literature review on consumer behaviour

• DOI: 10.1362/1469347012569896
• Corpus ID: 8289381

Consumer Behaviour: a Literature Review Consumer Behaviour: a Literature Review Consumer Behaviour: a Literature Review Consumer Behaviour: a Literature Review

• Moneesha Pachau
• Published 1 September 2001

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COVID-19, consumer behavior, technology, and society: A literature review and bibliometric analysis

Jorge cruz-cárdenas.

a Research Center in Business, Society, and Technology, ESTec, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador

b School of Administrative and Economic Science, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador

Ekaterina Zabelina

c Department of Psychology, Chelyabinsk State University, Bratiev Kashirinykh 129, 454001 Chelyabinsk, Russia

Jorge Guadalupe-Lanas

Andrés palacio-fierro.

d Programa doctoral en Ciencias Jurídicas y Económicas, Universidad Camilo José Cela, Castillo de Alarcón, 49, 28692 Madrid, Spain

Carlos Ramos-Galarza

e Facultad de Psicología, Universidad Católica del Ecuador, Av . 12 de octubre 1076, 170523, Quito, Ecuador

f Centro de Investigación MIST, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador

Associated Data

The COVID-19 crisis is among the most disruptive events in recent decades. Its profound consequences have garnered the interest of many studies in various disciplines, including consumer behavior, thereby warranting an effort to review and systematize the literature. Thus, this study systematizes the knowledge generated by 70 COVID-19 and consumer behavior studies in the Scopus database. It employs descriptive analysis, highlighting the importance of using quantitative methods and China and the US as research settings. Co-occurrence analysis further identified various thematic clusters among the studies. The input-process-output consumer behavior model guided the systematic review, covering several psychological characteristics and consumer behaviors. Accordingly, measures adopted by governments, technology, and social media stand out as external factors. However, revised marketing strategies have been oriented toward counteracting various consumer risks. Hence, given that technological and digital formats mark consumer behavior, firms must incorporate digital transformations in their process.

1. Introduction

The COVID-19 pandemic is among the most relevant events of recent decades. Its social and economic consequences on a global level are enormous. At the social level, the World Health Organization (WHO) has reported over four million global deaths due to COVID-19 ( WHO, 2021a ). Economies have also been severely affected ( Donthu and Gustafsson, 2020 ). The International Monetary Fund (IMF) predicts that the gross domestic product, worldwide, will plummet to about 4.9% in 2020 ( IMF, 2020 ). These remarkable social and economic implications of the pandemic and its unique features have inspired many studies from various disciplines, including consumer behavior. The crisis scenario has profoundly shifted consumer behavior toward one based on technology ( Sheth, 2020 ).

In prior pandemics, social and behavioral science research focused heavily on preventive and health behavior, while consumer behavior received less attention ( Laato et al., 2020 ). The situation has been different for the COVID-19 pandemic; COVID-19 and consumer behavior studies proliferate the literature. Reasonably, such rapidly accumulating bodies of knowledge require organization and systematization, lest such knowledge produced in fast-growing fields remains fragmented ( Snyder, 2019 ). Thus, this study fulfills this need by identifying knowledge generated by 70 relevant studies in the Scopus database, indexed up to January 5, 2021, for systematic processing.

Prior theoretical efforts created a global and general perspective of consumer behavior during the COVID-19 pandemic. Such efforts have sought to propose possible stages in behavior, comparing old and new consumption habits, or explain behaviors based on similarities with other crises and disruptive events, such as other pandemics, wars, or natural disasters (e.g., Kirk and Rifkin, 2020 ; Sheth, 2020 ; Zwanka and Buff, 2020 ). However, this study is evidently among the first to review the literature on COVID-19 and consumer behavior. The study is necessary because, beyond its similarities with other disruptive events, the COVID-19 crisis has several fundamental differences. First, it is truly global ( Brem et al., 2020 ). Second, it coincides with the rapid advance of various disruptive technologies, the confluence of which has been called “digital transformation” ( Abdel-Basset et al., 2021 ).

First, the study conducts descriptive and bibliometric analyses of the 70 selected COVID-19 and consumer behavior articles. Second, an input-process-output consumer behavior model is used to systematize the existing literature. The model, adapted by Cruz-Cárdenas and Arévalo-Chávez (2018) from Schiffman and Wisenblit (2015) for systematic reviews, furnished a comprehensive understanding of the pandemic-era consumer behavior via macro-environmental, micro-environmental, and internal-consumer-factor integration.

Accordingly, government regulations and technology stand out as fundamental forces at the macro level. At the micro-level, specific technological applications like social media and business platforms, social group and family pressure, and marketing strategies stand out. Meanwhile, many personal and psychological characteristics help us to understand how consumers process external influences and make decisions at the consumer level. Finally, regarding purchasing behaviors, the use and adoption of technologies like e-commerce platforms have had a prominent place in consumer behavior during the pandemic.

The remainder of this paper is organized as follows. Section 2 presents the construction of a theoretical framework on consumer behavior and disruptive events. The method is explained in Section 3 . Section 4 presents the descriptive and co-occurrence bibliometric technique results of generating an understanding of the literature interrelationships and characteristics. Section 5 documents the systematization and grouping of the knowledge generated based on an input-process-output model of consumer behavior. Finally, Section 6 concludes with the main implications and scope for future research.

2. Consumer behavior and disruptive events

Many consumer and human behavior studies in the context of disruptive events precede the COVID-19 pandemic. The term “disruptive event” is a situation that leads to profound changes regarding the unit analyzed ( Dahlhamer and Tierney, 1998 ). Thus, it can apply to individual consumers, organizations, industries, or society. Disruptive events can also be classified by their nature (e.g., pandemic, war, natural disaster, and personal calamity).

At the personal level, prior studies establish that in the aftermath of calamities or unfavorable events, such as the death of loved ones, divorces, and illness, consumers get rid of products that remind them of difficult times and, thus, buy new products ( Cruz-Cárdenas and Arévalo-Chávez, 2018 ). Although such disruption studies are interesting, they fail to shed enough light on consumer behavior during the COVID-19 crisis. On a larger scale, past disruptive events—such as other pandemics, natural disasters, or extreme social violence and terrorism—can contribute to understanding the pandemic-induced consumer behavior, because they affect a greater number of consumers simultaneously and in similar fashion.

Natural disasters like earthquakes, floods, hurricanes, and typhoons are frequent. They cause damage to infrastructure, economy, and human lives, thereby creating a permanent field of consumer behavior studies. Some natural disasters are carefully monitored, and their arrival and intensity can be anticipated (e.g., hurricanes). The anticipation of such events induces a behavior of stockpiling basic necessities ( Pan et al., 2020 ). Others cannot be anticipated in the short term (e.g., earthquakes). In both types of natural disasters, consumers may lose possessions and loved ones. The feeling of loss induces impulsive, therapeutic, and replacement purchases ( Delorme et al., 2004 ; Sneath et al., 2009 ). Natural disasters are primarily noted for their destructiveness and scope, which can reach regional levels.

Extreme social violence and so-called terrorism constitute another category of disruptive events affecting a country or region. Terrorism comprises violent actions by a group with less power that seeks to destabilize a government or a dominant organization ( Bates and LaBrecque, 2019 ). Such violent actions often impact human lives and negatively affect the economy and physical infrastructure. Moreover, their intensity and frequency in society are highly variable.

Although terrorist actions significantly affect the economy and infrastructure, the impact on consumer behavior is in the short term ( Baumert et al., 2020 ; Crawford, 2012 ), which induces an avoidant behavior, due to certain consumption options they consider to be of greater risk; that is, consumers choose an alternative option rather than give up their plans or consumption ( Herzenstein et al., 2015 ) (e.g., the choice between air and land travel or a destination change for tourism). The selection of consumption alternatives hinges on past events and anticipated threats ( Baumert et al., 2020 ).

Prior outbreaks from recent decades like SARS, Influenza A, and H1N1 present another type of disruptive event, which consumer behavior scholars have largely ignored ( Laato et al., 2020 ). Current knowledge on human behavior during disease outbreaks stems from other social and human sciences. Thus, two consumption-behavior types have been noted: purchasing necessities and protective equipment, and curbing leisure outside the home. For example, Goodwin et al. (2009) find that the purchase of protective items (e.g., masks and personal hygiene items) and food rose significantly during the influenza A, and H1N1 outbreaks, as people engaged in stockpiling. However, regarding SARS in China, Wen et al. (2005) found that people altered their leisure activities, modes of transportation, and the places they visited. Table 1 summarizes the features of prior disruptive events and the relevant knowledge regarding consumer behavior therein.

Disruptive events, their characteristics, and effects on the consumer.

The COVID-19 pandemic, like other prior disruptive events, has significantly impacted the economy and human life ( IMF, 2020 ; WHO, 2021a ). However, unlike natural disasters and terrorism, it (similar to prior disease outbreaks) does not damage physical infrastructure. Further, it is characterized by its persistence (the current pandemic has continued for a year and a half). Even so, the COVID-19 pandemic is unique in its global scope ( WHO, 2021b ). Moreover, it occurs within the context of significant technological advancement, known in the business and organizational world as “digital transformation” ( Abdel-Basset et al., 2021 ).

Against this comparison, prior to the systematic review, consumer behaviors reported in other disruptive events probably occurred on a large scale. However, the scope of the COVID-19 pandemic and technological advancement is expected to provide a distinctive character to consumer behavior, caught between the unique confluences of the two.

This study was developed in a series of stages, common to systematic literature reviews ( Balaid et al., 2016 ; Cruz-Cárdenas and Arévalo-Chávez, 2018 : Osobajo and Moore, 2017 ) (see Fig. 1 ).

Stages of this study.

3.1 Study objectives

Regarding Stage 1, this study primarily describes and systematizes the existing literature on consumer behavior during the COVID-19 pandemic. This objective can be broken down into three specific objectives. Thus, this study aims

• • O1: To describe the characteristics and interrelationships of relevant studies
• • O2: To generate a structured systematization of their contents and results
• • O3: To establish the limitations and gaps in existing knowledge, thereby ascertaining the scope for future lines of research

Accordingly, recognizing the multidisciplinary nature of consumer behavior, researchers from marketing, business administration, psychology, and economics teamed up to bring together experts in diverse research methodologies, such as machine learning and big data techniques. The study commenced when COVID-19 became a pandemic in March 2020.

3.2 Criteria for inclusion of articles

The study developed several article-inclusion criteria. Importantly, studies must address COVID-19 only from the perspective of consumer behavior. Thus, it was important to differentiate consumer behavior from other types of human behavior in the COVID-19 framework. Consumer behavior encompasses people's behavior in their search, purchase, usage, and disposal of goods and services ( Schiffman and Wisenblit, 2015 ). Further, articles must have an acceptable quality level, be written only in English, and have no time restriction on the date of their publication.

3.3 Search strategies

The search strategies were then developed, operationalizing the inclusion criteria. The study drew from the Scopus database, which offers a good balance between quality and coverage ( Singh et al., 2020 ). The search terms aimed to extract two central contents simultaneously: the COVID-19 pandemic and consumer behavior. The search process was initiated with the following terms: Covid AND (consum* AND behav*). The asterisk in the terms allowed for including variants of the keywords such as: consumer, consumers, consumption behavior, and behavior. Additionally, the search scanned the titles, abstracts, and keywords of the documents.

As the search process progressed, other terms were added, because they were also used significantly by relevant articles; this was particularly important because there was no consensus regarding the name for the pandemic at its inception. Hence, regarding the pandemic, alternative terms included “Covid-19,” “Sars-Cov-2,” “Pandemic,” and “Coronavirus.” Similarly, regarding consumer behavior, “marketing,” “purchasing,” “shopping,” and “buying” were the alternative terms.

The search process involved reading the titles and abstracts of the outputs generated for an initial and main debugging. A second purification was then conducted. Among the biggest search challenges was that, although some articles addressed consumer behavior and included “Covid” or its synonyms in their titles, keywords, and abstracts, as well as their topic incorporation, they were unclear. The situation is attributed to a temporal coincidence with the COVID-19 crisis, rather than a deliberate intention of studying its effects on consumer behavior. From the start of the study to its culmination on January 5, 2021, 347 articles were reviewed, of which 70 relevant articles were selected after satisfying the inclusion and search criteria.

3.4 Method describing and systematizing the literature

The study employed various bibliometric and literature systematization techniques, to describe the characteristics and interrelationships of the 70 articles and systematize their content. Bibliometric techniques estimated the main descriptive statistics of the relevant body of knowledge. Further, a visual analysis of co-occurrence was performed.

The study used content analyses of the generated knowledge and findings to systematize the literature ( Kaur et al., 2021 ), seeking a knowledge organization structure. The search focused on identifying a widely accepted model of consumer behavior. Thus, the selected model was the input-process-output model of Schiffman and Wisenblit (2015) , modified by Cruz-Cárdenas and Arévalo-Chávez (2018) to apply to literature reviews on consumer behavior topics. This model is employed in empirical research (e.g., Ting et al., 2019 ).

Fig. 2 presents the generic model. The left of the model presents the external influences or stimuli, processed and interpreted as per the personal and psychological characteristics of the consumer at the center of the model. The consumer also follows a decision-making process. Finally, the right of the model yields the results or outputs: the purchase and post-purchase behaviors. Furthermore, this study incorporates arrows connecting macro-environmental to micro-environmental forces, marketing strategies, and the consumer. It highlights that the macro-environment spans the entire model ( Kotler and Keller, 2016 ).

Generic model of consumer behavior. Adapted from Schiffman and Wisenblit (2015) and Cruz-Cárdenas and Arévalo-Chávez (2018) .

4. Descriptive and bibliometric analysis

4.1 descriptive analysis of relevant articles.

Table A.1 presents the 70 relevant articles, among which 57 were published in 2020; 12, 2021; and one, in press. Fig. 3 shows the number of articles per their methodology. Most articles (58 articles or 82.9%) employ quantitative empirical approximations, followed by studies with a theoretical approach (five articles or 7.1%). Notably, few studies employed qualitative or mixed methods (5.7% and 4.3%, respectively).

Number of articles according to their methodology.

This marginal use is likely for the following reasons. First, societies and funders exert time constraints for fast and conclusive results. Second, there are many studies on consumer behavior and the adoption of technologies before the COVID-19 pandemic. Third, the rise in machine learning methods, particularly natural language processing, allows for processing significant textual social media data using artificial intelligence ( Géron, 2019 ).

Considering only the 65 empirical studies, Fig. 4 presents the main countries where data was collected. China has 15 articles (23.1%), followed by the US, with seven articles (10.8%), and Italy, five articles (7.7%). Next are India, Romania, the UK, and Vietnam, each with three articles (4.6%). Others attracted 15 articles (23.1), and 11 articles (16.9%) had several countries simultaneously as study settings, either because they deliberately chose several countries or studied social media. China's dominance as a study setting can be attributed to its status as the origin of the pandemic. However, it can also be attributed to China's rapid growth in the scientific field.

Number of empirical articles according to their study setting.

Table 2 presents the journals in which the articles were published. Most articles appeared in three major journals: Sustainability had seven articles (10%), and the International Journal of Environmental Research and Public Health and the Journal of Retailing and Consumer Services each had five articles (7.1%), respectively. Notably, several journals not traditionally linked to consumer studies or marketing are represented, probably because of the multidisciplinary character of consumer studies ( Schiffman and Wisenblit, 2015 ).

Journals in which reviewed articles were published.

While the selected articles examined various products, food was the main preference in 29 articles (41.4%). Other products, studied to a lesser extent, included personal hygiene items, hotels, and the banking sector. Further, the studies widely employed two theories: the theory of planned behavior (TPB) ( Ajzen, 1991 ) and the technology acceptance model (TAM) ( Davis, 1989 ).

TPB stems from psychology, and it asserts that attitude toward behavior (personal view on behavior), subjective norm (perceived social pressure to act), and perceived behavioral control (difficulty in acting) determine the intention of a person to act out a behavior. This behavioral intention then determines whether the behavior occurs ( Ajzen, 1991 ). TAM stems from Information Technology and draws from TPB; it indicates that a user's acceptance of new technology is determined by the perceived usefulness and ease of use ( Davis, 1989 ). TPB and TAM are general theories that allow for much flexibility in application. The two theories and their many variants are widely used in consumer behavior research and, particularly, cases of a new product, service, and technology acceptance ( Lin and Chang, 2011 ; Schmidthuber et al., 2020 ).

Considering the prevalence of TPB and TAM, and their variants in consumer studies prior to COVID-19 (particularly regarding technologies) coupled with the massive popularity of technologies during the pandemic ( Baicu et al., 2020 : Sheth, 2020 ), the dominance of the two theories in this study is not surprising. Furthermore, they also explain the popularity of quantitative methods in the selected studies, and by specifying a set of directional relationships, they allow for testing the proposed models via structural equation modeling ( Kline, 2016 ). The studies reviewed largely model consumer purchasing behaviors in technological environments and include fear or concern about COVID-19 as an additional variable, either in an exogenous or moderating variable role.

4.2 Analysis of the co-occurrence

The study employed co-occurrence analysis to establish the topics of interest in the set of articles on COVID-19 and consumer behavior. The analysis was performed in two ways to obtain more reliable results: keyword-based and title- and abstract-based.

First, we sought to identify the clusters formed based on the co-occurrence of keywords in the set of articles ( Singh et al., 2020 ). We employed VOSviewer 1.6.15 ( VanEck and Waltman, 2010 ) for this analysis. VOSviewer suggests, by default, a minimum number of five occurrences for a term to be considered. However, we set this number to three, given the relatively small number of articles. Generic terms like “article” and “study” were removed during the data cleanup. Additionally, similar terms were grouped into a single term ( van Eck and Waltman, 2010 , 2020 ), such as “Covid-19,” “Covid,” and “pandemic.” Fig. 5 shows the obtained clusters. The nodes represent keywords or concepts, while their size corresponds with their frequency ( van Eck and Waltman, 2010 , 2020 ). VOSviewer represents each cluster of keywords or concepts with a different color.

Co-occurrence network of articles based on keywords.

Cluster 1 (yellow) has “consumer behavior” as a prominent node and groups together other keywords such as “social distance,” “social media,” and “electronic commerce.” Thus, the cluster is related to purchasing behavior during the COVID-19 pandemic, which is strongly marked by technology use. Cluster 2 (green) has the term “COVID-19″ as its central node. It gathers terms such as “public health,” “food waste,” “food consumption,” “sustainability,” and “panic buying.” Hence, this cluster regards the consumption and handling of food during the COVID-19 pandemic. Cluster 3 (blue) has no central node. However, “fear,” “decision making,” and “purchasing” suggest a cluster focused on the purchase decision process. Finally, Cluster 4 (red), while without a prominent node, is the most prevalent. Terms such as “materialism,” “adult,” “attitude,” and “psychology,” “government,” and “economics” suggest that this cluster is mainly about macro, micro, and internal influences on the consumer.

Further, to allow for greater context richness, the second analysis was based on the titles and abstracts of selected articles ( VanEck and Waltman, 2010 ). Similar to the procedure based on keywords and with the same criteria, the minimum number of occurrences of words was set to three. The data was also cleaned by elimination or grouping ( VanEck and Waltman, 2010 ). For example, generic or irrelevant words, such as “article,” “item,” “author,” and “study,” were eliminated. However, similar terms were grouped together, as in the case of “covid,” “covid-19,” and “pandemic.” Fig. 6 shows the results of the co-occurrence analysis based on titles and abstracts.

Co-occurrence network of articles based on titles and abstracts.

The analysis generated four clusters. Cluster 1 (red) had “consumer behavior” as a prominent node and included other terms like “risk perception,” “threat,” “panic buying,” “impulsive buying,” and “China.” Thus, this cluster is related to consumer panic buying. Cluster 2 (green) had as prominent nodes “service,” “emergency,” “purchasing,” and technology-related actions, such as “online shopping,” “e-commerce,” and “internet.” Hence, it regards consumer behavior and the use of technology in purchases. Cluster 3 (blue) featured “food” as a prominent node and included other terms like “stockpiling,” “covid lockdown,” “covid outbreak,” and “policymaker.” Therefore, this cluster focused on consumer behavior in the purchase and handling of food under lockdown conditions. Cluster 4 (yellow) did not have particularly prominent nodes. It included customer,” “infection,” “policy,” “home,” “uncertainty,” “business,” and “reduction,” showing that this cluster refers to the consumer subject to macro, micro, and internal influences.

The analysis of co-occurrence of keywords is similar to that of titles and abstracts in the dominance of the reviewed studies on Covid-19 and consumer behavior, thus increasing the confidence in the results. Accordingly, three fundamental areas can be identified: consumer behavior and technology use; purchasing and handling basic necessities, particularly food; and consumer subject to internal and external (micro and macro) forces. A possible fourth area may induce a discrepancy, putting the keyword analysis emphasis on the decision-making process and the analysis of titles and abstracts in panic purchases.

5. Systematization of the relevant literature

This section presents the analysis and systematization of the 70 relevant studies. The authors used content analysis techniques to identify the main findings from the literature ( Kaur et al., 2021 ). The relevant content is organized using the structure of the consumer behavior model in Fig. 2 .

5.1 Macro-environmental factors

Macro-environmental factors affect the entire analytical micro-environment ( Kotler and Keller, 2016 ). In this study, the micro-environment is built around the consumer, the center of the analysis. The consumer micro-environment is formed by organizations and groups of people close to the consumer (e.g., companies, the media, family, and friends).

Regarding COVID-19 and consumer behavior, five macro forces are fundamental: the COVID-19 pandemic and the technological, political-legal, economic, and socio-cultural environments. High importance is attached to COVID-19, the technological environment, and the politico-legal environment. Various studies indicate how the COVID-19 and available technology confluence has induced consumers to massively and rapidly adopt technologies and increase their consumption of highly digital business formats ( Baicu et al., 2020 : Sheth, 2020 ). Specifically, e-commerce and business platform formats solved possible shortage problems and allowed consumers to accumulate products ( Hao et al., 2020 ; Pillai et al., 2020 ). Further, the technology allowed social lives to thrive amidst the pandemic, reflecting the increased use of social media platforms ( Pillai et al., 2020 ).

The political-legal environment is strongly intertwined with economic performance. Significant legal regulations by many governments were enforced during quarantines, lockdowns, social distancing, and educational service closure ( Yoo and Managi, 2020 ). However, not all governments resorted to lockdown measures. Regardless, economies fell in many areas because of consumer decisions ( Sheridan et al., 2020 ). However, food and hygiene item purchases increased. In non-lockdown (lockdown) countries, consumers were guided by caution (anxiety and fear were) ( Anastasiadou et al., 2020 ; Prentice et al., 2020 ).

Another very important aspect derived from the political-legal environment is trust in government institutions. Increased confidence in governments and their actions made consumers less likely to experience fear of food shortages and engage in panic buying ( Dammeyer, 2020 ; Jeżewska-Zychowicz et al., 2020 ). Effective public announcements moderated the effects of negative feelings, such as anxiety and a sense of losing control in terms of panic buying ( Barnes et al., 2021 ).

A diagnosis of the state of knowledge on macro-environmental factors allows for seeing a significant amount of research on political-legal and technological factors. However, the COVID-19 crisis is dynamic. Currently, many governments have halted lockdown measures, betting more on social distancing as a new mass vaccination phase emerges, which is worthy of exploration. Further, few studies address cultural issues during the COVID-19 crisis, even though culture is another determining force in consumer behavior.

5.2 Micro-environmental factors

As noted, the political-legal macro-environment of the COVID-19 pandemic is marked by lockdown and social distancing measures, while the digital transformation process marks the technological macro-environment. A logical consequence of their interaction is that the micro-environment (family, friends, acquaintances, society, the media, and companies) interacts with consumers through technology and digital media. Section 5.3 will discuss consumer interaction with businesses and companies.

During the COVID-19 crisis, consumers use information as a valuable factor in decision-making, as they actively or passively seek it. Social media is a common source of information. Popular topics regard food acquisition and storage, health issues, social distancing, and economic issues ( Laguna et al., 2020 ). However, social media also induces panic buying, especially during lockdowns. Advice from associates, product shortage perceptions, the COVID-19 spread, official announcements, and global news inspired this behavior ( Ahmend et al., 2020 ; Grashuis et al., 2020 ; (Jeżewska-Zychowicz et al., 2020) ; Naeem, 2021a ). Further, the news, social media, and associates also influence technology use in purchases on company pages, platforms, or apps ( Koch et al., 2020 ; Troise et al., 2021 ).

Therefore, despite contributing to panic buying, the mainstream news media and social media have also curbed the spread of COVID-19 ( Liu et al., 2021 ). The extensive knowledge on the micro-environmental effects on consumer behavior was generated primarily due to previous non-relevant studies that focused on social media; they created a solid base of departure.

5.3 Marketing strategies and influences

Marketing influences are in the consumer's micro-environment. They are vital, because they are tools that companies can design and control. Thus, consumer behavior models usually consider them separately from other influences, such as those discussed in the preceding section. The main marketing tool is the product or service. Others are prices, distribution, and communication strategies.

Two key elements of marketing strategies during the pandemic are reducing various risks and increasing benefits perceived by the consumer. Two central risks marketing strategies must address are the risks of coinfection and conducting online transactions. Further, the reviewed studies address the forms of action regarding the two types of risks. Thus, while the perceived COVID-19 risk increases the probability of online purchases, the perceived risk of online purchases moderates this relationship ( Gao et al., 2020 ).

Accordingly, using technology to digitize processes or products, and reduce physical contact with employees or other consumers, has encouraged consumer purchases during the COVID-19 pandemic. For example, technology that allows consumers to make reservations via smartphones or kiosks reduces the perceived health risk, thereby increasing the probability of hotel reservations ( Shin and Kang, 2020 ). Moreover, state-of-the-art cleaning technology moderates the negative effect of staff interaction on service use intentions ( Shin and Kang, 2020 ). Thus, technology guarantees cleanliness and minimal contact for the consumer. Further, the perceived risk of online transactions involves the possible misuse of personal information and financial fraud ( Tran, 2021 ). Marketing strategies to reduce this risk have focused on building trust and image ( Lv et al., 2020 ; Troise et al., 2021 ). Regarding the strategy duration, other recommended marketing strategies for e-commerce sites and platforms with less renown are increasing profits or reducing prices ( Lv et al., 2020 ; Tran, 2021 ).

During the lockdowns in most countries, consumer demand centered on food products, personal hygiene, and disinfection. Thus, implementing or increasing promotions of non-priority items is a recommended strategy ( Anastasiadou et al., 2020 ). Finally, regarding small businesses that use technology less intensively, the speed of adaptation and digital transformation are vital, even at basic levels. Many small businesses have survived by adopting elementary digital transformation strategies in the form of a mix of social media sales and home delivery services ( Butu et al., 2020 ).

Hence, although there are interesting results, the transcendental importance of studies on marketing strategies within the framework of consumer studies deserves more research. Further, since the pandemic is dynamic, companies must adapt their strategies constantly. Notably, few studies employ case studies or experimental methodologies, which are appropriate for studying the effects of marketing strategies.

5.4 Personal and psychological characteristics and decision-making

Most of the reviewed studies stemmed from this area. The personal characteristics of consumers (e.g., age, gender, income, and educational level) and their psychological characteristics (e.g., motivation, perception, and attitudes) determine how they interpret stimuli ( Schiffman and Wisenblit, 2015 ).

For instance, many studies address gender. There is no consensus about which gender makes the most panic purchases. A study carried from Brazil reports that men tend to make the most panic purchases ( Lins and Aquino, 2020 ), while a study in China ( Wang et al., 2020a ) attributes this behavior to women. However, another study in several European countries found gender differences irrelevant in the tendency to make extra purchases ( Dammeyer, 2020 ). The inconsistency may be attributable to cultural issues; however, the methodology may also have a bearing on the conflicting results. For example, while the study by Lins and Aquino (2020) asked respondents about purchasing products in general, Wang et al. (2020a) focused on food, and Dammeyer (2020) on food, medicine, and hygiene items. The same discrepancy in gender issues and panic purchases extends to the age variable. Some studies found that age is negatively related to the tendency to panic buy ( Lins and Aquino, 2020 ), while other studies found no relationship at all (e.g., Dammeyer, 2020 ).

Many studies also examine the pandemic-induced negative psychological states and feelings. The perceived risk and information overload regarding COVID-19, led to sadness, anxiety, and cognitive dissonance ( Song et al., 2020b ). The perceived severity of the pandemic leads to self-isolation ( Laato et al., 2020 ). The negative psychological states that the consumer experiences, are associated with hoarding behavior. Excessive concern regarding health leads to excessive purchasing and stockpiling of food and hygiene items ( Laato et al., 2020 ). While negative emotions encourage excessive purchases, particularly the purchasing of necessities, they also discourage them from consuming services that involve contact. For example, the fear of contracting COVID-19 has been central to avoiding air transport during the pandemic ( Lamb et al., 2020 ).

Consumer personality traits were also critical to understanding consumer behavior during the COVID-19 crisis. Extraversion (conscientiousness) and neuroticism (openness to experience) were positively (negatively) associated with extra purchases ( Dammeyer, 2020 ). Another personality trait, such as agreeableness (sympathetic or considerate), led to the renunciation of consumption. Consumers with high scores on this trait gave up consumption that could negatively affect third parties ( Lamb et al., 2020 ).

The pandemic has also encouraged favorable attitudes among consumers, be they pro-environmental or pro-health attitudes. The fear of COVID-19 and the uncertainty it brings has a positive effect on people's pro-environmental attitudes, which, in turn, increase trust in green brands ( Jian et al., 2020 ). However, while consumers gave less importance to the nutritional value of food during the first months of the crisis ( Ellison et al., 2021 ), there was an increase in health awareness in later months ( Čvirik, 2020 ).

Despite great interest in consumers’ personal and psychological processes, the purchase decision-making process garnered less attention. Studies note three types of decision-making processes: impulse (e.g., Ahmed et al., 2020 ; Islam et al., 2020 ), panic (e.g., Prentice et al., 2020 ), and rational ( Wang and Hao, 2020 ) purchases.

In summary, consumer behavior, as it relates to consumers’ personal and psychological characteristics, has been widely studied, especially in its relationship with the first phases of COVID-19, characterized by lockdown and social distancing. The broad base of prior knowledge on consumer psychology and the adoption and use of technologies facilitates such studies. Here too, given the dynamic pandemic and its entry into new stages involving vaccination and social distancing, future studies must extend the discussion on personal and psychological processes. In addition, more research should be conducted on purchase decision-making processes during the COVID-19 crisis.

5.5 Purchasing behaviors

In consumer behavior models, purchasing behavior is the output of the model. This output is generated by selecting products and places or points of purchase. During the pandemic, these two behaviors were central to consumers’ strategies to ensure their own well-being.

The imposition lockdowns led to an increase in the purchase of food, beverages, hygiene items, and medicines, inducing frequent stockpiling. This behavior occurred before and during the measures and has been widely confirmed worldwide (e.g., Antonides and van Leeuwen, 2020 ; Prentice et al., 2020 ; Seiler, 2020 ;). After the lockdown and the transition to social distancing, moderate stockpiling may be expected ( Anastasiadou et al., 2020 ). Meanwhile, the consumption of goods and services in industries such as entertainment, dining, travel, and tourism decreased ( Antonides and van Leeuwen, 2020 ; Ellison et al., 2021 ; Seiler, 2020 ; Skare et al., 2021 ). Another essential aspect is the selection of the purchase method. Various purchase methods were implemented to reduce the risk of infection, among which consumers favored online purchases while making changes in their selection of physical retailers.

The lockdown and later, social distancing, inspired many consumers to rapidly adopt purchasing behaviors mediated by technology (e.g., online shopping) ( Butu et al., 2020 ), creating an “online awareness” among populations ( Zwanka and Buff, 2020 ). A digital means of purchase was extended to categories which did not have a strong online presence previously. Thus, online purchases of food, beverages, and cleaning supplies grew ( Antoides and van Leeuwen, 2020 ; Ellison et al., 2020; Hassen et al., 2020 ; Li et al., 2020b ; Wang et al., 2020b ). However, there was also an increase in the use of technology for entertainment. For example, there has been an increase in users and streaming hours on services such as Netflix and Spotify ( Madnani et al., 2020 ). Another change in consumer purchasing behavior regarded the physical point of sale. This change occurred as consumers aimed to decrease the number of trips they made to physical stores (purchase frequency) ( Laguna et al., 2020 ; Principato et al., 2020 , in press; Wang et al., 2020a ). In some countries and cities, consumers stopped buying from large retailers and places that could be crowded, preferring small local retailers instead ( Li et al., 2020b ).

Hence, there is a solid global consolidation of technology in purchasing (i.e., online shopping) and the strengthening of small local retailers. Given the dynamic nature of the COVID-19 crisis, future studies can evaluate the changes in the next stages of the pandemic.

5.6 Post-purchase behavior

Another key behavior is disposal, of which results are very interesting. During the lockdown, there is less food waste, more likely for future supply than ecological reasons ( Amicarelli and Bux, 2021 ; Jribi et al., 2020 ). However, dire health precautions increased the usage of disposable protective items, and more electronic commerce transactions increased waste created by packaging material ( Vanapalli et al., 2021 ). Thus, from a social and environmental perspective, the effects of the pandemic on product waste are mixed.

Future studies can examine product disposition and the new stages of the COVID-19 crisis. Moreover, consumer satisfaction with purchases has garnered less attention in the literature. Fig. 7 presents the model of consumer behavior during the COVID-19 crisis, summarizing the systematization of the literature.

Model of consumer behavior during the COVID-19 crisis.

5.7 Consumer behavior model under COVID-19: the near future

This subsection seeks to use the model ( Figs. 2 and ​ and7) 7 ) to anticipate consumer behaviors, given the ongoing, dynamic development of the pandemic ( WHO, 2021b ). Accordingly, the crisis thus far has induced intense consumer learning, particularly in the use of technologies (personal and psychological factors). Moreover, although technologies can satisfy both hedonic and utilitarian needs ( Cruz-Cárdenas et al., 2021 ), some consumer needs remain unsatisfied, particularly social needs (personal and psychological factors) ( Sheth, 2020 ). However, public vaccination campaigns (macro-environmental factor) and their protective effects on the population can reduce people's fear and avoidance behavior regarding certain products and services (personal and psychological factors). Further, consumers can have a greater range of consumption options (decision-making process), given their decreased fear, and due to the relaxation of restrictions on mobility and the congregation of people (macro-environmental factor). However, the trajectory of the COVID-19 pandemic (macro-environmental factor) will not be a linear process, given the appearance of new waves of infections and strains ( WHO, 2021b ).

Therefore, the new consumer behavior (output or results) will not embark on a gradual return to pre-pandemic conditions. Rather, consumer learning about technologies, attenuated avoidance behavior, and unsatisfied needs mark consumer practices that tend to combine pre-COVID-19 behaviors (some intensified by the level of unsatisfied needs) with new technology-based behaviors (e.g., use of electronic banking, e-learning, e-commerce, and social media). However, this combination of old and new consumer behaviors will likely be dynamic (in varying proportions) and creative, as consumers will have to go through new stages of the pandemic marked by uncertainty.

6. Discussion, implications, and limitations

6.1 the covid-19 pandemic versus other disruptive events: differences and similarities in their nature and consumer behavior.

The COVID-19 pandemic in the context of disruptive events affecting humanity shares traits with other disruptive events and has unique characteristics. Like any disruptive event, it has profoundly impacted societies ( Dahlhamer and Tierney, 1998 ). Among its unique characteristics are its truly global scope and occurrence within the context of the “digital transformation” technological advancement ( Abdel-Basset et al., 2021 ).

Regarding consumer behavior, comparing the study findings to behaviors observed in other disruptive events yield interesting conclusions. Impulsive and panic buying seems to be common to all disruptive events. Therapeutic purchases seem to be more linked to natural disasters, where physical possessions suffer damages. The avoidance behavior of certain products and services appears to be more linked to terrorism and pandemics. However, despite these similarities, the role of technology in shopping has induced a unique consumer behavior under COVID-19. Indeed, technology has been transversal to the different consumer behaviors under COVID-19.

Consumer behavior and COVID-19 studies are characterized by three thematic areas: consumer behavior and technology use; purchase and handling of essential, hygiene, and protective products; and internal and external influences on consumers. Notably, the current pandemic is an ongoing event that follows a non-linear trajectory (WHO, 221b). Hence, the study priorities will surely change, marked by the new stages of the pandemic. For example, in light of the vaccination campaigns, the interest of future studies in the purchase and handling of basic necessities and protection products will decline. Further, given the decreased avoidance behavior, interest in the study of fun and leisure behaviors will increase. However, the use of technologies in consumption will remain at a high profile throughout the pandemic.

6.2 The nature of consumer behavior studies under the COVID-19 pandemic

Studies examining consumer behavior under the COVID-19 pandemic exhibit unique characteristics. Prior studies on consumer behavior and other disruptive events had a significant presence of qualitative studies, given their ability to explore and thoroughly understand how certain phenomena profoundly affect people's lives ( Delorme et al., 2004 ). However, in studies on consumer behavior and COVID-19, their presence is modest, where quantitative studies dominate.

Various factors can explain the preeminence of quantitative studies; however, this subsection addresses the key factor of technology. Specifically, the confluence of intensive use of technologies by consumers during COVID-19, and the body of knowledge accumulated before the pandemic on consumer behavior and the use and adoption of technologies. Hence, this body of knowledge created a solid foundation for quantitatively oriented consumer studies. However, the existing knowledge about consumer behavior and disruptive events did not provide a solid foundation since its extension is rather modest. ( Laato et al., 2020 ).

6.3 Reassessment of pre-COVID-19 knowledge on key topics of consumer behavior and recommendation for future studies

A crucial consequence of the COVID-19 pandemic is the massive rise in the learning and use of technologies ( Baicu et al., 2020 : Sheth, 2020 ), which is unprecedented considering the global scale of the pandemic and its sustained duration. This massive and extensive learning of the use of technologies will have consequences in the validity of knowledge developed before the pandemic in key consumer behavior topics and technology use. Although there are various topics, this subsection will focus on two: Consumer segments in the use of technologies and the digital divide.

Before the pandemic, many studies in different countries apply various scales, including the technology readiness index scale ( Parasuraman and Colby, 2015 ), to gage consumer segments in technology markets. The studies yielded strong results on consumer segments and their sizes. Thus, considering the rapid adoption of technologies during the COVID-19 pandemic, an obvious question is how current this knowledge is. Hence, future studies can determine how the COVID-19 pandemic reconfigured consumer segments in the use of technologies, how they changed regarding their importance, and whether a revision of existing measuring instruments (scales) is necessary.

Moreover, the digital divide (i.e., the gaps in the access and use of technologies between different societal sectors) has also been extensively studied before COVID-19. For example, older and lower-income people used technology-based services to a much lesser degree ( Cruz-Cárdenas et al., 2019 ). The information is useful to design profitable and social marketing strategies. However, the pandemic-induced massive learning of technologies may leave out a part of society. Ultimately, future studies can focus on determining what happened to the digital gaps between social groups as an effect of the pandemic.

6.4 COVID-19 and the future: recommendations for practice and future studies

The review and systematization of the literature leave important recommendations for firms and organizations. Primarily, firms must incorporate rapid digital transformation in their processes. For example, although social media was already significant in societies before the COVID-19 crisis, its role has now been enhanced ( Naeem, 2021b ). The most diverse companies can find a profitable channel of communication and promotion in social networks. Smaller companies can utilize social media to sell products coupled with home delivery ( Butu et al., 2020 ), thereby beginning their digital transformation process. For larger companies, digital social networks can help build communities around their brands, especially during times of uncertainty and increased user traffic.

