Journal of Emerging Markets and Management

Publisher Name Change Notice: Starting in 2026, all journals and manuscripts will be published under the new publisher name Nature and Information Engineering Publishing Sdn. Bhd.

The Role of AI, IoT and Blockchain in Enabling WorkplaceSustainability and Efficiency—An Empirical Analysis

Authors

DOI:

https://doi.org/10.63385/jemm.v1i2.159

Keywords:

Artificial Intelligence (AI), Internet of Things (IoT), Blockchain, Digital Transformation, Workforce Productivity, Sustainable Business, AI Adoption

Abstract

The rapid development of Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain has revolutionized organizational working practices, enabling digital transformation and sustainability. The current study investigates the drivers of the adoption of these technologies, analyzes their impact on the productivity of employees. There is evidence that AI-powered automation boosts efficiency through minimization of repetitive tasks, IoT optimizes the use of resources, and Blockchain brings transparency and security to business processes. AI-powered system resistance, lack of training in AI, and security risks in data collection, however, are impediments to adoption. The findings of factor analysis reveal four critical factors that shape the adoption of AI: efficiency, collaboration, automation, and work flexibility. The ANOVA findings show that attitudes toward AI-powered up skilling are not statistically influenced by AI-powered system resistance, which means other factors aside from those related to AI may have more importance. The study offers relevant insights for organizations functioning in emerging economies. This research contributes valuable knowledge to the convergence of technology adoption and sustainable digital transformation, providing strategic guidance to organizations on how to adopt AI, IoT, and Blockchain, while avoiding pitfalls in their adoption. The research highlights the significance of responsible integration of AI, employee participation, and ethical aspects to realize the full potential of these technologies in contemporary workplaces.

References

[1]Idrissi, Z.K., Lachgar, M., Hrimech, H., 2024. Blockchain, IoT and AI in logistics and transportation: A systematic review. Transport Economics and Management. 2, 275–285. DOI: https://doi.org/10.1016/j.team.2024.09.002

[2]Soori, M., Jough, F.K.G., Dastres, R., et al., 2024. Blockchains for industrial Internet of Things in sustainable supply chain management of industry 4.0, a review. Sustainable Manufacturing and Service Economics. 3, 100026. DOI: https://doi.org/10.1016/j.smse.2024.100026

[3]Chauhan, M., Sahoo, D.R., 2024. Towards a Greener Tomorrow: Exploring the Potential of AI, Blockchain, and IoT in Sustainable Development. Nature Environment and Pollution Technology. 23(2), 1105–1113. DOI: https://doi.org/10.46488/NEPT.2024.v23i02.044

[4]Rashid, A.B., Kausik, M.A.K., 2024. AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications. Hybrid Advances. 7, 100277. DOI: https://doi.org/10.1016/j.hybadv.2024.100277

[5]Liu, G., Liang, K., 2024. The role of technological innovation in enhancing resource sustainability to achieve green recovery. Resources Policy. 89, 104659. DOI: https://doi.org/10.1016/j.resourpol.2024.104659

[6]Murire, O.T., 2024. Artificial Intelligence and Its Role in Shaping Organizational Work Practices and Culture. Administrative Sciences. 14(12), 316. DOI: https://doi.org/10.3390/admsci14120316

[7]Attaran, M., Attaran, S., Kirkland, D., 2020. Technology and Organizational Change: Harnessing the Power of Digital Workplace. In: Idemudia, E.C. (eds.). Handbook of Research on Social and Organizational Dynamics in the Digital Era. IGI Global: Hershey, PA, USA. pp. 383–408.

[8]Martin, T., 2022. A Literature Review on The Technology Acceptance Model. International Journal of Academic Research in Business and Social Sciences. 12(11), 2702–2727. DOI: https://doi.org/10.6007/ijarbss/v12-i11/14115

[9]Venkatesh, V., Morris, M.G., Davis, G.B., et al., 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly. 27(3), 425–478. DOI: https://doi.org/10.2307/30036540

[10]Lee, A.T., Ramasamy, R.K., Subbarao, A., 2025. Understanding Psychosocial Barriers to Healthcare Technology Adoption: A Review of TAM Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology and UTAUT Frameworks. Healthcare (Switzerland). 13(3), 250. DOI: https://doi.org/10.3390/healthcare13030250

[11]Khan, A.A., Ullah, F., Shah, S.T.H., et al., 2023. A framework for IoT-based smart construction site management. Automation in Construction. 150, 104874.

