Collaborative Knowledge Research Articles

THE INFLUENCE OF FIRM KNOWLEDGE CHARACTERISTICS ON TECHNOLOGICAL INNOVATION: A MULTILEVEL NETWORK STRUCTURE PERSPECTIVE

This study describes collaboration between firms and different organizations as a process of knowledge sharing, integrating inter-organizational collaboration networks and knowledge networks into a unified framework. It analyzes the bilayer structure of collaborative innovation networks, namely, the firm-knowledge bipartite network. The study investigates the impact of firm knowledge characteristics (diversity and uniqueness) on breakthrough and incremental innovation within collaborative innovation networks. The research employs patent data from Chinese A-share high-tech manufacturing companies listed from 2000 to 2018 and verifies the related hypotheses using a negative binomial regression model. The results suggest that, within collaborative innovation networks, firm knowledge diversity has a negative impact on breakthrough innovation but a positive impact on incremental innovation. On the other hand, firm knowledge uniqueness plays a positive role in breakthrough innovation but a negative role in incremental innovation. This study extends the understanding of firm technological innovation by considering both breakthrough and incremental innovation as distinct behaviors, providing a new perspective on the mechanisms underlying different innovation behaviors. By adopting a multilevel network structure approach to collaborative innovation, it contributes to a deeper understanding of internal and external factors influencing firm innovation behavior and expands the application scope of social network analysis.

Effects and mechanisms of analytics‐assisted reflective assessment in fostering undergraduates' collective epistemic agency in computer‐supported collaborative inquiry

AbstractBackgroundUndergraduates' collective epistemic agency is critical for their productive collaborative inquiry and knowledge building (KB). However, fostering undergraduates' collective epistemic agency is challenging. Studies have demonstrated the potential of computer‐supported collaborative inquiry approaches, such as KB—the focus of this study, and reflective assessment to foster collective epistemic agency.ObjectivesThis study used a quasi‐experimental design to examine the impact of reflective assessment on undergraduates' collective epistemic agency and the mechanisms of this impact.MethodsAn experimental class, comprising 40 undergraduates, engaged in KB inquiry enhanced by analytics‐assisted reflective assessment, while a comparison class, comprising 41 undergraduates, engaged in portfolio‐supported reflective assessment in KB inquiry. Classroom observations, audio recordings of group discussions and reflections, and student artefacts were collected in both conditions.Results and ConclusionsThe experimental class demonstrated significantly higher levels of collective epistemic agency than the comparison class, as indicated by their collective knowledge advancement and epistemic and metacognitive actions. Qualitative thematic analysis revealed that reflective assessment enhanced the undergraduates' collective epistemic agency through their collective monitoring and regulation of inquiry and ideas, negotiation and synthesis of the community's ideas, conceptualization of collective theories and identification of collective inquiry trajectories with an internal reflective structure.Major TakeawaysHigher‐level metacognitive actions are critical for productive collaborative inquiry and higher‐level epistemic agency that does not often occur naturally and should be promoted by appropriate scaffolding strategies. Students need data from learning analytics and accompanying prompt sheets to help them develop the internal metacognitive structure for agency and learning.

Productive interactions in a port city: a proximity approach to coordination in science-policy collaborations

Background:Many different concepts have been invoked in the literature to describe coordination between scientific and policy practices. However, a framework to understand different types of this boundary management is lacking, which allows ‘linear’ models and ‘gap’ metaphors to persist. Objectives:To operationalise the multidimensional ‘proximity’ approach from innovation studies in the context of coordination work between science and policy and employ it in a case study of hybrid research spaces in the port city of Rotterdam. Method:Semi-structured interviews and focus groups with scientists, policymakers and policy researchers involved in collaborative knowledge labs. Findings:Different proximity dimensions can both stimulate and impede productive interactions in collaborations between science and policy actors. There is no uniform mechanism to overcome coordination problems and different knowledge labs use different combinations of proximities. Discussion and conclusions:We conclude that the concepts of cognitive, social, organisational and geographic proximity enable a fine-grained articulation of the balancing act required for successful and enduring collaborative knowledge work between scientists and policymakers. The operationalisation of proximity for structured science-policy interactions led us to the insight that an analytical distinction can be made between ordering and operating enactments of proximity. Ultimately, we interpret this as two types of politics of knowledge production, and call on policymakers, researchers, and other involved parties to take this into consideration when organising structural knowledge collaborations between research and policy practices.

