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              <text>Sustainable Supply Chain Analytics for Anomalously Potential Fraudulent Logistics</text>
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              <text>fraud analytics; supply chain analytics; third-party logistics</text>
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              <text>The primary focus of this research is to detect potential anomalous and fraudulent cotton ginning transactions. The analysis of monitoring systems utilizing substantial analytics is often time-consuming and requires painstaking analysis afterward. In addition, the paper discusses how Third-Party Logistics affects the warehousing process and its antidromic role in distribution channels. Data for this study came from an established cotton gin operation in Tanganyika/Tanzania-East Africa. Ultimately, the results should allow cotton ginning to be improved by understanding anomalous activities. Cotton ginning fraud will be explained for the first time in scholarly journals using supply chain analytics.   2022 IEEE.</text>
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              <text>Godwin B.J.; Preethi N.; George F.J.P.</text>
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              <text>2022 International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2022</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/TQCEBT54229.2022.10041458" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/TQCEBT54229.2022.10041458&lt;/a&gt;
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              <text>ISBN: 978-166545361-5</text>
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              <text>Godwin B.J., CHRIST University, School of Business and Management, Lavasa, Pune, India; Preethi N., CHRIST University, School of Business and Management, Lavasa, Pune, India; George F.J.P., CHRIST University, School of Business and Management, Lavasa, Pune, India</text>
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