APPENDIX. Notes. Output Created 14-Jul :08:00 Comments Input Active Dataset DataSet0. N of Rows in Working Data

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xvii

APPENDIX

Brand Image

Factor Analysis

Notes

Output Created 14-Jul-2011 19:08:00

Comments

Input Active Dataset DataSet0 Filter <none> Weight <none> Split File <none> N of Rows in Working Data

File

100 Missing Value Handling Definition of Missing MISSING=EXCLUDE: User-defined

missing values are treated as missing. Cases Used LISTWISE: Statistics are based on

cases with no missing values for any variable used.

Syntax FACTOR

/VARIABLES BI28 BI29 /MISSING LISTWISE /ANALYSIS BI28 BI29

/PRINT INITIAL CORRELATION SIG DET KMO INV REPR AIC

EXTRACTION /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /ROTATION NOROTATE /SAVE REG(ALL) /METHOD=CORRELATION.

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Resources Processor Time 00 00:00:00.156

Elapsed Time 00 00:00:00.218

Maximum Memory Required 1192 (1.164K) bytes Variables Created FAC1_4 Component score 1

[DataSet0]

Correlation Matrixa

BI28 BI29 Correlation BI28 1.000 .380

BI29 .380 1.000 Sig. (1-tailed) BI28 .000

BI29 .000 a. Determinant = .856

Inverse of Correlation Matrix

BI28 BI29 BI28 1.169 -.444 BI29 -.444 1.169

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .500 Bartlett's Test of Sphericity Approx. Chi-Square 15.208

df 1

Sig. .000

Anti-image Matrices

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xix

Anti-image Covariance BI28 .856 -.325 BI29 -.325 .856 Anti-image Correlation BI28 .500a -.380 BI29 -.380 .500a a. Measures of Sampling Adequacy(MSA)

Communalities

Initial Extraction BI28 1.000 .690 BI29 1.000 .690 Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative %

1 1.380 69.002 69.002 1.380 69.002 69.002

2 .620 30.998 100.000

Extraction Method: Principal Component Analysis.

Component Matrixa Component 1 BI28 .831 BI29 .831 Extraction Method: Principal Component Analysis. a. 1 components extracted.

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xx

Reproduced Correlations

BI28 BI29 Reproduced Correlation BI28 .690a .690

BI29 .690 .690a

Residualb BI28 -.310

BI29 -.310 Extraction Method: Principal Component Analysis. a. Reproduced communalities

b. Residuals are computed between observed and reproduced correlations. There are 1 (100.0%) nonredundant residuals with absolute values greater than 0.05.

Karakteristik Produk

Factor Analysis

Notes

Comments

File

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xxi

Syntax FACTOR

/VARIABLES KP17 KP18 /MISSING LISTWISE /ANALYSIS KP17 KP18

Elapsed Time 00 00:00:00.406

[DataSet0]

Correlation Matrixa KP17 KP18 Correlation KP17 1.000 .263 KP18 .263 1.000 Sig. (1-tailed) KP17 .004 KP18 .004 a. Determinant = .931

KP17 KP18 KP17 1.074 -.282 KP18 -.282 1.074

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df 1 Sig. .008 Anti-image Matrices KP17 KP18 Anti-image Covariance KP17 .931 -.244 KP18 -.244 .931 Anti-image Correlation KP17 .500a -.263 KP18 -.263 .500a a. Measures of Sampling Adequacy(MSA)

Communalities

Initial Extraction KP17 1.000 .631 KP18 1.000 .631 Extraction Method: Principal Component Analysis.

