China Outbound 2026: A US$280B Travel Wallet: How Destinations Can Win It

China outbound is no longer a “reopening” headline. It’s turning into a competitive, corridor-by-corridor market-share fight — across hotels, attractions, airlines, airports, and retail.

In our latest upper-bound 2026 scenario, China outbound reaches 175M trips and US$280B in total overseas travel spend, building on a newly released macro foundation for 2025: US$254B in outbound travel spend and ~167.5M trips (based on the NIA crossings-to-trips framing we use for macro metrics).

This post explains:

• what’s inside the US$280B wallet,

• why volume destinations and value destinations are not the same,

• how our model works,

• and what the 2026 outlook implies for key markets and corridors. 

The 2026 wallet: where the money goes

In the 2026 upper-bound scenario, the outbound wallet is broad-based — meaning destinations win not only through arrivals, but by shaping how travellers spend once they arrive:

• Accommodation: ~US$85B

• Food & beverage: ~US$52B

• Local transport: ~US$40B

• Entertainment & services: ~US$24B

• Shopping (total): split into:

  • Travel Retail (airport / duty-free / travel retail): ~US$23B

  • Non-travel-retail shopping (downtown/in-market): ~US$56B

That last point matters: shopping is one of the most elastic (and therefore most winnable) parts of the wallet — especially for destinations that influence trip design, retail access, and the pre-trip decision journey.

The key idea: “volume” and “value” winners are different

China outbound isn’t one market. It’s a set of corridors with very different trip purpose, length-of-stay, and spend per visitor.

Volume engines

In our 2026 scenario, Hong Kong (~39.0M arrivals) and Macao (~30.0M) are the largest arrival markets by far. They win because friction is low: proximity, repeat behaviour, short lead times, and high-frequency travel.

Thailand, Vietnam, South Korea, Japan, Malaysia, Singapore and other short-haul markets compete in the next tier — often battling on air capacity, visa friction, and price/value perception.

Value engines

Long-haul markets win disproportionately on spend per visitor because trips tend to be longer and the daily basket is bigger. In our scenario, the United States and France are standout “value” markets. They may not be the biggest by arrivals, but they can be among the biggest by total spend.

The punchline: DMOs, hospitality groups, airport operators, and brands should stop asking only “how many arrivals can we get?” and start asking “how do we win nights, experiences, itinerary share—and conversion at the airport and in-market?”

What travellers are telling us (2025 Q4 sentiment)

Our Q4 travel sentiment read provides useful “operational signals” for 2026 planning:

• Near-term intent is active: 22.86% plan to travel within the next three months.

• Travel retail remains in the consideration set: 64.45% say they are likely/very likely to shop airport travel retail.

• Frequency matters: frequent travellers are far more “conversion-ready” than first-timers (and this shows up across behaviours, not just shopping).

A practical interpretation for destinations and hotels:

• Repeat travellers are easier to upsell (room upgrades, F&B, experiences),

• First-time travellers require friction removal (clear itineraries, “how-to” planning support, trust-building cues),

• and the fight is won early, upstream of booking.

How CTD’s model works

This forecast isn’t a single top-down guess. It’s a reconciled system that ties macro truth to corridor-level planning.

1. Start with a hard macro anchor (2025)

We anchor 2025 global outbound spend to the official SAFE BoP “Travel” debit total. This gives a defensible global benchmark that doesn’t depend on incomplete destination aggregation.

2. Convert “crossings” to “trips” for macro behaviour

NIA “exit-entry” reporting is useful, but crossings are not exactly trips. For macro spend-per-trip framing, we apply the working assumption trips ≈ crossings/2 (this is why we quote 167.5M trips as a 2025 macro estimate).

3. Build 2026 from parameterized levers

The model is designed to be updated quarterly by adjusting:

• destination arrivals assumptions,

• spend-per-trip assumptions (or daily basket × length-of-stay),

• category shares (accommodation, F&B, transport, entertainment, shopping),

• and shopping channel split (travel retail vs non-travel retail).

This is how we control the 2026 scenario range and keep outputs explainable.

4. Destination coverage: Top 11 + HK + Macao + Rest-of-World buckets

We explicitly model major destinations (including HK and Macao as all-modes arrivals), and then allocate the remainder into RoW buckets so we don’t hide a large residual in one opaque “other” line.

5. RoW isn’t a dump bucket: it has structure

RoW is split into multiple regional groups (e.g., EU ex-FR; SE Asia ex-modeled; Greater China fringe; Middle East ex-UAE; Americas ex-US). Trips allocate by share; spend allocates by (share × weight) so long-haul RoW doesn’t unrealistically look like short-haul spend.