ASKAT: Aspect Sentiment Knowledge Graph Attention Network for Recommendation

In modern online life, recommender systems can help us filter unimportant information. Researchers of recommendation algorithms usually utilize historical interaction data to mine potential user preferences. However, most existing methods use rating data to mine user interest preferences, ignoring rich textual information such as reviews. Although some researchers have attempted to combine ratings and reviews for recommendation, we believe the following shortcomings still exist. First, existing methods are overly dependent on the accuracy of external sentiment analysis tools. Second, existing methods do not fully utilize the features extracted from reviews. Further, existing methods focus only on the aspects that users like, while ignoring the aspects that users dislike, and they cannot completely model users’ true preferences. To address the above issues, in this paper, we propose a recommendation model based on the aspect of the sentiment knowledge graph attention network (ASKAT). We first use the improved aspect-based sentiment analysis algorithm to extract aspectual sentiment features from reviews. Then, to overcome the difficulty in underutilizing the information extracted from the comments, we build aspects of sentiment-enhanced collaborative knowledge mapping. After that, we propose a new graph attention network that uses sentiment-aware attention mechanisms to aggregate neighbour information. Finally, our experimental results on three datasets, Movie, Amazon book, and Yelp, show that our model consistently outperforms the baseline model in two recommendation scenarios, click-through-rate prediction and Top-k recommendation. Compared with other models, the method shows significant improvement in both recommendation accuracy and personalised recommendation effectiveness.

Robustness of open source community multi-project knowledge collaboration network based on structural hole theory.

Nodes in the structural hole position play a key role in the multi-project network of the open source community (OSC). This paper studies the robustness of this network based on structural hole theory. First, a semantic-based multi-project KCN is constructed, and four node types are identified: knowledge contribution nodes, knowledge dissemination nodes, structural hole nodes (SHNs) and opinion leader nodes. Second, a robustness analysis model of the edge failures of these four key nodes is constructed. Third, a simulation test is conducted on the proposed model using empirical data from the Local Motors multi-project OSC. The results show that the KCN has the lowest robustness when facing the edge failure of opinion leader nodes, followed by knowledge dissemination nodes, knowledge contribution nodes, SHNs and random nodes. The edge failure of opinion leader nodes causes the lowest network robustness because of the propagation effect of these nodes. Additionally, SHN failure has only a small initial impact on connectivity, whereas knowledge collaboration efficiency decreases rapidly (i.e., the edge failure of SHNs causes the network to enter a state of high connectivity and low efficiency). The proposed model can be used to provide comprehensive and targeted management guidance for OSC development.

A Review of Research on Digital Empowerment, Knowledge Collaboration and Collaborative Innovation

A Review of Research on Digital Empowerment, Knowledge Collaboration and Collaborative Innovation

Collaborative Logistics 4.0 Operations among Small and Medium-Sized Enterprises in Rural Areas

This paper investigates the collaborative logistics operations of small and medium-sized enterprises situated in rural areas, with a focus on leveraging Industry 4.0 technologies. Recognizing the crucial role of SMEs in rural development, the study explores collaborations with customers, government, and other businesses. The proposed framework integrates two phases: identifying collaborators and logistics operations and addressing challenges through Industry 4.0 technologies. Findings reveal opportunities for SMEs in reverse logistics, knowledge collaboration, transportation, warehousing, and resource planning. Challenges are addressed with Industry 4.0 solutions, outlining a meaningful approach to rural logistics collaboration. The paper concludes with managerial principles for successful implementation in the specific context of rural areas in Norway.