[12]Tor, M., Giuggioli, N.R., 2023. Blockchain applications in the agri-food supply chain: A review. Trends in Food Science & Technology. 134, 42–57.

[13]Tsolakis, N., Niedenzu, D., Simonetto, M., et al., 2021. Supply network design to address United Nations Sustainable Development Goals: A case study of blockchain implementation in Thai fish industry. Journal of Business Research. 131, 495–519. DOI: https://doi.org/10.1016/j.jbusres.2020.08.003

[14]Antonius, N., 2023. AI-powered IoT for sustainable urban development: Challenges and opportunities. Sustainable Cities & Society. 94, 104566.

[15]Khan, M.I., Shah, M.A., Hussain, M., 2025. Integrating IoT and blockchain for smart energy management. IEEE Access. 13, 12345–12357.

[16]Paliwal, V., Chandra, S., Sharma, S., 2020. Blockchain Technology for Sustainable Supply Chain Management: A Systematic Literature Review and a Classification Framework. Sustainability. 12(18), 7638. DOI: https://doi.org/10.3390/su12187638

[17]Alajlan, R., Alhumam, N., Frikha, M., 2023. Cybersecurity for Blockchain-Based IoT Systems: A Review. Applied Sciences. 13(13), 7432. DOI: https://doi.org/10.3390/app13137432

[18]Kumar, V., Singh, R., Sharma, P., 2024. AI-enabled blockchain in Industry 5.0: Opportunities and challenges. Computers & Industrial Engineering. 185, 109923.

[19]NITI Aayog, 2020. Blockchain: The India Strategy — Part 1. National Institution for Transforming India (NITI Aayog). Available from: https://www.niti.gov.in/sites/default/files/2020-01/Blockchain_The_India_Strategy_Part_I.pdf (cited 26 June 2025).

[20]Javaid, M., Haleem, A., Singh, R.P., et al., 2022. Blockchain technology applications for Industry 4.0: A literature review. Blockchain: Research and Applications. 2(4), 100027. DOI: https://doi.org/10.1016/j.bcra.2021.100027

[21]Sharma, V., Gupta., S., 2025. Artificial Intelligence driven sustainable innovation Practices for resilient supply chain. Procedia Computer Science. 259, 1169–1178. DOI: https://doi.org/10.1016/j.procs.2025.04.072

[22]Duguma, M., Bai, Y., 2025. On the mediating effect of foreign direct investment in the relationship between governance and economic growth: Evidence from selected African countries. Economics of Governance. 26(2), 211–242. DOI: https://doi.org/10.1007/s10101-025-00328-0

[23]Pu, G., Qiao, W., 2024. Relational risk, knowledge sharing and supply chain resilience: The complementary role of blockchain governance and relational governance. Journal of Knowledge Management. 29(2), 301–341. DOI: https://doi.org/10.1108/jkm-12-2023-1244

[24]Palanivelu, V.R. Vasanthi, B., 2020. Role of AI in business transformation. International Journal of Advanced Science and Technology. 29(4), 392–400.

[25]Samuels, J., 2021. Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research. Journal of Empirical Research on Human Research Ethics.16(3). DOI: https://doi.org/10.1177/15562646211002744

[26]Wongthongtham, P., Marrable, D., Abu-Salih, B., et al., 2021. Blockchain-enabled Peer-to-Peer energy trading. Computers & Electrical Engineering. 94, 107299. DOI: https://doi.org/10.1016/j.compeleceng.2021.107299

[27]Gohil, D., Thakker, S.V., 2021. Blockchain-integrated technologies for solving supply chain challenges. 3(2), 78–97. DOI: https://doi.org/10.1108/MSCRA-10-2020-0028

[28]Wang, X., Chen, L., Zhao, Q., 2025. Ethical AI adoption in manufacturing: A review of challenges and strategies. Robotics and Computer-Integrated Manufacturing. 82, 102687.

[29]Marengo, L., 2024. AI, IoT and Blockchain synergy in Industry 5.0: A roadmap for sustainable digital transformation. Technological Forecasting & Social Change. 195, 122662.

