john sum , mario w.t. liao

John Sum, Mario W.T. LiaoInstitute of E-Commerce, National Chung Hsing University, Taichung 40227, Taiwan

A SEM for the Purchase Intention of Video Game

Consoles

J. Sum & M. Liao, IEC NCHU Purchase Intention Model for VGC 2

Outline Introduction

Objective of study Methodology

Background Survey Conceptual Model Analysis

Preliminary analysis Competitive models

Model Identification Findings Conclusions


Popular home video game consoles (VGC) Microsoft XBOX360 Sony PlayStation 3 Nintendo Wii

1. Introduction


Attributes Nintendo Wii Sony PS3 MS Xbox360

PriceNT 8,500 NT 12,000 (80G)

NT 6,980 (Arcade 遊樂版 )

Product Characteristics

Wii Remote, NunchukVirtual console

FC, SFC, N64Mega DriverNEOGEO

Wii Connect 24

Blue-ray DiskDual-shock 3Playstation Network

Platform

HD-DVD XBOX Live

Compatibility Complementary product

Wii Zapper, 電車GO!,

動物之森 , Wii 方向盤

Wii Fit

Compatible with PSUnable to be

compatible with PlayStation 2

Compatible with Xbox

Brand Value US 8,772* US 13, 583* US 59,007*

“*” Source: Interbrand.com.


1. Introduction

Source: http://www.vgchartz.com/


1. Introduction

Interviews and Background Survey

Model Conceptualization

Data Collection

ScaleReliability and Validity

Model IdentificationModel Validation

Model Interpretation

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Model Conceptualization Literature survey for factors

influencing purchasing intention

Professional games players opinions

Preliminary Analysis In prior to Step 3 Small sample size Pilot study on the research

model Model Validation

In Step 5 Competitive analysis with

other possible models Based on GFI and related

indices


2. Survey Price

Limited budget on purchase intention (Gray M. Erickson and Johansson 1985) even in intrinsic attribute information (Mitra 1995).

Acceptable range when consumers purchase products (Dodds, 1991) Product characteristics

A measure for purchase intention (Lyman E. Ostlund 1974; Susan L. Holak 1988; Rosemary R. Seva, Henry Been-Lirn Duh et al. 2007)

Specialized product characteristics can be more attractive and influences purchase intention (Dhar and Sherman 1996)

Compatibility Associated with how the product fit with consumers’ behavior patterns,

life-styles and values (Rogers 1983). A measurable indictor on purchase intention for durable and non-

durable technology products (Peter C.R. 1979, Labay and Kinnear 1981).


2. Survey Word-of-mouth communication

Communicate the product (and services) information among consumers (Robert East, Kathy Hammond et al. 2007)

Purchase intention is governed by WOM recommendation sources is (Patricia A. Goering 1985).

NWOM will generate negative messages about product through interpersonal channels (Herr, Kardes et al. 1991, Maheswaran and Meyers-Levy 1990)

Brand Brand is a substantial effect on purchase decision making when product

quality is uncertainty (Chu;, Choi; et al. 2005). The brand is a collection of name, term, and symbol representing

producer and is determined as being distinguishable from other corporations (Kolter 1999).

Brand image is associated with brand. It has been recognized as an important concept in marketing (Gardner and Levy; 1955).


3. Research Model

Price

ProductCharacteristics

Comaptiblity

Brand

Word-of-mouthcommunication

PurchaseIntention

H4a

H5a

H7a

H6a

H3a H2a

H9a

H1a

H8a

exogenous latent variables endogenous latent variables


Notationsξ1

ξ2

ξ3

η1

η2

η3

ξ1 : Priceξ2: Product Char.ξ3: Compatibilityη1: Brand η2: WoM η3: Purchase intention

3. Research Model


3. Research ModelH1a: The brand has positive significant impact on purchase intention of home VGC

H2a: Compatibility has positive significant impact on purchase intention of home VGC

H3a: The compatibility has positive significant impact on WOM communication.

H4a: The price has positive significant impact on purchase intention of home VGC

H5a: The product characteristic has positive significant impact on the brand

H6a: The product characteristic has positive significant impact on WOM communication.

H7a: The product characteristics has positive significant impact on brand..

H8a: The WOM communication has positive significant impact on the brand.

H9a: The WOM communication has positive significant impact on purchase intention.


