Technological Factors and Supply Chain Transparency: Role of Decision Support System

Muhammad Awais Bhatti; Nasrulla Tilabov

doi:10.31181/dmame8120251456

Authors

Muhammad Awais Bhatti College of Business, King Faisal University, Al-hasa, Saudi Arabia. https://orcid.org/0000-0001-9555-1902
Nasrulla Tilabov Department of Finance and Financial Technologies, Tashkent State University of Economics, Uzbekistan. https://orcid.org/0000-0001-9555-1902

DOI:

https://doi.org/10.31181/dmame8120251456

Keywords:

Supply chain transparency, Digital technologies, Decision support system, SMEs.

Abstract

The study objective was to formulate the impact of digital technologies, namely RFID, IOT, blockchain technology, artificial intelligence, and cybersecurity on the supply chain transparency of manufacturing SMEs. The study also tested the moderating effect of decision support system. For this purpose, quantitative cross-sectional data were collected from 305 manufacturing SMEs using a convenient sampling technique. SPSS was used for both of demographic and regression analysis. Multiple regression analysis results show that all digital technologies positively and significantly affect supply chain transparency. The moderating effect also shows that the decision support system positively strengthens the relationship between digital technologies and supply chain transparency. The study with findings contributes to the literature by confirming that digital technologies significantly enhance supply chain transparency in manufacturing SMEs. It further contributes by highlighting the moderating role of decision support systems, which strengthens the impact of these technologies. These contributions guide SME managers and policymakers to invest in integrated digital solutions for improving supply chain visibility and performance. Limitations and future directions were also discussed at the end.

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References

[1] Aarland, M. (2025). Cybersecurity in digital supply chains in the procurement process: introducing the digital supply chain management framework. Information & Computer Security, 33(1), 5-24. https://doi.org/10.1108/ICS-10-2023-0198

[2] Abdunabiev, B. (2024). Implementation of RFID technology for warehouse management in SMEs. http://webthesis.biblio.polito.it/id/eprint/33359

[3] Adithya, K., & Girimurugan, R. (2023). Benefits of IoT in automated systems. Integration of Mechanical and Manufacturing Engineering with IoT: A Digital Transformation, 235-270. https://doi.org/10.1002/9781119865391.ch9

[4] Afrin, N., & Pathak, A. (2023). Blockchain-Powered Security and Transparency in Supply Chain: Exploring Traceability and Authenticity through Smart Contracts. International Journal of Computer Applications, 85, 5-15. http://dx.doi.org/10.5120/ijca2023923318

[5] Aggarwal, S., & Kumar, N. (2021). Basics of blockchain. In Advances in computers (Vol. 121, pp. 129-146). Elsevier. https://doi.org/10.1016/bs.adcom.2020.08.007

[6] Ait Mouha, R. A. R. (2021). Internet of things (IoT). Journal of Data Analysis and Information Processing, 9(02), 77. http://doi.org/10.4236/jdaip.2021.92006

[7] Akano, O. A., Hanson, E., Nwakile, C., & Esiri, A. E. (2024). Designing real-time safety monitoring dashboards for industrial operations: A data-driven approach. Global Journal of Research in Science and Technology, 2(02), 001-009. https://doi.org/10.58175/gjrst.2024.2.2.0070

[8] Akossou, A., & Palm, R. (2013). Impact of data structure on the estimators R-square and adjusted R-square in linear regression. Int. J. Math. Comput, 20(3), 84-93. https://www.researchgate.net/publication/289526309

[9] Al Maruf, A. (2025). A systematic review of ERP-integrated decision support systems for financial and operational optimization in global retails business. American Journal of Interdisciplinary Studies, 6(1), 236-262. https://doi.org/10.63125/qgbrmf24

[10] Ala'a, M., Ramayah, T., & Al-Sharafi, M. A. (2024). Exploring the impact of cybersecurity on using electronic health records and their performance among healthcare professionals: A multi-analytical SEM-ANN approach. Technology in Society, 77, 102592. https://doi.org/10.1016/j.techsoc.2024.102592

