The Impact of Environmental Recall and Carbon Taxation on the Carbon Footprint of Supermarket Shopping

Panzone, Luca A.; Ulph, Alistair; Zizzo, Daniel John; Hilton, Denis; Clear, Adrian K.

doi:10.2139/ssrn.3068222

Cited by 11 publications

(27 citation statements)

References 1 publication

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“…The notable improvements when a traffic-light label is provided gives an indication that difficulties in self-monitoring can be overcome by providing additional, even simple information (as also found inAndrews et al 2011;Muller et al 2019). These findings are particularly relevant for the growing niche of research studying sustainable choices in online environment(Demarque et al 2015;Muller et al 2019;Panzone et al 2018), where consumers make choices without physically seeing products.…”

mentioning

confidence: 85%

“…Whilst being a key source of nutrients for healthy living, food consumption has very important environmental implications: the production, supply, distribution, and consumption of food emits greenhouse gases (GHG) (Macdiarmid et al 2012;Panzone et al 2018;Poore and Nemecek 2018;Springmann et al 2016), which are often referred to as a product's carbon footprint. Behaviourally, the carbon footprint differs from kilocalories in the impact they have on society: the person who overconsumes kilocalories will directly pay the health consequences of the behaviour (in terms of ill health from e.g., heart disease); while an excessive amount of GHG emitted is reflected in the depletion of the environmental public good locally and globally, affecting negatively also those who consume sustainably.…”

Section: Food Consumption Environmental Sustainability and Environmmentioning

confidence: 99%

“…Current food consumption in developed economies is often considered unsustainable, harming both peoples' health and the environment (Macdiarmid et al 2012;Panzone et al 2018;Springmann et al 2016). The literature gives significant attention to what motivates sustainable consumption (Panzone et al 2016b;Prothero et al 2011;Steg and Vlek 2009), paying less attention to whether consumers can predict the impact of their consumption on health and the environment.…”

Section: Introductionmentioning

confidence: 99%

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The effect of traffic-light labels and time pressure on estimating kilocalories and carbon footprint of food

et al. 2020

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Food consumption decisions require consumers to evaluate the characteristics of products. However, the literature has given limited attention to how consumers determine the impact of food on health (e.g., kilocalories) and on the environment (e.g., carbon footprint). In this exercise, 1,511 consumers categorised 43 food products as healthy/unhealthy and good/bad for the environment, and estimated their kilocalories and carbon footprint, which were known to the investigator. The task was performed either with no stimuli (a control group), under time pressure only, with traffic-light labels only, or both. Results show that traffic-light labels: 1) operate through improvements in knowledge, rather than facilitating information processing under pressure; 2) improve the ability to rank products by both kilocalories and carbon footprint, rather than the ability to use the metric; 3) reduce the threshold used to categorise products as unhealthy/bad for the environment, whilst raising the threshold used to classify products as good for the environment (but not healthy). Notably, traffic-light increase accuracy by reducing the response compression of the metric scale. The benefits of labels are particularly evident for carbon footprint. Overall, these results indicate that consumers struggle to estimate numerical information, and labels are crucial to ensure consumers make sustainable decisions, particularly for unfamiliar metrics like carbon footprint.

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confidence: 85%

Section: Food Consumption Environmental Sustainability and Environmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The effect of traffic-light labels and time pressure on estimating kilocalories and carbon footprint of food

et al. 2020

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“…Participants could receive up to £1 in change and were told so. For examples of where consumers were asked to spend as much of the budget as possible please see [11] and [12].…”

Section: Experimental Designmentioning

confidence: 99%

“…The idea here is to collect information about food purchases in a low-cost and efficient way. The tool resembles similar tools that have been developed in other contexts, such as [11] and [12] who use a online shopping tool including a wide range of products (including non food items) to study environmentally friendly purchases.…”

Section: Introductionmentioning

confidence: 99%

A computer-based incentivized food basket choice tool: Presentation and evaluation

2019

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ObjectiveTo develop and evaluate a low-cost computer-based tool to elicit dietary choices in an incentive compatible manner, which can be used on-line or as part of a laboratory study.MethodsThe study was conducted with around 255 adults. Respondents were asked to allocate a fixed monetary budget across a choice of around a hundred grocery items with the prospect of receiving these items with some probability delivered to their home by a real supermarket. The tool covers a broad range of food items, allows inference of macro-nutrients and calories, and allows the researcher to fix the choice set participants can choose from. We compare the information derived from our incentivized tool, and compare it to alternative low-cost ways of measuring dietary intake, namely the food frequency questionnaire and a one-shot version of the 24-hour dietary recall, which are both based on self-reports. We compare the calorie intake indicators derived from each tool with a number of biometric measures for each subject, namely weight, body-mass-index (BMI) and waist size.ResultsThe results show that the dietary information collected is only weakly correlated across the three methods. We find that only the calorie intake measure from our incentivized tool is positively and significantly related to each of the biometric indicators. Specifically, a 10% increase in calorie intake is associated with a 1.5% increase in BMI. By contrast, we find no significant correlations for either of the two measures based on self-reports.ConclusionThe computer-based tool is a promising new, low-cost measure of dietary choices, particularly in one-shot situations where such behaviours are only observed once, whereas other tools like 24-hour dietary recalls and food frequency questionnaires may be more suited when they are administered repeatedly. The tool may be useful for research conducted with limited time and budget.

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Efficiency of Low-Carbon Finance: Its Interrelationships with Industry and Macroeconomic Environment

Antunes,

Hadi-Vencheh,

Jamshidi

et al. 2024

J Knowl Econ

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This study contributes to the literature by addressing the relevance of low-carbon finance efficiency and making significant contributions. We employ a simple weighted linear programming (LP) approach to estimate efficiency and compute entity scores with minimal optimization background, enhancing accessibility. Our study investigates interrelationships among the factors of production and outputs in estimating the efficiency of low-carbon finance, including financial index (renewable energy investment), renewable electricity output, renewable production, financial risk index, GDP, and research and development expenses, using the stochastic structural relationship programming (SSRP) model. Analyzing China, India, Brazil, and the USA, our findings show that China and the USA outperform other countries in low-carbon finance efficiency. This sheds light on comparative performance and variations across different contexts. A minimal initial overall renewable production plays an important role for the countries with lower financial indices to improve, while those with high indices should increase their focus on the energy sector. We identify a spillover effect of renewable production on financial index and financial risk index, emphasizing the positive relationship between renewable energy investments and overall financial outcomes. Integrating renewable energy initiatives into financial strategies brings potential benefits. This study significantly contributes to the literature on low-carbon finance efficiency, offering vital policy implications for sustainable finance and renewable energy sectors.

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The Impact of Environmental Recall and Carbon Taxation on the Carbon Footprint of Supermarket Shopping

Cited by 11 publications

References 1 publication

The effect of traffic-light labels and time pressure on estimating kilocalories and carbon footprint of food

The effect of traffic-light labels and time pressure on estimating kilocalories and carbon footprint of food

A computer-based incentivized food basket choice tool: Presentation and evaluation

Efficiency of Low-Carbon Finance: Its Interrelationships with Industry and Macroeconomic Environment

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