IDEAS home Printed from https://ideas.repec.org/a/aic/saebjn/v70y2023isip43-54n3.html
   My bibliography  Save this article

The Impact of Business Intelligence and Analytics Adoption on Decision Making Effectiveness and Managerial Work Performance

Author

Listed:
  • LuminiÈ›a Hurbean

    (West University of Timișoara)

  • Florin Militaru

    (West University of Timișoara)

  • Mihaela Muntean

    (West University of Timișoara)

  • Doina Danaiata

    (West University of Timișoara)

Abstract

Business Intelligence and Analytics systems have the capability to enable organizations to better comprehend their business and to increase the quality of managerial decisions, and consequently improve their performance. Recently, organizations have embraced the idea that data becomes a core asset, and this belief also changes the culture of the organization; data and analytics now determine a data-driven culture, which makes way for more effective data-driven decisions. To the best of our knowledge, there are few studies that investigate the effects of BI&A adoption on individual decision-making effectiveness and managerial work performance. This paper aims to contribute to bridging this gap by providing a research model that examines the relationship between BI&A adoption and manager’s decision-making effectiveness and then his individual work performance. The research model also theorizes that a data-driven culture promotes the BI&A adoption in the organization. Using specific control variables, we also expect to observe differences between different departments and managerial positions, which will provide practical implications for companies that work on BI&A adoption.

Suggested Citation

  • LuminiÈ›a 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.
  • Handle: RePEc:aic:saebjn:v:70:y:2023:i:si:p:43-54:n:3
    as

    Download full text from publisher

    File URL: http://saeb.feaa.uaic.ro/index.php/saeb/article/view/2010
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ashish Kumar Jha & Maher Agi & Eric W.T. Ngai, 2020. "A note on big data analytics capability development in supply chain," Post-Print hal-03164004, HAL.
    2. Jonathan Calof & Gregory Richards & Jack Smith, 2015. "Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 9(1), pages 68-81.
    3. 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.
    4. Rajeev Sharma & Sunil Mithas & Atreyi Kankanhalli, 2014. "Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations," European Journal of Information Systems, Taylor & Francis Journals, vol. 23(4), pages 433-441, July.
    5. 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.
    6. Jonathan Calof & Gregory Richards & Jack Smith, 2015. "Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient," Foresight-Russia Форсайт, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 9(1 (eng)), pages 68-81.
    7. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
    8. Bongsug Kevin Chae & David L. Olson, 2013. "Business Analytics For Supply Chain: A Dynamic-Capabilities Framework," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 9-26.
    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. Nam, Dalwoo & Lee, Junyeong & Lee, Heeseok, 2019. "Business analytics use in CRM: A nomological net from IT competence to CRM performance," International Journal of Information Management, Elsevier, vol. 45(C), pages 233-245.
    3. Rikhardsson, Pall & Yigitbasioglu, Ogan, 2018. "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 37-58.
    4. 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.
    5. Gershman, Mikhail & Bredikhin, Sergey & Vishnevskiy, Konstantin, 2016. "The role of corporate foresight and technology roadmapping in companies' innovation development: The case of Russian state-owned enterprises," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 187-195.
    6. Kalaitzi, Dimitra & Tsolakis, Naoum, 2022. "Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage," International Journal of Production Economics, Elsevier, vol. 248(C).
    7. Osman, Ibrahim H. & Anouze, Abdel Latef & Irani, Zahir & Lee, Habin & Medeni, Tunç D. & Weerakkody, Vishanth, 2019. "A cognitive analytics management framework for the transformation of electronic government services from users’ perspective to create sustainable shared values," European Journal of Operational Research, Elsevier, vol. 278(2), pages 514-532.
    8. Murat Sahin & Christophe Bisson, 2021. "A Competitive Intelligence Practices Typology in an Airline Company in Turkey," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 899-922, June.
    9. Bradford Ashton, 2020. "Intelligent Technology Scanning: Aims, Content, and Practice," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(3), pages 15-29.
    10. Hakmaoui, Abdelati & Oubrich, Mourad & Calof, Jonathan & El Ghazi, Hamid, 2022. "Towards an anticipatory system incorporating corporate foresight and competitive intelligence in creating knowledge: a longitudinal Moroccan bank case study," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    11. Maël Schnegg & Klaus Möller, 2022. "Strategies for data analytics projects in business performance forecasting: a field study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 33(2), pages 241-271, June.
    12. Wullianallur Raghupathi & Viju Raghupathi, 2021. "Contemporary Business Analytics: An Overview," Data, MDPI, vol. 6(8), pages 1-11, August.
    13. Perdana, Arif & Lee, Hwee Hoon & Koh, SzeKee & Arisandi, Desi, 2022. "Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance," International Journal of Accounting Information Systems, Elsevier, vol. 44(C).
    14. Philipp Korherr & Dominik Kanbach, 2023. "Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance," Review of Managerial Science, Springer, vol. 17(6), pages 1943-1970, August.
    15. 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.
    16. Madureira, Luís & Popovič, Aleš & Castelli, Mauro, 2021. "Competitive intelligence: A unified view and modular definition," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Svetlana V. Sibatrova & Konstantin Vishnevskiy, 2016. "Present and Future of the Production: Integrating Lean Management into Corporate Foresight," HSE Working papers WP BRP 66/STI/2016, National Research University Higher School of Economics.
    18. Anna Nikolaevna Schmeleva & Maria Gennadyevna Umnova, 2017. "Enhancement of Academic Research Activity in Higher Education Institutions with the Usage of Foresight Methodology," International Review of Management and Marketing, Econjournals, vol. 7(1), pages 442-451.
    19. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.
    20. Xiaoxu Dong & Huawei Zhao & Tiancai Li, 2022. "The Role of Live-Streaming E-Commerce on Consumers’ Purchasing Intention regarding Green Agricultural Products," Sustainability, MDPI, vol. 14(7), pages 1-13, April.

    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:aic:saebjn:v:70:y:2023:i:si:p:43-54:n:3. 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: Sireteanu Napoleon-Alexandru (email available below). General contact details of provider: https://edirc.repec.org/data/feaicro.html .

    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.