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Hiroshi Morita

Researcher at Osaka University

Publications -  71
Citations -  1053

Hiroshi Morita is an academic researcher from Osaka University. The author has contributed to research in topics: Data envelopment analysis & Inefficiency. The author has an hindex of 16, co-authored 70 publications receiving 940 citations. Previous affiliations of Hiroshi Morita include Kyocera & Kobe University.

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A slack-based measure of efficiency in context-dependent data envelopment analysis

TL;DR: In this article, a slack-based context-dependent DEA is proposed to evaluate the inefficiency represented by non-zero input and output slacks in the context-independent DEA, which allows a full evaluation of inefficiency in a DMUs performance.
Patent

Solar Cell Module and Photovoltaic Power Generator Using This

TL;DR: In this paper, the bus bar electrodes are used to retrieve light-produced current produced at the solar cell element to the outside and collecting finger electrodes connected to these bus bars, and the finger electrodes (5b) are 0.5 mm through 2 mm in width and the bus-bar electrodes were 0.05 mm through 0.1 millimeter in width.
Journal ArticleDOI

A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system

TL;DR: An improved two-stage heuristic algorithm to cope with uncertain demands and departure times of EVs is developed, and the effect of the smart charge and discharge scheduling of EVs on a peak load reduction in a building energy management system is evaluated.
Journal ArticleDOI

Benchmarking firm performance from a multiple-stakeholder perspective with an application to Chinese banking

TL;DR: In this paper, the authors use data envelopment analysis (DEA) to capture the interactions among different perceptions on a common set of performance measures, and demonstrate that different views from the stakeholder universe can be summarily captured in DEA scores.
Journal ArticleDOI

SELECTING INPUTS AND OUTPUTS IN DATA ENVELOPMENT ANALYSIS BY DESIGNING STATISTICAL EXPERIMENTS( Operations Research for Performance Evaluation)

TL;DR: This work proposes an input output selection method that uses diagonal layout experiments, which is a statistical approach to find an optimal combination of inputs and outputs.