학술논문

Model Testing and Validation of Factors Affecting Wellbeing of Retail Salesforce: Harnessing Machine Learning for Wireless Channel Prediction in Retail Environments
Document Type
Conference
Source
2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET) Sustainable Emerging Innovations in Engineering and Technology (ICSEIET), 2023 International Conference on. :596-600 Sep, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Wireless communication
Productivity
Employee welfare
Ethics
Technological innovation
Machine learning
Predictive models
Retail Salesforce
Retail Employees
Wellbeing
HR in Retail
CFA
Apparel Retailing
Language
Abstract
This abstract focus on model testing and validation of factors affecting the wellbeing of retail salesforce, with a particular emphasis on utilizing machine learning for wireless channel prediction in retail environments. The study aims to identify and understand the key factors that influence the wellbeing of retail salesforce, such as workload, job satisfaction, and work-life balance. By applying machine learning techniques to analyze wireless channel data in retail settings, the study seeks to predict and optimize wireless communication performance, ultimately enhancing the efficiency and productivity of the retail workforce. The findings of this research have implications for improving the working conditions and overall wellbeing of retail salesforce, while also leveraging advanced technologies for enhancing wireless communication in retail environments.