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Titlebook: Data Analytics for Supply Chain Networks; Niamat Ullah Ibne Hossain Book 2023 The Editor(s) (if applicable) and The Author(s), under exclu

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發(fā)表于 2025-3-21 19:07:33 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Data Analytics for Supply Chain Networks
編輯Niamat Ullah Ibne Hossain
視頻videohttp://file.papertrans.cn/263/262708/262708.mp4
概述Comprehends interdependency topics of the supply chain network against data analytics application‘s backdrop.Ready to use tools and techniques assessing the supply chain industry network’ s resilience
叢書(shū)名稱Greening of Industry Networks Studies
圖書(shū)封面Titlebook: Data Analytics for Supply Chain Networks;  Niamat Ullah Ibne Hossain Book 2023 The Editor(s) (if applicable) and The Author(s), under exclu
描述.The objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks..
出版日期Book 2023
關(guān)鍵詞Big data; Frameworks; Mathematical Modelling; Reliability; Risk; greening industry networks; supply chain
版次1
doihttps://doi.org/10.1007/978-3-031-29823-3
isbn_softcover978-3-031-29825-7
isbn_ebook978-3-031-29823-3Series ISSN 2543-0246 Series E-ISSN 2543-0254
issn_series 2543-0246
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Greening of Industry Networks Studieshttp://image.papertrans.cn/d/image/262708.jpg
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978-3-031-29825-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-22 14:23:50 | 只看該作者
https://doi.org/10.1057/9780230523210 chains. This chapter provides an overview of the recent developments in data analytics applications in supply chain resilience (SCR) and supply chain sustainability (SCS). There has been an exponential growth of literature on data analytics applications for SCR and SCS, with a particularly notable
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Chennat Gopalakrishnan (Professor) ones. A holistic assessment framework for viability assessment requires managers to rely on information sources that generate qualitative and subjective data, even often incomplete. To deal with the unique characteristics of subjective data, a data fusion technique, comprised of an integrated appro
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Toward a Theory of Property Rights ensuring that their implementation results in positive and non-detrimental applications is fundamental. Having an adequate performance measurement framework, able to include all relevant aspects of sustainability and resilience, in a comprehensive yet concise way, exploiting synergies and links bet
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Paul A. Banaszkiewicz,Deiary F. Kader product largely depend on the supply chain activities. Eliminating unproductive activities in SCM may bring down the product cost and improve efficiency. Recently, the integration of sustainability principles with SCM has gained significance and proven to be effective. However, several barriers rem
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