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...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 objectives more scientific. Sixthly, AI advances the timing of decision correction. Seventhly, AI drives the shift in enterprise decision-making from being “experience + information” driven to “information chain + algorithm” driven, transitioning from physiological bounded rational decision-making to scientific and fully rational decision-making.展开更多
针对现有故障预测与健康管理(prognostics and health management,PHM)系统难以给出实时、动态健康管理决策结果的问题,综合考虑不完善维修、多资源约束(人力、时间、成本等)、备件订购、任务规划等因素,基于选择性维修理论,建立了动态...针对现有故障预测与健康管理(prognostics and health management,PHM)系统难以给出实时、动态健康管理决策结果的问题,综合考虑不完善维修、多资源约束(人力、时间、成本等)、备件订购、任务规划等因素,基于选择性维修理论,建立了动态健康管理决策模型,得到了最优方案,包括部件最优维修对策、维修任务分配、备件订购数量、最优任务规划等。最后,结合算例,分析了维修人员数量、备件数量、任务规划等因素对动态健康管理决策结果的影响,验证了所提模型的有效性,对于指导装备健康管理实践、提升保障质效具有重要的意义。展开更多
文摘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 objectives more scientific. Sixthly, AI advances the timing of decision correction. Seventhly, AI drives the shift in enterprise decision-making from being “experience + information” driven to “information chain + algorithm” driven, transitioning from physiological bounded rational decision-making to scientific and fully rational decision-making.
文摘针对现有故障预测与健康管理(prognostics and health management,PHM)系统难以给出实时、动态健康管理决策结果的问题,综合考虑不完善维修、多资源约束(人力、时间、成本等)、备件订购、任务规划等因素,基于选择性维修理论,建立了动态健康管理决策模型,得到了最优方案,包括部件最优维修对策、维修任务分配、备件订购数量、最优任务规划等。最后,结合算例,分析了维修人员数量、备件数量、任务规划等因素对动态健康管理决策结果的影响,验证了所提模型的有效性,对于指导装备健康管理实践、提升保障质效具有重要的意义。
