The recent development of characteristic towns has encountered a multitude of challenges and chaos. Nevertheless, there have been many instances of information asymmetry due to the absence of an effective management model and an intuitive digital management system. Consequently, this has caused the erosion of public interests and inadequate supervision by public agencies. As society is progressing at a rapid pace, there is a growing apprehension regarding poor management synergy, outdated management practices, and limited use of technology in traditional construction projects. In today's technologically sophisticated society characterized by the “Internet+” and intelligent management, there is an urgent requirement to identify a more efficient collaborative management model, thereby reducing errors caused by information asymmetry. This paper focuses on the integration of building information modeling (BIM) and integrated project delivery (IPD) for collaborative management within characteristic towns in the PPP mode. By analyzing the available literature on the application status, this study investigates the implementation methods and framework construction of collaborative management while exploring the advantages and disadvantages. On this basis, this study highlights the problems that arise and provides recommendations for improvement. Considering this, the application of the BIM-based IPD model to characteristic towns in PPP mode will enhance the effectiveness of collaborative management among all parties involved, thereby fostering an environment that facilitates decision-making and operational management in the promotion of characteristic industries.

The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.

The Sustainable Development Goals (SDGs) can be viewed as the aftermath of the Millennial Development Goals (MDGs). This is due to the fact that the seventeen (17) SDGs are designed to continue the work expected to have been done by the MDGs. In other words, the failure of the MDGs to eradicate poverty birthed the SDGs. However, the SDGs seem not to be achieving the desired result. This has led to the projection for the need for a decade of action. In the African context, the questions of why the MDGs failed and the SDGs tend to be failing are yet to be asked. By projection, if the questions are not asked and answers are not provided, the projection of the decade of action may also fail. Hence, the reason for this conceptual paper which was targeted at exploring the possibility of considering the Africanization of the SDGs as remedy to ensuring sustainable development in the African continent. Different relevant sources were identified, reviewed and analysed. The findings from the reviewed and analysed sources showed among others that for Africanization of the SDGs to be a reality and practicable, glocalization must be embraced. Meanwhile, there will be need to question the use of Eurocentric curricula in African institutions of learning.

The construction industry is responsible for over 40% of global energy consumption and one-third of global greenhouse gas emissions. Generally, 10%–20% of energy is consumed in the manufacturing and transportation stages of materials, construction, maintenance, and demolition. The way the construction industry to deal with these impacts is to intensify sustainable development through green building. The author uses the latest Green Building Certification Standard in Indonesia as the Green Building Guidelines under the Ministry of Public Works and People’s Housing (PUPR) Regulation No. 01/SE/M/2022, as a basis for evaluating existing office buildings or what is often referred to as green retrofit. Structural Equation Modeling-Partial Least Squares (SEM-PLS) is used by the authors to detail the factors influencing the application of green building by analyzing several variables related to the problem studied, which are used to build and test statistical models of causal models. From this study, it is concluded that the most influential factors in the implementation of green retrofitting on office buildings are energy savings, water efficiency, renewable energy use, the presence of green building socialization programs, cost planning, design planning, project feasibility studies, material cost, use of the latest technology applications, and price fluctuations. With the results of this research, there is expected to be shared awareness and concern about implementing green buildings and green offices as an initiative to present a more energy-efficient office environment, save operating costs, and provide comfort to customers.

This study provides an evaluation of the environmental impact and economic benefits associated with the disposal of mango waste in Thailand, utilizing the methodologies of life cycle assessment (LCA) and cost-benefit analysis (CBA) in accordance with internationally recognized standards such as ISO 14046 and ISO 14067. The study aimed to assess the environmental impact of mango production in Thailand, with a specific focus on its contribution to global warming. This was achieved through the application of a life cycle assessment methodology, which enabled the determination of the cradle-to-grave environmental impact, including the estimation of the mango production’s global warming potential (GWP). Based on the findings of the feasibility analysis, mango production is identified as a novel opportunity for mango farmers and environmentally conscious consumers. This is due to the fact that the production of mangoes of the highest quality is associated with a carbon footprint and other environmental considerations.  Based on the life cycle assessment conducted on conventional mangoes, taking into account greenhouse gas (GHG) emissions, it has been determined that the disposal of 1 kg of mango waste per 1 rai through landfilling results in an annual emission of 8.669 tons of carbon. This conclusion is based on comprehensive data collected throughout the entire life cycle of the mangoes. Based on the available data, it can be observed that the quantity of gas released through the landfilling process of mango waste exhibits an annual increase in the absence of any intervening measures. The cost benefit analysis conducted on the life cycle assessment (LCA) of traditional mango waste has demonstrated that the potential benefits derived from its utilization are numerous. The utilization of the life cycle assessment (LCA) methodology and the adoption of a sustainable business model exemplify the potential for developing novel eco-sustainable products derived from mango waste in forthcoming time.