Insight

The strongest competitiveness is to promptly capture and respond effectively to dynamic changes in the competitive environment. Maximize competitiveness with Lobin's insights!
Domestic | Lodging | Overview | 2024-08-01
Domestic | Lodging | Overview | 2024-06-17
Domestic | Property | Analysis | 2022-08-15
Domestic | Lodging | Analysis | 2022-07-12
Global | Lodging | Analysis | 2021-10-01
Global | Lodging | Analysis | 2021-07-02
Domestic | Property | Issue | 2020-10-15
Domestic | Lodging | Overview | 2020-10-15
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Access Request for Member Dashboard

You can obtain a comprehensive view over the competitive environment of lodging markets in Korea.

2024 access fee is USD 528 USD 176(VAT included), for access to the Member Dashboard for a year until December 31, 2024.

Please check out the details for using the Member Dashboard here .

Data Source

  • GDP: GDP, Current $US (World Bank Open Data)
  • Establishments: Compendium of Tourism Statistics (UNWTO), Lodging Business Ledger (MOIS)
  • Rooms: Compendium of Tourism Statistics (UNWTO), Lodging Business Ledger (MOIS)
  • Lodging GDP: Value Added by Industry (BEA), National Accounts (Cabinet Office), GDP of Indonesia (BPS), GDP & GNI by Sector (BOK), Economic Census (KOSIS)
  • Period: 2017-2021

※ In Korea, general & residential accommodations are included while rural & urban minbaks are excluded. Comparable countries are selected based upon availability of lodging GDP statistics for all types of accommodations.

Data Source

  • Population: Population, Total (World Bank Open Data)
  • GDP: GDP, Current $US (World Bank Open Data)
  • Rooms: Compendium of Tourism Statistics (UNWTO), Lodging Business Ledger (MOIS)
  • Lodging GDP: Value Added by Industry (BEA), National Accounts (Cabinet Office), GDP of Indonesia (BPS), GDP & GNI by Sector (BOK), Economic Census (KOSIS)
  • Period: 2017-2021

※ In Korea, general & residential accommodations are included while rural & urban minbaks are excluded. Comparable countries are selected based upon availability of lodging GDP statistics for all types of accommodations.

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※ Messages intended for defamation or obstruction of business by Lobin Co. and /or other third parties, or containing content that is obscene, violent or unrelated to Lobin Co.’s business, will automatically be blocked by the system and not delivered to the administrator.

Data Source

  • Korea: Lodging Business Ledger (MOIS), Tourist Accommodation Ledger (MCST)
  • USA: Census Database (STR)
  • Period: As at the end of 2021

※ General & residential accommodations other than rural and urban minbaks asre included for Korea. Life cycle was calculated as of December 31, 2021 or actual closure date. If there exists a discrepancy between data sources for an establishment, the discrepancy was settled through an algorithm before use.

Data Source

  • Korea: Lodging Business Ledger (MOIS), Tourist Accommodation Ledger (MCST), Economic Census (KOSIS), Hotel Operating Statistics (KHA), DART (FSS), Trends Report (STR)
  • USA: Compendium of Tourism Statistics (UNWTO), Census Database (STR), Trends Report (STR)
  • Period: 2005-2021

※ General & residential accommodations other than rural and urban minbaks asre included for Korea. Visibility was calculated as the number of establishments for which revenue data is available divided by the total number of establishments. If there exists a discrepancy between data sources for an establishment, the discrepancy was settled through an algorithm before use.

Data Source

  • Guests(Korea): Domestic Traveler Survey (MCST), International Traveler Survey (MCST), Hotel Operating Statistics (KHA)
  • Rooms(Korea): Lodging Business Ledger (MOIS), Tourist Accommodation Ledger (MCST)
  • Guests(USA): Compendium of Tourism Statistics (UNWTO), Trends Report (STR)
  • Rooms(USA): Compendium of Tourism Statistics (UNWTO), Census Database (STR)
  • Period: 2005-2020

※ General & residential accommodations other than rural and urban minbaks asre included for Korea. If there exists a discrepancy between data sources for an establishment, the discrepancy was settled through an algorithm before use.