A model for simulating reputation dynamics in industrial districts

Giardini, Francesca; Tosto, Gennaro Di; Conte, Rosaria

doi:10.1016/j.simpat.2007.11.017

Cited by 21 publications

(20 citation statements)

References 10 publications

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“…Having a good reputation is a key element for success in a competitive market; customers will move to the most reputable suppliers. The reputation of a supplier can be the factor that determines whether an agent decides to sign a contract with one supplier or another (Giardini, Tosto, and Conte 2008).…”

Section: Results In the Fourth Scenario: Customers With Trustmentioning

confidence: 99%

Fairness in Recurrent Auctions With Competing Markets and Supply Fluctuations

Murillo¹,

López²,

Muñoz³

et al. 2012

Computational Intelligence

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Auctions have been used to deal with resource allocation in multiagent environments, especially in serviceoriented electronic markets. In this type of market, resources are perishable and auctions are repeated over time with the same or a very similar set of agents. In this scenario it is advisable to use recurrent auctions: a sequence of auctions of any kind where the result of one auction may influence the following one. Some problems do appear in these situations, as for instance, the bidder drop problem, the asymmetric balance of negotiation power or resource waste, which could cause the market to collapse. Fair mechanisms can be useful to minimize the effects of these problems. With this aim, we have analyzed four previous fair mechanisms under dynamic scenarios and we have proposed a new one that takes into account changes in the supply as well as the presence of alternative marketplaces. We experimentally show how the new mechanism presents a higher average performance under all simulated conditions, resulting in a higher profit for the auctioneer than with the previous ones, and in most cases avoiding the waste of resources.

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Section: Results In the Fourth Scenario: Customers With Trustmentioning

confidence: 99%

Fairness in Recurrent Auctions With Competing Markets and Supply Fluctuations

Murillo¹,

López²,

Muñoz³

et al. 2012

Computational Intelligence

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show abstract

“…In particular, through computer simulation, Burt (2001), Prietula (2001), Klos and Nooteboom (2001), Lin and Li (2003), Tychonov et al (2008), and Giardini et al (2008) elaborated on the specific issues of trust and reputation, which are crucial themes of this article. However, among these scholars, only Klos and Nooteboom (2001), Giardini et al (2008) and Tychonov et al (2008) deal with agents representing firms interacting at industry level, whereas the others modeled these phenomena at individual or organizational level.…”

Section: Methods Backgroundmentioning

confidence: 99%

“…However, among these scholars, only Klos and Nooteboom (2001), Giardini et al (2008) and Tychonov et al (2008) deal with agents representing firms interacting at industry level, whereas the others modeled these phenomena at individual or organizational level.…”

Section: Methods Backgroundmentioning

confidence: 99%

“…Based on Conte and Paolucci's (2002) theoretical approach, Giardini et al (2008) developed a model to study reputation dynamics in industrial districts. Its architecture and functioning is very similar to CIOPS model, because agents search for the best quality suppliers, the industry is structured into three segments, and under many other respects.…”

Section: Methods Backgroundmentioning

confidence: 99%

“…Besides some theoretical and implementation differences, Giardini's et al (2008) focus on the same issue of ours: the effects of cheating on the performance of a set of agents. Their results are consistent with ours excepted the one concerning FT performance, which in their model is always lower than that of FP, while in our model FT perform as well as FP with honest agents and better with cheating agents, and far better when industry size is large.…”

Section: Model Validity and Dockingmentioning

confidence: 99%

See 2 more Smart Citations

Opportunism by cheating and its effects on industry profitability. The CIOPS model

Biggiero

Sevi

2009

Comput Math Organ Theory

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CIOPS (Cognitive Inter-organizational Production System) is an agentbased model that integrates industry structural aspects and agents' cognitive characteristics. A demand-driven industry, whose profitability depends on the quality of suppliers' products, is represented by a three-stage vertically integrated industry. Four types of decision-making patterns are analyzed and confronted each other: from the simplest one (random choice) to the most complex one, which includes direct and indirect experience and reputation. They operate as selection devices supporting agents to select the best suppliers. Requiring agents' communication, indirect experience and reputation could be influenced by eventual opportunist behaviors. As the disturbing effect of falsity depends also on the size of decision and information space, the CIOPS model simulates different situations. Even though submitted to some restrictive assumptions, by testing five groups of hypotheses CIOPS model enables to fix many points that could be tested by empirical data and further developed by relaxing the assumptions. Results show that, especially in presence of reputation-based trust, cheating attitude severely damages industry profitability and the enlargement of information space dramatically strengthens the negative effects. Though indirect experience and reputation-based trust are powerful tools to improve industry profitability, when people cheat they dramatically reverses its effects. A sharp performance diversity is also evidenced between industry segments, because firms in the first tiers segment, who are also the suppliers of final producers, perform much better and more efficiently than final producers. Though industry size growth determines the negative url: www.knownetlab.it 192 L. Biggiero, E. Sevi effect of reducing performance, it produces the positive effect of shortening the time to reach the highest profitability and to stabilize it. Finally, it is also demonstrated that cheating half times determines almost the same negative impact of cheating always.

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Impact of Trust on Agent-Based Simulation for Supply Chains

Jalbut

Sichman

2019

Multi-Agent-Based Simulation XIX

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A model for simulating reputation dynamics in industrial districts

Cited by 21 publications

References 10 publications

Fairness in Recurrent Auctions With Competing Markets and Supply Fluctuations

Fairness in Recurrent Auctions With Competing Markets and Supply Fluctuations

Opportunism by cheating and its effects on industry profitability. The CIOPS model

Impact of Trust on Agent-Based Simulation for Supply Chains

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