Mobile Purchasing Behaviour

BRM Group Project ReportGroup 1

Study Effectiveness of Mobile Advertisements in the purchase decisionSubmitted to Prof. Ravi Shekhar Kumar byB13080 Bhavya SinglaB13092 Kevin ThomasB13105 P. R. RajaramB13109 Ronak DoshiB13111 Sandeep MishraB13122 Vaibhav Kaushik

Table of ContentsBackground of the Study3Management Decision Problem7Hypothesis7Research Problem/ Hypothesis/ Research Objective/ Research Questions7Questionnaire10Test Results13Conclusion of the study27Limitations of the Study28References28

Background of the StudyMobile internet applications enable consumers to access a variety of services: Web information search, SMS (short message service), MMS (multimedia message service), banking, payment, gaming, e-mailing, chat, weather forecast, GPS (global positioning service), and so forth. Collectively, this wide array of services is denominated as "mcommerce." These digital media are considered to potentially improve the possibilities to reach consumers by allowing personalization of the content and context of the message. Combining customer's user profile and the context situation, advertising companies can provide the target customers exactly the advertisement information they desire, not just "spam" them with irrelevant advertisements. With a lot of advanced marketing research and analytics tool being used by many companies it becomes an interesting and valuable study to estimate what is the level of penetration and effectiveness of mobile advertisements.

Personalization and mobility significantly separate mobile phone (m-commerce) advertising fromInternet advertising, potentially giving m-commerce the upper hand. Using advertising based on personalization and geography, firms can identify a users location precisely and deliver relevantmessages to users. The growth of m-commerce will likely contribute to the advancement of mobileadvertising techniques and the diversification of services. The traditional pattern of marketing would be transformed into an interactive one, which implies a move to one-to-one marketing from one-to-more marketing. This makes our study more relevant and interesting.

Some of the journals explored this possibility. One of them was Analysis of the determinants of consumers m-commerce usage activity by Felix T.S. Chan and Alain Yee-Loong Chong. Its purpose was to examine the factors examining the determinants of users mobile commerce usage activities. Data was collected from 402 users and structural equation modelling analysis was employed to test the research model. This research shows that motivational variables have only partial relationships with m-commerce usage activities. Young users, for example, are more likely to use m-commerce for content delivery and entertainment purposes. Young users are more likely to use their mobile devices and engage in activities such as downloading music, watching videos, and sending messages. However age does not have signicant relationships with transaction and location-based activities. Therefore activities such as transaction and location-based services are less commonly used than content delivery and entertainment.

Educational level was found to have a signicant positive relationship with transaction and location-based services. First those who have achieved higher educational levels might have more spending power, and might be more willing to purchase using their mobile devices. Contrary to the ndings of past studies, gender has no inuence on the types of m-commerce activities users engage in. Two intrinsic variables were chosen for this study: (1) Perceived enjoyment; and (2) Perceived ease of use.

Perceived enjoyment has a signicant relationship with all four m-commerce usage activities. The ndings reveal that besides downloading games and listening to music, which are fun and enjoyable activities, users need to perceive that it is enjoyable to engage in transactions such as transferring money, purchasing, and location-based activities, such as receiving mobile advertisements. One reason why users will use m-commerce to conduct mobile banking, for example, is related to the perceived usefulness of the activity. Results revealed that users are only concerned about the security risks involved in transaction and location-based services. Therefore, users are likely to download music or play mobile games without worrying about possible security threats.

This study investigated the relationships between demographic proles, users motivations and security perceptions, with m-commerce usage activities. The ndings have several implications. First, unlike existing studies of technology adoption, this study did not focus on whether or not a user will adopt m-commerce. Instead, it explored the relationships between adoption factors and m-commerce activities. Second, results included direct relationships between demographic variables and m-commerce activities, rather than using one as a control variable.

Third, the study reveals that security concerns only affected transaction and location-based activities. M-commerce providers should improve the security and privacy features of their systems. Fourth, ndings revealed that social inuence can affect content delivery and entertainment activities. Therefore application providers can formulate strategies to promote content delivery and entertainment activities through word of mouth, social network channels, and informal seminars (Wei et al., 2009). Fifth, results reveal that motivation, in particular intrinsic motivation, plays a crucial role in users engagement with m-commerce activities. Sixth, this research has also extended TAM, and applied the enhanced model to study the adoption of m-commerce usage activities. Finally, based on the results, perceived ease of use and perceived enjoyment are two of the most important adoption factors, as they were found to be signicant for all m-commerce usage activities.

Another study is Young consumers motives for using SMS and perceptions towards SMS advertising by Ian Phau and Min Teah. The purpose of it was to examine young consumers motives for using SMS, their SMS usage frequency and their attitudes towards SMS advertising. The approach was through convenience sampling via self-administered questionnaire. A total of 211 samples were collected and retained for analysis.

SMS advertising presents important future implications for marketers and is projected to be a booming advertising medium (Carroll et al., 2007; Muk, 2007). In summary, this paper has identied seven factors that inuence SMS usage. However, only convenience positively inuences SMS usage frequency, whereas economic reasons negatively inuence SMS usage frequency, and only social involvement inuences consumers attitudes towards SMS advertising. There is no signicant relationship between SMS usage frequency and the consumers attitudes towards SMS advertising. Lastly, attitudes towards SMS advertising is not a moderator of motives using SMS and SMS usage frequency. Based on the ndings, convenience is paramount in inuencing SMS usage frequency of the Australian young consumers.

Interestingly, economical reasons negatively inuence SMS usage frequency for high SMS users. Mobile phone service providers could lower costs to consumers and in turn will be able to attract more advertising revenue through SMS advertisements. A cost benet analysis should be performed to arrive with the best option of pricing strategies. Social involvement is found as the factor that inuences consumers attitudes towards advertising. This nding suggests that motivations to participate in contests, voting on reality shows and to donate to charities are well accepted as mainstream lifestyle activities and consumers have a positive acceptance towards such promotions.

It is found that SMS usage frequency does not inuence attitudes towards SMS advertising. This could be well due to the fact that consumers utilize SMS for the sake of communication, and probably do not consider it as an advertising channel as yet. It can be argued that because the market in Australia is relatively new, marketers would need to be careful in understanding what young consumers would benet from SMS ads.

Thus these journals provided some insights into the effectiveness of mobile advertisements and the various factors that impact user behaviour and how the mobile advertisements can play a bigger role in user purchase intentions.

3C MODEL FOR E-COMMERCE BUSINESS

The 3C's Model is a business model, which offers a strategic look at the factors needed for success. The 3Cs model points out that a strategist should focus on three key factors for success. In the construction of a business strategy, three main players must be taken into account: The Customer The Competitors The CorporationOnly by integrating these three, a sustained competitive advantage can exist.

COMPETITION

In E-commerce business it is necessary to have an accurate and current competitive analysis of rival merchants strengths and weaknesses relative to a corporations own operations, providing a significant advantage or identifying opportunities.For small and mid-sized online retailers, a basic competitive analysis should include a regular, qualitative review of the competitors websites, prices, product mix, customer service, policies, and marketing. This data can be used both offensively and defensively to improve our bottom line.In E-commerce business , the competitor is any company that can affect your profit. Some competitors may be weak while others may pose an imminent threat to sales and revenue. To create a competitive analysis, focus should be on those competitors that are either an immediate threat or that could become a threat within a year. To help identify these competitors we should ask two basic questions about our business and our market.1. What is our industry segment?2. Who are our customers?With this information in hand, we can make a list of potential competitors, by noting the following. Any competitor we already know. Retailers that appear at the top of organic search result pages for important queries. Retailers that purchase pay-per-click advertising for industry-specific keywords. Retailers that advertise in industry-related publications. Retailers that appear in dealer locators (from suppliers or manufacturers). Retailers that tweet about the industry on Twitter. Retailers that post about the topic on Facebook.

