Modeling information asymmetry mitigation through food traceability systems using partial least squares

Abstract

Originally food traceability is not something new, however its added values and potentials which are enabled by information technology is what’s new. Food traceability was imposed on the food industry as a regulatory requirement which came as a response toward food incidents crisis’s like the BSE, salmonella breakouts …etc. These events have made consumers more skeptic about the food they consume especially that a lot of information about food is only known by food producers ,i.e. Genetically modified ingredients, allergic components’ in food…etc, this gap in information has created an information asymmetry situation in the food industry between producers and consumers’, which is well reported in the literature. This study sheds the light on the role of food traceability in reducing uncertainties related to risks of food products, by helping consumers become more informed about the food they consume, through the potentials of tracing food products from farm to fork in a web-based format from the records of traceability systems provided by food producers. Through a survey research we found that food traceability can reduce the aforementioned information asymmetry because it reduces consumer’ perceived risks toward food, this good cause of reducing information asymmetry was found to be faced with a  willingness to pay price premiums for traceable products