Collaborative Behavior Research Articles

The role of individual preparation before collaboration: An exploratory study on students’ computer-supported collaborative argumentation in a primary classroom

ABSTRACT Background Collaborative learning is widely applied in real-world classrooms while young learners still have challenges engaging in high-quality knowledge co-construction processes. Researchers suggested an individual preparation activity before collaboration. However, there remains a limited understanding of the role of individual preparation on students’ collaborative learning. Method Conducted in a fifth-grade English language class in a Singapore primary school, this study explored students’ collaborative learning outcome and process under two conditions: individual preparation before collaboration (With-IP) and immediate collaboration (Without-IP) conditions. Student groups’ collaborative argumentation artifacts were collected and coded. Process analysis was conducted to reveal the distribution and transitional pattern of students’ verbal discussions and online collaboration behaviors. Findings This study reveals that individual preparation (With-IP) significantly enhanced the quality of collaborative argumentation compared to no preparation (Without-IP), by fostering more idea elaboration, deeper engagement with content knowledge, and higher quality of arguments. However, the students were also found to make more coordination and regulation efforts in the With-IP condition than Without-IP condition. Contribution This research underscores the role of individual preparation on collaborative learning processes and outcomes. This insight is pivotal for educators and practitioners in tailoring collaboration scripts to the objectives of classroom teaching and learning.

A Structural Equation Model on Interpersonal Trust in the Context of School Climate, Collaborative Behavior and Leadership Practices of School Heads

A Structural Equation Model on Interpersonal Trust in the Context of School Climate, Collaborative Behavior and Leadership Practices of School Heads

Focused Team Engagements to Enhance Interprofessional Collaboration and Safety Behaviors among Novice Nurses and Medical Residents.

Team communication remains a challenge in hospital settings. Hospital-based teams are diverse, team composition changes daily, and team members are frequently not co-located. Novice nurses and medical residents entering the workforce during the coronavirus 2019 pandemic experienced higher communication challenges than before and lacked adequate opportunities for interprofessional learning and communication. We evaluated perceptions of safety and communication among novice nurses and medical residents after a 1-hour focused team engagement consisting of an interprofessional virtual simulation and debrief. We conducted a retrospective pre/post survey to measure perceptions of interprofessional collaboration using the Interprofessional Socialization and Valuing Scale. Sixty-eight pediatric nurse residents and medical residents participated in the survey. Overall, the focused team engagements significantly improve participants' perceptions of interprofessional collaboration, with participants showing statistically significant improvement in seven of nine retrospective pre/post survey questions. When analyzing by discipline, nurse residents show stronger gains than medical residents. The interprofessional structured debriefings encourage nurses and medical residents to collaborate and discuss important safety topics away from bedside stressors. After completing the virtual simulation, the outcomes show improved perceptions of interprofessional collaboration and enhanced knowledge of safety techniques.

Recognition of carrier-based aircraft flight deck operations based on dynamic graph

Accurate recognition of flight deck operations for carrier-based aircraft, based on operation trajectories, is critical for optimizing carrier-based aircraft performance. This recognition involves understanding short-term and long-term spatial collaborative relationships among support agents and positions from long spatial–temporal trajectories. While the existing methods excel at recognizing collaborative behaviors from short trajectories, they often struggle with long spatial–temporal trajectories. To address this challenge, this paper introduces a dynamic graph method to enhance flight deck operation recognition. First, spatial–temporal collaborative relationships are modeled as a dynamic graph. Second, a discretized and compressed method is proposed to assign values to the states of this dynamic graph. To extract features that represent diverse collaborative relationships among agents and account for the duration of these relationships, a biased random walk is then conducted. Subsequently, the Swin Transformer is employed to comprehend spatial–temporal collaborative relationships, and a fully connected layer is applied to deck operation recognition. Finally, to address the scarcity of real datasets, a simulation pipeline is introduced to generate deck operations in virtual flight deck scenarios. Experimental results on the simulation dataset demonstrate the superior performance of the proposed method.

