The Impact of Big Data Analytics on Decision-Making Within the Government Sector.

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Big Data Pub Date : 2024-01-09 DOI:10.1089/big.2023.0019

Laila Faridoon, Wei Liu, Crawford Spence

引用次数: 0

Abstract

The government sector has started adopting big data analytics capability (BDAC) to enhance its service delivery. This study examines the relationship between BDAC and decision-making capability (DMC) in the government sector. It investigates the mediation role of the cognitive style of decision makers and organizational culture in the relationship between BDAC and DMC utilizing the resource-based view of the firm theory. It further investigates the impact of BDAC on organizational performance (OP). This study attempts to extend existing research through significant findings and recommendations to enhance decision-making processes for a successful utilization of BDAC in the government sector. A survey method was adopted to collect data from government organizations in the United Arab Emirates, and partial least-squares structural equation modeling was deployed to analyze the collected data. The results empirically validate the proposed theoretical framework and confirm that BDAC positively impacts DMC via cognitive style and organizational culture, and in turn further positively impacting OP overall.

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大数据分析对政府部门决策的影响。

政府部门已开始采用大数据分析能力（BDAC）来提高服务水平。本研究探讨了政府部门大数据分析能力（BDAC）与决策能力（DMC）之间的关系。研究利用基于资源的企业理论，探讨了决策者的认知风格和组织文化在 BDAC 与 DMC 关系中的中介作用。研究还进一步探讨了 BDAC 对组织绩效（OP）的影响。本研究试图通过重要的发现和建议来扩展现有的研究，以加强决策过程，从而在政府部门成功使用 BDAC。本研究采用调查方法收集阿拉伯联合酋长国政府组织的数据，并采用偏最小二乘结构方程模型对收集到的数据进行分析。研究结果从实证角度验证了所提出的理论框架，并证实 BDAC 通过认知风格和组织文化对 DMC 产生积极影响，进而进一步对 OP 整体产生积极影响。

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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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.