• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.189-213
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• 2017

This study seeks to critically examine the significance and limits of the cluster adaptive cycle model for analysis of cluster evolution and to propose research issues for future analysis of cluster evolution based on this critical examination. Until the 1980s, research on industrial complexes including clusters was based on a 'static perspective' that focuses on the aspect of economic space at a specific point in time, but the research paradigm has recently shifted to a 'dynamic perspective' focusing on 'evolution' of 'complex adaptive systems'. As a result, the adaptive cycle model has attracted attention as an analysis tool of dynamically evolving clusters. However, the cluster adaptive cycle model has emerged by being appropriately modified and expanded according to the properties of the cluster and its evolution. The cluster adaptive cycle model is a comprehensive analysis framework that identifies the characteristics of cluster evolution in terms of resource accumulation, interdependence, and resilience and classifies cluster evolution paths into six different categories. Nevertheless, there is still a need for further discussion and supplementation in terms of theoretical and empirical research to expand and deepen the model. Therefore, research issues for future analysis of cluster evolution are to specify and elaborate the cluster evolution model, to emphasize the concept of resilience, and to verify the applicability and usefulness of the model through empirical research.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.2
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• pp.249-263
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• 2014

Established as the first science park in the world in the late 1950's, the Research Triangle Park(RTP) has not jut grown significantly but also has been successful in the transition from the exogenous development model to the endogenous development model. In this context, this paper attempts to explore the evolutionary path of the RTP by drawing upon the concept of triple-helix spaces of regional innovation. Firstly, the three research universities in the triangle area, as a knowledge space, played a fundamental role for forming the RTP. However, it is difficult to say that the regional universities, as opposed to the Silicon Valley and the Boston area, have had a significant impact on inducing the dynamics of the cluster evolution and the triple helix spaces. Secondly, it can be argued that the North Carolina's Board of Science and Technology, which was formed in 1961 but traced back to the 1950's in its origin, has been a centerpiece of a consensus space that makes a contribution to creating, sustaining and transforming the RTP as a triple-helix-based innovation cluster. Thirdly, there have been a plenty of agents to be an innovation space in the RTP. Particularly, the North Carolina Biotechnology Center(NCBC) and the Microelectronic Center of North Carolina(MCNC) have been the boundary permeable agents to make triple-helix agents interact. Today, the RTP has the triple-helix spaces with the structure that a consensus spaces is centered on out of the three, but all of those are inter-connected and influenced by each other. It can be claimed that the RTP today shows the dynamic structure of cluster evolution in a way in which the existing industry sectors have adapted to the changes in external environment and the new industry sectors have emerged at the same time.

• Journal of the Korean association of regional geographers
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• v.18 no.3
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• pp.283-297
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• 2012

This study aims to analyze an evolutionary path and the dynamics of the Seoul Digital Industrial Complex in Korea based on the analysis of cluster life cycles. From the mid 1960s to the late 1990s, the life cycles and their characteristics of the Seoul Digital Industrial Complex (Guro Industrial Park) are examined as emergence-growth-sustainment-decline focused on the number of firms and employees. After the late 1990s, the number of firms and employees increases rapidly and the active actors of the growth and restructuring are transformed to the technology-intensive SMEs and knowledge-based service firms. Knowledge industry centers (apartment-type factories) help evolve into the life cycle of transformation as knowledge-based clusters after the mid 2000s.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.4
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• pp.567-584
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• 2013

This study aims to explore an evolutionary path of the IT service industry in Fairfax County using the Cluster Adaptive Cycle model in economic geography. The analysis is based on detailed historical and industrial information obtained through a variety of data sources including local archival materials, economic census, and interviews. This study also performs a shift-share analysis during the period of 1990 to 2011. Using the adaptive cycle model, the local IT service industry is indicated by a trajectory of constant cluster mutation. The evolution of the local IT service industry has been closely related to federal government policy due to the regional specificity of the National Capital Region and the proximity of the Department of Defense. Although the economic downturn of the late 2000s, the local IT service industry has been notable resilience and adapted to a changing market and technological environment. This constant mutation of the local industry is resulted from not only high resilience which is based on the large government procurement market, the reinforcement of adaptive capacity of the local firms and the network of economic agents such as firm and supporting institutions, but also high flexibility of the knowledge-based service industry to a changing business environment.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.1-18
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• 2023

Similar software is often developed with the Clone-And-Own (CAO) approach that copies and modifies existing artifacts. The CAO approach is considered as a bad practice because it makes maintenance difficult as the number of cloned products increases. Software product line engineering is a methodology that can solve the issue of the CAO approach by developing a product family through systematic reuse. Migrating product families that have been developed with the CAO approach to the product line engineering begins with finding, integrating, and building them as reusable assets. However, cloning occurs at various levels from directories to code lines, and their structures can be changed. This makes it difficult to build product line code base simply by finding clones. Successful migration thus requires unifying the source code's file path, class name, and method signature. This paper proposes a clustering method that identifies a set of similar codes scattered across product variants and some of their method full paths are different, so path unification is necessary. In order to show the effectiveness of the proposed method, we conducted an experiment using the Apo Games product line, which has evolved with the CAO approach. As a result, the average precision of clustering performed without preprocessing was 0.91 and the number of identified common clusters was 0, whereas our method showed 0.98 and 15 respectively.