This paper reports the results of an experiment on how team heterogeneity in terms of productivity influences both the revenue sharing proposed by the principal to the team and the employees’ performance. Experimental evidence shows that when the team is heterogeneous, the principal does not try to motivate the agents through her sharing offer. Regardless of the level of team-based compensation, a large amount of free riding occurs since each agent is mainly influenced by his teammate's behavior. In contrast, when the team is homogeneous, agents are better able to cooperate, reciprocating the principal's offer.

Teamwork has become increasingly important in modern organizations and the labor market. Yet, little is known about the role of self-confidence in teamwork. In this paper, we present evidence from a laboratory experiment using a team effort task. Effort and ability are complements and there are synergies between teammates’ efforts. We exogenously manipulate subjects’ self-confidence about their ability using easy and hard general knowledge quizzes. We find that overconfidence leads to more effort, less free riding, and higher team revenue. This finding is primarily due to a direct effect of overconfidence on own effort provision, while there is no evidence that subjects strategically respond to the teammate’s overconfidence.

The evolution of Artificial Intelligence (AI) and Machine Learning (ML) enables new ways to envision how computer tools will aid, work with, and even guide human teams. This paper explores this new paradigm of design by considering emerging variations of AI-Human collaboration: AI used as a design tool versus AI employed as a guide to human problem solvers, and AI agents which only react to their human counterparts versus AI agents which proactively identify and address needs. The different combinations can be mapped onto a 2×2 AI-Human Teaming Matrix which isolates and highlights these different AI capabilities in teaming. The paper introduces the matrix and its quadrants, illustrating these different AI agents and their application and impact, and then provides a road map to researching and developing effective AI team collaborators.

Engineering design is typically a collaborative process, and in the era of digital engineering, online collaboration platforms are increasingly being used to perform the work. Despite the development of e-collaboration technologies, there is a significant gap between actual collaboration and what is really needed. However, improving collaboration requires a proper measurement system. Yet, the common methods to measure and improve collaboration are challenging, usually not compatible with digitalized collaboration, and have limited scalability. This paper presents a new data-driven method for measuring, visualizing, and monitoring Active Engagement (AE) in web-based teamwork, which is a key element of effective collaboration. We applied the method in a case study of four engineering teams during a Technology Planning and Road-mapping course. The results suggest that measuring AE in web-based teams, with an available history log, is technically feasible and can meaningfully represent the team's collaboration. The presented approach can be used to upgrade e-collaboration platforms as a toolkit or for further investigation on improving web-based collaborative design and learning through monitoring dashboards and feedback systems.

In order to better understand the stakeholder choices of knowledge-based organisational actors, this study focuses on a novel application of Huber's (2012) dimensions of proximity salience, namely spatial proximity, social proximity and cognitive proximity. The population of the study is made up of knowledge-based organisational actors involved in developing an innovation ecosystem, in terms of stakeholder network creation. The extent to which the three proximity dimensions of stakeholder salience is evident in the stakeholder choices of these innovation-focused actors seeking knowledge-based collaborators is explored. Our findings show how various forms of proximity prompt the decision of who to work with among a diverse population of experts involved in building a cross-national innovation ecosystem. The various explanations that motivate stakeholder choice matched Huber's proximity dimensions. The findings provide new insight into stakeholder choice among knowledge-based organisations, and highlight a new proximity dimension indirectly linked to cognition proximity. Termed the “potential proximity” dimension, it involves attraction to stakeholders that represent strategic value.

The T-Shaped designer has previously been identified as a design engineer with the desirable set of skills for a successful career. Twelve design engineers ranging from novice to expert, were interviewed to gain an understanding of their skill set, how it has evolved and how it needs to evolve in order to be futureproofed. With the use of qualitative, quantitative data and the development of a novel engineering skills profiling method, this paper found that 75% of design engineers did not exhibit a T-shaped skill profile, but a skill shape that has been termed ‘M-shaped’ or ‘Comb-shaped’. The majority of participants exhibited a great depth of specialist skills in multiple disciplines, not limited to their immediate field of work. All participants exhibited a wide knowledge of skills that allowed them to work across different disciplines, which included electronics, management or manufacturing, and so the wide vertical bar of the T-Shape design predicted by previous literature has been supported.

Team composition in Project Based Learning is the first task for the class and has a great impact on the learning experience. Anyway, little space is dedicated in literature about team composition, considering their personal inclinations towards design tasks.

For these reasons we propose a tool that aims to map the design skills of students to optimise team composition. The tool is based on a questionnaire grounded in the design theory and aims at measuring the willingness of students at performing certain design tasks. The results of the questionnaires are analysed using Principal Component Analysis to normalise each students’ answers to the whole class, and to show the distribution of students in the space of engineering design skills.

We present the design process of the tool, and a first experimentation on two classes of master's degree students in Management Engineering and Data Science, testing the tool on a total of 72 students. The results are promising and demonstrate the robusteness of the questionnaire and of the analytical method. Also, we propose next steps for our research activity, calling for other researchers to test our method in different contexts.

