5 Strategy
Scenario 1. If an organization so far has applied an exclusive market-oriented strategy, then external determinants such as customers’ demands, the organiza-
5.3 Success factors, barriers and risks
5.3.5 Empirical study: KnowRisk
Table B-7 summarizes these influences. The symbol (+) means that the factor is positively correlated with probability of successful re-contextualization, frequency and mutuality of intended knowledge transfer or probability and frequency of unin- tended knowledge transfer respectively. The symbol (-) represents the opposite.
The symbol (+/-) means that it is undetermined how the factors affect knowledge transfer. Each factor is assigned to one of four categories according to the direc- tions of the influences. The last column shows implications for setting up gover- nance rules for managing knowledge risks. The symbol (>) suggests to strengthen the corresponding factor whereas the symbol (<) suggests the opposite. In the case of the symbol (!) the factors require weighing and corrective measures must be taken because it is undetermined what consequences increasing or decreasing the factors would have.
The expected influences of the factors suggest varying strategies for setting gov- ernance rules for knowledge risks. However, rules that reduce risks of unintended knowledge transfer rarely simultaneously enhance intended knowledge transfer.
Thus, organizations have to weigh potential gains of external knowledge transfer with potential losses and select their measures accordingly. Generally, organiza- tions supposedly either risk low intended and unintended knowledge transfer by limiting transfer too much or risk depreciating knowledge assets by transferring too generously. In order to avoid erosion of the market position, knowledge assets have to be restricted in a balanced way.
Heuristics are needed concerning rules governing knowledge risks. While com- piling this book, the author leads an empirical study described in the following sec- tion 5.3.5 on the basis of which an instrument can be developed that helps organi- zations to assess, weigh and prioritize factors influencing knowledge risks and select appropriate measures of governance.
ing. Next to the use of intellectual property rights, legal measures comprise e.g., the use of non-disclosure or non-compete agreements in work contracts or the use of alliance agreements in inter-organizational arrangements.
Consequently, an explorative research design is used to analyze the relation- ships between governance of knowledge risks on the one hand and the concepts knowledge quality, knowledge transfer, knowledge diffusion and knowledge loss on the other hand. Based on the literature, the following hypotheses are investi- gated in the empirical study261 (see Figure B-21).
FIGURE B-21. Hypotheses for management of knowledge risks
Hypothesis H1. Governance of knowledge risks positively affects knowledge quality.
Knowledge quality is a broad concept that comprises (1) content, i.e. e.g., cor- rectness or timeliness of knowledge, (2) community in which knowledge is created and used, (3) processes that provide knowledge as well as (4) IT infrastructures used to support access to documented knowledge or meta-knowledge about the knowledge sources262. In order to measure knowledge quality, exemplary variables
261. The empirical study extends beyond publication of this book and will be written up in a separate article. Interested readers should refer to http://iwi.uibk.ac.at/maier/kms/ about details on the publication. These hypotheses thus are not part of the original empirical study on KMS in the TOP 500 companies and TOP 50 banks and insurance companies in Germany that is reported in PART C - “State of Practice” on page 437.
262. See section 7.2.5 - “Quality of contents” on page 299, also Eppler 2003, 68.
H3 governance H2
of knowledge risks
knowledge quality
knowledge transfer
knowledge loss +
H1 +
-
knowledge diffusion H4 -
such as accessibility of IT infrastructures, applicability or correctness of docu- mented knowledge are included263. It is assumed that governance of knowledge risks positively affects knowledge quality, since companies are sensitized for the importance of knowledge assets and aim at reducing shortcomings concerning the various dimensions of knowledge quality by deploying appropriate measures.
Hypothesis H2. Governance of knowledge risks positively affects knowledge transfer.
In addition to motives such as economies of scale or access to markets, inter- organizational cooperations, particularly knowledge cooperations264, are means to get access to external knowledge that organizations can not create internally for reasons of time or cost265. Success of knowledge transfer can be determined e.g., by the extent to which the source’s knowledge is recreated at the recipient’s end (Cummings/Teng 2003, 41). Consequently, the concept of knowledge transfer is measured by variables such as contribution of transferred knowledge to other projects, tasks or processes, extension of the knowledge base or reduction of the dependency or reliance on partner knowledge266. It is assumed that companies without clear governance rules are rather restrictive concerning knowledge trans- fer. Employees might hold back knowledge, if they are in doubt whether it may, should, must or must not be transferred. Clear rules which are part of governance measures would increase certainty about which knowledge can be transferred and thus boost intended knowledge transfer while inhibiting knowledge diffusion267. Hypothesis H3. Governance of knowledge risks negatively affects knowledge loss.