6. Shopping is split into channels: Travel Retail vs Non-Travel Retail

This is the key GTR upgrade:

• Shopping_TR = TotalSpend × ShoppingShare × TR_share

• Shopping_NonTR = TotalSpend × ShoppingShare × (1 − TR_share)

Why this matters: airports, downtown duty-free, and in-market retail behave differently; DMOs and brands need the split to plan activations properly.

7. Calibration: directional payment data + sanity caps

We use directional payment signals (e.g., UnionPay duty-free/luxury corridor intensity) to calibrate relative travel-retail intensity by corridor—without treating payment data as the full market.

Then we sanity-check:

• TR per visitor reasonableness,

• corridor rankings,

• and external ceilings where available (e.g., Korea duty-free market size as an upper-bound reference).

Corridor playbook: what to do by destination (DMO/Hotel + Airport + Brand)

Destination / corridor	Wins on	DMO / Hotel move	Airport operator move	Brand move
Hong Kong ⚡	Volume + frequency (short lead times, repeat travel)	Always-on micro-stay offers; weekend/holiday bursts; neighborhood/event bundles	High-throughput conversion: fast wayfinding, top picks, pre-order; loyalty for repeat	Replenishment + gifting ladders; always-on bundles; quick “grab-and-go” SKUs
Macao ⚡ 💎	Repeat leisure + resorts	“One booking” bundles (stay + shows + dining); loyalty loops	Event-driven surges; resort-linked perks; simple value cues	Limited drops tied to events; sets/bundles; cross-promo with resorts
Japan 💎 🧭	High value + shopping intent	Seasonal itineraries; premium upsells; multi-city circuits	Planned-purchase conversion: reserve & collect; hero assortment	Premium sets/exclusives; seasonal editions; pre-trip content → airport conversion
South Korea ⚡ 💎	High conversion corridor	Tight funnel: inspiration → flights → hotel shortlist; city clusters	Promo mechanics that convert; clarity on value; downtown/airport linkage	Beauty/fragrance hero stories; bundles; timed offers and loyalty targeting
Thailand ⚡ 🧭	Scale; value via LOS	Multi-stop itineraries (city + beach); family bundles; experiences	Capture end-of-trip gifting; vouchers + pick-up flows	Essentials + gifting; price ladders; bundle with airline/OTA perks
Vietnam ⚡ 🧭	Scale; itinerary shaping	Multi-city circuits; “best time to go” planning; experience packaging	Convert short-haul leisure: curated edits; pre-order; seasonal peaks	Mid-price gifting + souvenirs; travel-friendly formats; seasonal themes
Singapore ⚡	Convenience + short breaks	48/72-hour bookable itineraries; event-led nights	Dwell-time conversion: curated “top 10 buys”; frictionless pre-order	Giftable sets + travel exclusives; event-tied drops (concert weekends)
Malaysia ⚡	Value + ease	City + nature pairings; family itineraries; safety/clarity	Improve navigation + basket drivers; bundles and price anchors	Value ladders; family-friendly gifting; cross-promo with attractions
United States 🧭 💎	Long-haul value (high spend/visitor)	Multi-city circuits; planning support; premium experiences	Premium traveler service; pre-order; loyalty audience targeting	Planned purchase + premium gifting; CRM; airport hero SKUs
France 🧭 💎	Long-haul value (culture + premium spend)	Paris + regions circuits; itinerary templates; shoulder-season wins	Premium conversion at departure/return; curated luxury edits	Premium gifting + limited editions; story-led assortments
UAE ⚡ 💎 🧭	Stopover-to-stay	Stopover bundles; airline partnerships; family + luxury segmentation	Hub optimization: short dwell, high-ticket; concierge selling	High-AOV categories; stopover perks tied to booking; premium audiences

Near-haul corridors are won on frequency and conversion speed; long-haul corridors are won on planning support, length-of-stay, and premium basket capture.

Legend

⚡ Speed = high-frequency conversion

💎 Premium = higher basket / planned purchase

🧭 Planning = length-of-stay + itinerary share

Closing: the 2026 fight is for share, not just recovery

China outbound is shifting from a rebound story to a competition for where value lands — by corridor, by destination, and by category. The winners in 2026 will be the teams that build real conversion architecture: influencing discovery early, reducing planning friction mid-funnel, and shaping itineraries on the ground to lift nights, experiences, and spend capture across the trip.

If you’d like a walkthrough of CTD’s projections — and how to turn them into sharper targeting, better content, and higher conversion with Chinese travelers — get in touch with the China Trading Desk team.

Sources: SAFE BoP (Travel debit, FY2025); China Trading Desk model (FY2026E upper-bound scenario); CTD Q4 Travel Sentiment Survey.