全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

人工智能影响企业管理决策的内在逻辑与分析框架
The Intrinsic Logic and Analytical Framework of Artificial Intelligence’s Impact on Enterprise Management Decisions

DOI: 10.12677/mm.2025.151019, PP. 141-153

Keywords: 人工智能,企业管理决策,决策辅助系统,决策实施,决策主体,最优决策
Artificial Intelligence
, Enterprise Management Decision, Decision Support System, Decision Implementation, Decision Subject, Optimal Decision

Full-Text   Cite this paper   Add to My Lib

Abstract:

人工智能在企业经营活动中的应用,使其成为了企业管理决策的辅助系统。特别是以大数据和深度算法为代表的人工智能技术,突破了企业传统决策中“信息不充分”以及“依赖主观经验”的局限,促使企业管理决策从“满意原则”向“最优原则”转变,已然成为新时代企业进行科学、高效决策不可或缺的新工具。本研究以从“满意决策”到“最优决策”为出发点,结合人工智能特性及人工智能对企业管理决策影响的相关研究,从决策基础、决策主体、决策实施、决策本质四个方面剖析其影响决策的内在逻辑,得出以下推论:其一,人工智能从信息链智能化升级、聚集效率、多向交互协同等方面提升企业决策依据的效用;其二,政府政策、产业环境等会影响人工智能在企业管理决策中的应用;其三,人工智能推动企业决策制度从中央集权式转变为全员授权式;其四,企业高层态度和组织资源会影响人工智能在企业管理决策中的应用;其五,人工智能使企业经营目标分解与评价更具科学性;其六,人工智能将决策修正时机提前;其七,人工智能促使企业决策从“经验 + 信息”驱动转变为“信息链 + 算法”驱动,从生理有限理性决策转变为科学完全理性决策。
The application of artificial intelligence in business activities has transformed it into an auxiliary system for enterprise management decision-making. In particular, artificial intelligence technologies, represented by big data and deep algorithms, have overcome the limitations of “insufficient information” and “reliance on subjective experience” in traditional enterprise decision-making. This has facilitated a shift from the “satisfaction principle” to the “optimal principle” in enterprise management decision-making, making AI an indispensable tool for scientific and efficient decision-making in the new era. This study begins with the transition from “satisfactory decision-making” to “optimal decision-making”. By integrating the characteristics of artificial intelligence with related research on its impact on enterprise management decision-making, it analyzes the inherent logic of how AI influences decision-making from four perspectives: decision-making basis, decision-making subject, decision-making implementation, and decision-making essence. The study arrives at the following conclusions: Firstly, AI enhances the effectiveness of enterprise decision-making by improving the intelligence of the information chain, aggregation efficiency, and facilitating multi-directional interaction and coordination. Secondly, government policies and industrial environment influence the application of AI in enterprise management decision-making. Thirdly, AI promotes the transformation of the enterprise decision-making system from a centralized to a fully delegated approach. Fourthly, the attitude of top management and organizational resources affect the application of AI in enterprise management decision-making. Fifthly, AI makes the decomposition and evaluation of business

