5.2. Saran dan Keterbatasan
5.2.2. Keterbatasan dan Saran Peneliti Lanjutan
Keterbatasan dan saran yang dapat diberikan kepada peneliti selanjutnya yang ingin meneliti tema tentang eWOM adalah sebagai berikut:
1. Indikator dan measurment yang ada belum seluruhnya merepresentasikan variabel yang ada dalam penelitian ini terutama di indikator eWOM. Saran untuk penelitian selanjutnya harus mencari indikator dan measurement yang kuat dan merepresentasikan variabel- variabel yang ada.
2. Responden dalam penelitian ini mempunyai jenjang umur yang beragram sehingga pemahaman dan tujuan melihat reviews pun beragam dan membuat data menjadi bias. Saran untuk penilitian selanjutnya harus lebih memiliki kriteria umur khusus seperti kategori usia 40 sampai 60
tahun (Baby Boomer) yang merupakan umur mapan dalam hal ekonomi karena pada umumnya masyarakat ekonomi mapan sudah bisa untuk membeli mobil merupakan suatu barang mewah.
3. Variabel yang di uji hanya 3 Variabel sehingga peranan eWOM belum tergambar secara baik. Saran untuk penelitian selanjutnya harus menambahkan variabel mediasi di antara variabel eWOM dan Purchase Intention seperti variabel Money for Value untuk melihat perbandingan pengaruh dengan Brand Attitude.
4. Objek yang di teliti dalam penelitian ini mobil yang merupakan golongan barang/produk mewah atau mahal. Saran penelitian selanjutnya dengan mengganti objek seperti produk makanan atau pakaian yang relatif bisa dijangkau oleh semua kalangan.
5. Penelitian ini dilakukan di DKI Jakarta. Saran penelitian lanjutan harus meneliti di daerah lain yang memiliki daya beli rendah untuk melihat pengaruh eWOM terhadap daerah yang memliki daya beli rendah.
DAFTAR PUSTAKA
Abzari, M., Ghassemi, R. A., & Vosta, L. N. (2014). Analysing the Effect of Social Media on Brand Attitude and Purchase Intention: The Case of Iran Khodro Company. Procedia - Social and Behavioral Sciences, 143, 822–826.
https://doi.org/10.1016/j.sbspro.2014.07.483
Alexa.com. (2018). Topsites in Indonesia. Retrieved from https://www.alexa.com/topsites/countries/ID
Banerjee, S., & Chua, A. Y. K. (2014). A Theoretical Framework to Identify Authentic Online Reviews. Online Information Review, 38(5), 634–649.
https://doi.org/10.1108/OIR-02-2014-0047
Belch, G. E., & Belch, M. A. (2012). Advertising and Promotion an Integrated Marketing Communication Perspective (9th Editio). Singapore: McGraw Hill/Irwin.
Bradley, G. L., Sparks, B. A., & Weber, K. (2016). Perceived Prevalence and Personal Impact of Negative Online Reviews. Journal of Service Management, 27(4).
Bradley, G., Sparks, B. A., & Weber, K. (2015). The stress of anonymous online reviews : A conceptual model and research agenda. International Journal of Contentporary Hostpitality Management, 27(5), 739–755.
https://doi.org/10.1108/IJCHM-01-2014-0005
Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of Electronic Word-of-Mouth: Informational and Normative Determinants of On-line Consumer Recommendations. International Journal of Electronic Commerce, 13(4), 9–38. https://doi.org/10.2753/JEC1086-4415130402
Chu, S.-C. (2009). Determinants of Consumer Engagement in Electronic Word of Mouth in Social Networking sites.
Fan, Y., & Miao, Y. (2012). Effect of Electronic Word-of-Mouth On Consumer Purchase Intention : The Perspective of Gender Differences. International Journal of Electronic Business Management, 10(3), 175–181.
Gaikindo. (2018). Wholesales, Production, Export Import by Brand 2018.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th Editio). USA: Pearson.
Hasan, A. (2010). Marketing Dari Mulut ke Mulut. Yogyakarta: Medpres.
Hong, S., & Park, H. S. (2012). Computer-mediated persuasion in online reviews:
Statistical versus narrative evidence. Computers in Human Behavior, 28(3), 906–919. https://doi.org/10.1016/j.chb.2011.12.011
Idris, M. (2018). 2017, Warga Jabar dan Jakarta Paling Banyak Beli Mobil Baru.