Second, companies and businesses must consider how to address the risk perceived by consumers. This risk has been articulated as two fundamental types: the risks of infection, and fraud and misuse of data in e-commerce transactions. The perceived risk of infection is expected to diminish with massive vaccination campaigns ( Shin and Kang, 2020 ). However, companies can address the perceived risk of fraud in online transactions via security protocols, incorporation and combination of technologies, and communication and promotion tools. In the latter, the best strategy will be to use the business image to generate consumer confidence ( Troise et al., 2021 ; Lv et al., 2020 ). Further, for an undecided consumer regarding online transactions, promotions aimed at reducing prices and increasing benefits proved useful during the pandemic ( Lv et al., 2020 ; Tran, 2021 ).

Finally, given the non-linear and uncertain trajectory of the pandemic, consumer behavior across the stages of the pandemic is a dynamic combination of old and new behaviors, highlighting the necessity for companies to incorporate flexibility and agility into their culture and operations, and fully align with digital transformation initiatives.

6.5 Limitations

This study has some limitations. Though the article search was performed in the Scopus database, which presents a good balance between quality and coverage ( Singh et al., 2020 ), several articles were not captured in the Scopus index, which could indicate that their quality is heterogeneous. However, this decision was necessary to systematize the literature in a reasonable amount of time.

Author statement

Jorge Cruz-Cárdenas: Writing

CRediT authorship contribution statement

Jorge Cruz-Cárdenas: Conceptualization, Methodology, Formal analysis, Writing – review & editing. Ekaterina Zabelina: Conceptualization, Methodology, Formal analysis, Visualization. Jorge Guadalupe-Lanas: Resources, Investigation. Andrés Palacio-Fierro: Resources, Investigation. Carlos Ramos-Galarza: Methodology, Formal analysis, Visualization.

Biographies

Jorge Cruz-Cárdenas is a senior lecturer at the School of Administrative and Economic Sciences and a researcher at the ESTec Research Center, both at Universidad Tecnológica Indoamérica, Ecuador. He holds a Ph.D. in Economics and Business Management from the University of Alcalá, Spain. His-main research area is consumer behavior in technological environments.

Ekaterina Zabelina is an associate professor at the Department of Psychology of Chelyabinsk State University, Russia. Her main research areas include economic psychology, positive psychology, organizational psychology, and behavioral Science.

Jorge Guadalupe-Lanas holds a Ph.D. in Economics from the University of Picardie Jules Vernes D'amiens in France. He currently serves as Director of ESTec Research Center at Universidad Tecnológica Indoamérica, Ecuador. His-fields of interest include macroeconomic theory, econometric modeling, and experimental economics.

Andrés Palacio-Fierro is a senior lecturer at the School of Administrative and Economic Sciences of Universidad Tecnológica Indoamérica, Ecuador, and a researcher at the ESTec Research Center. He is currently pursuing his doctoral studies at the Camilo José Cela University in Spain. His-research interests are related to topics of consumer behavior.

Carlos Ramos-Galarza is a senior lecturer at the School of Psychology of the Pontificia Universidad Católica del Ecuador and a researcher at Mist Research Center. He holds a Ph.D. from the University of Concepción, Chile. His-main research topics revolve around psychometry and human-technology interaction.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.techfore.2021.121179 .

Appendix: Articles included in the review according to the study setting

[I nsert Table A.1 here ]

Reviewed articles.

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A Brief Literature Review on Consumer Buying Behaviour

Introduction

It is worth noting that consumer buying behaviour is studied as a part of the marketing and its main objective it to learn the way how the individuals, groups or organizations choose, buy use and dispose the goods and the factors such as their previous experience, taste, price and branding on which the consumers base their purchasing decisions (Kotler and Keller, 2012).

One of such studies of consumer buying behaviour has been conducted by Acebron et al (2000). The aim of the study was to analyze the impact of previous experience on buying behaviour of fresh foods, particularly mussels. In their studies the authors used structural equation model in order to identify the relationship between the habits and previous experience on the consumer buying decision. Their findings show that personal habits and previous experience on of the consumers have a direct impact on the consumers’ purchase decision in the example of purchasing fresh mussels. They also found that the image of the product has a crucial impact on the purchasing decision of the consumer and further recommended that the product image should continuously be improved in order to encourage the consumers towards purchasing.

Another study conducted by Variawa (2010) analyzed the influence of packaging on consumer decision making process for Fast Moving Consumer Goods. The aim of the research was to analyze the impact of packaging for decision making processes of low-income consumers in retail shopping. A survey method has been used in order to reach the research objectives. In a survey conducted in Star Hyper in the town of Canterville 250 respondents participated. The findings of the research indicate that low-income consumers have more preferences towards premium packaging as this can also be re-used after the product has been consumed. Although the findings indicate that there is a weak relationship between the product packaging and brand experience. However, it has been proven by the findings of the research that low-income consumers have greater brand experience from the purchase of ‘premium’ products when compared to their experience from purchasing ‘cheap’ brand products.

Lee (2005) carried out study to learn the five stages of consumer decision making process in the example of China. The researcher focuses on the facts that affect the consumer decision making process on purchasing imported health food products, in particular demographic effects such as gender, education, income and marital status. The author employed questionnaire method in order to reach the objectives of the research. Analysis of five stages of consumer decision making process indicate that impact of family members on the consumer decision making process of purchasing imported health food products was significant.

The author further explains this by the fact Chinese tradition of taking care of young and old family members have long been developed and marriage is considered to be extremely important in Chinese tradition. This reflects in the findings of the study that the purchase of imported health food products made by a person for the people outside the family is declined significantly by both male and female Chinese after they get married.

Five Stages Model of consumer decision making process has also been studied by a number of other researchers. Although different researchers offer various tendencies towards the definitions of five stages, all of them have common views as they describe the stages in similar ways. One of the common models of consumer decision making process has been offered by Blackwell et al (2006). According to him, the five stages of consumer decision making process are followings: problem/need recognition, information search, evaluation of alternatives, purchase decision made and post-purchase evaluation.

Each stage is then defined by a number of researchers varying slightly but leading to a common view about what each stage involves. For example, according to Bruner (1993) first stage, need recognition occurs when an individual recognizes the difference between what they have and what they want/need to have. This view is also supported by Neal and Questel (2006) stating that need recognition occurs due to several factors and circumstances such as personal, professional and lifestyle which in turn lead to formation of idea of purchasing.

In the next stage, consumer searches information related to desired product or service (Schiffman and Kanuk, 2007). Information search process can be internal and external. While internal search refers to the process where consumers rely on their personal experiences and believes, external search involves wide search of information which includes addressing the media and advertising or feedbacks from other people (Rose and Samouel, 2009).

Once the relevant information about the product or service is obtained the next stage involves analyzing the alternatives. Kotler and Keller (2005) consider this stage as one of the important stages as the consumer considers all the types and alternatives taking into account the factors such as size, quality and also price.

Backhaus et al (2007) suggested that purchase decision is one of the important stages as this stage refers to occurrence of transaction. In other words, once the consumer recognized the need, searched for relevant information and considered the alternatives he/she makes decision whether or not to make the decision. Purchasing decision can further be divided into planned purchase, partially purchase or impulse purchase as stated by Kacen (2002) which will be discussed further in detail in the next chapters.

Finally, post-purchase decision involves experience of the consumer about their purchase. Although the importance of this stage is not highlighted by many authors Neal et al (2004) argues that this is perhaps one of the most important stages in the consumer decision making process as it directly affects the consumers’ purchases of the same product or service from the same supplier in the future.

The most noteworthy writers that serve as academic advocates of The Five Stage Model of consumer decision making include Tyagi (2004), Kahle and Close (2006) Blackwell et al. (2006), and others.

It is important to note that The Five Stage Model is not the only model related to consumer decision-making, and there are also a range of competing models that include Stimulus-Organism-Response Model of Decision Making developed by Hebb in 1950’s, Prescriptive Cognitive Models, The Theory of Trying (Bagozzi and Warsaw, 1990), Model of Goal Directed Behaviour (Perugini and Bagozzi, 2001) and others. All of these models are analysed in great detail in Literature Review chapter of this work.

Factors Impacting Consumer Buyer Behaviour

It has been established that the consumer buying behaviour is the outcome of the needs and wants of the consumer and they purchase to satisfy these needs and wants. Although it sounds simple and clear, these needs can be various depending on the personal factors such as age, psychology and personality. Also there are some other external factors which are broad and beyond the control of the consumer.

A number of researches have been carried out by academics and scholars on identifying and analyzing those factors affecting the consumers’ buying behaviour and as a result, various types of factors have been identified. These factors have been classified into different types and categories in different ways by different authors. For instance, Wiedermann et al (2007) classified them into internal and external factor. On the other hand, Winer (2009) divided them into social, personal and psychological factors. Despite the fact that they have been classified into different groups by different authors they are similar in scope and purpose (Rao, 2007).

There is a wide range of factors that can affect consumer behaviour in different ways. These factors are divided by Hoyer et al. (2012) into four broad categories: situational, personal, social and cultural factors.

Situational factors impacting consumer behaviour may include location, environment, timing and even weather conditions (Hoyer et al., 2012). In order to benefit from situational factors major retailers attempt to construct environment and situations in stores that motivate perspective customers to make purchase decision. Range of available tools to achieve such an outcome include playing relaxing music in stores, producing refreshing smells in stores and placing bread and milk products in supermarkets towards the opposite end of stores to facilitate movement of customers throughout the store to make additional purchases etc.

The temporary nature of situational factors is rightly stressed by Batra and Kazmi (2008).

Personal factors, on the other hand, include taste preferences, personal financial circumstances and related factors. The impact of personal factors on consumer decision-making is usually addressed by businesses during market segmentation, targeting and positioning practices by grouping individuals on the basis of their personal circumstances along with other criteria, and developing products and services that accommodate these circumstances in the most effective manner.

According to Hoyer et al. (2012) social factors impacting consumer behaviour arise as a result of interactions of perspective consumers with others in various levels and circumstances. Targeting members of society perceived as opinion leaders usually proves effective strategy when marketing products and services due to the potential of opinion leaders to influence behaviour of other members of society as consumers.

Lastly, cultural factors affecting consumer behaviour are related to cross-cultural differences amongst consumers on local and global scales. Culture can be defined as “the ideas, customs, and social behaviour of a particular people or society” (Oxford Dictionaries, 2015) and the tendency of globalisation has made it compulsory for cross-cultural differences amongst consumers to be taken into account when formulating and communicating marketing messages.

Marketing mix and consumer behaviour

Marketing mix or 4Ps of marketing is one of the major concepts in the field of marketing and each individual element of marketing mix can be adopted as an instrument in order to affect consumer behaviour.

Importance of the marketing mix can be explained in a way that “successful marketing depends on customers being aware of the products or services on offer, finding them available in favourably judging that practitioners of the offering in terms of both price and performance” (Meldrum and McDonald, 2007, p.4).

Core elements of marketing mix consist of product, price, place and promotion. Marketing mix has been expanded to comprise additional 3Ps as processes, people and physical evidence.

Product element of marketing mix relates to products and services that are offered to customers to be purchased. Products can have three levels: core, actual and supporting products. For example, core product in relation to mobile phones can be explained as the possibility to communicate with other people in distance.  Actual product, on the other hand, relates to specific brand and model of a mobile phone, whereas augmented product may relate to product insurance and one-year warranty associated with the purchase of a mobile phone.

Price represents another critically important element of marketing and four major types of pricing strategies consist of economy, penetration, skimming, and premium pricing strategies (East et al., 2013).

Place element of marketing mix relates to point of distribution and sales of products and services. Advent of online sales channel has changed the role of place element of marketing mix to a considerable extent.

Promotion element of marketing mix refers to any combination of promotion mix integrating various elements of advertising, public relations, personal selling and sales promotions to varying extents (Kotler, 2012).

Processes, on the other hand, refer to business procedures and policies related to products and services. For example, integration of a greater range of payment systems such as PayPal, SAGE Pay and Visa in online sales procedures may have positive implications on the volume of sales by creating payment convenience to customers.

People element of marketing mix is primarily related to skills and competencies of the workforce responsible for customer service aspect of the business. Importance of people element of marketing mix in general, and providing personalised customer services in particular is greater today than ever before.

Physical evidence relates to visual tangible aspects of a brand and its products. For instance, for a large supermarket chain such as Sainsbury’s physical evidence is associated with design and layout of a store, quality of baskets and trolleys, layout of shelves within the store etc.

It can be forecasted that further intensification of competition in global markets and more intensive search of businesses for additional bases for competitive advantage may result in emergence of additional ‘P’s to compliment the framework of marketing mix in the future.

Bagozzi, R. & Warsaw, L. (1990) “Trying to Consumer” Journal of Consumer Research 17, (2) pp. 127 – 140.

Backhaus, K. Hillig, T. and Wilken, R. (2007) “Predicting purchase decision with different conjoint analysis methods”, International Journal of Market Research . 49(3). Pp. 341-364.

Batra, S.K. & Kazmi, S. (2008) “Consumer Behaviour” 2 nd edition, EXCEL Books

Blackwell, R., Miniard, P. and Engel, J. (2006) “Consumer behavior”, Mason: Thompson

Culture (2015) Oxford Dictionaries, Available at: http://www.oxforddictionaries.com/definition/english/culture

East, R., Wright, M. & Vanhuele, M. (2013) “Consumer Behaviour: Applications in Marketing” 2 nd edition, SAGE

Hoyer, W.D. & Macinnis, D.J. (2008) “Consumer Behaviour”, 5 th edition, Cengage Learning

Hoyer, W.D., Macinnis, D.J. & Pieters, R. (2012) “Consumer Behaviour” 6 th edition

Kacen. J. J. and Lee. J. A., (2002) “The influence of culture on consumer impulsive buying behaviour”, Journal of consumer psychology. 12(2), pp. 163-174.

Kahle L.R. and Close, A. (2006) “Consumer Behaviour Knowledge for Effective Sports and Event Marketing”, Taylor & Francis, New York, USA

Kotler, P.  (2012) “Kotler on Marketing” The Free Press

Meldrum, M. & McDonald, M. (2007) “Marketing in a Nutshell: Key Concepts for Non-Specialists” Butterworth-Heinemann

Neal, C., Quester, P. and Pettigrew, S. (2006) “Consumer Behaviour: Implications for Marketing Strategy” (5 th edition) Berkshire: McGraw-Hill

Perugini, M. & Bagozzi, R. (2001) “The role of desires and anticipated emotions in goal-directed behaviours: Broadening and deepening the theory of planned behaviour” British Journal of Social Psychology , 40, pp. 79-98.

Rao, K. (2007) “Services Marketing”, New Delhi: Pearson Education

Rose, S. and Samouel, P., (2009) “Internal psychological versus external market-driven determinants of the amount of consumer information search amongst online shopper”, Journal of Marketing Management . 25(1/2), pp. 171-190

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Stallworth, P. (2008) “Consumer behaviour and marketing strategic”, online, pp.9.

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Wiedmann, K., Hennigs, N. and Siebels, A. (2007) “Measuring Luxury consumer perception: A cross-culture framework”, Academy of Marketing Science review , 2007(7)

Winer, R. (2009), “New Communications Approaches in Marketing: Issues and Research Directions,” Journal of Interactive Marketing , 23 (2), 108–17

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Consumer Buying Behaviour – A Literature Review

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Realizing, and as well, analyzing the purchasing behaviour of consumer is the core constituent to provide efficient consumer satisfaction. A consumer is not only purchasing a produce, but he alone determines the victory of a firm. Hence for every successful firm, there exists a consumer support behind it. That support is technically called behavioural support and behind the support there is lot of theories to analyze and discuss the various concerns involving to consumer behaviour. Since World War II, taking into account the dire need of the public, the marketers started to market and encourage the produce what the consumers needed, instead of producing what the companies prefer. The concept of understanding the behaviour of consumer emerged in late 1940’s from which it has taken into so many dimensions. This is now known as “modern concepts of marketing”. At present, Consumer behaviour is commonly influenced by social, psychoanalytic and economical approaches. Each factor openly or not directly accounts to the characteristics of a buyer. Hence it is vital to be aware of the role of factors influencing the buying nature of consumer. The main iota of this research paper is to analyze the theoretical underpinnings and factors involved in consumer behaviour and its implications, in the light of developments crop upped in the recent past.

The Springer Series on Demographic Methods and Population Analysis

David Swanson

nhlakanipho sdwaba

Ria Agustriana

International Journal of Management Studies

Vishesh Singh

ACR Asia-Pacific Advances

Dr. Wided Batat

airah guerrero

Consumer behaviour can be defined as the decisions and actions taken by the consumers which influence their purchasing behaviour. Consumers' response to external stimulus either in form of marketing strategies or personal, economic and social attributes and their decision and buying behaviour is largely affected by this stimulus. It is thus, an inter-disciplinary social science that draws upon the disciplines of anthropology, psychology, sociology and marketing apart from economics. Therefore, many marketers often believe that a clear understanding of the buying behaviour of the consumers helps to analyse both past, present and future market scenario. The examination of the economic theories is helpful in identifying the consumer behaviour from the perspective of utility, prices and other economic aspects. But they do not reflect the perceptions or attitude of a consumer towards a product. So, to understand the consumer behaviour, a more holistic approach is required, that involves economic, non-economic theories and the decision making models. This paper is an attempt to understand the economic and psychological theories that influences the consumer behaviour. Further, an attempt has been made to correlate the consumer behaviour theories and consumer decision making models to explain the factors affecting the buying decisions of the consumers.

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Comprehending the consumer behavior toward sustainable apparel.

1. Introduction

2. materials and methods, 2.1. data sources, 2.2. selection process, inclusion and exclusion criteria.

• Explored the psychological, social, or environmental drivers of sustainable fashion consumption.
• Addressed technological advancements, such as AI, influencing consumer engagement with sustainable fashion.
• Analyzed behavioral factors in relation to eco-friendly and ethical fashion purchasing decisions.
• Ethical fashion choices, eco-consciousness, and sustainable clothing practices.
• The role of consumer education and awareness in promoting sustainable apparel consumption.
• Studies published between the years 2013 and 2023 to ensure recent developments in sustainable fashion and consumer behavior are considered.
• Studies published in English to maintain consistency in language comprehension and analysis.
• Research aimed primarily at business models, supply chain management, or organizational behavior without a specific focus on consumer behavior related to sustainable fashion.
• Research projects and studies focusing on general fashion trends without integrating sustainable fashion elements or consumer behavior analysis towards sustainability.
• Non-consumer-focused studies, such as material development, addressing manufacturing processes, supply chain operations, or retail logistics, unless they directly examine their impact on consumer sustainable behavior.

3. Review Findings and Discussion

3.1. theoretical analysis, research type analysis, 3.2. content analysis, 3.2.1. consumer attitude, 3.2.2. consumer purchase, 3.2.3. consumer knowledge, 3.2.4. consumer preference, 3.2.5. consumer influence, 3.2.6. overlapped themes, 4. conclusions and future recommendations, 5. study limitation, author contributions, conflicts of interest.