References

[1]  徐鹏, 徐向艺. 人工智能时代企业管理变革的逻辑与分析框架[J]. 管理世界, 2020, 36(1): 122-129.
[2]  Minsky, M. (1961) Steps toward Artificial Intelligence. Proceedings of the IRE, 49, 8-30.
https://doi.org/10.1109/jrproc.1961.287775
[3]  Čerka, P., Grigienė, J. and Sirbikytė, G. (2015) Liability for Damages Caused by Artificial Intelligence. Computer Law & Security Review, 31, 376-389.
https://doi.org/10.1016/j.clsr.2015.03.008
[4]  贺倩. 人工智能技术发展研究[J]. 现代电信科技, 2016, 46(2): 18-21, 27.
[5]  张鑫. 2019全球人工智能产业发展回顾与展望[J]. 新经济导刊, 2019(4): 46-50.
[6]  李德毅. AI——人类社会发展的加速器[J]. 智能系统学报, 2017, 12(5): 583-589.
[7]  柳峰. 中国IT企业云计算技术采纳研究[D]: [博士学位论文]. 北京: 中国人民大学, 2010.
[8]  杨寅, 刘勤, 吴忠生. 科技资源开放共享平台创新扩散的关键因素研究——基于TOE理论框架[J]. 现代情报, 2018, 38(1): 69-75.
[9]  Kumar, A. and Kalse, A. (2021) WITHDRAWN: Usage and Adoption of Artificial Intelligence in SMEs. Materials Today: Proceedings.
https://doi.org/10.1016/j.matpr.2021.01.595
[10]  万江心, 张云龙, 田新月, 等. 人工智能的应用场景[J]. 现代企业文化, 2018(6): 28-29.
[11]  刘成, 李秀峰. “AI + 公共决策”: 理论变革、系统要素与行动策略[J]. 哈尔滨工业大学学报(社会科学版), 2020, 22(2): 12-18.
[12]  谷方杰, 张文锋. 基于价值链视角下企业数字化转型策略探究——以西贝餐饮集团为例[J]. 中国软科学, 2020(11): 134-142.
[13]  刘锦涛. 浅议人工智能发展历程及核心技术[J]. 中国科技纵横, 2019(18): 35-36.
[14]  张洪国, 陆平, 邵立国, 等. 中国人工智能发展简史[J]. 互联网经济, 2017(6): 84-91.
[15]  何军. 大数据对企业管理决策影响分析[J]. 科技进步与对策, 2014(4): 65-68.
[16]  Meagher, K. and Wait, A. (2008) Who Decides about Change and Restructuring in Organizations? SSRN Electronic Journal.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1271754
[17]  马学忠, 李世强. 大数据时代决策理论在企业管理中的应用[J]. 管理纵横, 2014(4): 8-9.
[18]  耿裕华. 建立完整智慧化信息链提高企业决策水平[J]. 建筑, 2018(2): 16-18.
[19]  百度、德勤管理咨询解析《知识中台白皮书》聚焦企业智能化跃升[EB/OL]. 2020-12-19.
https://www.sohu.com/a/439261345_630344, 2023-12-10.
[20]  陈国青, 曾大军, 卫强, 等. 大数据环境下的决策范式转变与使能创新[J]. 管理世界, 2020, 32(2): 95-105.
[21]  Alan N. Fish. 决策知识自动化: 大数据时代的商业决策分析方法[M]. 王飞跃, 王晓, 郑心湖, 等, 译. 北京: 人民邮电出版社, 2016.
[22]  耿如天. 大数据对企业管理决策影响分析[J]. 中小企业管理与科技, 2021, 22(5): 19-21.
[23]  Peiris, K.D.A., Jung, J. and Gallupe, R.B. (2015) Building and Evaluating ESET: A Tool for Assessing the Support Given by an Enterprise System to Supply Chain Management. Decision Support Systems, 77, 41-54.
https://doi.org/10.1016/j.dss.2015.05.004
[24]  DuHadway, S., Carnovale, S. and Hazen, B. (2017) Understanding Risk Management for Intentional Supply Chain Disruptions: Risk Detection, Risk Mitigation, and Risk Recovery. Annals of Operations Research, 283, 179-198.
https://doi.org/10.1007/s10479-017-2452-0
[25]  Liu, C., Xiang, X. and Zheng, L. (2019) Value of Information Sharing in a Multiple Producers-Distributor Supply Chain. Annals of Operations Research, 285, 121-148.
https://doi.org/10.1007/s10479-019-03259-2
[26]  Muggy, L. and Heier Stamm, J.L. (2019) Decentralized Beneficiary Behavior in Humanitarian Supply Chains: Models, Performance Bounds, and Coordination Mechanisms. Annals of Operations Research, 284, 333-365.
