Applications of management science. Vol. 21 /

Applications of Management Science showcases current studies in the application of management science, contributing to the solution of significant managerial decision-making problems. To those involved in the applications of multi-criteria decision making, data envelopment analysis, and decision mak...

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Altri autori: Kleinman, Gary (Redattore), Pai, Dinesh R. (Redattore)
Natura: Elettronico eBook
Lingua:inglese
Pubblicazione: Bingley, U.K. : Emerald Publishing Limited, 2022.
Serie:Applications of management science ; v. 21.
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Accesso online:https://doi.org/10.1108/S0276-8976202221
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Sommario:
  • Part a. Data envelopment analysis
  • Chapter 1. Insurance company efficiency analysis through data envelopment analysis (dea) during covid-19 pandemic / Gao Niu, John Quinn, and Alan Olinsky
  • Chapter 2. Are all gold medal mutual funds equally efficient? / D.K Malholtra, Rashmi Malholtra, and Robert Nydick
  • Chapter 3. Covid-19 and performance of cosmetics companies / Rashmi Malhotra, D. K Malhotra, and Shubha Bennur
  • Chapter 4. Productivity in the new jersey ppo health insurance industry, 2018 / Kenneth D. Lawrence and Sheila M. Lawrence
  • Chapter 5. Negative data in data envelopment analysis (dea) / Kenneth D. Lawrence, Sheila M. Lawrence, and Dinesh R. Pai
  • Part b. Optimization modeling
  • Chapter 6. Optimization of the geothermal energy for district heating in the Polish tatras region: A case study / Bartosz Sawik
  • Chapter 7. Profitability, sustainability, and product development / Nand K. Jha
  • Part c. Business analytical modeling
  • Chapter 8. Comprehensive business diagnostics of a company's activities / Naila Aliyeva, Sergei Chernov, Liudmila Babaskina, and Mariya Zakharova
  • Chapter 9. Optimal bundling of platform memberships under horizontal cooperation / Xingping Zhang, Feng Yang, Yaqin Hu, and Zhimin Huang
  • Chapter 10. Mitigating administrative fraud in warranty service for remanufactured products / Aditya Pandit, and Surendra M. Gupta
  • Chapter 11. Experiential learning exercise in an analytics class / Ronald Klimberg, Michael Marzano, and Michael Bruening.