大数据
业务
分析
服务(商务)
服务创新
数据科学
过程管理
知识管理
计算机科学
营销
数据挖掘
作者
Nian Liu,Zhaoquan Jian,Yanxia Tan
标识
DOI:10.1080/09537325.2024.2441807
摘要
Manufacturing enterprises are actively using big data analytics to pursue service innovation opportunities for sustainable development. However, the mechanisms underlying this influence require further discussion. Based on dynamic capability theory, this study aims to investigate how big data analytics capability affects service innovation performance of manufacturing enterprises by exploring the mediating effect of resource bricolage and the moderating roles of various learning orientation factors (learning commitment, open-mindedness and shared vision). The hypotheses were tested using questionnaire data from 245 manufacturing enterprises in China. The results show that big data analytics capability enables manufacturers to improve their service innovation performance both directly and via resource bricolage. In addition, open-mindedness boosts the effect of resource bricolage on service innovation performance, while learning commitment and shared vision do not. Our study enriches the big data analytics and servitization literature, and offers practical guidance for Chinese manufacturers that want to engage in service innovation in the digital era.
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