Okay, here’s a breakdown of teh text, focusing on the core data and key takeaways. I’ll present it in a concise, summarized format.
Main Topic: A study analyzing the factors influencing the location of datacenters in the US.
Key Researchers: Tommy Pan Fang (Rice University) and Shane Greenstein (Harvard Business School).
Study Methodology: Large-scale statistical analysis using county-level data.
Key Findings:
* different Types, Different Needs: The location strategies differ between third-party providers (colocation/hosting) and hyperscale facilities.
* Third-Party Providers: Prefer urban areas due to proximity to customers (especially in finance), and prioritize low latency, security, and regulatory compliance.
* Hyperscale Facilities: Need reliable power, water, and robust network infrastructure. Areas like Northern Virginia, with existing network investment, are prime locations.
* Future Trend: A potential shift towards a hybrid model – large regional hubs combined with strategically placed colocation facilities.
* Economic and strategic Incentives: The study aims to clarify how these incentives drive datacenter location decisions for both policymakers and businesses.
In essence: The study highlights that datacenter location isn’t random. It’s driven by a complex interplay of economic factors (cost of operations), strategic needs (proximity to customers, network connectivity), and existing infrastructure. The type of datacenter (third-party vs. hyperscale) significantly influences these priorities.
note: The text includes several ad blocks (indicated by <noscript> tags and URLs starting with pubads.g.doubleclick.net). These are irrelevant to the content of the article itself and have been ignored in this summary.
