1. The Influence of Network Form on Inter- organizational Knowledge Transfer Difficulty: Does Form Matter? DSI Conference Jennifer Lewis Priestley Subhashish Samaddar November 23, 2003

2. Presentation Outline 1.Why study knowledge transfer? 2.Network forms 3.Factors influencing knowledge transfer 4.Proposed model 5.Research Limitations and Implications

3. Why is knowledge important? Knowledge is a source of competitive advantage “…the essence of economic growth…” – Teece (1998) “…the underpinning of competencies…” (KBV) – Grant (1996) “…quickly displacing capital and labor as a firm’s basic economic resource…” – Drucker (1995)

4. Why is knowledge transfer important? Organizations cannot know all that is knowable (TCE) - Williamson (1973, 1975); “Second-hand” knowledge is often cheaper and faster to obtain than “first-hand” knowledge; “…Factors of production cannot become mobile unless they are known…” - Lippman and Rumelt (1982) Alliances/partnerships and networks provide a channel to access incremental knowledge in an effort to manage environmental uncertainty. – Madhavan (1998)

5. Specific examples of knowledge transfer studies within networks: Powell et al., 1996 – study of biotech firms Powell et al., 1996 – study of biotech firms Darr et al., 1995 – study of pizza franchises Darr et al., 1995 – study of pizza franchises Ingram and Simons, 2002 – study of kibbutzim Ingram and Simons, 2002 – study of kibbutzim Postrel, 2002 – recounting of the 1999 Mars Climate Orbiter Postrel, 2002 – recounting of the 1999 Mars Climate Orbiter Inter-organizational Network Forms NetworkTypeKnowledgeTransferDifficulty Factors of KnowledgeTransfer

6. ScopeLow High Centrality of Authority HighF C Competition High V I Inter-organizational Network Forms

7. How do each of these specific network types influence knowledge transfer difficulty? Factors of KnowledgeTransferNetworkTypeKnowledgeTransferDifficulty Franchise Value Chain Innovative Co-opetive

8. Factors of Knowledge Transfer Factors of Knowledge Transfer Several factors have been shown in the KM literature to influence knowledge transfer: Absorptive Capacity Absorptive Capacity “…the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities. We label this capability as a firm’s absorptive capacity.” (Cohen and Levinthal, 1990) Causal Ambiguity Causal Ambiguity “…ambiguity is an intermediate state between ignorance and risk…the level of causal ambiguity refers to the number of distributions that are not ruled out by one’s knowledge of the situation.” (Mosakowski, 1997) Outcome Ambiguity Outcome Ambiguity

9. Factors of Knowledge Transfer Factors of Knowledge Transfer Outcome Ambiguity “The inability of the knowledge source to identify the possible outcome associated with knowledge transfer.” (Samaddar and Priestley, 2003)  “The inability of the knowledge source to identify the possible outcome associated with knowledge transfer.” (Samaddar and Priestley, 2003)  Szulanski (1996) identifies “unprovenness” of knowledge as a factor of knowledge transfer difficulty. Simonin (1999), Szulanski (1996) and Hamel (1991) all identified different aspects of the relationship between the source and the recipient as a factor of knowledge transfer difficulty.  Simonin (1999), Szulanski (1996) and Hamel (1991) all identified different aspects of the relationship between the source and the recipient as a factor of knowledge transfer difficulty.

10. Type 1 (Low Outcome Ambiguity) Outcome Set: [O 1, O 2, O 3 ] Type 3 (Med Outcome Ambiguity) Outcome Set: [O 1, O 2, O 3 …O ∞ ] Type 2 (Med Outcome Ambiguity) Outcome Set: [O 1, O 2, O 3 …O ∞ ] Type 4 (High Outcome Ambiguity) Outcome Set: [O 1, O 2, O 3 …O ∞ ] Known Recipient Actions Bounded Recipient Action Set: [RA 1, RA 2, RA 3 ] [RA 1, RA 2, RA 3 ] Unknown Recipient Actions Unbounded Recipient Action Set: [RA 1, RA 2, RA 3 …RA ∞ ] Proven Knowledge Bounded Knowledge Usage Set: [KU 1, KU 2, KU 3 ] Unproven Knowledge Unbounded Knowledge Usage Set: [KU 1, KU 2, KU 3 …KU ∞ ] [KU 1, KU 2, KU 3 …KU ∞ ] Outcome Ambiguity Framework: Factors of Knowledge Transfer Factors of Knowledge Transfer

