Abstract
The evaluation of online education quality in e-commerce logistics can provide theoretical guidance and practical support for improving education quality, promoting industry development, and enhancing talent quality. However, the establishment of traditional evaluation system structures is complex and subjective, which affects the quality and efficiency of e-commerce logistics online education. Therefore, a study on the quality evaluation of e-commerce logistics online education based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed. Firstly, determine the principles for establishing an online education quality evaluation system and construct an e-commerce logistics online education quality evaluation system. Secondly, the entropy weight TOPSIS method is used to quantify the difference between different e-commerce logistics online education quality data samples through the entropy weight amplitude, calculate the weight of e-commerce logistics online education quality evaluation indicators, determine the entropy weight vector of the evaluation indicators according to the weight of the evaluation indicators, calculate the distance from the evaluation object to the best solution and the worst solution, and rank them. When the distance between the object to be evaluated and the best solution is the smallest, it is the best, Thus, a quality evaluation model for e-commerce logistics online education is constructed. Finally, calculate the evaluation scores of various indicators and incorporate them into the evaluation model to achieve the evaluation of the quality of e-commerce logistics online education. The case analysis results show that the method in this paper can evaluate the quality of e-commerce logistics online education, obtain the high and low order of e-commerce logistics online education quality, and has good performance in the evaluation accuracy and time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Yuan, F., Nie, Y.: Online classroom teaching quality evaluation system based on facial feature recognition. Sci. Program. 2021(Pt.14), 7374846.1–7374846.10 (2021)
Wanpeng, L., Hongmei, M., Huaming, H.: Evaluate teaching performance by residuals of student achievement. J. East China Normal Univ. (Educ. Sci.) 39(7), 84–91 (2021)
Yuyang, L.: Design of university teaching quality evaluation model based on data mining algorithm. Mod. Tlectron. Technol. 43(17), 119–122 (2020)
Jiang, H.F., Ren, X.W., Mei, Z., et al.: MSaaS credibility evaluation based on entropy weight-grey hierarchy process. Comput. Simul. 40(01), 6–10 (2023)
Ji, S., Tsai, S.B.: A study on the quality evaluation of English teaching based on the fuzzy comprehensive evaluation of bat algorithm and big data analysis. Math. Probl. Eng. 2021(Pt.43) :4418399.1–4418399.12 (2021)
Li, Q., Perez, Z.: An intelligent evaluation model of bilingual teaching quality based on network resource sharing. Int. J. Cont. Eng. Educ. Life-Long Learn. 30(2), 148–160 (2020)
Li, X.: A new evaluation method for English MOOC teaching quality based on AHP. Int. J. Cont. Eng. Educ. Life-Long Learn. 32(2), 201–215 (2022)
Yang, Y.: Quality evaluation method of a mathematics teaching model reform based on an improved genetic algorithm. Sci. Program. 2021(Pt.6), 6395349.1–6395349.10 (2021)
Han, Z.: A fuzzy logic and multilevel analysis-based evaluation algorithm for digital teaching quality in colleges and universities. Sci. Program. 2021(Pt.11) - 7026531.1–7026531.7 (2021)
Li, H., Sun, S.: Research on evaluation model of oral English teaching quality based on cloud computing. Int. J. Cont. Eng. Educ. Life-Long Learn. 30(4), 363–380 (2020)
Wang, Y.: Comprehensive evaluation system of teaching quality based on big data architecture. Int. J. Cont. Eng. Educ. Life-Long Learn. 30(2), 176–189 (2020)
Acknowledgement
Guangdong Provincial Department of Education Higher Vocational Education Teaching Quality and Teaching Reform Project: Research on the Training Model of High Quality Applied E-commerce Logistics Talents under the Collaborative Training of Higher Vocational and Undergraduate Education (GDJG2021303).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Li, J. (2024). Research on Online Education Quality Evaluation of E-Commerce Logistics Based on Entropy Weight TOPSIS. In: Gui, G., Li, Y., Lin, Y. (eds) e-Learning, e-Education, and Online Training. eLEOT 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 546. Springer, Cham. https://doi.org/10.1007/978-3-031-51503-3_12
Download citation
DOI: https://doi.org/10.1007/978-3-031-51503-3_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-51502-6
Online ISBN: 978-3-031-51503-3
eBook Packages: Computer ScienceComputer Science (R0)