INNOVATION THROUGH KNOWLEDGE
DISSSEMINATION:
'Creating new business opportunities for the building information modeling (BIM) innovation'
Contractor: Tam Vo Function: Intern
University: Rijksuniversiteit Groningen Faculty: Economics & Business Program: Business Administration Specialization: Business Development Place: Groningen
Supervisor: prof. dr. ir. J.M.L. van Engelen Client: ir. M.C. Versteegden BNA
Function: Commercial Manager / Project manager Organization: ARCADIS Nederland B.V.
Department: Division Buildings – Unit TAO Place: Amersfoort
Preface
Nobody said that writing a thesis would be done at a glance and this was definitely true for me. The topic I have chosen to conduct a research on did not made it easier, though at the same time it gave me an enjoyable feeling when supervisors and those interested gave me credits for bringing a difficult subject to light. A thesis is something you want to end in style and therefore I aimed high with my research subject. Maybe I was following Carl Sandburg (1907) too much who quoted; “I’m an idealist. I don’t know where I’m going, but I’m on my way”. The road to the topic for my thesis has been long and so was the rest of the process. ‘Learning on the job’, a process that has been embedded into ANL’s organization culture, and which I fully adopted during my time at the organization.
The Building Information Modeling (BIM) innovation and its ongoing development is rapidly being adopted by the Architecture, Engineering and Construction (AEC) industry and is in need of intensive collaborations to come up with industry standards and create value for all stakeholders. Proactive knowledge sharing has been seen as an important theme by the members of the organization, though the organization members are being holding back somehow and cannot be motivated enough to actively and consciously share knowledge. External collaborations for developing BIM also are going slowly as organizations tend to be reticent. With this thesis I have attempted to find the motivators and enablers of knowledge dissemination and come with practical recommendations that help the organization move forward in KM and the BIM innovation. The AEC industry has been conservative with innovation initiatives compared to other industries, practicing social sciences in a technical oriented organization should be difficult. In the contrary, organization members were open for a research in human social behavior and thereby helped to move the organization and science in gaining Knowledge Management insights from practice.
Interviewees helped me (re)defining the business problem, getting insight in the problems around KM and steering me towards appropriate solutions for the organization. I therefore want to thank the organization members who have helped me by volunteering as interviewee. The interviewees have talked openly about their feelings, which they sometimes had difficulties to describe. During the interviews it was clear that the individuals are very loyal to the organization, which explains their long employment in the organization. This did not stop them from being honest and criticizing about how KM is being practiced by the organization, as this is a way for them to improve business and helping the organization forward.
My most gratitude goes out to my mentors Marjolijn Versteegden, Jo van Engelen, and secretary Linda van Ruitenbeek. As the research process went slow, Marjolijn always tried to motivate me by being positive and gave guidance on moments when it was needed the most. Marjolijn is a good example of how knowledge should be shared. In my eyes she is one of the most valuable member of the organization due to her excellent communication skills and the knowledge network she has built during her career. Her recommendations to go and speak with certain people in the organization has steered me into the direction of graduating with a thesis I am satisfied with. Jo is a very busy person with little space in his agenda and still he managed to made time to discuss about my thesis. I have experienced him as a person that does not shy away from challenges and is an advocate of bringing science and business together. I was very pleased that Jo wanted to mentor me during the writing of my thesis. His knowledge sometimes went beyond my capacity but he always took the time to explain, made me understand and get me further when I got stuck. The collaboration has been experienced as pleasant and inspiring. Linda has been my personal “mental coach” during my stay at the organization. Her sociability and support at times I had to take a break from my thesis had been very helpful and motivational.
Completing my study with this thesis does not mean the end of knowledge accumulation. My next goal will be for me to make the best of what comes ahead and enjoy a little more.
“There is one thing one has to have: either a soul that is cheerful by nature, or a soul made cheerful by work, love, art, and knowledge.” - Friedrich Nietzsche
Executive summary
Organizational innovation has been described in academic literature but not specific ascribed to service oriented and highly knowledge intensive organizations that operate in the Architecture, Engineering and Construction (AEC) industry. The Building Information Modeling (BIM) innovation is still in need of new knowledge to solve teething problems and bring new ideas for the development of new business solutions. Knowledge Management (KM), specifically the call for proactive knowledge sharing, is still lacking in most organizations. As developments of BIM are still ongoing and the future of BIM is still unclear, this research tends to deepen the motivational and enabling factors of knowledge dissemination and increase incremental innovation initiatives for BIM.
Relations between knowledge sharing and innovation already have been proven by researchers, therefore the focus merely goes out to; assessing motivational and enabling factors for knowledge dissemination and knowledge creation that are founded in current research literature; explore new motivational and enabling factors; and seek practical solutions for organizations to motivate and enable knowledge sharing. Three approaches for exploratory investigations has been used, namely; semi structured individual in-depth interviews, participant observation, elite and expert interviewing, and document analysis (Cooper and Schindler, 2006). Information has been collected from BIM key users from two divisions. These two divisions are the most active ANL divisions who are using BIM in client projects. The in-depth interviews were held among disciplines that are leading in the use of BIM. Additionally, a survey has been spread among the members of TAO to see if knowledge sharing statements, adopted from the literature and gained from in-depth interviews, are supported by the TAO organization.
The findings of this research shows that the current economic downturn has a great influence on the innovation capacity of the organization and even reduces knowledge sharing activities and behaviors. So called ‘high fences’ withholds individuals from the various divisions to share knowledge with each other. The approach by ARCADIS towards Organizational Learning and Learning Organization, its strategic choices concerning innovation activities for BIM, and knowledge sharing among OPCOs, all affects the pace of the BIM innovation and innovativeness of its organization members. ARCADIS has taken many steps in facilitating knowledge sharing possibilities. The attention to motivational and enabling factors could be increased. This research sees ‘top management support’, ‘developmental performance appraisal’ and ´training´ are most influential and effective organizational factors for motivating and enabling organization members to disseminate knowledge. These factors supports the development of Knowledge Management competencies of organization members, that is needed for them to go from doing KM to ‘consciously practicing KM’, which also needs a change of organization culture. Technology factors enables knowledge sharing but is not the key in motivating individuals to do it. ICT influences the convenience of individuals in sharing their knowledge, this can be both positive and negative. Individuals can get overwhelmed by tools and methods and (codified) knowledge can get lost in all the various knowledge sharing mediums. On the other hand it simplifies knowledge sharing by overcoming barriers such as time and place.
This research shows, by conducting a case study at ARCADIS Netherlands (ANL), that knowledge sharing is synonymous to innovating, and vice versa. To enable and motivate individuals to share knowledge, organizations need to improve the KM competencies of their organization members, focusing on influencing human social behavior from front line workers to executive senior management. Competencies for KM (SCIE, 2010) includes; knowledge awareness; finding knowledge; keeping knowledge up-to-date; contributing to knowledge information management processes; using knowledge and information for decision making; sharing and contributing to knowledge and information of colleagues; learning from experience; networking and collaboration; communication; and development of Knowledge Management competence. The importance of
firms as a new way to increase an organization’s innovativeness. KM should be part of corporate strategy and embedded into the daily operations of the organization. For BIM this means that BIM advocates should be designated to disseminate BIM knowledge using their developed KM competencies, this could be also be implemented elsewhere to increase innovation initiatives.
The implications of this study is that it is a single case study conducted at certain departments of the organization and for a specific innovation. This research is therefore not reliable enough to be generalized. Practice and science can therefore only benefit from this research when circumstances are alike. In the future a smaller number of factors should be examined using quantitative methods for outcomes to be more versatile. The dissemination of knowledge with the external organization fell outside the scope of this research as external organization mostly includes different factors that influence motivational and enabling behaviors for knowledge sharing.
Future research should focus on finding practical solutions, for example the search for methods and tools to improve individual’s KM competencies. Other important topic in KM is finding out how organizations can overcome trustworthiness and the loss of competitive advantage when sharing knowledge with external organizations.
List of Figures and Tables
FiguresFigure 1. The knowledge lifecycle (KLC) (Firestone and McElroy, 2005) ... 10
Figure 2. The regulative cycle (Van Strien, 1997) ... 14
Figure 3. Technological discontinuity depicted as a pair of S-curves (Foster, 1986) ... 20
Figure 4. SECI model - Four alternatives for creation of knowledge (Ramirez, et al., 2012) ... 22
Figure 5. The decision execution cycle (DEC) and problem recognition (Firestone and McElroy, 2005) ... 23
Figure 6. General framework for knowledge sharing (Lin, 2007) ... 24
Figure 7. Knowledge-sharing behavior model (Gagné, 2009) ... 27
Figure 8. General framework for knowledge sharing adopted from Lin (2007) and Gagné (2009) ... 29
Figure 9. Survey results: “Have you established individual collaborations (e.g. projects) with other members of you online community as a result of your participation in it?... 41
Figure 10. Survey scores (median) of statements about individual and organizational factors for knowledge sharing. ... 43
Figure 11. Survey result: "Do you consider yourself to be an expert in your discipline?" ... 44
Figure 12. Survey result: "Do others consider you as an expert in your discipline?" ... 44
Figure 13. Respondents score of encouraging peers to become active in CoP(s)... 45
Figure 14. Respondents score of CoP activity as part of 'performance review' ... 47
Figure 15. Learning preference: "I prefer to learn from ..." ... 49
Figure 16. ‘Knowledge mediums’ use among respondents ... 51
Figure 17. Respondents scores of use of ‘offline‘ communities ... 52
Figure 18. ‘Knowledge mediums’ use per time period, among persons who say they do use the medium 53 Figure 19. Respondents scores of use of ‘online‘ communities (facilitated by ANL) ... 53
Tables Table 1. Performance areas for knowledge initiatives (Esterhuizen et al., 2011) ... 18
Table 2. Generic classification of innovation in a knowledge creation perspective (Popadiuk and Choo, 2006) ... 18
Table 3. Basic beliefs in Tacit versus Explicit Knowledge Management Approaches (Sanchez, 2004) ... 19
Table 4. Elements and issues related to the dissemination process and utilization of research outcomes (NCDDR, 1996) ... 26
Table 5. Participants in-depth interview ... 33
Table 6. Interval and ordinal scales of the survey ... 33
Table 7. Quantitative versus qualitative research: Constructs of research quality (Siegle, 2002) ... 34
Table 8. View of BIM structured by discipline ... 38
Table 9. Statements on individual and organizational factors for knowledge sharing ... 43
Index
Preface ... 2
Executive summary ... 3
List of Figures and Tables... 5
1 Introduction ... 8
1.1 Problem context ... 8
1.2 Problem analysis ... 9
1.3 Research aim and objective ... 11
2 Research framework ... 13
2.1 Research questions ... 13
2.2 Research structure ... 14
2.3 Literature ... 15
2.3.1 Business Information Modeling ... 15
2.3.2 (Second Generation) Knowledge Management ... 16
2.3.3 Knowledge creation ... 22
2.3.4 Knowledge dissemination ... 23
2.3.5 Knowledge-sharing motivation ... 27
2.4 Conclusions of the literature ... 28
3 Research approach ... 30
3.1 Research design... 30
3.2 data collection process ... 31
3.2.1 Qualitative approach: Semi structured in-depth interviews ... 31
3.2.2 Survey ... 33 3.3 Quality criteria ... 34 3.3.1 Credibility ... 34 3.3.2 Transferability ... 34 3.3.3 Dependability ... 35 3.3.4 Confirmability ... 35
4 Analysis and results ... 36
4.1 Analysis of current knowledge of BIM ... 36
4.1.1 Defining BIM ... 37
4.1.2 Types of BIM knowledge ... 40
4.2 Knowledge Dissemination ... 41
4.2.1 Knowledge networks ... 41
4.2.2 Motivating and enabling knowledge sharing ... 43
4.3 Conclusions of the analysis ... 54
5 Case study: Discussion, conclusions and recommendations ... 57
5.1 BIM knowledge ... 57
6 Evaluation and reflection of the research ... 63
6.1 Evaluation and reflection ... 63
6.2 Future research... 64
Annex I Glossary ... 66
Annex II References ... 67
Annex III Simplified organizational structure ARCADIS Nederland BV ... 71
Annex IV Organizational structure ARCADIS NV ... 72
Annex V In-depth interview questions ... 73
Annex VI (ONLINE) SURVEY - Dutch ... 75
Annex VII (ONLINE) SURVEY-English ... 82
Annex VIII Competencies of Knowledge Management ... 89
Annex IX KM Competencies: Executive Senior Management ... 92
1
Introduction
This research focuses on Knowledge Management disciplines at an engineering firm in the Architecture, Engineering and Construction (AEC) industry. Innovation in the AEC industry is low compared to other industries (TNO, 2012) and has mainly focused on the dimensions of cost, quality and time. Since the last decade, innovation has been seen as a new dimension. Innovation can be technological and organizational in nature, and it may be new to the world, or just new to the industry or the businesses concerned. Organizational innovation has been described in academic literature, but not specific ascribed to service oriented and highly knowledge intensive organizations that operate in the AEC industry, like ANL. Knowledge Management (KM), specifically the call for proactive knowledge sharing, is still lacking when it comes to increase innovation initiatives by the AEC industry.
1.1
PROBLEM CONTEXTThe global economic-crisis has sharpened business all over the world, pushing stakeholders and organizations to act according to principles of ‘corporate social responsibility.’ This shift to social responsibility demands a different way of doing business, and has led the AEC industry to an extra focus on reducing development costs, especially when public funding is involved, and the use of sustainable solutions for building construction projects. BIM (Building Information Modeling) can meet this demand, by integrating the entire structural supply chain, creating a project environment, using ICT, where firms can collaborate effectively to reduce risks, costs and easier integrate new innovative sustainable solutions. These benefits have led to more demand from clients for projects using BIM. A research conducted in 2010 2010 (McGraw Hill Construction, 2010) concerning the use of BIM by the European AEC industry showed that more than one third (36%) has adopted BIM. These numbers give a good illustration of the adoption of BIM. Some say that the industry is adopting BIM at an increasingly fast pace, and even believe that not adopting BIM will risk the survival of the firm -- others say that the adoption of BIM has not yet led to many substantive collaborations, and that the benefits of using BIM are comparatively small.
“ARCADIS (ANV) is an international company providing consultancy, design, engineering and management services in the fields of infrastructure, water, environment and buildings. ANV aims to enhance mobility, sustainability and quality of life by creating balance in the built and natural environment. With 19,000 people worldwide (ANV), 2,400 of them working in The Netherlands (ARCADIS Nederland BV) (ANL), the company has an extensive international network that is supported by strong local market positions.”1 The ANL organization is divided into key business lines, and operated
by divisions and their (market) groups. Unit Technisch Advies & Ontwerp (TAO) (Technical Advice and Design) is a market group, and carries out the engineering of mainly buildings. This concerns engineering, construction and installation advice for all types of buildings (excluding residential housing).
ANL BIM activities in 2011 show that the organization is working towards the creation of a broad support for BIM by the ANL organization; BIM has been included into the strategy of ANL, BIM-workgroups are running pilot projects, and an ICT platform for BIM with associated processes are (being) developed to increase the adoption of BIM by the ANL organization. The extent of adoption of BIM by the industry can foster new opportunities, leading to new product development (NPD) initiatives for new and existing markets. The management of ARCADIS sees the use of BIM as a logical step and a revolution in the process of creating and renovating building structures in the AEC industry.
Knowledge-intensive firms are continuously searching for new ways to handle new technical-economic developments. What kind of institutional capacities and infrastructures are needed to obtain knowledge and skills to address new social, economic and environmental issues (TNO, 2012, webpage)?
Opportunities in the development of BIM can be seized by collaborations among the various disciplines, bringing new ideas together, and share knowledge to capture new innovative solutions.
1.2
PROBLEM ANALYSISThe increasing pace of BIM adoption by the ANL organization, its parent and sister organizations, and the rest of the AEC industry demand a steep learning curve. The use of the technologically innovative BIM is not the key factor of success, but is mainly the process that accompanies BIM technologies (Bew, 2010). The BIM process is characterized by integral collaborations between various AEC disciplines, and demands members to foster the integration of these disciplines by looking outside their working field. Integration of these disciplines brings new business opportunities. An unstructured intake interview was held among a small group of workers of ANL and ANV. The interviewees were chosen based on their involvement in the several ANL BIM workgroups. The goal of these interviews was to discuss and find problems or opportunities that the organization is facing during the adoption and development of BIM. The interviews led to the following observation:
The ANL divisions are learning to apply BIM through their own learning processes. Knowledge about BIM is therefore scattered throughout the ANL organization and knowledge is not being used effectively to create new innovative products2 for BIM.
This paper is commenced by the commercial department of TAO with the question;
“The adoption of BIM technology brings new business opportunities. How can we capture these business opportunities to increase incrementally innovation initiatives?”
The newness of BIM means that each discipline, in this case the ANL divisions, are working towards and searching for ‘best practices’ for their BIM process. Along their search they will reuse knowledge to solve common problems but also create new knowledge to solve problems (Markus, 2001), the creation of knowledge will be described in subparagraph (2.3.3). Scattered newly created BIM knowledge should be validated and integrated/ disseminated (Senapathi, 2011; Firestone and McElroy, 2005; McElroy, 2000) to organization members who can see new opportunities for the creation of BIM related products by building further on knowledge, creating new knowledge, and thus completing the knowledge lifecycle (KLC) via double-loop learning (Figure 1) (Firestone and McElroy, 2005). Validation and dissemination of knowledge will be crystalized in respectively subparagraphs 2.3.3 and 2.3.4).
1.3
RESEARCH AIM AND OBJECTIVEThe aim of this research is to create more understanding of the role of Knowledge Management (KM) as a catalyst for innovation initiatives and possible business opportunities, by gaining insight in the process of knowledge dissemination and knowledge creation.
Knowledge is seen as an important resource by academics and organizations. Research in KM gives us more insight in how knowledge influences the way organizations do business and how the management can influence organization members to create, validate and disseminate knowledge for achieving organization goals like the increase of innovation initiatives for new solutions. The focus of this research lies on knowledge dissemination and knowledge creation, as both are seen as part of the Knowledge Processing Environment (Figure 1) (Firestone and McElroy, 2005). These elements trigger both the reuse of knowledge, and the creation of new knowledge -- both key processes in creating new ideas for innovation. To achieve the aim, this research needs to compare the theoretical field of KM with the current state of the ANL organization to come with a diagnose and an appropriate solution.
This research is an initiative of the management of TAO to find solutions for innovation issues that the ANL organization and AEC industry faces. “Complex knowledge processes are present at the root of every innovation,” understanding the knowledge process is the foundation for the creation of new insights and ideas for innovation (Peschl and Fundneider, 2012, p. 42). The collaboration between ANL and myself, a graduate student of the University of Groningen, should contribute to more academic insights in the relation between KM and the creation of new innovative products in a business setting; more specifically, innovation in the AEC industry through knowledge dissemination (Tallman & Chacar, 2011; Senapathi 2011) and knowledge creation (Lin, 2007; McElroy, 2000; Buckley & Carter, 1999).
The BIM innovation has been adopted in this case study to conduct a research where knowledge sharing is an essential factor to further the developments of the BIM innovation and create new business opportunities. TAO conducted this research to promote the aforementioned for both national and international markets. However integrated processes that come along with BIM and organizational learning (OL), through knowledge dissemination as key process for the initiation of incremental BIM innovations, concerns the entire ANL organization. Therefore this research topic is relevant to both the Market-Group TAO and for the complete ANL organization. If international BIM projects are taken into consideration, the relevance even concerns the entire ANV organization, as well as their respective Operating Companies (OPCOs). Moving knowledge can be achieved between firms (inter-firm knowledge exchanges), but also between knowledge carriers in a certain firm (intra-firm knowledge exchanges) (Tallman and Chacar, 2011). Due to the limited time for this research and the fast pace of business, the focus of this case study lies on dissemination and creation of (BIM) knowledge by the individual in the ANL organization.
The objective is to gain insight in the current state of ANL, with TAO as main focus for the case study, enabling knowledge dissemination and knowledge creation for increased new initiatives for incremental BIM innovations3
The aim and objective of the research has led to one main research question, which has been broken down further into sub-questions and are formulated in paragraph 2.1. The main question and sub-questions have been defined to simplify finding relevant theories in KM literature and reaching the aim and objective of this research by helping the ANL organization to understand the value of specific topics in KM for moving forward the BIM innovation and create new business opportunities.