Retrieved from https://oto.detik.com/mobil/d-3822854/2017-warga-jabar- dan-jakarta-paling-banyak-beli-mobil-baru
Jalilvand, M. R., & Samiei, N. (2012). The effect of electronic word of mouth on brand image and purchase intention An empirical study in the automobile.
Marketing Intelligence & Planning, 30(4), 460–476.
https://doi.org/10.1108/02634501211231946
Keller, K. L. (2013). Strategic Brand Management, Building, Measuring, and
Managing Brand Equity (4th Editio). England: Pearson.
Kominfo.go.id. (2018). Pengguna Internet Indonesia Nomor Enam Dunia.
Retrieved from https://kominfo.go.id/content/detail/4286/pengguna-internet- indonesia-nomor-enam-dunia/0/sorotan_media
Kotler, P., & Armstrong, G. (2018). Principles of Marketing (17th Editi). Pearson.
Kudeshia, C., & Kumar, A. (2017). Social eWOM : does it affect the brand attitude and purchase intention of brands ? Management Research Review, 40(3), 310–
330. https://doi.org/10.1108/MRR-07-2015-0161
Kusumaputra, R. A. (2012). Sejarah Mobil dan Kisah Kehadiran Mobil di Negeri
Ini. Retrieved from
http://bisniskeuangan.kompas.com/read/2012/07/11/11372133/Sejarah.Mobil .dan.Kisah.Kehadiran.Mobil.di.Negeri.Ini
Lee, J., Park, D., & Han, I. (2011). The Different Effects of Online Consumer Reviews on Consumers’ Purchase Intentions Depending on Trust in Online Shopping Malls. Internet Research, 21(2), 187–206.
https://doi.org/10.1108/10662241111123766
Lee, M., & Youn, S. (2009). Electronic word of mouth (E-WOM): How eWOM Platforms Influence Consumer Product Judgment. International Journal of Advertising, 28(3), 473–499. https://doi.org/10.2501/S0265048709200709 Lu, L. C., Chang, W. P., & Chang, H. H. (2014). Consumer attitudes toward
blogger’s sponsored recommendations and purchase intention: The effect of sponsorship type, product type, and brand awareness. Computers in Human Behavior, 34, 258–266. https://doi.org/10.1016/j.chb.2014.02.007
Malhotra, N. K. (2010). Marketing Research (6th Editio). USA: Pearson.
Matute, J., Polo-Redondo, Y., & Utrillas, A. (2016). The influence of EWOM characteristics on online repurchase intention: Mediating roles of trust and perceived usefulness. Online Information Review, 40(7), 1090–1110.
https://doi.org/10.1108/OIR-11-2015-0373
Otterbacher, J. (2009). “ Helpfulness ” in Online Communities : A Measure of Message Quality.
Santoso, S. (2012). Analisis SEM menggunakan AMOS. Jakarta: PT Elex Media Komputindo.
Schiffman, L. G., & Kanuk, L. L. (2010). Consumer Behavior (10th Editi). Pearson.
Sciffman, L. G., & Wisenblit, J. L. (2015). Consumer Behavior (11th Editi).
England: Pearson.
Strauss, J., & Frost, R. (2016). E-Marketing (7th Editio). England: Pearson.
Tariq, M. I., Rafay Nawaz, M., Nawaz, M. M., & Butt, H. A. (2013). Customer Perceptions About Branding and Purchase Intention: A Study of FMCG in an Emerging Market. Journal of Basic and Applied Scietific Research, 3(2), 340–
347.
Wearesocial.com. (2018). Digital in Asia 2018. Retrieved from https://www.slideshare.net/wearesocial?utm_campaign=profiletracking&utm _medium=sssite&utm_source=ssslideview
Wu, P. C. S., & Wang, Y. (2011). The Influences of Electronic Word‐of‐Mouth Message Appeal and Message Source Credibility on Brand Attitude. Asia Pacific Journal of Marketing and Logistics, 23(4), 448–472.
