Knowledge-sharing behavior seems to be important
for team functioning and performance. A theoretical
model explaining antecedents that impact knowledge-
sharing behavior and its interplay with shared knowl-
edge within teams was investigated. In the present study,
we examined the effect of the individual’s intention and
five organizational antecedents (team communication,
perceived appraisal, organizational communication,
organizational support, and social ties) on knowledge-
sharing behavior. Five production and five maintenance
teams (123 participants altogether) working in a steel
mill took part in the study to investigate the assumed
relationships. The results indicate that knowledge-
sharing behavior is positively affected by intention,
organizational communication, and social ties. in turn,
knowledge-sharing behavior had a significant impact on
the shared knowledge corresponding to the four types
of shared mental models (task, equipment, interaction,
team), and as a trend, teams with a higher knowledge-
sharing behavior seem to have greater shared mental
model similarity. The implications of the findings are
discussed in terms of further research in production
settings and with regard to developing a knowledge-
sharing intervention.
Keywords: knowledge-sharing behavior, shared mental
models, shared knowledge, similarity, production and
maintenance teams, steel industry
INTRODUCTION
Production teams nowadays form the back-
bone of modern production systems in most of
the heavy industries, like mining, iron, and steel
production. Work teams play a critical role in
handling the challenges of their complex envi-
ronments, which might go beyond the capaci-
ties of individuals (Cooke, Gorman, Myers, &
Duran, 2013; Cooke, Salas, Cannon-Bowers,
& Stout, 2000). Production teams are respon-
sible for stable processing times, a continuous
plant performance, and high product quality
by steering plants with huge dimensions. They
monitor the production process by interpreting
the numerous interacting system states; they
react to changes in the raw material and to the
quality of the final material and have to develop
an awareness concerning potentially upcoming
malfunctions and disruptions of the plant units.
Complementary to the work of the production
teams, the maintenance teams have to provide a
high degree of plant availability while executing
regular maintenance procedures (e.g., leakage
tests of pipelines, measurement of fluxes, weld-
ing works) and need to provide rapid assistance
in cases of detected malfunctions.
The teams of heavy industries addressed in
the present study work within extreme environ-
ments. Manzey, Lorenz, and Poljakov (1998)
defined an extreme environment as “any envi-
ronment to which humans are not naturally
suited, and which demands complex processes
of physiological and psychological adaptation”
(p. 538). Teams in steel mills work on huge cast-
ing plants that produce several million tons per
year. The working material is liquid steel with a
temperature of about 1500°C. The workers are
directly involved in the production process, and
540656EDM XX X 10.1177/1555343414540656Journal of Cognitive Engineering and Decision Making<sc>Predictors of Knowledge-Sharing Behavior</sc>
2014
Address correspondence to Annette Kluge, Department of
Computer and Cognitive Sciences, Institute of Business
and Organizational Psychology, Faculty of Engineering
| University of Duisburg-Essen, Lotharstraße 65, 47057
Duisburg, Germany, annette.kluge@uni-due.de.
Predictors of Knowledge-Sharing Behavior for
Teams in Extreme Environments: An Example
From the Steel Industry
Nina Gross, Hüttenwerke Krupp Mannesmann, Duisburg, Germany, and
Annette Kluge, University of Duisburg-Essen, Duisburg, Germany
Journal of Cognitive Engineering and Decision Making
2014, Volume 8, Number 4, December 2014, pp. 352–373
DOI: 10.1177/1555343414540656
Copyright © 2014, Human Factors and Ergonomics Society.
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