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• Adaptation of the Mahalanobis–Taguchi Method to Ordinal Scale

  IWAMOTO Hiroki, NAGATA Yasushi

  Total Quality Science   8 ( 1 )   14 - 22   2022年12月  [査読有り]

  DOI CiNii Research

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  担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：一般社団法人 日本品質管理学会   共著  

  <p>The Mahalanobis–Taguchi (MT) method is a multivariate analysis method that addresses problems such as pattern recognition and anomaly detection wherein outliers from data groups are detected. The MT method is applied to various other fields (e.g., medical examination, corporate bankruptcy discrimination, and employee turnover discrimination). At the time of application, the effectiveness of the MT method for scale data, other than continuous variables, has not been clarified. The MT method using the polyserial and polychoric correlation (MTP) method, which is an MT method using the Mahalanobis distance calculated by Pearson, polyserial and polychoric correlation coefficients, is proposed. Correlations between continuous variables are calculated using Pearson’s correlation coefficient, continuous and ordinal-scale variables are calculated using the polyserial correlation coefficient, and ordinal-scale variables are calculated using the polychoric correlation coefficient. Through simulation with artificial data, it was confirmed that the anomaly detection accuracy of the MT method decreased with respect to the ordinal scale and the correlation weakening by ordinal scaling can be eliminated using the polyserial and polychoric correlation coefficients. The results of this study indicate that the abnormality discrimination accuracy of the MTP method exceeds that of the MT method, although in a limited environment.</p>

• ワーク・ライフ・バランス支援と女性活躍の関係性―ベイジアンネットワークによる施策間関係分析―

  岩本 大輝, 鈴木 秀男

  経営情報学会誌   30 ( 4 )   245 - 258   2022年3月  [査読有り]

  DOI CiNii Research

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  担当区分：筆頭著者,　責任著者   記述言語：日本語   掲載種別：研究論文（学術雑誌）   出版者・発行元：一般社団法人 経営情報学会   共著  

  <p>世界中で女性の労働参入が進んでいる．日本でも女性活躍は進んでいるが，女性管理的職業従事者割合は世界と比して極めて低い．この課題の要因としてワーク・ライフ・バランス(WLB)問題がある．企業はWLB支援施策を採用，もしくは採用を検討しているが，施策が階級別女性比率に与える影響や施策間の影響関係が不明瞭であり，検討困難な現状がある．本研究はWLB施策の組合せ効果や施策間関係が女性活躍に与える影響に注目し，日本企業604社のWLB支援施策情報にベイジアンネットワーク分析を行った．結果として，従業員女性比率には残業時間の削減策，管理職女性比率には在宅勤務，部長以上職女性比率には在宅勤務と保育設備・手当の採用が有効であるとともに，これらの施策の採用に影響を与える基礎的な施策（例えば，有給休暇取得の奨励策など）から順を追って採用し，労働環境を整えることが施策の有効化につながるという示唆をえた．</p>

• Evaluation of personnel-adjusted added value: Estimating its relationship with future profit in Japan

  Iwamoto, H; Suzuki, H

  COGENT ECONOMICS & FINANCE   9 ( 1 )   2021年1月  [査読有り]

  DOI Web of Science

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  担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   共著  

• A Slacks-Based DEA-R Approach with an Application to Japanese Banks

  Wang Xu, Iwamoto Hiroki, Hasuike Takashi

  Journal of Advanced Computational Intelligence and Intelligent Informatics   30 ( 1 )   67 - 77   2026年1月  [査読有り]

  DOI Web of Science CiNii Research

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  記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：富士技術出版株式会社   共著  

  <p>Data envelopment analysis (DEA) is a powerful approach for evaluating the relative efficiency of decision-making units with multiple inputs and outputs. Integrating DEA with ratio analysis has become essential because of the increasing prevalence of ratio data (e.g., return on assets) in practical applications. This study develops a novel DEA-R model and the RAM-R model, which combines the well-established range-adjusted measure (RAM) with ratio analysis. The model effectively handles ratio data, accommodates negative values, and accounts large variations across indicators, thereby enhancing flexibility and robustness in efficiency evaluation. A case study of 93 Japanese banks compares the RAM-R model with the RAM and another slacks-based DEA-R (the slacks-based measure-R and SBM-R) models using ratio data to demonstrate its effectiveness in evaluating efficiency.</p>

• Improving the accuracy of robust parameter design by utilizing effective explanatory factors

  Mori Nayuta, Iwamoto Hiroki, Nagata Yasushi

  Total Quality Science   11 ( 1 )   1 - 11   2025年11月  [査読有り]

  DOI CiNii Research

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  記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：一般社団法人 日本品質管理学会   共著  

  Robust parameter design (RPD) is used in the Taguchi Method to reduce variability in system outputs and enhance quality. The technology development process utilizing RPD comprises an evaluation component for assessing robustness and a mechanism analysis component for devising new systems if the objectives are unmet. In this study, we focus on the Causality Search T-Method (CS-T method), an efficient method for mechanism analysis, and its development method, Knowledge Search-Instrumental variables (KS -IV). The CS-T method is a practical technique that can improve the efficiency of system selection while maintaining the efficiency of an RPD. However, the conditions under which these methods can be used with high accuracy and validity remain unclear. In this study, we propose an extension of the CS-T and KS-IV methods for dynamic parameter design. In addition, we discuss the differences between the data aggregation methods of the two methods and the relationship between the aggregation contents and results, and based on these discussions, we improve the accuracy and interpretability of the methods.

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