A remarkable fact is that knowledge dissemination and creation need attention in general. The well-known example of the application of academic theory into practice is often problematic, especially in social science; “The process of generating knowledge is rarely linked to the process of applying knowledge” (Conway et. al., 1976, p. 264). Therefore, my personal goal is to deliver a practical solution for Market Group TAO, and to promote the application of KM theories.
2
Research framework
In this chapter the aim and objective of this research, defined in previous chapter, have been translated into a main research question with sub-questions. The main research question has been revised numerous times to tackle the root of the problem the organization is struggling with. Sub questions were set up to structure and simple the analyzing of the problem and the search for solutions. Initially sub questions were answered by consulting Knowledge Management (KM), Learning Organization (LO) and Organizational Learning (LO) literature and previous conducted research.
2.1
RESEARCH QUESTIONSThe problem analysis, concerning BIM knowledge in the ANL organization, has led to the following main research question:
‘Incremental’ emphasizes the reuse of knowledge, the kind of knowledge that has already been available inside the ‘professional network’ of the individual.
To find the answer for the main research question, sub questions have to be answered:
How can ANL enable knowledge dissemination and knowledge creation to increase the amount of incremental innovation initiatives for BIM?
• What is BIM?
o What role does BIM play in the AEC industry? o How does BIM relate to KM?
• What is knowledge?
o What types of knowledge can we distinguish? o How does knowledge relates to innovation? o How is knowledge created?
• What is knowledge dissemination?
o How can knowledge dissemination be defined?
o What are the positive effects of knowledge dissemination for knowledge creation? o What are the negative effects of knowledge dissemination for knowledge
2.2
RESEARCH STRUCTUREThis research will follow the regulative or problem-solving cycle, depicted in Figure 2 (Saunders, Lewis and Thornhill, 2007; Easterby-Smith, Thorpe and Lowe, 2002; van Strien, 1997; Hedrick, Bickman and Rogers, 1993; Dewey, 1909). The regulative cycle is a methodology for problem solving in organizations and is found to be an appropriate guidance for this research (Aken et al., 2006). The questions are characterized by their search for definitions and interrelations, reflection of current organizational activities and exploration of human behavior. The cycle ensures the quality of the answers by dividing the research into logical steps from identifying the problem/ opportunity to the development of a suitable intervention. The process of
going from an unclear formulated business problem to solving a well-defined business problem (Aken et al. 2006) has therefore been the main reason to use the clear steps of the regulative cycle.
Formulation of a problem definition has been realized and confirmed by organizing a few intake meetings with the manager(s) of the unit TAO, selected organization members of ANL BIM workgroups, ANV KM-experts, and preliminary literature review.
• What are the enabling…
o individual factors for disseminating knowledge? o individual factors for creating knowledge?
o organizational factors for an individual to disseminate knowledge? o organizational factors for and individual to create knowledge? • How is BIM knowledge clustered in the organization?
o What levels of knowledge can we distinguish in the organization?
What types of knowledge for BIM can be distinguished for the each different ANL discipline?
• How can knowledge dissemination be organized in the TAO/ ANL organization? o How does the current dissemination process of BIM knowledge look like in the
organization?
o What kind of knowledge disseminations methods could be suitable for ANL? o How can BIM knowledge be directed to the right knowledge seeker?
o How can ANL foster knowledge dissemination with other OPCOs?
Problem mess Evaluation Intervention Plan of action Analysis and diagnosis Problem definition
2.3
LITERATUREThis research focuses mainly on Knowledge Management (KM), Organizational Learning (OL) and Learning Organization (LO) (Örtenblad, 2001) literature and more specifically on the processes of creation, dissemination, and the integration of knowledge as a way to foster innovation in Multinational Enterprises (MNE’s) in the Architecture, Engineering and Construction (AEC) industry. Identifying and analyzing the KM processes of an organization give more insight into the current KM status, and can help find appropriate KM interventions to enhance an organization’s KM processes. Suitable KM models from the literature have been found, and can be used to guide new enablers for knowledge dissemination and knowledge creation on an individual level. Firstly, a description of BIM will be given, focusing on the adoption and the developments, to show the role of KM. Further attention will be given to: the relationship between (Second Generation) KM and innovation, types and levels of knowledge, and the knowledge creation and dissemination process.
2.3.1
BUSINESS INFORMATION MODELINGThere are several descriptions for Business Information Modeling(BIM); - “BIM represents the process of development and use of a computer generated model to simulate the planning, design, construction and operation of a facility” (Azhar et al., 2011, p. 241) - or - “BIM is aimed at providing information about the entire building (in all life cycle phases) and a complete set of design information stored in an integrated database” (Hannele et al., 2012, p. 114). Bouferguene et al. (2011) distinguished several descriptive definitions of BIM among Canadian BIM users who see BIM as; a Technology, a Tool, a Process, a Philosophy or a Piece of Software.
Most of BIM definitions in recent literature are derived from the definition of The National Building Information Model Standard (NBIMS) Project Committee and is increasingly being adopted worldwide: “Building Information Modeling (BIM) is a digital representation of physical and functional characteristics of a facility. A BIM is a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life-cycle; defined as existing from earliest conception to demolition.” (National BIM Standard - United States, 2012).
The development of BIM has increasingly involved both academics and organizations in the AEC industry. Hannele et al. (2012) highlighted a distinction in the construction engineering literature about the development and integration of BIM. She sees a visible duality or incompatibility of the - technological change: role and features of the new technology, or a development of a family of BIM software based on it, – and – organizational change: new approach to the building process by using BIM in construction projects. Technological changes of BIM sets the pace for organizational changes and vice-versa, both aspects of change are in that sense interrelated and equally important for organizations in the AEC industry. The development of BIM can therefore be a slow and difficult process for organizations, as organizational change usually demands reformulation of the organizational culture. Even BIM skeptics acknowledge that this duality prevents the adaptation of BIM overnight. “BIM is such a new animal when compared to AutoCAD. But don’t think for a second that when a BIM-driven job comes along you’ll have time to plug-and-play with the necessary hardware, network upgrades, software acquisition fees, training costs and learning curves that will be necessary for the project” (Craig, 2009, p. 42). The Dutch AEC industry sees that BIM is slowly being demanded or even required by clients, and there is no escaping from the usage of BIM in building projects.
