| Title |
Examining the role of virtue ethics and big data in enhancing viable, sustainable, and digital supply chain performance |
| ID_Doc |
71287 |
| Authors |
Bag, S; Rahman, MS; Srivastava, G; Shore, A; Ram, P |
| Title |
Examining the role of virtue ethics and big data in enhancing viable, sustainable, and digital supply chain performance |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.techfore.2022.122154 |
| Abstract |
In the real world of practice, data-driven supply chains have gained huge popularity in recent years. This has led operations and supply management researchers to the focus on the role of advanced information and technology, including big data. Literature highlights that the use of big data can enhance business performance. Nonetheless, big data is analyzed by humans and a lack of virtue ethics could lead to disastrous consequences (erroneous decision-making can stem from bad data analysis resulting in not only huge business losses but also deterioration of relationships with suppliers and customers in the supply chain). To address the calls of previous researchers, this study utilizes the Ethical Theory of Organizing framework and Stakeholder theory to develop the theoretical model and further examine the relationships. The samples are drawn from the manufacturing industry. Hypothesis testing is executed through covariance-based structural equation modeling and finally, the conclusions are drawn. The findings of this work provide a more nuanced understanding of virtue ethics and big data implications, thereby answering the important questions of "why" and "how" data-driven green and lean practices increase the stakeholders' trust and enhance viable, sustainable, and digital supply chain performance. |
| Author Keywords |
Virtue ethics; Big data; Industry 4; 0; Ethical theory of organizing; Stakeholder theory; Viable; Sustainable; Digital supply chain performance |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:001035711500001 |
| WoS Category |
Business; Regional & Urban Planning |
| Research Area |
Business & Economics; Public Administration |
| PDF |
|