Search Results (466)

Community-based leisure may support newcomer women’s well-being and belonging, yet its role within settlement practice remains underexamined. This manuscript presents findings from a larger community-based research project that explored Iranian newcomer women’s (aged 30–55) experiences navigating leisure, community life, and well-being during their settlement in Ottawa, Canada. In this manuscript, the discussion focuses on data collected from virtual feedback consultation sessions with two women who participated in co-designed leisure activities, and an executive from a non-profit settlement service organization serving Iranian and Farsi-speaking newcomers. Data coding, translation, verification and reflexive thematic analysis guided our qualitative methodological approach, and findings were interpreted within an intersectional feminist framework. Our findings revealed the challenges the participating women faced in balancing employment, caregiving, and household labour while acclimatizing to Canada. The women in this study described leisure as a vital interruption of their layered responsibilities and a chance to connect with others who shared their migration experience. Leisure did not replace formal settlement supports but addressed dimensions of settlement that 33 conventional indicators often miss, including identity loss, unfamiliarity with the city, and 34 the need for connection in a shared language and cultural setting. In this case, the settlement organization functioned as a cultural infrastructure that made participation in public and cultural life accessible for the women who took part. Full article

Sustainable web development focuses on designing web pages that minimize their environmental impact by reducing digital carbon emissions while maintaining optimal website performance and user experience. This study emphasizes the necessity of adopting sustainable web development practices in the Balkan region, highlighting the role of institutional education and web developers in encouraging environmentally responsible web practices within a Technology-Enhanced Education context. A descriptive cross-country analysis was conducted on a total of 8976 websites across five Balkan countries—Albania, Greece, Serbia, Montenegro, and North Macedonia—selected from public domain registries and categorized by sector (education, organization, government, and commercial domains). Data were collected during December 2025. DNS verification was conducted to identify active domains, and hosting sustainability was determined through the Green Web Foundation API. “Green hosting” is operationally defined as hosting that is completely powered by renewable energy sources. Overall, the findings suggest that the prevalence of green hosting in the region is very low, at approximately 27.77%, with substantial variation across sectors. Educational institutions (.edu) and non-profit organizations (.org) have higher adoption rates, while public administrations (.gov) and small commercial websites generally fall behind. The country with the highest percentage of green hosting is Greece (64.07%), while the lowest is Albania, with less than 1%. These findings reveal significant gaps in knowledge and practices among developers and institutions, indicating an urgent need for targeted educational interventions. Crucially, this study connects empirical evidence directly to education. Recognized knowledge gaps guide curriculum development and the design of practical training modules to equip developers and institutional personnel with the skills to adopt sustainable web practices. This research establishes a regional comparative baseline and offers practical recommendations for incorporating sustainability into web development education. The findings endorse strategies and policies aimed at promoting environmentally sustainable digital infrastructure in the Balkan area. Full article

Understanding how vaccination-event characteristics relate to doses administered can inform public health delivery strategies. This study examined associations between modifiable characteristics of community-based COVID-19 vaccination events and doses administered per event. We conducted a retrospective analysis of 631 vaccination events coordinated by the Louisville Metro Department of Public Health and Wellness (LMPHW) in Jefferson County, Kentucky, between March 2021 and May 2022. The outcome was the number of COVID-19 vaccine doses administered per event. Multivariable regression models assessed associations between event characteristics and doses administered per event. Across all events, 27,767 COVID-19 vaccine doses were administered. Each additional hour of event duration was associated with 21.6% more doses administered per event (95% CI: 14.0–29.8%). Weekend events were associated with 87.8% more doses administered per event than weekday events (95% CI: 45.7–142.0%). Compared with government-hosted events, 44.7% more doses were administered at non-profit organizations, 110.0% more at business organizations, and 57.8% more at medical service providers. LMPHW-only events were associated with 198.4% more doses administered per event than partnered events (95% CI: 120.1–304.6%). Principal findings were generally consistent across sensitivity analyses. These findings may help inform planning of future community vaccination and other immunization initiatives. Full article

Rationale: This research explores the connections between shelter and rescue revenues and expenses and live release outcomes, specifically focusing on the implications of a nonprofit having a government contract to provide animal control and welfare services. Methods: Two data sources were used for the project: nonprofit I990s as reported to the Internal Revenue Service (for financial data) and live release data from Shelter Animals Count (to measure shelter outcomes). The project focuses on financing for nonprofit shelters and rescues and 252 organizations from the Shelter Animals Count database, classified as nonprofits with and without government contracts, were used in the analysis. Data on revenue and expenditures were pulled from the nonprofit 990s using the GuideStar website. Results: Two variables—relinquishment rate and diversification of revenue—account for 40% of the variation in live release rates. Organizations with greater diversification of revenue have significantly higher live release rates and those with higher numbers of relinquished animals have lower ones. Conclusions: The study concludes that: a more even distribution of revenue between donations, programs, and government contracts for service is related to better outcomes; it is not so much whether a shelter or rescue has a government contract, but the portion of its revenue provided by the contract that is related to live release rates; and, overall, there are few significant relationships between revenue, expenditures, and outcomes. Full article

Living shorelines are widely promoted as nature-based solutions to coastal erosion and wetland protection, yet hardened shoreline structures continue to dominate even in jurisdictions with explicit policy mandates prioritizing living shorelines. In this research, we examine why non-optimal shoreline modification outcomes persist in Virginia (USA) despite a regulatory framework designed to promote ecological alternatives. We use primary data from interviews with wetlands board members, marine contractors, and nonprofit organizations and findings from a secondary survey of shoreline property owners to analyze shoreline management as a multi-sector collaborative decision-making process. Findings show that shoreline outcomes are shaped less by individual regulatory decisions than by recurrent interaction mechanisms across sectors that operate upstream of permit review. Contractors play a critical agenda-setting role by shaping the alternatives presented to property owners, while social norms, anticipatory adaptation to regulatory expectations, and informal decision heuristics constrain option sets before projects reach wetlands boards. Formal co-management institutions are therefore asked to arbitrate projects that are already highly constrained, limiting their ability to advance policy goals. Improving policy fidelity requires attention to decision sequencing, intermediary incentives, and structural feedback dynamics, rather than simply refining permitting guidance. Targeting upstream decision points and interaction mechanisms offers greater potential to align shoreline management outcomes with living shoreline policy objectives. Full article

Customer complaints are considered one of the key indicators of customer discontentment with a service. In organizations, such as telecommunications companies, not all customers raise their complaints, which raises concerns about their potential churn or retention. As firms usually rely on the complaints raised to customer services, there exists an important portion of customers who claim their complaints through other platforms, such as social media, even though another portion does not complain at all. This places the company’s image in jeopardy and might affect its productivity and profits. To address this challenge, it is important to address possible customer problems before they turn into effective complaints. To do so, the current study aims to predict the complaints of customers in a telecommunication company and their potential churn through the usage of supervised machine learning models to test the correlation between churn and complaints. Through a thorough data analysis, it becomes evident that a good portion of clients who encounter service issues decide not to present any complaints to the company. In addition, among complainers, some do not complain directly to the company, while others who contact the company have their problems postponed. Among those, there is a proportion, considered as having unresolved concerns, turned into churn. Using a dataset of 1000 clients, recruited over a period of six months, the results showed that a considerable portion of customers using the services during the day were non-churners and continued using it over the overall period of 6 months. Whereas, day churn and evening churn both showed much lower frequencies compared to non-churn customers, with fewer calls across all durations. Additionally, the findings showed that there exists a correlation between customer complaints and customer churn, where churn events frequently coincide with complaints, indicating that customers without churn are generally content with their service, while those having complaints are more likely to quit. This study presents important insights into telecommunications companies to improve their service offerings, enhance customer satisfaction, and reduce churn rates, leading to a more stable and profitable customer base. Full article

This study investigates whether shareholder value creation, defined as beta-adjusted outperformance relative to a market benchmark, can be effectively predicted in an emerging market using a sequential machine learning framework. While prior research has predominantly focused on profitability forecasting or stock return prediction, the prediction of risk-adjusted shareholder value creation remains relatively underexplored, particularly in emerging economies such as Morocco. To address this gap, the study develops a predictive framework that combines market-based indicators, macroeconomic variables, and accounting fundamentals using only information realistically available to investors at each decision date. These variables are organized into firm-level temporal sequences based on a monthly decision-date panel of non-financial firms listed on the Casablanca Stock Exchange over the period 2010–2024. To capture nonlinear relationships and temporal dependencies in financial data, the empirical analysis compares baseline models with deep learning architectures, including GRU, LSTM, and CNN1D. The results indicate that deep learning models consistently outperform naïve and linear benchmark models, suggesting that shareholder value creation exhibits a measurable degree of predictability. With an AUC of 0.700 and a PR-AUC of 0.727, CNN1D achieves the strongest performance in the final evaluation setting and ranks as the best-performing model according to the primary AUC criterion. The findings also reveal that macroeconomic variables generate the strongest standalone predictive signal, whereas market-based variables exhibit comparatively weaker predictive power when considered in isolation. By extending financial prediction toward a risk-adjusted, benchmark-based, and investor-oriented framework, and by providing new empirical evidence on the value of temporal modeling and multi-source financial information for forecasting shareholder value creation in an emerging market context, this study contributes to the growing literature at the intersection of financial forecasting and artificial intelligence. Full article

