Big data analytics for enrichment of rural area content tourism in Okhotsk sub-prefecture of Japan

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Big data analytics for enrichment of rural area content tourism in Okhotsk sub-prefecture of Japan Ali Bakdur, Fumito Masui, Michal Ptaszynski Kitami Institute of Technology, Dept. of Computer Science, Japan

HELLO! I m Ali Bakdur PhD. Student Kitami Institute of Technology

Data sources

Topics Positioning of Japan, Hokkaido and Okhotsk Study plan Discussion

Positioning of Japan, Hokkaido, and Okhotsk

百万 Population forecast 140 120 100 80 60 40 124.0999 97.07578 87.9761 59.4001 36.1238 37.67568 20 0 2020 2050 Population All Population 65+ Population 65- United Nations DESA / Population Division

The world's biggest economies Trillion USD United States China Japan Germany United Kingdom France India Italy Brazil Canada 4.4 3.4 2.9 2.4 2.1 1.8 1.8 1.6 0 5 10 15 20 World Bank data, 2015 11 18

Assessment of tourism value chain International Trade Centre (ITC)

United States Spain France United Kingdom Italy Germany Australia Turkey Austria Japan Korea Greece Canada Switzerland Mexico Netherlands Belgium Portugal Sweden Poland New Zealand Denmark Czech Republic Hungary Israel Norway Luxembourg Ireland Finland Slovenia Slovak Republic Chile Estonia Iceland Latvia 十億 Inbound tourism indicators (USD - 2014) 200 180 160 140 120 100 80 60 40 20 0 OECD statistics from Statistics Directorate Japan red

United States Germany United Kingdom France Canada Italy Australia Belgium Korea Netherlands Japan Norway Sweden Spain Switzerland Austria Denmark Mexico Poland Ireland Finland Czech Republic Turkey Portugal Israel New Zealand Luxembourg Greece Slovak Republic Chile Hungary Estonia Slovenia Iceland Latvia Billions Outbound tourism indicators (USD - 2014) 120 100 80 60 40 20 0 OECD statistics from Statistics Directorate Japan red

United States Germany United Kingdom Japan France Mexico Italy Australia Spain Canada Korea Turkey Austria Sweden Switzerland Netherlands Chile Norway New Zealand Greece Belgium Israel Portugal Denmark Finland Poland Hungary Czech Republic Ireland Slovak Republic Slovenia Luxembourg Latvia Iceland Estonia 十億 Domestic tourism indicators (USD - 2014) 900 800 700 600 500 400 300 200 100 0 OECD statistics from Statistics Directorate Japan red

Country Rankings (2014) : Absolute Contribution Travel & Tourism's Total Contribution to GDP (USD Billions) 1 United States 1,402.5 2 China 943.1 3 Germany 343.5 4 Japan 343.1 5 United Kingdom 309.8 WTTC Travel & Tourism Economic Impact

343,100,000,000 $ 7.5% of Japan s GDP in 2014

Domestic vs Foreign (2014) 8% 92% Foreign visitor spending WTTC Travel & Tourism Economic Impact Domestic spending

30.0 25.0 20.0 15.0 10.0 5.0 0.0 Japan GDP (% of total - 2014) 16.5 7.5 WTTC Travel & Tourism Economic Impact

40 35 30 25 20 15 10 Trend of People's Priorities in the Near Future 5 0 37.237.137 37.1 35.335.3 36.6 36.2 34.8 36.2 37.7 36.8 36.9 37.537.3 35.5 35.1 35.8 33.7 33.8 34.433.933.3 33.2 31.631.7 32.3 26.3 25.127.928 29.429.5 30.330 30.8 27.627.629 29 29.5 30.2 29.7 28.1 28.3 28.3 27.125.725.2 25.3 25.7 25 25.825.8 23.5 24.124.1 24.8 25 25.125.4 25.5 26.2 26.5 25.2 25.1 26.3 26.7 25.2 25.4 24.1 24.2 25.2 24.4 22.6 23.123.122.6 22.9 23.123.3 21.9 21.5 21.2 22 21.922 22.8 23.1 22.220.7 21.3 20.9 19.5 20.321.8 19.9 19.8 18.1 18.1 18.8 16 16.5 16 16.3 17.317.1 16.1 14.7 15.2 14.5 15.1 14.513.2 15.1 13.4 15 15.415.5 16.3 12.6 13 13.213.6 11 6.8 6.7 5.8 5.7 6.3 6.2 7.4 5.2 5.2 6 6.8 5.1 5.6 5.9 6.7 7.6 7.5 7.7 8.1 7.8 8.6 9.5 8 8.3 8.7 8.8 8.6 8.9 4.8 4.6 4.6 4.4 4 4.1 4.1 3.5 3.7 4 4.4 3.8 3.1 4 Leisure/recreation Home environment improvement Improved eating habits Perchase of consumer durables Public Opinion Survey on National Lifestyle

