Crowd-based Platforms

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Now showing 1 - 9 of 9
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    Facts vs. Stories - Assessment and Conventional Signals as Predictors of Freelancers’ Performance in Online Labor Markets
    ( 2018-01-03) Holthaus, Christian ; Stock, Ruth Maria
    This paper investigates how freelancers’ use of signals predicts earnings in online labor markets. Extant literature has questioned the usefulness of some assessment signals to evaluate a freelancer’s quality. We find that conventional signals - signals based on non-verifiable information - can be predictors of higher revenue, when they are based on anecdotes of positive past events (self-promotion). However, mere kindness and flattery towards the customer (ingratiation) is negatively associated with a freelancers’ earnings in OLM. Moreover, we find evidence that the number of tests performed on the platform is significantly associated with higher earnings - with each test that is added to the profile a freelancer-˜s revenue increases by 4.1 %. We base our analysis on a sample of 1065 freelancers using objective financial earnings data, independent codings and survey data.
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    Home Bias in Online Employment
    ( 2018-01-03) Liang, Chen ; Hong, Yili (Kevin) ; Gu, Bin
    We study the nature of home bias in online employment, wherein the employer prefers workers from his/her own home country. Using a unique large-scale dataset from one of the major online labor platforms, we identify employers’ home bias in their online employment decisions. Moreover, we investigate the cause of employers’ home bias using a quasi-natural experiment wherein the platform introduces a monitoring system to facilitate employers to keep track of workers’ progress in time-based projects. After matching comparable fixed-price projects as a control group using propensity score matching, our difference-in-difference estimations show that the home bias does exist in online employment, and at least 54.0% of home bias is driven by statistical discrimination.
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    Exploring the Effect of Monetary Incentives on User Behavior in Online Sharing Platforms
    ( 2018-01-03) Lu, Yixin ; Ou, Carol ; Angelopoulos, Spyros
    We examine the impact of monetary incentives on user onboarding in online sharing platforms. Specifically, drawing upon the literature of monetary incentives, privacy, and consumer behavior, we conduct a randomized field experiment to explore users' initial engagement and interaction with an online car-sharing platform. Our empirical analyses show that monetary incentives are no better than simple email reminders in encouraging users' self-disclosure of private information nor their active engagement with the platform (i.e., actual booking via the platform). Our work sheds new light on the heated debate over the design and deployment of monetary incentives in digital platforms, and provides useful implications for both academia and the industry.
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    Temporally Networked Cournot Platform Markets
    ( 2018-01-03) Pang, John ; You, Pengcheng ; Chen, Minghua
    In networked markets, information can help firms make better decisions on which market (platform), and how much, to participate. However, these markets may be temporally separated, e.g., independent system operators in different geographical locations. We model these via networked Cournot markets, but instead consider the participation of one firm to either be with the realization (or full information) of a random market, or only with the statistics of the random market, modeled by an additive zero-mean random variable on the maximal price. We show that firms not knowing the realization of the random variable would participate in both markets in the same way as if the mean was realized. We then present global effects: we prove that profit is improved for every firm when one's information improves but social welfare may get better or worst with more information.
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    Investor’s Anticipation and Future Market Movement: Evidence of Self-Fulfilling Prophecy Effect from Chinese Stock Market
    ( 2018-01-03) Wan, Yun ; Yang, Xiaoguang
    We analyzed data collected from retail investors in Chinese stock market from a fin-tech mobile platform to find evidence of self-fulfilling prophecy effect. We found statistically significant correlation between the predicted and actual Shanghai Stock Exchange Composite Index (SSECI) as well as non-random deviation patterns. We also analyzed participating investor behaviors and discussed the implications and future research.
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    Effect of Auction Design on Bidder Entry: Evidence from An Online Labor Market
    ( 2018-01-03) Hong, Yili (Kevin) ; Shao, Benjamin ; Chen, Pei-yu ; Liang, Chen
    We propose that auction duration and auction description are two important auction design parameters that could serve as screening mechanisms for quality in online auctions. Using data from an online labor matching platform that connects buyers with IT service vendors, we examine the effects of auction duration and auction descriptions on auction outcomes (i.e., number of bids, bidder quality, bidding price) and project outcomes (i.e., project being contracted and being completed). Our empirical analyses show that, in buyer-determined reverse auctions of online labor matching, auctions with a longer duration and a longer description attract more bids, but they also attract more low quality bidders with less experience and lower completion rate, and hence result in a lower probability of successful contracting and completion of software service projects. Our research provides empirical evidence highlighting the strategic roles of auction design parameters like auction duration and descriptions as a potential screening mechanism for online labor matching platforms.
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    Success Factors in Title III Equity Crowdfunding in the United States
    ( 2018-01-03) Mamonov, Stanislav ; Malaga, Ross
    Title III of the JOBS Act took effect in May 2016 and it began a new chapter in equity crowdfunding in the United States by providing an opportunity for entrepreneurial ventures to solicit funding from non-accredited investors. Due to the relative novelty, little is known about factors that can affect equity crowdfunding success under Title III. To address this gap in research, we draw on the risk capital framework and we examine the effects of market, execution and agency risks in equity crowdfunding under Title III. We collect data on 133 ventures that attracted more than $11 million in funding commitments across sixteen Title III equity crowdfunding platforms. We find that all three types of risks can affect the likelihood of successful fundraising under Title III. We discuss the implications of these findings for entrepreneurs, investors, crowdfunding platforms and policy makers.
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    Managing Complex Work Systems via Crowdworking Platforms: How Deutsche Bank Explores AI Trends and the Future of Banking with Jovoto
    ( 2018-01-03) Mrass, Volkmar ; Peters, Christoph ; Leimeister, Jan Marco
    Crowdsourcing has evolved into a powerful new instrument for companies. In the last years, crowdworking platforms that manage work systems as intermediaries between crowdsourcers and crowd workers have increasingly been used. Nevertheless, they currently often manage rather simple work systems. Although they have the potential for managing more complex ones, there is still little knowledge how this can be done and what measures are necessary to do so. To explore this question in more detail, we investigate three seminal projects that Deutsche Bank completed with the crowdworking platform Jovoto and that aimed at exploring AI trends and developing concepts for the future of banking. We derive measures necessary for the successful management of complex work systems and provide a model as guidance for both companies and crowdworking platform operators. With our findings, we extend current knowledge in the realm of IS, organizational theory, and platform ecosystems
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    Introduction to the Minitrack on Crowd-based Platforms
    ( 2018-01-03) Hong, Yili ; Gu, Bin ; Huang, Nina (Ni)