Evidence from a Choice Experiment in Consumer Preference towards Infant Milk Formula (IMF) in the Context of Dairy Revitalization and COVID-19 Pandemic

Abstract

China is the largest global consumer of infant milk formula (IMF). Chinese consumer preferences towards IMF have evolved over time but have also been rocked in recent years by COVID-19 with major implications for the IMF industry, globally and within China. This study is the first to document parents’ preferences toward IMF since the outbreak. We used novel methods to do so, through an online choice experiment of 804 participants that included risk perceptions and socio-demographic variables. Our study finds that Chinese parents continue to prioritize quality and safety attributes of IMF represented by functional ingredients, organic labelling and traceability information. Notably, it also finds greatly increased confidence in Chinese domestically produced IMF and an underlying preference away from expensive products. This implies that the era of ‘go for foreign’ and ‘go for the most expensive’ in IMF purchasing may be coming to an end. The shift in sentiment is driven by the longer-term revitalization of the Chinese dairy industry, accelerated by COVID-19. Understanding these trends will be of major benefit to both Chinese producers and non-Chinese exporters of IMF.

Full text

Citation: Zhang, J.; Waldron, S.;
Dong, X. Evidence from a Choice
Experiment in Consumer Preference
towards Infant Milk Formula (IMF)
in the Context of Dairy Revitalization
and COVID-19 Pandemic. Foods 2022,
11, 2689. https://doi.org/10.3390/
foods11172689
Academic Editor: Elizabeth
H. Zandstra
Received: 26 July 2022
Accepted: 1 September 2022
Published: 3 September 2022
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4.0/).
foods
Article
Evidence from a Choice Experiment in Consumer Preference
towards Infant Milk Formula (IMF) in the Context of Dairy
Revitalization and COVID-19 Pandemic
Jing Zhang 1, Scott Waldron 1and Xiaoxia Dong 2,*
1School of Agriculture and Food Sciences, The University of Queensland, Brisbane 4072, Australia
2Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*Correspondence: dongxiaoxia@caas.cn
Abstract:
China is the largest global consumer of infant milk formula (IMF). Chinese consumer
preferences towards IMF have evolved over time but have also been rocked in recent years by
COVID-19 with major implications for the IMF industry, globally and within China. This study is the
first to document parents’ preferences toward IMF since the outbreak. We used novel methods to
do so, through an online choice experiment of 804 participants that included risk perceptions and
socio-demographic variables. Our study finds that Chinese parents continue to prioritize quality
and safety attributes of IMF represented by functional ingredients, organic labelling and traceability
information. Notably, it also finds greatly increased confidence in Chinese domestically produced
IMF and an underlying preference away from expensive products. This implies that the era of ‘go
for foreign’ and ‘go for the most expensive’ in IMF purchasing may be coming to an end. The shift
in sentiment is driven by the longer-term revitalization of the Chinese dairy industry, accelerated
by COVID-19. Understanding these trends will be of major benefit to both Chinese producers and
non-Chinese exporters of IMF.
Keywords: China; infant milk formula; consumer preference; choice experiment
1. Introduction
In an attempt to alleviate concerns about an ageing population and falling birth rate,
China ended its one-child policy in 2015 to allow all couples to have two children and
further relaxed the limit to three children on 31 May 2021 [
1
]. This was followed by incentive
measures including tax deductions, childcare services, financial subsidies, parental leave
and the increased protection of women’s rights in employment [
2
]. Given the very low
exclusive breastfeeding rate in China [
3
], more babies in China could be expected to mean
more babies drinking infant milk formula (IMF), which is one of the most in-demand
and frequently purchased childcare-related products in the country for a range of social,
economical and cultural reasons [4,5].
China relies heavily on imported IMF, especially after the melamine contamination
scandal that engulfed the domestic industry in 2008. Consumers have subsequently pri-
oritised product quality and safety as the most important factors when shopping for baby
food [
6
]. Imported IMF, serving as a proxy for quality and safety, was highly valued in
Chinese consumer preferences and decisions in the pre-COVID-19 era [
7
,
8
]. Particularly
with the introduction of the universal two-child policy in 2015, China’s IMF imports almost
doubled from 179,897 tons to 356,382 tons in 2019, taking around 50% of global export,
favoring mostly European brands as well as products from New Zealand and Australia [
9
].
However, growth ground to a halt after 2019 as China’s global imports of IMF declined by
3% in 2020 and a further 22% to 272,669 tons in 2021. Imports from the two largest global
sources—Netherlands and New Zealand—dropped 19 and 16% respectively, while other
countries dropped 20–40% in volume over between 2020 and 2021 [
9
]. Studies have not
Foods 2022,11, 2689. https://doi.org/10.3390/foods11172689 https://www.mdpi.com/journal/foods

Foods 2022,11, 2689 2 of 15
revealed whether it is a temporary disruption due to COVID-19 or a shift in consumer
preferences.
