{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T03:15:53Z","timestamp":1770779753458,"version":"3.50.0"},"reference-count":57,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T00:00:00Z","timestamp":1675123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2020R1A2C1005918"],"award-info":[{"award-number":["NRF-2020R1A2C1005918"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2022R1I1A1A01069422"],"award-info":[{"award-number":["NRF-2022R1I1A1A01069422"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>In contemporary times, science-based technologies are needed for launching innovative products and services in the market. As technology-based management strategies are gaining importance, associated patents need to be comprehensively studied. Previous studies have proposed predictive models based on patent factors. However, technology-based management strategies can influence the growth and decline of firms. Thus, this study aims to estimate uncertainties of the factors that are frequently used in technology-based studies. Furthermore, the importance of the factors may fluctuate over time. Therefore, we propose a Bayesian neural network model based on Flipout and four research hypotheses to evaluate the validity of our method. The proposed method not only estimates the uncertainties of the factors, but also predicts the future value of technologies. Our contribution is to (i) provide a tractable Bayesian neural network applicable to big data, (ii) discover factors that affect the value of technology, and (iii) present empirical evidence for the timeliness and objectivity of technology evaluation. In our experiments, 3781 healthcare-related cases of patents were used, and we found that the proposed hypotheses were all statistically significant. Therefore, we believe that reliable and stable technology-based management strategies can be established through our method.<\/jats:p>","DOI":"10.3390\/axioms12020145","type":"journal-article","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T01:36:59Z","timestamp":1675215419000},"page":"145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Estimation of Uncertainty for Technology Evaluation Factors via Bayesian Neural Networks"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3337-1134","authenticated-orcid":false,"given":"Juhyun","family":"Lee","sequence":"first","affiliation":[{"name":"Institute of Engineering Research, Korea University, Seoul 02841, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6804-2707","authenticated-orcid":false,"given":"Sangsung","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Data Science, Cheongju University, Chungbuk 28503, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0491-9690","authenticated-orcid":false,"given":"Junseok","family":"Lee","sequence":"additional","affiliation":[{"name":"Machine Learning Big Data Institute, Korea University, Seoul 02841, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1016\/S0048-7333(00)00118-9","article-title":"Science\u2013Industry Interaction in the Process of Innovation: The Importance of Boundary-Crossing between Systems","volume":"30","author":"Kaufmann","year":"2001","journal-title":"Res. Policy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.respol.2015.07.005","article-title":"Technological Diversification, Core-Technology Competence, and Firm Growth","volume":"45","author":"Kim","year":"2016","journal-title":"Res. Policy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1108\/02621710710726062","article-title":"An Empirical Analysis of Core Competence for High-Tech Firms and Traditional Manufacturers","volume":"26","author":"Chen","year":"2007","journal-title":"J. Manag. Dev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1109\/TEM.2005.861813","article-title":"Patent Portfolio Diversity, Technology Strategy, and Firm Value","volume":"53","author":"Lin","year":"2006","journal-title":"IEEE Trans. Eng. Manag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.jbusres.2019.04.020","article-title":"Patent Portfolio Diversity and Firm Profitability: A Question of Specialization or Diversification?","volume":"101","author":"Appio","year":"2019","journal-title":"J. Bus. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.techfore.2015.07.016","article-title":"Technological Advances in the Fuel Cell Vehicle: Patent Portfolio Management","volume":"100","author":"Ha","year":"2015","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Shi, X., Cai, L., and Song, H. (2019). Discovering Potential Technology Opportunities for Fuel Cell Vehicle Firms: A Multi-Level Patent Portfolio-Based Approach. Sustainability, 11.","DOI":"10.3390\/su11226381"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.techfore.2011.07.002","article-title":"Bin Using Patent Analysis to Establish Technological Position: Two Different Strategic Approaches","volume":"79","author":"Chang","year":"2012","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.techfore.2016.11.023","article-title":"A Novel Approach to Forecast Promising Technology through Patent Analysis","volume":"117","author":"Kim","year":"2017","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.wpi.2018.05.001","article-title":"Citations as a Measure of Technological Impact: A Review of Forward Citation-Based Measures","volume":"53","author":"Aristodemou","year":"2018","journal-title":"World Pat. Inf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1515\/jbvela-2016-0002","article-title":"Patent Valuation with Forecasts of Forward Citations","volume":"12","author":"Falk","year":"2017","journal-title":"J. Bus. Valuat. Econ. Loss Anal."