Impact of Regional Coupons on
Tourist Consumption Behavior
The University of Tokyo Behavior in Networks TeamB
Yudai Kaneda, Ryuhei Kurasawa
Honoka Shirai, Yuito Hayashi

1Background• コロナで深刻な影響を受けた観光業に対する政府の需要喚起策
Japanese government takes measures to recover demand for the tourism industry severely affected by the Covid-19.

• 旅⾏代⾦の割引＋地域共通クーポン(宿泊以外に利⽤可能）
discounts on travel + regional coupons(which is only available for accommodation)• ⾼級ホテルにのみ効果が偏るとの指摘
Only luxury hotels benefit from the policy.

• 旅⾏代⾦の割引は宿泊やツアー料⾦に使途が限定されがちであった
Discounts on travel tended to be used only for accommodation.

観光事業者を幅広く⽀援するには、適切な補助制度の設計が必要
Appropriate subsidy system design is needed to support a wide range of tourism businesses.

2

Purpose
地域共通クーポンが宿泊以外の観光業に与える効果を検証
Verify the effect of the regional common coupons on each sector of the tourism industry otherthan accommodation.

Transportation

FoodSouvenir

3

Data
道後2017調査(アンケート) Dogo2017-Questionnaire
サンプル：道後のホテルに泊まった観光客,有効サンプル197 (松⼭エリア内で３項⽬全てで消費⾏動)
Of the tourists stayed at a hotel in Dogo, valid sample 197 -those who record consumption behavior in all
three items within the Matsuyama area旅程に付随する滞在場所・時間帯・消費項⽬・消費⾦額のデータを利⽤
We used data on location, time of day, consumption categories, and amount spent at each of thedestinations visited during the trip.
訪問先1/destination
場所
location

道後温泉
Dogo Onsen

到着時間
arrival

16:50

消費1consumption1

消費2
consumption2

消費3
consumption3

項⽬

⾦額項⽬

⾦額項⽬

⾦額

categoryamountcategoryamountcategoryamount

⾷事

2,000

⼟産

3,500

交通

400

food

souvenirtransportation
4

Basic Analysis
道後2017調査(アンケート) Dogo2017-Questionnaire
Average of consumption [yen]Differences in Consumption Allocations by Budget

1400100%

120080%100060%800
60040%40020%

200
00%
Morning

Food

DaytimeTransportation

NightSouvenir

0 yen - 5,000 yen

Food

5,000 yen - 10,000 yen

Transportation

More than 10,000 yen

Souvenir

カテゴリ・時間帯ごとに消費⾦額は⼤きく違う

予算ごとに⾦額割り振りが変わる

Consumption varies widely by category and time of day

Amount allocations vary by budget

5Method
離散連続モデル（Discrete-Continuous model）
離散量と連続量を同時に選択し，配分するモデル
A model that simultaneously selects discrete and continuous quantities and allocates

離散量

連続量

Discrete

Continuous

カテゴリ

⽀払い⾦額

飲⾷費

𝑥! 円

category

Food or drink

交通費Transportation

お⼟産代
Souvenirexpense𝑥" 円
𝑥# 円

予算制約! 𝑥! = 𝐸!の中で効⽤を最⼤化する
ように配分
Distribute expense to maximize utility
under the budget constraint

6

Method
MDCEVモデル (MDCEV model)
選択した各カテゴリ(𝑘)に予算(𝑥! )を配分する．効⽤関数は以下の通り．
Allocate a budget to each selected category. The utility function is as follows.

(1)

𝛼"

𝛼"

𝑍!

選択肢固有属性や個⼈属性などの説明変数 (Explanatory variables such as choice-speciﬁc attributes and personal attributes)𝛽

パラメータ(parameters)𝜀!

ガンベル分布に従う確率項(Probability term following a Gumbel distribution)𝛾"

消費の増⼤に伴う効⽤の逓減度合いを表すパラメータ(Parameter representing diminishing utility with increasing consumption)𝛾" を同時に推定することは難しいため、𝛼" →0と固定し、𝛾" のみを推定。このとき(1)はSince it is too difficult to estimate 𝛼! 𝛾! at the same time, we presupposed 𝛼! →0 and only estimated 𝛾! . Then
(1) becomes7(2)Method
選択構造 Selection Structure
時間帯・⽀出項⽬ごとの９つの選択肢
9 alternatives for each time period and category

Morning-Food
Morning-Transportation
Morning-Souvenir
Afternoon-Food
Afternoon-Transportation
Afternoon-Souvenir
Night-Food
Night-Transportation
Night-Souvenir

Why not nested?
→Appendix
8

Detail of Utility Function
選択肢固有定数項
Alternative Specific Constant

個⼈属性 Personal Attributes
松⼭を初訪問visit Matsuyama for the first time3⼈以上のグループ
group of 3 or more

9

Estimation• 効⽤の減衰が，お⼟産代，飲⾷代，交通費の順に⼤きい
The decay of utility is faster for souvenirs, food and drinks, andtransportation costs, in that order→ 旅⾏先では交通費の増加をいとわない！
While travel, people are willing to pay more for transportation.