Information on consumer preferences is central to understanding and predicting
China’s import demand for IMF and its associated ingredients such as whey powder. How-
ever, there are few empirical studies on parent preferences for IMF in the latest literature,
particularly in post COVID-19 pandemic era. The pandemic has also revived debate glob-
ally and in China about the re-shoring of industries [
10
,
11
]. Consumer preferences are a
key aspect of this debate, with major implications for IMF and its associated products both
in and outside of China.
The study had a two-step objective: to explore the attributes that influence Chinese
parents’ purchase decisions of IMF; and to understand possible non-product reasons for the
preferences, especially given the uncertainty brought about by the COVID-19 pandemic.
The rest of this paper is organized as follows. Section 2provides a review of literature
followed by an explanation of choice experiment methodology including experimental
design, data collection and modelling. Research findings and discussion are presented in
Sections 4and 5, followed by conclusions.
2. Literature Review
Understanding consumer preferences is a fundamental aspect of businesses decision-
making including developing and delivering products to meet demand, as well as market-
ing and pricing. A range of stated preference approaches have been used to understand
consumer preferences including conjoint analysis [
12
,
13
], contingent valuation [
14
,
15
],
choice experiments [
16
,
17
] and (laboratory) experimental auctions [
18
–
20
]. Contingent
valuation is widely used in nonmarket valuation especially in the areas of environmental
and ecological impact assessment [
21
]. In the field of market valuation, experimental auc-
tions are commonly used by setting up a real environment such as supermarket to enable
participants to consecutively bid on real products rather than hypothetical products [
19
]. A
conjoint analysis approach typically requires participants to rate each product attribute in-
dividually, while choice experiments (also known as choice based conjoint analysis) present
multiple sets of product attributes and ask respondents to choose the set they prefer. This
method is generally considered most consistent with an actual shopping experience [
22
]
and was therefore selected for this study.
All techniques are regarded as experimental and subject to criticism on their hypo-
thetical biases and the reliability of results [
23
]. To avoid the hypothetical biases and
improve the external validity, Haghani et al. [
24
,
25
] suggest a set of ex-ante strategies for
choice experiment studies in the field of consumer economics, namely ensuring incentive
compatibility, providing an opt-out option and making the choice setting as tangible as
possible. These measures were adopted in this study. For instance, survey participants
were paid, but not if there were indications of a low-quality response, indicated by the
completion of the survey in less than five minutes or of repetitive patterns. Opt-out options
were provided (“I would not buy either of them”) and choice alternatives were presented
in pictures of IMF tins rather than more abstract words in table. In addition, the reliability
of results can also be mitigated by cross-verification of two or more modelling techniques
such as an ex-post strategy [
26
–
28
]. This study does so by applying two independent logit
(conditional logit and random parameter logit) models.
A number of themes emerge in the more specific literature on consumer preferences
towards IMF products. One is that a successful choice experiment requires the identification
of the most important and relevant attributes. The presence of either too many or too few
attributes may lead to unreliable results [
29
]. The main IMF attributes used in previous
studies include the country of origin, price, nutritional information (probiotics contained),
brand recognition, packaging, quality certification, organic certification and traceability
systems [
7
,
8
,
30
–
34
]. Choice experiments in this study selected the relevant attributes of
nutritional information, organic certification and traceability codes as indicators of product
quality and safety, which has been confirmed by most studies above. Two other primary

Foods 2022,11, 2689 3 of 15
attributes—price and origin—were of particular interest in the context of COVID-19. Mul-
tiple studies conducted before 2020 show that Chinese consumers lack confidence in the
safety of domestically produced IMF, and mistrust domestic IMF supply chains, which
means that consumers often use the country of origin and price to infer the quality of a
product [
7
,
8
]. However anecdotal evidence and various studies [
35
–
38
] suggest that con-
sumer preferences, perceptions and habits may have changed in the era of
COVID-19.
This
paper aimed to provide up-to-date empirical evidence on current consumer perceptions
and confidence to IMF in the COVID-19 era.
3. Materials and Methods
3.1. Choice Experiment Design
In the context of this study, IMF is viewed as a collection of product attributes from
which consumers derive utility. Choice experiments enable the target consumers to evaluate
trade-offs among attributes by replicating real-life purchasing situations and allowing the
evaluation of multiple attributes. As one of the key issues in designing a choice experiment,
attributes and their corresponding levels set in this study were extracted from prior studies
(as shown in Table 1), but were tailored in this study to preferences toward IMF in partic-
ular. Two four-level and three two-level IMF attributes were included including product
origin, price, organic label, functional ingredients and traceability information. Detailed
information regarding the specific attributes and their corresponding levels is presented
in Table 1. The full list of attributes was tested in a pilot survey. Some were dropped
because they overlapped with others or were identified as being relatively unimportant
(e.g., packaging and taste).
Table 1. Product attributes and attribute levels.
Product Attribute Description Attribute Levels
Product origin
[32,34]
Origin of main ingredients (‘nai yuan’),
origin of manufacturing (processing
location) and country-of-purchase
1 = domestic main ingredients, produced
domestically
2 = imported main ingredients, produced
domestically
3 = produced overseas, imported in its original
packaging, labelled in Chinese
4 = purchased from overseas through private or
cross-border e-commerce retail import, labelled in
a foreign language
Organic
[39–41]
Logo or other trademark to show organic
certification, regardless of Chinese or
non-Chinese origin
1 = With organic label
0 = No organic label
Functional ingredients
[30,33]
Functional ingredients, such as
DHA/ARA for brain development,
prebiotics for digestive health, lutein for
vision and cognitive function etc.
