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Despite its health benefits, vegetable consumption is low in urban Nigeria. Interventions have been successful in increasing urban Nigerians' vegetable intake in the home environment, but interventions doing so for popular out-of-home consumption are lacking. This study aimed to design, implement and assess an intervention to increase the vegetable intake of urban Nigerians through street foods.

A quasi-experimental design was applied in Lagos, Nigeria. During the intervention, 12 trained street food vendors (SFVs) actively promoted the health benefits of vegetables to their customers (using marketing statements and posters) and provided the option to buy an additional green leafy vegetables (GLVs) side dish to their meal. Purchases were observed, and a survey was conducted before and during the intervention to measure perceived meal quality and satisfaction. Six to eight weeks after the intervention, a mystery shopper visited the vendor to assess if they were still selling additional GLVs.

Almost half (46%) of the 1,506 observed customers bought additional GLVs during the intervention. Both at baseline (N = 452) and during intervention (N = 564), meal satisfaction was high. Users were on average more educated and older than non-users. Most vendors did not perceive the sale of additional GLVs as additional work. Six to eight weeks after the intervention, nine vendors (75%) were still selling additional GLVs.

This study showed that SFVs informing consumers on the potential health benefits of vegetables and offering these vegetables in street food dishes at a commercially viable price is an interesting option to increase vegetable intake.

While it is incontestable that eating in restaurants leads to a higher energy intake than eating at home, this paper explores the even more environmentally relevant connection between meat intake and the location of eating.

Based on secondary data from the US National Health and Nutrition Examination Survey (NHANES), the authors apply a latent class model (LCM), combining latent profile analysis (LPA) and regression analysis. Different (latent) consumer classes are modeled based (1) on share of meat consumption and (2) share of eating out by means of LPA, while class-specific socio-demographic characteristics are estimated by means of ordered logistic regression.

Results of the LPA reveal four (latent) consumer classes with regard to the share of meat consumption and the share of eating out. One class consists mostly of male meat lovers with a high share of eating out, which, however, only represents 7% of the sample. A much larger class represents an affluent social group that consumes the majority of food outside of the home but does not consume significantly more meat than the large group of moderates who mostly eat at home. The fourth class mostly consists of children with a very low intake of meat.

By applying a LCM, the authors shed some light on the relation between meat consumption and eating out. The authors demonstrated that commonly assumed relations, such as men eating more meat than women, do not necessarily apply. Similar findings apply to factors potentially influencing meat consumption, such as education, marital status and income.

Collective catering sector is increasingly offering alternative and more sustainable food propositions, but their success rests on their reception by guests and changes induced in individual behaviors. The authors investigate food-change determinants by examining the relationship between food behavior at staff restaurants and at home.

In an experiment over four days conducted in three staff restaurants, the authors monitored the behavioral changes and motivations of guests (n = 599) offered choices between standard and sustainable options for meat, fish, dairy products, fruit-based desserts and a vegetarian dish. The calculation of a “sustainable consumption score,” based on actual consumption at a restaurant by a subsample (n = 160) of guests gives an indication of interest for sustainable options.

Higher overall choices were observed for vegetarian dishes and for the sustainable meat options rather than for the sustainable fish and desserts options, thus suggesting contrasted perceptions of the sustainable alternatives. The results revealed two profiles of consumers with contrasting scores. The “lower receptive guests” had lower commitment to sustainable food at home and at staff restaurants, while the “higher receptive guests” found in the intervention meaningful propositions for pursuing their existing at-home commitment.

Long-term research would be required to verify whether repeated sustainable offers can break down deep-rooted choices and instill durable changes among consumers with lower commitment to sustainable food. This research contributes to the identification of some types of food that are more suitable for sustainable-oriented interventions.

Some food triggers are identified to further norm activation among the lower receptive profile of consumers.

By addressing continuities/discontinuities between at-home and at-restaurant consumption and mobilizing the “norm-activation” concept, the authors question the efficiency of sustainable food offers at work.

This study aims to understand pumpkin waste awareness among people by converting unstructured quantitative data into insightful information to understand the public's awareness of pumpkin waste during Halloween.

To fulfil the study's purpose, we extracted Halloween-related tweets by employing #halloween and #pumpkin hashtags and then investigated Halloween-related tweets via a topic modelling approach, specifically Latent Dirichlet Allocation. The tweets were collected from the UK between October 25th and November 7th, 2020. The analysis was completed with 11,744 tweets.

The topic modelling results revealed that people are aware of the pumpkin waste during Halloween. Furthermore, people tweet to reduce pumpkin waste by sharing recipes for using leftover pumpkins.

The study offers a novel approach to convert social media data into meaningful knowledge about public perception of food waste. This paper contributes to food waste literature by revealing people's awareness of pumpkin waste during Halloween using social media analytics. Norm activation model and communicative ecology theory are used for the theoretical underpinning of topic modelling.

The purpose of this paper is to present a cross‐country study comparing Colombia and Vietnam, two of the major coffee exporting countries in the world, in terms of their infrastructures, the roles of external shocks, technology adoption at different stages of production, added value, positioning in both domestic and global markets, internationalisation patterns, marketing and branding innovations, regulatory frameworks, and policy environments. This study also explores other aspects linked to production, and marketing strategies that open niche markets such as speciality coffees, and socially‐, labour‐ and environmentally‐responsible trade. Furthermore, it identifies opportunities of cooperation and competition between these two countries.

Using value chain analysis as primary research method, this paper identifies links and dynamics in the value chains that have been developed in the coffee industry in both countries to improve competitiveness, increase sustainability, and respond to market demands.

