Skip to main content

Advertisement

SpringerLink
Log in

Accounting Information Systems and Strategic Performance: The Interplay of Digital Technology and Edge Computing Devices

  • Research
  • Published:
Journal of Grid Computing Aims and scope Submit manuscript

Abstract

With the rapid development of digital technologies, scholars and industries are pushing into the information age, where data processing is the accounting industry's major challenge. This study aimed to analyze the use of these digital technologies for strategic performance attainment and mediating the accounting information system (AIS). Further, this study also explores the moderation of the DT and strategic performance linkage. In this rapid change, the business organization is crucial to competition. Hence, technology is the key factor for maintaining the competitiveness of the industrialists, specifically where information plays a vital role in making management decisions. Accounting software is a significant tool that efficiently collects data and makes timely decisions to declare the business strategy to respond quickly to the market. However, the available accounting software is costly, and small-scale businesses cannot afford it. Therefore, this paper developed a digital accounting system using artificial intelligence (AI) and edge computing (EC) to process and store the accounting data. This article introduces novel edge framework for digital data processing with advanced data processing methods. The with the growth of IoT, the data sizes have increased significantly. Moreover, the traditional cloud platforms are enriched with EC to process the vast amount of data where it is collected. Therefore, the business can adapt to new size data and raise its standards in terms of technical content. It will define the distributed storage in the cloud and test the cluster performance of the system once the system design and its effects on the system. In the end, the system operation time, load balancing and rows of data is tested experimentally. The results and its analysis demonstrated that the data processing with EC for AIS utilized is improved acceleration rate, operational efficiency and execution rate.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Govindarajo, N.S., Kumar, D., Shaikh, E., Kumar, M., Kumar, P.: Industry 4.0 and business policy development: Strategic imperatives for SME performance. Etikonomi 20, 239–258 (2021)

    Article  Google Scholar 

  2. Ardolino, M., Rapaccini, M., Saccani, N., Gaiardelli, P., Crespi, G., Ruggeri, C.: The role of digital technologies for the service transformation of industrial companies. Int. J. Prod. Res. 56, 2116–2132 (2018)

    Article  Google Scholar 

  3. Wang, Y., Han, X., Jin, S.: MAP based modeling method and performance study of a task offloading scheme with time-correlated traffic and VM repair in MEC systems. Wireless Netw. (2022).

  4. Khan, S.A.R., Zia-Ul-Haq, H.M., Umar, M., Yu, Z.: Digital technology and circular economy practices: An strategy to improve organizational performance. Bus. Strategy Dev. 4, 482–490 (2021)

    Article  Google Scholar 

  5. Trendov, M.; Varas, S.; Zeng, M.: Digital technologies in agriculture and rural areas: Status report. In Digital Technologies in Agriculture and Rural Areas: Status Report; FAO: Rome, Italy. Available online: https://www.cabdirect.org/cabdirect/abstract/20198400418 (2019) Accessed 20 November 2022

  6. Zhang, J., Tang, Y., Wang, H., & Xu, K, ASRO-DIO: Active Subspace Random Optimization Based Depth Inertial Odometry. IEEE Trans. Robot. 1–13 (2022)

  7. Natorina, A.: The adaptive management system of marketing commodity policy. Balt. J. Econ. Stud. 5(1), 131–136 (2019)

    Article  Google Scholar 

  8. Ni, Q., Guo, J., Wu, W., Wang, H., Wu, J.: Continuous Influence-Based Community Partition for Social Networks. IEEE Trans. Netw. Sci. Eng. 9(3), 1187–1197 (2022)

    Article  MathSciNet  Google Scholar 

  9. Dai, Q.: Designing an Accounting Information Management System Using Big Data and Cloud Technology. Hindawi Sci. Program. 2022, Article ID 7931328, 11 https://doi.org/10.1155/2022/7931328

  10. Li, J., Deng, Y., Sun, W., Li, W., Li, R., Li, Q., ..., Liu, Z.: Resource orchestration of cloud-edge–based smart grid fault detection. ACM Trans. Sen. Netw. 18(3), (2022)

  11. Li, T., Li, Y., Hoque, M. A., Xia, T., Tarkoma, S., ..., Hui, P.: To what extent we repeat ourselves? Discovering daily activity patterns across mobile app usage. IEEE Trans. Mobile Comput. 21(4), 1492–1507 (2022)

  12. Li, T., Fan, Y., Li, Y., Tarkoma, S., Hui, P.: Understanding the long-term evolution of mobile app usage. IEEE Trans. Mobile Comput. 22(2), 1213–1230 (2023)

  13. Zhao, S., Jianchun, M., Zhao, J., Naghshbandi, N.: A comprehensive and systematic review of the banking systems based on pay-as-you-go payment fashion and cloud computing in the pandemic era. Inf. Syst. e-Bus.Manag. (2023).  https://doi.org/10.1007/s10257-022-00617-9

  14. Tan, J., Jin, H., Hu, H., Hu, R., Zhang, H., ..., Zhang, H.: WF-MTD: evolutionary decision method for moving target defense based on wright-fisher process. IEEE Trans. Dependable Secure Comput. (2022).

