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dc.contributor.authorMather, Damien Wen_NZ
dc.contributor.authorKnight, John Gen_NZ
dc.contributor.authorHoldsworth, David Ken_NZ
dc.date.available2011-04-07T03:11:50Z
dc.date.copyright2005en_NZ
dc.identifier.citationMather, D. W., Knight, J. G., & Holdsworth, D. K. (2005). Pricing differentials for organic, ordinary and genetically modified food. Journal of Product and Brand Management, 14(6), 387–392. Marketing Working Paper Series. doi:10.1108/10610420510624549en
dc.identifier.issn1061-0421en_NZ
dc.identifier.urihttp://hdl.handle.net/10523/1253
dc.descriptionThis is a post-print (i.e., final draft post-refereeing) of this article. There may be some differences between this version and the final version published in the journal.en_NZ
dc.description.abstractAbstract: Purpose – Aims to conduct research on consumer willingness to buy genetically modified (GM) foods with a price advantage and other benefits, compared with organic and ordinary types of foods, employing a robust experimental method. The importance of this increases as the volume and range of GM foods grown and distributed globally increase, as consumer fears surrounding perceived risk decrease and consumer benefits are communicated. Design/methodology/approach – In contrast with survey-based experiments, which lack credibility with some practitioners and academics, customers chose amongst three categories of fruit (organic, GM, and ordinary) with experimentally designed levels of price in a roadside stall in a fruit-growing region of New Zealand. Buyers were advised, after choosing, that all the fruit was standard produce, and the experiment was revealed. Data were analysed with multi-nomial logit models. Findings – Increasing produce type and price sensitivity coefficient estimates were found in order from organic through ordinary to spray-free GM produce, requiring market-pricing scenario simulations to further investigate the pricing implications. Practical implications – The real market experimental methodology produced robust, useful findings. Originality/value – It is concluded that, when the GM label is combined with a typical functional food benefit, GM fruit can indeed achieve significant market share amongst organic and ordinary fruit, even in a country where the GM issue has been highly controversial; GM fruit can gain a sustainable competitive advantage from any price reduction associated with production cost savings; and market shares of organic fruit are least sensitive to pricing and the introduction of GM fruit.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherEmerald Insighten_NZ
dc.relation.ispartofJournal of Product and Brand Managementen_NZ
dc.relation.ispartofseriesMarketing Working Paper Seriesen_NZ
dc.relation.urihttp://www.emeraldinsight.com/10.1108/10610420510624549en_NZ
dc.subjectexperimentationen_NZ
dc.subjectgenetic modificationen_NZ
dc.subjectorganic foodsen_NZ
dc.subjectpricingen_NZ
dc.subject.lcshHF Commerceen_NZ
dc.subject.lcshHF5601 Accountingen_NZ
dc.titlePricing differentials for organic, ordinary and genetically modified fooden_NZ
dc.typeJournal Articleen_NZ
dc.description.versionPublisheden_NZ
otago.bitstream.pages22en_NZ
otago.date.accession2005-11-28en_NZ
otago.schoolMarketingen_NZ
otago.relation.issue6en_NZ
otago.relation.pages387-392en_NZ
otago.relation.volume14en_NZ
dc.identifier.doi10.1108/10610420510624549en_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints57en_NZ
dc.description.refereedPeer Revieweden_NZ
otago.school.eprintsMarketingen_NZ
