208 188
Full Length Article
American Journal of Business and Operations Research
Volume 11 , Issue 1, PP: 79-88 , 2024 | Cite this article as | XML | Html |PDF

Title

Data-Driven Decision Support Systems for Business Process Improvement

  Betul Aktas 1 *

1  Higher Vocational School, Cag University, Mersin, Turkey
    (betulaktas@cag.edu.tr)

Full Text Download


Doi   :   https://doi.org/10.54216/AJBOR.110109

Received: July 27, 2023 Revised: October 18, 2023 Accepted: December 11, 2023

Abstract :

The accessibility of data is altering how businesses make decisions at different levels. Scholars and professionals are investigating the ways in which Business Process suppliers can profit from the availability and application of data, particularly in relation to decision-making concerning service provision. Business Process Improvement is one of the applications that is anticipated to gain the most from the accessibility of information. Suppliers of services can avoid failures by making prompt and well-informed decisions based on the evaluation of the resource's health state. Despite this, providing data-driven BPI services is not simple, and providers must set up their systems to correctly gather, process, and utilize past and current data. This study introduces a data-driven business intelligence framework to provide use full insights for improving business process activities. This framework offers a set of visualization tools that help interpret the relation between different factors that can improve the management of different business processes. Moreover, our framework provides successful integration of random forests to allow predictive modeling of sales, profits, and discounts across different regions.

Keywords :

Business Intelligence; Decision Making; Data-driven Intelligence; Business Process.

References :

[1]    Power, D. J. (2008). Understanding data-driven decision support systems. Information Systems Management, 25(2), 149-154.

[2]    Fleig, C. (2020). Design of data-driven decision support systems for business process standardization (Doctoral dissertation, Dissertation, Karlsruhe, Karlsruher Institut für Technologie (KIT), 2020).

[3]    Rejikumar, G., Aswathy Asokan, A., & Sreedharan, V. R. (2020). Impact of data-driven decision-making in Lean Six Sigma: an empirical analysis. Total Quality Management & Business Excellence, 31(3-4), 279-296.

[4]    Hedgebeth, D. (2007). Data‐driven decision making for the enterprise: an overview of business intelligence applications. Vine, 37(4), 414-420.

[5]    Mandinach, E. B., Honey, M., & Light, D. (2006, April). A theoretical framework for data-driven decision making. In annual meeting of the American Educational Research Association, San Francisco, CA.

[6]    Abd Rahman, M. S. B., Mohamad, E., & Abdul Rahman, A. A. B. (2021). Development of IoT—enabled data analytics enhance decision support system for lean manufacturing process improvement. Concurrent Engineering, 29(3), 208-220.

[7]    Antomarioni, S., Lucantoni, L., Ciarapica, F. E., & Bevilacqua, M. (2021). Data-driven decision support system for managing item allocation in an ASRS: A framework development and a case study. Expert Systems with Applications, 185, 115622.

[8]    Diván, M. J. (2017, December). Data-driven decision making. In 2017 international conference on Infocom technologies and unmanned systems (trends and future directions)(ICTUS) (pp. 50-56). IEEE.

[9]    Tripathi, V., Chattopadhyaya, S., Mukhopadhyay, A. K., Saraswat, S., Sharma, S., Li, C., & Rajkumar, S. (2022). Development of a data-driven decision-making system using lean and smart manufacturing concept in industry 4.0: A case study. Mathematical Problems in Engineering, 2022.

[10] Polenghi, A., Roda, I., Macchi, M., & Pozzetti, A. (2023). A methodology to boost data-driven decision-making process for a modern maintenance practice. Production Planning & Control, 34(14), 1333-1349.

[11] Hannila, H., Kuula, S., Harkonen, J., & Haapasalo, H. (2022). Digitalisation of a company decision-making system: a concept for data-driven and fact-based product portfolio management. Journal of Decision Systems, 31(3), 258-279.

[12] Bousdekis, A., Lepenioti, K., Apostolou, D., & Mentzas, G. (2021). A review of data-driven decision-making methods for industry 4.0 maintenance applications. Electronics, 10(7), 828.

[13] Hamoud, A. K., Marwah, K. H., Alhilfi, Z., & Sabr, R. H. (2021). Implementing data-driven decision support system based on independent educational data mart. International Journal of Electrical and Computer Engineering, 11(6), 5301.

[14] Clark, A., Zhuravleva, N. A., Siekelova, A., & Michalikova, K. F. (2020). Industrial artificial intelligence, business process optimization, and big data-driven decision-making processes in cyber-physical system-based smart factories. Journal of Self-Governance and Management Economics, 8(2), 28-34.

[15] Troisi, O., Maione, G., Grimaldi, M., & Loia, F. (2020). Growth hacking: Insights on data-driven decision-making from three firms. Industrial Marketing Management, 90, 538-557.

[16] Power, D. J. (2002). Decision support systems: concepts and resources for managers. Quorum Books.

[17] Kratsch, W., Manderscheid, J., Reißner, D., & Röglinger, M. (2017). Data-driven process prioritization in process networks. Decision Support Systems, 100, 27-40.

[18] Zhu, Y. (2018). A data driven educational decision support system. International Journal of Emerging Technologies in Learning (Online), 13(11), 4.

[19] Burstein, F., W Holsapple, C., & Power, D. J. (2008). Decision support systems: a historical overview. Handbook on decision support systems 1: Basic themes, 121-140.

[20] Wu, L., Li, Z., & AbouRizk, S. (2022). Automating Common Data Integration for Improved Data-Driven Decision-Support System in Industrial Construction. Journal of Computing in Civil Engineering, 36(2), 04021037.

Cite this Article as :
Style #
MLA Betul Aktas. "Data-Driven Decision Support Systems for Business Process Improvement." American Journal of Business and Operations Research, Vol. 11, No. 1, 2024 ,PP. 79-88 (Doi   :  https://doi.org/10.54216/AJBOR.110109)
APA Betul Aktas. (2024). Data-Driven Decision Support Systems for Business Process Improvement. Journal of American Journal of Business and Operations Research, 11 ( 1 ), 79-88 (Doi   :  https://doi.org/10.54216/AJBOR.110109)
Chicago Betul Aktas. "Data-Driven Decision Support Systems for Business Process Improvement." Journal of American Journal of Business and Operations Research, 11 no. 1 (2024): 79-88 (Doi   :  https://doi.org/10.54216/AJBOR.110109)
Harvard Betul Aktas. (2024). Data-Driven Decision Support Systems for Business Process Improvement. Journal of American Journal of Business and Operations Research, 11 ( 1 ), 79-88 (Doi   :  https://doi.org/10.54216/AJBOR.110109)
Vancouver Betul Aktas. Data-Driven Decision Support Systems for Business Process Improvement. Journal of American Journal of Business and Operations Research, (2024); 11 ( 1 ): 79-88 (Doi   :  https://doi.org/10.54216/AJBOR.110109)
IEEE Betul Aktas, Data-Driven Decision Support Systems for Business Process Improvement, Journal of American Journal of Business and Operations Research, Vol. 11 , No. 1 , (2024) : 79-88 (Doi   :  https://doi.org/10.54216/AJBOR.110109)
↑