Improving the quality of life of the population and introducing sustainable practices into people’s daily life has appeared on the agenda of global society [1]. Access to healthy food and the introduction of sustainable nutrition practices are two important challenges today. The growing interest in sustainable practices and high-quality and healthy products is reflected in the UN Sustainable Development Goals (SDGs): goal 2, ‘end hunger, achieve food security and improved nutrition and promote sustainable agriculture’ [2]. Support of short food supply chains (SFSC) may be one of the solutions to achieve this goal. SFSCs are considered as drivers of sustainable development, as they increase sustainability in all its dimensions; they reduce economic uncertainties, ensure fairness and trust between consumers and producers, and minimize pollution [3]. SFSCs are often associated with the concept of ‘local food’ and ‘local food systems’ but the connection between these concepts remains unclear ^[3][4][5][3,4,5]. Furthermore, the factors influencing consumer preference towards local food have obtained limited attention among scholars [6].

The application of sustainable practices is important and beneficial for SFSC stakeholders: producers, buying organizations, local governments, and consumers. Indeed, local food has been promoted by governmental and civil society organizations for decades [7]. Raising awareness of local food consumption as a sustainable practice among stakeholders could contribute to the further promotion of local food production and distribution.

The COVID-19 pandemic has brought new challenges for food security and social and economic systems, but at the same time, it has provided opportunities for local food production. The Food and Agriculture Organization of the United Nations (FAO) has conducted a survey among different cities in order to monitor local food system status during the COVID-19 pandemic. About 40 percent of the cities that responded to the survey indicated that restrictive measures on human mobility introduced during the pandemic have led to a shortage of labor in local agriculture and food-related activities. The respondents further stated that the shortage of labor negatively affected local food production [8]. TIn this report, the FAO identified five main areas to support local food production and create resilient local food systems. One of these areas is promotion of local food production and providing SFSCs with a greater degree of self-sufficiency. The new barriers to, and opportunities for, local food production during the COVID-19 pandemic have been studied in the scientific literature. The COVID-19 pandemic has forced both customers and restaurants to shift their food habits to more locally grown products; therefore, purchasing local food products has become one of the most notable sustainable practices [9]. The COVID-19 pandemic will have long-lasting effects on food supply chains, including the growth of online grocery shopping and the extent to which consumers will prioritize ‘local’ food supply chains [10]. While in some countries the COVID-19 pandemic significantly restricted local food systems and created more food insecurity, in other countries local food systems continued to operate and were even strengthened by higher social capital and adaptive capacities [11].

2. Study Characteristics

The literature retrieved shows a steady growing trend of the research in the field of consumers’ preference for local food starting from 2016 (Figure 1). Although researchers observe a slight decrease in the studies in the year 2020, the decrease can be explained by the COVID-19 pandemic. Given that almost all the studies were conducted using surveys the lockdowns made it impossible to conduct the research properly. The literature sample comprises 2 quarters of the year 2021 and as researchers can see the number of literature publications in 6 month of 2021, researchers may expect that the total number of the studies in 2021 will approach the pre-COVID period.

Figure 1. Literature publications per year.

Figure 2 shows the distribution of the literature works by the countries which the researchers whose papers researchers examined in this study belong. The leader of research on consumer preference for local food is the USA, with 24 papers on the topic. Italy and Germany have seven papers each, which make them European leaders in research in the field of consumer preference for local food. Researchers also observed the presence of research from Canada (5 papers), and Czech Republic and Spain (4 papers).

Figure 2. Distribution of the literature by country.

The authors of this researchers found it interesting to track the distribution of food types by country. In order to do so, researchers collected the food types discussed in the literature and matched them with the countries where the research was conducted. As can be observed from Table 1, there is no dependence of the food type on geography, except for Guadeloupe (yams) and India (mung bean), who considered these products as indigenous. The USA and Germany had the widest range of studied products. This evidence is apt, as the USA and Germany are the leaders in research on this topic.

Table 1. Food type distribution by country.

	Australia	Canada	Denmark	Estonia	Finland	Germany	Guadeloupe	Hungary	India	Italy	New Zealand	Spain	USA
apples			/	/		/							/
beef		/
beef salami			/
beer						/
blackberry jam													/
bread						/

,23]. This outcome underlines that sustainable issues were not widely studied in the literature sample.

Table 2. Distribution of the keywords by frequency.

Word Combination	Frequency	%	Rank
local food

Table 3. Research method.

