STUDY OF CONSUMER SATISFACTION TOWARDS ONLINE SHOPPING

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1ResearchScholar,SabarmatiUniversity,Ahmedabad,Gujarat,India.

2AssistantProfessor,SabarmatiUniversity,Ahmedabad,Gujarat,India.

ABSTRACT

Customerattractionandsatisfactionarebothheavilyinfluencedbyonlinebuying.Intoday'stechnologyenvironment,mostbusinessesemployonlinepurchasingto pleaseclientswhilealsorecruitingnewones.Theimpactofinternetshoppingonimprovingcustomersatisfactioninretailenterprisesisthesubjectofthisstudyreport. Thepurposeofthisstudywastodeterminetheinfluenceofonlinepurchasingontheretailindustry Asidefromthisgoal,thestudypaperalsoincludessomeadditional objectives,suchasdeterminingclientsatisfactionwithretailcompanyitemsandservices.Thestudyalsosoughttodeterminetheinfluenceofinternetpurchasingon improvingcustomersatisfactioninretailbusinesses.Theresearcherconductedthestudyusingpositivistprinciple,descriptivedesign,deductiveresearchstrategy,and primary data gathering method. According to the findings of the study, internet shopping assists firms in increasing their commercial opportunities as well as increasingconsumerhappinessintheworkplace.Thestudyalsorevealedthatonlineshoppinghasavarietyofconsequencesonanorganization'scompany,andbased onthefindings,itcanbeconcludedthatonlineshoppinghelpsanorganisationbuilditsbusiness,resultinginmorefinancialbenefitsinthelongrun.

KEYWORDS:OnlineShopping,CustomerSatisfaction,Services,RetailCompanies,FinancialBenefit.

INTRODUCTION:

InIndia,e-commercehaschangedthewaypeopledobusiness.FromUS$46.2 billionin2020,theIndiane-commercesectorispredictedtoexpandtoUS$188 billionby2025.ItisestimatedtoreachUS$350billionby2030.TheIndianecommerce sector is expected to grow by 21.5 percent to US$ 74.8 billion by 2022.

By2024,India'se-commercebusinessispredictedtobeworthUS$111billion, andby2026,itwillbeworthUS$200billion.Asurgeininternetandsmartphone usage has sparked most of the industry's growth. Because of the 'Digital India' campaign,thenumberofinternetconnectionsexpandeddramaticallyto830million in 2021. In metropolitan areas, 55 percent of internet connections were made,with97percentofthoseconnectionsbeingwireless.

MarketSize:

TheIndianonlinegroceryindustryisexpectedtogrowataCAGRof33%from US$3.95billioninFY21toUS$26.93billionin2027.India'sconsumerdigital economyispredictedtoreachUS$1trillionby2030,upfromUS$537.5billion in 2020, thanks to the country's rapid adoption of online services such as ecommerceandedtech.

By2025,e-commerceinIndiaisanticipatedtobeworthUS$188billion,according to Grant Thornton. India became the eighth-largest e-commerce market in 2020,followingFrancebutaheadofCanada,withaturnoverof$50billion.

TheIndianE-commercemarketispredictedtorisetoUS$200billionby2026, from US$ 38.5 billion in 2017, thanks to rising smartphone penetration, the rolloutof4Gnetworks,andrisingconsumerwealth.

India,behindChinaandtheUnitedStates,hasthethird-largestonlineshopping basein2020,with140millionpeople.Evenbeforethecountry'snext-generation mobileinternettechnologyisrolledout,Indianconsumersareincreasinglybuying5Ghandsets.In2021,smartphoneshipmentshit169million,with5Gshipmentsincreasingby555percentyearoveryear Evenbeforethecountry'snextgeneration mobile internet technology is rolled out, Indian consumers are increasinglybuying5Ghandsets.Smartphoneshipmentssurpassed150million units in 2020, with 5G smartphone shipments surpassing 4 million, thanks to strongcustomerdemandfollowingthelockdown.Accordingtoasurveyreleased byIAMAIandKantarResearch,India'sinternetusersarepredictedtoreach900 million by 2025, up from 622 million in 2020, with a CAGR of 45 percent between2020and2025.Indiane-commerceplatformsachievedsalesworthUS$ 9.2billionGrossMerchandiseValue(GMV)forthefestiveseasonof2021,up23 percentfromlastyear'sUS$7.4billion.