Program for the development of digital competencies in teachers of the Stomatology career. Isla de la Juventud

Introduction: information and communication technologies are important tools for training and communication. To facilitate their work in the educational system as a requirement for change in the profile of the education professional, teachers must develop suitable digital skills to implement in their teaching-learning process. Objective: design a program for the development of digital skills in teachers of the Stomatology career of the Faculty of Medical Sciences of the Isla de la Juventud, 2022. Methods: a descriptive study was carried out, from a methodological perspective based on the qualitative paradigm. The universe was made up of 150 teachers, of which 40 made up the sample. The theoretical level research methods were used: analytical-synthetic, inductive-deductive and historical-logical analysis; at the empirical level: documentary analysis, survey and specialist criteria. Results: the need to train the teaching staff and guide the preparation of teachers in the appropriate use of computer techniques and resources, as well as in the preparation and development of virtual courses using the Moodle platform, was confirmed. Conclusions: information and communication technologies are fundamental in the teaching-learning process. The development of digital competencies in teachers shows a low level of performance; the expressed limitations focus mainly on knowledge and domains in content creation, communication and collaboration

An overview of environmental risk factors for type 2 diabetes research using network science tools.

Current studies lack a comprehensive understanding of the environmental factors influencing type 2 diabetes, hindering an in-depth grasp of the overall etiology. To address this gap, we utilized network science tools to highlight research trends, knowledge structures, and intricate relationships among factors, offering a new perspective for a profound understanding of the etiology. The Web of Science database was employed to retrieve documents relevant to environmental risk factors in type 2 diabetes from 2012 to 2024. Bibliometric analysis using Microsoft Excel and OriginPro provided a detailed scientific production profile, including articles, journals, countries, and authors. Co-occurrence analysis was employed to determine the collaboration state and knowledge structures, utilizing social network tools such as Gephi, Tableau, and R Studio. Additionally, theme evolutionary analysis was conducted using SciMAT to offer insights into research trends. The publications and themes related to environmental factors in type 2 diabetes have consistently risen, shaping a well-established research domain. Lifestyle environmental factors, particularly diet and nutrition, stand out as the most represented and rapidly growing topics. Key focal hotspots include sedentary and digital behavior, PM2.5, ethnicity and socioeconomic status, traffic and greenspace, and depression. The theme evolutionary analysis revealed three distinct paths: (1) oxidative stress-air pollutants-PM2.5-air pollutants; (2) calcium-metabolic syndrome-cardiovascular disease; and (3) polychlorinated biphenyls (PCBs)-persistent organic pollutants (POPs)-obesity. Digital behavior signifies a novel approach for preventing and managing type 2 diabetes. The influence of PM2.5 and calcium on oxidative stress and abnormal vascular contraction is intricately linked to microvascular diabetes complications. The transition from PCBs and POPs to obesity underscores the disruption of endocrine function by chemicals, elevating the risk of diabetes. Future studies should explore the connections between environmental factors, microvascular complications, and long-term outcomes in diabetes.

Bridging State and Society: College Students’ Collaborative Participation in Rural Construction in China

Collaborative participation of college students is an emerging trend in mitigating the brain drain from rural communities. However, the impact of the collaboration on community capacity building and the roles of these students have remained unclear. This article gives some theoretical concerns on collaborative planning in the specific context of China. It employs historical materials and illustrative cases to demonstrate that rural construction in China is an interactive process between state and society, with college students, exerting a mediating role. Cases indicate that during collaborative participation, expert knowledge and local knowledge are integrated.

Student Learning Improvement using Collaborative Presentations and Knowledge Sharing

Academic institutions hold the key responsibility for developing knowledge and skills to produce responsible and qualified engineering graduates. A lot of research has already been done regarding the importance of active learning techniques for engineering education. Active learning techniques help both teachers and students in many ways. Learning by teaching method encourages students to take the role of teacher to enrich their learning experience. This paper addresses the implementation of outcome-based education with Learning by presentation tactics and creating a databank of related subjects for student reference. This method improves a student’s communication skills, presentation skills, confidence level and thinking ability. Students were asked to study assigned topics and prepare a detailed presentation. Each student will teach the assigned topic to the whole class and should clear the doubts about the topic asked by peers. All the presentations are well arranged according to the topic and application. The whole bunch of presentations are returned to all the students for their reference and study when they face doubts or difficulties. Students were enthusiastic regarding their topic and presentations. There was healthy competition, and everyone was working hard to prove themselves. Two internal assessment modules are implemented in the same class which are compared using statistical methods. The results were analyzed using Statistical Package for the Social Sciences (SPSS) software and show that the method assists students learning and understanding students’ skills and performance.. Keywords— Collaborative Presentations, Knowledge Sharing, Learning, Teaching, SPSS, ANOVA

