Promoting Sustainable Food Consumption: An Agent-Based Model About Outcomes of Small Shop Openings

A useful way of promoting sustainable food consumption is to consider the spread of food retail operations focused on food diversification, food specialization, and fresh and local products. These food shops are generally small, which is a great problem for survival against ruthless competition from supermarkets. Our research objective was to construct a simulation with an agent-based model, reproducing the local food consumption market and to investigate how a new, small food retailing shop interacts with this market. As a case study, the model simulates the opening of a small farmers' market. The intent of the model is to reproduce the current status of consumption for food products within a certain territorial context and given time period, and to investigate how consumers' behaviour changes with the opening of the new shop. As a result, we could predict changes in consumers' habits, the economic positioning of new, small shops and its best location. This information is of considerable interest for farmers' markets and also for policymakers

Applications of agent-based modelling and simulation in the agri-food supply chains

Agri-food supply chains (ASC) are an important application domain for Operational Research/Management Science. In particular, the use of agent-based simulation (ABS) has increased in ASC research in recent years. This paper reviews existing ASC research that use ABS. The review begins by analysing the characteristics of the models and modelling reported in the literature. It illustrates that existing modelling research features extensive use of: single echelon supply chains; cases from high and middle income countries; unprocessed food products, empirical (as opposed to hypothetical) data; decision-making related to production planning and investment; and the use of black box validation. The second part of the review uses bibliographic mapping to analyse areas in ASC research which are yet to be addressed using ABS. We find that areas such as collaboration and competition, buyer–seller relationships, and service are under-researched. In addition, key actors in ASC such as food processors, supermarkets and retailers have not been included in the ABS models reported. Furthermore, these models have yet to incorporate important supply chain management theories such as Transaction Cost Economics and Resource-Based View as part of their design

Improving and comparing data collection methodologies for decision rule calibration in agent-based simulation : a case study of dairy supply chain in Indonesia

This study contributes to human behaviour (decision rule) modelling in the agent based simulation, by improving the existing data collection methodologies and comparing their benefits. Improving data collection methodologies can help in developing a more realistic agent’s decision rule and increasing the validity and credibility of the final model. This study uses a dairy supply chain case because the actors in this context can have one to one correspondence with the agents in the simulation. This study begins by presenting a literature review on the applications of agent-based simulation in the agri-food supply chain. This literature review highlights existing agent-based modelling practices in the agri-food supply chain such as the scope of the modelling, data collection, validation and sensitivity analysis techniques. This study then proposes some improvements to the existing data collection methodologies namely questionnaire survey and role-playing game. This study proposes the use of a scenariobased questionnaire to improve the benefits of a questionnaire survey for decision rules calibration. While to extend the usefulness of role-playing game this study propose the use of the design of experiment, and game scaling based on empirical probability distribution. The improved data collection methods are then used to calibrate a base model that was developed from the previous literature. Primary data from 16 villages in Indonesia is used to elicit empirical decision rules in this calibration process. The result from simulation experiments shows that the improved data collection methods can produce models with higher operational validity. This study is concluded by evaluating the advantages and disadvantages of each data collection methodology