The trickle-down effect of big data use to predict organization innovation: the roles of business strategy alignment and information sharing

Yu Wang, Zulqurnain Ali, Aqsa Mehreen, Khawar Hussain
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引用次数: 5

Abstract

PurposeIn this age of digitalization, organizations are generating large data from the organizations' manufacturing processes that are valuable for capturing a competitive edge. Chinese small and medium enterprises (SMEs) can bring organizations radical innovation by investing in innovation projects (i.e. big data use; BDU) using the SMEs' scarce resources. Thus, the authors' research aims to predict Chinese SMEs' radical innovation (RI) through BDU using the theoretical lenses of the resource-based view. Moreover, the authors' study also pursues to realize the undermining mediating process of business strategy alignment (BSA) and the buffering role of information sharing in BDU–RI linkage.Design/methodology/approachIn total, 297 Chinese SMEs entrepreneurs and managers were recruited from the Yangtze River Economic Belt, China using a survey approach. In Mplus 7.4, the authors tested the proposed hypotheses.FindingsThe sample of 297 shows that BDU is directly and indirectly (via BSA) related to RI. Further, information sharing moderates the linkage between BDU and BSA and BSA and RI. The association between BSA and RI is only significant and stronger when information sharing is high.Practical implicationsThis research is beneficial for SME entrepreneurs/managers to enhance the understanding of BDU, eliminate challenges of BSA via BDU and align business strategies to bring RI to Chinese SMEs.Originality/valueSMEs always search for new ways to enhance SMEs' productivity using scarce resources. This is the first research that advances big data and innovation literature by predicting firm RI through BDU using a resource-based view. Moreover, this study is novel because the study investigates the mediation role of BSA and the moderating role of information sharing in the linkage between BDU and firm RI in Chinese SMEs.
大数据用于预测组织创新的涓滴效应:商业战略一致性和信息共享的作用
在这个数字化时代,组织正在从组织的制造过程中产生大量数据,这些数据对于获得竞争优势很有价值。中国的中小企业(SMEs)可以通过投资创新项目(即大数据的使用;BDU)利用中小企业的稀缺资源。因此,本文旨在运用资源基础观的理论视角,通过BDU对中国中小企业的突破性创新进行预测。此外,本研究还试图实现企业战略结盟(BSA)的破坏中介过程和信息共享在BDU-RI联动中的缓冲作用。设计/方法/方法采用问卷调查的方法,从中国长江经济带招募了297名中国中小企业的企业家和管理者。在Mplus 7.4中,作者测试了提出的假设。结果297个样本显示BDU与RI有直接或间接(通过BSA)关系。此外,信息共享调节了BDU与BSA、BSA与RI之间的联系。只有当信息共享程度高时,BSA和RI之间的关联才显著且更强。实践意义本研究有助于中小企业企业家/管理者加强对业务流程分析的理解,通过业务流程分析消除业务流程分析带来的挑战,调整企业战略,将业务流程分析引入中国中小企业。创新/价值中小企业一直在寻找新的方法,利用稀缺的资源提高中小企业的生产力。这是第一个利用基于资源的观点通过BDU预测企业RI的大数据和创新文献。此外,本研究的新颖之处在于,本研究考察了中国中小企业企业绩效评价在企业绩效评价与企业绩效关系中的中介作用和信息共享的调节作用。
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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