The creation of new knowledge comes along when organizations are aligning new technology with their organization processes. (BIM) Knowledge is seen by many as an important factor for competitiveness and even some say sharing knowledge is an important aspect to accelerate adoption and the further development of an innovation (Jippes et al., 2010). Early adopters of BIM, who are using discussion
integration are important aspects for the adoption and further development of BIM. At the moment intra- and inter-organizational BIM collaborations, also respectively called ‘little BIM’ and ‘Big BIM’ (Jernigan, 2008), are the most discussed factors for the pace of BIM adoption by the AEC industry. To fully benefit the use of BIM in projects, BIM process has to be integrated and utilized by all disciplines in the building process (Arayici et al., 2011). Intra-organizational BIM collaborations are in general easier to control by a single organization, whereas inter-organizational BIM collaborations have to lead to greater benefits for the AEC industry. In view of intra-organizational collaborations for BIM developments, ‘multidisciplinary’ is the advantage ANL has over its competitors. This multidisciplinary approach is expressed by the interrelatedness of the ANL divisions’ disciplines and brings the possibility to adopt and further develop the BIM process by efficient and effective knowledge sharing (Kluge et al., 2001) with merely the internal ANL organization or even the extensive ANV network.
Sub-conclusion 2.3.1.
In the research literature much attention has been given to the adoption of BIM, herein users are distinguished by their functional disciplines or business activities; e.g., architects, structural engineers, building engineers, civil engineers, Building Service engineers, contractors, BIM consultants, software application vendors, information technology specialists, project managers, facility managers, interior designers, landscape designers, property developers, academics, delegates from government agencies, etc. (National Bim Report, 2012; Bouferguene, 2011; Gu and London, 2010). These users operate in various disciplines, on different levels in the organization. Each discipline approaches BIM differently, this difference may lead to the emergence of different views, ideas and knowledge. Bringing these views together will foster more empathy for each other’s discipline, faster adoption of BIM and creation of new knowledge, all resulting in increased business (in terms of new products, services and processes, better served markets and increased profit). Knowledge Management therefore has to be the motto for ANL to discover new (business) opportunities for BIM.
2.3.2
(SECOND GENERATION) KNOWLEDGE MANAGEMENT“The focus on knowledge has increased significantly in recent years, the possibilities for the exchange of information has increased and the development of new knowledge goes faster than ever” (Gielen, 2009, p. 7). “Knowledge is increasingly being recognized as a vital organizational resource that gives market leverage and competitive advantage” (Nonaka and Takeuchi, 1995; Leonard-Barton, 1995). “It is also seen as fundamental to organizational competence, which Sanchez et al. (1996) define as an ability to sustain the coordinated deployment of assets and capabilities in a way that promises to help a firm achieve its goals” (Egbu, 2000, p. 83). “Knowledge is one of the most important intangible assets possessed by human beings” (Kumaraswamy et al, 2011, p. 309), an infinite resource (Dodgson, 1993) and the key differentiating resource among firms (Tiwana et al., 2001). Knowledge is mainly used in strategic sense to sustain competitive advantage and organizational survival and is therefore an important streaming among both managerial practice and academics (Aizpurúa et al., 2011; Tallman et.al, 2011; Zack, 1999). Several definitions for knowledge has been described in the literature, which explains why it is so hard to manage knowledge. This difficulty lies in “knowledge as being human based, dynamic, and involves many organizational and cultural issues” (Chen and Huan, 2012, p. 389).
In this paper I will use Davenport and Prusak’s (1998) definition of knowledge who see it as; “a fluid-mix of framed experience, values, contextual information and expert insights that provide a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of the knower. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms”. This definition shows that knowledge originates in the mind of the
individual but is transferable, which means that knowledge dissemination plays an important role. Knowledge can be evaluated and incorporated, this involves a thinking process where new knowledge could be created by the individual. This affirms the focus of the research questions on knowledge dissemination and knowledge creation process at the individual level. These processes will be discussed respectively in subparagraphs 2.3.3 and 2.3.4. .
Second Generation Knowledge Management (SGKM) is a view that focuses on the ‘demand-side’ of KM and suggest accelerating the creation of new knowledge is more valuable than just codifying and sharing existing knowledge (McElroy, 2000). Nonaka and Takeuchi (1995) stress the development of ideal conditions that enables knowledge creation. This same focus on ‘enabling’ and ‘acceleration’ is being applied in the field of innovation, as Peschl and Fundneider (2012, p. 42) argue that ‘enabling innovations’ must be the core of the innovation process as opposed to ‘managing innovations’. Solely practicing KM, by helping fields or techniques is not sufficient, organizations have to see KM as; “the set of processes that seeks to change the organization’s present pattern of knowledge processing to enhance both it and its outcomes” (Firestone and McElroy, 2005, p. 191).
Sub-conclusion 2.3.2.1.
The Second Generation Knowledge Management (SGKM) definition clearly describes Knowledge Management (KM) activities should focus on continuous improvement of the KM process and knowledge itself, which is essential for Learning Organizations (LO). Improving the pattern of knowledge processing by enabling individuals in proactively sharing knowledge means organizations should support and motivate a sharing attitude. Second Generation Knowledge Management (SGKM) therefore should be the standard for practicing Knowledge Management. Following the SGKM philosophy enables individuals to disseminate knowledge more effectively which increases the creation of new ideas and knowledge for new innovations.
Relation between KM and INNOVATION
In the literature KM is inseparably intertwined with innovation and NPD initiatives (Tang and Murphy, 2012; Peschl and Fundneider, 2012; Peters et al., 2011; Bradfield, 2007; Scarborough, 2003).
Innovation seems to be a vital condition for organizations to give them a sustainable competitive advantage in a time that globalization is indisputable and therefore essential for them to pursue continuous innovations by growing and mature their innovation capability (Esterhuizen et al., 2011, p. 362; Popadiuk and Choo, 2006). Increasing an organizations innovation capability requires continuous improvement of the knowledge creation process and concerns enabling organizational means for generating innovative outputs (Esterhuizen et al., 2011; Essmann, 2000).
Knowledge creation plays a central role in the innovation process, as innovation is considered to be dependent on knowledge creation (Popadiuk and Choo, 2006). Plessis (2007) describes innovation as: “the creation of new knowledge and ideas to facilitate new business outcomes” (cited by Vallejo-Alonso et al., 2010, p. 89), aimed at improving internal business processes and structures and to create market driven products and services. Innovation encompasses both radical and incremental innovation (Albury, 2005). Peters et al. (2011) view the innovation process as; “organizational actions where through learning and information acquisition, knowledge is created” (Chia and Holt, 2008; Jorna, 2006; McElroy, 2003; Nonaka and Takeuchi, 1995). “Firms accomplish innovation by embedding internal knowledge and external knowledge spillovers from other entities” (Tang and Murphy, 2012, p. 41) into new products, services and/ or processes that cover the needs of users (Tang and Murphy, 2012; Popadiuk and Choo, 2006; Afuah, 1998). The well-known NPD process by Cooper (2008) describes that the development of new innovative product starts with discovering opportunities and generating new ideas, it emphasizes that new
knowledge and new ideas are being commercialized as products or implemented as processes (Popadiuk and Choo, 2006).
