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This research examines impacts from tourists’ destination knowledge and destination interest upon Generation Z’s recognition memory of advertisement for a new travel destination (Taiwan). The findings of this study indicated that participants with high destination knowledge are more likely to exhibit a lower level of new travel destination advertising recognition than participants with low destination knowledge, while the destination interest is low. Practical and theoretical implications of this outcome for destination marketers and tourism scholars are suggested to better understand and anticipate the processes of tourists’ learning and retaining of new travel destination information.

In this fast-changing world, digitization has become crucial to organizations, allowing decision-makers to alter corporate processes. Companies with a higher corporate social responsibility (CSR) level not only help encourage employees to focus on their goals, but they also show that they take their social responsibility seriously, which is increasingly important in today’s digital economy. So, this study aims to examine the relationship between digital transformation and CSR disclosure of Chinese A-share companies. Furthermore, this research investigates the moderating impact of governance heterogeneity, including CEO power and corporate internal control (INT) mechanisms.

This study used fixed effect estimation with robust standard errors to examine the relationship between digital transformation and CSR disclosure and the moderating effect of governance heterogeneity among Chinese A-share companies from 2010 to 2020. The whole sample consists of 17,266 firms, including 5,038 state-owned enterprise (SOE) company records and 12,228 non-SOE records. The whole sample data is collected from the China Stock Market and Accounting Research, the Chinese Research Data Services and the WIND databases.

The regression results lead us to three conclusions after classifying the sample into non-SOE and SOE groups. First, Chinese A-share businesses with greater levels of digitalization have lower CSR disclosures. Both SOE and non-SOE are consistent with these findings. Second, increasing CEO authority creates a more centralized company decision-making structure (Breuer et al., 2022; Freire, 2019), which improves the negative association between digitalization and CSR disclosure. These conclusions, however, also apply to non-SOE. Finally, INT reinforces the association between corporate digitization and CSR disclosure, which is especially obvious in SOEs. These findings are robust to alternative HEXUN CSR disclosure index. Heterogeneity analysis shows that the negative relationship between corporate digitalization and CSR disclosures is more pronounced in bigger, highly levered and highly financialized firms.

Digitalization and CSR disclosure are well studied, but few have examined their interactions from a governance heterogeneity perspective in China. Practitioners and policymakers may use these insights to help business owners implement suitable digital policies for firm development from diverse business perspectives.

This paper analysises China’s optimal scale of foreign reserve during 1985‐2004 with single ratio and synthesis ratio. The single ratio analysis shows that China’s foreign reserve to import ratio has exceeded 40 per cent after foreign exchange rate united in 1994. The foreign reserve to money supply ratio is high as 23.8 per cent, and will exceed 25 per cent of international alertness in 2005. The foreign reserve to debt ratio largely exceeded 30 per cent of international alertness. The current account balance to GDP ratio and the current account balance plus FDI to GDP ratio is out of international alertness in most years. The synthesis ratio analysis show that China’s real foreign exchange reserve exceeded foreign exchange demand of debt, FDI and import during 1996‐2004, and the exceeded ratio is close to 90 per cent in 2004. This paper also discusses influence of capital flight after 1995 and international hot money after 2002 to China’s optimal scale of foreign exchange.

In the fabric manufacturing industry, various unfavorable factors, including machine fault and yarn breakage, can easily cause fabric defects and affect product quality, begetting huge economic losses to enterprises. Thus, automatic fabric defect detection systems have become an important development direction. Herein, the most common defects in the fabric production process, like ribbon yarn, broken yarn, cotton ball, holes, yarn shedding and stains, are detected. Current fabric defect detection systems afford low detection accuracy and a high missed detection rate for small target fabric defects. Therefore, this study proposes deep learning technology for automatically detecting fabric defects by improving the YOLOv5s target detection algorithm. The improved algorithm is termed YOLOv5s-4SCK, which can effectively detect fabric defects. This study aims to discuss the aforementioned issues.

Specifically, based on the YOLOv5s algorithm, first, the structure of YOLOv5s is modified to add a small target detection layer, fully utilize deep and shallow features and reduce the missed detection rate of small target fabric defects. Second, the integration of CARAFE upsampling enables the effective retention of feature information and maintenance of a certain computational efficiency, thereby improving the detection accuracy. Finally, the K-Means++ clustering algorithm is used to analyze the position of the center point of the prior box to better obtain the anchor box and improve the average accuracy and evaluation index of detection.

The research results show that the YOLOv5s-4SCK algorithm increases the accuracy by 4.1% and the detection speed by 2 f.s-1 compared to the original YOLOv5s algorithm, and it effectively improves the original YOLOv5s problem of high missed detection rate of small targets.

The YOLOv5s-4SCK proposed in this paper can effectively reduce the missed detection rate of fabric defects, improve the detection efficiency and has certain industrial value.

The proposed algorithm can quickly identify fabric defects, effectively improving the detection rate. In the future, the proposed algorithm will be applied in the actual industry.

Automatic fabric defect detection reduces the manpower of inspectors, and the proposed YOLOv5s-4SCK algorithm is also suitable for other recognition fields.

The proposed YOLOv5s-4SCK algorithm has been tested using real cloth to ensure its accuracy, and its performance is better than the original YOLOv5s algorithm.

Digitalization is increasingly important for promoting authentic CSR practices. Firms with higher CSR levels motivate their employees to pursue their goals and demonstrate their social responsibility. However, the literature has not adequately examined how firm-level digitalization influences corporate sustainability from a governance perspective. This study aims to fill this gap by exploring how digitalization affects CSR disclosure, a key aspect of sustainability, at the firm level. Furthermore, this study also aims to investigate how governance factors, such as management power, internal control and minority shareholder pressure, moderate this effect.

This study employs a fixed effect model with robust standard errors to analyze how digitalization and CSR disclosure are related and how this relationship is moderated by governance heterogeneity among Chinese A-share companies from 2010 to 2020. The sample consists of 2,339 firms, of which 360 are SOEs and 1,979 are non-SOEs. To ensure robustness, this study has excluded the observations in 2020 to avoid the effects of COVID-19 and used an alternative measure of CSR disclosure based on the HEXUN CSR disclosure index. Furthermore, this study also explores the link in various corporate-level CSR settings.

The regression findings reveal that: First, Chinese A-share firms with higher digitalization levels disclose less CSR information. This finding holds for both SOEs and non-SOEs. Second, stronger management power has a negative moderating effect that weakens the link between digitalization and CSR disclosure, and this effect is mainly driven by SOEs. Third, internal control attenuates the negative association between firm digitalization and CSR disclosure, which is more pronounced in SOEs. Finally, minority shareholders exacerbate the negative relationship between digitalization and CSR disclosure, and this effect is more evident in non-SOEs. These results are robust to excluding the potential COVID effect and using an alternative HEXUN CSR disclosure index measure.

Digitalization and sustainability have been widely discussed at a macro level, but their relationship at a micro level has been largely overlooked. Moreover, there is hardly any evidence on how governance heterogeneity affects this relationship in emerging economies, especially China. This paper addresses these issues by providing empirical evidence on how digital transformation influences CSR disclosure in China, a context where digitalization and CSR are both rapidly evolving. The paper also offers implications for both practitioners and policymakers to design appropriate digital strategies for firm development from diverse business perspectives.