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This study aims to increase knowledge of the ability of nutrition labels to guide consumer choices in real-life environments.

Food consumption and plate waste data were collected from two self-service restaurants (SSR) with different customer groups over six observation days: three control and three intervention (with nutrition labelling) periods. Study Group 1 consisted of vocational school students, mostly late adolescents (N = 1,710), and Group 2 consisted of spa hotel customers, mostly elderly (N = 1,807). In the experimental restaurants, the same food was served to the buffets during the control and intervention periods.

The nutrition label in the lunch buffet guides customers to eat fewer main foods and salads and to select healthier choices. Increased consumption of taste enhancers (salt and ketchup) was observed in the study restaurants after nutritional labelling. Nutrition labelling was associated with a reduction in plate waste among the elderly, whereas the opposite was observed among adolescents.

The results provide public policymakers and marketers with a better understanding of the effects of nutrition labelling on consumer behaviour. Future studies should further evaluate the effects of nutrition labelling on the overall quality of customer diets and the complex environmental, social, and psychological factors affecting food choices and plate waste accumulation in various study groups.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

Purpose: Previous research identified a measurement gap in the individual assessment of social misconduct in the workplace related to gender. This gap implies that women respond to comparable self-reported acts of bullying or sexual discrimination slightly more often than men with the self-labeling as “bullied” or “sexually discriminated and/or harassed.” This study tests this hypothesis for women and men in the scientific workplace and explores patterns of gender-related differences in self-reporting behavior.

Basic design: The hypotheses on the connection between gender and the threshold for self-labeling as having been bullied or sexually discriminated against were tested based on a sample from a large German research organization. The sample includes 5,831 responses on bullying and 6,987 on sexual discrimination (coverage of 24.5 resp. 29.4 percentage of all employees). Due to a large number of cases and the associated high statistical power, this sample for the first time allows a detailed analysis of the “gender-related measurement gap.” The research questions formulated in this study were addressed using two hierarchical regression models to predict the mean values of persons who self-labeled as having been bullied or sexually discriminated against. The status of the respondents as scientific or non-scientific employees was included as a control variable.

Results: According to a self-labeling approach, women reported both bullying and sexual discrimination more frequently. This difference between women and men disappeared for sexual discrimination when, in addition to the gender of a person, self-reported behavioral items were considered in the prediction of self-labeling. For bullying, the difference between the two genders remained even in this extended prediction. No statistically significant relationship was found between the frequency of self-reported items and the effect size of their interaction with gender for either bullying or sexual discrimination. When comparing bullying and sexual discrimination, it should be emphasized that, on average, women report experiencing a larger number of different behavioral items than men.

Interpretation and relevance: The results of the study support the current state of research. However, they also show how volatile the measurement instruments for bullying and sexual discrimination are. For example, the gender-related measurement gap is considerably influenced by single items in the Negative Acts Questionnaire and Sexual Experience Questionnaire. The results suggest that women are generally more likely than men to report having experienced bullying and sexual discrimination. While an unexplained “gender gap” in the understanding of bullying was found for bullying, this was not the case for sexual discrimination.

Front-of-pack nutritional labels have been extensively studied to support consumers in making healthier and more informed food choices. However, existing research has gathered conflicting evidence about which category of label, nutrient-specific or summary labels, is more effective. As a result, the European Union has postponed its decision on selecting a unified label to collect additional information. This study specifically focusses on individuals with noncommunicable diseases, an overlooked yet relevant segment of consumers who can significantly benefit from the proper use of nutritional labels in their self-care.

In a sequence of three studies grounded in the front-of-pack acceptance model and focussing on customers with specific noncommunicable diseases, the authors examined the different effects of the NutrInform Battery and Nutri-Score on food acceptance and portion selection. This research involved the use of structural equation modelling and ANOVA and was conducted with a cumulative sample of 2,942 EU adults, residing in countries with or without previous exposure to nutritional labels.

The results suggest that among individuals with noncommunicable diseases, nutrient-specific labels are perceived as more useful and easier to use. They also generate a better attitude towards the usage of nutritional labels and are more effective in nudging those consumers towards a proper selection of portions.

The results provide valuable insights into how front-of-pack nutritional labels can impact the food choices of individuals with noncommunicable diseases and have implications for public health policies.

