Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach

2015 ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Behzad Esmaeilian ◽  
Sara Behdad
Keyword(s):  
Electronic Waste ◽  
Peer Pressure ◽  
Waste Stream ◽  
Contributing Factors ◽  
Agent Based Simulation ◽  
Design Features ◽  
Agent Based ◽  
Consumer Decisions ◽  
Take Back ◽  
The Impact

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.

Simulation Modeling of Consumers' Participation in Product Take-Back Systems

2016 ◽  
Vol 138 (5) ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Behzad Esmaeilian ◽  
Sara Behdad
Keyword(s):  
Electronic Waste ◽  
Peer Pressure ◽  
Design Features ◽  
Agent Based ◽  
Simulation Tools ◽  
Lack Of Information ◽  
Choice Analysis ◽  
Take Back ◽  
Promising Solution ◽  
The Impact

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing may be a promising solution. However, the profitability of take-back systems is hampered by several factors, including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Factors that contribute to this unpredictability in the waste stream include product design features, consumers' awareness of recycling opportunities, sociodemographic characteristics, peer pressure, and the tendency of consumers to keep used items in storage. A system that helps predict when the consumer will stop using a product and store, resell, recycle, or discard it could help manufacturers better estimate return trends. The objective of this paper is to develop an agent-based simulation (ABS) framework that integrates a discrete choice analysis (DCA) technique to predict consumer end-of-use (EOU) decisions. The proposed simulation tools examine the impact of design features, interaction among individual consumers, and sociodemographic criteria related to the number of e-product returns. A numerical example of a cellphone take-back system has been provided to show the application of the model.

Agent Based Simulation Optimization of Waste Electrical and Electronics Equipment Recovery

2016 ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Sara Behdad ◽  
Jun Zhuang
Keyword(s):  
Life Cycle ◽  
Product Life Cycle ◽  
Electronic Waste ◽  
Recovery Process ◽  
Planning Horizon ◽  
Agent Based Simulation ◽  
Product Life ◽  
Agent Based ◽  
Take Back ◽  
Product Identity

The profitability of Electronic waste (e-waste) recovery operations is quite challenging due to various sources of uncertainties in quantity, quality and timing of returns originating from consumers’ behavior. The cloud-based remanufacturing concept, data collection and information tracking technologies seems a promising solution toward proper collection and recovery of product life cycle data under uncertainty. A comprehensive model that takes every aspect of recovery systems into account will help policy makers perform better decisions over a planning horizon. The objective of this study is to develop an Agent Based Simulation (ABS) framework to model the overall product take-back and recovery system based on the product identity data available through cloud-based remanufacturing infrastructure. Socio-demographic properties of the consumers, attributes of the take-back programs, specific characteristics of the recovery process and product life cycle information have been considered to capture the optimum buyback price proposed for a product with the aim of controlling the timing and quality of incoming used products to collection sites for recovery. A numerical example of an electronic product take-back system and a simulation-based optimization are provided to illustrate the application of the model.

Agent Based Simulation Optimization of Waste Electrical and Electronics Equipment Recovery

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Sara Behdad ◽  
Jun Zhuang
Keyword(s):  
Life Cycle ◽  
Product Life Cycle ◽  
Electronic Waste ◽  
Recovery Process ◽  
Planning Horizon ◽  
Agent Based Simulation ◽  
Product Life ◽  
Agent Based ◽  
Take Back ◽  
Product Identity

The profitability of electronic waste (e-waste) recovery operations is quite challenging due to various sources of uncertainties in the quantity, quality, and timing of returns originating from consumers' behavior. The cloud-based remanufacturing concept, data collection, and information tracking technologies seem promising solutions toward the proper collection and recovery of product life cycle data under uncertainty. A comprehensive model that takes every aspect of recovery systems into account will help policy makers perform better decisions over a planning horizon. The objective of this study is to develop an agent based simulation (ABS) framework to model the overall product take-back and recovery system based on the product identity data available through cloud-based remanufacturing infrastructure. Sociodemographic properties of the consumers, attributes of the take-back programs, specific characteristics of the recovery process, and product life cycle information have all been considered to capture the optimum buy-back price (bbp) proposed for a product with the aim of controlling the timing and quality of incoming used products to collection sites for recovery. A numerical example of an electronic product take-back system and a simulation-based optimization are provided to illustrate the application of the model.

scholarly journals Process Modeling and Simulation of Tableting—An Agent-Based Simulation Methodology for Direct Compression

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 996
Author(s):  
Niels Lasse Martin ◽  
Ann Kathrin Schomberg ◽  
Jan Henrik Finke ◽  
Tim Gyung-min Abraham ◽  
Arno Kwade ◽  
...  
Keyword(s):  
Raw Materials ◽  
Pilot Scale ◽  
Physical Models ◽  
Agent Based Simulation ◽  
Validation Data ◽  
Agent Based ◽  
Industrial Processing ◽  
Digital Twins ◽  
Product And Process ◽  
The Impact