1 = functional ingredients contained
0 = No functional ingredients
Traceability
[31,42–45]
QR (Quick Response) code to trace any
supply chain information covering milk
producing, IMF processing and
marketing.
1 = With traceable QR code
0 = No traceable QR code
Price
[8,30,32,46]
Average price of IMF available in markets
at the time of study, with intervals of
CNY 50
1 = 180 CNY/900 g (around 26 USD/900 g)
2 = 230 CNY/900 g (around 33 USD/900 g)
3 = 280 CNY/900 g (around 41 USD/900 g)
4 = 330 CNY/900 g (around 48 USD/900 g)
The combination of attributes and levels in Table 1form a total of 4
2×
2
3
= 128 virtual
product profiles, which is too many to request respondents to compare and select from.
A total of 15 to 20 profiles will fatigue the consumer [
47
]. Therefore, to accommodate our

Foods 2022,11, 2689 4 of 15
study objective while maximising the statistical performance of coefficient estimates, we
employed a fractional factorial orthogonal design to ensure attribute level balance over
alternatives using SPSS 28 software. This generated 16 alternatives for a single block of
eight choice sets. Each participant was presented with the same eight choice sets (without
multiple versions) and was asked to choose one and only one option out of two IMF
packages and an opt-out option “I would not buy either of them” to better simulate an IMF
purchasing decision in each choice set. Pictures of tins of IMF featuring the attribute levels
were used to represent the alternatives (see Figure 1for a sample choice set). Prior to being
presented with the choice sets, respondents were fully informed of the definition of each of
the quality attributes and their corresponding levels. The respondents were also informed
that, except for these attributes in a choice set, the IMF products presented had no difference
in appearance, taste, grade, or any other attributes. To control for hypothetical bias, a note
was added for respondents to assume that the product is for their own child, that they
apply real budgetary constraints and that they have the option of not purchasing any IMF
in a choice set. Additional information on participants’ socio-economic demographics,
consumption habits, risk perceptions and attitudes toward products currently in use were
also collected after the choice experiment.
Foods 2022, 11, x FOR PEER REVIEW 4 of 15
multiple versions) and was asked to choose one and only one option out of two IMF pack-
ages and an opt-out option “I would not buy either of them” to better simulate an IMF
purchasing decision in each choice set. Pictures of tins of IMF featuring the attribute levels
were used to represent the alternatives (see Figure 1 for a sample choice set). Prior to being
presented with the choice sets, respondents were fully informed of the definition of each
of the quality attributes and their corresponding levels. The respondents were also in-
formed that, except for these attributes in a choice set, the IMF products presented had no
difference in appearance, taste, grade, or any other attributes. To control for hypothetical
bias, a note was added for respondents to assume that the product is for their own child,
that they apply real budgetary constraints and that they have the option of not purchasing
any IMF in a choice set. Additional information on participants’ socio-economic de-
mographics, consumption habits, risk perceptions and attitudes toward products cur-
rently in use were also collected after the choice experiment.
Figure 1. Example of one choice set (A, B, C stand for different options).
3.2. Survey Design and Data
Face-to-face interviews are currently difficult to conduct in China because of the
health concerns of COVID-19, social distancing requirements and the “zero COVID” and
“dynamic clearing” policies (The “zero COVID” and “dynamic clearing” policies refer to
stopping transmission of the coronavirus through lockdowns, mass testing and quaran-
tines to achieve zero cases). The survey was therefore necessarily administrated online,
which has several additional benefits. Online surveys for choice experiments are likely to
elicit a more thoughtful and real-life response than face-to-face surveys due to social de-
sirability bias and interviewer effects [48]. A pilot survey was conducted through personal
contacts (“Friends Circle”) on Wechat App (a popular social media platform in China) and
feedback was incorporated to ensure the clarity of attributes/levels and understanding of
each statement to the respondents. The formal questionnaire was distributed to the tar-
geted population with child(ren) younger than three years old through an online platform
called Agri-watch (http://www.agriwatch.cn/, accessed on 21 August 2022). Participants
were paid a small incentive fee (CNY20/person, equivalent to around USD3/person) to
complete the questionnaire. In an attempt to obtain reliable data, the questionnaire started
with a clear description of the objectives and instructions of the study and concluded with
a specific request for each participant to take a real-time photo of the IMF package cur-
rently consumed by their baby at home. The questionnaire was available online for two
weeks in April 2022, resulting in a final sample of 804 responses after removing the re-
sponses that took less than five minutes to answer.
Figure 1. Example of one choice set ((A–C) stand for different options).
