Search Results (38)

This study proposes an indicator system for evaluating AI-assisted learning in higher education, combining evidence-based indicator development with expert-validated weighting. First, we review recent studies to extract candidate indicators and organize them into coherent dimensions. Next, a Delphi session with domain experts refines the second-order indicators and produces a measurable, non-redundant, implementation-ready index system. To capture interdependencies among indicators, we apply a hybrid Decision-Making Trial and Evaluation Laboratory–Analytic Network Process (DEMATEL–ANP, DANP) approach to derive global indicator weights. The framework is empirically illustrated through a course-level application to examine its decision usefulness, interpretability, and face validity based on expert evaluations and structured feedback from academic staff. The results indicate that pedagogical content quality, adaptivity (especially difficulty adjustment), formative feedback quality, and learner engagement act as key drivers in the evaluation network, while ethics-related indicators operate primarily as enabling constraints. The proposed framework provides a transparent and scalable tool for quality assurance in AI-assisted higher education, supporting instructional design, accreditation reporting, and continuous improvement. Full article

Cultural heritage digitization (CHD) has become a strategic priority in European cultural and digital policies, driving efforts to enhance accessibility, preservation, and economic engagement. As digital technologies reshape the cultural sector, CHD increasingly intersects with the digital economy, fostering new forms of value creation. Despite this, empirical research on the socioeconomic drivers of CHD remains limited, with existing studies focused mainly on conceptual discussions, expert-based assessments, or institutional case studies. This study systematically analyzes the socioeconomic drivers shaping CHD across Europe using large-scale data from ENUMERATE and Eurostat. An econometric approach combining Ordinary Least Squares (OLS) and Generalized Additive Models (GAMs) is employed to capture both linear and non-linear relationships. The findings show that CHD is shaped by a complex interplay of economic capacity, digital infrastructure, institutional strategy, and societal demand, rather than by targeted funding initiatives alone. By bridging conceptual discussions and systematic econometric analysis, the study provides a robust empirical framework for understanding the external conditions that influence CHD and offers evidence-based insights to support more targeted digital transformation strategies in the European cultural sector. Full article

Bangladesh has significantly reduced child undernutrition, yet micronutrient deficiencies and diet-related non-communicable diseases remain pressing challenges. While the afordability of healthy diets is recognized as a key determinant of nutrition outcomes, limited attention has been paid to the uncertainties that affect diet costs and access over time. This paper addresses this gap by exploring the major drivers of uncertainty in the cost of healthy diets in Bangladesh and their implications for nutrition policy. This study emloyed foresight tools to explore future uncertainties affecting the cost and accessibility of healthy diets in Bangladesh. Key drivers of change, such as climate variability, market dynamics, income inequality, and dietary behavior, were identified through a structured expert workshop. Two critical uncertainties were selected using the 2 × 2 scenario planning method: food price volatility and changing dietary patterns. These formed the basis for four plausible future scenarios, each illustrating different trajectories for nutrition and food system outcomes. This foresight approach supports proactive, multisectoral policymaking by highlighting potential risks and opportunities for ensuring affordable, nutritious diets in a changing context. The resulting scenarios underscore the need for integrated, multisectoral strategies to build resilient food systems, improve the affordability of nutrient-rich foods, and promote dietary behavior change. Full article

The Qinghai–Tibet Plateau (QTP), a globally significant tourist destination and critical ecological barrier, faces an intrinsic conflict between development and conservation. The scientific identification of suitable tourism zones is therefore crucial for formulating sustainable development policies. Conventional suitability assessments, however, which typically rely on subjective, expert-based weighting and static, supply-side data, often fail to capture the complex, non-linear dynamics of actual tourist–environment interactions. To overcome these limitations, an innovative analytical framework is presented, integrating massive tourist trajectory big data (66.7 million GPS points) as an objective, demand-driven suitability proxy, a Geo-detector model to identify key drivers and their interactions, and a Random Forest algorithm for spatial prediction. The framework achieves high predictive accuracy (AUC = 0.827). The results reveal significant spatial heterogeneity: over 85% of the QTP is unsuitable for tourism, while suitable zones are intensely concentrated in southeastern river valleys, forming distinct agglomerations around core cities and along primary transport arteries. Analysis demonstrates that supporting conditions—particularly transport accessibility and service facility density—are the dominant drivers, their influence substantially surpassing that of natural resource endowment. Furthermore, the formation of high-suitability zones is not attributable to any single factor but rather to the synergistic coupling of multiple conditions. This research establishes a replicable, data-driven paradigm for tourism planning in environmentally sensitive regions, offering a robust scientific basis to guide the sustainable development of the QTP. Full article

The core driver of enterprise operations is data, making data lineage crucial for data management. It not only tracks data flow but also links data sources, workflows, applications, and decision-making, improving efficiency and governance. However, current data lineage parsing methods face challenges like high costs, long development cycles, and poor generalization, especially for non-SQL scripts. In this paper, we introduce an innovative approach leveraging pre-trained large language models (LLMs) to overcome these bottlenecks in data lineage parsing. LLMs are employed across the entire parsing pipeline, encompassing prompt construction, lineage extraction, and result standardization. Specifically, this study developed a few-shot prompting method incorporating error cases to optimize parsing performance across various types of scripts. Additionally, a collaborative Chain of Thought (CoT) and multi-expert prompting framework was designed to further enhance parsing accuracy at the operator level. The proposed approach was empirically validated using LLMs of different parameter scales on datasets comprising multiple script types (SQL, Python, Shell, Flume, etc.). The experimental results show that LLMs with 10 billion and 100 billion parameters achieved over 95% accuracy in table-level lineage parsing when utilizing the newly designed prompts. Furthermore, 100-billion-parameter LLMs exhibited substantial accuracy improvements at the operator level. Our method reinforces the feasibility and practicality in advancing data lineage parsing methodologies. Full article

Since 2019, Togo has been strengthening financial decentralization through municipalization and the election of municipal councilors. Municipal financial autonomy is a key driver of local governance, allowing municipalities to mobilize their own resources, manage tax and non-tax revenues, and implement development projects. However, despite a legal framework governing local taxation, Togolese municipalities continue to face chronic financial constraints that limit their ability to finance public services and infrastructure. This study examines the mechanisms of financial decentralization in Togo and their contribution to municipal budgets. Using a quantitative approach that combines documentary analysis and interviews with 188 experts and practitioners in local finance, the study identifies the following four primary financing mechanisms: local, national, community-based and international. Among these, own revenues, including tax revenues, non-tax revenues, and revenues from the provision of services, together with government transfers through the Local Authorities Support Fund (FACT) are the main sources of local government finance. However, the results show that several legally defined fiscal instruments remain underutilized or outdated in many municipalities, significantly limiting their effectiveness in mobilizing resources. These results highlight the need to optimize fiscal decentralization strategies in order to strengthen the financial autonomy of municipalities and support sustainable territorial development. Full article

Dogs are among the most popular pets worldwide, and ownership is increasing in many regions. Responsible pet ownership positively impacts animal welfare, yet little is known about the drivers of pet choices or their regional variation. To address this knowledge gap, a structured online questionnaire was developed to investigate the motivations, behaviours, perceptions, and demography of owners acquiring dogs. Quality control measures included content validity evaluation by independent experts and back-translation to optimize semantics. Non-probability convenience and purposive sampling was used to recruit respondents through social media and interest groups. In total, 2036 eligible responses were received. Three out of four respondents were female, which is a pattern reported in other regions. Mixed-breed dogs were the most popular, representing around 40% of the total, and non-commercial sources, such as shelters, were the predominant source for new pets (65%). In stark contrast to the UK, USA, and parts of Europe, brachycephalic breeds were the least popular of the purebreds. Poodles were the most frequently owned purebred in both HKSAR and MC. “Companionship for humans” was the most common reason for acquiring a pet dog, and strong agreement with the statement “I consider my dog part of my family” was almost universal (99%). Over half of respondents carried out no research before they acquired their dog (55%), and veterinary professionals were the least frequent resource used by the remainder. Our study reveals commonalities with other regions in drivers for, and perceptions of, pet dogs. Encouragingly from an animal welfare perspective, brachycephalic breeds were the least preferred type. Investigation of the drivers of this observation may be useful to encourage the acquisition of non-brachycephalic dogs in other regions. Overall, our study provides preliminary but valuable insights for developing targeted programs promoting responsible ownership in the region to enhance the well-being of both humans and dogs. Full article

