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1 – 2 of 2Jiao Chen, Dingqiang Sun, Funing Zhong, Yanjun Ren and Lei Li
Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may…
Abstract
Purpose
Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.
Design/methodology/approach
The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.
Findings
The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.
Originality/value
This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.
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Suruchi Singh and Shubhomoy Banerjee
This study employs the Social Identity Theory to examine the differential effects of personal and social dimensions of fear of missing out (FOMO) on sustainable food consumption…
Abstract
Purpose
This study employs the Social Identity Theory to examine the differential effects of personal and social dimensions of fear of missing out (FOMO) on sustainable food consumption (SFC) practices.
Design/methodology/approach
An online survey-based empirical study was conducted with 395 respondents. The data were analysed using structural equation modelling and Hayes process Macro in SPSS.
Findings
SFC was found to be positively influenced by personal FOMO. Contrary to expectations, social FOMO had a negative correlation with SFC. Social influence and social identity were shown to be positively correlated, whilst the social influence-SFC relationship was favourable. This approach was aided by social identity.
Research limitations/implications
The study supports personal FOMO as an SFC-influencing factor. It evaluates the differential effects of FOMO’s personal and social dimensions on SFC. It also demonstrates that social FOMO negatively affects SFC, contrary to expectations.
Practical implications
The study advises sustainable food firms to reduce personal FOMO via advertising and messaging.
Originality/value
This research is amongst the first to segregate the differential effects of social and personal FOMO regarding SFC behaviour. Research has examined FOMO as a higher-order construct involving social and personal aspects. Second, FOMO is often associated with negative behaviours including social media addiction and substance abuse. This FOMO-related research analyses a desired behaviour.
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