A Method for Determining SRI Selection Ratios That Reflect Investors' Value Judgments : Model of a Multifactor Information Channel Weighted Using Fuzzy Entropy
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- UEHARA Mamoru
- Aichi Shukutoku University
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- YAMASHITA Hiroshi
- Meiji University
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- OHNO Takahiro
- Waseda University
Bibliographic Information
- Other Title
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- 投資家の価値判断を反映したSRI投資銘柄選択比率の決定方法 : ファジィ・エントロピーを用いた重みつき多因子情報路モデル
- トウシカ ノ カチ ハンダン オ ハンエイシタ SRI トウシ メイガラ センタク ヒリツ ノ ケッテイ ホウホウ ファジィ エントロピー オ モチイタ オモミ ツキ タインシ ジョウホウロ モデル
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Abstract
In recent years investors have began to observe socially responsible investment (SRI) and selecting companies that are evaluated highly in this respect over those performing well in the area of corporate social responsibility (CSR). However, investors' needs or value judgments do not fully reflect present SRI screenings. In this study, the authors clarify the problems related to investment selection and decisions for present SRI screening selection ratios, and introduce a new model the resolves the problems related to determining investment selection ratios. Specifically, assuming a set with an undefined border (fuzzy set), we consider the fuzzy entropy expressing an unspecified amount of information. Then we introduce a model of a multifactor information channel weighted using fuzzy entropy. This model briefly expresses the decision-making process of the investment selection ratios, which reflects investors' value judgments in evaluation weights, thereby showing both sides of the human self-seeking selection action (randomness+fuzziness: fuzzy entropy) and satisfaction (average characteristic value) regarding the quality of the CSR characterized in each investment (alternatives). Using questionnaires, we estimate the SRI selection ratio, and examine and compare the proposed model with actual selection ratios.
Journal
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- Journal of Japan Industrial Management Association
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Journal of Japan Industrial Management Association 58 (2), 125-135, 2007
Japan Industrial Management Association
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Keywords
Details 詳細情報について
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- CRID
- 1390001205505597056
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- NII Article ID
- 110007521716
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- NII Book ID
- AN10561806
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- ISSN
- 21879079
- 13422618
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- NDL BIB ID
- 8860531
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed