Virtual reality (VR) offers a new instrument for food scientists to evaluate different aspects of food products. The possible applications range from product design testing, evaluation of the labels, effects of different placements or the evaluation of store layouts. These analyses help us to get a deeper understanding of consumers' minds. Additionally, VR can be coupled by several different tools (e.g. eye-trackers or skin conductance sensors or even electroencephalographs). However, as there have been only a limited number of applications published, there are several open questions which need to be answered. In the presented paper the authors aim i) to introduce the current knowledge on VR applications in food science by introducing several fields of applications and ii) to point out the most important questions regarding the applications of VR in food science.

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Environmental stimuli can have a significant impact on our decisions. Elements of the store atmosphere, such as music, lights and smells, all have effects on choices, but these have been only vaguely investigated. In the present study, we aim to uncover the effect of strawberry scent on the gazing behavior and choices of the 62 recruited participants. A static eye-tracker was used to study the effect of scent, released by a diffuser. In total, 31 participants completed the study under odorless conditions, while another 31 participants had strawberry fragrance sprayed into the air. The objectives of the study were (1) to determine whether the most gazed-upon product in each of the four categories (chocolate, tea, muesli bar, yoghurt) was chosen, (2) whether the presence of the strawberry scent influenced consumer decision making, i.e., whether the strawberry scent influenced more people to choose strawberry-flavored products, and (3) to introduce the application of a fast and easy-to-use technique for the qualitative analysis of strawberry aroma present in the air during eye-tracking measurements. The results show that (1) participants chose the product they had studied the longest, for all four categories, and (2) the presence or absence of the scent had no significant effect on choice, with the same frequencies of choosing each product in the two conditions regardless of the flavor of the products.

PurposeHungarian economy went through substantial changes in the past few decades and hypermarkets gained high popularity among customers, therefore profiling Hungarian hypermarket shoppers is essential to understand their behavior.Design/methodology/approachThe paper investigates the profile of Hungarian hypermarket shoppers based on a wide questionnaire survey. In the presented research, Computer-Aided Personal Interviewing questionnaires were analyzed using multidimensional scaling and k-means clustering.FindingsResults showed that Hungarian hypermarket shoppers regularly plan their shopping but they buy 8–9 items instead of the planned 4–5 items. However, only 25% of respondents reported the use of shopping list and in spite of the wide digital possibilities, they do not use their mobile devices neither for creating shopping list nor for checking coupons online.Originality/valueThis study explores the profile of Hungarian hypermarket shoppers, which may give additional information for the players of the retail environment about the customers' behavior and preferences.

Predicting the success of National Football League drafts has always been an exciting issue for the teams, fans and even for scientists. Among the numerous approaches, one of the best techniques is to ask the opinion of sport experts, who have the knowledge and past experiences to rate the drafts of the teams. When asking a set of sport experts to evaluate the performances of teams, a multicriteria decision making problem arises unavoidably. The current paper uses the draft evaluations of the 32 NFL teams given by 18 experts: a novel multicriteria decision making tool has been applied: the sum of ranking differences (SRD). We introduce a quick and easy-to-follow approach on how to evaluate the performance of the teams and the experts at the same time. Our results on the 2021 NFL draft data indicate that Green Bay Packers has the most promising drafts for 2021, while the experts have been grouped into three distinct groups based on the distance to the hypothetical best evaluation. Even the coding options can be tailored according to the experts’ opinions. Statistically correct (pairwise or group) comparisons can be made using analysis of variance (ANOVA). A comparison to TOPSIS ranking revealed that SRD gives a more objective ranking due to the lack of predefined weights.