This study explores how project team resilience influences agile practices, socio-cognitive spaces, and project success in road construction projects in Uganda. Data were gathered via questionnaires from 44 completed projects and analyzed using Partial Least Squares regression with SmartPLS. Findings indicate a strong positive relationship between agile practices, team resilience, and project success. Project team resilience emerges as a critical factor in achieving successful outcomes. Although socio-cognitive space does not directly affect project success, it significantly shapes team resilience, especially in the dynamic context of road construction. Interestingly, project team resilience does not mediate the link between agile practices and project success; instead, agile practices and socio-cognitive space independently influence project success, jointly explaining 58.3% of its variance. The study emphasizes the need to strengthen project team resilience during both the design and implementation stages of road construction projects. Elements like social capital, mastery approaches, and collective efficacy are highlighted as key to building project resilient teams capable of adapting to uncertainty and complexity. A major limitation of the research is its cross-sectional nature, which prevents analysis of changes over time. Future research is advised to adopt a longitudinal approach to better understand how these relationships evolve across a project’s lifecycle.

Purpose This study investigates the factors driving Indonesian youth’s voluntary compliance with the Fatwa to boycott Israeli-affiliated products amid governmental ambivalence. Grounded in moral foundations theory, it examines the extent to which national solidarity, self-enhancement values, religious beliefs and boycott impact beliefs interact to shape faith-driven consumer activism. Design/methodology/approach This study employed a quantitative approach, analyzing data from 410 Millennial and Gen Z respondents using SmartPLS 4 to assess direct, mediating and moderating effects. Framed within the ongoing Israel boycott, it captures real-time responses, revealing the extent to which contextual factors influence voluntary adherence to non-binding religious directives. Findings Defying conventional assumptions, the study reveals that national solidarity alone does not drive compliance with the Fatwa. Self-enhancement emerges as a key mediator, transforming collective identity into action. Beliefs about the boycott’s impact further moderate this relationship – stronger convictions shift focus toward practical efficacy, while weaker beliefs amplify reliance on collective identity and moral obligation. Religious belief intensifies the influence of self-enhancement, underscoring its pivotal role in shaping voluntary compliance. Practical implications Policymakers, religious authorities and civic advocates can leverage these findings to design evidence-based campaigns that strengthen moral identity, integrate faith-based motivation with civic responsibility and enhance public confidence in the collective efficacy of ethical boycotts, particularly in contexts where moral authority substitutes for direct state intervention. Originality/value This study extends moral foundations theory to a non-Western, faith-driven context, illuminating how moral authority, care and fairness interact with religiosity, self-enhancement and perceived efficacy to shape voluntary compliance with a non-binding Fatwa. It offers fresh insight into faith-based collective action sustained by moral persuasion rather than legal enforcement.

In the face of increasing situations of destruction, violence, hunger, forced migration and armed conflicts, this paper – drawing on previous research into affective, organisational and social convivence and recalling the appeals of the United Nations and a number of religious authorities on the need for the planet's population to live together in peace, harmony and justice – proposes a framework for interpreting convivence on a planetary scale in order to enable a multidimensional reading of situations and behaviours, thereby allowing the inhabitants of the planet to make their own representation of reality felt. The construct of convivence among peoples is defined and articulated along seven dimensions: culture of legality and respect for signed agreements; respect and tolerance of diversity; common goals and collective efficacy; solidarity and support; equity in access to and management of resources; power and international relations; trust and hope. The paper concludes with a call to researchers to form a network to promote studies on new forms of convivence and planetary development.

BackgroundCommunity mutual aid is a form of community engagement involving multiple stakeholders working together to provide both material and emotional support. During the COVID-19 pandemic in China, community group buying (CGB) exhibited distinct features of community mutual aid, reflected in its flexible product supply and spontaneous neighborhood support. However, the mechanisms driving the emergence of such mutual aid practices remain insufficiently explored.MethodsThis study employed a qualitative research design combining ethnographic observation and interpretive case analysis to examine whether, why, and how CGB in China transformed into community mutual aid practices during the lockdown, as well as the outcomes of this transformation. Data were collected primarily through semi-structured interviews (N = 12) and participant observation within WeChat groups.ResultsThe analysis identified six interrelated dimensions shaping the transformation of CGB into community mutual aid: disaster risk, community networks, participation pathways, psychological motivations, community resilience, and social inequality. Disaster risk acted as an external catalyst that activated social capital, while pre-existing community networks served as internal driving forces—together forming the prerequisites for this transformation. Participation pathways and psychological motivations further facilitated the reproduction of structural and relational social capital, constituting the core process of transformation. This transformation strengthened community resilience by reinforcing trust, reciprocity, and collective efficacy, but also revealed the “dark side” of social capital, as digital divides and unequal access to resources deepened social inequality.ConclusionOur findings offer new insights into CGB-based mutual aid in context of China’s crisis. This study not only contributes to the theoretical understanding of mutual aid–based community engagement, but also offers practical insights for mobilizing social capital in future public health emergencies. Further research should investigate the applicability of the CGB model across diverse sociocultural contexts and assess its long-term impact.

