Game Theoretic Analysis of Tree Based Referrals for Crowd Sensing Social Systems with Passive Rewards

Participatory crowd sensing social systems rely on the participation of large number of individuals. Since humans are strategic by nature, effective incentive mechanisms are needed to encourage participation. A popular mechanism to recruit individuals is through referrals and passive incentives such as geometric incentive mechanisms used by the winning team in the 2009 DARPA Network Challenge and in multi level marketing schemes. The effect of such recruitment schemes on the effort put in by recruited strategic individuals is not clear. This paper attempts to fill this gap. Given a referral tree and the direct and passive reward mechanism, we formulate a network game where agents compete for finishing crowd sensing tasks. We characterize the Nash equilibrium efforts put in by the agents and derive closed form expressions for the same. We discover free riding behavior among nodes who obtain large passive rewards. This work has implications on designing effective recruitment mechanisms for crowd sourced tasks. For example, usage of geometric incentive mechanisms to recruit large number of individuals may not result in proportionate effort because of free riding.Comment: 6 pages, 3 figures. Presented in Social Networking Workshop at International Conference on Communication Systems and Networks (COMSNETS), Bangalore, India, January 201

CENTURION: Incentivizing Multi-Requester Mobile Crowd Sensing

The recent proliferation of increasingly capable mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to a crowd of participating workers that carry various mobile devices. Aware of the paramount importance of effectively incentivizing participation in such systems, the research community has proposed a wide variety of incentive mechanisms. However, different from most of these existing mechanisms which assume the existence of only one data requester, we consider MCS systems with multiple data requesters, which are actually more common in practice. Specifically, our incentive mechanism is based on double auction, and is able to stimulate the participation of both data requesters and workers. In real practice, the incentive mechanism is typically not an isolated module, but interacts with the data aggregation mechanism that aggregates workers' data. For this reason, we propose CENTURION, a novel integrated framework for multi-requester MCS systems, consisting of the aforementioned incentive and data aggregation mechanism. CENTURION's incentive mechanism satisfies truthfulness, individual rationality, computational efficiency, as well as guaranteeing non-negative social welfare, and its data aggregation mechanism generates highly accurate aggregated results. The desirable properties of CENTURION are validated through both theoretical analysis and extensive simulations

An Abstract Formal Basis for Digital Crowds

Crowdsourcing, together with its related approaches, has become very popular in recent years. All crowdsourcing processes involve the participation of a digital crowd, a large number of people that access a single Internet platform or shared service. In this paper we explore the possibility of applying formal methods, typically used for the verification of software and hardware systems, in analysing the behaviour of a digital crowd. More precisely, we provide a formal description language for specifying digital crowds. We represent digital crowds in which the agents do not directly communicate with each other. We further show how this specification can provide the basis for sophisticated formal methods, in particular formal verification.Comment: 32 pages, 4 figure

Serial Integration, Real Innovation: Roles of Diverse Knowledge and Communicative Participation in Crowdsourcing

Despite a burgeoning public and scholarly interest on open innovation and crowdsourcing, how to enable members of online temporary crowd to maintain knowledge integration and innovation remains underexplored. This study seeks to understand the ways in which online crowd members collectively generate more innovative and serial integrative solutions to crowdsourced open innovation challenges. Analyzing 3,200 unique posts generated by 486 participants of 21 organization-sponsored online crowdsourcing innovation challenges, this research demonstrates that crowd members contribute more innovative solutions when being exposed to explicitly shared diverse knowledge, and that crowd members’ communicative participation acts as a catalyst for the production of both innovation and serial knowledge integration. Findings suggest that managers who seek to generate knowledge integration and innovation should endeavor to implement systems that afford high-level communicative participation, as well as encourage crowd members to make their diverse knowledge explicit while minimizing their cognitive load in knowledge sharing

Small-scale piped water supply: end-user inclusive water research in arsenic affected areas in India and Bangladesh (DELTAP)

DELTAP is s multi-disciplinary research project, where geologists, water treatment scientists and industrial design engineers join forces to develop an integrated approach towards small-scale piped water supply (SPWS) systems in the arsenic-affected Ganges-Brahmaputra-Meghna Delta. The project has started in 2016 with a field study in Bihar (India) with a focus on water quality mapping with mobile crowd participation. The coming years the research will continue with 3 PhD candidates, both in India and Bangladesh, with the ultimate aim to develop blueprints for end-user inclusive SPWS systems

Is it more than allocating funds? Exploring the effect of enterprise crowdfunding on employee engagement

Enterprise crowdfunding (ECF) has evolved as a novel form to foster innovation and collaboration inside organizations. Research has so far focused on functional aspects related to the introduction of the crowdfunding mechanisms in enterprises (e.g., proposal characteristics or decision-making styles) leaving socio-economic effects on the organization and workforce unexplored. This work investigates the relationship between enterprise crowdfunding and the engagement of participating employees. By conducting an online survey with 321 employees of a multi-national manufacturing and electronics corporation, we find increased levels of employee engagement contingent upon participation in enterprise crowdfunding. These findings contribute to the understanding of effects related to the introduction of crowd-innovation platforms and enterprise social systems. From a practical perspective, they may foster the spread of enterprise crowdfunding as a tool being recognized to promote both, crowd-based innovation and employee engagement

Incentive mechanism design for mobile crowd sensing systems

The recent proliferation of increasingly capable and affordable mobile devices with a plethora of on-board and portable sensors that pervade every corner of the world has given rise to the fast development and wide deployment of mobile crowd sensing (MCS) systems. Nowadays, applications of MCS systems have covered almost every aspect of people's everyday living and working, such as ambient environment monitoring, healthcare, floor plan reconstruction, smart transportation, indoor localization, and many others. Despite their tremendous benefits, MCS systems pose great new research challenges, of which, this thesis targets one important facet, that is, to effectively incentivize (crowd) workers to achieve maximum participation in MCS systems. Participating in crowd sensing tasks is usually a costly procedure for individual workers. On one hand, it consumes workers' resources, such as computing power, battery, and so forth. On the other hand, a considerable portion of sensing tasks require the submission of workers' sensitive and private information, which causes privacy leakage for participants. Clearly, the power of crowd sensing could not be fully unleashed, unless workers are properly incentivized to participate via satisfactory rewards that effectively compensate their participation costs. Targeting the above challenge, in this thesis, I present a series of novel incentive mechanisms, which can be utilized to effectively incentivize worker participation in MCS systems. The proposed mechanisms not only incorporate workers' quality of information in order to selectively recruit relatively more reliable workers for sensing, but also preserve workers' privacy so as to prevent workers from being disincentivized by excessive privacy leakage. I demonstrate through rigorous theoretical analyses and extensive simulations that the proposed incentive mechanisms bear many desirable properties theoretically, and have great potential to be practically applied