[11] Alam, S., Shuaib, M., Khan, W. Z., Garg, S., Kaddoum, G., Hossain, M. S., & Zikria, Y. B. (2021). Blockchain-based initiatives: current state and challenges. Computer Networks, 198, 108395. https://doi.org/10.1016/j.comnet.2021.108395

[12] Aljazzazen, S., & Schmuck, R. (2021). The impact of knowledge management practice on lean six sigma implementation: The moderating role of human capital in health service organisations. International Journal of Operations and Quantitative Management, 27(3), 267-285. http://doi.org/10.46970/2021.27.3.5

[13] AllahRakha, N. (2024). Cybersecurity Regulations for Protection and Safeguarding Digital Assets (Data) in Today’s Worlds. Lex Scientia Law Review, 8(1). https://doi.org/10.15294/lslr.v8i1.2081

[14] Alqasa, K. M. A., & Sundram, V. P. K. (2024). Decision Support System Success and Operations Sustainability: Moderating Role of Supply Chain Resilience. Operational Research in Engineering Sciences: Theory and Applications, 7(1). http://oresta.org/menu-script/index.php/oresta/article/view/704

[15] Alzarooni, A. M., Khan, S. A., Gunasekaran, A., & Mubarik, M. S. (2022). Enablers for digital supply chain transformation in the service industry. Annals of Operations Research, 1-25. https://doi.org/10.1007/s10479-022-05047-x

[16] Amini Khiabani, G., & Mahmoudian, F. (2020). How Financial Performance Can Be Improved By Decision Support Systems; The Role Of Knowledge Management Capacity Academy of Accounting and Financial Studies Journal 4(1), 62-84. https://www.abacademies.org/articles/How-financial-performance-can-be-improved-by-decision-support-systems-the-role-of-knowledge-management-capacity-1528-2635-24-5-509.pdf

[17] Baah, C., Opoku Agyeman, D., Acquah, I. S. K., Agyabeng-Mensah, Y., Afum, E., Issau, K., Ofori, D., & Faibil, D. (2022). Effect of information sharing in supply chains: understanding the roles of supply chain visibility, agility, collaboration on supply chain performance. Benchmarking: An International Journal, 29(2), 434-455. https://doi.org/10.1108/BIJ-08-2020-0453

[18] Bello, O. A., & Olufemi, K. (2024). Artificial intelligence in fraud prevention: Exploring techniques and applications challenges and opportunities. Computer science & IT research journal, 5(6), 1505-1520. http://doi.org/10.51594/csitrj.v5i6.1252

[19] Benjamin, L. B., Adegbola, A. E., Amajuoyi, P., Adegbola, M. D., & Adeusi, K. B. (2024). Digital transformation in SMEs: Identifying cybersecurity risks and developing effective mitigation strategies. Global Journal of Engineering and Technology Advances, 19(2), 134-153. https://doi.org/10.30574/gjeta.2024.19.2.0084

[20] Bernard, H. R. (2017). Research methods in anthropology: Qualitative and quantitative approaches. Rowman & Littlefield. https://cir.nii.ac.jp/crid/1130282270705380352

[21] Bhutta, M. N. M., & Ahmad, M. (2021). Secure identification, traceability and real-time tracking of agricultural food supply during transportation using internet of things. IEEE Access, 9, 65660-65675. https://doi.org/10.1109/ACCESS.2021.3076373

[22] Brown, W., Wilson, G., & Johnson, O. (2024). Understanding the Adoption of Advanced Analytics in Supply Chain Decision-Making. http://doi.org/10.20944/preprints202408.0235.v1

[23] Cerić, A. (2021). Reducing information asymmetry and building trust in projects using blockchain technology. Gradevinar, 73, 967-978. https://doi.org/10.14256/JCE.3310.2021

[24] Cerullo, G., Guizzi, G., Massei, C., & Sgaglione, L. (2016). Efficient supply chain management: Traceability and transparency. 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 150905698X. https://doi.org/10.1109/SITIS.2016.124

