Details of a Researcher - Takahashi, Hiroshi

Papers - Takahashi, Hiroshi

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Interdependencies of female board member appointments

Matthias Raddant, Hiroshi Takahashi

International Review of Financial Analysis (ELSEVIER) 81 2022.05

Research paper (scientific journal), Joint Work, Last author, Accepted

Corporate boards, interorganizational ties and profitability: the case of Japan

Raddant Matthias, Takahashi Hiroshi

EMPIRICAL ECONOMICS (Empirical Economics) 62 ( 3 ) 1365 - 1406 2021.05

Research paper (scientific journal), Joint Work, Accepted, ISSN 0377-7332

We analyze the ties between 4000 Japanese corporations in the time period from 2004 until 2013. We combine data about the board composition with ownership relationships and indicators of corporate profitability. The board network exhibits some clustering, which can partly be explained by ownership relations, and a tendency to form ties to other corporations from the same sector. Connectivity in the board network (corporate board interlocks) and ownership network (shareholdings) does have an influence profitability. Firms that are linked to peers with above average profitability are more profitable than firms in other relationships. Hence, network effects partly explain why board interlocks and ownership ties are not always beneficial.

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Impact of financing method on J-REIT unit price around seasoned equity offerings: Dilution and borrowing ratio effects on abnormal returns

Ota A., Takahashi H.

Pacific Basin Finance Journal 91 2025.06

ISSN 0927538X

This study attempts to identify the determinants of changes in real estate investment trust (REIT) unit prices at the time of seasoned equity offering (SEO) in the Japanese financial market. As Japanese REIT (J-REIT) announces SEOs, dividends, and borrowings at the same time, this analysis can consider each factor simultaneously. This study uses the event study method to conduct an ordinary least squares multivariate regression analysis (regression analysis) of the average cumulative abnormal return for 11 days during SEOs in J-REIT. We add the change in a borrowing ratio before and after an SEO and the dilution ratio of investment units from the perspective of the financing method as new candidate factors not used in previous studies. The sample period is from 2013 to 2017, and the number of the analyzed SEOs is 150. This study simultaneously analyzes the impact of the changes in dividends, the changes in borrowing ratios, and the dilution ratios on J-REIT unit prices at the time of SEOs and clarifies each impact. This study showed that investors were aware of the importance of the dilution impact from the perspective of net asset value as well as the dividend as profitability. Unlike previous studies, we also showed that the increase in the borrowing ratio negatively affected the unit price.

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AI-Assisted Approach in Frail Prevention: A Proposal for Prompt Design Based on Emotional Analysis

HIGUCHI Akiyo, MURAKAMI Eiji, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2025 ( BI-026 ) 34 2025.03

2060年、日本では高齢化率が39.9%およそ2.5人に1人が後期高齢者（65歳以上）となる。本研究では、健康寿命の延伸に向けてフレイル予防のプロンプト構築と自然言語処理技術（NLP）を活用したプロンプト評価を行った。とくにフレイル予防や健康支援の分野では、EBMに加えユーザーに個別化されたアプローチが効果的である。本分析では、複数の大規模言語モデル（LLM）による比較を行うことでモデルの特徴と課題を確認した。

Developing BCP Indicators through Road Network Analysis: A Multi-City Comparative Study in the Philippines

YAGI Marina, MURAKAMI Eiji, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2025 ( BI-026 ) 05 2025.03

近年，防災・減災の重要性の高まりとともに，企業経営においても災害レジリエンスを強化するための定量的なBCP（事業継続計画）策定が求められている．本研究では，フィリピンの複数都市を対象に，道路ネットワーク分析を用いて災害時の道路寸断がLPガスの復旧点検時間に及ぼす影響を評価し，定量的な指標を構築する．これにより，各都市の地理的特性に応じた実効性のあるBCP立案を可能にし，LPG事業者のレジリエンス強化の支援，ならびに災害に強い地域づくりに貢献することを目指す．

Analysis of Extracting Corporate Trends from News Data Using BERTopic

Okazaki H., Takahashi H.

New Generation Computing 43 ( 1 ) 2025.02

ISSN 02883635

News is an immediate source of information. However, it is difficult to obtain information on the trends in each business unit of a company from individual news items. This study attempts to obtain information on each business unit of a company through news analysis using BERTopic by targeting multiple companies that hold similar business domains. The validity of the analysis results was verified by comparing the news analysis results with the securities reports published by the companies. As a result of the analysis, we found that (1) it is possible to follow the trends of each specific business unit in a company through news data analysis, and (2) news data contains timely information on corporate trends and product strategies, compared to securities reports. This research presents a novel analytical approach utilizing natural language processing techniques within the finance sector, highlighting a study with substantial potential for future advancements.