Once all the competing e-commerce websites have been identified, the corporate strategy needs to be designed to gain a competitive advantage over them. Such as greater advertising, through mobile advertising.

CUSTOMER

Clients are the base of any strategy. Therefore, the primary goal is supposed to be the interest of the customer. In the long run, a company that is genuinely interested in its customers will be interesting for its investors and take care of their interests automatically. Segmentation is one way to help us understand the customer. Segmenting by objectiveThe differentiation is done in terms of the different ways that various customers use a product. Segmenting by customer coverageThis segmentation normally emerges from a trade-off study of marketing costs versus market coverage. There appears always to be a point of diminishing returns in the cost versus coverage relationship. The corporations task is to optimize its range of market coverage, geographically and/ or channel wise. Re-segmenting the marketIn fierce competition, competitors are likely to be dissecting the market in similar ways. Over an extended period of time, the effectiveness of a given initial strategic segmentation will tend to decline. In such situations it is useful to pick a small group of customers and reexamine what it is that they are really looking for.A market segment change occurs where the market forces are altering the distribution of the user-mix over time by influencing demography, distribution channels, customer size, etc. This kind of change means that the allocation of corporate resources must be shifted and/ or the absolute level of resources committed in the business must be changed.

Customers may choose a E-commerce website for any number of reasons, including how much they trust the retailer or like the retailers business philosophy. Some of the factors that consider a customer's decision are: Contact Information & Customer Service:How easy does your ecommerce competition make it for their customers to contact them? Do they clearly display a phone number; make it easy to email them? Have live chat? When you call, email, or chat, note how quick they are to respond; gauge the quality of the help you receive. Purchase :what are various pain points that would cause customers to abandon their shopping cart. If you see that your ecommerce competition has a poorly designed conversion funnel making it harder for their customers to make a purchase, then you can work to ensure it is smooth and quick at your site. Website aesthetics: how good a site looks impacts how much it is trusted. Website content. Includes blogs, articles, videos, and product descriptions. Product selection. Does the site have one type of widget or several to choose from. Price. Pricing relative to the market. Customer service. A site with a phone number might be better than one that only allows email contact. Shipping options. Is free shipping available? Social media presence. It is almost mandatory to have a presence on top social media sites like Facebook and Twitter. These sites help drive traffic and increase reputation. Email marketing. How is email used? Search engine position. In organic search results what is the position of the site. Advertising. Mobile advertisements, Pay-per-click, banners, video, other.

Due to ubiquitous nature of mobile phones, E-commerce websites are finding mobile advertisements, an effective medium to target the customers.

COMPANY

Top 5 E-commerce websites in India are Ebay.com Jabong.com Myntra.com Flipkart.com Snapdeal.com

There are various models of E-commerce such as Business to business (B2B) Business to consumer (B2C) Business to government (B2G) Consumer to consumer (C2C)

In our research we have focused on Business to consumer (B2C) websites. In the super competitive industry, advertising is one of the most important mediums for the companies to increase and maintain their customer base. Because of ubiquitous nature of mobile phones, companies are increasing their spend on mobile ads.Management Decision ProblemShould mobile advertisements be used to promote purchases through e-commerce websites?HypothesisResearch Problem/ Hypothesis/ Research Objective/ Research QuestionsClick on the question number to see the test results and conclusion for each test.Q No.Research ProblemResearch Objective /Research QuestionHypothesis

1To determine the effectiveness of mobile advertisements in its present form

Compare the click through ratio of mobile advertising with the industry average of 7.14% (source: http://appflood.com/blog/average-ctr-by-ad-formats)Mean click through ratio of Mobile Advertising >= Industry Average of 7.14%

2Compare the effectiveness across different Indian citiesMean click through ratio of Mobile Advertising across different cities is the same

