Construction and Implementation of Multi Collaborative Service Platform Based on Industrial Competitive Intelligence

With the economic globalization and the increasingly fierce industrial competition at home and abroad, the importance of industrial competitive intelligence service is becoming increasingly prominent. Under the policy background of cooperation and sharing, pluralistic coordination has become a new trend in regional economic development. The multi collaborative online service platform of industrial competitive intelligence is jointly constructed by all service subjects. The platform is guided and promoted by the government. Colleges and universities provide support for industrial competitive intelligence theory and professionals, scientific research institutes provide talent and advanced technology support, industry associations are responsible for dynamic monitoring of industrial development, and profit-making institutions are responsible for supplementing industrial competitive intelligence achievements. All service subjects integrate and explore existing intelligence resources and services through the unified online industrial competitive intelligence sharing platform, so as to realize benign cooperation, collaborative management, resource integration, user integration and service integration among subjects, so as to realize multiple collaborative services of industrial competitive intelligence.

Multiple Collaborative Service Model and System Construction Based on Industrial Competitive Intelligence

This paper constructs a multiple collaborative service model of industrial competition intelligence with the main purpose of promoting the development of regional industries. The multiple service subjects include enterprises, governments, colleges and universities, scientific research institutes, industry associations and for-profit institutions. This article starts from the overall development of regional industrial economy, weighs the mutual relationship between the elements of the service model, and promotes multiple service subjects such as enterprises, governments, universities, research institutes, industry associations, and profit-making organizations to realize the collaborative service of resource intelligence, demand intelligence and data intelligence provides linkage intelligence service for the development and innovation of regional industries. This service model can improve the efficiency of industrial competitive intelligence services and the overall competitiveness of regional industries.

Enhancing College English Teachers’Teaching and Practical Abilities in the New Era:The Role of Educational Technology Amid US-China AI Rivalry

In the 21st century,the rapid development of artificial intelligence(AI)and educational technology has revolutionized the global education landscape.As the United States and China engage in strategic competition in the AI field,the impact of this rivalry extends beyond technology and economics,permeating education and international relations.This paper explores how educational technology can be leveraged to enhance the teaching and practical abilities of college English teachers in China within the context of the US-China AI competition.The intersection of AI development,educational strategies,and international diplomacy provides a unique backdrop for examining the potential and challenges of integrating advanced technology in English language teaching(ELT).This paper aims to provide insights for policymakers,educators,and researchers on how to effectively utilize educational technology to enhance the teaching and practical abilities of college English teachers,emphasizing the importance of strategic planning and international cooperation in this rapidly evolving field.

Employing Computational Intelligence to Generate More Intelligent and Energy Efficient Living Spaces

Our living environments are being gradually occupied with an abundant number of digital objects that have networking and computing capabilities. After these devices are plugged into a network, they initially advertise their presence and capabilities in the form of services so that they can be discovered and, if desired, exploited by the user or other networked devices. With the increasing number of these devices attached to the network, the complexity to configure and control them increases, which may lead to major processing and communication overhead. Hence, the devices are no longer expected to just act as primitive stand-alone appliances that only provide the facilities and services to the user they are designed for, but also offer complex services that emerge from unique combinations of devices. This creates the necessity for these devices to be equipped with some sort of intelligence and self-awareness to enable them to be self-configuring and self-programming. However, with this ＂smart evolution＂, the cognitive load to configure and control such spaces becomes immense. One way to relieve this load is by employing artificial intelligence （AI） techniques to create an intelligent ＂presence＂ where the system will be able to recognize the users and autonomously program the environment to be energy efficient and responsive to the user＇s needs and behaviours. These AI mechanisms should be embedded in the user＇s environments and should operate in a non-intrusive manner. This paper will show how computational intelligence （CI）, which is an emerging domain of AI, could be employed and embedded in our living spaces to help such environments to be more energy efficient, intelligent, adaptive and convenient to the users.

Competitive Intelligence Management in Knowledge Economy

This paper is to discuss management of competitive Intelligence （CI） from the viewpoint of knowledge management, in which the author creatively uses adapted SECI model to make explanation, and points out the different roles played by individual and organization in this process. At the end of this paper, some implications are given in respect with some fundamental problems with application of individual knowledge and organizational knowledge resulting from their idiosyncrasy, and orientation for CI management.

