This study aims to scrutinize specific long-term sustainability industrial indicators in Thailand as a representative of an emerging economy. The study uses a Bloomberg database comprising all Thai listed companies on the Stock Exchange of Thailand from 2013 to 2023. The research employs a two-step Generalized Method of Moments (GMM) statistics to assess the enduring impact on industrial sustainability. These results provide consistent, significant and positive relationships between asset turnover and sales with all industrial sustainability. The results additionally reveal that some other factors may moderate industrial sustainability but reveal the GDP growth rate and institutional shareholders are less likely to be corporate sustainability to all indicators. The results provide insight into valuable guidance to management teams, financial statements’ users, investors and other stakeholders on designing effective operations and investment strategies to improve sustainability.

The quest for quality postgraduate research productivity through education is on the increase. However, in the context of the African society, governance structures and policies seem to be impacting on the quality level of the provided education. Hence, this conceptual study explored the roles of governance structures and policies in enhancing and ensuring quality postgraduate education programmers in African institutions of higher learning. To this end, various relevant literature was reviewed. The findings showed amongst others that governance structures and policies affect the quality of education provided. Meanwhile, other factors such as curriculum, foreign influence, lack of resources, training, amongst others contribute to the quality of education provided. The study concludes that there is need for the current structures of governance and the designed and implemented policies for postgraduate education to be reviewed and adjusted towards ensuring the desired transformation.

Introduction: In contemporary healthcare education, the integration of technology has emerged as an essential factor in enhancing the efficiency and efficacy of training methodologies. Particularly within the domain of cardiopulmonary resuscitation (CPR) training, the adoption of technology-driven approaches holds considerable potential for enriching the skills and proficiencies of healthcare practitioners. Through the utilization of innovative technologies, such as simulation software and leveraging smartphones as primary tools, CPR training programs can be customized to provide immersive, interactive, and authentic learning experiences. This study aims to validate a comprehensive CPR training module tailored explicitly for healthcare professionals, to integrate it into smartphones as a medium for delivering CPR training. Methods: Two validity tests, namely content validity and face validity were conducted to evaluate the validity of the Smart-CPR training module. A self-constructed measurement scale was utilized to assess four parameters: consistency, representativeness, clarity, and relevancy. Content validity employed the content validity ratio, with scores ranging between 1 and −1, indicating the level of consensus among experts regarding the significance of each item. Face validity was assessed using two indices: the item face validity index and the scale face validity index. Ratings of 3 or 4 were given a score of 1, while ratings of 1 or 2 received a score of 0. Result: The content validity shows that CVI values for ‘consistency’ and ‘representativeness’ were 0.99 for the module and questionnaire, and 0.96 and 0.97, respectively. ‘Clarity’ scored 0.99 for the module and 0.96 for the questionnaire, while ‘relevance’ achieved 0.99 for both. All 44 items exceeded the 0.83 threshold for face validity. The Lawshe’s content validity ratio (CVR) and content validity index (CVI) value were used to evaluate the content validity of both the CRSTP module and questionnaire, with CVR values result ranging from 0.80 to 0.99 across dimensions. These findings demonstrate robust content validity. Additionally, high CVI scores, mostly exceeding 0.95, suggest favorable outcomes and indicate no need for revisions. In face validity method, all 44 items surpassed the minimum threshold of 0.83, signifying a favourable outcome. Thus, all items were deemed acceptable. Conclusion: The Smart-CPR training module and questionnaires were meticulously developed to meet both face and content validity standards. All 44 items demonstrated appropriate levels of validity, ensuring they effectively enhance and maintain CPR competency among healthcare providers and potentially benefit the broader community. The positive results of the Smart-CPR training module confirm the high validity of the CPR competency assessment. Content validity, evaluated by experts, received a perfect score, demonstrating agreement on the relevance of each module component. Similarly, face validity, assessed by healthcare professionals, also received a flawless score, indicating consensus on the module’s clarity and relevance. These findings validate the module’s effectiveness in teaching CPR techniques to a diverse audience and ensuring compliance with established standards. With such strong validity, digitizing the module becomes more straightforward, facilitating easier sharing and use across digital platforms. Ultimately, the module’s high validity facilitates its integration into digital platforms, thereby enhancing CPR education and improving outcomes during real emergencies.

The low-carbon economy is the major objective of China’s economy, and its goal is to achieve sustainable economic development. The study enriches the literature on the relationship between digital Chinese yuan (E-CNY), low-carbon economy, AI trust concerns, and security intrusion. The rapid growth of Artificial Intelligence (AI) offered more ways to achieve a low-carbon economy. The digital Chinese yuan (E-CNY), based on the AI technique, has shown its nature and valid low-carbon characteristics in pilot cities of China, it will assume important responsibilities and become the key link. However, trust concerns about AI techniques result in a limitation of the scope and extent of E-CNY usage. The study conducts in-depth research from the perspective of AI trust concerns, explores the influence of E-CNY on the low-carbon economy, and discusses the moderating and mediating mechanisms of AI trust concerns in this process. The empirical data results showed that E-CNY positively affects China’s low-carbon economy, and AI trust concerns moderate the positive impact. When consumers with higher AI trust concerns use E-CNY, their feeling of security intrusion is also higher. It affects the growth of trading volume and scope of E-CNY usage. Still, it reduces the utility of China’s low-carbon economy. This study provides valuable management inspiration for China’s low-carbon economy.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.