3To determine consumer preferences towards mobile advertising

Do users who subscribe to mobile ads find mobile advertisements informative?Users who subscribe to mobile ads find mobile advertisements informative

4Consumer perception of mobile advertisement safety.Consumers feel safe when they receive mobile advertisements

5Effect of promotional offers received on mobile on buying decisionUsers who enjoy receiving promotional offers on mobile phones believe that promotional Offers that come on mobile are more attractive than traditional media

6Identify the factors that affect the attitude of users towards mobile advertisementsAttitude of consumers towards mobile advertisements depend on whether the user finds advertisements entertaining, finds advertisements to make decisions, finds mobile ads informative, finds mobile ads irritating, finds mobile ads unsafe, uses mobile phone to purchase products through e-commerce websitesPerform factor analysis to group variables and then Regression to find the beta's for each factorHypothesis: If user finds advertisements entertaining, finds advertisements to make decisions, finds mobile ads informative, finds mobile ads irritating, finds mobile ads unsafe, uses mobile phone to purchase products through e-commerce websites will describe the attitude of user towards mobile advertisements

7Study user preference for receiving advertisementsIdentify whether user prefers mobile advertisements over online advertisements (web based)Users prefer mobile advertisements over online advertisements

8Gender affects the attitude towards mobile advertisementsMales have a higher positive attitude towards mobile ads as compared to female users

9Users who download mobile apps of e-commerce sites get customized adsUsers who download mobile applications of e-commerce websites receive customized ads

10Identify whether users who perceive mobile ads as unsafe find mobile advertisements an intrusion of privacyUsers who perceive mobile ads as unsafe find mobile advertisements an intrusion of privacy

11Find whether users who pay extra to block ads on mobile aps also use the DND featureUsers who pay extra to block ads on mobile aps use the DND feature

12People who subscribe to mobile advertisements because they believe that mobile advertisements help them make purchase decisionsUsers who believe that mobile advertisements help them make purchase decisions subscribe to mobile advertisements

13Study preferences of users for different types of mobile advertisementsUsers have equal preferences for all the three types of mobile advertisements (sms, flash, in-application ad)

14How many ads per day would users want to receiveWill users prefer to receive less than an average of 2.5 ads per dayUsers prefer to receive less than 2.5 ad per day

QuestionnaireQ1 Please answer the following questions regarding advertisements on mobile phone by e-commerce websitesHighly Agree (1)Agree (2)Neutral (3)Disagree (4)Highly Disagree (5)

You have a positive attitude towards Mobile Advertisements

You enjoy getting promotional offers on your phone

You prefer getting product information via advertisements from e-commerce websites on your mobile phone

You subscribe to offers of your favorite E-commerce websites

Mobile Advertisements helps to keep you updated on latest trends on your favorite e-commerce website

Mobile Advertisements are Informative

Mobile Advertisements help make decision on the go

Mobile Advertisements videos are entertaining

Advertisements on mobile phone are irritating

Advertisements on mobile phone are unsafe

Advertisements on mobile phone violate privacy

You use your mobile phone for mobile internet browsing

You use your phone to download e-commerce shopping application

You purchase items through e-commerce portal apps on your mobile phones

you prefer online advertisement as a medium for receiving product information

You receive customized advertisements on your phone

customized Ads help in your purchase decision

Promotional Offers that come on mobile are more attractive than traditional media

Q3 Tell us about the mobile advertisements you receive on your phone0 (1)1 (2)2 (3)3 (4)4 (5)5 (6)More than 6 (7)

On an average how many mobile advertisements do you get in day

How many SMS ads do you get on an average in a day?

How many mobile advertisements do you click on an average in a day?

How frequently do would you like to receive ads on your mobile?

Q4 Tell us a little more about the mobile advertisements you receive on your phoneAlways (1)Sometimes (2)Never (3)

Do you forward attractive mobile Ads to friends

Do you pay extra in an app to block ads?

