著者

谷口 諒 高田 直樹 村瀬 俊朗

出版者

日本経営学会

雑誌

日本経営学会誌 (ISSN:18820271)

巻号頁・発行日

vol.51, pp.32-46, 2022-12-20 (Released:2023-12-23)

参考文献数

60

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Innovation starts with creative ideas. While creativity and innovation have been separately studied, a growing body of work examines the process of creativity leading to innovation. There are a variety of problems in that process. One of them is the selection of creative ideas. Some experimental studies have shown that idea selection is a difficult task due to the cognitive tendency of individuals. This difficulty is exacerbated for managers since their cognitive resources are limited. If managers fail to correctly perceive and select highly creative ideas among many alternatives, creativity does not lead to innovations. Thus, as prior literature does, idea selection by managers is worth examining. However, idea selection by idea generators matters as well. Since the pool of ideas that managers evaluate consists of ones that idea generators propose, organizations cannot enjoy their employees' creativity if idea generators fail to select highly creative ideas among those they generate. Although this possibility has been mentioned in existing studies, little attention has been paid to idea selection by idea generators, in particular teams, that generated those ideas. In this paper, we develop a theoretical model of team idea selection, focusing on the diversity of members, psychological safety, and psychological ownership. While the former two concepts have been shown to contribute to idea generation (creativity), we argue that those can impede effective idea selection. Moreover, psychological ownership can lead teams away from proper evaluation and selection of creative ideas. Our model implies the potential difficulties and paradoxes in selecting ideas that idea generator teams can face.

著者

村瀬 俊朗 王 ヘキサン 鈴木 宏治

出版者

特定非営利活動法人 組織学会

雑誌

組織科学 (ISSN:02869713)

巻号頁・発行日

vol.55, no.1, pp.16-30, 2021-09-20 (Released:2021-10-15)

参考文献数

103

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理論を構成する抽象概念の変数化は,実証を行う上で重要な作業である.経営学者はアンケート調査を活用して概念の抽出を行ってきたが,データの大規模化や時系列での取得が困難であるため,一部の理論の検証が難しい.このデータに関する問題を解消するために,自然な人の行動の記録であるログデータの活用方法を模索する必要がある.そのため,本稿では自然言語処理と機械学習を応用したログデータの活用方法を検討する.