Conventional approaches to motivating individuals within firms emphasize external incentives, sometimes referred to as the “carrot and stick” paradigm. However, such elements are often absent in volunteer environments, where incentive is derived from psychological and relational influences. In the work context, volunteers are an exceptional case as they lack traditional extrinsic incentives, making them suitable for researching motivation outside this paradigm. This study, based on Self-Determination Theory, explores the impact of communication methods on motivation, satisfaction, and retention of volunteers. The study employs a qualitative design to analyze data from 91 volunteers and 6 coordinators in nonprofit organizations, using content analysis conducted with ATLAS.ti version 26. The findings demonstrate that communication functions as a crucial motivator by promoting autonomy, competence, and relatedness. Volunteers are intrinsically driven by their engagement, the opportunity to make a significant contribution, and experiential learning. Conversely, coordinators influence these experiences by providing feedback, advice, and chances for engagement. The findings indicate a struggle between autonomy and control, illustrating variations in motivation within organizational contexts. The study contributes to existing knowledge by demonstrating that communication serves as a primary motivator and engagement catalyst in the absence of external rewards. This holds significant ramifications for nonprofit administration and motivational philosophy. Full article

This study analyzes cyberattack trends targeting non-profit organizations using longitudinal data collected over a three-year period within the Non-Profit Cybersecurity Incident Repository (NPCIR). Developed through a National Security Agency Center of Academic Excellence in Cyber Defense (NSA CAE-CD) designated center, the NPCIR applies an open-source intelligence (OSINT) methodology to systematically document cybersecurity incidents affecting the global non-profit sector. This study examines attack types, threat actor characteristics, sectoral distribution, and cybersecurity impacts using the Confidentiality–Integrity–Availability (CIA) triad framework. The results indicate that availability-related incidents, particularly ransomware and distributed denial-of-service (DDoS) attacks, constitute the most prevalent threats, while confidentiality breaches remain highly significant due to frequent data exposure incidents. Statistical analyses further demonstrate significant differences between non-profit organizations aligned with DHS CISA critical infrastructure sectors and those operating outside these sectors, especially regarding the prevalence of availability-focused attacks. In addition to its empirical contribution, the NPCIR initiative supports experiential learning opportunities for undergraduate and graduate students in cybersecurity and information technology. The resulting dataset provides actionable cyber threat intelligence for researchers, practitioners, and non-profit leaders seeking to strengthen organizational cybersecurity resilience and awareness. Full article

Despite the growing relevance of governance and sustainability in port management, there is still limited empirical evidence on how economic, social, and environmental dimensions interact in a non-linear and configurational manner to explain port economic efficiency. This study applies an explainable machine learning approach based on Random Forest to classify the economic efficiency of Spanish Port Authorities using an integrated set of governance-related indicators. Economic efficiency is approximated through the E_02 indicator (EBITDA per tonne), which is discretized into three ordinal levels: low, medium, and high efficiency. A classification approach is preferred over regression because the objective is not only to predict a continuous value, but to identify interpretable efficiency profiles and extract decision rules associated with different governance configurations. Model performance was evaluated using a confusion matrix, global accuracy, precision, recall, and F1-score for each efficiency class. The results reveal three differentiated patterns: low-efficiency ports, associated with environmental weaknesses, fragile labor structures, and low profitability; medium-efficiency ports, characterized by partial strategies and transitional configurations; and high-efficiency ports, linked to coherent combinations of environmental management, balanced labor organization, and strong economic performance. Overall, the findings show that port efficiency does not depend solely on size or isolated factors, but on specific governance-related configurations. The study highlights the value of explainable artificial intelligence as a complementary tool to support evidence-based decision-making in sustainable port management. Full article

