Brian Danley

Swedish University of Agricultural Sciences (SLU) - Department of Forest Economics

Doctoral Student at the Institutionen for Skogsekonomi

S-901 83 Umea

Sweden

http://www.slu.se/en/cv/brian-danley/

SCHOLARLY PAPERS

4

DOWNLOADS

541

TOTAL CITATIONS

21

Scholarly Papers (4)

1.

Leveraging Regional Assets: Insights from High-Growth Companies in Kansas City

Number of pages: 32 Posted: 10 Aug 2013
University of Kansas - Geography & Atmospheric Science Department, Swedish University of Agricultural Sciences (SLU) - Department of Forest Economics, Amazon, Independent and Startup Genome
Downloads 221 (298,885)
Citation 13

Abstract:

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Kansas City, regional, entrepreneur, entrepreneurial, economic development, growth, high-growth, policy

2.

An Analysis of the Geography of Entrepreneurship: Understanding the Geographic Trends of Inc. 500 Companies Over Thirty Years at the State and Metropolitan Levels

Number of pages: 36 Posted: 12 Sep 2012
Yasuyuki Motoyama and Brian Danley
University of Kansas - Geography & Atmospheric Science Department and Swedish University of Agricultural Sciences (SLU) - Department of Forest Economics
Downloads 192 (341,143)
Citation 8

Abstract:

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geography, entrepreneurship, high-growth, firms, companies, inc. 500

3.

State Profiles of America's High-Growth Companies: State-by-State Analysis of Inc. 500 Firms Over Thirty Years

Number of pages: 51 Posted: 12 Sep 2012 Last Revised: 20 Feb 2014
Yasuyuki Motoyama and Brian Danley
University of Kansas - Geography & Atmospheric Science Department and Swedish University of Agricultural Sciences (SLU) - Department of Forest Economics
Downloads 68 (728,813)

Abstract:

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state, inc. 500, geography, states, growth, firm

4.

Forest Owner Objectives Typologies: Instruments for Each Owner Type or Instruments for Most Owner Types?

CERE Working Paper, 2019:7
Number of pages: 33 Posted: 18 Jun 2019
Brian Danley
Swedish University of Agricultural Sciences (SLU) - Department of Forest Economics
Downloads 60 (778,247)

Abstract:

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forest policy, k-means cluster analysis, non-industrial private forest owners