1. Drewnowski A & Fulgoni F (2008) Nutrient profiling of foods: creating a nutrient-rich food index. Nutr Rev 66, 23–39.
3. Drewnowski A (2005) Concept of a nutritious food: toward a nutrient density score. Am J Clin Nutr 82, 721–732.
6. Borra S (2006) Consumer perspectives on food labels. Am J Clin Nutr 83, 1235S.
7. Krieger B, Cappuccio R & Moskowitz H (2003) Next generation healthy soup: an exploration using conjoint analysis. J Sens Stud 18, 249–268.
8.Food and Drug Administration (2009) [Docket No. 2007N-0277] Food Labeling: Use of Symbols to Communicate Nutrition Information, Consideration of Consumer Studies and Nutritional Criteria. http://www.fda.gov/OHRMS/DOCKETS/98fr/E7-23211.pdf (accessed December 2009).
10. Moskowitz H, Gofman A, Itty B et al. (2001) Rapid, inexpensive, actionable concept generation and optimization: the use and promise of self-authoring conjoint analysis for the food service industry. Food Service Technol 1, 149–167.
11. Box GEP, Hunter WG & Hunter JS (1978) Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building. New York: Wiley.
12. Gofman A (2006) Emergent scenarios, synergies and suppressions uncovered within conjoint analysis. J Sens Stud 21, 373–414.
14. Fulgoni VL 3rd, Keast DR & Drewnowski A (2009) Development and validation of the nutrient-rich foods index: a tool to measure nutritional quality of foods. J Nutr 139, 1549–1554.
15. Darmon N, Vieux F, Maillot M et al. (2009) Nutrient profiles discriminate between foods according to their contribution to nutritionally adequate diets: a validation study using linear programming and the SAIN,LIM system. Am J Clin Nutr 89, 1227–1236.
17. Ippolito PM & Mathios AD (1993) New food labeling regulations and the flow of nutrition information to consumers. J Public Policy Mark 12, 188–205.
18. Cowburn G & Stockley L (2005) Consumer understanding and use of nutrition labelling: a systematic review. Public Health Nutr 8, 21–28.
19. Drichoutis AC & Lazaridis P (2005) Nutrition knowledge and consumer use of nutritional food labels. Eur Rev Agric Econ 32, 93–118.
20. Kim S-Y, Nayga RM Jr & Capps O Jr (2001) Health knowledge and consumer use of nutrition labels: the issue revisited. Agric Resource Econ Rev 30, 10–19.
21. Burton S & Andrews JC (1996) Age, product nutrition, and label format effects on consumer perceptions and product evaluations. J Consum Aff 30, 69–89.
22. Nayga RJ (2000) Nutrition knowledge, gender, and food label use. J Consum Aff 34, 97–112.
23. Andrews JC, Netemeyer RG & Burton S (1998) Consumer Generalization of Nutrient Content Claims in Advertising. Cambridge, MA: Marketing Science Institute.
24. Garretson JA & Burton S (2003) Effects of nutrition facts panel values, nutrition claims, and health claims on consumer attitudes, perceptions of disease-related risks, and trust. J Public Policy Mark 19, 213–227.
25. Kozup J, Creyer E & Burton S (2003) 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 67, 19–34.
26. Mhurchu C & Gorton D (2007) Nutrition labels and claims in New Zealand and Australia: a review of use and understanding. Aust N Z J Public Health 31, 105–112.
27. Luce DR & Tukey JW (1964) Simultaneous conjoint measurement: a new type of fundamental measurement. J Math Psychol 1, 1–27.
28. Green PE, Krieger AM & Wind Y (2001) Thirty years of conjoint analysis: reflections and prospects. Interfaces 31, S56–S73.
29. Wittink DR & Cattin P (1989) Commercial use of conjoint analysis: an update. J Mark 53, 91–96.
30. Wittink DR, Vriens M & Burhenne W (1994) Commercial use of conjoint analysis in Europe: results and critical reflections. Int J Res Mark 11, 41–52.
31. Harrison RW & McLennon E (2004) Analysis of consumer preferences for biotech labelling formats. J Agric Appl Econ 36, 159–171.
32. Hu W, Veeman MM & Adamowicz WL (2005) Labelling genetically modified food: heterogeneous consumer preferences and the value of information. Can J Agric Econ 53, 83–102.
33. Pardoe I & Simonton DK (2008) Applying discrete choice models to predict academy award winners. J R Stat Soc Ser D, The Statistician 171, 375–394.