https://doi.org/10.1108/13555851111165020
Zhang, J., Ren, M., Xiao, X., & Zhang, J. (2017). Providing consumers with a representative subset from online reviews. Online Information Review, 41(6), 877–899. https://doi.org/10.1108/OIR-05-2016-0125
LAMPIRAN
Lampiran 1.1. Kuesioner Penelitian
Lampiran 1.2. Hasil Uji Validitas Pre-test (30 Responden)
1. eWOM
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,742
Bartlett's Test of Sphericity
Approx. Chi-Square 97,421
df 15
Sig. ,000
Anti-image Matrices
eWOM1 eWOM2 eWOM3 eWOM4 eWOM5 eWOM6
Anti-image Covariance
eWOM1 ,591 -,190 ,203 -,180 ,043 -,085
eWOM2 -,190 ,436 -,198 ,002 ,013 -,051
eWOM3 ,203 -,198 ,394 -,074 -,024 -,065
eWOM4 -,180 ,002 -,074 ,452 -,138 ,048
eWOM5 ,043 ,013 -,024 -,138 ,208 -,149
eWOM6 -,085 -,051 -,065 ,048 -,149 ,218
Anti-image Correlation
eWOM1 ,553a -,375 ,421 -,348 ,124 -,238
eWOM2 -,375 ,790a -,477 ,004 ,043 -,164
eWOM3 ,421 -,477 ,745a -,174 -,085 -,222
eWOM4 -,348 ,004 -,174 ,793a -,451 ,154
eWOM5 ,124 ,043 -,085 -,451 ,735a -,699
eWOM6 -,238 -,164 -,222 ,154 -,699 ,758a
a. Measures of Sampling Adequacy(MSA)
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative %
1 3,673 61,214 61,214 3,673 61,214 61,214
2 ,966 16,105 77,318
3 ,601 10,009 87,328
4 ,406 6,760 94,088
5 ,237 3,944 98,032
6 ,118 1,968 100,000
Extraction Method: Principal Component Analysis.
Component Matrixa
Component 1
eWOM1 ,511
eWOM2 ,791
eWOM3 ,765
eWOM4 ,782
eWOM5 ,888
eWOM6 ,896
Extraction Method:
Principal Component Analysis.
a. 1 components extracted.
2. Brand Attitude
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,791
Bartlett's Test of Sphericity
Approx. Chi-Square 81,182
df 10
Sig. ,000
BA1 BA2 BA3 BA4 BA5
Anti-image Covariance
BA1 ,260 -,123 -,046 -,136 -,135
BA2 -,123 ,313 -,144 -,061 ,158
BA3 -,046 -,144 ,362 -,038 -,166
BA4 -,136 -,061 -,038 ,406 -,004
BA5 -,135 ,158 -,166 -,004 ,644
Anti-image Correlation
BA1 ,792a -,431 -,151 -,419 -,329
BA2 -,431 ,752a -,428 -,172 ,351
BA3 -,151 -,428 ,831a -,100 -,344
BA4 -,419 -,172 -,100 ,876a -,007
BA5 -,329 ,351 -,344 -,007 ,640a
a. Measures of Sampling Adequacy(MSA)
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative %
1 3,364 67,286 67,286 3,364 67,286 67,286
2 ,827 16,531 83,817
3 ,386 7,712 91,529
4 ,247 4,949 96,478
5 ,176 3,522 100,000
Extraction Method: Principal Component Analysis.
Component Matrixa
Component 1
BA1 ,919
BA2 ,850
BA3 ,874
BA4 ,847
BA5 ,564
Extraction Method:
Principal Component Analysis.
a. 1 components extracted.
3. Purchase Intention
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,759
Bartlett's Test of Sphericity
Approx. Chi-Square 44,727
df 6
Sig. ,000
Anti-image Matrices
PI1 PI2 PI3 PI4
Anti-image Covariance
PI1 ,802 -,137 -,020 -,075
PI2 -,137 ,526 -,155 -,087
PI3 -,020 -,155 ,369 -,227
PI4 -,075 -,087 -,227 ,399
Anti-image Correlation
PI1 ,876a -,211 -,037 -,132
PI2 -,211 ,822a -,353 -,190
PI3 -,037 -,353 ,703a -,591
PI4 -,132 -,190 -,591 ,729a
a. Measures of Sampling Adequacy(MSA)
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative %
1 2,616 65,405 65,405 2,616 65,405 65,405
2 ,731 18,276 83,681
3 ,415 10,365 94,046
4 ,238 5,954 100,000
Extraction Method: Principal Component Analysis.
Component Matrixa
Component 1
PI1 ,618
PI2 ,835
PI3 ,882
PI4 ,871
Extraction Method:
Principal Component Analysis.
a. 1 components extracted.