3.2. Survey Design and Data
Face-to-face interviews are currently difficult to conduct in China because of the
health concerns of COVID-19, social distancing requirements and the “zero COVID” and
“dynamic clearing” policies (The “zero COVID” and “dynamic clearing” policies refer to
stopping transmission of the coronavirus through lockdowns, mass testing and quarantines
to achieve zero cases). The survey was therefore necessarily administrated online, which
has several additional benefits. Online surveys for choice experiments are likely to elicit a
more thoughtful and real-life response than face-to-face surveys due to social desirability
bias and interviewer effects [
48
]. A pilot survey was conducted through personal contacts
(“Friends Circle”) on Wechat App (a popular social media platform in China) and feedback
was incorporated to ensure the clarity of attributes/levels and understanding of each
statement to the respondents. The formal questionnaire was distributed to the targeted
population with child(ren) younger than three years old through an online platform called
Agri-watch (http://www.agriwatch.cn/, accessed on 21 August 2022). Participants were
paid a small incentive fee (CNY20/person, equivalent to around USD3/person) to complete
the questionnaire. In an attempt to obtain reliable data, the questionnaire started with
a clear description of the objectives and instructions of the study and concluded with a
specific request for each participant to take a real-time photo of the IMF package currently
consumed by their baby at home. The questionnaire was available online for two weeks in

Foods 2022,11, 2689 5 of 15
April 2022, resulting in a final sample of 804 responses after removing the responses that
took less than five minutes to answer.
3.3. Econometric Modelling
The choice experiment methodology is underpinned by two core consumer theories—
Lancaster’s characteristics demand theory [
49
] and McFadden’s random utility theory [
50
].
The former states that consumers usually derive utility from the characteristics of a product
rather than the product itself. This study presented the IMF product to respondents as
different combinations of five key component attributes (Origin, Functional, Organic, Trace-
able and Price). The latter theory states that consumers generally choose the product that
carries greater utility based on the values derived from different combinations of product
attributes. Given the existence of unobserved and random factors in the decision-making
process, it is difficult to predict with certainty that the consumer would select a particular
alternative, while it is possible to estimate the probability of that the perceived utility of one
alternative is greater than that of all the other available alternatives. Lancaster’s character-
istics demand theory and McFadden’s random utility theory allowed this study to divide
the respondent’s utility into an observable deterministic component and an unobserved
random component as shown in Equation (1) below.
Uin = Vin +εin =α0Xin +β0Zin +εin (1)
where U
in
denotes the utility of IMF alternative i in a choice set responded by individual
n; V
in
denotes the observable deterministic component that specified as a function of
alternative-specific attributes vector X
in
and case-specific demographic and perception
vector Z
in
, estimating how consumers’ preferences vary with different levels of demo-
graphic and perception variables;
α0
and
β0
are the vector of coefficients describing the
marginal utility of the attributes vector as well as demographic and perception vectors;
εin
is a random variable that accounts for the effects on preferences of unobserved attributes
of the alternative i and individual n. Then, the probability that the individual n chooses
alternative i over any other options j from a given choice set is:
Pin = P (Uin)>P(Ujn) for all j 6=i (2)
The estimation of choice probabilities P
in
differs with the distribution of unobserved
random components. Conditional logit (CL) and random parameter logit (RPL) were
applied in this study as two alternative approaches to account for differences in consumer
preferences, where CL assumed the random components are independently and identically
distributed (IID) with the implication that alternatives have independence from irrelevant
attributes, while RPL, also known as the mixed logit model, is undertaken in case the IID
assumption is violated. Conditional logit (CL) and random parameter logit (RPL) models
were conducted through the commands of “clogit” and “mixlogit” in Stata 14.2.
4. Results
4.1. Consumer Characteristics
Descriptive statistics of selected demographic characteristics for the final sample are
presented in Table 2. As could be expected, a greater number of responses were obtained
from female than male respondents, as mothers are most likely to be more interested in
and to make the decisions on IMF selection. The age of the respondents was concentrated
in the 20 to 40 years old range, with a family size of three to four persons. Compared
to the Chinese population, the sample had a higher percentage of individuals holding a
bachelor’s degree or above (65.2%). The sample also had a higher percentage of families
with above national average family income; 89.3% of the respondents’ reported a yearly
family income of more than CNY 100,000, which is close to urban statistics of family of
three in 2020 [51].

Foods 2022,11, 2689 6 of 15
Table 2. Demographic frequency distribution of samples (N= 804).
Demographic/Perception Category %
Gender Male 41.5
Female 58.5
Age (years)
20–30 37.7
30–40 56.7
40–50 4.9
Over 50 0.7
Education
Junior high 1.6
Senior high 10.8
College (2–3 years) 24.8
Undergraduate 53.8
Postgraduate & above 9.0
Family size (peoples)
3 39.6
4 31.7
5 17.9
6 and more 10.8
Income (CNY)
≤100,000 11.8
100,000–200,000 46.4
200,000–300,000 27.4
300,000–400,000 8.8
400,000–500,000 2.2
>500,000 3.4
The quality and safety of domestic
produced IMF is reliable to me
Strongly disagree 3.7
Disagree 12.6
Somewhat disagree 15.4
Neutral 27.7
Somewhat agree 18.8
Agree 11.0
Strongly agree 10.8
China’s quality and safety supervision
of IMF is the strictest in history
Strongly disagree 2.6
Disagree 4.6
Somewhat disagree 8.5
Neutral 23.8
Somewhat agree 17.3
Agree 24.0
Strongly agree 19.3
I would be concerned about imported
IMF due to the possible delays,
shortages or virus risks
Strongly disagree 1.6
Disagree 5.1
Somewhat disagree 6.2
Neutral 12.9
Somewhat agree 24.1
Agree 26.0
Strongly agree 24.0
Consumers’ perception on product quality and safety were asked in the form of how
much you disagree or agree with each of these statements by using seven-point Likert
scale of one to seven where one means strongly disagree and seven means strongly agree.
