Modelling the Factors Influencing Polish Consumers’ Approach towards New Food Products on the Market
| Autor: | Arkadiusz Piwowar, Wioletta Wolańska, Agnieszka Orkusz, Magdalena Kapelko, Joanna Harasym |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Sustainability Volume 15 Issue 3 Pages: 2818 |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su15032818 |
| Popis: | The sustainability of food systems and circular economy aspects are ending the traditional food approaches and are demanding changes in raw materials and products supplied by agriculture and the food industry. However, the “supply” of new products is the easiest to achieve, while gaining the acceptance of consumers for a new product will always be the toughest. For the consumer the new product is an item which until recently was not known or used. However, considering the newness of products concept on a scientific basis, it is obvious that the concept covers new, novel, and innovative food products. The study applies an advanced analysis of the factors that drive the consumers’ acceptance of new products (perceived as new, novel, and innovative) on the food market in Poland. Specifically, seaweeds (as new), edible insects (as novel), and 3D-printed personalized food products (as innovative) were chosen. The selected factors influencing the Polish consumers’ approach towards the newness of food products, including the different tendencies to accept innovations in this area, were analyzed by using factor and reliability analysis. The assessment of the differences towards an acceptance of new products based on the socio-demographic characteristics of the consumer was completed using the Kruskal–Wallis test. Furthermore, to analyze the features favoring the acceptance of new products, the logistic regression was estimated. The article presents the results of a survey of 500 Polish respondents in the 20–44 age group. The profound statistical analysis showed that the destiny of foreign travel turned out to be an important variable in the logistic regression model. |
| Databáze: | OpenAIRE |
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