Esterhuizen et al. (2011, p. 355) recognizes, based on the works of Davenport and Prusak (2000), the need for “knowledge initiatives to initiate new knowledge behaviors through technical and organizational infrastructure”, increasing an organizations’ innovation capability. They focus on both knowledge “process” (tacit knowledge) and knowledge “stock” (explicit knowledge), as they categorized it. Their framework aims to provide an ‘as is’ and ‘to be’ refer point for evaluating and benchmarking firms’ organizational conditions and business tools, increasing the performance areas for knowledge initiatives (Table 1), in order to go from sustaining innovation capability to the growth of innovation capability. Linking KM initiatives to innovation performance by measuring it creates more understanding and support, a culture where KM is adopted and being practiced by the entire organization that foster the growth of innovation capability.
Performance areas for knowledge initiatives (Esterhuizen et al., 2011)
Generating, capturing and reusing accessible knowledge. Capturing and sharing lessons learned from practice. Identifying sources and networks of expertise.
Structuring and mapping knowledge needed to enhance performance. Measuring and managing the economic value and/or impact of knowledge.
Accessing, synthesizing and sharing knowledge from external sources.
Embedding knowledge in processes, products and/or services. Facilitating knowledge growth through culture and incentives.
Table 1. Performance areas for knowledge initiatives (Esterhuizen et al., 2011)
To understand the relation between ‘knowledge creation’ and ‘innovation’, Popadiuk and Choo (2006) compared four major models of innovation (models: Abernathy and Clark, 1985; Henderson and Clark, 1990; Tushman et al., 1997; Chandy and Tellis, 1998). They came with a model that categorizes innovation in a knowledge creation perspective (Table 2; Popadiuk and Choo, 2006) and found that the use of tacit knowledge faster leads to radical innovation, while explicit knowledge leads to incremental innovations. Radical innovations are seen as more valuable as they are hard to develop and thus scarce. Achieving radical innovation gives organizations (temporarily) a big leap ahead of competitors, on the other hand it
has a large impact on organizational resources. Not surprisingly researchers have given much attention to the use of tacit knowledge as they see more competitive advantage can be gained if this is done in an efficient and effective manner. By understanding the difference between tacit and explicit knowledge, and their relation with the type of innovation, we will understand that both types of knowledge are indispensable for the innovation trajectory.
Sub-conclusion 2.3.2.2.
This part of literature illustrates that Knowledge Management has an impact on innovation. Research is still seeking a way to measure what impact certain Knowledge Management practices exactly have on innovation. This part of literature lets us understand that organizations can positively affect the innovation capabilities of the organization by increasing certain Knowledge Management activities (Esterhuizen et al., 2011). It supports this research in finding enablers for knowledge dissemination and knowledge creation.
Tacit knowledge and Explicit knowledge
Tacit and explicit knowledge (Nonaka and Takeuchi, 1995) are a much made distinction in Knowledge Management (KM). Sanchez (2004) describes (Table 3) the basic believes between the tacit and explicit KM approach. He opts for a hybrid design, synthesizing the right combination and balance of the knowledge approaches. “Much knowledge in the AEC industry is experience-based and tacit” (Woo et al., 2004), it is often hard to describe in a verbally and written form and therefore plays a crucial role in the AEC industry (Styhre, 2009). Opposed to explicit knowledge, tacit knowledge plays a greater role at the individual level as it is highly personal, context specific and thus hard to formalize and communicate, and hard to transfer (Tallman and Chacar, 2011; Senapathi, 2011; Endres et al., 2007; Sanchez, 2004; Woo et al., 2004). Tacit knowledge is best transferred and internalized by a receiver using face-to-face communication (Endres et al., 2007) and requires the transfer of people as ‘knowledge carriers’ across the organization (Sanchez, 2004), which is costly and time-consuming.
Basic beliefs in Tacit versus Explicit Knowledge Management Approaches
Tacit KM approach Explicit KM approach
Knowledge is personal in nature and very difficult to extract from people.
Knowledge must be transferred by moving people within or between organizations.
Learning must be encouraged by bringing the right people together under the right circumstances.
Knowledge can be articulated and codified to create explicit knowledge assets.
Knowledge can be disseminated (using information technologies) in the form of documents, drawings, best practices, etc.
Learning can be designed to remedy knowledge deficiencies through structured, managed, scientific processes.
Table 3. Basic beliefs in Tacit versus Explicit Knowledge Management Approaches (Sanchez, 2004)
The conversion of tacit knowledge into explicit knowledge has been adopted by many as the process of knowledge creation (Nonaka and Takeuchi, 1995; Nonaka, 1994). In view of promoting KM into practice (McElroy, 2000), by making KM better to understand, this paper adopts a more simplified and easy to use description of tacit and explicit knowledge by Woo’s (Woo et al., 2004, p. 203); “Tacit knowledge is knowledge
housed in the human brain, such as expertise, understanding, or professional insight formed as a result of experience. Explicit knowledge, on the other hand, refers to codified knowledge that is transmittable in formal, systematic language and is easily transferred by using Information Technology (IT)”. The distinction between tacit and explicit knowledge is seen as great value for both researchers and the practice (Nonaka and Krogh, 2009). It gives insight into; the value of knowledge, the process of capturing and making knowledge visible, knowledge as asset for competitive advantage; knowledge in relation to organization activities; measurement of knowledge management activities in relation to organizational performance; etc. Covering these topics give organizations continuous access to ‘human knowledge’ as the most powerful asset.
Where mainly tacit knowledge assets are translated into radical innovations and are highly valued innovations that increases the competitive advantage of an organization, does not mean incremental innovations are negligible. The evolution path of an innovation requisite a “hybrid design” of both tacit and explicit knowledge in the creation of new knowledge as opted by Sanchez (2004). Radical innovation precedes and evolves through incremental innovations. This can be explained by Figure 3, it shows the relation between knowledge and innovation using the Innovation S-curve, a model that describes how a product, service, technology or business progresses and evolves over time. The model shows a S-shaped curve with three major stages; introduction, growth and maturity (Abernathy and Utterback 1978; Utterback 1994), and is usually followed by a radical/ disruptive innovation in the form of a new S-curve. Incremental innovation is displayed on the curve and radical innovation by the discontinuity area. Linked to the framework of Popadiuk and Choo (2006) we can consider that the evolution of an innovation builds on existing and new knowledge and thus also on both tacit and explicit knowledge. From an organizations’ strategic perspective (under the condition that the organization does not abandon the development of the particular innovation) an organization should take into account both existing and new knowledge when planning KM initiatives, as obtaining new knowledge and the development of radical innovations can be resource-devouring. This limitation shows that a continuous urge for radical innovation is impossible to pursue and that the reuse of knowledge can reduce the use of organizational resources for new innovation initiatives, thus reducing innovation costs.
Nonaka and Krogh (2009, p. 638) notices that “tacit and explicit knowledge are not separate but ‘mutually complementary’ in that they dynamically interact with each other in creative activities by individuals and groups”. This interaction is best illustrated by the SECI model (subparagraph 2.3.3) which describes the process of knowledge creation by converting tacit and explicit knowledge. Nonaka and Krogh (2009) further see that “competitive advantage of firms rests on processes of coordinating and combining assets, shaped by the firms’ knowledge asset positions, as well as path dependencies in asset acquisition and development”. “The sustainable competitive advantage of business firms flows from the creation, ownership, protection, and use of difficult-to-imitate commercial and industrial knowledge assets” (Teece, 2000, p. 35). Tacit knowledge and the social process for the creation of new knowledge are the most interesting topics for organizations to do research in at the moment, as tacit knowledge houses in human brains which is often unique, complex and hard to manage. Nonetheless, focusing merely on tacit knowledge and radical innovations does not mean that this is the only way to achieve competitive advantage. Biemans (2010, college presentation) says innovation strategies have to have; “stimulating objectives, hurdles that are not set too high and a scope that is not too narrow.” He opts that organizations have to be realistic, and see that not all innovations have to be a blockbusters; be open to ideas from other functions than just innovation (minded) departments (or even from outside sources); finding the balance between expensive big bets with limited incremental ideas or product improvements/modifications.
Sub-conclusion 2.3.2.3.
Disseminating both tacit and explicit knowledge should initiate the process of knowledge conversion and thus the creation of knowledge for both radical and incremental innovations. Mastering the dissemination of tacit and explicit knowledge for the increase of new innovation initiatives means taking a leap ahead of competition. Pursuing radical innovation is a healthy ambition though incremental innovations should not be ignored. Chasing a certain Knowledge Management strategy, by focusing on tacit or explicit knowledge, is a decision that has to be made by taking into account all sorts of environmental factors, e.g. ,life cycle of a product , demand from market, economic climate, organizational structure, etc. This research will look at the sharing of both tacit and explicit knowledge, it both covers the creation of new innovation.
Knowledge at individual, group and organizational level
“Smart businesses are looking for ways to connect communities of employees, partners, customers and others to create a world of new innovators” (IBM, 1998, p. 3). IBM (1998) sees that collaboration is a way to tap into both internal and external organizational knowledge. IBM (1998) showed that a gap exists between managers saying ‘they find collaboration important for their innovation efforts’ (75%) and managers saying ‘they actually collaborate for innovation to a large extent’ (+50%). This gap highlights that there are still improvements to be made among managers in enabling collaborations to actively share and create new knowledge and increase innovation initiatives. Sanchez (2004) says: “managers often do not know what specific knowledge an individual in their organization possesses”. This does not only applies for managers but for the majority off the workers in an organization. He illustrates the importance of knowledge housed in individuals, by using a citation from the ‘80s of a Hewlett Packard manager; “If we only knew what we know, we could conquer the world” (Sanchez, 2004).
The focus of KM on the process of enabling the dissemination and creation of knowledge is viewed by many on three levels; organizational, group and individual level (Markus, 2001; McElroy, 2000; Tallman and Chacar, 2011 ). Schultze (2000) sees that in the KM literature “much attention is given to discovering an individual’s tacit knowledge and converting it into organizational knowledge that can be communicated and stored in organizational routines and databases”. Others also acknowledge the importance of the individual as knowledge creator (e.g.,Egbu, 2000; McElroy, 2000), “the context and control of knowledge
management is shifting from global and organizational levels to communities and ultimately to individuals” (Bedford, 2012). However you view it, knowledge is being acquired by the individual and subsequently transformed from individual to organizational level (Endres et al., 2007; Kogut and Zander, 1993; Polanyi, 1962). In this view I see individuals (both as source and recipient) (Markus, 2001) are central to KM who are in control of their knowledge dissemination and creation process, which will be discussed in the following subparagraph. Bedford (2012) calls for organizations to shift their focus towards Personal Knowledge Management (PKM), a streaming focusing on the knowledge processes of the individual.
Sub-conclusion 2.3.2.4.
Knowledge sharing takes place on various levels. Literature has showed the importance of KM at the individual level as the individual are at the basis of knowledge creation. This paper is interested in enabling individuals to disseminate or utilize knowledge, fostering the creation of new knowledge and innovations to gain advantage over competitors. Before finding the enablers for knowledge creation and knowledge dissemination we need to understand these two processes on individual level.
2.3.3
KNOWLEDGE CREATION“Organizational knowledge creation is the process of making available and amplifying knowledge created by individuals as well as crystallizing and connecting it to an organization’s knowledge system” (Nonaka and Krogh, 2009, p. 635). The SECI model (Figure 4; Nonaka and Tackeuchi, 1995) and its four modes of knowledge conversion – socialization, externalization, combination and internalization – describes this knowledge creation process. It sees knowledge creation as; “a transformation of an individual’s tacit knowledge into explicit knowledge at the group and organizational levels and internalized by each member of these groups, who convert it into new tacit knowledge” (Ramirez, et al., 2012, p. 167).
Figure 4. SECI model - Four alternatives for creation of knowledge (Ramirez, et al., 2012)
“The conversion of tacit and explicit knowledge is seen as a continuum social process between individuals, but is not limited to a single person“ (Popadiuk and Choo, 2006, p. 307; Nonaka and Krogh, 2009). However, this knowledge creation process itself is being influenced by decision making process, described by the Decision Execution Cycle (DEC, Figure 5) (Firestone and McElroy, 2005). This cycle shows that the individual is being influenced by the social process in their decision making. Firestone and McElroy (2005) see the decision making process of the individual as a cognitive process that is influenced by social, geo-physical, economic, and cultural conditions, and also social network effects that are presented to other individuals.
Individuals go through the DEC when they make a decision, following a sequence of cognitive operations that includes; planning, acting, monitoring, and evaluating behaviors (Firestone and McElroy, 2005; Firestone, 2000). The DEC complements the SECI by putting the decision making process of the individual at the core of knowledge creation process. Knowledge creation is based on recognizing epistemic gaps or ‘problems’
due to different beliefs and belief predispositions an individual has towards knowledge claims (Peters et al., 2011, Firestone and McElroy, 2005). If mismatches between a knowledge claim and the knowledge of a knowledge user occurs, ‘double-loop learning’ (DLL) is the foundation for the creation of new knowledge (Figure 1 and Figure 5; Firestone and McElroy, 2005; Argyris, 1974).
Figure 5. The decision execution cycle (DEC) and problem recognition (Firestone and McElroy, 2005)
The moment an epistemic gap/ problem is recognized, an individual chooses to leave the problem, by abandoning it, or motivated by a learning incentive and engaging DLL, a process that comprises problem formulation, developing alternative solutions, and selecting alternatives through error elimination.
Sub-conclusion 2.3.3.1.