Top 10 Leisure Activities Potential Demand Mountaineering 7.6 8.3 Theater going 8.9 10.3 Auto camping 2.8 9.0 Picnicing, hiking and walking 10.5 20.1 Events and exhibitions 11.2 15.9 Barbecuing 11.8 20.8 Onsen (hot spring) and spa facilities 12.0 30.2 Passenger cruises 1.9 14.6 Domestic leisure travel 17.9 55.1 Overseas travel 12.8 30.2 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Participation Latent demand White Paper of Leisure 2015 (Japan Productivity Center)

百万 Trends in Domestic Travel (2015) 350 340 330 320 310 300 290 280 270 260 250 2010 2011 2012 2013 2014 2015 Overnight travel (person) Same-Day trip (person) Survey of Trend in Travel and Tourism Consumption (JTA)

Guest Nights in Japan (2015) 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 13,89 10,000 Guest-Night 7,668 6,006 5,386 4,224 4,263 3,217 2,506 2,089 1,295 Accommodation Survey (JTA)

Hokkaido is located on similar latitudes to major American and European cities.

Japan vs Hokkaido Place Hokkaido Japan Area (Km²) 83,424 377,970 Population 2015 5,431,000 127,110,000 Population Growth Rate 2015-0.53-0.12 Population Density 2015 69 341 Gross Domestic Production 2013 (Trillion YEN) 18.3 479.1 MLIT (Minister of Land, Infrastructure, Transport and Tourism)

The Hokkaido Comprehensive Development Plan

OKHOTSK SUB-PREFECTURE of HOKKAIDO, JAPAN

Population Census 140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 112,040 110,715 108,632 105,979 43,395 42,045 40,998 39,077 28,476 26,632 24,750 23,109 2000 2005 2010 2015 Abashiri-shi Kitami-shi Monbetsu-shi Statistics Japan, Ministry of Internal Affairs and Communications

6,000 5,000 4,000 3,000 2,000 1,000 0 Establishment s Existence (2014) 5,713 4,947 Abashiri-shi Kitami-shi Monbetsu-shi 1,936 1,701 1,296 1,196 766 846 235 100 254 173 Total Existing New Abolished Statistics Japan, Ministry of Internal Affairs and Communications

Accommodation, Food Service Business 1,000 948 842 800 600 400 200 348 311 235 201 0 Abashiri-shi Kitami-shi Monbetsu-shi 2006 2014 Statistics Japan, Ministry of Internal Affairs and Communications

120 100 80 60 40 20 0 KIT Foreign Students 112 101 102 108 93 71 74 73 79 85 88 90 96 89 68 57 60 56 56 49 38 23 27 25 26 29 10 16 1 3 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 Kitami Institute of Technology

China Malesia Indonesia Bangladesh Korea Cambodia Russia Tunisia Nicaragua Greece Iran Syria Finland Morocco Egypt Myanmar India Nigeria Poland Thai Mongolia Saudi Arabia Taiwan Vietnam USA Panama Algeria Peru Turkey KIT Foreign Student Distribution (2017) 60 50 40 30 20 10 0 50 7 2 4 10 7 5 1 1 1 1 Kitami Institute of Technology

Study Plan Better and Sustainable Tomorrow!

Big Data

Data science process

Model process steps 1. Determine problem 2. Collect and observe the data sets 3. Bayesian Approaches 4. Model & Algorithms 5. Monte Carlo Simulation 6. Accumulation of results 7. Action and Decisions

Problem statement Why Japanese domestic travel and tourism industry has been declining gradually since 1998? Proof of Concept

Data Years 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 Trillion Yen 26 28 31 33 32 31 31 30 29 28 27 28 26 25 23 21 20 19 21 21 21 21 import pandas tourism_df = pandas.read_csv('/resources/japands.csv') jpn_spending_year = tourism_df[tourism_df.cc == 'JPN'].groupby('Year').mean()

Expen./Year Regression line graph

Model & Sampling model = tourism_model(jpn_spending_year) mcmc = pymc.mcmc(model) mcmc.sample(50000, 10000, 1) lambda_1_samples = mcmc.trace('lambda_1')[:] lambda_2_samples = mcmc.trace('lambda_2')[:] tau_samples = mcmc.trace('tau')[:]

Posterior distributions of λ1, λ2 and τ.

Conclusions It s been seen that Japanese domestic travel and tourism is a significant sector. Needs to be recovered. Combining more random variables and development of the model is required. Contribution of Hokkaido Development Plan is essential. 2020 Tokyo Summer Olympics

THANKS!