scholarly journals Social identity and meat consumption - An agent-based model

2021 ◽  
Author(s):  
Jiaqi Ge ◽  
Andrea Scalco ◽  
Tony Craig
Keyword(s):  
Social Identity ◽  
Social Interactions ◽  
Large Scale ◽  
Eating Behaviour ◽  
System Level ◽  
Dietary Behaviour ◽  
Agent Based Model ◽  
Agent Based ◽  
Meat Eating ◽  
Group Members

Humans are social animals. Even the very personal decision of what someone eats is influenced by others around them. In this study, we propose four social interaction mechanisms driven by social identity that affect a person’s decision to eat or not eat meat. Using data from the British Social Attitude Survey in 2014, we operationalise social identity in an agent-based model to study the effect of social interactions on the spread of meat-eating behaviour in the British population. We find that social interactions are crucial in determining the spread of meat-eating behaviour. In order to bring about large-scale behavioural changes at the system level, people need to 1) have a strong openness to influences from both in-group and out-group members who have a different dietary behaviour, and 2) have a weak tendency to reinforce their current behaviour after seeing in-group members sharing the same behaviour. The agent-based model is shown to be a useful tool to operationalise social theories in a well-defined context, and to upscale the system to study its dynamic evolutions under different scenarios.

Gaming the System: An Agent-Based Model of Estimation Strategies and their Effects on System Performance

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
John Meluso ◽  
Jesse Austin-Breneman
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
System Level ◽  
Conservation Strategy ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Bias Estimation ◽  
Agent Based Model ◽  
Agent Based ◽  
Complex Engineered Systems

Parameter estimates in large-scale complex engineered systems (LaCES) affect system evolution, yet can be difficult and expensive to test. Systems engineering uses analytical methods to reduce uncertainty, but a growing body of work from other disciplines indicates that cognitive heuristics also affect decision-making. Results from interviews with expert aerospace practitioners suggest that engineers bias estimation strategies. Practitioners reaffirmed known system features and posited that engineers may bias estimation methods as a negotiation and resource conservation strategy. Specifically, participants reported that some systems engineers “game the system” by biasing requirements to counteract subsystem estimation biases. An agent-based model (ABM) simulation which recreates these characteristics is presented. Model results suggest that system-level estimate accuracy and uncertainty depend on subsystem behavior and are not significantly affected by systems engineers' “gaming” strategy.

Gaming the System: An Agent-Based Model of Estimation Strategies and Their Effects on System Performance

2017 ◽  
Author(s):  
John Meluso ◽  
Jesse Austin-Breneman
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Model Simulation ◽  
System Level ◽  
Conservation Strategy ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Bias Estimation ◽  
Agent Based Model ◽  
Agent Based

Parameter estimates in large-scale complex engineered systems affect system evolution yet can be difficult and expensive to test. Systems engineering uses analytical methods to reduce uncertainty, but a growing body of work from other disciplines indicates that cognitive heuristics also affect decision-making. Interviews with several expert aerospace practitioners suggest that engineers bias estimation strategies. Practitioners reaffirmed known system features and posited that engineers may bias estimation methods as a negotiation and resource conservation strategy. Specifically, participants reported that some systems engineers “game the system” by biasing requirements to counteract subsystem estimation biases. An agent-based model simulation which recreates these characteristics is presented. Model results suggest that the systems engineers’ “gaming” strategy of counteracting subsystem bias may decrease system-level estimate accuracy and increase uncertainty.

Learning by failure vs learning by habits

2017 ◽  
Vol 23 (3) ◽  
pp. 524-546 ◽  
Author(s):  
Lorella Cannavacciuolo ◽  
Luca Iandoli ◽  
Cristina Ponsiglione ◽  
Giuseppe Zollo
Keyword(s):  
Learning Strategies ◽  
Diffusion Of Innovation ◽  
System Level ◽  
Alternative View ◽  
Agent Based Model ◽  
Content Type ◽  
Agent Based ◽  
Business Transactions ◽  
Virtual Lab ◽  
Start Up

