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J East Asian Soc Diet Life 27(3): 243 256 (2017) http://dx.doi.org/10.17495/easdl.2017.6.27.3.243 243 Purchasing Needs of Frying Powder according to Purchasing Attributes - Analysis for Selection Attributes through Importance-Satisfaction Analysis and Conjoint Analysis - Hyesun Chang and Ki Hyeon Sim Dept. of Traditional Dietary Life, Graduate School of Traditional Culture and Arts, Sookmyung Women s University, Seoul 04310, Korea ABSTRACT This study attempted to improve frying powder products based on 272 consumers purchase conditions. Factor analysis by type was conducted on purchase attributes of consumers who purchased frying powder by categorizing them based on five factors-namely, convenience, information, diversity, safety, and economy. Five main factors were divided into four purchase attributes named various pursuit, convenience pursuit, economical pursuit, and inform/safety pursuit. Purchasing status of frying powder products was analyzed according to three independent variables such as age, meal preparation type, and purchase attributes. The top motivation for using frying powder was convenience. According to the importance-satisfaction analysis survey, taste, expiration date, and certification mark were chosen as highly important and high satisfaction characteristics for frying powder (p<0.001), whereas nutrition, oil absorption, adhesiveness, crispiness, origin, and food additives were highly important and low satisfaction characteristics (p<0.001). In the conjoint analysis, crispiness was the most important attribute of fried food. Key words : Purchasing needs, purchasing attributes, frying powder, importance-satisfaction analysis, conjoint analysis Corresponding author : Ki Hyeon Sim, Tel: +82-2-2077-7475, Fax: +82-2-2077-7475, E-mail: santaro@sm.ac.kr (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013). (premix) (prepared mix),, (Kim HS & Song E 2011). 2013 2009, (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013). 4,,,,,,, (Asia economic news 2016; Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2016). 2012 22.5% 2015 30.3% 3 7.8% (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2016; Trot news 2016).

244. 140 180 (Yoon YJ 2007; Choi SI 2011). (Lee SJ 2001; Kim BS & Lee YE 2009)..,. (Dziezak JD 1991), (Balasubramaniam VM 1997), (Lee SJ 2001), (Baixauli R 2003; Myers AS & Brannan RG 2012), (Sanz T 2004), (Lee MJ 2005), (Yoon YJ 2007), (Shim JY 2007), (Kim BS & Lee YE 2009), (Choi SI 2011). 2013 (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013) - (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2016).. - (Importance-Satisfaction Analysis; ISA) - (Importance-Performance Analysis; IPA) (Hammit WE 1996; Lee HR & Seo YM 2013; Oh JE & Cho MS 2016). (Kim HS & Lyu ES 2012; Lim HM & Moon HY 2015; Oh JE & Cho MS 2016). (conjoint analysis) (Jung YW & Lee EY 2008; Jo MN 2010). (Jung YW & Lee EY 2008; Jo MN 2010)., -.,,. 1. 20 300 2016 5 15 5 30 (self-administered questionnaire survey).. 300 291 ( 97.0%), 272 ( 90.7%). (χ 2 -test), t- (independent samples t-test), (One-way ANOVA) G Power 3.1 0.25, 0.05 0.80 180. 2. Kwon TS (2005) Ju SY (2012).,,,,.,,,,, 5., Nam SH & Sim KH(2013) Park JS & Sim KH(2014), Hwang SY & Na JG (2015) (convenience),

27(3): 243 256 (2017) 245 (informativity), (diversity), (safety), (economical efficiency) 30., 1,, 1,, 5., 19 (1 : 5 : ) (1 : 5 : ) 5., (Choi WS 2012; Kim HA & Lee KH 2013)., (Lee SJ 2001; Lee MJ 2005; Choi SI 2011; Kim HS & Song E 2011),, (Focus Group Interview; FGI),, 3. 3 2 ( ), 4 (,,, ), 2 (, ). (full-profile approach) 16 (2 4 2). 16, (fractional factorial design). SPSS for Window(ver. 23.0, IBM, Armonk, NY, USA) (orthogonal array) 8. 2 10. 3. SPSS for Window (ver. 23.0, IBM, Armonk, NY, USA). (frequency analysis). (factor analysis), K-, Cronbach s α., t-,,, Duncan multiple range test. t- (paired t-test), -. 10. α=0.05, α=0.01, α=0.001. 1. Table 1. 20 87 (32.0%), 50 68 (25.0%), 40 66 (24.3%), 30 51 (18.8 %). 4 / 128 (47.1%), / 69 (25.4%), 2 / 47 (17.3%), 28 (10.3%). 59 (21.7%), 57 (21.0%) 52 (19.1%). 31 (11.4%), 24 (8.8%), 18 (6.6%). 119 (43.8%), 87 (32.0%), 66 (24.3%). 50 75 69 (25.4%), 25 50 65 (23.9%), 75 100 60 (22.1%), 100 53 (19.5%), 25 25 (9.2%).

