Simulation-Based Participatory Modelling in Urban and Production Logistics: A Review on Advances and Trends

Abstract

Simulation-based participatory modelling allows integration of all types of knowledge including empirical, technical and scientific from all disciplines and domains. Thus, in recent years, the use of participatory modelling has been continuously increasing in many fields including logistics. With a view of achieving better understanding of the subject, this article systematically reviews the advances made in participatory modelling in the field of urban and production logistics in the last decade. It further reports the findings transparently following a categorization based on (i) the purpose of participatory modelling in the domain, and (ii) depending on the purpose how data is collected, processed and outcomes are presented. The review resulted in 97 articles which were analysed and categorized based on the above two questions formulated in the literature surveyed. The review revealed that apart from the three existing categories of purposes, namely, reflexive, descriptive and normative there is an emerging fourth category that was analytical in nature and 15 out of 97 articles analyzed belonged to this category. The authors decided to call this category analytical field empirical modelling which is primarily based on mathematical modelling and use of computational methods. We present these results with the help of a categorization. During the analysis for the second research question, we discovered that though the conventional ways of data collection and processing, such as interviews and workshops, which remain significantly present, in electronic data crowdsourcing and data processing via computational methods are emerging.

From novice to expert: advancing step-by-step simulation guideline for urban logistics with an open-source simulation tool

“…Yet, the task of meticulously crafting these simulation scenarios, tailored for participatory design, is daunting. It mandates a nuanced understanding of the urban landscape, bolstered by adept simulation modelling prowess (Raghothama and Meijer, 2015;Singh et al, 2021). Challenges manifest in requirement definition (Wiesner et al, 2015), simulation model granularity decision-making (Leavell, 2020) and data identification (Black, 1981).…”

“…A generic simulation model using SUMO was introduced to enhance understanding of how various factors and different decision levels could support the realisation of a specific SUMP (Singh et al. , 2022a, b). The objective was to deliver a multi-actor-based SUMP/SULP scenario model, primarily for urban and peri-urban areas.…”