Master Of Science Dissertation

Consumer Attitudeson

M O B I L E

An Empyrical Analysis

PAYMENTSSOLUTIONS

MSc Marketing Management Dissertation Alessio Aristide Di Salvo - 1656719

12-12-2014 Relator Prof.ssa Deborah Carolina Raccagni

Corelator Prof.ssa Lei Wang

2MSc Marketing Management Dissertation - Alessio Aristide Di Salvo - 12/12/2014

Agenda c

Research Process 3Literature Review 4

Research Model 57Data Analysis9Implications

3. Literature Review1. Observation 2. Qualitative Analysis

3

7 months as Business Developer @ Payleven*

Two Semi-Structured Focus Groups

1. 5 students @ Bocconi Library

2. 3 Merchants already using Payleven mPOS @ payleven HQ

Obtaining more information from past research

• Matching up insights from qualitative research to generate constructs

and hypotheses

4. Research Model

Generating various adoption hypotheses to be

tested quantitatively:

Proposed Effect

Relative Advantage Perceived Cost Compatibility (Pr. + Ex.) Effort Expectancy Trust/Perceived Risks Age Income

5. Quantitative Analysis

Questionnaire

CAWI (Payleven Newsletter)

#Questions

• 5 Constructs • 5 Demographics • NetPromoterScore • DSI

5

+-+++-+

[10][5][1][2]

The Journey cResearch Process

*Mobile POS provider, part of Rocket Internet GmbH

MSc Marketing Management Dissertation - Alessio Aristide Di Salvo - 12/12/2014

4

Existing Research

Percentage of Mobile Payments Publications By Focus Of Research

c

38%

9%

53%

Merchants play a significant role in mobile payment market as both adopters and promoters of the new system. More research is needed to examine the power and participation of merchants in the mobile payments market.

“

’’Dahlberg, Past Present and Future of mPayments

Literature Review

Business Model AnalysesEcosystems CharacterizationAdoption/Acceptance Analyses

Research QuestionThe number of research in this field began increasing in 20071, focusing mainly on three streams of knowledge

Their role in the diffusion studies of Mobile P O S t e c h n o l o g y h a s b e e n w i d e l y underestimated

Merchants as key players in the diffusion of mobile payments solutions

1: Dahlbergh et. al., Past Present and Future of mPayments, 2012


5

Relative Advantage

Perceived Costs

Compatibility (Existing Practices)

Compatibility (Prior Practices)

Age Income Previous Use Innovativeness

Effort Expectancy

Proposed Research Model Result of qualitative research and

review of existing literature

Effects On Adoption c

+

+

+

-

Trust

Adoption

Research Model

++- + +

Direct EffectModerating Effect

+

+

+ + + ++

-

+


6

Relative Advantage

Perceived Costs

Compatibility(Existing Practices)

Compatibility(Prior Practices)

Effort Expectancy

Adoption

Measures the extent to which technology fits with existing and prior values and

practices. Adapted from IDT

Comprises smartphone, POS, fees and added value services.

Measures the degree to which an innovation is perceived better than its

precursor. Adapted from UTAUT

Measures the degree to which an innovation is perceived better than its

precursor. Adapted from UTAUT2 Age Income Previous UseTrust

UTAUT: Unified Theory of Acceptance and Use of Technology, Venkatesh et. al. IDT: Innovation Diffusion Theory, Rogers TAM: Technology Acceptance Model, Rogers

H1

+

H7 -

Constructs and Hypotheses

H2

-H

4 -

H4

-H

5 -

H8 - H9 -H6 -

Technological Behavioral/Social

cResearch ModelEffects On Adoption


7

The Sample [Target: Payleven’s newsletter subscribed customers] 544 completed questionnaires

54% of respondents have been using Payleven for more than 1 year

TurnoverOccupation <50k 50-100k 100-500k 500k+ Total

Lawyers/Notaries 0 0 0 100% 8Consultants 100% 0 0 0 8

Architects/Engineers 60% 40% 0 0 7Doctors/Veterinaries 70% 30% 0 0 54

Craftsmen 78% 11% 11% 0 72Merchants (No mobility) 56% 19% 17% 15% 190

Trade Agents 50% 50% 0 0 16Peddlers 77% 0 23% 0 31

Drivers/Taxis 83% 7% 0 0 48Vacation Rentals 94% 6% 0 0 88

Total 387 87 47 23 544

3%3%

7%

12%

75%

Sole ProprietorshipPartnershipsCorporationsCooperativesOthers

Figure 2 - Type Of Company

Figure 1 - Age Distribution (y.o.)

51+ 25%

41-50 43%

31-40 24%

26-30 7%

18-25 1%

Table 1 - Turnover*Occupation

Descriptive Statistics cData Analysis


8* Constructs are reliable at .6 - .7

√ Convergent Validity√ Discriminant Validity

Adj R2 60%Construct Score

Relative Advantage .89

Perceived Costs .72

Compatibility (Existing) .76

Compatibility (Prior) .72

Effort Expectancy .89

Construct

Relative Advantage 1 component

Perceived Costs 1 component

Compatibility (Existing) 1 component

Compatibility (Prior) 1 component

Effort Expectancy 1 component

Table 3 - Factor Analysis

Table 2 - Cronbach’s Analysis* Table 4 - Linear Regression Results

Adj R2 70%Reference (Venkatesh)

Construct ß Weights

Relative Advantage 37%

Compatibility (Prior) 31%

Compatibility (Existing) 16%

Effort Expectancy 11%

Perceived Costs 5%

Table 4.1 - Beta Scores

√ High level of reliability

√ Linear relations

H1 - Relative Advantage H2 - Perceived Costs H3 - Compatibility (prior & existing) H4 - Effort Expectancy H5 - Trust and perceived risks H6 - Age H7- Income Level H8 - Previous use of POS systems

Hypotheses Summary

√ X √ √ √ X X X

Multivariate Statistics cData Analysis

Obtained


9

Marketing Activities Managerial Implications

Relative Advantage H1

Perceived Costs H2

Compatibility(Ex. Practices)

Compatibility(Pr. Practices)

H3-4

Effort Expectancy H5

Trust & Perceived Risks H6

Age

Income

Previous Use

Innovativeness √

H7

H8

H9

can’t be based on emphasizing convenience (H2).The growth of mobile payments

Consistent and rewarding User experience (H1, H5)together withopportunities for businesses’ revenue growth (H6)

of customers’/users’ (Inn.) behavioral patternsand deep knowledge

could truly influence changes in behavior.

ConfirmedNot Confirmed


10

Service Before And After Transactions

“Cards on file”

Data-analytics driven added value services and tools such as price comparison addons, location-based gratification tools, ad-hoc service/product discovery platforms.

Three trends that will make the difference for mobile payments solutions

Increased Security

“Cards on file” has emerged as a key enabler of transactions being initiated on the mobile devices. This will makes payment seamless and more transparent to consumers

Industry-wide initiatives, such as “tokenization” could significantly increase the perceived level of security.

Questionnaire Results

Value Added ServicesRanked higher than device costs and service fees

57% of respondentsused the mPayment solution as the main payment gateway

Security is the main concern preventing consumers from adopting mobile payments solutions

Future Trends Managerial Implications


11

you.

Thank

Master Of Science Dissertation

Business

Transcript of Master Of Science Dissertation