Creating and Distributing Innovative Knowledge within Universities: Virtuous Spiral or Vicious Circle? Martin Rehm, Katerina Bohle Carbonell, Karen D. Könings, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands Email:
[email protected],
[email protected],
[email protected] Amber Dailey-Hebert, Park University, 8700 NW River Park Drive, Parkville, MO 64152, Unite States
[email protected] Abstract: In light of growing complexity and volatility in the world, universities are challenged to tackle interconnected, ill-defined problems in need of innovative solutions. Yet, higher education finds difficulty in organizing initiatives to address such issues and continues to structure solutions in traditional, hierarchical, and restrictive ways. In contrast, bottom-up projects recognize the unique knowledge individual faculty hold and their importance for knowledge sharing and creation within organizations. Here, the creation of Innovative Knowledge Communities (IKC) has been suggested to foster the development of new ideas and innovative approaches. Yet, for successful innovations it is crucial to know whether, and to what extent, members of IKC are able to accomplish their task of distributing newly gained knowledge and information within an organization. In order to investigate this issue the current paper will present an intercontinental project that investigates the level of organizational learning at a European and an American university. Additionally, preliminary findings from social network analyses and questionnaires on individuals' knowledge sharing attitudes will be presented, which will provide valuable input to create new educational and administrative procedures, methods and tools to pinpoint where new knowledge is created and how (far) this knowledge is spread.
Introduction In light of growing complexity and volatility in the world, universities are challenged to tackle interconnected, ill-defined problems in need of innovative solutions. Yet, higher education finds difficulty in organizing initiatives to address such issues and continues to structure solutions in traditional, hierarchical, and restrictive ways. This is problematic as top-down innovation suffers from resistance to change (Kotter & Schlesinger, 2008). In contrast, bottom-up projects acknowledge the unique knowledge individual faculty hold and their importance for knowledge sharing and creation within organizations (Argote & Ingram, 2000). The success of bottom-up projects lies in the organization’s ability to make use of faculty’s tacit knowledge composed of their on-the-job experiences (e.g. Gherardi & Nicolini, 2000). By using individuals’ tacit knowledge to create new explicit knowledge, organizations could contribute to the process of (innovative) knowledge creation within organizations. However, little is known about how these processes are shaped. It is known that the transfer from tacit to explicit knowledge depends, among others, on two factors. Firstly, the conversion of tacit knowledge into explicit knowledge is stimulated through social interaction, which promotes the articulation of ideas and experiences, integrating them in one’s actions and practices (Nonaka, 1994). Secondly, the creation of Innovative Knowledge Communities (IKC), which foster the development of new ideas and innovative approaches to deal with (new) problems (Hakkarainen, Palonen, Paavola, & Lehtinen, 2004). Yet, for successful innovations it is crucial to know whether, and to what extent, members of IKC are able to accomplish their task of distributing newly gained knowledge and information within an organization. In order to investigate this issue our paper will present an intercontinental project that investigates the level of organizational learning at a European and an American university (Maastricht University and Park University, respectively). At Maastricht University the focus is on a 3-year project that piloted innovative learning approaches from baseline faculty to inform organizational practice. At Park University a 2-year multidisciplinary team to innovate faculty development for all modes of the university forms the basis for our analysis. As both institutes used project structures similar to IKC, this underlying research investigates how project members contribute to the process of innovation adoption and organizational learning. The main research question is formulated as: How do educational innovators collaborate and spread their newly gained knowledge throughout an organization in “bottom-up” initiatives? What are possible differences in this respect when comparing initiatives in the Netherlands and the United States? By answering these questions using social network analysis (e.g. de Laat, Lally, Lipponen, & Simons, 2007), as well as data on individuals' knowledge sharing attitudes (Bock, Zmud, Kim, & Lee, 2005), the results
will contribute to understanding how knowledge flows within universities, whether and how IKC members can contribute to this process, and will assess the involved faculty members ability and willingness to engage in knowledge sharing activities..
