This paper aims to explain the administrative and the Environmental, Social and Governance (ESG) of the Indonesian Spaceport Project in Biak, Papua, Indonesia, under the Public-Private Partnerships (PPP) scheme, particularly from the protest to fear of environmental damage and traditional rights. This paper analyzes the factors that cause the local society’s reluctance to accept the development of Indonesia’s very first commercial spaceport. This paper uses a doctrinal methodology, which examines changes in the trend of ESG in implementing PPP projects. The method used is a qualitative systematic review of national and international studies. This paper finds that the lack of legal certainty for administrative and ESG as the main factor contributing to the pitfall of the PPP project in Biak Papua. No clear Government Contracting Agency (GCA), plus the fact that the Indonesian government puts too much weight on business consideration in PPP while Papuan people need more ESG, especially considering the historical conflict in the region, has been the epicenter of the problem. Given the ESG-PPP regulatory failure of spaceport development in Biak, more focused studies using comparative study methodology are needed to propose a more robust and customized ESG in PPP regulations in a politically and historically sensitive area. The authors forward a regulatory reform to balance administration, ESG, and business considerations in PPP projects for a spaceport.

Given the growing significance of the metaverse in research, it is crucial to understand its scope, relevance in the tourism industry, and the human-computer interaction it involves. The emerging field of metaverse tourism has a noticeable research gap, limiting a comprehensive understanding of the concept. This article addresses this gap by conducting a hybrid systematic review, including a variable-oriented literature review, to assess the extent and scope of metaverse tourism. A scrutiny on Scopus identified a reduced number of relevant documents. The analysis exposes theoretical and empirical gaps, along with promising opportunities in the metaverse and tourism intersection. These insights contribute to shaping a contemporary research agenda, emphasizing metaverse tourism. While this study offers an overview of current research in metaverse tourism, it is essential to recognize that this field is still in its early stages, marked by the convergence of technology and transformations in tourism. This exploration underscores the challenges and opportunities arising from the evolving narrative of metaverse tourism.

Environmental Education (EE) programs are of crucial importance. EE are aimed at global citizenship to generate new knowledge and new, more participatory and conscious ways of acting in the environment. This study, therefore, wants to verify the effectiveness of a training intervention that is based on education on climate change issues and on the active participation of subjects in the dimension of the small psychological group. At the intervention 309 students took part, equally distributed by gender (52.1% males), 64.4% enrolled in primary school, 35.6% enrolled in lower secondary school. A quantitative protocol was administered to evaluate the effectiveness of the intervention. The study shows an increase in pro-environmental behaviors and their stability even after 15–30 days. The intervention seems to be effective in triggering pro-environmental behaviors and maintaining them in the following weeks. The results of this study highlight the need to develop environmental education pro-grams in schools to increase levels of knowledge and awareness on the issue of climate change.

Amidst China’s burgeoning population and rapid technological strides, this study explores how elderly citizens navigate and embrace electronic governance (e-governance) platforms. Addressing a crucial gap in knowledge, we delve into their limited digital fluency and its impact on e-governance adoption. Our meticulously crafted online survey, distributed via WeChat across significant cities (Beijing, Shanghai, Tianjin, Changsha), yielded 396 responses (384 analyzable). Utilizing Structural Equation Modeling (SEM), we unearthed key influencers of subjective norms, including perceived ease and usefulness, trust, supportive conditions, and past tech exposure. These norms, in turn, positively shape attitudes. Crucially, educational background emerges as a moderator, amplifying the positive link between attitudes and e-governance engagement intent. This underscores the necessity of an inclusive, customized e-governance approach, offering valuable policy insights and advocating for holistic solutions for older adults. Our research yields empirical and theoretical contributions, paving the way for actionable Social Sustainability Marketing Technologies in China, particularly championing digital inclusivity for seniors.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.