Lampiran 1.3. Hail Uji Realibilitas Pre-test (30 Responden)
1. eWOM
Case Processing Summary
N %
Cases
Valid 30 100,0
Excludeda 0 ,0
Total 30 100,0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics Cronbach's
Alpha
N of Items
,861 6
Item Statistics
Mean Std. Deviation N
eWOM1 4,13 ,937 30
eWOM2 4,03 ,850 30
eWOM3 3,67 ,661 30
eWOM4 3,57 ,728 30
eWOM5 3,70 ,837 30
eWOM6 3,63 ,999 30
Item-Total Statistics Scale Mean if
Item Deleted
Scale Variance if Item Deleted
Corrected Item- Total Correlation
Cronbach's Alpha if Item
Deleted
eWOM1 18,60 11,628 ,406 ,886
eWOM2 18,70 10,562 ,690 ,831
eWOM3 19,07 11,857 ,616 ,846
eWOM4 19,17 11,247 ,680 ,835
eWOM5 19,03 10,171 ,792 ,812
eWOM6 19,10 9,197 ,809 ,806
2. Brand Attitude
Case Processing Summary
N %
Cases
Valid 30 100,0
Excludeda 0 ,0
Total 30 100,0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics
Cronbach's Alpha
N of Items
,876 5
Item Statistics
Mean Std. Deviation N
BA1 4,10 ,995 30
BA2 4,43 ,858 30
BA3 4,07 ,907 30
BA4 3,80 ,997 30
BA5 4,13 ,776 30
Item-Total Statistics Scale Mean if
Item Deleted
Scale Variance if Item Deleted
Corrected Item- Total Correlation
Cronbach's Alpha if Item
Deleted
BA1 16,43 8,047 ,852 ,811
BA2 16,10 9,266 ,735 ,843
BA3 16,47 8,809 ,782 ,831
BA4 16,73 8,547 ,739 ,842
BA5 16,40 11,007 ,434 ,904
3. Purchase Intention
Case Processing Summary
N %
Cases
Valid 30 100,0
Excludeda 0 ,0
Total 30 100,0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics Cronbach's
Alpha
N of Items
,821 4
Item Statistics
Mean Std. Deviation N
PI1 3,53 ,776 30
PI2 2,97 ,928 30
PI3 3,30 ,877 30
PI4 3,33 ,884 30
Item-Total Statistics Scale Mean if
Item Deleted
Scale Variance if Item Deleted
Corrected Item- Total Correlation
Cronbach's Alpha if Item
Deleted
PI1 9,60 5,628 ,438 ,857
PI2 10,17 4,351 ,680 ,758
PI3 9,83 4,351 ,745 ,726
PI4 9,80 4,372 ,727 ,734
Lampiran 1.4. Hasil Uji Normalitas Data & GOF (Model pengukuran)
1. Computation of degrees of freedom (Default model)
Number of distinct sample moments: 120 Number of distinct parameters to be estimated: 33 Degrees of freedom (120 - 33): 87
2. Result
Minimum was achieved Chi-square = 183,621 Degrees of freedom = 87 Probability level = ,000
Maximum Likelihood Estimates
Regression Weights: (Group number 1 - Default model)
Estimate S.E. C.R. P Label
eWOM6 <--- eWOM 1,000
eWOM5 <--- eWOM ,914 ,097 9,432 ***
eWOM4 <--- eWOM ,641 ,090 7,145 ***
eWOM3 <--- eWOM ,780 ,092 8,458 ***
eWOM2 <--- eWOM ,801 ,093 8,603 ***
eWOM1 <--- eWOM ,646 ,106 6,076 ***
BA5 <--- Brand_Attitude 1,000
BA4 <--- Brand_Attitude 1,184 ,157 7,542 ***
BA3 <--- Brand_Attitude 1,148 ,146 7,871 ***
BA2 <--- Brand_Attitude 1,180 ,140 8,442 ***
BA1 <--- Brand_Attitude 1,283 ,159 8,050 ***
PI4 <--- Purchase_Intention 1,000
PI3 <--- Purchase_Intention 1,073 ,125 8,563 ***
PI2 <--- Purchase_Intention 1,068 ,134 7,980 ***
PI1 <--- Purchase_Intention ,988 ,115 8,590 ***
Standardized Regression Weights: (Group number 1 - Default model)
Estimate
eWOM6 <--- eWOM ,798
eWOM5 <--- eWOM ,817
eWOM4 <--- eWOM ,654
eWOM3 <--- eWOM ,750
eWOM2 <--- eWOM ,760
eWOM1 <--- eWOM ,569
BA5 <--- Brand_Attitude ,705 BA4 <--- Brand_Attitude ,768 BA3 <--- Brand_Attitude ,803 BA2 <--- Brand_Attitude ,867 BA1 <--- Brand_Attitude ,822 PI4 <--- Purchase_Intention ,777 PI3 <--- Purchase_Intention ,797 PI2 <--- Purchase_Intention ,749 PI1 <--- Purchase_Intention ,800
Covariances: (Group number 1 - Default model)
Estimate S.E. C.R. P Label eWOM <--> Brand_Attitude ,322 ,066 4,875 ***
Brand_Attitude <--> Purchase_Intention ,232 ,054 4,283 ***
eWOM <--> Purchase_Intention ,427 ,081 5,254 ***
Correlations: (Group number 1 - Default model)
Estimate eWOM <--> Brand_Attitude ,777 Brand_Attitude <--> Purchase_Intention ,620 eWOM <--> Purchase_Intention ,841
3. Model Fit
Model Fit Summary CMIN
Model NPAR CMIN DF P CMIN/DF
Default model 33 183,621 87 ,000 2,111
Saturated model 120 ,000 0
Independence model 15 1123,291 105 ,000 10,698
RMR, GFI
Model RMR GFI AGFI PGFI
Default model ,048 ,824 ,758 ,598 Saturated model ,000 1,000
Independence model ,327 ,225 ,114 ,197
Baseline Comparisons
Model NFI
Delta1
RFI rho1
IFI Delta2
TLI
rho2 CFI Default model ,837 ,803 ,907 ,885 ,905
Saturated model 1,000 1,000 1,000
Independence model ,000 ,000 ,000 ,000 ,000
Parsimony-Adjusted Measures
Model PRATIO PNFI PCFI
Default model ,829 ,693 ,750 Saturated model ,000 ,000 ,000 Independence model 1,000 ,000 ,000
NCP
Model NCP LO 90 HI 90
Default model 96,621 61,501 139,499
Saturated model ,000 ,000 ,000
Independence model 1018,291 914,319 1129,695
FMIN
Model FMIN F0 LO 90 HI 90
Default model 1,685 ,886 ,564 1,280 Saturated model ,000 ,000 ,000 ,000 Independence model 10,305 9,342 8,388 10,364
RMSEA
Model RMSEA LO 90 HI 90 PCLOSE
Default model ,101 ,081 ,121 ,000
Independence model ,298 ,283 ,314 ,000
AIC
Model AIC BCC BIC CAIC
Default model 249,621 260,976 338,737 371,737 Saturated model 240,000 281,290 564,058 684,058 Independence model 1153,291 1158,452 1193,798 1208,798
ECVI
Model ECVI LO 90 HI 90 MECVI
Default model 2,290 1,968 2,683 2,394 Saturated model 2,202 2,202 2,202 2,581 Independence model 10,581 9,627 11,603 10,628
HOELTER
Model HOELTER
.05
HOELTER .01
Default model 66 72
Independence model 13 14
Minimization: ,009 Miscellaneous: ,729 Bootstrap: ,000
Total: ,738
Lampiran 1.5. Hasil Uji Validitas & Realibilitas (Model Struktural)
Notes for Model (Default model)
Computation of degrees of freedom (Default model)
Number of distinct sample moments: 120 Number of distinct parameters to be estimated: 33 Degrees of freedom (120 - 33): 87
Result (Default model)
Minimum was achieved Chi-square = 183,621 Degrees of freedom = 87 Probability level = ,000
Model Fit Summary CMIN
Model NPAR CMIN DF P CMIN/DF
Default model 33 183,621 87 ,000 2,111
Saturated model 120 ,000 0
Independence model 15 1123,291 105 ,000 10,698
RMR, GFI
Model RMR GFI AGFI PGFI
Default model ,048 ,824 ,758 ,598 Saturated model ,000 1,000
Independence model ,327 ,225 ,114 ,197
Baseline Comparisons
Model NFI
Delta1
RFI rho1
IFI Delta2
TLI
rho2 CFI Default model ,837 ,803 ,907 ,885 ,905
Saturated model 1,000 1,000 1,000
Independence model ,000 ,000 ,000 ,000 ,000
