Decision Sciences Journal
Volume 30, Number 4
Fall 1999
Information-Processing Alternatives for Coping with Manufacturing
Environment Complexity
Barbara B. Flynn and E. James Flynn
Wake Forest University, Babcock Graduate School of Management,
P.O. Box 7659, Reynolda Station, Winston-Salem, NC 27109-7659,
email: barb.flynn@mba.wfu.edu,
jim.flynn@mba.wfu.edu
ABSTRACT. Investment in information systems and technology
is often justified as a necessary strategy for coping with the
increased complexity and information needs of today’s manufacturing
environments. However, the world class manufacturing paradigm
suggests that increased complexity is not always necessary to
meet the needs of markets and customers. Galbraith’s (1973,
1977) seminal information-processing model is applied to a manufacturing
environment, supported by the world class manufacturing paradigm,
to test the role of various information-processing alternatives
for coping with increased environmental complexity. Moderated
regression and multiple discriminant analysis are used to test
hypotheses in a sample of 164 manufacturing plants. Environmental
complexity was found to be related to manufacturing performance
for each of the five dependent variables. This relationship was
moderated by at least one information-processing alternative
for each dependent variable, including self-contained tasks,
lateral relations, and environmental management strategies for
reducing manufacturing, supplier, and goal diversity. Investments
in information systems and reduction of labor and customer diversity
did not moderate this relationship. Practices that were found
to be particularly effective in moderating this relationship
included the use of multifunctional employees, communication
of manufacturing strategy, coordination of decision making, product
design simplicity, reduction of parts counts, supervisory interaction
facilitation, recruiting and selection for flexible employees,
JIT practices, blanket purchase orders, and strong customer relationships.
Subject Areas: Manufacturing Information Systems, Production
and Inventory Control Systems, and Survey Research/Design. |