Bioeconomic Models

Author(s):  
Ihtiyor Bobojonov

Bioeconomic models are analytical tools that integrate biophysical and economic models. These models allow for analysis of the biological and economic changes caused by human activities. The biophysical and economic components of these models are developed based on historical observations or theoretical relations. Technically these models may have various levels of complexity in terms of equation systems considered in the model, modeling activities, and programming languages. Often, biophysical components of the models include crop or hydrological models. The core economic components of these models are optimization or simulation models established according to neoclassical economic theories. The models are often developed at farm, country, and global scales, and are used in various fields, including agriculture, fisheries, forestry, and environmental sectors. Bioeconomic models are commonly used in research on environmental externalities associated with policy reforms and technological modernization, including climate change impact analysis, and also explore the negative consequences of global warming. A large number of studies and reports on bioeconomic models exist, yet there is a lack of studies describing the multiple uses of these models across different disciplines.

2017 ◽  
Vol 21 (4) ◽  
pp. 499-511 ◽  
Author(s):  
Jon Edward Spragg

Purpose The purpose of this paper is to describe a framework for predicting the seasonal demand for fashion based on the Bass Diffusion model of demand and the Newsvendor inventory management model. Sales and inventory management simulations based on these models have been implemented in the Julia programming language to demonstrate how theoretical models can be made operational using open-source software for the benefit of small- to medium-scale enterprises with limited resources. Design/methodology/approach The paper employs simulation models implemented in the Julia programming languages to explore the use of theoretical models of demand on the seasonal management of fashion inventory. Findings The research demonstrates that further exploration of the framework described is worth undertaking. Research limitations/implications The paper employs theoretical models and is therefore conceptual in its outlook. Nonetheless it provides insights that could be explored further if real-world sales data would become available. Practical implications The framework provides simple models for predicting the demand for fashion that allows “what-if” scenarios to be constructed based on the manipulation of a few model parameters. Social implications The framework provides low-cost analytical tools that support small fashion enterprises with regards to market understanding and the operational management requirements necessary to support those markets. Originality/value The analytical use of the Bass model of demand with the Newsvendor model of inventory management within a fashion context.


Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 91-96
Author(s):  
Patrick Jagla ◽  
Georg Jacobs ◽  
Justus Siebrecht ◽  
Stefan Wischmann ◽  
Jonathan Sprehe

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