Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
定性調査と定量分析をMixする、Mixed methodsの活用事例と有効性 #pmconf2021
Search
Maya Fujiwara
November 05, 2021
Technology
3.8k
1
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
定性調査と定量分析をMixする、Mixed methodsの活用事例と有効性 #pmconf2021
pmconf 2021発表資料
https://2021.pmconf.jp/sessions/JZdvrz5F
Maya Fujiwara
November 05, 2021
More Decks by Maya Fujiwara
See All by Maya Fujiwara
CSSフレームワークでつながる、デザイナーとフロントエンドエンジニア
mayalfs
0
94
Other Decks in Technology
See All in Technology
synctest時代のhttptest Go 1.27で変わるHTTPサーバテストの裏側 / go conference2026 synctest and httptest
budougumi0617
1
2.7k
Redmine 7.0で私が開発した新機能の狙いと背景
vividtone
1
160
越境するなら専門用語を使うな高校校歌 / If you wanna cross border, you shouldn't use jargon
vtryo
0
120
Adaptive Warehouse を今すぐ導入すべき理由と迷ったときの判断基準
__allllllllez__
0
200
Amazon Quick on DesktopがIAM Identity Centerで動かない理由
yukiogawa
0
170
アリアドネの糸と、20年ごとの建て替え ── 長尾真『電子図書館』を、伊勢で読み直す / Rereading Makoto Nagao’s "Electronic Library" in Ise
ykiyota
0
160
Slack上でインフラをトラブルシュートする! Agentic Platform Engineeringの第一歩
teru0x1
4
1.3k
生成AIのテナント制御とシャドーMCP対策 | AIを"止めずに"、情報を守る
yukun
0
160
株式会社シーエーシー エンジニア向け会社紹介資料
cac
0
57k
Podは生きているのにGoだけが落ちる:GOGCとGOMEMLIMITで追うInvisible OOM Killの謎
tkc66buzz
1
590
家のリアーキテクト・リファクタリング
suguruooki
0
120
Snowflakeのコスト最適化を支えるアーキテクチャ設計
ktatsuya
1
1.5k
Featured
See All Featured
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
194
17k
Producing Creativity
orderedlist
PRO
348
41k
A Tale of Four Properties
chriscoyier
163
24k
Data-driven link building: lessons from a $708K investment (BrightonSEO talk)
szymonslowik
1
1.3k
How to optimise 3,500 product descriptions for ecommerce in one day using ChatGPT
katarinadahlin
PRO
2
3.8k
Git: the NoSQL Database
bkeepers
PRO
432
67k
Noah Learner - AI + Me: how we built a GSC Bulk Export data pipeline
techseoconnect
PRO
0
430
Optimizing for Happiness
mojombo
378
71k
The Impact of AI in SEO - AI Overviews June 2024 Edition
aleyda
6
1.2k
Everyday Curiosity
cassininazir
0
310
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
230
23k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
Transcript
ఆੑௐࠪͱఆྔੳΛMix͢Δ Mixed methodsͷ׆༻ࣄྫͱ༗ޮੑ -*/&גࣜձࣾ౻ݪຑ
ࣗݾհ ౻ݪຑ LINEΞϓϦͷνϟοτͷػೳͷاըɾվળΛ୲ 2018 UXσβΠφʔͱͯ͠ೖࣾ 2020 LINEاըࣨʹҟಈ → UXσβΠφʔ͔࣌ΒҾ͖ଓ͖ɺఆੑௐ͕ࠪಘҙͳPMͰ͢ɻ
·ͣɺMixed methods ʹ͍ͭͯ 🤔
.JYFENFUIPETͱ ఆੑɾఆྔͷॴΛ݁ͼ͚ͭͯϦαʔνΛ͢Δ͜ͱͰɺΑΓૣ͘ɾਂ͘ɾਖ਼֬ʹཧղ͢Δ͜ͱ͕ Ͱ͖Δௐࠪઃܭํ๏Ͱ͢ ྫ͑ɿ • ϢʔβʔΠϯλϏϡʔͰൃݟͨ͠ΠϯαΠτ͕ͲΕ͘Β͍Ұൠతͳͷͳ ͷ͔ΛఆྔతͳΞϯέʔτͰ֬ೝ͢Δ • ఆྔੳͰग़͖ͯͨϢʔβʔߦಈ͕ͲͷΑ͏ͳίϯςΫετͷதͰى͖ͯ ͍Δͷ͔ΛΠϯλϏϡʔͰ֬ೝ͢Δ
• ΞϯέʔτͰ"ͱ͑ͨϢʔβʔΛநग़͠ɺͦͷϢʔβʔͷߦಈϩάΛ ੳ͢Δ Auther/publisher Sam Ladner, PhD https://www.samladner.com/
.JYFENFUIPETͱ ఆྔੳ ఆੑௐࠪ Ωʔϫʔυ ԋ៷తࢥߟɺดܕɺਖ਼֬ੑɺ࣮ূओٛ ؼೲతࢥߟɺ։์ܕɺίϯςΫετɺղऍओٛ ڧΈ ҰൠԽنଇੑΛݟग़͢ػձΛఏڙ͢Δ ݸਓͷܦݧʹؔ͢Δਂ͍ࢹΛఏڙ͢Δ ௐࠪऀ͕࣋ͨͳ͍৽ͨͳࢹΛࣔࠦ͢Δ
ऑΈ ར༻ՄೳͳϩάͷൣғͰͷΈͷੳͱͳΔ ͳͥͦͷߦಈ͕ى͖ͨͷ͔Θ͔Βͳ͍ நग़ͷ࣠Ծઆʹجͮͨ͘Ίɺൃݟ͕ظ ͞Ε͍ͯΔߦಈͷཱূɾઆ໌ͱͳΔ σʔλ͕ۃΊͯओ؍తͰɺج४͕ଘࡏ͠ͳ͍ ੍͕ݶ͞ΕΔ͜ͱʹΑΓɺҰൠԽՄೳੑ͕ ੍ݶ͞ΕΔ ੳͷεςοϓͰ͞ΒʹੳऀͷόΠΞε͕ ͔͔Δ ମܥతʹֶͿͱఆྔɾఆੑͷҧ͍ΛΑΓਂ͘ཧղͰ͖ɺޮՌతʹ.JYͰ͖ΔΑ͏ʹͳΔ Auther/publisher Sam Ladner, PhD https://www.samladner.com/