Do you post advertisements and offers you receive on your phone on social networking platforms

Do you activate do not disturb to block advertisements on your mobile phone

Q5 Didyou receive any kind of mobile advertisement for the product or e-commerce website before buying it?YesNo

If No Is Selected, Then Skip To Q10 Gender

Q6 What type of Advertisement it wasSMSFlash AdAdvertisement with applications

Q7 How helpful was the Mobile Ad in your purchase decisionVery helpfulSomewhat helpfulNot Helpful

Q8 The Mobile Ad was deceiving?Highly Agree (1)Agree (2)Neutral (3)Disagree (4)Highly Disagree (5)

Q9 GenderMale (1)Female (2)

Q10 Age

Q11 City

Q12 Annual Family IncomeAbove Rs 1 Lac (1)1 to 2.5 Lac (2)2.5 to 5 Lac (3)Above 5 Lac (4)

Q13 EducationUp to Senior SecondaryGraduatePost-Graduate

Q14 OccupationStudentSalaried ProfessionalSelf Employed

Test ResultsAssumption for significance level: alpha = 0.05Mean click through ratio of Mobile Advertising >= Industry Average of 7.14%One-tailed testOne-Sample Statistics

NMeanStd. DeviationStd. Error Mean

CTR5026.460030.622264.33064

One-Sample Test

Test Value = 7.14

TdfSig. (2-tailed)Mean Difference95% Confidence Interval of the Difference

LowerUpper

CTR4.46149.00019.3200010.617228.0228

Conclusion: Since the p-value/2 < 0.05, we accept the hypothesis that Mean click through ratio of Mobile Advertising >= Industry Average of 7.14%Top

Mean click through ratio of Mobile Advertising across different cities is the sameDescriptives

CTR

NMeanStd. DeviationStd. Error95% Confidence Interval for MeanMinimumMaximum

Lower BoundUpper Bound

Mumbai1.0000.....00.00

Delhi1423.071429.216607.808476.202339.9406.0075.00

Chennai632.000028.1780111.503622.429061.5710.0067.00

Kolkata2927.862132.612146.0559215.457140.2671.00100.00

Total5026.460030.622264.3306417.757235.1628.00100.00

ANOVA

CTR

Sum of SquaresDfMean SquareFSig.

Between Groups1102.0433367.348.377.770

Within Groups44846.37746974.921

Total45948.42049

Conclusion: Since the p value > 0.05, we can say that the attitude of consumers vary across the different cities.TopUsers who subscribe to mobile ads find mobile advertisements informativeTwo-tailed test

Paired Samples Statistics

MeanNStd. DeviationStd. Error Mean

Pair 1 You subscribe to offers of your favourite E-commerce websites3.22501.217.172

Mobile Advertisements are Informative3.04501.177.167

Paired Samples Correlations

NCorrelationSig.

Pair 1 You subscribe to offers of your favourite E-commerce websites & Mobile Advertisements are Informative50.449.001

Paired Samples Test

Paired DifferencestDfSig. (2-tailed)

MeanStd. DeviationStd. Error Mean95% Confidence Interval of the Difference

LowerUpper

Pair 1 You subscribe to offers of your favourite E-commerce websites - Mobile Advertisements are Informative.1801.257.178-.177.5371.01349.316

Conclusion: As p value is greater than 0.05 we reject the hypothesis that Users who subscribe to mobile ads find mobile advertisements informativeTop

Consumers feel safe when they receive mobile advertisementsTwo-tailed testWe compare users response to whether they feel unsafe with mobile ads with a mean of 2. A value more than 2 implies users perceive mobile ads as safe. We use a one-sample t-test.

One-Sample Statistics


Advertisements on mobile phone are unsafe492.84.943.135

One-Sample Test

Test Value = 2.5

tDfSig. (2-tailed)Mean Difference95% Confidence Interval of the Difference

LowerUpper

Advertisements on mobile phone are unsafe2.49948.016.337.07.61

Conclusion: Since p value is less than 0.05 we accept the hypothesis that consumers feel safe when they receive mobile advertisementsTopUsers who enjoy receiving promotional offers on mobile phones believe that promotional offers that come on mobile are more attractive than traditional mediaTwo-tailed testPaired Samples Statistics


Pair 1You enjoy getting promotional offers on your phone3.30501.359.192

Promotional Offers that come on mobile are more attractive than traditional media3.04501.177.167


NCorrelationSig.

Pair 1You enjoy getting promotional offers on your phone & Promotional Offers that come on mobile are more attractive than traditional media50.464.001

Paired Samples Test



LowerUpper

Pair 1You enjoy getting promotional offers on your phone - Promotional Offers that come on mobile are more attractive than traditional media.2601.322.187-.116.6361.39149.171

Conclusion: Since the p-value is more than 0.05 we reject the hypothesis that Users who enjoy receiving promotional offers on mobile phones believe that promotional offers that come on mobile are more attractive than traditional media.TopHypothesis: If user finds advertisements entertaining, finds advertisements to make decisions, finds mobile ads informative, finds mobile ads irritating, finds mobile ads unsafe, uses mobile phone to purchase products through e-commerce websites will describe the attitude of user towards mobile advertisementsWe have performed factor analysis to group variables and then Regression to find the beta's for each factorKMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy..619

Bartlett's Test of SphericityApprox. Chi-Square101.804

Df15

Sig..000

Conclusion for KMO and Bartlett's Test: Since Kaiser-Meyer-Olkin Measure of Sampling Adequacy>0.5, we can do factor analysisCommunalities

InitialExtraction

Mobile Advertisements are Informative1.000.827

Mobile Advertisements help make decision on the go1.000.723

Mobile Advertisements videos are entertaining1.000.463

Advertisements on mobile phone are irritating1.000.586

Advertisements on mobile phone are unsafe1.000.649

You purchase items through e-commerce portal apps on your mobile phones1.000.496

Extraction Method: Principal Component Analysis.

Total Variance Explained

ComponentInitial EigenvaluesExtraction Sums of Squared LoadingsRotation Sums of Squared Loadings

Total% of VarianceCumulative %Total% of VarianceCumulative %Total% of VarianceCumulative %

12.72245.36445.3642.72245.36445.3642.16036.00436.004

21.02217.03962.4031.02217.03962.4031.58426.40062.403

3.90215.03577.438

4.66211.03088.468

5.5849.72798.195

6.1081.805100.000


Component Matrixa

Component

12

Mobile Advertisements are Informative.908.059

Mobile Advertisements help make decision on the go.820.226

Mobile Advertisements videos are entertaining.660.164

Advertisements on mobile phone are irritating-.658.391

Advertisements on mobile phone are unsafe-.475.651

You purchase items through e-commerce portal apps on your mobile phones.363.604


a. 2 components extracted.

Rotated Component Matrixa

Component

12

Mobile Advertisements are Informative.777-.473

Mobile Advertisements help make decision on the go.800-.286

Mobile Advertisements videos are entertaining.635-.246

Advertisements on mobile phone are irritating-.313.699

Advertisements on mobile phone are unsafe-.015.805

You purchase items through e-commerce portal apps on your mobile phones.644.285

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 3 iterations.

Conclusion of Factor Analysis: Mobile Advertisements are Informative, Mobile Advertisements help make decision on the go, Mobile Advertisements videos are entertaining, and You purchase items through e-commerce portal apps on your mobile phones are part of component 1 and Advertisements on mobile phone are irritating and Advertisements on mobile phone are unsafe are part of component 2

Component Transformation Matrix

Component12

1.818-.575

2.575.818

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Now we apply regression on the attitude of customer towards mobile ads using independent variables as Mobile Advertisements are Informative and Advertisements on mobile phone are irritating

Variables Entered/Removedb

ModelVariables EnteredVariables RemovedMethod

1 Advertisements on mobile phone are irritating, Mobile Advertisements are Informativea.Enter

a. All requested variables entered.

b. Dependent Variable: You have a positive attitude towards Mobile Advertisements

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate

1.675a.456.433.962

a. Predictors: (Constant), Advertisements on mobile phone are irritating, Mobile Advertisements are Informative

Conclusion of the regression analysis: From the R2 Value of 0.433 we can comment that 43.3% of the value of attitude of customers towards mobile advertisements can be explained from the two variables selected for regression.

