TY - CHAP
T1 - A preliminary approach to identify the best function that fits the growth of company total assets
AU - Juárez, Fernando
N1 - Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2018/4
Y1 - 2018/4
N2 - Total Assets define companies; it is relevant in determining the size of the companies, ranking them by economic relevance and making predictions about their future. That makes necessary to analyze how companies growth, according to Total Assets, so this research problem focuses on identifying what the trend in Total Assets growth is across industries and company size categories, to find similarities and differences. Accordingly, the purpose of the study is to analyze the Total Assets company growth finding a function that fits across industries and company size categories. The method is analytical, deductive and empirical; it is a cross-sectional analysis with two industries and four different company sizes, based on Total Assets grouped into the categories of micro, small, medium or big enterprise. Every combination of industry-company size is analyzed to see which function draws the best fit. The functions are: 1) Linear, 2) Logarithmic, 3) Inverse, 4) Quadratic, 5) Cubic, 6) Compound, 7) Power, 8) S, 9) Growth, 10) Exponential, and 11) Logistic. The test consists of a regression analysis. ANOVA significance test and explained variance allow identifying the best function fit. Results show that cubic function gives the best results in all industry-company size combination. Other functions are relevant in some, but not all, combinations of categories. The conclusion is that cubic function provides the best fit to total assets company growth across several industry-company size combinations. However, it requires more in deep analysis and replication of the research in other industries to confirm the results.
AB - Total Assets define companies; it is relevant in determining the size of the companies, ranking them by economic relevance and making predictions about their future. That makes necessary to analyze how companies growth, according to Total Assets, so this research problem focuses on identifying what the trend in Total Assets growth is across industries and company size categories, to find similarities and differences. Accordingly, the purpose of the study is to analyze the Total Assets company growth finding a function that fits across industries and company size categories. The method is analytical, deductive and empirical; it is a cross-sectional analysis with two industries and four different company sizes, based on Total Assets grouped into the categories of micro, small, medium or big enterprise. Every combination of industry-company size is analyzed to see which function draws the best fit. The functions are: 1) Linear, 2) Logarithmic, 3) Inverse, 4) Quadratic, 5) Cubic, 6) Compound, 7) Power, 8) S, 9) Growth, 10) Exponential, and 11) Logistic. The test consists of a regression analysis. ANOVA significance test and explained variance allow identifying the best function fit. Results show that cubic function gives the best results in all industry-company size combination. Other functions are relevant in some, but not all, combinations of categories. The conclusion is that cubic function provides the best fit to total assets company growth across several industry-company size combinations. However, it requires more in deep analysis and replication of the research in other industries to confirm the results.
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U2 - 10.1109/ICAMCS46079.2018.000-3
DO - 10.1109/ICAMCS46079.2018.000-3
M3 - Chapter
AN - SCOPUS:85078896350
SN - 978-1-7281-3258-7
T3 - Proceedings - 2018 International Conference on Applied Mathematics and Computer Science, ICAMCS 2018
SP - 23
EP - 27
BT - Proceedings - 2018 International Conference on Applied Mathematics and Computer Science, ICAMCS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on Applied Mathematics and Computer Science, ICAMCS 2018
Y2 - 13 April 2018 through 15 April 2018
ER -