A Probe into the Competitive Intelligence Mode in Embedded Software Enterprises

As one of the key elements in various enterprises' core competitiveness,competitive intelligence has universal laws and methods in its managing mode.At the same time,different features lie in different industries,scales,regions and developing stages.The enterprises must be good at choosing and constructing proper and efficient competitive intelligence modes.In this paper,the author bases his paper on the features of embedded software enterprises - high degree of homogenization and quick upgrade of products,and discusses the basic approaches and process of establishing efficient competitive intelligence in this kind of enterprises.The author hopes his research will provide decision support for those enterprises in strengthening their competitive advantages.

Bibliometrics-based analysis on competitive intelligence in China

By applying to the theories and methodologies on informetrics,the authors collected the statistical data of relevant published articles,and then made some analysis including the prolific authors community,the long tail distribution of authors,and the disciplinary distribution of the published articles.To conclude,some development trends and suggestions were put forward for the reference.

面向国家战略的产业竞争情报场景化智慧服务模式研究

通过对面向国家战略的产业竞争情报智慧服务进行场景化、细粒度描述,构建产业竞争情报场景化智慧服务模式,以赋能复杂环境下产业高质量发展。首先,梳理国内外关于“场景化服务、产业竞争情报服务模式、智慧情报与情报智能服务”等相关研究,提出“产业竞争情报场景化智慧服务”的概念内涵;其次,沿着“战略引领与需求牵引—场景解构与细粒度刻画—平行系统与虚实交互—范式转变与服务升维”的研究逻辑,融合场景理论、平行智能思想,构建产业竞争情报场景化智慧服务模式;最后,以新能源汽车产业进行实证研究,为该行业竞争情报服务融慧进阶提出有效路径。本文提出了产业数字化升级、产业核心技术攻关、产业应急协同处突、新产业新业态培育四大情报服务场景,基于产业情报场景描述五元组,从服务内容、服务主体、服务客体、服务工具/手段、服务能力维度对其进行全景式描绘,构建了面向国家战略的产业竞争情报场景化智慧服务模式,并以新能源汽车产业为例,验证了本文模式的可行性与有效性。

大数据下企业供应链风险管理与竞争情报融合模型构建--以华为公司为例

[研究目的]国际经贸对抗环境下,中美贸易摩擦将持续升级,国家层面的技术创新竞争使得企业面临的供应链风险大幅提升。同时,大数据改变了供应链风险管理模式,而竞争情报可以从理论、技术和方法等方面提升大数据下企业供应链风险管理能力,因此大数据下企业供应链风险管理与竞争情报的融合研究具有重要意义。[研究方法]采用文献分析、案例研究等方法,分析供应链风险管理与竞争情报的异同点,继而论证大数据下供应链风险管理与竞争情报融合的可行性和必要性,再辅之以标杆企业华为的供应链中断风险事件验证,最终构建大数据下华为供应链风险管理与竞争情报融合模型,并分析运行维护此模型的保障要素。[研究结论]研究表明,基于战略、组织、制度、技术和资源五要素的共同保障,大数据下供应链风险管理与竞争情报的融合能够实现供应链风险管理的全面性、及时性和有效性。

大国竞争背景下的人工智能安全治理与战略稳定

在大国战略竞争加剧的背景下,实现对人工智能的有效治理,不仅关乎人类社会的发展,而且影响国际战略稳定。中国和美国作为全球人工智能领域的两大关键行为体,在该领域的治理理念和方式上存在差异。美国依赖技术优势推行单边主导型治理,将人工智能界定为战略竞争的前沿领域,坚持绝对安全理念,试图将监管体系按照人工智能技术和产业生态延展并聚焦于数据资源,尝试构建以美国为中心的非对称单向度的数据流动秩序。中国则坚持真正的多边主义,以总体国家安全观为指引,朝着构建网络空间命运共同体的方向,推动人工智能的全球治理朝着普惠、包容、弹性、灵活的方向发展。中国也非常关切支撑人工智能创新与产业发展所必需的数据资源,努力构建并持续完善以有序流动、分级分类治理为核心特征的数据治理架构,强调均衡考量各方利益,统筹安全与发展,以此作为推进人工智能全球安全治理的核心思路。展望未来,全球人工智能安全治理面临诸多挑战和机遇,各国需要加强沟通与协调,共同应对安全风险,推动人工智能技术健康发展。

