CAUSAL FACTORS IN RFID TECHNOLOGY UTILIZATION INFLUENCING BUSINESS SUPPLY CHAIN MANAGEMENT EFFICIENCY THROUGH LOGISTICS MANAGEMENT PROCESS A CASE STUDY OF FROZEN FOOD INDUSTRY IN THAILAND
DOI:
https://doi.org/10.60101/rmuttgber.2024.277118Keywords:
RFID technology, Logistics Management, Supply chain Management PerformanceAbstract
The objective of this research was to study the impact on supply chain efficiency. RFID technology utilization was an independent variable. Logistics management was an intermediary variable, while supply chain management efficiency was the dependent variable. Samples consisted of 315 medium- and large-sized IT executives or professionals in the frozen food industry selected by objective stratified sampling. Data were analyzed using structural equation modeling (SEM), which applied model structure in hypothetical models testing. Results indicated that the model was proportional where all the regression assumptions were accepted with p value < 0.05. The results of the consistency and harmony checked were consistent with the empirical data and the subcomponents of the structural model, with the value /df. = 2.516, GFI = 0.942, AGFI = 0.899, RMR = 0.60, RMSEA = 0.69, NFI = 0.975, CFI = 0.984 (p-value < 0.01). It was found that RFID technology utilization had no direct impact on the efficiency of supply chain however, indirect effects were also shown in logistics management. It was stated that RFID technology should be utilized in the organizations with proper logistics management.
References
Akram, H. W., Akhtar, S., Ahmad, A., Anwar, I., & Sulaiman, M. A. B. A. (2023). Developing a conceptual framework model for effective perishable food cold-supply-chain management based on structured literature review. Sustainability, 15(6), 4907. https://doi.org/10.3390/su15064907
Angeles, R. (2005). RFID technologies: Supply-chain applications and implementation issues. Information Systems Management, 22(1), 51-65.
Bandyopadhyay, S. (2023). Decision support system: Tools and techniques. CRC Press.
Botilias, G.-P., Margariti, S. V., Besarat, J., Salmas, D., Pachoulas, G., Stylios, C., & Skalkos, D. (2023). Designing and developing a meat traceability system: A case study for the greek meat industry. Sustainability, 15(16). https://doi.org/10.3390/su151612162
Cantini, A., Peron, M., De Carlo, F., & Sgarbossa, F. (2024). A decision support system for configuring spare parts supply chains considering different manufacturing technologies. International Journal of Production Research, 62(8), 3023-3043. https://doi.org/10.1080/00207543.2022.2041757
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. https://doi.org/10.1007/BF02310555
Delen, D., Hardgrave, B. C., & Sharda, R. (2007). RFID for better supply-chain management through enhanced information visibility. Production and Operations Management, 16(5), 613-624. https://doi.org/10.1111/j.1937-5956.2007.tb00284.x
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
Haddara, M., & Elragal, A. (2015). The readiness of ERP systems for the factory of the future. Procedia Computer Science, 64, 721-728. https://doi.org/10.1016/j.procs.2015.08.598
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of The Academy of Marketing Science, 40(3), 414-433. http://doi.org/10.1007/s11747-011- 0261-6
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer Nature.
Hugos, M. (2024). Essentials of supply chain management. John Wiley & Sons. https://doi.org/10.1002/9781118386408.ch1
Hunt, V. D., Puglia, A., & Puglia, M. (2007). RFID: A guide to radio frequency identification. John Wiley & Sons.
Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396-403. http://doi.org/10.9734/BJAST/2015/14975
Judijanto, L., Asniar, N., Kushariyadi, K., Utami, E. Y., & Telaumbanua, E. (2024). Application of integrated logistics networks in improving the efficiency of distribution and delivery of goods in Indonesia a literature review. Sciences Du Nord Economics and Business, 1(01), 01-10.
Liu, F., Shafique, M., & Luo, X. (2023). Literature review on life cycle assessment of transportation alternative fuels. Environmental Technology & Innovation, 32. https://doi.org/10.1016/j.eti.2023.103343
Melski, A., Mueller, J., Zeier, A., & Schumann, M. (2008). Assessing the effects of enhanced supply chain visibility through RFID.
In Proceedings of the Fourteenth Americas Conference on Information Systems (pp. 51). AMCIS. Toronto, ON, Canada. August 14–17, 2008.
Min, W., Liu, J., & Zhang, S. (2016). Network-regularized sparse logistic regression models for clinical risk prediction and biomarker discovery. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(3), 944-953. https://doi.org/10.1109/tcbb.2016.2640303
Regattieri, A., Gamberi, M., & Manzini, R. (2007). Traceability of food products: General framework and experimental evidence. Journal of Food Engineering, 81(2), 347-356. https://doi.org/10.1016/j.jfoodeng.2006.10.032
Sapbamrer, R., Kitro, A., Panumasvivat, J., & Assavanopakun, P. (2023). Important role of the government in reducing pesticide use and risk sustainably in Thailand: Current situation and recommendations. Frontiers in Public Health, 11. https://doi.org/10.3389/fpubh.2023.1141142
Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair Jr, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM):
A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105-115. https://doi.org/10.1016/j.jfbs.2014.01.002
Smith, A. J. (2020). Framework for establishing asset visibility and traceability of medical devices. Massachusetts Institute of Technology.
Talari, G., Cummins, E., McNamara, C., & O'Brien, J. (2022). State of the art review of Big Data and web-based Decision Support Systems (DSS) for food safety risk assessment with respect to climate change. Trends in Food Science & Technology, 126, 192-204.
Tikwayo, L. N., & Mathaba, T. N. (2023). Applications of industry 4.0 technologies in warehouse management: A systematic literature review. Logistics, 7(2), 24. https://doi.org/10.3390/logistics7020024
Voipio, V., Elfvengren, K., & Korpela, J. (2020). In the bowling alley: Acceptance of an intelligent packaging concept in European markets. International Journal of Value Chain Management, 11(2), 180-197.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Jakraphun Srisawat
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
บทความที่ได้รับการตีพิมพ์เป็นลิขสิทธิ์ของผู้นิพนธ์
ข้อความที่ปรากฏในบทความแต่ละเรื่องในวารสารวิชาการเล่มนี้เป็นความคิดเห็นส่วนตัวของผู้เขียนแต่ละท่านไม่เกี่ยวข้องกับมหาวิทยาลัยเทคโนโลยีราชมงคลธัญบุรี และคณาจารย์ท่านอื่นๆในมหาวิทยาลัยฯ แต่อย่างใด ความรับผิดชอบองค์ประกอบทั้งหมดของบทความแต่ละเรื่องเป็นของผู้เขียนแต่ละท่าน หากมีความผิดพลาดใดๆ ผู้เขียนแต่ละท่านจะรับผิดชอบบทความของตนเองแต่ผู้เดียว
