New knowledge creation within manufacturing: a pattern analysis of behaviours and interactions that underpin knowledge creation and innovation in a large German automotive manufacturer

Auernhammer, J., Hall, H. (2013, ). New knowledge creation within manufacturing: a pattern analysis of behaviours and interactions that underpin knowledge creation and innovation in a large German automotive manufacturer. Paper presented at Information: interactions and impact (i3) 2013, Aberdeen.



NB The slides for this presentation are available on SlidesShare at Elements of this presentation were developed into a peer-reviewed journal article: Auernhammer, J. & Hall, H. (2014). Organizational culture in knowledge creation, creativity and innovation: towards the Freiraum model. Journal of Information Science. (DOI 10.1177/0165551513508356.) See further details of the article and links to full-text versions at

Organisational culture is regularly cited in the knowledge management literature as a barrier to information and knowledge sharing (for example, Hall & Goody, 2007, p. 182). In addition, it has been noted that the degree of success of knowledge management initiatives to underpin new knowledge creation and innovation is highly dependent on local contexts (for example, Detlor, Ruhi, Turel, Bergeron, Choo, Heaton & Paquette, 2006) and the nature of social and cognitive systems (Iba, 2010). Thus a particular approach that works well in one environment may fail elsewhere. While the umbrella term of “culture” might account for the difficulties organisations face in generating ideas for new products and services, practitioners who hope to draw on examples of good practice to address what is encompassed by this term are often disappointed when the specifics of published case studies do not match their own local environment.

Based on findings drawn from an in-depth study executed within the German automotive manufacturer, this paper addresses questions related to culture and knowledge creation. It highlights specific determinants and conditions as patterns that bear influence on a number of organisational behaviours, including those that underpin influence information and knowledge sharing, such as dialogue (Bohm & Peat, 2011). These are derived from a pattern analysis (Alexander, Ishikawa, & Silverstein, 1977) of interactions that relate to (a) shared behaviours at the macro level of the organisation and (b) situated interactions performed between individuals and small groups at the micro level, reflecting the duality of structure as identified by (Giddens, 1984). This pattern analysis identifies components of culture as determinants for new knowledge creation, and offers practical advice that can apply across a number of contexts.

Data for the study were gathered in the period November 2007 to December 2008:

• by survey: 201 participants from across a range of business functions responded;
• from two focus groups that comprised 18 development department staff (total);
• in interviews with 46 employees who work in innovation management functions.

A factor analysis of the survey responses related to ten statements on innovation performance provided a macro-level gauge of how participants perceived this within the firm. These findings (amongst others related to wider aspects of the study) were presented at the two focus groups. Here participants verified the survey findings and discussed the impact of the macro-structure on individual behaviours and interactions as related to new knowledge creation. The interviews provided a further opportunity to discuss these themes, in this instance on a one-to-one basis with (mainly) senior managers. Coding and cognitive mapping of the qualitative data from the focus groups and interviews generated valuable output that was reformulated as patterns. These patterns describe the situations in which creative ideas emerge within interactions of individuals at the micro level, as bound within the broader social structures of the macro level. They explain the impact of cultivated behaviours on group interactions as related to team creativity and innovation.

Following the analysis of the empirical data the results were presented to the case study organisation in a series of presentations in 2010 and 2011. These presentations provided an opportunity to verify the research findings and confirm their relevance, and for the staff a chance to reflect on their implications in practice.

The main findings from the quantitative analysis of the survey data reveal the characteristics of an environment that is conducive to new knowledge creation and, ultimately, innovation. Such an environment is one that is open to change, values free communication and new and/or unusual ideas, tolerates mistakes, and is populated by staff who are intrinsically motivated. It is supported by leaders who promote these characteristics as shared values, while challenging and empowering their staff to generate new ideas in a drive to further innovation.