美国军事战略的人工智能化趋势及其影响

近年来,在新一轮科技革命影响下,美国对其军事战略进行了人工智能化调整,试图沿袭技术制胜的军事思想传统,围绕在大国战略竞争中取胜这一目标,以新兴技术推进军事能力建设,打造一体化协同作战部队和军事情报系统,塑造针对特定目标进行精准打击的能力。为此,美国发布了一系列战略文件和具体方案推动人工智能的军事化应用。美国国防部建立了以人工智能为核心的组织架构和管理系统,重点发展人工智能人才队伍,加大新技术研发的军费投入,推动军民产业和技术融合,加强与盟友的技术合作。美国军事战略的人工智能化调整会刺激其他国家进行相应变革,进而加剧以人工智能竞争为焦点的大国战略竞争。人工智能技术难以溯源和易于扩散的特点将削弱核威慑的效用,其广泛军事化应用将催生新的战争形态。基于此,中国应密切关注新技术革命的发展趋势和美国军事战略变化的动向,做好应对准备。

中国典型涉外经营企业竞争情报工作调查研究

[目的/意义]针对中国科学技术情报学会竞争情报分会会员企业之外的中国典型涉外经营企业开展竞争情报工作实态调查,更好展示中国企业竞争情报实际工作全貌,为新时期竞争情报研究与服务工作创新发展提供新的视野、素材和参考。[方法/过程]按照透过“名”与“实”分离表象了解新时期中国企业竞争情报工作真实情况的逻辑思路,以企业合规管理为竞争情报“名”与“实”分离的典型场景,基于2018—2023年合规管理主题公开会议,采取对派出报告人的企业统计分析、专家咨询访谈、合规管理标杆企业案例研究、承接企业合规管理体系建设项目的咨询服务机构企业客户名单调查研究、公开资料收集分析相结合的研究方法,对中国典型涉外经营企业进行竞争情报工作实态调查。[结果/结论]调查得到以下主要发现:(1)所有涉外经营企业的合规管理都是无“名”有“实”的竞争情报工作;(2)新时期中国典型涉外经营企业对事实上的竞争情报普遍具有强烈而持久的需求;(3)中国典型涉外经营企业的竞争情报工作专业水平呈现显著的差异性;(4)中国典型涉外经营企业对名为合规管理实为竞争情报的工作有很高的要求;(5)中国典型涉外经营企业对符合企业需要的竞争情报专业人才需求迫切且需求数量巨大;(6)有“实”而无“名”是中国典型涉外经营企业竞争情报工作存在的最大问题。

突发事件中的嵌入式协同情报服务机制

[目的/意义]面对错综复杂的跨域突发事件时,必须破除情报资源、情报服务和应急管理内权责之间的壁垒,以产生嵌入式协同效应,从而提高应急管理效能。[方法/过程]文章从情报制度保障、情报组织保障及预警情报机制3个层面的视角出发,研究跨域情报服务突发事件的基础保障、情报缺失问题和实现路径。基于应急管理体系和传统情报协同服务体系,利用嵌入式协同情报监测采集系统和危机预警情报系统等工具,构建嵌入式协同情报服务体系框架。[结果/结论]情报理应成为突发事件应急管理的“冲锋号”。文章以嵌入式协同视角从3个层面提出变革情报支持范式:在法律法规层面凸显情报主导、提升情报组织保障和赋能、建立常态化危机预警情报机制。通过构建耦合联动的情报共同体,优化功能互补的应急管理工具箱,打造双重共轭的情报保障体系,从而形塑“随时待命、明辨真相、贴身决策”的嵌入式情报主导的突发事件应急管理情报服务机制。

基于竞争情报能力提升的中国版权服务高质量发展体系建设分析

[研究目的]版权服务是知识产权服务的重要组成部分,在大国之间围绕知识产权战略竞争日趋激烈的新形势下,运用竞争情报的理论方法对我国版权服务产业的高质量发展问题进行研究,为新形势下我国版权服务产业创新发展的理论方法研究与实务工作提供参考。[研究方法]按照产业竞争情报系统建设的理论方法,分析中国版权服务产业竞争情报系统建设的必要性和可行性,研究其目标用户识别遴选、系统的需求和功能设定、组织结构和人员设置、竞争情报服务产品和流程设计、需要的信息技术支持选择、运行机制等关键问题,从竞争情报理论方法视角研究中国版权服务高质量发展体系建设的实现路径。[研究结论]我国的版权服务是新的竞争情报应用场景,中国版权服务产业竞争情报系统建设既有必要又切实可行,围绕导入竞争情报、基于提升竞争情报能力,从五个方面就开展中国版权服务高质量发展体系建设提出了解决方案和实现路径。

