Browsing by Author "Tone, Kaoru"

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DEA models incorporating uncertain future performance
(2016-10-16)
Chang, Tsung-Sheng
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Tone, Kaoru
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Wu, Chen-Hui
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Conventional data envelopment analysis (DEA) models are designed for measuring the productive efficiency of decision making units (DMUs) based merely on historical data. However, in many practical applications, such past results are not sufficient for evaluating a DMU\'s performance in highly volatile operating environments, such as those with highly volatile crude oil prices and currency exchange rates. That is, in such environments, a DMU\'s whole performance may be seriously distorted if its future performance, which is sensitive to crude oil price volatility and/or currency fluctuations, is ignored in the evaluation process. However, despite its importance, to our knowledge, there are no DEA models proposed in the literature that explicitly take future performance volatility into account. Hence, this research aims at developing a new system of DEA models that incorporate a DMU\'s uncertain future performance, and thus can be applied to fully measure their efficiency. (C) 2016 Elsevier B.V. All rights reserved.
Handling negative data in slacks-based measure data envelopment analysis models
(2020-05-01)
Tone, Kaoru
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Chang, Tsung-Sheng
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Wu, Chen-Hui
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This paper proposes slacks-based measure (SBM) data envelopment analysis (DEA) models that handle negative data. Unlike existing negative data allowable DEA models, the proposed SBM DEA models are consistent with ordinary SBM models and units invariant, they handle various types of returns to scale, and they avoid division by zero. These new SBM DEA models transform original negative inputs and outputs into positive counterparts based on a newly defined "base point". Hence, these models are referred to as the BP-SBM DEA models. In addition to the basic BP-SBM DEA models, this research further develops data-oriented and application-oriented BP-SBM DEA-type models for different application problems involving negative data. Numerical examples are provided to illustrate various aspects and implementation details of these models. (C) 2019 Elsevier B.V. All rights reserved.
Past-present-future Intertemporal DEA models
(2015-01-01)
Chang, Tsung-Sheng
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Tone, Kaoru
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Wu, Chen-Hui
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交大名義發表
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運輸與物流管理系註：原交通所+運管所
It has been well recognized that to thoroughly evaluate a firm\'s performance, the evaluator must assess not only its past and present records but also future potential. However, to the best of our knowledge, there are no data envelopment analysis (DEA)-type models proposed in the literature that simultaneously take past, present and, especially, future performance indicators into account. Hence, this research aims at developing a new type of DEA model referred to as Intertemporal DEA models that can be used to fully measure a firm\'s efficiency by explicitly considering its key inputs and outputs involving the past-present-future time span. In this research, the proposed Intertemporal DEA models are applied to the performance evaluation of high-tech Integrated Circuit design companies in Taiwan to demonstrate their advantages over other DEA models that ignore intertemporal efficiency.