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Comparison of college students' behavior toward nutrition information communication between Korea and the US

  • Kim, Chang-Sik (Department of Hospitality and Tourism Management, Sejong University) ;
  • Bosselman, Robert (Department of Apparel, Events & Hospitality Management, College of Human Sciences, Iowa State University) ;
  • Choi, Hyung-Min (International Center for Hospitality Research & Development, Dedman School of Hospitality, Florida State University) ;
  • Lee, Keum Sil (Department of Tourism Management, Jangan University) ;
  • Kim, Eojina (Department of Hospitality & Tourism Management, Pamplin College of Business, Virginia Tech) ;
  • Moon, Hyeyoung (Department of Food & Nutrition, Institute of Symbiotic Life-TECH, College of Human Ecology, Yonsei University) ;
  • Jang, Yoon Jung (Department of Food & Nutrition, Institute of Symbiotic Life-TECH, College of Human Ecology, Yonsei University) ;
  • Ham, Sunny (Department of Food & Nutrition, Institute of Symbiotic Life-TECH, College of Human Ecology, Yonsei University)
  • Received : 2019.12.17
  • Accepted : 2019.12.27
  • Published : 2020.08.01

Abstract

BACKGROUND/OBJECTIVES: The expansion of menu labeling to restaurants has created a need to study customers' behavior toward nutrition information. Therefore, the purpose of this research was to compare college students' behavior toward nutrition information communication between Korea and the US. This study consisted of three objectives: 1) to compare the frequency of usage as well as degree of trust regarding smartphone-based communication channels in the acquisition of nutrition information among college students between Korea and the US, 2) to compare knowledge-sharing behavior related to nutrition information among college students between Korea and the US, and 3) to identify the role of country in the process of knowledge-sharing behavior. SUBJECTS/METHODS: A survey was distributed via the web to college students in Korea and the US. Data were collected in the 2nd week of March 2017. Completed responses were collected from 423 Koreans and 280 Americans. Differences between Koreans and Americans were evaluated for statistical significance using a t-test. In order to verify the effects of knowledge self-efficacy and transactive memory capability on knowledge-sharing behavior related to nutrition information, a regression analysis was performed. RESULTS: Significant differences were found in the frequency of usage as well as degree of trust in communication channels related to nutrition information between Korean and American college students. While knowledge self-efficacy and tractive memory capability had positive effects on knowledge-sharing behavior related to nutrition information, country had a significant effect on the process. CONCLUSIONS: This study is the first to compare customer behavior toward nutrition information acquisition and sharing between Korea and the US. Comparative research on nutrition information revealed differences among the different countries. Therefore, this study contributes to the body of knowledge on the nutrition information research, in particular, by providing a comparison study between countries.

