Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn
To explore the effects of different incentives on crowdsourcing participation and submission quality, we conduct a randomized field experiment on Taskcn, a large Chinese crowdsourcing site using mechanisms with features of an all-pay auction. In our study, we systematically vary the size of the rewa...
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| Veröffentlicht in: | Management science 2014-08, Vol.60 (8), p.2020-2037 |
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| container_title | Management science |
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| creator | Liu, Tracy Xiao Yang, Jiang Adamic, Lada A. |
| description | To explore the effects of different incentives on crowdsourcing participation and submission quality, we conduct a randomized field experiment on Taskcn, a large Chinese crowdsourcing site using mechanisms with features of an all-pay auction. In our study, we systematically vary the size of the reward as well as the presence of a soft reserve, or early high-quality submission. We find that a higher reward induces significantly more submissions and submissions of higher quality. In comparison, we find that high-quality users are significantly less likely to enter tasks where a high-quality solution has already been submitted, resulting in lower overall quality in subsequent submissions in such soft reserve treatments.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2013.1845
.
This paper was accepted by Uri Gneezy, behavioral economics. |
| doi_str_mv | 10.1287/mnsc.2013.1845 |
| format | Article |
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Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2013.1845
.
This paper was accepted by Uri Gneezy, behavioral economics.</description><identifier>ISSN: 0025-1909</identifier><identifier>EISSN: 1526-5501</identifier><identifier>DOI: 10.1287/mnsc.2013.1845</identifier><identifier>CODEN: MNSCDI</identifier><language>eng</language><publisher>Linthicum: INFORMS</publisher><subject>all-pay auctions ; Auction theory ; Auctions ; Bidding ; China ; Crowdsourcing ; Descriptive statistics ; Economic incentives ; Experienced users ; Experiment design ; Experiments ; field experiment ; Field experiments ; Field study ; Field work ; Management science ; Market theory ; Nash equilibrium ; Permutation tests ; Reputations ; Rewards ; Studies ; Tournaments & championships</subject><ispartof>Management science, 2014-08, Vol.60 (8), p.2020-2037</ispartof><rights>2014 INFORMS</rights><rights>Copyright Institute for Operations Research and the Management Sciences Aug 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c487t-6a94df2818fd5d4a2d66d2d62c2886457a1e1d8feabbbf1c87a2ce7701fca3ff3</citedby><cites>FETCH-LOGICAL-c487t-6a94df2818fd5d4a2d66d2d62c2886457a1e1d8feabbbf1c87a2ce7701fca3ff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/42919649$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://pubsonline.informs.org/doi/full/10.1287/mnsc.2013.1845$$EHTML$$P50$$Ginforms$$H</linktohtml><link.rule.ids>314,780,784,803,3692,27924,27925,58017,58250,62616</link.rule.ids></links><search><creatorcontrib>Liu, Tracy Xiao</creatorcontrib><creatorcontrib>Yang, Jiang</creatorcontrib><creatorcontrib>Adamic, Lada A.</creatorcontrib><title>Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn</title><title>Management science</title><description>To explore the effects of different incentives on crowdsourcing participation and submission quality, we conduct a randomized field experiment on Taskcn, a large Chinese crowdsourcing site using mechanisms with features of an all-pay auction. In our study, we systematically vary the size of the reward as well as the presence of a soft reserve, or early high-quality submission. We find that a higher reward induces significantly more submissions and submissions of higher quality. In comparison, we find that high-quality users are significantly less likely to enter tasks where a high-quality solution has already been submitted, resulting in lower overall quality in subsequent submissions in such soft reserve treatments.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2013.1845
.
