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通过分析科技管理中的大数据特征,研究大数据对科技管理决策的作用机理.在此基础上,分析大数据驱动高校科技管理决策的要素、关键环节和特点,研究大数据驱动的科技管理决策模型结构,提出大数据驱动科技管理决策是解决高校科技管理高效精准决策的有效办法,最终给出推动大数据驱动高校科技管理决策的建议. 相似文献
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Fast development of IT and ICT facilitate customers to post a large volume of their concerns and expectation online, which are widely accepted to be a valuable resource for product designers. However, it is found that only a small number of small and medium-sized enterprises (SMEs) have capabilities to leverage customer online insights for design innovation, which often demonstrate a significant share in national economies growth. To discover the beneath reasons regarding the barrier that prevent them to make effective utilization, in this study, as a concrete example, manufacturing SMEs in the South Wales and Greater Manchester industrial areas of the UK are focused and their potential motivations for using and knowledge of big data-based customer analytics are investigated. An exploratory survey was conducted in terms of the type of customer data they have, the storage approaches, the volume of customer data, etc. Next, a carefully devised exploratory study was undertaken to understand how SMEs perceive the relations between customer data and product design, how about their expectations from big customer data analytics and what really challenges SMEs to exploit the value of big customer data. Besides, a demonstration platform is developed to present SMEs an automatic process of analysing customer online reviews and the capacity on customer insights acquisition and strategic decision making. Finally, findings from two focus groups indicate the different managerial and technical considerations required for SMEs considering implementing big data and customer analytics. This study encourages SMEs to welcome big customer data and suggests that a cloud-based approach may be the most appropriate way of giving access to big data analytics techniques. 相似文献
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大数据时代信息技术发展促使安全管理研究进一步生成数据密集型科学发现范式,并扩展安全绩效管理研究的边界。首先,从数据、信息、知识、智慧4个层面分析数据驱动决策的内涵,并构建数据驱动的安全绩效反馈流程;然后,从时间维、逻辑维和领域维3个维度探讨数据驱动下安全绩效管理的三维结构,归纳数据驱动下安全绩效管理的6个研究特征,并从用户层、指导层、数据驱动决策层、业务层、基础设施层5个层面提出数据驱动下企业层面的安全绩效管理框架模型。研究结果表明,数据驱动下的安全绩效管理有助于推动大数据与安全管理融合,以数据主导方式持续优化安全管理,为安全管理信息化提供理论支撑。 相似文献
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Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean). 相似文献
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若想提高教学质量,就要保障教学质量评价结果的客观性、公正性。在大数据时代背景下,高等院校可以应用大数据技术开展教学质量评价。教育大数据技术的存在,实现了数据驱动决策的目标,为多方参与教育评价提供了便利。目前,通过平板电脑、数码笔及可穿戴设备等,可实时了解多种学习数据,可谓是全过程采集学生的学习数据,为教育领域的各种评估及决策提供了可靠的数据基础。 相似文献
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刘石兰 《科学学与科学技术管理》2008,29(1):121-125
顾客价值已成为营销学者和企业家共同关注的焦点,被视为竞争优势的新来源.但以往的顾客价值管理实践较多地把顾客价值看作一种管理理念,并没有从战略高度渗透到整个企业的组织能力上,也没有落实到整个企业的具体组织行为上.将顾客价值与组织能力进行有机地结合,从能力的角度定义顾客价值、从顾客的角度定义能力,并分别从顾客和供应商角度探讨了能力与顾客价值的相互作用. 相似文献
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近年以来，无论是在管理理论研究领域还是在企业生产实践领域，对客户价值创造的研究兴趣均已呈现再次回升的趋势，企业行为的决策不仅取决于企业自身的能力，还取决于企业客户的需求和企业生存的环境．肩负着企业间物品流通职能的物资流通领域和肩负着企业与普通消费者物品流通职能的商业流通领域不同。其客户价值的创造也不相同。本文通过客户价值创造的理论，以华东某城市生产资料市场的现状调查为背景，分析生产资料领域内现存有形市场形式的产生原因、演化趋势和生命期限，阐述其中存在的客户价值创造和正确决策的选择。 相似文献
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分析了通信企业客户流失现状,给出选择CART算法的原因,然后利用CART算法建立客户流失预测模型并以移动通信企业为例,对其客户流失情况进行预测,把预测结果反馈给相关部门,从而制定出有效的营销措施预防客户流失。 相似文献