246 Table 1. General characteristics of the respondents Age (yrs) Education level Occupation Meal preparing type Monthly expenses for food (Unit: 10,000 Korean won) Variables Respondents N (%) 20s 87 ( 32.0) 30s 51 ( 18.8) 40s 66 ( 24.3) 50s 68 ( 25.0) Less than high school 28 ( 10.3) College 47 ( 17.3) University 128 ( 47.1) More than graduate school 69 ( 25.4) Housewife 59 ( 21.7) Specialized job 57 ( 21.0) Student 52 ( 19.1) Office work 31 ( 11.4) Self-employed 31 ( 11.4) Sales and service 24 ( 8.8) Technical post 18 ( 6.6) By own 119 ( 43.8) Family or friend 87 ( 32.0) Convenient food 66 ( 24.3) <25 25 ( 9.2) 25 <50 65 ( 23.9) 50 <75 69 ( 25.4) 75 <100 60 ( 22.1) 100 53 ( 19.5) Total 272 (100.0) 2. 5 (Table 2). 1,,,, 17.58%. 2,,,, 14.69%. 3,,,, 11.87%. 4 (Hazard Analysis and Critical Control Point; HACCP),, (Genetically Modified Organism; GMO),, 9.26%. 5, 1+1,, PB(Private Brand), 8.00%. Cronbach s α, 0.70, (p<0.001).. K- 4. Table 3. 1, 2, 3, 4 /., (p<0.001). 3. 1,, 1, Table 4. 1, 1 3 54.4%, 4 6 21.9%, 15.2%, 7 8.5%., 1 1 3 60.9%, 57.8%, 54.2%, / 46% (p<

27(3): 243 256 (2017) 247 Table 2. Examination of reliability according to the factor analysis of purchasing attribute Factors Item Factor loading Eigen value Variance explained (%) Cronbach's α 1) Factor 1. Convenience Factor 2. Informativity Factor 3. Diversity Factor 4. Safety Factor 5. Economical efficiency I frequently buy instant food. 0.88 I like to eat fast food. 0.84 I frequently eat delivery food. 0.78 I prefer foods that are easy to cook. 0.67 I consult the review when I purchase foods. 0.77 I prefer food company which I purchased before. 0.76 I get a recommendation when I buy the product for the first time. 0.76 Brand image is important when buying food. 0.75 I try new products right away when it comes out. 0.79 I buy food made by different company every time. 0.79 I try to cook a variety of recipes. 0.74 I often use online shopping mall to buy food. 0.63 I prefer food with the HACCP label. 0.79 I put emphasis on food ingredients safety. 0.77 I do not buy GMOs. 0.75 I prefer organic processed foods. 0.58 I prefer foods that are relatively cheap. 0.83 I purchase 1+1 event food. 0.73 I compare the price of the food before purchasing. 0.70 I prefer retailers' PB products. 0.66 3.52 17.58 0.82 2.94 14.69 0.78 2.38 11.87 0.75 1.86 9.26 0.73 1.60 8.00 0.72 Total variance ratio (%) 61.40 Kaiser-Meyer-Olkin scale=.742, Bartlett s test of sphericity: χ 2 =1,745.865 (p<0.001), 1) Cronbach's α=0.70. Table 3. Analysis of factor differences according to purchasing attribute Factor Cluster 1) Various pursuit (N=49) Convenience pursuit (N=69) Economical pursuit (N=93) Inform/safety pursuit (N=61) F-value Convenience 2.58±0.65 b2) 3.68±0.62 c 2.23±0.53 a 3.59±0.67 c 104.199 *** Informativity 2.74±0.67 a 3.65±0.53 b 3.84±0.51 b 4.05±0.67 c 52.526 *** Diversity 3.09±0.75 c 2.16±0.50 a 2.54±0.56 b 3.78±0.53 d 97.301 *** Safety 3.23±0.75 a 3.13±0.70 a 3.88±0.47 b 4.15±0.61 c 41.017 *** Economical efficiency 3.04±0.61 a 3.50±0.73 bc 3.33±0.62 b 3.66±0.76 c 8.329 *** *** p<0.001. 1) Each value represents the means (M) and standard deviation (S.D.) of ratio of using 5-point scale (1: very negative 5: very positive). 2) a d Means in each row with different superscript letters are significantly different by Duncan s multiple range test (p<0.05).

