Amid the deep integration of next-generation digital technologies and supply chain management, it is of great significance to explore how supply chain digitalization (SCD) promotes corporate carbon reduction performance. Drawing on the supply chain innovation and application pilot cities (SCIAPC) policy, this paper empirically examines the impact mechanism of SCD on carbon reduction performance from the perspective of resource orchestration theory, using the data of A-share manufacturing enterprises in Shanghai and Shenzhen from 2011 to 2021. Meanwhile, it reveals the capability allocation paths leading to high carbon reduction performance using dynamic QCA analysis. The results show that SCD can significantly promote carbon reduction performance. Mechanism examination reveals that SCD promotes carbon reduction performance by influencing supply chain capabilities and enterprise capabilities. Dynamic QCA analysis indicates that, under the backdrop of SCD, there are two distinct paths to improving carbon reduction performance: the coordination-operational type and the integration-innovation type. This paper provides empirical evidence for promoting supply chain digital transformation and enhancing corporate carbon reduction performance, and provides theoretical support and policy recommendations for promoting the SCIAPC policy.

Although corporate social responsibility (CSR) is widely recognized as a multi-dimensional construct, it remains unclear whether these dimensions function as substitutes or complements to one another. This uncertainty arises because decisions regarding the allocation of resources to different CSR dimensions are simultaneous and interrelated. To address this issue, we use an exogenous shock, namely China’s new Environmental Protection Law (NEWL), to examine how changes in corporate environmental responsibility (CER) engagement impact other CSR activities. Our findings suggest that increased CER engagement crowds out product-related CSR activities, primarily due to the overall CSR strategy and heightened environmental attention from top management. This research provides empirical evidence on the interactions between various CSR dimensions and offers insights into how regulatory changes shape CSR resource allocation in China. Moreover, our paper enhances our understanding of firms’ strategic decisions in balancing different CSR activities in the context of government-driven CSR in developing countries.

As the climate crisis drives the uptake of nature-based solutions (NbS), daylighting culverted urban streams is gaining traction. Yet, questions abound on how to approach stream daylighting and on its impacts. This study responds through a scaffolded literature review: 1) a scoping review on transformative and incremental adaptations that led to a comparative framework of four transformative-incremental adaptations criteria and their corresponding 18 parameters; and 2) a systematic content analysis of two fundamentally different approaches to stream daylighting: Seoul’s (S. Korea) mega-project that daylighted over 6 kilometers of the Cheonggyecheon and Zürich’s (Switzerland) small-scale Bächkonzept that daylighted over 25 kilometers of small stream segments. The findings reveal that, notwithstanding temporal, scale, and cost differences, Seoul’s Cheonggyecheon and Zürich’s Bächkonzept are both transformational, albeit differently. Yet, neither fits the abrupt (maintained functions, changed structures) nor the directed (changed functions, maintained structures) transformations; instead, lessons are gleaned from these two daylighting interventions.

Urban Land Cover (LC) change classification is vital for monitoring environmental impacts and urban expansion, but traditional methods face challenges such as noise, class imbalance, and LC variability. This research introduces a multi-step framework to address these issues. Gabor Filtering is applied to enhance texture and boundary details to achieve clearer features. Segmentation is done using a U-Net Transformer Encoder, with the capability to extract spatial and contextual information. A Spatial and Channel Dual Conditional Generative Adversarial Network (SCDCGAN) extracts features and represents intricate relationships of LC for classification. The Mountaineering Team-based Optimization Algorithm (MTOA) optimizes SCDCGAN parameters to reduce classification errors and improve accuracy. The suggested method exhibits better performance on Dataset A (99.33% accuracy) and Dataset B (95.67% accuracy). These performances show significant improvements in classification and segmentation accuracy, especially for skewed urban datasets, providing a strong solution for urban LC change classification.

