Evaluation Framework for the Boosting Effect of Turkey's Visa-Free Policy on Outbound Tourism Airlines and OTA Performance

Based on available information and facts provided by the user, the following is an evaluation framework for the boosting effect of Turkey’s visa-free policy on the performance of outbound tourism airlines and OTAs (to be quantitatively calibrated after subsequent access to brokerage APIs).

I. Facts and Timeline

• Policy Node: Turkey issued a presidential decree in the Official Gazette on 2025-07-09, announcing visa-free entry for Chinese citizens (tourism/transit, no more than 90 days cumulative within 180 days). According to a report by Sina Finance, there was an update on the last day of 2025 stating that it would be implemented from 2026-01-02; subsequent implementation shall be subject to the latest official statement (this analysis temporarily adopts the effective date of 2026-01-02). Sources: Presidential Decree of Turkey’s Official Gazette [1], Sina Finance [2].
• User Side Immediate Reaction (from Qunar Data):
  • Search volume for domestic flights to Istanbul increased by 3.2x month-on-month; Antalya by 1.3x; Izmir by more than 2x.
  • Ten cities including Shanghai, Guangzhou, and Beijing all saw a search heat increase of more than 2x. Source: User-provided context (Qunar data).

II. Conversion Reference from Search Volume to Actual Bookings

• Industry Experience: The conversion from outbound tourism search volume to orders usually has a lag, affected by visa convenience, price sensitivity, seasonal capacity, inventory and launch rhythm, destination safety/exchange rate, etc. Visa-free policy mainly eliminates visa time costs and procedural friction, helping to increase the probability of “from intention to booking”.
• Comparable Reference for Visa-Free Driving Conversion (Policy Level):
  • Guangzhou Border Inspection sample (not representative of national data) shows that visa-free entry persons accounted for about 50% of the total number of foreign entry persons in 2025, indicating that the reduction of policy thresholds significantly drove passenger flow; the annual visa-free entry of this sample increased by 133% year-on-year, and the entry-exit passenger flow increased by 19% year-on-year, indicating that visa-free contributed significantly at relevant ports. Source: Guangzhou Border Inspection Data [3].
  • According to the official disclosure of Shenzhen Airport, the number of foreign entry-exit personnel in the first 11 months of 2025 increased by 44% year-on-year, among which visa-free entry foreign personnel increased by 133% year-on-year, indicating that hub airports benefited significantly from the visa-free policy. Source: Shenzhen Airport Data [4].
• Note: The above are all qualitative evidence of policy effects, not direct quantification of “Turkey routes”.

III. Evaluation Ideas for Performance Impact (Including Parameterization Methods)

1. Evaluation Main Line (“Policy Signal - Search - Booking - Capacity - Revenue - Profit” Link)

• Step 1: Traffic Verification (Search and Intention) — Continuously track changes in search/browse/add-to-cart on platforms like Qunar and Ctrip.
• Step 2: Booking Conversion and Customer Order — Focus on order volume, average ticket price/product average price, and the proportion of pre-sale and last-minute bookings.
• Step 3: Capacity and Supply-Demand Matching — New/encrypted flights, aircraft type and seat supply, fare elasticity, load factor and revenue management.
• Step 4: Structure and Profit — Changes in the proportion of international route revenue and gross profit, single route profit and loss, and impact on overall profit margin.

2. Key Observation Indicators (Quantifiable after API Data Return)

• Airlines (taking the three major airlines with routes to Istanbul/Antalya/Izmir and possible direct/transfer carriers as examples):
  • Revenue Side: Revenue per passenger kilometer (RPK), load factor, average fare, freight/belly cargo revenue.
  • Cost Side: Cost per available seat kilometer (CASK), fuel and exchange rate hedging, flight distance and take-off/landing costs.
  • Profit Side: Single route gross profit/EBIT contribution, changes in international business profit margin.
• OTAs (e.g., Ctrip, Ly.com, Qunar, etc.):
  • Traffic and Conversion: Search-to-order conversion rate, hotel/air ticket/package product order volume.
  • Customer Order and Profit: Customer unit price, cross-selling rate, advertising/commission revenue, profit margin.
  • Structural Changes: Changes in the proportion of Turkey and related destinations in outbound business.