https://doi.org/10.1007/s10479-019-03246-7
[27]  Grover, P., Kar, A.K. and Dwivedi, Y.K. (2020) Understanding Artificial Intelligence Adoption in Operations Management: Insights from the Review of Academic Literature and Social Media Discussions. Annals of Operations Research, 308, 177-213.
https://doi.org/10.1007/s10479-020-03683-9
[28]  王改性. 企业信息资源开发与利用研究[J]. 时代经贸, 2018(24): 101-102.
[29]  刘莉. “数据-信息-情报”转化理论与实证研究[D]: [硕士学位论文]. 长春: 东北师范大学, 2014.
[30]  郭华, 宋雅雯, 曹如中, 等. 数据、信息、知识与情报逻辑关系及转化模型[J]. 图书馆理论与实践, 2016(10): 43-46, 51.
[31]  于洪, 何德牛, 王国胤, 等. 大数据智能决策[J]. 自动化学报, 2020, 46(5): 878-896.
[32]  陈涛. 大数据对企业管理决策的影响分析[J]. 企业改革与管理, 2017(23): 11-32.
[33]  徐蕾. 企业经营者特质对微型企业电子商务采纳意愿影响的实证研究[D]: [博士学位论文]. 成都: 西南交通大学, 2016.
[34]  Dirican, C. (2015) The Impacts of Robotics, Artificial Intelligence on Business and Economics. ProcediaSocial and Behavioral Sciences, 195, 564-573.
https://doi.org/10.1016/j.sbspro.2015.06.134
[35]  Bolton, C., Machová, V., Kovacova, M. and Valášková, K. (2018) The Power of Human-Machine Collaboration: Artificial Intelligence, Business Automation, and the Smart Economy. Economics, Management and Financial Markets, 13, 51-56.
[36]  刘雪宁. 人工智能发展对经济的影响[J]. 合作经济与科技, 2019(15): 34-35.
[37]  张俊杰, 杨利. 大数据背景下企业决策管理的现实困境与应对策略[J]. 商业经济研究, 2015(7): 106-107.
[38]  王峰. 建立健全国有企业科学决策机制[EB/OL]. 2020-04-13.
http://www.jjckb.cn/2020-04/13/c_138970623.htm, 2023-12-13.
[39]  李忠尚. 论科学决策和国家治理现代化——从智囊、软科学到智库的理论与实践[J]. 智库理论与实践, 2018, 3(3): 8-16.
[40]  胡大立. 企业竞争力决定因素及其形成机理分析[M]. 北京: 经济管理出版社, 2005.
[41]  李俊山, 刘俊生. 提高企业核心竞争力的重要途径[J]. 沈阳农业大学学报(社会科学版), 2008, 10(1): 30-32.
[42]  Gonçalves, J.M., Ferreira, F.A.F., Ferreira, J.J.M. and Farinha, L.M.C. (2019) A Multiple Criteria Group Decision-Making Approach for the Assessment of Small and Medium-Sized Enterprise Competitiveness. Management Decision, 57, 480-500.
https://doi.org/10.1108/md-02-2018-0203
[43]  Zhuang, Y., Wu, F., Chen, C. and Pan, Y. (2017) Challenges and Opportunities: From Big Data to Knowledge in AI 2.0. Frontiers of Information Technology & Electronic Engineering, 18, 3-14.
https://doi.org/10.1631/fitee.1601883
[44]  刘刚. 企业组织的决策过程及其效率分析[J]. 经济理论与经济管理, 2000(3): 34-38.
[45]  沈蕾. 论专业化分工与我国大企业的发展[J]. 经济问题探索, 2004(7): 4-6.
[46]  He, Z.L., Zhang, Z.L., and Sun, H. (2018) On the Relationship between the Specialization of China’s Tourism and Economic Growth. Journal of Xinjiang Normal University (Edition of Philosophy and Social Sciences), 39, 151-160.
[47]  张汉文. 完善企业决策机制与运行模式提高企业效率[J]. 市场周刊∙理论版, 2020(17): 13-14.
[48]  李忠顺, 周丽云, 谢卫红, 等. 大数据对企业管理决策影响研究[J]. 科技管理研究, 2015, 35(14): 160-166.
[49]  Shrestha, Y.R., Ben-Menahem, S.M. and von Krogh, G. (2019) Organizational Decision-Making Structures in the Age of Artificial Intelligence. California Management Review, 61, 66-83.
https://doi.org/10.1177/0008125619862257
[50]  张武农. 集成管理决策探讨[J]. 武汉理工大学学报(信息与管理工程版), 2002, 24(6): 55-58.