Impact assessment (IA) can play an important role in informing and improving project design, particularly when viewed and used by proponents as a planning tool rather than a means of obtaining regulatory approval for a predetermined project concept. There has, however, been limited consideration of proponent decision-making about voluntary project design modifications during IA. This paper reviews various theories of corporate voluntary environmental behaviours to evaluate their applicability and utility in this context. It finds that these do address some known or potential rationales for IA-related design changes and show general alignment with previous research on this topic, as well as highlighting some further possible motivations and approaches. Future research should focus on understanding how such decisions are actually made by proponents, including the development of new decision models that address how multiple factors may be considered, balanced and ultimately influential, and which reflect the IA context in general.

Wildfire poses an increasing threat to communities in the Western US, driven by climate change and rising human settlement in the wildland-urban interface (WUI). It is imperative that communities in fire-prone areas become “fire-adapted” to safely manage their risk. Community Wildfire Protection Plans (CWPPs) constitute an approach by the federal government to enable communities to collaboratively plan for, and adapt to, wildfire. How well these plans have enabled at-risk rural Colorado communities to become “fire-adapted” since their development is still debated. Through interviews with key informants, we explored the role of CWPPs in building fire-adapted Colorado WUI communities since their development. We found that CWPPs are most effective in communities with certain characteristics that either necessitate a CWPP or create an enabling environment for plan success. Overall, our results highlight the importance of community context in adaptation planning and that CWPPs are not a “one size fits all” solution for WUI communities.

Invasive species cause global challenges with massive long-term impacts, and reduction of impacts relies on both international and local interventions. At national level, mismatches between how AIS are classified and managed, and how different governmental bodies deal with these species, produce a messy reality of changeable standards for the species and the people who are expected to manage them. We explore such mismatches through the case of wild boar in Norway. While native in Sweden, wild boar is an AIS in Norway and to be eradicated. By comparing management of wild boar in Norway with management of other invasive mammals, we found clear mismatches between risk assessment, species-specific action plans, management aim and management interventions. We also found that selective prioritization and inter-governmental conflicts shape the current eradication policy for wild boar in Norway. The consequences are many, including changing priorities, declining political legitimacy, and lack of public participation.

Extreme weather intensification due to climate change will necessitate significant human adaptation, either by implementing flood mitigation measures, or by vacating flood zones altogether. Although household-level decision-making strategies for flood mitigation have been studied, little attention has been given to how these decisions are made when repeated floods occur. To address this gap, we interviewed 13 flood-impacted residents of Waterbury, VT – a community that has experienced recent reoccurring flooding – to explore the factors influencing their flood mitigation decisions. Using Trust Ecology as a theoretical framework to guide our analysis, we uncovered key themes relevant to the adoption of mitigation behaviors. Specifically, our results suggest that two forms of distrust – rational and procedural – played important roles in determining behavior following repeated flooding. These findings are relevant for practitioners who assist with localized flood mitigation efforts and advance an understanding of how (dis)trust impacts mitigation efforts broadly.

Reducing carbon emissions from residential areas is crucial for achieving carbon neutrality. With the widespread use of the Internet, there has been a significant increase in digital literacy among individuals, which may influence their daily lifestyle and impact household carbon emissions. Using panel data from China, the study not only estimates household carbon emissions but also examines digital literacy’s influence and underlying mechanism on household carbon emissions. The results show that digital literacy can increase household carbon emissions by increasing household wage and business income and expanding social networks, supported by a series of robustness tests. This effect is particularly pronounced among households without outstanding debt, those engaged in non-farm employment, and those residing in regions with higher levels of digital economic activity.

This study proposes the use of a spatial-based travel cost model of multiple discrete/continuous demand to analyze recreational visits to five selected Italian National Parks. The proposed model has a spatial structure which allows us to capture potential patterns of environmental and economic dependency that may influence the destination choice and the number of trips taken to each destination. The model is estimated from revealed preference data collected through a general population survey of Italian National Park visitors. Results suggest that users are more inclined to visit destinations with improved visitor services and that those with similar economic characteristics show a similar sensitivity to changes in travel costs. Policy simulations based on the predicted number of visits across destinations are used to explore potential changes in travel patterns between sites. Simulation results suggest improving the site accessibility is likely to boost visitation rates for all national parks under study.