Innovation through Collaboration: Volume 12

Michael M. Beyerlein is director of the Center for Collaborative Organizations (www.workteams.unt.edu) and professor of Industrial/Organizational Psychology at the University of North Texas. His research interests include all aspects of collaborative work systems, organization transformation, creativity/innovation, knowledge management and the learning organization, and science education. He has published in a number of research journals and has been a member of the editorial boards for TEAM Magazine, Team Performance Management Journal, and Quality Management Journal. Currently, he is the senior editor of the Elsevier annual series Advances in Interdisciplinary Studies of Work Teams and the Jossey-Bass/Pfeiffer Collaborative Work Systems series. He has authored or edited 18 books. His most recent books include: Guiding the Journey to Collaborative Work Systems: A Strategic Design Workbook (2004) and Collaborative Capital (2005). He has been involved in projects at the Center for Collaborative Organizations (formerly, The Center for the Study of Work Teams) with such companies as Boeing, Shell, NCH, AMD, Intel, Raytheon, First American Financial, Westinghouse, and Xerox and with government agencies such as Veterans Affairs, DCMAO, EPA, and the City of Denton.

Sternberg & Lubart (1991); Sternberg & Lubart (1992).

High-technology firms often institute cross-functional teams to manage product innovation initiatives. The assumption is that (a) creative and successful products from new technologies must reflect the integration of multiple talents, therefore the innovation process will require integration among people who possess them, and (b) when people with multiple talents are placed in teams, they will interact, cross-fertilize ideas, and collaborate to produce creative new products from new technologies faster and cheaper than those produced by alternative structural arrangements. While teams are easy to institute, fostering high levels of collaboration among participants has proved harder in practice. While some teams achieve high levels of collaboration, others merely replicate rivalries that exist in the organization and breed cynicism.

Based on our study of product innovation processes in high-technology industrial manufacturers, this chapter discusses the differences between high- and low-collaboration teams. Specifically, we report the key (a) developmental milestones in the process by which groups of people from diverse functional areas become high-collaboration teams and create new products faster and cheaper, and (b) factors associated with participants, team leaders, senior management, and the organizational culture that seem to shape the emergence of collaboration in teams.

This chapter explores the unique role of leadership in organizational innovation. Drawing from the investment theory of creativity (Sternberg & Lubart, 1995), we show that organizational innovation begins with a leadership decision. Based on a review of the creativity, organizational, and leadership literatures, the key components of organizational innovation are examined from individual, group, and organization-wide perspectives. Leading innovation is conceptualized as a special case of leading organizational change, which requires creative leadership skills applied to social systems. Establishing an organizational environment that supports innovation in the current market environment increases systemic paradoxes that must be managed by leaders. We conclude that leading innovation increases the creative demand on the leadership system, which requires leaders who have a developed understanding of the process of innovation and its environmental requirements.

The importance of collaboration had been widely recognized but its nature has remained obscure. This chapter suggests that an appropriate level of analysis for collaboration research would be social interaction and the optimal unit of analysis would be communities of practice. Such a sociocultural approach departs from the traditional positivist approach, which echoes the long-standing conflict between postmodernism and modernism. Principles of organization in traditional institutions and communities of practice are then contrasted. The differences among coordination, cooperation, and collaboration are presented, suggesting that the prototypical form of collaboration locate in communities of practice. Finally, a new look at the relationships between collaboration and learning, collaboration and innovation is extended to describe the workspace created by communities of practice.

As other researchers have done previously, we conceptualize innovation not as a linear process but as a cyclical one (e.g., Van de Ven, Polley, Garud, & Venkataraman, 1999), which consist periods of innovation initiation, implementation, adaptation, and stabilization (West, 1990). Within this cycle it is possible to distinguish two major components: the beginning of the cycle, which is dominated by the generation of ideas that is generally also designated as creativity; whereas the dominant activity at the end of the cycle which is the implementation of ideas (hereafter referred to as the implementation of innovation). Creativity is then likely to be most evident in the early stages of the innovation process, when those in teams are required to develop or offer ideas in response to a perceived need for innovation. Creative thinking is also likely when teams proactively initiate proposals for change and consider their initial implementation. As the innovation is adapted to organizational circumstances, there is less need for creativity. At the outset of the process, creativity dominates, to be superseded later by innovation implementation processes. Of course, it can be argued that creativity is important throughout the innovation process, but in general, the requirements for creative ideas will be greater at the earlier stages of the innovation process than the later stages.