As shown in Table 2, 40.6% agreed (scale > 4) that the quality and safety of domestically
produced IMF is reliable, 31.7% disagreed (scale < 4) that the quality and safety of domestic
produced IMF is reliable, while 27.7% neither agreed nor disagreed (scale = 4). Respondents
were also asked questions on the performance and strictness of the system that oversees
quality and safety standards form domestic IMF (i.e., regulation, testing, inspection and
enforcement). A proportion of 60.6% of respondents perceived the system to be strict, 23.8%
were neutral, and only 15.7% perceived it to be not strict. The respondents were found to
be concerned about imported IMF due to reasons ranging from delays, shortages, and virus

Foods 2022,11, 2689 7 of 15
risks. Of the 804 participants, 74.1% acknowledged these concerns, 12.9% were not sure,
and the remaining 13.0% were not concerned.
The distribution of Likert scale scores and mean values of respondents’ trust in IMF
chain actors are shown in Figure 2. The results indicate medium–high trust levels in all
actors, with all mean values above the midpoint of the scale. There are differences in
the overall trust between the seven actors (p< 0.001). Respondents trust regulatory and
supervisory authorities most (5.51 refers to a level between somewhat trustful and trustful),
followed by traceability systems with 5.49 and organic certifying bodies with 5.42. The
average trust in dairy farmers (5.11) and IMF manufacturers (5.04) was slightly above
“somewhat trustful”, whereas the mean value of trust in distributors was the lowest, with
minor differences between online (4.82) or offline (4.42) distributors.
Foods 2022, 11, x FOR PEER REVIEW 7 of 15
were found to be concerned about imported IMF due to reasons ranging from delays,
shortages, and virus risks. Of the 804 participants, 74.1% acknowledged these concerns,
12.9% were not sure, and the remaining 13.0% were not concerned.
The distribution of Likert scale scores and mean values of respondents’ trust in IMF
chain actors are shown in Figure 2. The results indicate medium–high trust levels in all
actors, with all mean values above the midpoint of the scale. There are differences in the
overall trust between the seven actors (p < 0.001). Respondents trust regulatory and su-
pervisory authorities most (5.51 refers to a level between somewhat trustful and trustful),
followed by traceability systems with 5.49 and organic certifying bodies with 5.42. The
average trust in dairy farmers (5.11) and IMF manufacturers (5.04) was slightly above
“somewhat trustful”, whereas the mean value of trust in distributors was the lowest, with
minor differences between online (4.82) or offline (4.42) distributors.
Figure 2. Respondents’ trust in IMF chain.
4.2. Consumer Preferences
Before proceeding to the estimation stage, the data collected from the online survey
were organized in a long form structure as required by Stata 14.2 (StataCorp), meaning
that the dataset has one row per alternative for each choice scenario that the respondents
face. Thus, with 804 decision-makers choosing amongst three alternatives across eight sce-
narios, the dataset has 19,296 rows (804 × 3 × 8). The opt-out option was defined as a
dummy variable ASC (Alternative-Specific Constant) which is equal to one in the row
corresponding to the relevant alternative and zero otherwise. The dependent variable was
coded as one for the chosen alternative in each scenario and zero for the non-chosen alter-
natives. The independent variables include alternative-specific attributes variables of
product and the case-specific social-economic variables of respondents. Results for the
models can be seen in Table 3, where the signs and significance values on the estimated
coefficients of product attributes were consistent in both models and the random param-
eter logit model improved the goodness-of-fit as shown by the lower values of Log likeli-
hood, Prob>chi2(6), AIC and BIC.
0
10
20
30
40
50
60
70
80
90
100
%
Strongly untrustful Untrustful Somewhat untrustful Neutral
Somewhat trustful Trustful Strongly trustful
Figure 2. Respondents’ trust in IMF chain.
4.2. Consumer Preferences
Before proceeding to the estimation stage, the data collected from the online survey
were organized in a long form structure as required by Stata 14.2 (StataCorp), meaning
that the dataset has one row per alternative for each choice scenario that the respondents
face. Thus, with 804 decision-makers choosing amongst three alternatives across eight
scenarios, the dataset has 19,296 rows (804
×
3
×
8). The opt-out option was defined as
a dummy variable ASC (Alternative-Specific Constant) which is equal to one in the row
corresponding to the relevant alternative and zero otherwise. The dependent variable
was coded as one for the chosen alternative in each scenario and zero for the non-chosen
alternatives. The independent variables include alternative-specific attributes variables
of product and the case-specific social-economic variables of respondents. Results for the
models can be seen in Table 3, where the signs and significance values on the estimated
coefficients of product attributes were consistent in both models and the random parameter
logit model improved the goodness-of-fit as shown by the lower values of Log likelihood,
Prob>chi2(6), AIC and BIC.

