Descriminent Analysis

8/13/2019 Descriminent Analysis

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ASSIGNMENT

SUBMITTED BY: SHAHID JAVAID

STUDENT I .D : 17181

COURSE : QTA

CLASS DAY: SUNDAY

TIM ING : 03:00 PM TO 6:00 PM

DATE : 19/12/2013

SUBMITTED TO Sir ghulam abbas

IQRA UNIVERSITY IU


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Mobile shopping motivation: an application of multipleDiscriminant analysis

PURPOSE:

This study aims to examine mobile shoppersshopping motivations compared with those of

non-mobile shoppers (i.e. .potential adopters) and to identify driving motivations for consumers

to use the mobile shopping channel.

HYPOTHESIS:

H1. Mobile Shoppers Are More Motivated As Compared To Non Mobile Shoppers

H2. Consumer Behavior Is Directly Dependent On The Communication Of The Seller.

STATITICAL WORK:

Conclusions

Retailers have a chance to inspect their portable shopping capacities and characteristicsand try to position them as push variables to drive shoppers to shop in the versatilechannel. In view of the study comes about, portable shopping services/applications needto be planned and positioned with different shopper inspirations in utilizing anothershopping channel. Thought, productivity, endeavor, and satisfaction shopping causes areinferred as fundamental portable shopping inspirations for the present versatilecustomers. Portable shopping administration offers that composed with those shopping

profits will pick up notoriety around the present versatile customers and rouse thepotential portable customers to utilize the administrations.

One constraint of this study is identified with examining. Since this study example isessential of Us purchasers and the biggest aggregation of respondents is ages 19 to 30years of age, the outcome might have a restricted requisition to different nations andother age bunches. There are numerous other various boulevards for further researchproposed by our effects.

Future exploration is swayed to classify portable shopping administration aspects inconnection to shopping causes to create an improved comprehension of how versatile siteoutline can help. An augmentation of our division approach to additional nations andparticularly non-western societies guarantees intriguing comes about. Moreover, analysts

are urged to broaden division variables to permit a considerably more particular tweakingof the primary shopping inspirations recognized in this research. For instance, a deepercomprehension of portable customers and their lifestyle distinctions might be greatlyadvantageous. Knowing increasingly about how shopping inspirations advance andchange after some time might additionally be helpful. In this way, more longitudinalstudies keeping tabs on portable shopping courses of action are required. Do someportable customers come to be more hedonic or utilitarian as time advances? We trust thisstudy will invigorate the investment of a couple of specialists to seek after these issues intheir future exertions.


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Results:

The majority of the respondents were females (59 percent); most were between the agesof 19 and 30 years (77.2 percent); 40.3 percent had a college degree; 23.5 percent of

respondents were in the mid income level ($50,000-74,999); and 79 percent of theparticipants use their mobile phones for private purposes. As it is reported that mobileshopping continues to rise significantly in the 18 to 34 years old consumer group (ArtTechnology Group, 2010), the sample of this study is representative of current andpotential mobile shoppers. In addition, 26.3 percent (n 105) of the respondents hadshopped from their mobile devices while 73.7 percent (n 295) had no mobile shoppingexperience. Table I provides demographic profiles for the sample in terms of mobileshoppers versus non-mobile shoppers.

Tables:

Percentage of sample

Mobile shoppers Non-mobile shoppersDemographic profile (n105) (n295)

Age21-29 91.4 69.230-39 4.8 18.540-49 2.8 10.550-59 1 6.1Over 60 0 0.7

GenderFemale 41.9 65.1Male 58.1 34.9

EducationHigh School 14.3 12.9Some College 36.2 38.0College 41.9 39.7Graduate School 4.8 9.2Others 2.9 0.3

IncomeUnder $ 25,000 16.2 16.9$25,001-$34,999 15.2 11.5$35,000-$49,999 17.1 15.6$50,000-$74,999 21.9 24.4$75,000-$99,999 21 12.5$100,000-$124,999 3.8 11.5Over $125,000 4.8 7.5

Purpose of mobile phone useExclusively for private 42.9 50.8

Table I. More for private 31.4 29.5Demographics of mobile About 50/50 private and business 22.9 16.3shoppers versus More for business 1.9 3.4non-mobile shoppers Exclusively for business 1 0

Percentage of sampleMobile shoppers Non-mobile shoppers

Demographic profile (n105) (n295)

Age21-29 91.4 69.230-39 4.8 18.5


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40-49 2.8 10.550-59 1 6.1Over 60 0 0.7

GenderFemale 41.9 65.1Male 58.1 34.9

EducationHigh School 14.3 12.9Some College 36.2 38.0College 41.9 39.7Graduate School 4.8 9.2Others 2.9 0.3

IncomeUnder $ 25,000 16.2 16.9$25,001-$34,999 15.2 11.5$35,000-$49,999 17.1 15.6$50,000-$74,999 21.9 24.4$75,000-$99,999 21 12.5$100,000-$124,999 3.8 11.5Over $125,000 4.8 7.5

Purpose of mobile phone use

Exclusively for private 42.9 50.8Table I. More for private 31.4 29.5Demographics of mobile About 50/50 private and business 22.9 16.3shoppers versus More for business 1.9 3.4non-mobile shoppers Exclusively for business 1 0

SHORT COMMINGS:

Results based on the limited data Age limitation limits the reliability of the reearch

Documents

Descriminent Analysis