This work is licensed under a Creative Commons Attribution 4.0 International License.
Enhancing Human Resource Management Efficiency through Scalable Blockchain Networks with an Adaptive AI Approach
Corresponding Author(s) : Indira Puspa Gustiah
Startupreneur Business Digital (SABDA Journal),
Vol. 4 No. 2 (2025): Startupreneur Business Digital (SABDA)
Abstract
Blockchain technology has attracted considerable attention in recent years due to its decentralized architecture, transparency, and inherent security features. Despite these advantages, Blockchain networks continue to face persistent challenges related to scalability, efficiency, and performance, particularly as transaction volumes and user demands increase. This study introduces an adaptive Artificial Intelligence (AI) driven framework designed to enhance the scalability and efficiency of Blockchain networks. By integrating AI algorithms capable of real-time learning and predictive optimization, the proposed model dynamically manages critical network functions such as transaction scheduling, resource allocation, and congestion control. The framework leverages both historical data and real-time analytics to make informed adjustments, thereby reducing latency, improving throughput, and optimizing energy consumption within Blockchain systems. The urgency of this research lies in addressing the scalability bottleneck that continues to hinder widespread Blockchain adoption across sectors such as finance, supply chain, healthcare, and human resource management. The novelty of this work resides in the fusion of adaptive AI techniques with Blockchain infrastructures, a combination that has been relatively underexplored in current scholarship. By advancing beyond static optimization methods, this research provides a more resilient and intelligent approach to Blockchain performance enhancement. The findings are expected to contribute to both aca- demic discourse and practical applications by offering a scalable, AI-empowered framework that can be adapted across multiple domains. Ultimately, this study aims to broaden the real-world applicability of Blockchain technology by overcoming its most pressing limitations.
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References
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Y. Xu, Z. Bai, Z. Wang, X. Song, Y. Zhang, and Q. Zhang, “Research on business model innovation of smes in the industrial internet era: building theory from the case of paya,” Nankai Business Review International, vol. 16, no. 1, pp. 104–127, 2025.
C. Y. Pacubas, L. T. Lucero Jr, N. R. Umpar, K. L. Armas et al., “Enabling digital servitization in philip- pine manufacturing: A business model innovation framework for msmes in the industry 4.0 era,” Edel- weiss Applied Science and Technology, vol. 9, no. 5, pp. 457–465, 2025.
F. Wang, J. Gu, and A. Liu, “Leveraging structural it capabilities to promote novelty and efficiency in business model design: A knowledge-based view,” Information & Management, vol. 62, no. 2, p. 104090, 2025.
B. Prabawa, A. Z. Majid, B. Hugo, A. B. Nandya, S. E. Wicaksono, P. Aditia, and A. M. Prajana, “Busi- ness model innovation and brand strengthening at artarindo insurance. a case study of how design is applied at the strategic level,” KnE Social Sciences, vol. 10, no. 1, pp. 84–90, 2025.
J. Yang, X. Zhang, and Y. Pei, “Digital transformation of the business models of chinese sporting goods enterprises in the post-covid-19 era: a knowledge-management perspective,” Journal of Knowledge Man- agement, vol. 29, no. 3, pp. 723–734, 2025.
H. Nurhaeni, A. Delhi, O. P. M. Daeli, S. A. Anjani, and N. A. Yusuf, “Optimizing electrical energy use through ai: An integrated approach for efficiency and sustainability,” International Transactions on Artificial Intelligence, vol. 2, no. 2, pp. 106–113, 2024.
C. Duan, “Thematic evolution, emerging trends for sharing economy business model research, and future research directions in the post-covid-19 era,” R&D Management, vol. 54, no. 5, pp. 1104–1130, 2024.
M. N. Mondra and N. A. Rakhmawati, “Analysis of market potential and business model of establishment of automotive parts startup in the digital era with the lean startup method,” in 2024 International Confer- ence of Adisutjipto on Aerospace Electrical Engineering and Informatics (ICAAEEI). IEEE, 2024, pp. 1–6.
CNBC, “Human resources and employment services cnbc,” https://www.cnbc.com/ human-resources-and-employment-services/, 2025, accessed: 2025-09-18.
W. Villegas-Ch, J. Govea, R. Gurierrez, and A. Mera-Navarrete, “Optimizing security in iot ecosystems using hybrid artificial intelligence and blockchain models: a scalable and efficient approach for threat detection,” IEEE Access, 2025.
G. Qiao, Y. Li, and A. Hong, “The strategic role of digital transformation: Leveraging digital leadership to enhance employee performance and organizational commitment in the digital era,” Systems, vol. 12, no. 11, p. 457, 2024.
HR Dive, “Hr dive: News and analysis on human resources,” https://www.hrdive.com/, 2025, accessed: 2025-09-18.
M. Plechero, E. Santini, and G. Cor`o, “Through firms’ eyes: How manufacturing smes define their tech- nological spaces and trajectories in the digital era,” Available at SSRN 5170326.
S. Lestari, S. Watini, and D. E. Rose, “Impact of self-efficacy and work discipline on employee perfor- mance in sociopreneur initiatives,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 2, pp. 270–284, 2024. [16] S. B. Rane and Y. A. M. Narvel, “Data-driven decision making with blockchain-iot integrated architec- ture: a project resource management agility perspective of industry 4.0,” International Journal of System Assurance Engineering and Management, vol. 13, no. 2, pp. 1005–1023, 2022.