Transition activities, such as design reviews, are often utilised in product development to evaluate the conducted work and plan future actions. While key decisions are made during these activities, they are still underexplored. This paper studies the effect of transition goals and virtual reality (VR) on transition team performance. In an experimental study, four-member teams conducted two transition-related experimental tasks (validation and verification) working in one of the two conditions (VR or desktop interface). The results show that transition goals and VR affect performance. More specifically, the validation-oriented transition was more efficient but less effective than the verification one. Furthermore, the performance of the validation-oriented transition compared to the verification one was increased in VR and decreased in a desktop interface. Finally, the high-performing teams consistently discussed new issues, while low-performing teams had prolonged moments of not discussing anything new. These findings suggest that desktop interface and VR are not substitutable but rather complementary technologies.

The application of agile development methods in response to increasing market dynamics and product complexity is a key lever in the automotive industry. Agile methods originally come from the software industry and enable fast, flexible and customer-oriented product development. These methods are also increasingly being used in hardware development. However, the evaluation of the benefits of agile methods in the context of automotive development has been primarily subjective. The publication aims to present a first data-based approach to objectify the benefits of agile methods in automotive development by highlighting the effects in the quality of collaboration within teams. A standardised procedure is therefore designed and presented. On the one hand, a model for measuring the agile maturity of teams is described. On the other hand, the quality of collaboration within a team is examined in different aspects using standardised key performance indicators. Based on the proposed procedure, a strong positive correlation was found between the considered key performance indicators of the quality of collaboration and the agile maturity of the development teams within the investigated organisation.

use-case scenarios, including homes, hospitals, workplaces, and recreation. Though the area of Social Robotics has gained traction in recent years, the majority of the studies so far have studied single-human and single-robot interaction. In comparison, Social Robots are increasingly being placed in human teams, likely affecting team dynamics. On the other hand, Engineering teams work together to deliver outstanding results and the processes in these teams are social. We propose that Social robot can be added to engineering human team to enhance team cohesion and performance. Therefore, this paper presents a preliminary framework towards developing a conceptual framework to study team cohesion in Human-Robot Teams (HRTs) in engineering context, looks at different roles of social robot and how the responses, behaviours, emotions of social robots shape outcomes in the engineering team. The research specifically focuses on team cohesion because team cohesion is reportedly one of the most critical concepts in team dynamics. The paper outlines the research objectives, framework and concept workflow.

As the demands for new complex products/services increase, leading to strict constraints on budget and time-to-market, it is hard to learn from experience and improve practice. Improvement can be exercised in all aspects contributing to project management: the skill set of project personnel, the project structure, and the development process. People are the key asset of the project. Identifying the key participants in a project whose role is influential is important for improving the project's success. These people can receive support, remove their burdens, make sure their communication channels work well, etc. This paper offers a multilayer network-based method to examine an actor's influence in a project while combining two additional organizational key aspects: products and processes. Considering these three aspects together allows for a more informed evaluation of the actors' influence on the project. Using the insight from graph theory, we gain indicators related to each network actor. The influence of the actors in a multidimensional network makes it possible to present a clearer picture to decision-makers in the organization to make better decisions related to increasing the effectiveness of the development project.

Studies revealed that, while collaborating, humans tend to synchronise on multiple levels (e.g., neurocognitive or physiological). Inter-brain synchrony has been linked to improved problem-solving, decision-making, and creativity. Nevertheless, studies on synchrony in design teams started to emerge only recently. This study contributes to this stream of research by utilising a computational model of a design team to explore the relationships between team cohesion, synchrony, and team performance. The experiments revealed a positive link between team cohesion level and the emergence of (cognitive) synchrony. Furthermore, cohesive teams were found to be more efficient, converging quicker and producing solutions at a higher rate. In addition, the diversity of the solutions generated by highly cohesive teams tends to increase over time. Teams in medium- and low-cohesive settings initially generate highly diverse solutions, but such diversity decreases as the simulation progresses. Finally, highly-cohesive teams were found to be prone to premature convergence.

Conflict can be both a productive and detrimental reality of design collaboration. While most studies on conflict characterize findings by type (conflict about the task, process, or interpersonal relationships), we extend this typology to understand the causes, topics, and outcomes of conflict. To do so, we analyze communications in a virtual chat platform, collected in a hybrid work environment. A thematic analysis on over 6000 messages between student design teams on the enterprise communication platform Slack revealed three emergent conflict themes: Engineering Design, Project Management, and Communication. A mapping of the themes to a widely-cited typology of conflict found an over- representation of task (productive) and process (detrimental) conflict in the Engineering Design and Project Management themes, respectively. The distribution of types of conflict in the Communication theme is representative of the entire dataset, suggesting that communication can be a cause and outcome in all types of conflict. Overall, our classification of conflict is the first step towards describing triads of the causes, topics, and outcomes of conflict, a contribution which will drive the development of interventions for design team conflict.

Prior work has demonstrated that gender identity affects team psychological safety, which is critical to the development of a shared understanding of the task. Further, we know that a shared understanding can increase team cohesion and team performance. Little work has investigated how gender differences affect communicative acts within the context of design, and more specifically how gender differences may affect the development of a shared understanding of the design concept between designers. As a first step towards filling this gap, the current work presents findings from a controlled study conducted at The Pennsylvania State University with 22 design dyads (44 designers). The findings from this study indicate that gender identity within design dyads does not affect participants’ shared understanding of a design concept.