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Theories that describe how people assign prices and make choices are typically based on the idea that both of these responses are derived from a common static, deterministic function used to assign utilities to options. However, preference reversals-where prices assigned to gambles conflict with preference orders elicited through binary choices-indicate that the response processes underlying these different methods of evaluation are more intricate. We address this issue by formulating a new computational model that assumes an initial bias or anchor that depends on type of price task (buying, selling, or certainty equivalents) and a stochastic evaluation accumulation process that depends on gamble attributes. To test this new model, we investigated choices and prices for a wide range of gambles and price tasks, including pricing under time pressure. In line with model predictions, we found that price distributions possessed stark skew that depended on the type of price and the attributes of gambles being considered. Prices were also sensitive to time pressure, indicating a dynamic evaluation process underlying price generation. The model out-performed prospect theory in predicting prices and additionally predicted the response times associated with these prices, which no prior model has accomplished. Finally, we show that the model successfully predicts out-of-sample choices and that its parameters allow us to fit choice response times as well. This price accumulation model therefore provides a superior account of the distributional and dynamic properties of price, leveraging process-level mechanisms to provide a more complete account of the valuation processes common across multiple methods of eliciting preference.

In this work, the techno-economic analysis of a 20,000 metric ton (MT) green ammonia production facility is presented. This facility is 30 times smaller than a large-scale conventional process, producing ammonia from totally renewable resources: hydrogen from water electrolysis and nitrogen from pressure swing adsorption. Two different configurations of the Haber-Bosch (HB) process are investigated: high-pressure reaction-condensation (RXN-CON) and low-pressure reaction-absorption (RXN-ABS). Process simulation was implemented using ASPEN Plus, where the reactor and absorber columns were designed as a custom model. The results obtained were then used to estimate the total capital and operating costs. The high-pressure processing improves the single-pass conversion and loop efficiency but relies on costly compression, whereas the low-pressure processing is more favorable for both capital and operating costs. The performance analysis of the FIB process indicates that the operating pressure affects ammonia production costs. The levelized cost of ammonia (LCOA) from our small-scale Haber process was found to be about twice more expensive than the conventional commodity ammonia prices. Our sensitivity analysis suggests that inherently safer low-pressure RXN-ABS can be utilized for thermochemical energy storage of renewable resources-for scenarios that numerous small ammonia plants can be implemented in areas with local ammonia demand, with access to excess renewable electricity at the time of high penetration of renewable resources. Under such conditions, the LCOA from this plant can be comparable with the ammonia commodity prices. When the revenue from selling oxygen is considered into economics, small-scale all-electric ammonia can be profitable with an after-tax rate of return of 27.50% for RXN-ABS.