IDEAS home Printed from https://ideas.repec.org/a/vrs/founma/v16y2024i1p67-82n1005.html
   My bibliography  Save this article

Optimization of Accounting information System in Public Sector for Sustainable Risk Management Under Big Data Analytics. Does forensic Accountants’ Skill Generate Differences?

Author

Listed:
  • HUY Pham Quang

    (University of Economics Ho Chi Minh City (UEH), School of Accounting, Chi Minh City, VIETNAM)

  • PHUC Vu Kien

    (University of Economics Ho Chi Minh City (UEH), School of Accounting, Vinh Long Campus, Vinh Long, VIETNAM)

Abstract

This article sets its sight to allot an intelligible picture of how to optimize accounting information system (AIS) in public sector organization (PSO) for sustainable risk management (SRM) under the big data analytics (BDA) and offers in-depth understandings concerning to the role of forensic accountants’ skill (FAS) on these aforementioned interconnections. The structural equation modeling (SEM) and multi-group SEM were wielded to testify the hypothesized model rested on cross-sectional data formulated by a closed-ended questionnaire survey distributed to convenience and snowball sample of 683 respondents in PSOs. All the proffered hypotheses in the theoretical model were authenticated by the soundly statistical evidences. The observations of the current study also generated the numerous practical implications for the practitioners in organizational management and policymakers in building up the strategies and promulgating rules in relation to digital initiatives adoption, accounting practices and risk management toward sustainable development within PSOs.

Suggested Citation

  • HUY Pham Quang & PHUC Vu Kien, 2024. "Optimization of Accounting information System in Public Sector for Sustainable Risk Management Under Big Data Analytics. Does forensic Accountants’ Skill Generate Differences?," Foundations of Management, Sciendo, vol. 16(1), pages 67-82.
    • Handle: RePEc:vrs:founma:v:16:y:2024:i:1:p:67-82:n:1005
    DOI: 10.2478/fman-2024-0005
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/fman-2024-0005
    Download Restriction: no
    File URL: https://libkey.io/10.2478/fman-2024-0005?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. Qaisar Ali & Hakimah Yaacob & Shazia Parveen & Zaki Zaini, 2021. "Big data and predictive analytics to optimise social and environmental performance of Islamic banks," Environment Systems and Decisions, Springer, vol. 41(4), pages 616-632, December.
    2. James A. DiGabriele, 2009. "Implications of regulatory prescriptions and audit standards on the evolution of forensic accounting in the audit process," Journal of Applied Accounting Research, Emerald Group Publishing Limited, vol. 10(2), pages 109-121, September.
    3. Adrian Gepp & Martina K. Linnenluecke & Terrence J. O’Neill & Tom Smith, 2018. "Big data techniques in auditing research and practice: Current trends and future opportunities," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 40(1), pages 102-115, February.
    4. Kevin L. Papiorek & Martin R.W. Hiebl, 2023. "Information systems quality in management accounting and management control effectiveness," Journal of Accounting & Organizational Change, Emerald Group Publishing Limited, vol. 20(3), pages 433-458, June.
    5. Baljinder Kaur & Kiran Sood & Simon Grima, 2022. "A systematic review on forensic accounting and its contribution towards fraud detection and prevention," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 31(1), pages 60-95, June.
    6. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    7. Barnes, Stuart J., 2020. "Information management research and practice in the post-COVID-19 world," International Journal of Information Management, Elsevier, vol. 55(C).
    8. Stephen Oduro & Leul Girma Haylemariam, 2019. "Market orientation, CSR and financial and marketing performance in manufacturing firms in Ghana and Ethiopia," Sustainability Accounting, Management and Policy Journal, Emerald Group Publishing Limited, vol. 10(3), pages 398-426, July.
    9. 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.
    10. Abubakar, A. Mohammed & Behravesh, Elaheh & Rezapouraghdam, Hamed & Yildiz, Selim Baha, 2019. "Applying artificial intelligence technique to predict knowledge hiding behavior," International Journal of Information Management, Elsevier, vol. 49(C), pages 45-57.
    11. Muhammad Fiaz & Amir Ikram & Asad Ilyas, 2018. "Enterprise Resource Planning Systems: Digitization of Healthcare Service Quality," Administrative Sciences, MDPI, vol. 8(3), pages 1-12, 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. 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.
    2. Shamim, Saqib & Zeng, Jing & Khan, Zaheer & Zia, Najam Ul, 2020. "Big data analytics capability and decision making performance in emerging market firms: The role of contractual and relational governance mechanisms," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    4. Hossain, Md Afnan & Akter, Shahriar & Yanamandram, Venkata, 2021. "Why doesn't our value creation payoff: Unpacking customer analytics-driven value creation capability to sustain competitive advantage," Journal of Business Research, Elsevier, vol. 131(C), pages 287-296.
    5. 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.
    6. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    7. Mihai BOGDAN & Anca BORZA, 2019. "Big Data Analytics and Organizational Performance: A Meta-Analysis Study," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 4(2), pages 1-13, June.
    8. Mihai BOGDAN & Anca BORZA, 2020. "Big Data Analytics And Firm Performance: A Text Mining Approach," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 14(1), pages 549-560, November.
    9. Vicky Ching Gu & Bin Zhou & Qing Cao & Jeffery Adams, 2021. "Exploring the relationship between supplier development, big data analytics capability, and firm performance," Annals of Operations Research, Springer, vol. 302(1), pages 151-172, July.
    10. 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.
    11. Liang, Xiaoning & Li, Guoxin & Zhang, Hao & Nolan, Eimear & Chen, Fadong, 2022. "Firm performance and marketing analytics in the Chinese context: A contingency model," Journal of Business Research, Elsevier, vol. 141(C), pages 589-599.
    12. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Grenoble Ecole de Management (Post-Print) halshs-01923259, HAL.
    13. Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    14. Dignity Paradza & Olawande Daramola, 2021. "Business Intelligence and Business Value in Organisations: A Systematic Literature Review," Sustainability, MDPI, vol. 13(20), pages 1-27, October.
    15. Muhammad Anwar & Sher Zaman Khan & Syed Zulfiqar Ali Shah, 2018. "Big Data Capabilities and Firm’s Performance: A Mediating Role of Competitive Advantage," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1-28, December.
    16. Kim, Jaemin & Dibrell, Clay & Kraft, Ellen & Marshall, David, 2021. "Data analytics and performance: The moderating role of intuition-based HR management in major league baseball," Journal of Business Research, Elsevier, vol. 122(C), pages 204-216.
    17. Elisa Rodepeter & Christoph Gschnaidtner & Hanna Hottenrott, 2024. "Big Data and Start-up Performance," Working Papers 232, Bavarian Graduate Program in Economics (BGPE).
    18. Mihai BOGDAN & Anca BORZA, 2019. "Big Data Analytics As A Strategic Capability: A Systematic Review," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 13(1), pages 575-583, November.
    19. Ciampi, Francesco & Demi, Stefano & Magrini, Alessandro & Marzi, Giacomo & Papa, Armando, 2021. "Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation," Journal of Business Research, Elsevier, vol. 123(C), pages 1-13.
    20. 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.

    More about this item

    Keywords

    accounting information system; big data analytics; forensic accountants; skill; sustainable risk management; public sector;
    All these keywords.

    JEL classification:

    • H83 - Public Economics - - Miscellaneous Issues - - - Public Administration
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    Statistics

    Access and download statistics

    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:founma:v:16:y:2024:i:1:p:67-82:n:1005. 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.