With the arbitrariness of family business decision-making and the complexity of interests become increasingly prominent, the transformation and innovation of family business are imminent. Under the above background, via analysis of data from 259 valid questionnaires from more than ten family businesses in China as a sample and with the help of the SPSS and AMOS, this study explored the impacts of identification on creativity of the family business as well as the mediating role of family business support by constructing a mediating model. The results show that the employee’s identification has a positive impact on the creativity of the family business. Besides, identification has a positive impact on family business support and family business support has a partial mediating role between identification and family business creativity. Especially, the emotional support does not have a mediating role, whereas the instrumental support has a complete mediating role between identification and family business creativity.

With the ongoing development of the digital economy, the productive function of data as an economic factor has become increasingly salient. Scientifically and rigorously assessing the value of data assets is essential for improving the national economic accounting system and promoting sustainable economic growth. In light of the limitations inherent in existing cost-based and market-based valuation approaches, this paper proposes a comprehensive valuation model that integrates the cost approach with the income approach and applies it to the commercial banking sector. Specifically, text analysis is employed to estimate human capital investment in data assets from the perspective of labor supply and demand, after which total costs are derived based on the proportion of human capital. An ARIMA model is used to forecast future cost inputs and net profits associated with data assets. Furthermore, the income-based approach is adopted to estimate the average present value of data assets, with the results of the two methods serving to validate each other. The comparison of estimation results under the cost approach and the income approach further validates the relationship between input and output in data assets. This also demonstrates that data assets follow the law of diminishing marginal utility, thereby contradicting the notion that data increases in value with greater usage. This study enriches the theoretical framework of data asset valuation, broadens its application scope, and provides meaningful guidance for advancing data asset accounting practices and related research.

In the context of a progressively intricate and uncertain global economic landscape, the credit risk businesses encounter is intensifying. This study seeks to analyze whether intelligent transformation, a significant trend in current organization development, might serve as a novel method for mitigating credit risk. We employ panel data from 1533 listed enterprises in China’s manufacturing sector to investigate how intelligent transformation influences credit risk empirically. This research indicates that intelligent transformation can mitigate business credit risk. The production, management, and financing effects are the primary mechanisms via which intelligent transformation mitigates credit risk. Heterogeneity analysis indicated that the credit risk reduction effect of the intelligent transformation of traditional manufacturing firms surpassed that of intelligent manufacturing enterprises. In contrast to high-growth firms, low-growth enterprises exhibited more robust credit risk mitigation benefits from intelligent transformation. Subsequent analysis indicated that enhancing supply chain finance can facilitate intelligent transformation and, hence, more effectively mitigate credit risk.

Based on the data of peer-to-peer (P2P) platforms, employing the ARIMAX model and analyzing the risk outbreak process of P2P platforms, we find that the risk outbreak of P2P is a spreading process from weak to strong along the “qualification chain” of the platforms. This risk outbreak process along the qualification chain is dubbed the “fuze effect” in this paper as the process is similar to that of the fuze detonating explosives. This finding implies that the real risk comes from the uneven quality of P2P platforms, which is different from the dominant opinion that of their “credit enhancement services”. Our further study suggests that the fuze effect comes from deadweight cost caused by market competition. This study is of significance for risk prevention in emerging industries such as FinTech; that is, for the sake of sustainable development of emerging industries, the government must be vigilant about the fuze effect.