The qualitative analysis of the focus group and interview data sheds light on three main determinants for new knowledge creation. These are:

1. Expertise and experience of individuals. This comes from close engagement in essential tasks, i.e. working “in the thick of it”, experiencing problems and opportunities where and when they occur.
2. Propensity of individuals to experiment with ideas, even at risk of failure i.e. a degree of “innovation willingness”.
3. Authorised, protected and dedicated “space” designated specifically for the exploration of new ideas. This takes the form of free time away from the usual extreme time pressures and other work constraints. We use the German term “Freiraum” to encompass the sense of “space” that is both a place and time that offers “freedom” for idea exploration and creation. Freiraum may be conceived as a type of “Ba” (Nonaka & Konno, 1998) where there is high system redundancy (Bakken, Hernes & Wiik, 2009a; Bakken, Hernes & Wiik, 2009b). In this kind of space individuals have the freedom to be creative. Freiraum adds a further dimension to the concept of Ba with its focus on human creativity.

An implication of these findings is that individuals need to be supported so that they both engage in the routine to develop their expertise and experience, and periodically step out of it in order to explore new ideas. Where this is successful, the new ideas are then brought into the routine to be shared and prototyped. They thus contribute to new routines and practices, and – it is hoped – innovation in products and services delivery. An advantage of this approach over standard models for facilitating creativity and innovation (such as linear innovation processes with shared routines and fixed structures) is that it can be adopted to fit with the extant management style of the organisation, and its own particular context. This is important given the dynamic nature of new knowledge creation.

This paper is of particular interest to researchers and practitioners keen to explore information and knowledge management issues related to organisational culture and management, and conditions that enhance practices of creativity and innovation as individuals interact within broader organisational contexts. It also affords an opportunity for discussion of methodological choice when undertaking case study research of this nature, and the use of pattern analysis as a tool for data analysis and presentation.


Alexander, C., Ishikawa, S., & Silverstein, M. (1977). A pattern language : towns, buildings, construction. New York: Oxford University Press.

Auernhammer, J. M. (2012). Autopoietic organisation of knowledge, creativity and innovation: a case study of the automotive manufacturer Daimler AG. Edinburgh Napier University Edinburgh.

Bakken, T., Hernes, T., & Wiik, E. (2009a). An Autopoietic Understanding of "Innovative Organization". In R. Magalhães & R. Sanchez (Eds.), Autopoiesis in organization theory and practice (pp. 169-182). Bingley: Emerald.

Bakken, T., Hernes, T., & Wiik, E. (2009b). Innovation and Organization: An Overview from the Perspective of Luhmann's Autopoiesis. In R. Magalhães & R. Sanchez (Eds.), Autopoiesis in organization theory and practice (pp. 69-88). Bingley: Emerald.

Bohm, D., & Peat, F. D. (2011). Science, order and creativity. London: Routledge.

Detlor, B., Ruhi, U., Turel, U., Bergeron, P., Choo, C.W., Heaton, L., & Paquette, S. (2006). The effect of knowledge management context on knowledge management practices: an empirical investigation Electronic Journal of Knowledge Management 4(2), 117-128.

Giddens, A. (1984). Constitution of society : outline on the theory of structuration. Cambridge: Polity Press.

Hall, H. & Goody, M. (2007). KM culture and compromise – interventions to promote knowledge sharing supported by technology in corporate environments. Journal of Information Science, 33(2), 181-188.

Iba, T. (2010). An autopoietic systems theory for creativity. Paper presented at the 1st Collaborative Innovation Networks Conference, COINs Procedia Soc. Behav. Sci. Procedia - Social and Behavioral Sciences.

Nonaka, I. & Konno, N. (1998). The concept of "Ba": building a foundation for knowledge creation. California Management Review, 40(3), 40-54.
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Jan M. Auernhammer
Visiting Scholar, Center for Design Research, Stanford University
+44 131 455
Hazel Hall
Director of CSI
+44 131 455 2760

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