Component

1 1.263 63.127 63.127 1.263 63.127 63.127

2 .737 36.873 100.000

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Component Matrixa Component 1 KP17 .795 KP18 .795 Extraction Method: Principal Component Analysis. a. 1 components extracted. Reproduced Correlations KP17 KP18 Reproduced Correlation KP17 .631a .631 KP18 .631 .631a Residualb KP17 -.369 KP18 -.369 Extraction Method: Principal Component Analysis. a. Reproduced communalities

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xxiv

Life Style

Factor Analysis

Notes

Comments

File

Syntax FACTOR

/VARIABLES LF22 LF23 LF25 /MISSING LISTWISE

/ANALYSIS LF22 LF23 LF25 /PRINT INITIAL CORRELATION SIG DET KMO INV REPR AIC

Elapsed Time 00 00:00:00.484

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[DataSet0]

Correlation Matrixa LF22 LF23 LF25 Correlation LF22 1.000 .539 .363 LF23 .539 1.000 .444 LF25 .363 .444 1.000 Sig. (1-tailed) LF22 .000 .000 LF23 .000 .000 LF25 .000 .000 a. Determinant = .555

LF22 LF23 LF25 LF22 1.448 -.682 -.223 LF23 -.682 1.566 -.447 LF25 -.223 -.447 1.279

df 3

Sig. .000

LF22 LF23 LF25 Anti-image Covariance LF22 .691 -.301 -.120

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LF23 -.301 .639 -.223 LF25 -.120 -.223 .782 Anti-image Correlation LF22 .646a -.453 -.164 LF23 -.453 .615a -.316 LF25 -.164 -.316 .721a a. Measures of Sampling Adequacy(MSA)

Communalities

Initial Extraction LF22 1.000 .643 LF23 1.000 .712 LF25 1.000 .545 Extraction Method: Principal Component Analysis.

Component

1 1.901 63.355 63.355 1.901 63.355 63.355

2 .651 21.706 85.061

3 .448 14.939 100.000

Component Matrixa Component 1 LF22 .802 LF23 .844 LF25 .738

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Extraction Method: Principal Component Analysis. a. 1 components extracted. Reproduced Correlations LF22 LF23 LF25 Reproduced Correlation LF22 .643a .677 .592 LF23 .677 .712a .623 LF25 .592 .623 .545a Residualb LF22 -.138 -.230 LF23 -.138 -.179 LF25 -.230 -.179 Extraction Method: Principal Component Analysis.

a. Reproduced communalities

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xxviii

Price

Factor Analysis

Notes

Comments

File

Syntax FACTOR

/VARIABLES P11 P14 P15 /MISSING LISTWISE /ANALYSIS P11 P14 P15

Elapsed Time 00 00:00:03.791

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xxix

[DataSet0]

Correlation Matrixa P11 P14 P15 Correlation P11 1.000 .507 .532 P14 .507 1.000 .576 P15 .532 .576 1.000 Sig. (1-tailed) P11 .000 .000 P14 .000 .000 P15 .000 .000 a. Determinant = .439

P11 P14 P15 P11 1.523 -.457 -.547 P14 -.457 1.633 -.697 P15 -.547 -.697 1.692

df 3

Sig. .000

P11 P14 P15 Anti-image Covariance P11 .657 -.184 -.212

(14)

xxx

P14 -.184 .612 -.252 P15 -.212 -.252 .591 Anti-image Correlation P11 .730a -.290 -.341 P14 -.290 .694a -.419 P15 -.341 -.419 .678a a. Measures of Sampling Adequacy(MSA)

Communalities

Initial Extraction P11 1.000 .660 P14 1.000 .698 P15 1.000 .719 Extraction Method: Principal Component Analysis.

Component

1 2.077 69.234 69.234 2.077 69.234 69.234

2 .502 16.717 85.951

3 .421 14.049 100.000

Component Matrixa Component 1 P11 .812 P14 .836 P15 .848

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xxxi

Extraction Method: Principal Component Analysis. a. 1 components extracted. Reproduced Correlations P11 P14 P15 Reproduced Correlation P11 .660a .679 .689 P14 .679 .698a .709 P15 .689 .709 .719a Residualb P11 -.172 -.157 P14 -.172 -.133 P15 -.157 -.133 Extraction Method: Principal Component Analysis.

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xxxii

Motivation

Factor Analysis

Notes

Comments

File

Syntax FACTOR

/VARIABLES M31 M32 M33 M34 /MISSING LISTWISE

/ANALYSIS M31 M32 M33 M34 /PRINT INITIAL CORRELATION SIG DET KMO INV REPR AIC

Elapsed Time 00 00:00:00.390

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[DataSet0]

Correlation Matrixa M31 M32 M33 M34 Correlation M31 1.000 .393 .435 .402 M32 .393 1.000 .421 .504 M33 .435 .421 1.000 .569 M34 .402 .504 .569 1.000 Sig. (1-tailed) M31 .000 .000 .000 M32 .000 .000 .000 M33 .000 .000 .000 M34 .000 .000 .000 a. Determinant = .362

M31 M32 M33 M34

M31 1.344 -.278 -.355 -.199 M32 -.278 1.448 -.203 -.502 M33 -.355 -.203 1.627 -.680 M34 -.199 -.502 -.680 1.720

df 6

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xxxiv

Anti-image Matrices M31 M32 M33 M34 Anti-image Covariance M31 .744 -.143 -.162 -.086 M32 -.143 .691 -.086 -.202 M33 -.162 -.086 .615 -.243 M34 -.086 -.202 -.243 .581 Anti-image Correlation M31 .815a -.200 -.240 -.131 M32 -.200 .787a -.132 -.318 M33 -.240 -.132 .742a -.407 M34 -.131 -.318 -.407 .723a a. Measures of Sampling Adequacy(MSA)

Communalities Initial Extraction M31 1.000 .503 M32 1.000 .563 M33 1.000 .635 M34 1.000 .667 Extraction Method: Principal Component Analysis.

Component

1 2.367 59.185 59.185 2.367 59.185 59.185

2 .637 15.928 75.113

3 .585 14.633 89.746

4 .410 10.254 100.000

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xxxv

Component 1 M31 .709 M32 .750 M33 .797 M34 .817 Extraction Method: Principal Component Analysis. a. 1 components extracted. Reproduced Correlations M31 M32 M33 M34 Reproduced Correlation M31 .503a .532 .565 .579 M32 .532 .563a .598 .613 M33 .565 .598 .635a .650 M34 .579 .613 .650 .667a Residualb M31 -.139 -.130 -.177 M32 -.139 -.176 -.109 M33 -.130 -.176 -.082 M34 -.177 -.109 -.082 Extraction Method: Principal Component Analysis.

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xxxvii

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xxxix

KUESIONER MOTIVASI KONSUMEN DALAM MEMBELI

PAKAIAN DI MANGO

No

:

Nama

: (optional,

tidak

harus

diisi)

Telepon : (optional,

tidak

harus

diisi)

KUESIONER

Kuesioner ini digunakan untuk keperluan penelitian dalam rangka menyusun

Tesis dengan judul “Pengaruh Persepsi Harga, Karakteristik Produk, Gaya

Hidup, dan Citra Merk”. Untuk itu mohon kiranya saudara-I dapat membantu

penulis dalam menjawab kuisioner ini dengan sejujur-jujurnya. Hal ini demi

keobjektivitasan penelitian yang sedang penulis lakukan. Atas bantuan dan

kesediaanya penulis ucapkan banyak terima kasih.

Petunjuk pengisian :

Berilah jawaban pertanyaan berikut sesuai dengan pendapat anda, dengan cara

memberikan tanda (√) pada kolom yang tersedia.

1. Bacalah terlebih dahulu dan jawablah semua pertanyaan dengan benar.

2. Berilah tanda (√) pada kolom jawaban anda.

(24)

xl

Apakah anda pernah menggunakan pakaian merk Mango (Jika Ya, isilah

pertanyaan dibawah ini)

Ya

Tidak

1. KARAKTERISTIK RESPONDEN

a. Jenis Kelamin :

Pria

Wanita

b. Usia anda saat ini :

< 20 tahun 35- 50 tahun

21-35 tahun >50 tahun

c. Pendidikan terakhir anda :

SMA S1 S2

d. Pekerjaan anda :

Mahasiswa/ Pelajar Ibu rumah tangga

Wirausaha Pegawai negeri / swasta

Lainnya, Sebutkan : ……….

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xli

e. Pengeluaran per bulan anda :

< Rp. 2.000.0000 Rp. 5.000.000 –Rp. 10.000.000

Rp. 2.000.000 – Rp. 5.000.000 > Rp. 10.000.000

f. Frekuensi anda melakukan pembelanjan per bulan :

1 – 2 kali 3 – 5 kali > 6 kali

g. Berikan tanda (√) pada merk pakaian yang Anda sering gunakan:

Mango Zara GAP

Top Shop Giordano Muji

Lainnya, Sebutkan ………..

h. Bagaimana Anda pertama kali mengetahui produk Mango? (Pilih satu ):

Teman Website Koran / Majalah

Brosur Banner

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xlii

2. KUESIONER

Anda sebagai pelanggan “ MANGO” diharapkan menjawab pertanyaan dibawah ini

sesuai dengan tingkat kesetujuan anda dan berilah tanda silang (X) pada kolom

jawaban yang telah disediakan.

Keterangan :

Kategori Bobot

Nilai

STS = Sangat Tidak Setuju

1 TS = Tidak Setuju

2 S = Setuju

3 SS = Sangat Setuju

4 No Harga

(Price)

ST

S

TS S SS

1 Harga pakaian ini sudah memuaskan bila dibandingkan

dengan merk sejenis

2 Harga pakaian mahal

3 Harga sesuai dengan kualitasnya produknya

4 Harga sesuai dengan apa yg diharapkan

5 Harga sesuai dengan manfaat yang saya peroleh

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xliii

No

GAYA HIDUP

STS

TS

S

SS

1 Saya memakai pakaian ini untuk tampil fashionable

2 Untuk memenuhi kebutuhan sosial saya

3 Merubah Penampilan

4 Saya tertarik untuk memakai pakaian ini

5 Saya memakai pakaian ini agar tidak ketinggalan zaman

No

Citra Merek ( Brand image)

STS

TS

S

SS

1 Mango adalah pakaian yang dapat digunakan untuk

No

Karakteristik Produk

STS

TS

S

SS

1 Dapat dipakai sehari‐hari

2 Bahan pakaiannya nyaman

3 Rapi pengemasannya

4 Desain menarik

5 Cara mencuci mudah

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xliv

sehari‐hari

2 Mango adalah pakaian dengan harga yang mahal

3 Mango lebih baik dibandingkan pesaingnya

4 Mango menjual pakaian yang berkualitas

5 Mango sudah mempunyai reputasi

No

Motivasi untuk membeli / Minat Beli

STS

TS

S

SS

1 Saya tertarik menggunakan pakaian ini karena

kualitasnya

2 Saya berencana membeli pakaian ini di lain waktu

3 Saya berharap dapat menggunakan pakaian merk

MANGO selalu

4 Saya akan merekomendasikan merk pakaian ini kepada

teman saya

5 Saya membutuhkan model pakaian bermerk MANGO

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xlv

WAWANCARA

No

:

Nama

:

Pekerjaan

:

Mahasiwa/ Pelajar

Pegawai Negeri / swasta

Pertanyaan :

1. Apakah Anda ingin membeli produk MANGO dilihat dari harganya ?

2. Apakah Anda melihat karakteristik produk pada saat membeli pakaian di

MANGO?

3. Apakah Anda membeli produk MANGO sebagai lifestyle ?

Jawab :

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xlvi

4. Apakah Anda ingin membeli produk MANGO dilihat dari citra merek pakaian

itu sendiri?

