1. Accelerating Adaptive Processes: Product Innovation in the Global Computer Industry 2011. 11. 30 박사과정 4 학기 송경희 박사과정 1 학기 한상연 Kathleen M. Eisenhardt and Behnam N. Tabrizi Administrative Science Quarterly, 40 (1995): 84-110 2011 Fall Seminar on Technological Innovation

2. 2 Ⅰ. Introduction “2011 년 내년 경제 최대 걸림돌은 대외 불확실성 ” ( 조선일보, ‘11. 1.15) 윤증현 장관 “ 세계경제 불확실성 더욱 증가 ” ( 연합뉴스, ‘11. 3.29) “ 우리경제의 시급한 과제는 불확실성의 제거 ” ( 동아일보, ’01.2.1) Uncertainty

3. 3 Compression ModelExpriential Model Key Assumption CertaintyUncertainty Image of product innovation Predictable series of well-defined steps Uncertain path through foggy & shifting markets & technologies Strategy for speed Rationalize & then squeeze the process Quickly build understanding & options while maintaining focus & motivation Organization features BereaucraticFlexible Routine Improvisational Experimental Hypothesis (Independent Variables) (H1) Planning (H2) Supplier Involvement (H3) Using the CAD (H4) Overlap (H5) Multifunctional team (H6) Greater Award (H7) Multiple Iteration (H8) Extensive Testing (H9) Frequent Milstones (H10) Power Leader Dependent Variables Development Time Data and Method Survey and deep interview results from 72 projects(36 Computer Companies) Summary(1) Ⅱ. Summary(1) Compression Model Vs. Experintial Model

4. 4 Summary(2) Ⅱ. Summary(2) Empirical Results(1) Confirm Compressing Model Experiential Model Opposite N.S

5. 5 Summary(2) Ⅱ. Summary(2) Empirical Results(2) - Split Sample analysis Compressing ModelExperiential Model Confirm Opposite N.S Confirm N.S Confirm

6. 6 Ⅲ. Discussion(1) The authors suggested computer industries as an example of fast moving industry while mentioning automobiles and heavy industrial equipments as examples of predictable and mature product development. But in fact, many industries are in the fast moving and competitive environment. What industry or products can we think of more as an example we can apply experimental model for faster product development? This paper provides firms with strategies for faster product development. The results implicate that fast product development is more likely to emerge as uncertain than predictable, more experimental than planned, and more iterative than linear. In applying these results to the real industrial world, what are difficult things?

7. 7 Ⅲ. Discussion(2) In this paper, “Adaptation” might mean that firms adapt to environmental change somewhat passively. Can we make consideration the firms that penetrate to market and take innovation new to firms or market or world? It may be able to related to variables which used in empirical study. Dependent Variables : NPD can subdivide to new to firm/industry/world In split sample analysis, was the division of certain and uncertain based on insufficient evidence(Business Week)? Information Myopia/ Degree of Uncertainty Independent Variables : degree of skill, communication within organization e.g. ) Relative comparison of each groups’ NPD Cycle

8. Thank You!