Paper	Methodology
29	56.86	1
Holmes and Yan 2012 [16]	Holmes and Yan 2012 [24]	hypothetical choice experiment
willingness to pay	14	27.45	2
consumer preferences	13	25.49	3
organic	13	25.49	3
choice experiment	11	21.57	5
analysis	Rikkonen et al. 2013 [7	2913.73	6
]	online questionnaires or/and phone interviews	broccoli						attributes			6	11.76	7
Tempesta and Vecchiato 2013		[22		]	Tempesta and Vecchiato 2013 [30		]			/
choice experiment	butter						/			consumer behavior	5	9.80
Denver and Jensen 2014	8
[23]	Denver and Jensen 2014 [
31]	choice experiment	chicken breasts	/									consumer preference			4	7.84	9		/
clams
local foods	4		7.84	9
oysters	4	7.84	9
Gracia 2014 [24]	Gracia 2014 [32]								/
craft beer													/
eggs			/			/							/
regional food	4	7.84	9	flour						/
latent class	3	5.88	13	fresh lamb meat												/
marketing	3	5.88	13	fruit yogurt	/
real choice experiment
perception
Moor et al. 2014 [25	3	5.88	13	garlic											/
product	3	5.88	13	hard apple cider													/
honey								/		/
sustainability	3	5.88	13
branding program	2	3.92	18	ketchup
choice experiments	2	3.92	18		/
lemons											/
choice-based conjoint analysis	2	3.92	18	lettuce													/
cider	2	3.92	18
]	Moor et al. 2014 [33]	Survey	milk			/			/				/			class segmentation	/
2	3.92	18	mung bean									/
mussels
component analysis	2	3.92					/
18
conjoint analysis	2	3.92	18	oysters
consumer behavior								2	3.92	18					/
pork					/
consumer demand	2	3.92	18	pork chops
country of origin					2				/
3.92	18	pork cutlet						/
3.92	18
experiments	2	3.92	18
Lesschaeve et al. 2012 [17]	Lesschaeve et al. 2012 [25]
credence attributes	2	rice										/	farm	2	3.92	18
farmers	2	3.92	18
field experiment	2	3.92	18
online survey	food miles	2	3.92	18
food origin	2	3.92	18
food system	2	3.92	18
health	2	3.92	18
horticulture	2	3.92	18
latent class segmentation	2	3.92	18
logistic regression	2	3.92	18
market	2	3.92	3.92
Carroll et al. 2012 [18]	Carroll et al. 2012 [26]	choice experiment	18
Grebitus et al. 2013 [19
18
]	Grebitus et al. 2013 [27]	3.92	18
experimental auction, non-hypothetical Vickrey auction
Kalabova et al. 2013 [20]	Kalabova et al. 2013 [28]	online/offline questionnaire survey	discrete choice experiment	2	3.92	18
organic production	2	3.92	18
price	2	3.92
Rikkonen et al. 2013 [21	economics	2	18
principal component analysis	2	3.92	18
]
Barlagne et al. 2015 [26]	Barlagne et al. 2015 [34]	an economic experiment
Hasselbach and Roosen 2015 [27]	Hasselbach and Roosen 2015 [35]	Interviews
Meas et al. 2015 [28]	Meas et al. 2015 [36]	choice experiment
Aprile et al. 2016 [29]	Aprile et al. 2016 [37]	Survey
Hempel and Hamm 2016a [30]	Hempel and Hamm 2016a [38]	survey, choice experiment
Hempel and Hamm 2016b [31]	Hempel and Hamm 2016b [39]	offline survey, choice experiment
Lim and Hu 2016 [32]	Lim and Hu 2016 [40]	choice experiment
Schifani et al. 2016 [33]	Schifani et al. 2016 [41]	face-to-face questionnaire
Berg and Preston, 2017 [34]	Berg and Preston, 2017 [42]	online and offline survey
Ferrazzi et al. 2017 [35]	Ferrazzi et al. 2017 [43]	Survey
Kecinski et al. 2017 [36]	Kecinski et al. 2017 [44]	dichotomous choice field experiment
Mugera et al. 2017 [37]	Mugera et al. 2017 [45]	random utility discrete choice model framework
Palmer et al. 2017 [38]	Palmer et al. 2017 [46]	focus groups, survey
Sanova et al., 2017 [39]	Sanova et al., 2017 [47]	Survey
Singh et al. 2017 [40]	Singh et al. 2017 [48]	semi-structured and structured interviews
Arsil et al. 2018 [41]	Arsil et al. 2018 [49]	Survey
Brayden et al. 2018 [42]	Brayden et al. 2018 [50]	online survey, choice experiment
Byrd et al. 2018 [43]	Byrd et al. 2018 [51]	online survey, choice experiments
Hashem et al. 2018 [44]	Hashem et al. 2018 [52]	semi-structured interviews, survey	saffron												/
production
Picha and Skorepa 2018 [14]	Picha and Skorepa 2018 [22]	Survey	scallops													/
Picha et al. 2018 [45]	Picha et al. 2018 [53]	offline survey	seaweed salad
Printezis and Grebitus 2018 [46]	Printezis and Grebitus 2018 [		54			]	hypothetical online choice experiment		/
steak						/
strawberries		2
Wenzig and Gruchmann 2018 [47]	Wenzig and Gruchmann 2018 [55]	Survey
Annunziata et al. 2019 [12							]					Annunziata et al. 2019 [		/
20]	self-administered questionnaire	tomatoes						/					/		/
wine						/		quality perception	2	3.92	18
seafood	2	3.92
Denver et al. 2019 [48]	Denver et al. 2019 [56]	quantitative survey, choice experiment
Fan et al. 2019 [49]	Fan et al. 2019 [57]	economic experiment
yams
Farris et al. 2019		[50]	Farris et al. 2019 [58]	discrete choice experiment	/