The DEC theory sees bringing (new) knowledge among knowledge users can be achieved by firstly disseminating it to the appropriate knowledge user, “integrating new produced knowledge into the DEC and business process environment that originated it, and putting it into organizational memory making it available for reuse” (Firestone and McElroy, 2005 [p.194]). The knowledge creation process also shows a cognitive process at the individual level, which must be taken into account in the choice of data collection.
2.3.4
KNOWLEDGE DISSEMINATIONKnowledge dissemination can be interpreted as sharing and utilizing knowledge (Senapathi, 2011; NCDDR, 1996). In previous subparagraph the individual was depicted as the core of KM and therefore increasing attention is given to this individual level by researchers. Lin (2007) conducted a research (Figure 6) on individual level to the relationship between; a)knowledge sharing enablers, b)knowledge sharing process and c)innovation performance. Whereas for the enabler dimension, both individual as organizational factors were included in her research. She recognizes positive relationship between certain variables of the dimensions. The enablers; Enjoyment in helping others, knowledge self-efficacy and top management support have significance influence on the knowledge sharing process, while the employee willingness to donate and collect knowledge improves a firms innovation capability.
Figure 6. General framework for knowledge sharing (Lin, 2007)
Abdullah et al. (2009) recognizes the importance of enabling people in the organization to share their knowledge through active learning and use that learning to generate new knowledge. In their research they identified five enablers for knowledge sharing in a knowledge intensive organization that needs support from the (top) management. ‘Access to learning resources’ and ‘feedback on learning’ are the enablers that correlate the most with enabling knowledge sharing (Abdullah et al., 2009, p. 116);
Commitment to training and education by organization; “transfers explicit and tacit competencies to the employees for talent regeneration , provides formal and organized occasion for people to learn from each other, and investment in employees engenders stronger commitment to the organization’s value and to stay on.”
Access to learning resources; “to motivate employees in continuously self-learning, using; e.g., professional memberships, subscription to professional journals, attendance at forums, conference and exhibitions, sabbaticals, etc.”
Retention of knowledge; ”enhances the learning capacity of individuals by making knowledge explicit in practices like reporting, reflections, review and insight papers and regular open sharing with associates.”
Incentive for learning; “knowledge sharing is time consuming and dilutes power, in fact, people rather hoard knowledge as the nature of many workplaces are: individualistic, political and
competitive. Reward systems have to be dependent on the KM strategies pursued i.e. codification or personalization, rely mostly on intrinsic rewards and be used calibrated and judicious.”
Feedback on learning; “is regularly evaluate and give feedback, to employees, on the state of knowledge sharing within the organization and between groups.”
While knowledge sharing has a positive effect on an organizations innovation capability, people on the other hand can process only a certain amount of information. ‘Information overload’ (Senapathi, 2011) makes it hard to find the right information at the right moment to successfully create and bring new ideas and products to the market, profiting from ‘first mover advantages’. “Researchers (e.g. Doz et al., 2001; Ghoshal and Bartlett, 1990; Gupta and Govindarajan, 2000; Nonaka and Takeuchi, 1995) have even proposed that effective and efficient transfer and exploitation of knowledge is the primary reason for the existence of firms in general and in particular of ‘network firms’ – firms such as MNEs with highly autonomous units in different geographic locations” (Tallman et al., 2011, p. 278).
E
N
A
B
LE
R
D
IM
E
N
S
IO
N
Individual factors
•Enjoyment in helping others •Knowledge self-efficacyOrganizational
factors
•Top management support •Organizational rewardsTechnology factors
•ICT useP
R
O
C
E
S
S
D
IM
E
N
S
IO
N
Knowledge
sharing processes
•Knowledge donating •Knowledge collectingO
U
T
C
O
M
E
S
D
IM
E
N
S
IO
N
Firm innovation
capability
Effective knowledge transferring means, besides fast, cheap and accurate transmission of knowledge, a receiver can interpret and use the obtained information (Majumder et. al., 1994; cited by NCDDR, 1996). Foss and Pedersen (2004, p. 343) see that “there is little disciplined attention to individual behavior in recent work on knowledge transfer in Multinational Corporations (MNCs).” Research conducted by Tallman and Chacar (2011) focuses on the process dimension of knowledge sharing networks in MNEs, using the relations between Communities of Practices (CoPs), Network of Practices (NoPs) and Internal Network of Practices (INoPs). Their model (Tallman and Chacar, 2011) describe the accumulation and dissemination of explicit and tacit knowledge, starting at micro-level, turning location-specific knowledge into firm-specific knowledge through local embeddedness, and turning location-bound knowledge into non-location bound knowledge through organizational embeddedness. An important part in their research is that explicit and tacit knowledge should be disseminated using the associated channels of an organizations network to transfer and develop knowledge which can lead to radical or incremental innovations.
NCDDR (National Center of Dissemination of Disability Research, 1996, p. 28; cited by Senapathi, 2011) looked at factors that influenced the disseminating process and utilization of research outcomes. In their research the NCDDR calls for a focus on knowledge dissemination which they see as “a process requiring a careful match among (a) the creation of products or knowledge, and the context of that creation, (b) the needs, contexts, prior experiences, values, and beliefs of target audiences, and (c) the content, media, formats, and language used in getting the outcomes into the hands, minds, and activities of those target audiences.” They look further than organizing the movement of knowledge through a network to enable knowledge workers in sharing knowledge, as described by Tallman and Chacar (2011). NCDDR (1996) says that utilization of knowledge is the goal of knowledge dissemination and therefore uses both words interchangeable. “Utilization may mean different things to different members of a target audience. The critical element of utilization is that the outcome must be critically and thoroughly digested, and the individual (or organization) must fit the new information with her or his prior understandings and experience” (NCDDR, 1996, p. 28). This means that an organization member who digested the knowledge sees opportunities or ‘gaps’ in knowledge claims by applying the knowledge in his or her domain or discipline (Driver, 1995; Huberman, 1990) through the process of socialization and/ or combination (Popadiuk and Choo, 2006), a process that fosters the creation of new knowledge. NCDDR (1996, p. 8) sees the utilization of knowledge as an ‘active learning process’ where knowledge is “a fluid set of understandings shaped both by those who originate it and by those who use it”. NCDDR’s definition and interchangeable use of the terms dissemination and utilization corresponds with the Knowledge Processing Environment and Business Processing Environment described in the KLC by Firestone and McElroy (2005).
The NCDDR (1996, p. 12) mentions ‘Four Dimensions of Knowledge’ that play a role in dissemination efforts of disseminating research knowledge:
“Dissemination as a ‘source’, that is, the agency, organization, or individual responsible for creating the new knowledge or product , and/or for conducting dissemination activities,
the ‘content’ or message that is disseminated, that is, the new knowledge or product itself, as well as any supporting information or materials,
the dissemination ‘medium’, that is, the ways in which the knowledge or product is described, “packaged”, and transmitted, and
the ‘user’, or intended user, of the information or product to be disseminated.”
The NCDDR (1996) composed a list with issues related to the dissemination process for each of the knowledge dimension (Table 4).
