基于大数据技术的企业并购隐性知识逆向转移

苏屹, 郭稳, 张傲然

科研管理 ›› 2022, Vol. 43 ›› Issue (9) : 48-57.

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PDF(1594 KB)
科研管理 ›› 2022, Vol. 43 ›› Issue (9) : 48-57.
论文

基于大数据技术的企业并购隐性知识逆向转移

  • 苏屹1,郭稳1,张傲然2
作者信息 +

Reverse transfer of tacit knowledge in M&A based on big data technology

  • Su Yi1, Guo Wen1,Zhang Aoran2
Author information +
文章历史 +

摘要

   大数据技术的应用可有效促进企业对隐性知识的识别与提取,提高创新效率。基于隐性知识本身固有特征和并购双方“有限理性”特征所引发的双方关于隐性知识逆向转移策略的多重选择问题,构建基于大数据技术的企业并购中并购双方隐性知识逆向转移的演化博弈模型,分析了不同因素影响下并购双方在隐性知识逆向转移中策略选择的演化路径。研究表明:大数据知识整合技术能力、大数据预测分析技术水平、目标企业隐性知识的敏感程度、转移成本与预期收益的比率等是影响双方策略选择的关键因素;处于一定范围内的大数据技术分析水平对隐性知识逆向转移有促进作用;对目标企业的补偿率存在最优区间;成本与预期收益比率的变化将导致并购双方的博弈策略向不同的方向演化。

Abstract

   In order to quickly obtain the core technology of the target enterprises, M&A has become the most effective way for enterprises to improve their competitive advantage. However, the success rate of China′s booming M&A activities is very low, and many enterprises have not obtained key technologies as they wished through M&A. As the most strategic resource of an enterprise, the enterprise′s operating experience, know-how and innovative thinking and other tacit knowledge are the source of competitive advantage. The main difficulty for Chinese enterprises to improve their performance through technological M&A lies in the low efficiency of tacit knowledge transfer and integration. The high tacit characteristics of the tacit knowledge of the targets makes the parties to the M&A whose interests are not completely the same have the right to choose whether to actively contribute and absorb the tacit knowledge. Meanwhile, with the rapid development of modern information technology, big data technology has become a powerful force to promote the efficiency of reverse tacit knowledge transfer in M&A. 
   Based on this, in order to characterize the long-term, dynamic and imperfectly rational game process of reverse tacit knowledge transfer between the both parties to the M&A, the evolutionary game theory was used in this paper. And based on the characteristics of the application of big data technology in reverse tacit knowledge transfer, the evolutionary game process of reverse tacit knowledge transfer in the context of the application of big data technology by both parties was analyzed and explored, and then understood the mechanism of the key influencing factors on the evolutionary law of the strategic choice of the both parties to the M&A. 
   The innovations of this paper are mainly reflected in: first, different from the previous research perspectives on reverse knowledge transfer in M&A, this paper considers the interactive relationship between the both parties in the process of reverse tacit knowledge transfer from the perspective of big data technology, and provides a comprehensive research perspective on reverse tacit knowledge transfer of M&A. It also provides new ideas for the potential ways of future research. Second, this paper focuses on the negative impact of cross-organizational culture and inherent characteristics of tacit knowledge on reverse knowledge transfer, and from the perspective of big data technology, the influence mechanism of various factors on reverse tacit knowledge transfer under the background of big data technology application was analyzed. It is helpful to promote the development of relevant literature, and it can also provide more specific and operable guidance for M&A.
   The research conclusions show that: first of all, the rational use of big data technology by M&A has a positive effect on reverse tacit knowledge transfer within a certain range, but excessive reliance on big data technology is counterproductive. Meanwhile, the rational use of big data technology in acquirers will enhance the willingness of targets to contribute their own sensitive tacit knowledge. Secondly, the risk cost caused by the unreasonable use of big data technology by the acquirer should be controlled within a certain range compared with the expected benefits. When the cost-to-income ratio is unacceptable and reluctant, the acquirer will eventually choose a negative strategy; When the cost-to-benefit ratio is acceptable, both parties to the merger will eventually choose an active strategy. Finally, an appropriate increase in the intensity of punishment can help both parties evolve toward the optimal direction. 
   This research expands and enriches the research perspective and research content in the field of reverse knowledge transfer. Besides, the research conclusions can provide practical guidance for the formulation of reverse tacit knowledge transfer strategies in M&A under the background of big data technology application from two aspects: improving information communication mechanisms and channels, and implementing the whole process of big data technology risk management.