The transition towards nature-based cities has increasingly become a central focus in political–environmental agendas and urban design practices, aiming to enhance climate adaptation, urban biodiversity, spatial equilibrium, and social well-being as part of the ongoing socio-ecological urban transition process. Climate adaptation in cities is a complex problem and one of the main collective challenges for society, but the relationships between city managers and citizens as to urban green care still face many challenges. Parks design guided by technical-expert and globalised criteria; inflexibility from bureaucratic inertia; and citizens’ demands to participate in the urban green transition, sometimes without the necessary knowledge or time, are some of the challenges that require further research. In this study, we examine four long-lasting approaches to green-space management in four cities in the Netherlands, ranging from municipality-driven to community-driven management forms, and encompassing diverse spatial configurations of greenery within the urban fabric. Utilising the theoretical lens of the Social–Ecological Systems Framework, we employ a multiple-case-study approach and ethnographic fieldwork analysis to gain a comprehensive understanding of the norms, collective-choice rules, and social conventions embodied in each urban green management arrangement. The purpose of this research is applied, that is, to provide urban managers and decision-makers with a deeper understanding of drivers to promote effective collaborative management approaches, focusing on specific organisational rules that may contribute to more sustained planning and maintenance pathways for urban green spaces, regardless of changes in political leadership or significant external funding sources. The results of the investigated cases show that long-lasting collaborative management of forests and parks has established a set of collective-choice rules for resource transfer between municipalities and citizens, including non-monetary resources (such as pruning-training courses or guided tours that attract tourists and researchers). Additionally, these arrangements have been favoured by the existence of legal norms that enable co-ownership of the land, and monitoring and sanctioning mechanisms that offer a slightly different interpretation from the evidence identified so far in the scientific literature on collective resource management and organisational studies. Full article

This study examined the effect of free trade on intra-African bilateral trade balances for Kenya, Rwanda, Uganda, and Tanzania to assess the potential implications of the African Continental Free Trade area. The four countries have experienced persistent trade deficits. Whether free trade within Africa can improve the national trade balances, and the drivers of bilateral trade balances are important questions for policy and strategic programmes for the countries to make the most gains from free trade area. The econometric model estimated for each country is an extension of the standard Keynesian model of trade balance to include determinants of bilateral trade flows from the gravity model. Quantitative analysis using panel regression was augmented with qualitative data from interviews with trade policy experts and trade officials from various African countries and focus group discussions with small-scale cross-border traders at the Busia and Namanga border posts in East Africa. Findings show that complete tariff elimination on intra–African trade may not impact the bilateral trade balances of Kenya, Rwanda, and Tanzania but could improve bilateral trade balances for Uganda by 6 percent. Within the free trade areas, Uganda’s bilateral trade balances were higher within the Common Market for Eastern and Southern Africa but lower within the East African Community, than outside these areas. Kenya’s trade balances were lower in the Common Market for Eastern and Southern Africa, than otherwise. On the contrary, no significant difference in trade balances is established for the membership of Kenya, Rwanda, and Tanzania in the East African Community; Rwanda in the Common Market for Eastern and Southern Africa; and Tanzania in the Southern African Development Community, when compared to trade balances with non-members. The importance of macroeconomic factors is demonstrated by the increase in bilateral trade balances with higher relative price levels of trade partners; the reduction with increase in relative production and expenditure capacities of trade partners; and improvements following a depreciation of home currency for Tanzania and Uganda, yet a worsening of trade balances in Kenya. A lack of harmony in documents required for cross-border movements within the free trade areas is reported as counterproductive. All African countries should therefore fully implement protocols and cooperate in the harmonization of trade procedures for the free movement of people and goods across borders. Country policies and trade programmes should pursue increased productivity in the leading intra-African export sectors and diversify exports via foreign direct investment in strategic sectors to substitute imports from outside Africa; reduce costs of production; increase the quality of products; and improve transport infrastructure. Full article