[25] Cheah, J.-H., Sarstedt, M., Ringle, C. M., Ramayah, T., & Ting, H. (2018). Convergent validity assessment of formatively measured constructs in PLS-SEM: On using single-item versus multi-item measures in redundancy analyses. International journal of contemporary hospitality management, 30(11), 3192-3210. https://doi.org/10.1108/IJCHM-10-2017-0649

[26] Chen, J.-Y. (2022). Responsible sourcing and supply chain traceability. International Journal of Production Economics, 248, 108462. https://doi.org/10.1016/j.ijpe.2022.108462

[27] Costa, F., Genovesi, S., Borgese, M., Michel, A., Dicandia, F. A., & Manara, G. (2021). A review of RFID sensors, the new frontier of internet of things. Sensors, 21(9), 3138. https://doi.org/10.3390/s21093138

[28] Creswell, J. W. (2014). Research design: qualitative, quantitative, and mixed methods approaches. https://doi.org/10.1453/jsas.v4i2.1313

[29] Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications. https://doi.org/10.1453/jsas.v4i2.1313

[30] Creswell, J. W., Klassen, A. C., Plano Clark, V. L., & Smith, K. C. (2011). Best practices for mixed methods research in the health sciences. Bethesda (Maryland): National Institutes of Health, 2013, 541-545. https://www.csun.edu/sites/default/files/best_prac_mixed_methods.pdf

[31] Dawson, J. (2024). Building a Cybersecurity Compliance Index of Capabilities to Explore Strategies and Trends That Enhance Decision Making in Organizations The Claremont Graduate University]. https://www.proquest.com/openview/4b2e8aa325e3e879dc6866e3f516ffb0/1?pq-origsite=gscholar&cbl=18750&diss=y

[32] Dolgui, A., & Ivanov, D. (2022). 5G in digital supply chain and operations management: fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. International Journal of Production Research, 60(2), 442-451. https://doi.org/10.1080/00207543.2021.2002969

[33] Etemadi, N., Borbon-Galvez, Y., Strozzi, F., & Etemadi, T. (2021). Supply chain disruption risk management with blockchain: A dynamic literature review. Information, 12(2), 70. https://doi.org/10.3390/info12020070

[34] Gade, K. R. (2021). Data-driven decision making in a complex world. Journal of Computational Innovation, 1(1). https://researchworkx.com/index.php/jci/article/view/2

[35] Gajić, T., Petrović, M. D., Pešić, A. M., Conić, M., & Gligorijević, N. (2024). Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability. Sustainability, 16(17), 7279. https://doi.org/10.3390/su16177279

[36] Garcia‐Torres, S., Rey‐Garcia, M., & Sáenz, J. (2024). Enhancing sustainable supply chains through traceability, transparency and stakeholder collaboration: A quantitative analysis. Business Strategy and the Environment, 33(7), 7607-7629. https://doi.org/10.1002/bse.3884

[37] Hadi, D. K., Song, Z., Rahmadya, B., Kozume, S., Sumiya, T., Sun, R., Takeda, S., & Wang, X. (2024). Indoor Area Estimation System Using RSSI-Measuring Handheld Reader Utilizing Directional Reference RFID Tags and Machine Learning. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3486792

[38] Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624

[39] Hammi, B., Zeadally, S., & Nebhen, J. (2023). Security threats, countermeasures, and challenges of digital supply chains. ACM Computing Surveys, 55(14s), 1-40. https://doi.org/10.1145/3588999

[40] Hasan, I., Mohamed, Z., Habib, M. M., Hanafi, H. B. M., & Bt, H. (2024). Impact Of Internet Of Things (Iot) On Enhancing Transparency And Efficiency In Bangladesh's Agri-Food Supply Chain. Environmental & Social Management Journal/Revista de Gestão Social e Ambiental, 18(9). https://doi.org/10.24857/rgsa.v18n9-059

