Circular supply chain management: Antecedent effect of social capital and big data analysis capability and their impact on sustainable performance

被引:2
|
作者
Zhou, Xiaochen [1 ]
Jiang, Jijiao [1 ]
Zhou, Cong [1 ]
Li, Xiang [1 ]
Yin, Ming [2 ]
机构
[1] Northwestern Polytech Univ, Sch Management, Xian, Peoples R China
[2] Northwestern Polytech Univ, Sch Software, Xian, Peoples R China
关键词
big data analytics capability; circular economy; circular supply chain management; performance; social capital; sustainability; HUMAN-RESOURCE MANAGEMENT; PARTIAL LEAST-SQUARES; DATA ANALYTICS; GREEN INNOVATION; ECONOMY; CUSTOMER; SYSTEMS; PLS; CONSTRUCTION; INTEGRATION;
D O I
10.1002/sd.2963
中图分类号
F0 [经济学]; F1 [世界各国经济概况、经济史、经济地理]; C [社会科学总论];
学科分类号
0201 ; 020105 ; 03 ; 0303 ;
摘要
The circular economy era has begun, and circular supply chain management (CSCM) is widely acknowledged as a management paradigm that promotes firm sustainability. Through previous research, we have learned that the key challenge in the circular transformation of manufacturing firms is to encourage supply chain partners to collaborate and effectively participate in resource cycles. Drawing inspiration from social capital theory and resource-based views, we explored how social capital effect sustainable performance through CSCM and the moderating effect of big data analytics capability (BDAC). We tested this by collecting data from 414 Chinese manufacturing firms. The results indicate that both internal and external social capital are positively correlated with CSCM. In addition, CSCM mediates the relationship between social capital and organizational environmental and social sustainability. The results also indicate that BDAC strengthen the impact of external social capital on CSCM, but the moderating effect on the relationship between internal social capital and CSCM is not significant. This essay advances the theory and practice of CSCM by offering fresh perspectives on how social capital influences sustainable performance of firms.
引用
收藏
页码:5311 / 5330
页数:20
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