3D Printing & Marketing « Adoption of 3D printers and online sunglasses shopping »

Tarig Bouazzati

Directeur : Pr. Sandra Rothenberger Assesseur : Pr. Jean-Pierre Baeyens

MEMOIREPresenté en vue de l’obtention du Master en Ingénieur de gestion,

à finalité Advanced Management

Année académique 2014 - 2015

AGENDA PRESENTATION

IntroductionI

II

III

IVV

VI

VII

VIII

Research Objective

Research Model

Research Method Results

Discussion

Managerial Implications

Limitations

8 PARTS

2

I. Introduction

Intentions to purchase fashion products online is low compared to others products

18.3 %CAGR =E-tailers’ sales (2013 - 2018)

E-commerce turnover (2014)

€ 363 billion

I

GAOPI* FOR DURABLE GOODS

Events tickets 19 %

Computer softwares 18 %

Flowers 11 %

Fashion products 4 %4

Sources : Nielsen (2015), Ecommerce Europe (2014)

*Global Average of Purchase Intentions

Fashion consumers need a multi-sensorial evaluation approach in physical and virtual platforms I

BRICK & MORTAR EXPERIENCE ONLINE SHOPPING EXPERIENCE

Visual Cues

Tactile Cues

Visual Cues

Tactile Cues

EVALUATION OF FASHION PRODUCTS

Sources : Workman,2010; Kim et al.,2009

GAP

5

Sensory enabling technologies are used as proxies to reduce the gap between a physical and a virtual experience I

EVALUATION OF FASHION PRODUCTS

Sources : Workman,2010; Kim et al.,2009

Sensory Enabling Technologies« Technologies providing sensory input in the online shopping environment as a proxy for sensory experiences encountered in direct product examination, and include both product visualization technologies (visual support) and haptic interfaces (tactile support) » (Kim et al., 2009, p.1102)

• Zoom facility • Virtual try-on • 2D & 3D rotation OK

OK

X

6

3D Printers could be the technology allowing tactile inputs triggering in an online shopping process I

Sensory Enabling Technology • Generates tactile cues • Allow to print a prototype of a product

Additive manufacturing machine • Used by product designers & manufacturers• Decreasing prices• Variety of raw materials widening • Performances improving

Mass Adoption

7

II. Research Objective

The future mass-adoption of this specific SET requires a determination of its impact on online consumers’ behavior II

Research Objective

Determine the impact of a 3D printer use in the online evaluation process on the intentions to purchase sunglasses online.

9

III. Research Model

E-shopping experience (EXPE)

H9

Income (INCO)H11

Website design (WDES) H10

H8Intention to use 3DP

(USE)

Perceived usefulness of

3DP (PU)

Perceived ease-of-use of 3DP (PEOU)

Perceived entertainment

value of 3DP (PE)

Functional role

Hedonic role

H1

H2

H3a

H3c

H3b

SE - TAM adapted to the 3DPs (M1)

Attitude toward using 3DP

(ATT)

Technology anxiety (TA)

Innovativeness (INN)

H4

H6

H5

Pre-usage evaluation of a 3DP (EVA

)

H7

aNFTS

iNFTS

Control variables

H12a

H12b

Intention to purchase

sunglasses online using a 3DP!

(Y)

Prediction of online purchase intentions for sunglasses (M2)

11

IV. Research Method

The Research Method was conducted in two steps IV

First step : Qualitative research1. Design of the questionnaire !

• 44 questions • 13 measures • Based on previous studies • 5 points Likert scale

!

2. Pre-test group !

• 5 participants • Location in the surroundings of ULB • Test of the questionnaire in 3 stages

with recursive improvements

Second step : Quantitative research

1. Sample characteristic • 64 answers required (min. 140 in the literature) • 74 valid answers (18% return rate) • 61% women • Restrained e-shoppers • 71% students

!

2. Distribution • Facebook, Twitter and Google+

!

3. Structure of the online survey • Socio-demographics (age, income and gender) • Adoption of a 3DP (attitude,intentions,…) • Online shopping behavior • Need For Touch

13

M1 and M2 were analyzed with two different approaches IV

First sub-model (M1) : SE-TAM (Kim et al., 2009) Partial Least Squares Structure Equation

Modeling (PLS-SEM) !

• More efficient for small samples (Wong, 2013) than covariance based SEM

• Do not focus on data distribution (Esposito Vinzi, 2010) • Aims at maximizing the explained variance of the dependent

variable !

EVAUSEATT

TAINN

PEOU

PU

PE

Second sub-model (M2) :

Multiple Linear Regression !

• Based on previous studies : White and Lloyd (2006), Young Kim and Kim (2004), Cho and Kim (2012), Peck and Childers (2003)

• Dependent variable (Y): intentions to purchase sunglasses online with the use of a 3DP in the evaluation process

!• Independent variables :

✴ EVA : Pre-use evaluation of the prototypes ✴ EXPE : Online purchasing experience ✴ WDES : Website design ✴ INCO : Household income ✴ iNFT : Instrumental need for touch ✴ aNFT : Autotelic need for touch

14

V. Results

Each sub-model has been analyzed with the use of different statistical softwares V

Softwares

Methods

Results

!

"Statistical Tools

First sub-model (M1) Second sub-model (M2)

16

V

Software

Constructs Validation

Results

!

"

1. Measurement model assessment criteria

Items reliability #Loading and cross-loading table

Assessment Criterion Threshold

.50

Convergent validity Average variance extracted (AVE) > .50 #

Discriminant validity

Square-root of AVE More than the correlation of latent variables

#

Reliability Chronbach’s alpha

Variance inflation factor (VIF)

> .70

< 10

#

#

Composite reliability > .70 #

The criteria assessed the validity of the constructs and allow to further analyze the model

The First sub-model (M1) has been analyzed in two steps (1/2)

17

The First sub-model (M1) has been analyzed in two steps (2/2) V

Software

Constructs Validation

Results

!

"

2. Structural model results

!

Seven hypothesized relationships out of eight were validated for the SE-TAM model adapted to the 3DP

18

The Second sub-model (M2) has been analyzed with the use of a backward method V

Software

Method

Results

!

"

Backward Method (alpha .05)

Three variables out of six were found to be significantly impacting the intentions to purchase online with the use of a 3DP

Ord

er

of

elim

inat

ion

Improvement of the statistical model at each step

Income

Website design Autotelic need for touch

Instrumental need for touch

Online purchase experienceEvaluation

19

Software

Method

Results

!

"

The Second sub-model (M2) has been analyzed with the use of a backward method V

The model explained a low percentage of the variance indicating that variables are missing

Multiple linear regression results

R Square

22percent

Fisher test

6.05

Hypothesis Model Beta Validity

H8 EVA 0,38 #

H9 EXPE -0,23 #

H12a iNFT 0,24 #

20

VI. Discussion

The research provided an empirical validation of the SE-TAM for 3D printers (M1) VI

The results indicated that 3D printers could effectively help consumers to collect required information about sunglasses while shopping online

22

Hypothesis Model ValidityH1 PU ATT #H2 PE ATT #H3a PEOU ATT #H3a PEOU PU #H3a PEOU PE #H4 ATT USE #H5 TA USE #H6 INN USE XH7 USE EVA #

SE-TAM adapted to 3D Printers !

• Individuals with high level of technology avoidance would be less prompted to make use of a 3DP when evaluating sunglasses in an online shopping process

!• Hedonic and functional values of 3DPs

!• Innovativeness was not found to influence the adoption of

a 3D printer !

• A strong relationship between the intention to use the 3DP and the evaluation of the sunglasses’ prototypes

!

Two main variables were affecting the intentions to purchase sunglasses online using a 3D printer (M2) VI

The results indicated that 3D printers could effectively help consumers to collect required information about sunglasses while shopping online

23

The Second Sub-model results indicated that : !

• Prior experience of online fashion products purchases inhibits the willingness to make use of a 3DP when purchasing sunglasses online.

!

• Individuals with high instrumental need for touch are more likely to purchase sunglasses online with the use of a 3DP.

!

• Adoption of a 3DP enhances the willingness to purchase sunglasses online when used to gather product related information (visual & tactile inputs).

!

VII. Managerial implications

Sunglasses e-tailers should cease the 3DPs’ mass adoption to come as an opportunity to revamp their online strategy VII

The 3DPs could convince the most reluctant fashion consumers to purchase sunglasses online through an effective collection of visual and tactile information about the products

25

1. Better ressource allocation !

• Limited costs of adaptations but could provide high added value to tech-friendly online fashion consumers.

• Reallocate investments from website designs to integration of 3DPs in the online experience. • Selection of adequate interactive technology could foster long relationships with online

consumers. !

2. Complementary technology !

• Limited costs of adaptations but could provide high added value to tech-friendly online fashion consumers.

VIII. Limitations

This research entails many limitations that suggest further research to be conducted VIII

Conclusions should be considered with due caution and future research is needed in order to enhance the understandings on potential added value 3DPs could bring the online experience

27

1. Experimental conditions • The study did not go beyond behavioral intention of using a 3DP and an online purchase • Picture in the survey might have biased individuals’ evaluation of the outcomes

!

2. Product nature • Sunglasses main evaluation attribute is weight (no glasses, no metallic parts)

!

3. The model • Low R-Squared of M2 • Study of a master model only but more efficient to compare models • Sample size below 140 that limits the inferences

!

4. The measurement • Measurement based on self-report basis • NFT is suggested to be measured on a 7 point Likert scale instead of 5

Thank You for your attention

Questions ?

