The application of multivariate statistical methods for understanding food consumer behaviour

Understanding consumer behaviour is a necessary precondition for a targeted communication strategy. The behaviour is a complex phenomenon and research needs to undertake a rigorously apply sophisticated methods. This article entails the combined utilisation of categorical principal component analysis and cluster analysis to determine the major, relatively homogenous consumer groups and this is coupled with confirmatory factor analysis and structural model building to understand consumer behaviour, based on Fishbein and Ajzent’s theoretic model.Categorical principal component analysis, cluster analysis, confirmatory factor analysis, consumers’ segmentation, structural model building, Research Methods/ Statistical Methods,

Nutrition for the ageing brain: towards evidence for an optimal diet

As people age they become increasingly susceptible to chronic and extremely debilitating brain diseases. The precise cause of the neuronal degeneration underlying these disorders, and indeed normal brain ageing remains however elusive. Considering the limits of existing preventive methods, there is a desire to develop effective and safe strategies. Growing preclinical and clinical research in healthy individuals or at the early stage of cognitive decline has demonstrated the beneficial impact of nutrition on cognitive functions. The present review is the most recent in a series produced by the Nutrition and Mental Performance Task Force under the auspice of the International Life Sciences Institute Europe (ILSI Europe). The latest scientific advances specific to how dietary nutrients and non-nutrient may affect cognitive ageing are presented. Furthermore, several key points related to mechanisms contributing to brain ageing, pathological conditions affecting brain function, and brain biomarkers are also discussed. Overall, findings are inconsistent and fragmented and more research is warranted to determine the underlying mechanisms and to establish dose-response relationships for optimal brain maintenance in different population subgroups. Such approaches are likely to provide the necessary evidence to develop research portfolios that will inform about new dietary recommendations on how to prevent cognitive decline

The application of multivariate statistical methods for understanding food consumer behaviour

Understanding consumer behaviour is a necessary precondition for a targeted communication strategy. The behaviour is a complex phenomenon and research needs to undertake a rigorously apply sophisticated methods. This article entails the combined utilisation of categorical principal component analysis and cluster analysis to determine the major, relatively homogenous consumer groups and this is coupled with confirmatory factor analysis and structural model building to understand consumer behaviour, based on Fishbein and Ajzent’s theoretic model

Consumer Perception of the Use of High-Pressure Processing and Pulsed Electric Field Technologies in Food Production

New food processing technologies are developed on a continuous basis. While food scientists may applaud the progress of science, consumers have been known to take a more conservative approach and do not always readily see the benefits of new processing methods. As learned from earlier examples (such as GM and irradiation), the advantages that a new processing technology has to offer do not necessarily guarantee the success of a product in the market place. If consumers do not perceive the benefits of a new technology as relevant, its application is threatened. For example, studies of consumer attitudes towards GM foods have found that consumer acceptance depends on whether consumers perceive specific benefits associated with the product (Frewer et al. 1996; Frewer et al. 1997). Hence, a benefit that is perceived only to be in the interest of the manufacturer is not sufficient. This paper examines consumers’ attitudes towards apple juice produced by two new food processing technologies, high-pressure processing (HPP) and pulsed electric field processing (PEF) in four European countries.2 Products produced by these technologies are soon to be introduced on the markets in Europe on a larger scale. Therefore, from a managerial point of view it is interesting to learn more about how consumers perceive food products produced by these novel processing technologies

Consumer Perception of the Use of High-Pressure Processing and Pulsed Electric Field Technologies in Food Production

New food processing technologies are developed on a continuous basis. While food scientists may applaud the progress of science, consumers have been known to take a more conservative approach and do not always readily see the benefits of new processing methods. As learned from earlier examples (such as GM and irradiation), the advantages that a new processing technology has to offer do not necessarily guarantee the success of a product in the market place. If consumers do not perceive the benefits of a new technology as relevant, its application is threatened. For example, studies of consumer attitudes towards GM foods have found that consumer acceptance depends on whether consumers perceive specific benefits associated with the product (Frewer et al. 1996; Frewer et al. 1997). Hence, a benefit that is perceived only to be in the interest of the manufacturer is not sufficient. This paper examines consumers’ attitudes towards apple juice produced by two new food processing technologies, high-pressure processing (HPP) and pulsed electric field processing (PEF) in four European countries.2 Products produced by these technologies are soon to be introduced on the markets in Europe on a larger scale. Therefore, from a managerial point of view it is interesting to learn more about how consumers perceive food products produced by these novel processing technologies.Agribusiness, Agricultural and Food Policy, Farm Management, Food Consumption/Nutrition/Food Safety, Research and Development/Tech Change/Emerging Technologies, Risk and Uncertainty,