关键词

隐性知识逆向转移 / 演化博弈 / 大数据技术 / 企业并购

Key words

reverse transfer of tacit knowledge / evolutionary game / big data technology / M&A

引用本文

导出引用
苏屹, 郭稳, 张傲然. 基于大数据技术的企业并购隐性知识逆向转移[J]. 科研管理. 2022, 43(9): 48-57
Su Yi, Guo Wen, Zhang Aoran. Reverse transfer of tacit knowledge in M&A based on big data technology[J]. Science Research Management. 2022, 43(9): 48-57

参考文献

[1] Rui H, Yip G S. Foreign Acquisitions by Chinese Firms: A Strategic Intent Perspective[J]. Journal of World Business, 2008, 43(2): 213-226.
[2] 程聪,谢洪明,池仁勇.中国企业跨国并购的组织合法性聚焦:内部,外部,还是内部+外部?[J].管理世界,2017(04):158-173.
Cheng C, Xie H M, Chi R Y. Focus on the Organizational Legitimacy of Chinese Companies’ Cross-border Mergers and Acquisitions: Internal, External, or Internal + External? [J]. Management World, 2017(04): 158-173.
[3] Kumar N. Managing reverse knowledge flow in multinational corporations[J]. Journal of Knowledge Management, 2013, 17(5): 695–708.
[4] Kandora M. Managing Reverse Knowledge Flows in Routine Replication Programs: The Case of Global Manufacturing ERP Template Rollout. Journal of Management and Business Administration, 2018, 26(2), 47-75.
[5] Wang N, Wang Y. Does Parenting Matter in Subsidiary Innovation in Emerging Economies? Exploring the Role of Parent Superior Competitiveness in Affecting Subsidiary Contextual Ambidexterity[J]. International Business Review, 2020, doi:10.1016/j.ibusrev.2020.101673.
[6] 赵剑波,吕铁.中国企业如何从“逆向并购”到“逆向吸收”?—以工程机械制造业跨国并购为例[J].经济管理,2016,38(07):35-47.
Zhao J B, Lv T. Reverse Knowledge Transfer in Cross-border Acquisitions: Evidence from M&A of China Engineering Mechanical Enterprises[J]. Business Management Journal, 2016, 38(07):35-47.
[7] 杜丽虹,吴先明.跨国公司逆向知识转移的母公司作用机制:基于战略和能力视角[J].科技管理研究,2017,37(09):149-156.
Du L H, Wu X M. Effecting Mechanisms of Reverse Knowledge Transfer in Parent Enterprises Investing Overseas Based on the Insights of Strategy and Capability[J]. Science and Technology Management Research, 2017, 37(09):149-156.
[8] 崔连广,冯永春,苏萌萌.中国企业海外子公司逆向知识转移研究[J].管理学报,2019,16(01):142-149.
Cui L G, Feng Y C, Su M M. Research on Reverse Knowledge Transfer of Overseas Subsidiaries of Chinese Enterprises[J]. Chinese Journal of Management, 2019, 16(01):142-149.
[9] Secches K C, Cotta D M R D. Reverse Knowledge Transfer on Emerging Market Multinationals: A Case Study of the Largest Private Bank in Latin America[J]. Latin American Business Review, 2018, 19(1): 77-103.
[10] Raziq M M, Rodrigues C D, Borini F. M., et al. Linking Corporate Entrepreneurship, Expatriation and Reverse Knowledge Transfers[J]. European Journal of Innovation Management, 2019, 23(1), 67-89.
[11] Najafi-Tavani Z, Robson M J, Zaefarian G, et al. Building Subsidiary Local Responsiveness: (When) does the Directionality of Intrafirm Knowledge Transfers Matter?[J]. Journal of World Business, 2018, 53(4), 475-492.