(31)

Regression

Notes

Comments

Input Data D:\Thesis Ve2\Final\100 Rspd.sav

Active Dataset DataSet0

Filter <none>

Weight <none>

Split File <none>

N of Rows in Working Data File 100

Missing Value Handling Definition of Missing User-defined missing values are treated as missing.

Cases Used Statistics are based on cases with no

missing values for any variable used.

(32)

Syntax REGRESSION /MISSING LISTWISE

/STATISTICS COEFF OUTS CI(95) BCOV R ANOVA COLLIN TOL CHANGE ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN

/DEPENDENT M

/METHOD=ENTER P KP LF BI.

Elapsed Time 00 00:00:00.312

Memory Required 2788 bytes

Additional Memory Required for Residual Plots

0 bytes

[DataSet0] D:\Thesis Ve2\Final\100 Rspd.sav

(33)

Variables Entered/Removedb

Model Variables Entered

Variables Removed Method 1 Brand Image, Characteristic Product, Life Style, PRICE . Enter

a. All requested variables entered. b. Dependent Variable: Motivation

Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics

R Square Change F Change df1 df2 Sig. F Change

1 .647a .419 .394 .77831650 .419 17.107 4 95 .000

a. Predictors: (Constant), Brand Image, Characteristic Product, Life Style, PRICE

(34)

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 41.451 4 10.363 17.107 .000a

Residual 57.549 95 .606

Total 99.000 99

a. Predictors: (Constant), Brand Image, Characteristic Product, Life Style, PRICE b. Dependent Variable: Motivation

Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig.

95.0% Confidence Interval for B Correlations

B Std. Error Beta Lower Bound Upper Bound Zero-order Partial

1 (Constant) 3.618E-16 .078 .000 1.000 -.155 .155

PRICE .131 .086 .131 1.529 .130 -.039 .300 .362 .155

Characteristic Product .100 .082 .100 1.222 .225 -.062 .261 .242 .124

Life Style .169 .083 .169 2.033 .045 .004 .335 .354 .204

Brand Image .484 .086 .484 5.646 .000 .314 .655 .593 .501

a. Dependent Variable: Motivation

(35)

Coefficient Correlationsa

Model Brand Image

Charateristic

Produc Life Style PRICE

1 Correlations Brand Image 1.000 -.056 -.203 -.299

Characteristic Product -.056 1.000 -.159 -.152

Life Style -.203 -.159 1.000 -.116

PRICE -.299 -.152 -.116 1.000

Covariances Brand Image .007 .000 -.001 -.002

Characteristic Product .000 .007 -.001 -.001

Life Style -.001 -.001 .007 -.001

PRICE -.002 -.001 -.001 .007

Collinearity Diagnosticsa

Model Dimension Eigenvalue Condition Index

Variance Proportions

(Constant) PRICE

Characteristic

Product Life Style Brand Image

1 1 1.733 1.000 .00 .14 .09 .12 .14 2 1.000 1.316 1.00 .00 .00 .00 .00 3 .864 1.416 .00 .07 .73 .01 .21 4 .776 1.494 .00 .25 .10 .77 .00 5 .627 1.662 .00 .53 .07 .09 .64

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Collinearity Diagnosticsa

Model Dimension Eigenvalue Condition Index

Variance Proportions

(Constant) PRICE

Characteristic

Product Life Style Brand Image

1 1 1.733 1.000 .00 .14 .09 .12 .14

2 1.000 1.316 1.00 .00 .00 .00 .00

3 .864 1.416 .00 .07 .73 .01 .21

4 .776 1.494 .00 .25 .10 .77 .00

5 .627 1.662 .00 .53 .07 .09 .64

(37)

BIOGRAPHY

Name : Felicia Andrey Kalingga

Place and Date of Birth : Jakarta and 5

th