A Comprehensive Economic Analysis of Vertical Farming: Quantitative Models and a Decision Support System for the Competitive Marketplace




Moghimi, Faraz

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There are various problems associated with our conventional practice of farming. In the past few years alone, agriculture has been responsible for a million square kilometers of deforestation. The world is facing a water crisis, and farming is responsible for using 80% of its freshwater. Also, the prospect of global climate change is projecting a much riskier future to practices of conventional farming due to more pesticide incidences, weather uncertainties, changing rain patterns, and more frequent climate extremes. One could argue that these alarming problems might someday be treated as more imminent as the population grows, less fertile land becomes available, and the effects of global climate change become more apparent. Vertical farming solves a lot of the discussed issues associated with traditional farming by using considerably less water, requiring less land, and not relying on the environmental conditions whatsoever. These are all excellent features, but vertical farming is also energy and labor intensive and can be quite expensive in some cases. This study worked to quantitatively model and evaluate the economic prospect of pursuing vertical farming as a business venture in a competitive marketplace under different circumstances. This effort is deeply needed by both the scholarly field and the young industry. This project initially develops a comprehensive stochastic theoretical model to evaluate vertical farming with respect to traditional farming in various conditions. This comprehensive theoretical model is then revised to match the real-world data. The revised model is then utilized to develop a Decision Support System that could help identify the best competitive location alternative to pursue vertical farming as a business practice. The system would account for both profit and risk decision factors as well as stakeholder preferences. Moreover, the developed Decision Support System is employed for a case study to locate the best location alternatives for implementing vertical farming in the US by considering the relative profit potentials and risks in each region. The results from the system identify the most suitable locations to pursue vertical farming as a business venture. These results also contribute towards forming a better understanding of current and future states of the vertical farming industry.



vertical farming, quantitative modeling, financial modeling, decision support system, economic analysis, business analytics, location based suitability


Moghimi, F. (2020). A comprehensive economic analysis of vertical farming: Quantitative models and a decision support system for the competitive marketplace (Unpublished thesis). Texas State University, San Marcos, Texas.


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