Journal of the Korean Society of Food Culture (한국식생활문화학회지)

Korean Society of Food Culture (한국식생활문화학회)
권호 표지
DOI QR코드

DOI QR Code

Measuring Attribute Levels Influencing Tourists' Preference for Restaurants in Tourist Area and Marginal Willingness to Pay: Among Tourists in Jeonnam Area

관광객 선호도에 영향을 미치는 관광지 음식점의 속성수준 평가 및 한계지불의사액 분석: 전남지역 관광객을 대상으로

  • Published : 2007.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study was to measure the tourists' preference for alternative restaurants with different combinations of 4 attribute levels: origin description, food type, price and service guarantee. A total of 210 questionnaires were completed from tourists who visited Kwangyang, Suncheon and Yeosu during Jan. 2 - Jan. 15, 2007. Conjoint experiment method was used to develop hypothetical restaurants. Ordinal probit model was used to measure the effects of attribute levels on the tourists' preference. Results of the study demonstrated that the ordinal probit model analysis result for the data indicated excellent model fit. The effects of attribute levels (origin description, traditional food, fusion food, price, service guarantee) on the tourists' preference were statistically significant. As expected, estimates of marginal willingness to pay for origin description(3.063), food type(2.349), and service guarantee(2.356) were statistically significant. Moreover, tourists were more willing to pay for origin description than other attribute levels. Tourists also considered the origin description as the very important attribute. In conclusion, based on conjoint analysis, a model was proposed of marginal willingness to pay of attribute levels. It should be noted that the original model was modified and should, preferably, be validated in future research.