The task to manage the municipal solid waste (MSW) in the urban localities specifically in the cities which are growing faster is very challenging as the city administration need to cope up with the pace at which today’s cities are growing which is almost impossible without incorporating the latest technologies like Artificial Intelligence (AI). The static waste collection system which is being used conventionally currently facing issues like inadequate allocation of the resources required which in turn raises the overall costs of the operations and ultimately harm the environment, too. To overcome this, the present study introduces an innovative approach of combining Decision Support System (DSS) with machine learning driven waste generation forecasts. This study attempts to optimize the vehicle routing to improve the MSW collection efficacy in the city of Surat, India. The framework proposed here combines Long Short-Term Memory (LSTM) neural networks for MSW prediction with Capacitated Vehicle Routing Problem (CVRP) algorithms for the optimization of routes. We have developed our LSTM model using the dataset of past 16 years (2009-2024) obtained from Surat Municipal Corporation which achieved considerable forecasting accuracy with RMSE of 0.1095 and R² value of 0.93. The integrated DSS demonstrated considerable benefits in operations, cutting the overall collecting distance by 50.31% and the use of vehicles by 24% compared to traditional static routing methods. The technology uses predictive analytics to dynamically allocate the required resources helping the waste management authorities make decisions in real time. This study enhances sustainable urban development by offering a data-driven methodology that corresponds with the objectives of the Smart Cities Mission and Sustainable Development Goals (SDGs) 11, 12, and 13. The suggested architecture provides scalable methods for implementing a circular economy and making municipal waste management systems more environmentally friendly.

Gritty optimism is the belief that students can become more of who they are created to be based on evidence and experience. To achieve flourishing, eudaimonia , the goal education since Aristotle, educators must exhibit gritty optimism in the form of collective leadership and collective efficacy to support flourishing schools. In this study, we used school climate and teacher retention as components of flourishing. We conducted a path analysis with data from 22 schools to determine the relationship between collective leadership, collective efficacy, school climate, and teacher retention. Additional data from site visits that included focus groups and interviews triangulates our findings that collective leadership is a strong predictor of improved school climate and enhanced teacher retention.

This study investigates how primary school leaders build high levels of faculty trust by integrating Transformational (TL), Instructional (IL) and Distributed Leadership (DL) within a highly centralised education system. Using a sequential mixed-methods multi-case design, survey data from 1320 teachers across 85 public schools identified five high-trust sites for in-depth qualitative inquiry through interviews and observations. Principals in these schools enacted context-responsive blends of leadership; articulated shared moral purpose and vision (TL), sustained instructional quality and credibility (IL) and empowered teachers through participatory decision-making (DL). Trust functioned simultaneously as a precondition and a product of these practices, reinforcing collaboration, collective efficacy and professional learning despite systemic constraints. Contextual variables – particularly governance centralisation, school size and relational culture – shaped how integration occurred. School leaders can strengthen trust by modelling fairness and transparency, engaging meaningfully with teaching and learning and sharing decision-making that recognises teacher expertise. Leadership preparation programmes should subsequently prioritise the development of these relational, instructional and collaborative competencies that enable principals to build cohesive, trust-rich school cultures within policy-driven environments. Ultimately, the study advances understanding of how integrated, trust-based leadership sustains professional cohesion and organisational resilience, offering a transferable model for leadership in both centralised and decentralised education systems.

