Search results

In the current era of Industry 4.0, the manufacturing industries are striving toward mass production with mass customization by considering human–robot collaboration. This study aims to propose the reconfiguration of assembly systems by incorporating multiple humans with robots using a human–robot task allocation (HRTA) to enhance productivity.

A human–robot task scheduling approach has been developed by considering task suitability, resource availability and resource selection through multicriteria optimization using the Linear Regression with Optimal Point and Minimum Distance Calculation algorithm. Using line-balancing techniques, the approach estimates the optimum number of resources required for assembly tasks operating by minimum idle time.

The task allocation schedule for a case study involving a punching press was solved using human–robot collaboration, and the approach incorporated the optimum number of appropriate resources to handle different types of proportion of resources.

This proposed work integrates the task allocation by human–robot collaboration and decrease the idle time of resource by integrating optimum number of resources.

The link between relationship typologies and effectiveness of conflict resolution approaches remains to be tested despite its significance in conflict management in construction project delivery. By using the four relationships attributes based on the group attachment theory, the purpose of the study was to explore the cluster of relationships among project teams and organisations and the performance of conflict management strategies across these clusters in the Ghanaian construction industry.

Using a deductive questionnaire survey in the Ghanaian construction industry, a total of 137 responses were gathered and analyzed using cluster analysis, mean scores and ANOVA to reveal the relationship clusters and performance of conflict management strategies across these clusters.

The results revealed eight relationship clusters that exist among project teams and organisations with distinct influence of roles & tasks function, cognition, emotions and behavior attributes across the relationship clusters. In the aspect of the effectiveness of conflict management strategies, it was noted that the performance of these strategies were significantly different across the groups. For instance, integrating as a conflict management strategy was deemed to be effective in resolving conflict in unitary, adversarial, pluralist, mutuality, collaborative and partnering relationship clusters. In the case of coopetitive and coercive relationships, the performance of integrating as a conflict management strategy was less effective. This study thus has empirically proved that, different relationship clusters of teams and organizations exist within the Ghanaian construction industry, and that they perform different roles & tasks functions, cognition, emotions and behavioural attributes in their formation. Additionally, the performance effectiveness of conflict management strategies differed across the relationship clusters.

By aligning the relationship attributes to the dynamics of relationship clusters experienced in project teams and organisations, relationship quality, suitability and effectiveness of conflict management strategies can be optimized. The findings can inform project teams and stakeholders to develop fit-for-purpose relationship attributes among teams and organisations to enhance team effectiveness, relationship quality and conflict management in the industry.

This paper aims to present a lesson that showcases how artificial intelligence (AI) tools may be chiefly used in L2 language classrooms to design culture-focussed telecollaboration tasks and aid their completion by students.

The paper begins by reviewing traditional approaches and guidance for developing telecollaboration tasks. It then models how tasks can be designed using the popular AI tool “Chat Generative Pre-training Transformer (ChatGPT)” and then simulates how tasks may be completed by learners using ChatGPT-generated information as a springboard for their own culturally appropriate outputs.

The simulated lesson illuminates the potential value of AI tools for teachers and students. However, it also highlights particular aspects of AI literacy that teachers and learners need to be aware of.

This paper has clear practical implications for teacher development by raising awareness of the importance of teachers upskilling in telecollaboration task design and in their understanding of how AI tools can collaborate with them in language classrooms.

The paper adds to the current body of literature on telecollaboration and more specifically adds weight to current discussions taking place around AI tools in language education. By the end of reading the paper, teachers will have a comprehensive grounding in how to use ChatGPT in their classrooms. In doing so, the author demystifies how teachers and students may start exploring these tools in ways that target developing intercultural communicative competence.

The relationship between variation in time perspectives and collaborative performance is scarcely explored, and even less is known about the respective mechanisms that lead to varying task performance. Thus, we aim to further the literature on time perspectives and collaborative performance, shedding light on the underlying behavioral patterns.

We report a quasi-experiment analyzing the impact of past, present and future orientation variation in dyads (N = 76) on their quantitative and qualitative performance when confronted with a simple incentivized creative task with constraints. Subsequently, we offer a qualitative analysis of comments given by the participants after the task on the collaboration.

Results indicate that a dyad's elevation of past orientation and diversity in future orientation negatively affect collaborative performance. At the same time, there is a positive effect of elevation of future orientation. The positive effect is driven by clear communication and agreement during the task, while the negative effect arises from work sharing and complementation.

This study provides insights for organizations on composing individuals regarding their temporal focus for collaborative tasks that should be executed rapidly and require creative solutions.

Our study distinguishes by considering the composition of past, present and future time perspectives in dyads and focuses on a creative task setting. Moreover, we explore the mechanisms in the dyads with a substantial elevation of/diversity in future orientation, leading to their stronger/weaker performance.

This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations.

A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy.

The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems.

This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

This paper aims to report the development of the multiparty collaborative leadership scale (MCLS) that assesses four dimensions of collaborative leadership that have been defined in the literature regarding the functions of collaborative leadership in intra- and interorganizational settings.

The authors have tested the validity and reliability of the MCLS in a sample of 110 managers and professionals who participated in five multiparty collaboration workshops, each lasting for two days. The authors used multilevel analyses to test the construct, discriminant and predictive validity of the MCLS.

