以聯合分析法探討品牌鮮奶網路訂購之重要屬性

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(1)An Exploration with Conjoint Analysis for Brand Milk on Internet Purchasing. 100. 6.

(2) An Eploration with Conjoint Analysis for Brand Milk on Internet Purchasing. Advisor By. Dr. Jeun-Sheng Lin. Chien-Han Hsu. A Thesis Submitted to the Graduate Program of Marketing and Logistics Management In Partial Fulfillment of the Requirements For the Degree of Master of Business Administration National Pingtung Institute of Commerce. Pingtung, Taiwan, R.O.C. June, 2011.

(3) 8 975ml $65 975ml. $72. I.

(4) Abstract Web-based virtual market became one of the fastest growing market, and the growth exceeded traditional retailing. Sales of domestically produced fresh milk rely predominantly on the real channel, and only very few producers try to use the virtual channel to increase the sales volume. To know that whether the consumers are willing to accept this new channel, and what are the characteristics that the consumers are looking for when purchasing over the Internet are important questions for the stakeholders. This research conducts the conjoint analysis in measuring the consumers’ attribute preference and also compares the influence of these contributes on consumers’ relatively important. The experiment design used in survey including four attributes. The attributes are perceived risk, price, produced freshness, and reputation. By using orthogonal design, eight cards were generated. The respondents were asked to give a scare of one to nine on each card. Then the relative importance of characteristics can be calculated. The results showed that the combination for milk produced by Lu Ying Ranch, day of production and distribution the same day, low temperature delivery, and price per bottle NT$65 is the most preference for respondents’ preference. The other combination for milk produced by Lu Ying Ranch, day of production and distribution the next day, and price per bottle NT$72 is the least preference. To analysis the preference for each attribute, the orders are produced freshness, reputation, perceived risk, and price. Therefore, price is no longer the first consideration of buying milk, managers should pay attention to make sure the milk’s produced freshness (for instance, day of production and distribution the same day) and promote the brand to the public.. Keywords: Internet marketing, Attribute preference, Conjoint analysis , Reputation. II.

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(12) 1997. 2007. 69.5% 2000. 2010. 2000. 2003. 2002 24.97. 2000. WTO. 2003. 1. 21.85. 2005.

(13) 2007. 619. 2010. 1994. DIY 2007. 2008 Yahoo. 2010 2010 162 72.56%. 02. 12 2009. 1,466 1.61%. 1,359 2.

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(16) 2000. DIY. HACCP. ISO 20000. 40. ( ). 5.

(17) 1. 2. 3. 4.. 6.

(18) 1963. 180c.c.. 1960. 3 1964-1984 1970. 1972. 6-8. 180c.c. ( 2009) 7.

(19) Dairy Herd Improvement,. DHI. 1977. 139 3,500. 650 7,000. 1980. 300. 20 2005. Jersey. 10. 2006. 8. 2.

(20) 30. 2008 1985. 5. 1,071. 2004. 1994. 873 38. 2008. 2 2005 9 108. 2. 917. 8,425 2005. 9. 13.

(21) 2002. 2003. (TNS) 2007 2008 3 2008 3. 2007. 100. 32. 26.5% 2007. 3 (. 饋008). 10. 8.

(22) 1988. 2. 10 12. 1999. 1997. 6. 7. 。. 11. 2007.

(23) (. ). (. ). (. ). (. ). 50 100 90 85. (. ). (. ). 1993 8. 2. 1995. 12.

(24) 5. 2008. 1986. 15. 85. 80. 20. 2-1 10. 1986. 1995. 25. 30 10. 80 2008 2-1 1986. 1986 1987. 2006. 1988. 1989. 1990. 1991. 1992. 109,723 144,390 173,407 182,421 203,830 225,656 246,281 1993. 1994. 1995. 1996. 1997. 1998. 1999. 278,476 289,574 317,806 315,927 330,469 338,369 338,005 2000. 2001. 2002. 2003. 2004. 2005. 2006. 358,049 345,970 357,804 354,421 322,660 303,496 323,165 2008. 13.

(25) Perceptions Preferences. Stimulus. Attributes. Multiattribute Purchase Decision. 1989. 1999. 14.

(26) 1964. Luce. 1971. Tukey Green. Green Derita 1974. Interaction Effect Goldhor. Rao. Wind Grahold. 1978. Pekelman Sen. Moore. 1979. 1980. Green. Carral. Goldberg 1981. Product Optimization and Selected Segment Evaluation POSSE. Cattin Gelfand. Danes 1983. Simple Bayesian Regression Procedure. Green 1984. Hybrid Model. Hagerty 1985. Q-TYPE. Johnson 1987. Adaptive Conjoint Analysis,. ACA 15.

(27) Kamakura 1989. Allenby Arora. LINMAP. Ginter 1995. Vriens Wedel. Wilms 1996. R2 RMSE. LCN Latent Class Normal Distribution Model. FCR Fuzzy Clusterwise Regression. 2-2. Green 1974. Derita. interaction effect. Wind Grahold Goldhor 1978. Pekelman 1979. Sen. Moore 1980. Green Carral Goldberg 1981. 16.

(28) Cattin Gelfand Danes 1983. Simple Bayesian Regression Procedure. Green 1984 HybridModel Q-TYPE. Hagerty 1985. Johnson 1987. Adaptive Conjoint Analysis, ACA. Kamakura 1989. Allenby Arora Ginter 1995. LINMAP LCN Latent Class Normal Distribution Model FCR Fuzzy Clusterwise Regression. Vriens Wedel Wilms 1996. 1993. Green 1989. 17. Allenby 1995. R2 RMSE. Vriens 1996.

(29) Green Approach. 1984. Self-explicited. Hybrid Conjoint Analysis Adaptive Conjoint Analysis. 18.

(30) Hawkins Best & Coney, 1983. Zeithaml. 1988. Perceived Price Perceived Price. Kashyap & Bojanic, 2000 Olson. Jacoby. Zeithaml 1988. 1972. Objective Price Perceived Nonmonetary Price Monroe. Krishnan 1985. 2-1. 19.

(31) +. +. +. -. 2-1 Monroe. Jacoby. Krishnan. 1985. Olson 1972. 1.. 2.. Lichtenstein Ridgway. 1.. 2.. Netemeyer 1993. Price-quality Schema. Prestige Sentivity. 20.

(32) 1.. Price Consciousness. 2.. Coupon Proneness. 3.. Sale Proneness. 4.. Price Mavenism. 2-3. Woodside 1974. Shimp Hirschman. Monroe. Zeithaml. Beardn 1982 Holbrook 1982. Krishnan 1985. 1988. 21.

(33) Alba 1994. Niedrich 2001 2002 2003 2005. 2009. 22.

(34) America Marketing Association, Name Sign. Term. AMA Symbol. Design. Retail Business Economist Intelligence Unit,1968. 1998. Ghosh 1990. 1. Manufacture Brands. National Brand /. 2. Private Brands 3. No-Name Brand. Hoch, 1996. 23. Generics.

(35) Brand-related Experiences Keller 1993. Alba & Hutchinson, 1987 Brand Knowledge Brand Recall. Brand Recognition. Keller, 1993. Keller 1993 1 2 3. Roa. Monroe 1989 Gardner. Mazursky & Jacoby, 1985. 24. Hoyer. 1971. Brown 1990.

(36) Bauer. 1960 Cox. 1967. Bauer. 2006. 2006. 2007 2009. Jacoby. （1）. Kaplan 1972 （2）. Financial Risk. （3）. Risk. Performance Physical Risk （4）. Psychological Risk （5）. Social Risk. 1972;. 2000. 1972. 25. Jacoby. Kaplan,. Jacoby. Kaplan.

(37) 11. 11 11. 5. 23. 1. 2 5. 4. 26.

(38) Green. Srinivasan. 1.. 1978 2.. 4.. 3.. 5.. 6. 3-1. 3-1 (1) (2) (3) (4) (1) (2) (1) (2) (3) (1) (2) (3) (1) (2) (3) (4) (5) (1) (2) (3) (4) (5) (6). 1.. 2. 3.. 4.. 5.. 6.. Green. Srinivasan. 1978. 27. MONANOVA LINPAC LINMAP PROBIT PREFMAP LOGIT.

(39) Multiattribute Decision. Green. Wind. 1973. Noncompensatory Model. Compensatory. Model Green & Wind, 1973 Models. Ideal-point Models. Vector Part-worth. utility Models. Two-factor-at-a time Procedure Full-profile Approach Full-profile Approach. 1. Fractional Factorial Design Balance Incomplete Block Design Partially Balance Incomplete Block Design 28. 2 3.

(40) Fractional Factorial Design. 1 2. 3. Ratio Scales. Interval Scales. Rank Order Scales Scales. Nominal. Paired Comparison Scales. Rank Order Scales 1. 29. 2. 9.

(41) 1 2. Kruskal Chang. 3. Carmane. 1978. PREFMAP 1995 Srinivasan. Shock. MONANOVA Johnson 1993. 1973. MONANOVA. LINMAP PREFMAP. LINMAP. 30. Carroll.