[41] Hellani, H., Sliman, L., Samhat, A. E., & Exposito, E. (2021). On blockchain integration with supply chain: Overview on data transparency. Logistics, 5(3), 46. https://doi.org/10.3390/logistics5030046

[42] Holloway, S. (2025). Assessing the Impact of Supply Chain Disruption Management on Brand Resilience and Consumer Perception. Available at SSRN 5123727. https://dx.doi.org/10.2139/ssrn.5123727

[43] Hossain, M. I., Steigner, T., Hussain, M. I., & Akther, A. (2024). Enhancing data integrity and traceability in industry cyber physical systems (ICPS) through Blockchain technology: A comprehensive approach. arXiv preprint arXiv:2405.04837. https://doi.org/10.48550/arXiv.2405.04837

[44] Jean, G. (2024). Supply Chain Cybersecurity and Data Privacy. https://www.researchgate.net/publication/384371265

[45] John, A. O., Adejumo, E. K., & Larbi, S. Y. (2025). AI-Driven Supply Chain Risk Management in the Manufacturing Sector: Tackling Data Bias, Ensuring Algorithmic Transparency, and Enhancing Human-AI Collaboration. Iconic Research and Engineering Journals (IRE Journal), 8(11), 77-94. https://www.researchgate.net/publication/392496390

[46] Jones, J. (2025). AI-Driven Demand Forecasting in Supply Chains: A Qualitative Analysis of Adoption and Impact. http://doi.org/10.20944/preprints202501.1349.v1

[47] Kademeteme, E., & Bvuma, S. (2023). Using blockchain technology to improve the integrity and transparency of procurement processes between SMMEs and government: A systematic literature review. The Journal of The British Blockchain Association. https://doi.org/10.31585/jbba-7-1-(1)2024

[48] Kalusivalingam, A. K., Sharma, A., Patel, N., & Singh, V. (2022). Enhancing Supply Chain Resilience through AI: Leveraging Deep Reinforcement Learning and Predictive Analytics. International Journal of AI and ML, 3(9). https://www.cognitivecomputingjournal.com/index.php/IJAIML-V1/article/view/68

[49] Khan, R. S., Sirazy, M. R. M., Das, R., & Rahman, S. (2022). An ai and ml-enabled framework for proactive risk mitigation and resilience optimization in global supply chains during national emergencies. Sage Science Review of Applied Machine Learning, 5(2), 127-144. https://www.researchgate.net/publication/387584681

[50] Kılıç, S. (2016). Cronbach’s alpha reliability coefficient. Psychiatry and Behavioral Sciences, 6(1), 47. http://doi.org/10.5455/jmood.20160307122823

[51] Kirtane, A., Tiwari, A., Lalwani, Y., Sood, J., Pasha, A., & Hisham, M. (2024). Supply Chain Visualization and Optimization using Machine Learning. 2024 IEEE 9th International Conference for Convergence in Technology (I2CT), 9798350394474. https://doi.org/10.1109/I2CT61223.2024.10544305

[52] Kumar, N. (2022). IoT-Enabled Real-Time Data Integration in ERP Systems. https://doi.org/10.32628/IJSRSET2215479

[53] Kwon, O., Yoo, K., & Suh, E. (2005). UbiDSS: a proactive intelligent decision support system as an expert system deploying ubiquitous computing technologies. Expert systems with applications, 28(1), 149-161. https://doi.org/10.1016/j.eswa.2004.08.007

[54] Layode, O., Naiho, H. N. N., Labake, T. T., Adeleke, G. S., Udeh, E. O., & Johnson, E. (2024). Addressing cybersecurity challenges in sustainable supply chain management: A review of current practices and future directions. International Journal of Management & Entrepreneurship Research, 6(6), 1954-1981. http://doi.org/10.51594/ijmer.v6i6.1208

[55] Lee, I., & Mangalaraj, G. (2022). Big data analytics in supply chain management: A systematic literature review and research directions. Big data and cognitive computing, 6(1), 17. https://doi.org/10.3390/bdcc6010017

