Опубликована: Янв. 1, 2024
Язык: Английский
Research Policy, Год журнала: 2024, Номер 53(6), С. 105026 - 105026
Опубликована: Май 21, 2024
Interdisciplinary scientific fields, such as synthetic biology, bioinformatics, and human brain science, often emerge at the intersection of existing disciplines. This fundamental process is described in literature streams 'science convergence' 'evolution new fields'. However, despite their empirical relevance potential for science convergence to accelerate evolution these two concepts have been developed separately up this point. In study, we therefore investigate interplay between by first conducting a systematic review on examine its underlying dynamics. We then integrate concept into current understanding evolutionary leading theoretical conceptualization typology different pathways interdisciplinary fields. The exhibit varying levels research activities stages process. apply cases illustrating how an early emphasis drive field. essence, our related proxies enable policymakers other actors understand gives rise
Язык: Английский
Процитировано
6
Environmental Impact Assessment Review, Год журнала: 2024, Номер 108, С. 107608 - 107608
Опубликована: Июль 23, 2024
Язык: Английский
Процитировано
6
Technovation, Год журнала: 2024, Номер 133, С. 103022 - 103022
Опубликована: Апрель 30, 2024
Язык: Английский
Процитировано
5
Sustainability, Год журнала: 2025, Номер 17(2), С. 415 - 415
Опубликована: Янв. 8, 2025
In recent years, organizations have increasingly turned to digital transformation (D) drive innovation (I) and sustainability (S). However, the rapid growth of studies on this topic, particularly since 2019, has made it challenging clearly define these concepts, operationalize their constructs, understand positive organizational impacts. This article addresses gaps through a systematic literature review (SLR) that combines quantitative qualitative analysis. study begins with comprehensive bibliometric analysis 3099 articles published between 2010 2023 in Scopus database containing terms “digital,” “innovation,” “sustainability” (or “sustainable”). It then covers detailed 20 high-quality from VHB-JOURQUAL-C-ranked journals or higher. By employing an inductive–deductive approach, authors identify consistent conflicting definitions, diverse constructs for each D-I-S concept, numerous effects. provides structured overview existing definitions introduces model distinguish environmental, organizational, solution levels. Additionally, presents visual framework direct mediated effects organizations. Overall, insights underscore critical role advancing sustainability, offering valuable guidance researchers practitioners alike.
Язык: Английский
Процитировано
0
Journal of Innovation & Knowledge, Год журнала: 2025, Номер 10(2), С. 100660 - 100660
Опубликована: Янв. 30, 2025
Язык: Английский
Процитировано
0
Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145148 - 145148
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0
Technovation, Год журнала: 2025, Номер 142, С. 103200 - 103200
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0
Architectural Engineering and Design Management, Год журнала: 2025, Номер unknown, С. 1 - 32
Опубликована: Март 25, 2025
Urbanization and built-up areas negatively impact ecosystems, contributing to climate change, pollution, biodiversity loss. In response, the interdisciplinary framework of Ecosystem Services (ES) has gained prominence in sustainability resilience agendas. The potential bio-inspired design (BID) provide or improve ES built environment is investigated this study. Its originality stems from attempt bridge gap literature by examining relationship between BID environments. By focusing on specific ES, establishing evaluation criteria, analyzing different strategies at micro, meso, macro urban scales, research highlights influence ES. For example, green roofs have a direct, high regulation, while sponge cities medium regulation. This study identifies purification, energy as most relevant due their integrability, available technologies, ability be executed various scales. findings are synthesized into matrix, linking methods assessing based established criteria.
Язык: Английский
Процитировано
0
Smart and Sustainable Built Environment, Год журнала: 2025, Номер unknown
Опубликована: Апрель 1, 2025
Purpose Achieving sustainable development goals requires efficient decision-making and stakeholder engagement in infrastructure projects. This research aims to investigate how at the project governance level can be advanced using digital technology improve sustainability performance Design/methodology/approach Grounded acceptance model, this qualitative study explored perceptions of professionals facilitating within Seventeen semi-structured interviews were conducted with purposively selected data analyzed inductive thematic analysis. Findings Digital enables evidence-based aligned by providing real-time data, optimizing analysis enhancing authenticity while reducing resource time pressure. It promotes offering integrated, collaborative centralized platforms which foster transparency, collaboration, mitigate risk greenwashing modern slavery streamlining communication siloed engagement. However, human oversight remains essential prevent technological misinterpretation. Practical implications provides valuable insights for management seeking integrate into demonstrates enhance environmental, social economic dimensions projects, helping them remain competitive a dynamic environment. Social presents reliable, up date required informed decision-making, enabling socially choices. reduces risks erroneous decision benefit broader communities addressing challenges, fostering resilience well-being. Originality/value Despite slow adoption Australian crucial. addresses gap comprehensive understanding level.
Язык: Английский
Процитировано
0
BIO Web of Conferences, Год журнала: 2025, Номер 172, С. 02001 - 02001
Опубликована: Янв. 1, 2025
The novel research incorporates high-level machine learning algorithms for optimizing agricultural performance regarding sustainability and resource efficiencies. By using random forests SVMs, this work successfully achieved 92% prediction accuracy crop yields an 89% classification of regions, thereby highly enhancing the decision-making power farmers policymakers. With over 10,000 historical records, forest model established a hypothesis that maize could be increased by almost 25% in ideal conditions. At same time, SVM identified more strongly within high-productivity areas yield increase 15% targeted crops. Furthermore, Convolutional Neural Networks processed nearly 5,000 satellite images to register precision rate up 94% early stress resulting reduction loss 30%. Reinforcement Learning was used also reduce water use irrigation 20% without impacting crops while schedules adapt real-time data concerning environment toward helping meet goals. Network (CNN) stands out as best algorithm context due its exceptional detection symptoms, achieving accuracy. Findings have indicated multi-algorithm approach not only promotes predictive capabilities optimization but raises food safety with threats agriculture.
Язык: Английский
Процитировано
0