An innovative sliding-controllable laminated rubber bearing for enhancing seismic performance of highway bridges

Economical laminated rubber bearings have been widely utilized in highway bridges for their exceptional performance under service conditions. These bearings effectively mitigate seismic responses during earthquakes through shear deformation or sliding, contingent upon their bonding methods, whether bonded or unbonded. Nevertheless, past seismic events have underscored vulnerabilities, with unbonded laminated rubber bearings susceptible to excessive displacement and bonded bearings prone to fracture during large earthquakes. To address these seismic deficiencies and improve bridge seismic performance, a novel controllable sliding laminated rubber bearing (SC-LRB) is proposed in this study. The SC-LRB seamlessly integrates the shear-deforming behavior of bonded laminated rubber bearings (B-LRB) with the frictional sliding behavior of unbonded bearings (U-LRB). A quasi-static experiment was initially conducted to investigate the cyclic behaviors of the SC-LRB, leading to the development and calibration of the numerical model for the bearing. Subsequent nonlinear time history analyses were carried out to evaluate the influence of SC-LRBs on the seismic performance of bridges. Results indicate that, with its three-stage working mechanism (pre-sliding, sliding, and post-sliding), the SC-LRB exhibits a friction-shear collaborative behavior, effectively balancing the energy dissipation and recentering capacities of the bearing during earthquakes. Bridges equipped with the SC-LRB demonstrate an ability to maintain balance between controlling bearing displacements and isolating pier seismic demands. The proposed SC-LRB presents promising potential for enhancing the seismic resilience of highway bridges.

Community detection on elite mathematicians’ collaboration network

Abstract Purpose This study focuses on understanding the collaboration relationships among mathematicians, particularly those esteemed as elites, to reveal the structures of their communities and evaluate their impact on the field of mathematics. Design/methodology/approach Two community detection algorithms, namely Greedy Modularity Maximization and Infomap, are utilized to examine collaboration patterns among mathematicians. We conduct a comparative analysis of mathematicians’ centrality, emphasizing the influence of award-winning individuals in connecting network roles such as Betweenness, Closeness, and Harmonic centrality. Additionally, we investigate the distribution of elite mathematicians across communities and their relationships within different mathematical sub-fields. Findings The study identifies the substantial influence exerted by award-winning mathematicians in connecting network roles. The elite distribution across the network is uneven, with a concentration within specific communities rather than being evenly dispersed. Secondly, the research identifies a positive correlation between distinct mathematical sub-fields and the communities, indicating collaborative tendencies among scientists engaged in related domains. Lastly, the study suggests that reduced research diversity within a community might lead to a higher concentration of elite scientists within that specific community. Research limitations The study’s limitations include its narrow focus on mathematicians, which may limit the applicability of the findings to broader scientific fields. Issues with manually collected data affect the reliability of conclusions about collaborative networks. Practical implications This study offers valuable insights into how elite mathematicians collaborate and how knowledge is disseminated within mathematical circles. Understanding these collaborative behaviors could aid in fostering better collaboration strategies among mathematicians and institutions, potentially enhancing scientific progress in mathematics. Originality/value The study adds value to understanding collaborative dynamics within the realm of mathematics, offering a unique angle for further exploration and research.

The Manta mystique: Destination image and its effect on tourist citizenship behavior and willingness to sacrifice

The COVID-19 pandemic has forced tourism managers to reevaluate their strategies for attracting visitors and aiding in the recovery of destinations. This new approach emphasizes increased tourist engagement with the destination and stresses the importance of concepts like tourist citizenship behaviors and their willingness to sacrifice. This research investigates the correlations among destination image, tourist citizenship behaviors, and the willingness to sacrifice. By examining these factors, the study provides valuable information into the emotional and cognitive aspects of tourists’ interactions with the destination image and their collaborative behaviors. This information can be used to enhance the visitor experience and the attraction of the destination. Conducted in the captivating city of Manta, Ecuador, this research aims to address the gap in understanding tourists’ perceptions of South American destinations, presenting a unique perspective on the region's tourism potential. Beyond advancing tourism literature, this comprehensive study offers practical approaches for destination marketing organizations to attract tourists and enhance destination competitiveness.

