Abstract
Background: Technological advancements have revolutionized business operations, particularly in predicting market trends and growth. While Bitcoin (BTC) is not intended to replace traditional currency, its adoption in business practices is increasing. Concurrently, blockchain (Blch) technology facilitates secure and transparent information sharing. Blockchain’s decentralized database, especially for Bitcoin transactions, offers businesses valuable insights and opportunities in cryptocurrency exchanges.
Method: This research explores the relevance of (Blch) technology in predicting Bitcoin's market price (MktP) and its business implications. Four critical success factors (CSFs) for predicting BTC's MktP were identified: Currency Statistics, BTC cycle indicators, Blockdetail, and Mining Information. These CSFs encompass 23 indicators, measured using data from secondary sources such as newspapers, Bitcoin companies in the US, social networking sites, and other web sources. The study employed a comprehensive analytical approach to assess how these indicators contribute to predicting BTC's MktP and impact business strategies.
Results: The study demonstrates (Blch) technology’s effectiveness in predicting Bitcoin's MktP for businesses. By analyzing the identified CSFs and their indicators, the study elucidates how (Blch) works. The findings underscore blockchain’s significance as a tool for enhancing market prediction and strategic decision-making in the cryptocurrency landscape.
Conclusion: This research highlights business implications. By identifying CSFs and leveraging diverse data sources, businesses can use blockchain-driven insights to navigate the cryptocurrency market, capitalize on opportunities, and mitigate BTC exchange risks. Future advancements in (Blch) technology promise to reshape market prediction and drive innovation in business practices.
Recommended Citation
Naim, Arshi; Khan, Shad Ahmad; Mohammed, Arshiya; Sabahath, Asfiya; and Malik, Praveen Kumar, "Achieving Performance and Reliability in Predicting the Marketing Price of Bitcoins through Blockchain Technology" (2024). PAJAIS Preprints (Forthcoming). 23.
https://aisel.aisnet.org/pajais_preprints/23