dc.description.referencesBishop, R. C. and Heberlein, T. A., 1979 “Measuring Values of Extramarket Goods: Are Indirect Measures Biased?” American Journal of Agricultural Economics, Vol 61 No 5, pp. 926 Bishop, R. C. and Heberlein, T. A., (1986), Does Contingent Valuation Work?, Littlefield, Adams; Rowman and Allanheld, Totowa, N.J. Boccaletti, S. and Moro, D., 2000 “Consumer willingness-to-pay for GM food products in Italy”, AgBioForum, Vol 3 No 4, pp. 259-267 Bohm, P., 1972 “Estimating demand for public goods: an experiment”, European Economic Review, Vol 3 No 2, pp. 111-130 Boyed, J. and Mellman, J., 1980 “The effect of fuel economy standards on the U.S. automotive market: a hedonic demand analysis”, transportation research, Vol 14A No 5-6, pp. 367-378 Burton, M. and Pearse, D., 2003 “Consumer Attitudes Towards Genetic Modification, Functional Foods, and Microorganisms: A Choice Modeling Experiment for Beer”, AgBioForum, Vol 5 No 2, pp. 51-58 Carson, R. T., 1995, “Contingent Valuation Surveys and Tests of Insensitivity to Scope”, in University of California at San Diego, Economics Working Paper Series, 1995 - 5 Chen, Z. and Kuo, L., 2001 “A Note on the Estimation of the Multinomial Logit Model with Random Effects”, The American Statistician, Vol 55 No 2, pp. 89-107 Cummings, R. G., Harrison, G. W. and Rutstrom, E. E., 1995, “Homegrown values and hypothetical surveys: Is the dichotomous choice approach incentive-compatible?” American Economic Association, pp 260 Dickie, M., Fisher, A. and Gerking, S., 1987, “Market Transactions and Hypothetical Demand Data: A Comparative Study.” American Statistical Association, pp 69 Gaskell, G., Allum, N. and Stares, S., 2003, “Europeans and Biotechnology in 2002: Eurobarometer 58.0” Haubel, G., Elrod, T. and Tipps, 1999, “Random Coefficient Structural Equation Modelling”, in 10th. Annual Advanced Research Techniques Forum, Chicago, 23 Jain, D., Vilcassim, N. and Chintagunta, P., 1994 “A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data”, Journal of Business and Economic Statistics, Vol 12 No 3, pp. 317-328 Kealy, M. J., Montgomery, M. and Dovidio, J. F., 1990 “Reliability and Predictive Validity of Contingent Values: Does the Nature of the Good Matter?” Journal of Environmental Economics and Management, Vol 19 No 3, pp. 244-63 Knight, J., Holdsworth, D. and Mather, D., 2003, “Trust and Country Image: Perceptions of European Food Distributors Regarding Factors That Could Enhance or Damage New Zealand’s Image - Including GMOs”, University of Otago, pp 89 List, J. A. and Gallet, C. A., 2001 “What Experimental Protocol Influence Disparities between Actual and Hypothetical Stated Values?” Environmental and Resource Economics, Vol 20 No 3, pp. 241-54 Loomis, J., Brown, T., Lucero, B. and Peterson, G., 1996, “Improving validity experiments of contingent valuation methods: Results of efforts to reduce the...” University of Wisconsin Press, pp 450 Louviere, J. J., Hensher, D. A. and Swait, J. D., (2000), Stated Choice Methods, University Press, Cambridge Lusk, J., 2003 “Effects of cheap talk on consumer willingness-to-pay for golden rice”, American Journal of Agricultural Economics, Vol 85 No 4, pp. 840-856 Mather, D., 2003, “Simple and Improved Heterogeneous MNL Model Estimation”, in Proceedings of ANZMAC 2003, D. R. Kennedy (Ed.), Hyatt, Adelaide, South Australia,2486-2491 McFadden, D., (1973), Conditional logit analysis of qualitative choice behaviour, Academic Press, Inc., New York McFadden, D. and Train, K., 2000 “Mixed MNL models for discrete response”, Journal of Applied Econometrics, Vol 15 No pp. 447-470 Moon, W. and Balasubramanian, S., 2003 “Is there a market for genetically modified foods in Europe? Contingent valuation of GM and non-GM breakfast cereals in the United Kingdom”, Journal of Agrobiotechnology Management & Economics, Vol 6 No 3, pp. article 6 Morrison, M. D., Blamey, R. K., Bennett, J. W. and Louviere, J. J., 1996, “A Comparison of Stated Preference Techniques for Estimating Environmental Variables”, Australian National University, pp 34 Neill, H. R., Cummings, R. G., Ganderton, P. T., Harrison, G. W. and McGuckin, T., 1994 “Hypothetical surveys and real economic commitments.” Land Economics, Vol 70 No 2, pp. 145en_NZ
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