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Erschienen in:
Introduction: Entrepreneurial Ecosystems Kapitel lesen Erstes Kapitel lesen

2023 | OriginalPaper | Buchkapitel

9. A Tale of Two Cities: How Arlington Won and Baltimore Lost in Battle for Amazon’s HQ2

verfasst von : Abraham Song, Keith Waters

Erschienen in: The Entrepreneurial Ecosystem

Verlag: Springer Nature Switzerland

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Abstract

Song and Waters narrate a tale of two cities, namely, Washington metropolitan area and Baltimore metropolitan area; about the rise of one and the fall of the other; about a metro that landed Amazon’s distribution centers and the other, highly coveted the company’s second headquarters (HQ2). In today’s knowledge economy where the most valuable companies are digital platforms, it’s a winner-take-all when it comes to regional economic development. The authors discuss how the paradigm of place-based policies of the industrial age that sought to attract large manufacturers with tax incentives is outdated. There is no better example of this paradigm shift in economic development from cost minimization to value maximization, from emphasis on physical capital to human capital, embodied in the case of Amazon HQ2 race, which ultimately landed in Crystal City, Virginia. Amazon HQ2 race represents a great lesson for what technology businesses value: talent. Virginia demonstrated a good understanding of tech firms’ market needs and its development strategy evidenced the importance of prioritizing the talent pipeline.

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Vorheriges Kapitel Digital Inequality and the Signature of Digital Technologies and the Digital Ecosystem: Analysis of Deviations in the Rank-Size Rule of Internet Access Data
Nächstes Kapitel Measuring the Modern Entrepreneur: An Evaluation of Elon Musk
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Fußnoten
8
We use employment data from the Bureau of Labor Statistics’ Quarterly Census of Employment and Wages. We use 4-digit NAICS codes. NAICS data are used unaltered. While NAICS updates the classifications on occasion, we do not control for changes. We use Metropolitan Statistical Areas as the geography of analysis, with no alterations to control for changes among years. Thus, each year is calculated independently.
 
9
Negative values are dropped as they indicate a repulsion between two industries.
 
10
Networks are visualized with the Kamada–Kawai algorithm that works to both minimize edge crossings and output evenly spaced nodes (Cheong & Si, 2016; De Nooy et al., 2018).
 
11
LVC communities have higher co-occurrence values between industries within the community than with industries outside the community. For the entire period analyzed (1990 to 2020), the same resolution parameter of 0.8 is used to find communities. This parameter was chosen to reveal 2 communities for the entire period.
 
12
Exceptions were the years 1995, 2001, 2004, 2005, and 2018. These years, the community with the highest share of MTT industries was identified as the MTT community.
 
13
In 2020, the larger community, which we refer to as MTT community, had 178 industries. Of the 178 total industries in the MTT community, 111 (62.4%) were accounted for by MTT industries
 
14
In the Service community, only 46 of the 126 industries (36.5%) were MTT. Despite the identification of two communities, community modularity, which ranges from 0 to 1, was just 0.12 in 2020. This indicates that the internal cohesion of the communities is relatively weak.
 
15
While the specialized industries of the two MSAs are located in different portions of the network, given the low modularity, the differing locations are subtle. While the two communities are found in all years, the definitions and xi, j values vary annually. It may be the case that if occupation or skills networks were used, the variation would be smaller, as such communities have been found to be more distinct (Alabdulkareem et al., 2018; Shutters & Waters, 2020).
 
16
This is the combination of all industry specialties.
 
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Metadaten
Titel
A Tale of Two Cities: How Arlington Won and Baltimore Lost in Battle for Amazon’s HQ2
verfasst von
Abraham Song
Keith Waters
Copyright-Jahr
2023
Buch
The Entrepreneurial Ecosystem

Print ISBN: 978-3-031-25930-2

Electronic ISBN: 978-3-031-25931-9

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-3-031-25931-9_9

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