This paper was accepted by Uri Gneezy, behavioral economics.</description><subject>all-pay auctions</subject><subject>Auction theory</subject><subject>Auctions</subject><subject>Bidding</subject><subject>China</subject><subject>Crowdsourcing</subject><subject>Descriptive statistics</subject><subject>Economic incentives</subject><subject>Experienced users</subject><subject>Experiment design</subject><subject>Experiments</subject><subject>field experiment</subject><subject>Field experiments</subject><subject>Field study</subject><subject>Field work</subject><subject>Management science</subject><subject>Market theory</subject><subject>Nash equilibrium</subject><subject>Permutation tests</subject><subject>Reputations</subject><subject>Rewards</subject><subject>Studies</subject><subject>Tournaments & championships</subject><issn>0025-1909</issn><issn>1526-5501</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqFkDFPwzAQhS0EEqWwsiFFYmFJ8Dlx7LBFVQtISDCUOXIdG1ISu9iJSv89joIYWFjuhvve072H0CXgBAhnt53xMiEY0gR4Ro_QDCjJY0oxHKMZxoTGUODiFJ15v8UYM87yGSoXzu5rbwcnG_MW7Zv-PSrbNn4Rh6gcZN9Y4--iMlo1qq2j5ddOuaZTpo-sidbCf0hzjk60aL26-Nlz9LparhcP8dPz_eOifIplxlkf56LIak04cF3TOhOkzvM6DCIJ53lGmQAFNddKbDYbDZIzQaRiDIOWItU6naObyXfn7OegfF91jZeqbYVRdvAV0BxzgIJnAb3-g25DQBO-CxQlDFjK0kAlEyWd9d4pXe1CNuEOFeBqbLQaG63GRqux0SC4mgRb31v3S2ekgCLPinCPp3tjtHWd_8_vG8vVgV4</recordid><startdate>20140801</startdate><enddate>20140801</enddate><creator>Liu, Tracy Xiao</creator><creator>Yang, Jiang</creator><creator>Adamic, Lada A.</creator><general>INFORMS</general><general>Institute for Operations Research and the Management Sciences</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>20140801</creationdate><title>Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn</title><author>Liu, Tracy Xiao ; Yang, Jiang ; Adamic, Lada A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c487t-6a94df2818fd5d4a2d66d2d62c2886457a1e1d8feabbbf1c87a2ce7701fca3ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>all-pay auctions</topic><topic>Auction theory</topic><topic>Auctions</topic><topic>Bidding</topic><topic>China</topic><topic>Crowdsourcing</topic><topic>Descriptive statistics</topic><topic>Economic incentives</topic><topic>Experienced users</topic><topic>Experiment design</topic><topic>Experiments</topic><topic>field experiment</topic><topic>Field experiments</topic><topic>Field study</topic><topic>Field work</topic><topic>Management science</topic><topic>Market theory</topic><topic>Nash equilibrium</topic><topic>Permutation tests</topic><topic>Reputations</topic><topic>Rewards</topic><topic>Studies</topic><topic>Tournaments & championships</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Tracy Xiao</creatorcontrib><creatorcontrib>Yang, Jiang</creatorcontrib><creatorcontrib>Adamic, Lada A.</creatorcontrib><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Management science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Tracy Xiao</au><au>Yang, Jiang</au><au>Adamic, Lada A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn</atitle><jtitle>Management science</jtitle><date>2014-08-01</date><risdate>2014</risdate><volume>60</volume><issue>8</issue><spage>2020</spage><epage>2037</epage><pages>2020-2037</pages><issn>0025-1909</issn><eissn>1526-5501</eissn><coden>MNSCDI</coden><abstract>To explore the effects of different incentives on crowdsourcing participation and submission quality, we conduct a randomized field experiment on Taskcn, a large Chinese crowdsourcing site using mechanisms with features of an all-pay auction. In our study, we systematically vary the size of the reward as well as the presence of a soft reserve, or early high-quality submission. We find that a higher reward induces significantly more submissions and submissions of higher quality. In comparison, we find that high-quality users are significantly less likely to enter tasks where a high-quality solution has already been submitted, resulting in lower overall quality in subsequent submissions in such soft reserve treatments.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mnsc.2013.1845
.
This paper was accepted by Uri Gneezy, behavioral economics.</abstract><cop>Linthicum</cop><pub>INFORMS</pub><doi>10.1287/mnsc.2013.1845</doi><tpages>18</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Management science, 2014-08, Vol.60 (8), p.2020-2037 |
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| language | eng |
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| source | Business Source Complete; JSTOR; INFORMS Pubs Suite |
| subjects | all-pay auctions Auction theory Auctions Bidding China Crowdsourcing Descriptive statistics Economic incentives Experienced users Experiment design Experiments field experiment Field experiments Field study Field work Management science Market theory Nash equilibrium Permutation tests Reputations Rewards Studies Tournaments & championships |
| title | Crowdsourcing with All-Pay Auctions: A Field Experiment on Taskcn |
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