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In order to deepen understanding of team processes in dynamic organizational contexts, we suggest that analyses employing techniques to identify and analyze team member interaction patterns and trajectories are necessary. After presenting a brief review of interaction data coding and reliability requirements, we first review examples of two approaches used in the identification and analysis of interaction patterns in teams: lag sequential analysis and T-pattern analysis. We then describe and discuss three statistical techniques used to analyze team interaction trajectories: random coefficient modeling, latent growth modeling, and discontinuous growth analysis. We close by suggesting several ways in which these techniques could be applied to data analysis in order to expand our knowledge of team interaction, processes, and outcomes in complex and dynamic settings.

The current study builds on the non-linear Dynamic Systems (NDS) perspective to test the assumption that change in sickness absenteeism is non-linear, and that such change is due to workload, team adaptability and task cohesion. Participants were 37 firefighter teams (n = 250 individuals) from a main European capital city. The research hypotheses were tested using SPSS and the “cusp” package, in the statistical software R. The results suggest that change in sickness absenteeism behaviours over time is non-linear, with the cusp catastrophe model predicting such behaviours better than the linear and logistic models. In our model, task cohesion functions as an asymmetry factor (i.e., the independent variable that determines the strength and discrepancy between the two stable states of the dependent variable) leading to a linear change in sickness absenteeism. Interestingly, both workload and team adaptability function as bifurcation (i.e., the independent variable that determines the change between the two stable states of the order parameter) and asymmetry factors leading to non-linear and linear change in sickness absenteeism over time. This study contributes to the growing evidence that incorporating the NDS perspective enables a better understanding of action teams, namely those working in extreme environments. info:eu-repo/semantics/acceptedVersion

Purpose The purpose of this paper is to investigate the effects of two formal controls, namely target rigidity and process autonomy, on team adaptability and project success in new product development (NPD) projects. Target rigidity refers to performance goals that are non-negotiable once they have been set. Process autonomy refers to the extent to which a project team is free to choose ways to achieve its goals. Team adaptability is considered a key factor that explains the relationship between formal controls and project success. Design/methodology/approach Two separate models related to resource and cost measures are analysed, since different target types may influence managerial perceptions. This study uses data collected from a survey with 113 project managers as respondents. Findings The findings show that target rigidity and process autonomy support team adaptability. Furthermore, team adaptability mediates the impact of formal controls on project success. The effects are more pronounced for cost targets as compared to resource targets. Practical implications Firms can increase project success by using formal controls in such a way that they allow project managers to provide their teams with motivating guidelines (target rigidity) and discretion (process autonomy) to adapt to new circumstances. Originality/value This study reveals the impact of formal controls on NPD project success through team adaptability. A balanced use of target rigidity and process autonomy may help improving NPD project success.

As the result of the first phase of building a computational laboratory which is aimed to enable detail study of the emergent team properties and team behaviour in product development, this paper focuses on the design of a computational representation of a member of product development team. Since team members are often faced with the necessity to adjust to changes in their environment, the emphasis was put on modelling of human adaptive capacity. Specifically, the paper brings together the theoretical findings on mechanisms individuals use when faced with disruptions and introduces the architecture of an adaptable agent that can be used for studying adaptation of product development team. Building on the findings from psychology, sociology and cognitive science, the proposed agents are defined as cognitive, situated, affective and social. The proposed computational workbench is aimed to augment understanding of team processes prior, and in response to adaptation triggers in the context of product development projects, and should enable anticipation of possible pitfalls, enhance the development of design methodologies and tools, and provide guidelines for design education.

Teams play a significant role in the process of product development, regardless of whether the product developed is a machine, software or service. As such, a number of studies have been conducted to determine factors influencing team effectiveness and performance. Due to flexibility, effectiveness and applicability of computational models, modelling and simulation approach has been used to aid research on teams, and simulations have been successfully utilised for studies on different aspects of teamwork. However, the full potential of computational experiments has yet to be achieved, as studies focusing on emergent properties of product development teams are seldom. One of team properties essential for product development’s success is team adaptability, as teams have to constantly adjust to market changes, alterations in team structure, technology advancements, changes in product requirements, or upcoming deadlines. Thus, the development of a simulation framework which would enable studies of product development team’s adaptation is of particular interest. This work presents the research aimed at the development of such framework.

The authors draw on resource allocation theory (Kanfer & Ackerman, 1989) to develop hypotheses regarding the conditions under which collective learning and performance orientation have interactive effects and the nature of those effects on teams' ability to adapt to a sudden and dramatic change in workload. Consistent with the theory, results of a laboratory study in which teams worked on a computerized, decision-making task over 3 performance trials revealed that learning and performance orientation had independent effects on team adaptability when teams had slack resources available for managing their changed task. Time helped explain the independent effects of performance orientation. Results also revealed that learning and performance orientation had interactive effects when teams did not have slack resources. Finally, the results of this study indicate that teams lacking slack resources were better able to balance high levels of learning and performance orientation over time with practice on the changed task.