{"id":"https://openalex.org/W4390098238","doi":"https://doi.org/10.23919/wiopt58741.2023.10349860","title":"How to Price Fresh Data with Strategic Users","display_name":"How to Price Fresh Data with Strategic Users","publication_year":2023,"publication_date":"2023-08-24","ids":{"openalex":"https://openalex.org/W4390098238","doi":"https://doi.org/10.23919/wiopt58741.2023.10349860"},"language":"en","primary_location":{"id":"doi:10.23919/wiopt58741.2023.10349860","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wiopt58741.2023.10349860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","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/A5101723460","display_name":"Junyi He","orcid":"https://orcid.org/0000-0001-7795-9357"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyi He","raw_affiliation_strings":["Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Science and Engineering, The Chinese University of Hong Kong,Shenzhen,Guangdong,china","Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, china"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Science and Engineering, The Chinese University of Hong Kong,Shenzhen,Guangdong,china","institution_ids":["https://openalex.org/I4210116924"]},{"raw_affiliation_string":"Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Guangdong, china","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437745","display_name":"Meng Zhang","orcid":"https://orcid.org/0000-0002-4893-6946"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]},{"id":"https://openalex.org/I4210158570","display_name":"Zhejiang University-University of Edinburgh Institute","ror":"https://ror.org/04jth1r26","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210158570","https://openalex.org/I76130692","https://openalex.org/I98677209"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Meng Zhang","raw_affiliation_strings":["Zhejiang University/University of Illinois at UrbanaChampaign Institute, Zhejiang University,Haining,China,314400"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University/University of Illinois at UrbanaChampaign Institute, Zhejiang University,Haining,China,314400","institution_ids":["https://openalex.org/I157725225","https://openalex.org/I4210158570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103248914","display_name":"Qian Ma","orcid":"https://orcid.org/0000-0002-8672-6069"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Ma","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University,Shenzhen,Guangdong,China,518107"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University,Shenzhen,Guangdong,China,518107","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062346297","display_name":"Jianwei Huang","orcid":"https://orcid.org/0000-0001-6631-1096"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Huang","raw_affiliation_strings":["School of Science and Engineering, Shenzhen Institute of Artificial Intelligence and Robotics for Society, The Chinese University of Hong Kong,Shenzhen,Shenzhen,China,518172"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science and Engineering, Shenzhen Institute of Artificial Intelligence and Robotics for Society, The Chinese University of Hong Kong,Shenzhen,Shenzhen,China,518172","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7256,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67152897,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10300","display_name":"Congenital Heart Disease Studies","score":0.964900016784668,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.6721967458724976},{"id":"https://openalex.org/keywords/purchasing","display_name":"Purchasing","score":0.6687406301498413},{"id":"https://openalex.org/keywords/dynamic-pricing","display_name":"Dynamic pricing","score":0.6624939441680908},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6488475799560547},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.47078531980514526},{"id":"https://openalex.org/keywords/pricing-strategies","display_name":"Pricing strategies","score":0.4540494382381439},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.4268726110458374},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.29979902505874634},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.24206387996673584},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.2360890805721283},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.19673499464988708},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11096429824829102}],"concepts":[{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.6721967458724976},{"id":"https://openalex.org/C2778813691","wikidata":"https://www.wikidata.org/wiki/Q1369832","display_name":"Purchasing","level":2,"score":0.6687406301498413},{"id":"https://openalex.org/C2779391423","wikidata":"https://www.wikidata.org/wiki/Q17009728","display_name":"Dynamic