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UAV-Vehicle Delivery System: Heterogeneous Time Sensitivity and Economic Efficiency

Woo Sejun, Yagi Marina, Higuchi Akiyo, Shin Kiyotaka, Takahashi Hiroshi

Abstracts of Annual Conference of Japan Society for Management Information (THE JAPAN SOCIETY FOR MANAGEMENT INFORMATION (JASMIN)) 202411 ( 0 ) 110 - 113 2025.01

Evaluating the Effects of LP Gas Restoration Activities on Disaster-Prepared Urban Development: A Foundational Analysis of Kohoku Ward, Yokohama

Yagi Marina, Murakami Eiji, Takahashi Hiroshi

Abstracts of Annual Conference of Japan Society for Management Information (THE JAPAN SOCIETY FOR MANAGEMENT INFORMATION (JASMIN)) 202411 ( 0 ) 208 - 210 2025.01

This research conducted a road blockage simulation aimed at optimizing LP gas restoration efforts during disasters. The analysis focused on Kohoku Ward, Yokohama City, to investigate the relationship between road blockage rates and travel times. As a result of the analysis, it was found that under the given conditions, travel time tends to saturate once the road blockage rate exceeds a certain threshold. Although this analysis is in its preliminary stage, further detailed analysis will be conducted in the future with the aim of providing insights that contribute to strengthening disaster resilience and developing business continuity plans.

Construction of prompts aimed at preventing frailty : An Analysis Focused on Continuity of Conversation

Higuchi Akiyo, Murakami Eiji, Takahashi Hiroshi

Abstracts of Annual Conference of Japan Society for Management Information (THE JAPAN SOCIETY FOR MANAGEMENT INFORMATION (JASMIN)) 202411 ( 0 ) 178 - 180 2025.01

This study aims to explore methods for preventing frailty by using a large-scale language model to focus on conversational continuity. It is well-established that older adults with frailty are approximately twice as likely to require assistance or care. Therefore, the goal of this study is to create prompts for frailty prevention that can enhance the quality of life for individuals. The analysis will utilize a large-scale language model (LLM) to assess the feasibility and challenges of implementing multiple prompts.

Customer Story Generation based on Quantitative Persona Creation Method through Large Language Model

Kikuchi Takamasa, Takahashi Hiroshi

Bulletin of Human Centered Design Organization (Human Centered Design Organization) 20 ( 2 ) 25 - 34 2024.09

ISSN 18829635

Targeting customers in the asset formation domain necessitates analysis that considers both current customer attributes and future attribute changes. The authors have proposed a simulation-based quantitative persona creation method, but it is limited to establishing persona skeletons, and creating customer stories with additional narratives remains a challenge. Our previous method involves a cross comparison of several skeletons based on a combination of current customer attributes, the possibility of future attribute changes, and the assumed effects of measures, and thus there are limitations to conventional manual story creation. To address this, our study proposes a methodology to generate customer stories based on skeletons mechanically and semi-automatically, using a large language model. The main findings of this research are as follows: our methodology could 1) generate a set of stories with a certain level of consistency in terms of structure, 2) write stories according to the attributes of each skeleton, 3) generate logically coherent stories, incorporating future attribute changes, and 4) provide suggestions to foster awareness among stakeholders involved in the final phase of persona creation. The proposed method is applicable not only to persona creation but also to lifecycle management, such as version upgrades, and is expected to find industrial applications.

Initial research on frailty prevention using large-scale language models (LLM)

HIGUCHI Akiyo, MURAKAMI Eiji, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-025 ) 08 2024.09

This study uses a large-scale language model to examine methods for preventing frailty. In Japan, one out of every 2.5 persons will be 65 or older in the first half of life in 2060. Compared to healthy elderly, frail elderly people are at about twice the risk of needing assistance or nursing care. This study examines prompts to prevent frailty, improve quality of life, and realize a sustainable society. Utilizing a large-scale language model, we confirmed the feasibility of several prompts and the challenges.

Consideration of Community Gas Pricing Model Implementation through Agent-Based Modeling (ABM)

WOO Sejun, MURAKAMI Eiji, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-025 ) 06 2024.09

This study examines the effectiveness of a community-based gas pricing plan. The community- based pricing system determines rates based on the overall usage within a community, making cooperation among community members a crucial element. Through agent-based modeling, this research investigates the potential for energy consumption reduction under a community-based gas pricing system. The paper specifically explores the effectiveness of this approach when there is a high degree of similarity in attributes within the community.

Time Series Analysis of CEO Messages Using Cosine Similarity - Targeting Major Real Estate Developers in Japan ?