.JYFENFUIPETͱ ఆྔੳ ఆੑௐࠪ Ωʔϫʔυ ԋ៷తࢥߟɺดܕɺਖ਼֬ੑɺ࣮ূओٛ ؼೲతࢥߟɺ։์ܕɺίϯςΫετɺղऍओٛ ڧΈ ҰൠԽنଇੑΛݟग़͢ػձΛఏڙ͢Δ ݸਓͷܦݧʹؔ͢Δਂ͍ࢹΛఏڙ͢Δ ௐࠪऀ͕࣋ͨͳ͍৽ͨͳࢹΛࣔࠦ͢Δ
ऑΈ ར༻ՄೳͳϩάͷൣғͰͷΈͷੳͱͳΔ ͳͥͦͷߦಈ͕ى͖ͨͷ͔Θ͔Βͳ͍ நग़ͷ࣠Ծઆʹجͮͨ͘Ίɺൃݟ͕ظ ͞Ε͍ͯΔߦಈͷཱূɾઆ໌ͱͳΔ σʔλ͕ۃΊͯओ؍తͰɺج४͕ଘࡏ͠ͳ͍ ੍͕ݶ͞ΕΔ͜ͱʹΑΓɺҰൠԽՄೳੑ͕ ੍ݶ͞ΕΔ ੳͷεςοϓͰ͞ΒʹੳऀͷόΠΞε͕ ͔͔Δ ମܥతʹֶͿͱఆྔɾఆੑͷҧ͍ΛΑΓਂ͘ཧղͰ͖ɺޮՌతʹ.JYͰ͖ΔΑ͏ʹͳΔ Auther/publisher Sam Ladner, PhD https://www.samladner.com/ ࠓɺ͜ͷຊͷ༰Λ۷ΓԼ͛Δͱ͍͏ΑΓɺ .JYFENFUIPETͱ͍͏ݴ༿Λελʔτͱ͠ɺ ͲͷΑ͏ʹνʔϜɾϓϩδΣΫτʹྑ͍Өڹ͕͔͋ͬͨΛ͓͍ͨ͠͠ͱࢥ͍·͢
ࢲͱ.JYFENFUIPETͷग़ձ͍ ϓϩδΣΫτνʔϜ 1. %BUB TDJFOUJTU 1. σʔλαΠΤϯςΟετ ։ൃɾσβΠϯ ͭΑͭΑ
ࢲͱ.JYFENFUIPETͷग़ձ͍ .F ͭΑͭΑσʔλαΠΤϯςΟετ 1. %BUB 4DJFOUJTU 1. %BUB 4DJFOUJTU ࠓྠಡձͷޙɺिʹҰܧଓతʹू·ͬͯࡶஊˍֶशΛਐΊ͍ͯ·͢
࠷ۙ.JYFENFUIPET͍ͬͯ͏ຊ ʹͳͬͯ·͢ͶɺؾʹͳΔ ໘നͦ͏Ͱ͢ΑͶ ಡΜͰΈΑ͏͔ͳ
ࢲͱ.JYFENFUIPETͷग़ձ͍ .F ͭΑͭΑσʔλαΠΤϯςΟετ 1. %BUB 4DJFOUJTU 1. %BUB 4DJFOUJTU ࠓྠಡձͷޙɺिʹҰܧଓతʹू·ͬͯࡶஊˍֶशΛਐΊ͍ͯ·͢
͔͔ͤͬͩ͘Βྠಡձʹ ͠·͢ʁ ʢ৯͍ؾຯͰʣ͍͍Ͱ͢ ͶʂΓ·͠ΐ͏ʂʂ
ࢲͱ.JYFENFUIPETͷग़ձ͍ .F ͭΑͭΑσʔλαΠΤϯςΟετ 1. %BUB 4DJFOUJTU 1. %BUB 4DJFOUJTU ࠓྠಡձͷޙɺिʹҰܧଓతʹू·ͬͯࡶஊˍֶशΛਐΊ͍ͯ·͢
͜Εσʔλৄ͍͠ͱɺ ͬͱίϥϘϨʔγϣϯΛ ߴΊΔΊͬͪΌྑ͍ νϟʔϯεʂʂ
ʢࢲ͕ߟ͑Δʣ.JYFENFUIPET͕ͨΒ͢༗ޮੑ ͖͋ΒΊͣɺຊ࣭తͳՁΛνʔϜͰٻ͢ΔͨΊʹศརͳڞ௨ݴޠ ϝΠϯσʔλநग़ͱϦαʔνΛಘҙͱ͢Δϝϯόʔؒ .JYFENFUIPETલ .JYFENFUIPETΛڞ௨ݴޠͱͯ࣋ͬͨ͠ޙ • ఆੑɾఆྔͷௐ͕ࠪผͷϑΣʔζతஅ͞ΕΔ͜ͱ͕ଟ͘ɺͦΕͧΕͷௐࠪͰΘ͔Βͳ͍ͱ ͜Ζ͖͋ΒΊ͍ͯͨ •
ʮ͜Ε͔Βͳ͍Ͱ͢ͶʯͰऴΘΒͳ͘ͳΓɺʮ͓͜͜ئ͍Ͱ͖·͔͢ʁʯͱύεΛૹΔΑ͏ʹͳͬͨ • खஈΛબͣҰͭͷతͷͨΊʹνʔϜͰ՝ՁΛٻ͠ɺ৽ͨͳ݁ʹḷΓண͚ΔΑ͏ʹͳͬͨ • νʔϜ։ൃͷָ͠͞Λ࠷େԽͰ͖Δ