Foods 2022,11, 2689 8 of 15
Table 3. Results of conditional logit and random parameter logit main effects.
Conditional Logit
Model (A) Random Parameter Logit Model (B)
Choice Coef. Std. Err. Mean
Coef. Std. Err. SD Coef. Std. Err.
Origin −
0.3641 ***
0.0185 −
0.5412 ***
0.0334 0.6257 *** 0.0358
Functional
ingredient 0.1130 ** 0.0450 0.1324 ** 0.0553 0.1427 * 0.1641
Organic 0.4175 *** 0.0491 0.5849 *** 0.0645 0.5581 *** 0.1161
Tracible 1.2909 *** 0.0382 1.8237 *** 0.0753 1.2046 *** 0.0818
Price −0.0048 0.0190 −0.0052 0.0248 0.2908 *** 0.0366
ASC 0.6732 *** 0.0777 1.5624 *** 0.1298 −
1.8538 ***
0.1324
Log likelihood −5851.6058 −5298.18
Number of obs. 19,296 19,296
LR chi2(6) 2429.34 1106.86
Prob>chi2 0.0000 0.0000
Pseudo R2 0.1719 -
AIC 11,715.21 10,620.35
BIC 11,762.42 10,714.76
*, **, *** denotes significance level at the 10%, 5% and 1% respectively; ASC stands to Alternative-specific Constant.
The significance values and the signs on the estimated coefficients of selected IMF
attributes were mostly as expected, although some unexpected results emerged that can
be explained. The coefficients for “functional ingredient”, “organic” and “tracible” are all
positive and statistically significant at the 1 and 5% levels in both models, indicating that
consumer utility could be significantly improved. Thus, respondents are more likely to
purchase when the information of functional ingredients, organic labelling and traceable
codes are specified on IMF packaging. Whether or not the product is traceable was by far
the most influential attribute in determining the selection of IMF as the largest coefficient
value in the model result. In addition, the coefficient of the opt-out option (ASC) is positive
and statistically significant as expected, indicating that consumers gain more utility from
choosing one of the experimentally designed IMF profiles rather than the opt-out choice.
However, unexpected negative coefficients were found for the attributes of origin and
price, indicating that the consumer utility could decrease with the levels of product origin
and price moving up. In other words, respondents preferred a domestic brand (domestic
main ingredients and domestically produced) to a foreign brand (directly purchased from
a foreign country through private or cross-border e-commerce retail import, labelled in a
foreign language). Respondents tend to steer away from higher-priced IMF, as the estimated
coefficient of price was not significant and positive under the significance level of 5%.
The results in Table 3also show that the corresponding standard deviations of all
product attributes except for functional ingredients are statistically significant, suggesting
that consumer preferences for these attributes are heterogeneous. The random parameter
logit model B1–B3 (Table 4) added the interaction terms between the case-specific demo-
graphic and perspective variables (Table 2) and alternative-specific variables (attribute
variables). Dummy variable ASC illustrates the proportion of people who opted out of
any of the pairs by selecting the “I would not buy either of them” option. A proportion
of 41.5% (334/804) of participants selected one of the two IMF products in all eight of
the choice sets, and the remainder opted out at least once. The significance of interaction
coefficients ASC*Trust_Dqual and ASC*Trust_Dreguin in the result of model B1 shows that
respondents are more likely to choose an alternative product rather than opt-out if they
trust the quality and safety of domestically produced IMF and the governance system for
the industry. Similar but more pronounced results were observed for model B3, where
consumer utility was higher for a lower-priced product when they trust the quality and
safety of domestically produced IMF, as well as governance. Even if the main effect of
price on consumer preferences was not significant, there was also a significant interaction

Foods 2022,11, 2689 9 of 15
between price and income, where a high income would make consumer utility much higher
for lower-priced products than for low-income consumers. As could be expected given
the interactions in model B2, consumer utility would be higher for domestically produced
products when they trust the quality and safety of domestically produced IMF, when
they are confident in and satisfied with governance systems, and when they agree that
COVID-19 would greatly compromise the supply of imported IMF.
Table 4.
Results of a random parameter logit model interacting the case-specific with alternative-
specific variables.
Interacting
Case-Specific Variables
with ASC (B1)
Interacting
Case-Specific
Variables with
Origin (B2)
Interacting
Case-Specific
Variables with
Price (B3)
Choice 1Coef. Std. Err. Coef. Std. Err. Coef. Std. Err.