(42) (. ). 1 $65. (. ). (. ) 1 Performance Risk Psychological Risk. $72. Financial Risk 3. 2. Physical Risk 5. 31. Social Risk. 4.

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(44) 1 9. 16. Systematic or Quasi-random Sampling. 33.

(45) Hair, Anderson, Tatham 10. 15. Black 1998 Steckel, DeSarbo. Mahajan, 1991 1 Reutterer. Kotzab. 2000. the use of conjoint-analysis for measuring preferences in supply chain design. 12. 3. 4 1. 12 4. × 4 36. 41 4. 2 4x2 4 1 x 4. 2011. 2011 4. 3. 20. 20. 25. 5. 160 157. 34. 3.

(46) 4-1. 157. 52.9%. 47.1%. 21-30. 31-40. 65.6%. 14.0% 77.7%. 10.2%. 12.1%. 45.7% 20.4%. 18.5%. 4. 5 48.4%. 45.2% 25.5%. 2. 40.1%. 0. 3. 17.8%. 10,000 45.9%. 20,001-30,000. 22.9%. 35.

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(53) 1. 4-2. 4-2. 42.

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(61) 1. 4-12. 4-12. 50.

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(63) 4-13. 4-14. 4-15. 4-16. 52.

(64) 1. 4-17. /. 4-17. /. /. 53.

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(66) /. 4-18. 4-19. 4-20. 4-21. /. 55.

(67) 1.. 4-22. 1 2. 3. 4 5. 4-22. 1. 4. 2. 3. 5. 2. 5. 3 1. 4 56.

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(69) 1. 2 3. 5 ( ). -.0313 -.4167 -.9730 -.0490 -.5227 Total %. 100. 5.7187 5.3333 5.9500 5.7108 5.878. 4-23. 4-24. 4-25. 4-26. 58.

(70) 1.. 4-27. 0 1. 2. 3 4. 5. 59.

(71) 4-27. 0. 2. 1. 3. 5. 4. 2. 4. 60.

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(73) 0 1. 3 2. 5. (. ). 4-28. 4-29. 4-30. 4-31. 62. 4.

(74) 1.. 4-32. 10,000. 10,001-20,000. 20,001-30,000. 30,001 -40,000. 40,001 -50,000. 50,001. 4-32 63.

(75) 10,000 40,001 -50,000. 20,001-30,000. 50,001 10,001-20,000. 30,001 -40,000. 2. 4-16. 4-33. 4-17. 4-36 4-16 % 10,000. 50,001. 10,001-. 20,001-. 30,001. 40,001. 20,000. 30,000. -40,000. -50,000. 17.77. 饋4.饋饋. 27.81. 27.42. 20.65. 25.05. 23.36. 21.93. 11.67. 19.69. 23.99. 22.37. 31.6. 23.91. 35.46. 22.45. 34.98. 31.7. 27.27. 29.95. 25.06. 30.44. 20.38. 20.08. Total %. 100. 64.

(76) 4-17. 10,000 10,001-. 30,001. 40,001. -40,000. -50,000. 50,001. 20,001-. 20,000. 30,000. -0.2581. -0.2798. -0.3792. -0.5909. -0.1875. -0.4375. 0.2581. 0.2798. 0.3792. 0.5909. 0.1875. 0.4375. $72. -0.2419. -0.3036. -0.1125. -0.2955. -0.4375. 0.0625. $65. 0.2419. 0.3036. 0.1125. 0.2955. 0.4375. -0.0625. -0.5403. -0.4226. -0.7375. -0.3864. -0.5208. -0.0625. 0.5403. 0.4226. 0.7375. 0.3864. 0.5208. 0.0625. 0.3024. 0.1726. 0.3125. 0.2955. 0.4375. 0.5000. -0.3024. -0.1726. -0.3125. -0.2955. -0.4375. -0.5000. 5.9395. 5.2321. 5.5458. 5.8636. 6.7292. 7.0625. 4-13. 50,001. 50,001 2.5%. 65. ( ). ( ).

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(83) (2005). 2005 16-21. (2008) 3. 80 89-92. (1989) (1998) (2010). (2010) 2. 11 185-199. (1993). 245-260 (2007) -. e-Business (2011). 9. Yahoo!. 2 MIT. (2000) 95. 72. Journal of.

(84) (2010). (2006). (2009) 28. 1. 87-103 (2000). (1999) 599 (2010). -. (2006). (2009). (2006). 73.

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