APPENDIX

* The demographic variables have been voluntarily ignored (Income)

Coefficient of determination : R squared

Criterion Note

.67 substantial

Predictive relevance : Q squared

Effect size : f squared

> 0

.19 weak

.35 large

.02 small

Global fit measure : GoF > .36

The First sub-model (M1) assessment was made with the use of 4 criterion

Assessment of the structural model

The model exhibited a global fit that was found to be good with a GoF = 0.59

PLS-SEM Results Hypothesis

Coefficient p-value Significance Effect sizes Std. Errors Block VIF

H1 0,161 0,030 * 0,061 0,085 1,510H2 0,634 < 0,001 *** 0,400 0,085 1,381H3a 0,256 0,002 ** 0,037 0,085 1,111H3b 0,272 < 0,001 *** 0,074 0,085H3c 0,339 < 0,001 *** 0,115 0,085H4 0,355 < 0,001 *** 0,164 0,085 1,326H5 -0,077 0,002 ** 0,025 0,085 1,289H6 0,255 0,183 NS 0,105 0,085 1,595H7 0,737 < 0,001 *** 0,542 0,085Notes: * = Significant at p < 0.05; ** = Significance at p < 0.01; *** = Significant at p < 0.001

A

Reliability of each of the constructs for the M1 A

Reliability and validity indicators of the constructs Constructs Items Loadings Reliability Alpha AVE

Technology avoidance (TA) TA1 0,902 0,780 0,699TA2 0,873TA3 0,721

Innovativeness (INN) INN1 0,895 0,833 0,750INN2 0,857INN3 0,845

Perceived usefulness (PU) PU1 0,883 0,835 0,676PU2 0,915PU3 0,791PU4 0,778

Perceived ease-of-use (PEOU) PEOU1 0,881 0,873 0,798PEOU2 0,888PEOU3 0,910

Perceived entertainment (PE) PE1 0,864 0,655 0,573PE2 0,850PE3 0,907PE4 0,804

Attitude (ATT) ATT1 0,746 0,769 0,522ATT2 0,872ATT3 0,705ATT4 0,873

Intentions to use a 3DP (USE) USE1 0,858 0,743 0,737USE2 0,858

Pre-use evaluation (EVA) EVA1 0,929 0,841 0,863EVA2 0,929

The Need For Touch entails two main dimensions A

The Need For Touch Peck and Childers (2003a, 2003b)

Instrumental NFT Autotelic NFT

Individuals’ pleasure and satisfaction to touch products for the experiential enjoyment.

The need to gather information over a product through tactile inputs in order to make an informed purchase decision.

Utilitarian Motives Hedonic Motives

Low iNFTmales

fashion followersHigh aNFT

females

fashion leadersWorkman (2010)

Scale items : adapted SE-TAM model Kim et al. 2008 1 : strongly disagree 2 : strongly agree

1 2 3 4 51 Technical terms sound like confusing jargon to me2 I have avoided technology because it is unfamiliar to me 3 I hesitate to use most forms of technology for fear of making mistakes i cannot correct4 If I heard about a new technology, I would look for ways to experiment with it 5 Among my peers, I am usually the first to try out new technologies 6 I like to experiment with new technologies 7 the 3DP would improve my online shopping productivity8 The 3DP would enhance my effectiveness when shopping online 9 The 3DP would be helpful in buying what I want online 10 The 3DP would improve my online ability shopping ability11 Using a 3DP is clear and understandable 12 Using a 3DP does not require a lot of mental effort 13 The 3DP is easy to use 14 Shopping with the 3DP would be fun for its own sake

TA

INN

PU

PEOU

Questionnaire A

Scale items : adapted SE-TAM model Kim et al. 2008 1 : strongly disagree 2 : strongly agree

1 2 3 4 515 Shopping with a 3DP would be exciting

16 Shopping with a 3DP would be enjoyable

17 Shooping with a 3DP would be interesting

18 Using a 3DP is a good idea

19 Using a 3DP is supperior/inferior

20 Using a 3DP is pleasant/unpleasant

21 Using a 3DP is appealing/unappealing

22 I would use the 3DP for purchasing sunglasses online

23 I would use the 3DP for browsing for sunglasses online

24 Overall, I would be satisfied with using a 3DP

25 In my opinion, the 3DP would provide satisfactory help when I make a purchase decision

26 I would be likely to purchase apparel from a site providing the ability to print a 3D prototype

27 I am experienced consumer at purchasing durable goods online

28 The website design matters to determine if I would be likely to purchase online SG using a 3DP

PE

ATT

USE

EVA

X2

X4

Questionnaire A

Need For Touch (control variables) Peck & Childers 2003 1 : strongly disagree 2 : strongly agree

1 2 3 4 51 When walking through stores, I can’t help touching all kind of products A2 Touching products can be fun A3 I place most trust in products that can be touched before purchase I4 I feel more comfortable purchasing a product after physically examine it I5 When browsing in stores, it is important for me to handle all kind of products A6 If I can’t touch a product in the store, I am reluctant to purchase the product I7 I like to touch products even if I have no intention of buying them A8 I feel more confident making a purchase after touching a product I9 The only way to make sure a product is worth buying is to actually touch it I10 Browsing in stores, I like to touch lots of products A11 There are many products that I would only buy if I could handle them before purchase I12 I find myself touching all kind of products in stores A

A = autotelic factor (pleasure to touch) B = instrumental factor ( gathering information about the product in order to help the decision making process

AQuestionnaire