248 장혜선 심기현 東아시아 食生活學會誌

27(3): 243 256 (2017) 249 0.01)., 50 1 3, 20 30, 40 54.5% 55.6%, 65.6% 1 3 (p<0.01). 50 1 4 6 42.3%, 1 3 32.7%. 1 1 3 62.0% 57.8% (p<0.001). 21 (52.5%). 2013 6 1 (31.6%), 3 1 (22.5%), 1 1 (15.9), 2 1 (14.9%), 1 1 (11.4%), 2 1 (4.2%), 1 (1.0%), 20 3 1 (24.6%), 6 1 (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013). 1 1 3, (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013). 2012, 1/4 4/4,. 3/4 (7 9 ) 2/4(4 6 ) 9 (Ministry of Agriculture, Food and Rural Affairs & Korea Agro- Fisheries Trade Corporation 2013)., (easy cook) 39.3 %, (good taste) 28.5%, (curiosity) 11.6%, (cost cutting) 11.2%, (nutritious value) 9.4%.,,, / 39.1% 35.5 %, 38.6%, 44.0%, / 30.5 % 31.1%, 33.7%.,,. 43.4% 43.7%, 24.8% 32.4 % (p<0.05). 32.5%, 22.5%. Song MJ(2009) (Home Meal Replacement; HMR),,, Choi SW & Ra YS(2013) HMR, HMR.., (Lee JS 2008).,.,,, (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013). 1, 2,000 3,000 49.6%, 3,000 4,000 25.0%, 4,000 14.7%, 1,000 2,000 10.7%., 2,000 3,000, / 58.0%, 54.4%, 45.8%, 42.2%

250 (p<0.05)., 2,000 3,000 (p<0.01). 1 2,000 3,000 20 34.9%, 30 48.9%, 40 65.6%, 50 50.0%. 1 2,000 3,000, 51.3%, 50.7%, 42.5 %. -, 2014 1 2,207 2016 11 2,266 2.7%, 1 2,000 3,000 (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2016).,,. (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013).,,. 0, 5 3.56. 3.57, 3.38, 3.64, / 3.58,. 30 40 3.64, 50 3.56, 20 3.42,., 3.69, 3.44, 3.40 (p<0.05). (Oliver RL 1980)., (Lee YJ 1994). (Jeon IH 2009)., 3.56.,. (Ministry of Agriculture, Food and Rural Affairs & Korea Agro-Fisheries Trade Corporation 2013). 3 Table 5. 28.1%, 25.4%, 21.4%. 1.9% Table 5. Preferred ingredients for the frying dish Variables N % Meat 144 21.4 Seafood 171 25.4 Vegetables 189 28.1 Fruits 40 6.0 Nuts 40 6.0 Cheese 75 11.2 Other 13 1.9 Total 672 100.0 1) Plural response.