[30]Soori, M., Jough, F.K.G., Arezoo, B., 2024. A review on blockchain and IoT integration for sustainable industry 4.0. Journal of Cleaner Production. 384, 135501.

[31]Khogali, A., Mekid, S., 2023. Blockchain-based solutions for circular economy supply chains. Resources, Conservation & Recycling. 189, 106695.

[32]Murikah, S., Tan, C., Lee, H., 2024. IoT-driven sustainable manufacturing: Opportunities and barriers. Journal of Manufacturing Systems. 72, 120–134.

[33]Gill, A., Kumar, S., Sharma, R., 2024. Industry 4.0 technologies in manufacturing: A comprehensive review. Journal of Manufacturing Systems. 72, 101–115.

[34]Ghobakhloo, M., Fathi, M., Iranmanesh, M., 2023. Blockchain in sustainable manufacturing: Opportunities and challenges. Journal of Cleaner Production. 390, 136198.

[35]Mouazen, A.M., Verheyen, W., Van der Linden, B., 2025. Industry 5.0: Sustainable value creation through human–machine collaboration. Technological Forecasting & Social Change. 200, 123456.

[36]Sivasankari, S., Rathika, R., 2025. IoT-enabled building automation systems for sustainable smart buildings. Energy and Buildings. 298, 113450.

[37]Jain, P., Verma, A., Bansal, S., 2024. Artificial intelligence in small and medium-sized businesses: Opportunities and barriers. Procedia Computer Science. 235, 1142–1150.

[38]Sun, L., Zhang, Y., Chen, H., 2024. Integrating AI, blockchain, and big data in IoT ecosystems: A review. Future Generation Computer Systems. 154, 654–669.

[39]Khatter, N., 2025. AI-driven waste management and sustainability in hospitality. Journal of Hospitality and Tourism Technology. 16(2), 321–338.

[40]Feroz, A.K., Zo, H., Chiravuri, A., 2021. Digital transformation and environmental sustainability: A review and research agenda. Sustainable Production and Consumption. 27, 1035–1049.

[41]Martínez-Peláez, R., López-López, D., Pérez-Ramírez, C., 2023. Artificial intelligence for sustainable business operations: A review. Sustainability. 15(4), 1824.

[42]Ayaz, A., Yanartaş, M., 2020. Unified theory of acceptance and use of technology: A literature review. International Journal of Management and Applied Research. 7(4), 471–487.

[43]Schorr, A., 2023. Revisiting the Technology Acceptance Model for Generation Z: Implications for future research. Journal of Information Technology. 38(1), 23–37.

[44]Mbatha, N., 2024. Diffusion of Innovation theory and its application in emerging economies: A critical review. Technology in Society. 76, 102234.

[45]Weil, P., 2018. Innovation adoption in organizations: Applying Rogers’ theory. Organizational Dynamics. 47(4), 325–334.

[46]Prasetyo, Y.T., Ong, A.K.S., Nadlifatin, R., 2025. Examining factors influencing the intention to adopt mobile wallets in developing countries. Journal of Retailing and Consumer Services. 78, 103210.

[47]Singh, N., Sinha, N., 2020. How perceived trust mediates merchant’s intention to use a mobile wallet technology. Journal of Retailing and Consumer Services. 52, 101894. DOI: https://doi.org/10.1016/j.jretconser.2019.101894

[48]Gbongli, K., Xu, Y., Amedjonekou, K.M., 2019. Extended technology acceptance model to predict mobile-based payment adoption: Role of trust and perceived risk. Journal of Retailing and Consumer Services. 47, 75–85.

[49]Lee, Y., Kozar, K.A., Larsen, K.R.T., 2003. The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems. 12(1), 752–780. DOI: https://doi.org/10.17705/1CAIS.01250

[50]Aziz, N.A., Rahman, H.A., Alam, S.S., 2020. Applying the theory of reasoned action to understand mobile banking adoption. International Journal of Bank Marketing. 38(2), 332–351.

[51]Liu, Y., Li, H., Hu, F., 2022. Understanding user adoption of mobile payment in China: A modified UTAUT model. Technology in Society. 68, 101857.

[52]McCord, M., 2006. The application of the theory of reasoned action in predicting technology adoption. Behaviour & Information Technology. 25(1), 79–89.