Parsimony-Adjusted Measures
Model PRATIO PNFI PCFI Default model ,829 ,693 ,750 Saturated model ,000 ,000 ,000 Independence model 1,000 ,000 ,000
NCP
Model NCP LO 90 HI 90
Default model 96,621 61,501 139,499
Saturated model ,000 ,000 ,000
Independence model 1018,291 914,319 1129,695
FMIN
Model FMIN F0 LO 90 HI 90
Default model 1,685 ,886 ,564 1,280 Saturated model ,000 ,000 ,000 ,000 Independence model 10,305 9,342 8,388 10,364
RMSEA
Model RMSEA LO 90 HI 90 PCLOSE
Default model ,101 ,081 ,121 ,000
Independence model ,298 ,283 ,314 ,000
AIC
Model AIC BCC BIC CAIC
Default model 249,621 260,976 338,737 371,737 Saturated model 240,000 281,290 564,058 684,058 Independence model 1153,291 1158,452 1193,798 1208,798
ECVI
Model ECVI LO 90 HI 90 MECVI
Default model 2,290 1,968 2,683 2,394 Saturated model 2,202 2,202 2,202 2,581 Independence model 10,581 9,627 11,603 10,628
HOELTER
Model HOELTER .05
HOELTER .01
Default model 66 72
Independence model 13 14
Execution time summary
Minimization: ,094 Miscellaneous: 1,045 Bootstrap: ,000
Total: 1,139
Lampiran 1.6. Hasil Uji Struktural
Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates
Regression Weights: (Group number 1 - Default model)
Estimate S.E. C.R. P Label Brand_Attitude <--- eWOM ,734 ,101 7,289 ***
Purchase_Intention <--- Brand_Attitude -,081 ,135 -,599 ,549 Purchase_Intention <--- eWOM ,819 ,153 5,335 ***
eWOM6 <--- eWOM 1,000
eWOM5 <--- eWOM ,914 ,097 9,432 ***
eWOM4 <--- eWOM ,641 ,090 7,145 ***
eWOM3 <--- eWOM ,780 ,092 8,458 ***
eWOM2 <--- eWOM ,801 ,093 8,603 ***
eWOM1 <--- eWOM ,646 ,106 6,076 ***
BA1 <--- Brand_Attitude 1,000
BA2 <--- Brand_Attitude ,920 ,086 10,660 ***
BA3 <--- Brand_Attitude ,895 ,093 9,582 ***
BA4 <--- Brand_Attitude ,923 ,103 9,007 ***
BA5 <--- Brand_Attitude ,780 ,097 8,050 ***
PI4 <--- Purchase_Intention 1,000
PI3 <--- Purchase_Intention 1,073 ,125 8,563 ***
PI2 <--- Purchase_Intention 1,068 ,134 7,980 ***
PI1 <--- Purchase_Intention ,988 ,115 8,590 ***
Standardized Regression Weights: (Group number 1 - Default model)
Estimate
Brand_Attitude <--- eWOM ,777
Purchase_Intention <--- Brand_Attitude -,084 Purchase_Intention <--- eWOM ,907
eWOM6 <--- eWOM ,798
eWOM5 <--- eWOM ,817
eWOM4 <--- eWOM ,654
eWOM3 <--- eWOM ,750
eWOM2 <--- eWOM ,760
eWOM1 <--- eWOM ,569
BA1 <--- Brand_Attitude ,822
BA2 <--- Brand_Attitude ,867
BA3 <--- Brand_Attitude ,803
Estimate
BA4 <--- Brand_Attitude ,768
BA5 <--- Brand_Attitude ,705
PI4 <--- Purchase_Intention ,777 PI3 <--- Purchase_Intention ,797 PI2 <--- Purchase_Intention ,749 PI1 <--- Purchase_Intention ,800
Variances: (Group number 1 - Default model)
Estimate S.E. C.R. P Label eWOM ,562 ,115 4,882 ***
e16 ,199 ,047 4,225 ***
e17 ,133 ,040 3,296 ***
e1 ,321 ,052 6,138 ***
e2 ,234 ,039 5,955 ***
e3 ,309 ,045 6,858 ***
e4 ,266 ,041 6,473 ***
e5 ,263 ,041 6,413 ***
e6 ,490 ,069 7,047 ***
e7 ,241 ,041 5,874 ***
e8 ,141 ,027 5,201 ***
e9 ,222 ,037 6,077 ***
e10 ,299 ,047 6,354 ***
e11 ,308 ,046 6,676 ***
e12 ,300 ,051 5,940 ***
e13 ,302 ,053 5,730 ***
e14 ,408 ,066 6,178 ***
e15 ,252 ,044 5,703 ***