This study investigates the impact of perceived innovative leadership on team innovation performance, with innovation climate acting as a mediating variable. A quantitative research approach, including a survey of team members across various industries, was used to collect data. Analysis through Structural Equation Modeling (SEM) reveals that perceived innovative leadership significantly positively influences team innovation performance, with innovation climate partially mediating this relationship. The findings emphasize the critical role of innovative leadership and a positive innovation climate in fostering organizational innovation, offering valuable insights for management practices. This paper also discusses the study’s limitations and provides directions for future research.

In the context of a globalized economic environment, businesses are facing an increasing number of environmental challenges, prompting them not only to pursue economic benefits but also to focus on environmental protection and social responsibility. Green supply chain management (GSCM) and green innovation have become key strategies for enterprises aiming for sustainable development. This study explores the impact of green supply chain practices on green innovation performance, with a focus on how knowledge management and organizational integration serve as mediating variables in this relationship. Grounded in the resource-based view (RBV) and knowledge-based view (KBV) theories, this research employs surveys and in-depth interviews with companies across various industries, combined with the analysis of structural equation modeling, to reveal the complex relationship between GSCM practices, knowledge management capabilities, levels of organizational integration, and green innovation performance. The results show that GSCM practices significantly enhance corporate green innovation performance through effective knowledge management and organizational integration. These findings enrich the theories of GSCM and green innovation, providing practical guidance for enterprises on how to enhance green innovation performance through strengthening knowledge management and organizational integration. Finally, this study discusses its limitations and suggests possible directions for future research, such as exploring the differences in findings across different industry backgrounds and examining other potential mediating or moderating variables.

The purpose of this research is to investigate the relationship between transformational leadership variables and organizational citizenship behavior (OCB) variables, investigate the relationship between job satisfaction variables and organizational citizenship behavior (OCB), and investigate the relationship between organizational commitment variables and organizational citizenship behavior (OCB). This research method uses quantitative methods. In this study, the researchers used a simple random sampling technique with a sample size of 368 SMEs employee. The data collection method for this research is by distributing an online questionnaire designed using a Likert scale of 1 to 7. The data analysis technique uses Partial Least Square—Structural Equation Modeling (PLS-SEM) and data analysis tools use SmartPLS software version 3.0. The stages of data analysis are validity testing, reliability testing and hypothesis testing. The independent variables in this research are transformational leadership, job satisfaction and organizational commitment, while the dependent variable is organizational citizenship behavior (OCB). The results of this research are that transformational leadership has a positive influence on organizational citizenship behavior (OCB), Job Satisfaction has a positive influence on organizational citizenship behavior (OCB) and organizational commitment has a positive influence on organizational citizenship behavior (OCB). The theoretical implications of this research support the results of previous research that transformational leadership, job satisfaction, and organizational commitment make a positive contribution to increasing organizational citizenship behavior in SME employees. The practical implication of this research is that SME owners apply transformational leadership, create work breadth and create organizational commitment within the SME organization to support increasing employee organizational citizenship behavior so that it can encourage increased performance and competitiveness of SMEs.

The purpose of this study is to examine the impact of tourist spending and the growth of Oman’s tourism industry on the country’s GDP from 1996 to 2018. The study uses the error correction model and other tests for assessing the link among variables, such as the cointegration test and the Granger causality test, to accomplish its aims. Findings from the error correlation model and cointegration test show that there is a link between the variables in Oman over the long and short term. There is a positive and statistically significant relationship between tourist expenditures and economic growth, as well as a negative and statistically significant relationship between tourism expansion and economic growth. We now use ARDL regression estimators to assess the robustness of the empirical results. There is no evidence of a direct relationship between increased tourism and GDP growth, according to the study’s results. According to the research, sustainable tourism development is an achievable economic growth driver, and Oman should prioritize economic policies that support this trend.

Integrated risk value response is designed to reduce threats and increase opportunities, especially in terms of running the spun pile method innovation process in accordance with the ISO 56002:2019 standard. Implementing innovation can reduce risks and increase the competitiveness of the company. The method of making or producing spun piles is the research area examined in this study. Questionnaires were distributed to workers in precast concrete companies and most of them were involved in each spun pile production line in the company in order to identify the risk factors that existed in the production line for the spun pile manufacturing method. 30 respondents were workers from organizations in the positions of Director, Manager and Staff. The risk values and impacts are mapped for each dimension to the activity details and it is found that there are 5 high risks as dominant ones, mainly risks with codes R41, R10, R4, R37, and R36. Based on a survey, the highest risk of 30% was found in the stressing & spinning dimension, which is recommended for the innovation process. Innovation is conducted with 5 innovation processes, mainly identifying opportunities, creating concepts, validating concepts, developing solutions, and deploying solutions. Recommendations for improvements are made with preventive and corrective actions that must be taken from every aspect of the spun pile production method activities. Innovation recommendations are also proposed to monitor production activities in real-time utilizing existing information and communication technology. Handling of spun pile waste material must also be implemented with certain methods and produce products that add value for the company. Ultimately, to increase the company’s competitiveness by increasing assets, it is recommended to increase the company’s intangible assets. The company’s intangible assets encompass IPR ownership in the form of Patents and Copyrights.

This study aims to explore the relationship between classroom anxiety and self-efficacy among Chinese Korean language learners and the impact of these variables on learning outcomes. Utilizing a quantitative research approach, the study conducted a questionnaire survey with 300 learners to assess their levels of Korean language learning classroom anxiety and self-efficacy. The questionnaire comprised two parts: one for assessing learning anxiety and the other for self-efficacy. Data were analyzed using descriptive statistical analysis, Pearson correlation coefficients, and multiple regression analysis. The results indicate a significant negative correlation between classroom anxiety and self-efficacy. That is, higher levels of classroom anxiety in Korean language learners correspond to lower levels of self-efficacy. Additionally, self-efficacy played a partial mediating role between classroom anxiety and learning outcomes. The study also found that teaching strategies offering positive feedback and encouragement can effectively reduce learners’ classroom anxiety and enhance their self-efficacy, thereby improving learning outcomes. This research is significant for understanding the psychological characteristics of Chinese Korean language learners and their impact on the learning process. The findings underscore the need to focus on learners’ psychological states in language teaching and provide strategies for teachers on how to improve teaching effectiveness by alleviating classroom anxiety and enhancing self-efficacy.

This study is about the influence of ethical leadership in both employees wellbeing and employee performance in Egypt’s tourism industry. Besides, it examines the indirect effect of ethical leadership on performance through its influence on the well-being of employees. The research was based on a quantitative research method and the surveys were self-administered, distributed and collected from a random sample of the employees of the Tourism companies. Analysis of 515 valid responses using structural equation modeling (SEM) unveiled several key findings: Ethical leadership is the main reason why both employee well-being and performance are significantly increased, and the fact that employee well-being is also the main reason for the improvement of performance. In addition, the employee well-being plays the role of the bridge between the ethical leadership and the performance. These insights are of great help for the decision-makers in the crafting of the effective leadership strategies that will lead to the creation of the thriving and high-performed work environments in Egyptian tourism sector.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.