Targeting market opportunity for port growth: a CART-based decision support system
Complex decisions, such as those facing port managers when targeting market opportunities for growth, are multifaceted and follow complex patterns of sequential and iterative decision subsets that are not well captured nor represented by current parametric modelling approaches. Nonetheless, understanding how such decisions are made and the patterns they follow have important implications for policy formulation and execution. This paper uses a classification and regression trees (CART) framework—a non-parametric decision trees modelling approach–and develops a decision support system to assist port managers in making effective decisions about market opportunities they should pursue for growth. The CART-based decision support system reveals the predictive structure and complex patterns that the market opportunity selection process follows. It also advances our knowledge and understanding of the interaction and behaviour of the key decision variables and the decision makers in a port context.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/2899960
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Supplemental Notes:
- Abstract reprinted with permission from Taylor & Francis.
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Authors:
- Magala, Mateus
- Publication Date: 2007-4
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References; Tables;
- Pagination: pp. 131-150
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Serial:
- Maritime Policy & Management
- Volume: 34
- Issue Number: 2
- Publisher: Taylor & Francis
- ISSN: 0308-8839
- EISSN: 1464-5254
- Serial URL: http://www.tandfonline.com/loi/tmpm20
Subject/Index Terms
- TRT Terms: Decision support systems; Forecasting; Marine terminals; Mathematical models; Nonparametric analysis; Port operations
- Uncontrolled Terms: Classification and regression trees; Marketability; Patterns; Targeting
- Subject Areas: Data and Information Technology; Marine Transportation; Terminals and Facilities;
Filing Info
- Accession Number: 01049922
- Record Type: Publication
- Files: TRIS
- Created Date: May 16 2007 8:40AM