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Balasubramanian, M.; Sheykhmaleki, P. Comprehending the Consumer Behavior toward Sustainable Apparel. Sustainability 2024 , 16 , 8026. https://doi.org/10.3390/su16188026

Balasubramanian M, Sheykhmaleki P. Comprehending the Consumer Behavior toward Sustainable Apparel. Sustainability . 2024; 16(18):8026. https://doi.org/10.3390/su16188026

Balasubramanian, Mahendran, and Pariya Sheykhmaleki. 2024. "Comprehending the Consumer Behavior toward Sustainable Apparel" Sustainability 16, no. 18: 8026. https://doi.org/10.3390/su16188026

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• Published: 19 September 2024

Dataset on Electric Road Mobility: Historical and Evolution Scenarios until 2050

• Irvylle Cavalcante 1 ,
• Alberto Rodrigues da Silva 1 , 2 ,
• Matej Zajc 3 ,
• Igor Mendek 3 ,
• Lisa Calearo 4 ,
• Anna Malkova 4 ,
• Charalampos Ziras 4 ,
• Panagiotis Pediaditis 4 , 5 ,
• Konstantinos Michos 5 ,
• João Mateus 6 ,
• Samuel Matias 6 ,
• Miguel Brito 6 ,
• Alexis Lekidis 7 , 8 ,
• Cindy P. Guzman 1 ,
• Ana Rita Nunes 1 &
• Hugo Morais   ORCID: orcid.org/0000-0001-5906-4744 1 , 2  

Scientific Data volume  11 , Article number:  1019 ( 2024 ) Cite this article

Metrics details

• Energy economics
• Energy supply and demand

An increasing adoption of electric vehicles (EVs) is expected in the coming decades mainly due to the need to achieve carbon neutrality until 2050. However, predicting electric mobility’s future is challenging due to three main factors: technological advancements, regulatory policies, and consumer behaviour. The projections presented in this study are based on several scenarios driven mainly from reports published by public entities and consultants. It considers the evolution of electric road mobility by defined targets in the electrification of the transport sector. Therefore, the gathered data addresses different horizon times regarding EV penetration in the World, Europe, Portugal, Denmark, Greece, and Slovenia. Thus, an extensive literature review and estimating approach for EV forecast was conducted concerning EV markets, charging infrastructure, and electricity demand. Also, the dataset aims to provide a demand projection by 2050 and serving as a critical input to further work on EV mass deployment in the context of the project Electric Vehicles Management for carbon neutrality in Europe (EV4EU) and other works related to this field.

Background & Summary

Increased awareness of climate change is advancing toward several strategies, among them accelerating electric mobility. The transport sector contributes around 23% of the global greenhouse gas (GHG) emissions 1 . However, it has the lowest share of renewable energy 2 comparing with other sectors. To change this paradigm, adopting electric vehicles (EVs) is a key path. The global EV fleet is growing considerably thanks to incentive policies focused on GHG emissions standards, infrastructure development, and financial incentives. Several reports 3 , 4 , 5 projected an accelerated growth of electric mobility in the coming years, leading to a significant impact on mitigating GHG emissions. The projections also present an increase in electricity consumption and public charging points in the next decades. Nevertheless, a resilient power system is essential to support the increasing demand on network, avoiding peak loads, ensuring the electricity supply 6 , and the industrial level capacity.

For instance, Europe is embracing the shift to zero-emission mobility. The ‘fit for 55 packages’ proposed by the European Green Deal aims to reduce at least 55% of GHG emissions by 2030 compared to 1990 levels 7 . One of the document that is part of ‘fit for 55’ is the Alternative Fuels Infrastructure Regulation (AFIR) 8 that is centred in the development of electric mobility. AFIR defines targets for minimum installed capacity in public charging stations that should be higher than 1.0 kW per per battery electric vehicle (BEV) and 0.66 KW per plug-in hybrid electric vehicle (PHEV). Considering the abovementioned, almost all internal combustion engine (ICE) vehicle sales are expected to be banned in Europe by 2035 9 .

Considering the most recent data, Global EV sales more than doubled, driven by policy attention. It represents a global EV sales share of 8.57%, which accounts for 6.6 million units. Also, this stands current for over 16.4 million of BEVs (68%) and PHEVs (32%) on the roads. China and Europe lead the EV market, accounting for 85% of the global fleet, followed by the United States 10 .

Despite barriers to EV adoption, such as high acquisition cost, limited battery capacity, and insufficient infrastructure 11 , it has proven to be a promising solution for the energy transition. Therefore, estimating the evolution of electric mobility to prepare the future of the automotive industry, policymakers, and energy providers for EV mass deployment is crucial. Few papers approach the scenarios analysed in this study for the long-term due to gaps in publicly available data making it difficult to output straightforwardly. In this sense, this paper presents a dataset on electric road mobility based on historical and evolutionary scenarios until 2050. It was provided by public entities and consultants, addressing the targets from different assumptions, time horizons, and market behaviours at the international, national, and regional levels. However, it defines objectives but does not specify the path to achieve the targets. These projections will enable measuring the impact of the EV penetration that will be relevant to planning studies regarding energy systems and foster innovative business models for more sustainable mobility.

Some scenarios in the literature cover different approaches to predict the future of electric mobility and sometimes consider hurdle factors like consumer behaviour in the trajectory. These range from machine-learning tools and diffusion models, which can be subdivided into stochastic and population models 12 . While the stochastic models are based on consumers’ preferences considering the purchase decision, the population models consider the market diffusion curve or different growth rate scenarios. Nevertheless, both are less accurate for long-term predictions than the statistical model 13 , 14 .

Furthermore, the datasets described in this study include an EV forecast concerning the stock, sales, electricity demand, and the number of public charging points in the World, Europe, Portugal, Denmark, Greece, and Slovenia. The analysis is performed by growth scenarios on a five-year increment to 2050. Further, the scenarios presented in this study, if not obtained from available sources, the values for some years have been applied to the regression model, and estimated assumptions are used. Figure  1 illustrates the main steps approached for EV demand projections.

Schematic method approach.

EV Forecast is based on existing production forecasts mainly from reports by public entities and consultants, which considers market and policy targets aiming to achieve carbon neutrality for different time horizons in the context of EV4EU member countries (Portugal, Denmark, Greece and Slovenia) and worldwide. In terms of analysis, these countries are interesting due to the cultural differences, relative position in Europe and the stage of adoption of electric vehicles.

Input data processing: In addition to the data gathered from the open source, we use the interpolation and S-shaped curve to estimate the unavailable data from five-year increments until 2050 and applied some assumptions. The interpolation as been performed using the Eq. ( 1 ) where the values of y represent the number of vehicles and the values of x the years. The indexes \({\prime} 1{\prime} \) and \({\prime} 2{\prime} \) represent the known values and the variables without indexes the values to be calculated.

The S-shaped curve is presented in Eq. ( 2 ) where L presented the maximum value of the curve, e the natural logarithm base (or Euler’s number), x 0 the x-value of the sigmoid’s midpoint (year in the present case), and k the steepness of the curve or the logistic growth rate.

Several reports have presented projections regarding the evolution of EVs, considering diverse aspects as follows. The input data and sources used are publicly available and described in Table  4 . the data have been collected, organized and computed based on existing references. Values not available in the references have been computed using Eqs. ( 1 ) and ( 2 ).

The input data sourced from the available literature is descrived in the following paragraphs. The missing values regarding EV evolution scenarios were obtained by interpolation function for different time horizons. Figure  2 shows one EV scenario built in the case of worldwide.

IEA 3 addresses three scenarios until 2030: (i) Announced pledge Scenario (IEA-APS) based on climate policy pledges up to 2030 and driven by the economic and technological development in the coming years impacting the EV market. (ii) Staded Policies Scenario (IEA-SPS) embraces current policy plans up to 2030. (iii) Net Zero Emissions by 2050 Scenario (IEA-NZE) considering the main energy-related targets of the united nations’ sustainable development goals (SDGs).

Bloomberg 4 assesses three scenarios by 2050: (i) Economic Transition Scenario (BBG-ETS) driven by the economic and technological development in the coming years impacting the EV market; (ii) Net Zero Scenario (BBG-NZS) analyses the main path to zero-emission in the transport sector and considers the economy a decisive factor for achieving carbon neutrality by 2050.

IRENA 5 , 15 presents three scenarios: (i) 1.5 ° C scenario (IRN-PRT) pathway to reach the 1.5 ° C targets of the Paris Agreement through six technological avenues comprising electrification of the sectors, increasing renewable energy generation and improvements in energy efficiency in the context of the energy transition. (ii) Planned Energy Scenario (IRN-PES) is based on the energy plans established by governments besides other policy targets in this field. (iii) Transforming Energy Scenario (TES) proposes an ambitious scenario considering renewable source penetration and energy efficiency improvements.

Global EV evolution Scenarios. ( a ) Global EV Stock scenarios. ( b ) Global EV sale scenarios. ( c ) Global EV electricity demand scenarios. ( d ) Global EV charging point scenarios.

Different assumptions were considered, and interpolation was applied for missing values in some years. The results were adjusted for each geo-zone of Europe in order to obtain a fair comparison between projections. Furthermore, constant car stock(333.3 million) and new car registrations (14.5 million/year) are assumed for values obtained from percentage sales until 2050.

Virta 16 analyses two scenarios, “Low estimates” (VRTLOW) and “High estimates” (VRT-HGH). Both differ from each other mainly by the deployment of “EVs romaning around Europe” (EU-28).

Fraunhofer 17 proposes a scenario (FRH-SCN) from EV sales that could reach 100% share in (EU-28+NO+IS+CH) and sales growth fitting the S-shaped diffusion curve adjusted on the baseline of Norwegian EV sales.

Eureletric 18 in association with EY analyses the increasing penetration of EVs in Europe (EU-28+NO+CH) based on the charging infrastructure considering the impact on the electricity grid. It also considers the key participation of industry leaders in the evolution of EVs from market experience.

European Alternative Fuels Observatory (EAFO) 19 Following three scenarios for 2050 in (EU-28): (i) ZEV Base Case (EFO-ZBV) considers a medium adoption of zero-emission vehicles (ZEV); (ii) PHEV Bridging (EFO-PHV) assumes a significant increase in the market share of PHEVs around 2030. (iii) ZEV leader (EFO-ZLD) is based on the high adoption of ZEV.

Strategy& 20 reports the (SPC-SCN) scenario based on the declining global car stock of over 11% driven by car-sharing adoption in (EU-27+NO+GBR+CH).

Strategy& in partnership with European Association of Automotive Suppliers 21 (CLEPA) presents three scenarios for 2040 in (EU-28 + EFTA): (i) “Mixed-technology scenario” (CLP-MTS) based on the government recovery post-COVID, consider a 50% reduction of CO 2 emissions from 2020 to 2030.; (ii) “EV-only scenario” (CLP-EVS) addresses the projections by STEP in IEA 10 , fit for 55 package 7 and incentives for EV adoption and charging infrastructure development.; (iii) “Radical scenario” (CLP-RAD) takes into account a total 100% reduction in CO 2 emissions by 2030.

ElementEnergy 22 covers two scenarios for 2050 that consider price parity a critical factor for EV adoption in (EU-28 + EFTA). (i) “Baseline” (ELM-BAS) assumes price parity will be reached in 2030 only for passenger cars; (ii) “2028 Purchase price parity” (ELM-PPP) goes further and considers price parity to be achieved in 2030 for all segments.

ChargeUp 23 presents three scenarios following different shares of charging infrastructure deployment in (EU-27). Further, it takes into account the EV adoption based on current policies and EV strategies of the leading European automotive industries, production forecasts of market intelligence companies and some assumptions: (i) ChargeUP-minimum (CHU-MIN) set a minimum number of charging point stations; (ii) ChargeUP-AC station (CHU-ACS) assumes a high share of AC charging points; (iii) ChargeUP-higher share (CHU-HPS) also considers a high share (45% instead of 35% in the CHU-MIN scenario).

Transport & Environment 24 discusses the scenario (TeE-SCN) in (EU-27), emphasising the impact on the development of charging infrastructure in Europe with increasing EV stock to reach the European target of 100% ZEV registration for passenger cars and vans until 2035.

International Council on Clean Transportation (ICCT) 25 analyses the evolution of EV stock by the scenario (ICT-SCN) in (EU-27) until 2030 based on the goal of reaching 100% ZEV sales by 2030 through the roadmap model 26 .

Regarding the EV evolution scenarios in Greece are based on four uptake scenarios covering market and policy decisions on projections as described:

NECP uptake 27 scenario uses the targets set by the Greek authorities’ National Energy and Climate Plan (NECP) as a constant.

2030 ban uptake 28 scenario is based on a recent decision by the Greek authorities that bans all new internal combustion engine (ICE) car (non-PHEVs) sales by 2030.

C-curve uptake scenario is determined based on the corresponding mathematical model and uses fitting on past data (from 2015 to 2021) to project the likely uptake of new BEVs and PHEVs.

S-curve uptake scenario splits the adoption timeline into 4 phases: Emerging (early adopters), Growth, Maturity, and Saturation. Furthermore, similarly to the C-curve, data from 2015 to 2021 are used for the initial fitting. Concerning the infrastructure demand analysis, assumptions about the typical annual mileage and the likely number of vehicles from different specifications have been used to estimate the total charging needs. These data, combined with the duration of charging that depends on the power of the charging point and the proportion of public charging needs, further define the number of projected charging points per type. These numbers are adjusted based on 29 and accessibility factors, regionalisation and creating targets. The projected numbers for public charging points following considerations: (i) 2025 projections: the NECP numbers are driven by population, and the 2030 ban numbers are driven by EU regulations of power per vehicle; (ii) 2030 projections: Both numbers (NECP & 2030 ban) are driven by the EU target of 1 charging point per 10 vehicles.

Portugal approaches a population model by a logistic growth (S-shaped curve), which allows the comparison between early- and late-adopters. In this sense, the logistic growth models increase slowly at the beginning, depicting early adopters, and then more rapidly until the inflection point. Thus, the innovation share starts to decrease and achieve a saturation limit. Therefore the model is built from three scenarios extrapolated based on national guidelines and policies, motorization ratio, renewable fleet rates, and the average age of the vehicles by 2050: (i) Conservative is based on conservative scenario in RMSA 30 and “off-track” scenario in RNC 2050 31 and takes into account a reduction of 10% in car ownership 32 , 33 ; (ii) Progressive addresses ambitions goals considering PNEC 2030 34 , RMSA 30 and RNC 2050 31 , besides a 10% in the motorization rate of the country; (iii) Disruptive considers a high adoption of EVs by the population and public transport. The motorization rate will remain constant until 2050 and will experience rapid PHEV growth. It is based on the “yellow jersey” scenario in RNC 2050 31 .

Two scenarios were developed (pessimistic and optimistic) until 2050. The pessimistic scenario uses a linear function to estimate the EVs’ evolution, and the optimistic scenario considers the quadratic function. The functions were adjusted after the strategy 35 was adopted for the data from 2018 to 2021. Also, the electricity consumption 36 was estimated following the pessimistic and optimistic scenarios approach. These values were calculated considering the number of EVs in the fleet, the average energy efficiency and the average travelled distance per vehicle. Also, a gradual improvement to 15 kWh/100 km in 2050 was assumed, and an average mileage of 10 000 kilometres per year was considered. Since there is no centralized authority concerning the number of charging stations 37 , 38 , it was estimated the number of charging sites assumed a ratio of 40 EVs per charging point(pessimistic) and 10 EVs per charging point by 2050 (optimistic).

An acceleration in EV adoption is expected from 2025 onwards based on the Danish government’s climate neutrality targets until 2050. Besides the scenarios taken from the indicated resources 39 , 40 , 41 , 42 , 43 , 44 , three scenarios are also built to project EV fleet size and electricity demand from the study started in 45 . Also, the scenarios projected considering different EV stock share for 2030 (optimistic 43%, intermediate 33% and pessimistic 17%) and 2050 (optimistic 100%, intermediate 100% and pessimistic 90%). Further, data on electricity consumption related to EV charging in Denmark is not directly available. Therefore, an estimate of electricity demand due to BEVs and PHEVs was based on the number of vehicles, the average driven kilometres (45 Km/day) and energy consumption (5 km/kWh).

Data Records

The dataset arose from deliverable D1.1-Electric Road Mobility Evolution Scenarios from the Horizon Europe Project EV4EU - Electric Vehicles Management for carbon neutrality in Europe. The data records with the respective projection results have been stored and are available on Zenodo for download at https://doi.org/10.5281/zenodo.10443418 46 . Figure  3 illustrates the dataset’s file arrangement.

Dataset scheme.

Description of features

The dataset contains a total of 22 features available in Open XML spreadsheet (XLSX) format and divided into metadata, detailed header description, and scenario projection for EV and charging points. The results are tabulated by technology (BEV and PHEV), type of charging point (slow and fast) for each scenario and geo zone considered in five-year increments until 2050. Further, the column headers in the file are summarized according to Table  3 .

Breadth and coverage

The breadth and coverage encompass current and future information on electric road mobility collected from scenario data released by public entities and consultants in five-year increments from 2021 to 2050. In addition to the data obtained directly from the source, the data from the interpolation was also included. The dataset has a total of 1405 records. Table  1 shows the classification of the data sample according to the type of EV technology (BEV or PHEV), EV charging point type (slow or fast) and collection method (interpolation, extrapolation, reported or estimated). Table  2 also shows the data classification based on the type of geographical area covered by each scenario. Further, the data allows for comparison with the main EV policy targets. The file path is the year and scenario reference following the chronological growth projections listed as follows:

Metadata: Provide clarification instructions on spreadsheets containing datasets. The data relates to historical and future (evolution scenarios) EV markets, including EV sales and stocks, electricity demand and public charging points worldwide, in Europe and the countries of the EV4EU project members (Denmark, Greece, Portugal and Slovenia). The evolution scenarios presented are based on the European Commission’s target for zero emissions by 2050.

EV scenarios: Historical data and scenarios for BEV and PHEV related sales, stock, market share, and electricity demand in World, Europe (EU), Denmark (DK), Slovenia (SL) and Greece (GR).

Charging points scenario: Historical data and scenarios for public charging point (fast and slow chargers) distribution in World, Europe, Denmark, Slovenia and Greece.

Config: Description of the scenarios, geo zone, and variables used in the dataset.The evolution scenarios presented are based on the European Commission’s target for zero emissions by 2050. The data comprises historical and forecasting, including EV sales and stocks, electricity demand and public charging points worldwide, Europe and the EV4EU project members (Denmark, Greece, Portugal and Slovenia). The projection data is categorised according to the geographical area in which the projections are analysed and the type of forecast scenario. The type of EV technology (BEV or PHEV) and charging point (slow or fast) are also considered. In addition, the method for obtaining the data (Interpolation, extrapolation, reported or estimated) is specified.

Technical Validation

The scenarios regarding the evolution of EV markets, charging infrastructure, and electricity demand considers different market behaviours and targets at the international, national, and regional levels. The data gathered is validated from peer review by entities and consultants. Furthermore, our projections were compared in some scenarios with the Norwegian BEV fleet evolution, which presents a higher maturity of EV market adoption. Afterwards, a comparison of the forecast obtained is performed according to a political perspective and proved to be aligned favourably against EV key policy targets as summarised in Table  5 .

Overview on data quality

Cross-comparison.

The entities and consultants that submit its methodology for peer reviewing validate the dataset. Also, it is compared our results ( https://doi.org/10.5281/zenodo.10443418 ) with the key policies for EV and zero-emission vehicles (ZEVs) deployment, including goals for light-duty vehicles (LDV) and charging infrastructure. These policies are structured across published government targets and incorporated in legislation fulfilling the Paris climate agreement, EU, or nationally announced climate plans. The policy scope presents targets on Global, European, Danish, Portuguese, Slovenian, and Greek EV markets, including EV sales and stock, charging infrastructures, and electricity demand. Besides, It was possible to compare the data with the Norwegian BEV fleet benchmark.

In Denmark, based on our projections, we estimate in the optimistic scenario an EV stock of 1.3 million (43% share) and 3.2 million (100% share) by 2050. It follows the trend of phasing out ICE sales and aligns with the EV stock targets set by the Danish government above. Also, regarding the evolution of EV stock in Slovenia, the values obtained for the optimistic scenario could represent about 100% of the total vehicles. This means it will reach the target of phasing out the sale of passenger LDV above 50g CO 2 /Km by 2030, as proposed by the government of Slovenia.