This study investigates the use of biometric technology in public transit to improve trip safety and effectiveness. The incorporation of biometric technology into transit networks improves efficiency and security but also poses substantial challenges of privacy, standardisation, and public acceptability. Conducted via a poll of 25 specialists in Lithuania, the objective was to assess the level of acceptability and practicality of using biometric identification for both drivers and passengers. The results suggest a divided view about the specific demographic that biometric applications should target. However, there is agreement on the considerable potential of these technologies to enhance transportation safety. Face recognition has been the favoured approach due to its non-intrusive nature and simplicity of integration. The statistical research demonstrated significant positive correlations between different biometric approaches, indicating that a multimodal strategy is effective for providing full security coverage. The research highlights the significance of resolving privacy issues, emphasising that public acceptability depends on the open management and strong safeguarding of biometric data. The findings support the deliberate use of biometric technologies in sustainable public transportation, emphasising their ability to improve safety, optimise operations, and even revolutionise the passenger experience. This emphasises the equitable examination of technology, security, and privacy in the progress of sustainable public transportation systems. Biometric technology in public transport, especially for monitoring driver health and ensuring passenger safety, is supported by experts as a means to enhance service quality, reduce accidents, and optimize route planning. Full article

The surge in mobile shopping faces a challenge as not all potential consumers are comfortable with this mode. Retailers need a deeper understanding of factors influencing user experience to enhance marketing strategies. Despite extensive research, a gap remains in comprehending this aspect. Using a statistical PLS-SEM-ANN approach, this research aims to explore the psychological dimensions of expert and non-expert mobile shoppers for establishing better targeted marketing strategies in m-commerce settings. Analyzing experience levels in mobile commerce (m-commerce), key drivers like enjoyment, usefulness, subjective norms, and trust were scrutinized as interaction settings for consumers using mobile technologies. The findings reveal that, for less experienced m-shoppers, trust is the most significant driver of attitude and satisfaction, while, for experienced users, trust and usefulness are the primary antecedents. This research provides novel insights, aiding mobile marketers in refining targeting strategies based on consumer experience levels, emphasizing the importance of usefulness and trustworthiness for a seamless m-shopping experience. Full article

This study examines the vaccine market access pathway in Poland to evaluate its efficiency and propose recommendations for its improvement. The research spans a comprehensive analysis of the vaccine assessment process, ranging from pre-registration to sustainability, encompassing critical components such as national immunization technical advisory groups (NITAGs), health technology assessments, resource evaluations, and decision making. This investigation utilizes a multi-phase approach. Initial desk research aimed to collect accumulated evidence about each step of the vaccine access pathway. This constituted the background for an expert panel discussion (n = 13) and a final online questionnaire (n = 12), evaluating the timeframes, inclusiveness, transparency, and consistency of the elements of the process. Poland is a late adopter of new vaccines. The country faces budget constraints and lacks a formalized framework for the inclusion of vaccines into the national immunization program. Notably, NITAGs play a crucial role, yet their limited resources and dependence on public health stakeholders diminish their impact. A formal and well-supported advisory body may become a foundation for decision-making processes. The health technology assessment conducted by the national agency is recognized for its timeliness and transparency, though the absence of fiscal analyses in vaccine assessments is identified as a gap that limits the understanding of the value of vaccinations. Resources are key drivers of decision making, and recent changes in legislation offer increased flexibility in financing vaccines. Challenges in the procurement process include a limited consideration of non-acquisition costs and an increased absence of a documented general strategy for immunization program development in Poland, pointing to a need for strategic planning. In conclusion, this study recommends the establishment of a robust NITAG with enhanced resources, incorporating fiscal analyses, transparent resource allocation, and strategic planning for immunization program development. Addressing these recommendations is crucial for optimizing Poland’s vaccine market access pathway, ensuring timely and efficient population-wide vaccine access. Full article

