Volume 14 , Issue 1 , PP: 245-258, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Quintana Churches Janneth Ximena 1 * , Machado Maliza Messiah Elias 2 , Stefany Lizbeth Ocana Lliguin 3 , Yusupov Sherzod Abdusalamovich 4
Doi: https://doi.org/10.54216/JCIM.140117
The first aim of this paper is to solve the problem of protocol optimization by the means of data integration through DEMATEL (Decision Evaluation and Laboratory Testing Method). The research addresses one key question: how can complexities management protocols be extended in relations with systems where interactions as well as feedback of multiple factors make the process full of uncertainties and hard to analyse? In the present setting, where there is transformation of information systems and critical processes are interwoven, there is a need for proper design of viable protocols to avert redundancy and improve effectiveness of operation. This appraisal is especially important considering the challenge of handling massive data volumes and risk management decision making in complex scenarios. Using DEMATEL pens out a systematic procedure in this research to disentangle the complexity of the interrelations of the variables and accomplish the task of identifying and ordering the key elements affecting protocol performance. The results also show that the methodology enables one to have a good perspective of several factors and the procedures followed in establishing the protocols also enhance the concerned decision making. The main contribution of the study lies in providing a robust and adaptable tool that can be used to optimize protocols in various areas, from logistics to network management, offering a theoretical and practical framework of great value for the advancement of research and practice in complex systems management.
Data integration , DEMATEL , Protocol optimization , Complex systems , Interdependency management , Decision making , Operational efficiency , Causal relationships , Variable visualization , Performance improvement
[1] Jaramillo, MN, Chuga, ZN, Hernández, CP, & Lits, RT (2022). Multicriteria analysis in the health field: selection of the most appropriate triage system for emergency care units in Ecuador. Rev Investig Opera , 43 (3), 316-324
[2] Lenzerini, M. (2002, June). Data integration: A theoretical perspective. In Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (pp. 233-246).
[3] Altamirano, O., Hernández, R., Espinoza, L. & Ibrahim, M. (2023). Selection of treatment options for the management of medical waste under neutrosophic scenarios. Journal International Neutral Optics Sciences. Volume 21(1), PP: 141-152.
[4] Alfonso, I., Guida, G., & Morocho, F.B. (2023). Supplier selection for healthcare supply chains based on the neutrosophic multicriteria decision-making method. International Journal of neutrosophic science . Vol. 21(2). Pages: 98-106.
[5] Naranjo Luzuriaga, E., Pérez Mayorga, B., Paredes López, J., & Salame Ortiz, M. (2022). Analysis of gender equality in education using mental maps and the Mann-Whitney u test. OPERATIONAL RESEARCH JOURNAL, 43(3), 400-408.
[6] Li, C.W. and Tzeng, G.H. (2009). Identifying a threshold value for the DEMATEL method using the maximum mean deentropy algorithm to find critical services provided by a semiconductor intellectual property trading center. Systems experts with applications, 36 (6), 9891–9898.
[7] Vujanović , D., Momčilović , V., Bojović , N. and Papić , V. (2012). Evaluation of vehicle fleet maintenance management indicators by applying DEMATEL and ANP. Systems experts with applications, 39 (12), 10552–10563.
[8] Si, S., You, X., Liu, H., & Zhang, P. (2018). DEMATEL technique: a systematic review of the state-of-the-art literature on methodologies and applications. Problems mathematicians in engineering, 2018 (3696457), 1 –33. [9] Saaty, T. L. (2004). Network analytic process foundations: dependency and feedback in single - network decision making. Journal of Systems Science and Systems Engineering, 13(1) , 129-157.
[10] Wu, WW (2008). Choosing knowledge management strategies using a combined ANP and DEMATEL approach. Expert Systems with Applications, 35 (3), 828–835.
[11] Costa, F., Denis Granja, A., Fregola, A., Picchi, F., & Portioli Staudacher , A. (2019). Understanding the relative importance of barriers to improving customer-supplier relationships within construction supply chains using the DEMATEL technique. Journal of Management in Engineering, 35 (3), 1 –13.
[12] Fang, H., Wang, B., & Song, W. (2020). Analysis of the interrelationships among barriers to green procurement in the photovoltaic industry: An integrated method. Journal of Cleaner Production, 249 , 119408.
[13] Bostancı , B. & Erdem , N. (2020). Investigating citizens’ satisfaction with municipal services using fuzzy models. Socio-Economic Planning Sciences, 69 (January 2019), 100754.
[14] Fernández, JJ (2012). Historical background of the protocol and its influence throughout history in the States, in society and in politics in Spain and Europe. Yearbook Legal and economic Escurialense , (45), 737-754.
[15] Singh, V., Rani, A., & Goyal, S. (2020). An improved hyper smoothing function based edge detection algorithm for noisy images. Journal of Intelligent & Fuzzy Systems, 38(5), 6325-6335.
[16] SENECYT. (2017). Protocol for prevention and action in cases of harassment, discrimination and violence based on gender and sexual orientation in higher education institutions. Quito: SENECYT.
[17] Markin, M. V. (2019). On the Gevrey ultradifferentiability of weak solutions of an abstract evolution equation with a scalar type spectral operator of orders less than one. Open Mathematics, 17(1), 1-14.
[18] Mohamed, Z., M. Ismail, M. and Abd El- Gawad, A. (2023) “Sustainable supplier selection using the neutrosophic multi-criteria decision-making methodology”, Sustainable Machine Intelligence Journal, 3, pp. (2):1–9. Doi: 10.61185/ SMIJ.2023.33102.
[19] Catalano, C., Paiano, L., Calabrese, F., Cataldo, M., Mancarella, L., & Tommasi, F. (2022). Anomaly detection in smart agriculture systems. Computers in Industry, 143, 103750.
[20] Moore, D., & Hurwitz, D. S. (2013). Fuzzy logic for improved dilemma zone identification: driving simulator study. Transportation research record, 2384(1), 25-34.
[21] Hurwitz, D. S., Wang, H., Knodler Jr, M. A., Ni, D., & Moore, D. (2012). Fuzzy sets to describe driver behavior in the dilemma zone of high-speed signalized intersections. Transportation research part F: traffic psychology and behaviour, 15(2), 132-143.
[22] Estupiñan , J. Leyva, M. (2022). Neutrosophic Multicriteria Methods for the Selection of Sustainable Alternative Materials in Concrete Design. American Journal of Business and Operations Research, 6(2), 28-38. DOI: https://doi.org/10.54216/AJBOR.060203
[23] Izquierdo, L. R., Olaru, D., Izquierdo, S. S., Purchase, S., & Soutar, G. N. (2015). Fuzzy logic for social simulation using NetLogo. Journal of Artificial Societies and Social Simulation, 18(4), 1
[24] Badjajian, N. Leyva, M. Hernández, B. (2024). On The Classification of 3-Cyclic/4-Cyclic Refined Neutrosophic Real and Rational Von Shtawzen's Group. International Journal of Neutrosophic Science, (), 26-31. DOI: https://doi.org/10.54216/IJNS.230203
[25] Botelho, C., Santos, H., Lucca, G., Cruz, A., Yamin, A. C., & Reiser, R. H. S. (2024, August). A Novel Quantum Fuzzy Approach to Interpret Dilemmas of Game Theory. In 2024 L Latin American Computer Conference (CLEI) (pp. 1-9). IEEE.