Organizations are reorganizing into collaborative subunits or teams in order to generate innovative ideas and stay ahead of the competition. Traditional control systems were established to direct employees and prevent control problems, such as fraud or theft, and were designed for vertically managed systems where managers and supervisors made decisions and their subordinates performed tasks. As companies evolve into a team-based structure, decisions are made at lower levels. Restructuring for teams makes information more available and decisions more transparent. Traditional controls no longer apply and can be detrimental to empowerment and the generation of innovative ideas. With increased empowerment there will be a need for different controls and maybe even more control. Innovation can thrive when collaboration takes place and collaboration can occur best when teams are empowered. This chapter presents three separate domains – models of empowerment and innovation, decision-influencing and decision-facilitating information, and management control systems – and illustrates how they interact in a holistic way to either enhance innovative culture or inhibit the generation of ideas.

This chapter considers the role of technology transfer intermediaries (TTIs) in the processes of innovation in networks involving universities, research and development centres, and business firms from an international perspective. A diversity of types of TTIs is recognised in terms of their particular interests in the operation of innovation processes and the conditions they impose in transactions involving intellectual property. It will identify the various objectives of sponsoring stakeholders as differentiating the missions and accountabilities and, in turn, determining the focus and roles of different types of TTIs and the interactions and networking between them, both formal and informal.

In discussion, the chapter will propose that the significance of systemic influence on the processes of technology transfer and innovation should be researched at two levels. At the micro-level of personal interactions, examining how systemic influences shape tacit knowledge transfer between and learning by individuals engaged in research and innovation processes. Second, at the level of national cultures, examining the ways in which the cultural context institutionalises patterns of innovation and technology transfer networking.

Collaboration as a means to enabling and nourishing innovation is an important theme in the extant literature, which posits that face-to-face interactions lubricate the knowledge flow between actors, and that clusters of complementary knowledge assets provide the necessary infrastructure for this process. What happens to firms that are located outside of urban agglomerations or in peripheral regions? Are they less innovative, or can information and communication technologies (ICT) serve as a proxy for face-to-face collaboration? Theory is polarized in terms of the role that ICT may play in collaborative transactions. For example, network theory explains that weak ties are important in terms of refreshing a firm's innovation capacity by forcing it to include ideas from the periphery. Others argue that ICT cannot supplant face-to-face interaction since it is not an efficient medium for transferring tacit knowledge. This chapter uses data from the Statistics Canada 2003 Survey of Innovation to investigate empirically the relationship between firm location, innovativeness, and the extent of local and more distant collaboration.

This chapter takes a closer look at how social networks can affect the early development of new ventures. The dynamic role of social networks is discussed and exemplified by two longitudinal cases that illustrate the radically different ways in which social networks can influence venture development. These differences relate to social or individual ownership of the innovation process, to risks or opportunities as the focus of attention, and to the creative relationship between networking and financial bootstrapping techniques.

The aim of this chapter is to analyse and to define the role and opportunities offered by the adoption of a new ICT (Information and Communication Technology) tool within an organization, focusing attention on internal collaborative processes that have been induced by the development and use of the new tool. As noted by some authors, ICT tools may create a virtual meeting place where individuals can engage in dialogue and collaboration. However, other authors argue that technology could reduce direct involvement, social interaction, collaboration and reflective conversations that traditionally give rise to knowledge processes and thus to innovation processes inside the organizations. Nevertheless, some research contributions show that it is not an ICT tool itself that provides positive or negative effects on organizations, but how the tool is used in conjunction with complementary human resources. These contributions avoid technological determinism by stressing contingency and by coupling human design intent and activity with the disposition of actors inside organizations.

In order to fulfil the aim of the chapter, a study was carried out in a leading firm in the automotive industry, till now involved in a project aimed at implementing a new simulation tool for the assembly process. The evidence from the case seems to suggest that the development and use of the simulation tool activated the social interactions and collaborations that enacted innovation processes. The simulation tool seemed to facilitate a productive dialogue among the different departments and a deeper understanding of the different challenges involved. The development of the simulation “forced” experts of different departments to meet and to keep the focus on salient aspects. The simulation acted as a boundary object. The development of this boundary object was un-intentional but it is clear that the simulation contributed to the formation of a community of collaborators.

It is worth noting that this was not the result of the simulation tool itself but rather the result of management actions aimed at making sense of the whole project, supporting the initiative and thus motivating users.

Recent events such as the terrorist attacks of September 11, 2001 against the United States and the national disaster of Hurricane Katrina demonstrated the acute need for interagency collaboration. Using a semi-inductive method, we conducted two studies with senior homeland security leaders to learn more about organizations’ collaborative capacity during the early planning stages. In study One, we used an interorganizational systems perspective to identify factors that create or deter effective collaboration. Study Two elicited vignettes from a second group of senior homeland security leaders to gain further insights into the ways in which their organizations are successfully building collaborative capacity.