results of the study may have both theoretical and practical implications. First, this paper will supplement and broaden the existing knowledge of the determinants of the valuation of consumer goods, as well as improve current research methods for eliciting the market prices. As using the framing effect (especially, the positive attribute framing) is remarkably common in advertising messages and slogans, the research will also facilitate recommendations within marketing sciences.
2 Literature review
The first behavioural effect relevant to my study is the
Different Flavors You Never Know What Behavior You're Going to Get. Advances in Consumer Research. Association for Consumer Research (U. S.), 37 , 24-27.
Chang, W. Y., and Chang, I. Y., 2014. The Influences of Humorous Advertising on Brand Popularity and Advertising Effects in the Tourism Industry. Sustainability, 6 (12), 9205-9217. doi: 10.3390/su6129205
Davies, M., 1993. Developing Combinations of Message Appeals for Campaign Management. European Journal of Marketing, 27 (1), 45-63. doi: 10.1108/03090569310024558
Dong-Jenn, Y., Chen-Yin, L., Hsiung
Pablo de Pedraza, Stefano Visintin, Kea Tijdens and Gábor Kismihók
.g., low frequencies correspond to the long-term, high frequencies to very short-time periods).
An important difference with the traditional method presented above is that in spectral and cross-spectral analysis timescales are not a priori imposed by the researcher. Structural characteristics and cyclical behavior are extracted from the data itself and identified at different timescales. Periodicity of short-, medium-, and long-term components is endogenous from the analysis ( Granger and Hatanaka, 2015 ; Iacobucci, 2005 ) and the statistical comparison of frequency
sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. Doi: 10.1111/j.1083-6101.2007.00393.x
Briggs, R., & Hollis, N. (1997). Advertising on the web: Is there response before click-through? Journal of Advertising Research, 37(2), 33- 45.
Buami, E. K. (2014). Social networking site as platform for advertisement: Does it really work? International Journal of ICT and Management, 2(1), 40-47.
Burgess, D. (2015). Online banner adverts: More than the final click. Journal of
,” Journal of Marketing , Vol. 74, No. 6, 1-17.
14. Phelps, J. & Hoy, M. (1996). “The A ad-Ab-PI Relationship in Children: The Impact of Brand Familiarity and Measurement Timing,” Psychology & Marketing, Vol. 13, No.1, 77-101
15. Shimp, T. & Gresham, L. (1985). “Attitude toward the Advertisement and Brand Attitudes: A Classical Conditioning Perspective,” Journal of Advertising, Vol. 14, No.1, 10-18.
16. Solomon, M.R. (2009). Consumer Behavior Buying, Having and Being (8 th ed). New Jersey, NJ: Pearson Education.
17. Spears, N., & Singh, S. N
Aertsens, J., Verbeke, W., Mondelaers, K., & van Huylenbroeck, G. (2009). Personal determinants of organic food consumption: A review, British Food Journal , Vol. 111 (10), 1140–1167. DOI: 10.1108/00070700910992961.
Ajzen, I. (1991). The theory of planned behavior, O rganizational Behavior and Human Decision Processes, 50(2), 179-211. DOI: 10.1016/0749-5978(91)90020-T.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour . Englewood Cliffs, NJ: Prentice-Hall
Alibabic, V., Jokic, S., Mujic
Risk: Risk Preference, Monetary Goals and Information Search. Personality and Individual Differences, 18(6), 771-782.
Moisa, S., Fruja, I., Elena Pet, E. et al. (2010). A comparative study on the effectiveness of advertising leaflets for kaufland stores in timisoara. Agricultural Management, 12(2), 1-10.
Nagyová, Ľ., Stávková, J,. Tonkovičová, Z. (2008). Selected characteristics of slovak consumers purchasing behaviour. In Acta universitatis agriculturae et silviculturae mendelianae brunensis. Sborník Mendelovy zemědělské a lesnické univerzity v Brně, 56
Consumer Behavior, Harvard University Press, pp. 82-109.
7. Donthu, N. & Garcia, A. (1999), ‘The Internet Shopper’, Journal of Advertising Research 39(3), 52 - 58.
8. Featherman, M. S. & Pavlou, P. A. (2003), Predicting e-services adoption: a perceived risk facets perspective, International Journal of Human-Computer Studies 59(4), 451-474.
9. Finucane, M. L.; Slovic, P.; Mertz, C.; Flynn, J. & Satterfield, T. A. (2000), Gender, race, and perceived risk: the ‘white male’ effect., Health, Risk & Society 2(2), 159 - 172.
10. Forsythe, S.; Liu, C
reality: Transformation of native visitor experiences. Journal of Business Research, 69(2), p. 985-991.
10. Christensen, G. & Olson, J., 2002. Mapping consumers' mental models with ZMET. Psychology and Marketing, 19(6), pp. 477-501.
11. Coulter, R., Zaltman, G. & Coulter, K., 2001. Interpreting Consumer Perceptions of Advertising: An Application of the Zaltman Metaphor Elicitation Technique. Journal of Advertising, 30(4).
12. Donald, H., Rosen, P. & Mossholder, K., 2012. Social Networking Websites, personality ratings and
1. Anderson, Eugene W. (1998), “Customer satisfaction and word of mouth”, Journal of service research , Vol. 1, No. 1, pp. 5-17. doi:10.1177/109467059800100102
2. Audrain-Pontevia, Anne-Françoise, and Allan J. Kimmel (2008), “Negative word-of-mouth and redress strategies: An exploratory comparison of French and American managers”, Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior , Vol. 21, pp. 124-136.
3. Bachleda, Catherine, and Boutaina Berrada-Fathi (2015), “Is negative eWOM more influential than