[12] 冯永春,苏萌萌,郑丽霞.海外子公司自主权对逆向知识转移的影响研究[J].科学学研究,2020,38(08):1451-1463.
Feng Y C, Su M M, Zheng L X. Research on the Influence of Overseas Subsidiary Autonomy on Reverse Knowledge Transfer[J]. Studies in Science of Science, 2020, 38(08):1451-1463.
[13] Su C, Kong L. The Challenge of Chinese State‐affiliated Multinationals in Benefiting from Foreign Subsidiary Knowledge Transfer: A Criticism of Light‐touch Integration[J]. Thunderbird International Business Review, 2020, 62(3):1-17.
[14] 魏江,王丁,刘洋.来源国劣势与合法化战略—新兴经济企业跨国并购的案例研究[J].管理世界,2020,36(03):101-120.
Wei J, Wang D, Liu Y. Disadvantages of Original Country and Legitimacy Strategies: Case Studies on EMNEs' Cross-border M&A[J]. Management World, 2020, 36(03):101-120.
[15] Degbey W Y, Eriksson T, Rodgers, P, & Oguji, N. Understanding Cross-border Mergers and Acquisitions of African Firms: The Role of Dynamic Capabilities in Enabling Competitiveness Amidst Contextual Constraints[J]. Thunderbird International Business Review, 2020, 43(5): 1-17.
[16] Sarala R M, Vaara E. Cultural Differences, Convergence, and Crossvergence as Explanations of Knowledge Transfer in International Acquisitions[J]. Journal of International Business Studies, 2010, 41(8): 1365-1390.
[17] 陈侃翔,谢洪明,程宣梅,王菁.新兴市场技术获取型跨国并购的逆向学习机制[J].科学学研究,2018,36(06):1048-1057.
Chen K X, Xie H M, Cheng X M. The Mechanism of Reverse Knowledge Transfer of Sourcing Cross-border Acquisitions from Emerging Market[J]. Studies in Science of Science, 2018, 36(06):1048-1057.
[18] 陈怀超,丛贞,张晶.制度落差影响跨国公司逆向知识转移的系统动力学研究—合法性与效率的逻辑[J].科技进步与对策,2020,37(03):124-132.
Chen H C, Cong Z, Zhang J. The System Dynamics Research of the Effect of Institutional Gap on Reverse Knowledge Transfer of Multinational Company—The Logic of Legitimacy and Efficiency[J]. Science & Technology Progress and Policy, 2020, 37(03):124-132.
[19] Ahsan, M, Fernhaber, S A. Multinational Enterprises: Leveraging a Corporate International Entrepreneurship Lens for New Insights into Subsidiary Initiatives[J]. Journal of International Management, 2018, 25(1), 51-65.
[20] 贾镜渝,赵忠秀.创造性资产寻求型中国企业跨国并购知识转移与动态技术能力提升——以南京汽车为例[J].现代管理科学,2015(04):9-11.
Jia J Y, Zhao X Z. Knowledge Transfer and Dynamic Technological Capability Improvement of Cross-border M&A of Creative Asset Seeking Chinese Enterprises — A Case Study of Nanjing Automobile[J]. Modern Management Science, 2015(04):9-11.
[21] Smitha R. Nair M D, Kamel M. Reverse Knowledge Transfer in Emerging Market Multinationals: The Indian Context[J]. International Business Review, 2016, 25(1): 152-164.
[22] Oh K S, Anchor J. Factors Affecting Reverse Knowledge Transfer from Subsidiaries to Multinational Companies: Focusing on the Transference of Local Market Information[J]. Canadian Journal of Administrative Sciences, 2017, 34(4): 329-342.
