{"id":15897,"date":"2026-09-18T10:00:55","date_gmt":"2026-09-18T01:00:55","guid":{"rendered":"https:\/\/www.waseda.jp\/fcom\/soc\/?p=15897"},"modified":"2026-09-18T10:53:20","modified_gmt":"2026-09-18T01:53:20","slug":"2022%e5%b9%b47%e6%9c%88-%e7%94%a3%e6%a5%ad%e7%b5%8c%e5%96%b6%e7%a0%94%e7%a9%b6%e6%89%80%e3%82%a4%e3%83%99%e3%83%b3%e3%83%88%e3%81%ae%e3%81%8a%e7%9f%a5%e3%82%89%e3%81%9b-2-2-3-3","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/fcom\/soc\/news\/15897","title":{"rendered":"2026\u5e74\u5ea6 \u7523\u696d\u7d4c\u55b6\u7814\u7a76\u6240\u30a4\u30d9\u30f3\u30c8\u306e\u304a\u77e5\u3089\u305b"},"content":{"rendered":"

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\u3010\u7523\u7814\u8b1b\u6f14\u4f1a\u3011<\/p>\n

\u25ce2026\u5e749\u670828\u65e5(\u6708)\u30fb29\u65e5(\u706b) \u8b1b\u6f14\u4f1a\uff08\u8a73\u7d30\u306f\u3053\u3061\u3089<\/a>\uff09<\/p>\n

\n\n\n\n\n\n
\u30c6\u30fc\u30de<\/td>\nStockholm School of Economics-Waseda Innovation Workshop<\/td>\n<\/tr>\n
\u8b1b\u6f14\u8005<\/p>\n

\u30b9\u30b1\u30b8\u30e5\u30fc\u30eb<\/td>\n

\uff19\u6708\uff12\uff18\u65e5\uff08\u6708\uff09<\/u><\/strong><\/p>\n

10:00-10:05: Opening Remarks<\/strong><\/p>\n

 <\/p>\n

10:05-10:55: Presentation 1<\/strong><\/p>\n

Xiayan Dai \u6c0f<\/p>\n

(Research Associate, Graduate School of Commerce, Waseda University)<\/p>\n

\u300cStrategic Communication under Socioemotional Constraints:<\/p>\n

Family Firms’ Forward-Looking Narratives in MD&A\u300d<\/p>\n

 <\/p>\n

11:10-11:50: Presentation 2<\/strong><\/p>\n

Stefan Haefliger \u6c0f<\/p>\n

(Professor, House of Innovation, Stockholm School of Economics)<\/p>\n

\u300cKnowledge Creation between Accountability and Alienation\u300d<\/p>\n

 <\/p>\n

11:50-13:00: Lunch (Room 901)<\/strong><\/p>\n

 <\/p>\n

13:00-13:50: Presentation 3<\/strong><\/p>\n

Hiroshi Shimizu \u6c0f<\/p>\n

(Professor, School of Commerce, Waseda University)<\/p>\n

\u300cGeneral Purpose Technologies: Identification\u300d<\/p>\n

 <\/p>\n

13:55-14:45: Presentation 4<\/strong><\/p>\n

Valentina Tartari \u6c0f<\/p>\n

(Professor, House of Innovation, Stockholm School of Economics)<\/p>\n

\u300cEvaluator Turnover and the Recovery of Good Ideas\u300d<\/p>\n

 <\/p>\n

14:50-15:40: Presentation 5<\/strong><\/p>\n

Hao Zhang \u6c0f<\/p>\n

(PhD student, Department of Business Design and Management,<\/p>\n

Graduate School of Creative Science and Engineering, Waseda University)<\/p>\n

\u300cCoopetition, Greenwashing, and Governance in the Circular Economy:<\/p>\n

An Agent-Based Model\u300d<\/p>\n

 <\/p>\n

15:40-16:00: Coffee Break<\/strong><\/p>\n

 <\/p>\n

16:00-16:50: Presentation 6<\/strong><\/p>\n

Constantin Blome \u6c0f<\/p>\n

(Professor, House of Innovation, Stockholm School of Economics)<\/p>\n

\u300cSupply Chain and Geopolitics: Supply Chain Weaponization & Securitization\u300d<\/p>\n