The results generally supported the reliability and validity of the MCLS. The scale has good internal consistency and in terms of validation, the authors show that MCLS negatively predicts the conflictuality and positively predicts the collaborativeness of the leading party as well as trust in the multiparty system and its entitativity.

The MCLS can be used to extend literature on collaborative leadership and generate insights on the antecedents and consequences of effective collaborative leadership in multiparty systems.

Multiparty systems are set to deal with important societal challenges and mediators involved in multiparty issues are asked to settle important international disputes and conflicts. Understanding collaborative leadership in such systems and its role in establishing effective multiparty collaboration is key. The MCLS can be used as a research instrument and as a development tool toward realizing much-needed collaboration.

The authors present a first attempt to develop a short scale to assess collaborative leadership in complex systems in which participating stakeholders lack position power.

Societies depend on interconnected infrastructures that are becoming more complex over the years. Multi-disciplinary knowledge and skills are essential to develop modern infrastructures, requiring close collaboration of various infrastructure owners. To effectively manage and improve inter-organizational collaboration (IOC) in infrastructure construction projects, collaboration status should be assessed continually. This study identifies the assessment criteria, forming the foundation of a tool for assessing the status of IOC in interconnected infrastructure projects.

A systematic literature study and in-depth semi-structured interviews with practitioners in interconnected infrastructure construction projects in the Netherlands are performed to identify the criteria for assessing the status of IOC in infrastructure construction projects, based on which an assessment tool is developed.

The identified assessment criteria through the literature and the practitioner’s perspectives results in the designing and development of a collaboration assessment tool. The assessment tool consists of 12 criteria and 36 sub-criteria from three different categories of collaborative capacity: individual, relational, and organizational.

The assessment tool enables practitioners to monitor the status of IOC between infrastructure owners and assists them in making informed decisions to enhance collaboration. The assessment tool provides the opportunity to assess and analyze the status of collaboration based on three categories (i.e., individual, relational, and organizational).

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

The research questions probe into the heart of participatory learning’s scholarly landscape. They inquire about historical trends, shifts in research interest, and regional contributions, highlighting the global reach of participatory learning discourse. The study also reaches into the most cited papers, emphasizing their pivotal role in shaping the field’s trajectory.

The research design of our study involves a retrospective analysis focused on the topic of participatory learning in education. A retrospective analysis is a methodological approach that entails examining existing literature, data, and publications within a specific field to identify trends, patterns, and insights over a defined period. In the context of participatory learning in education, this research design allows us to gain a comprehensive understanding of the evolution, contributions, and emerging directions within this pedagogical approach.

The culmination of this study lies in formulating 75 thought-provoking future research questions. These questions are designed to guide the future trajectory of participatory learning research, addressing existing gaps and propelling the field toward new horizons. The findings of the study contribute to a panoramic view of participatory learning’s evolution, global impact, and potential for reshaping education. It is a compass for researchers, educators, and policymakers navigating the intricate landscape of participatory learning in education.

Themes and topics are thoroughly explored, unrevealed the multidimensional nature of participatory learning research. The investigation spans time, revealing enduring themes while unveiling emerging areas of inquiry that capture the attention of researchers and practitioners. Current trends and focus areas are scrutinized, offering insights into the ever-evolving scholarly pursuits within participatory learning.

This comprehensive study investigates the evolution and impact of research on participatory learning in education from 1995 to 2023. The research objectives encompass a broad spectrum, including trend analysis, geographical distribution assessment and identification of influential papers, thematic exploration, and the formulation of future research questions. Through a meticulous examination of published literature, this study aims to shed light on the development of participatory learning as a transformative educational approach.

This study’s originality lies in its comprehensive analysis of participatory learning in education from 1995 to 2023, revealing temporal trends, global contributions, influential papers, thematic nuances, and emerging trends. By amalgamating these dimensions, it offers a holistic view of participatory learning’s evolution, impact, and future directions, enriching the understanding of this transformative educational approach and guiding further research and practice.

This paper aims to empirically investigate how knowledge coordination is carried out within and across expert teams in the outsourcing service desk context from the standpoint of the information and communication technologies (ICT) provider.

The authors draw on an embedded case study to unravel the mechanisms used by expert teams to achieve knowledge coordination. Data collection included semi-structured interviews and document analysis over eight months.

Four groups of coordination mechanisms were found according to their nature and role in helping MESA achieve its organizational goals. The authors also identified how this set of mechanisms responds to the task-resource dependency and how it evolves over time to provide reliable ICT services. Furthermore, the analysis of four knowledge coordination dimensions inside each group uncovers the complexity of coordination in the studied context, with the “who” dimension being predominant across the groups. The analysis further reveals that the content (what) and mode of coordination (how) of each group respond to elements in the knowledge coordination process relevant for the different stages of the ICT service delivery process.

The case study addresses how people in outsourced services coordinate their knowledge to manage the interdependencies among the involved organizations and thus, achieving their goals. This study extends previous research that had analyzed the consequences of knowledge coordination for providers and customers by delving into the mechanisms used in this process from the provider’s point of view.