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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mehrbakhsh, Nilashi | - |
| dc.contributor.author | Abdullah M., Baabdullah | - |
| dc.contributor.author | Rabab Ali, Abumalloh | - |
| dc.date.accessioned | 2023-05-04T04:57:29Z | - |
| dc.date.available | 2023-05-04T04:57:29Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s10479-023-05272-y | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/8397 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | Big data and predictive analytics (BDPA) techniques have been deployed in several areas of research to enhance individuals’ quality of living and business performance. The emergence of big data has made recycling and waste management easier and more efficient. The growth in worldwide food waste has led to vital economic, social, and environmental effects, and has gained the interest of researchers. Although previous studies have explored the influence of big data on industrial performance, this issue has not been explored in the context of recycling and waste management in the food industry. In addition, no studies have explored the influence of BDPA on the performance and competitive advantage of the food waste and the recycling industry. Specifically, the impact of big data on environmental and economic performance has received little attention. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | BDPA | vi |
| dc.subject | performance and competitive advantage | vi |
| dc.title | How can big data and predictive analytics impact the performance and competitive advantage of the food waste and recycling industry? | vi |
| dc.type | Book | vi |
| Appears in Collections | OER - Kinh tế và Quản lý | |
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