| Title | The Relationship between Big Data Analytic-Artificial Intelligence and Environmental Performance: A Moderated Mediated Model of Green Supply Chain Collaboration (GSCC) and Top Management Commitment (TMC) |
|---|---|
| ID_Doc | 18741 |
| Authors | Gallo, H; Khadem, A; Alzubi, A |
| Title | The Relationship between Big Data Analytic-Artificial Intelligence and Environmental Performance: A Moderated Mediated Model of Green Supply Chain Collaboration (GSCC) and Top Management Commitment (TMC) |
| Year | 2023 |
| Published | |
| Abstract | Academics and practitioners have shown growing interests in big data analytics and artificial intelligence (BDA-AI) in recent years. Despite this, research on the application of BDA-AI for green supply chain collaboration (GSCC) and its influence on environmental performance (EP) is still limited. The current research addresses this gap and extends organizational information processing theory by incorporating BDA-AI and exploring top management commitment (TMC) as a moderator. The current study developed a moderated mediation model based on 402 samples of data from Turkish manufacturing firms. The result revealed that the application of BDA-AI has a positive impact on GSCC and EP. The results also indicated that GSCC has a positive impact on EP. Our findings revealed that GSCC mediated the association between BDA-AI and EP. The results also revealed that TMC moderated the positive relationship between BDA-AI and GSCC, such that the strength of the positive relationship is further intensified at higher levels of TMC. The results also show that TMC moderated the positive relationship between BDA-AI and EP, such that the strength of the positive relationship is dampened at lower levels of TMC; significant findings have not been outlined in the extant literature. The current research will assist supply chain and logistics managers and top management in deploying BDA-AI technology to support GSCC and improve EP. |
| https://downloads.hindawi.com/journals/ddns/2023/4980895.pdf |
Similar Articles
| ID | Score | Article |
|---|---|---|
19567
|
Rashid, A; Baloch, N; Rasheed, R; Ngah, AH Big data analytics-artificial intelligence and sustainable performance through green supply chain practices in manufacturing firms of a developing country(2024) | |
| 19144
|
Benzidia, S; Makaoui, N; Bentahar, O The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance(2021) | |
| 31119
|
Waqas, M; Tan, LL Big data analytics capabilities for reinforcing green production and sustainable firm performance: the moderating role of corporate reputation and supply chain innovativeness(2023)Environmental Science And Pollution Research, 30, 6 | |
| 19575
|
Waqas, M; Xue, HG; Ahmad, N; Khan, SAR; Iqbal, M Big data analytics as a roadmap towards green innovation, competitive advantage and environmental performance(2021) | |
| 67325
|
AL-Khatib, AW; Shuhaiber, A Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?(2022)Sustainability, 14, 16 | |
| 65766
|
Raut, RD; Mangla, SK; Narwane, VS; Dora, M; Liu, MQ Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains(2021) | |
| 65562
|
Singh, SK; El-Kassar, AN Role of big data analytics in developing sustainable capabilities(2019) | |
| 74417
|
Tipu, SAA; Fantazy, K Examining the relationships between big data analytics capability, entrepreneurial orientation and sustainable supply chain performance: moderating role of trust(2023) | |
| 32601
|
Singh, RK; Joshi, HT Greening the supply chain: Institutional pressures, data-driven innovations, and the road to circular sustainability(2024) | |
| 18689
|
Shafique, MN; Yeo, SF; Tan, CL Roles of top management support and compatibility in big data predictive analytics for supply chain collaboration and supply chain performance(2024) |