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Data Science and Productivity Analytics

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Cover of 'Data Science and Productivity Analytics'

Table of Contents

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    Book Overview
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    Chapter 1 Data Envelopment Analysis and Big Data: Revisit with a Faster Method
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    Chapter 2 Data Envelopment Analysis (DEA): Algorithms, Computations, and Geometry
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    Chapter 3 An Introduction to Data Science and Its Applications
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    Chapter 4 Identification of Congestion in DEA
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    Chapter 5 Data Envelopment Analysis and Non-parametric Analysis
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    Chapter 6 The Measurement of Firms’ Efficiency Using Parametric Techniques
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    Chapter 7 Fair Target Setting for Intermediate Products in Two-Stage Systems with Data Envelopment Analysis
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    Chapter 8 Fixed Cost and Resource Allocation Considering Technology Heterogeneity in Two-Stage Network Production Systems
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    Chapter 9 Efficiency Assessment of Schools Operating in Heterogeneous Contexts: A Robust Nonparametric Analysis Using PISA 2015
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    Chapter 10 A DEA Analysis in Latin American Ports: Measuring the Performance of Guayaquil Contecon Port
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    Chapter 11 Effects of Locus of Control on Bank’s Policy—A Case Study of a Chinese State-Owned Bank
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    Chapter 12 A Data Scientific Approach to Measure Hospital Productivity
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    Chapter 13 Environmental Application of Carbon Abatement Allocation by Data Envelopment Analysis
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    Chapter 14 Pension Funds and Mutual Funds Performance Measurement with a New DEA (MV-DEA) Model Allowing for Missing Variables
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    Chapter 15 Sharpe Portfolio Using a Cross-Efficiency Evaluation
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Title
Data Science and Productivity Analytics
Published by
Springer International Publishing, July 2020
DOI 10.1007/978-3-030-43384-0
ISBNs
978-3-03-043383-3, 978-3-03-043384-0
Editors

Charles, Vincent, Aparicio, Juan, Zhu, Joe

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