Mixed methods ཱ͕ͬͨ ࣄྫΛհ͠·͢ 🤔
ϓϩδΣΫτͷਐߦ .JYFENFUIPET
None
-*/&-BCTͷػೳͰ͢ɻͥͻࢼͯ͠Έ͍ͯͩ͘͞ʂ
ղܾ͍ͨ͠՝ -*/&ΛΞΫςΟϒʹ͑͏΄ͲɺτʔΫϦετͷະಡϝοηʔδͷཧ͕͘͠ͳΔ ະಡ999+͕ৗଶԽ!!
ղܾ͍ͨ͠՝ ຊʹେͳ༑ͩͪɾՈͱͷ ৽ணτʔΫ͕ຒΕͯ͠·͏
ղܾ͍ͨ͠՝ τʔΫΛΧςΰϦʔ ͝ͱʹ͚Δ
ղܾ͍ͨ͠՝ "OESPJE൛Λ݄ɺJ04൛Λ݄ʹϦϦʔε
"OESPJE൛Λ݄ɺJ04൛Λ݄ʹϦϦʔε ղܾ͍ͨ͠՝ Ұఆ࣌ؒτʔΫλϒ͔Β ΕͨΒɺʦͯ͢ʧΛ։͘ ༷Ͱ৽ணϝοηʔδΛ· ͱΊͯΈ͘͢
ϦϦʔε &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF ͞ΒͳΔఆྔੳ &QJTPEF ఆྔੳͰޮՌݕূ
ϓϩδΣΫτͷਐߦ
&QఆྔੳͰޮՌݕূ 🤔
&QఆྔੳͰޮՌݕূ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ 8% ͯ͢ 85% →
݁Ռɿ ʦͯ͢ʧϑΥϧμʔͰϝοηʔδ֬ೝ͕ѹతʹଟ͔ͬͨ ϑΥϧμผϝοηʔδ֬ೝ ఆɿϢʔβʔ ʦ༑ͩͪʧʦάϧʔϓʧϑΥϧμʔͰϝοηʔδΛ֬ೝ͢ΔΑ͏ʹͳΔͩΖ͏
&QఆྔੳͰޮՌݕূ ݁ՌɿϑΥϧμʔػೳΛ͜ͷ··ਖ਼ࣜϦϦʔε͢ΔͱϏδωεʹѱӨڹΛ༩͑ΔՄೳੑ͕ݟ͑ͨ 🥺
&QఆྔੳͰޮՌݕূ Ϣʔβʔʦ༑ͩͪʧʦάϧʔϓʧϑΥϧμʔͰϝοηʔδ Λ֬ೝ͢Δ͕ͣɺʦͯ͢ʧ͕ѹతʹଟ͔ͬͨ ϏδωεʹѱӨڹΛ༩͑ͦ͏ͩ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁ → ͦ͜·ͰϦεΫΛͱͬͯΔ͜ͱͳͷʁ
&QఆྔੳͰޮՌݕূ Ϣʔβʔʦ༑ͩͪʧʦάϧʔϓʧϑΥϧμʔͰϝοηʔδ Λ֬ೝ͢Δ͕ͣɺʦͯ͢ʧϑΥϧμʔͰͷ֬ೝ͕ѹత ʹଟ͔ͬͨ τʔΫλϒʹؔΘΔ༷ʑͳϏδωεεςʔΫϗϧμʔ͕͍Δ தͰɺҰ෦KPIʹӨڹ͕͋Γͦ͏ͳੳ݁Ռ͕͋ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁ → ͦ͜·ͰϦεΫΛͱͬͯΔ͜ͱͳͷʁ
͜ͷ࣌Ͱɺࣾੈ͔ͳΓωΨςΟϒ ʢ-BCTܧଓ͕ਫ਼ҰഋɻػೳͷΫϩʔζࢹʹೖΔɾɾɾʣ
&QఆྔੳͰޮՌݕূ ͨͩɺଞʹؾʹͳΔσʔλ͕͋Γ·ͨ͠
&QఆྔੳͰޮՌݕূ ػೳΛ0/͢ΔϢʔβʔͱͯଟ͍ ݄࣌Ͱ(MPCBMͰສϢʔβʔɻ5BJXBOͩͱ͍ۙϢʔβʔ͕͜ͷػೳΛ͍ͬͯΔɻ 0 1750 3500 5250 7000 2020/5 2020/12
2021/6 now "OESPJESFMFBTF J04SFMFBTF ສϢʔβʔ
&QఆྔੳͰޮՌݕূ -*/&্ͷ༑͕ͩͪଟ͍ਓ΄Ͳɺ͍ଓ͚Δʹ͋Δ Ϣʔβʔ͝ͱͷ-*/&্ͷ༑ͩͪͷ Ұϲ݄ҎʹػೳΛ0/ͷ··ɺ͍ଓ͚Δਓͷׂ߹ 91% 93% 95% 96% 98% 0-29ਓ
30-59ਓ 60-89ਓ 90ਓҎ্ 97% 96% 94% 92% େྔͷϝοηʔδΛड͚औΓɺఆͨ͠՝Λ๊͕͑ͪͳϢʔβʔ
&QఆྔੳͰޮՌݕূ 4/4Ͱͷڹ͕ͱͯྑ͍
&QఆྔੳͰޮՌݕূ 4/4Ͱͷڹ͕ͱͯྑ͍
