Narrow Results

This paper examines the effects of uncertainty on an individual's own contribution to the provision of the collective good using an impure public good model. Two types of uncertainty analyzing free-riding behavior are evaluated: (i) uncertainty surrounding the contributions of others to the public characteristic and (ii) uncertainty surrounding the response of others to an individual's own contribution. We extend previous studies by examining both the compensated and uncompensated effects of increases in such risks on the provision of the collective good. We also establish the conditions that are sufficient to determine both compensated and the total, uncompensated effects of an increase in risk on the voluntary provision of the collective good.

With the rapid development of the Internet, many manufacturers nowadays are increasingly adopting a dual-channel strategy to sell their products. In this paper, we present an analytical framework in a single-channel supply chain and a dual-channel supply chain, respectively. We compare the optimal service levels under different scenarios to investigate the impacts of bidirectional free-riding and service competition on members' decisions. In order to realize system optimization, we propose contracts to coordinate the decentralized supply chain under different cases. We find that when a new channel is added, the retailer will always increase his service level to compete with the manufacturer, while the manufacturer needs to take the relationship with the retailer into consideration and decides whether to increase or decrease her service level. We also find that the contracts for different cases can make the optimal solutions the same as those under the centralized scenario by adjusting service levels based on the relative size of competition effect and spillover effect. Finally, we conduct numerical examples to verify the existence of Pareto improvement intervals and derive some managerial insights.

We consider a dynamic contribution game in which a group of agents collaborates to complete a public project. The agents exert efforts over time and get rewarded upon completion of the project, once the cumulative effort has reached a pre-specified level. We explicitly derive the cooperative solution and a noncooperative Markov-perfect Nash equilibrium. We characterize the set of socially efficient projects, i.e., projects that cooperative groups find worth completing. Comparing with the Markov-perfect Nash equilibrium, we find that noncooperative groups give up large socially efficient projects. Moreover, they take too much time to complete the projects that they undertake.

Briata, F. and Fragnelli, V. [2017] Free-riding in common facility sharing, in Transaction on Computation Collective Intelligence XXVII, pp. 129–138. dealt with the inefficiency and the free-riding situations that may arise from sharing the maintenance cost of a facility among its potential users and from dividing the cost of a check to assess who the users are among the agents that asked for it.They introduced two mechanisms for reducing the free-riding behaviors and considered the possibility that the check provides also information on the level at which the facility is used by each agent.

In this paper, we improve the profitability of the check, introducing a TU-cost game for determining the quota of the total cost assigned to each agent in order to satisfy as many agents as possible. Two solutions are proposed and analyzed and the balancedness of the TU-cost game is studied and characterized.

Nowadays, to cater the increasing green customers, firms have switched to green manufacturing. In a dual-channel green supply chain (DCGSC), customers experience products at offline stores and buy them online (free-riding). Often imprecise cognitive biases (“fairness concern” and “overconfidence”) are observed among the supply chain (SC) members. With these facts, this study introduces the free-riding and above cognitive biases in a DCGSC with a manufacturer selling a green product through own online and offline retail channels and examines their effects. A centralized and four decentralized models (for green and nongreen products) are formulated depending upon channel members’ cognitive biases individually and jointly with and without free-riding. The fuzzy objectives and constraints are made deterministic using expectation and possibility measures, respectively. Models are solved and illustrated numerically. The results indicate that free-riding is harmful and beneficial to retailer and manufacturer, respectively. Manufacturer’s overconfidence enhances the retailer’s profit but decreases or increases own profit depending upon the salvage value. Retailer’s fairness concern is catastrophic for manufacturer but beneficial for her. Product greening increases manufacturer’s profit than the carbon tax regulation for lower emissions. In addition to above observations, for maximum profit, management should not go for greening beyond an optimum level.

We consider a dynamic contribution game in which a group of agents collaborates to complete a public project. The agents exert efforts over time and get rewarded upon completion of the project, once the cumulative effort has reached a pre-specified level. We explicitly derive the cooperative solution and a noncooperative Markov-perfect Nash equilibrium. We characterize the set of socially efficient projects, i.e., projects that cooperative groups find worth completing. Comparing with the Markov-perfect Nash equilibrium, we find that noncooperative groups give up large socially efficient projects. Moreover, they take too much time to complete the projects that they undertake.