertainty: A Venture Capital Perspective” Applied Sciences 15(18): 10060. DOI: 10.3390\/app151810060.<\/li>\n
  18. [18] S. Puzovi\u0107, J. Vesi\u0107 Vasovi\u0107, D. D. Milanovi\u0107, and V. Paunovi\u0107, (2023) “A hybrid fuzzy MCDM approach to open innovation partner evaluation” Mathematics 11(14): 3168. DOI: 10.3390\/math11143168.<\/li>\n
  19. [19] Y. Xu and D. Zhang, (2025) “Identifying AI-driven emerging trends in service innovation and digitalized industries using the circular picture fuzzy WASPAS approach” Symmetry 17(9): 1546. DOI: 10.3390\/sym17091546.<\/li>\n
  20. [20] Z. Wu and N. E. Huang, (2009) “Ensemble empirical mode decomposition: a noise-assisted data analysis method” Advances in adaptive data analysis 1(01): 1\u201341. DOI: 10.1142\/S1793536909000047.<\/li>\n
  21. [21] J. H. Yoon, Y. Y. Koo, W. Lee, and D. J. Kim, (2025) “Fuzzy multinomial logistic regression analysis and its applications to sovereign credit ratings” International Journal of Fuzzy Systems: 1\u201316. DOI: 10.1007 \/ s40815-025-02013-0.<\/li>\n
  22. [22] A. Banal-Esta\u00f1ol, I. Macho-Stadler, J. Nieto-Postigo, and D. P\u00e9rez-Castrillo, (2023) “Early individual stakeholders, first venture capital investment, and exit in the UK startup ecosystem” Journal of Corporate Finance 80: 102420. DOI: 10.1016\/j.jcorpfin.2023.102420.<\/li>\n
  23. [23] M. Valaei and V. Khodakarami, (2024) “A framework for valuation and portfolio optimization of venture capital deals with contractual terms” Mathematical Problems in Engineering 2024(1): 3427721. DOI: 10.1155\/2024\/ 3427721.<\/li>\n
  24. [24] M. Jin, J. Zhang, S. Cui, M. Kang, Y. Xiao, R. Xiang, and Z. Yan. “Research on comprehensive evaluation of data link based on G1 method and entropy weight method”. In: Journal of Physics: Conference Series. 1820. 1. IOP Publishing. 2021, 012115. DOI: 10.1088\/1742- 6596\/1820\/1\/012115.<\/li>\n
  25. [25] D. Yang and Y. Ma. “Application of combination weighting based on g1-mse in qfd”. In: Journal of Physics: Conference Series. 2037. 1. IOP Publishing. 2021, 012050. DOI: 10.1088 \/ 1742 – 6596 \/ 2037 \/ 1 \/ 012050.<\/li>\n
  26. [26] A. Obayemi and K. A. Nguyen. “Uncertainty quantification of multimodal models”. In: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. Springer. 2025, 272\u2013280. DOI: 10.1007\/978-981-96-8889-0_23.<\/li>\n
  27. [27] V. A. Knights, M. Prchkovska, L. Kra\u0161njak, and J. G. Kljusuri\u0107, (2026) “Uncertainty-Aware Multimodal Fusion and Bayesian Decision-Making for DSS” Applied Math 6(1): 16. DOI: 10.3390\/appliedmath6010016.<\/li>\n
  28. [28] Z. Shao, H. Wang, Y. Cai, L. Chen, and Y. Li, (2025) “UA-Fusion: Uncertainty-aware multimodal data fusion framework for 3D object detection of autonomous vehicles” IEEE Transactions on Instrumentation and Measurement: DOI: 10.1109\/TIM.2025.3548184.<\/li>\n
  29. [29] Y. Wang, Y. Lei, N. Li, K. Feng, Z. Wang, Y. Tan, and H. Li, (2025) “Machinery multimodal uncertainty-aware RUL prediction: A stochastic modeling framework for uncertainty quantification and informed fusion” IEEE Internet of Things Journal: DOI: 10.1109\/JIOT.2025. 3573703.<\/li>\n
  30. [30] C. Wang, P. Zheng, F. Zhang, Y. Qian, Y. Zhang, and Y. Zou, (2022) “Exploring quality evaluation of innovation and entrepreneurship education in higher institutions using deep learning approach and fuzzy fault tree analysis” Frontiers in Psychology 12: 767310. DOI: 10.3389\/fpsyg.2021.767310.<\/li>\n
  31. [31] E. Khajavi, A. R. T. Khanghah, and A. J. Khiavi. “An efficient prediction of punching shear strength in reinforced concrete slabs through boosting methods and metaheuristic algorithms”. In: Structures. 74. Elsevier. 2025, 108519. DOI: 10.1016 \/ j.istruc . 2025 . 108519.<\/li>\n
  32. [32] D. Wang, X. An, X. Zhou, and X. L\u00fc, (2019) “Data cache optimization model based on cyclic genetic ant colony algorithm in edge computing environment” International Journal of Distributed Sensor Networks 15(8): 1550147719867864. DOI: 10. 1177 \/ 1550147719867864.<\/li>\n
  33. [33] X. Zhao and X. Wang, (2022) “The influence of college entrepreneurship education system on the cultivation of applied innovative talents” Frontiers in Psychology 13: 844234. DOI: 10.3389\/fpsyg.2022.844234.<\/li>\n
  34. [34] B. Naeim, A. Javadzade Khiavi, E. Khajavi, A. R. Taghavi Khanghah, A. Asgari, R. Taghipour, and M. Bagheri, (2025) “Machine learning approaches for fatigue life prediction of steel and feature importance analyses” Infrastructures 10(11): 295. DOI: 10.3390 \/ infrastructures10110295.<\/li>\n
  35. [35] Z. Yingying, W. Mei, and S. Dewen, (2023) “Analysis of Innovation and Entrepreneurship Education in Chinese Universities” Kuram ve Uygulamada Egitim Bilimleri 23(1): 15\u201327. DOI: 10.12738\/jestp.2023.1.002.<\/li>\n
  36. [36] X. Hong and W. Xingqi, (2023) “The Applicability of Kirkpatrick’s Four-Level Evaluation Model in the Evaluation of Innovation and Entrepreneurship Education in Colleges and Universities” The Theory and Practice of Innovation and Enntrepreneurship 6(8): 170.<\/li>\n
  37. [37] B. Zhang, J. Larsson, and W. Reim, (2025) “Circular business models for construction companies: a literature review and future research directions” Sustainability 17(10): 4688. DOI: 10.3390\/su17104688.<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

    <\/p>\n","protected":false},"author":3,"template":"wp-custom-template-detail-4-aricles","meta":{"_uag_custom_page_level_css":""},"categories":[12,1483,6],"tags":[1488],"acf":[],"uagb_featured_image_src":[],"uagb_author_info":{"display_name":"\u6797\u923a\u6db5","author_link":"\/jase\/?author=3"},"uagb_comment_info":0,"uagb_excerpt":" Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited. Download Citation:\u00a0 BibTeX | http:\/\/dx.doi.org\/10.6180\/jase.202610_33.005\u00a0\u00a0 Download PDF Evaluating market competitive advantage requires the effective integration of multidimensional data…","_links":{"self":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope\/7894"}],"collection":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope"}],"about":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/types\/tkuisotope"}],"author":[{"embeddable":true,"href":"\/jase\/index.php?rest_route=\/wp\/v2\/users\/3"}],"wp:attachment":[{"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7894"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7894"},{"taxonomy":"post_tag","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7894"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}