Assessing the impact of big data analytics capability on radical innovation: is business intelligence always a path?

IF 7.3 2区工程技术 Q1 ENGINEERING, INDUSTRIAL

Journal of Manufacturing Technology Management Pub Date : 2024-04-18 DOI:10.1108/jmtm-12-2023-0532

Weiwei Wu, Yang Gao, Yexin Liu

{"title":"Assessing the impact of big data analytics capability on radical innovation: is business intelligence always a path?","authors":"Weiwei Wu, Yang Gao, Yexin Liu","doi":"10.1108/jmtm-12-2023-0532","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.</p>\n<h3>Design/methodology/approach</h3>\n<p>A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.</p>\n<h3>Findings</h3>\n<p>Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.</p>\n<h3>Practical implications</h3>\n<p>The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.</p>\n<h3>Originality/value</h3>\n<p>This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.</p>","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":"8 1","pages":""},"PeriodicalIF":7.3000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Technology Management","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1108/jmtm-12-2023-0532","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}

引用次数: 0

Abstract

Purpose

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

Design/methodology/approach

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Findings

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

Practical implications

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

Originality/value

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

查看原文本刊更多论文

评估大数据分析能力对激进创新的影响：商业智能总是一条路吗？

目的本研究探讨了商业智能的三个维度（感知能力、转化能力和驱动能力）在大数据分析能力的三个维度（大数据分析管理能力、技术能力和人才能力）与中国制造企业激进创新之间关系中的中介作用。结果实证结果表明，在中国制造业背景下，商业智能感知能力、商业智能转化能力和商业智能驱动能力对大数据分析能力对激进式创新的影响具有正向中介作用。研究结果为领导者正确使用大数据分析能力、商业智能和激进创新提供了管理指导，也为制造业激进创新的未来研究提供了理论启示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Manufacturing Technology Management Engineering-Control and Systems Engineering

CiteScore

16.30

自引率

7.90%

发文量

期刊介绍： The Journal of Manufacturing Technology Management (JMTM) aspires to be the premier destination for impactful manufacturing-related research. JMTM provides comprehensive international coverage of topics pertaining to the management of manufacturing technology, focusing on bridging theoretical advancements with practical applications to enhance manufacturing practices. JMTM seeks articles grounded in empirical evidence, such as surveys, case studies, and action research, to ensure relevance and applicability. All submissions should include a thorough literature review to contextualize the study within the field and clearly demonstrate how the research contributes significantly and originally by comparing and contrasting its findings with existing knowledge. Articles should directly address management of manufacturing technology and offer insights with broad applicability.