共查询到17条相似文献，搜索用时 140 毫秒
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“大数据”作为时下最火热的IT行业的词汇,数据中隐藏着大量有价值的模式和信息,它的商业价值的利用逐渐成为行业人士争相追捧的利润焦点。在本篇文章中,探讨了中小企业在迎接大数据时代应注意什么,应做些什么,最终使中小企业在大数据时代中把握先机。 相似文献
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基于172份企业调研数据,从数据赋能视角探讨信息技术(IT)与业务融合对企业商业模式创新的作用机制,并在此基础上基于资源整合、数据挖掘与分析、组织决策的逻辑框架以及企业的环境适配性问题,考察企业大数据能力的中介作用以及环境动态性的调节效应.研究发现:IT与业务融合对商业模式创新有正向影响;大数据能力在IT与业务融合和商业模式创新的关系间具有显著中介作用;IT与业务融合通过大数据能力对商业模式创新的间接影响受到环境动态性的负向调节作用.研究结论对于企业开展商业模式创新实践的主要启示包括:企业应注重信息技术与当前自身基础架构、业务流程与战略方向之间的匹配问题,重视并发挥大数据能力积极的影响,积极开展对外部环境的监测工作等. 相似文献
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刘庆林 《大科技．科学之谜》2014,(6):212-213
“大数据”作为时下最热门的词汇,随着IT行业的蓬勃发展逐步赚得更多人的眼球,以其巨大的商业和实用性价值成为行业人士争相追捧的利润焦点。国土资源的管理在大数据时代来临下也获得了新生,城市规划、GIS数据以及居民生活消费等方面,数据网络的便捷有序化为国土管理补充了新鲜的血液。测量工程随着工程建设技术的不断发展,大型工程建设项目的不断上马,对于网络等数据管理的补充辅助作用日益强大。由此,测量工程对于国土大数据系统的支持作用不言而喻。 相似文献
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《The Journal of High Technology Management Research》2023,34(2):100465
Businesses have begun using IT apps for a variety of reasons in recent years. The rapid advancement of new technologies has opened up vast prospects for businesses to digitise their operations, enhance their use of information systems, and compete more effectively in the global marketplace. Information technology (IT) businesses can benefit greatly from Big Data analytics due to the depth and breadth of their data analysis. Big data can be used to examine IT departments in the following ways: performance analysis, forecast maintenance, security analysis, and resource analysis. When it comes to boosting their business's dependability, speed, quality, and effectiveness, most companies rely on big data. Companies can gain a competitive edge thanks to the massive amounts of data that big data is able to collect, store, and manage. Big data analytics is being used by a growing number of businesses to make sense of their mountain of data. In this paper, we examine the ways in which IBM, TCS, and Cognizant use big data within their operations. Long-term planning strategies and business intelligence practises are also suggested in this research as means of protecting personal information. 相似文献
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京津冀IT产业条块分割、配置不均的格局严重地影响了中国经济第三增长级的快速发展。分析了京津冀IT产业大集群模式产生的背景和原因,并由此界定了京津冀IT产业大集群模式,依据钻石模型分析了京津冀采用大集群战略发展IT产业的可行性,运用因子分析法系统分析了我国三大IT产业集群区的产业发展状况,明晰了影响京津冀IT产业集群发展的关键要素,提出了IT产业竞争优势理论模型并据此探求了IT产业发展的动力机制。最后,针对京津冀IT产业大集群战略给出了发展路径、策略与详尽的政策建议。 相似文献
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Big data analytics associated with database searching, mining, and analysis can be seen as an innovative IT capability that can improve firm performance. Even though some leading companies are actively adopting big data analytics to strengthen market competition and to open up new business opportunities, many firms are still in the early stage of the adoption curve due to lack of understanding of and experience with big data. Hence, it is interesting and timely to understand issues relevant to big data adoption. In this study, a research model is proposed to explain the acquisition intention of big data analytics mainly from the theoretical perspectives of data quality management and data usage experience. Our empirical investigation reveals that a firm's intention for big data analytics can be positively affected by its competence in maintaining the quality of corporate data. Moreover, a firm's favorable experience (i.e., benefit perceptions) in utilizing external source data could encourage future acquisition of big data analytics. Surprisingly, a firm's favorable experience (i.e., benefit perceptions) in utilizing internal source data could hamper its adoption intention for big data analytics. 相似文献
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The number of firms that intend to invest in big data analytics has declined and many firms that invested in the use of these tools could not successfully deploy their project to production. In this study, we leverage the valence theory perspective to investigate the role of positive and negative valence factors on the impact of bigness of data on big data analytics usage within firms. The research model is validated empirically from 140 IT managers and data analysts using survey data. The results confirm the impact of bigness of data on both negative valence (i.e., data security concern and task complexity), and positive valence (i.e., data accessibility and data diagnosticity) factors. In addition, findings show that data security concern is not a critical factor in using big data analytics. The results also show that, interestingly, at different levels of data security concern, task complexity, data accessibility, and data diagnosticity, the impact of bigness of data on big data analytics use will be varied. For practitioners, the findings provide important guidelines to increase the extent of using big data analytics by considering both positive and negative valence factors. 相似文献
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随着我国企业信息化进程的不断推进.信息化面临着技术和管理日益复杂的巨大挑战,如何合理地管理企业信息资源.充分发挥IT效用,实现IT价值.使IT与企业业务活动真正融合.是当今企业信息化的目标.本文在介绍信息资源规划的理论和方法的基础上.提出复杂科学管理系统思维模式下的信息资源规划方法论--企业架构EA,并对EA的实施方法以及开发工具进行了介绍. 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