  15. Li, X., Sun, Y.: Stock intelligent investment strategy based on support vector machine parameter optimization algorithm. Neural Comput Appl 32(6), 1765–1775 (2020)

    Article  Google Scholar 

  16. Wahyuningsih, D., Nuraliaty, R.A., Darma, D.C., Kasuma, J., Sriwardani: Why dynamic capacity influences the quality of management accounting Information systems in the public sector? Int J Psychosoc Rehabil 24(10), 4032–4044 (2020)

    Google Scholar 

  17. Li, X., Sun, Y.: Application of RBF neural network optimal segmentation algorithm in credit rating. Neural Comput Appl 33(14), 8227–8235 (2021)

    Article  Google Scholar 

  18. Liu, X., Wang, S., Lu, S., Yin, Z., Li, X., Yin, L., ..., Zheng, W.: Adapting feature selection algorithms for the classification of Chinese texts. Systems 11(9), 483 (2023)

  19. Zhu, L.H.: Strategy on accounting informatization management based on financial shared services. J. Nantong Textile Vocational Technol. College 18(3), 63–66 (2018)

    Google Scholar 

  20. Jiang, Z., Xu, C.: Disrupting the technology innovation efficiency of manufacturing enterprises through digital technology promotion: An evidence of 5G technology construction in China. IEEE Trans. Eng. Manage. (2023)

  21. Cheng, B., Zhu, D., Zhao, S., Chen, J.: Situation-Aware IoT Service Coordination Using the Event-Driven SOA Paradigm. IEEE Trans Netw Serv Manage 13(2), 349–361 (2016)

    Article  Google Scholar 

  22. Dai, X., Xiao, Z., Jiang, H., Alazab, M., Lui, J.C.S., Min, G., ..., Liu, J.: Task offloading for cloud-assisted fog computing with dynamic service caching in enterprise management systems. IEEE Trans. Ind. Inf. 19(1), 662–672 (2023)

  23. Dai, X., Xiao, Z., Jiang, H., Alazab, M., Lui, J. C. S., Dustdar, S., ..., Liu, J.: Task Co-Offloading for D2D-Assisted Mobile Edge Computing in Industrial Internet of Things. IEEE Trans. Ind. Inf. 19(1), 480–490 (2023)

  24. Jiang, H., Dai, X., Xiao, Z., Iyengar, A.K.: Joint task offloading and resource allocation for energy-constrained mobile edge computing. IEEE Trans. Mobile Comput. (2022)

  25. Xiao, Z., Shu, J., Jiang, H., Min, G., Chen, H., ..., Han, Z.: Perception task offloading with collaborative computation for autonomous driving. IEEE J. Sel. Areas Commun. 41(2), 457–473 (2023)

  26. Dai, X., Xiao, Z., Jiang, H., Lui, J.C.S.: UAV-Assisted Task Offloading in Vehicular Edge Computing Networks. IEEE Trans. Mobile Comput. (2023)

  27. Ali, T.A.A., Xiao, Z., Jiang, H., Li, B.: A class of digital integrators based on trigonometric quadrature rules. IEEE Trans. Ind. Electron. (2023)

  28. Zhang, J., Liu, Y., Li, Z., Lu, Y.: Forecast-Assisted Service Function Chain Dynamic Deployment for SDN/NFV-Enabled Cloud Management Systems. IEEE Syst. J. (2023)

  29. Gu, Q., Li, S., Liao, Z.: Solving nonlinear equation systems based on evolutionary multitasking with neighborhood-based speciation differential evolution. Expert Syst. Appl. 238 (2024)

  30. Yi, H., Meng, X., Linghu, Y., Zhang, Z.: Can financial capability improve entrepreneurial performance? Evidence from rural China. Econ Res-Ekon Istraž 36(1), 1631–1650 (2023)

    Google Scholar 

  31. Fan, W., Yang, L., Bouguila, N.: Unsupervised Grouped Axial Data Modeling via Hierarchical Bayesian Nonparametric Models With Watson Distributions. IEEE Trans Pattern Anal Mach Intell 44(12), 9654–9668 (2022)

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not Applicable.

Funding

I have received no funding for this research.

Author information

Authors and Affiliations

  1. School of Economics and Management, China University of Petroleum, Beijing, 102249, China

    Xi Zhen

  2. School of Economics and Management, Northeast Agricultural University, Harbin, 150038, China

    Li Zhen

Authors
  1. Xi Zhen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Zhen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

X.Z: Conceptualization, Methodology, Formal analysis, Supervision, Investigation, Data Curation, Writing—original draft, Writing—review & editing.

L.Z: Data Curation, Writing—original draft, Writing—review & editing.

Corresponding author

Correspondence to Xi Zhen.

Ethics declarations

Ethics Approval and Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Competing Interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhen, X., Zhen, L. Accounting Information Systems and Strategic Performance: The Interplay of Digital Technology and Edge Computing Devices. J Grid Computing 22, 5 (2024). https://doi.org/10.1007/s10723-023-09720-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10723-023-09720-8

Keywords

Search

Navigation