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2010 8 月第十三卷三期 • Vol. 13, No. 3, August 2010 服飾網路代購服務之市場區隔與消費者行 為研究 呂佳茹 廖家鴻 http://cmr.ba.ouhk.edu.hk

服飾網路代購服務之市場區隔與消費者行 為研究cmr.ba.ouhk.edu.hk/cmr/webjournal/v13n3/CMR247C09.pdf · 買決策因素及人口統計變數上是有顯著性差異。並分析

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  • 2010 8 Vol. 13, No. 3, August 2010

    http://cmr.ba.ouhk.edu.hk

  • 1

    1

    2

    _____________________________________

  • 2

    2007 1 15 1,523

    0-100 66.91% 47 1.84%

    (surrogate shoppers)

    2008 1 Google

    618

    96 10 430 9.39%

    1.45%

    Plummer (1974)

    (1)

    (2)

    (3)

  • 3

    (4)

    (2006)

    Hollander & Rassuli (1999)

    2006

    2008 1 Google

    618

    ebay

    1

    1

    iGo

    ebay

    BBS

    kijiji

    Wii

    CD

    2

  • 4

    2

    CD

    :

    :

    :

    1000

    10% 100

    1000

    100 1000 5000 200

    3

    3

  • 5

    Wendell R. Smith 1956 (market segmentation)

    Kotler

    & Keller (2005) (heterogeneous)

    Plummer (1974)

    Wind (1978)

    Plummer (1974)

    2000

    (Activity) (Interest) (Opinion) AIO (Activities,

    Interest, Opinion) Plummer (1974) AIO

    Williams (1982)

    Engel et al.

  • 6

    (1995)

    Kotler & Keller (2005)

    Engel et al.1995

    1

    2

    3

    Plummer1974 AIO 2004

    0.6

    Likert Scale 20

  • 7

    Engel et al. (1995)

    EKB

    1999

    0.6

    Likert Scale 20

    2004

    4

    6

    2008 3 10 3 23

    30 1

    0.5 Cronbachs 0.6

    15

    15 4

    6 2008 3 31

    2008 4 27

    203

    178 87.6%

    56.7% 19~30

    88.2%

    62.4% 10000 (38.8%)

    20001~30000 (18.5%)~

  • 8

    37.6%

    30.3% 4

    4

    77

    101

    43.3%

    56.7%

    18 19~22 23~26 27~30

    31~35 36~40 41~45 46~50 50

    6

    59

    55

    43

    8

    3

    3

    0

    1

    3.4%

    33.1%

    30.9%

    24.2%

    4.5%

    4.7%

    4.7%

    0%

    0.6%

    67

    11

    16

    21

    0

    6

    10

    12

    35

    37.6%

    6.2%

    9.0%

    11.8%

    0%

    3.4%

    5.6%

    6.7%

    19.7%

    30

    111

    34

    2

    1

    16.9%

    62.4%

    19.1%

    1.1%

    0.6%

    10000 10001~20000 20001~30000 30001~40000

    40001~50000 50001~60000 60001~70000 70001~80000 80001

    69

    30

    33

    27

    10

    4

    2

    2

    1

    38.8%

    16.9%

    18.5%

    15.2%

    5.6%

    2.2%

    1.1%

    1.1%

    0.6%

    67

    54

    46

    9

    2

    37.6%

    30.3%

    25.8%

    5.1%

    1.1%

  • 9

    :

    (1)

    0~1 6

    3.4%2~3 47 26.4%4~5 42 23.6%6~7

    25 14%8~9 13 7.3%10~11 10 5.6%

    12 35 19.7%

    2~3 4~5

    (2)

    499

    5 2.8%500~1000 28 15.7%1001~2000

    76 42.7%2001~3000 32 18%3001~4000

    19 10.7%4001~5000 5 2.8%5001 13

    7.3% 1001~2000 42.7%

    2001~3000

    (3) ?

    51

    28.7% 42 23.6% 85 47.8%

    (4)

    4

    2.2% 146 82% 20 11.2%

    BBS 7 3.9% 0 0% 1

    0.6%

    Cronbachs

    0.8216 0.6534 Malhotra

    2007 Cronbach 0.6

  • 10

    0.6

    15 KMO (Kaiser-Meyer-Olkin)

    0.739Bartlett 988.019 (p=0.000)

    =105 Kaiser (1974)

    1 0.5

    62.411%Cronbachs

    0.7

    Cronbachs 5

    5

    12.

    03.

    09.

    07.

    .762

    .707

    .678

    .556

    11.

    10.

    05.

    08.

    .819

    .797

    .650

    .641

    06.

    15.

    04.

    .740

    .671

    .633

  • 11

    14.

    .602

    01.

    13.

    02.

