{"id":"https://openalex.org/W2182911845","doi":null,"title":"Forecasting Models of Additional Use of Mobile Digital Contents: A Comparison of Artificial Neural Networks and Logistic Regression Analysis","display_name":"Forecasting Models of Additional Use of Mobile Digital Contents: A Comparison of Artificial Neural Networks and Logistic Regression Analysis","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W2182911845","mag":"2182911845"},"language":"en","primary_location":{"id":"mag:2182911845","doi":null,"is_oa":false,"landing_page_url":"http://paper.ijcsns.org/07_book/200606/200606B03.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},"volume":null,"type":"article","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":null,"display_name":"Se Hun Lim","orcid":"https://orcid.org/0000-0001-8450-0595","observed_orcids":["https://orcid.org/0000-0001-8450-0595"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Se Hun Lim","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8450-0595","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.0,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.7832000255584717,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.7832000255584717,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.1080000028014183,"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"}},{"id":"https://openalex.org/T12659","display_name":"Innovation Diffusion and Forecasting","score":0.022099999710917473,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.878000020980835},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9779999852180481},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.5740000009536743},{"id":"https://openalex.org/keywords/mobile-network-operators","display_name":"mobile operators","score":0.9559999704360962},{"id":"https://openalex.org/keywords/mobile-enterprise","display_name":"mobile enterprise","score":0.5189999938011169}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6732076406478882},{"id":"https://openalex.org/C2777402642","wikidata":"https://www.wikidata.org/wiki/Q2557224","display_name":"Explanatory power","level":2,"score":0.6591063141822815},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.6256654858589172},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6055090427398682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5955438017845154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4337792992591858},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4279623031616211},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.4230615794658661},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3566593527793884},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.1386147439479828},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.09768033027648926},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07287928462028503},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2182911845","doi":null,"is_oa":false,"landing_page_url":"http://paper.ijcsns.org/07_book/200606/200606B03.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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1596432671","https://openalex.org/W1782977420","https://openalex.org/W1988115241","https://openalex.org/W2005436039","https://openalex.org/W2016207894","https://openalex.org/W2026368098","https://openalex.org/W2040870580","https://openalex.org/W2042664747","https://openalex.org/W2047649690","https://openalex.org/W2059148040","https://openalex.org/W2085831731","https://openalex.org/W2088504266","https://openalex.org/W2768260999","https://openalex.org/W3151727758","https://openalex.org/W3212604620"],"related_works":["https://openalex.org/W2029408951","https://openalex.org/W3113546604","https://openalex.org/W6922696564","https://openalex.org/W4251385314","https://openalex.org/W2901376892","https://openalex.org/W3198829739","https://openalex.org/W4398235080","https://openalex.org/W2476637696","https://openalex.org/W3087378185","https://openalex.org/W1578467894"],"abstract_inverted_index":{"Summary":[0],"Forecasting":[1],"of":[2,5,63,68,75,87,97,100],"Additional":[3],"Use":[4],"Mobile":[6,15],"Digital":[7],"Contents":[8],"has":[9,59],"attracted":[10],"research":[11,58],"interests":[12],"in":[13,34,113],"the":[14,32,61,92],"Service":[16],"Provider":[17],"(MSP)":[18,117],"and":[19,78,118],"academic":[20],"researchers.":[21],"This":[22,57],"study":[23],"introduces":[24],"an":[25,65],"Artificial":[26],"Neural":[27],"Network":[28],"(ANN)":[29],"model":[30,39],"to":[31,36,82],"problem":[33],"attempt":[35],"provide":[37,110],"a":[38,55,84],"with":[40],"better":[41],"explanatory":[42],"power.":[43],"In":[44],"this":[45],"research,":[46],"we":[47],"used":[48],"logistic":[49],"regression":[50],"n":[51],"analysis":[52],"(LRA)":[53],"as":[54],"benchmark.":[56],"compared":[60],"performance":[62],"forecasting":[64,101],"additional":[66,85],"use":[67,86],"mobile":[69,88,114,119],"digital":[70,89],"contents":[71,90],"through":[72],"two":[73],"types":[74],"models;":[76],"LRA":[77,104],"ANN.":[79,106],"Using":[80],"ANN":[81],"forecast":[83],"is":[91,102],"most":[93],"outstanding.":[94],"The":[95],"order":[96],"outstanding":[98],"performances":[99],"following;":[103],"<":[105],"Our":[107],"results":[108],"can":[109],"practical":[111],"connotations":[112],"service":[115],"provider":[116],"enterprises.":[120]},"counts_by_year":[{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-09-27T08:07:27.782135","created_date":"2016-06-24T00:00:00"}