IDEAS home Printed from https://ideas.repec.org/a/eee/ijoais/v41y2021ics1467089521000130.html
   My bibliography  Save this article

Explaining the (non-) adoption of advanced data analytics in auditing: A process theory

Author

Listed:
  • Krieger, Felix
  • Drews, Paul
  • Velte, Patrick

Abstract

Audit firms are increasingly engaging with advanced data analytics to improve the efficiency and effectiveness of external audits through the automation of audit work and obtaining a better understanding of the client’s business risk and thus their own audit risk. This paper examines the process by which audit firms adopt advanced data analytics, which has been left unaddressed by previous research. We derive a process theory from expert interviews which describes the activities within the process and the organizational units involved. It further describes how the adoption process is affected by technological, organizational and environmental contextual factors. Our work contributes to the extent body of research on technology adoption in auditing by using a previously unused theoretical perspective, and contextualizing known factors of technology adoption. The findings presented in this paper emphasize the importance of technological capabilities of audit firms for the adoption of advanced data analytics; technological capabilities within audit teams can be leveraged to support both the ideation of possible use cases for advanced data analytics, as well as the diffusion of solutions into practice.

Suggested Citation

  • Krieger, Felix & Drews, Paul & Velte, Patrick, 2021. "Explaining the (non-) adoption of advanced data analytics in auditing: A process theory," International Journal of Accounting Information Systems, Elsevier, vol. 41(C).
  • Handle: RePEc:eee:ijoais:v:41:y:2021:i:c:s1467089521000130
    DOI: 10.1016/j.accinf.2021.100511
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1467089521000130
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.accinf.2021.100511?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. George Salijeni & Anna Samsonova-Taddei & Stuart Turley, 2019. "Big Data and changes in audit technology: contemplating a research agenda," Accounting and Business Research, Taylor & Francis Journals, vol. 49(1), pages 95-119, January.
    2. Christopher Humphrey & Asad Kausar & Anne Loft & Margaret Woods, 2011. "Regulating Audit beyond the Crisis: A Critical Discussion of the EU Green Paper," European Accounting Review, Taylor & Francis Journals, vol. 20(3), pages 431-457, June.
    3. Tim D. Bauer & Cassandra Estep & Bertrand Malsch, 2019. "One Team or Two? Investigating Relationship Quality between Auditors and IT Specialists: Implications for Audit Team Identity and the Audit Process†," Contemporary Accounting Research, John Wiley & Sons, vol. 36(4), pages 2142-2177, December.
    4. Mary B. Curtis & Elizabeth A. Payne, 2014. "Modeling voluntary CAAT utilization decisions in auditing," Managerial Auditing Journal, Emerald Group Publishing, vol. 29(4), pages 304-326, April.
    5. M. Lynne Markus & Daniel Robey, 1988. "Information Technology and Organizational Change: Causal Structure in Theory and Research," Management Science, INFORMS, vol. 34(5), pages 583-598, May.
    6. Amir Michael & Rob Dixon, 2019. "Audit data analytics of unregulated voluntary disclosures and auditing expectations gap," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 16(4), pages 188-205, December.
    7. Huang, Feiqi & Vasarhelyi, Miklos A., 2019. "Applying robotic process automation (RPA) in auditing: A framework," International Journal of Accounting Information Systems, Elsevier, vol. 35(C).
    8. Gray, Glen L. & Chiu, Victoria & Liu, Qi & Li, Pei, 2014. "The expert systems life cycle in AIS research: What does it mean for future AIS research?," International Journal of Accounting Information Systems, Elsevier, vol. 15(4), pages 423-451.
    9. Rindang Widuri & Brendan O’Connell & Prem W.S. Yapa, 2016. "Adopting generalized audit software: an Indonesian perspective," Managerial Auditing Journal, Emerald Group Publishing, vol. 31(8/9), pages 821-847, September.
    10. Siew, Eu-Gene & Rosli, Khairina & Yeow, Paul H.P., 2020. "Organizational and environmental influences in the adoption of computer-assisted audit tools and techniques (CAATTs) by audit firms in Malaysia," International Journal of Accounting Information Systems, Elsevier, vol. 36(C).
    11. Aidi Ahmi & Simon Kent, 2012. "The utilisation of generalized audit software (GAS) by external auditors," Managerial Auditing Journal, Emerald Group Publishing, vol. 28(2), pages 88-113, December.
    12. Miklos A. Vasarhelyi & Silvia Romero, 2014. "Technology in audit engagements: a case study," Managerial Auditing Journal, Emerald Group Publishing, vol. 29(4), pages 350-365, April.
    13. Lina Dagilienė & Lina Klovienė, 2019. "Motivation to use big data and big data analytics in external auditing," Managerial Auditing Journal, Emerald Group Publishing Limited, vol. 34(7), pages 750-782, June.
    14. Alles, Michael & Gray, Glen L., 2016. "Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors," International Journal of Accounting Information Systems, Elsevier, vol. 22(C), pages 44-59.
    15. Jans, Mieke & Alles, Michael & Vasarhelyi, Miklos, 2013. "The case for process mining in auditing: Sources of value added and areas of application," International Journal of Accounting Information Systems, Elsevier, vol. 14(1), pages 1-20.
    16. Khaldoon Al-Htaybat & Larissa von Alberti-Alhtaybat, 2017. "Big Data and corporate reporting: impacts and paradoxes," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 30(4), pages 850-873, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Afsay, Akram & Tahriri, Arash & Rezaee, Zabihollah, 2023. "A meta-analysis of factors affecting acceptance of information technology in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    2. Anastassia Fedyk & James Hodson & Natalya Khimich & Tatiana Fedyk, 2022. "Is artificial intelligence improving the audit process?," Review of Accounting Studies, Springer, vol. 27(3), pages 938-985, September.
    3. Mihai-Răzvan Sanda & Marian-Ilie Siminică & Costin-Daniel Avram & Luminița Popescu, 2024. "Ghosts in the Machine: How Big Data Analytics Can Be Used to Strengthen Online Public Procurement Accountability," Sustainability, MDPI, vol. 16(9), pages 1-15, April.
    4. Ruhnke, Klaus, 2023. "Empirical research frameworks in a changing world: The case of audit data analytics," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 51(C).
    5. Nathanael Betti & Steven DeSimone & Joy Gray, 2022. "The impacts of the use of data analytics and the performance of consulting activities on perceived internal audit quality," Working Papers 2202, College of the Holy Cross, Department of Economics.
    6. 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).

