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Agglomeration vs. Heritage: The Molds and Plastics Industries in Portugal

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posted on 2020-07-28, 15:21 authored by Carla Costa
The evolution of regional industry clusters is examined by exploring two perspectives: the mechanisms driving the performance of one clustered industry, and the mechanisms and cross-industry effects driving the collocation of related industries and enhancing their performance in the clustered region. In the first study, the analysis focuses on one clustered industry (molds manufacture for injection-molded plastics fabrication). The second study broadens the scope to examine in more detail the linkages between two closely related industries (molds manufacture and injection-molded plastics manufacture). Two theories that aim to explain these phenomena are taken into consideration: agglomeration economies and organizational heritage. The setting
for this research is in Portugal, where the molds industry developed into world-class, high-technology leaders driven heavily by exports. When looking at one specific agglomerated industry characterized by a network of small,
vertically disintegrated companies, we find that both mechanisms have significant effects on performance. However, effects associated with heritage through spinoffs seem to have a stronger impact. In addition, when looking at more advanced stages of the cluster’s evolution, we find
evidence of durability of heritage effects in the growth and sustainment stages of the cluster life cycle. Results also point to the importance of spinoffs from related industries. When analyzing collocation of related industries, results imply that organizational reproduction through the
transmission of capabilities from parent firms in the related industry to spinoffs locating in the same region is the foremost driver of collocation of the molds and plastics injection industries. The presence of the plastics industry also has a positive impact on the molds industry, but the
inverse relationship is not significant.

History

Date

2013-05-01

Degree Type

  • Dissertation

Department

  • Social and Decision Sciences

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

David Hounshell

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