Further, for the Greek evolution scenario, an average of 53% percentage of new BEVs is expected for the four scenarios (NECP,2030 ban, C-curve, S-curve) towards 2030, which represents more than 30% of the target share in new sales for ZEV passenger LDV until 2030 presented by the Greek government. Also the projections were compared with an uptake curve for Norway 47 included in 48 . In the case of the Portuguese EV evolution scenario, besides the RNC 2050 31 targets, also considered the goals for PNEC 2030 34 and RMSA 30 in the analyse for the respective scenarios (conservative, progressive and disruptive), which show from the projections, an average share of 57% for light-duty EVs until 2040. Furthermore, a comparison of BEV fleet share evolution based on the Norwegian BEV fleet with a 6-year shift is performed in the study 48 .

At the European level, the scenarios present an average of 30 million vehicles by 2025 and, for the most optimistic ones, foresee an EV stock of around 330 million by 2050. In addition, following the ambitious scenarios for the other countries analysed in our projections, about 3.2 million in Denmark (100% share), 6.3 million in Portugal, 1.5 million in Slovenia and less than 50% of EV stock share in Greece until 2050. Furthermore, an average of about 3 million public charging points in Europe by 2030 is estimated from the scenarios. Also, the ratio between the number of EVs and the number of CPs(charging points) is around 26 EVs/CPs.This demonstrates that the scenarios between the methodologies addressed are on track towards European EV adoption and carbon neutrality targets.

From this, it is estimated that over 1800 million EVs worldwide (90% of the global fleet) instead of the 1.4% 10 currently, representing about 40 million EVs/year until 2030 and 95 million EVs/year between 2030 and 2050. Following the trend of the scenarios, achieving the EV share sales target in the leading markets and globally will be possible.

Usage Notes

The format of the results is Office Open XML spreadsheet (XLSX). All the results are available on the Zenodo Open-Access repository ( https://doi.org/10.5281/zenodo.10443418 ).

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Acknowledgements

This work received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement no. 101056765 (DOI: 10.3030/101056765). However, the views and opinions expressed in this document are those of the authors only and do not necessarily reflect those of the European Union or the European Climate, Infrastructure and Environment Executive Agency (CINEA). Neither the European Union nor the grating authority can be held responsible for them. I.C., C.P.G., A.S., A.R.N. and H.M are also supported by national funds through FCT, Fundação para a Ciência e a Tecnologia, under project UIDB/50021/2020 (DOI: 10.54499/UIDB/50021/2020).

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Cavalcante, I., Rodrigues da Silva, A., Zajc, M. et al. Dataset on Electric Road Mobility: Historical and Evolution Scenarios until 2050. Sci Data 11 , 1019 (2024). https://doi.org/10.1038/s41597-024-03801-3

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Effectiveness of implemented global dietary interventions: a scoping review of fiscal policies

• Wisdom Dogbe 1 ,
• Faical Akaichi 2 ,
• Vanessa Rungapamestry 1 &
• Cesar Revoredo-Giha 2  

BMC Public Health volume  24 , Article number:  2552 ( 2024 ) Cite this article

Metrics details

Although the World Health Organisation (WHO) has proposed the use of fiscal policies to mitigate consumption externalities such as overweight and obesity-related diseases, very little is known about the impacts of the different types and framing of national and/or regional fiscal policies that have been implemented over the years. There is the need to provide up-to-date evidence on the impact of fiscal policies that have been enacted and implemented across the globe.

We conducted a scoping review of all implemented government fiscal policies in the food and drinks sector to identify the different types of fiscal policies that exist and the scope of their impact on consumers as well as the food environment. Electronic databases such as the Web of Science and Google Scholar were used to search for appropriate literature on the topic. A total of 4,191 articles were retrieved and 127 were synthesized and charted for emerging themes.

The results from this review were synthesized in MS Excel following Arksey & O’Malley (2005). Emerging themes were identified across different countries/settings for synthesis. The results confirms that fiscal policies improve consumers’ health; increase the prices of foods that are high in fats, sugar, and salt; increase government revenue; and shift consumption and purchases towards healthier and untaxed foods.

Governments already have the optimum tool required to effect changes in consumer behaviour and the food environment.

Peer Review reports

Introduction

Scotland is known for eating too much of the wrong things [ 1 ]. The food environment is populated with inexpensive salt, fat, and sugary foods. Poor dietary choices have resulted in an increased risk of obesity-related diseases such as hypertension, cardiovascular diseases, type 2 diabetes and certain types of cancers [ 2 , 3 , 4 ]. Statistically, in 2021, a total of 3.1 million people in the UK were registered to have diabetes, 700,000 more than in 2010 [ 5 ]. A switch from the consumption of discretionary foods Footnote 1 —high fat, salt, and sugar foods—to healthy diets high in fruit and vegetables, oil-rich, fibre and whole grains—is required to reduce the burden of diseases in Scotland. However, poor dietary choices are known to persist among people living in the most deprived areas [ 1 ].

Food Standard Scotland (FSS) data show that currently, the average person in Scotland consumes 15.1% of energy from saturated fat, which is 4% higher than the recommended percentage. In addition, 14.4% of the energy is derived from sugar, which is 9.4% above the recommended level. The average salt intake is 7.8 g, which is 1.8 g greater than the recommended intake [ 1 ].

A 2018 FSS report suggested that 65% of Scotland’s population is either overweight or obese [ 1 ]. In 2019, approximately 29% of Scottish adults were classified as obese, ranging from 23% in the least deprived areas to 36% in the most deprived areas. The prevalence of obesity-related NCD has slowly increased since 2014. Estimates show that the rate of obesity-related noncommunicable diseases (NCD) deaths could increase by 10%, from 56 per 100,000 to 62 per 100,000 [ 6 ]. In addition, 10% and 20% of five-year-olds and 11-year-olds, respectively, are obese [ 5 ], indicating a gloomy health outlook for Scotland.

In addition, a total of 6,697 and 2,181 deaths due to coronary heart disease (CHD) and stroke, respectively, were recorded in 2016. Sadly, 31% of children experience dental decay, while 29% of the population has high blood pressure [ 1 ]. NCD such as heart disease, cancer, diabetes, stroke, and liver and lung diseases were the leading causes of death in Scotland, accounting for almost 2/3 of all deaths in 2020. However, studies have shown that 1 in 5 of these deaths could be prevented through public health actions involving unhealthy food and drinks as well as tobacco and alcohol. Estimates suggest that poor health and disability caused by tobacco, alcohol and unhealthy food and drink costs the Scottish economy between £5.6 and £9.3 billion every year [ 7 , 8 , 9 ]. These statistics demand that policymakers engage with the food system to address these problems.

A recent survey by FSS suggested that more than half of Scottish adults want to see the Scottish Government do more to improve health. The first step is to nudge consumers to reduce the number of discretionary foods consumed by at least half [ 1 ]. Suggestions for the government to improve healthy choices include influencing marketing, price and promotion and the availability of unhealthy foods to the populace [ 10 ]. Price and promotions are the two dominant tools used by the food industry to drive the consumption of unhealthy products. According to The Food Foundation (2021), 46% of food and drink advertisements involve confectionery, sweet and savoury snacks and soft drinks, while only 2.5% involve fruits and vegetables.

Internationally, many countries and jurisdictions have introduced policies, programs, and guidelines to nudge consumers towards healthy eating. In the UK, the soft drink industry levy, five-a-day campaign, and the Eatwell Guide are the most prominent. Despite the implementation of these policies, the National Health Service is still overburdened by the cost of treating diet-related NCD. As a result, there is a high political interest in taxes and subsidies to improve diets and prevent the economic burden of diseases. Fiscal policies such as taxes come in different forms and sizes, including ad valorem taxes, value-added taxes (VATs), excise taxes, and import tariffs and taxes Footnote 2 . Theoretically, taxes (subsidies) create fiscal incentives for buyers to buy less (more) of affected foods, recalibrating overall diet quality [ 11 ]. Subsidising nutrient-rich foods Footnote 3 is relevant because the poorest households in the UK would need to spend more than 70% of their disposable income on food to meet the UK’s Eatwell Guide [ 5 ]. Moreover, 10% of children live in households facing severe food insecurity, while 16% of UK adults skip meals due to a lack of money [ 5 ]. Ironically, unhealthy foods are three times cheaper than healthy foods.

The World Health Organisation strongly supports the use of fiscal measures to reduce the consumption of nutrient-poor, energy-dense foods [ 11 , 12 ]. As a result, many countries and jurisdictions such as USA, Mexico, United Kingdom, Chile, Portugal, South Africa, Samoa, Bermuda, Ecuador, Ireland, Mauritius, Mexico, Norway, etc. have implemented fiscal policies to nudge consumers towards eating healthily. However, to our knowledge, there is no synthesis of worldwide studies assessing the impact of existing fiscal policies and drawing lessons that could help shape the food arena in Scotland and the UK. Previous literature reviews are based on simulation studies, including experimental and modelling studies. This scooping review goes beyond previous works by (1) presenting a comprehensive summary of all the fiscal policies implemented globally, (2) focusing on empirical studies based on implemented fiscal policies (excluding simulation studies), and (3) grouping the identified impact under broad themes relevant to policymakers. This review collates diverse research work from different jurisdictions under specific themes to help policy makers make informed decisions about the direction of impact.

The results from the current scoping review show that fiscal policies have significant impacts irrespective of the goal of the government. The positive aspects of fiscal policies include reducing the consumption of targeted foods, increasing the consumption of healthy untargeted foods, and increasing revenue to support government and health goals, i.e., reducing overweight and NCD. On the negative side, taxes increase the cost of consumption, especially for low-income households.

Literature search strategy

The following electronic databases were used to search for appropriate literature on the topic: PubMed, Academic Search Premier, Web of Science and Google Scholar. A keyword search strategy was developed and based on three main concepts using the search function “AND” to identify relevant articles: “tax/subsidy/fiscal”, “food/nutrition/diet/sugar-sweetened/energy-dense” and “policy/program”. The “OR” function was used to vary the keywords or concepts to expand the results. The search was implemented using (“tax” OR “subsidy” OR “fiscal”) AND (“food” OR “nutrition” OR “diet” OR “sugar-sweetened” OR “energy-dense”) AND (“policy”).

The inclusion criteria were restricted to studies related to fiscal policies that have been implemented and evaluated across various jurisdictions across the world irrespective of methodology or depth of analysis. The period during which the policy or program was implemented and whether it was ongoing or abolished were irrelevant Footnote 4 . However, since most fiscal policies on nutrition started in the 1980s, the search period started from 1980 to 2022. The goal is to identify fiscal policies that have been implemented to improve nutrition and/or health.

Studies that were not based on existing government policies were excluded from the analysis. Additionally, studies based on fiscal policies directed towards agriculture, inputs/fertiliser, trade, and farming were excluded from the final analysis. Studies that were not directed towards health or nutrition were excluded. Finally, simulation studies that were not based on existing government policies or programs were also excluded.

We followed the criteria suggested by Arksey & O’Malley [ 13 ] to refine the literature for inclusion and exclusion. Before the review, the primary author ensured that duplicate studies were excluded based on the titles of the studies. Examination of the remaining articles was based on their titles, followed by their abstracts and then the full paper. The references of the articles were screened to increase the number of articles included. All articles were independently reviewed by WD, FA, and where there is disagreement VR and CRG were consulted. The final articles included in the final review were charted by WD and refined by the remaining authors (FA, VR, CRG).

Data from the articles were charted using MS Excel following Arksey & O’Malley [ 13 ]. The information collected for further analysis included author(s), study country/location, setting intervention, measurable outcomes, effect on outcomes, year, data and method. Emerging themes were identified across different countries/settings for synthesis.

Data abstraction and synthesis

We followed the work of [ 13 , 14 ] by charting through the literature to synthesise studies relevant to the topic. The data from the studies were analysed using Microsoft Excel, and the characteristics of the studies considered included the name of the authors, the description of the intervention, the country and year the intervention was implemented, and the outcome of the study assessing the impact of the intervention. Outcomes from the various studies were coded, and emerging themes were identified for the results and discussion.

Flowchart of search results Source: Own computation based on literature search

Search outcome

A total of 4,191 articles were retrieved from the three databases shown in Fig.  1 . Approximately 2,587 duplicate articles were excluded from the total. Through manual searching, 5 articles were included in the review (mainly from Google Scholar). Table  1 shows the countries and the number/percentage of studies found; the USA had the highest number of studies (44), followed by Mexico (18), the United Kingdom (13), South Africa (5), Portugal (5) and Chile (5). Additionally, there were studies from Australia, Barbados, Bermuda, Canada, Denmark, Ecuador, France, French Polynesia, Hungary, Ireland, Mauritius, Navajo, Norway, the Philippines, Samoa, Saudi Arabia, Spain, Thailand, and Tonga. Tax policies had an impact on household purchases/retail sales, consumer welfare, government revenue, health, diet, and nutrition across 24 different jurisdictions.

Theme 1: Tax policies may affect household purchases/consumption/sales

This theme considers the impact of taxes on household purchases or consumption and sales across different jurisdictions and policy scenarios. Table  2 shows that tax policies are effective in reducing household purchases and sales.

The United Kingdom: United Kingdom Soft Drinks Industry Levy (SDIL) was announced in March 2016 and implemented in April 2018; it charges manufacturers and importers at £0.24 per litre for drinks with over 8 g of sugar per 100 mL (high levy category), £0.18 per litre for drinks with 5 to 8 g of sugar per 100 mL (low levy category), and no charge for drinks with less than 5 g of sugar per 100 mL (no levy category). Scarborough et al. [ 32 ] studied the impact of the announcement of the SDIL and found that the number of drinks in the high levy category fell by 3% when the SDIL was announced. Rogers et al. [ 33 ] found that the volume of all soft drinks purchased combined increased by 2.6% per household per week a year after the implementation of the tax. On the positive side, the amount of sugar consumed from soft drinks decreased by 2.7% per household per week over the same period. Dickson et al. [ 34 ] reported that the reformulation of the SDIL led to a 6,600 calories per year per capita reduction in soft drinks. Bandy et al. [ 35 ] reported that the volume of sugar sold per capita per day from soft drinks declined by 30% or 4.6 g per capita per day. In addition, the weight means sugar content of soft drinks decreased from 4.4 g/100 in 2015 to 2.9 g/100 in 2018. Sales of soft drinks subjected to the levy fell by 50%, while those exempted from the levy rose by 40%. Rogers et al. [ 36 ] found evidence of a small increase in sugar purchased from all drinks compared to before the announcement of the levy. Pell et al. [ 37 ] reported that one year after implementation, the volume of drinks purchased did not change, but sugar purchases declined by 9.8%. Dogbe and Revoredo-Giha [ 38 ], considering a tax pass-through of 50%, found that levies reduced annual volume purchases and sugar by 1.4% and 3.9%, respectively. Law et al. [ 39 ] found that the announcement of SDIL had a significant negative impact on the turnover of manufacturers; however, this was not carried out postimplementation.

Barbados: In 2015, the government of Barbados implemented a 10% ad valorem tax on SSBs. Alvarado et al. [ 15 ] estimated the impact of the policy on SSB purchases using electronic point-of-sale data. The authors applied an interrupted time series (ITS) design to assess grocery store SSB and non-SSB sales from January 2013 to October 2016. The authors found that sales for taxed SSBs decreased by 4.3%, while non-SSB sales increased by 5.2%.

Bermuda: Bermuda implemented a discretionary food tax based on import tariff changes on retail prices and sales of SSBs and tariff reductions for selected fruits and vegetables. The first country to implement both tax and subsidy policies concurrently. Assessing the implications of both policies, Segal et al. [ 40 ] found that the market share of SSBs decreased by 8% due to the tax; however, the subsidy policy had no significant effect on sales.

Chile: The Chilean government revised (increased) its SSB tax from 13 to 18% for SSBs with sugar greater than 6.25 g/100 mL and revised (decreased) the SSB tax from 13 to 10% for SSBs with sugar less than 6.25 g/100 mL in 2014. Caro et al. [ 16 ] assessed the implications of these changes in Chile using the Chilean Household Budget Survey. The authors found evidence of substitution for cheaper SSBs and a reduction in the average household’s sweetened beverage purchases of 0.9 L per month. Caro et al. [ 17 ] also assessed the implications of tax revisions for SSB purchases in Chile and reported that households decreased their monthly per capita purchases of SSBs with a sugar content greater than 6.25 g/100 mL by 3.4% by volume (4% by calories). However, the purchase of SSBs with less than 6.25 g of sugar/100 mL increased by 10.7%. Nakamura et al. [ 18 ] also used a fixed effect model to assess the implications of the Chilean SSB tax increase from 13 to 18% for SSBs with a sugar content greater than 6.25 g. The authors found a highly significant decrease in the monthly purchased volume of the taxed drinks by 21.6%.

Denmark: In 2011, the Danish government imposed a tax of 16 DKK/kg (2.14 €/kg) on foods with saturated fat above 2.3 g/100 g. Smed et al. [ 19 ] assessed the effect of this tax on food and nutrient intake in Denmark. According to the study, the tax resulted in a 4% decrease in saturated fat purchases. Bødker et al. [ 20 ] assessed the implications of the policy for health and consumption and concluded that the total sale of foodstuffs decreased by 0.9%. Another study by Jensen et al. [ 21 ] investigated the effects of the tax on meat and dairy demand. The authors found that the tax induced a total decrease of 4–6% in saturated fat intake from minced beef and regular cream but had no effect on the intake of sour cream. Finally, Jensen and Smed [ 41 ] assessed the short-term effects of the Danish fat tax on consumption, substitution patterns and consumer prices of fat and found that the level of consumption of fat decreased by 10–15%. In addition, they found that the purchase of butter, margarine, blends and oil decreased by approximately 10%.

Ecuador: Ecuador implemented a volumetric tax of 18 cents per Liter on sugary drinks with more than 25 g of sugar per Liter in 2016. Comparing the tax to a 20% ad-valorem tax, Segovia et al. [ 42 ] concluded that the tax imposed by the Ecuadorian government was less effective than the simulated ad-valorem tax.

France: In January 2012, the French soda tax was introduced and set to €0.0716 per liter on the producer price of SSBs. It is applied to all sweetened drinks, including sugar substitutes used in diet drinks, and is paid for by manufacturers, processors and importers [ 23 ]. The authors estimated the impact of the French soda tax on both purchases and prices using a difference-in-differences approach. The results indicate that a small reduction in soft drink purchases (approximately half a liter per capita per year) could be due to the low tax rate. Assessing the effect of the same policy, Kurz and König [ 22 ] found a slight decrease in SSB sales but an overall increase in soft drink sales. The two studies suggest that the French soda tax had a marginal impact on both purchases and sales.

Hungary: Hungary imposed a 4-cent tax public health product (PHPT) on foods high in salt, sugar, or caffeine in 2011. The objective was to promote healthier eating habits through reformulation and to increase revenues for public health. Assessing the effectiveness of the tax, Zámbó et al. [ 26 ] found that the consumption of taxed products increased in all categories (except for salty condiments) between 2013 and 2018. Bíró [ 25 ] assessed the effectiveness of the tax on the consumption of processed and unprocessed foods before and after the tax came into effect. The results from the study suggest that the consumption (in terms of quantities) of processed foods decreased by 3.4% due to the tax. Martos et al. [ 43 ] also found that the policy reduced the consumption of targeted taxed foods both in the short and long run. Kurz and König [ 22 ] assessed and compared the impact of the soda tax implemented in France and Hungary. The authors found a slight decrease in SSB sales after tax implementation, but overall soft drink sales increased in France. For Hungary, there was only a short-term decrease in SSB sales, which disappeared after 2 years, leading to an overall increase in SSB sales. The authors concluded that the tax had a short-term impact in Hungary but had no effect on soft drinks in France.

Ireland: Briggs et al. [ 44 ] assessed the potential health impact of a proposed 10% tax on SSBs in Ireland. The authors found that the proposed tax could reduce average energy intake by 2.1 kcal per person per day and reduce the percentage of the obese population by 1.3%.