4. Analysis


Preliminary analysis – 100 Samples

Scale Measure Composite Reliability (CR)

To measure items whether to be internal consistency on the variable. The value of items above 0.7 is an acceptable.

Average Variance Extracted (AVE) To measure the total variances in the indicators which estimated by

latent variables. The value of items above 0.7 is an acceptable.

4. Analysis


Variables and items

Construct reliability and validity

Standardized Factor Loading

CompositeReliabilities

Average Variance Extracted

Price

P1 0.53

0.83 0.77P2 0.75

P2 0.69Product Characteristics

PC1 0.85

0.96 0.90PC2 0.82

PC3 0.59Compatibility

C1 0.76

0.95 0.86C2 0.70

C3 0.56Brand

B1 0.80

0.90 0.75B2 0.87

B3 0.74Word-of-mouth Communication

WOM1 0.76

0.90 0.74WOM2 0.76

WOM3 0.81Purchase Intention

PI1 0.73

0.92 0.79PI2 0.80

PI3 0.84

Standardized factor loading, internal composite reliability and average variance extracted of the scale


4. Analysis

Model fit indicesGFI 0.8

2AGFI 0.7

9PGFI 0.6

7RMR 0.1

1RMSEA 0.0

7CFI 0.8

0NFI 0.7

5

Preliminary test result (GLS, 100 Samples)

Price Purchase Intention (Not Sign.)Price Brand (Not Sign.)Compatibility Purchase Intention (Negative Impact)


Path

Model: 1, 2

Price → Brand

Price →Purchase intention

Product Characteristics →Brand

Product Characteristics → WoM

Compatibility→ Purchase Intention

Compatibility →Word-of-mouth

Brand → Purchase Intention

Word-of-mouth →Brand

Word-of-mouth → Purchase Intention

Model 3,4 (For Comparative Analysis)

Price → Purchase Intention

Product Characteristics →Purchase Intention

Compatibility → Purchase Intention

Brand →Purchase Intention

Word-of-mouth → Purchase Intention

Model fit indices GFI, AGFI, PGFI, RMR, RMSEA, CFI, NFI

ξ1

ξ2

η1

ξ3

η2

η3

ξ3

ξ2

η1

η2

η3

η3

ξ1

ξ2

ξ3

ξ4

ξ5

η3

ξ2

ξ3

ξ4

ξ5


Model fit indices Goodness-of-fit index (GFI), Adjusted goodness-of-fit index (AGFI), Parsimonious goodness-of-fit index (PGFI), Root mean residual (RMR) Root mean squared error of approximation (RMSEA), Comparative fit index (CFI), Normed fit index (NFI),

Significant determinant Explanatory power

Squared multiple correlation (SMC),

5. Model Identification


250 samples Gender

Male: 162 Female: 99

Age < 20: 25 21-30: 190 31-40: 35

Experience on VGC < 1: 34 2-5: 46 6-10: 115 >11 : 55

Occupation Student: 172 Private sectors: 26 Govt. agencies: 10 Freelance: 36 Professional players: 6



5. Model IdentificationThe structural model results for Model 1ML

Results:1)All hypotheses are significant except H8a. 2)The brand is affected extremely through WoM communications.


5. Model IdentificationThe structural model results for Model 1GLS

Results:1)The results is the same as Model 1ML. 2)The model performance is the poor in the relative to model 1ML.


5. Model IdentificationThe structural model results for Model2ML

Results:1) The model performance is well but its explanatory power of purchase intention is somewhat poor in comparison to Model1ML.


5. Model IdentificationThe structural model results for Model2GLS

Results:1)The residuals are somewhat higher in relative to Model1ML and Model2ML except for GFI. 2) The explanatory power of word-of-mouth communication is poor for predicting purchase intention.


5. Model IdentificationThe structural model results for Model3ML The structural model results for Model3GLS

Results:1) In either model, its significant impact are not found except for H1a 2) Both performance of model are extremely poor.


