scholarly journals A Two-Step Methodology for Free Rider Mitigation with an Improved Settlement Algorithm: Regression in CBL Estimation and New Incentive Payment Rule in Residential Demand Response

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3417 ◽  
Author(s):  
Eunjung Lee ◽  
Dongsik Jang ◽  
Jinho Kim
Keyword(s):  
Demand Response ◽  
Electricity Consumption ◽  
Free Rider ◽  
Estimation Accuracy ◽  
Peak Time ◽  
Incentive Payment ◽  
Step Method ◽  
Free Riders ◽  
Free Rider Problem ◽  
Baseline Estimation

Recent demand response (DR) research efforts have focused on reducing the peak demand, and thereby electricity prices. Load reductions from DR programs can be viewed as equivalent electricity generation by conventional means. Thus, utility companies must pay incentives to customers who reduce their demand accordingly. However, many key variables intrinsic to residential customers are significantly more complicated compared to those of commercial and industrial customers. Thus, residential DR programs are economically difficult to operate, especially because excess incentive settlements can result in free riders, who get incentives without reducing their loads. Improving baseline estimation accuracy is insufficient to solve this problem. To alleviate the free rider problem, we proposed an improved two-step method—estimating the baseline load using regression and implementing a minimum-threshold payment rule. We applied the proposed method to data from residential customers participating in a peak-time rebate program in Korea. It initially suffered from numerous free riders caused by inaccurate baseline estimation. The proposed method mitigated the issue by reducing the number of free riders. The results indicate the possibility of lowering the existing incentive payment. The findings indicate that it is possible to run more stable residential DR programs by mitigating the uncertainty associated with customer electricity consumption.

The Measles and Free Riders

2016 ◽  
Vol 25 (3) ◽  
pp. 472-478 ◽  
Author(s):  
KATHARINE BROWNE
Keyword(s):  
Collective Action ◽  
Free Rider ◽  
Collective Action Problem ◽  
Free Riders ◽  
Free Rider Problem ◽  
Free Ride ◽  
Game Theoretic ◽  
Parental Decisions

Abstract:This article takes up a game-theoretic perspective on California’s recently passed bill (SB 277) that closes all nonmedical exemptions for school-mandated vaccination. Such a perspective characterizes parental decisions to vaccinate their children as a collective action problem and reveals the presence of an incentive to free ride—to enjoy the benefits of others’ efforts to vaccinate their children without vaccinating one’s own. This article defends California’s legislation as a reasonable means of overcoming the free rider problem and of ensuring that the burdens of vaccination are shared equally.

On the limits of unsolvability of the “free rider problem”

2016 ◽  
pp. 57-75
Author(s):  
A. Yudanov ◽  
O. Pyrkina ◽  
E. Bekker
Keyword(s):  
Mathematical Model ◽  
Markov Chain ◽  
Social Groups ◽  
Free Rider ◽  
Public And Private ◽  
Institutional Conditions ◽  
Free Riders ◽  
Free Rider Problem ◽  
Effective Decision ◽  
Absorbing States

The article reinterprets the classic «free rider problem» known as unsolvable from the position of how the free rider’s surrounding affects him. It introduces the concepts of public and private harm from the free rider’s activity. It also describes a wide variety of manifestations of the “free ridership” in which the private harm suffered by significant social groups is large enough to cause on their part an active opposition to free riders. According to the authors, under proper institutional conditions this opposition results in effective decision of the “free rider problem”. They offer a mathematical model of the process: the Markov chain with a single or multiple absorbing states.

Costs and benefits in hunter-gatherer punishment

2012 ◽  
Vol 35 (1) ◽  
pp. 19-20 ◽  
Author(s):  
Christopher Boehm
Keyword(s):  
Capital Punishment ◽  
Free Rider ◽  
Second Order ◽  
Costs And Benefits ◽  
Free Riders ◽  
Free Rider Problem ◽  
Social Structural ◽  
Ethnographic Analysis ◽  
Made In

AbstractHunter-gatherer punishment involves costs and benefits to individuals and groups, but the costs do not necessarily fit with the assumptions made in models that consider punishment to be altruistic – which brings in the free-rider problem and the problem of second-order free-riders. In this commentary, I present foragers' capital punishment patterns ethnographically, in the interest of establishing whether such punishment is likely to be costly; and I suggest that in many cases abstentions from punishment that might be taken as defections by free-riders are actually caused by social-structural considerations rather than being an effect of free-rider genes. This presentation of data supplements the ethnographic analysis provided by Guala.

