Enhancing the emphasis on incorporating sustainable practices reinforces a linear transition towards a circular economy by organizations. Nevertheless, although studies on circular economy demonstrate an increasing trend, the drivers that support circular economy practices towards sustainable business performance in the Small and Medium-Sized Enterprise (SME) sector, especially in developing nations, demand exploration. Accordingly, the study examines circular economy drivers, i.e., green human resource management, in establishing sustainability performance and environmental dynamism as moderating variables. The study engaged 207 SMEs and 621 respondents who were analyzed utilizing structural equation modeling. The analysis indicated that sustainable business performance was affected by green human resource management and a circular economy. Subsequently, the circular economy mediated the linkage between green human resources management and sustainable business performance. The environmental dynamism moderated the linkage between green human resources management and the circular economy.

Plant growth-promoting rhizobacteria (PGPR) offer eco-friendly alternatives to chemical fertilizers, promoting sustainable agriculture by enhancing soil fertility, reducing pathogens, and aiding in stress resistance. In agriculture, they play a crucial role in plant growth promotion through the production of agroactive compounds and extracellular enzymes to promote plant health and protection against phytopathogens. In the rhizosphere, diverse microbial interactions, including those with bacteria and fungi, influence plant health by production of antimicrobial compounds. The antagonism displayed by rhizobacteria plays a crucial role in shaping microbial communities and has potential applications in developing a natural and environmentally friendly approach to pest control. The rhizospheric microbes showcase their ecological importance and potential for biotechnological applications in the context of plant-microbe interactions. The extracellular enzymes produced by rhizospheric microbes like amylases, chitinases, glucanases, cellulases, proteases, and ACC deaminase contribute to plant processes and stress response emphasizing their importance in sustainable agriculture. Moreover, this review highlights the new paradigm including artificial intelligence (AI) in sustainable horticulture and agriculture as a harmonious interaction between ecological networks for promoting soil health and microbial diversity that leads to a more robust and self-regulating agricultural system for protecting the environment in the future. Overall, this review emphasizes microbial interactions and the role of rhizospheric microbial extracellular enzymes which is crucial for developing eco-friendly approaches to enhance crop production and soil health.

This study simultaneously examined the linkages among environmental dynamism, three dynamic capabilities, and the competitive advantages of retail businesses, which have not been identified before. Furthermore, this study fills the significant gaps in the literature and practical guidelines for retail development through improving retailer’s dynamic capabilities in response to environmental dynamism. The study used a quantitative approach by partial least squares SEM (PLS-SEM) to examine the hypotheses. Data were collected from 304 Vietnamese retail business managers. The results show that environmental dynamism plays a significant role in fostering the improvement of retailers’ dynamic capabilities. The findings also reveal positive linkages among the three dynamic capabilities before they significantly improve retailers’ competitive advantage. These are the valuable guidelines for retailers to nurture their dynamic capabilities, including service innovation capabilities, multi-channel integration, and brand orientation for sustaining their competitive advantages.

This research presents a comprehensive model for enhancing the road network in Thailand to achieve high efficiency in transportation. The objective is to develop a systematic approach for categorizing roads that aligns with usage demands and responsible agencies. This alignment facilitates the creation of interconnected routes, which ensure clear responsibility demarcation and foster efficient budget allocation for road maintenance. The findings suggest that a well-structured road network, combined with advanced information and communication technology, can significantly enhance the economic competitiveness of Thailand. This model not only proposes a framework for effective road classification but also outlines strategic initiatives for leveraging technology to achieve transportation efficiency and safety.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.