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.

Infrastructure development is critical for sustaining Asia’s economic growth. Unfortunately, huge financing gaps—estimated by a recent Asian Development Bank study to be USD22.5 trillion—constrain the ability of most emerging Asian countries to fully realize the benefits of infrastructure development. For instance, over 70% of infrastructure investments in Asia are still funded by public resources, which pose acute financing challenges for many countries with limited budgets and fiscal constraints. This paper discusses some of the challenges associated with public financing of infrastructure projects in emerging Asian countries, before introducing some new options for alleviating their infrastructure investment needs. In particular, it proposes a new approach to infrastructure financing by utilizing the spillover effects of infrastructure investment, where additional revenues generated from such investment can be channeled back to investors as subsidy to increase the returns to their investment. The paper also argues the need for Asian countries to implement fiscal reforms and to develop a more balanced approach to financing, one that involves both the private and public sector. 

The high unemployment rate among university graduates is prompting universities to enhance the business skills of their students. This research aims to holistically explain the role of university support and entrepreneurial resilience in increasing students’ business innovation capabilities. To analyze phenomena and relationships between variables, a quantitative approach using partial least square structural equation modeling (PLS-SEM) was used. This research sample involved 165 student entrepreneurs who are members of the student entrepreneur community in Indonesia. Knowledge management does not significantly impact increasing business innovation capabilities. However, perceived university support and entrepreneurial resilience have been shown to significantly impact business innovation capabilities and strengthen the influence of knowledge management activities on increasing business innovation capabilities. Universities must create policies supporting extracurricular entrepreneurship programs, focusing on building entrepreneurial resilience. This can be achieved through workshops and business incubator initiatives involving partnerships with industry and the entrepreneurial community. This research provides a new perspective in analyzing higher education entrepreneurship education through a more in-depth explanation of the extracurricular activities of the student business community to build business innovation capabilities based on knowledge, institutional, and trait theory perspectives.

This research seeks to identify the value of a few common factors determining the speed of economic growth in Baltic states and analyzes their impact in detail on Latvia’s lagging. Latvia’s economic starting point after regaining independence because of the collapse of the Soviet Union was at least comparable to its neighbors. Still, after the implementation of liberal reforms towards a free market’ economy and 20 years of operation as an EU full member, Latvia is lagging in growth, prosperity, and innovation. Within the analysis, this scientific paper pays special attention to the three less discussed factors, namely, the impact of post-Soviet mind-set effects as a part of local innovation culture, lasting since regaining independence in 1991; the importance of the availability of talent pull, its density, diversity, and accessibility; and readiness and capability to capture external knowledge and technology adoption. The overall approach is the systemic assessment of the national innovation system and/or innovation ecosystem, trying to understand the differences between these two models. Research is performed by analysis of the performance of the local innovation ecosystem in connection with export- and Foreign Direct Investment (FDI) policies. The authors present a novel method for visually representing economic growth and its application in analyzing process development within transitional economic nations. The study uses an analytical and synthetical literature review. It offers a new GDP data visualization method useful for monitoring economic development and forecasting potential economic crises—the outcomes from aggregative literature analysis in a consolidated concept are provided for required talent policy proposals. The post-Soviet mindset is seen as a heritage and devious underdog that has left incredibly diverse consequences on today’s society, power structures, economic growth potential, and the emergence of healthy, well-managed, and sustainable innovation ecosystems. The post-Soviet mindset is a seemingly hidden and, at the same time, an intriguing factor that has a significant impact on the desire to make and implement the right decisions related to innovation, education, and other policies promoting business development. The key outcome of the article is that sociocultural aspects and differences in innovation culture led to a slow-down of Latvia’s economic growth compared to Estonia’s and Lithuania’s slightly more successful economic reforms.

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.

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.