scholarly journals Domestic Policies as Strategic Measures in Multinational Markets

2016 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Ali Dadpay
Keyword(s):  
Free Rider ◽  
Public Firms ◽  
Free Riders ◽  
Free Rider Problem ◽  
Strategic Measures ◽  
Private And Public ◽  
Domestic Policies

<p>This paper studies the role of privatization and subsidization policies as trade strategies in a single multinational market where private and public firms of different nationalities interact. It finds out when a country subsidizes its industry the rival country would have the incentive to retaliate by adopting a subsidization regime to prevent a free riders’ situation from happening when it moves to liberalize the market. However this step does not eliminate the free rider problem governments are facing in this market when they privatize their public firms unilaterally. </p>

scholarly journals How the Second-Order Free Rider Problem Is Solved in a Small-Scale Society

2017 ◽  
Vol 107 (5) ◽  
pp. 578-581 ◽  
Author(s):  
Sarah Mathew
Keyword(s):  
Free Rider ◽  
Second Order ◽  
Small Scale ◽  
High Stakes ◽  
Free Riders ◽  
Free Rider Problem ◽  
Outstanding Question ◽  
Moralistic Punishment

Moralistic punishment enables human cooperation, but an outstanding question is why people voluntarily sanction when they can obtain the benefits of punishment without being enforcers themselves. To address how decentralized societies solve this second-order free rider issue, I examine why people punish among the Turkana, a population in Kenya in which informal peer sanctioning sustains participation in high-stakes interethnic warfare. Using vignette experiments I show that Turkana subjects express punitive sentiments toward second-order free riders and those who sanction irresponsibly. The prevalence of such meta norms regulating punishment reveal a possible pathway by which moralistic punishment could have evolved.

scholarly journals Vaccine Refusal Is Not Free Riding

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ethan Bradley ◽  
Mark Navin
Keyword(s):  
Free Riding ◽  
Free Rider ◽  
Ethical Analysis ◽  
Costs And Benefits ◽  
Free Riders ◽  
Free Rider Problem ◽  
Vaccine Refusal ◽  
Policy Interventions ◽  
Community Protection ◽  
The Relationship

Vaccine refusal is not a free rider problem. The claim that vaccine refusers are free riders is inconsistent with the beliefs and motivations of most vaccine refusers. This claim also inaccurately depicts the relationship between an individual’s immunization choice, their ability to enjoy the benefits of community protection, and the costs and benefits that individuals experience from immunization and community protection. Modeling vaccine refusers as free riders also likely distorts the ethical analysis of vaccine refusal and may lead to unsuccessful policy interventions.

scholarly journals Nodes with the highest control power play an important role at the final level of cooperation in directed networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ali Ebrahimi ◽  
Marzieh Yousefi ◽  
Farhad Shahbazi ◽  
Mohammad Ali Sheikh Beig Goharrizi ◽  
Ali Masoudi-Nejad
Keyword(s):  
Free Rider ◽  
The Other ◽  
Public Goods Game ◽  
The Public ◽  
Free Riders ◽  
Control Power ◽  
Final Level ◽  
Input Signals ◽  
Tumoral Cells ◽  
Power Play

AbstractControllability of complex networks aims to seek the lowest number of nodes (the driver nodes) that can control all the nodes by receiving the input signals. The concept of control centrality is used to determine the power of each node to control the network. The more a node controls the nodes through connections in the network, the more it has the power to control. Although the cooperative and free-rider strategies and the final level of cooperation in a population are considered and studied in the public goods game. However, it is yet to determine a solution to indicate the effectiveness of each member in changing the strategies of the other members. In a network, the choice of nodes effective in changing the other nodes’ strategies, as free-riders, will lead to lower cooperation and vice versa. This paper uses simulated and real networks to investigate that the nodes with the highest control power are more effective than the hubs, local, and random nodes in changing the strategies of the other nodes and the final level of cooperation. Results indicate that the nodes with the highest control power as free-riders, compared to the other sets being under consideration, can lead to a lower level of cooperation and are, therefore, more effective in changing the strategies of the other nodes. The obtained results can be considered in the treatment of cancer. So that, destroying the tumoral cells with the highest control power should be a priority as these cells have a higher capability to change the strategies of the other cells from cooperators to free-riders (healthy to tumoral).

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