中小企业间竞争情报共享策略演化博弈与仿真研究

随着中小企业间的关系由竞争转向竞合,竞争情报在中小企业之间共享成为可能。本文旨在探讨中小企业间竞争情报共享策略的演化博弈过程与影响因素,有望为中小企业的共享策略选择提供依据,并为后续理论研究与实践探索提供新的思路和参考借鉴。基于演化博弈理论,推演双方中小企业的竞争情报共享演化博弈过程,分析利益得失、博弈系统的演化稳定策略和不同参数的影响程度,并通过数值仿真对结果进行验证。研究结果显示,协同收益和惩罚成本对中小企业间竞争情报共享策略具有正向显著影响,而泄露风险和共享成本对其具有负向显著影响;当其余所有参数均确定时,可共享竞争情报的质量和竞争情报的吸收能力在某个区间内具有负向显著影响,并且两者在中小企业之间的差距越小,越有可能最终稳定于共享策略。最后,提出促进中小企业间竞争情报共享的针对性建议。

引力理论框架下基于综合竞争力的自动驾驶拟人换道决策模型

为有效刻画城市快速路中自动驾驶环境下的车辆换道决策机理,考虑主车与周边车辆的位置属性、驾驶风格属性及车辆运动属性对主车换道行为的影响,建立基于综合竞争力的拟人换道决策模型。首先,以邻近前车间距、邻近前车速度差及驾驶风格这3种因素作为自动驾驶车辆的拟人化换道意愿属性,量化表征主车的换道意愿;然后,基于人类决策中的悲观主义准则,分析换道过程中周边车辆与主车可能产生的竞争行为,利用车头间距比和驾驶风格差异提出潜在竞争强度概念;其次,考虑环境稳定性对驾驶舒适性的影响,提出“速度伪距”“加速度伪距”概念,衡量换道后的环境稳定性;最后,结合引力理论建立以车辆横向速度为求解目标的综合竞争力换道决策模型。在模型标定中,筛选Ubiquitous Traffic Eyes开源数据集,得到非强制换道片段数据,利用蚁群算法标定模型参数。采用随机排列交叉验证方法进行验证,以正确率为模型精度和泛化能力的评价指标,并将其与传统模型进行对比。结果表明,将训练与验证比设置为72%∶28%、65%∶35%、57%∶43%和50%∶50%时,平均正确率区间为87.67%~90.34%,说明该模型具有较强的鲁棒性和可行性,相比于传统模型,本文模型具有更高的预测精度,可为自动驾驶环境下车辆的车道选择提供依据。

竞争情报视角的美中经济与安全评估委员会听证会研究

[研究目的]从竞争情报专业视角研究美中经济与安全评估委员会(U.S.-China Economic and Security Review Commission,USCC)的听证会,为我国新时期新范式下的竞争情报研究与服务创新发展提供参考。[研究方法]对USCC成立至今已经召开的168场听证会进行研读分析,围绕USCC主要关注哪些问题、USCC主要邀请哪些人和机构参加听证会、USCC听证会的竞争情报产品形成机理、USCC技术领域听证会特点4个典型问题,从竞争情报专业角度进行研究。[研究结论]研究发现,USCC主要关注美国的安全与发展问题,USCC听证会确定主题和议题的过程也是事实上的关键情报课题识别凝练确定过程;对USCC168场听证会参会作证人和参会机构进行统计分析,发现并展示介绍了高频次参会作证人和参会机构;USCC听证会是一个典型的高质量竞争情报产品生产过程;USCC技术领域听证会具有跳出技术看技术、着眼国家安全与发展全局看技术、从技术要素在经济贸易等领域产生实际影响角度凝练问题、聚焦政策与战略开展技术问题研究的特点。

基于上市公司年报供应链的核心企业识别方法研究

以上市公司年度报告中披露的供应商和客户信息为基础,构建供应链企业合作网络,并运用社会网络分析中的特征向量中心性、中介中心性和接近中心性指标,量化供应链核心企业的强影响力、强吸引力和强融合力。通过收集信息技术行业的数据进行实证分析,识别出该领域对整个供应链有重要影响力的核心企业,验证方法的有效性。研究结果表明,该方法能够准确识别供应链中的核心企业,并揭示其网络结构特征。此项研究扩展技术竞争情报的应用场景,为供应链管理和优化提供新的思路和定量分析方法,有望提高供应链管理效率,帮助企业更好地优化他们的供应链结构。

基于情报感知的企业竞争情报平台建设

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