Conceptual Framework Figure 1 below provides a visual representation of the conceptual framework. In the process of starting with an innovative idea and embedding it in organizational learning, three stages can be identified during which tacit knowledge is transformed into explicit knowledge. Figure 1. Research Model
Group A represents participants closely involved in the bottom-up initiatives and who thus internalized, combined and shared their tacit knowledge. Group B represents participants attending inter-university knowledge dissemination events. The main aim is to assess whether, and to what extent, information flow exists between IKCs and whether the newly created knowledge is shared and refined among similar initiatives. The combined group in Stage 3 is used to measure the potential impact of the IKC on organizational learning.
Research Methodology Commonly used network statistics are used to analyze the data. More specifically, the data provides valuable insights on: 1) An actor’s: a) ability and/or power to spread certain information – e.g. betweeness (Hanneman & Riddle, 2005) b) position within the IKC – e.g. centrality (Johnson-Cramer, Parise, & Cross, 2007) c) amount of contacts within the IKC– e.g. ego-networks (Rienties, Tempelaar, Giesbers, Segers, & Gijselaers, 2012) 2) The position of the IKC within an organization. This is done through an analysis of (potential) cliques (e.g. McPherson, Smith-Lovin, & Cook, 2001). Additionally, questionnaires are developed that measure factors that have the potential of influencing individuals' knowledge sharing attitudes. Depending on the (external) circumstances, it has been suggested that individuals might refrain from openly sharing information and instead exhibit a tendency to hoard their knowledge (Fishbein & Ajzen, 1975). In order to assess these types of behavior, we follow the work of Bock and colleagues (2005), who designed a questionnaire that measures the factors supporting or inhibiting individuals' knowledge sharing intentions.
(Preliminary) Findings Social Network Analysis At the stage of writing this paper, we have already been able to conduct a first preliminary analysis of Group A (Stage 1) at Maastricht University. As can be seen from Figure 2(a) below, which accounts for all ties among members, the applicable IKC network is densely connected, which suggests that a fluent exchange of tacit knowledge among members might have been promoted. However, when qualifying the nature of the connections and focusing on those linkages that have occurred frequently, as displayed in Figure 2(b), the picture changes and reveals that there appear to be two cliques. The underlying reasons remain to be determined in subsequent analyses. However, considering more detailed information that has been gathered on the project team’s members, it seems that geographical location, as well as content-related project considerations might be able to
explain some of the observed creation of cliques. Additionally, some evidence suggests that the initiators of the IKC (grey squares) withdrew from the project activities, once the main actors were connected and engaging into discussions. Figure 2. Degree Networks for connecting with colleagues (a) at least once, and (b) frequently
(a)
(b)
Knowledge Sharing Attitudes Furthermore, based on the results of our distributed questionnaire, we were able to identify a positive attitude towards sharing knowledge and contributing to innovative processes within the university. For more information, please consider Table 1 below. Table 1. Results of the Questionnaire “Knowledge Sharing Attitudes @ Maastricht University”
Interestingly, the intention to share knowledge with colleagues seems to be positively influenced by individuals’ perception of how this would then translate into their organizational network position. More specifically, one driving factor that contributed to knowledge sharing appears to be the belief that this will “strengthen the ties between existing members in the organization and [an individual]” (M = 4.6, SD = .52) and “expand the scope of [an individual’s] association with other members in the organization” (M = 4.6, SD = .52). Additionally, respondents of the questionnaire also indicated that “My colleagues think I should share my knowledge with other members” (M = 4.1, SD = .88), which suggests a certain (organizational) culture that is supportive of these type of activities.
Outlook The data and results presented in this paper have provided a first preliminary idea of how educational innovators collaborate and spread their newly gained knowledge throughout an organization in “bottom-up” initiatives. However, as has been previously indicated, this merely constitutes the first step of a larger research initiative that will expand its scope to include a broader group of individuals from within the entire organizations (both universities), in order to provide more detailed insights whether, and to what extent, the IKC in question have been able to contribute to the learning process within their organization. Additionally, by conducting a cross comparison of similar initiatives from a European and American university, this research can help to identify possible differences in how knowledge is spread throughout an organization within different (cultural) contexts. Overall, this research can thereby contribute to our understanding of how new educational and administrative procedures are created, which methods and tools might be suitable to foster this process and the degree with which the outcomes spread within an organization.
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