Using value chain analysis, it was found that Colombia and Vietnam produce different types of coffee, and that both have implemented diverse strategies in order to be more competitive in domestic and foreign markets via product differentiation. These differences make explicit room for cooperation between these two countries in an international environment where fierce competition persists.

Cooperation between producing countries is an under‐researched subject. These findings will be useful both for policy makers in coffee‐producing countries and agribusiness researchers.

This paper aims to examine the impact of the daily growth rate of COVID-19 cases in the USA (COVIDg), the Federal Fund Rate (FFR) and the trade-weighted US dollar index (USDX) on S&P500 index daily returns and its 11 constituent sectors’ indices for the time period between January 22, 2020, until June 30, 2020.

The study uses the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model to gauge the impacts over the whole period of study, as well as over two sub-periods; first, January 22, 2020, until March 30, 2020, reflecting uncertainty in the US markets and second, from April 1, 2020, until June 30, 2020, reflecting the lockdown.

Results of the MGARCH model reveal a negative and significant relation between COVIDg and S&P500 index daily returns over the first sub-period and the whole study period in the following sectors, namely, communications, consumer discretionary, consumer staples, health, technology and materials. Yet, COVIDg showed a positive and significant relation with S&P500 index daily returns during the second time period in the following sectors, namely, communication, consumer discretionary, financial, industrial, information technology (IT) and utilities. Besides, USDX showed a negative significant effect on S&P500 index daily returns and on the daily return on each of its 11 constituent sectors over the second sub-period and the whole period. Further, FFR showed a significant effect only in the second sub-period, specifically, a negative effect on the daily return of the financial sector and a positive effect on the daily return of the technology sector index. Nevertheless, FFR had a positive significant effect on the daily return of the utilities sector index for the whole period under study.

The impact of the crisis on the S&P500 index can be assessed only with some limitations owing to available global data and the limited time frame of the lock-down.

The study proposes supporting a smooth, functioning and resilient financial system; increasing fiscal measures by the US Government to increase liquidity on constraints; measures by The Federal Reserve to alleviate US dollar funding shortages; support market integrity; ensure continuous transparency and sharing of information; support the health sector, as well as consumer-based sectors that faced demand shocks and facilitate investments in the technology sector.

The originality of this paper lies in the examination of the impact of the novel COVID-19 pandemic on each of the 11 sectors constituting the S&P500 index separately, reflecting how the main economic sectors formulating the US economy reacted to the shock during the peak time of the pandemic to observe a full picture of the economic consequences amid the pandemic.

Halving food waste has been included within the 17 UN Sustainable Development Goals. Food wasted out-of-home is the second source of food waste. However, the majority of the studies have focused on home generated food waste, and still little is known about out-of-home food waste and how it is managed by food service companies. The purpose of this paper is to adopt a double perspective in analyzing food waste generated at a food service level, by focusing on both the client and business perspective.

First, from the client perspective, the authors aim at analyzing consumer out-of-home habits, self-reported waste quantification, and doggy bag usage by reporting the results of an exploratory survey which involved 411 individuals living in central Italy. Second, from a business perspective, the authors analyzed an award-winning practice that manages out-of-home food waste in Italy by combining food surplus management and digital solutions with a profitable business model innovation.

Results obtained from the two perspectives of analysis support the need of business investments in innovations and digital solutions, in order to meet client needs and behavior, thus contributing to better manage and reduce food surplus and waste.

This study will raise practitioners’ knowledge on the advantages of digital solution in food surplus management, along with a better comprehension on food waste behavior from the client perspective.

This is the first study that analyses out-of-home waste from both the client and business perspective, emphasizing how digital solutions can help in reducing the phenomenon.

This study aims to focus on consumers’ preferences towards rosé wine and explore whether and how the consumption context may influence consumers’ choices.

Using social networks platform, the authors conducted a choice experiment, to evaluate Italian consumers’ preferences for a glass of rosé in two consumption contexts, restaurant and wine bar. Characteristics of the rosé wine also included price, origin and type of wine. The authors applied a latent class analysis to define rosé wine consumers’ segments and incorporated personality traits in the model.

The results define three rosé wine drinkers’ profiles: “Wine bar visitors”, “The unenthusiastic” and “Restaurant visitors”. Socio-demographic characteristics and personality traits significantly affect consumers’ membership to the different segments. Who prefers to drink a rosé glass at the wine bar is younger, more opened to new experiences and, therefore, more inclined towards more sophisticated choices. Consumers at the restaurants tend to be more extrovert and sensitive to price.

This study offers insight for practitioners of both wine and hospitality industries in the development of strategies for new products market placement and, at the same time, for academics who are interested in the understanding of behavioural reasoning of consumers’ wine purchase choices.

This research investigates the effect of consumption context on individuals’ preference formation for a less familiar wine, such as rosé in Italy. To the authors’ knowledge, no previous studies explored how personality traits may affect consumers’ wine consumption context choices.

New trends are emerging in the brewery sector; but to date beer consumer segmentations are scarce. In this context, the present study addresses the following questions: “Are beer consumers monolithic or are there different segments in the beer market?; and “What are the main characteristics of the beer consumer segments?”. The purpose of this paper is to examine the potential beer consumer segments and to profile them regarding their consumption behaviour.

Data from a sample of 592 consumers were analysed through hierarchical cluster analysis; and the validity of the cluster solutions was then examined through a MANOVA analysis.

A five-cluster solution emerged, revealing different beer consumption patterns and preferences. These segments are identified as “beer lovers”, “circumspect seniors”, “social drinkers”, “homelike women” and “beer to fuddle consumers”.

The findings suggest that beer consumers cannot be seen as a homogenous consumer group; and managers and brewers could manage beer as five different products, instead of considering beer as a single item.