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 case study employs the Asset-Based Community Development (ABCD) theory as a conceptual framework, utilizing semi-structured interviews combined with focus group discussions to uncover the driving forces influencing rural revitalization and sustainable development within communities. ABCD is considered a transformative approach that emphasizes achieving sustainable development by mobilizing existing resources within the community. Conducted against the backdrop of rural revitalization in China, the study conducts on-site investigations in Yucun, Zhejiang Province. Through the analysis of Yucun’s community development and asset utilization practices, the study reveals successful experiences in various aspects, including community construction, industrial development, cultural heritage preservation, ecological conservation, organizational management, and open economic thinking. The results indicate that Yucun’s sustainable development benefits from its unique resources, leveraging policy advantages, collective financial organizations, and open economic thinking, among other factors. These elements collectively drive rural revitalization in Yucun, leading to sustainable development.

Small-scale businesses have long been recognized as an important part of economic development and integrating them with industrial parks is both recommended and necessary for long-term success. In line of this, the objective of this study was to investigate the role of IPs entrepreneurial ecosystem in boosting the capabilities of small businesses. Data were collected from 245 small manufacturing business owners via simple random sampling and analysed using multivariate regression analysis. Thus, the ability of small enterprises is positively impacted by the presence of a more robust and appropriate entrepreneurial ecosystem. Similarly, a firm’s resource capabilities are more impacted by the entrepreneurial ecosystem when there is a better link between academia and industry. Furthermore, entrepreneurial skills are found to play a mediating role between the entrepreneurial ecosystem and firms’ technological capabilities. Another finding revealed that managerial expertise significantly mediates entrepreneurial ecosystems and firms’ resource capabilities. This finding suggested that the policymakers, better to formulate policies that encourages small businesses to engage in the industrial parks which results in an inclusive firm’s performance.

Cobalt-ion batteries are considered a promising battery chemistry for renewable energy storage. However, there are indeed challenges associated with co-ion batteries that demonstrate undesirable side reactions due to hydrogen gas production. This study demonstrates the use of a nanocomposite electrolyte that provides stable performance cycling and high Co²⁺ conductivity (approximately 24 mS cm⁻¹). The desirable properties of the nanocomposite material can be attributed to its mechanical strength, which remains at nearly 68 MPa, and its ability to form bonds with H₂O. These findings offer potential solutions to address the challenges of co-dendrite, contributing to the advancement of co-ion batteries as a promising battery chemistry. The exceptional cycling stability of the co-metal anode, even at ultra-high rates, is a significant achievement demonstrated in the study using the nanocomposite electrolyte. The co-metal anode has a 3500-cycle current density of 80 mA cm⁻², which indicates excellent stability and durability. Moreover, the cumulative capacity of 15.6 Ah cm⁻² at a current density of 40 mA cm⁻² highlights the better energy storage capability. This performance is particularly noteworthy for energy storage applications where high capacity and long cycle life are crucial. The H₂O bonding capacity of the component in the nanocomposite electrolyte plays a vital role in reducing surface passivation and hydrogen evolution reactions. By forming strong bonds with H₂O molecules, the polyethyne helps prevent unwanted reactions that can deteriorate battery performance and efficiency. This mitigates issues typically associated with excess H₂O and ion presence in aqueous Co-ion batteries. Furthermore, the high-rate performance with excellent stability and cycling stability performance (>500 cycles at 8 C) of full Co||MnO₂ batteries fabricated with this electrolyte further validates its effectiveness in practical battery configurations. These results indicate the potential of the nanocomposite electrolyte as a valuable and sustainable option, simplifying the development of reliable and efficient energy storage systems and renewable energy applications.

Due to the lack of clear regulation of management accounting at the state level in Russia, the authors conducted a study based on an analysis of information sources, an expert survey on their reliability, and a case method, which resulted in a reporting form compiled for the production process of an agro-industrial enterprise (grain products) as part of inter-organizational company cooperation. The developed management reporting system (composed of eight consecutive stages: standard reports, specialized reports, itemized query reports, notification reports, statistical reports, prognostic reports, modeling results reports, and process optimization reports), on one hand, allows solving a set of tasks to increase the competitiveness of Russian agro-industrial enterprises within the framework of inter-organizational management accounting. On the other hand, the introduction of ESG principles into the management reporting system (calculation of the environmental (E) index, which assesses the company’s impact on the natural ecosystem and covers emissions and efficient use of natural resources in the agricultural production process) increases the level of control and minimizes the risks of an unfair approach of individual partners to environmental issues.

Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).