Table 2 represents the distribution of the keywords used in the studied papers by frequency, in a numerical expression and in percentage. A significant finding of this analysis was that the only keywords that included the word ‘sustainable’ or its derivatives were ‘sustainable food’, which was mentioned twice ^[12][13][20,21] in the studied literature, which amounts to ‘sustainable food’ only being included in 3.92% of all the keywords used; and with ‘sustainability’ being mentioned three times, 5.88% ^[14][15][22

Meyerding and Trajer 2019
[
51
]
Meyerding and Trajer 2019 [
59
]
survey, choice experiment
Meyerding et al. 2019
[
52
]
Meyerding et al. 2019 [
60
]
survey, choice experiment
Profeta and Hamm 2019
[
53
]
Profeta and Hamm 2019 [
61
]
Interviews
Richard and Pivarnik 2019
[
54
]
Richard and Pivarnik 2019 [
62
]	Survey
Skallerud and Wien 2019 [55]	Skallerud and Wien 2019 [63]	Survey
Werner et al. 2019 [56]	Werner et al. 2019 [64]	focus groups
Chen et al. 2020 [13]	Chen et al. 2020 [21]	online survey
Kiss et al. 2020 [57]	Kiss et al. 2020 [65]	online survey
18
Li et al. 2020a [58]	Li et al. 2020a [66]	framed field experiment
Li et al. 2020b [59]	Li et al. 2020b [67]	incentive-compatible framed field experiment
Oravecz et al. 2020 [60]	Oravecz et al. 2020 [68]	personal interview by a paper-based questionnaire with open and decisive questions	supply chain
Sanjuan-Lopez and Resano-Ezcaray 2020 [15]	Sanjuan-Lopez and Resano-Ezcaray 2020 [2	233.92	18
]	hypothetical and real choice experiments	sustainable food	2	3.92	18
Yang and Leung 2020 [61]	Yang and Leung 2020 [69]	hedonic price model	tomatoes	2	3.92
Attalah et al. 2021 [62]	Attalah et al. 2021 [70	18

Figure 3 represents a word cloud of the keywords of the studied papers. As in Table 3, researchers see the common presence of the keyword combinations ‘local food’, ‘consumer preferences’, and ‘willingness to pay’, which isi obvious for this research, since these keywords were used to retrieve the sample. Other noticeable keywords are related to the research and analysis methods applied in the studies: ‘choice experiment’, ‘principal component analysis’, and ‘logistic regression’. Another interesting finding was the frequent presence of the keyword ‘organic’, which stresses the link between local and organic food concepts, and which researchers will discuss later in the paper.

Figure 3. Keyword word cloud.

]

choice experiment

He et al. 2021

[

63

]

He et al. 2021 [

71

]

Experiment

Jensen et al. 2021

[

64

]

Jensen et al. 2021 [

72

]

online survey

Moreno and Malone 2021

[

65

]

Moreno and Malone 2021 [

73

]

a discrete choice experiment, the open-ended survey

Table 3 shows the methodologies applied in the studied literature. Since, all the articles studied consumer preferences for local food, in most of the cases, quantitative methods of analysis were applied: offline and online consumer surveys with open-end and closed-end questions and choice experiments. Some research works applied qualitative methods, such as focus groups and interviews, in order to gather evidence.