Best workation city" lists are wrong for half their readers. Here is the data and a fix.
If you have ever read a "best cities for remote work" ranking and thought "this is useless for me," you were probably right, and there is a structural reason. These lists assume one type of reader. In reality the constraints split sharply in two.
A freelancer can fly to Bali and stay for months. An employee on a German contract cannot: they need an A1 certificate to stay in their home social-insurance system, and they have to watch the 183-day threshold before they trigger tax residence abroad. Same dream, completely different rulebook. So a single ranking cannot be right for both.
I open-sourced the underlying data of the "Workation Atlas 2026" so you can re-weight it for whichever rulebook you live under.
A surprisingly German obsession
While gathering the search data, one figure jumped out: Germany alone accounts for 52% of global "workation" searches, far ahead of anyone else.
import pandas as pd
shares = pd.read_csv("https://raw.githubusercontent.com/DatapulseResearch/"
"workation-atlas/main/data/workation_search_share_by_country.csv")
print(shares.sort_values("share_of_global_workation_searches_percent", ascending=False))
| Country | Share |
|---|---|
| Germany | 52% |
| Rest of the World | 30% |
| Poland | 6% |
| India / Netherlands | 5% each |
| United States | 3% |
Three rulebooks, three rankings
Instead of one list, the data is weighted three ways:
ranks = pd.read_csv("https://raw.githubusercontent.com/DatapulseResearch/"
"workation-atlas/main/data/workation_city_rankings_top5.csv")
print(ranks.pivot(index="rank", columns="ranking", values="city"))
Adventure Seeker (freelancers): Bangkok, Kuala Lumpur, Chiang Mai, Da Nang, Ubud.
Smart Spender (best value): Jaipur, Bangkok, Da Nang, Chennai, Weligama.
Easy Mover (employees, EU-only): Seville, Ericeira, Valencia, Faro, Rome.
The freelancer lists are almost entirely Asian. The employee list is entirely EU/Southern Europe, not because those cities are objectively better, but because the A1 form and the 183-day rule quietly rule everything else out. The bureaucracy is the ranking.
Data and sources
Rankings weight climate, cost of living, flights, infrastructure, safety and (for employees) EU/EFTA membership differently per reader type.
Search demand from Ahrefs; analysis by DataPulse Research.
Open dataset: https://github.com/DatapulseResearch/workation-atlas
Full study with methodology: https://www.datapulse.de/en/workation-atlas
Fork the CSV, plug in your own weights, and see if your winner changes.