Mauritius: In January 2013, the government of Mauritius imposed a tax on SSBs based on their sugar content. The tax applied to both locally manufactured and imported drinks was equivalent to 8 US cents per 100 g of sugar content. Cawley et al. [ 27 ] assessed the implications of the policy on youth consumption and body mass index using a difference-in-differences model. There was no evidence of an effect of the tax on SSB consumption for the full sample of youth, but subgroup analyses indicated that the tax reduced the probability that boys would consume SSBs by 9.1% points (11%).

Mexico: In 2014, the Mexican government implemented an excise tax of one peso ($0.008) per litre (equivalent to a 10% price increase) on SSBs except for medical beverage products. The tax was implemented by the Mexican Congress as an initiative to limit Mexico’s obesity epidemic. Colchero et al. [ 45 ] assessed the impact of the tax on SSB and water purchases across different locations, household types and income levels. Their results suggest that purchases of SSBs decreased by 6.3% in 2014 compared with the trend from 2008 to 2012. Additionally, water purchases increased by 16.2% during the same period. Colchero et al. [ 31 ] again estimated how consumers responded to the Mexican beverage tax two years after it was implemented. The results from the study revealed that purchases of taxed beverages decreased by 5.5% in 2014 and 9.7% in 2015 compared to purchases in 2012-13. Colchero et al. [ 28 ] assessed the impact of the tax on beverage sales before and after the implementation of the policy. The authors found a decrease of 7.3% in per capita sales of SSB and an increase of 5.2% in per capita sales of plain water in 2014–2015 compared to the pretax period (2007–2013). Ng et al. [ 30 ] assessed how highly SSB purchasers responded to the excise tax. The authors found that SSB purchasers had the largest absolute and relative reductions in taxed beverages and increased their purchases of untaxed beverages. Colchero et al. [ 46 ] estimated the impact of the tax on purchases of SSBs from retail stores one year after implementation. The results from the study suggest that beverage purchases decreased by 6% in 2014 compared with 2012 at a decreasing rate of up to 12%. Sánchez-Romero et al. [ 29 ] assessed the association between SSB tax and soft drink consumption among adults in Mexico using an open cohort longitudinal analysis of health workers. The authors compared four categories of consumers: non, high-, low- and medium-level consumers. The results from the study showed that the proportion of medium and high consumers of soft drinks decreased by 7% after the tax came into effect. In addition, the percentage of non-consumers of soft drinks increased by 4% (from 10 to 14%). Finally, Pedraza et al. [ 47 ] studied the effect of the SSB tax on the caloric and sugar content of beverages bought in different stores in Mexico. They found that the volume of SSBs purchased declined by 49 ml and 30 ml in 2014 and 2015, respectively.

The Mexican government also imposed an 8% tax on nonessential energy-dense foods with an energy density of 275 kcal/100 g or more in the same year the SSB tax was implemented. Batis et al. [ 48 ] assessed the effect of the tax on both taxed and untaxed packaged foods through an observational study. The results showed that purchases of taxed packaged foods were reduced by 5.1% per person per month. However, purchases of untaxed packaged foods remained the same. Taillie et al. [ 49 ] also assessed the impact of the nonessential energy-dense tax two years after its implementation by comparing the impact on high and low purchasers before and after the implementation of the tax. The tax was sustainable; decreases in purchases for taxed foods increased from 4.8% in the first year to 7.4% in the second year. Hernández-F et al. [ 50 ] also assessed the effect of the energy-dense tax on the purchases of energy-dense nutrient-poor foods a year after the policy was implemented. The results from the study showed that the purchases of energy-dense nutrient-poor foods decreased by an average of 5.3% in 2014–2016 compared with purchases made in 2008–2012. Focusing on snacks, Aguilera Aburto et al. [ 51 ] showed that the Mexican energy-dense tax resulted in a moderate reduction in the consumption of snacks.

Navajo Nation: In 2014, the Navajo Nation passed the Healthy Diné Nation Act (HDNA), which combined a 2% tax on foods of ‘minimal-to-no-nutritional value’ and a waiver of a 5% sales tax on healthy foods. George et al. [ 52 ] assessed the implications of the tax on the pricing and availability of unhealthy foods. The authors found that compared to border town stores, in 2019, the availability of fresh vegetables and fruits was greater in convenience stores in Navejo. Trujillo Lalla et al. [ 53 ] also assessed the impact of the tax on purchasing trends using a multiyear cross-sectional survey. They found trends towards reduced purchasing of SSBs due to the tax.

Norway: In January 2018, the Norwegian government increased taxes on chocolate and sugar products from 2.09 EUR per kg to 3.82 EUR per kg and taxes on non-alcoholic beverages from 0.35 EUR per litre to 0.49 EUR per litre. Assessing the implications of taxes on retail sales, Øvrebø et al. [ 54 ] did not detect any significant reductions in sales that coincided with the increase in taxes.

Pacific: Thow et al. [ 24 ] assessed the impact of the soda tax in the Pacific Empire, which consists of Fiji, Samoa, Nauru, and French Polynesia. In Samoa, survey data analysed by Keighley et al., [ 55 ] suggest that the number of servings of soda consumed by the Samoan population decreased slightly between 1991 and 2003, from approximately 2.5 to just over two servings per week.

Philippines: Additionally, in January 2018, the Philippines implemented a tax of 0.185 US dollars per litre on beverages containing locally sourced sweeteners and 0.37 US dollars per litre on beverages containing imported sweeteners. Assessments by Onagan et al. [ 56 ] showed that sales of sweetened beverages decreased significantly; the greatest decrease was 8.7% in convenience stores just a month after implementation.

Portugal: In February 2017, the Portuguese government implemented a tiered sugar-sweetened beverage tax on producers based on the amount of sugar contained in drinks. The rates are as follows: 1 euro cent per litre for drinks with less than 25 g of sugar per litre; 6 cents for drinks with 25–49.99 g of sugar per litre; 8 cents for drinks with 50–79.99 g of sugar per litre; and 20 cents for drinks with 80 g or more of sugar per litre. The goal was to incentivise firms to reformulate towards lower sugar content. Goncalves et al. [ 57 ] reported a significant decrease in the domestic sales of SSBs following the implementation of the policy. Goiana-da-Silva, Nunes, et al. [ 58 ] also found a 15% decline in the total volume of sugar consumed from all ranges of beverages covered by the tax. In addition, they estimate a decrease of 4.3% in sales. Goiana-da-Silva, Cruz-e-Silva, et al. [ 59 ] estimated a 7% reduction in sales and an 11% reduction in total energy intake from sweetened beverage consumption as a result of reformulation. Goiana-da-Silva et al. [ 60 ] reported a reduction of 6.6 million litres of SSBs sold per year due to the tax. In addition, the average energy density of the SSBs decreased by 3.1 kcal/100 ml as a result of product reformulation. In contrast, Gonçalves and Pereira dos Santos [ 61 ] found no impact of the consumption tax, except for low-sugar drinks.

Saudi Arabia: Saudi Arabia imposed a 50% excise on soft drinks and a 120% excise on energy drinks, which came into effect in 2017. Alhareky et al. [ 62 ] assessed the impact of the tax on SSB consumption among Saudi school children. The authors found that energy drink consumption declined by 8%, but soft drink consumption increased by 2% after tax implementation. However, Alsukait et al. [ 63 ] estimated a 35% reduction in the volume sales of soft drinks relative to other Araba Gulf states. Furthermore, Megally and Al-Jawaldeh [ 64 ] estimated a 57.64% decrease in the sales volume of soft drinks from 2010 to 2017 following the implementation of the policy.

South Africa: Last, in April 2018, the South African government implemented a health promotion levy (HPL) payable by producers and importers of sugary beverages at a rate of 2.1 cents per gram of total sugar over 4 g per 100 mL. Bercholz et al. [ 65 ] estimated a 4.9 gram per capita per day reduction in sugar purchases from SSBs following the announcement of the tax. Another study by Koen et al. [ 66 ] revealed that self-reported consumption of SSBs decreased by 7.7% after the HPL was enacted. Finally, Essman et al. [ 67 ] assessed the implications of the tax and showed that sugar intake decreased significantly from 28.8 g/capita/day pretax to 19.8 g/capita/day post-tax implementation. In addition, the volume intake decreased from 315 ml/capita/day pretax to 198 ml/capita/day post-tax.

Spain - Catalonia: In May 2017, Catalonia, a state in Spain, implemented a tax of 0.08€ per Liter on beverages containing between 5 and 8 g per 100 ml and 0.12€ per Liter on beverages containing more than 8 g per 100 ml. Assessing the implications of the tax, Fichera et al. [ 68 ] found a 2.2% reduction in purchases from beverages. Royo-Bordonada et al. [ 69 ] assessed the impact of the tax on young people living in poorer neighbourhoods in Catalonia using Madrid as a control group. The authors found a 39% reduction in the prevalence of regular consumers of taxed beverages. However, the prevalence of consumers of nontaxed beverages remained the same after the tax. Assessing the impact of the tax on SSB sales, Vall Castelló and Lopez Casasnovas [ 70 ] estimated a reduction of 7.7%. Focusing on the impact of the tax on Coca-Cola, Puig-Codina et al. [ 71 ] found that the policy significantly reduced the volume of purchases (12.1%) and penetration rates (1.27%) of regular cola. However, the volume of purchases and penetration of diet cola increased by 17% and 1.65%, respectively.

Tonga, Oceania: In August 2013, Tonga’s 15% import tariff on SBs was replaced with an excise tax of T$0.50/L (US$0.28/L, 42% of import value) and subsequently doubled to T$1.00/L in July 2016 (63% of import value). The excise is applied to full sugar and artificially sweetened soft drinks, energy drinks, and other SBs. Water (sparkling or flat), juice (sweetened or unsweetened), powdered juice drinks, tea, coffee or hot chocolate were exempted from the tax. Teng et al. [ 72 ] assessed the implications of the tax and found significant decreases in all soft drink purchases. Teng et al. [ 73 ] also reported that the imports of sweetened beverages decreased by 10.4%, 30.3% and − 62.5% in 2013, 2016 and 2017, respectively, after tax imposition.

Thailand: In September 2017, Thailand also imposed a tax on SSBs according to their sugar content. The SSB products that contain less than 6 g of sugar per 100 mL are exempt from the tax, while those products containing 6 g or more of sugar per 100 mL are taxed at a higher rate. This is expected to increase every two years based on inflation rates. By assessing the impact of the tax policy on both taxed and nontaxed SSBs, Phulkerd et al. [ 74 ] found a significant reduction in taxed SSBs compared with nontaxed ones.

Berkeley, USA: In November 2014, the city of Berkeley passed a penny-per-ounce levy on SSBs, which included soda, energy, sports and fruit-flavoured drinks; sweetened water, coffee, and tea; and syrups used in the production of SSBs. Falbe et al. [ 75 ] assessed the impact of the tax on sugar-sweetened beverage consumption. The results from the study showed that the consumption of SSBs declined by 21% in Berkley but increased by 4% in Oakland and San Francisco. However, water consumption increased more in Berkley than in Oakland and San Francisco. Silver et al. [ 76 ] assessed the implications of the tax on sales and found that sales of SSBs in Berkley declined by 9.6% but increased in controlled cities by 6.9%. The authors did not find a significant difference in self-reported SSB intake before and after tax imposition. The study by Lee et al. [ 77 ] was conducted 3 years after the implementation of the Berkley SSB tax. The authors found that SSB consumption was reduced by 0.55 times per day, while water consumption increased by 1.02 times per day. In addition, the changes in SSB and water consumption in Berkley were significantly different from those in the neighbouring city, San Francisco, and Oakland comparison groups.

Cook County, USA: Cook County, Illinois, implemented an SSB tax of a 1.00-cent-per-ounce tax on the retail sale of sweetened beverages on August 2, 2017, and later repealed, effective November 30, 2017. Assessing the changes in beverage prices and volume following the implementation and repeal of the tax, Powell and Leider [ 78 ] found that in the 4 months that the Sweetened Beverage Tax was in place, the volume sold decreased while the tax was in place, but the sales volume returned to their pretax levels 8 months after the tax was repealed. Similarly, Powell, Leider, and Léger [ 79 ] assessed the impact of the Cook County SSB tax on the volume of SSB sold in the city and its border area. They estimate a 27% reduction in the volume of SSB sold. However, the impact differed between soda and energy drinks, between artificially sweetened beverages and SSBs, and between family-size and individual-size beverages.

Oakland, USA: Cawley et al. (2020) assessed the impact of the Oakland 1 cent per ounce SSB tax on prices, purchases and consumption by adults and children. Although not statistically significant, the tax decreased purchases by 11.33 ounces per shopping trip. However, the tax did not reduce the consumption of SSBs or added sugars for either adults or children. In contrast, Léger and Powell [ 80 ] reported that the volume of taxed beverages sold decreased by 14%, but 46% of this decrease was offset by an increase in cross-border purchases.

Seattle, USA: In January 2018, Seattle implemented a 1.75 cent per ounce Sweetened Beverage Tax (SBT) on SSBs with at least 40 calories per 12 ounces; milk, including flavoured/sweetened milk, as well as 100% juice, was exempted from the tax. Powell, Leider, and Oddo [ 81 ] evaluated changes in the grams of sugar sold after the implementation of the tax policy using a difference-in-differences analysis. The authors found a 23% (28%) decrease in sugar sold from taxed beverages (soda) from the pretax period to year 1 and year 2 post-tax implementation. Powell and Leider [ 82 ] assessed the impact of the tax on prices, volume sold and cross-border shopping. They found that the average volume of taxed beverages sold fell by 22%, 29% for larger families versus 10% for individual families. Oddo, Leider, and Powell [ 83 ] compared the sales of sweets and salty snacks in Seattle and Portland and reported that Seattle SBT increased the sales of sweets by 4% and 6%, respectively, a year and two years after implementation. However, there was no impact on the sales of salty snacks. Powell and Leider [ 84 ] reported a reduction of 22% in the volume of sugary drinks sold in Seattle following the implementation of the tax.

Philadelphia, USA: In 2017, Philadelphia imposed a beverage tax of $0.015/ounce on sugar (regular) and sugar substitute (diet) beverages. This was an excise tax paid by distributors. However, products containing more than 50% milk and 100% fruit drinks were exempted from the tax. Zhong et al. [ 85 ] assessed the immediate impact of the tax on the consumption of soda, fruit drinks, energy drinks, and bottled water. The authors found that the consumption of soda declined by 40% 2 months after the tax came into effect. Similarly, purchases of energy drinks were reduced by 64%, while bottled water purchases increased by 58%. Roberto et al. [ 86 ] further assessed the impact of taxes on beverage prices and sales at chain retailers in a large urban setting. They compared beverage prices and sales in Philadelphia with those in Baltimore, Maryland (a control city with a tax). The results showed that the total volume of sales of taxed beverages decreased by 1.3 billion dollars in Philadelphia; however, sales in Pennsylvania borders increased by 308.2 million ounces. A study by Bleich et al. [ 87 ] revealed that the purchase of taxed beverages declined by 6.1 fl. oz, corresponding to a 42% decline in Philadelphia compared with Baltimore (a controlled city). Edmondson et al. [ 88 ] also assessed the implications of tax SSBs among high school students. They found a reduction of 0.81 servings of soda per week 2 years after tax implementation. Longitudinal studies by Lawman et al. [ 89 ] did not find statistically significant changes in SSB purchases one year after the implementation of the Philadelphia beverage tax. However, an analysis excluding holiday purchasing or aggregating post-tax time revealed a reduction of between 4.9 and 12.5 ounces per day. Zhong et al. [ 90 ] assessed the effect of the tax on sugar-sweetened and diet beverage consumption and concluded that there was no overall impact on population-level consumption of sugar-sweetened or diet beverages or bottled water a year after the tax was implemented. Petimar et al. [ 91 ] found that the volume of sales of taxed beverages decreased by 35% (after adjusting for cross-border shopping) two years after the implementation of the tax. Bleich et al. [ 92 ] found larger declines in the volume of taxed beverages sold (5.76 ounces, or 38.9%) after tax implementation. After accounting for cross-border shopping to shops outside of Philadelphia, Seiler, Tuchman, and Yao [ 93 ] concluded that the tax led to a 22% reduction in sales. Additionally, Seiler, Tuchman, and Yao [ 93 ], analysed the impact of the Philadelphia SSB tax on calories and found that calories from beverages decreased by 16% after the implementation of the tax. According to Cawley et al. [ 94 ], the Philadelphia tax reduced the frequency of adults’ soda consumption by 31%, but no detectable impacts on children’s soda consumption were found. Grummon et al. [ 95 ] found a reduction in the purchases of taxed beverages following the implementation of the tax.

Theme 2: Impact of taxes on prices/pass-through effect

A summary of the impact of tax policies on the prices of taxed beverages and pass-through effects is shown in Table  3 . In summary, tax polices result in higher prices paid for by consumers at retail shops. However, the proportion of the tax paid for by consumers differs by jurisdiction, type of product, type of retail shop, etc.

United Kingdom: Scarborough et al. [ 32 ] estimated a price increase of £0.075 per litre for high-level drinks, corresponding to a 31% pass-through rate. The price of low-intensity drinks decreased marginally, while that of no-intensity drinks increased marginally. Dickson et al. [ 34 ] found that the SDIL was over shifted to soft drink brands that maintained their recipes, leading to a significant increase in their retail prices.

Barbados: Alvarado et al. [ 96 ] assessed price changes in SSBs following the implementation of the government’s 10% ad valorem tax. The SSB prices from a major supermarket in Barbados were used for the case study. The authors found that before the tax, both SSBs and non-SSBs had similar year-on-year price growth. However, the growth in SSB prices reached 5.9%, while non-SSB prices grew below 1% after the tax came into effect.

Bermuda: Segal et al. [ 40 ] estimated a price increase of 26% for taxed SSB but no impact on the prices of untaxed beverages. In addition, the subsidy policy had no significant impact on the prices of fruits and vegetables sold in the country.

Chile: In Chile, Caro et al. [ 17 ] reported that the price of SSBs with a high sugar content increased by 2.0%, while the price of SSBs with a sugar content less than 6.25 g/100 mL decreased by 6.7%. Nakamura et al. [ 18 ] found that the purchase prices of soft drinks decreased for items for which the tax rate was reduced from 13 to 10%, but they remained unchanged for sugary items for which the tax was increased. However, they suggest that the purchase prices of SSBs increased when the tax revision was announced. Cuadrado et al. [ 97 ] assessed the impact of the tax revision on the affordability of soft drinks and concluded that the policy was effective in increasing prices.

Denmark: Jensen et al. [ 21 ] concluded that the Danish fat tax had an insignificant or small negative effect on low- and medium-fat varieties but led to a 13–16% price increase for high-fat varieties of minced beef and cream products. Jensen and Smed [ 41 ] assessed the impact of the same policy on butter (8.17–11.38 DKK/kg higher) and margarine (4.57–6.18 DKK/kg higher) and concluded that prices were higher than in the pretax period.

France: Berardi et al. [ 103 ] assessed the impact of the French soda tax on prices using French microdata. The authors concluded that the SSB tax was fully shifted to soda and almost fully shifted to the price of fruit drinks six months after implementation. However, the authors found that the pass-through for flavoured water was incomplete. Etilé, Lecocq, and Boizot-Szantai [ 98 ] also assessed the impact of French soda taxes on consumer prices and welfare. They showed that the pass-through effect of the policy was approximately 39%, less than that estimated by Berardi et al. [ 103 ]. As a result, the prices of SSBs and NCSBs increased by 4% after the tax came into effect. Capacci et al. [ 23 ] assessed the impact of the French soda tax and confirmed the findings of Berardi et al. [ 103 ], showing that the tax was transmitted to the prices of taxed drinks, with full transmission for soft drinks.

Mexico: Arantxa Colchero et al. [ 104 ] assessed the impact of the Mexican excise tax on the prices of SSBs in urban areas. A fixed effect model was applied to data obtained from the National Institute of Statistics and Geography from 2011 to 2014. They found that the tax was passed through to all SSBs and was over shifted for carbonated SSBs. However, the increase in the price of SSBs with small package sizes was greater and differed by region.