CGJO: a novel complex-valued encoding golden jackal optimization

Golden jackal optimization (GJO) is inspired by mundane characteristics and collaborative hunting behaviour, which mimics foraging, trespassing and encompassing, and capturing prey to refresh a jackal’s position. However, the GJO has several limitations, such as a slow convergence rate, low computational accuracy, premature convergence, poor solution efficiency, and weak exploration and exploitation. To enhance the global detection ability and solution accuracy, this paper proposes a novel complex-valued encoding golden jackal optimization (CGJO) to achieve function optimization and engineering design. The complex-valued encoding strategy deploys a dual-diploid organization to encode the real and imaginary portions of the golden jackal and converts the dual-dimensional encoding region to the single-dimensional manifestation region, which increases population diversity, restricts search stagnation, expands the exploration area, promotes information exchange, fosters collaboration efficiency and improves convergence accuracy. CGJO not only exhibits strong adaptability and robustness to achieve supplementary advantages and enhance optimization efficiency but also balances global exploration and local exploitation to promote computational precision and determine the best solution. The CEC 2022 test suite and six real-world engineering designs are utilized to evaluate the effectiveness and feasibility of CGJO. CGJO is compared with three categories of existing optimization algorithms: (1) WO, HO, NRBO and BKA are recently published algorithms; (2) SCSO, GJO, RGJO and SGJO are highly cited algorithms; and (3) L-SHADE, LSHADE-EpsSin and CMA-ES are highly performing algorithms. The experimental results reveal that the effectiveness and feasibility of CGJO are superior to those of other algorithms. The CGJO has strong superiority and reliability to achieve a quicker convergence rate, greater computation precision, and greater stability and robustness.

Attending 12 weekly sessions of Forest School sessions improves mood and cooperation in 7–8-year-old children

ABSTRACT Being in nature improves wellbeing and health, but opportunities for children to spend time outside in a natural environment can be limited. Forest School programmes offer this opportunity. This study aimed to examine whether participation in a 12-week Forest School programme would improve mood, self-esteem, spatial cognition and collaborative behaviour. One hundred and seventy-nine UK school children aged 7–8 years took part, with a final sample comprising 151 children. A Forest School and classroom group were assessed at baseline and after 12 weeks. Children who attended the Forest School rated themselves as less tired, less bored, calmer and happier than children in the classroom. There were also greater improvements in cooperation in Forest School attendees. There were no differences in self-esteem, but some initial evidence of better competence-related self-esteem. Performance on the spatial cognition task was unchanged. Our findings suggest that Forest School participation is beneficial for children’s mood and cooperation.

Integration of Collaborative Filtering Into Naive Bayes Method to Enhance Student Performance Prediction

This article introduces a novel method that integrates collaborative filtering into the naive Bayes model to enhance predicting student academic performance. The combined approach leverages collaborative user behavior analysis and probabilistic modeling, showing promising results in improved prediction precision. Collaborative Filtering explores user behavior patterns, while Naive Bayes employs Bayes' theorem for probabilistic data classification. Focused on predicting academic success, the integration incorporates collaborative patterns from student data for increased accuracy. The method considers similar students' performance and behavior for nuanced, personalized predictions. Starting with diverse data collection, including collaborative patterns among students, Collaborative Filtering identifies relationships and patterns among those with similar academic histories. These insights enrich the naive Bayes algorithm, creating a holistic approach for more accurate predictions, and contributing to ongoing machine learning initiatives in education.