&QఆྔੳͰޮՌݕূ ૬͢Δσʔλ ʦͯ͢ʧϑΥϧμʔͰͷ֬ೝ͕ѹతʹଟ͔ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁʁ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ
8% ͯ͢ 85% ػೳΛ0/͢ΔϢʔβʔͱͯଟ͘ɺ ఆͨ͠՝ͷ͋ΔϢʔβʔ͍ଓ͚͍ͯΔ 1750 3500 5250 7000 2020/5 2020/12 2021/6 now ສ
ϦϦʔε .JYFENFUIPET &QJTPEF ఆྔੳͰޮՌݕূ &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF
͞ΒͳΔఆྔੳ
&QఆੑௐࠪΛ࣮ࢪ ͦΕͧΕͷௐࠪख๏ͷಛੑ ఆྔੳ ఆੑௐࠪ Ωʔϫʔυ ԋ៷తࢥߟɺดܕɺਖ਼֬ੑɺ࣮ূओٛ ؼೲతࢥߟɺ։์ܕɺίϯςΫετɺղऍओٛ ڧΈ ҰൠԽنଇੑΛݟग़͢ػձΛఏڙ͢Δ ݸਓͷܦݧʹؔ͢Δਂ͍ࢹΛఏڙ͢Δ
ௐࠪऀ͕࣋ͨͳ͍৽ͨͳࢹΛࣔࠦ͢Δ ऑΈ ར༻ՄೳͳϩάͷൣғͰͷΈͷੳͱͳΔ ͳͥͦͷߦಈ͕ى͖ͨͷ͔Θ͔Βͳ͍ நग़ͷ࣠Ծઆʹجͮͨ͘Ίɺൃݟ͕ظ͞Ε͍ͯΔߦ ಈͷཱূɾઆ໌ͱͳΔ σʔλ͕ۃΊͯओ؍తͰɺج४͕ଘࡏ͠ͳ͍ ੍͕ݶ͞ΕΔ͜ͱʹΑΓɺҰൠԽՄೳੑ੍͕ݶ͞ΕΔ ੳͷεςοϓͰ͞ΒʹੳऀͷόΠΞε͕͔͔Δ
ʦͯ͢ʧϑΥϧμʔͰͷ֬ೝ͕ѹతʹଟ͔ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁʁ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ 8% ͯ͢
85% &QఆੑௐࠪΛ࣮ࢪ ૬͢Δσʔλ ػೳΛ0/͢ΔϢʔβʔͱͯଟ͘ɺ ఆͨ͠՝ͷ͋ΔϢʔβʔ͍ଓ͚͍ͯΔ 1750 3500 5250 7000 2020/5 2020/12 2021/6 now ສ ϢʔβʔԿΛظͯ͠ػೳΛ0/ͨ͠ʁ ͬͨ݁Ռɺظ௨Γͩͬͨʁ ར༻ҙߴͦ͏ͳͷʹɺʦͯ͢ʧλοϓ͕ଟ͍ͷͳͥʁ
ʦͯ͢ʧϑΥϧμʔͰͷ֬ೝ͕ѹతʹଟ͔ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁʁ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ 8% ͯ͢
85% &QఆੑௐࠪΛ࣮ࢪ ૬͢Δσʔλ ػೳΛ0/͢ΔϢʔβʔͱͯଟ͘ɺ ఆͨ͠՝ͷ͋ΔϢʔβʔ͍ଓ͚͍ͯΔ 1750 3500 5250 7000 2020/5 2020/12 2021/6 now ສ ݁Λग़͢ͷ·ͩૣ͍ɻ ʹఆੑௐࠪΛ࣮ࢪ͠Α͏ ૬͢ΔϢʔβʔߦಈͷʮͳͥʯΛಛఆ͍ͨ͠
&QఆੑௐࠪΛ࣮ࢪ 🤔
&QఆੑௐࠪΛ࣮ࢪ ɾλΠɾຊϢʔβʔ໊ΛରʹΠϯλϏϡʔ࣮ࢪ • ಉηάϝϯτϢʔβʔਓΛηοτʹYύλʔϯͷ ΠϯλϏϡʔ • ͍ଓ͚͍ͯΔਓɺ͏͜ͱΛΊͨਓ
&QఆੑௐࠪΛ࣮ࢪ ԿΛظ͍͔ͯͨ͠ʁ ʦ༑ͩͪʧͱʦLINEެࣜΞΧϯτʧΛ ͚ͯཧͰ͖Δ τʔΫϧʔϜ͕ཧͰ͖Δ ϢʔβʔτʔΫϧʔϜΛ༏ઌͰཧ͍ͨ͠ͱࢥ͍ͬͯͯɺҙਤ௨Γ