ABSTRACT This qualitative study examines how young people from marginalised sectors in Chile construct historical narratives about the October 2019 protests and identifies key elements that may foster future collective action. Based on interviews with nine participants (aged 24–29), the analysis reveals: (a) a narrative trajectory that begins in a negatively evaluated context—characterised by precarity, submission and individualism—and progresses toward experiences of solidarity and community organisation, before diverging during the constituent process, perceived either as a continuation of transformative momentum or as a moment of stagnation following the COVID‐19 pandemic; and (b) the incorporation of motivational frameworks that could encourage collective mobilisation, such as perceptions of relative deprivation, attribution of responsibility, beliefs in collective efficacy—particularly at the community level—and group normative content. Furthermore, the study highlights the importance of distinguishing between perceptions of efficacy at the community and institutional levels, proposing the integration of these multi‐level dynamics into future models of collective action.

Alongside the growing demand for educational reform, calls for commitment to teacher learning have increased exponentially in the last decade. Yet, little is known about the effects teacher learning across different educational systems (what we will also call “cross‐system teacher learning practices”) have on the work itself, or how the learning these teachers experience across schools is reflected in their engagement in practices and activities when they return to their original schools and classrooms. Through the lens of activity theory, this study aims to ascertain the experiences of groups of teachers in mainland China and Hong Kong who participate in cross‐system teacher learning activities. A qualitative multi‐case study was adopted where three schools were sampled in both Guangzhou and Hong Kong. Six principals and 12 teachers participated in the study. Interviews were collected and qualitatively analysed to categorise the major processes and effects of cross‐system teacher learning and capture the nature of cross‐system teacher learning in China. The study showed that: (a) education departments “set the tone” for teacher education across different educational systems; (b) teaching methods and “the other side” of educational development serve as boundary objects; (c) principals function as boundary brokers; and (d) different types of learning activities regulate teacher learning. Four recurrent themes emerged related to the impact of cross‐system teacher education: (a) awareness and understanding; (b) increased collective efficacy; (c) decision‐making and problem‐solving; and (d) teaching knowledge and skills. It is argued that equity and sustainability were central issues that teachers faced during the study. Relational trust contributed to teachers’ collaboration across different educational systems and community‐building. In the end of this article, suggestions to support cross‐system teacher learning are made and implications for future research are proposed.

In multi-arm clinical trials, several new treatments are often evaluated concurrently to identify the best and confirm their superiority over a control. In this paper, we propose a framework that introduces an intermediate stage aimed at assessing the collective efficacy of treatments retained after initial screening. Estimating the average effect of the selected treatments provides an interpretable measure of their collective potential and serves as a data-driven criterion for deciding whether to continue or terminate the trial. Consider experimental treatments whose effects are described by independent Gaussian responses with unknown means and a common variance. For the purpose of selecting the effective treatments (drugs) and estimating their average worth, we employ a two-stage drop-the-losers design (DLD). To get an idea about the structure of an optimal estimator, we first assume that the common variance is known. In the first stage of the design, data is collected to select a subset of experimental treatments so that the probability of including the best treatment is at least a prespecified level . This selection rule ensures that inferior treatments are eliminated while maintaining a minimum confidence that the best treatment remains among those advanced. Given this requirement, the design either advances all selected treatments to the next stage or stops for futility. The treatment(s) selected in the subset then proceed to the second stage for estimating their collective effectiveness through point estimation of their average worth, defined as the arithmetic average of their mean effects. Since the bias of estimators is crucial in clinical studies, we derive the uniformly minimum variance conditionally unbiased estimator (UMVCUE) of the worth of the selected treatments, conditioned on the indices of treatments selected at the first stage. The mean squared error and bias performances of the UMVCUE are compared with the naive estimator (maximum likelihood estimator) via a simulation study. For the unknown variance scenario, we propose a plug-in estimator based on the structure of the UMVCUE derived for the known variance case and study its performance through simulations. A real-life data example is also provided to illustrate an application of our findings.

ABSTRACT The study investigates the mediating role of organisational learning mechanisms in the relationship between principals' system thinking and collective teacher efficacy and senior management team innovation after accounting for students' socioeconomic backgrounds. A four‐source survey design was used, from a sample of 494 participants, principals, school management team members, and teachers, from 71 elementary schools. The results from structural equation modelling and bootstrapping analysis indicated that organisational learning mechanisms mediate the relationship between principals' systems thinking and collective teacher efficacy and senior management team innovation. Theoretical and practical implications for teacher education are discussed.