[56] Lele, C. (2022). Internet of Things (IoT) A Quick Start Guide: A to Z of IoT Essentials (English Edition). BPB Publications. https://www.amazon.com/Internet-Things-Quick-Start-Guide/dp/9389845866

[57] Lin, I.-C., Kuo, Y.-H., Chang, C.-C., Liu, J.-C., & Chang, C.-C. (2024). Symmetry in blockchain-powered secure decentralized data storage: Mitigating risks and ensuring confidentiality. Symmetry, 16(2), 147. https://doi.org/10.3390/sym16020147

[58] Massaro, A. (2022). Multi-level decision support system in production and safety management. Knowledge, 2(4), 682-701. https://doi.org/10.3390/knowledge2040039

[59] Modgil, S., Singh, R. K., & Hannibal, C. (2022). Artificial intelligence for supply chain resilience: learning from Covid-19. The International Journal of Logistics Management, 33(4), 1246-1268. https://doi.org/10.1108/IJLM-02-2021-0094

[60] Mssassi, S., & El Kalam, A. A. (2023). Leveraging Blockchain for Enhanced Traceability and Transparency in Sustainable Development. International Conference on Advanced Intelligent Systems for Sustainable Development, 162-177. https://doi.org/10.1007/978-3-031-54318-0_14

[61] Nikolaev, D. (2024). Systematic review: opportunities and barriers to online marketing caused by the development of the Internet of Things. Verslas: teorija ir praktika, 25(1), 36-50. https://www.ceeol.com/search/article-detail?id=1253303

[62] Nweje, U., & Taiwo, M. (2025). Leveraging Artificial Intelligence for predictive supply chain management, focus on how AI-driven tools are revolutionizing demand forecasting and inventory optimization. International Journal of Science and Research Archive, 14(1), 230-250. https://doi.org/10.30574/ijsra.2025.14.1.0027

[63] Nyimbili, F., & Nyimbili, L. (2024). Types of purposive sampling techniques with their examples and application in qualitative research studies. British Journal of Multidisciplinary and Advanced Studies, 5(1), 90-99. https://doi.org/10.37745/bjmas.2022.0419

[64] Odimarha, A. C., Ayodeji, S. A., & Abaku, E. A. (2024). Securing the digital supply chain: Cybersecurity best practices for logistics and shipping companies,'. World Journal of Advanced Science and Technology, 5(1), 026-030. https://doi.org/10.53346/wjast.2024.5.1.0030

[65] Ogunyankinnu, T., Onotole, E. F., Osunkanmibi, A. A., Adeoye, Y., Aipoh, G., & Egbemhenghe, J. (2022). Blockchain and AI synergies for effective supply chain management. International Journal of Multidisciplinary Research and Growth Evaluation. https://doi.org/10.54660/.IJMRGE.2022.3.1-626-637

[66] Onu, P., Mbohwa, C., & Pradhan, A. (2024). Blockchain-Powered Traceability Solutions: Pioneering Transparency to Eradicate Counterfeit Products and Revolutionize Supply Chain Integrity. Procedia Computer Science, 232, 1420-1427. https://doi.org/10.1016/j.procs.2024.01.140

[67] Ospital, P., Masson, D., Beler, C., & Legardeur, J. (2023). Toward product transparency: communicating traceability information to consumers. International Journal of Fashion Design, Technology and Education, 16(2), 186-197. https://doi.org/10.1080/17543266.2022.2142677

[68] Owusu, J., Boateng, P. A., & Yeboah, N. (2024). Strategic Decision Support Systems for Enhancing Competitive Advantage in Small and Medium Enterprises. 2024 IEEE SmartBlock4Africa, 1-10. https://doi.org/10.1109/SmartBlock4Africa61928.2024.10779545

[69] Pajic, V., Andrejic, M., & Chatterjee, P. (2024). Enhancing cold chain logistics: A framework for advanced temperature monitoring in transportation and storage. Mechatron. Intell Transp. Syst, 3(1), 16-30. https://doi.org/10.56578/mits030102