Origin −
0.5817 ***
0.0372 −
0.8749 ***
0.1690 −
0.5837 ***
0.0373
Functional
ingredient 0.1247 ** 0.0558 0.1379 ** 0.0561 0.1266 ** 0.0558
Organic 0.5980 *** 0.0659 0.6239 *** 0.0642 0.6004 *** 0.0660
Tracible 1.8464 *** 0.0759 1.8586 *** 0.0779 1.8474 *** 0.0759
Price −0.0063 0.0252 −0.0062 0.0249 −0.1294 0.0944
ASC −0.2639 0.6921 1.6459 *** 0.1391 −0.6796 0.4999
Gender * −0.3000 0.2052 −
0.1840 ***
0.0517 0.0214 0.0439
Education * −0.1861 0.1497 0.1134 *** 0.0390 −0.0232 0.0323
Income * 0.0857 0.1208 0.0460 0.0304 0.0686 *** 0.0258
Trust_Dqual * 0.2364 *** 0.0658 −
0.1598 ***
0.0175 0.2343 *** 0.0660
Trust_Dregu * 0.2096 *** 0.0715 −
0.1127 ***
0.0184 0.2094 *** 0.0725
Impact_CV * 0.0297 0.0728 −
0.0929 ***
0.0172 0.0288 0.0702
Log likelihood −5278.5997 −5165.5757 −5277.2314
Number of obs
19,296 19,296 19,296
LR chi2(6) 1104.94 1060.80 1118.49
Prob>chi2 0.0000 0.0000 0.0000
AIC 10,593.20 10,367.15 10,590.46
BIC 10,734.82 10,508.77 10,732.08
1
Other variables omitted for lack of statistical significance were age and family size; *, **, *** denotes significance
level at the 10, 5 and 1% level respectively; ASC stands to Alternative-specific Constant; Trust_Dqual stands for
Trust of Domestic product quality; Trust_Dregu stands for Trust of Domestic industry regulation; Impact_CV
stands for Impacts of COVID-19.
5. Discussion
This study comes two and a half years after the first COVID-19 case was reported in
late December 2019. The Chinese government implemented strict public health measures on
travel restrictions, lock downs and isolation policies, all of which are ongoing. Throughout
our online survey period, several of China’s major cities including Shanghai, Shenzhen
and Beijing were hit with their most severe outbreaks with hundreds or thousands of cases
logged. Several cases uncovered in Beijing, Zhuhai and Shenzhen were reported to be
linked to contaminated goods from overseas (cold chains and international parcels) [
52
].
This link has been made by several local governments and media outlets but has not been
scientifically established by international organizations. Chinese health officials continue
to warn the public to minimise orders from overseas during the COVID-19 period and to
wear protective gear when handling inbound packages [
53
]. China’s delivery companies
have also been ordered to disinfect international packages upon arrival and hold items
for about seven days before final dispatch to recipients, while postal workers exposed
to international mail are required to undergo two nucleic acid tests every seven days
(once every day at high-risk areas) [
54
]. With those COVID-19 control protocols in place,
customers who purchased directly from overseas through private “daigou” cross-border
e-commerce platforms were seriously discouraged from buying foreign IMF. Conventional
international supply chains have also been disrupted, resulting in fluctuations in stocks and

Foods 2022,11, 2689 10 of 15
loss of customers. As described by one respondent: “Currently I prefer products produced
in China for safety concerns, because we would be isolated as a close contact once the parcel
was suspected of contacting a virus”. Or another, saying “We changed to domestic brands
because of logistics delays; I do not like waiting that long for product from overseas”.
The study also reveals changes in Chinese consumer behaviour that may be longer-
term in nature than the shock caused by the pandemic. In line with previous findings that
Chinese parents are highly quality- and safety-focused [
8
], this study finds that non-price
attributes play a much more important role than price in affecting respondents’ purchasing
IMF. Like parents everywhere, Chinese parents want the best IMF product for their children
and thus select the safest (organic and traceable) products with the best nutritional value
(functional ingredients). These findings on respondents’ trust in IMF chain actors are
consistent with those of Wei et al. [
55
] who found that Chinese consumers are generally
confident in the safety of domestic IMF, which has greatly increased in recent years. At
the same time, consumer preferences toward domestically sourced main ingredients and
domestically manufactured IMF are more pronounced for respondents that are female or
with low education levels, a finding that aligns with that of Jianakoplos and Bernasek [
56
].
These respondents might be more likely to have concerns about the impacts of COVID-19,
such as risks from imported products or product packaging. This demographic tends to
pay more attention to dairy safety and is more sensitive about the related negative food
scandals, which impairs their trust.
Previous studies show consumer behaviour in China as being “going for the most
expensive”, which is a price–quality heuristic where consumers use price as a proxy for
quality, leading to a positive correlation between prices and consumer preference [
57
]. This
has been found in a range of contexts. Parents of a newborn babies, particularly if they are
having their first and possibly only child, are very likely rely on this heuristic in deciding
which brand to buy, inferring that a higher price means higher quality [
46
]. Parents lacking
confidence in food safety are willing to pay a high price premium on the assumption that
the IMF consumed by their children is reliable [
7
,
8
,
12
,
42
]. From a consumer psychology
perspective, Chang [
58
] argued that parents tend to be price-insensitive in buying IMF
because the decision involves people to whom they are very close to, and therefore depends
more on their subjective feelings towards children than an objective assessment towards
product attributes. Purchasing decisions are also influenced by consumers’ income and
purchasing power, which has increased markedly in upper and middle strata of Chinese
urban households over at least the last decade [8,59].
