Linking big data analytics capability and sustainable supply chain performance: mediating role of innovativeness, proactiveness and risk taking
Syed Awais Ahmad Tipu, Kamel Fantazy
University of Sharjah The University of Winnipeg
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Purpose Drawing on the dynamic capability view (DCV), the current study aims to examine the mediating effects of entrepreneurial orientation (EO), in terms of innovativeness, proactiveness and risk taking, on the relationships between big data analytics (BDA) capability and sustainable supply chain performance (SSCP). Design/methodology/approach Data were collected by questionnaire survey from 300 manufacturing organizations. Structural equation modeling (SEM) was used to test the hypotheses. Findings The findings showed that innovativeness and proactiveness fully mediated the link between BDA capability and SSCP. However, risk taking only partially mediated the relationship between BDA capability and SSCP. There was also a negative relationship between BDA and risk taking. Research limitations/implications Given that the current study focused on the manufacturing sector, future research is needed to compare different sectors and cultural contexts. Further exploration is also needed into the dimension of risk taking in terms of the role of risk taking in linking BDA capability with SSCP in different cultural settings. Practical implications Technology may not increase the risk taking capability. Organizations may be creative and proactive but may remain risk averse despite having access to big data. Organizations need a more balanced approach to dynamically integrate and reconfigure the organizations' BDA and EO capabilities in order to enhance SSCP. Originality/value The role of EO in mediating the relationship between BDA capability and SSCP has not been studied before. The current study aimed to address the gap and contribute to the existing debate on better understanding the factors that are needed by organizations to effectively employ technology to enhance SSCP. Untapped areas for future research are also identified.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
经济 / 管理Big Data and Business Intelligence
Sustainable Supply Chain Management · Supply Chain Resilience and Risk Management
参考文献 93
此处列出前 3 条
引用本文 18
按被引量排序,此处列出前 3 条