The importance of face-to-face and virtual teams in product development is well recognised in research and practice. Engineering teams are often used in dynamic environments that require adaptation and constant change due to external and internal circumstances; they have to adjust to changes in market trends, respond to new customer’s requirements and adapt to changing technologies or resources constraints. As the research field concerning engineering teams develops, it continues to require interdisciplinary approaches to understand, model and improve the role of the teamwork in product development. However, since there are numerous factors influencing teamwork and the mutual effects of these factors depend on time and context, understanding and predicting face-to-face and virtual team performance is exceptionally challenging, and there are insufficient research studies.
The goal of TAIDE is the development of the research framework for experimental studies of engineering teams (both face-to-face and virtual). This framework should serve as the foundation for enhancement of the usage and effectiveness of teams within innovation-oriented product development projects. The project will contribute to both the theory and practice by bringing together interdisciplinary research, conceptualisation and modelling approaches and it will build on the results of the Croatian Science Foundation (CSF) project MINMED 2014-2018. During the project, the Design Science Research (DSR) framework consisting of the three related cycles of research activities (relevance, design and rigour cycle) will be applied as the research methodology, while experimental design research will be the primary research paradigm including experimentation with the real-world teams in DEPICT lab and CADLab, and computational simulations of the teams’ emergent properties.
The research results are expected to delineate how empirical research and computational simulations can lead to better understanding, modelling, reflection on and improvement of team adaptability as one of the most important emergent properties of the engineering teams in relation to innovation. The resulting computational tools should enable researchers and practitioners from the industry to utilise simulations to understand the role that the different types of disruption triggers have on the resulting team adaptation, as well as for prediction of the impact that different levels of the team adaptability may have on various teamwork outputs. The research is conducted by a multidisciplinary research group including the researchers and research infrastructure for experimentation from Croatia, USA, Denmark and Sweden.
The two main research aims are:
- Aim I: To review and devise the research and technology strategy for capturing data relevant for studying engineering teams (face-to face and virtual teams); and to design and utilise the experimental research framework for studying emergent properties of the teams;
- Aim II: To analyse data gathered by experimentation with the teams, to identify and characterise teams’ emergent properties, and to computationally model and simulate the effects of the team adaptability during critical activities in innovation-oriented product development (such as ideation, problem-solving or decision-making).
In EUROPE 2020 Flagship Initiative Innovation Union, it is highlighted that is more important than ever to deliver the so-called “fifth freedom”, which is not only the free movement of R&D resources but also the free movement of innovative ideas between people. Genuinely open innovation requires brokerage, intermediaries and networks in which all players can participate on an equal basis as the members of the product and services development teams. Internationally competitive teams play a vital role in bringing together – physically and virtually – large companies and SMEs, universities, research centres and communities of scientists and practitioners to exchange knowledge and ideas. The proposed research is therefore aimed to understand and better support teams in conceiving, developing and deploying of engineering systems of increasing capability and richness of functions and features, within an environment of competitiveness and innovation on a global market scale.
Alongside with years of research on benefits of teams and teamwork, recently the research focus started shifting on team functionality, mainly performance and effectiveness (see Kozlowski et al., 2015), but also to the different emergent properties of the of the teams critical to the innovation. The same was confirmed in our past project (2014-2018) funded by CSF titled Models and Methods of Innovation Management in Complex Engineering Systems Development – MINMED. The goal of the MINMED project was to develop a set of fundamental models and methods for innovation management within and across hierarchical social networks existing in contemporary product and service development organisations, and to explore and develop analysis tools in quantifying team dynamics as a mean for prediction of the future trends in innovation.
The impact that the acquired research and scientific competencies and skills during the research realisation will have on potential beneficiaries appears in three ways:
- It will enable them to better understand, design and manage engineering teams and their dynamics to support pressing needs for more efficient development and management of complex engineering systems, e.g. transport and energy resilience, environment and sustainability, supply chain dynamics, etc.
- It will enable them to better understand complex environments in which engineering teams exist and work, e.g. regulations, ethics, markets, etc.
- It will allow them better control of the means for innovation management as adaptive dynamic complex socio-technological process applicable for different industrial sectors and public organisations.
During the project, the Design Science Research (DSR) framework illustrated by the three related cycles of activities will be applied as the research methodology.