Knowledge loss is non-recoverable and concerns knowledge assets that are bound to people or are incorporated in objects. Also, a lack of documenting knowl- edge may result in knowledge loss. The concept of knowledge loss can be mea- sured by variables such as non-documentation of knowledge in day-to-day busi- ness or in projects as well as the degree of losses caused by job succession or sub- stitution268. It is expected that governance measures negatively affect probability and exposure of knowledge losses by rules concerning e.g., email and document retention planning, documentation and reduction of dependencies.
Hypothesis H4. Governance of knowledge risks negatively affects knowledge dif- fusion.
263. Kahn et al. 2002, 187, Eppler 2003, 74.
264. Also Badaracco 1991, Doz/Hamel 1998, Aulinger 1999, Moser 2002, Maier/Trögl 2005.
265. Baughn et al. 1997, 103, Teece 2000, 138.
266. Wathne et al. 1996, 75, Simonin 1999, 621.
267. See also section 5.3.4 - “Management of knowledge risks” on page 140, see “Hypothe- sis H4” on page 148.
268. van den Brink 2001, 66, Schindler/Eppler 2003, 221ff, Desouza/Vanapalli 2005, 84.
Knowledge diffusion means unintended access to sensitive knowledge by unau- thorized persons. Unlike knowledge loss, diffused knowledge is still present, but not exclusively at the original organization. Knowledge diffusion reduces the value of the knowledge due to loosing its exclusivity. The concept of knowledge diffu- sion can be measured by variables such as access by unauthorized persons, unfa- vorable employee fluctuation or reverse engineering activities by competitors269. It is assumed that probability and exposure of knowledge diffusion is reduced by the deployment of governance measures such as access control, non-disclosure agree- ments or alliance agreements.
These hypotheses are subject to a broad explorative empirical study. Based on a population of 3.2 million German enterprises270, the study targets about 130 Ger- man organizations that were selected on the basis of a stratified random sample.
The stratification of the sample is based on the two criteria industry and number of employees. The study covered all industries because there has been no evidence of differences between industries in terms of management of knowledge risks prior to this empirical study271. The study targets organizations with more than 50 employ- ees since relevance of knowledge risks assumedly increases with the number of employees. However, also some companies with fewer than 50 employees are included in this study in order to check this assumption.
Structured questionnaires were sent out to contact persons of the target group that were identified by telephone. The questionnaire should be filled out by chief executive officer, chief security officer, chief knowledge officer or the head of public relations. Based on the results of the broad study, ten companies will be con- tacted a second time for an in-depth study with personal face-to-face interviews and multiple feedback rounds. These attempt to identify which governance mea- sures are most appropriate to govern what types of knowledge risks.
269. Zander/Kogut 1995, 88f, Norman 2004, 612, Desouza/Vanapalli 2005, 81f.
270. According to the German Federal Bureau of Statistics (Statistisches Bundesamt), source: URL: http://www.destatis.de/.
271. Zack (2003) also backs this assumption of no influence between industry sector and importance of knowledge which is plausible due to the observation that knowledge assets are of increasing importance to all industries. However, one could also assume that high-tech industries are more aware of the competitive value of knowledge assets and thus are at the forefront of applying corresponding measures to manage knowledge risks. If this is the case, one should find correlations between the ordinal value of an industry along a scale from low tech to high tech on the one hand and the extent to which corresponding organizations employ measures to govern knowledge risks on the other hand. Concerning technology intensity, an index was developed by OECD. The index is based on R&D intensity measured by R&D expenditure in relation to output and indirect R&D expenditure that is caused by transfer of technology or R&D-inten- sive goods between industries. This conceptualization of R&D intensity is the basis for a classification of industries in high-tech, medium-high tech, medium-low tech and low-tech industries (Hatzichronoglou 1997).