• Login
    View Item 
    •   Home
    • Research from April 2016
    • Business and management
    • View Item
    •   Home
    • Research from April 2016
    • Business and management
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UOBREPCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalDepartmentThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalDepartment

    My Account

    LoginRegister

    About

    AboutLearning ResourcesResearch Graduate SchoolResearch InstitutesUniversity Website

    Statistics

    Display statistics

    Big data analytics using multiple criteria decision making models

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Authors
    Ramanathan, Ramakrishnan
    Mathirajan, Muthu
    Ravindran, A. Ravi
    Issue Date
    2017-07-17
    Subjects
    big data
    operations capability
    multiple criteria decision-making
    decision making
    
    Metadata
    Show full item record
    Abstract
    The field of multi-criteria decision-making (MCDM) assumes special importance in this era of Big Data and Business Analytics (BA). Big Data and BA are relatively recent phenomena, and studies on understanding the power of Big Data and BA are rare with a few studies being reported in the literature. While there are several textbooks and research materials in the field of multi-criteria decision-making (MCDM), there is no book that discusses MCDM in the context of emerging Big Data. Thus, the present volume addresses the knowledge gap on the paucity of MCDM models in the context of Big Data and BA. The book has 13 chapters. The first chapter is Festschrift in Honor of Professor Ravindran (which has been the primary purpose for developing this book) by Professor Adedeji B Badiru. The rest of the volume is broadly divided into three sections. The first section, consisting of chapters 2 and 3, is intended to provide the basics of MCDM and Big Data Analytics. The next section, comprising of Chapters 4-10, discusses applications of traditional MCDM methods. The last section, comprising of the final three chapters, discusses the application of more sophisticated MCDM methods, namely, Data Envelopment Analysis and the Analytics Hierarchy Process. The chapters are aimed to illustrate how MCDM methods can be fruitfully employed in exploiting Big Data, and it is hoped that this book will kindle further research avenues in this exciting new field.  This book will serve as a reference for MCDM methods, Big Data, and linked applications.
    Citation
    Ramanathan R, Mathirajan M and Ravindran AR (ed(s).). (2017) 'Big data analytics using multiple criteria decision making models', Florida, USA: CRC Press, Taylor & Francis.
    Publisher
    CRC Press, Taylor & Francis
    URI
    http://hdl.handle.net/10547/622174
    DOI
    10.1201/9781315152653
    Additional Links
    https://www.crcpress.com/Big-Data-Analytics-Using-Multiple-Criteria-Decision-Making-Models/Ramanathan-Mathirajan-Ravindran/p/book/9781498753555
    Type
    Book
    Language
    en
    ISBN
    9781498753555
    ae974a485f413a2113503eed53cd6c53
    10.1201/9781315152653
    Scopus Count
    Collections
    Business and management

    entitlement

     
    DSpace software (copyright © 2002 - 2021)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.