• Produktbild: Data Science and Productivity Analytics
  • Produktbild: Data Science and Productivity Analytics
Band 290

Data Science and Productivity Analytics

148,99 €

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.05.2021

Herausgeber

Vincent Charles + weitere

Verlag

Springer

Seitenzahl

439

Maße (L/B/H)

23,5/15,5/2,5 cm

Gewicht

680 g

Auflage

1st ed. 2020

Sprache

Englisch

ISBN

978-3-030-43386-4

Beschreibung

Portrait

Vincent Charles is an experienced researcher in the field of Artificial Intelligence and Management Science, currently with the School of Management, University of Bradford. He has more than two decades of teaching, research, and consultancy experience, having been a full professor and director of research for more than a decade. He has published over 130 research outputs. He is a recipient of many international academic honours and awards.

Juan Aparicio is an Associate Professor at the Department of Statistics, Mathematics an Information Technology of the University Miguel Hernandez, Elche (Alicante), Spain. He is the director of the Center of Operations Research and is also Co-Chair (with Knox Lovell) of the Santander Chair on Efficiency and Productivity. He has published over 100 research contributions, mainly on Data Envelopment Analysis, Efficiency and Productivity Analysis.

Joe Zhu is Professor of Operations Analytics in the Foisie Business School, Worcester Polytechnic Institute. He is an internationally recognized expert in methods of performance evaluation and benchmarking using Data Envelopment Analysis (DEA), and his research interests are in the areas of operations and business analytics, productivity modeling, and performance evaluation and benchmarking. He has published and co-edited several books focusing on performance evaluation and benchmarking using DEA and developed the DEA Frontier software.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.05.2021

Herausgeber

Verlag

Springer

Seitenzahl

439

Maße (L/B/H)

23,5/15,5/2,5 cm

Gewicht

680 g

Auflage

1st ed. 2020

Sprache

Englisch

ISBN

978-3-030-43386-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)

  • Produktbild: Data Science and Productivity Analytics
  • Produktbild: Data Science and Productivity Analytics
  • 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 Abatement Allocation by Data Envelopment Analysis.- Chapter 14. Pension Funds and Mutual Funds Performance Measurement With a New DEA (Mv-DEA) Model Allowing for Missing Variables.- Chapter 15. Sharpe Portfolio Using a Cross-Efficiency Evaluation.