The following CWTS working paper is available upon request:
An International Investigation of Problem-Solving Performance
in the Semiconductor Industry
by Melissa M. Appleyard, Clair Brown, and Linda Sattler
Abstract Using a unique survey of engineers
in major semiconductor companies located in Japan, South Korea,
and the United States, this article analyzes how a firm's knowledge
system (i.e., information access, sharing and control) and Human
Resource (HR) system (i.e., practices that structure work, develop
skills, and reward performance) are related to the problem-solving
performance of engineers. Because of the short product market lifecycles
in the semiconductor industry, expeditious problem solving is an
important performance goal. Therefore, we examine the performance
of engineers in terms of the time it takes them to solve problems
in the context of their firms' knowledge and HR systems. We anticipated
that externally-focused organizational systems would lead to superior
performance. Our findings support the hypothesis that engineers
who use external private networks (both personal and those supported
by the firm) and who work in externally-oriented HR systems (which
support individual career performance and mobility) solve problems
more quickly than engineers who rely on internal networks and publicly-available
information and who work in internally-oriented HR systems (which
focus on internal rules and training). These findings are applicable
to engineers in our sample from the United States, while the findings
for the Korean and Japanese engineers are inconclusive. We find
international variation where the U.S. engineers work under the
most externally-oriented and the Japanese engineers under the least
externally-oriented systems, and the Korean engineers fall in between.
The findings of this article suggest that when constructing a work
environment for new product development, managers need to take into
account a broad spectrum of employment policies that go beyond traditional
HR practices and include specific policies that influence knowledge
flows.
Online Data Appendix:
Description of Variables
Cross-country Analysis of Variance
Verification of Variable Classification
across the Indices
Summary Statistics and Correlations
across Key Variables
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