The Informational Role of Online Recommendations: Evidence from a Field Experiment
We conduct a field experiment on a movie-recommendation platform to investigate whether and how online recommendations influence consumption choices. Using a within-subjects design, our experiment measures the causal effect of recommendations on consumption and decomposes the relative importance of...
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| creator | Aridor, Guy Goncalves, Duarte Kluver, Daniel Kong, Ruoyan Konstan, Joseph |
| description | We conduct a field experiment on a movie-recommendation platform to
investigate whether and how online recommendations influence consumption
choices. Using a within-subjects design, our experiment measures the causal
effect of recommendations on consumption and decomposes the relative importance
of two economic mechanisms: expanding consumers' consideration sets and
providing information about their idiosyncratic match value. We find that the
informational component exerts a stronger influence - recommendations shape
consumer beliefs, which in turn drive consumption, particularly among less
experienced consumers. Our findings and experimental design provide valuable
insights for the economic evaluation and optimisation of online recommendation
systems. |
| doi_str_mv | 10.48550/arxiv.2211.14219 |
| format | Article |
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investigate whether and how online recommendations influence consumption
choices. Using a within-subjects design, our experiment measures the causal
effect of recommendations on consumption and decomposes the relative importance
of two economic mechanisms: expanding consumers' consideration sets and
providing information about their idiosyncratic match value. We find that the
informational component exerts a stronger influence - recommendations shape
consumer beliefs, which in turn drive consumption, particularly among less
experienced consumers. Our findings and experimental design provide valuable
insights for the economic evaluation and optimisation of online recommendation
systems.</description><identifier>DOI: 10.48550/arxiv.2211.14219</identifier><language>eng</language><subject>Computer Science - Computers and Society ; Computer Science - Information Retrieval ; Quantitative Finance - Economics</subject><creationdate>2022-11</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2211.14219$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2211.14219$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Aridor, Guy</creatorcontrib><creatorcontrib>Goncalves, Duarte</creatorcontrib><creatorcontrib>Kluver, Daniel</creatorcontrib><creatorcontrib>Kong, Ruoyan</creatorcontrib><creatorcontrib>Konstan, Joseph</creatorcontrib><title>The Informational Role of Online Recommendations: Evidence from a Field Experiment</title><description>We conduct a field experiment on a movie-recommendation platform to
investigate whether and how online recommendations influence consumption
choices. Using a within-subjects design, our experiment measures the causal
effect of recommendations on consumption and decomposes the relative importance
of two economic mechanisms: expanding consumers' consideration sets and
providing information about their idiosyncratic match value. We find that the
informational component exerts a stronger influence - recommendations shape
consumer beliefs, which in turn drive consumption, particularly among less
experienced consumers. Our findings and experimental design provide valuable
insights for the economic evaluation and optimisation of online recommendation
systems.</description><subject>Computer Science - Computers and Society</subject><subject>Computer Science - Information Retrieval</subject><subject>Quantitative Finance - Economics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNqFjr0KwjAURrM4iPoATt4XMDZpC-oqLToJpXu4tDcYyE9JS6lvby3uTt_wHTiHsb1IeHbO8-SEcTIjl1IILjIpLmtW1S-Ch9chOhxM8GihCpYgaHh6azxBRU1wjny7_P0VitG05BsCHYMDhNKQbaGYOopm5oYtW2m0Pe1-u2GHsqhv9-NiV91MYXyrb4VaKtL_xAdRpDzq</recordid><startdate>20221125</startdate><enddate>20221125</enddate><creator>Aridor, Guy</creator><creator>Goncalves, Duarte</creator><creator>Kluver, Daniel</creator><creator>Kong, Ruoyan</creator><creator>Konstan, Joseph</creator><scope>ADEOX</scope><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20221125</creationdate><title>The Informational Role of Online Recommendations: Evidence from a Field Experiment</title><author>Aridor, Guy ; Goncalves, Duarte ; Kluver, Daniel ; Kong, Ruoyan ; Konstan, Joseph</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2211_142193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Computers and Society</topic><topic>Computer Science - Information Retrieval</topic><topic>Quantitative Finance - Economics</topic><toplevel>online_resources</toplevel><creatorcontrib>Aridor, Guy</creatorcontrib><creatorcontrib>Goncalves, Duarte</creatorcontrib><creatorcontrib>Kluver, Daniel</creatorcontrib><creatorcontrib>Kong, Ruoyan</creatorcontrib><creatorcontrib>Konstan, Joseph</creatorcontrib><collection>arXiv Economics</collection><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Aridor, Guy</au><au>Goncalves, Duarte</au><au>Kluver, Daniel</au><au>Kong, Ruoyan</au><au>Konstan, Joseph</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Informational Role of Online Recommendations: Evidence from a Field Experiment</atitle><date>2022-11-25</date><risdate>2022</risdate><abstract>We conduct a field experiment on a movie-recommendation platform to
investigate whether and how online recommendations influence consumption
choices. Using a within-subjects design, our experiment measures the causal
effect of recommendations on consumption and decomposes the relative importance
of two economic mechanisms: expanding consumers' consideration sets and
providing information about their idiosyncratic match value. We find that the
informational component exerts a stronger influence - recommendations shape
consumer beliefs, which in turn drive consumption, particularly among less
experienced consumers. Our findings and experimental design provide valuable
insights for the economic evaluation and optimisation of online recommendation
systems.</abstract><doi>10.48550/arxiv.2211.14219</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Computers and Society Computer Science - Information Retrieval Quantitative Finance - Economics |
| title | The Informational Role of Online Recommendations: Evidence from a Field Experiment |
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