&QఆੑௐࠪΛ࣮ࢪ ԿΛظ͍͔ͯͨ͠ʁ ͬͯɺظ௨Γ͔ͩͬͨʁ Ҡಈ͕໘ͳͷͰɺ݁ہʦͯ͢ʧ͔͠ ։͍͍ͯͳ͍ ʦ༑ͩͪʧͱʦLINEެࣜΞΧϯτʧΛ ͚ͯཧͰ͖Δ τʔΫϧʔϜ͕ཧͰ͖Δ ظͱҧͬͨ
ʦ༑ͩͪʧPS<άϧʔϓ>ΛσϑΥϧτͰ։͍͓͖͍ͯͨ ࠷ޙʹ։͍ͨϑΥϧμʔΛ࣍ΞΫηεͨ࣌͠ʹ։͖͍ͨ ϢʔβʔࣗͷҙͷϑΥϧμʔΛ։͍͍͍ͯͨͱࢥ͍ͬͯΔ͕ɺ ʦͯ͢ʧʹΔ༷͕ͦͷߦಈΛ੍ݶ͍ͯ͠Δ
&QఆੑௐࠪΛ࣮ࢪ ૬͢Δσʔλ “ͯ͢”ϑΥϧμͰͷ֬ೝ͕ѹతʹଟ͔ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁʁ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ
8% ͯ͢ 85% ػೳΛ0/͢ΔϢʔβʔͱͯଟ͘ɺ ఆͨ͠՝ͷ͋ΔϢʔβʔ͍ଓ͚͍ͯΔ 1750 3500 5250 7000 2020/5 2020/12 2021/6 now ສ
ʦͯ͢ʧϑΥϧμʔͰͷ֬ೝ͕ѹతʹଟ͔ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁʁ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ 8% ͯ͢
85% &QఆੑௐࠪΛ࣮ࢪ ૬͢Δσʔλ ͜ͷՁΛϢʔβʔ࣮ࡍʹײ͍ͯͯ͡ɺҙਤʹԊͬͨར༻Λ͍ͯ͠Δ ʮେͳτʔΫΛݟಀ͞ͳ͍ʯ ػೳΛ0/͢ΔϢʔβʔͱͯଟ͘ɺ ఆͨ͠՝ͷ͋ΔϢʔβʔ͍ଓ͚͍ͯΔ 1750 3500 5250 7000 2020/5 2020/12 2021/6 now ສ
૬͢Δσʔλ ػೳΛ0/͢ΔϢʔβʔͱͯଟ͘ɺ ఆͨ͠՝ͷ͋ΔϢʔβʔ͍ଓ͚͍ͯΔ 1750 3500 5250 7000 2020/5 2020/12
2021/6 now ສ ʦͯ͢ʧͰͷϝοηʔδ֬ೝϢʔβʔ͕ ΜͰ͍ΔߦಈͰͳ͍ Ϣʔβʔڧ੍తʹʦͯ͢ʧʹΒ͞ΕΔͨΊ ͦ͜ͰϝοηʔδΛ֬ೝ͍ͯ͠Δ͕ɺ͜ͷ༷Λมߋ͢Δͱσʔλ ͕େ͖͘มΘΔՄೳੑ͕ߴ͍ɻ ʢʦͯ͢ʧ͔͠Θͳ͍ʹػೳʹՁ͕ͳ͍ͱࢥ͍͜ΜͰ͍ͨʣ &QఆੑௐࠪΛ࣮ࢪ ʦͯ͢ʧϑΥϧμʔͰͷ֬ೝ͕ѹతʹଟ͔ͬͨ → ͜Εͬͯຊʹ՝Λղܾͯ͠Δͷʁʁ ެࣜ 3% άϧʔϓ 4% ༑ͩͪ 8% ͯ͢ 85%
&QఆੑௐࠪΛ࣮ࢪ ωΨςΟϒͳӨڹݒ೦͕͋ΔϏδωεαΠυͷਓ ͱͯྑ͍ػೳͩͱࢥ͏ɻظతʹϏδωεઢͰ՝͕͋ͬͯɺϢʔβʔͷ͍͢͞Λߟ ͑ΔͱඞཁෆՄܽͩ͠ɺͦΕظతʹϏδωεʹϙδςΟϒʹಇͣͩ͘ͱࢥ͏ɻؔऀ ͷઆ໌ͬͪ͜ͰΔ͔ΒɺͳΜͱ͔ͦͷՁΛূ໌ͯ͠΄͍͠ɻ
&QJTPEF ఆྔੳͰޮՌݕূ &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF ͞ΒͳΔఆྔੳ ϦϦʔε
.JYFENFUIPET .JYFENFUIPETͷߟ͑ํ͕߹ྲྀ ఆྔੳͷΓͳ͍෦Λ͞Βʹਂ΅Γɺ શମ૾Λཧղ͠Α͏ͱ͍͏ํੑʹ͔ͬͨ
&Q͞ΒͳΔఆྔੳ 🤔
&Q͞ΒͳΔఆྔੳ ՝ɿະಡ ͕ৗଶԽͯ͠ɺຊʹେͳ༑ͩͪɺՈͱͷ৽ணτʔ Ϋ͕ຒΕͯ͠·͏ τʔΫϑΥϧμʔ͕՝Λղܾ͢Δͱɿ ະಡόοδΧϯτ͕ݮΔˡ͜Εσʔλͱͯ͠औ͍ͬͯͳ͍ • ະಡΛফԽ͢Δ׆ಈʢ/ফ͠ʣΑ͋͘ΔϢʔβʔߦಈͷͨ Ίɺະಡ͕ݮ͍ͬͯͨͱͯ͠ɺͦΕ՝Λղܾ͍ͯͯ͜͠ ͷػೳʹՁ͕͋Δͱݴ͍Εͳ͍