[23] Lingshuang K, Francesco C, Martín Martín Oscar. Expatriate Managers' Relationships and Reverse Knowledge Transfer Within Emerging Market MNCs: The Mediating Role of Subsidiary Willingness[J]. Journal of Business Research, 2018, 93: 216-229.
[24] 金源,李东红,金占明.社会资本在跨国并购逆向知识转移中的作用—以中国化工并购法国安迪苏为例[J].国际经济合作,2017(03):57-62.
Jin Y, Li D H, Jin Z M. The Role of Social Capital in Reverse Knowledge Transfer of Cross-border M&A — A Case Study of China's Chemical M&A of France Adisseo[J]. Journal of International Economic Cooperation, 2017(03):57-62.
[25] Quinn J B. The Intelligent Enterprise a New Paradigm[J]. The Executive, 1992, 6(4): 48-63.
[26] 余向前,张正堂,张一力.企业家隐性知识、交接班意愿与家族企业代际传承[J].管理世界,2013(11):77-88+188.
Yu X Q, Zhang Z T, Zhang Y L. The Tacit Knowledge of the Entrepreneur, the Succession Willingness and the Intergenerational Succession in Family Business[J]. Management World, 2013(11):77-88+188.
[27] 侯贵生,郭延禄,杨磊.立象尽意:基于“象思维”视角的隐性知识共享研究[J].情报科学,2019,37(11):11-19.
Hou G S, Guo Y L, Yang L. Image up, Meaning out: Research on Tacit Knowledge Sharing Based on the Perspective of “Imaging Thinking”[J]. Information Science, 2019, 37(11):11-19.
[28] 张志勇.基于动态网络模型的研发团队隐性知识转移研究[J].运筹与管理,2007,16(06):142-147.
Zhang Z Y. Dynamic Network Model of Tacit Knowledge Transfer among R&D Groups[J]. Operations Research and Management Science, 2007, 16(06):142-147.
[29] 王诗翔,魏江,路瑶.跨国技术并购中吸收能力与技术绩效关系研究-基于演化博弈论[J].科学学研究,2014,32(12):1828-1835.
Wang S X, Wei J, Lu Y. The Impact of Absorptive Capacity on Technological Performance in Transnational Technology M&As Based on Evolutionary Game Theory[J]. Studies in Science of Science, 2014, 32(12):1828-1835.
[30] Cooper P. Data, Information, Knowledge and Wisdom[J]. Anaesthesia & Intensive Care Medicine, 2014, 15(1): 44-45.
[31] Akhtar P., Z. Khan R. Rao-Nicholson M., et al. Building Relationship Innovation in Global Collaborative Partnerships: Big Data Analytics and Traditional Organizational Powers[J]. R&D Management, 2019, 49(1): 7-20.
[32] Braganza A L, Brooks D, Nepelski M, et al. Resource Management in Big Data Initiatives: Processes and Dynamic Capabilities[J]. Journal of Business Research, 2017, 70: 328-337.
[33] El-Kassar A N, Singh S K, Green Innovation and Organizational Performance: The Influence of Big Data and the Moderating Role of Management Commitment and HR Practices[J]. Technological Forecasting and Social Change, 2019, 144: 483-498.
[34] 赵付春.大数据环境下用户隐私保护和信任构建[J].探索与争鸣,2017,1(12):97-100.
Zhao F C. User Privacy Protection and Trust Construction in Big Data Environment[J]. Exploration and Free Views, 2017, 1(12):97-100.
[35] 魏道江,李慧民,康承业.组织内部知识共享激励机制研究—基于知识接受者评价模式[J].科学学与科学技术管理,2014,35(7):23-30.
