System Engineering and Productivity

System Engineering and Productivity

Estimation of Step Change Point in Business Models by Simultaneously Considering Discrete and Continuous Indicators

Document Type : Research Paper

Authors
Erfaneh Pourzarkeshian 1
Mohammad Reza Maleki 2
Mohsen Ahmadvand 3
1 M.Sc.,, Department of Industrial Engineering, Faculty of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran
2 Corresponding author: Assistant Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran
3 Lecturer, Department of Industrial Engineering, Faculty of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran
10.22034/sep.2022.243410
Abstract
In today's society, despite the fierce market competition for more income, it is necessary that the business models used are up-to-date and appropriate models. In many cases, over time, the business model no longer meets the needs, which managers realize that the business model needs to change. And the main factor causing the change must be found, which will incur huge costs for the business. Therefore, it is necessary to find the exact time of making changes so that the two main points of change can be followed by the factors causing the change. Therefore, the purpose of this research is to find the point of change in the business model and provide a new approach to study and examine the time of making changes in each business and take corrective measures to improve the performance of the model. In many businesses, the factors under investigation are both discrete and continuous, which is why this study examines these indicators simultaneously. In this paper, the maximum likelihood method is developed to estimate the change point in a business model with mixed continuous and discrete data. For this purpose, the inverse Norta method will be used to transform the data and the t-square control chart will be used to monitor the model. For this purpose, the type of change is considered to be a step type, and a real example related to a company active in the environmental field is used to demonstrate the capability of the presented model in estimating the change point. The simulation results show that the presented model has sufficient accuracy and precision to estimate the change point under different changes in the model.
Keywords
Business model
Change point
Business model change
Correlation
Maximum likelihood method

Copyright ©, Erfaneh Pourzarkeshian, Mohammad Reza Maleki, Mohsen Ahmadvand

 

License

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System Engineering and Productivity
Volume 2, Issue 2 - Serial Number 3
Serial No. 3, Summer Quarterly
Summer 2022
Pages 49-72

  • Receive Date 05 June 2022
  • Revise Date 06 August 2022
  • Accept Date 11 August 2022
  • First Publish Date 11 August 2022
  • Publish Date 23 August 2022