Keywords

References

  1. Ahn SS, Park KY, Yang JH. 2005. Research on Success Factor of Family Restaurant through conjoint analysis. Journal of Foodservice Management Society of Korea, 8(1):87-104
  2. Aristides M, Chen J, Schulz M, Williamson E, Clarke 5, Grant K. 2002. Conjoint analysis of a new chemotherapy: willingness to pay and preference for the features of raltitrexed versus standard therapy in advanced colorectal cancer. Pharmaco Economics, 20(1):775-784 https://doi.org/10.2165/00019053-200220110-00006
  3. Chae IS, Lee MA, Shin SY, Yang IS, Cha JA. 2002. A conjoint based approach to analyze the importance of brand choice attributes: pizza restaurant cases. Korean J Community Nutrition, 7(3):354-360
  4. Gil J, Sanchez M. 1997. Consumer preferences for wine attributes: a conjoint approach. British Food Journal, 99(1):3-11 https://doi.org/10.1108/00070709710158825
  5. Green PE, Rao VR. 1971. Conjoint measurement for quantifying judgement data. Journal of Marketing Research, 8:355-363 https://doi.org/10.2307/3149575
  6. Hoffmann R. 2000. Country of origin-a consumer perception perspective of fresh meat. British Food Journal, 102(3):211-229 https://doi.org/10.1108/00070700010332304
  7. June LP, Smith SLJ. 1987. Service attributes and situational effects on customer preferences for restaurant dining. Journal of Travel Research, 26(2):20-27 https://doi.org/10.1177/004728758702600205
  8. Kang JH. 2003. Conjoint measurement of tourist preference for foodservice in Sunchon City. Korean J. Soc. Food Cookery Sci. 19(3):308-317
  9. Kang SK, Oh SY. 2000. Consumer preferences on Shik-Hye's attributes using conjoint analysis. Korean Food Marketing Association, 17(4):207-222
  10. Kim KJ, Park KY. 2006. Research on efficient operation of university foodservice through conjoint analysis. The Korean Journal of Culinary Research, 12(4):33-45
  11. Koo LC, Tao FKC, Yeung JHC. 1999. Preferential segmentation of restaurant attributes through conjoint analysis. International Journal of Contemporary Hospitality Management, 11(5):242-250 https://doi.org/10.1108/09596119910272784
  12. Kupiec B, Revell B. 2001. Measuring consumer quality judgements. British Food Journal, 103(1):7-22 https://doi.org/10.1108/00070700110382911
  13. Lee JS, Lee DH, Lee JD, Park YR. 2004. Estimating the switching cost in the Korean residential electricity market using discrete choice model. Environmental and Resource Economics Review, 13(2):219-243
  14. Louis LA, Talaga J. 1997 Service guarantee and consumers' evaluation of services. The Journal of Service Marketing, 11(1): 10-18 https://doi.org/10.1108/08876049710158330
  15. Luce RD, Tukey JW. 1964. Simultaneous conjoint measurement. Journal of Mathematical Psychology, 1:1-27 https://doi.org/10.1016/0022-2496(64)90015-X
  16. MacKenzie J. 1992. Evaluating recreation trip attributes and travel time via conjoint analysis. Journal of Leisure Research, 24:171-184 https://doi.org/10.1080/00222216.1992.11969884
  17. Martinez LMC, Molla-Bauza MB, Gomis FJDC. 2006. Influence of purchase place and consumption frequency over quality wine preferences. Food Quality and Preference, 17:315-327 https://doi.org/10.1016/j.foodqual.2005.02.002
  18. Ness MR, Gerhardy H. 1994. Consumer preferences for quality and freshness attributes of eggs. British Food Journal, 96(3):26-34
  19. Orth UR, Krska P. 2002. Quality signals in wine marketing. International Food and Agribusiness Management Review, 4(4):385-397 https://doi.org/10.1016/S1096-7508(02)00066-6
  20. Patterson PM, Burkink TJ, Lipsey RS, Lipsey J, Roth RW, Martin MK. 2003. Targeting tourists with state branding programs. Agribusiness, 19(4):525-238 https://doi.org/10.1002/agr.10073
  21. Pol M, Ryan M. 1996. Using conjoint analysis to establish consumer preferences for fruit and vegetables. British Food Journal, 98(8):5-1
  22. Quester PG, Smart J. 1998. The influence of consumption situation and product involvement over consumers' use of product attribute. Journal of Restaurant & Foodservice Marketing, 15(3):220-238
  23. Ryan M, Hughes J. 1997. Using conjoint analysis to assess women's preferences for miscarriage management. Health Economics, 6:261-273 https://doi.org/10.1002/(SICI)1099-1050(199705)6:3<261::AID-HEC262>3.0.CO;2-N
  24. San MF, Ryan M, Mcintosh E. 2000. Applying conjoint analysis in economic evaluations: an application to menorrhagia. Applied Economics, 32:823-833 https://doi.org/10.1080/000368400322165
  25. Shin SY, Chang HJ, Yang IS, Chung LN, Lee HY. 2004. Assessing relative importance of Korean traditional food tour program attributes based on conjoint analysis. Korean J Community Nutrition, 9(5):654-662
  26. Shin YK, Rhee SY, Park MS. 2001. The consumer's preference for beef using conjoint analysis. The Korean Journal of Agricultural Economics, 42(2):17-32
  27. Souza Monteiro D, Ventura Lucas MR. 2001. Conjoint measurement of preferences for traditional cheeses in lisbon. British Food Journal, 103(6):414-424 https://doi.org/10.1108/00070700110400406
  28. Steenkamp JB. 1987. Conjoint measurement in ham quality evaluation. Journal of Agricultural Economics, 38:473-480 https://doi.org/10.1111/j.1477-9552.1987.tb01065.x
  29. Ulengin B. 1998. Using hierarchical information integration to examine customer preferences in banking. The International Journal of Bank Marketing, 16(5):202-210 https://doi.org/10.1108/02652329810228217
  30. Wei S, Ruys H, Muller TE. 1999. A gap analysis of perceptions of hotel attributes by marketing managers and older people in Australia. Journal of Marketing Practice: Applied Marketing Science, 5(6):200-212 https://doi.org/10.1108/EUM0000000004574
  31. Wetzels M, Ruyter K, Lemmink J, Koelemeijer K. 1995. Measuring customer service quality in international marketing channels: a multimethod approach. The Journal of Business and Industrial Marketing, 10(5):50-59 https://doi.org/10.1108/08858629510103905
  32. Yang IS, Shin SY, Lee HY, Lee SJ, Chae IS. 2000. Constructing strategic management plan for university foodservice using conjoint analysis and multidimensional scaling. Korean J. Dietary Culture, 15(1):51-58