Wei D J, Li H M, Kang C Y. A Research on Incentive Mechanism of Knowledge Sharing Within the Organization: A Model Based on the Evaluation of Knowledge Recipient[J]. Science of Science and Management of S.&T., 2014, 35(7):23-30.
[36] Kwan M M, Cheung P. The Knowledge Transfer Process: From Field Studies to Technology Development[J]. Journal of Database Management, 2006, 17 (6):16-32.
[37] Liu D, Ren X B. Research on Knowledge Transfer Dynamic Mechanism of School – Enterprise Cooperation Innovation Network Based on the Evolution of Trust[J]. Science Technology & Industry, 2014, 6(6): 391-396.
[38] Kenneth H, Snejina M. Diagnosing and Fighting Knowledge Sharing Hostility[J]. Organizational Dynamics, 2002, 31(1): 60-73.
[39] Kenneth H, Snejina M, Dana B. Minbaeva et al. Knowledge-sharing Hostility and Governance Mechanisms: An Empirical Test[J]. Journal of Knowledge Management, 2012, 16(5): 754-773.
[40] 刘晓婷,佟泽华,师闻笛.大数据时代科研人员数据共享演化博弈研究:信任机制视角[J].情报理论与实践,2019,42(03):92-100.
Liu X T, Tong Z H, Shi W D. An Evolutionary Game of Scientific Researchers’ Data Sharing in the Big Data Era: from the Trust Mechanism Perspective[J]. Information Studies: Theory & Application, 2019, 42(03):92-100.
[41] 徐岩,胡斌,杨永清.团队知识共享行为的随机突变模型及仿真[J].运筹与管理,2013,22(05):240-249.
Xu Y, Hu B, Yang Y Q. A Stochastic Catastrophe Model of Knowledge Sharing Within a Team Including Simulations[J]. Operations Research and Management Science, 2013, 22(05):240-249.
[42] Friedman D. Evolutionary Games in Economics[J]. Econometrica, 1991, 59(3): 637.
[43] 约翰·D·斯特曼.商务动态分析方法:对复杂世界的系统思考与建模[M].清华大学出版社,2008.
John D Sterman. Business Dynamic Analysis Method: Systematic Thinking and Modeling of Complex World [M]. Tsinghua University Press, 2008.
[44] 李天博,齐二石,李青.企业并购文化整合的演化博弈及动态仿真研究[J].软科学,2017,31(03):42-48.
Li T B, Qi E S, Li Q. The Evolutionary Game and Dynamic Simulation of Cultural Integration of Enterprises’ Mergers and Acquisitions[J]. Soft Science, 2017, 31(03):42-48.
[45] 周国华,张羽,李延来,赵国堂.基于前景理论的施工安全管理行为演化博弈[J].系统管理学报,2012,21(4):501-509.
Zhou G H, Zhang Y, Li Y L, et al. Evolutionary Game Analysis of the Behavior of Construction Safety Management Based on Prospect Theory[J]. Journal of Systems & Management, 2012, 21(4):501-509.
[46] 于鲲鹏,郭东强.转型企业知识转移的非对称演化博弈分析[J].情报科学,2013,31(3):87-91.
Yu K P, Guo D Q. Analysis of Non-Symmetric Evolutionary Game of Transformation Business Knowledge Transfer[J]. Information Science, 2013, 31(3):87-91.
[47] 吴洁,吴小桔,李鹏等.基于累积前景理论的联盟企业知识转移演化博弈分析[J].运筹与管理,2017,26(03):92-99.
Wu J, Wu X J, Li P. Evolutionary Game Analysis of Knowledge Transfer in Industry Alliance Based on Cumulative Prospect Theory[J]. Operations Research and Management Science, 2017, 26(03):92-99.

基金

国家自然科学基金项目(72074059,2021—2024);黑龙江省社会科学基金项目(20GLB120,2020—2023);黑龙江省重点研发计划指导类项目(GZ20210003,2021—2023)。

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