Relevance cycle (2019)
Initially, literature review on experimental studies within team context and associated computational models will be conducted to establish a valid basis for an experimental research framework focusing on emergent properties of the teams. In addition, the set of preliminary experiments in DEPICT lab and CADLab will be performed to deepen understanding on various aspects of teamwork and team behaviour. Based on the obtained insights from both literature review and preliminary experiments, it will be possible to define preliminary needs and requirements for development of experimental research framework and architecture tailored for conducting team adaptability studies.
2. Design cycle (2019-20)
To put proposed research study on scientific foundations, it is essential to clearly identify variables and factors relevant to the primary subject of the empirical studies. The detailed design of experiments will include a multiple problem statements (e.g. specific hypothesis testing), identification of response variables for each case, controlled and manipulated factors, levels, and ranges, subjects chosen, sample size, type of data collected, statistical analysis of the data, and expected results (such as hypothesis validation or rejection). Significant effort will be placed on analysis of data mining methods and tools that will allow different analytical approaches to the gathered dataset. Self- and external monitoring technologies coupled with data mining and machine learning technologies can offer possibilities for developing and implementing of semi-automatic and automatic procedures for post-experimental data analysis. The findings will be implemented in the form of computational models to address dynamic contexts of the innovation-oriented product development teams and to simulate how teams react to acute and unexpected events.
3. Rigour cycle (2020-22)
In the final cycle, the main focus will be to use the developed experimental research framework to study teams’ adaptability. Computational models, which were developed in the Design cycle, will now be specifically tailored for various adaptability simulations. The obtained simulation outputs will be compared and validated with experimental results in the DEPICT lab and CADLab to identify potential drawbacks and deficiencies. The resulting computational framework should enable researchers and practitioners from the industry to utilise simulations to understand the role that the different types of disruption triggers have on the resulting team adaptation, as well as to predict the impact that different levels of the team adaptability may have on various teamwork outputs. To applicability of proposed computational framework in practice, it will be necessary to properly address scalability issues and conduct additional studies in industrial settings. Also, the new research propositions will be created and evaluated that could bring consistency and transparency to various aspects of teamwork influencing the initiation of the new research cycles in the project.
Infrastructure and international collaboration
Following the successful collaboration within the MINMED project, for the proposed research the critical part of the infrastructure needed for experimentation with face-to-face and virtual teams will be enabled by collaboration with DEPICT lab (www.ltu.se/depict) being built up at Luleå University of Technology – LTU (Sweden) and open in early 2017. The DEPICT lab worth several million of SEK is a bright example of the Swedish research support model in uniting many different measurement methods for advanced research on human behaviour and enables new cross-disciplinary research projects by the interdisciplinary research groups. In additional to the traditional equipment for external monitoring, the lab has the equipment to measure brain activity, eye and muscle movements, pulse, respiration, skin redness, brain waves and software to interpret and analyse gathered content. The lab is fully equipped with the means needed for studying virtual teams as well. Part of the equipment in DESPICT lab is mobile, to be able to bring it to other laboratories and outside the university, what will be critical when experiments including participants from the industry will be conducted. In addition to the infrastructure available in the DEPICT lab, the part of the equipment needed for the research on the virtual teams will be acquired and installed at the CADLab at UNIZG-FSB thus enabling experimentation with virtual teams composed of members located in geographically different locations. The part of the equipment needed for computational modelling and simulation of the emergent properties of the teams will be also acquired and installed at the CADLab at UNIZG-FSB.
Dr Peter Törlind, the Head of the Innovation and Design Division at the Department of Business Administration, Technology and Social Sciences, will be main contact point at LTU and research associate offering his expertise in quantitative experimental research for innovation oriented product development. In addition to the support from LTU, the project will be actively supported by the other two international research associates. Prof. John Gero (currently at UNCC USA, Department of Computational Social Science) is the most cited author in the field of engineering design science, design computing and design cognition (>20.000 citations and H-index of 65 on Google Scholar) and editor of 52 books and over 700 papers and book chapters, with more than 30 years of experience in multidisciplinary research and applications related to the human behaviour in product development. Prof. Phil Cash (currently at DTU Denmark, Department of Engineering Management) is still considered as young academic by the ERA rules, but he already published 15 high-quality journal papers in last five years after he acquired PhD degree in UK, and authored and co-edited two scientific books focusing on the engineering work and behavioural design. Also, Prof. Vedran Podobnik from Faculty of Electrical Engineering and Computing of the University of Zagreb will support the research group in a role of the consultant for the field of the computational studies of team behaviour specialising in research of behaviour in virtual collaborative environments and social networks.