Final paper reporttourist prediction.docx

Final paper reporttourist prediction.docx

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Finalpaperreporttouristprediction

StudyonthePredictionofTouristAttractionsbasedontheBaiduIndex:

ACaseStudyoftheForbiddenCity

Course:

Englishfortourism

1：

Number:

51153902033Name:

杨舒婷Major：

Geography

2：

Number:

51150601169Name:

张教根Major：

Math

3：

Number:

51150601151Name:

胡夏朕Major：

Math

4：

Number:

51150601168Name:

袁东Major：

Math

5：

Number:

51150601194Name:

涂欢Major：

Math

6：

Number:

51153903030Name:

朱小静Major：

Ecology

Adviser：

严文庆

2016年6月

Catalog

Abstract：

..........................................................................................................................................1

1:

Introduction...................................................................................................................................2

2:

Researchstatusreview...................................................................................................................3

3:

Empiricalanalysis..........................................................................................................................5

3.1:

TheselectionofBaidukeywordwiththedata......................................................................5

3.2:

RelationshipbetweenWebsearchdataandtheactualdata................................................6

3.3Establishmentofpredictionmodelandanalysis..................................................................9

3.3.1:

establishmentofpredictionARMAmodelandanalysis.........................................9

3.3.2:

Establishmentandpredictionanalysisofautoregressivedistributedlagmodel..11

4:

Conclusion..................................................................................................................................12

5:

Refercences...................................................................................................................................14

StudyonthePredictionofTouristAttractionsbasedontheBaiduIndex:

ACaseStudyoftheForbiddenCity

AbstractTouristsoverflowingduringthe“GoldenWeek”isnotanuncommonsituationinChinatoday.Predictingtouristflowsissignificantfortouristattractionsmanagementandplanning.Internetsearchrecordscanreflectconcernsandinterestsofpotentialtourists,andprovidealargevolumeofunstructuredorsemi-structureddataforstudyingtourismeconomicbehavior.ThispaperproposesanovelapproachforpredictingtouristflowbasedontheBaiduIndex,whichprovidessearchhistorycontainingdifferentkeywordsonadailybasisdatingbackto2006.Inthispaper,weconductacasestudyusingsearchdatarelatedtotheForbiddenCityfromtheBaiduIndexandstatisticaldataoftouristflowsintheForbiddenCity.Firstly,usingtheeconometricco-integrationtheoryandGrangercausalityanalysisthispaperfindsrelationshipsbetweentheinternetsearchdataandtheactualtouristflow,whichindicatesapositivecorrelationbetweenthem.Then,thispapercomparesanalysisresultsobtainedbytwokindsofpredictivemodelswith（ARDL）orwithout（ARMA）consideringBaiduIndex.TheARDLmodelimprovesthepredictionaccuracyofthetrainingsampleby12.4%,andthetestingsampleby14.5%.OurapproachcanpredictthenumberofdailyvisitorsoftheForbiddenCityusingtheoneortwodayslaggingdatafromtheBaiduIndex,whilethepreviousforecastingmethodrequiresdataofamuchlongerperiod.Inconclusion,itimprovesthetimelinessandaccuracyoftheprediction,andprovidestourismmanagementdepartmentswithbetterevidencefordecision-making.

Keywords:

BaiduIndex;touristattractions;co-integration;autoregressivemovingaveragemodel（ARMA）;autoregressivedistributedlagmodel（ARDL）

1.Introduction

WiththeboomingdevelopmentoftourisminChina,thereisalargeincreaseinnumberofbothdomesticandforeignvisitorstosomefamoustouristcityandscenicspots.EspeciallyduringGoldenWeek,suchasNationalDay,LaborDay,severaltouristattractionsareovercrowdedandfarbeyondthecarryingcapacityofthescenicarea.Thereisalistoftop10spotsweshouldnevervisitduringGoldenWeekfromNeteaseNews,includingtheForbiddenCity,HuangshanMountain,Dali-Lijiang,JiuzhaigouNationalPark,etc.Thereareevensometragediescausedbycrowd.Forexample,in2012,duringtheNationalDayholiday,thekillingcausedbythousandsofstrandedvisitorsinHuashanMountaincreatedagreatstirinourcountry.Inordertoavoidtragedyandprovideabettertravelenvironment,amoreaccuratepredictionoftouristflowscombinedwiththecarryingcapacityofthescenicspotisparticularlyurgentandsignificantformakingtimelyarrangementsandreasonableplanning.Therefore,thekeyproblemofourresearchishowtopredictvisitornumbersofscenicspotsmorescientifically.

Atpresent,mostexistingpredictionmethodsrelyonwell-stru