Assessing the association between the Mexican tax on nonessential high-calorie foods and consumer prices, Gračner, Kapinos, and Gertler [ 102 ] found that the average price of energy-dense food in Mexico increased by 4.8% immediately after the tax came into effect. In addition, price increases were greater in supermarkets than in mini-markets and convenience stores. Grogger [ 99 ] also found similar evidence indicating that the price of soda rose by more than the amount of the tax. Aguilera Aburto et al. [ 51 ] studied how the prices of snacks changed after the Mexico food and beverage tax by estimating the potential impact of the price increase on the consumption of snacks. Their results indicated that the snack industry transferred all the tax to the prices of snacks. Salgado and Ng [ 101 ] found evidence that suggested that price changes might be the result of an increasing price trend rather than tax implementation. In addition, their firm-level analyses mostly showed that price increases by leading firms were greater than the overall increase at the food market level.

Navajo: George et al. [ 52 ] reported that the average cost per item of fresh fruit decreased by 13% in Navajo stores but increased by 16% in border stores.

Pacific: Thow et al. [ 24 ] reviewed the effectiveness of taxing soft drinks in the Pacific, specifically Fiji, Samoa, Nauru, and French Polynesia. The authors found that, in Fiji, casual monitoring of prices by the Ministry of Health staff suggested that the price of a 2-liter bottle of branded soft drink increased by 10 cents over the first half of 2006 (consistent with a 5-cents/Liter tax increase) from FJ$1.70 to 1.80.

Philippines: Onagan et al. [ 56 ] found that the implementation of the sugar-sweetened beverage tax led to a 20.6% and 16.6% increase in the price of sweetened beverages in convenience stores and supermarkets, respectively, a month after the tax came into effect.

Portugal: Gonçalves and Pereira dos Santos [ 61 ] reported a full-price pass-through for taxed beverages containing more than 80 g per Liter of sugar and more than a 100% price pass-through for beverages containing less than 80 g per Liter of sugar.

Saudi Arabia and South Africa: Alsukait et al. [ 63 ] estimated a pass-through rate of 110% for carbonated drinks after the implementation of the Saudi Arabia SSB tax. Stacey et al. [ 105 ] estimated that the price of carbonated drinks increased by 1.006 ZAR/litre following the introduction of the South African SSB tax.

Berkley, USA: Silver et al. [ 76 ] assessed the implications of the Berkley beverage tax one year after it came into effect. The results of the study suggested that supermarkets (both large and small) and gas stations had a 100% tax pass-through; pharmacies had a partial tax pass-through, while corner stores and independent gas stations had a negative tax pass-through. Falbe et al. [ 106 ] assessed the short-term (3 months after the tax) ability of the Berkely SSB tax to increase retail prices. They found that for smaller beverages (≤ 33.8 oz), the price increases in Berkeley relative to those in comparison cities were 0.47–0.68 cents/oz. For 2-L bottles and multipacks of soda, the relative price increases were 0.46 and 0.49, respectively. However, the prices of nontaxed drinks remained the same. Cawley and Frisvold [ 107 ] also assessed the pass-through of the Berkley SSB tax using a difference-in-differences model. They found that across all brands and sizes of products examined, 43.1% of the tax was passed on to consumers.

Boulder, USA: In July 2017, Boulder, Colorado, implemented a two-cents per ounce excise tax on the distribution of beverages with added sugar and other sweeteners. Cawley et al. [ 108 ] assessed the pass-through rate of the tax and found that consumers bear most but not all the tax; in both the hand-collected store data and restaurant data, the pass-through was slightly less than 75%, whereas the pass-through was just over 50% using scanner data.

Cook County, USA: Powell and Leider [ 78 ] found that prices increased by 1.13 cents per fluid ounce during the 4 months that the Cook County sugar-sweetened beverage tax was implemented. Another study by Powell, Leider, and Léger [ 109 ] showed that the tax had a pass-through of 119%, increasing the average price of SSBs by 34%. However, the price increase ranged from a 52% increase for family-size soda to a 10% increase for family-size energy drinks.

Oakland, USA: Marinello, Pipito, et al. [ 110 ] used a difference-in-differences analysis to evaluate the effect of the Oakland 1-cent/ounce sugar-sweetened beverage tax on the prices of beverages sold in fast-food restaurants two years after the tax was implemented. The authors found that the price of bottled regular soda increased by 1·44 cents/oz (tax pass-through rate of 144%), and the price of bottled diet soda increased by 1·17 cents/oz. Cawley et al. [ 111 ] assessed the impact of the Oakland SSB tax on prices, purchases and consumption by adults and children. They concluded that approximately 60% of the tax was passed on to consumers. Assessing the pass-through effect of the tax two years after its implementation, Leider, Li, and Powell [ 112 ] found that taxed beverage prices increased by 0.73 cents/ounce on average in supermarkets and grocery stores in Oakland relative to comparison sites and 0.74 cents/ounce in pharmacies but did not change in convenience stores. Marinello et al. [ 113 ] found that the Oakland SSB tax had an 82% pass-through a year after its implementation. They also showed that both diet and regular soda had similar price changes, even though they were not significant.

Seattle, USA: Powell and Leider [ 82 ] assessing the impact of the Seattle SBT showed that the prices of taxed beverages increased by 1.04 cents per ounce (59% tax pass-through rate). However, Jones-Smith et al. [ 114 ] reported an average increase of 1.58 cents per ounce among Seattle retailers, a pass-through rate of 58–104%. The price increases were greatest for smaller grocery stores and drug stores. Another study by Powell and Leider [ 84 ] found a much lower price increase of 1.03 cents per ounce corresponding to a 59% pass-through rate.

Philadelphia, USA: Roberto et al. [ 86 ] assessed the impact of the Philadelphia beverage tax on beverage prices and sales in Philadelphia and Baltimore, Maryland (a control city without a tax). The authors found a significant increase in prices: 0.65 cents per ounce at supermarkets, 0.87 cents per ounce at mass merchandise stores, and 1.56 cents per ounce at pharmacies. Bleich et al. [ 87 ] found that the Philadelphia beverage tax increased taxed beverage prices by 2.06 cents per ounce, corresponding to a 137% pass-through rate two years after implementation. Cawley, Willage, and Frisvold [ 115 ] assessed the pass-through of the tax at the airport and found that prices had increased by 0.83 cents per ounce more in tax than untaxed stores, corresponding to a pass-through of 55.3%. A study by Petimar et al. [ 91 ] revealed that taxed beverage prices increased by 1.02 cents per ounce two years after the policy came into effect. Bleich et al. [ 92 ] found a much greater impact of the tax, with a 1.81 cents per ounce or a 120.4% increase in prices after the tax was implemented. However, Seiler et al. [ 93 ] found that the tax led to only a 34% price increase, corresponding to a 97% pass-through. Cawley et al. [ 116 ] found that, on average, distributors and retailers fully passed the Philadelphia SSB tax to consumers. However, the pass-through rate varied by store type, neighbourhood, and proximity to untaxed stores.

Theme 3: Implication of taxes for health

Table  4 shows a summary of the results discussed in this section. Most of the studies are based on simulating the health implications of implemented government policies. The results conclusively revealed a significant impact of tax policies on improving population health, reducing obesity and related diseases, increasing the number of lives saved, and reducing NCD such as diabetes, ischaemic heart disease and stroke.

Rogers et al. [ 122 ] assessed the impact of the SDIL on obesity in the United Kingdom and reported that there was a reduction in obesity among 6-year-old girls, with the greatest differences in those living in deprived areas. No significant changes were found for boys. Rogers et al. [ 123 ] estimated a relative reduction of 12.1% in hospital admissions for carious tooth extractions in all children (0–18 years) following the implementation of the levy.

Denmark: Smed et al. [ 19 ] found that the fat tax imposed on saturated fat saved 123 lives annually, 76 of which were less than 75 years old, equivalent to 0.4% of all deaths from NCD. In general, the tax had a more positive impact on men than women. Bødker et al. [ 20 ] also examined the effects of fat tax on the risk of ischemic heart disease (IHD) using retail outlet data on 12 foodstuffs targeted by the tax. The results from the study were inconclusive, suggesting an increase in the population risk of IHD of 0.2%, and the other estimate suggested that the risk of IHD decreased by 0.3%.

Mauritius: Cawley et al. [ 27 ] found that the Mauritius SSB tax had no effect on BMI for the full sample of youth considered in their data. However, BMI among male youth was reduced by 11% after the tax was implemented.

Mexico: Using published data on the reductions in beverage purchases due to the Mexican SSB tax, Barrientos-Gutierrez et al. [ 124 ] modelled the expected long-term impacts on body mass index (BMI), obesity, and diabetes. Their results showed an average BMI reduction of 0.15 kg/m2 per person, which translates to a 2.54% reduction in obesity incidence. People with the lowest socioeconomic status and those between 20 and 35 years of age had the greatest reductions in BMI and in the prevalence of overweight and obesity. Basto-Abreu et al. [ 118 ] assessed the cost-effectiveness of the SSB excise tax in Mexico. The results from their study suggest that the current tax is projected to prevent 239,900 cases of obesity, 39% of which are among children. It could also prevent 61,340 cases of diabetes, lead to gains of 55,300 quality-adjusted life-years, and avert 5,840 disability-adjusted life-years. Grogger [ 99 ] concluded that soda price increases could lead to a 2- to 3-point reduction in mean weight, which amounts to approximately 1–2% of the mean body mass. Hernández-F, Cantoral, and Colchero [ 119 ] studied the effect of the Mexican food and beverage tax on dental health in Mexico. The authors showed that taxes were associated with a lower probability of having dental caries and with a lower number of teeth with caries experience in the samples studied.

Philippines: Saxena, Koon, et al. [ 120 ] modelled the impact of the Philippine’s sweetened beverage tax and reported that the tax could avert an estimated 5,913 deaths related to diabetes, 10,339 deaths from ischaemic heart disease and 7,950 deaths from stroke over 20 years.

Thailand: Urwannachotima et al. [ 121 ] assessed the impact of the sugar-sweetened beverage tax on dental caries and concluded that the policy could reduce dental caries in the country by only 1% by 2040.

South Africa: Assessing the impact of the South African HPL on health, Saxena, Stacey, et al. [ 125 ] estimated a reduction of 8,000 Type 2 Diabetes Mellitus (T2DM)-related premature deaths over 20 years, with most deaths averted among the third and fourth income quintiles.

Portugal: Goiana-da-Silva et al. [ 60 ] estimated that the sugar-sweetened beverage tax prevented 40–78 obese patients per year between 2016 and 2018. Goiana-da-Silva, Cruz-e-Silva, et al. [ 59 ] concluded that the decline in sales and SSB consumption due to the tax could translate into 1,600 fewer obese people or delay 27 deaths directly related to excessive sugar consumption in Portugal every year.

Theme 4: Implications for nontargeted foods

Eleven studies across nine jurisdictions were found to address the impact of taxation on nontargeted foods (See Table  5 ). The authors found that increasing taxes on unhealthy foods could drive up the consumption of vegetables and water, increase the sales of untaxed food products, and increase the prices of untaxed beverages, juices, etc. It is evident that tax policies have the potential to redistribute consumption towards healthier food options while reducing purchases of unhealthy foods.

United Kingdom: Chu et al. [ 126 ] reported that children’s and lunchbox beverages, though exempted from the SDIL, had higher sugar contents than recommended after the levy implementation.

Denmark: According to Smed et al. [ 19 ], the Danish fat tax increased the consumption/purchases of vegetables as well as salt.

France: According to Capacci et al. [ 23 ], the 2012 French soda tax did not have any significant impact on the demand for nontargeted foods such as fruit juices and water.

Navajo, USA: Trujillo Lalla et al. [ 53 ] reported that the Navajo tax on unhealthy foods and beverages resulted in increased demand for water. Specifically, shoppers in 2019 were 1.5 times more likely to purchase water than were those in 2017.

Berkley, USA: Silver et al. [ 76 ] assessed the implications of the Berkley beverage tax one year after it came into effect. They found that the sales of untaxed beverages in Berkley increased. Falbe et al. [ 75 ] found that water consumption increased more in Berkley than in the neighbouring untaxed cities of Oakland and San Francisco. A study by Lee et al. [ 77 ] concluded that water consumption increased by 1.02 times per day 3 years after implementation.

Cook County, USA: Powell et al. [ 79 ] found that the Cook County SSB tax had no significant effect on the volume of untaxed beverages sold in the city or its border area. Marinello et al. [ 110 ] reported similar price increases for both taxed and untaxed bottled soda in fast-food restaurants. Leider et al. [ 112 ] reported that the price of untaxed beverages increased by 0.40 cents/ounce in pharmacies following the implementation of the tax. However, the price remained unchanged for the other store types.

Seattle, USA: Powell et al. [ 127 ] found no change in the sales of untaxed beverages two years after the Seatle SSB tax was implemented. Assessing the implications of the Seattle tax for alcoholic beverages, Powell and Leider [ 128 ] reported that the overall volume of alcohol (both beer and wine) sold increased by 4% a year after the tax came into effect and by 5% two years after the tax was implemented. Powell and Leider [ 84 ] reported that Seattle SBT had a moderate impact on untaxed beverages, resulting in a 4% increase in volume sold.

Philadelphia, USA: Zhong et al. [ 85 ] found a positive impact of the tax on the consumption of bottled water; purchases increased by 58%. However, Bleich et al. (2021b) did not find significant changes in the purchases of nontaxed beverages in Philadelphia. Among high school students, Edmondson et al. [ 88 ] found that the tax shifted purchases towards more juice than those in nontaxed cities. Gibson [ 129 ] found no evidence of an increase in snacks or spirits following the Philadelphia tax, but there was evidence of substitution for beverage concentrates in supermarkets. Petimar et al. [ 91 ] reported that the Philadelphia SSB tax resulted in a 34% increase in the volume of nontaxed beverage concentrates sold; however, there was no evidence of substitution for high-calorie foods. Seiler et al. [ 93 ] did not find any significant substitution for bottled water, but there was a modest substitution for untaxed natural juices. Cawley et al. [ 116 ], on the other hand, reported that the Philadelphia tax increased the availability of untaxed beverages, particularly bottled water, in Philadelphia stores. Cawley et al. [ 94 ] compared the impact of the tax on beverage consumption by children and adults and found that there was no impact on the consumption of other untaxed beverages. Lozano-Rojas and Carlin [ 130 ] found that the imposition of the Philadelphia SSB tax increased sugar purchases by 4.3% and 3.7% in neighbouring cities, indicating substitution for other sugary foods. Grummon [ 95 ] found that the Philadelphia tax had no impact on other high-calorie/high-sugar nontaxed foods, beverages, or alcohol.

Tonga: Teng et al. [ 72 ] and Teng et al. [ 73 ] reported a significant increase in bottled water purchases following the implementation of the Tonga sweetened beverage tax.

Spain: Fichera et al. [ 68 ] found a very small impact of the Catalonia SSB tax on nontaxed beverages.

South Africa: Stacey et al. [ 105 ] showed that the SSB tax had no impact on the prices of nontaxed beverages in South Africa.

Theme 5: Implications for economic welfare

Seven studies across six jurisdictions were found to assess the impact of taxes on the economic welfare of consumers (see Table  6 ).

United Kingdom: A study by Fage [ 131 ] concluded that SDIL resulted in nontrivial economic welfare loss, especially among low-income households.

France: Etilé et al. [ 98 ]assessing the economic welfare of the French soda taxon, found that the impact of the tax was greater for low-income and high-consuming households.

Hungary: Bíró [ 25 ] also assessed the implications of the junk food tax on consumer welfare and found that lower-income households were more affected by the tax.

Mexico: Colcheroet al. [ 45 ] found that the Mexican SSB tax had differential impacts on different demographic factors, with greater reductions in SSB purchases for lower-income households, households living in urban areas and households with children. Rivera-Dommarco et al. [ 31 ] also confirmed that the Mexican SSB tax affected lower-income households more than all other income groups. In addition, Colchero et al. [ 46 ] estimated the impact of the SSB excise tax on purchases of SSBs from stores one year after its implementation and found that lower-income households reduced their purchases more than middle- and higher-income households. Batis et al. [ 48 ] also found that the Mexican nonessential energy-dense tax had a greater impact on lower-income households than on higher-income households. Similarly, Hernández et al. [ 50 ] found that urban and lower-income households and households with children were more financially affected by the tax on nonessential energy-dense foods. In contrast, Sánchez-Romero et al. [ 29 ] did not find any significant variation in the impact of the SSB tax across income levels and consumers based on their educational backgrounds.

Tonga: Teng et al. [ 72 ] found that the sweetened-beverage tax had a greater financial impact on low-income than on high-income households in terms of purchase prevalence.

Thailand: Phulkerd et al. [ 74 ] showed that the SSB tax in Thailand had a greater impact on males, lower-income populations, older persons and unemployed individuals. Finally, in South Africa, Bercholz et al. [ 65 ] showed that the South African SSB tax was more regressive in lower socioeconomic status households.

Theme 6: Implications for marketing

Table  7 shows the implications of the tax policies for marketing. One study in one jurisdiction analysed the implications of food and beverage taxes for retail marketing. The authors concluded that taxes have a negative impact on retail marketing practices. Oakland: Zenk et al. [ 132 ] examined the impact of the Oakland tax on in-store marketing practices—advertising and price promotions. They found that the odds of SSB price promotions fell by 50% in Oakland but only 22% in Sacramento. In addition, price promotions for regular soda declined by 47% at 6 months and 39% at 12 months in Oakland (versus no change in Sacramento). Similarly, the price of artificially sweetened beverages decreased by 55% after 6 months and 53% after 12 months. However, the tax did not affect the advertising of sugar-sweetened or artificially sweetened beverages. Surprisingly, Zenk et al. [ 133 ] did not find any long-term (2 years) pre-post impact of the tax on in-store marketing practices—price promotions, exterior or interior advertising, or sale depth—for SSBs and untaxed beverages.

Theme 7: Other impacts

The final scope of the review includes strands of studies that do not fall under themes 1–6. Table  8 shows that these strands of studies assessed the impact of employment in the SSB industry on Supplemental Nutrition Assistance Program Users, stockpiling behaviour, cross-border shopping, government savings and expenditures as well as store type.

Pedraza et al. [ 144 ] found that taxes may have differential effects on different store types; consumers choose different stores to purchase beverages than to purchase foods.

Léger and Powell [ 80 ] found cross-border shopping following the implementation of the Oakland SSB tax. However, Powell and Leider [ 84 ] found no cross-border shopping associated with Seattle’s sweetened beverage tax.

Marinello et al. [ 134 ] assessed the implications of the San Francisco tax on employment and concluded that the tax had no negative impact on net employment, employment in the private sector, or employment in specific SSB-related industries. Marinello et al. [ 136 ] also assessed the impact of the Philadelphia beverage tax on employment using synthetic control analysis. The authors found that the city’s employment count was not lower than its synthetic control, indicating that the tax had no impact on employment.

Assessing the Philadelphia SSB tax on the Supplemental Nutrition Assistance Program (SNAP) run by the government, Chrisinger [ 135 ] found that the tax contributed to increased SNAP shopping in Philadelphia’s neighbouring counties but decreased spending in Philadelphia.

Gonçalves and Pereira dos Santos [ 61 ] found stockpiling by consumers before the implementation of the Portuguese soda tax in 2017. A similar situation occurred in the UK before the implementation of soft drink industry levy. In addition, producers reduce the sugar content of several drinks to pay a lower tax [ 145 ].

Saxena et al. [ 120 ] found that the Philippine sugar tax could generate total healthcare savings of 627 million United States dollars over 20 years and increase revenue by US$ 813 million annually. Another study by Saxena et al. [ 125 ] estimated that the South African government would save US$140 million in subsidised healthcare over 20 years and would raise US$450 million in tax revenues per annum. In Nauru, Thow et al. [ 24 ] showed that the government was able to raise approximately US$200,000 because of the tax. In French Polynesia, the total annual revenue increase was US$10 million from domestic production and US$4.2 million from import taxes [ 24 ].