    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. Afsay, Akram & Tahriri, Arash & Rezaee, Zabihollah, 2023. "A meta-analysis of factors affecting acceptance of information technology in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    2. 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.
    3. Vicky Arnold, 2018. "The changing technological environment and the future of behavioural research in accounting," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(2), pages 315-339, June.
    4. Siew, Eu-Gene & Rosli, Khairina & Yeow, Paul H.P., 2020. "Organizational and environmental influences in the adoption of computer-assisted audit tools and techniques (CAATTs) by audit firms in Malaysia," International Journal of Accounting Information Systems, Elsevier, vol. 36(C).
    5. Moll, Jodie & Yigitbasioglu, Ogan, 2019. "The role of internet-related technologies in shaping the work of accountants: New directions for accounting research," The British Accounting Review, Elsevier, vol. 51(6).
    6. Dermarkar, Simon & Hazgui, Mouna, 2022. "How auditors legitimize commercialism: A micro-discursive analysis," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 83(C).
    7. Ruhnke, Klaus, 2023. "Empirical research frameworks in a changing world: The case of audit data analytics," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 51(C).
    8. Federica De Santis, 2018. "Big Data e revisione contabile: uno studio esplorativo nel contesto italiano," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2), pages 129-154.
    9. Ahmad Almagrashi & Abdulwahab Mujalli & Tehmina Khan & Osama Attia, 2023. "Factors determining internal auditors’ behavioral intention to use computer-assisted auditing techniques: an extension of the UTAUT model and an empirical study," Future Business Journal, Springer, vol. 9(1), pages 1-19, December.
    10. Fábio Albuquerque & Paula Gomes Dos Santos, 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools," FinTech, MDPI, vol. 2(2), pages 1-27, April.
    11. Amir Michael & Rob Dixon, 2019. "Audit data analytics of unregulated voluntary disclosures and auditing expectations gap," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 16(4), pages 188-205, December.
    12. Alnoor Bhimani, 2020. "Digital data and management accounting: why we need to rethink research methods," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 9-23, April.
    13. Rakipi, Romina & De Santis, Federica & D'Onza, Giuseppe, 2021. "Correlates of the internal audit function’s use of data analytics in the big data era: Global evidence," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 42(C).
    14. Pall Rikhardsson & Kishore Singh & Peter Best, 2019. "Exploring Continuous Auditing Solutions and Internal Auditing: A Research Note," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 18(4), pages 614-639, December.
    15. Ravi Seethamraju & Angela Hecimovic, 2023. "Adoption of artificial intelligence in auditing: An exploratory study," Australian Journal of Management, Australian School of Business, vol. 48(4), pages 780-800, November.
    16. Kumar, Satish & Marrone, Mauricio & Liu, Qi & Pandey, Nitesh, 2020. "Twenty years of the International Journal of Accounting Information Systems: A bibliometric analysis," International Journal of Accounting Information Systems, Elsevier, vol. 39(C).
    17. Rajiv Kohli & Sarv Devaraj, 2003. "Measuring Information Technology Payoff: A Meta-Analysis of Structural Variables in Firm-Level Empirical Research," Information Systems Research, INFORMS, vol. 14(2), pages 127-145, June.
    18. Bianco, Federica & Michelino, Francesca, 2010. "The role of content management systems in publishing firms," International Journal of Information Management, Elsevier, vol. 30(2), pages 117-124.
    19. Sony, Michael & Naik, Subhash, 2020. "Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical model," Technology in Society, Elsevier, vol. 61(C).
    20. repec:dau:papers:123456789/3232 is not listed on IDEAS
    21. Mähring, Magnus, 2002. "IT Project Governance: A Process-Oriented Study of Organizational Control and Executive Involvement," SSE/EFI Working Paper Series in Business Administration 2002:15, Stockholm School of Economics.

    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:ijoais:v:41:y:2021:i:c:s1467089521000130. 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: https://www.journals.elsevier.com/international-journal-of-accounting-information-systems/ .

    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.