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Understanding local economic development

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This book offers insights into the process and the practice of local economic development. Bridging the gap between theory and practice it demonstrates the relevance of theory to inform local strategic planning in the context of widespread disparities in regional economic performance.

The book summarizes the core theories of economic development, applies each of these to professional practice, and provides detailed commentary on them. This updated second edition includes more recent contributions - regional innovation, agglomeration and dynamic theories – and presents the major ideas that inform economic development strategic planning, particularly in the United States and Canada. The text offers theoretical insights that help explain why some regions thrive while others languish and why metropolitan economies often rise and fall over time. Without theory, economic developers can only do what is politically feasible. This text, however, provides them with a logical tool for thinking about development and establishing an independent basis from which to build the local consensus needed for evidence-based action undertaken in the public interest.

Offering valuable perspectives on both the process and the practice of local and regional economic development, this book will be useful for both current and future economic developers to think more profoundly and confidently about their local economy.

The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

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Detail Information

Series Title

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Call Number

650 MAL u

Publisher

London : Routledge., 2020

Collation

312 p

Language

English

ISBN/ISSN

9780367815134

Classification

650

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Business & Industry

Specific Detail Info

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Statement of Responsibility

Emil Malizia

Other Information

Cataloger

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Source

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Validator

Maya

Digital Object Identifier (DOI)

https://doi.org/10.4324/9780367815134

Journal Volume

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Journal Issue

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Subtitle

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Parallel Title

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