Indoor agriculture (IA) has emerged as a promising solution to address global challenges such as increasing food demand and limited natural resources. The potential benefits of IA as a sustainable agricultural production method have been widely discussed, but the industry's success hinges on consumer acceptance of IA technology and their willingness to consume leafy greens produced through this innovative approach. This dissertation aims to explore consumer attitudes and preferences towards IA, as well as to propose a comprehensive optimization model for sustainable IA systems in urban settings.The first chapter focuses on understanding consumer acceptance of IA produce. By employing cluster analysis, distinct groups of U.S. leafy green consumers were identified, including "IA Skeptics," "IA Open," "IA Supportive," and "IA Engaged." The study reveals a strong positive consumer cluster with a broad willingness to consume IA produce, suggesting significant market opportunities for the IA industry. However, it also highlights the presence of consumers who have not yet formed a clear attitude towards IA technology. Consequently, the chapter suggests marketing strategies to expand consumer awareness and acceptance of IA produce. The second chapter investigates consumer preferences and willingness-to-pay (WTP) for leafy green attributes, particularly in relation to different production methods, including IA, field farming, and greenhouses. Through a discrete choice experiment, preferences and WTP for attributes such as taste, freshness, nutrient level, and food safety were assessed among U.S. leafy green consumers. The study identifies significant preference heterogeneity, categorized into three latent classes: 'quality seekers,' 'price conscious,' and 'focused practicals.' Notably, preference heterogeneity is higher for production methods, indicating that consumers' preferences for IA technology are still evolving. The chapter emphasizes that IA has the potential to achieve consumer acceptance but highlights the importance of understanding the varying WTP among different consumer segments. The third chapter addresses the optimization of IA systems for economic and environmental sustainability. By employing a multiobjective optimization framework, the study proposes a comprehensive optimization model that integrates a plant growth module, a cost module, and a revenue module. The model aims to optimize both profitability and energy use efficiency of IA systems in urban settings, using decision variables such as production schedule, farm size, and farm location. The findings reveal the trade-offs between profit and energy use efficiency within a short production schedule window, emphasizing the need for fine-tuning the production schedule based on preferences related to these two objectives. Furthermore, the optimal location of IA farms is found to vary based on farm size, suggesting the need for tailored approaches rather than a uniform strategy. By encompassing consumer acceptance, preferences, and optimization strategies, this dissertation contributes to the understanding and advancement of IA as a sustainable agricultural production method. The findings provide valuable insights for stakeholders in the IA industry, enabling them to develop strategies that enhance consumer acceptance, optimize IA systems, and promote sustainable food production for the growing urban population.
Read
