Abstract
Recent advances in data analysis and processing methods can improve the ability of computational applications to perform complex steps of different tasks. With the progress of information and communication technologies (ICT), Blockchain-based complex data processing for transaction analysis and smart contract agreement has become a new research area in the fields of mathematics and computation. Stability of financial sector based on the ICT is a core component for growing the economics of medium and small enterprises. This stability brings the innovation to businesses productivity, while the management of information takes more prospective for improving the efficiency and more ways for innovating the business of products. In this study, we use the autoregressive distribution lag (ARDL) model with Blockchain-based complex data processing approach to emphasize the role of ICT in the field of trade credit maintainability. Actually, the ICT connects the industries in the entire world and makes business sectors that use its technologies be more advanced. Based on the ARDL model conducted on the records gathered from 2000 to 2019, the analysis concludes that the ICT-based complex data processing is a critical component of trade credit. The statistics of ICT are chosen based on the economy penetrations through the Internet and mobile phones. The causality exposed between the trade credit and ICT is bidirectional in nature. Also, it is found that the usage of mobile phones has a substantial influence on the business sectors, as a substantial amount of trading and business transactions are conducted over the phone. Therefore, the primary concern is the association between the Blockchain and trade credit, which is thoroughly discussed in this work. The trade credit improves the stability of financial sector and the Blockchain supports its maintainability by the role of ICT. The results of the study can help the business stakeholders and investors to estimate the marketing for future useful execution.
Highlights
Graph-based data analysis (GDA) concept is theoretically applicable in the computer science (CS) field for several practical applications
In the United States, most businesses offer their products and services based on trade credit. e trade credit is considered a major source of short-term funding in many businesses
Results of Empirical Research e first and most critical step in any study is to ensure that the data is stationary. is is accomplished through the use of the unit root
Summary
Graph-based data analysis (GDA) concept is theoretically applicable in the computer science (CS) field for several practical applications. Blockchain-based complex data processing in information and communication technology (ICT) such as graph-based smart contract based agreement modelling, computing resource allocation, and users’ interactions and transaction analysis has become popular in recent years. In most parts of the world, trade credit is significant short-term funding for SME’s businesses [1, 2]. In the United States, most businesses offer their products and services based on trade credit. E trade credit is considered a major source of short-term funding in many businesses. E biggest consumers of trade credit are the nonfinancial firms as these firms are mostly facing a lack of financing. Companies depend more on trade credit for external financing due to the same nature of business between all trading parties
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