This study investigates the willingness of Indonesian consumers, particularly in West Java, to pay for green products by applying and expanding the Theory of Planned Behavior (TPB). It examines how perceived green product value and willingness to pay premiums influence consumer intentions and behavior toward green purchases. The research highlights the gap between consumers’ willingness to pay for environmentally friendly products and the actual sales of such products. By incorporating perceived value and willingness to pay into the TPB framework, the study aims to find what factors that can address the gap particularly in a developing country context to contribute to shaping a pro-environmental socio-cultural community in Indonesia and mitigates country’s significant environmental challenges. In the context of 251 young consumers in Indonesia, this study finds that subjective norms do not significantly influence purchase intentions. However, attitudes and behavioral controls do effectively encourage green behavior, suggesting that societal norms for green behavior may not be fully established. In addition, while willingness to pay a premium and perceived value of green purchases can influence green behavior, consumers are generally reluctant to pay higher prices for environmentally friendly products.

Many studies have called for more research and increased knowledge about Family Businesses (FB), notably their sustainability. This work aims to reduce this limitation through a narrative literature review and thus contribute to knowledge about FB’s compliance and sustainability design. The results suggest that interest in sustainability practices is growing but still low, and implementation is challenging. This work presents scientific contributions, notably to the Theories of Vision Based on Resources, Dynamic Capabilities, and Stewardship. At the same time, it contributes to the operationalization of FB, as they can design their sustainability practices and compliance strategies similar to those of others. The value of this work culminates in the original proposal of a framework identifying the leading information representative of the main challenges for the sustainability of FB.

Sustainability has turned into a critical focus for businesses, drawing considerable interest from the commercial sector and scholarly environments. While empirical investigations have been conducted regarding sustainability reporting within small and medium enterprises, only a limited number of companies are subjected to increased pressure to adopt sustainability reporting practices, thereby ensuring enhanced transparency and disclosure in their financial and sustainability disclosures. This research, framed by Institutional Theory, delves into how challenges in sustainability reporting obstruct organizations from properly evaluating and sharing their progress on sustainability aims. With an explanatory research framework in place, we circulated survey questionnaires to 400 participants, who were randomly drawn from a population of 28,927 registered SMEs in Metro Manila, Philippines. The application of Interpretative Structural Modelling and MICMAC Analysis revealed that the absence of regulatory frameworks, governmental assistance, and sustainability infrastructure constitutes the most critical obstacles impacting other determinants. In contrast, neither the deficiency in sustainability awareness nor the inadequacy of training and skills demonstrated a considerable impact on the other identified barriers. This study clarifies the complex interactions and interrelations among the obstacles to sustainability reporting, thus providing significant perspectives for organizations aiming to overcome these difficulties. The findings suggest that business leaders and stakeholders can formulate targeted strategies and interventions to facilitate the adoption of sustainability reporting practices within organizations. The application of the institutional theory framework highlights that pressures arise from a diverse array of institutional actors, including regulators, customers, and local communities, which collectively shape corporate behavior and reporting methodologies.

The destructive geohazard of landslides produces significant economic and environmental damages and social effects. State-of-the-art advances in landslide detection and monitoring are made possible through the integration of increased Earth Observation (EO) technologies and Deep Learning (DL) methods with traditional mapping methods. This assessment examines the EO and DL union for landslide detection by summarizing knowledge from more than 500 scholarly works. The research included examinations of studies that combined satellite remote sensing information, including Synthetic Aperture Radar (SAR) and multispectral imaging, with up-to-date Deep Learning models, particularly Convolutional Neural Networks (CNNs) and their U-Net versions. The research categorizes the examined studies into groups based on their methodological development, spatial extent, and validation techniques. Real-time EO data monitoring capabilities become more extensive through their use, but DL models perform automated feature recognition, which enhances accuracy in detection tasks. The research faces three critical problems: the deficiency of training data quantity for building stable models, the need to improve understanding of AI's predictions, and its capacity to function across diverse geographical landscapes. We introduce a combined approach that uses multi-source EO data alongside DL models incorporating physical laws to improve the evaluation and transferability between different platforms. Incorporating explainable AI (XAI) technology and active learning methods reduces the uninterpretable aspects of deep learning models, thereby improving the trustworthiness of automated landslide maps. The review highlights the need for a common agreement on datasets, benchmark standards, and interdisciplinary team efforts to advance the research topic. Research efforts in the future must combine semi-supervised learning approaches with synthetic data creation and real-time hazardous event predictions to optimise EO-DL framework deployments regarding landslide danger management. This study integrates EO and AI analysis methods to develop future landslide surveillance systems that aid in reducing disasters amid the current acceleration of climate change.

One of the most frequently debated subjects in international forums is economic growth, which is regarded as a global priority. Consequently, researchers have turned their attention from conventional economic growth at a single average coefficient to divisible economic growth at levels of its value. Although the existing literature has discussed several determinants of economic growth, our article contributes to examining the sources of economic growth in African countries during the generations of reforms from 1990 to 2019 and in the context of economic vulnerability. The variables used in the analysis are gross domestic product, trade openness, financial development, and economic vulnerability. The study uses a quantile regression econometric model to examine these variables at different stages of reform. Quantile regression (QR) estimates for quantiles 0.05 to 0.95 showed mixed results: financial development is favorable to African economic growth at all quantile levels. However, economic vulnerability is a major impediment to economic growth at all quantile levels. In addition, it was found that a high degree of trade openness has a detrimental effect on African economic growth from quantile 0.5 of the dependent variable. Finally, another important result proves that financial development is a remedy for decision-makers against economic vulnerability.

Qatar FIFA 2022 was the first FIFA Football World Cup to be hosted by an Arab state and was predicted by some to fail. However, it did not only succeed but also showed a new display of destination sustainability upon hosting mega-sport events and linked tourism. Yet, some impacts tend to be long-term and need further analysis. The study aims to understand both positive and negative impacts on destination sustainability resulting from hosting mega-sport events, using bibliometric analysis of published literature during the last forty-seven years, and reflecting on the recent World Cup 2022 tournament in Qatar. A total of 2519 sources containing 665 open-access articles with 10,523 citations were found using the keywords “sport tourism” and “mega-sport”. The study found various literature researching the economic impacts in-depth, less on environmental impacts, and much less on social and cultural impacts on host communities. Debates exist in the literature concerning presumed economic benefits and motivations for hosting, and less on actual results achieved. Although World Cup 2022 is considered the most expensive among previous versions, destination sustainability seems to have benefited from the event’s hosting. Socio-cultural impacts of hosting mega-sport events seem to be addressed to an extent in the Qatar version of the World Cup, as well as environmental impacts while creating a unique image for FIFA 2022 and the destination itself. FIFA showcased this as using carbon-neutral technologies to create the micro-climate including perforated walls in the eight state-of-the-art stadiums, with the incorporation of a circular modular design for energy and water efficiency and zero-waste deconstruction post-event. The global event also drew attention and respect to the local community and underprivileged groups such as people with disabilities. Further research is needed to understand the demand-side perspective including the local community of Qatar and the event’s participants, and to analyze the long-term impacts and lessons learned from the Qatari experience.