United Arab Emirates beef consumer consumption behaviours and product preferences: A Latent Class Analysis of New Zealand beef mince

Abstract

This study is part of a research programme entitled Unlocking Export Prosperity from the Agri-food Values of Aotearoa New Zealand. It is funded by the Ministry of Business, Innovation and Employment (MBIE) Endeavour Fund for science research programmes. The research aims to provide new knowledge on how local enterprises can achieve higher returns by ensuring global consumers understand the distinctive qualities of the physical, credence and cultural attributes of agri-food products that are “Made in New Zealand”. Agricultural exports are an important contributor to the New Zealand (NZ) economy. While NZ historically relied on key markets such as the United Kingdom for export trade, NZ has more recently significantly expanded its export markets and the United Arab Emirates (UAE) offers potential to become established as an important beef product destination. It is critically important for NZ exporters to understand export markets and the different cultures and preferences of those consumers to safeguard market access, and for realising potential premiums. This report describes the application of a survey of United Arab Emirates beef mince consumers designed to examine consumption behaviour and consumer Willingness-to-Pay (WTP) for credence attributes. While search attributes such as price or colour can be observed directly, and experience attributes such as flavour can be assessed when consumed, credence attributes such as environmental sustainability cannot be immediately seen or experienced at the point of sale. For products promoting credence attributes, the role of verification including labelling is of significant importance. Our approach is to apply a Discrete Choice Experiment economic valuation method, analysed using a statistical approach called Latent Class Modelling that describes profiles for different consumer segments identified in the data and provides estimates of attribute WTP across these segments.