Investigation of the effects of NutrInform Battery and Nutri-Score on consumers with noncommunicable diseases, an area currently under-researched.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

Sustainability labels play a crucial role in providing consumers with quick and easily accessible information to assess the environmental, social and economic impacts of products. This research examines how different sustainability labels influence consumer perceptions and assessments of alternative food networks (AFNs).

The authors conducted three cross-sectional studies to explore consumer perceptions of sustainability labels for AFNs. The authors tested labels representing the three sustainability dimensions, labels of different graphical quality and different awarding bodies.

Consumers did not differentiate between sustainability dimensions but assessed labels in a holistic manner. The overall rating of a label positively influenced perceived sustainability. Self-designed and professionally designed labels had a positive effect on the intention to buy from an AFN. Professionally designed labels also enhanced the perceived authenticity of the networks. Notably, the source of the label, whether self-awarded or awarded by an official body, did not significantly impact consumer perceptions. However, interaction effects revealed professionally designed labels had a stronger positive effect on purchase intention when they were self-awarded.

AFNs can derive benefits from using labels. Self-organized, non-profit AFNs are well advised to have labels professionally designed.

This research contributes to the understanding of the effects of sustainability labels for community-based AFNs, diverging from the traditional focus on individual products.

This review explores the phenomenon of front-of-pack nutrition labels (FoPNLs) in the European Union (EU). FoPNLs highlight the nutritional quality of food and non-alcoholic beverages and help consumers to make healthier choices. The review explores different types of FoPNLs and evaluates their effectiveness.

A policy analysis was conducted, relying on extant academic literature, grey literature and policy documents. The use of current FoPNLs is interpreted in light of national and economic interests.

Our review identifies and describes seven government endorsed FoPNLs that are currently used in the EU. Five are positive endorsement labels (Croatia, Czech Republic, Denmark, Lithuania, Slovenia and Sweden), which only provide a positive indication on more healthy products. The Keyhole is used in three EU countries (Denmark, Lithuania and Sweden), while the others are used in one country each. The Nutri-Score represents a summary label, which provides an overall grade of how healthy a product is. It is used in six countries (Belgium, France, Germany, Netherlands, Spain and Luxembourg). Finally, the Nutrinform battery is a nutrient-specific non-interpretive scheme, indicating the content of nutrients in a portion of a food product. All identified labels are only used on a voluntary basis, encouraging selective use.

This review contributes to a significant discussion about food labeling in the EU. It summarizes existing approaches and evaluates them in terms of their effectiveness. The current schemes in use reflect regional clustering. The most common scheme is the Nutri-Score. This is predominantly found in western EU states. Another major label is the Keyhole, with summary endorsement schemes being prevalent in northern EU states. The least common is Nutrinform, which has some support in southern EU states. The Nutri-score is most effective although economic interests are pushing for the Nutrinform battery in a small number of states. Finally, the review suggests that all existing FoPNLs are voluntary, these labels fail to provide consumers with adequate information about nutrition quality of food products. The EU needs to mobilize support to agree on a single one.

This study aims to explore the similarities and differences between the three concepts that are commonly used to describe the knowledge of traditional and indigenous communities, namely, indigenous knowledge, traditional knowledge and local knowledge, with a view to contributing to the discourse on conceptualizing indigenous knowledge.

Data was extracted from the Scopus database using the main terms that are used for indigenous knowledge, namely, “indigenous knowledge” (IK), “traditional knowledge” (TK) and “local knowledge” (LK). Data were analyzed according to the themes drawn from the objectives of the study, using the VOSviewer software and the analytical tool embedded in the Scopus database.

The findings indicate that whereas IK and LK are older concepts than TK, TK has become more visible in the literature than the former; there is minimal overlap in the use of the labels in the literature; the three labels’ literature is largely domiciled in the social sciences; and that there were variations in representation of the labels according to countries and geographic regions.

The author avers that the scatter of literature on the knowledge of traditional and indigenous peoples under the three main labels has huge implications on the accessibility and use the literature by stakeholders including researchers, students, information and knowledge managers and information service providers.

This study demonstrates the application of informetrics beyond is traditional use to assess trends, nature and types of research patterns and mathematical modeling of information patterns to encompass the definition of the scope of concepts as covered in the literature.