• ϝοηʔδ͕ཧͰ͖ͯɺେࣄͳϝοηʔδΛݟಀ͞ͳ͘ͳΔͱɺ Կ͕ى͖Δ͔ʁ Ͳ͏ͨ͠ΒՁΛଌΕΔ͔ ະಡόοδ େͳ৽ணτʔΫͷطಡϦʔυλΠϜʁ ϝοηʔδͷૹ৴ τʔΫλϒࡏ࣌ؒ ৽ணϝοηʔδ͕ དྷ͔ͯΒ֬ೝ͢Δ ϦʔυλΠϜ ͜ͷػೳʹՁ͕͋Γ·͢ʂͱݴ͍ΕΔࢦඪ͕΄͍͠ ఆੑௐࠪͷ݁ՌΛݟΔݶΓɺͲ͔͜ʹ͋Δͣʂ
&Q͞ΒͳΔఆྔੳ ՝ΛτʔΫϑΥϧμʔͰղܾ͢Δͱ Ͳ͏ͨ͠ΒՁΛଌΕΔ͔ τʔΫλϒࡏ࣌ؒ ৽ணϝοηʔδͷطಡ ϦʔυλΠϜ ະಡόοδ େͳ৽ணτʔΫͷ طಡϦʔυλΠϜʁ
• ະಡόοδΧϯτ͕ݮΔ ˡͰ͜Εσʔλͱͯ͠औ͍ͬͯͳ͍ • εϫΠϓطಡͳͲະಡΛফԽ͢Δ׆ಈҰൠతͳͨ Ίɺྫ͑ະಡόοδ͕ݮ͍ͬͯͨͱͯ͠ɺͦΕ ͜ͷػೳʹՁ͕͋Δͱݴ͍Εͳ͍ େͳ৽ண͔Ͳ͏͔ͳΜͯΘ͔Δʁ
&Q͞ΒͳΔఆྔੳ ՝ɿະಡ ͕ৗଶԽͯ͠ɺຊʹେͳ༑ͩͪɺՈͱͷ৽ணτʔ Ϋ͕ຒΕͯ͠·͏ τʔΫϑΥϧμʔ͕՝Λղܾ͢Δͱɿ ະಡόοδΧϯτ͕ݮΔˡ͜Εσʔλͱͯ͠औ͍ͬͯͳ͍ • ະಡΛফԽ͢Δ׆ಈʢ/ফ͠ʣΑ͋͘ΔϢʔβʔߦಈͷͨ Ίɺະಡ͕ݮ͍ͬͯͨͱͯ͠ɺͦΕ՝Λղܾ͍ͯͯ͜͠ ͷػೳʹՁ͕͋Δͱݴ͍Εͳ͍
• ϝοηʔδ͕ཧͰ͖ͯɺେࣄͳϝοηʔδΛݟಀ͞ͳ͘ͳΔͱɺ Կ͕ى͖Δ͔ʁ Ͳ͏ͨ͠ΒՁΛଌΕΔ͔ ະಡόοδ େͳ৽ணτʔΫͷطಡϦʔυλΠϜʁ ϝοηʔδͷૹ৴ τʔΫλϒࡏ࣌ؒ ৽ணϝοηʔδ͕ དྷ͔ͯΒ֬ೝ͢Δ ϦʔυλΠϜ 1. %BUB 4DJFOUJTU ͋͋Ͱͳ͍ ͜͏Ͱͳ͍ ϝοηʔδ͕ཧͰ͖ͯɺେࣄͳϝοηʔδΛݟಀ͞ͳ͘ͳΔͱɺԿ͕ى͖ΔͩΖ͏ʁ ୯७ʹɺίϛϡχέʔγϣϯ͕૿͑ΔͷͰʁ
&Q͞ΒͳΔఆྔੳ ՝ɿະಡ ͕ৗଶԽͯ͠ɺຊʹେͳ༑ͩͪɺՈͱͷ৽ணτʔ Ϋ͕ຒΕͯ͠·͏ τʔΫϑΥϧμʔ͕՝Λղܾ͢Δͱɿ ະಡόοδΧϯτ͕ݮΔˡ͜Εσʔλͱͯ͠औ͍ͬͯͳ͍ • ະಡΛফԽ͢Δ׆ಈʢ/ফ͠ʣΑ͋͘ΔϢʔβʔߦಈͷͨ Ίɺະಡ͕ݮ͍ͬͯͨͱͯ͠ɺͦΕ՝Λղܾ͍ͯͯ͜͠ ͷػೳʹՁ͕͋Δͱݴ͍Εͳ͍
• ϝοηʔδ͕ཧͰ͖ͯɺେࣄͳϝοηʔδΛݟಀ͞ͳ͘ͳΔͱɺ Կ͕ى͖Δ͔ʁ Ͳ͏ͨ͠ΒՁΛଌΕΔ͔ ະಡόοδ େͳ৽ணτʔΫͷطಡϦʔυλΠϜʁ ϝοηʔδͷૹ৴ τʔΫλϒࡏ࣌ؒ ৽ணϝοηʔδ͕ དྷ͔ͯΒ֬ೝ͢Δ ϦʔυλΠϜ ͦͦࢲͨͪͷϛογϣϯͬͯϢʔβʔʹ ΑΓָ͘͠ศརͳίϛϡχέʔγϣϯΛఏڙ͢Δ͜ͱͩͬͨʂ ʢ͍ΖΜͳࢦඪʹṆΕͯݟࣦ͍͔͚ͯͨɾɾɾʣ
&Q͞ΒͳΔఆྔੳ -*/&νϟοτͷҰ൪େ͖ͳՁ ʮϝοηʔδૹ৴ʯΛΈͯΈΑ͏ ະಡόοδ େͳ৽ணτʔΫͷ طಡϦʔυλΠϜʁ τʔΫλϒࡏ࣌ؒ ৽ணϝοηʔδͷطಡ
ϦʔυλΠϜ ʙഎਫͷਞʙ ΑΓָͯ͘͠ศརͳ ίϛϡχέʔγϣϯ ϝοηʔδͷૹ৴
ϔϏʔϢʔβʔͷτʔΫϑΥϧμʔར༻։࢝ϲ݄Ͱͷϝοηʔδૹ৴ͷมԽ &Q͞ΒͳΔఆྔੳ ϝοηʔδɺཧ༝͕͋ͬͯ ૹΔίϛϡχέʔγϣϯ׆ಈ ͷͨΊɺ6*มߋͰϝοηʔδ ͕༗ҙʹ૿͑ͨʢมԽ͕ ͋ͬͨʣલྫগͳ͍Ͱ͢ɻ
