摘要：Identifying the determining factors of utilities’ profitability is vital in making strategic deci- sions such as optimal resource allocation and business strategy orientation to increase the invested capital. We analyze information from private and public companies in the energy, gas, and oil sectors in Colombia and other American countries. We construct a panel data model from 2000 to 2010 and propose a method that identifies the determining factors of profitability for homogeneous groups of companies using cluster analysis. We use regression analysis to quantify those factors for each cluster. Fixed assets are essential determining factors of profitability; however, investment regulation may lead to significant losses in the realizable value of fixed assets and an increase in the companies’ capital costs. Debt and a munificent environment only affect medium-sized companies. We found some benefits for large companies derived from non-transparent institutional environments.
其他摘要：Identifying the determining factors of utilities’ profitability is vital in making strategic deci- sions such as optimal resource allocation and business strategy orientation to increase the invested capital. We analyze information from private and public companies in the energy, gas, and oil sectors in Colombia and other American countries. We construct a panel data model from 2000 to 2010 and propose a method that identifies the determining factors of profitability for homogeneous groups of companies using cluster analysis. We use regression analysis to quantify those factors for each cluster. Fixed assets are essential determining factors of profitability; however, investment regulation may lead to significant losses in the realizable value of fixed assets and an increase in the companies’ capital costs. Debt and a munificent environment only affect medium-sized companies. We found some benefits for large companies derived from non-transparent institutional environments.
关键词：business performance; regulated industries; electric utilities; gas utilities; cluster analysis