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1111\/j.1468-0297.2004.00216.x","article-title":"Patent Quality and Research Productivity: Measuring Innovation with Multiple Indicators","volume":"114","author":"Lanjouw","year":"2004","journal-title":"Econ. J."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1007\/s10961-014-9367-6","article-title":"Patent Valuation Based on Text Mining and Survival Analysis","volume":"40","author":"Han","year":"2015","journal-title":"J. Technol. Transf."},{"key":"ref_14","first-page":"1521","article-title":"Worthless Patents","volume":"20","author":"Moore","year":"2005","journal-title":"Berkeley Technol. Law J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1016\/j.respol.2008.03.005","article-title":"Internal Sequential Innovations: How Does Interrelatedness Affect Patent Renewal?","volume":"37","author":"Liu","year":"2008","journal-title":"Res. Policy"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1016\/S0048-7333(99)00093-1","article-title":"Technology Transfer and Public Policy: A Review of Research and Theory","volume":"29","author":"Bozeman","year":"2000","journal-title":"Res. Policy"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1007\/s10961-016-9491-6","article-title":"A Review of Qualitative Case Methods Trends and Themes Used in Technology Transfer Research","volume":"42","author":"Cunningham","year":"2016","journal-title":"J. Technol. Transf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1080\/09537325.2018.1516864","article-title":"Exploring Promising Vacant Technology Areas in a Technology-Oriented Company Based on Bibliometric Analysis and Visualisation","volume":"31","author":"Yoon","year":"2019","journal-title":"Technol. Anal. Strateg. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1016\/j.respol.2015.06.006","article-title":"What Is an Emerging Technology?","volume":"44","author":"Rotolo","year":"2015","journal-title":"Res. Policy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.technovation.2017.10.006","article-title":"How to Improve a Technology Evaluation Model: A Data-Driven Approach","volume":"72\u201373","author":"Noh","year":"2018","journal-title":"Technovation"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lee, J., Kang, J., Park, S., Jang, D., and Lee, J. (2020). A Multi-Class Classification Model for Technology Evaluation. Sustainability, 12.","DOI":"10.3390\/su12156153"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Jun, S. (2022). Text Data Analysis Using Generalized Linear Mixed Model and Bayesian Visualization. Axioms, 11.","DOI":"10.3390\/axioms11120674"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Uhm, D., and Jun, S. (2022). Zero-Inflated Patent Data Analysis Using Generating Synthetic Samples. Futur. Internet, 14.","DOI":"10.3390\/fi14070211"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Lee, J., and Park, S. (2022). A Study on the Calibrated Confidence of Text Classification Using a Variational Bayes. Appl. Sci., 12.","DOI":"10.3390\/app12189007"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"122161","DOI":"10.1016\/j.techfore.2022.122161","article-title":"Exploring a Technology Ecology for Technology Opportunity Discovery: A Link Prediction Approach Using Heterogeneous Knowledge Graphs","volume":"186","author":"Choi","year":"2023","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/0040-1625(91)90002-W","article-title":"An Evaluation of Delphi","volume":"40","author":"Woudenberg","year":"1991","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1108\/MEQ-09-2014-0133","article-title":"The Application of Delphi and AHP Method in Environmentally Conscious Solid Waste Treatment and Disposal Technology Selection","volume":"27","author":"Kharat","year":"2016","journal-title":"Manag. Environ. Qual."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1007\/s10961-006-0022-8","article-title":"Predicting Technology Success: Identifying Key Predictors and Assessing Expert Evaluation for Advanced Technologies","volume":"31","author":"Galbraith","year":"2006","journal-title":"J. Technol. Transf."},{"key":"ref_29","unstructured":"Akoka, J., and Comyn-Wattiau, I. (2017). Conceptual Modeling Perspectives, Springer."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"100907","DOI":"10.1016\/j.rtbm.2022.100907","article-title":"A Delphi Study of Business Models for Cycling Urban Mobility Platforms","volume":"45","author":"Carvalho","year":"2022","journal-title":"Res. Transp. Bus. Manag."},{"key":"ref_31","first-page":"392","article-title":"A Novel Methodology for Extracting Core Technology and Patents by IP Mining","volume":"25","author":"Kim","year":"2015","journal-title":"J. Korean Inst. Intell. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"16175","DOI":"10.3390\/su71215809","article-title":"A Predictive Model of Technology Transfer Using Patent Analysis","volume":"7","author":"Choi","year":"2015","journal-title":"Sustainability"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"658","DOI":"10.1177\/0165551519887878","article-title":"Topic Modelling and Social Network Analysis of Publications and Patents in Humanoid Robot Technology","volume":"47","author":"Kumari","year":"2021","journal-title":"J. Inf. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"122173","DOI":"10.1016\/j.techfore.2022.122173","article-title":"Mapping Technological Trajectories and Exploring Knowledge Sources: A Case Study of E-Payment Technologies","volume":"186","author":"Lai","year":"2023","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_35","first-page":"700","article-title":"Some Methods Determining Reasonable Royalty Rates for Patent Valuation\u2014An Infringement Damages Model","volume":"15","author":"Yang","year":"2012","journal-title":"J. Korea Technol. Innov. Soc."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.aei.2011.06.005","article-title":"A Patent Quality Analysis for Innovative Technology and Product Development","volume":"26","author":"Trappey","year":"2012","journal-title":"Adv. Eng. Inform."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.cie.2019.04.011","article-title":"A Transferability Evaluation Model for Intellectual Property","volume":"131","author":"Ko","year":"2019","journal-title":"Comput. Ind. Eng."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1334","DOI":"10.1109\/TEM.2019.2957842","article-title":"Patent Value Analysis Using Deep Learning Models\u2014The Case of IoT Technology Mining for the Manufacturing Industry","volume":"68","author":"Trappey","year":"2021","journal-title":"IEEE Trans. Eng. Manag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"120146","DOI":"10.1016\/j.techfore.2020.120146","article-title":"Early Detection of Valuable Patents Using a Deep Learning Model: Case of Semiconductor Industry","volume":"158","author":"Chung","year":"2020","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Lee, C.-W., Tao, F., Ma, Y.-Y., and Lin, H.-L. (2022). Development of Patent Technology Prediction Model Based on Machine Learning. Axioms, 11.","DOI":"10.3390\/axioms11060253"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Huang, Z., Li, J., and Yue, H. (2022). Study on Comprehensive Evaluation Based on AHP-MADM Model for Patent Value of Balanced Vehicle. Axioms, 11.","DOI":"10.3390\/axioms11090481"},{"key":"ref_42","unstructured":"Lecun, Y. (1988). Proceedings of the 1988 Connectionist Models Summer School, Morgan Kaufmann."},{"key":"ref_43","unstructured":"Nair, V., and Hinton, G. (2010, January 21\u201324). Rectified Linear Units Improve Restricted Boltzmann Machines. Proceedings of the ICML\u201910: 27th International Conference on Machine Learning, Haifa, Israel."},{"key":"ref_44","first-page":"1929","article-title":"Dropout: A Simple Way to Prevent Neural Networks from Overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref_45","first-page":"1","article-title":"A Theoretically Grounded Application of Dropout in Recurrent Neural Networks","volume":"29","author":"Gal","year":"2016","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_46","unstructured":"Blundell, C., Cornebise, J., Kavukcuoglu, K., and Com, W. (2015, January 6\u201311). Weight Uncertainty in Neural Networks. Proceedings of the ICML\u201915: 32nd International Conference on Machine Learning, Lille, France."},{"key":"ref_47","first-page":"1","article-title":"Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm","volume":"29","author":"Liu","year":"2016","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_48","first-page":"1","article-title":"Practical Variational Inference for Neural Networks","volume":"24","author":"Graves","year":"2011","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_49","first-page":"1058","article-title":"Regularization of Neural Networks Using DropConnect","volume":"28","author":"Wan","year":"2013","journal-title":"PMLR"},{"key":"ref_50","unstructured":"Kingma, D.P., and Welling, M. (2013). Auto-Encoding Variational Bayes. arXiv."},{"key":"ref_51","first-page":"1","article-title":"Variational Dropout and the Local Reparameterization Trick","volume":"28","author":"Kingma","year":"2015","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_52","unstructured":"Wen, Y., Vicol, P., Ba, J., Tran, D., and Grosse, R. (2018). Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. arXiv."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1038\/s41591-018-0316-z","article-title":"A Guide to Deep Learning in Healthcare","volume":"25","author":"Esteva","year":"2019","journal-title":"Nat. Med."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2603","DOI":"10.1109\/JBHI.2018.2887209","article-title":"Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks","volume":"23","author":"Ding","year":"2019","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1624","DOI":"10.1126\/sciadv.abj1624","article-title":"CancerVar: An Artificial Intelligence\u2013Empowered Platform for Clinical Interpretation of Somatic Mutations in Cancer","volume":"8","author":"Li","year":"2022","journal-title":"Sci. Adv."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1093\/biomet\/52.3-4.591","article-title":"Biometrika Trust An Analysis of Variance Test for Normality (Complete Samples)","volume":"52","author":"Shapiro","year":"1965","journal-title":"Biometrika"},{"key":"ref_57","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., and Polosukhin, I. (2017). Attention Is All You Need. arXiv."}],"container-title":["Axioms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1680\/12\/2\/145\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:19:26Z","timestamp":1760120366000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1680\/12\/2\/145"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,31]]},"references-count":57,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["axioms12020145"],"URL":"https:\/\/doi.org\/10.3390\/axioms12020145","relation":{},"ISSN":["2075-1680"],"issn-type":[{"value":"2075-1680","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,31]]}}}