Purpose The purpose of this paper is to explain the emergence of collaboration networks in entrepreneurial clusters as determined by the way entrepreneurs exchange knowledge and learn through business transactions needed to implement temporary supply chains in networks of co-located firms. Design/methodology/approach A socio-computational approach is adopted to model business transactions and supply chain formation in Marshallian industrial districts (IDs). An agent-based model is presented and used as a virtual lab to test the hypotheses between the firms’ behaviour and the emergence of structural properties at the system level. Findings The simulation findings and their validation based on the comparison with a real world cluster show that the topological properties of the emerging network are influenced by the learning strategies and decision-making criteria firms use when choosing partners. With reference to the specific case of Marshallian IDs it is shown that inertial learning based on history and past collaboration represents in the long term a major impediment for the emergence of hubs and of a network topology that is more conducive to innovation and growth. Research limitations/implications The paper offers an alternative view of entrepreneurial learning (EL) as opposed to the dominant view in which learning occurs as a result of exceptional circumstances (e.g. failure). The results presented in this work show that adaptive, situated, and day-by-day learning has a profound impact on the performance of entrepreneurial clusters. These results are encouraging to motivate additional research in areas such as in modelling learning or in the application of the proposed approach to the analysis of other types of entrepreneurial ecosystems, such as start-up networks and makers’ communities. Practical implications Agent-based model can support policymakers in identifying situated factors that can be leveraged to produce changes at the macro-level through the identification of suitable incentives and social networks re-engineering. Originality/value The paper presents a novel perspective on EL and offers evidence that micro-learning strategies adopted and developed in routine business transactions do have an impact on firms’ performances (survival and growth) as well as on systemic performances related to the creation and diffusion of innovation in firms networks.

The Peculiar Temporality of Violence: a Source of Perplexity about Social Power

KronoScope ◽  
2002 ◽  
Vol 2 (1) ◽  
pp. 41-69 ◽  
Author(s):  
Robert Thornton
Keyword(s):  
Social Identity ◽  
Social Interactions ◽  
Social Relations ◽  
Large Scale ◽  
Social Power ◽  
Violent Event ◽  
Final Cause ◽  
The Past ◽  
Social Forms ◽  
Origin Myths

AbstractMost national myths of origin begin with some transcendent or sacrificial story of violent revolution, warfare or liberation. This is also true of many origin myths of ethnic, tribal or other forms of social identity. This makes it appear that some act of violence is the cause of their coming into being. This paper argues that this is an artefact of the temporal 'peculiarity' of violence. Violent events, it is argued, are essentially unpredictable even when statistically probable. This means that violence is only 'visible' after the fact, and rarely before and that plausible causal models can rarely be constructed in advance. Violence is always seen in retrospect, then, and where it has caused significant death and destruction, it requires that we begin to make sense of what caused it. Unlike other planned or and emotionally charged social interactions (such as eating, sexuality, ritual) acts of violence interrupt (disrupt, breach, rupture, break, etc.) and terminate parts or all of previous social relations. Since the cause of violence can only be assigned retrospectively, this means that we must (re-)construct the past in a way that allows us to make sense of it. Where some violent event is followed by the eventual emergence of a new identity, the new identity is often explained as having 'originated' in violence. This implies that violence caused the new social identity in some way, and that it functions as a political instrument. But violence can only create a void, and is chaotic. After violence, we require the (re-)telling of the past in a new way. This makes violence appear at the beginning of narratives of origin, but does not imply that violence caused these identities. Since large scale violence leads cultural loss and to large scale social (re)construction, narratives of identity tend to begin at these moments in time. This account of violence seeks, therefore, to undermine the notion that violence is an efficient or final cause of social forms.

scholarly journals An Agent-Based Model of Social Identity Dynamics

2012 ◽  
Vol 15 (4) ◽  
Author(s):  
Paul Smaldino ◽  
Cynthia Pickett ◽  
Jeffrey Sherman ◽  
Jeffrey Schank
Keyword(s):  
Social Identity ◽  
Agent Based Model ◽  
Agent Based

scholarly journals An Agent Based Model to Detect Variations in the Transmission of Potters from Baetica Province

2021 ◽  
Author(s):  
Maria Coto-Sarmiento ◽  
Simon Carrignon
Keyword(s):  
Roman Empire ◽  
Social Learning ◽  
Material Culture ◽  
Learning Strategies ◽  
Large Scale ◽  
Scale Production ◽  
Agent Based Model ◽  
Pottery Production ◽  
Agent Based ◽  
Modes Of Transmission

