Strategic Development and Innovation in Business Leveraging Artificial Intelligence and Blockchain Technology
Subject Areas : information technology
1 - Senior Expert in Information Technology Management-Electronic Business-Islamic Azad University-Tehran North Branch
Keywords: Advanced technologies, Artificial intelligence, Blockchain, Innovation,
Abstract :
In an era where business transformations are occurring at an unprecedented pace, advanced technologies such as Artificial Intelligence (AI) are providing new capabilities to enhance commercial performance. These advancements are revolutionizing corporate interactions with customers and employees through information technology-based services. With the expanding use of AI, businesses must re-evaluate their current strategies and actively seek to discover new market opportunities. With increased focus on research in the field of commercial innovations, blockchain has been proposed as a solution for ensuring data security. This article introduces the AI and Blockchain-based Business Innovation Model (BI-AIBT) to strengthen business processes and ensure secure interactions among diverse customers. The model has been examined using qualitative empirical data from participants in two business sectors. BI-AIBT, by analyzing the impact of information technology usage on value creation, proposals, and business attraction, has demonstrated that blockchain can be effective in enhancing interactions between organizational capacities and employee skills. Experimental results of this model indicate that the transformation brought about by information technology is recognized as a significant element in bolstering business innovation strategies, and the BI-AIBT model enhances ratios of demand forecasting (97.1%), product quality (98.3%), business development (98.9%), customer behavior analysis (96.3%), and customer satisfaction (97.2%).
[1] Amin, M., Faragallah, O. S., & El-Latif, A. A. (2010). A chaotic block cipher algorithm for image
cryptosystems. Communications in Nonlinear Science and Numerical Simulation, 15(11), 3484–3497.
[2] Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., et al (2019). Blockchain technology in the
energy sector: A systematic review of challenges and opportunities. Renewable and Sustainable Energy Reviews, 100, 143–174.
[3] Arjun, R., & Suprabha, K. R. (2020). Innovation and Challenges of Blockchain in Banking: A Scientometric View. International Journal of Interactive Multimedia & Artificial Intelligence, 6(3).
[4] Asghar, M. Z., Subhan, F., Ahmad, H., Khan, W. Z., Hakak, S., Gadekallu, T. R., et al. (2021). Senti-eSystem:
A sentiment-based eSystem-using hybridized fuzzy and deep neural network for measuring customer satisfaction. Software: Practice and Experience, 51(3), 571–594.
[5] Belazi, A., Khan, M., El-Latif, A. A., & Belghith, S. (2016). Efficient cryptosystem approaches: S-boxes and permutation–substitutionbased encryption. Nonlinear Dynamics, 87(1), 337–361.
[6] Borah, A., Banerjee, S., Lin, Y. T., Jain, A., & Eisingerich, A. B. (2020). Improvised marketing interventions in social media. Journal of Marketing, 84(2), 69–91.
[7] Feng, Q., He, D., Zeadally, S., Khan, M. K., & Kumar, N. (2019). A survey on privacy protection in blockchain system. Journal of Network and Computer Applications, 126, 45–58.
[8] Filimonau, V., & Naumova, E. (2020). The blockchain technology and the scope of its application in hospitality operations. International Journal of Hospitality Management, 87, Article 102383.
[9] Fu, H., Manogaran, G., Wu, K., Cao, M., Jiang, S., & Yang, A. (2020). Intelligent decision-making of online
shopping behavior based on internet of things. International Journal of Information Management, 50, 515–525
[10] Gao, J., Wang, H., & Shen, H. (2020a). Machine learning based workload prediction in cloud computing. In 29th International Conference on Computer Communications and Networks (ICCCN).
[11] Gao, J., Wang, H., & Shen, H. (2020b). Smartly handling renewable energy instability in supporting a cloud datacenter. In IEEE International Parallel and Distributed Processing Symposium (IPDPS).
[12] Hakala, H., O’Shea, G., Farny, S., & Luoto, S. (2020). Re-storying the business, innovation and
entrepreneurial ecosystem concepts: The model-narrative review method. International Journal of Management Reviews, 22(1), 10–32.
[13] Hu, L., Nguyen, N. T., Tao, W., Leu, M. C., Liu, X. F., Shahriar, M. R., et al (2018). Modeling of cloud-based digital twins for smart manufacturing with MT connect. Procedia manufacturing, 26, 1193–1203.
[14] Jan, M. A., Cai, J., Gao, X. C., Khan, F., Mastorakis, S., Usman, M., et al (2020). Security and blockchain
convergence with Internet of Multimedia Things: Current trends, research challenges and future directions. Journal of Network and Computer Applications, Article 102918.
[15] Kaur, K., Garg, S., Kaddoum, G., Ahmed, S. H., & Atiquzzaman, M. (2019). Keids: Kubernetes-based energy
and interference driven scheduler for industrial iot in edgecloud ecosystem. IEEE Internet of Things Journal, 7(5), 4228–4237.
[16] Khelifi, H., Luo, S., Nour, B., Moungla, H., Ahmed, S. H., & Guizani, M. (2020). A blockchain-based
architecture for secure vehicular Named Data Networks. Computers & Electrical Engineering, 86, Article 106715.
[17] Kumar, G., Saha, R., Buchanan, W. J., Geetha, G., Thomas, R., Rai, M. K., et al. (2020). Decentralized
accessibility of e-commerce products through blockchain technology. Sustainable Cities and Society, 62, Article 102361.