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Undoubtedly, the change in consumers’ choices and expectations, stemming from the emerging technology and also significant availability of different products and services, created a highly competitive landscape in various customer service sectors, including the financial industry. Accordingly, the Canadian banking industry has also become highly competitive due to the threats and disruptions caused by not only direct competitors, but also new entrants to the market.The primary objective of this paper is to construct a predictive churn model by utilizing big data, including the structured archival data, integrated with unstructured data from sources such as online web pages, the number of website visits and phone conversation logs, for the first time in the financial industry. It also examines the effect of different aspects of customers’ behavior on churning decisions. The Datameer big data analytics tool on the Hadoop platform and predictive techniques using the SAS business intelligence system were applied to study the client retirement journey path and to create a churn prediction model. By deploying the above systems, we were able to uncover a wealth of data and information associated with over 3 million customers’ records within the retiree segment of the target bank, from 2011 to 2015. 相似文献
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顾客价值的创造潜力根源在于企业所拥有的能力.越来越多的管理实践表明,供应商的能力是衡量其将来价值创造潜力的关键因素,是产业顾客选择供应商的主要指标.本文将顾客价值与企业能力进行有机结合,分别从顾客和供应商的角度探讨了能力对顾客价值的作用,阐述了不同价值类型生产的特点以及所需的能力类型.本文通过实证分析所获得的有关企业能力与不同价值类型的匹配框架对供应商如何利用能力为顾客创造价值以及对产业顾客如何从能力的角度评估供应商的价值创造潜力提供了具体的思路和工具. 相似文献
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【目的/意义】从理论层面探究面向医院管理的数据驱动决策过程,深化医疗数据应用,拓宽情报学的问题
域,为跨学科情报学理论发展提供新的增长点。【方法/过程】通过对数据驱动决策相关研究的回顾,在新技术环境
下信息链理论、BASM模型等相关理论指导下,深入分析数据到决策的驱动路径,突出医院管理场景下的决策特征,
构建面向医院管理的数据驱动决策过程模型,最后以J医院的日间手术管理实践为案例进行了分析验证。【结果/结
论】面向医院管理的数据驱动决策模型以驱动要素、需求要素和支持要素为结构基础,协同面向医院管理决策的数
据处理过程和数据驱动的医院管理决策制定过程,实现面向医院管理的决策支持功能。【创新/局限】提出了面向医
院管理的数据驱动决策过程模型,融合了数据和决策的处理过程,并提出了支持要素。 相似文献
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企业智慧安全绩效管理是以数据驱动方式自动评估安全生产状况,持续提升企业的过程安全管理水平.首先,提出智慧安全绩效管理的定义,并阐述其内涵、意义与特征.然后基于此,从基础设施、数据采集、数据分析、信息服务4个方面构建企业智慧安全绩效管理模型,并分别解析智慧安全绩效管理基础设施子模型、智慧安全绩效数据采集子模型、智慧安全绩效数据分析子模型、智慧安全绩效信息服务子模型的内容.最后,从加强智慧安全绩效管理的战略规划布局、增强智慧安全技术的敏感性、加强员工对智慧系统的熟悉度、加强管理层的智能安全素养、增加个性化的安全绩效信息服务能力5个方面,提出智慧安全绩效管理的发展策略. 相似文献
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To develop highly competitive products, companies need to understand customer needs (CNs) by effectively gathering and analysing customer data. With the advances in Information Technology, customer data comes not only from surveys and focus groups but also from social media and networking sites. Few studies have focused on developing algorithms that are devised exclusively to help to understand customer needs from big opinion data. Topic mining, aspect-based sentiment analysis and word embedding are some of the techniques adopted to identify CNs from text data. However, most of them do not consider the possibility that part of the customer data analysed is already known by companies. With the aim to continuously enhance company understanding of CNs, this paper presents an autonomous methodology for automatically classifying a set of text data (customer sentences) as referring to known or unknown CN statements by the company. For verification purposes, an example regarding a set of customer answers from an open survey questionnaire regarding the climate system of a car is illustrated. Results indicate that the proposed methodology helps companies to validate and update the customer need database with an average of 90 % precision and 60 % recall. 相似文献
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利用多案例分析和扎根理论探讨了平台型企业开放式服务创新风险的内在机理及作用机制。研究发现了风险因素的9个主范畴,3个风险核心范畴,以及2个风险发生后果,构成了平台型企业开放式服务创新的风险成因。实证研究表明,商业环境风险、平台战略风险、管理风险这三个风险对平台创新活动影响巨大,显著影响了平台型企业客户流失以及经营绩效。商业环境风险是平台创新面临的外部风险,与平台战略风险和管理风险呈显著正向关系,战略风险会增加管理风险发生的可能性。三大风险与客户流失呈正比,与平台经营绩效呈反比。本研究拓展了传统的管理要素模型,揭示了互联网平台企业创新过程中的风险互动机制。 相似文献
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《Research Policy》2023,52(7):104812
Recent research frames big data as a resource enhancing dynamic capabilities through improved prediction, decision-making, and data-driven innovation. In contrast, this study frames big data as an evolutionary driver that channels firms' knowledge and attention in specific directions, implying that firms need multiple big data sources to be receptive and dynamically capable. I apply this framework to the context of the digital revolution and focus on the impact of big data on firms' digitalization priorities. By leveraging a large-scale survey of more than twenty thousand Italian firms of all sizes, I find that big data improves the digitalization awareness of firms only if they gather big data from more than one source (otherwise, counterintuitively, it may even decrease it). I also find a positive effect of source variety both on the likelihood of prioritizing individual digitalization factors and on the variety of digitalization factors prioritized. Such effects appear to be stronger for small firms relative to their larger counterparts. Given the path dependence of digitalization trajectories, these findings have relevant policy implications in the context of initiatives like the European strategy for data and the SME strategy for a sustainable and digital Europe. 相似文献
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管理学习(managerial learning)是后发企业学习先进管理知识、技术、规范、方法和程序等的过程,是企业提高管理能力的重要途径,但目前该领域缺乏深入、系统化的研究。通过综述国内外管理学习领域的研究进展,为未来的学术研究夯实基础;与此同时,识别制约该领域学术进步的障碍,并指出该领域未来需要研究的问题。 相似文献
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Trade union policy with regard to technical and technological change is subject to a number of constraints and dilemmas. From an analysis of a series of case studies, in which a shop stewards' committee of a large chemical company engaged in issues which seemed to be instances of technical innovation, it is concluded that in reality complicated fusions of science, technology and management strategy were at stake. The union was more successful in issues of less far-reaching technological content. Its lack of information and access to higher level managerial strategic decision-making greatly limited its effectiveness. In order for a union to have influence on the direction of technological change, it is necessary for it to advance strategic demands, transcending practical contingencies. If trade unions and other interest groups are to achieve such influence, institutional mechanisms of public control on technological change, in which they can play a part, will have to be established. 相似文献
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管理能力是企业竞争优势的重要来源,现在普遍认为企业通过管理学习能够获取先进的管理技术、推动管理水平的提升,但关于管理学习的具体过程还鲜有研究。本研究以苏宁云商集团为例,通过案例研究揭示了管理学习的动因以及学习过程中的内容选择、路径选择、网络构建三大核心问题。研究表明,①管理升级的困境是管理学习的关键动因;②企业可以通过参观和考察优秀企业、借助外部专业机构辨别学习内容,降低信息不对称性;③企业应该根据管理知识的属性、嵌入性及企业积累的知识基础等特征选择恰当的学习路径;④多元的内外部学习网络能够为企业提供异质的知识来源,从而降低信息不对称性,同时这也是内外部学习代理人的重要来源。 相似文献
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Over recent years, organizations have started to capitalize on the significant use of Big Data and emerging technologies to analyze, and gain valuable insights linked to, decision-making processes. The process of Competitive Intelligence (CI) includes monitoring competitors with a view to delivering both actionable and meaningful intelligence to organizations. In this regard, the capacity to leverage and unleash the potential of big data tools and techniques is one of various significant components of successfully steering CI and ultimately infusing such valuable knowledge into CI strategies. In this paper, the authors aim to examine Big Data applications in CI processes within organizations by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations. Overall, research findings have indicated a preference for a rather centralized informal process as opposed to a clear formal structure for CI; the use of basic tools for queries, as opposed to reliance on dedicated methods such as advanced machine learning; and the existence of multiple challenges that companies currently face regarding the use of big data analytics in building organizational CI. 相似文献