27(3): 243 256 (2017) 251. Lee JK & Yoon KS(2011),,,,.,,,. 4. - 19 - Table 6. 3.84 3.22. 4.00, (4.58 ), (4.29 ), (4.25 ), (4.19 ), (4.07 ), (4.00 ). (3.90 ), (3.89 ), (3.84 ), (3.87 ) 3.84,., (3.69 ), (3.48 ), (3.47 ), (3.46 ), (3.43 ), (3.43 ), (3.35 ), (3.31 ), (3.29 ), (3.27 ) 3.22,. t 2.598 (p<0.05).. - Fig. 1.,, 1. 2 (, ),,,,,,.,, 3 Table 6. Importance-satisfaction analysis for selective characteristic of frying powder Selective characteristic 1) Importance Satisfaction t p A1. Taste 4.25±0.63 3.48±0.61 14.613 0.000 *** A2. Nutrition 3.90±0.83 3.11±0.68 11.985 0.000 *** A3. Price 3.84±0.78 3.43±0.71 6.013 0.000 *** A4. Volume 3.79±0.77 3.46±0.70 5.085 0.000 *** A5. Package style 3.61±0.89 3.35±0.72 3.358 0.001 ** A6. Design 3.10±0.89 3.29±0.68 2.598 0.010 * A7. Cookery 3.83±0.70 3.43±0.69 7.545 0.000 *** A8. Organic 3.73±0.87 3.04±0.77 9.532 0.000 *** A9. Gluten free 3.46±0.93 2.87±0.80 7.196 0.000 *** A10. Functional supplement 3.37±0.95 3.03±0.69 4.417 0.000 *** A11. Oil absorption 4.07±0.85 2.93±0.82 13.359 0.000 *** A12. Adhesiveness 4.19±0.79 2.85±0.89 15.557 0.000 *** A13. Crispiness 4.58±0.58 2.84±1.03 21.720 0.000 *** A14. Origin 3.89±0.86 3.17±0.83 10.008 0.000 *** A15. Company 3.70±0.85 3.47±0.71 3.405 0.001 ** A16. Discount 3.55±0.89 3.27±0.83 3.981 0.000 *** A17. Expiration date 4.29±0.67 3.69±0.80 9.994 0.000 *** A18. Food additive 4.00±0.86 3.10±0.79 12.928 0.000 *** A19. Certification mark 3.87±0.83 3.31±0.74 9.446 0.000 *** Total 3.84±0.41 3.22±0.43 * p<0.05, ** p<0.01, *** p<0.001. 1) Each value represents the means (M) and standard deviation (S.D.) of ratio of using 5-point scale (1: very negative~5: very positive).. 4,,,,,,,., Lee JS(2008),,,,,,,,.

252 Fig. 1. Importance-satisfaction analysis matrix for selective characteristic of frying powder.,,. Kim HS & Song E(2011),,,.,,,,,.,.,.,. 5. Table 7. 62.74%. 25.58%, 11.68%., (0.647) ( 0.647). (1.957), (0.215), ( 0.778), ( 1.394)

27(3): 243 256 (2017) 253 Table 7. Utility value and relative importance of the frying powder High attribute Lower attribute Utility value Relative importance (%) Utility combination Correlation Batter thickness Texture Fortify nutrition Thin 0.647 16.551 25.581 Thick 0.647 16.551 Hardness 1.394 87.464 Crispiness 1.957 122.788 62.743 Chewiness 0.215 13.490 Adhesiveness 0.778 48.814 Yes 0.213 2.487 11.676 No 0.213 2.487 Pearson s R=0.986, p<0.001 Kendall s tau=0.929, p<0.01. (0.213) ( 0.213). Table 8.,,,.,. Table 8. Final rank of the profiles consumers prefer for frying powder Preference ranking Composite attributes levels Texture Batter thickness Fortify nutrition Effectiveness level 1 Crispiness Thin No 2.817 2 Crispiness Thick Yes 1.097 3 Chewiness Thin No 1.075 4 Chewiness Thick No 0.219 5 Adhesiveness Thin Yes 0.344 6 Chewiness Thick Yes 0.645 7 Hardness Thin Yes 0.960 8 Adhesiveness Thick No 1.212 9 Hardness Thick No 1.828 10 Hardness Thick Yes 2.254 Pearson R Kendall. Pearson R,, 0.6 (Lee HY 2010). Kendall (Lee HY 2010)., Pearson R 0.986(p<0.001)., Kendall 0.929(p<0.01) 10. Han MH(2014),,,.,,,. Hong EY(2005).,. -,,

254. 20 272 -,.,,.,,,, 5,,, / 4.,, 4. 1, 1 3 54.4%, 21.9% 4 6. (p<0.01) (p<0.001) 1 3, 50 1 3 (p<0.01). 39.3%, 28.5%. (p<0.05). 1, 2,000 3,000 49.6%, 3,000 4,000 25.0%, 4,000 14.7%, 1,000 2,000 10.7%. (p<0.05) (p<0.01) 1 2,000 3,000. - (p<0.001), (p<0.001), (p<0.001), (p<0.001), (p<0.001), (p<0.001), (p<0.001), (p<0.001), (p<0.001)., 62.74%, 25.58%, 11.68 %., (0.647), (1.957), (0.213).. -,,. -,,,. -,. REFERENCES Asia economic news (2016) Blowing the premium winds into the pan frying and deep frying powder. http://view.asiae.co. kr/news/view.htm?idxno=2016042009000810364. Accessed November 30, 2017. Baixauli R, Sanz T, Salvador A, Fiszman SM (2003) Effect of the addition of dextrin or dried egg on the rheological and textural properties of batters for fried foods. Food Hydrocol 17(3): 305-310. Balasubramaniam VM, Chinnan MS, Mallikarjunan P, Phillips

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