How is L2 pair interaction related to fluency and language use? A quantitative approach

Previous research examined L2 interaction by describing salient features exhibited in different patterns of peer interaction. These studies mostly used qualitative methods and focused on the collaborative aspect of such construct (Galaczi, 2008). The present study adopts a quantitative approach to explore and describe L2 interaction, utilizing the data of the Corpus of Collaborative Oral Tasks (CCOT). Specifically, it measures pairs’ interaction by creating a composite score of interactivity to understand the relationship between the dyads' degree of interactivity and their use of lexico-grammatical features as well as their L2 fluency. Pearson's correlation tests showed weak to moderate positive relationships between interactivity and discourse particles, response forms, wh-questions, and second person pronouns. Additionally, the tests revealed weak negative relationships between interactivity and both nominal forms and hesitations. Furthermore, revealing moderate relationships, Pearson's correlation tests showed that interactivity was associated with more fluent L2 speech, where learners of higher interactivity levels tended to produce fewer silent pauses and faster speech rates. The study provides insights for scholars interested in L2 interaction. It suggests that some linguistic features were not only associated with collaborative behaviors (as reported in the literature) but also with interactivity as broad aspect. Furthermore, it provides a description of how the act of turn taking might potentially serve the fluency of higher interactivity students, warranting further investigation of turn frequency among L2 test takers as test raters might potentially be influenced by the test candidates’ fluency. Finally, it reports that L2 interactivity exhibited a relationship pattern with linguistic features that resembles patterns reported in the literature of studies on native speakers of English.

Coevolution of Collaborative Networks and Innovation Implementation Behaviors of Project-Based Firms

Coevolution of Collaborative Networks and Innovation Implementation Behaviors of Project-Based Firms

Internet development, information availability, and Chinese enterprises’ cooperative green technology innovation

Cooperative green technology innovation is potentially the answer to the lack of motivation for independent green innovation, which can effectively alleviate many difficulties faced by enterprises engaging in independent green innovation. Internet development provides new opportunities to stimulate innovative cooperation of enterprises. However, little literature has studied the impact of Internet development on enterprises' cooperative green technology innovation. Based on the data of Chinese A-share 3284 listed companies from 2010 to 2019, this paper uses a panel two-way fixed effects model to assess the effect of Internet development on enterprises' cooperative green innovation. The findings are: (1) Internet development significantly drives firms' collaborative green innovation behavior. The result remains robust even after performing a series of robust tests. (2) The Internet empowers green innovation cooperation among firms by improving information availability, including market information availability and technical information availability. (3) The heterogeneous results show enterprises use the Internet to accomplish high-quality collaborative green innovation. Internet development is more helpful in encouraging the cooperative green innovation of enterprises located in central cities and state-owned enterprises. This study provides novel and targeted policy implications to empower enterprises’ green innovation cooperation and drive sustainable economic development through Internet development.

Long Short‐Term Memory‐Based Multi‐Robot Trajectory Planning: Learn from MPCC and Make It Better

The current trajectory planning methods for multi‐robot systems face challenges due to high computational burden and inadequate adaptability in complex constrained environments, obstructing efficiency improvements in production and logistics. This article presents an innovative solution by integrating model predictive contouring control (MPCC) and long short‐term memory (LSTM) networks for real‐time trajectory planning of multiple mobile robots. Based on the datasets generated by MPCC, a customized LSTM network is constructed to learn the collaborative planning behavior from these datasets offline, subsequently producing smooth and efficient trajectories online with a low computational burden. Moreover, a hybrid control scheme, incorporating a lidar‐based safety evaluator, avoids unexpected collision risks by switching to MPCC when necessary, ensuring the overall safety and reliability of the multi‐robot system. The proposed hybrid LSTM method is implemented and tested in the robot operating system (ROS) within diverse constrained scenarios. Experimental results demonstrate that the hybrid LSTM method achieves ≈6% enhancements in trajectory productivity and a reduced computational burden of roughly 75% compared to MPCC, thereby providing a promising solution for local multi‐robot trajectory planning in logistics transportation tasks.

