IDEAS home Printed from https://ideas.repec.org/a/vrs/morgsr/v82y2019i1p1-11n1.html
   My bibliography  Save this article

Application of Big Data Analytics in Customization of E-mass Service: Main Possibilities and Obstacles

Author

Listed:
  • Baranauskas Gedas

    (PhD student at Institute of Leadership and Strategic Management, Faculty of Public Governance, Mykolas Romeris University, Lithuania. Address: Ateities str. 20, LT-08303, Vilnius, Lithuania Phone: +370 62 151 887.)

Abstract

The paper is based on a scientific literature analysis and, by examining scientific insights, it focuses on the assumption that Big Data Analytics (BDA) is an alternative used in modern organizations in decision making at e-mass service customization. An overall orientation to BDA application in management processes is presented as a useful construct not only for improving the decision-making procedure but also as a relevant source for strategic planning, process and cost optimization activities as well as for changes in supply chain and risk management. The data was obtained through the scientific literature analysis and systematized theoretical insights of the BDA influence in both possibility and obstacle dimensions to e-mass service customization.

Suggested Citation

  • Baranauskas Gedas, 2019. "Application of Big Data Analytics in Customization of E-mass Service: Main Possibilities and Obstacles," Management of Organizations: Systematic Research, Sciendo, vol. 82(1), pages 1-11, December.
  • Handle: RePEc:vrs:morgsr:v:82:y:2019:i:1:p:1-11:n:1
    DOI: 10.1515/mosr-2019-0009
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/mosr-2019-0009
    Download Restriction: no

    File URL: https://libkey.io/10.1515/mosr-2019-0009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    2. OGREAN Claudia, 2019. "Relevance Of Big Data For Business And Management. Exploratory Insights (Part Ii)," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(1), pages 169-180, April.
    3. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gupta, Shivam & Kar, Arpan Kumar & Baabdullah, Abdullah & Al-Khowaiter, Wassan A.A., 2018. "Big data with cognitive computing: A review for the future," International Journal of Information Management, Elsevier, vol. 42(C), pages 78-89.
    2. Lee, Alice J. & Ames, Daniel R., 2017. "“I can’t pay more” versus “It’s not worth more”: Divergent effects of constraint and disparagement rationales in negotiations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 141(C), pages 16-28.
    3. Hussain, Hadia & Murtaza, Murtaza & Ajmal, Areeb & Ahmed, Afreen & Khan, Muhammad Ovais Khalid, 2020. "A study on the effects of social media advertisement on consumer’s attitude and customer response," MPRA Paper 104675, University Library of Munich, Germany.
    4. A. G. Fatullayev & Nizami A. Gasilov & Şahin Emrah Amrahov, 2019. "Numerical solution of linear inhomogeneous fuzzy delay differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 315-326, September.
    5. Arun Advani & William Elming & Jonathan Shaw, 2023. "The Dynamic Effects of Tax Audits," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 545-561, May.
    6. Philippe Aghion & Ufuk Akcigit & Matthieu Lequien & Stefanie Stantcheva, 2017. "Tax simplicity and heterogeneous learning," CEP Discussion Papers dp1516, Centre for Economic Performance, LSE.
    7. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    8. Chuangen Gao & Shuyang Gu & Jiguo Yu & Hai Du & Weili Wu, 2022. "Adaptive seeding for profit maximization in social networks," Journal of Global Optimization, Springer, vol. 82(2), pages 413-432, February.
    9. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    10. Annette Alstadsæter & Wojciech Kopczuk & Kjetil Telle, 2019. "Social networks and tax avoidance: evidence from a well-defined Norwegian tax shelter," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(6), pages 1291-1328, December.
    11. Sebastian Kaumanns, 2019. "“Some fuzzy math”: relational information on debt value adjustments by managers and the financial press," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 755-794, December.
    12. Samuel J Gershman, 2015. "A Unifying Probabilistic View of Associative Learning," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-20, November.
    13. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.
    14. Steve Fortin & Ahmad Hammami & Michel Magnan, 2021. "Re‐exploring Fair Value Accounting and Value Relevance: An Examination of Underlying Securities," Abacus, Accounting Foundation, University of Sydney, vol. 57(2), pages 220-250, June.
    15. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    16. Jacobs, Mattis & Kurtz, Christian & Simon, Judith & Böhmann, Tilo, 2021. "Value Sensitive Design and power in socio-technical ecosystems," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 10(3), pages 1-26.
    17. Kristian D. Allee & Daniel D. Wangerin, 2018. "Auditor monitoring and verification in financial contracts: evidence from earnouts and SFAS 141(R)," Review of Accounting Studies, Springer, vol. 23(4), pages 1629-1664, December.
    18. Bertschek, Irene & Kesler, Reinhold, 2022. "Let the user speak: Is feedback on Facebook a source of firms’ innovation?," Information Economics and Policy, Elsevier, vol. 60(C).
    19. Peretzke, Julia & Sandhaus, Gregor, 2017. "Einsatzpotentiale von Cognitive Computing zur Unterstützung der Entscheidungsfindung im Supply Chain Management," ild Schriftenreihe 53, FOM Hochschule für Oekonomie & Management, Institut für Logistik- & Dienstleistungsmanagement (ild).
    20. Németh Tamás, 2019. "How to back up Modules with blended learning The e-Learning platform of FAME," Prosperitas, Budapest Business University, vol. 6(1), pages 102-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:morgsr:v:82:y:2019:i:1:p:1-11:n:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.