11. How are each of these factors of knowledge transfer difficulty influenced by network type? Factors of KnowledgeTransferNetworkTypeKnowledgeTransferDifficulty Franchise Value Chain Innovative Co-opetive Absorptive Capacity Causal Ambiguity Outcome Ambiguity Factors of Knowledge Transfer Factors of Knowledge Transfer

12. RQ1: What factors influence inter-organizational knowledge transfer difficulty? Proposed Model OutcomeAmbiguityOutcomeAmbiguity + AbsorptiveCapacityAbsorptiveCapacity - CausalAmbiguityCausalAmbiguity + KnowledgeTransferDifficulty

13. OutcomeAmbiguityOutcomeAmbiguity AbsorptiveCapacityAbsorptiveCapacity CausalAmbiguityCausalAmbiguity ValueChain Innovative Franchise Co-opetive RQ2: How does network type affect the factors of inter- organizational knowledge transfer difficulty?

14. OutcomeAmbiguityOutcomeAmbiguity + AbsorptiveCapacityAbsorptiveCapacity - CausalAmbiguityCausalAmbiguity + KnowledgeTransferDifficulty ValueChain Innovative Franchise Co-opetive Proposed Model Comprehensive Research Model:

15. FranchiseInnovative Value Chain Co-opetive Absorptive Capacity H1a – High H2a – Low H3a – Low H4a – High Causal Ambiguity H1b – Low H2b – High H3b – Low H4b – High Outcome Ambiguity H1c – Low H2c – High H3c – Low H4c – High Knowledge Transfer Difficulty H1d – Low H2d– Mixed H3d – Low H4d – High Proposed Model - Hypotheses

16. Proposed Model – Hypotheses Franchise Absorptive Capacity H1a – High Causal Ambiguity H1b – Low Outcome Ambiguity H1c – Low Knowledge Transfer Difficulty H1d – Low The Franchise Network will be associated with a high state of absorptive capacity. The Franchise Network will be associated with a low state of causal ambiguity. The Franchise Network will be associated with a low state of outcome ambiguity. The Franchise Network will be associated with low knowledge transfer difficulty. Detailed hypothesis -

17. Proposed Model – Hypotheses Innovative Absorptive Capacity H2a – Low Causal Ambiguity H2b – High Outcome Ambiguity H2c – High Knowledge Transfer Difficulty H2d – Mixed The Innovative Network will be associated with a low state of absorptive capacity. The Innovative Network will be associated with a high state of causal ambiguity. The Innovative Network will be associated with a high state of outcome ambiguity. The Innovative Network will be associated with mixed knowledge transfer difficulty. Detailed hypothesis -

18. Proposed Model – Hypotheses Value Chain Absorptive Capacity H3a – Low Causal Ambiguity H3b – Low Outcome Ambiguity H3c – Low Knowledge Transfer Difficulty H3d – Low The Value Chain Network will be associated with a low state of absorptive capacity. The Value Chain Network will be associated with a low state of causal ambiguity. The Value Chain Network will be associated with a low state of outcome ambiguity. The Value Chain Network will be associated with low knowledge transfer difficulty. Detailed hypothesis -

19. Proposed Model – Hypotheses Co-opetive Absorptive Capacity H4a – High Causal Ambiguity H4b – High Outcome Ambiguity H4c – High Knowledge Transfer Difficulty H4d – High The Co-opetive Network will be associated with a high state of absorptive capacity. The Co-opetive Network will be associated with a high state of causal ambiguity. The Co-opetive Network will be associated with a high state of outcome ambiguity. The Co-opetive Network will be associated with high knowledge transfer difficulty. Detailed hypothesis -

20. “…there is a growing realization that the variables which are most theoretically Interesting are those which are least identifiable and measurable.” Spender and Grant (1996)

21. Limitations Data Collection Data Collection Unit of Analysis Unit of Analysis Sample Size Sample Size

22. Implications For practice – Enable management of organizations currently outside of a network (or considering the formation of a network) to determine which form will most effectively support its knowledge-based objectives. Enable management of organizations currently operating within a network to determine how they can manage their relationships within the network to minimize knowledge transfer difficulty.

23. Implications For Research – Introduces a new factor of inter-organizational knowledge transfer difficulty for further research and refinement (outcome ambiguity). Introduces a unique framework through which to address the issues associated with inter-organizational knowledge transfer difficulty. Further research could pursue a network-oriented focus or a factor-oriented focus.

24. Questions? Comments? Discussion?