Determinants of Smartphone Prices using Backward Elimination Technique in Multiple Linear Regression
Keywords:
quantitative variable, multiple linear regression, price determinants, correlation, backward elimination methodAbstract
Problem: The rapidly evolving market for smart gadgets causes smartphone prices to vary widely, frequently posing challenges to what consumers expect and can afford. Therefore, understanding the complex interrelationship of factors that determine smartphone prices has emerged as an important subject for study in an era defined by technological developments.
Aims/Objectives: This study seeks to identify the factors that influence the pricing of smartphones.
Methodology/approach: The study focused on various factors, including the battery capacity, camera quality, screen size, charging speed, device weight, and age in months. The primary data for the research came from the Global System for Mobile Communication (GSM) online marketplace, comprising sixty smartphones selected through a simple random sampling technique. We initially developed a multiple linear regression model with SPSS and then refined it using backward elimination.
Results/finding: The results highlight the strong influence of several characteristics on smartphone pricing, namely battery capacity, charging speed, weight, and model age. Interestingly, the examination of six variables revealed that camera and screen size had no effect on price.
Implication/impact: The knowledge acquired from this quantitative analysis not only advances our comprehension of the interplay between technology and consumer demand but also has implications for manufacturers, policymakers, and consumers who desire to navigate the ever-changing sphere of smartphone pricing.
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Copyright (c) 2024 Sarah Yusoff, Muhammad Hazwan Mohd Hazhar, Dzul Dzaihan Dzul Dzailani, Nuralya Sofea Hairulanuar, Nurfatihah Anizan
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