Developing Effective Community Collaborations: A Qualitative Case Study of Three High‐Quality Partnerships Set in Aotearoa New Zealand

There is widespread and growing support and requirement for researchers and larger organisations to collaborate with communities. This ensures that social, educational, or health programmes are relevant and acceptable and address the needs of groups that experience inequity. There is limited research about the processes and approaches that impact successful collaboration. The aim of this study was to identify the best‐practice processes used to develop and sustain collaborative partnerships between community members and formal organisations in Aotearoa New Zealand. Using a qualitative case study methodology and guidance from our community advisory group, we selected three effective collaborations with groups that experienced inequity in Aotearoa New Zealand. We examined these by reviewing their publicly available documents and conducting focus group discussions and interviews with key stakeholders. We coded and analysed transcriptions thematically to develop case study summaries of findings and then conducted cross‐case analysis to identify themes inherent in the data. Seven themes emerged from the data: (1) work together under Te Tiriti to ensure that collaborations are built on the articles of this founding document of Aotearoa New Zealand; (2) start before the beginning by forming strong relationships with diverse and representative community members; (3) walk the talk by using critically reflexive processes built on shared values and equal power relations; (4) use pencils not pens to implement ensuring an iterative project process; (5) recognise all contributions and especially the value of lived experience and local knowledge; (6) journey at a pace that allows all to participate; and (7) listen twice, talk once to give priority to hearing quieter voices. These seven practices can be utilised by other collaborative initiatives to increase genuine and power‐shared participation. These participatory processes can make sure that collaborative projects respect local knowledge, indigenous culture, and respond iteratively to community needs.

Cloud Computing Resource Scheduling Algorithm Based on Unsampled Collaborative Knowledge Graph Network

Cloud Computing Resource Scheduling Algorithm Based on Unsampled Collaborative Knowledge Graph Network

Co-creation in healthcare and research to improve service delivery for young people with chronic pain.

The process of co-creation can enable more effective, agile and integrated healthcare solutions achieving outcomes that effectively translate to healthcare delivery. Collaborative knowledge generation is particularly important in fields such as pediatric chronic pain where there is a complex interplay between biological, social, environmental, emotional, familial and school factors. The co-creation initiative described here was designed to amplify the voices of youth with chronic pain and their families and a variety of key stakeholders and generate novel approaches to the management of chronic pediatric pain in the setting of the South Australian Pediatric Chronic Pain Service. Stakeholders who were identified as influential in this ecosystem were allocated to 6 groups. A skilled facilitator co-prepared and delivered the workshop, engaging participants in three structured activities. Firstly, the challenges to service delivery were outlined, followed by the groups discussing what is currently working. The second activity involved lateral thinking without restrictions on time, resources or system to generate solutions to the key challenges presented. Finally, stakeholders were asked to agree on a generated solution from Activity 2 and build a case for actionable implementation of this solution. Data were summarised by the workshop facilitator and reflexive thematic analysis was used for coding and generating themes. From Activity 1, six themes collectively demonstrated that stakeholders valued many of the existing strengths of the service delivery, but some areas such as pain education was undervalued. Activity 2 generated solutions from high-level ideas to more day-to- day management strategies. Each of six groups generated unique solutions to an identified challenge for Activity 3. Engaging a wide variety of stakeholders in collaborative knowledge generation successfully provided the South Australian Pediatric Chronic Pain Service with a variety of novel, scalable solution across the healthcare continuum. Equally important is that this initiative helped to raise awareness about the complex issues faced in pediatric chronic pain care and helped to establish new partnerships that have led to enhanced service delivery.