3. Quantitative Calculation Template (Taking Airlines as an Example)

• Basic Information (Need to be supplemented through brokerage API/company announcement/airline official website):
  • Existing seat supply (Seats/week), load factor (LF0), average fare (Y0) for relevant routes.
  • Expected Capacity Deployment Changes: ΔCapacity (seat number/flight increase).
  • Expected Load Factor Change: ΔLF (e.g., from LF0 to LF1).
  • Expected Fare Change: ΔY (fare elasticity, can refer to competing routes or historical fluctuations).
• Formula (Simplified Version):
  • Original Single Route Revenue R0 = Seats0 × LF0 × Y0
  • New Single Route Revenue R1 = Seats1 × LF1 × Y1
  • Revenue Increment ΔR = R1 - R0
  • Impact on Overall Profit ≈ ΔR × International Route Net Profit Margin Level (or approximate with company’s overall net profit margin)
• Parameter Assumption Explanation (Need Subsequent Calibration):
  • Search-to-order conversion rate can refer to historical data of similar visa-free destinations within the platform;
  • Fare elasticity and seasonality need to introduce historical fluctuations and peer benchmarking;
  • Capacity deployment rhythm and season scheduling will affect the time of incremental realization.

4. Time Rhythm and Realization

• Phase Division (To be Calibrated with API):
  • T0 (Policy Announcement): Surge in search volume, driven by sentiment, orders lag.
  • T1 (Capacity Response): Airlines evaluate capacity matching; new/encrypted flights take a certain cycle.
  • T2 (Peak Season Realization): If overlapping with peak seasons like summer vacation or Spring Festival, the increment is more significant.
  • T3 (Normalization): With competition and supply response, marginal effects gradually return to stability.
• Risk Tips: Geopolitics, oil prices and exchange rates, capacity bottlenecks (slots/crews/take-off and landing), epidemics or safety incidents, visa policy fine-tuning or entry control changes may all disturb expectations.

IV. Subsequent Calibration and Data Supplement (Planned to be Completed After Accessing Brokerage API)

• Obtain and verify the following key data to form quantitative conclusions:
  • Seat supply, flight frequency, load factor, fare history and expectations of Istanbul/Antalya/Izmir routes of the three major airlines and related airlines (source: brokerage API/airline disclosure).
  • Outbound tourism order volume, customer unit price, profit margin and destination structure of OTA platforms (source: brokerage API/company announcement).
  • Outbound tourism volume-price and profit margin elasticity of comparable visa-free destinations (e.g., some newly visa-free countries for China) (historical comparison).
  • Macro and international travel demand recovery and consumer willingness indicators (source: brokerage API/industry report).
• After obtaining the above data, I will:
  • Establish a parameterized calculation model and output “elasticity range for revenue/profit” and “confidence interval”;
  • Distinguish the structural benefit degree of airlines and OTAs, and give ranking and scenario analysis;
  • Update the risk monitoring list and set tracking thresholds and signal points.

V. Concluding Points (Current Stage)

• Qualitative Judgment: The visa-free policy significantly reduces the threshold for outbound travel, and combined with the surge in search volume, it is expected to drive revenue growth in related routes and destination businesses after capacity matching and product supply are in place. The specific magnitude depends on the above key parameters and supply-demand matching.
• Next Steps: Continuously monitor platform search-order conversion, airline capacity deployment announcements, fare and load factor trends, and conduct quantitative calculations and scenario corrections after obtaining brokerage API data. If you specify airlines (e.g., Air China, China Eastern Airlines, China Southern Airlines, etc.) and OTA targets to focus on, I can prioritize supplementing the analysis of relevant routes and business structures of these companies.

References (Web Search)
[1] Presidential Decree of Turkey’s Official Gazette (2025-07-09) — Turkey implements visa-free entry for Chinese citizens from 2025-08-01 (no more than 90 days cumulative within 180 days).
[2] Sina Finance — Turkey suddenly implements visa-free entry for China! The report includes an update on the implementation date as “from 2026-01-02”.
[3] Guangzhou Border Inspection Data — In 2025, visa-free entry persons accounted for about 50% of the total number of foreign entry persons; visa-free entry increased by 133% year-on-year, and entry-exit passenger flow increased by 19% year-on-year (sample is Guangzhou Border Inspection, not representative of the whole country).
[4] Shenzhen Airport Data — In the first 11 months of 2025, the number of foreign entry-exit personnel increased by 44% year-on-year, among which visa-free entry foreign personnel increased by 133% year-on-year.

Note: After accessing the brokerage API, quantitative calibration will be carried out based on authoritative financial data, and specific figures and scenario results will be given based on this framework. If you specify airlines (e.g., Air China, China Eastern Airlines, China Southern Airlines, etc.) and OTA targets to focus on, I can prioritize supplementing the analysis of relevant routes and business structures of these companies.