RoadAhead:

The e-commerce industry has had a direct impact on India's micro, small, and mediumcompanies(MSME)byprovidingfunding,technology,andtraining,as well as having a positive cascade effect on adjacent industries. The Indian ecommercebusinesshasbeenonanincreasingtrack,andby2034,itispredicted to surpass the United States to become the world's second largest e-commerce market. Digital payments, hyper-local logistics, analytics-driven customer

engagement, and digital marketing are examples of technology-enabled developmentsthatwilllikelyboostthesector'sgrowth.Inthelongrun,theriseoftheecommercesectorwillboostemployment,raiseexportearnings,increasetaxcollection by exchequers, and give better products and services to customers. By 2022,smartphoneusageispredictedtoincreaseby84percent,to859million.

Thee-retailmarketispredictedtokeepgrowingatarapidpace,withaCAGRof more than 35% expected to reach Rs. 1.8 trillion (US$ 25.75 billion) in FY20. TheIndiane-retailbusinessisexpectedtogrowto300-350millionshoppersin thenextfiveyears,bringingtheonlineGrossMerchandiseValue(GMV)toUS$ 100-120 billion by 2025. According to a report by Bain & Company, India's socialcommercegrossmerchandisevalue(GMV)in2020willbeUS$2billion. Due to growing mobile usage, it is estimated to reach US$ 20 billion by 2025, withapossiblymassiveclimbtoUS$70billionby2030.

LITERATUREREVIEW:

Consumers all throughout the world are increasingly turning from crowded storefronts to one-click internet buying, according toVijay, Sai.T., and Balaji, M. S. (2009). Despite the ease, online buying is not the most popular mode of shoppinginIndia.

SanjeevKumarandSavitaMaanareacouple(2013)Theresearchshedslighton customers'onlineshoppinghabitsandpreferences.Furthermore,thearticleidentifiesthechallengesthatbuyersexperiencewhenattemptingtomaketheinternet theirprimarybuyingmedium.Toexplorethenotionofonlineshopping,thecurrentstudyisadescriptivestudybasedonacarefulevaluationofpreviousrelevant studies connected to the various concepts of online shopping. Consumers benefitmorefromonlinebuying,accordingtothefindings.Privacyandsecurity concernsarecommonlycitedasreasonstoavoidonlineshopping.

K.Vaitheesewaran(2013)investigatedtheeaseofshoppingonline.Theretailer's post-sale responsibility has decreased dramatically as products have become morestandardised,specificationshavebecomemorefixed,andtheideaofservice has become undermined. As a result, people visit retailers to personally inspecttheproduct,buttheymaydosoonlineforalowerprice.Duetotheirlack ofawarehouse,e-commercecompaniescanoffersubstantialdiscounts.

While MingyaoHu, Elliot Rabinovich, and HanpingHou (2014) focused on onlinecustomerpre-purchaseperceptions,thisstudyfocusesononlinecustomer pre-purchaseperceptions.Trustworthyonlineretailersconveysignalstodistinguishthemselvesfromretailerswhoareuntrustworthyintheopinionofclientsin anonlinemarket.Untrustworthyonlineretailers,ontheotherhand,canimitate thebehaviouroftrustworthyonlineretailersbysendingidenticalsignalswithout providingtheservicesindicatedbythesignals.

R.Swarna,DevaKumari,Dr D.Sudhakar(2016)AstudyofcustomersatisfactionwithinternetpurchasingintheChittoordistrict.Customers'satisfactionratingswiththechosenproductswereinvestigatedinthisstudy Accordingtothe findings,themajorityofrespondentsprefertobuythingsontheFlipkartwebsite, followedbyAmazon,andtheyareextremelysatisfiedwithproductdeliveryon time.