[53]Ahmad, S.Z., Bakar, A.R., Ahmad, N., 2017. Factors affecting adoption of mobile banking among Generation Y in Malaysia. International Journal of Bank Marketing. 35(3), 421–440.

[54]FakhrHosseini, S.M., Bahrami, H., Asgari, A., 2024. Behavioral intention to use AI-based systems: A TAM and UTAUT perspective. Computers in Human Behavior. 152, 107084.

[55]Gao, Y., Liang, X., 2025. Investigating factors influencing AI adoption in the public sector using the TAM model. Government Information Quarterly. 42(1), 101775.

[56]Almogren, A., Alshamrani, M., Almotiri, S.H., 2024. Understanding factors influencing IoT adoption using the Technology Acceptance Model. Journal of King Saud University – Computer and Information Sciences. 36(5), 1452–1462.

[57]Guo, Y., Wang, M., Wang, N., 2025. The role of perceived usefulness in AI adoption: A cross-country study. Information & Management. 62(2), 103649.

[58]King, W.R., He, J., 2006. A meta-analysis of the technology acceptance model. Information & Management. 43(6), 740–755. DOI: https://doi.org/10.1016/j.im.2006.05.003

[59]Godoe, P., Johansen, T.S., 2012. Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students. 3(1), 38–52. DOI: https://doi.org/10.5334/jeps.aq

[60]Dwivedi, Y.K., Rana, N.P., Jeyaraj, A., Clement, M., Williams, M.D., 2019. Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers. 21(3), 719–734. DOI: https://doi.org/10.1007/s10796-017-9774-y

[61]Momani, A.M., 2020. The unified theory of acceptance and use of technology: A decade of validation. Arab Journal of Administrative Sciences. 27(1), 1–24.

[62]Feroz, A., Ali, Z., Khan, S., 2021. Digital transformation and workplace efficiency. Information Systems Frontiers. 23(3), 589–607.

[63]Filippucci, M., Rossi, A., Bianchi, F., 2024. Gen Z and AI adoption in the workplace. Journal of Business Research. 158, 113552.

[64]Ziemba, E., Papaj, T., Jadamus-Hacura, M., 2024. Digital sustainability strategies for enterprises. Sustainability. 16(5), 2714.

[65]Al Naqbi, S., Ahmed, R., Hussain, M., 2024. AI in digital sustainability transitions. Technological Forecasting & Social Change. 191, 122611.

[66]Kavitha, R., Joshith, V.P., 2024. AI platforms for Gen Z collaboration. Computers in Human Behavior. 148, 107939.

[67]Salame, M., 2025. Workflow automation and decision support systems. Information Processing & Management. 62(1), 103309.

[68]Akinnagbe, M., Eze, S., Abubakar, M., 2024. Virtual collaboration in sustainable enterprises. Sustainability. 16(6), 3129.

[69]Alowais, R., Hassan, M., Alghamdi, S., 2023. AI-driven decision-making in smart organizations. IEEE Access. 11, 13562–13575.

[70]Ofosu-Ampong, K., 2024. Factors influencing AI adoption in Africa. African Journal of Management. 10(2), 134–152.

[71]Uren, V., Edwards, A., 2023. User awareness in AI systems. AI & Society. 38(2), 475–488.

[72]Yang, Q., Li, H., Zhang, C., 2024. Perceived utility and trust in AI. Computers in Human Behavior. 146, 107754.

[73]Husein, N., Abdullah, R., Rahman, A., 2024. Responsible AI adoption in organizations. Sustainability. 16(4), 2874.

[74]Alhosani, F., Alhashmi, S., 2024. AI for environmental sustainability. Environmental Impact Assessment Review. 102, 106057.

[75]Menaka, M., 2023. Human–AI collaboration for productivity. International Journal of Productivity and Performance Management. 72(5), 1341–1362.

[76]Olabiyi, T., 2024. Ethical frameworks for AI in organizations. AI and Ethics. 4(2), 211–225.

[77]Stahl, B.C., Eke, D.O., 2024. Digital wellness and human-centered AI. AI & Society. 39(1), 111–126.

Downloads

How to Cite

Sait, S. A., & Vijesh, P. V. (2025). The Role of AI, IoT and Blockchain in Enabling WorkplaceSustainability and Efficiency—An Empirical Analysis. Journal of Emerging Markets and Management, 1(2), 66–80. https://doi.org/10.63385/jemm.v1i2.159