&QఆྔੳͰޮՌݕূ 4/4Ͱͷڹ͕ͱͯྑ͍ շదʹͳͬͯɺϝοηʔδΛ ΑΓૹͬͯ͘ΕΔΑ͏ʹ ͳͬͨ շదʹͳͬͯɺΑΓଟ͘ͷϝοηʔδΛૹͬͯ͘ΕΔΑ͏ʹͳͬͨ
ٞͷํੑʹมԽ τʔΫϑΥϧμʔϔϏʔϢʔβʔ͚ʹ -*/&ͷຊ࣭తͳՁʮίϛϡχέʔγϣϯྔʯΛ૿͢ػೳͰ͋Δ ˠػೳΛΩʔϓͯ͠͞ΒͳΔվળΛݕ౼͍ͯ͘͠👏👏👏
&QJTPEF ఆྔੳͰޮՌݕূ &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF ͞ΒͳΔఆྔੳ ϦϦʔε
.JYFENFUIPET ػೳͷຊ࣭తͳՁͷ࠶ఆٛɾ࠶֬ೝ Λ͢Δ͜ͱ͕Ͱ͖ͨ
ࣄྫΛ௨ͯ͠Mixed methods ͕ ͨΒͨ͠ޮՌͷ·ͱΊ 🤔
&QJTPEF ఆྔੳͰޮՌݕূ &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF ͞ΒͳΔఆྔੳ ϦϦʔε
.JYFENFUIPET ͜ͷஈ֊ͰௐࠪྃɺػೳࣗମͷΫ ϩʔζΛݕ౼ɺͱ͍͏ྲྀΕʹͳ͍ͬͯ ͓͔ͯ͘͠ͳ͔ͬͨ
&QJTPEF ఆྔੳͰޮՌݕূ &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF ͞ΒͳΔఆྔੳ ϦϦʔε
.JYFENFUIPET .JYFENFUIPETͷߟ͑ํ͕߹ྲྀ ఆྔੳͷΓͳ͍෦Λ͞Βʹਂ΅Γɺ શମ૾Λཧղ͠Α͏ͱ͍͏ํੑʹ͔ͬͨ
&QJTPEF ఆྔੳͰޮՌݕূ &QJTPEF ఆੑௐࠪΛ࣮ࢪ &QJTPEF ͞ΒͳΔఆྔੳ ϦϦʔε
.JYFENFUIPET ػೳͷຊ࣭తͳՁͷ࠶ఆٛɾ࠶֬ೝ Λ͢Δ͜ͱ͕Ͱ͖ͨ
վΊͯɺMixed methods ͱ 🤔
• ʮ͜Ε͔Βͳ͍Ͱ͢ͶʯͰऴΘΒͳ͘ͳΓɺʮ͓͜͜ئ͍Ͱ͖·͔͢ʁʯͱύεΛૹΔΑ͏ʹͳͬͨ • खஈΛબͣҰͭͷతͷͨΊʹνʔϜͰ՝ՁΛٻ͠ɺ৽ͨͳ݁ʹḷΓண͚ΔΑ͏ʹͳͬͨ • νʔϜ։ൃͷָ͠͞Λ࠷େԽͰ͖Δ ʢࢲ͕ߟ͑Δʣ.JYFENFUIPET͕ͨΒ͢༗ޮੑ ͖͋ΒΊͣɺຊ࣭తͳՁΛνʔϜͰٻ͢ΔͨΊʹศརͳڞ௨ݴޠ ओʹɺσʔλநग़ͱϦαʔνΛಘҙͱ͢Δϝϯόʔؒ
࠶ܝ .JYFENFUIPETલ .JYFENFUIPETΛڞ௨ݴޠͱͯ࣋ͬͨ͠ޙ • ఆੑɾఆྔͷௐ͕ࠪผͷϑΣʔζతஅ͞ΕΔ͜ͱ͕ଟ͘ɺͦΕͧΕͷௐࠪͰΘ͔Βͳ͍ͱ ͜Ζ͖͋ΒΊ͍ͯͨ
"QQFOEJY͙͢Ͱ͖Δ͓͢͢Ίεςοϓ .JYFENFUIPETͱʁ֓ཁΛΈΜͳͰಡΜͰΈΔ • ͓͢͢ΊBNBUBQMVTᖒ͞Μͷ/PUFͰ͢ IUUQTOPUFDPNIJSPLP@OP[BXBOOGDEG ҰਓͻͱΓͷࣝΛɺڞ௨ݴޠԽ͢Δʂ ࠓ·ͰͷϓϩδΣΫτͰ.JYFENFUIPETతͳࣄྫ͋Δ͔ʁΛ ͠߹͏ •
͚ͬ͜͏ग़ͯ͘Δͱࢥ͍·͢ • ఆੑఆྔͷύλʔϯɺఆྔఆੑͷύλʔϯɺϓϩδΣΫτ͝ ͱʹͲͷύλʔϯ͕ଟ͍͔ɺ࠷దͦ͏͔Λ͢ͱ໘ന͍Ͱ͢
Thanks for listening • ࠓޙษڧձ࣮ࢪ͍ͯ͘͠ͷͰɺͥͻօ͞ΜͷࣄྫΛڭ͍͑ͯͩ͘͞ʂ • 1.ɺ69Ϧαʔνϟʔɺ1..࠾༻ͬͯ·͢ • ͜ͷޙͷ"TLUIFTQFBLFSʹͭΑͭΑσʔλαΠΤϯςΟετ͡ΊϓϩδΣΫτ ؔऀΛݺΜͰ͍·͢ͷͰɺଟ༷ͳ࣭͓͍ͪͯ͝͠·͢ʂ
@mayooon