| Project/Area Number |
15K17062
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Economic policy
|
|---|
| Research Institution | Nagoya City University (2016-2018)
Kinki University (2015) |
|---|
Principal Investigator |
Yamada Eri 名古屋市立大学, 大学院経済学研究科, 講師 (30706742)
|
|---|
| Project Period (FY) |
2015-04-01 – 2019-03-31
|
| Project Status |
Completed (Fiscal Year 2018)
|
| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
|
|---|
| Keywords | 確率フロンティア分析 / TFP / 産業集積 / イノベーション / 自動車製造業 / ネットワーク分析 / Product space / 技術的複雑性指標 / 自動車部品 / 産業クラスター / ネットワーク / 全要素生産性 |
|---|
| Outline of Final Research Achievements |
Using establishment-level micro data, we estimate the productivity of companies that manufacture transportation equipment and find that the factor that contributes to growth is related to innovations. Moreover, we represent these results on maps with the addresses of each establishment. It becomes clear that the establishments that have higher innovation effects on dynamics tend to construct industrial agglomerations.
To explore knowledge networks related to innovations from linkage of knowledge combinations regarding automobile parts, we measure the knowledge relatedness between automobile parts by focusing on similarities in technologies embedded in products. We find that the density of relatedness differ according to the part type. This result confirms that the parts that have high-density relatedness are located on the core or hub of the knowledge networks and are next-generation parts. It is suggested that new parts emerge when new knowledge is connected to the existing network.
|
| Academic Significance and Societal Importance of the Research Achievements |
従来，地域経済成長の計測には事前に産業や地域が集計されたデータを利用してきたが，本研究は事業所の個票データを用いることにより，実際の生産活動単位である事業所レベルでの生産性や知識ネットワークを計測した。また，分析結果を地図上に可視化したことにより，行政境界にとらわれることなく実データにもとづく成長傾向が似ている地域や産業集積を検出した。本研究は，産業集積におけるイノベーションの波及過程を定量的に評価する手法を提案し，ミクロ的側面から解明した点において学術的意義が大きい。研究成果は，実践が先行してきた産業クラスター関連政策のこれまでの評価や今後の立案に際し，より実証的根拠を持つ情報を提供する。
|
