IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v96y2019icp228-237.html
   My bibliography  Save this article

Business analytics and firm performance: The mediating role of business process performance

Author

Listed:
  • Aydiner, Arafat Salih
  • Tatoglu, Ekrem
  • Bayraktar, Erkan
  • Zaim, Selim
  • Delen, Dursun

Abstract

Due to the rapidly increasing popularity of business analytics (BA), investigation of the antecedents/determinants of the adoption of BA and the subsequent impact of the same to the firm performance has become an important research topic. Drawing on the fundamentals of the resource-based view (RBV), this study proposes a model that examines the effects of the BA adoption on business process performance (BPER) and the mediating role that BPER plays in the relationship between the adoption of BA and firm performance (FP). Based on the data collected from 204 medium- to high-level business executives in various industries, the results of this empirical study indicate that the adoption of BA positively influences BPER. There is also positive relationship between BPER and FP. Finally, the results show that BPER fully mediates the relationship between BA adoption and FP.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jbrese:v:96:y:2019:i:c:p:228-237
    DOI: 10.1016/j.jbusres.2018.11.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296318305800
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2018.11.028?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Delen, Dursun & Zolbanin, Hamed M., 2018. "The analytics paradigm in business research," Journal of Business Research, Elsevier, vol. 90(C), pages 186-195.
    2. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    3. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    4. Troilo, Michael & Bouchet, Adrien & Urban, Timothy L. & Sutton, William A., 2016. "Perception, reality, and the adoption of business analytics: Evidence from North American professional sport organizations," Omega, Elsevier, vol. 59(PA), pages 72-83.
    5. Moon, Karen Ka-Leung & Yi, Candace Ying & Ngai, E.W.T., 2012. "An instrument for measuring supply chain flexibility for the textile and clothing companies," European Journal of Operational Research, Elsevier, vol. 222(2), pages 191-203.
    6. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    7. Hindle, Giles A. & Vidgen, Richard, 2018. "Developing a business analytics methodology: A case study in the foodbank sector," European Journal of Operational Research, Elsevier, vol. 268(3), pages 836-851.
    8. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    9. Elbashir, Mohamed Z. & Collier, Philip A. & Davern, Michael J., 2008. "Measuring the effects of business intelligence systems: The relationship between business process and organizational performance," International Journal of Accounting Information Systems, Elsevier, vol. 9(3), pages 135-153.
    10. Marc Gruber & Florian Heinemann & Malte Brettel & Stephan Hungeling, 2010. "Configurations of resources and capabilities and their performance implications: an exploratory study on technology ventures," Strategic Management Journal, Wiley Blackwell, vol. 31(12), pages 1337-1356, December.
    11. Martin Bichler & Armin Heinzl & Wil M. P. Aalst, 2017. "Business Analytics and Data Science: Once Again?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(2), pages 77-79, April.
    12. 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.
    13. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    14. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    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. Bayraktar, Erkan & Demirbag, Mehmet & Koh, S.C. Lenny & Tatoglu, Ekrem & Zaim, Halil, 2009. "A causal analysis of the impact of information systems and supply chain management practices on operational performance: Evidence from manufacturing SMEs in Turkey," International Journal of Production Economics, Elsevier, vol. 122(1), pages 133-149, November.
    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. 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.
    2. Ashrafi, Amir & Zare Ravasan, Ahad & Trkman, Peter & Afshari, Samira, 2019. "The role of business analytics capabilities in bolstering firms’ agility and performance," International Journal of Information Management, Elsevier, vol. 47(C), pages 1-15.
    3. 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.
    4. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    5. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    6. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
    7. Conboy, Kieran & Mikalef, Patrick & Dennehy, Denis & Krogstie, John, 2020. "Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda," European Journal of Operational Research, Elsevier, vol. 281(3), pages 656-672.
    8. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    9. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    10. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    11. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    12. Mareike Bergmann & Christian Brück & Thorsten Knauer & Anja Schwering, 2020. "Digitization of the budgeting process: determinants of the use of business analytics and its effect on satisfaction with the budgeting process," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 25-54, April.
    13. 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.
    14. 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).
    15. Hossain, Md Afnan & Akter, Shahriar & Yanamandram, Venkata, 2020. "Revisiting customer analytics capability for data-driven retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    16. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    17. Raguseo, Elisabetta & Vitari, Claudio & Pigni, Federico, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," International Journal of Production Economics, Elsevier, vol. 229(C).
    18. Candice WALLS & Brian BARNARD, 2020. "Success Factors of Big Data to Achieve Organisational Performance: Theoretical Perspectives," Expert Journal of Business and Management, Sprint Investify, vol. 8(1), pages 1-16.
    19. Osama Musa Ali Al-Darras & Cem Tanova, 2022. "From Big Data Analytics to Organizational Agility: What Is the Mechanism?," SAGE Open, , vol. 12(2), pages 21582440221, June.
    20. S. Vijayakumar Bharathi, 2017. "Prioritizing and Ranking the Big Data Information Security Risk Spectrum," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 183-201, September.

    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:eee:jbrese:v:96:y:2019:i:c:p:228-237. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.