Servant leadership is widely conceptualized as an effective model for nonprofit and project-based organizations, yet systematic evidence on whether its relationships with team processes and project success remain similar across regional NGO contexts is limited. This paper examines that question in two NGO groupings, Latin America and Africa, by combining moderated regression, measurement invariance testing, and multi-group structural equation modeling. The results show that servant leadership positively predicts team identification and team climate in both regional samples, with positive bootstrapped indirect effects in both groups. At the same time, the cross-group structural comparison is not statistically significant ($p=0.072$), the total effects are similar across groups ($0.755$ in Latin America and $0.757$ in Africa), and the free structural SEM shows only adequate fit ($RMSEA=0.095$). Accordingly, the findings are more consistent with a broadly similar cross-regional pattern than with strong evidence of major regional divergence, but they should be interpreted cautiously in light of partial scalar invariance and sample limitations. Full article

With the rapid expansion of avocado cultivation in southern Italy, growers have had to deal with the emergence of new diseases often caused by invasive and polyphagous pathogens responsible for leaf spot, branch cankers, dieback and fruit and root rot. Given the severity of these emerging diseases, a study was conducted in the main avocado growing areas in Sardinia and Sicily (Italy) to isolate and characterize the causal agents. Specifically, a total of 430 symptomatic leaf, fruit, branch, stem and root samples were collected and examined. Isolations performed on both non-selective and selective growth media yielded 22 species (fungi and oomycetes) belonging to the genera Botryosphaeria, Colletotrichum, Diplodia, Dothiorella, Macrophomina, Neofusicoccum and Phytophthora, including 14 new host–pathogen records in Italy. Notably, Neofusicoccum australe, Phytophthora cinnamomi and Phytophthora palmivora emerged as the main pathogens involved in the emerging avocado diseases. The identified pathogens were often isolated simultaneously from the same plants, which exhibited a complex of symptoms. Pathogenicity bioassays have helped to clarify the differences in aggressiveness among the different species and their specificity towards the different plant organs. The results achieved suggest that avocado orchards’ productivity and profitability is threatened by a plethora of unrelated pathogens whose control represents a major challenge for the success of this crop in Italy. Full article

Food insecurity persists in Ecuador, and organizations like the Quito Food Bank (BAQ) are key to mitigating it. This study evaluatesBAQ’s management from a sustainability perspective, analyzing its social, economic, and environmental impacts in line with the Sustainable Development Goals (SDGs). A mixed, exploratory, and descriptive case study approach was employed. Data collection included direct observation, a review of internal records, and semi-structured surveys administered to 240 volunteers. The environmental impact was quantified using a “gate-to-gate” Life Cycle Assessment (LCA) with OpenLCA software and the ReCiPe 2016 methodology, while The social and economic analysis was conducted in R, using non-parametric statistical tests. The LCA identified storage as the main critical environmental, responsible for over 80% of the impacts due to high-energy consumption for refrigeration. Socially and economically, the BAQ’s food basket provides significant savings for beneficiary households, allowing them to redirect resources to other essential needs. However, this assistance is only partial and does not generate full economic security. The study highlights the duality of the BAQ’s operations: while food redistribution generates social and environmental benefits by reducing waste, it has its own environmental footprint due to the use of energy resources. A more holistic perspective is therefore proposed to ensure these interventions are truly sustainable in the long term. Full article

The CSDU-CSSI DAYS 25—II International Conference on “Challenges and Perspectives in Urban Water Management Systems”—was held on the 18th and 19th of November 2025 in Trieste (Italy), hosted by Università degli Studi di Trieste and jointly organized by Centro Studi Idraulica Urbana (CSDU) and Centro Studi Sistemi Idrici (CSSI), which are two Italian non-profit private societies engaged in urban water scientific research and dissemination [...] Full article

People with special needs often face barriers to participating in adapted outdoor leisure physical activities. A participatory action research project involving a nonprofit organization, a citizen with motor disabilities, and researchers aimed to co-develop a digital platform connecting people with special needs interested in outdoor leisure physical activities with trained volunteers. The adopted co-design methodology followed four stages: (1) Exploration (identifying users’ needs and preferences), (2) Co-design (defining key information and platform features), (3) Validation (prioritizing features), and (4) Development (implementing and testing the platform). This article focuses on stages 2, 3, and 4. During stage 2, key information and features were identified to support matching people with special needs and volunteers and informing users about adapted outdoor leisure physical activities. In stage 3, these elements were prioritized using eight key considerations, including technological (e.g., ease of use), environmental (e.g., avoiding redundancy with existing initiatives), organizational (e.g., availability of human resources), and financial factors (e.g., grant planning). Stage 4 resulted in the launch of Tandem Actif, followed by user testing to document user experience and guide improvements. This article details the application of co-design within a participatory action research project aimed at promoting safe, ethical, and accessible participation in outdoor leisure physical activities for people with special needs. Full article