Research Paper Commerce E-ISSN No : 2454-9916 | Volume : 8 | Issue : 3 | Mar 2022
36 InternationalEducation&ResearchJournal[IERJ]
Copyright©2022,IERJ.Thisopen-accessarticleispublishedunderthetermsoftheCreativeCommonsAttribution-NonCommercial4.0InternationalLicensewhichpermitsShare(copyandredistributethematerialinany mediumorformat)andAdapt(remix,transform,andbuilduponthematerial)undertheAttribution-NonCommercialterms.
OF CONSUMER SATISFACTION TOWARDS ONLINE
STUDY
SHOPPING

RESEARCHOBJECTIVE:

1. Tostudytheperceptionofconsumerstowardsonlineshopping

2. Tostudytheconceptofonlineshopping.

SampleSize:

Thespecimensizeis100customer.

DATAANALYSIS:

Interpretation:

Accordingtothedataanalysis,15%oftherespondentsarebetweentheagesof 18and25,30%arebetweentheagesof26and35,35%arebetweentheagesof 36and45,and20%oftherespondentsareovertheageof46.Malerespondents makeup36%ofthetotal,whilefemalerespondentsmakeup35%.50percentare married,25%aresingle,10%aredivorced,and15%areinalive-inrelationship. Non-graduates make up 10% of the responses, graduates make up 50%, postgraduatesmakeup35%,anddoctoratesmakeup5%oftherespondents.5percentofrespondentshaveamonthlyincomeoflessthan30000rupees,20%have a monthly income of 30001 to 45000 rupees, 35% have a monthly income of 45001 to 60000 rupees, and 40% have a monthly income of more than 60000 rupees. 5 percent of the respondents are students, 10% of the respondents are housewives, 20% of the respondents work for the government, 25% of the respondentsruntheirownbusiness,20%oftherespondentsworkforaprivate corporation,and20%oftherespondentsarefreelancers.5percentoftherespondentsliveinajointfamily,while95%liveinanuclearfamily

1. RelationbetweenAgeandSatisfactionlevel:

Fromtheabovetableitisshownthatpvalueis0.000whichissmallerthansignificantvalue0.05soitisconcludedthatthereisrelationbetweenAgeandSatisfactionlevel.

2. RelationbetweenGenderandSatisfactionlevel:

Fromtheabovetableitisshownthatpvalueis0.000whichissmallerthansignificantvalue0.05soitis

