Biomimicry is increasingly being used to drive sustainable constructional development in recent years. By emulating the designs and processes of nature, biomimicry offers a wealth of opportunities to create innovative and environmentally friendly solutions. Biomimicry in industrial development: versatile applications, advantages in construction. The text emphasizes the contribution of bio-mimetic technologies to sustainability and resilience in structural design, material selection, energy efficiency, and sensor technology. Aside from addressing technical constraints and ethical concerns, we address challenges and limitations associated with adopting biomimicry. A quantitative research approach is implemented, and respondents from the construction industry rank biomimicry principles as the optimal approach to enhance sustainability in the industry. Demographic and descriptive analyses are underway. By working together, sharing knowledge, and innovating responsibly, we suggest approaches to tackle these obstacles and fully leverage the transformative power of biomimicry in promoting sustainable construction industry practices. In an evolving global environment, biomimicry reduces environmental impact and enhances efficiency, resilience, and competitiveness in construction industries.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

Urban infrastructures and services—such as public transportation, innovation bodies and environmental services—are important drivers for the sustainable development of our society. How effectively citizens, institutions and enterprises interact, how quickly technological innovations are implemented and how carefully new policies are pursued, synergically determine development. In this work, data related to urban infrastructure features such as patents and recycled waste referred to 106 province areas in Italy are investigated over a period of twenty years (2001–2020). Scaling laws with exponents characterizing the above mentioned features are observed and adopted to scrutinize whether and how multiple interactions within a population have amplification effects on the recycling and innovation performance. The study shows that there is a multiplication effect of the population size on the innovation performance of territories, meaning that the dynamic interactions among the elements of the innovation eco-systems in a territory increase its innovation performance. We discuss how to use such approach and the related indexes for understanding metropolitan development policy.

Housing is one of the most significant components of sustainable development; hence, the need to come up with sustainable housing solutions. Nevertheless, the sales of houses are steadily falling due to the unaffordability of houses to many people. Based on the expanded community acceptance model, this research examines the relationships between sustainable housing and quality of life with the moderating factors of knowledge, technology, and innovation in Shenzhen. Additionally, it aims to delineate the principal dimensions influencing quality of life. The study employs purposive sampling and gathers data from residents of Shenzhen via a Tencent-distributed survey. Analysis was conducted using Smart Partial Least Squares (PLS) 4.0. Results indicate a positive correlation between economic sustainability in housing and quality of life. Contrarily, the social and environmental aspects exhibited negligible impacts on quality of life. Knowledge, technology, and innovation were identified as significant moderators in the correlation among all three sustainable housing dimensions and quality of life. The findings are anticipated to enhance understanding of the perceived impacts of sustainable housing on quality of life in Shenzhen and elucidate the role of knowledge, technology, and innovation in fostering this development.

Current study examines the intervening role of team creativity for the relationship of four kinds of KM practice with innovation and the moderating effect of proactiveness in IT companies based on a Knowledge-Based View (KBV). Data was collected from 316 employees of IT companies who engage in software development in teams with the help of a simple random sampling method. Results indicate that KM practices have a positive impact on innovation. Also, team creativity plays mediating role in the relation of two KM practices i.e., knowledge sharing and knowledge application with innovation. Whereas proactiveness plays a positive moderating role in the relation of knowledge application and knowledge generation with innovation. Moreover, it plays a negative moderating role in relation of Knowledge sharing with innovation. This research adds to the body of literature by suggesting a framework of knowledge diffusion, knowledge storage, knowledge generation, knowledge application, team creativity, proactiveness, and innovation in a single model. This research also adds to the body of literature by proposing the intervening role of team creativity in the relationships of knowledge diffusion, knowledge storage, knowledge generation, and knowledge application, with innovation. The results of this research help the managers to use the team creativity concept to intervene in relation of knowledge diffusion, knowledge storage, knowledge generation, and knowledge application, with innovation. The results of the current study also give valuable insights to managers into why they can use the proactiveness to moderate the relations of knowledge diffusion, knowledge storage, knowledge generation, and knowledge application, with innovation. Current study adds in the body of literature by proposing the entire manuscript on the basis of two theories i.e., Knowledge-Based View (KBV) builds on and expands the RBV.

This research aims to determine and analyze the extent of the influence of community empowerment and sustainability-oriented innovation on sustainable performance through coworking spaces in the city of Bandung. To achieve the research objectives, a deductive approach is employed, intending to test a hypothesis to strengthen or reject existing hypotheses. Therefore, this research is also categorized as explanatory research. The research method used is the survey research method. The research sample is determined based on proportional stratified random sampling. This study focuses on business groups in coworking spaces in the 28 districts of Bandung City, with a total of 408 business operators. The sample selected consists of 208 business operators. Based on the research results, several conclusions are drawn, as follows: (1) Community empowerment has a significantly positive influence on sustainability performance, with a contribution of 84.5%; (2) Sustainability-oriented innovation has a significantly positive influence on sustainability performance, with a contribution of 69.2%; (3) Community empowerment has a significantly positive influence on Coworking Space, with a contribution of 93.6%; (4) Sustainability-oriented innovation has a significantly positive influence on Coworking Space, with a contribution of 36%; (5) Community empowerment has a significantly positive influence on sustainability-oriented innovation, with a contribution of 90.6%; (6) Coworking Space has a significantly positive influence on sustainability performance, with a contribution of 34%; (7) Community empowerment has a significantly positive influence on sustainability performance through Coworking Space, with a contribution of 20.7%; and (8) Sustainability oriented innovation has a significantly positive influence on sustainability performance through Coworking Space, with a contribution of 12.2%.