Production and operations management : POMS Lima, Peru, December 2-4, 2021 (virtual edition)

Production and operations management : POMS Lima, Peru, December 2-4, 2021 (virtual edition) / Jorge Vargas Florez, Irineu de Brito Junior, Adriana Leiras, Sandro Alberto Paz Collado, Miguel Domingo González Alvarez, Carlos Alberto González-Calderón, Sebastian Villa Betancur, Michelle Rodríguez, Diana Ramirez-Rios, editors.

This proceedings volume convenes selected, peer-reviewed contributions presented at the POMS 2021 International Conference on Production and Operations Management, which was virtually held in Lima, Peru, December 2-4, 2021. This book presents results in the field of Operations Management of key rele...

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Bibliographic Details
Corporate Author: International Conference on Production and Operations Management Online
Other Authors: Vargas Florez, Jorge (Editor), Brito Junior, Irineu de (Editor), Leiras, Adriana (Editor), Paz Collado, Sandro (Editor), González Alvarez, Miguel Domingo (Editor), González-Calderón, Carlos Alberto (Editor), Villa Betancur, Sebastian (Editor), Rodriguez, Michelle (Editor), Ramirez-Rios, Diana (Editor)
Format: eBook
Language:English
Published: Cham : Springer, [2022]
Series:Springer proceedings in mathematics & statistics ; v.391.
Subjects:
Production management > Congresses.
Logística > Matemáticas
Production management
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Table of Contents:
  • Intro
  • Preface
  • Contents
  • Part I: Business Operations Management
  • Socially Optimal Retail Return Strategies Under the Influence of Endowment Effect
  • 1 Introduction
  • 2 Literature Review
  • 3 Model Setup
  • 4 Problem Formulation
  • 5 Numerical Experiments
  • 6 Conclusion
  • References
  • Sales & Operations Planning a Practical Implementation Guide
  • 1 Introduction
  • 2 Theoretical Background
  • 3 Methodology
  • 4 S&OP Process in the Latin American Company
  • 5 Practical Guide for S&OP Implementation
  • 6 Conclusion
  • References
  • Better Efficiency on Non-performing Loans Debt Recovery and Portfolio Valuation Using Machine Learning Techniques
  • 1 Introduction
  • 1.1 Context and Overview
  • 1.2 Justification
  • 1.3 Purpose and Tools
  • 1.4 Methodology
  • 1.5 Hypothesis
  • 2 Data
  • 2.1 Dataset Clients
  • 2.2 Dataset Contact Management
  • 2.3 Dataset Payments
  • 2.4 Variable Selection and Mapping
  • 2.4.1 Variable Interaction
  • 2.4.2 Variable Mapping
  • 3 Algorithm Selection, Results, and Deployment
  • 3.1 Structure
  • 3.2 Modeling Algorithms
  • 3.3 Metrics
  • 3.4 Data Pre-processing and Development
  • 3.4.1 Binary Classification
  • Base Model Experimentation
  • Further Experimentation (Fine Tunning)
  • 3.4.2 Hypothesis Testing
  • 4 Conclusions
  • 5 Recommendations
  • References
  • Defense Offsets as a Public Policy: A Bibliometric Review in Brazilian Publications
  • 1 Introduction
  • 2 Literature Review
  • 2.1 Offset Definitions
  • 2.2 Offsets in Brazil
  • 3 Methodology
  • 3.1 Choice of Journals
  • 3.2 Choice of Search Period
  • 3.3 Choice of Search Terms
  • 4 Analysis and Discussion of Results
  • 5 Conclusion and Suggestions for Future Research
  • References
  • A Proposal for Collaborative Research Projects Involving Academy and a Brazilian Navy Science and Technology Institution
  • 1 Introduction
  • 2 Material and Methods
  • 2.1 Collaborative Research Projects
  • 2.2 Domain Knowledge and Methodological Knowledge
  • 3 Framework
  • 3.1 Proposed Framework
  • 3.2 Processes
  • 4 Practical Contributions
  • 5 Discussion and Conclusion
  • References
  • Part II: Production Process Innovation and New Technologies
  • Assessing the Attractiveness of Onshore Wind and Solar Photovoltaic Sources in Brazil
  • 1 Introduction
  • 2 Data and Methods
  • 3 Short-Term LCOE Results
  • 4 Medium and Long Term LCOEs
  • 5 Conclusions and Directions for Further Research
  • References
  • Forecasting Total Hourly Electricity Consumption in Brazil Through Complex Seasonality Methods
  • 1 Introduction
  • 2 Methods
  • 2.1 Critical Components in Hourly Consumption Time Series
  • 2.2 Univariate Models for Time Series with Simple Seasonal Patterns
  • 2.3 Models for Complex Seasonality Time Series
  • 3 Data and Empirical Setup
  • 3.1 Forecasting Total Hourly Consumption
  • 3.2 Robustness Checks
  • Forecasting Across Subsystems
  • 4 Results

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