Research Paper E-ISSN No : 2454-9916 | Volume : 8 | Issue : 3 | Mar 2022
Relation
MaritalStatus
Satisfaction
37 InternationalEducation&ResearchJournal[IERJ] Variable Frequency % Age Below18Years 5 5% 18-25Years 30 30% 26-35Years 25 25% 36-45Years 25 25% 46andabove 15 15% Total 100 100% Gender Male 65 65% Female 35 35% Total 100 100% MaritalStatus Married 50 50% Unmarried 25 25% Divorcee 10 10% Liveinrelation 15 15% Total 100 100% Education Matriculation 10 10% Graduate 50 50% Postgraduate 35 35% Professional 5 5% Total 100 100% MonthlyIncome Below30000Rs 5 5% 30001to45000Rs 20 20% 45001to60000Rs 35 35% Above60000Rs 40 40% Total 100 100% Occupation Study 5 5% GovernmentJob 10 10% PrivateJob 20 20% Trading 15 15% Manufacturer 20 20% Homemaker 10 10% Freelancer 20 20% Total 100 100% FamilyType Joint 5 5% Nuclear 95 95% Total 100 100% SatisfactionLevel*AgeCrossTabulation Count Age Total Below18 Years 18-25 Years 26-35 Years 36-45 Years 46and above Satisfaction Level Highly Satisfied 5 15 0 0 0 20 Satisfied 0 15 25 0 0 40 Neutral 0 0 0 20 0 20 Dissatisfied 0 0 0 5 10 15 Highly Dissatisfied 0 0 0 0 5 5 Total 5 30 25 25 15 100 Chi-SquareTests Value df AsymptoticSignificance (2-sided) PearsonChi-Square a208.194 16 .000 LikelihoodRatio 203.225 16 .000 Linear-by-LinearAssociation 83.592 1 .000 NofValidCases 100 a. 15 cells (60.0%) have expected count less than 5. The minimum expected countis.25. SatisfactionLevel*GenderCrossTabulation Count Gender Total Male Female Satisfaction Level HighlySatisfied 20 0 20 Satisfied 40 0 40 Neutral 5 15 20 Dissatisfied 0 15 15 HighlyDissatisfied 0 5 5 Total 65 35 100 Chi-SquareTests Value df AsymptoticSignificance (2-sided) PearsonChi-Square a83.516 4 .000 LikelihoodRatio 106.996 4 .000 Linear-by-LinearAssociation 68.303 1 .000 NofValidCases 100 a. 2 cells (20.0%) have expected count less than 5. The minimum expected countis1.75. SatisfactionLevel*MaritalStatusCrossTabulation Count MaritalStatus Total Married Unmarried Divorcee Livein relation Satisfaction Level Highly Satisfied 20 0 0 0 20 Satisfied 30 10 0 0 40 Neutral 0 15 5 0 20 Dissatisfied 0 0 5 10 15 Highly Dissatisfied 0 0 0 5 5 Total 50 25 10 15 100
concludedthatthereisrelationbetweenGenderandSatisfactionlevel. 3.
between
and
level:

Fromtheabovetableitisshownthatpvalueis0.000whichissmallerthansignificant value 0.05 so it is concluded that there is relation between Marital Status andSatisfactionlevel.

4. RelationbetweenEducationandSatisfactionlevel:

CONCLUSION:

WiththeincreaseduseoftheWorldWideWeb,alsoknownaswww,onlineshoppingisgrowingmorepopularbytheday Understandingtheneedsofcustomers for online selling has become a difficult task for marketers. Understanding the attitudesofcustomerstowardonlinebuying,improvingthevariablesthatdrive consumers to shop online, and working on factors that influence consumers to shoponlinecanhelpmarketersachieveacompetitiveadvantageovertheircompetitors.Finally,havingaccesstoonlinebuyinghashadasignificantimpacton oursocietyasawhole.Thisapplicationoftechnologyhasopenedupnewavenuesandpossibilities,allowingforamoreconvenientexistencetoday Basedon thehypothesistesting,itwasdeterminedthatthereisarelationshipbetweenage andsatisfactionlevel,thatthereisarelationshipbetweengenderandsatisfaction level,thatthereisarelationshipbetweenmaritalstatusandsatisfactionlevel,that thereisarelationshipbetweeneducationandsatisfactionlevel,andthatthereisa relationshipbetweenincomeandsatisfactionlevel.

BIBLIOGRAPHY:

I. Hooda, S. and Singh, N., 2018. Online apparel shopping. Man-Made Textiles in India,46(3).Jiang,Y.,Shang,J.,Liu,Y andMay,J.,2015.

II. K Maran, S Usha (2014),Work Life Balance ofWomen Employees Satisfaction-A StudyWithReferencetoITSectorinIndia'-AsiaPacificJournalofResearch,Volume:1.

III. KMaran,VChandraShekar(2015), Astudyonstudent’sperceptionofemployabilityskillswithrespecttoengineeringinstitutions-InternationalJournalofResearch inEngineering,Volume5,Issue3,PP:21-34.

IV KKMaran,JBadrinarayanan,PKumar(2017),AstudyonbrandedapparelscustomerspurchasebehaviorwithreferencetoIndia-InternationalJournalofAppliedBusiness,Volume21,Issue15,PP:215-222.