Keywords

References

  1. Currie J, Della Vigna S, Moretti E, Pathania V. The effect of fast food restaurants on obesity and weight gain. Am Econ J 2010;2:32-63.
  2. Drichoutis AC, Nayga RM Jr, Lazaridis P. Nutritional labeling. In: Lusk JL, Roosen J, Shogren J, editors. The Oxford Handbook of the Economics of Food Consumption and Policy. Oxford: Oxford University Press; 2011. p.520-45.
  3. Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass index in US children and adolescents, 2007-2008. JAMA 2010;303:242-9. https://doi.org/10.1001/jama.2009.2012
  4. United States Department of Agriculture. Food CPI and expenditures: analysis and forecasts of the CPI for food [Internet]. Washington, D.C.: United States Department of Agriculture; 2011 [cited 2019 November 13]. Available from: https://www.ers.usda.gov/data-products/food-price-outlook/.
  5. Burton S, Creyer EH, Kees J, Huggins K. Attacking the obesity epidemic: the potential health benefits of providing nutrition information in restaurants. Am J Public Health 2006;96:1669-75. https://doi.org/10.2105/AJPH.2004.054973
  6. Boger CA Jr. Food labeling for restaurants: fact versus fiction. Cornell Hotel Restaur Adm Q 1995;36:62-70.
  7. Conklin MT, Lambert CU, Cranage DA. Nutrition information at point of selection could benefit college students. Topics Clin Nutr 2005;20:90-6. https://doi.org/10.1097/00008486-200504000-00002
  8. Kozup JC, Creyer EH, Burton S. Making healthful food choices: the influence of health claims and nutrition information on consumers' evaluations of packaged food products and restaurant menu items. J Mark 2003;67:19-34. https://doi.org/10.1509/jmkg.67.2.19.18608
  9. Kral TV, Roe LS, Rolls BJ. Does nutrition information about the energy density of meals affect food intake in normal-weight women? Appetite 2002;39:137-45. https://doi.org/10.1006/appe.2002.0498
  10. Sproul AD, Canter DD, Schmidt JB. Does point-of-purchase nutrition labeling influence meal selections? A test in an Army cafeteria. Mil Med 2003;168:556-60. https://doi.org/10.1093/milmed/168.7.556
  11. Roe B, Levy AS, Derby BM. The impact of health claims on consumer search and product evaluation outcomes: results from FDA experimental data. J Public Policy Mark 1999;18:89-105. https://doi.org/10.1177/074391569901800110
  12. Wansink B, Painter J, van Ittersum K. Descriptive menu labels' effect on sales. Cornell Hotel Restaur Adm Q 2001;42:68-72.
  13. Variyam J. Nutrition Labeling in the Food-away-from-Home Sector: an Economic Assessment. Economic Research Report No. (ERR-4). Washington, D.C.: United States Department of Agriculture; 2005.
  14. Cooke R, Papadaki A. Nutrition label use mediates the positive relationship between nutrition knowledge and attitudes towards healthy eating with dietary quality among university students in the UK. Appetite 2014;83:297-303. https://doi.org/10.1016/j.appet.2014.08.039
  15. Deshpande S, Basil MD, Basil DZ. Factors influencing healthy eating habits among college students: an application of the health belief model. Health Mark Q 2009;26:145-64. https://doi.org/10.1080/07359680802619834
  16. Graham DJ, Laska MN. Nutrition label use partially mediates the relationship between attitude toward healthy eating and overall dietary quality among college students. J Acad Nutr Diet 2012;112:414-8. https://doi.org/10.1016/j.jada.2011.08.047
  17. Martinez OD, Roberto CA, Kim JH, Schwartz MB, Brownell KD. A survey of undergraduate student perceptions and use of nutrition information labels in a university dining hall. Health Educ J 2012;72:319-25. https://doi.org/10.1177/0017896912443120
  18. Robinson E, Fleming A, Higgs S. Prompting healthier eating: testing the use of health and social norm based messages. Health Psychol 2014;33:1057-64. https://doi.org/10.1037/a0034213
  19. Croker H, Whitaker KL, Cooke L, Wardle J. Do social norms affect intended food choice? Prev Med 2009;49:190-3. https://doi.org/10.1016/j.ypmed.2009.07.006
  20. Kwahk KY, Park DH. The effects of network sharing on knowledge-sharing activities and job performance in enterprise social media environments. Comput Human Behav 2016;55:826-39. https://doi.org/10.1016/j.chb.2015.09.044
  21. Kwahk KY, Park DH. Leveraging your knowledge to my performance: the impact of transactive memory capability on job performance in a social media environment. Comput Human Behav 2018;80:314-30. https://doi.org/10.1016/j.chb.2017.10.047
  22. Burford S, Park S. The impact of mobile tablet devices on human information behavior. J Doc 2014;70:622-39. https://doi.org/10.1108/JD-09-2012-0123
  23. Bellur S, Nowak KL, Hull KS. Make it our time: In class multitaskers have lower academic performance. Comput Human Behav 2015;53:63-70. https://doi.org/10.1016/j.chb.2015.06.027
  24. PEW Research Center. Mobile fact sheet [Internet]. Washington, D.C.: PEW Research Center; 2018 [cited 2019 November 13]. Available from: https://www.pewresearch.org/internet/fact-sheet/mobile/.
  25. Fox S, Duggan M. Health Online 2013. Washington, D.C.: Pew Research Center's Internet & American Life Project; 2013.
  26. Thackeray R, Crookston BT, West JH. Correlates of health-related social media use among adults. J Med Internet Res 2013;15:e21. https://doi.org/10.2196/jmir.2297
  27. Fox S. Social life of health information [Internet]. Washington, DC.: Pew Internet Center, Internet and American Life Project; 2011 [cited 2012 July 7]. Available from: https://www.pewresearch.org/internet/wp-content/uploads/sites/9/media/Files/Reports/2011/PIP_Social_Life_of_Health_Info.pdf.
  28. Academy of Nutrition and Dietetics. eatright.org [Internet]. Cleveland (OH): Academy of Nutrition and Dietetics; 2014 [cited 2019 November 13]. Available from: http://www.eatright.org.
  29. U.S. Food and Drug Administration. Food labelling: nutrition labelling of standard menu items in restaurants and similar retail food establishments. Final regulatory impact analysis [Internet]. Silver Spring (MD): U.S. Food and Drug Administration; 2014 [cited 2019 December 15]. Available from: https://www.fda.gov/media/116833/download.
  30. Ministry of Food and Drug Safety. Korean government has enacted the special act on children's food safety and nutrition [Internet]. Cheongju: Ministry of Food and Drug Safety; 2016 [cited 2019 November 17]. Available from: http://www.mfds.go.kr/index.do.
  31. Kwahk KY. The impacts of social networks on individual adaptation to technochanges. Asia Pac J Inf Syst 2011;21:29-47.
  32. Subrahmanyam K, Greenfield P. Online communication and adolescent relationships. Future Child 2008;18:119-46. https://doi.org/10.1353/foc.0.0006
  33. Kankanhallid A, Tan BC, Wei KK. Contributing knowledge to electronic knowledge repositories: an empirical investigation. Manage Inf Syst Q 2005;29:113-43. https://doi.org/10.2307/25148670
  34. Kim CS, Kwahk KY. Effects of network positions of organizational members on knowledge sharing. Knowl Manag Res 2015;16:67-89. https://doi.org/10.15813/kmr.2015.16.2.004
  35. Hsu MH, Ju TL, Yen CH, Chang CM. Knowledge sharing behavior in virtual communities: the relationship between trust, self-efficacy, and outcome expectation. Int J Hum Comput Stud 2007;65:153-69. https://doi.org/10.1016/j.ijhcs.2006.09.003
  36. Cortina JM. What is coefficient alpha? An examination of theory and applications. J Appl Psychol 1993;78:98-104. https://doi.org/10.1037/0021-9010.78.1.98

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