The viability of novel network-level circular business models (CBMs) is debated heavily. Many companies are hesitant to implement CBMs in their daily practice, because of the various roles, stakes and opinions and the resulting uncertainties. Testing novel CBMs prior to implementation is needed. Some scholars have used digital simulation models to test elements of business models, but this this has not yet been done systematically for CBMs. To address this knowledge gap, this paper presents a systematic iterative method to explore and improve CBMs prior to actual implementation by means of agent-based modelling and simulation. An agent-based model (ABM) was co-created with case study participants in three Industrial Symbiosis networks. The ABM was used to simulate and explore the viability effects of two CBMs in different scenarios. The simulation results show which CBM in combination with which scenario led to the highest network survival rate and highest value captured. In addition, we were able to explore the influence of design options and establish a design that is correlated to the highest CBM viability. Based on these findings, concrete proposals were made to further improve the CBM design, from company level to network level. This study thus contributes to the development of systematic CBM experimentation methods. The novel approach provided in this work shows that agent-based modelling and simulation is a powerful method to study and improve circular business models prior to implementation.
Deployment and management of environmental infrastructures, such as charging infrastructure for Electric Vehicles (EV), is a challenging task. For policy makers, it is particularly difficult to estimate the capacity of current deployed public charging infrastructure for a given EV user population. While data analysis of charging data has shown added value for monitoring EV systems, it is not valid to linearly extrapolate charging infrastructure performance when increasing population size.We developed a data-driven agent-based model that can explore future scenarios to identify non-trivial dynamics that may be caused by EV user interaction, such as competition or collaboration, and that may affect performance metrics. We validated the model by comparing EV user activity patterns in time and space.We performed stress tests on the 4 largest cities the Netherlands to explore the capacity of the existing charging network. Our results demonstrate that (i) a non-linear relation exists between system utilization and inconvenience even at the base case; (ii) from 2.5x current population, the occupancy of non-habitual charging increases at the expense of habitual users, leading to an expected decline of occupancy for habitual users; and (iii) from a ratio of 0.6 non-habitual users to habitual users competition effects intensify. For the infrastructure to which the stress test is applied, a ratio of approximately 0.6 may indicate a maximum allowed ratio that balances performance with inconvenience. For policy makers, this implies that when they see diminishing marginal performance of KPIs in their monitoring reports, they should be aware of potential exponential increase of inconvenience for EV users.
In Eastern Africa, increasing climate variability and changing socioeconomic conditions are exacerbating the frequency and intensity of drought disasters. Droughts pose a severe threat to food security in this region, which is characterized by a large dependency on smallholder rain-fed agriculture and a low level of technological development in the food production systems. Future drought risk will be determined by the adaptation choices made by farmers, yet few drought risk models … incorporate adaptive behavior in the estimation of drought risk. Here, we present an innovative dynamic drought risk adaptation model, ADOPT, to evaluate the factors that influence adaptation decisions and the subsequent adoption of measures, and how this affects drought risk for agricultural production. ADOPT combines socio-hydrological and agent-based modeling approaches by coupling the FAO crop model AquacropOS with a behavioral model capable of simulating different adaptive behavioral theories. In this paper, we compare the protection motivation theory, which describes bounded rationality, with a business-as-usual and an economic rational adaptive behavior. The inclusion of these scenarios serves to evaluate and compare the effect of different assumptions about adaptive behavior on the evolution of drought risk over time. Applied to a semi-arid case in Kenya, ADOPT is parameterized using field data collected from 250 households in the Kitui region and discussions with local decision-makers. The results show that estimations of drought risk and the need for emergency food aid can be improved using an agent-based approach: we show that ignoring individual household characteristics leads to an underestimation of food-aid needs. Moreover, we show that the bounded rational scenario is better able to reflect historic food security, poverty levels, and crop yields. Thus, we demonstrate that the reality of complex human adaptation decisions can best be described assuming bounded rational adaptive behavior; furthermore, an agent-based approach and the choice of adaptation theory matter when quantifying risk and estimating emergency aid needs.