 <\/p>\n

16:55-17:45: Presentation 7<\/strong><\/p>\n

Shosuke Noguchi \u6c0f<\/p>\n

(Assistant Professor, School of Commerce, Waseda University)<\/p>\n

\u300cWhen Commitments Fail: Cancellations and Retention on a Two-Sided Platform\u300d<\/p>\n

 <\/p>\n

\uff19\u6708\uff12\uff19\u65e5\uff08\u706b\uff09<\/u><\/strong><\/p>\n

9:30-10:20: Presentation 8<\/strong><\/p>\n

Tasuku Yasui \u6c0f<\/p>\n

(PhD student, Department of Business Design and Management,<\/p>\n

Graduate School of Creative Science and Engineering, Waseda University)<\/p>\n

\u300cA Portfolio-State Methodology for Classifying Investors and Tracking Trajectories<\/p>\n

in Startup Ecosystems\u300d<\/p>\n

 <\/p>\n

10:25-11:15: Presentation 9<\/strong><\/p>\n

P\u00e4r \u00c5hlstr\u00f6m \u6c0f<\/p>\n

(Torsten and Ragnar S\u00f6derberg Professor of Operations Management at the Stockholm School of Economics)<\/p>\n

\u300cProcess Innovation and Artificial Intelligence\u300d<\/p>\n

 <\/p>\n

11:20-12:10: Presentation 10\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0<\/strong><\/p>\n

Yuxuan Liu \u6c0f<\/p>\n

(PhD student, Graduate School of Commerce, Waseda University)<\/p>\n

\u300cWhen Rivals Disappear: Incumbent Response to Government-Imposed Competitor Bans\u300d<\/p>\n

 <\/p>\n

12:10-12:20: Closing Remarks<\/strong><\/td>\n<\/tr>\n

\u5bfe\u8c61<\/td>\n\u5b66\u751f\u30fb\u6559\u8077\u54e1\u30fb\u4e00\u822c<\/td>\n<\/tr>\n
\u4e16\u8a71\u4eba<\/td>\n\u5c71\u91ce\u4e95\u3000\u9806\u4e00\uff08\u65e9\u7a32\u7530\u5927\u5b66\u5546\u5b66\u5b66\u8853\u9662 \u6559\u6388\uff09<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n

\u25ce2026\u5e749\u670830\u65e5(\u6c34) \u8b1b\u6f14\u4f1a\uff08\u8a73\u7d30\u306f\u3053\u3061\u3089<\/a>\uff09<\/p>\n

\n\n\n\n\n\n
\u30c6\u30fc\u30de<\/td>\n\u3000\u300eM&A\/PMI\u3092\u64cd\u308b\u6b21\u4e16\u4ee3\u30ea\u30fc\u30c0\u30fc\u306e\u30ad\u30e3\u30ea\u30a2\u6226\u7565\u300f
\n\uff5e\u300c\u6226\u7565\u7acb\u6848\u304b\u3089\u7d71\u5408\u5b9f\u52d9\u300d\u307e\u3067\u3092\u7e4b\u3050\u5e02\u5834\u4fa1\u5024\u306e\u9ad8\u3081\u65b9\uff5e<\/td>\n<\/tr>\n
\u8b1b\u6f14\u8005<\/td>\n\u5c0f\u5cf6\u3000\u79c0\u6bc5\u3000\u6c0f
\n\u682a\u5f0f\u4f1a\u793eSHIFT \u30b0\u30eb\u30fc\u30d7\u7d4c\u55b6\u63a8\u9032\u672c\u90e8 \u672c\u90e8\u9577
\n\u682a\u5f0f\u4f1a\u793eSHIFT\u30b0\u30ed\u30fc\u30b9\u30fb\u30ad\u30e3\u30d4\u30bf\u30eb \u4ee3\u8868\u53d6\u7de0\u5f79
\nSHIFT USA Inc. \u53d6\u7de0\u5f79CEO<\/td>\n<\/tr>\n
\u5bfe\u8c61<\/td>\n\u5b66\u751f\u30fb\u6559\u8077\u54e1\u30fb\u4e00\u822c<\/td>\n<\/tr>\n
\u4e16\u8a71\u4eba<\/td>\n\u5c71\u91ce\u4e95\u3000\u9806\u4e00\uff08\u65e9\u7a32\u7530\u5927\u5b66\u5546\u5b66\u5b66\u8853\u9662 \u6559\u6388\uff09<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n

