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This systematic literature review highlights the growing global interest in self-managed organizations (SMOs), with significant contributions emerging from the United States and the European Union—particularly from Arizona State University and Nyenrode Business Universiteit. Prominent scholars such as Charles Manz and Susan G. Cohen have shaped the theoretical and empirical foundations of this field. The findings indicate that SMOs enhance job satisfaction, commitment, and performance by fostering autonomy, shared decision-making, and a sense of ownership among employees. However, challenges persist in implementation, including resistance to change, complexity in decision-making, and leadership gaps. Drawing on Peter Senge’s Learning Organization Framework, the review identifies best practices, including clarifying roles, co-creating shared visions, fostering transparency, promoting continuous learning, and reinforcing accountability. It concludes by underscoring the need for future research on the long-term effectiveness of SMOs, the evolving role of leadership, and the influence of technology and cultural contexts on self-management practices.

Background Interest in value-based healthcare, generally defined as providing better care at lower cost, has grown worldwide, and learning health systems (LHSs) have been proposed as a key strategy for improving value in healthcare. LHSs are emerging around the world and aim to leverage advancements in science, technology and practice to improve health system performance at lower cost. However, there remains much uncertainty around the implementation of LHSs and the distinctive features of these systems. This paper presents a conceptual framework that has been developed in Canada to support the implementation of value-creating LHSs. Methods The framework was developed by an interdisciplinary team at the Institut national d’excellence en santé et en services sociaux (INESSS). It was informed by a scoping review of the scientific and grey literature on LHSs, regular team discussions over a 14-month period, and consultations with Canadian and international experts. Results The framework describes four elements that characterise LHSs, namely (1) core values, (2) pillars and accelerators, (3) processes and (4) outcomes. LHSs embody certain core values, including an emphasis on participatory leadership, inclusiveness, scientific rigour and person-centredness. In addition, values such as equity and solidarity should also guide LHSs and are particularly relevant in countries like Canada. LHS pillars are the infrastructure and resources supporting the LHS, whereas accelerators are those specific structures that enable more rapid learning and improvement. For LHSs to create value, such infrastructures must not only exist within the ecosystem but also be connected and aligned with the LHSs’ strategic goals. These pillars support the execution, routinisation and acceleration of learning cycles, which are the fundamental processes of LHSs. The main outcome sought by executing learning cycles is the creation of value, which we define as the striking of a more optimal balance of impacts on patient and provider experience, population health and health system costs. Conclusions Our framework illustrates how the distinctive structures, processes and outcomes of LHSs tie together with the aim of optimising health system performance and delivering greater value in health systems.

The number of adult learners who participate in online learning has rapidly grown in the last two decades due to online learning's many advantages. In spite of the growth, the high dropout rate in online learning has been of concern to many higher education institutions and organizations. The purpose of this study was to determine whether persistent learners and dropouts are different in individual characteristics (i.e., age, gender, and educational level), external factors (i.e., family and organizational supports), and internal factors (i.e., satisfaction and relevance as sub-dimensions of motivation). Quantitative data were collected from 147 learners who had dropped out of or finished one of the online courses offered from a large Midwestern university. Dropouts and persistent learners showed statistical differences in perceptions of family and organizational support, and satisfaction and relevance. It was also shown that the theoretical framework, which includes family support, organizational support, satisfaction, and relevance in addition to individual characteristics, is able to predict learners' decision to drop out or persist. Organizational support and relevance were shown to be particularly predictive. The results imply that lower dropout rates can be achieved if online program developers or instructors find ways to enhance the relevance of the course. It also implies that adult learners need to be supported by their organizations in order for them to finish online courses that they register for.

