{"id":"https://openalex.org/W2914811309","doi":"https://doi.org/10.1109/allerton.2018.8635934","title":"Coupon Targeting Competition in Privacy Sensitive Market","display_name":"Coupon Targeting Competition in Privacy Sensitive Market","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2914811309","doi":"https://doi.org/10.1109/allerton.2018.8635934","mag":"2914811309"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2018.8635934","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2018.8635934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5007357643","display_name":"Omid Javidbakht","orcid":"https://orcid.org/0000-0001-6926-5136"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omid Javidbakht","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014965408","display_name":"Parv Venkitasubramaniam","orcid":"https://orcid.org/0000-0002-0999-3331"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Parv Venkitasubramaniam","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080282461","display_name":"Alberto J. Lamadrid","orcid":"https://orcid.org/0000-0003-2539-9487"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alberto J. Lamadrid","raw_affiliation_strings":["Department of Economics, Lehigh University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Economics, Lehigh University","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I186143895"],"apc_list":null,"apc_paid":null,"fwci":0.8782,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85987359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"267","last_page":"274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11045","display_name":"Privacy, Security, and Data Protection","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11045","display_name":"Privacy, Security, and Data Protection","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9904999732971191,"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/coupon","display_name":"Coupon","score":0.776272177696228},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.6739544868469238},{"id":"https://openalex.org/keywords/purchasing","display_name":"Purchasing","score":0.6629089713096619},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.5483050346374512},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4905511736869812},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.41556042432785034},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.3817632496356964},{"id":"https://openalex.org/keywords/advertising","display_name":"Advertising","score":0.341460257768631},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.25516852736473083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2209310233592987},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.2062569558620453}],"concepts":[{"id":"https://openalex.org/C2779307704","wikidata":"https://www.wikidata.org/wiki/Q11794832","display_name":"Coupon","level":2,"score":0.776272177696228},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.6739544868469238},{"id":"https://openalex.org/C2778813691","wikidata":"https://www.wikidata.org/wiki/Q1369832","display_name":"Purchasing","level":2,"score":0.6629089713096619},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.5483050346374512},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4905511736869812},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.41556042432785034},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.3817632496356964},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.341460257768631},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.25516852736473083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2209310233592987},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.2062569558620453},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/allerton.2018.8635934","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2018.8635934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W204355211","https://openalex.org/W1496590343","https://openalex.org/W1596057795","https://openalex.org/W1805249784","https://openalex.org/W1972577594","https://openalex.org/W1975879390","https://openalex.org/W2044006590","https://openalex.org/W2067534308","https://openalex.org/W2081349667","https://openalex.org/W2109426455","https://openalex.org/W2125475233","https://openalex.org/W2152518947","https://openalex.org/W2162297215","https://openalex.org/W2296525532","https://openalex.org/W2551236831","https://openalex.org/W2727450595","https://openalex.org/W2914811309","https://openalex.org/W2995235436","https://openalex.org/W3122338044","https://openalex.org/W3125675149","https://openalex.org/W4232057862","https://openalex.org/W6683665485"],"related_works":["https://openalex.org/W2974050152","https://openalex.org/W1481018110","https://openalex.org/W3150641959","https://openalex.org/W2200893828","https://openalex.org/W2606802280","https://openalex.org/W2083573183","https://openalex.org/W2285295461","https://openalex.org/W1537782856","https://openalex.org/W2106608244","https://openalex.org/W4387066559"],"abstract_inverted_index":{"The":[0,93],"problem":[1],"of":[2,102,115,122,165],"coupon":[3,48,168],"targeting":[4,49],"competition":[5,50,94],"between":[6,51,72,95],"two":[7,97],"retailers":[8,98,123],"who":[9],"sell":[10],"the":[11,47,52,116,161],"same":[12],"product":[13,29],"in":[14,139],"a":[15,62,73,91,108,142,149,166],"privacy":[16,35,57,74,78,147],"sensitive":[17,144],"market":[18],"is":[19,43,59,105,133,136,148],"considered.":[20],"In":[21,112],"particular,":[22],"consumers":[23,66,151],"purchasing":[24],"decisions":[25],"are":[26],"influenced":[27],"by":[28,37,107],"prices":[30],"as":[31,33],"well":[32],"prior":[34],"violations":[36],"retailers.":[38,53],"A":[39],"Hotelling":[40,103,117],"line":[41,104],"model":[42],"utilized":[44],"to":[45,141],"investigate":[46],"Within":[54],"this":[55],"framework,":[56],"sensitivity":[58],"modeled":[60,106],"using":[61],"Markov":[63],"chain,":[64],"wherein":[65],"switch":[67],"back":[68],"and":[69,77],"forth":[70],"probabilistically":[71],"alerted":[75],"state":[76,80],"non-alerted":[79],"depending":[81],"on":[82],"whether":[83],"or":[84],"not":[85],"they":[86],"receive":[87],"targeted":[88,167],"coupons":[89],"from":[90,160,169],"retailer.":[92,171],"these":[96],"at":[99],"each":[100],"segment":[101,114],"stochastic":[109],"nonzero-sum":[110],"game.":[111],"every":[113],"line,":[118],"stationary":[119],"equilibrium":[120],"strategies":[121],"that":[124,138,170],"provide":[125],"optimal":[126],"discounted":[127],"return":[128],"over":[129],"an":[130],"infinite":[131],"horizon":[132],"studied.":[134],"It":[135],"demonstrated":[137],"contrast":[140],"price":[143],"market,":[145],"when":[146],"factor,":[150],"with":[152],"weak":[153],"brand":[154],"loyalty":[155],"can":[156],"be":[157],"driven":[158],"away":[159],"popular":[162],"retailer":[163],"because":[164]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}