| 研究課題/領域番号 |
23K01591
|
|---|
| 研究種目 |
基盤研究(C)
|
| 配分区分 | 基金 |
|---|
| 応募区分 | 一般 |
|---|
| 審査区分 |
小区分07080:経営学関連
|
|---|
| 研究機関 | 日本大学 |
|---|
研究代表者 |
Joe Geluso 日本大学, 法学部, 准教授 (20938055)
|
|---|
| 研究分担者 |
臼井 哲也 学習院大学, 国際社会科学部, 教授 (60409422)
|
|---|
| 研究期間 (年度) |
2023-04-01 – 2026-03-31
|
| 研究課題ステータス |
交付 (2023年度)
|
| 配分額 *注記 |
4,160千円 (直接経費: 3,200千円、間接経費: 960千円)
2025年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
2024年度: 1,690千円 (直接経費: 1,300千円、間接経費: 390千円)
2023年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
|
|---|
| キーワード | In progress / Automotive corporations / Annual Reports / Self representation / linguistic analysis / corpus linguistics |
|---|
| 研究開始時の研究の概要 |
We intend to elucidate how Japanese automotive multinational corporations (MNCs) differ from or are similar to their counterparts abroad in the way they choose to engage their stakeholders through their annual reports (ARs) and how this relationship evolved over time.
To achieve our goals, we will collect ARs from 2016 through 2022, from MNCs representing five different countries. We will conduct statistical and qualitative linguistic analyses to examine language variation in how the companies engage their audiences' via their ARs (e.g., focus on shareholders vs focus on broader stakeholders).
|
| 研究実績の概要 |
The 2023 fiscal year was spent collecting, cleaning, and annotating data. The data is Annual Reports published by multinational automotive companies (e.g., Ford, Toyota, BMW). To date, we have collected, converted, cleaned, and annotated over 5,000 pages and 2.25 million words of text from PDF files into cleaned and annotated utf-8 .txt files. Preliminary data analysis in 2023 focused on BMW, Volkswagen, GM, and Ford. Findings include that BMW and Volkswagen have longer reports with higher word counts on average than their American counterparts, and are more consistent with word counts and the number of figures and tables that are used per ten pages of report. Meanwhile GM and Ford show more variation between years in terms of word counts and the number of tables and figures used.
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
The main reason for the slight delay revolves around the cleaning of text data. Specifically, how quickly students workers clean and annotate the converted PDF files, and how many hours students can work. To the first point, the students work slightly slower than expected. A second point is that principal researcher assumed that the student workers could work year round, but it seems that it is hard to employ students between semesters as rules dictate that the student must work in the presence of one of the investigators. Balancing schedules when students and the researcher are available at the same time has limited the amount of time that students can work. Nevertheless, we continue to progress and I am confident that we will produce meaningful research results, if slightly delayed.
|
| 今後の研究の推進方策 |
We plan to continue collecting, converting, cleaning, and annotating data. This year we will also begin data analysis in earnest and start writing. Our first set of analyses will revolve around RQ1 focusing on the statistical side of linguistic analysis (e.g., keyword analysis, topic modeling). The second step will involve more qualitative analyses of images and text organization.
Both of these analyses are aimed at exploring how multinational automotive companies represent themselves in the documents entitled "Annual Reports" with an eye toward whether the Annual Reports use language that will resonate more with shareholders or broader stakeholders in the general public.
|