Food subsidy programs

Baronberg et al. [ 141 ] assessed the impact of New York City’s Health Bucks Program on EBS at farmers’ markets. In an attempt to increase the accessibility and reduce the cost of fresh produce, health bucks were introduced in 2005 by the New York City Department of Health and Mental Hygiene (DOGHMH). This was a coupon distribution program providing financial incentives for low-income New Yorkers to buy at farmers’ markets in the city’s highest poverty areas. The health bucks were distributed to residents by community-based organisations and could be used at any of the participating markets during the annual growing season (i.e., July 1–November 15). The recipients were SNAP participants who received 2 dollars for every 5 dollars spent using SNAP benefits in participating farmers’ markets. The authors found that farmers’ markets that offered health buck coupons to SNAP recipients had higher average daily EBT sales than markets without incentives. They concluded that implementing the program in other urban areas among low-income shoppers could increase healthful food access and affordability in low-income neighbourhoods.

Young et al. [ 140 ] assessed the impact of the Philly Food Bucks program on increasing fruit and vegetable consumption in Philadelphia, USA. From 2010 to 2011, the Food Trust, in collaboration with the Philadelphia Department of Public Health, funded Get Philly to give 2 dollars bonus incentives for every 5 dollars in SNAP that could be redeemed from farmers’ markets only for fresh fruits and vegetables. The goals of the initiative were (1) to increase fruit and vegetable consumption among low-income communities, (2) to increase purchasing power for fruits and vegetables, and (3) to increase the use of SNAP at farmers’ markets. Similar to the program in New York, the coupons were distributed by community-based organisations that served SNAP-eligible populations to promote farmers’ market access among low-income residents. Additionally, the coupons could be redeemed by making a SNAP purchase. The study relied on a convenience sample of 662 customers at 22 farmers’ markets in low-income neighbourhoods in Philadelphia using face-to-face interviews. Their results showed that compared with nonusers, individuals who use food bucks were significantly more likely to report increasing fruit and vegetable consumption. In addition, SNAP sales increased for participating farmers’ markets in low-income communities.

Gleason et al. [ 139 ] assessed the impact of the revised WIC Food Package on Small WIC Vendors in four US states. In an attempt to promote healthy diets and reduce childhood obesity epidemics among children and their families in the USA, the Federal Government implemented nutrition programs such as the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Participation in the WIC program is limited to low-income pregnant, postpartum, and breastfeeding women and infants and children under the age of 5 years. The impact assessment was based on data collected from WIC-authorised vendors gathered from agencies before and after the package changes were introduced. The authors analysed store inventory data to assess the overall availability of the new WIC foods following the implementation of the new food packages, changes in food availability over time, and how the availability of foods and food categories differed over time by store size and by state. The study revealed that the majority of WIC stores were able to maintain their authorisation status. Additionally, small WIC stores added healthy foods to their inventory in response to the changes in the WIC food package. In addition, the majority of the stores made changes to their registers to meet the new WIC food package requirements. The authors concluded that the implementation of the WIC food package program was generally successful.

In 2016, Lu et al. [ 138 ] built on the work of [ 139 ] by evaluating the influence of the Revised Special Supplemental Nutrition Program for Women, Infants and Children (WIC) on food allocation packages on healthy food availability, accessibility, and affordability in WIC authorised grocery stores in Texas (a state not included in the Gleason et al. study). They went further to show how the impact of the policy differs among different stores and locations (urban vs. rural). As explained previously, the Special Nutrition Program for Women, Infants, and Children (WIC) was implemented to improve the health of pregnant women and children with low socioeconomic status. The study sampled 105 stores across Texas, and data were collected before and after the implementation of the program. The authors used paired sample t tests to assess the differences before and after the policy implementation. The results from the evaluation study suggest that the availability of most healthy food options (i.e., fruits, vegetables, cereals, and a variety of vegetables) increased in terms of shelf space. The visibility of WIC program labelling increased for fruits, cereals and whole-grain or whole-wheat bread. In general, healthy food availability and visibility increased for stores of different types and in different locations. However, the affordability of healthy foods did not improve in WIC-authorised stores in Texas.

Galloway et al. [ 146 ] evaluated the performance of the Nutrition North Canada retail subsidy to ascertain whether it was meeting its goal of making nutritious and perishable food more accessible and affordable in northern counties. Nutrition North Canada was launched by the Aboriginal Affairs and Northern Development Canada (AANDC) in 2011 to offset the cost of transporting perishable foods to northern counties that do not have road access all year round. The program replaced the older Food Mail program, which has offered flight subsidies through Canada Post Corporation since the 1960s. The current program is a federal retail subsidy designed to make nutritious, perishable food more widely available and affordable in northern communities. The author found that there is little evidence to show that the program met its goal of improving the availability of nutritious food. Specifically, the fiscal reporting and food costing tools used by the program were insufficiently detailed to evaluate the accuracy of community subsidy rates and the degree to which retailers are passing on the subsidy to consumers.

In 2017, Galloway [ 137 ] performed another comprehensive assessment of the Nutrition North Canada retail subsidy. The assessment was based on program documents, including fiscal and food cost reports for the period 2011 to 2015, retailer compliance reports, audits of the program, and the program performance measurement strategy. The author found that the program lacked a price cap to ensure that food is affordable and equitably priced in communities. In addition, it was difficult to account for the program due to gaps in food cost reporting. The author concluded that the existing structure and regulations of the NNC are not sufficient to ensure that the program meets its goal.

The Mexican government has implemented a subsidy scheme since the mid-1960s. The government has implemented subsidy programs for staple foods usually consumed by poor households. These include maize, wheat, beans, cooking oil, oilseed, rice, sorghum, soybeans and sugar. In principle, the government purchases these foods at the domestic or international market at the prevailing price and then sells them to the processor or packager or directly at a lower price, excluding the distribution and storage cost to consumers. The price consumers pay is set by the Ministry of Commerce. In addition, the government also intervenes in the wholesale and retail of basic foodstuffs. The government’s distribution network reduces the wholesale cost of participating government retail stores and small private shops. Most participating shops are located in low-income urban neighbourhoods. The prices consumers pay in government-run retail shops are estimated to be 10–12% lower than those in nonparticipating stores.

The Healthy Start program was introduced in 2006, providing vouchers to pregnant women and families with children younger than 4 years of age who receive certain benefits. Beneficiaries are allowed to exchange vouchers for fruit and vegetables, milk or infant milk. Eligible persons are sent a Healthy Start card containing money for use in retail shops. The card can be used to purchase plain liquid cow’s milk; fresh, frozen, and tinned fruit and vegetables; fresh, dried, and tinned pulses; and infant formula milk. Scantlebury et al. [ 147 ] assessed the impact of the Healthy Start program on fruit and vegetable intake among beneficiaries. The authors relied on repeated cross-sectional data from the Healthy Survey for England. Outcomes were compared across the four groups over four time periods: 2001–2003, 2004–2006, 2007–2009 and 2010–2014. This study revealed that during the period from 2001 to 2003 to 2010–2014, fruit and vegetable consumption among adults and children in households deemed eligible for HS changed similarly to that of other adults and children. The authors explained that vouchers might have been spent on other foodstuffs, i.e., milk or infant formula, instead of fruit and vegetables.

The Mexican tortilla program started in the mid-1960s. The government purchases maize at a given price and sells it to mills at a lower price. The government also absorbs all the distribution and storage costs. The final price of the product, i.e., tortillas, maize flour and maize dough, is set by the government. Assessing the nutritional and economic impact of the tortilla subsidy program, Shamah Levy et al. [ 143 ] found that tortilla consumption represented 45% of total household food expenditure and that the subsidy program reduced it to 9%. In addition, the authors found that communities engaged in the program had a lower malnutrition index than those outside of the program.

A fruit and vegetable subsidy program was instituted by the Bulgarr Ngaru Medical Aboriginal Corporation for the Aboriginal Communities in Rural Towns in the Clarence Valley in New South Wales, Australia, in 2005. The beneficiaries paid approximately 5 dollars for a box containing 40 dollars of fruits and vegetables. Low-income households with one or more young children were invited to participate in the program. Black et al. [ 142 ] assessed the nutritional impact of the subsidy program and revealed that fruit and vegetable intake increased; β-cryptoxanthin, vitamin C, and lutein–zeaxanthin levels increased significantly after 12 months of participation in the program.

The present study reviewed 127 papers assessing the impact of existing fiscal policies (taxes and subsidies) across the globe on consumer behaviour and the food environment. The studies included in this review were from Europe, Africa, Asia, and South and North America. The results from the various studies were grouped into 7 themes for taxes and 1 theme for subsidies. The themes include the impact of fiscal policies on consumption, purchases, and sales; targeted and nontargeted foods; consumer economic welfare; prices of nontargeted foods; and retail marketing strategies. The studies considered for this review consider different types of taxes and subsidies applied to different types of foods high in fat, sugar and salt. The focus of most fiscal policies is on SSBs or sweetened beverages, foods that are energy-dense and fruits and vegetables. Approximately 39% of the studies are from the United States (comprising states such as Philadelphia, New York, Oakland, San Francisco, Seattle, Navajo, Cook County and Boulder), 16% are from Mexico, 13 are from the United Kingdom, and 4% are from each of the following countries: Chile, Portugal, South Africa, Denmark, France, Hungary, and Spain. Fewer than 4% of the remaining countries evaluated the impact of fiscal measures implemented.

The degree to which fiscal policies can achieve their desired impact is a function of the tax rate and the tax pass-through rate [ 70 ]. Most studies suggest a tax rate of 20% and above to achieve significant changes in consumer behaviour. The present review shows two findings: government taxes on SSBs and energy-dense foods are usually less than a 20% price increase, and not all taxes are transmitted to consumers. A lower pass-through rate is usually due to reformulation by firms and the absorption of a significant amount of taxes by manufacturers and retailers to maintain their market shares. Price increases and pass-through rates are different for different countries and even different studies within the same country. For instance, in Philadelphia, Bleich et al. [ 92 ] reported a 120% price increase due to the beverage tax; however, Seiler et al. reported a 34% price increase, approximately four times lower than the former. Similarly, in France, Capacci et al. [ 23 ]found a full-price pass-through, while Etilé et al. [ 98 ] found a 34% price pass-through of the same policy. Silver et al. [ 76 ] also showed that a tax policy in one country could have different pass-through rates for different types of stores or shops. This indicates that tax policies are asymmetrically transmitted from point of application to consumers. Despite the profound variations in the results across different jurisdictions, the impact of the policies on prices was positive and significant.

The majority of the studies in this review were centred on Theme 1, the implications of tax policies for consumption, purchases, and sales. A total of 72 studies out of the 126 studies were grouped under this theme. Five out of the 72 studies did not find any impact of the policy on sales, purchases or consumption. However, the majority of the studies found a significant impact of tax policies on the consumption, sales, and purchases of consumers. For instance, studies assessing the implications of the Danish fat tax found that saturated fat purchases fell. A similar result was obtained for Mexico following the implementation of the one peso per Liter excise tax on sweetened beverages. In Chile, although the impact of the policy was found to be small, observable reductions in purchases were confirmed.

The results for the implications of taxes on sales are mixed. Øvrebø et al. [ 54 ] and Gibson et al. [ 129 ], assessing the implications of government policies for Norway and Philadelphia, found no significant impact on the targeted foods. However, studies from France, Mexico, Hungary, Portugal, Spain, Saudi Arabia, and Berkley (USA) found significant reductions in sales. For instance, Colchero et al. [ 148 ] found that SSB sales in Mexico declined by 7.3% per capita sales. In the Philippines, Claire et al. [ 56 ] estimated an 8.7% decrease in convenience stores. Castelló and Casasnovas [ 70 ] estimated a 7.7% decrease in SSB sales due to the tax. The largest decrease in sales volume was for Saudi Arabia, at 57% from 2010 to 2017. Finally, Goiana-da-Silva, Cruz-e-Silva, et al. [ 58 ] estimated a 7% reduction in sales due to the Portuguese sweetened beverage tax. These results show that SSB taxes have a significant impact on retail sales. Studies finding that the positive impact of the tax outweighs those that did not find any impact of taxes and cuts across different jurisdictions.

Various studies have shown that households with lower incomes rely on less nutritious and energy-dense foods for their daily caloric intake [ 149 , 150 ]. This is evident not only in Scotland but also across different countries and continents. As a result, lower socioeconomic groups suffer financially when fiscal policies are implemented by governments. The results from studies by Etilé F et al. [ 98 ], Bíró [ 25 ], Colchero MA et al. [ 31 ], Batis et al. [ 151 ], Teng et al. [ 72 ], and Phulkerd et al. [ 74 ] confirmed that socioeconomically disadvantaged groups were highly negatively impacted by the tax policies implemented by governments in France, Hungary, Mexico, Tonga and Thailand. In addition, residents, in urban areas, households with children, underemployed individuals, males and older persons or populations are likely to suffer more from tax policies than all other demographic groups. The reason is that these groups derive most of their energy intake from food products imposed with the tax.

Eleven studies assessed the impact of government policies on consumers’ health and nutrition. The evaluation studies were from Denmark (2), Mauritius (1), Mexico (4), the Philippines (1), Portugal (1), Thailand (1) and South Africa (1), which span Europe, Africa, Asia and North America, respectively. Bødker et al. [ 20 ] were inconclusive about the implications of the policy in Denmark for health, while Cawley et al. found no effect of the Mauritius policy on the BMI of the average population but a significant effect on the BMI of men. Aside from these two studies, the remaining 9 studies found a significant impact of the policies on population health. Barrientos-Gutierrez et al. [ 117 ] and Grogger [ 99 ] reported that the average BMI and prevalence of obesity decreased following the implementation of the Mexican sugar-sweetened beverage tax. Saxena et al. [ 120 ] estimated a reduction in deaths related to diabetes, ischaemic heart disease and stroke in the Philippines. Urwannachotima et al. [ 121 ] and Basto-Abreu, Ana, et al. [ 118 ] reported significant reductions in dental caries in Thailand and Mexico, respectively. In Denmark, Smed et al. [ 19 ] estimated that 123 lives could be saved annually due to the fat tax. These results confirm the conclusion made by Blakely et al. [ 152 ] regarding proposed food taxes and subsidies in New Zealand. In addition, the results of this review support the use of fiscal policies such as all forms of food and nutrition taxes to nudge consumers towards healthy living.

Approximately 24 studies explored the implications of implemented tax policies on nontargeted foods. Seven out of the 24 studies concluded that tax policies had no significant impact on the consumption [ 94 , 129 ], purchase [ 23 , 79 , 95 ], price [ 105 ] or sales [ 81 ] of nontargeted food products. The majority of the studies found a significant impact of the policy on nontargeted foods resulting from the substitution effect. For instance, in Tonga, Teng et al. [ 72 ] and Teng et al. [ 73 ] found a significant increase in bottled water purchases following the imposition and revision of the tax on SSBs. A similar result was found by Lee et al. [ 77 ] in Berkley, Lalla et al. [ 53 ] in Navajo, and Zhong et al. [ 85 ] in Philadelphia. Additionally, in Philadelphia, Edmondson et al. [ 88 ] and [ 93 ] reported a significant shift in the demand for fruit juice. In Denmark, Smed et al. [ 19 ] found that the tax led to a significant increase in the consumption of vegetables. Other authors have found significant increases in the sales [ 76 , 91 ], purchases [ 92 ] and prices [ 113 ] of untaxed foods. These results clearly show that fiscal policies tend to have unintended effects on inter-category and intra-category purchases, prices and sales. Therefore, a prior assessment of the tax, as in the case of New Zealand, is relevant before implementation.

The last part of the review on taxes did not fit into any of the proposed themes for this review. However, the results were captured considering their relevance to the topic (see Table). Both [ 110 , 136 ] found no impact of taxes on employment in the counties (San Francisco and Philadelphia) and the SSB sector. The results from this theme also confirm that the government could raise revenues from taxes. Saxena et al. [ 120 ] and Saxena et al. [ 125 ] estimated 813 million dollars and 450 million dollars per annum increase in revenue for governments in the Philippines and South Africa, respectively. In addition, both governments could save on healthcare expenditures because of the tax policy. Gonçalves and dos Santos [ 61 ] found that the prior announcement of the tax in Portugal resulted in stockpiling. A strategy adopted by consumers to reduce cost or evade price increases due to the tax. Although Léger and Powell [ 80 ] found evidence of cross-border shopping in Oakland, Powell and Leider (2020) [ 84 ] found no evidence of cross-border shopping in Seattle. As a result, the impact of the policy on cross-border shopping is conclusive. More impact assessments are required to ascertain how consumers along borders react to taxes. Interestingly, the Philadelphia SSB tax had a negative impact on consumers of the Supplemental Nutrition Assistance Program (SNAP).

The final section of the review considered the impact of subsidy policies on sales, purchases and consumption. Four subsidy policies were identified in the US: 1 in Canada, 1 in Australia, and 1 in Mexico. Gleason et al. [ 139 ] and [ 140 ] reported an increase in the consumption of fruits and vegetables or healthy food options in response to the policy. Baronberg et al. [ 141 ] found that subsidising consumers increased the sales of participating farmers’ markets. On the negative side, Galloway (2017) found that the NIP did not have a positive impact on the prices paid by consumers. However, in Mexico, it was found that consumers saved on expenditures on Tortillas.

The current review has the following strengths. First, this is the first study to review studies on existing fiscal policies across the globe. Second, we explored all areas impacted by government fiscal policies irrespective of the jurisdiction and period of implementation. As a result, the review presents governments and policymakers with adequate knowledge on the topic and the types of fiscal policies that have been implemented elsewhere.

A major limitation of the present review is the exclusion of impact studies that are based on simulations and controlled experiments. However, the results from these types of studies may be relevant to the policy they are excluded because they are not based on actual government policies. Another limitation is that we could not ascertain the quality of the papers included in this review, which could impact the conclusions drawn from them. Moreover, the impact of fiscal policies on health is not based on observed changes but rather on expected changes. Future research could compare the results from implemented tax policies with simulation or controlled experimental studies. Finally, a restriction of scoping reviews is that the broad nature tend to ignore quality assessment as a result the quality of the evidence reviewed cannot be confirmed in this study [ 14 ].

Fiscal policies are necessary to make significant changes within the food market environment. This scooping review provides considerable evidence to suggest that existing fiscal policies have improved consumers’ health, increased the prices of targeted food products, increased government revenue, and shifted consumption and purchases towards healthier food options. The impact of fiscal policies is positive for most continents, countries, jurisdictions, consumer groups and store types. Governments could take advantage of fiscal policies to increase revenues, shape consumer attitudes and reduce the burden of diseases and their propounding effects on healthcare costs. There is limited research on the impact of SSB fiscal policies on cross-border shopping and environmental goals.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Discretionary foods are foods that are not essential for our health. They are a subset of foods high in saturated fat, sugar and salt comprising confectionery, sweet biscuits, crisps, savoury snacks, cakes, sweet pastries, puddings and sugar containing soft drinks.

Ad valorem tax is a tax based on the value of the product; Value-added tax (VAT) is a consumption tax on goods and services that is levied at each stage of the supply chain where value is added; Excise tax is a legislated tax on a product at the time of purchase; and import tariffs are taxes imposed on products imported from other countries.

These are foods low in calories, sugar, unhealthy fats, salts, but high in minerals and vitamins.

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This work was supported by the Rural and Environment Science and Analytical Services Division of the Scottish Government SRUC B4-5 (Food supply and security) and SRUC B5 (Food and Drink Improvement).

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Dogbe, W., Akaichi, F., Rungapamestry, V. et al. Effectiveness of implemented global dietary interventions: a scoping review of fiscal policies. BMC Public Health 24 , 2552 (2024). https://doi.org/10.1186/s12889-024-19988-4

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