Introduction Continuous quality improvement (CQI) initiatives are commonly used to enhance patient safety and quality of care. A novel South Australian Local Health Network (SALHN) Continuous Improvement Program (CIP009) has integrated a top-down model of executive-directed change initiatives, with a bottom-up approach of clinician designed interventions to address an organisational-wide goal of improved patient flow. This study evaluated the strengths and challenges of CIP009 implementation from the perspective of participants and deliverers. Methods A qualitative study was conducted in 2023/2024 to evaluate the implementation of CIP009 and 12 associated quality improvement projects. Semi-structured interviews and focus groups were conducted with key stakeholders (executives, coaches and CIP009 fellows) and guided by the Consolidated Framework for Implementation Research (CFIR). A document review and observations of CIP009 team meetings were also conducted. Data were analysed inductively using thematic analysis, then deductively mapped against the five CFIR domains. Results Thirty-one participants were interviewed individually or in focus groups, two presentation days and six team meetings were observed, and 78 documents were reviewed. Seven key themes were identified highlighting key challenges and strengths of CIP009 implementation within the SALHN setting. These included four key strengths: the CIP framework and culture (the flexible framework, common language, training, and a culture of flattened hierarchy); the benefits of support from a dedicated, internal improvement Faculty (wrap around support from coaches); the advantages of an enthusiastic team member disposition and incentives (vested interests to enhance workflow and patient outcomes); and e ffective teams and team composition (teams comprised of senior clinician change agents). Three key challenges included: workforce and organisation-level challenges (individual workloads, workforce capacity, and data access); team cohesion, logistics and stakeholder engagement challenges (issues in the way teams worked together); and training and support shortcomings (the training course, and the top-down nature of CIP009). Conclusion This evaluation identified that CIP009 was considered an effective multifaceted CQI program. The strengths of CIP009 support a learning health system (a data driven model, utilising systematic frameworks, with commitment from leadership, and a culture of continuous learning). Further integration of implementation science principles may support the program to overcome the key challenges identified. These findings will inform and guide improvement efforts within future iterations of CIP.

PurposeThe purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.Design/methodology/approachSample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.FindingsSynthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.Originality/valueParticularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

This paper develops a motivation, opportunity, and ability framework to examine knowledge sharing and organizational learning as a mean to drive entrepreneurship and innovation in complex organizational networks. Utilizing the theoretical linkages and antecedents suggested in established corporate entrepreneurship models that identify what is necessary for innovation to occur in existing organizations, we offer both a theoretical model and an additional tool of analysis looking at how corporate entrepreneurial activity emerges in organizational networks. Using survey data collected from 200 franchise operators of a single large hybrid organization, our results demonstrate how knowledge sharing and organizational learning are associated with the motivation, opportunity, and ability to act within the corporate entrepreneurial context. Moreover, this motivation, opportunity, and ability framework was observed to provide a complementary tool to traditional measures of CE (e.g., CEAI from Hornsby et al. in J Bus Ventur 17(3):253-273, 2002) as it provided insights into functional and process variables affecting corporate entrepreneurial activity. As such, this research introduces both practical and theoretical implications that further our understanding of how to develop, manage, and leverage corporate entrepreneurship in a complex organizational network to achieve both operational performance and entrepreneurial innovation.

The widespread use of smart devices and the numerous security weaknesses of networks has dramatically increased the number of cyber-attacks in the internet of things (IoT). Detecting and classifying malicious traffic is key to ensure the security of those systems. This paper implements a distributed framework based on deep learning (DL) to prevent many different sources of vulnerability at once, all under the same protection system. Two different DL models are evaluated: feed forward neural network and long short-term memory. The models are evaluated with two different datasets (i.e.NSL-KDD and BoT-IoT) in terms of performance and identification of different kinds of attacks. The results demonstrate that the proposed distributed framework is effective in the detection of several types of cyber-attacks, achieving an accuracy up to 99.95% across the different setups.