[70] Pamisetty, V. (2022). AI-Powered Decision Support Systems for Enhancing Tax Compliance and Public Revenue Management. Available at SSRN 5281689. https://dx.doi.org/10.2139/ssrn.5281689

[71] Pandey, S., Singh, R. K., Gunasekaran, A., & Kaushik, A. (2020). Cyber security risks in globalized supply chains: conceptual framework. Journal of Global Operations and Strategic Sourcing, 13(1), 103-128. https://doi.org/10.1108/JGOSS-05-2019-0042

[72] Parmentola, A., Petrillo, A., Tutore, I., & De Felice, F. (2022). Is blockchain able to enhance environmental sustainability? A systematic review and research agenda from the perspective of Sustainable Development Goals (SDGs). Business Strategy and the Environment, 31(1), 194-217. https://doi.org/10.1002/bse.2882

[73] Pattanayak, S., Ramkumar, M., Goswami, M., & Rana, N. P. (2024). Blockchain technology and supply chain performance: The role of trust and relational capabilities. International Journal of Production Economics, 271, 109198. https://doi.org/10.1016/j.ijpe.2024.109198

[74] Paul, T., Islam, N., Mondal, S., & Rakshit, S. (2022). RFID-integrated blockchain-driven circular supply chain management: A system architecture for B2B tea industry. Industrial Marketing Management, 101, 238-257. https://doi.org/10.1016/j.indmarman.2021.12.003

[75] Rane, N., Choudhary, S., & Rane, J. (2024). Artificial intelligence for enhancing resilience. Journal of Applied Artificial Intelligence, 5(2), 1-33. https://doi.org/10.48185/jaai.v5i2.1053

[76] Reyes, P. M. (2023). Radio frequency identification (RFID) and supply chain management. In The Palgrave Handbook of Supply Chain Management (pp. 1-35). Springer. https://doi.org/10.1007/978-3-030-89822-9_109-1

[77] Sadeghi, K., Ojha, D., Kaur, P., Mahto, R. V., & Dhir, A. (2024). Explainable artificial intelligence and agile decision-making in supply chain cyber resilience. Decision Support Systems, 180, 114194. https://doi.org/10.1016/j.dss.2024.114194

[78] Saidu, Y., Shuhidan, S. M., Aliyu, D. A., Aziz, I. A., & Adamu, S. (2025). Convergence of Blockchain, IoT, and AI for Enhanced Traceability Systems: A Comprehensive Review. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3528035

[79] Sandul, M. (2023). Transformational factors in the development of global supply chains. International Economic Policy(38), 77-100. http://doi.org/10.33111/iep.eng.2023.38.04

[80] Shobhana, N. (2024). AI-powered supply chains towards greater efficiency. In Complex AI Dynamics and Interactions in Management (pp. 229-249). IGI Global. http://doi.org/10.4018/979-8-3693-0712-0.ch011

[81] Sobb, T., Turnbull, B., & Moustafa, N. (2020). Supply chain 4.0: A survey of cyber security challenges, solutions and future directions. Electronics, 9(11), 1864. https://doi.org/10.3390/electronics9111864

[82] Solanke, A. (2024). Blockchain Implementation for Enterprise Data Integrity: Distributed Ledger Strategies for Supply Chain Transparency and Trustworthy Data Verification. https://www.researchgate.net/publication/390212745

[83] Solfa, F. D. G. (2022). Impacts of cyber security and supply chain risk on digital operations: evidence from the pharmaceutical industry. International Journal of Technology Innovation and Management (IJTIM), 2(2), 18-32. https://doi.org/10.54489/ijtim.v2i2.98

[84] Soori, M., Jough, F. K. G., Dastres, R., & Arezoo, B. (2024). AI-based decision support systems in Industry 4.0, A review. Journal of Economy and Technology. https://doi.org/10.1016/j.ject.2024.08.005