Interplay of paradoxical virtual leadership and psychological contract violation – impact on organizational citizenship behavior

PurposeThe daunting task of managing knowledge workers virtually has not always yielded positive results. This empirical work discusses the impact of Virtual Leadership on Organizational Citizenship Behavior. The study investigated how Psychological Contract Violation moderates the relationship between Virtual Leadership and Organizational Citizenship Behavior.Design/methodology/approachData was collected from 392 IT engineers working in software companies in India. The cross-sectional data was analyzed using Warp-PLS software, IBM SPSS and IBM Amos.FindingsThe results support the proposition that virtual leadership is negatively associated with Organizational citizenship behavior, at sub-dimension levels except obedience. The moderating role of psychological contract violation is also established by the results.Practical implicationsVirtual leaders should demonstrate collaborative behaviors to generate organizational citizenship behavior among team members. Leaders should be imparted training to enable them to adapt themselves to virtual environment. This study highlights the paradoxical nature of virtual leadership and opens the possibilities for future research.Originality/valueThe study is one of the first to report a negative association between Virtual leadership and Organization citizenship behavior. There is uniqueness in the use of the “Contingency theory of leadership” to explain the difficulties faced while managing a virtual team.

Promote or inhibit? Examining the influence of youth digital advocacy on digital social entrepreneurship

PurposeThis study aims to investigates the impact of felt obligation for constructive change, constructive voices on social media and social media knowledge competence on digital social entrepreneurship among Indonesian youth.Design/methodology/approachThis study uses Hayes’ process model to assess the stated hypotheses using survey data gathered from 489 Indonesian youth.FindingsYouth with elevated social media knowledge competency might display diminished motivation to participate in digital social entrepreneurship, even when their felt obligation for constructive change remains robust. While promotive voice on social media mediates the relationship between felt obligation and digital social entrepreneurship, the notable absence of a mediating role for prohibitive voice on social media contradicts traditional Positive Youth Development (PYD) theoryResearch limitations/implicationsThis research challenges conventional PYD theory by suggesting that youth with high social media knowledge competence may have reduced motivation for digital social entrepreneurship, despite a strong commitment to positive change. While promotive voice behavior mediates the relationship between felt obligation and digital entrepreneurship, the absence of mediation by prohibitive voice contradicts traditional PYD principles. This study expands the PYD framework, highlighting the challenges related to social media knowledge competence and prohibitive voice in engaging youth advocates for digital social entrepreneurship. It emphasizes the need to adapt PYD theory to address the complexities of the digital age effectively.Practical implicationsThe findings offer valuable insights for students, aspiring young entrepreneurs, educators and policymakers interested in advancing the development of digital social entrepreneurship in a developing nation.Social implicationsThis research offers valuable practical implications for policymakers, educators and society. It suggests the importance of nurturing a sense of responsibility among young individuals, enabling their active involvement in addressing issues like environmental degradation and discrimination. Creating supportive online communities for collaboration and constructive voice behavior on social media can provide judgment-free environments. Additionally, advocating for partnerships between youth and various stakeholders can boost resources, mentorship and funding opportunities, enhancing the prospects for impactful digital social entrepreneurship.Originality/valueThis study contributes to an underexplored area in the field of social entrepreneurship by investigating the intersection of youth, digital advocacy and digital social entrepreneurship. The incorporation of the PYD theory introduces a novel dimension to recent research in this domain

Navigating organizational change: sequential vs simultaneous approaches to innovation management in modern enterprises

Purpose This study aims to explore the relationship between innovation and strategic management in contemporary enterprises, emphasizing the navigation of organizational change for sustainable competitive advantage. This study addresses the challenge of adapting to dynamic environments and the critical role of leadership, organizational culture and collaboration in successful innovation management. Design/methodology/approach The authors used the typology research design and comparative analysis to explore the principles and strategies underlying different innovation approaches. This study examines their impact on organizational structures, resource allocation and the integration of technological advancements with managerial practices. Findings The authors developed a typology of two innovation management models. The sequential approach emphasizes phased and incremental innovation, while the simultaneous approach advocates for dynamic and comprehensive integration of innovation across the organization. Each model presents distinct advantages and challenges, underscoring the need for a tailored approach based on the enterprise’s context and objectives. Mature companies may benefit from the sequential approach to gradually evolve their innovation, while new and high-tech-intensive companies can leverage the simultaneous approach for dynamic and continuous innovation. Research limitations/implications Future research should examine local bodies and trade unions’ perception on the energy crisis’ impact toward rural entrepreneurship. Practical implications The findings are useful to Greek and European policymakers and rural micro-entrepreneurs as the experience of dealing with several previous crises can be a useful tool when dealing with current and future crises. Originality/value This study enhances understanding of the complex interplay between organizational innovation and strategy. The authors recommend further exploration of emerging technologies, cultural values, collaboration, sustainable practices and changing customer behavior to boost innovation capabilities and achieve success.