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

scholarly journals Application of Agent-based Modeling for Cultural Information-based Decisions Making

2020 ◽  
Vol 88 ◽  
pp. 8-28
Author(s):  
Rimvydas Laužikas ◽  
Darius Plikynas ◽  
Vytautas Dulskis ◽  
Leonidas Sakalauskas ◽  
Arūnas Miliauskas
Keyword(s):  
Social Capital ◽  
Simulation Model ◽  
Cultural Participation ◽  
Agent Based Simulation ◽  
Research Issues ◽  
Agent Based ◽  
Cultural Events ◽  
The Social ◽  
Cultural Processes ◽  
The Impact

The impact of cultural processes on personal and social changes is one of the important research issues not only in contemporary social sciences but also for simulation of future development scenarios and evidence-based policy decision making. In the context of the theoretical concept of cultural values, based on the system theory and theory of social capital, the impact of cultural events could be analyzed and simulated by focussing on the construction/deconstruction of social capital, which takes place throughout the actor’s cultural participation. The main goal of this research is the development of measuring metrics, and agent-based simulation model aimed at investigation of the social impact of cultural processes.  This paper provides new insights of modeling the social capital changes in a society and its groups, depending on cultural participation. The proposed measurement metrics provide the measurement facility of three key components: actors, cultural events and events flow and social capital. It provides the initial proof of concept simulation results, - simplified agent-based simulation model showcase. The NetLogo MAS platform is used as a simulation environment.  

scholarly journals Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics

2021 ◽  
Vol 9 ◽  
Author(s):  
Longzhao Liu ◽  
Xin Wang ◽  
Xuyang Chen ◽  
Shaoting Tang ◽  
Zhiming Zheng
Keyword(s):  
Public Opinion ◽  
Large Scale ◽  
Confirmation Bias ◽  
Opinion Dynamics ◽  
Peer Pressure ◽  
Homogeneous Population ◽  
Agent Based ◽  
Collective Decisions ◽  
Personal Opinion ◽  
The Impact

Confirmation bias and peer pressure are regarded as the main psychology origins of personal opinion adjustment. Each show substantial impacts on the formation of collective decisions. Nevertheless, few attempts have been made to study how the interplay between these two mechanisms affects public opinion evolution on large-scale social networks. In this paper, we propose an agent-based model of opinion dynamics which incorporates the conjugate effect of confirmation bias (characterized by the population identity scope and initiative adaptation speed) and peer pressure (described by a susceptibility threshold and passive adaptation speed). First, a counterintuitive non-monotonous phenomenon arises in the homogeneous population: the number of opinion clusters first increases and then decreases to one as the population identity scope becomes larger. We then consider heterogeneous populations where “impressionable” individuals with large susceptibility to peer pressure and “confident” individuals with small susceptibility coexist. We find that even a small fraction of impressionable individuals could help eliminate public polarization when population identity scope is relatively large. In particular, the impact of impressionable agents would be greater if these agents are hubs. More intriguingly, while impressionable individuals have randomly distributed initial opinions, most of them would finally evolve to moderates. We highlight the emergence of these “impressionable moderates” who are easily influenced, yet are important in public opinion competition, which may inspire efficient strategies in winning competitive campaigns.

Agent Based Model to Analyze Consumer Behavior in Consuming the Electricity Energy

2015 ◽  
Vol 72 (4) ◽  
Author(s):  
Erma Suryani ◽  
Rully Agus Hendrawan ◽  
Umi Salama ◽  
Lily Puspa Dewi
Keyword(s):  
Consumer Behavior ◽  
Simulation Model ◽  
Environmental Awareness ◽  
Electricity Consumption ◽  
Point Of View ◽  
Agent Based Model ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Save Energy ◽  
The Impact

Several studies have been conducted regarding save energy in consuming the electricity through the simple changes in routines and habits. In the case of electricity consumption, consumer behavior might influenced by several factors such as consumer profession, season, and environmental awareness. In this paper, we developed an Agent Based Model (ABM) to analyze the behavior of different agents in consuming the electricity energy for each type of profession (agent) as well as their interaction with the environment. This paper demonstrates a prototype agent based simulation model to estimate the electricity consumption based on the existing condition and some scenarios to reduce the electricity consumption from consumer point of view. From the scenario results, we analyzed the impact of the save energy to increase the electrification ratio. 

scholarly journals Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Stephan Leitner ◽  
Friederike Wall
Keyword(s):  
Decision Making ◽  
Performance Improvement ◽  
Coordination Mode ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Multiobjective Decision Making ◽  
Overall Performance ◽  
Hierarchical Organizations ◽  
The Impact ◽  
Adaptive Walk

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions).

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