The influence of socio-psychological factors on environmental sustainability, including wetlands, is widely recognized; however, in some cases, their role is overlooked. The management and protection of wetlands is considered a collective action that requires the participation of all stakeholders. Based on this, a social identity-based behavioral intention model was used to identify and analyze the social and psychological factors affecting the intention of landowners to engage in sustainable wetland use. The studied population were landowners around Kani Barazan Wetland in Iran, who were surveyed using a cross-sectional study and selection of a representative sample through simple random sampling approach. Reliability and validity of the data gathering tool were evaluated using different indices. Findings showed that the constructs of participative efficacy (Beta = 0.158; Sig = 0.003) and collective efficacy (Beta = 0.183; Sig = 0.011) towards engagement in sustainable wetland use had significant effects on the intention. Landowners’ social identity had positive and significant effects on participative efficacy (Beta = 0.052; Sig = 0.007), collective efficacy (Beta = 0.045; Sig = 0.017), and intention to engage in sustainable collective management and use of the wetlands (Beta = 0.156; Sig = 0.014). Analysis of the moderating role of attitude showed that this construct positively and significantly moderates the effect of collective efficacy on the intention to engage in sustainable collective use of the wetlands (Beta = 0.070; Sig = 0.006). This study has practical contributions by providing practical suggestions for environmental policy makers, sustainable management planners of the wetlands, and decision makers at micro and macro levels. Also, by providing evidence in the field of the moderating effect of attitude on the relationship between collective efficacy and intention, it theoretically helps to develop the body of knowledge in the field of social-psychological indicators explaining the intention to engage in the sustainable collective management of the wetlands.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-26295-4.

Abstract Large language models (LLMs) have achieved superior performance in powering text-based AI agents, endowing them with decision-making and reasoning abilities that are analogous to those exhibited by humans. Concurrently, an emerging research trend is focused on extending these LLM-powered AI agents into the multimodal domain. This extension facilitates the interpretation and response of AI agents to diverse multimodal user queries, thereby handling more intricate and nuanced tasks. In this paper, we conduct a systematic review of LLM-driven multimodal agents, which we refer to as large multimodal agents ( for short). First, we introduce the essential components involved in developing and categorize the current body of research into four distinct types. Subsequently, we review the collaborative frameworks that integrate multiple , with the aim of enhancing collective efficacy. One of the critical challenges in this field is the diverse evaluation methods used across existing studies, which impedes effective comparison among different . Therefore, we compile these evaluation methodologies and establish a comprehensive framework to bridge the gaps. This framework aims to standardize evaluations, facilitating more meaningful comparisons. Concluding our review, we highlight the extensive applications of and propose potential future research directions. Our discussion aims to provide valuable insights and guidelines for future research in this rapidly evolving field.

Transformational leadership and organizational commitment: unlocking the potential of collective teacher efficacy

ABSTRACT Recent research has called for a more nuanced perspective on social life in structurally disadvantaged neighbourhoods. Drawing on a mixed-methods approach with a combination of Danish register data and in-depth interviews of residents and local key stakeholders, we investigate dimensions of community life, collective efficacy and structural conditions in six Danish neighbourhoods labelled “ghettos” by the Danish government. Our findings reveal considerable variation in structural characteristics, collective efficacy, and social life in these areas, challenging the homogeneity implied by the “ghetto” label. Despite their structural disadvantages, some neighbourhoods exhibit high levels of mutual support and organized activities driven by passionate residents or by targeted social initiatives. The results suggest that simplistic structural criteria and negative theoretical assumptions about disadvantaged neighbourhoods may overlook the unique social dynamics and resilience within these communities, and they underscore the importance of nuanced policies that recognize neighbourhood diversity in disadvantaged areas beyond one-size-fits-all categorizations.

Host plant resistance (HPR) has shown potential for suppressing sweetpotato whitefly, Bemisia tabaci Gennadius (Hemiptera: Aleyrodidae), in smooth (glabrous) crop varieties lacking leaf trichomes. The objective of this study was to investigate the interaction between HPR and insecticidal control, aiming to enhance their collective efficacy in whitefly management. Field trials were conducted in cotton and cantaloupe planted as strip crops at 2 locations in southern Georgia, United States: Tifton and Camilla. Treatments comprised 2 insecticides, based on the active ingredients pyriproxyfen and cyantraniliprole, with 2 different trichome conditions: pubescent (hairy), or smooth varieties. During the crop growing season, B. tabaci adult, egg, and nymph populations were monitored, and whitefly preferences were evaluated. Results indicate a preference of whiteflies for cotton and cantaloupe pubescent varieties, largely attributed to the presence of leaf trichomes. Pyriproxyfen predominantly reduced nymph populations, while cyantraniliprole was effective against both immatures and adults. Significant interactions among crop type, trichome presence, and insecticide application in determining B. tabaci abundance were measured. The glabrous cotton variety demonstrated greater whitefly suppression compared to glabrous melon, and cyantraniliprole exhibited a heightened initial mortality in pubescent cultivars. The study underscores the importance of selecting smooth leaf crop varieties in integrated B. tabaci management strategies. The results illuminate the need for developing real-world testing models with compatible strategies of integrated pest management (IPM) programs for B. tabaci and provide a wide-ranging insight into the interactive effects and dependency of multiple components involved in whitefly control in multicropping systems.