Exploring team collaboration in the metaverse from a human capital perspective

PurposeWe aim to help better understand how organizations can develop their human capital in virtual teams through technological advances in the metaverse. To this end, we examine how virtual team collaboration with virtual reality technologies in the metaverse compares to traditional videoconferencing. Our study demonstrates how the metaverse can facilitate collaboration in virtual teams and examines the factors that are critical to successful team collaboration in the metaverse.Design/methodology/approachWe conduct a lab experiment comparing Meta Horizon Workrooms with Zoom. Using a between-subjects design, we observe virtual team collaboration in five teams. All teams solved the Lost on the Moon Exercise used by NASA to train teamwork. We collected data during and after the experiment to explore emerging collaborative behaviors based on audio and video recordings, a quantitative survey, and qualitative feedback.FindingsWe find higher levels of immersion, social presence, and collaboration among team members in the metaverse. We further identify new opportunities for social interaction and greater focus on team members and shared tasks. Our study suggests that the metaverse can enable effective collaboration in virtual teams and uncovers related guidance for organizations.Originality/valueWe connect the research streams on the metaverse, team collaboration, and human capital. We add empirical evidence to the largely theoretical discussion on the metaverse and explore collaboration tools for virtual teams, helping to enable effective collaboration of organizations’ virtual teams. We hope to stimulate further research to unlock the full collaborative potential of the metaverse and establish the metaverse for effective development of human capital.

An Investigation of the Teacher Collaboration According to the Instructional Leadership Behaviors of Principals

This correlational study examines the relationship between the instructional leadership behaviors of school administrators and the collaboration behaviors among the teachers in the same branch according to teachers' perceptions. The research sample was determined by an easily accessible sampling method and consisted of 403 teachers working in public primary and secondary schools in the central districts of Ankara. The data in the study were collected using the "Instructional Leadership Behavior Scale" and "Scale for Determining the Level of Collaboration of Group Teachers." Mean and standard deviation values were calculated in the data analysis, and correlation and hierarchical regression analyses were conducted. The study results show that principals exhibit high levels of instructional leadership behaviors according to teachers' perceptions. Similarly, teachers' collaboration behaviors are also high. A positive and significant relationship was found between principals' instructional leadership and teachers' collaborative behaviors. According to the regression results, principals' instructional leadership behaviors significantly predicted teacher collaboration. Based on the results, some implications for the future were made, and suggestions were made to researchers and practitioners.

Diffusion model of multi-agent collaborative behavior in public crisis governance network based on complex network evolutionary game

In order to explore the phenomenon of diffusion of group decision making formed by the emergence of decision-making behaviors of governance agents in public crisis governance systems, this research uses a complex network evolutionary game approach, considers BA scale-free networks as network vectors of public crisis governance systems, and develops a diffusion model of collaborative governance decision making behaviors. Simulation experiments are also conducted to show the macro-level impact of micro-subjects’ decision-making behavior on group “Emergence-Diffusion”. The results of this study show that the cost of collaborative governance has the most significant effect on the depth and breadth of the spread of collaborative behavior in governance networks. The size of the network determines the speed of network diffusion. The smaller the network size, the more sensitive it is to the spillover benefits of collaborative governance, and the larger the network size, the more sensitive it is to the penalties of non-compliance. The findings of the study have implications for the collaborative behavior of multiple agents in public crisis governance. The main findings are that (1) in order to ensure the stability of the collaborative governance system, decision making options should be selected according to the size of the network. (2) A reasonable penalty mechanism for breach of contract should be set up to avoid the phenomenon of “free-riding” in collaborative governance. (3) Reasonable allocation of collaboration benefits and maintenance of cooperative relationships between nodes in the neighborhood. (4) External regulators should ensure that information in the network is disseminated without barriers and reduce the phenomenon of information asymmetry.