通过大数据分析能力创造战略价值:一种配置方法

R. V. D. Wetering, Patrick Mikalef, J. Krogstie
{"title":"通过大数据分析能力创造战略价值:一种配置方法","authors":"R. V. D. Wetering, Patrick Mikalef, J. Krogstie","doi":"10.1109/CBI.2019.00037","DOIUrl":null,"url":null,"abstract":"Despite the documented potential of Big Data Analytics Capabilities (BDAC), it is by no means clear how they support the capacity of firms to purposefully create, extend, or modify their resource bases, i.e., dynamic capabilities (DC). This study extends current literature by exploring and elucidating various contingent big data capabilities, resources, and conditions that lead to the formation of these DCs in today's turbulent business environment. We use a qualitative approach using a cross-interview study method. Hence, we collected data through semi-structured interviews with field domain experts. In total, 27 interviews were held with key and senior informants from different firms. Co-authors analyzed the obtained data through the use of qualitative coding techniques. Our results show that there are various contingent BDAC resource solutions that drive, moderate, and condition the development of DCs. These outcomes also show that no single antecedent condition explains DCs in practice. These insights are important for firms that are becoming more data-driven. Outcomes are valuable for practice as firm executives now have insight into the process and main BDA capabilities they can focus on while planning, initiating, and evolving big data analytics projects and their digital business strategies.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Strategic Value Creation through Big Data Analytics Capabilities: A Configurational Approach\",\"authors\":\"R. V. D. Wetering, Patrick Mikalef, J. Krogstie\",\"doi\":\"10.1109/CBI.2019.00037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite the documented potential of Big Data Analytics Capabilities (BDAC), it is by no means clear how they support the capacity of firms to purposefully create, extend, or modify their resource bases, i.e., dynamic capabilities (DC). This study extends current literature by exploring and elucidating various contingent big data capabilities, resources, and conditions that lead to the formation of these DCs in today's turbulent business environment. We use a qualitative approach using a cross-interview study method. Hence, we collected data through semi-structured interviews with field domain experts. In total, 27 interviews were held with key and senior informants from different firms. Co-authors analyzed the obtained data through the use of qualitative coding techniques. Our results show that there are various contingent BDAC resource solutions that drive, moderate, and condition the development of DCs. These outcomes also show that no single antecedent condition explains DCs in practice. These insights are important for firms that are becoming more data-driven. Outcomes are valuable for practice as firm executives now have insight into the process and main BDA capabilities they can focus on while planning, initiating, and evolving big data analytics projects and their digital business strategies.\",\"PeriodicalId\":193238,\"journal\":{\"name\":\"2019 IEEE 21st Conference on Business Informatics (CBI)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 21st Conference on Business Informatics (CBI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBI.2019.00037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 21st Conference on Business Informatics (CBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBI.2019.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

尽管记录了大数据分析能力(BDAC)的潜力,但它们如何支持公司有目的地创建、扩展或修改其资源基础的能力,即动态能力(DC),这一点并不清楚。本研究通过探索和阐明在当今动荡的商业环境中导致这些dc形成的各种偶然大数据能力、资源和条件,扩展了现有文献。我们使用交叉访谈研究方法的定性方法。因此,我们通过与领域专家的半结构化访谈来收集数据。总共与来自不同公司的关键和高级线人进行了27次访谈。合著者通过使用定性编码技术分析了获得的数据。我们的研究结果表明,有各种偶然的BDAC资源解决方案可以驱动、调节和调节DCs的发展。这些结果也表明,在实践中,没有单一的先决条件可以解释DCs。这些见解对于那些越来越受数据驱动的公司来说非常重要。结果对于实践是有价值的,因为公司高管现在对流程和主要BDA能力有了深入的了解,他们可以在规划、启动和发展大数据分析项目及其数字业务战略时关注这些能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strategic Value Creation through Big Data Analytics Capabilities: A Configurational Approach
Despite the documented potential of Big Data Analytics Capabilities (BDAC), it is by no means clear how they support the capacity of firms to purposefully create, extend, or modify their resource bases, i.e., dynamic capabilities (DC). This study extends current literature by exploring and elucidating various contingent big data capabilities, resources, and conditions that lead to the formation of these DCs in today's turbulent business environment. We use a qualitative approach using a cross-interview study method. Hence, we collected data through semi-structured interviews with field domain experts. In total, 27 interviews were held with key and senior informants from different firms. Co-authors analyzed the obtained data through the use of qualitative coding techniques. Our results show that there are various contingent BDAC resource solutions that drive, moderate, and condition the development of DCs. These outcomes also show that no single antecedent condition explains DCs in practice. These insights are important for firms that are becoming more data-driven. Outcomes are valuable for practice as firm executives now have insight into the process and main BDA capabilities they can focus on while planning, initiating, and evolving big data analytics projects and their digital business strategies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信