[85] Staples, M., Chen, S., Falamaki, S., Ponomarev, A., Rimba, P., Tran, A., Weber, I., Xu, X., & Zhu, J. (2017). Risks and opportunities for systems using blockchain and smart contracts. Data61. CSIRO), Sydney. http://dx.doi.org/10.4225/08/596e5ab7917bc

[86] Suganthi, V., & Kalaiselvi, K. (2024). Decision Support System in Healthcare Monitoring. Artificial Intelligence‐Based System Models in Healthcare, 55-78. https://doi.org/10.1002/9781394242528.ch3

[87] Tahmasebi, M. (2024). Cyberattack Ramifications, The Hidden Cost of a Security Breach. Journal of Information Security, 15(2), 87-105. https://doi.org/10.4236/jis.2024.152007

[88] Talla, R. R. (2022). Integrating Blockchain and AI to Enhance Supply Chain Transparency in Energy Sectors. Asia Pacific Journal of Energy and Environment, 9(2), 109-118. https://hal.science/hal-04862355/

[89] Tan, W. C., & Sidhu, M. S. (2022). Review of RFID and IoT integration in supply chain management. Operations Research Perspectives, 9, 100229. https://doi.org/10.1016/j.orp.2022.100229

[90] Tiwari, S. (2021). Supply chain integration and Industry 4.0: a systematic literature review. Benchmarking: An International Journal, 28(3), 990-1030. https://doi.org/10.1108/BIJ-08-2020-0428

[91] Tongco, M. D. C. (2007). Purposive sampling as a tool for informant selection. http://hdl.handle.net/10125/227

[92] Udeh, E. O., Amajuoyi, P., Adeusi, K. B., & Scott, A. O. (2024). The role of IoT in boosting supply chain transparency and efficiency. Magna Scientia Adv. Res. Rev., 12(1), 178-197. https://doi.org/10.30574/msarr.2024.11.1.0081

[93] Unhelkar, B., Joshi, S., Sharma, M., Prakash, S., Mani, A. K., & Prasad, M. (2022). Enhancing supply chain performance using RFID technology and decision support systems in the industry 4.0–A systematic literature review. International Journal of Information Management Data Insights, 2(2), 100084. https://doi.org/10.1016/j.jjimei.2022.100084

[94] Van Hoang, T. (2024). Impact of integrated artificial intelligence and internet of things technologies on smart city transformation. Journal of Technical Education Science, 19(Special Issue 01), 64-73. https://doi.org/10.54644/jte.2024.1532

[95] Want, R. (2022). RFID explained: A primer on radio frequency identification technologies. Springer Nature. https://doi.org/10.1007/978-3-031-02474-0

[96] Wylde, V., Rawindaran, N., Lawrence, J., Balasubramanian, R., Prakash, E., Jayal, A., Khan, I., Hewage, C., & Platts, J. (2022). Cybersecurity, data privacy and blockchain: A review. SN computer science, 3(2), 127. https://doi.org/10.1007/s42979-022-01020-4

[97] Xu, P., Lee, J., Barth, J. R., & Richey, R. G. (2021). Blockchain as supply chain technology: considering transparency and security. International Journal of Physical Distribution & Logistics Management, 51(3), 305-324. https://doi.org/10.1108/IJPDLM-08-2019-0234

[98] Yang, M., Fu, M., & Zhang, Z. (2021). The adoption of digital technologies in supply chains: Drivers, process and impact. Technological Forecasting and Social Change, 169, 120795. https://doi.org/10.1016/j.techfore.2021.120795

[99] Zelbst, P. J., Green, K. W., Sower, V. E., & Bond, P. L. (2020). The impact of RFID, IIoT, and Blockchain technologies on supply chain transparency. Journal of Manufacturing Technology Management, 31(3), 441-457. https://doi.org/10.1108/JMTM-03-2019-0118

[100] Zhang, Y., Lin, Y., & Esfahbodi, A. (2025). Digital Transformations of Supply Chain Management via RFID Technology: A Systematic Literature Review. Journal of Digital Economy. https://doi.org/10.1016/j.jdec.2025.06.001