Decision Support System in Dynamic Pricing of Horticultural Products Based on the Quality Decline Due to Bacterial Growth

Abstract

A decision support system (DSS) was developed to help reduce food waste at traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. This computational tool includes two major functions: (1) the prediction of the remaining shelf life of fresh horticultural product, namely lettuce, onion, carrot, and cabbage based on its microbial growth status, governed by extrinsic and intrinsic parameters (temperature, water activity and pH, respectively). The remaining shelf life of the studied horticultural products is determined by using the online predictive food microbiology tool— the Combined Database for Predictive Microbiology (Combase). The time to reach the infectious doses of bacteria considered in the study for each of the four horticultural products are predicted; (2) the calculation of the dynamic price of the produce that should be set each day, depending on the predicted end of the marketing period to increase the demand and potential for sale to the final consumer. The proposed dynamic pricing model assumes a linear relation with the remaining shelf life of the analyzed vegetable to set the selling price. The shelf life determined by the DSS for optimal storage conditions is, in general, conservative, ensuring food safety. The automatic dynamic pricing gives new opportunities to small retailers to manage their business, fostering profit and simultaneously contributing to reduce food waste. Thus, this decision support system can contribute to the sustainable value of reducing food waste by providing information to small grocers and retailers on the safety of their perishable status depending on storage conditions and allowing them to suggest a fair price depending on that quality.

Development of a Decision Support System for Perishable Food Management in Culinary Education Institutions Using Machine Learning with Linear Regression

“…Perform crossvalidation to ensure the system's robustness and generalization to new data. (Pina et al, 2021)…”

Fuzzy Logic Decision Support System to Predict Peaches Marketable Period at Highest Quality

“…Pina et al [20] developed a DSS to help with food waste reduction for traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. The computational tool predicts the remaining shelf life of fresh horticultural products by determining when the doses of bacteria that affect these products reach the infectious threshold.…”

“…Additionally, the DSS encompasses the dynamic price of the products that should be set each day, depending on the predicted end of the marketing period. The shelf life determined by the DSS for optimal storage conditions is, in general, conservative, ensuring food safety [20]. Thus, the DSS contributes to sustainable development by promoting information to retailers and encouraging sustainable consumption based on perishable horticultural safety and quality across time and fair pricing depending on that quality.…”

“…Thus, the DSS contributes to sustainable development by promoting information to retailers and encouraging sustainable consumption based on perishable horticultural safety and quality across time and fair pricing depending on that quality. The effects of vegetables' regular distribution chain on bacterial growth should be quantified more effectively than by simply disregarding the lag phase, since this parameter may affect, both positively and negatively, the estimated remaining shelf life of a food product [20].…”

Forecasting Seasonal Sales with Many Drivers: Shrinkage or Dimensionality Reduction?

“…Ordering excess inventory, to reduce the risk of stock-outs and to improve customer's satisfaction, increases costs significantly (e.g., labor and storage) reducing the profit margin [7]. Additionally, there is an increasing awareness that food waste should be reduced [8,9] with the European Parliament calling for urgent measures to halve food waste by 2025 [10]. Efficient inventory management relies on accurate forecasts of SKU sales at the store level, which enable the retailer to replenish in time and meet the customers expectations.…”