ABSTRACT We integrate the long short-term memory (LSTM) network into an ensemble model composed of the least squares support vector machine, echo state network, and extreme-learning machine for wind power generation forecasting. This study presents the first unified forecasting framework that combines these four machine learning techniques to evaluate their collective efficacy in improving prediction accuracy for wind power. Empirical analyses demonstrate that incorporating LSTM into the ensemble does not yield performance improvements over the three-method model. These findings indicate that the added complexity from LSTM does not enhance forecasting accuracy. Additionally, the choice of loss function is observed to have a negligible impact on the models’ predictive performance.

This study examines how equity, diversity, and inclusion (EDI) are understood and implemented within a large, diverse, urban school division in Canada. Using a mixed-methods approach and grounded in theoretical perspectives, including critical race theory, intersectionality, the ecology of inclusive education, and collective efficacy theory, we gathered insights from surveys and focus groups with educators, administrators, clinicians, educational assistants, caregivers, and students. Findings suggest that, while support for EDI is broad, the implementation is inconsistent and shaped by systemic barriers, resource constraints, and unclear leadership. We highlight the need for shared language, coordinated supports, and ongoing professional learning and instructional redesign. We offer a model for examining EDI at a systems level and share lessons to guide sustained transformation in other school organizations.

This study investigated the role of peer support in enhancing sewing skills among Garments Technology students through the framework of Social Learning Theory. Conducted during the 2024–2025 academic year in a Philippine technical-vocational institution, the research sought to determine how emotional, informational, instrumental, and motivational forms of peer support influence students’ skill acquisition and confidence in sewing. Employing a descriptive mixed-method design, data were collected from 30 purposively selected students using a researcher-made survey and semi-structured interviews. Quantitative data were analyzed using weighted mean, while qualitative responses underwent thematic analysis to complement statistical findings. The results revealed an overall mean of 3.08, indicating a generally positive perception of the peer support system in sewing laboratory classes. Among the four dimensions, informational support obtained the highest mean (3.26), suggesting that peer knowledge sharing, modeling, and demonstrations were the most influential in improving sewing competence. Emotional and motivational support also contributed significantly by fostering persistence, confidence, and reduced learning anxiety, while instrumental support facilitated practical assistance during sewing tasks. These findings affirm the centrality of observation, imitation, and social reinforcement in vocational learning contexts as articulated in Bandura’s Social Learning Theory. In summary, peer support systems play a vital role in developing technical proficiency, emotional resilience, and collaborative skills among Garments Technology students. Integrating structured peer learning strategies into vocational education programs may thus enhance both individual competence and collective efficacy, ultimately preparing learners for the teamwork-driven demands of the garment industry.

Against the backdrop of global biodiversity crises and climate change, integrated forest management (IFM) has emerged as a critical pathway for sustainable forest development. Grounded in the social–ecological system (SES) framework, we examine the mechanisms and pathways through which knowledge transfer influences IFM, with a focus on residents in China’s state-owned forest regions in the Northeast. By constructing an IFM-SES theoretical framework and utilizing survey data, we employ OLS regression and mediation effect models to empirically assess the driving effects of knowledge transfer on IFM and its heterogeneous impacts. We show that: (a) community-based knowledge transfer significantly enhances IFM; (b) knowledge transfer indirectly promotes IFM by fostering collective action efficacy, strengthening institutional rule compliance, and optimizing conflict resolution mechanisms; and (c) heterogeneity analysis indicates that the impact of knowledge transfer varies across governance models, with stronger effects observed among local residents compared to migrants. This study provides theoretical insights for integrating traditional ecological knowledge with modern scientific management and offers empirical support for global forest sustainability policy design.