[18] Manogaran, G., Alazab, M., Shakeel, P. M., & Hsu, C. H. (2021). Blockchain Assisted Secure Data Sharing Model for Internet of Things Based Smart Industries. IEEE Transactions on Reliability.
[19] Manogaran, G., Baskar, S., Hsu, C. H., Kadry, S. N., Sundarasekar, R., Kumar, P. M., et al. (2020a). FDM:
Fuzzy-optimized Data Management Technique for Improving Big Data Analytics. IEEE Transactions on Fuzzy Systems.
[20] Manogaran, G., Rawal, B. S., Saravanan, V., Kumar, P. M., Martínez, O. S., Crespo, R. G., et al. (2020b).
Blockchain based integrated security measure for reliable service delegation in 6G communication
environment. Computer Communications, 161, 248–256. https://doi.org/10.1016/j.comcom.2020.07.020
[21] Manogaran, G., Rawal, B. S., Saravanan, V., Kumar, P. M., Martínez, O. S., Crespo, R. G., et al. (2020c).
Blockchain based integrated security measure for reliable service delegation in 6G communication environment. Computer Communications, 161, 248–256.
[22] Manogaran, G., Srivastava, G., Muthu, B. A., Baskar, S., Shakeel, P. M., Hsu, C. H., et al. (2020d). A
Response-aware Traffic Offloading Scheme using Regression Machine Learning for User-Centric Large-Scale Internet of Things. IEEE Internet of Things Journal.
[23] Mistry, I., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Blockchain for 5G enabled IoT for industrial automation: A systematic review, solutions, and challenges.
[24] Mechanical Systems and Signal Processing, 135, Article 106382. Morkunas, V. J., Paschen, J., & Boon, E. (2019). How blockchain technologies impact your business model. Business Horizons, 62(3), 295–306.
[25] Mustafa, & Khan, S. (2020). FinTech, Blockchain and Islamic Finance: An Extensive Literature Review.
International Journal of Economics and Business Administration, 65–86. https://doi.org/10.35808/ijeba/444. VIII (Issue 2).
[26] Nguyen, N. T., Liu, B. H., Chu, S. I., & Weng, H. Z. (2018a). Challenges, designs, and performances of a
distributed algorithm for minimum-latency of data-aggregation in multi-channel WSNs. IEEE Transactions on Network and Service Management, 16(1), 192–205.
[27] Nguyen, N., Leu, M. C., & Liu, X. F. (2017). Real-time communication for manufacturing cyber-physical
systems. In IEEE 16th International Symposium on Network Computing and Applications (NCA) (pp. 1–4). Cambridge, MA, USA.
[28] Nguyen, N. T., Leu, M. C., Zeadally, S., Liu, B. H., & Chu, S. I. (2018b). Optimal solution for data collision avoidance in radio frequency identification networks. Internet Technology Letters 2018, 1, E49.
[29] P, A. K., G, S. S., Maddikunta, P. K., Gadekallu, T. R., Al-Ahmari, A., & Abidi, M. H. (2020). Location Based Business Recommendation Using Spatial Demand.Sustainability, 12(10), 4124.
[30] Pham, D. V., Nguyen, G. L., Nguyen, T. N., Pham, C. V., & Nguyen, A. V. (2020). Multi-Topic
Misinformation Blocking With Budget Constraint on Online Social Networks. IEEE access : practical innovations, open solutions, 8, 78879–78889.
[31] Ruan, J., Hu, X., Huo, X., Shi, Y., Chan, F. T., Wang, X., et al. (2019). An IoT-based E-business model of
intelligent vegetable greenhouses and its key operations management issues. Neural Computing and Applications, 32(19), 15341–15356.
[32] Sheron, P. F., Sridhar, K. P., Baskar, S., & Shakeel, P. M. (2019). A decentralized scalable security
framework for end-to-end authentication of future IoT communication. Transactions on Emerging Telecommunications Technologies, e3815. https://doi.org/10.1002/ett.3815.
[33] Stratan, A., Novac, A., & Vinogradova, N. (2020). Cooperation for Innovation: Opportunities and Challenges for SMEs (The Case of the Republic of Moldova). LUMEN Proceedings, 14, 01–20.
[34] Sun, J., Yan, J., & Zhang, K. Z. (2016). Blockchain-based sharing services: What blockchain technology can contribute to smart cities. Financial Innovation, 2(1), 1–9.
[35] Thuethongchai, N., Taiphapoon, T., Chandrachai, A., & Triukose, S. (2020). Adopt big-data analytics to explore and exploit the new value for service innovation. Social Sciences, 9(3), 29.
[36] Trad, A. (2021). The business transformation framework and enterprise architecture framework for managers
in business innovation: An applied holistic mathematical model. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 12(1), 142–181.
[37] Ur-Rehman, A., Gondal, I., Kamruzzaman, J., & Jolfaei, A. (2020). Vulnerability modelling for hybrid industrial control system networks. Journal of Grid Computing, 18 (4), 863–878.
[38] Wang, S., Huang, L., Hsu, C. H., & Yang, F. (2016). Collaboration reputation for trustworthy Web service selection in social networks. Journal of Computer and System Sciences, 82(1), 130–143.
[39] Zhao, J., Xue, F., Khan, S., & Khatib, S. F. (2021). Consumer behaviour analysis for business development.
Aggression and Violent Behavior. Article 101591. https://doi.org/10.1016/j.avb.2021.101591