Values (why to conserve) and Attributes (what to conserve) are essential concepts of cultural heritage. Recent studies have been using social media to map values and attributes conveyed by the public to cultural heritage. However, it is rare to connect heterogeneous modalities of images, texts, geo-locations, timestamps, and social network structures to mine the semantic and structural characteristics therein. This study presents a methodological framework for constructing such multi-modal datasets using posts and images on Flickr for graph-based machine learning (ML) tasks concerning heritage values and attributes. After data pre-processing using pre-trained ML models, the multi-modal information of visual contents and textual semantics are modelled as node features and labels, while their social relationships and spatio-temporal contexts are modelled as links in Multi-Graphs. The framework is tested in three cities containing UNESCO World Heritage properties—Amsterdam, Suzhou, and Venice— which yielded datasets with high consistency for semi-supervised learning tasks. The entire process is formally described with mathematical notations, ready to be applied in provisional tasks both as ML problems with technical relevance and as urban/heritage study questions with societal interests. This study could also benefit the understanding and mapping of heritage values and attributes for future research in global cases, aiming at inclusive heritage management practices. Moreover, the proposed framework could be summarized as creating attributed graphs from unstructured social media data sources, ready to be applied in a wide range of use cases.

Purpose In this paper, using the antecedents, decisions and outcomes (ADO) framework, the factors/key performance indicators (KPIs) most relevant for creating or building a learning organization (LO) are identified. This study aims to contribute to the field of knowledge management (KM) in terms of introducing KPIs to foster a business organization with a continuous learning process, mechanisms of knowledge creation and memorization. Design/methodology/approach In total, 57 papers were selected for this systematic literature review (SLR) from Web of Science and Scopus covering the period 1985–2019. Findings The 12 most relevant KPIs are identified based on the literature survey conducted in the field of LO. Research limitations/implications The managerial implications of this review paper will be an added advantage to the modern business organization worldwide that have adopted KM practices to foster knowledge management with information technology (IT) infrastructure. As IT infrastructure focuses on knowledge acquisition, dissemination and storage but the KPIs revealed through this review will help in transforming stored information as learning for the organization to improve its overall performance. Originality/value This review synthesizes prior studies and provides directions for future research.

Background The engagement of community partners in equitable partnerships with academic teams is necessary to achieve health equity. However, there is no standardized approach to support bidirectional engagement among research stakeholders in the context of partnership equity at each phase of the research process. Objective We describe the development of a systematic framework along with competencies and tools promoting bidirectional engagement and equity within community–academic partnerships at each phase of the research process. Design We conducted a four‐step research process between November 2020 and December 2023 for framework development: (1) a narrative literature review; (2) expansion of existing bidirectional, equitable framework; (3) a scientific review with two groups of cognitive interviews (five community engagement researchers and five community leaders and members); and (4) three community‐based organization leader focus groups. Thematic analysis was used to analyse focus group data. Results Using results of each step, the framework was iteratively developed, yielding four phases of the bidirectional engagement and equity (BEE) research framework: Relationship building and assessment of goals and resources (Phase I); form a community–academic partnership based on shared research interests (may include multilevel stakeholders) (Phase II); develop a research team comprising members from each partnering organization (Phase III); and implement the six‐step equitable research process (Phase IV). Bidirectional learning and partnership principles are at the core of the partnership, particularly in Phases II–IV. Competencies and tools for conducting an equitable, engaged research process were provided. Discussion This conceptual framework offers a novel, stepwise approach and competencies for community–academic partners to successfully partner and conduct the research process equitably. Conclusion The BEE research framework can be implemented to standardize the conduct of an equitable, engaged research process within a community–academic partnership, while improving knowledge and trust across partners and, ultimately, an increased return on investment and sustainability to benefit both partners in the area of health outcomes and ultimately health equity. Patient or Public Contribution The development of this framework was co‐led with a community organization in which two leaders in the organization were equitably involved in each phase of the research process, including grant development, study design, participant recruitment, protocol development for focus groups and community and researcher review, framework design and content and dissemination of this manuscript as a co‐author. For grant development, the community leader completed the give‐get grid components for them as a partner. They also wrote up their lived experience in the research process for the progress report. For the focus groups, one community leader co‐led the focus group with the academic partner. For the narrative review, the community leaders did not actively conduct the narrative review but observed the process through the academic partners. One community leader wrote the section ‘relationship building’ and ‘bidirectional learning’ sections with the assistance of the academic partner, while they both equally provided input on other sections of the manuscript alongside academic partners. The community leaders have extensive experience in leading programmes, along with partnering with researchers to address health equity issues and improve health outcomes.