大数据
活力
商业智能
分析
数据科学
商业分析
数据分析
计算机科学
服务(商务)
知识管理
业务
数据挖掘
营销
商业模式
业务分析
物理
量子力学
作者
Wagner Júnior Ladeira,Fernando de Oliveira Santini,Tareq Rasul,Isaac Cheah,Samer Elhajjar,Naveed Yasin,Shakeb Akhtar
标识
DOI:10.1080/02642069.2024.2374990
摘要
Big data analytics have impacted nearly every service industry in the last decade. Furthermore,using artificial intelligence in big data analytics has introduced a new trend, resulting in different performance types, e.g. sales, marketing, innovation, organizational, financial, and operational. A systematic review of the empirical results from publications addressing big data analytics in the services industry becomes necessary to understand these performances better. Based on this rationale, this study conducted a meta-analysis to identify the relevant dimensions of big data analytics and evaluate artificial intelligence as a potential moderator of its effects on service performance. The results demonstrate that environmental dynamism, resources and capabilities, and competitive pressure drive big data analytics adoption. Environmental dynamism, followed by resources and capabilities, has greater effects on adopting big data analytics. The findings suggest that adopting big data analytics powered by artificial intelligence enhances service performance more than adopting big data analytics without using artificial intelligence.
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