A. Agarwal, “Use cases of blockchain technology for sustainable global hr operations in industry 4.0,” Blockchain in a Volatile-Uncertain-Complex-Ambiguous World, pp. 149–161, 2023.
D.-S. Kim and R. Syamsul, “Integrating machine learning with proof-of-authority-and-association for dynamic signer selection in blockchain networks,” ICT Express, vol. 11, no. 2, pp. 258–263, 2025.
V. Mukesh, “A comprehensive review of advanced machine learning techniques for enhancing cybersecu- rity in blockchain networks,” Journal ID, vol. 8736, p. 2145, 2025.
G. A. Pangilinan, S. Audiah, M. R. Shauqy, and O. F. P. Wahyudi, “Entrepreneurial marketing mindset as a determining factor for digital startup success,” Startupreneur Business Digital (SABDA Journal), vol. 4, no. 1, pp. 34–46, 2025.
M. Monem, M. T. Hossain, M. G. R. Alam, M. S. Munir, M. M. Rahman, S. A. AlQahtani, S. Almutlaq, and M. M. Hassan, “A sustainable bitcoin blockchain network through introducing dynamic block size adjustment using predictive analytics,” Future Generation Computer Systems, vol. 153, pp. 12–26, 2024.
D. Cason, E. Fynn, N. Milosevic, Z. Milosevic, E. Buchman, and F. Pedone, “The design, architecture and performance of the tendermint blockchain network,” in 2021 40th International Symposium on Reliable Distributed Systems (SRDS). IEEE, 2021, pp. 23–33.
M. Dotan, Y.-A. Pignolet, S. Schmid, S. Tochner, and A. Zohar, “Survey on blockchain networking: Context, state-of-the-art, challenges,” ACM Computing Surveys (CSUR), vol. 54, no. 5, pp. 1–34, 2021.
P. Rani, P. Sharma, and I. Gupta, “Toward a greener future: A survey on sustainable blockchain applica- tions and impact,” Journal of Environmental Management, vol. 354, p. 120273, 2024.
M. Pineda, D. Jabba, W. Nieto-Bernal, and A. P´erez, “Sustainable consensus algorithms applied to blockchain: A systematic literature review,” Sustainability, vol. 16, no. 23, p. 10552, 2024.
K. Haritha, S. S. Vellela, L. R. Vuyyuru, N. Malathi, L. Dalavai et al., “Distributed blockchain-sdn mod- els for robust data security in cloud-integrated iot networks,” in 2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE, 2024, pp. 623–629.
A. Sonkar, S. K. Sahu, A. Nayak, D. Sahu, P. Verma, and R. Tiwari, “An efficient privacy-preserving ma- chine learning for blockchain network,” in 2023 4th International Conference on Intelligent Technologies (CONIT). IEEE, 2024, pp. 1–6.
A. Pal, C. K. Tiwari, and N. Haldar, “Blockchain for business management: Applications, challenges and potentials,” The Journal of High Technology Management Research, vol. 32, no. 2, p. 100414, 2021.
H. Mishra and M. Venkatesan, “Blockchain in human resource management of organizations: an em- pirical assessment to gauge hr and non-hr perspective,” Journal of Organizational Change Management, vol. 34, no. 2, pp. 525–542, 2021.
K. Arora, M. Faisal et al., “The use of data science in digital marketing techniques: Work programs, performance sequences and methods.” Startupreneur Business Digital (SABDA Journal), vol. 1, no. 2, pp. 143–155, 2022. [31] A. N. Mohammad Saif and M. A. Islam, “Blockchain in human resource management: a systematic review and bibliometric analysis,” Technology Analysis & Strategic Management, vol. 36, no. 4, pp. 635– 650, 2024.
R. Ramachandran, V. Babu, and V. P. Murugesan, “The role of blockchain technology in the process of decision-making in human resource management: a review and future research agenda,” Business Process Management Journal, vol. 29, no. 1, pp. 116–139, 2023. [33] R. Pratomo, M. Hardini, D. Julianingsih, D. Suprianti, and Q. Aini, “Blockchain-enabled analytics in banking enhancing risk management for the future of the industry,” in 2024 2nd International Conference on Technology Innovation and Its Applications (ICTIIA). IEEE, 2024, pp. 1–6.
Z. Azhar, “Blockchain as a catalyst for green and digital hr transformation: Strategies for sustainable workforce management,” Available at SSRN 5183293, 2024.
A. Supriyadi, S. Anhar, A. Y. Farchani, N. Lutfiani, S. N. W. Putra, and S. V. Sihotang, “Fintechs role in asset management efficiency and economic growth in emerging markets,” in 2024 3rd International Conference on Creative Communication and Innovative Technology (ICCIT). IEEE, 2024, pp. 1–7.
Z. Chen, “Revolutionising hrm practice with blockchain technology: unleashing disruptive paradigms of work and overcoming management challenges,” Technology Analysis & Strategic Management, vol. 37, no. 2, pp. 125–138, 2025.
A. Agarwal, K. Kapoor, and S. Walia, “Modelling the barriers to blockchain implementation in human resource function,” International Journal of Quality & Reliability Management, vol. 41, no. 8, pp. 2075– 2094, 2024.