This research reviews the environmental, social, and governance (ESG) performance of corporate social responsibility (CSR) and technology innovation development, and analyzes the impact of technology innovation on ESG performance and its influencing mechanism. In additional, the main purpose of this study is to gain an understanding the relationships of ESG performance, CSR and technology innovation in Art industry. We found that technology innovation impact CSR of art firm, and ESG performance with the moderating variable of technology innovation has a significant and positive impact on CSR. Likewise, the study is based on primary panel data collected from 161 consumer, product and service manufacturing companies through an electronic questionnaire (Google, Microsoft online survey) with five-point Likert measurement scale. The exploratory factor analysis is proposed to be carried out using IBM SPSS 27.0 and the confirmatory factor analysis (CFA analysis) is proposed to be carried out using SmartPLS.4.0 analysis software, and this study investigate the measurement factors and the reliability of the construct items and to validate the factorial structure of the research variables. Moreover, digital technology and CSR has the potential to contribute to this impact. Based on these findings, we propose relevant ESG performance recommendations to improve technology innovation and CSR. Our findings offer an excited knowing and learning of the impact of ESG performance, CSR and technology innovation in Chinese art industry. Furthermore, this study extends stakeholders theory and Schumpeter’s Innovation Theory by proving their utility in the perspective of CSR, ESG performance.

This study addresses the present limited understanding of the complex relationship between ethical leadership, job stress, and employee job performance in the hotel business. This study shows that job stress moderates the association between ethical leadership and employee job performance, underlining the necessity for more research in the industry. The present study fills a crucial research void in our understanding of the complex interaction between these factors. The study utilizes a sample of 292 employees in the accommodation and hotel industry. Prior to commencing data collection, the questionnaire underwent thorough validation and reliability testing to ensure that the instrument met all specified criteria and demonstrated robustness. Using hierarchical regression analysis, the study reveals substantial findings. It has been discovered that ethical leadership has a direct and positive effect on employee job performance. Notably, job stress emerges as a significant moderating variable that affects the relationship between ethical leadership and employee job performance. This highlights the crucial role that job stress plays in determining outcomes. The research indicates that reducing workplace stress and fostering ethical leadership can result in improved employee job performance. In addition, the study highlights the importance of social learning theory in enhancing employee job performance, with job stress and ethical leadership serving as significant moderating factors.

Innovation has always been a key driver of economic development, particularly in the context of small and medium-sized enterprises (SMEs). Despite their significant contributions, many of these enterprises currently lack strong research and development capabilities, face challenges in innovation investment, and struggle to produce high-quality innovative results. To address these issues and overcome funding obstacles, many SMEs are turning to supply chain finance (SCF) as a supplementary financing method. This study utilizes stata16 and fixed effects models to analyze the impact and mechanism of SCF on enterprise innovation performance (EIP), focusing on companies listed on the SME Board and GEM in Shenzhen, China from 2011 to 2020. The findings reveal that SCF can effectively enhance enterprise innovation output, facilitating the conversion of resources into high-quality innovation results. Additionally, the study demonstrates that supply chain concentration acts as a mediator between SCF and EIP. Moreover, SCF is found to significantly boost EIP with low supplier concentrations and high customer concentrations. This suggests that SMEs encounter obstacles to innovation from suppliers and customers, and SCF may not fully address the challenges posed by these relationships. Overall, this research offers new empirical insights into the economic implications of companies adopting SCF, providing valuable guidance for enterprises in optimizing innovation decisions and for the government in enhancing supplier and customer information disclosure systems.

Indonesia, an emerging archipelagic nation, possesses abundant natural resources spanning marine, land (including forests and water sources), and diverse biological riches. The agricultural sector emerges as a pivotal driver of growth across the country, exhibiting extensive distribution. Consequently, there is an urgent imperative for comprehensive research to bolster and optimize the performance of this sector. This study aims to meticulously analyze and scrutinize macroeconomic variables aimed at enhancing Indonesia’s agricultural sector. Through the utilization of a dynamic panel model, the study zeroes in on crucial variables: economic growth in the agricultural sector, farmer terms of exchange, human development index, population density, inflation, average daily wages, and lagged economic growth data from each province in Indonesia. The best model for dynamic panel testing, employing both First Difference Generalized Method of Moments (FD-GMM) and Generalized Method of Moments System (SYS-GMM) approaches, is identified as the SYS-GMM model. This model exhibits unbiased and consistent estimation, as evidenced by the Arellano-Bond (AB) test and Sargan test results. The analysis conducted using this selected model reveals notable findings. Lagging agricultural sector performance, human capital measured by the Human Development Index (HDI), and farmers’ exchange rates are found to significantly and positively influence the economic growth of the agricultural sector. Conversely, inflation exerts a significant and negative impact on sectoral growth. However, wage levels and population density do not demonstrate a significant partial effect on the economic growth of the agricultural sector.

This research investigates the impact of modern technological methods of knowledge management (KM) and total quality management (TQM) on the performance of faculty members in educational colleges in Jordan. Drawing on a survey conducted with 306 faculty members, the study examines the influence of technology on teaching methodologies and academic quality within the Jordanian higher education context. The study utilizes the Technology Acceptance Model (TAM) to back up the modern technological methods of knowledge management (KM) and total quality management (TQM) models. The findings reveal a generally positive perception among respondents regarding the beneficial effects of modern technological tools on teaching effectiveness, collaboration, and innovation. Additionally, technology-enhanced TQM practices were found to contribute to improvements in curriculum design, student engagement, and administrative processes. Regression and correlation analyses support significant relationships between technology-enabled KM and TQM practices and faculty performance, highlighting the transformative role of technology in shaping the future of higher education in Jordan. Recommendations are provided for educational institutions to enhance the integration of technology and foster a culture of innovation and continuous improvement among faculty members.

The objective of this study was to examine the impact of utilizing smart algorithms on enhancing the operational performance of sports facilities in the Kingdom of Saudi Arabia. These algorithms, based on principles and concepts of artificial intelligence, aim to achieve functions such as learning, decision-making, data analysis, pattern recognition, planning, and problem-solving. The study aimed to identify the extent to which smart algorithms are utilized in sports facilities, assess the level of operational performance, explore the correlation between the use of smart algorithms and operational performance, and predict the level of operational performance based on the use of smart algorithms. The study employed a descriptive approach, specifically utilizing a survey study method. Participants included chairmen and members of boards of directors, executive directors, sports directors, administrators, specialists, and members of various committees. The study sample was intentionally selected from different categories within the study population. Two questionnaires were used to collect data from 325 participants. The findings revealed a lack of utilization of smart algorithms in sports facilities in the Kingdom of Saudi Arabia, indicating a low level of operational performance. Additionally, a correlation was observed between the use of smart algorithms and operational performance, suggesting that the level of operational performance can be predicted based on the utilization of smart algorithms. The study concludes that the implementation of intelligent algorithms can enhance the operational performance of sports facilities in the Kingdom of Saudi Arabia. It provides valuable insights into the effects of utilizing smart algorithms on improving operational performance.