[51]  Chatterjee, D., Grewal, R. and Sambamurthy, V. (2002) Shaping up for E-Commerce: Institutional Enablers of the Organizational Assimilation of Web Technologies. MIS Quarterly, 26, 65-89.
https://doi.org/10.2307/4132321
[52]  刘伟鑫, 陈允行. 探究网络时代背景下大数据对企业管理决策的影响[J]. 中国市场, 2020(19): 81-82.
[53]  杜龙波. 企业用户人工智能技术采纳行为研究[D]: [硕士学位论文]. 北京: 北京邮电大学, 2019.
[54]  钱晶晶, 何筠. 传统企业动态能力构建与数字化转型的机理研究[J]. 中国软科学, 2021(6): 135-143.
[55]  宋词. 基于人工智能的信息处理研究[J]. 无线互联科技, 2020, 17(16): 34-35.
[56]  陈国青, 曾大军, 卫强, 等. 大数据环境下的决策范式转变与使能创新[J]. 管理世界, 2020, 32(2): 95-105.
[57]  杨善林, 周开乐, 张强, 等. 互联网的资源观[J]. 管理科学学报, 2016, 19(1): 1-11.
[58]  舒程. 大数据对企业管理决策的影响研究[J]. 企业改革与管理, 2018(19): 12-13.
[59]  徐达实, 徐幼民. 论技术创新驱动经济发展效率决定的国家经济状态[J]. 财经理论与实践, 2018, 39(6): 131-135.
[60]  彼得∙德鲁克. 管理的实践[M]. 齐若兰, 译. 北京: 机械工业出版社, 2006.
[61]  迈克尔E∙哈特斯利, 林达∙麦克詹妮特. 管理沟通: 原理与实践[M]. 原书第3版. 北京: 机械工业出版社, 2008.
[62]  孙新波, 钱雨, 张明超, 李金柱. 大数据驱动企业供应链敏捷性的实现机理研究[J]. 管理世界, 2019, 35(9): 133-151, 200.
[63]  戚聿东, 肖旭. 数字经济时代的企业管理变革[J]. 管理世界, 2020, 36(6): 135-152, 250.
[64]  刘敏. 企业目标管理实施方法研究[D]: [硕士学位论文]. 哈尔滨: 哈尔滨工业大学, 2008.
[65]  王玉亭. 如何进行追踪决策[J]. 领导科学, 2001(23): 25.
[66]  黄孟藩, 王凤彬. 决策行为与决策心理[M]. 北京: 机械工业出版社, 1995.
[67]  刘宸希. “互联网+”时代传统企业互联网化转型路径研究[J]. 技术经济与管理研究, 2020(11): 56-60.
[68]  熊健超. 大数据对企业管理决策影响的探析[J]. 中国产经, 2020, 39(6): 131-135.
[69]  肖旭, 戚聿东. 产业数字化转型的价值维度与理论逻辑[J]. 改革, 2019(8): 61-70.
[70]  Bag, S., Pretorius, J.H.C., Gupta, S. and Dwivedi, Y.K. (2021) Role of Institutional Pressures and Resources in the Adoption of Big Data Analytics Powered Artificial Intelligence, Sustainable Manufacturing Practices and Circular Economy Capabilities. Technological Forecasting and Social Change, 163, Article ID: 120420.
https://doi.org/10.1016/j.techfore.2020.120420
[71]  徐印州, 李丹琪, 龚思颖. 人工智能与企业管理创新相结合初探[J]. 商业经济研究, 2020(10): 113-116.
[72]  王晶, 武昌. 智能决策支持系统框架研究[J]. 信息记录材料, 2021, 22(1): 183-184.
[73]  姚苏. 智能决策支持系统研究[J]. 甘肃科技, 2011(1): 23-24.
[74]  李媛. 大数据对企业管理决策影响分析[J]. 全国流通经济, 2020(8): 44-45.
[75]  孙波, 林宣雄, 李怀祖. 高层管理者决策支持系统的多层次处理模型研究[J]. 管理科学学报, 1999, 2(1): 54-67.
[76]  Dubey, R., Gunasekaran, A., Childe, S.J., Bryde, D.J., Giannakis, M., Foropon, C., et al. (2020) Big Data Analytics and Artificial Intelligence Pathway to Operational Performance under the Effects of Entrepreneurial Orientation and Environmental Dynamism: A Study of Manufacturing Organisations. International Journal of Production Economics, 226, Article ID: 107599.
https://doi.org/10.1016/j.ijpe.2019.107599
[77]  陈国青, 吴刚, 顾远东, 等. 管理决策情境下大数据驱动的研究和应用挑战——范式转变与研究方向[J]. 管理科学学报, 2018, 21(7): 1-10.
[78]  何军. 大数据对企业管理决策影响分析[J]. 科技进步与对策, 2014(4): 65-68.
[79]  陈国青, 曾大军, 卫强, 等. 大数据环境下的决策范式转变与使能创新[J]. 管理世界, 2020, 36(2): 95-105.
[80]  Jarrahi, M.H. (2018) Artificial Intelligence and the Future of Work: Human-AI Symbiosis in Organizational Decision Making. Business Horizons, 61, 577-586.
https://doi.org/10.1016/j.bushor.2018.03.007

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133