5. Model IdentificationThe structural model results for Model4ML The structural model results for Model4 GLS

Results:1) In either model, the residuals are poor above the average. 2) Both explanatory power on purchase intention are better in comparison to Model3. (Model4ML:SMC (PI)=20%; model 4GLS: SMC (PI)=13%)


5. Model IdentificationPaths / Estimation Method Model 1ML Model 1GLS Model 2ML Model 2GLS

γ11 (Price → Brand) 0.2404** 0.0983

γ13 (Price →Purchase intention) 0.2688** -0.0647

γ21 (Product Characteristics →Brand) 0.2582** 0.2132** 0.3196** 0.3181***

γ22(Product Characteristics →Word-of-mouth) 0.3560** 0.2341** 0.3522** 0.2803**

γ33 (Compatibility→ Purchase Intention) -0.2168* -0.2168* -0.2191 -0.2736*

γ32 (Compatibility →Word-of-mouth) 0.2532*** 0.1753* 0.2520** 0.1678*

β13 (Brand → Purchase Intention) 0.2281* 0.1825 0.3401*** 0.2564***

β21 (Word-of-mouth →Brand) 0.4779*** 0.4378*** 0.4698*** 0.4185***

β23 (Word-of-mouth → Purchase Intention) 0.012 -0.0444 -0.0264 -0.0573

Model fit indicesGFI 0.89 0.90 0.91 0.92AGFI 0.84 0.85 0.86 0.88PGFI 0.70 0.70 0.67 0.69RMR 0.10 0.16 0.08 0.13RMSEA 0.07 0.05 0.07 0.09CFI 0.86 0.70 0.90 0.79NFI 0.79 0.55 0.85 0.65


Paths / Estimation Method Model 3 ML Model 3GLS Model 4ML Model 4GLS

γ11 (Price → Purchase Intention) -0.2730*** -0.00459

γ21 (Product Characteristics →Purchase Intention) 0.1950 -0.0813 0.3264** 0.2237*

γ31 (Compatibility → Purchase Intention) -0.0176 -0.00516 -0.2258* -0.2455*

γ41 (Brand →Purchase Intention) 0.1646 -0.00642 0.1924** 0.1024

γ51 (Word-of-mouth → Purchase Intention) -0.0284 -0.0558 -0.0428 -0.0069

Model fit indicesGFI 0.75 0.85 0.86 0.91

AGFI 0.66 0.79 0.79 0.86

PGFI 0.61 0.69 0.68 0.70

RMR 0.17 0.23 0.15 0.20

RMSEA 0.13 0.08 0.09 0.06

CFI 0.56 0.42 0.82 0.73

NFI 0.52 0.35 0.77 0.60




ξ1

ξ2

ξ3

η2 η3

η1

Model fit indicesGFI 0.87

AGFI 0.82

PGFI 0.68

RMR 0.11

RMSEA 0.08

CFI 0.83

NFI 0.76

Yet another alternative



Direct effects Indirect effects Total effects

Variable B WOM PI BWO

MPI B

WO

MPI

P 0.22 0.26 0.05 0.22 0.31

PC 0.25 0.35 0.16 0.05 0.41 0.35 0.05

C 0.25(-

0.21)0.12 0.003 0.12 0.25 -0.18

B 0.22 0.22

WOM 0.47 0.012 0.10 0.47 0.11

1 2 31 2

For example, The direct effect of price toward purchase intention is 0.26 and the indirect effect through brand is calculated by multiplying an effect the price on brand and an effect the brand on purchase intention: 0.22*0.22=0.05. Consequently, the total effect between price and purchase intention is 0.26+0.05=0.31.

ξ1

ξ2

η1

ξ3

η2

η3


Hypotheses

γ11 (Price → Brand)H5a

Support

γ13 (Price →Purchase intention)H4a

Support

γ21 (Product Characteristics →Brand)H7a

Support

γ22 (Product Characteristics →Word-of-mouth Communication)H6a

Support

γ33 (Compatibility→ Purchase Intention)H2a

Support

γ32 (Compatibility →Word-of-mouth Communication) H3a

Support

β13 (Brand → Purchase Intention)H1a

Support

β21 (Word-of-mouth Communication →Brand)H9a

Support

β23 (Word-of-mouth Communication → Purchase Intention)H8a

Not Support

6. Findings


Conclusions

Brand Perceived quality of a VGC

Word-of-Month Communication Professional players opinion No direct impact on the purchase intention

Compatibility should not be a focus on marketing strategy

Professional opinions (blogs) should be adopted as a strategy to boost the sales of a VGC.


Conclusions

Evaluation copies should be released for professional players to assess.

Official forums or blogs should be set up for them to discuss and feedback on those VGCs being evaluated.

Further questions: John Sum, [email protected]

THANK YOU!

john sum , mario w.t. liao

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