SATO Naoya, TAKAHASHI Hiroshi, OTA Akira

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-025 ) 04 2024.09

In recent years, information issued by companies has become more diversified, increasing corporate transparency to stakeholders. Especially, in CEO messages, which are a source of information indicating a company's future vision, changes over time are likely to emerge. Therefore, we collect CEO messages for each year as text data, vectorize them using natural language processing techniques, and then calculate the cosine similarity between messages for each year. Cosine similarity is a quantitative measure of similarity between documents by calculating the cosine of the angle between two vectors. Using this method, we quantitatively evaluate the similarities and differences between the CEO messages of each company for each year to identify trends in the real estate industry and the differences and characteristics of each company. As a result, it was observed that when social conditions undergo significant changes, the CEOs work to further promote the traditional businesses held by the companies by adapting the direction of the companies to the social conditions.

The Impact of News on Pharmaceutical Procurement in Emerging Markets on Companies' Market Evaluation

YAGI Marina, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-025 ) 03 2024.09

In Bottom of the Pyramid (BOP) business, the supply of pharmaceuticals is a critical issue. This study analyzes the impact of news articles on market evaluations of companies facing pharmaceutical supply shortages or logistics delays in emerging markets. By examining these factors, the research aims to clarify the market's response to BOP business challenges and contribute to the improvement of corporate management strategies, while providing insights for investor decision-making. The findings of this research are expected to enhance understanding of sustainable corporate management and foster the development of new markets in emerging economies.

A Study on the Characteristics of Sensory Evaluation in Condominium Floor Plans -Towards the Development of an AI Model-

HIROI Shun, TAKAHASHI Hiroshi, OTA Akira

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-025 ) 02 2024.09

The study acquires sensory evaluations of property floor plans as a form of tacit knowledge of experts and examines the impact of these evaluations on the price of condominium unit (Unit). The floor plans of Units are evaluated by the expert sensory with their ease of use and efficiency, but it has not been quantified to date. This study targets the floor plan images of the second-hand Units for sale, and these sensory evaluations acquired from experts. The multiple regression analysis for the Unit price is conducted by adding the sensory evaluation of the floor plan to the candidate factor variables such as building age and total exclusive area. The result of the multiple regression analysis indicates that the sensory evaluation of the floor plan was selected with the statistically significant level in the model. Therefore, it was suggested that the sensory evaluation of the floor plan has a certain impact on the Unit price.

Opportunities for a Simulation-Based Quantitative Persona Creation Method: Implications from Practitioner Interviews

Takamasa Kikuchi, Hiroshi Takahashi

Proceedings of the International Multi-Conference on Society, Cybernetics and Informatics (International Institute of Informatics and Cybernetics) 80 - 85 2024.09

ISSN 2831-722X

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Can a Large Language Model Generate Plausible Business Cases from Agent-Based Simulation Results?

Takamasa Kikuchi, Yuji Tanaka, Masaaki Kunigami, Hiroshi Takahashi, Takao Terano

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (Springer Nature Switzerland) 147 - 162 2024.05

ISSN 1860-949X

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Examining the impact of the spread of next-generation automobiles on gasoline demand in Japan and the delivery system based on these changes using an agent-based model

WATANABE Emiko, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-024 ) 21 2024.03

This research focuses on the decline in demand due to the spread of next-generation EV and hybrid vehicles, uses an agent-based model to predict gasoline demand, and predicts demand for a delivery model in which gasoline is delivered from a refinery or oil depot to a gas station by tank truck. We conducted a search for efficient delivery methods by reflecting the prediction results. The following results were obtained. Although oil depots have the function of reducing the number of tank trucks needed, using oil depots tends to increase delivery costs. If future gasoline demand decreases, the number of tanker trucks needed will also decrease. This is expected to reduce the need for the depot's ability to reduce the number of tanker trucks needed, making closure more economically advantageous.

Factor Analysis for Cap Rate of Property Using Space Syntax Measures

TOYOYOSHI Naoki, TAKAHASHI Hiroshi, KANEDA Toshiyuki, OTA Akira

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-024 ) 13 2024.03

Employee work environment analysis using natural language processing techniques and large-scale language models

KAMIYAMA Naoya, TAKAHASHI Hiroshi

JSAI Technical Report, Type 2 SIG (The Japanese Society for Artificial Intelligence) 2024 ( BI-024 ) 16 2024.03

This study aimed to understand how employees feel about their work environment and the factors influencing those feelings, by analyzing reviews on job-switching websites. The data extracted using advanced natural language processing (BERT) revealed common factors affecting employee satisfaction, including workplace environment, career development, business growth, interpersonal relationships, and evaluation and rewards. Furthermore, by utilizing large language models to generate employee personas, the study identified specific challenges and motivations, suggesting the potential to infer employee characteristics and provide valuable insights for decision-making.

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