pricing","level":2,"score":0.6624939441680908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6488475799560547},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.47078531980514526},{"id":"https://openalex.org/C2780193402","wikidata":"https://www.wikidata.org/wiki/Q3394670","display_name":"Pricing strategies","level":2,"score":0.4540494382381439},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.4268726110458374},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.29979902505874634},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.24206387996673584},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.2360890805721283},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.19673499464988708},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11096429824829102},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/wiopt58741.2023.10349860","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wiopt58741.2023.10349860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2029050771","https://openalex.org/W2066786775","https://openalex.org/W2744248483","https://openalex.org/W2949681263","https://openalex.org/W2963053102","https://openalex.org/W2963270598","https://openalex.org/W2964345816","https://openalex.org/W2969447045","https://openalex.org/W2970983057","https://openalex.org/W2971937201","https://openalex.org/W2976172112","https://openalex.org/W3029672350","https://openalex.org/W3104436821","https://openalex.org/W3113239917","https://openalex.org/W3128630999","https://openalex.org/W3134599018","https://openalex.org/W3134611604","https://openalex.org/W3137257456","https://openalex.org/W3139018907","https://openalex.org/W3154774595","https://openalex.org/W3202543149","https://openalex.org/W4205984110","https://openalex.org/W4206560348","https://openalex.org/W4211024811","https://openalex.org/W4225350605"],"related_works":["https://openalex.org/W4388979845","https://openalex.org/W2127655346","https://openalex.org/W4324280545","https://openalex.org/W2560846000","https://openalex.org/W4205804895","https://openalex.org/W3204277590","https://openalex.org/W2884216436","https://openalex.org/W4285574754","https://openalex.org/W4391005281","https://openalex.org/W2559922324"],"abstract_inverted_index":{"The":[0,61,110],"interests":[1],"in":[2,6,123,191,228],"obtaining":[3],"fresh":[4,11,19,47],"data":[5,12,20,35,48,55,68,74,83,126,133,225],"real-time":[7],"applications":[8],"have":[9,22,201],"facilitated":[10],"markets.":[13],"However,":[14],"existing":[15],"works":[16],"on":[17],"designing":[18],"markets":[21],"ignored":[23],"strategic":[24,27,51,62,199,232],"users.":[25],"Being":[26],"means":[28],"that":[29,148],"users":[30,52,63,117,200,208,233],"can":[31,239],"optimally":[32],"time":[33,66,87],"their":[34,125],"purchases,":[36],"which":[37],"affects":[38],"markets'":[39],"profit.":[40,91,246],"In":[41],"this":[42],"paper,":[43],"we":[44,140,171],"study":[45,172],"a":[46,95,103,142,173,192,221],"market,":[49],"where":[50,99,177],"with":[53],"heterogeneous":[54,116],"valuations":[56],"stochastically":[57],"arrive":[58],"over":[59,86,182],"time.":[60,183],"decide":[64],"the":[65,71,79,82,100,138,149,155,160,168,178,186,224,229],"of":[67,73,132,231],"purchase,":[69],"considering":[70],"evolution":[72],"freshness":[75],"and":[76,158],"prices,":[77],"while":[78],"platform":[80,101,222],"decides":[81],"pricing":[84,97,162,175],"policy":[85,163],"to":[88,106,166,242],"maximize":[89],"its":[90],"We":[92,146,184],"first":[93],"consider":[94],"dynamic":[96],"policy,":[98,176],"offers":[102],"price":[104,179,189],"menu":[105],"each":[107],"arrival":[108],"user.":[109],"analysis":[111],"is":[112,180],"technically":[113],"challenging,":[114],"as":[115],"face":[118],"different":[119],"integer":[120],"programming":[121],"problems":[122],"optimizing":[124],"purchase":[127],"time,":[128],"making":[129],"direct":[130,150],"optimization":[131],"prices":[134],"infeasible.":[135],"To":[136],"tackle":[137],"challenge,":[139],"adopt":[141],"mechanism":[143,151],"design":[144,152],"approach.":[145],"show":[147,218],"problem":[153,157],"relax":[154],"original":[156],"obtain":[159],"optimal":[161,187],"analytically.":[164],"Next,":[165],"reduce":[167],"implementation":[169],"complexity,":[170],"single":[174,188],"fixed":[181],"derive":[185],"analytically":[190],"two-period":[193],"refreshing":[194],"model.":[195],"Perhaps":[196],"surprisingly,":[197],"although":[198,220],"more":[202],"purchasing":[203],"options":[204],"than":[205,234],"non-strategic":[206],"users,":[207,237],"who":[209],"behave":[210],"strategically":[211],"may":[212],"be":[213],"worse":[214],"off.":[215],"Simulation":[216],"results":[217],"that,":[219],"refreshes":[223],"less":[226],"frequently":[227],"presence":[230],"facing":[235],"myopic":[236],"it":[238],"earn":[240],"up":[241],"5":[243],"times":[244],"higher":[245]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
