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| Dynamic and Static Analysis of Cross-Domain Technological Coopetition Based on Dual BERT Text Analysis Approach |
| Zhang Haonan1, Zhu Fangwei1, Lin Yuan2, Xu Kan3, Wang Haoyue1 |
1.School of Economics and Management, Dalian University of Technology, Dalian 116023
2.School of Public Administration and Policy, Dalian University of Technology, Dalian 116023
3.School of Computer Science and Technology, Dalian University of Technology, Dalian 116023 |
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Abstract Anchored in the strategy of strengthening the nation through corporate science and technology, we promote the development of interdisciplinary engineering projects and the advancement of cross-domain technologies within enterprises. This study proposes a strategy for matching the distribution of enterprise technology based on deep learning. Utilizing deep learning, this study constructed four types of BERT (bidirectional encoder representations from transformers) models, combining professional engineering tags to pretrain 70,000 patent texts, thereby identifying corporate attributes. By constructing a tag tension matrix and calculating the weighted cosine similarity function, a technology cooperation matching module was created to filter collaborators. Additionally, based on a temporal analysis, the technological competition and cooperation between partnering enterprises were tracked, determining the scope of cooperation. Thus, from both ‘static’ and ‘dynamic’ perspectives, a quantitative strategy for cross-domain technological cooperation in enterprises is proposed. The reliability of the method was demonstrated through a case study of a high-growth enterprise in the biopharmaceuticals engineering sector.
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Received: 04 February 2024
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1 施炳展, 李坤望. 中国制造业国际分工地位研究——基于产业内贸易形态的跨国比较[J]. 世界经济研究, 2008(10): 3-8, 87.
2 O’Sullivan A. Interpersonal boundary spanning for supplier integration in complex NPD[J]. IEEE Transactions on Engineering Management, 2022, 69(5): 2117-2128.
3 Wang Z, Szolnoki A, Perc M. Optimal interdependence between networks for the evolution of cooperation[J]. Scientific Reports, 2013, 3: Article No.2470.
4 Perc M, Jordan J J, Rand D G, et al. Statistical physics of human cooperation[J]. Physics Reports, 2017, 687: 1-51.
5 Frenkel A, Maital S, Leck E, et al. Demand-driven innovation: an integrative systems-based review of the literature[J]. International Journal of Innovation and Technology Management, 2015, 12(2): 1550008.
6 Nalebuff B J, Brandenburger A M. Coopetition—kooperativ konkurrieren: mit der spieltheorie zum gesch?ftserfolg[M]. Eschborn: Campus Fachbuch, 1996.
7 汪传雷, 简慧玲, 牛传琼. 基于专利共类的跨领域企业合作模式研究——以物流和AGV领域企业合作为例[J]. 湖南工业大学学报(社会科学版), 2020, 25(5): 37-47.
8 严玲, 李志钦, 邓娇娇. 公共建设项目中合同策略及其关系行为测量研究[J]. 科技进步与对策, 2016, 33(16): 39-46.
9 Zhou J H, Zhu J J, Wang H H. Dual-sourcing and technology cooperation strategies for developing competitive supplier in complex product systems[J]. Computers & Industrial Engineering, 2021, 159: 107482.
10 赵伟华. 复杂产品技术能力增长机理研究[J]. 经济管理, 2008, 30(10): 67-72.
11 童亮. 基于跨组织合作联结的复杂产品系统创新知识管理机制研究[D]. 杭州: 浙江大学, 2006: 37-41.
12 孙继伟. 跃上第二曲线——企业创新发展之道[J]. 经济管理, 1998(6): 19-21.
13 Hu A G Z, Jaffe A B. Patent citations and international knowledge flow[J]. International Journal of Industrial Organization, 2003, 21(6): 849-880.
14 Hoberg G, Phillips G. Product market synergies and competition in mergers and acquisitions: a text-based analysis[J]. The Review of Financial Studies, 2010, 23(10): 3773-3811.
15 Gulati V, Kumar D, Popescu D E, et al. Extractive article summarization using integrated TextRank and BM25+ algorithm[J]. Electronics, 2023, 12(2): 372.
16 Zhou N, Shi W Q, Liang R Y, et al. TextRank keyword extraction algorithm using word vector clustering based on rough data-deduction[J]. Computational Intelligence and Neuroscience, 2022, 2022: 5649994.
17 李雪山, 刘鹏鹏, 李子林, 等. 融合注意力机制的铁路科技文献关键词抽取研究[J]. 铁道学报, 2022, 44(12): 65-72.
18 王昊, 刘丹, 刘硕. 基于句法分析及主题分布的关键词抽取模型[J]. 计算机应用研究, 2022, 39(9): 2603-2607.
19 张玉洁, 白如江, 刘明月, 等. 融合语义联想和BERT的图情领域SAO短文本分类研究[J]. 图书情报工作, 2021, 65(16): 118-129.
20 李铁飞, 生龙, 吴迪. BERT-TECNN模型的文本分类方法研究[J]. 计算机工程与应用, 2021, 57(18): 186-193.
21 Yu S S, Su J D, Luo D. Improving BERT-based text classification with auxiliary sentence and domain knowledge[J]. IEEE Access, 2019, 7: 176600-176612.
22 Liu C Y, Zhao F B, Qing L Z, et al. A Chinese prompt attack dataset for LLMs with evil content[OL]. (2023-09-21). https://arxiv.org/pdf/2309.11830v1.
23 Ainslie J, Lee-Thorp J, de Jong M, et al. GQA: training generalized multi-query transformer models from multi-head checkpoints[C]// Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Stroudsburg: Association for Computational Linguistics, 2023: 4895-4901.
24 周磊, 张玉峰. 基于专利情报分析的企业合作竞争模式研究[J]. 情报学报, 2013, 32(6): 593-600.
25 肖然, 刘娟. 供应链环境下企业竞争情报合作分析[J]. 企业经济, 2011, 30(8): 44-46.
26 李翠娟, 宣国良. 知识合作剩余: 合作知识创新创造企业竞争优势的机理分析[J]. 科学学与科学技术管理, 2005, 26(7): 87-91.
27 孙玉涛, 张晓飞, 张晨. 企业与合作伙伴技术竞争如何影响产品竞争?[J]. 科学学研究, 2021, 39(1): 83-92.
28 丁树良, 祝玉芳, 林海菁, 等. Tatsuoka Q矩阵理论的修正[J]. 心理学报, 2009, 41(2): 175-181. |
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