{"id":"https://openalex.org/W2109923704","doi":null,"title":"The Dynamics of Competitive Drug Detailing","display_name":"The Dynamics of Competitive Drug Detailing","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2109923704","mag":"2109923704"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.521.2235","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.521.2235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.chicagobooth.edu/research/workshops/marketing/docs/liu-jobpaper.pdf","raw_type":"text"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100409434","display_name":"Qiang Liu","orcid":"https://orcid.org/0000-0001-7727-0090","observed_orcids":["https://orcid.org/0000-0001-7727-0090","https://orcid.org/0000-0001-8466-3108"]},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qiang Liu","raw_affiliation_strings":["Cornell University"],"raw_orcid":"https://orcid.org/0000-0001-7727-0090","affiliations":[{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100409434"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":1.653,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85424493,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11792","display_name":"Pharmaceutical Economics and Policy","score":0.7099999785423279,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11792","display_name":"Pharmaceutical Economics and Policy","score":0.7099999785423279,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11649","display_name":"Pharmaceutical industry and healthcare","score":0.14990000426769257,"subfield":{"id":"https://openalex.org/subfields/2910","display_name":"Issues, ethics and legal aspects"},"field":{"id":"https://openalex.org/fields/29","display_name":"Nursing"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.09300000220537186,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pharmaceutical-marketing","display_name":"pharmaceutical marketing","score":0.8220000267028809},{"id":"https://openalex.org/keywords/dynamic-oligopoly","display_name":"dynamic oligopoly","score":0.734000027179718},{"id":"https://openalex.org/keywords/carryover-effects","display_name":"residual effects","score":0.6909999847412109},{"id":"https://openalex.org/keywords/markov-perfect-nash-equilibrium","display_name":"Markov perfect Nash equilibrium","score":0.8299999833106995},{"id":"https://openalex.org/keywords/hierarchical-bayesian-estimation","display_name":"hierarchical Bayesian estimation","score":0.6489999890327454},{"id":"https://openalex.org/keywords/policy-functions","display_name":"policy functions","score":0.6359999775886536},{"id":"https://openalex.org/keywords/supersaturation","display_name":"supersaturation","score":0.878000020980835},{"id":"https://openalex.org/keywords/two-stage-estimation","display_name":"two-stage estimation","score":0.4490000009536743}],"concepts":[{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5931317806243896},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.547524094581604},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.4632502794265747},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43946823477745056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41050148010253906},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.37951427698135376},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.3224945068359375},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19658240675926208},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.521.2235","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.521.2235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.chicagobooth.edu/research/workshops/marketing/docs/liu-jobpaper.pdf","raw_type":"text"},{"id":"mag:2109923704","doi":null,"is_oa":false,"landing_page_url":"https://www.chicagobooth.edu/research/workshops/marketing/docs/Liu-jobpaper.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W192712645","https://openalex.org/W389907844","https://openalex.org/W1494281971","https://openalex.org/W1524366261","https://openalex.org/W1532759091","https://openalex.org/W2014754981","https://openalex.org/W2033496161","https://openalex.org/W2054869847","https://openalex.org/W2058647728","https://openalex.org/W2059183841","https://openalex.org/W2061494965","https://openalex.org/W2067534308","https://openalex.org/W2077852757","https://openalex.org/W2103464736","https://openalex.org/W2126163471","https://openalex.org/W2130747900","https://openalex.org/W2136752008","https://openalex.org/W2142505346","https://openalex.org/W2142748967","https://openalex.org/W2151084171","https://openalex.org/W2152977846","https://openalex.org/W2157131530","https://openalex.org/W2169139179","https://openalex.org/W2169627451","https://openalex.org/W2316430202","https://openalex.org/W2460824078","https://openalex.org/W2739855053","https://openalex.org/W2793317277","https://openalex.org/W3025669945","https://openalex.org/W3124684770","https://openalex.org/W3125341908","https://openalex.org/W3125496587"],"related_works":["https://openalex.org/W3124602828","https://openalex.org/W3209791850","https://openalex.org/W1888188549","https://openalex.org/W2466184285","https://openalex.org/W2198798058","https://openalex.org/W3123970538","https://openalex.org/W4224289464","https://openalex.org/W2465209676","https://openalex.org/W4390064377","https://openalex.org/W2042785097"],"abstract_inverted_index":{"The":[0,83,166],"pharmaceutical":[1],"industry":[2],"spends":[3],"more":[4],"funds":[5],"on":[6,10],"drug":[7],"detailing":[8,24,71,77,121,135,142,164],"than":[9],"any":[11],"other":[12],"marketing":[13],"instrument.":[14],"Similar":[15],"to":[16,36,46,65,75],"the":[17,21,29,94,130,140],"effect":[18,40],"of":[19,23,61,70,134,158,163],"advertising,":[20],"impact":[22],"ex-penditures":[25],"spills":[26],"over":[27,72],"beyond":[28],"current":[30],"period.":[31],"We":[32,56],"expect":[33],"forward-looking":[34],"firms":[35,67],"observe":[37],"this":[38],"carry-over":[39],"and":[41,74],"adopt":[42],"a":[43,58,88,102,108,125,147],"dynamic":[44,62],"approach":[45],"determine":[47],"optimal":[48],"de-tailing":[49],"levels":[50,162],"by":[51],"maximizing":[52],"their":[53],"long-term":[54],"profits.":[55],"develop":[57],"structural":[59],"model":[60,84,155],"oligopoly":[63],"competition":[64],"analyze":[66],"\u2019":[68],"scheduling":[69],"time":[73],"estimate":[76,112],"costs":[78,133],"consistent":[79,145],"with":[80,146],"such":[81],"scheduling.":[82],"is":[85,99],"estimated":[86,100,137,153,167],"us-ing":[87],"recently":[89],"developed":[90],"two-stage":[91],"method.":[92],"In":[93,129],"first":[95],"stage,":[96,132],"physician-level":[97,113],"demand":[98,154],"in":[101,124],"hierarchical":[103,126],"Bayesian":[104,127],"framework.":[105,128],"Further,":[106],"using":[107],"semi-parametric":[109],"ap-proach,":[110],"we":[111],"policy":[114,168],"functions":[115,169],"that":[116,139],"describe":[117],"each":[118],"firm\u2019s":[119],"observed":[120,141],"actions,":[122],"also":[123],"second":[131],"are":[136,144],"assuming":[138],"data":[143],"Markov":[148],"perfect":[149],"Nash":[150],"equilibrium.":[151],"Our":[152],"shows":[156],"evidence":[157],"supersaturation":[159],"at":[160],"high":[161],"stock.":[165],"show":[170]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}