V Krassadaki,E.andGrigoroudis,E.,2018,June.DefiningcustomersatisfactioncriteriacategoriesusingMCDAandKano’smodel.

VI. SSankar,KMaran(2013),MarketTradinginIndia-CustomerPerception-InternationalJournalofEngineeringandManagement,Volume3,Issue2,PP:1-13.

VII. V Suresh, K Maran (2018), A Study On Impact Of An Affiliate Marketing In EBusinessForConsumer’sPerspective,SPAR-InternationalJournalofEngineering andTechnology,Volume10,Issue2,PP:471-475.

VIII. VSuresh,MChitra,KMaran(2016),Astudyonfactorsdeterminingsocialmediaon cosmetic products, - Journal of Pharmaceutical Sciences and Research, Volume 8, Issue1,PP:1.

IX. Venkatesh.P (2013) “Viral Marketing of Digital Products Using Social Media” PEZZOTTAITEJOURNALS,ISSN:2319-9016,onlineISSNNo:2319-9024,Volume.2,PP 120-125.

X. Venkatesh.P(2020),“AStudyAndAnalysisOnImpactOfBrandEquityWithReferenceToAirIndia”,StudiesInIndianPlaceName,ISSN:2394-3114,Vol40issue40 (s1)March2020,PP:304.

Fromtheabovetableitisshownthatpvalueis0.000whichissmallerthansignificantvalue0.05soitisconcludedthatthereisrelationbetweenEducationand Satisfactionlevel.

5. RelationbetweenIncomeandSatisfactionlevel:

Fromtheabovetableitisshownthatpvalueis0.000whichissmallerthansignificantvalue0.05soitisconcludedthatthereisrelationbetweenIncomeandSatisfactionlevel.

XI. VSRekha,KMaran(2012),AdvertisementPressureAndItsImpactOnBodyDissatisfactionAnd Body Image Perception Of Women In India, Global Media Journal: IndianEdition,Violume.3,Issue1,2012.

38 InternationalEducation&ResearchJournal[IERJ] Research Paper E-ISSN No : 2454-9916 | Volume : 8 | Issue : 3 | Mar 2022 Chi-SquareTests Value df AsymptoticSignificance (2-sided) PearsonChi-Square a146.944 12 .000 LikelihoodRatio 155.019 12 .000 Linear-by-LinearAssociation 79.961 1 .000 NofValidCases 100 a. 12 cells (60.0%) have expected count less than 5. The minimum expected countis.50. SatisfactionLevel* Education CrossTabulation Count Education Total Matriculation Graduate Postgraduate Professional Satisfaction Level Highly Satisfied 10 10 0 0 20 Satisfied 0 40 0 0 40 Neutral 0 0 20 0 20 Dissatisfied 0 0 15 0 15 Highly Dissatisfied 0 0 0 5 5 Total 10 50 35 5 100 Chi-SquareTests Value df AsymptoticSignificance (2-sided)
Chi-Square a240.000 12 .000 LikelihoodRatio 191.085 12 .000 Linear-by-LinearAssociation 82.940 1 .000 NofValidCases 100 a. 12 cells (60.0%) have expected count less than 5. The minimum expected
.25. SatisfactionLevel*IncomeCrossTabulation Count Income Total Below 30000Rs 30001to 45000Rs 45001to 60000Rs Above 60000Rs Satisfaction Level Highly Satisfied 5 15 0 0 20 Satisfied 0 5 35 0 40 Neutral 0 0 0 20 20 Dissatisfied 0 0 0 15 15 Highly Dissatisfied 0 0 0 5 5 Total 5 20 35 40 100 Chi-SquareTests Value df AsymptoticSignificance (2-sided) PearsonChi-Square a171.875 12 .000 LikelihoodRatio 188.491 12 .000 Linear-by-LinearAssociation 73.434 1 .000 NofValidCases 100 a. 11 cells (55.0%) have expected count less than 5. The minimum expected count
.25.
Pearson
countis
is

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