The goal of this study is to analyse the transmission of technical skills among potters within the Roman Empire. Specifically, our case study has been focused on the production processes based on Baetica province (currently Andalusia) from 1st to 3rd century AD. Variability of material culture allows observing different production patterns that can explain how social learning evolves. Some differences can be detected in the making techniques processes through time and space that might explain different degrees of specialization. Unfortunately, it is extremely difficult to identify some evidence of social learning strategies in the archaeological record. In Archaeology, this process has been analysed by the study of the production of handmade pottery. In our case, we want to know if the modes of transmission could be similar with a more standardized production as Roman Age. We propose here an Agent-Based Model to compare different cultural processes of learning transmission. Archaeological evidence will be used to design the model. In this model, we implement a simple mechanism of pottery production with different social learning processes under different scenarios. In particular, the aim of this study is to quantify which one of those processes explain better the copying mechanisms among potters revealed in our dataset. We believe that the model presented here can provide a strong baseline for the exploration of transmission processes related to large-scale production.

scholarly journals Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model

2020 ◽  
Author(s):  
Junjiang Li ◽  
Philippe J. Giabbanelli
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Contact Tracing ◽  
Remote Work ◽  
Agent Based Model ◽  
Agent Based ◽  
Global Pandemic ◽  
Small Set ◽  
Factorial Design Of Experiments ◽  
The Individual

AbstractThere is a range of public health tools and interventions to address the global pandemic of COVID-19. Although it is essential for public health efforts to comprehensively identify which interventions have the largest impact on preventing new cases, most of the modeling studies that support such decision-making efforts have only considered a very small set of interventions. In addition, previous studies predominantly considered interventions as independent or examined a single scenario in which every possible intervention was applied. Reality has been more nuanced, as a subset of all possible interventions may be in effect for a given time period, in a given place. In this paper, we use cloud-based simulations and a previously published Agent-Based Model of COVID-19 (Covasim) to measure the individual and interacting contribution of interventions on reducing new infections in the US over 6 months. Simulated interventions include face masks, working remotely, stay-at-home orders, testing, contact tracing, and quarantining. Through a factorial design of experiments, we find that mask wearing together with transitioning to remote work/schooling has the largest impact. Having sufficient capacity to immediately and effectively perform contact tracing has a smaller contribution, primarily via interacting effects.

scholarly journals Real-time Analysis of City Scale Transportation Networks in New Orleans Metropolitan Area using an Agent Based Model Approach

2019 ◽  
Vol 271 ◽  
pp. 06007
Author(s):  
Millard McElwee ◽  
Bingyu Zhao ◽  
Kenichi Soga
Keyword(s):  
New Orleans ◽  
Real Time ◽  
High Performance ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Regional Scale ◽  
Agent Based Model ◽  
Agent Based ◽  
Real Time Analysis

The primary focus of this research is to develop and implement an agent-based model (ABM) to analyze the New Orleans Metropolitan transportation network near real-time. ABMs have grown in popularity because of their ability to analyze multifaceted community scale resilience with hundreds of thousands of links and millions of agents. Road closures and reduction in capacities are examples of influences on the weights or removal of edges which can affect the travel time, speed, and route of agents in the transportation model. Recent advances in high-performance computing (HPC) have made modeling networks on the city scale much less computationally intensive. We introduce an open-source ABM which utilizes parallel distributed computing to enable faster convergence to large scale problems. We simulate 50,000 agents on the entire southeastern Louisiana road network and part of Mississippi as well. This demonstrates the capability to simulate both city and regional scale transportation networks near real time.

How the Mechanism of Dynamic Representation Affects Policy Change and Stability

2016 ◽  
Vol 38 (1) ◽  
Author(s):  
Simon Tobias Franzmann ◽  
Johannes Schmitt
Keyword(s):  
Policy Change ◽  
Party System ◽  
Party Competition ◽  
System Level ◽  
Agent Based Model ◽  
Additional Mechanism ◽  
Agent Based ◽  
Veto Player ◽  
Dynamic Representation ◽  
Veto Points

AbstractIn politics, we often observe stasis when, at first sight, no reason exists for such policy blockades. In contrast., we sometimes see policy change when one would expect blockades resulting from veto points or countervailing majorities. How can we explain these contradictory results concerning policy stability? In order to solve this theoretical puzzle, we develop an agent-based model (ABM). We combine established models of veto player theory (Tsebelis 2002: Ganghof-Bräuninger 2006) with the findings of political sociology and party competition. By aggregating previous party-level findings, we show that dynamic representation (Stimson et. al. 1995) provides an additional mechanism that can explain these macro-level outcomes. Parties behaving responsively to their electorate do not automatically guarantee perfect responsivity on the party system level. Further, if opposition parties also fear punishment by the electorate for government inaction, the opposition behaves more accommodatingly than previous approaches have predicted.

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