{"id":"https://openalex.org/W4384134540","doi":"https://doi.org/10.1145/3591569.3591581","title":"Research on Evaluation of courier efficiency based on information entropy and data envelopment analysis","display_name":"Research on Evaluation of courier efficiency based on information entropy and data envelopment analysis","publication_year":2023,"publication_date":"2023-02-24","ids":{"openalex":"https://openalex.org/W4384134540","doi":"https://doi.org/10.1145/3591569.3591581"},"language":"en","primary_location":{"id":"doi:10.1145/3591569.3591581","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3591569.3591581","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3591569.3591581","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3591569.3591581","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077659971","display_name":"Xinyun He","orcid":"https://orcid.org/0000-0002-3697-7302"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyun He","raw_affiliation_strings":["Postal Green Packaging Technology Research and Development Center\u0f0cBeijing\u0f0cChina, Beijing Institute Graphic Communication, China"],"raw_orcid":"https://orcid.org/0000-0002-3697-7302","affiliations":[{"raw_affiliation_string":"Postal Green Packaging Technology Research and Development Center\u0f0cBeijing\u0f0cChina, Beijing Institute Graphic Communication, China","institution_ids":["https://openalex.org/I4210135483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368755","display_name":"Yuan Zhang","orcid":"https://orcid.org/0000-0003-0801-643X"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["Postal Green Packaging Technology Research and Development Center\u0f0cBeijing\u0f0cChina, Beijing Institute Graphic Communication, China"],"raw_orcid":"https://orcid.org/0000-0003-0801-643X","affiliations":[{"raw_affiliation_string":"Postal Green Packaging Technology Research and Development Center\u0f0cBeijing\u0f0cChina, Beijing Institute Graphic Communication, China","institution_ids":["https://openalex.org/I4210135483"]}]},{"author_position":"last","author":{"id":null,"display_name":"Lei Zhu","orcid":"https://orcid.org/0000-0002-9570-2632"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhu","raw_affiliation_strings":["Postal Green Packaging Technology Research and Development Center\u0f0cBeijing\u0f0cChina, Beijing Institute Graphic Communication, China"],"raw_orcid":"https://orcid.org/0000-0002-9570-2632","affiliations":[{"raw_affiliation_string":"Postal Green Packaging Technology Research and Development Center\u0f0cBeijing\u0f0cChina, Beijing Institute Graphic Communication, China","institution_ids":["https://openalex.org/I4210135483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210135483"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13815219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"77"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12306","display_name":"Urban and Freight Transport Logistics","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/data-envelopment-analysis","display_name":"Data envelopment analysis","score":0.7900199294090271},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.6575729846954346},{"id":"https://openalex.org/keywords/generalized-entropy-index","display_name":"Generalized entropy index","score":0.6428157687187195},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5836685299873352},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5303828120231628},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.5029520392417908},{"id":"https://openalex.org/keywords/operational-efficiency","display_name":"Operational efficiency","score":0.46802622079849243},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22443950176239014},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22027695178985596},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2030107080936432},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1467946469783783},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.08301743865013123}],"concepts":[{"id":"https://openalex.org/C22088475","wikidata":"https://www.wikidata.org/wiki/Q647974","display_name":"Data envelopment analysis","level":2,"score":0.7900199294090271},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.6575729846954346},{"id":"https://openalex.org/C166832808","wikidata":"https://www.wikidata.org/wiki/Q254487","display_name":"Generalized entropy index","level":3,"score":0.6428157687187195},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5836685299873352},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5303828120231628},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.5029520392417908},{"id":"https://openalex.org/C2778964270","wikidata":"https://www.wikidata.org/wiki/Q7097774","display_name":"Operational efficiency","level":2,"score":0.46802622079849243},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22443950176239014},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22027695178985596},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2030107080936432},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1467946469783783},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.08301743865013123},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3591569.3591581","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3591569.3591581","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3591569.3591581","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3591569.3591581","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3591569.3591581","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3591569.3591581","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Intelligent Information Technology","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384134540.pdf","grobid_xml":"https://content.openalex.org/works/W4384134540.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2481198332","https://openalex.org/W2954738045","https://openalex.org/W3002723854","https://openalex.org/W3022496655","https://openalex.org/W3123266901","https://openalex.org/W4242499807","https://openalex.org/W4242735564"],"related_works":["https://openalex.org/W2365865727","https://openalex.org/W111377563","https://openalex.org/W2043018577","https://openalex.org/W3174201586","https://openalex.org/W3093945082","https://openalex.org/W1982911282","https://openalex.org/W2380588550","https://openalex.org/W1988108393","https://openalex.org/W2198724947","https://openalex.org/W2366110630"],"abstract_inverted_index":{"Measuring":[0],"the":[1,6,11,15,24,29,35,38,41,53,71,88,95,103,124,136],"efficiency":[2,16,43,73,138],"of":[3,17,20,44,55,74,81,91,98,112,139],"couriers":[4,18,45,75,92,99,141],"in":[5,27,76],"last":[7,30],"kilometre":[8,31],"and":[9,48,64,84,102,106,127,135],"determining":[10],"key":[12],"factors":[13],"affecting":[14,40],"are":[19,51,58,93,108,131],"great":[21],"significance":[22],"to":[23,34,69],"courier":[25],"industry":[26],"solving":[28],"problem.":[32],"According":[33],"distribution":[36,104,125,137],"process,":[37],"indexes":[39],"delivery":[42,72,89],"before,":[46,134],"during":[47,87],"after":[49,129],"dispatch":[50],"established,":[52],"weights":[54],"each":[56],"index":[57],"determined":[59],"by":[60],"using":[61],"information":[62],"Entropy,":[63],"DEA":[65,117],"model":[66],"is":[67,100,114,142],"established":[68],"calculate":[70],"express":[77],"outlets.":[78],"The":[79,110,120],"differences":[80],"sorting,":[82],"dispatching":[83],"service":[85],"ability":[86],"process":[90],"analyzed,":[94],"improvement":[96],"direction":[97],"defined,":[101],"areas":[105],"routes":[107],"re-divided.":[109],"result":[111],"optimization":[113,130],"brought":[115],"into":[116],"evaluation":[118],"model.":[119],"example":[121],"shows":[122],"that":[123],"route":[126],"time":[128],"less":[132],"than":[133],"most":[140],"significantly":[143],"improved.":[144]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}