Agent-based simulation for computational experimentation: Developing an artificial labor market

Chaturvedi, Alok; Mehta, Shailendra Raj; Dolk, Daniel R.; Ayer, R. W.

doi:10.1016/j.ejor.2004.03.040

Cited by 23 publications

(12 citation statements)

References 15 publications

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“…In the literature, agents are usually defined as autonomous software entities that exhibit intelligent behavior which resembles that of customers and business organizations [3,7,15,42,55]. Because agent-based models can capture the characteristics of independent entities naturally and realistically, it is increasingly being regarded as a powerful tool for analyzing the complex dynamics of customers and businesses in various market environments [14,29,35,44,47,48,51,53]. There are other types of studies that apply traditional operations research techniques to modeling and analyzing customer behavior.…”

Section: Customer Behavior Modelsmentioning

confidence: 99%

Evaluating customer aid functions of online stores with agent-based models of customer behavior and evolution strategy

Ahn

2010

Information Sciences

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Section: Customer Behavior Modelsmentioning

confidence: 99%

Evaluating customer aid functions of online stores with agent-based models of customer behavior and evolution strategy

Ahn

2010

Information Sciences

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“…Ce constat s'applique aussi aux travaux recensés dans les revues de littérature de Terzi et Cavalieri (2004) traitant de la simulation dans un contexte de chaîne logistique, de Monostori et al (2006) portant sur les systèmes multi-agents pour modéliser et simuler des systèmes manufacturiers, et enfin de Ko et al (2010) traitant des applications informatiques dédiées à la gestion des chaînes logistiques. Afin de modéliser et de simuler de manière individuelle les attentes et les comportements, de nombreux travaux s'appuient sur le paradigme agent pour représenter à large échelle de multiples consommateurs (Ben Said et al, 2002), la dynamique du système induite par leurs interactions avec un marché écono-mique (Chaturvedi et al, 2005), ou avec une chaîne logistique (Labarthe et al, 2007). Toute la difficulté de représentation réside alors dans la définition de profils de consommateurs et dans les caractéristiques qui leurs sont associées.…”

Section: Revue De Littératureunclassified

Modélisation de la demande et du comportement des consommateurs pour la simulation de chaînes logistiques de biens de consommation à haute valeur ajoutée

Cloutier

Montreuil

Labarthe

et al. 2010

Logistique & Management

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Cet article propose une approche de modélisation de la demande permettant de représenter explicitement le comportement des consommateurs dans le cadre de simulations holistiques de chaînes logistiques de biens de consommation à haute valeur ajoutée. La demande globale sur une période de simulation est détaillée de façon à considérer les besoins personnalisés de consommateurs interagissant avec un réseau de détaillants. L'approche de modélisation des comportements clients, l'approche de génération de la demande ainsi que des résultats de simulation représentatifs sont présentés dans cet article.

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“…An intuitive argument is to interview participants to develop a well-established decision-making process, such as has been done in wholesale electric power markets [Koesrindartoto et al 2005;Macal and North 2005] and labor markets [Chaturvedi et al 2005], but the literature indicates that this approach can be problematic in general context. Only when the rules by which decision makers operate may be clearly defined can we know what questions to ask the decision makers and in turn they know what kinds of answers we expect.…”

Section: Background: Abstraction and Methodsmentioning

confidence: 99%

Open- and Closed-Loop Supply Chain Dynamics: Specification and Exploration of an Agent-based Model

Ruebeck

Pfaffmann

2010

Eastern Econ J

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We develop an inter-firm shipping pallet supply chain model and explore the geographic features of market structures that can evolve within it, focusing on the common resource nature of pallet durability. While exploring the model's parameter space we find regions in which the outcomes do not put the model's assumptions in doubt. The insights reveal modeling considerations for an "open-loop" structure, where the shipping pallets received by retailers pass through third parties before returning to manufacturers. Our approach to validation is at the level of "stylized facts," accepting model parameters that produce outcomes matching characteristics of firms' geographic location. Eastern Economic Journal (2011Journal ( ) 37, 85-109. doi:10.1057Journal ( /eej.2010 Keywords: agent-based modeling; validation; supply chain; shipping pallet; common resource JEL: C63; L14; L23; L73; L81 INTRODUCTIONEnvironmental concerns are important drivers of innovation today, and such issues are pervasively linked to the supply chain of every good we produce and consume [Thomas and Griffin 1996]. The supply chain itself has impacts that are difficult to model [Mabert and Venkataramanan 1998]. We study an important component of delivering goods from producer to retailer: the shipping pallet.Shipping pallets are used at every stage of production, including distributing material within the firm. For simplicity, we focus on the final step of shipment to the retailer, a significant component of total pallet use [Freedonia 2008]. This final step is particularly important because the pallet is moving between economic actors. While a pallet stays within a firm, the firm's incentives to manage its private resources align well with the optimal social outcome, but as the pallet moves between firms, natural externalities may cause the firm's optimal choice to diverge from social welfare.This investigation is part of a larger effort to include the effects of private incentives -market interactions -in environmental policy considerations, particularly when performing a life cycle analysis (LCA) on a system of interest. We are not the first to use agent-based modeling in a supply chain context [see, e.g., Swaminathan et al. 1998;Choi et al. 2001;Gosling 2003;Hensher and Puckett 2005;Chaturvedi et al. 2006;Gosling et al. 2006]. Our innovation is to link this analysis with policy making. To date the LCA policy tool does too little to recognize the interaction between policy and markets [Fischhoff and Small 2000] and also does not address durable goods issues well [Cooper 2005]. Our approach to melding policy interests and markets is through agent-based modeling of the market Eastern Economic Journal, 2011, 37, (85-109) r 2011 EEA 0094-5056/11 www.palgrave-journals.com/eej/ itself. This will allow the policy maker to observe and interact with the model as it demonstrates the consequences of changed market incentives.In this paper we describe our model's structure and the results from validating at the level of a "stylized fact." In particular, we de...

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Agent-based simulation for computational experimentation: Developing an artificial labor market

Cited by 23 publications

References 15 publications

Evaluating customer aid functions of online stores with agent-based models of customer behavior and evolution strategy

Evaluating customer aid functions of online stores with agent-based models of customer behavior and evolution strategy

Modélisation de la demande et du comportement des consommateurs pour la simulation de chaînes logistiques de biens de consommation à haute valeur ajoutée

Open- and Closed-Loop Supply Chain Dynamics: Specification and Exploration of an Agent-based Model

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