Sales Forecasting for Firms based on Multiple Regression Model

Guanyi Wang

2022

Abstract

This paper focuses on the building and usage of a multiple linear regression model (MLR) for predicting a firm’s sales. According to the data provided by a semiconductor manufacturing company, ABCtronics on its historical sales from 2004 to 2013 and the data with three factors that may affect the sales (i.e., overall market demand, price per chip, and economic condition), a multiple linear regression model can be built based on these data. Hence, the future sales figure can be also estimated by using the model. The model is constructed via the Excel in order to find the values of coefficients for each independent variable. The resulting model offers a guideline for a way of more accurately and validly forecasting a firm’s sales or predicting other trends and relationships in a situation of having multiple variables by using a multiple linear regression model.

Paper Citation

in Harvard Style

Wang G. (2022). Sales Forecasting for Firms based on Multiple Regression Model. In Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM, ISBN 978-989-758-593-7, pages 628-633. DOI: 10.5220/0011198600003440

in Bibtex Style

@conference{bdedm22,
author={Guanyi Wang},
title={Sales Forecasting for Firms based on Multiple Regression Model},
booktitle={Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,},
year={2022},
pages={628-633},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011198600003440},
isbn={978-989-758-593-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,
TI - Sales Forecasting for Firms based on Multiple Regression Model
SN - 978-989-758-593-7
AU - Wang G.
PY - 2022
SP - 628
EP - 633
DO - 10.5220/0011198600003440