Regression Analysis Of Inter-Variable Relationships Within Business Canvas Model: Value Proposition, Key Resources, Revenue And Cost Structure With The Cobb Douglass Production Function Approach (Study Case: Basic And Chemical Industries From 2006-2017)
In the 21st century disruptive era, in order to survive a company must innovate their business model constantly. In 2006 – 2017, the number of finish goods produced by base and chemical industry sector compare to agriculture and consumer goods sector were lower. Thus, this research tries to do regression with simultenous approach by analyzing variabel combined from the business model canvas concept by Osterwalter and Pigneur, 2010 and production function Cobb Douglas. The BMC was filled with financial report from Bloomberg. From the data, only several variables from BMC can be analyzed, the variables are value proposition, key resources, revenue and cost structure. This research also tries to analyze the relation between BMC internal variabel with external variabel from macro economy. The research results are revenue positively influence finish goods, while revenue is positively influenced by cost of good sols and external variabel national GDP. ARIMA forecast is done in static and dynamic model. From the static model founded that, from 2017-2018 BRNA and TPIA increase their finish goods significantly. For the longer prediction 2017 – 2025 a dynamic model is used, founded that all companies will not have significant growth in their finish goods production. The basic and chemical industry’s finish goods still going to be lower than agriculture and consumer goods industry. Concluded that manufacture industry that relates directly to human’s primary needs, the finish goods average will always be higher than basic industry and chemical in which this sector is not directly needed by human.
Keywords: business model canvas; production function cobb douglas; 2sls