IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v6y2021i8p86-d608520.html
   My bibliography  Save this article

Contemporary Business Analytics: An Overview

Author

Listed:
  • Wullianallur Raghupathi

    (Gabelli School of Business, Fordham University, New York, NY 10023, USA)

  • Viju Raghupathi

    (Koppelman School of Business, Brooklyn College of the City University of New York, Brooklyn, NY 11210, USA)

Abstract

We examine the state-of-the-art of the business analytics field by identifying and describing the four types of analytics and the three pillars of modeling. Further, we offer a framework of the interplay between the types of analytics and those pillars of modeling. The article describes the architectural framework and outlines an analytics methodology life cycle. Additionally, key contemporary design issues and challenges are highlighted. In this paper, we offer researchers and practitioners a contemporary overview of business analytics. As business analytics has emerged as a distinct discipline with the key objective to gain insight to make informed decisions, this state-of-the art survey sheds light on recent developments in the business analytics discipline.

Suggested Citation

  • Wullianallur Raghupathi & Viju Raghupathi, 2021. "Contemporary Business Analytics: An Overview," Data, MDPI, vol. 6(8), pages 1-11, August.
  • Handle: RePEc:gam:jdataj:v:6:y:2021:i:8:p:86-:d:608520
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/6/8/86/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2306-5729/6/8/86/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ritu Agarwal & Vasant Dhar, 2014. "Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research," Information Systems Research, INFORMS, vol. 25(3), pages 443-448, September.
    2. Ilias O. Pappas & Patrick Mikalef & Michail N. Giannakos & John Krogstie & George Lekakos, 2018. "Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies," Information Systems and e-Business Management, Springer, vol. 16(3), pages 479-491, August.
    3. Mihaela Muntean, 2018. "Business Intelligence Issues for Sustainability Projects," Sustainability, MDPI, vol. 10(2), pages 1-10, January.
    4. Wullianallur Raghupathi & Viju Raghupathi, 2018. "An Empirical Study of Chronic Diseases in the United States: A Visual Analytics Approach to Public Health," IJERPH, MDPI, vol. 15(3), pages 1-24, March.
    5. Vidgen, Richard & Shaw, Sarah & Grant, David B., 2017. "Management challenges in creating value from business analytics," European Journal of Operational Research, Elsevier, vol. 261(2), pages 626-639.
    6. Iman Raeesi Vanani & Seyed Mohammad Jafar Jalali, 2018. "A comparative analysis of emerging scientific themes in business analytics," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 29(2), pages 183-206.
    7. Appelbaum, Deniz & Kogan, Alexander & Vasarhelyi, Miklos & Yan, Zhaokai, 2017. "Impact of business analytics and enterprise systems on managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 25(C), pages 29-44.
    8. Vidgen, Richard & Hindle, Giles & Randolph, Ian, 2020. "Exploring the ethical implications of business analytics with a business ethics canvas," European Journal of Operational Research, Elsevier, vol. 281(3), pages 491-501.
    9. Kyoung-jae Kim & Kichun Lee & Hyunchul Ahn, 2018. "Predicting Corporate Financial Sustainability Using Novel Business Analytics," Sustainability, MDPI, vol. 11(1), pages 1-17, December.
    10. Martin Kunc & Frances A. O’Brien, 2019. "The role of business analytics in supporting strategy processes: Opportunities and limitations," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(6), pages 974-985, June.
    11. Aurora Martínez-Martínez & Juan Gabriel Cegarra Navarro & Alexeis García-Pérez & Ana Moreno-Ponce, 2019. "Environmental knowledge strategy: driving success of the hospitality industry," Management Research Review, Emerald Group Publishing Limited, vol. 42(6), pages 662-680, January.
    12. Seyed Mohammad Jafar Jalali & Han Woo Park, 2018. "State of the art in business analytics: themes and collaborations," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 627-633, March.
    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. Ranjan Chaudhuri & Sheshadri Chatterjee & Demetris Vrontis & Alkis Thrassou, 2024. "Adoption of robust business analytics for product innovation and organizational performance: the mediating role of organizational data-driven culture," Annals of Operations Research, Springer, vol. 339(3), pages 1757-1791, August.
    2. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    3. Shiyu Liu & Ou Liu & Junyang Chen, 2023. "A Review on Business Analytics: Definitions, Techniques, Applications and Challenges," Mathematics, MDPI, vol. 11(4), pages 1-20, February.
    4. Chotia, Varun & Cheng, Yue & Agarwal, Reeti & Vishnoi, Sushant Kumar, 2024. "AI-enabled Green Business Strategy: Path to carbon neutrality via environmental performance and green process innovation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    5. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
    6. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
    7. Erkan Bayraktar & Ekrem Tatoglu & Arafat Salih Aydiner & Dursun Delen, 2024. "Business Analytics Adoption and Technological Intensity: An Efficiency Analysis," Information Systems Frontiers, Springer, vol. 26(4), pages 1509-1526, August.
    8. Ashrafi, Amir & Zareravasan, Ahad, 2022. "An ambidextrous approach on the business analytics-competitive advantage relationship: Exploring the moderating role of business analytics strategy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    9. Omar, Yamila M. & Minoufekr, Meysam & Plapper, Peter, 2019. "Business analytics in manufacturing: Current trends, challenges and pathway to market leadership," Operations Research Perspectives, Elsevier, vol. 6(C).
    10. Richly, Marc A., 2022. "Big Data Analytics Capabilities: A Systematic Literature Review on Necessary Skills to Succeed in Big Data Analytics," Junior Management Science (JUMS), Junior Management Science e. V., vol. 7(5), pages 1224-1241.
    11. Fotis Kitsios & Maria Kamariotou, 2021. "Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    12. Ilias O. Pappas & Patrick Mikalef & Michail N. Giannakos & John Krogstie & George Lekakos, 2018. "Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies," Information Systems and e-Business Management, Springer, vol. 16(3), pages 479-491, August.
    13. Luminița Hurbean & Florin Militaru & Mihaela Muntean & Doina Danaiata, 2023. "The Impact of Business Intelligence and Analytics Adoption on Decision Making Effectiveness and Managerial Work Performance," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 70(SI), pages 43-54, February.
    14. Francis Aboagye‐Otchere & Cletus Agyenim‐Boateng & Abdulai Enusah & Theodora Ekua Aryee, 2021. "A Review of Big Data Research in Accounting," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(4), pages 268-283, October.
    15. Aydiner, Arafat Salih & Tatoglu, Ekrem & Bayraktar, Erkan & Zaim, Selim & Delen, Dursun, 2019. "Business analytics and firm performance: The mediating role of business process performance," Journal of Business Research, Elsevier, vol. 96(C), pages 228-237.
    16. Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Burger, Katharina & White, Leroy & Yearworth, Mike, 2019. "Developing a smart operational research with hybrid practice theories," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1137-1150.
    18. Mikalef, Patrick & Boura, Maria & Lekakos, George & Krogstie, John, 2019. "Big data analytics and firm performance: Findings from a mixed-method approach," Journal of Business Research, Elsevier, vol. 98(C), pages 261-276.
    19. Hughes, Jeffrey & Ball, Kirstie, 2020. "Sowing the seeds of value? Persuasive practices and the embedding of big data analytics," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    20. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.

    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:gam:jdataj:v:6:y:2021:i:8:p:86-:d:608520. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.