\u25ce2026\u5e7410\u67087\u65e5(\u6c34) \u8b1b\u6f14\u4f1a\uff08\u8a73\u7d30\u306f\u3053\u3061\u3089<\/a>\uff09<\/p>\n

\n\n\n\n\n\n\n
\u30c6\u30fc\u30de<\/td>\n\u3000\u300eClassifying firms’ technological capabilities from website text: A longitudinal study of AI adoption in Europe\u300f<\/td>\n<\/tr>\n
\u8b1b\u6f14\u8005<\/td>\n <\/p>\n

Alexander Kopka \u6c0f\u3000<\/span><\/p>\n

\uff08Senior Researcher, Th\u00fcnen Institute of Rural Economics\uff09<\/td>\n<\/tr>\n

\u8981\u65e8<\/td>\nAI adoption is expected to drastically impact economic activity in the coming years. However, assessing and tracking firm-level AI adoption in real time remains difficult. Firm-level measures of technological capabilities typically rely on patents, R&D reporting, or surveys, which capture only a narrow and lagged slice of firm activity and tend to skew toward larger firms. We explore whether firm websites, scraped longitudinally and processed with text-mining methods, can serve as a complementary signal of technological capabilities, using AI as a test case. The study draws on the CommonCrawl database, which has captured snapshots of the internet at regular intervals since 2014, combined with firm-level information from ORBIS, to construct a longitudinal EU-wide (EU27+UK) firm-level website text database for classifying (stated) technological capabilities. To classify, we plan a two-stage approach: relevant paragraphs are first identified through a dictionary-based keyword search and then classified using a supervised Sentence-BERT model.<\/p>\n

We address two research questions: (a) whether firm website texts are a useful indicator of technological capabilities and how they compare with well-established measures, and (b) how AI adoption is descriptively distributed across the EU. While research on website data for classifying technological capabilities is still young, it tends to (a) focus on individual countries and (b) neglect the potential weaknesses of the indicator itself. This study therefore aims to deliver both a methodological contribution, assessing what a website-based indicator actually captures, and a data contribution, in the form of a longitudinal database of AI capabilities for European firms.<\/td>\n<\/tr>\n

\u5bfe\u8c61<\/td>\n\u5b66\u751f\u30fb\u6559\u8077\u54e1\u30fb\u4e00\u822c<\/td>\n<\/tr>\n
\u4e16\u8a71\u4eba<\/td>\n\u4e09\u6a4b\u3000\u5e73\uff08\u65e9\u7a32\u7530\u5927\u5b66\u5546\u5b66\u5b66\u8853\u9662 \u6559\u6388\uff09<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n

 <\/p>\n

\u25ce2026\u5e7410\u670812\u65e5(\u6708) \u8b1b\u6f14\u4f1a\uff08\u8a73\u7d30\u306f\u3053\u3061\u3089<\/a>\uff09<\/p>\n

\n\n\n\n\n\n\n
\u30c6\u30fc\u30de<\/td>\n\u3000\u300eWaseda Organizational and Financial Economics Seminar\uff1aBefore the Vote is Cast\u300f<\/td>\n<\/tr>\n
\u8b1b\u6f14\u8005<\/td>\n\u3000Julian Franks \u6c0f\u3000<\/span><\/p>\n

\uff08Emeritus Professor, Finance, London Business School\uff09<\/td>\n<\/tr>\n

\u8981\u65e8<\/td>\nMany scholars and some market participants argue that institutional investor engagement is insufficient, often pointing to the tendency of funds to vote in line with management and against shareholder proposals. This criticism frequently overlooks that voting decisions are typically the culmination of extensive engagement processes. Negative votes may not accurately reflect engagement efforts and influence because, in equilibrium, powerful and influential investors may resolve issues long before the vote takes place. To distinguish between rival explanations\u2014whether the scarcity of negative votes is due to investors wanting to please management, or because negative votes are part of an engagement process tied to private communications and meetings\u2014it is essential to analyze data on pre-voting engagements, contacts, and the decision-making processes behind votes, in addition to the actual votes cast.This paper will examine a new private database of voting decisions from one of the largest UK asset managers, containing textual records for each vote cast since 2010 across all UK holdings. Utilizing GPT-4 language models to analyze these records, we aim to test whether negative votes are rare because the investor is friendly with management\u2014even in private\u2014or if negative votes are integral to the engagement process and connected to private communications and meetings. Thus, we will investigate the interaction between private meetings, voting decisions, and voting outcomes over time. We will also analyse the interaction between these engagements and voting outcomes and trading decisions in the stocks.<\/td>\n<\/tr>\n
\u5bfe\u8c61<\/td>\n\u5b66\u751f\u30fb\u6559\u8077\u54e1\u30fb\u4e00\u822c<\/td>\n<\/tr>\n
\u4e16\u8a71\u4eba<\/td>\n\u8c37\u5ddd \u5be7\u5f66\uff08\u65e9\u7a32\u7530\u5927\u5b66\u5546\u5b66\u5b66\u8853\u9662 \u6559\u6388\uff09<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n