• 初めて訪れた⼈はお⼟産，交通にお⾦を使いやすい
First-time visitors are more likely to spend money on souvenirs andtransportation• 夜はお⼟産，交通費と⽐べて飲⾷費に使いやすい
In the evening, visitors are more likely to spend money on food anddrink compared to other categories

10Simulation
⾃由に使える3000円クーポンを付与した場合のカテゴリ別消費変化
Change in spending when a \3,000 coupon which can be used for every category is given.
2000
1800

仮定
発⾏したクーポンは全て利⽤され、クーポンの使⽤分だけ予算が増加
Assumption
All coupons issued would be used.
The budget would increase by theamount of coupons used.

消費額の増分Allocation(yen)

1600
1400
1200
1000
800
600
400
200
0
food

souvenirtranspo rtation

クーポン額の多くはsaturation effectが⼩さい交通費に使われたMost of the coupon amount was spent on transportation costs, which have a small saturation effect.
11Simulation
各カテゴリ限定の3000円クーポンを付与した場合のカテゴリ別消費額変化

Change in spending by category when a \3,000 coupon which is only available for each category is given.
Saturation effect が⼩さい
交通費の消費も微増
3000

2500

2500

2000

→飲⾷費の増分は3000円を下回る
2000

1500

Incremental food costs areless than \3,000.

1000
500

Allocation(yen)

消費額の増分Allocation(yen)

2500

3000

Allocation(yen)Allocation for transportation
increased which have a small
saturation effect.

3000

1500
1000
500

0souveniortranspo rtation

飲⾷費限定の3000円
クーポンを配布
Only for food

1500
1000
500

0
food

2000

0
foodsouveniortranspo rtation

⼟産代限定の3000円
クーポンを配布
Only for souvenir

foodsouveniortranspo rtation

交通費限定の3000円クーポンを配布
Only for transportation

12

Simulation
合計5000円分のクーポンをカテゴリ間で平等に配分されるように設計する
Design the allocations so that a total of 5,000-yen worth of coupons are distributed equally among
the categories
1000円単位で離散化し，配分のされ⽅を全通り検証

平等な配分（＝全てに5000/3 円ずつ）

Discretize in units of 1,000 yen and verify how theallocation is made in all streets.

からどれほど離れているかを評価ex)

Subsidy

Allocation

Food and drink

3000円

𝑥# 円

Souvenir

1000円

𝑥$ 円

Transportation

1000円

𝑥% 円

Evaluate how far away from equal
distribution (i.e., 5,000/3 yen each for all)%

Minimize ! 𝑥! −!&#5000313

Simulation
合計5000円分のクーポンをカテゴリ間で平等に配分されるように設計する(⾷事，お⼟産，交通)＝(2000円，2000円，1000円)で補助⾦を出すことが平等配分に最も近くなる(food，souvenir，transportation)＝(2000yen，2000yen，1000yen) is nearest to equal distribution

𝛾! が⼤きい交通費は，補助⾦の額が他より低くなる
Transportation costs with larger 𝛾! have lower subsidies than others

14References
Bhat CR. A multiple discrete‒continuous extreme value model: formulation and application to discretionary time-use
decisions. Transportation research.Part B: methodological. 2005;39(8):679-707.

Pinjari AR. A multiple discrete‒continuous nested extreme value (MDCNEV) model: Formulation and application tonon-worker activity time-use and timing behavior on weekdays. Transportation research.Part B: methodological.
2010;44(4):562-83.

北村拓也, 柳沼秀樹, 寺部慎太郎, 康楠. 活動パターンと時間配分の同時選択を考慮したアクティビティモデルの構築, 第 55
回⼟⽊計画学研究発表会・講演集. ⼟⽊計画学研究・講演集. 2017;55.

⽇本経済新聞. 2021年10⽉6⽇,朝刊,GoTo⾒直し、中⼩旅館⽀援を強化

⻫藤国交相が⽰唆.

Matsumura T, Saito H. Designing a tourism stimulus during the Covid-19 pandemic in Japan. RIETI Discussion PaperSeries. 21-E-012.

15

Appendix

当初はネスト構造を仮定したMDCNEVモデルを構築したが、スケールパラメーターが１に張り付いたため、誤差相関がないものとみなしMDCEVモデルとしたInitially, we constructed MDCNEV model because wepresupposed the situation as nested. Since the scaleparameter stuck to 1, the MDCEV model was assumed tohave no error correlation.

16Appendix
Simulation
各カテゴリ限定の3000円クーポンを付与した場合の時間帯別消費変化

1800

2000

1800

1600

1800

1600

1400

1600

1400

1000
800
600

1400

Allocation(yen)1200

Allocation(yen)Allovation(yen)Change in spending by time when a \3,000 coupon which is only available for each category is given.

1200
1000
800
600

1200
1000
800
600

400

400

400

200

200

200

00morning

afternoonnight0morning

afternoonnight

飲⾷費限定の3000円
クーポンを配布

⼟産代限定の3000円
クーポンを配布

Only for food

Only for souvenir

morning

afternoonnight

交通費限定の3000円
クーポンを配布
Only for transportation

17