The fertilizer sector aims to provide sufficient supplies across the world to provide the necessary fertilizer products for the smooth operation of the global market. Such a task requires the utilization of supply chain firms’ participation. Their role is critical to the development of modern economies. Supply chain firms seek to exploit any available technologies that would enhance their profitability, such as the increase of their stock price. Towards the satisfaction of the objective of supply chain firms, in the fertilizer industry, the capitalization of various digital innovations would be fruitful. Digital innovations like blockchain technology, applications, and the cryptocurrency market provide sufficient data to assist the aim of supply chain firms in achieving profitability. Thus, big data derived from decentralized finance applications like the cryptocurrency markets could be harvested in favor of enhancing the stock market price of supply chain firms in the fertilizer industry, hence their profitability.

Many issues arose from the improper use of terms (Peráček 2021), thus the authors opted to provide a clear definition of Bitcoin. Bitcoin (BTC) is a cryptocurrency, or virtual currency, meant to function as money and a means of exchange independent of a single individual, organization, or organization, hence eliminating the need for third-party participation in transactions involving money. It is given to blockchain producers as payment for their efforts in verifying transactions and may be acquired on multiple markets (Frankenfield 2023). The operation of the stock market exchange is a sensitive matter and would require more concise supervision regarding the security of trading (Sidak et al. 2023).

Various initiatives, like innovation advancement, studies, blog monitoring, and advertising, are critical for the expansion of fertilizer and agribusiness supply chain enterprises (Singh et al. 2022). Agribusinesses make contributions to the economy by increasing agricultural productivity, creating jobs, and supplying materials to multiple food supply chain enterprises (Qingxue and Wu 2016). The area set aside for agribusiness is small, but the need for agricultural output is significant. As a result, fulfilling demand with fewer resources is somewhat difficult, as sustainability solutions must be employed to achieve a sustainable future (Cappelli et al. 2022).

Multiple digital innovations across the fertilizer and supply chain context seek to transform the sector and facilitate additional flexibility in manufacturing processes, effective utilization of resources, and procedure optimization from smartphone tracking to the last-end delivery using innovations, such as the assimilation of cyber-physical systems (CPS), IoT, real-time customer engagement, digital applications, etc. (Kaburuan and Jayadi 2019). Therefore, for the fertilizer industry to increase production and sustainability, incorporating data and knowledge has grown increasingly important (Ghorbel et al. 2022). Internet of Things (IoT) innovations (Ketu and Mishra 2022; Frikha et al. 2021) greatly expand the availability and utility of data collecting, storing, interpretation, and usage in the sector.

The usage of blockchain is not just associated with cryptocurrencies, but additionally with other industries that are beginning to engage in specific application scenarios, such as Industry 4.0 and 5.0 (Xu et al. 2021). Leng et al. (2018) proposed a decentralized blockchain-based agricultural supply chain infrastructure. Li et al. (2006) developed an innovative modeling technique for agricultural and fertilizer supply chain firms. As a consequence, they were capable of maximizing output, raising efficiencies, and reducing waste. Surasak et al. (2019) demonstrated a blockchain-based IoT monitoring platform tailored specifically for agricultural goods.

Decentralized finance, or DeFi, is an economy of financial services developed on a blockchain network (Binance 2023a). The purpose of DeFi should be to develop an alternative financial infrastructure that does not rely on financial institutions or trusted third parties. Cryptocurrencies were founded to decentralize finance, enabling simpler transactions, drastically cutting the duration required to move cash, and lowering processing costs. However, authority can be accumulated in the control of a handful of businesses, even with Bitcoin, if customers opt to employ centralized fiduciary facilities (Kumar et al. 2020).

Much experimental research has been conducted to investigate the possible factors of cryptocurrency values. Such variables are classified in terms of macroeconomic context and societal awareness (Clark et al. 2023). In terms of the macroeconomic landscape, stock market values, currency exchange, asset prices, and fiscal policy volatility have been highlighted as determinants of cryptocurrency pricing and returns. Numerous publications have examined the fiscal capacities of cryptocurrencies, particularly Bitcoin, by investigating their involvement in the market and where they stand in comparison to other commodities (Corbet et al. 2018, 2019).

Cryptocurrency markets are the principal and, in many cases, the only place to buy, sell, and swap cryptocurrencies and coins. Several trades run 24 h a day, seven days a week, with no regional restrictions. Investors from virtually everywhere are allowed to participate in trading with no constraints or limitations. Many markets allow every investor to register and begin exchanging in seconds, unless an authentication procedure is necessary, which can involve anything from a couple of seconds to days (Saleh 2018).

Big data has provided fresh options for doing data processing work to enhance decision-making assistance mechanisms (Power 2015). Big databases are becoming more widely accessible as technology progresses in commercial operations. Big Data Analytics can alter enterprises and offer them the knowledge management to adjust to existing prospects and problems (Seles et al. 2018). Physically acquiring, retrieving, and evaluating data would not be necessary anymore (Falahat et al. 2023). This opens the way for utilizing Big Data Analytics in modeling and predicting share prices course.

Big Data Analytics is applying superior analysis techniques, both quantitative and qualitative, to massive amounts of organized and unorganized information. Forecast analytics (Schoenherr and Speier-Pero 2015), digital marketing analytics, big data analytics, and supply chain analytics (Wang et al. 2016) are examples of such research. Forecast analytics, for instance, is a significant element in Supply Chain Management (SCM), in projecting market trends and projected consumption, limiting inventory levels sometimes throughout situations of unexpected demand, such as in the latest years. It may be utilized to uncover SCM’s latent capability in terms of necessary competencies (Schoenherr and Speier-Pero 2015).

Apart from the referred application of Big Data Analytics, such tools could be used in producing important financial insights, such as the prediction of stock price variations. These data are capable of providing sufficient information for the development of innovative models to achieve digital marketing efficiency (Sakas et al. 2022b, 2022c). Capitalization of Big Data Analytics, combined with blockchain applications’ innovativeness, would be capable of producing the required value of data for potential investors in specific markets. Hence, while building a more universal product that may deliver analytical benefits to even more sectors may be difficult, it is not out of the realm of possibility through the utilization of Big Data Analytics (Mousavian et al. 2023).