Data Science and Productivity Analytics

by Aparicio, Juan Charles, Vincent Zhu, Joe

Type Book

Rate 0.0 /5

Details

Files

Reviews

Download

Title Statements

Full title :Data Science and Productivity Analytics / edited by Vincent Charles, Juan Aparicio, Joe Zhu.

Edition Statements

Publication Date:2020.
Edition:First edition 2020

Publication Statements

Publisher(s):Imprint: Springer, Springer International Publishing
Place of Publication:Cham
Language:eng
Publication Date:2020.

The Physical Object

Description:1 online resource (X, 439 pages 98 illustrations, 49 illustrations in color. :) : online resource.

Edition Identifiers

ISBN:9783030433840, 3030433846, 9783030433833, 3030433838, 9783030433857, 3030433854, 9783030433864, 3030433862
oclc:on1340087528
LC Classification:HD30.23
Dewey Decimal:658.40301

Chapter 1. Data Envelopment Analysis and Big Data: Revisit with a Faster Method -- Chapter 2. Data Envelopment Analysis (DEA): Algorithms, Computations, and Geometry -- Chapter 3. An Introduction to Data Science and Its Applications: an Introduction to Data Science and Its Applications -- Chapter 4. Identification of Congestion in DEA -- Chapter 5. Data Envelopment Analysis and Non-Parametric Analysis -- Chapter 6. The Measurement of Firms' Efficiency Using Parametric Techniques -- Chapter 7. Fair Target Setting for Intermediate Products in Two-Stage Systems With Data Envelopment Analysis -- Chapter 8. Fixed Cost and Resource Allocation Considering Technology Heterogeneity in Two-Stage Network Production Systems -- Chapter 9.Efficiency Assessment of Schools Operating in Heterogeneous Contexts: A Robust Nonparametric Analysis Using Pisa 2015 -- Chapter 10. A DEA Analysis in Latin-American Ports: Measuring the Performance of Guayaquil Contecon Port -- Chapter 11. Effects of Locus of Control on Bank's Policy -- a Case Study of a Chinese State Owned Bank -- Chapter 12. A Data Scientific Approach to Measure Hospital Productivity -- Chapter 13. Environmental Application of Carbon Abatem…