 <\/p>\n

\u3010\u7523\u7814\u30d5\u30a9\u30fc\u30e9\u30e0\u3011<\/p>\n

2026\u5e741\u670819\u65e5\uff08\u6708\uff09\u7b2c46\u56de\u7523\u7814\u30d5\u30a9\u30fc\u30e9\u30e0\u300c\u65e5\u672c\u306b\u304a\u3051\u308bPR\uff08\u30d1\u30d6\u30ea\u30c3\u30af\u30ea\u30ec\u30fc\u30b7\u30e7\u30f3\u30ba\uff09\u306e\u6b74\u53f2\u3068\u4eca\u5f8c\u306e\u5c55\u671b\u300d<\/a>\u304c\u958b\u50ac\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n

\u3010\u305d\u306e\u4ed6\u30a4\u30d9\u30f3\u30c8\u3011<\/p>\n

2025\u5e747\u670822\u65e5\uff08\u706b\uff09\u65e9\u7a32\u7530\u5927\u5b66\u7b2c28\u56de\u30d3\u30b8\u30cd\u30b9\u30d7\u30e9\u30f3\u30b3\u30f3\u30c6\u30b9\u30c8<\/a>\u304c\u958b\u50ac\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n

\u3010\u30a2\u30ab\u30c7\u30df\u30c3\u30af\u30fb\u30d5\u30a9\u30fc\u30e9\u30e0\u3011\uff082024\u5e74\u5ea6\uff09<\/p>\n

2025\u5e743\u670815\u65e5(\u571f) \u3000\u7b2c29\u56de\u7523\u7814\u30a2\u30ab\u30c7\u30df\u30c3\u30af\u30fb\u30d5\u30a9\u30fc\u30e9\u30e0\u300c\u7d4c\u55b6\u5b66\u7814\u7a76\u306e\u8ecc\u8de1\u3068\u5c55\u671b\u300d<\/a>\u304c\u958b\u50ac\u3055\u308c\u307e\u3057\u305f\u3002\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u65e9\u7a32\u7530\u5927\u5b66\u5546\u5b66\u5b66\u8853\u9662\u3000\u5742\u91ce\u53cb\u662d\u6559\u6388\u9000\u8077\u8a18\u5ff5<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

\u4ee5\u4e0b\u306e\u3068\u304a\u308a\u3001\u7523\u696d\u7d4c\u55b6\u7814\u7a76\u6240\u306e\u30a4\u30d9\u30f3\u30c8\u3092\u958b\u50ac\u3057\u307e\u3059\u3002 \u3010\u7523\u7814\u8b1b\u6f14\u4f1a\u3011 \u25ce2026\u5e749\u670828\u65e5(\u6708)\u30fb29\u65e5(\u706b) \u8b1b\u6f14\u4f1a\uff08\u8a73\u7d30\u306f\u3053\u3061\u3089\uff09 \u30c6\u30fc\u30de Stockholm School of Economics-Waseda […]<\/p>\n","protected":false},"author":5,"featured_media":8322,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[100,1],"tags":[73,45],"class_list":["post-15897","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-en","category-news","tag-events-en","tag-events"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/posts\/15897","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/comments?post=15897"}],"version-history":[{"count":2,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/posts\/15897\/revisions"}],"predecessor-version":[{"id":16424,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/posts\/15897\/revisions\/16424"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/media\/8322"}],"wp:attachment":[{"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/media?parent=15897"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/categories?post=15897"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.waseda.jp\/fcom\/soc\/wp-json\/wp\/v2\/tags?post=15897"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}