MULTIFILE
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
Elektrisch rijden staat aan de vooravond van een schaalsprong. De ambitie van zowel de Nederlandse overheid als internationale overheden is om binnen nu en 12 jaar alleen nog maar elektrische auto’s nieuw op de markt toe te laten. De elektrisch vervoer (EV) keten staat voor de grote uitdaging om deze schaalsprong op tijd met voldoende laadinfrastructuur te faciliteren. Nederlandse ketenpartners willen, net als de afgelopen jaren, koploper blijven op het gebied van EV-laadinfrastructuur en daarom goed voorbereid zijn op deze schaalsprong. De centrale praktijkvraag van de EV-ketenpartners is “Hoe kan de toekomstige laadbehoefte voor elektrische voertuigen in een snel groeiende markt met nieuwe gebruikersgroepen goed worden ingevuld?” Het doel van Future Charging is om bij te dragen aan de doorbraak van elektrisch rijden door kennis over de laadbehoefte van nieuwe gebruikersgroepen te ontwikkelen en toekomstig laadgedrag in een agent-based model te simuleren. Simulaties geven EV-ketenpartners concrete inzichten in effecten van toekomstscenario’s op het gebruik van laadinfrastructuur, de impact op het elektriciteitsnet en openbare ruimte. Deze kennis ondersteunt EV-ketenpartners bij de uitrol van toekomstbestendige laadinfrastructuur. In totaal brengt dit project 17 consortiumpartners bij elkaar waarmee de volledige EV-keten voor laadinfrastructuur vertegenwoordigd is: gemeenten, netbeheerders, laadpaal-exploitanten, energiebedrijven en gebruikers. De partners bieden hiermee een rijke praktijkomgeving waar continu kan worden geleerd over de veranderende laadbehoefte van verschillende gebruikersgroepen en in verschillende ruimtelijke settings: van grootstedelijk tot “laden in de regio”. Sinds 2014 beheert en monitort de Hogeschool van Amsterdam de laaddata voor G4/MRA-E. Meer dan 8,5 miljoen laadsessies zijn opgeslagen in een professioneel datawarehouse en middels beveiligde accounts toegankelijk voor onderzoek. Future Charging slaat de brug tussen theorie over laadbehoefte, laadgedrag en agent-based simuleren en de praktijk van laadinfrastructuur. Het resultaat is een praktisch toepasbaar simulatiemodel waarmee ontwerpstudies en praktijkcases worden doorgerekend.
Socio-economic pressures on coastal zones are on the rise worldwide, leaving increasingly less room for natural coastal change without affecting humans. The challenge is to find ways for social and natural systems to co-exist, co-develop and create synergies. The recent implementation of multi-functional, nature-based solutions (NBS) on the sandy Dutch coast seem to offer great potential in that respect. Surprisingly, the studies evaluating these innovative solutions paid little attention to how the social and natural systems interact in the NBS-modified coastal landscapes and if these interactions strengthen or weaken the primary functions of the NBS. It is not clear whether the objectives to improve coastal resilience and spatial quality will be met throughout the lifetime of the intervention. In the proposed project we will investigate the socio-bio-physical dynamics of anthropogenic sandy shores applying a Living Lab approach, documenting and analyzing interactions between evolving anthropogenic shores (Sand Motor and Hondsbossche Duinen, Fig.1) and people that use and manage these NBS-modified landscapes. Socio-bio-physical interactions will be investigated at various scales, and consequences for the long-term functionality of the NBS will be assessed, by coupling an agent-based social model and a cellular automata landscape model. By studying the behavior of the coupled system we aim to identify limits to, and optima in, multi-functionality of the NBS design, and will study how various stakeholders can influence the development of the NBS in desired directions with respect to primary NBS functions, including social and ecological goals. Together with consortium partners from public and private sectors we will co-create guidelines for management and maintenance of multifunctional NBS and design procedures and visualization tools for intervention design.