ANOVAb

ModelSum of SquaresdfMean SquareFSig.

1Regression36.483218.24219.702.000a

Residual43.51747.926

Total80.00049

a. Predictors: (Constant), Advertisements on mobile phone are irritating, Mobile Advertisements are Informative

b. Dependent Variable: You have a positive attitude towards Mobile Advertisements

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig.

BStd. ErrorBeta

1(Constant).697.6531.067.291

Mobile Advertisements are Informative.762.131.7025.817.000

Advertisements on mobile phone are irritating.080.151.064.532.597

a. Dependent Variable: You have a positive attitude towards Mobile Advertisements

Conclusion: After performing factor analysis and regression, we can comment that attitude of users towards advertisements depends on how users perceive advertisements as "informative" or "irritating" with a beta value of 0.702 and 0.064 respectively. TopUsers prefer mobile advertisements over online advertisementsOne-tailed testPaired Samples Statistics


Pair 1You prefer getting product information via advertisements from e-commerce websites on your mobile phone3.20501.212.171

you prefer online advertisement as a medium for receiving product information2.74501.139.161


NCorrelationSig.

Pair 1You prefer getting product information via advertisements from e-commerce websites on your mobile phone & you prefer online advertisement as a medium for receiving product information50.585.000

Paired Samples Test



LowerUpper

Pair 1You prefer getting product information via advertisements from e-commerce websites on your mobile phone - you prefer online advertisement as a medium for receiving product information.4601.073.152.155.7653.03149.004

Conclusion: We see that p value is significant hence we accept the hypothesis that mobile advertisements are preferred over online advertisements by users to receive product informationTop

Males have a higher positive attitude towards mobile ads as compared to female usersOne-tailed testGroup Statistics

GenderNMeanStd. DeviationStd. Error Mean

You have a positive attitude towards Mobile AdvertisementsMale413.221.194.186

Female82.881.642.581

Independent Samples Test

Levene's Test for Equality of Variancest-test for Equality of Means

FSig.tDfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference

LowerUpper

You have a positive attitude towards Mobile AdvertisementsEqual variances assumed2.300.136.70147.487.345.491-.6441.333

Equal variances not assumed.5658.503.587.345.610-1.0471.736

Conclusion: From the table above we see that the p/2 value is greater than 0.05 and hence we reject the hypothesis that males have a higher positive attitude towards mobile ads as compared to female usersTopUsers who download mobile applications of e-commerce websites receive customized adsTwo-tailed testPaired Samples Statistics


Pair 1 You use your phone to download e-commerce shopping application2.88501.239.175

You receive customized advertisements on your phone2.94501.132.160


NCorrelationSig.

Pair 1 You use your phone to download e-commerce shopping application & You receive customized advertisements on your phone50.416.003

Paired Samples Test

Paired DifferencestdfSig. (2-tailed)


LowerUpper

Pair 1 You use your phone to download e-commerce shopping application - You receive customized advertisements on your phone-.0601.284.182-.425.305-.33049.743

Conclusion: Since p value is greater than 0.05 we reject the hypothesis that users who download mobile applications of e-commerce websites receive customized ads

Top

Users who perceive mobile ads as unsafe find mobile advertisements an intrusion of privacyTwo-tailed testPaired Samples Statistics


Pair 1 Advertisements on mobile phone are unsafe2.8449.943.135

Advertisements on mobile phone violate privacy2.4949.960.137


NCorrelationSig.

