概念化大数据:案例分析

Q1 Economics, Econometrics and Finance Intelligent Systems in Accounting, Finance and Management Pub Date : 2016-05-11 DOI:10.1002/isaf.1393

Ossi Ylijoki, Jari Porras

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引用次数: 25

摘要

数字化和相关的数据化产生了大量的数据。组织已经开始利用这些新数据来获得利益。探索这个“大数据丛林”对学者和实践者来说都是一个新的领域，早期采用者的经验是有价值的。本文采用计算机化内容分析方法对学术文献中描述的大数据用例进行分析。根据分析结果，我们概念化了组织背景下的大数据主题和指导方针，从而为新兴的大数据研究做出了贡献。除了实现的利益之外，案例研究还揭示了有关技术、技能、组织文化和决策过程的问题。本文还指出了一些新的研究途径，作为学术来源中发现的大数据案例研究的参考汇编，并通过指出从业者应该考虑的几个主题来连接理论和实践。版权所有©2016 John Wiley &儿子,有限公司

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Conceptualizing Big Data: Analysis of Case Studies

Digitization and the related datafication produce huge amounts of data. Organizations have started to exploit these new data in order to gain benefits. Exploring this ‘big data jungle’ is a new area for both scholars and practitioners, and the experiences of early adopters are valuable. This paper analyses big data use cases described in the academic literature by using computerized content analysis methods. Based on the analysis results, we have conceptualized themes and guidelines of big data in the context of an organization, thus contributing to the emerging research of big data. In addition to the realized benefits, the case studies reveal issues regarding technology, skills, organizational culture and decision-making processes. The paper also points out several new research avenues, acts as a reference collection to big data case studies found in academic sources, and bridges theory and practice by pointing out several topics that practitioners should consider. Copyright © 2016 John Wiley & Sons, Ltd.

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来源期刊

Intelligent Systems in Accounting, Finance and Management Economics, Econometrics and Finance-Finance

CiteScore

6.00

自引率

0.00%

发文量

期刊介绍： Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.