Incentivizing High-quality Content from Heterogeneous Users: On the Existence of Nash Equilibrium

We study the existence of pure Nash equilibrium (PNE) for the mechanisms used in Internet services (e.g., online reviews and question-answer websites) to incentivize users to generate high-quality content. Most existing work assumes that users are homogeneous and have the same ability. However, real-world users are heterogeneous and their abilities can be very different from each other due to their diverse background, culture, and profession. In this work, we consider heterogeneous users with the following framework: (1) the users are heterogeneous and each of them has a private type indicating the best quality of the content she can generate; (2) there is a fixed amount of reward to allocate to the participated users. Under this framework, we study the existence of pure Nash equilibrium of several mechanisms composed by different allocation rules, action spaces, and information settings. We prove the existence of PNE for some mechanisms and the non-existence of PNE for some mechanisms. We also discuss how to find a PNE for those mechanisms with PNE either through a constructive way or a search algorithm

A Puff of Steem: Security Analysis of Decentralized Content Curation

Decentralized content curation is the process through which uploaded posts are ranked and filtered based exclusively on users\u27 feedback. Platforms such as the blockchain-based Steemit employ this type of curation while providing monetary incentives to promote the visibility of high quality posts according to the perception of the participants. Despite the wide adoption of the platform very little is known regarding its performance and resilience characteristics. In this work, we provide a formal model for decentralized content curation that identifies salient complexity and game-theoretic measures of performance and resilience to selfish participants. Armed with our model, we provide a first analysis of Steemit identifying the conditions under which the system can be expected to correctly converge to curation while we demonstrate its susceptibility to selfish participant behaviour. We validate our theoretical results with system simulations in various scenarios

Internationalisation of SMEs and firm performance: evidences from Bangladesh

One of the key objectives of this paper is to identify the impacts of internationalisation of SMEs on firm performance. Although there have been a number of research that examined the relationship between SME internationalisation and firm performance, research from the context of smaller developing economies are really scant. This is against the fact that SMEs are main vehicle for growth in those economies and extensive research on various dimensions of SMEs including its impact on firm performance may help to better understand the operational aspects of SMEs in those economies. Using primary data and structural equation modelling to analyse those data, the paper has found that internationalisation of SMEs has significant impact on both financial and non-financial performance of SMEs in Bangladesh. More specifically, the paper has found that internationalisation impacts in two dimensions (Financial impacts and non-financial impacts) with 8 indicators (higher sales, higher profit, assets maximization, market expansion, competitive advantage, better reputation, better customer service and added knowledge)

Gig Economy: A Dynamic Principal-Agent Model

The gig economy, where employees take short-term, project-based jobs, is increasingly spreading all over the world. In this paper, we investigate the employer's and the worker's behavior in the gig economy with a dynamic principal-agent model. In our proposed model the worker's previous decisions influence his later decisions through his dynamically changing participation constraint. He accepts the contract offered by the employer when his expected utility is higher than the irrational valuation of his effort's worth. This reference point is based on wages he achieved in previous rounds. We formulate the employer's stochastic control problem and derive the solution in the deterministic limit. We obtain the feasible net wage of the worker, and the profit of the employer. Workers who can afford to go unemployed and need not take a gig at all costs will realize high net wages. Conversely, far-sighted employers who can afford to stall production will obtain high profits

Surprising Results from Large Crowds Using Micro-Purchase Challenges - Using Contests on Freelancing Communities to Source Innovative, Impactful and Cost-Effective Solutions

Our world is more connected than ever before. The new digital economy is empowering platforms and crowds to become a progressively strategic way for organizations to innovate ahead of their competition. Existing research shows the effectiveness and quality of solutions crowdsourcing yields, yet few organizations genuinely understand it nor are leveraging those solutions to unlock the full range of benefits. Moreover, early adopters often face structural and financial barriers towards evangelizing digital platforms at scale within their organizations. NASA is an exception - being an advocate of the field since 2010, it has paved the path for large organizations to follow. An empirical analysis is conducted on NASA's Center of Excellence for Collaborative Innovation (CoECI) micro-purchase challenges on a crowd-based platform to assess the cost-savings, quality of work, time for work turnaround and brand effects of using this problem-solving mechanism. The results proved to provide a tangible impact on all four parameters. As such, micro-purchases could become a compelling entry-point for organizations who are willing to experiment and subsequently build a convincing business case to present to stakeholders. The paper concludes with NASA's learnings, supplemented by literature, on how to redesign business processes, change conventional thinking and create an organization that will transform its future with crowds

Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems

Crowdsourcing markets have emerged as a popular platform for matching available workers with tasks to complete. The payment for a particular task is typically set by the task's requester, and may be adjusted based on the quality of the completed work, for example, through the use of "bonus" payments. In this paper, we study the requester's problem of dynamically adjusting quality-contingent payments for tasks. We consider a multi-round version of the well-known principal-agent model, whereby in each round a worker makes a strategic choice of the effort level which is not directly observable by the requester. In particular, our formulation significantly generalizes the budget-free online task pricing problems studied in prior work. We treat this problem as a multi-armed bandit problem, with each "arm" representing a potential contract. To cope with the large (and in fact, infinite) number of arms, we propose a new algorithm, AgnosticZooming, which discretizes the contract space into a finite number of regions, effectively treating each region as a single arm. This discretization is adaptively refined, so that more promising regions of the contract space are eventually discretized more finely. We analyze this algorithm, showing that it achieves regret sublinear in the time horizon and substantially improves over non-adaptive discretization (which is the only competing approach in the literature). Our results advance the state of art on several different topics: the theory of crowdsourcing markets, principal-agent problems, multi-armed bandits, and dynamic pricing.Comment: This is the full version of a paper in the ACM Conference on Economics and Computation (ACM-EC), 201

The Anchoring Effect of “Quality Threshold for Monetary Incentive” on Online Review Platforms

The “quality threshold for monetary incentive” mechanism is a common practice in online review platforms. However, the effect of the quality threshold is still not clear in the extant literature. This study attempts to investigate how the introduction of the quality threshold affects content quality. Based on the Anchoring Effect theory, this study first derives some theoretical conclusions based on theoretical models and then conducts a natural experiment to test the conclusions. The findings show that after introducing the quality threshold, (1) the proportion of content with the threshold-level quality will increase; (2) the proportion of content higher than the quality threshold is reduced when there is the “Anchoring Effect”. Moreover, the empirical study also shows that the quality threshold leads to an overall negative effect on the average review quality. Our findings are meaningful to the stakeholders of the online review platforms