Unveiling the power of knowledge graph embedding in knowledge aware deep recommender systems for e-commerce: A comparative study

Recommendation systems address content delivery system information overload. Recent recommender systems include knowledge-aware deep recommender models. These models train user and item embeddings using Graph Neural Networks and operate on collaborative knowledge graphs that combine user-item interactions with item-entity relationships to deliver more item information. Certain models employ a two-step learning procedure wherein the primary objective is to generate recommendations while simultaneously training knowledge graph embeddings. By co-learning, the models are able to comprehend the structural connections that exist between entities and relations, while also improving user embeddings through the use of previous encounters. The objective of this research endeavour is to assess the efficacy of cutting-edge models through the integration of knowledge graph embedding co-learning and the manipulation of embedding techniques. Co-learning boosts quicker learning and enhances the precision of recommendations, according to empirical findings. When a KG embedding layer was incorporated into KGCN, the recall metric outperformed the initial model by as much as 37%. Compared to translational embedding techniques, RotatE decreased training duration by 18% and demonstrated a noteworthy 15% improvement in the recall metric. The study’s outcome offer valuable guidance for enhancing recommendation accuracy and reducing training time for models incorporating Knowledge Graph (KG) embeddings. Furthermore, the study introduces a new application for complex-valued KG embeddings.

Social Emotional Learning Modeling for Enhancement in Preschool Education

Abstract Social-emotional learning is an important part of young children’s overall development and has a positive effect on their social development, good emotional and moral character, and the formation of a healthy personality. This paper proposes a social-emotional learning model based on collaborative knowledge construction. It investigates the social-emotional learning ability of 50 toddlers in two large classes of X kindergarten in G city by combining the Peer Interaction Ability Scale, Emotional Understanding Test, and Interpersonal Problem Solving Test. The factors that affect social-emotional learning ability in the activities of the older class were studied to explore the enhancement of the social-emotional learning model in preschool education. The results showed that the social-emotional learning model can significantly (p<0.05) enhance the social-emotional learning level of young children in five dimensions: self-awareness, self-management, social awareness, interpersonal skills, and making responsible decisions. This study enriches the existing theoretical system of social-emotional learning and provides theoretical and practical support.

The Role of Relationship Quality in Collaborative Knowledge Networks and Organizational Learning in Enhancing the Quality of Hajj Services

The Role of Relationship Quality in Collaborative Knowledge Networks and Organizational Learning in Enhancing the Quality of Hajj Services

Understanding Collaborative Design Practice Through Self-Study

Designing online teacher professional development (oTPD) grounded in participatory practices is complex. An intense interdisciplinary collaboration of teacher educators, online learning experts, and instructional designers is needed. Achieving shared understanding is essential for successful collaboration, yet varied perspectives of interdisciplinary experts can cause tensions. Under the right conditions, conflict can be positive and productive. This study of collaborative design practice examined the process of aligning technology and pedagogy when designing participatory oTPD using the self-study methodology. Data analysis revealed relevant interrelationships and uncovered a consistent pattern related to purposeful use of technology. While self-study was an effective inquiry method and provided valuable insights into our practice, it also fostered an environment of trust and collaborative knowledge exchange necessary for successful joint problem solving, cognitive synchronization, and innovation in interdisciplinary design teams.

Incentivizing Socio-Ethical Integrity in Decentralized Machine Learning Ecosystems for Collaborative Knowledge Sharing

Incentivizing Socio-Ethical Integrity in Decentralized Machine Learning Ecosystems for Collaborative Knowledge Sharing

Pursuing openness in the digital age: Insights from client–contractor knowledge collaboration at the project front end

Digitalization, with its potential to enhance the openness of client–contractor knowledge collaboration (KC) at the front end of complex engineering projects, is gaining traction among project scholars and practitioners. Despite this growing interest, project actors still struggle to bring client and contractor experts into an open, digitally enabled collaborative space where they can freely access and cocreate project-related knowledge. In this context, our case study explores client–contractor KC in the front-end phase of oil and gas projects in Norway to understand why project actors struggle to achieve KC openness in the digital age. Based on our qualitative analysis, we developed a model that displays two intertwined aspects giving rise to tensions between knowledge sharing and protection. First, we show that these tensions stem from fragmented awareness of the expertise in the collaborating project organization. Second, we highlight how intrainstitutional complexity, instantiated in coexisting conflicting logics of digital and collaborative action, underlies divergent beliefs and behavior toward client–contractor KC and its digitalization. We offer novel insights into the project management literature by showcasing how organizational heterogeneity, in terms of expertise and institutions, challenges project organizations' pursuit of open, digitally enabled client–contractor KC during the front-end project phase.