Understanding key factors influencing consumers’ willingness to try, buy, and pay a price premium for mycoproteins

Mycoprotein is a fungal-based meat alternative sold in food retail in various countries around the world. The present study builds on a multi-national sample and uses partial least square structural equation modeling. The proposed conceptual model identified key factors that are driving and inhibiting consumer willingness to try, buy, and pay a price premium for mycoprotein. The results relate to the overall sample of 4088 respondents and to two subsample comparisons based on gender and meat consumption behavior. The results show that the biggest drivers of willingness to consume mycoprotein were healthiness, followed by nutritional benefits, safe to eat, and sustainability. Affordability and taste had mixed results. Willingness to consume mycoprotein was inhibited if nutritional importance was placed on meat and, to a lesser extent, if the taste, texture, and smell of meat were deemed important. Best practice recommendations address issues facing marketing managers in the food industry

Is cultured meat a promising consumer alternative? Exploring key factors determining consumer's willingness to try, buy and pay a premium for cultured meat

Cultured meat is a relatively new product, enjoying consumer appreciation as a more sustainable meat option. The present study builds on a sample from a diverse set of countries and continents, including China, the US, the UK, France, Spain, Netherlands, New Zealand, Brazil, and the Dominican Republic and uses partial least square structural equation modelling. The proposed conceptual model identified key factors driving and inhibiting consumer willingness to try, buy, and pay a price premium for cultured meat. Results relate to the overall sample of 3091 respondents and two sub-sample comparisons based on gender and meat consumption behaviour. Food neophobia, having food allergies, being a locavore, and having concerns about food technology were found to be inhibiting factors towards willingness to try, buy, and pay a price premium for cultured meat. Food curiosity, meat importance, and a consumer's perception of cultured meat as a realistic alternative to regular meat were found to be important drivers that positively impacted consumers' willingness to try, buy and pay more. Best practice recommendations address issues facing marketing managers in food retail and gastronomy

Largest ancient fortress of South-West Asia and the western world?:Recent fieldwork at Sasanian Qaleh Iraj at Pishva, Iran

The article presents recent works at Qale Iraj, near Varamin, Iran. My short contribution is on the Middle Persian ostraka found at the site

Mate Value and Self-Esteem: Evidence from Eight Cultural Groups

This paper explores self-perceived mate value (SPMV), and its association with self-esteem, in eight cultures. 1066 participants, from 8 cultural groups in 7 countries, rated themselves on 24 SPMVs and completed a measure of self-esteem. Consistent with evolutionary theory, women were more likely to emphasise their caring and passionate romantic nature. In line with previous cross-cultural research, characteristics indicating passion and romance and social attractiveness were stressed more by respondents from individualistic cultures, and those higher on self-expression (rather than survival) values; characteristics indicative of maturity and confidence were more likely to be mentioned by those from Traditional, rather than Secular, cultures. Contrary to gender role theory, societal equality had only limited interactions with sex and SPMV, with honesty of greater significance for male self-esteem in societies with unequal gender roles. These results point to the importance of cultural and environmental factors in influencing self-perceived mate qualities, and are discussed in relation to broader debates about the impact of gender role equality on sex differences in personality and mating strategies

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships