Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • Author(s): Kumar, R.1; Bishnu, P.S.2
  • Source:
    In: Data Science and Engineering. (Data Science and Engineering, 1 December 2019, 4(4):367-384)
  • Publication Information:
    Springer
  • Document Type:
    Article
  • Language:
    English
  • معلومة اضافية
    • Affiliation:
      1Cambridge Institute of Technology
      2Birla Institute of Technology
    • Publication Date:
      2019
    • Author Keywords:
      Business intelligence
      Data mining
      Decision making
      Market entry
    • ISSN:
      23641541
      23641185
    • Accession Number:
      10.1007/s41019-019-00106-z
    • Rights:
      Copyright 2019 Elsevier B.V., All rights reserved.
    • Accession Number:
      edselc.2-52.0-85074464263
  • Citations
    • ABNT:
      KUMAR, R. ( 1 ); BISHNU, P. S. ( 2 ). Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making. Data Science and Engineering, [s. l.], v. 4, n. 4, p. 367–384, [s. d.]. DOI 10.1007/s41019-019-00106-z. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edselc&AN=edselc.2-52.0-85074464263&custid=s8280428. Acesso em: 24 fev. 2020.
    • AMA:
      Kumar R( 1 ), Bishnu PS( 2 ). Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making. Data Science and Engineering. 4(4):367-384. doi:10.1007/s41019-019-00106-z.
    • APA:
      Kumar, R. ( 1 ), & Bishnu, P. S. ( 2 ). (n.d.). Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making. Data Science and Engineering, 4(4), 367–384. https://doi.org/10.1007/s41019-019-00106-z
    • Chicago/Turabian: Author-Date:
      Kumar, R. ( 1 ), and P.S. ( 2 ) Bishnu. 2020. “Identification of K-Most Promising Features to Set Blue Ocean Strategy in Decision Making.” Data Science and Engineering 4 (4): 367–84. Accessed February 24. doi:10.1007/s41019-019-00106-z.
    • Harvard:
      Kumar, R. ( 1 ) and Bishnu, P. S. ( 2 ) (no date) ‘Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making’, Data Science and Engineering, 4(4), pp. 367–384. doi: 10.1007/s41019-019-00106-z.
    • Harvard: Australian:
      Kumar, R( 1 ) & Bishnu, PS( 2 ) n.d., ‘Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making’, Data Science and Engineering, vol. 4, no. 4, pp. 367–384, viewed 24 February 2020, .
    • MLA:
      Kumar, R. (. 1. )., and P. S. (. 2. ). Bishnu. “Identification of K-Most Promising Features to Set Blue Ocean Strategy in Decision Making.” Data Science and Engineering, vol. 4, no. 4, pp. 367–384. EBSCOhost, doi:10.1007/s41019-019-00106-z. Accessed 24 Feb. 2020.
    • Chicago/Turabian: Humanities:
      Kumar, R. ( 1 ), and P.S. ( 2 ) Bishnu. “Identification of K-Most Promising Features to Set Blue Ocean Strategy in Decision Making.” Data Science and Engineering 4, no. 4: 367–84. Accessed February 24, 2020. doi:10.1007/s41019-019-00106-z.
    • Vancouver/ICMJE:
      Kumar R( 1 ), Bishnu PS( 2 ). Identification of k-Most Promising Features to Set Blue Ocean Strategy in Decision Making. Data Science and Engineering [Internet]. [cited 2020 Feb 24];4(4):367–84. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edselc&AN=edselc.2-52.0-85074464263&custid=s8280428