Pair 1 Advertisements on mobile phone are unsafe & Advertisements on mobile phone violate privacy49.665.000

Paired Samples Test



LowerUpper

Pair 1 Advertisements on mobile phone are unsafe - Advertisements on mobile phone violate privacy.347.779.111.123.5713.11948.003

Conclusion: As p value is less than 0.05 we accept the hypothesis that users who perceive mobile ads as unsafe find mobile advertisements an intrusion of privacyTop

Users who pay extra to block ads on mobile aps use the DND featureTwo-tailed testPaired Samples Statistics


Pair 1Do you activate do not disturb to block advertisements on your mobile phone1.8849.781.112

Do you pay extra in an app to block ads?2.6749.591.084


NCorrelationSig.

Pair 1Do you activate do not disturb to block advertisements on your mobile phone & Do you pay extra in an app to block ads?49.228.116

Paired Samples Test



LowerUpper

Pair 1Do you activate do not disturb to block advertisements on your mobile phone - Do you pay extra in an app to block ads?-.796.866.124-1.045-.547-6.43748.000

Conclusion: Since p value is greater than 0.05 we accept the hypothesis that users who pay extra to block ads on mobile aps use the DND featureTop

Users who believe that mobile advertisements help them make purchase decisions subscribe to mobile advertisementsTwo-tailed testPaired Samples Statistics


Pair 1 Mobile Advertisements help make decision on the go3.14501.212.171

You subscribe to offers of your favourite E-commerce websites3.22501.217.172


NCorrelationSig.

Pair 1 Mobile Advertisements help make decision on the go & You subscribe to offers of your favourite E-commerce websites50.477.000

Paired Samples Test



LowerUpper

Pair 1 Mobile Advertisements help make decision on the go - You subscribe to offers of your favourite E-commerce websites-.0801.243.176-.433.273-.45549.651

Conclusion: Since p-value is not significant the hypothesis is rejected. So we cannot say that users who believe that mobile advertisements help them make purchase decisions subscribe to mobile advertisementsTopUsers have equal preferences for all the three types of mobile advertisements (sms, flash, in-application ad)One-Way AnovaDescriptives

How helpful was the Mobile Ad in your purchase decision

NMeanStd. DeviationStd. Error95% Confidence Interval for MeanMinimumMaximum


SMS121.58.900.2601.012.1613

Flash Ad52.40.548.2451.723.0823

Advertisement with applications52.00.707.3161.122.8813

Total221.86.834.1781.492.2313

ANOVA

How helpful was the Mobile Ad in your purchase decision

Sum of SquaresdfMean SquareFSig.

Between Groups2.47421.2371.940.171

Within Groups12.11719.638

Total14.59121

Post HOCMultiple Comparisons

How helpful was the Mobile Ad in your purchase decisionLSD

(I) What type of Advertisement it was(J) What type of Advertisement it wasMean Difference (I-J)Std. ErrorSig.95% Confidence Interval


SMSFlash Ad-.817.425.070-1.71.07

Advertisement with applications-.417.425.339-1.31.47

Flash AdSMS.817.425.070-.071.71

Advertisement with applications.400.505.438-.661.46

Advertisement with applicationsSMS.417.425.339-.471.31

Flash Ad-.400.505.438-1.46.66

Conclusion: We see that the preference of users for the three ads is different. And from the LSD we see that SMS and advertisement with applications and SMS with Flash ads have variances which are significantly different.Top

Users prefer to receive less than 2.5 ad per dayOne-tailed testOne-Sample Statistics


How frequently do would you like to receive ads on your mobile?482.001.185.171

One-Sample Test

Test Value = 2.5

tDfSig. (2-tailed)Mean Difference95% Confidence Interval of the Difference

LowerUpper

How frequently do would you like to receive ads on your mobile?-2.92347.005-.500-.84-.16

Conclusion: Since, P value is

Mobile Purchasing Behaviour

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