The Effect of Shipper, Carrier, and Supervisory Management Data Mining of Online Freight Platforms on The Innovation of Financing Model For Chinese Financial Institutions
Authors: Wang Xiaojun , Suwandej Niyom , Khan Muhammad Shahid 
Published: June 2024

Objective: To analyze the sources of platform operation-related behavioral data elements needed to influence the effectiveness of innovative financing services for online freight platforms by financial institutions in China. To uncover the value of data elements affecting the effectiveness of the innovative financing services provided by China's financial institutions for online freight transport platforms. To explore the data value credit-enhancing innovation ability enhancement path that affects the effectiveness of China's financial institutions in providing innovative financing services for online freight transport platforms.

Theoretical Framework: In the TIS framework, innovation is seen as the result of a dynamic interaction among a network of actors (e.g., organizations, individuals) operating within an institutional context (e.g., policy, regulatory framework). These actors, through their activities and interactions, form a system that generates, diffuses, and utilizes new technologies (Bergek et al., 2008). The TIS can be described in terms of functions such as knowledge development, resource mobilization, market formation, and influence on the direction of search.

Method: Ma et al. (2022) made a significant contribution to the field of statistics and research methodology. Their proposal, suggesting that the estimated sample size should be 20 times the number of observational variables, has the potential to revolutionize the way studies are designed and conducted. The authors asserted that a larger sample size relative to the number of variables could lead to a more robust and reliable statistical analysis. They argued that by maintaining a high ratio of observations to variables, the precision of estimates can be improved, and the risk of overfitting can be reduced.

Results and Discussion: This study utilizes a mixed research approach to explore the impact of freight platform operations, data mining and innovation capabilities on the effectiveness of financial institutions. The main conclusions drawn are1) Online freight platform operation, has a positive correlation effect on promoting financial institution effectiveness; 2) Online freight platform operation has a positive effect on data mining and innovation capability; 3) Data mining plays a mediating role between online freight platform operation and financial institution effectiveness; and 4) innovation capability mediates the relationship between online freight platform operation and financial institution effectiveness.

Research Implications: The geographical and contextual specificity of the study potentially constrains the generalizability of the findings across varied regions and contexts. The cross-sectional nature of the research inhibits the exploration of temporal dynamics and the evolution of the examined variables. Furthermore, the focus on specific variables and dimensions might overlook other factors that could significantly impact the online freight platform ecosystem. The methodologies, while robust, may not fully capture the complexities and nuances of real-world operations and might omit the diverse perspectives and experiences of all relevant stakeholders in the online freight industry.