Literature DB >> 26766385

Recent Development in Big Data Analytics for Business Operations and Risk Management.

Tsan-Ming Choi, Hing Kai Chan, Xiaohang Yue.   

Abstract

"Big data" is an emerging topic and has attracted the attention of many researchers and practitioners in industrial systems engineering and cybernetics. Big data analytics would definitely lead to valuable knowledge for many organizations. Business operations and risk management can be a beneficiary as there are many data collection channels in the related industrial systems (e.g., wireless sensor networks, Internet-based systems, etc.). Big data research, however, is still in its infancy. Its focus is rather unclear and related studies are not well amalgamated. This paper aims to present the challenges and opportunities of big data analytics in this unique application domain. Technological development and advances for industrial-based business systems, reliability and security of industrial systems, and their operational risk management are examined. Important areas for future research are also discussed and revealed.

Year:  2016        PMID: 26766385     DOI: 10.1109/TCYB.2015.2507599

Source DB:  PubMed          Journal:  IEEE Trans Cybern        ISSN: 2168-2267            Impact factor:   11.448


  2 in total

1.  A video summarization framework based on activity attention modeling using deep features for smart campus surveillance system.

Authors:  Wasim Muhammad; Imran Ahmed; Jamil Ahmad; Muhammad Nawaz; Eatedal Alabdulkreem; Yazeed Ghadi
Journal:  PeerJ Comput Sci       Date:  2022-03-25

2.  Viable supply chain model: integrating agility, resilience and sustainability perspectives-lessons from and thinking beyond the COVID-19 pandemic.

Authors:  Dmitry Ivanov
Journal:  Ann Oper Res       Date:  2020-05-22       Impact factor: 4.854

  2 in total

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