Identifying the underlying factors derived from geospatial and remote sensing data that contribute to forest fires is of paramount importance. It aids experts in pinpointing areas and periods most susceptible to these incidents. In this study, we employ the geographically and temporally weighted regression (GTWR) method in conjunction with a refined continuous invasive weed optimization (CIWO) algorithm to assess certain spatially relevant drivers of forest fires, encompassing both biophysical and anthropogenic influences. Our proposed approach demonstrates theoretical utility in addressing the spatial regression problem by meticulously accounting for the autocorrelation and non-stationarity inherent in spatial data. We leverage tricube and Gaussian kernels to weight the GTWR for two distinct temporal datasets, yielding coefficients of determination (R2) amounting to 0.99 and 0.97, respectively. In contrast, traditional geographically weighted regression (GWR) using the tricube kernel achieved R2 values of 0.87 and 0.88, while the Gaussian kernel yielded R2 values of 0.8138 and 0.82 for the same datasets. This investigation underscores the substantial impact of both biophysical and anthropogenic factors on forest fires within the study areas. Full article

During the COVID-19 pandemic, many restaurants implemented online food delivery (OFD) platforms to serve customers. However, it remains unclear how restaurant managers decide to implement OFD and whether or not the implementation can improve performance. We view OFD implementation as a form of service innovation. This study investigates and explains the reasons why restaurants implemented an OFD platform during the COVID-19 pandemic, and the impact of that implementation on restaurant performance, based on service innovation theory. An internet survey was conducted to collect data from restaurant owners or managers to test the proposed research model. The results show that the perceived benefit of increasing the firm’s reach is the key driver of OFD implementation, and the implementation has a positive impact on both financial and non-financial performance. A follow-up interview was also conducted to obtain the opinions of industry experts, who explained the phenomena. The research findings can advance our understanding of how restaurant managers decide to innovate by implementing OFD services and help them better understand whether and how the implementation of this service can actually improve performance. Full article

Activating mutations in Kirsten rat sarcoma viral oncogene homologue (KRAS), in particular, a point mutation leading to a glycine-to-cysteine substitution at codon 12 (G12C), are among the most frequent genomic alterations in non-small cell lung cancer (NSCLC). Several agents targeting KRAS G12C have recently entered clinical development. Sotorasib, a first-in-class specific small molecule that irreversibly inhibits KRAS G12C, has since obtained Health Canada approval. The emergence of novel KRAS-targeted therapies warrants the development of evidence-based consensus recommendations to help clinicians better understand and contextualize the available data. A Canadian expert panel was convened to define the key clinical questions, review recent evidence, and discuss and agree on recommendations for the treatment of advanced KRAS G12C-mutated NSCLC. The panel agreed that testing for KRAS G12C should be performed as part of a comprehensive panel that includes current standard-of-care biomarkers. Sotorasib, the only approved KRAS G12C inhibitor in Canada, is recommended for patients with advanced KRAS G12C-mutated NSCLC who progressed on guideline-recommended first-line standard of care for advanced NSCLC without driver alterations (immune-checkpoint inhibitor(s) [ICIs] +/− chemotherapy). Sotorasib could also be offered as second-line therapy to patients who progressed on ICI monotherapy that are not candidates for a platinum doublet and those that received first-line chemotherapy with a contraindication to ICIs. Preliminary data indicate the activity of KRAS G12C inhibitors in brain metastases; however, the evidence is insufficient to make specific recommendations. Regular liver function monitoring is recommended when patients are prescribed KRAS G12C inhibitors due to risk of hepatotoxicity. Full article