    .863

    .755

    .716

    2.635 2.409 2.274 2.044

    17.565 33.622 48.785 62.411

    Cronbachs 0.7009 0.7848 0.7099 0.7124

    K-means

    1 68 2 50

    3 60

    1 92.6% 2 96.0% 3 90.0%

    92.7% 6

    (Scheffe)

    7

  • 12

    6 N=178

    1 2 3

    1 63 5 0 6838.2% 92.6%

    2 0 48 2 5028.1% 96.0%

    3 6 0 54 6033.7% 90.0%

    :=92.7%

    7

    1

    N=68

    2

    N=50

    3

    N=60

    F P Scheffe

    0.7196 0.2988 1.0138 76.106 0.000*** 3>1>2

    0.9966 0.1475 1.1142 93.723 0.000*** 3>1>2

    0.2316 0.8142 1.0458 87.557 0.000*** 3>1>2

    0.2888 0.8033 0.5144 49.450 0.000*** 3>2>1

    :***p

  • 13

    8

    14.

    13.

    04.

    09.

    01.

    .918

    .893

    .839

    .838

    .673

    10.

    12.

    11.

    15.

    .834

    .820

    .807

    .722

    03.

    08.

    02.

    .889

    .845

    .841

    05.

    06.

    07.

    .877

    .834

    .766

    2.961 2.232 2.174 2.133

    24.480 43.244 59.567 74.291

    Cronbachs 0.9048 0.8563 0.85411 0.7960

  • 14

    9

    3.01 3.03

    3.81

    3.52 4.13

    3.47 3.44

    1

    9

    1

    N=68

    2

    N=50

    3

    N=60

    F P

    3.11 2.66 3.52 21.830 0.000**

    3.56 2.90 4.13 40.774 0.000**

    3.01 3.81 3.47 20.311 0.000**

    3.03 3.28 3.44 4.390 0.014**

    :***p

  • 15

    3

    10

    1

    N=68

    2

    N=50

    3

    N=60

    2 P

    40

    28

    19

    31

    18

    42

    11.572 0.003***

    18

    19~22

    23~26

    27~30

    31~35

    36~40

    41~45

    46~50

    50

    1

    17

    26

    18

    3

    1

    1

    0

    1

    4

    8

    10

    20

    4

    2

    2

    0

    0

    1

    34

    19

    5

    1

    0

    0

    0

    0

    44.209 0.000***

    14

    6

    8

    10

    0

    3

    6

    3

    18

    14

    4

    7

    8

    0

    3

    2

    4

    8

    39

    1

    1

    3

    0

    0

    2

    5

    9

    39.377 0.000***

    21

    26

    20

    0

    1

    7

    31

    10

    2

    0

    2

    54

    4

    0

    0

    43.788 0.000***

    10000

    10001~20000

    20001~30000

    30001~40000

    40001~50000

    50001~60000

    60001~70000

    19

    12

    16

    14

    3

    1

    2

    20

    10

    8

    8

    3

    0

    0

    30

    8

    9

    5

    4

    3

    0

    19.396 0.249

  • 16

    70001~80000

    80001

    1

    0

    1

    0

    0

    1

    25

    24

    15

    3

    1

    15

    14

    16

    5

    0

    27

    16

    15

    1

    1

    8.315 0.403

    :***p

  • 17

    38.2%28.1%

    33.7%

    23~26

    27~30

    19~22 ()

  • 18

    Kotler & Keller2005

    Plummer1974

    (Engel et al., 1995)

    Engel

    (1)

  • 19

    (2)

    37.6%

    10000

    (3)

    1001~2000

    2~3

    (4)

  • 20

    (1)

    (2)

    (3)

    (4)

    (2006)

    11 6970

    (1999)

    (2000)2000

    (2004)

    2 1 89121

    Engel, J. F., Blackwell, R. D., & Kollat, D. T. (1995). Consumer Behavior (8th

    ed.).Chicago: Dryden Press.

  • 21

    Hollander, S. C., & Rassuli, K. M. (1999). Shopping with Other Peoples Money:

    The Marketing Management Implications of Surrogate-Mediated Consumer

    Decision Making. Journal of Marketing, 63(2), 102118.

    Kotler, P., & Keller, K. L. (2005). Marketing Management. NJ: Prentice-Hall.

    Kaiser, H. F. (1974). An Index of Factorial Simplicity. Psychometrika, 39(1),

    3136.

    Malhotra, N. K. (2007). Marketing Research: An Applied Orientation. Upper

    Saddle River, NJ: Pearson Prentice Hall.

    Plummer, J. T. (1974). The Concept and Application of Life Style Segmentation.

    Journal of Marketing, 38(1), 3338.

    Smith, W. R. (1956). Product Differentiation and Market Segmentation as

    Alternative Marketing Strategies. Journal of Marketing, 21(1), 38.

    Williams, T. G. (1982). Consumer Behavior: Fundamental and Strategies. St. Paul,

    Minn.: West Publishing Co.

    Wind, Y. (1978). Issues and Advances in Segmentation Research. Journal of

    Marketing Research, 15(3), 317337.