To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

This study examines the impact of innovation governance and policies on government funding for emerging science and technology sectors in Saudi Arabia, addressing key bureaucratic, regulatory, and cultural barriers. Using a mixed-methods approach, the research integrates qualitative insights from stakeholder interviews with quantitative survey data to provide a comprehensive under-standing of the current innovation landscape. Findings indicate a high level of policy awareness among stakeholders but reveal significant challenges in practical implementation due to bureaucratic inefficiencies and stringent regulations. Cultural barriers, such as a risk-averse mindset and traditional business practices, further impede innovation. Successful initiatives like the National Transformation Program (NTP) demonstrate the potential for well-coordinated efforts, highlighting the importance of regulatory reform and cultural shifts towards entrepreneurship. Strategic recommendations include streamlining bureaucratic processes, enhancing policy coordination, and fostering a culture of innovation through education and stakeholder engagement. This study contributes to the existing literature by offering actionable insights to enhance innovation governance, supporting Saudi Arabia’s Vision 2030 goals.

This study analyzes the interaction between legitimacy, innovation, uncertainty, and electric vehicle (EV) purchase intention in Spain, Portugal, Italy, and Greece. Using partial least squares structural equation modeling (PLS-SEM) and data from 2016 to 2023, the relationships between these key variables are assessed. The results show that legitimacy has a positive impact on purchase intention, while innovation influences legitimacy but does not directly affect purchase intention. Uncertainty moderates these relationships in complex ways. The findings suggest that enhancing the perception of legitimacy is crucial to increase EV purchase intention, and strategies promoting innovation and managing uncertainty can improve market acceptance.

This study explored the relationship between Chinese graduate students’ English language proficiency (ELP) and intercultural communicative competence (ICC). With the acceleration of globalization, an increasing number of Chinese students choose to study abroad, making it crucial to enhance their intercultural communication ability and language skills. However, China’s exam-oriented education system to some extent limits students’ holistic development and poses challenges for them in intercultural exchange. A quantitative survey method was employed, collecting questionnaire data from 249 Chinese English-major graduate students to analyze the relationship between their English ability and intercultural competence. The results indicated a certain positive correlation between English proficiency and intercultural competence but also pointed to the need for further unpacking of complexity and influencing factors. Future research with more robust methodology is still warranted to provide deeper insights into the linkage between the two constructs in the Chinese graduate context.

This study aims to examine the impact of open innovation and disruptive innovation on the financial performance of SMEs in the tourism sector in Tanjungpinang City, Indonesia. A quantitative research method was employed, utilizing a sample of 273 SMEs in the tourism sector. Data were collected through surveys and analyzed using regression and ANOVA techniques to understand the relationships between innovation, digitalization, and financial performance. The analysis revealed that both open and disruptive innovation significantly influence the financial performance of SMEs. The study found that innovation and digitalization explain approximately 79.6% of the financial performance variance in the tourism sector. The findings suggest that SMEs that adopt innovative practices and digitalization are more likely to achieve better financial outcomes, such as increased profitability and market share. Open and disruptive innovations are critical drivers of financial success for SMEs in the tourism sector. SMEs should focus on leveraging internal and external knowledge and adapting to technological changes to enhance their competitive advantage. Policymakers should create supportive environments that foster innovation and digitalization among SMEs. This could include providing access to technological resources, training programs, and incentives for innovative practices.

State-owned enterprises (SOEs) manage significant portion of world economy, including in the developing countries. SOEs are expected to be active and play significant role in improving the country’s economic performance and welfare through enhancing innovation performance. However, closed innovation process and lack of collaboration hinders SOEs to reach satisfying innovation performance level. This paper explores the construction and role of innovation ecosystem in the strategic entrepreneurship process of SOEs, of which is represented by dynamic capability framework, business model innovation, and collaborative advantage. Based on the analysis, this paper concluded that the collaboration between actors in the Innovation Ecosystem (IE) has positive effect to strengthening SOE’s Sensing Capabilities (SC) related to the process of exploring and identifying innovation opportunities. The increase of Sensing Capabilities (SC) will play significant role as input or antecedent on formulating proactive Innovation Strategy (IS) in orchestrating SOE’s innovation process. SOEs which has implementing proactive Innovation Strategy (IS) will be able to build collaboration and finding right Business Model Innovation (BMI). Finally, by building collaboration with other actors through the innovative business model has significant role to increase SOE’s Collaborative Advantage (CA), which considered as a proxy for competitiveness of SOEs.