This study aims to reveal the implications that trust, as a key driver of consumer behaviour, might have on consumer acceptance of front-of-pack labels (FOPLs) and policy effectiveness. By conducting three studies on 1956 European consumers with different levels of exposure to FOPLs, this study offers additional theoretical and experimental support through a deep investigation of the central role of trust in consumers’ decision-making towards healthier and more informed food choices.

Study 1 used structural equation modelling to assess whether trust is a relevant mediator of the relationship between attitude and behavioural intention (BI), thus upgrading the front-of-pack acceptance model (FOPAM); Study 2 tested the model by comparing two labels at the extremes of the current European scheme (NutrInform Battery [NiB], Nutri-Score [NS]); Study 3 assessed the effect in cases where the connection between trust and algorithms is made transparent and evaluated trust dimensions, focusing on the perception of an algorithm presence behind FOPLs information.

Study 1 strengthens the FOPAM model with the mediating role of trust in FOPLs, demonstrating a positive effect of attitude on trust and, in turn, on BI, and resulting in a higher model fit with all the significant relationships; Study 2 revealed that the relative performance of the different labels on the FOPAM can be explained by the trust dimension; Study 3, investigating the dynamics of trust in the FOPAM, revealed that the NS is less effective than the NiB on attitude, BI and trust.

The sample was limited to Italian, French and English respondents, and two labels at the extreme of the spectrum were examined. Furthermore, the research has relevance to the issue of trust. Other moderators used in previous studies on technology acceptance model, such as actual use versus perceptual use, user experience level or type of users and type of use might be investigated.

The investigation of trust, with the upgrade of FOPAM, enhances understanding of consumers’ decision-making processes when aided by food labels and makes a new contribution to the European Union “Inception Impact Assessment” in preparation for the finalization of the “From-Farm-to-Fork Strategy”, providing new insights into the role of trust by assessing the relative performance of FOPLs in consumers’ acceptance of food-related information. Furthermore, this study revealed that consumers’ perception of FOPLs worsens when they realize that they are the result of an algorithmic calculation. Finally, the new FOPAM represents a reliable theoretical model for future research on FOPL.

This study increases the knowledge about the performance of different FOPLs on several dimensions of food decision-making, positions the upgraded FOPAM as a valid alternative to existing theoretical models to assess the relative performance of labels, also extending the literature in the context of algorithm-based FOPL, and could be used as a valid support to policymakers and industry experts in their decision towards a unified label at European level.

The purpose of this paper is to assess the usefulness of nutrition labels in Thailand during nutrition transition from traditional to modern diets that increase salt, sugar, and calorie intake and to note socio-demographic interactions and associations with consumption of transitional processed foods.

The authors studied 42,750 distance learning Open University adults aged 23-96 years in 2013 residing nationwide and participating in an ongoing community-based prospective cohort study. The authors used multivariable logistic regression to relate nutrition label experiences (“read”, “good understand”, “frequent use”), socio-demographic factors, and consumption of four transitional foods. These foods included “unhealthy” instant foods, carbonated soft drinks, and sweet drinks, or “healthy” milk.

Overall, two-thirds reported good understanding and frequent use of nutrition labels. Unhealthy transition-indicator processed foods were frequently consumed: instant foods (7 per cent), (carbonated) soft drinks (15 per cent), and sweet drinks (41 per cent). Frequent users of nutrition labels (e.g. females, older persons, professionals) were less likely to consume unhealthy indicator foods. Those with the most positive overall nutrition label experience (“read” + “good understanding” + “frequent use”) had the best indicator food profiles: instant foods (odds ratio (OR) 0.63; 95%CI, 0.56-0.70); soft drinks (OR 0.56; 95%CI, 0.52-0.61); sweet drinks (OR 0.79; 95%CI, 0.74-0.85); milk (OR 1.87; 95%CI, 1.74-2.00).

Knowledge protected – those with most nutrition label experience were least likely to consume unhealthy foods. Results support government regulated nutrition labels, expanding to include sweet drinks. The study is remarkable for its large size and nationwide footprint. Study subjects were educated, represent Thais of the future, and show high awareness of transition-indicator foods.