Findings in this study suggest that the price–quality heuristic is breaking down. The
correlation found in this study between price and consumer preference is negative and
insignificant, which implies that consumers did not evaluate price levels closely and
that there was an underlying preference away from expensive products. Contrary to the
findings of previous research, the insignificant price attribute suggests that price may not
be a prominent factor affecting Chinese parents’ purchase decisions. A contributing factor
may be income constraints in recent years. Zhang et al. [
60
] estimated that the COVID-19
pandemic would reduce household per capita income by 8.75% for rural residents and
6.13% for urban residents. The relaxation of the birth policy also decreases the expenditure
available for each child in the family. Pei [
61
] showed that the two-child families are more
willing to buy domestic-brand infant formula at a lower price level when compared with a
one-child family due to the income constraints.
Various past studies also show that Chinese parents favor imported IMF over domestic
IMF for a number of reasons [
4
,
7
]. Consumers disappointed by scandals surrounding the
safety of domestic IMF turned to imported IMF brands, especially those with a strong brand
reputation. At the same time, China implemented a provisional import tax rate (5%) which
is lower than the most-favoured-nation tax rate on IMF products (15%) to facilitate the
imports of IMF products. It also signed free trade agreements that reduced tariffs on IMF
imports from New Zealand and Australia to zero. These factors resulted in a sky-rocketing
increase for IMF imports in the post-melamine period from 2008. Import volumes of IMF

Foods 2022,11, 2689 11 of 15
increased from 42,218 tons in 2008 to 302,509 tons in 2017 with an annual increase of 61.6%
over the decade. This reduced the market share of domestically produced IMF from 60% in
2008 to 40.7% in 2017 [9].
Since that era, the Chinese government has become very concerned about the rapid
decline in the self-sufficiency rate of dairy products. Government and industry responded
through efforts to revitalise the domestic dairy industry and improve the quality and safety
of domestic IMF to meet the nutritional needs of children (Figure 3). Efforts during in first
decade (2008–2017) were directed at improving the quality and safety of IMF products
through tightening regulations, systems, governance and accountability. Policies and
regulations since 2018 have sought the promotion of competitiveness between domestic
IMF and imported IMF. The apparent success in doing so appears to have contributed to
a slowdown in year-on-year growth of imported IMF to under 10% in 2018 and 2019. It
then turned negative:
−
3% in 2020 and
−
22% in 2021. In the first four months of 2022, the
import volume fell further by another 6% year on year and showed no signs of recovery in
May and June [62].
Foods 2022, 11, x FOR PEER REVIEW 11 of 15
tariffs on IMF imports from New Zealand and Australia to zero. These factors resulted in
a sky-rocketing increase for IMF imports in the post-melamine period from 2008. Import
volumes of IMF increased from 42,218 tons in 2008 to 302,509 tons in 2017 with an annual
increase of 61.6% over the decade. This reduced the market share of domestically pro-
duced IMF from 60% in 2008 to 40.7% in 2017 [9].
Since that era, the Chinese government has become very concerned about the rapid
decline in the self-sufficiency rate of dairy products. Government and industry responded
through efforts to revitalise the domestic dairy industry and improve the quality and
safety of domestic IMF to meet the nutritional needs of children (Figure 3). Efforts during
in first decade (2008–2017) were directed at improving the quality and safety of IMF prod-
ucts through tightening regulations, systems, governance and accountability. Policies and
regulations since 2018 have sought the promotion of competitiveness between domestic
IMF and imported IMF. The apparent success in doing so appears to have contributed to
a slowdown in year-on-year growth of imported IMF to under 10% in 2018 and 2019. It
then turned negative: −3% in 2020 and −22% in 2021. In the first four months of 2022, the
import volume fell further by another 6% year on year and showed no signs of recovery
in May and June [62].
Figure 3. Policy and measures toward the Chinese Infant Milk Formula sector, 2008–2022. Source:
Authors collected and translated from multiple Chinese official websites including State Council,
Ministry of Agriculture, China Food and Drug Administration, State Administration for Market
Regulation, Development and Reform Committee and Ministry of Industry and Information Tech-
nology.
This study might indicate that the era where Chinese consumers preferred foreign
over domestic IMF is cooling off. Consumers appear to have built confidence in the quality
and safety of domestic IMF. On the premise that basic quality and safety can be guaran-
teed, consumers may then choose to reduce their monetary outlays (e.g., break the price–
quality heuristic). Some consumers could be expected to revert back to their preferences
for imported IMF products when the COVID-19 pandemic ends, but this may not neces-
sarily be widespread. As stated by respondents: “if my daughter doesn’t react negatively
to it [domestic IMF] we won’t necessarily go back to imported IMF, especially given the
variety and price of domestic brands and given no end in sight to the disruption caused
Figure 3.
Policy and measures toward the Chinese Infant Milk Formula sector, 2008–2022. Source:
Authors collected and translated from multiple Chinese official websites including State Council,
Ministry of Agriculture, China Food and Drug Administration, State Administration for Market Reg-
ulation, Development and Reform Committee and Ministry of Industry and Information Technology.
This study might indicate that the era where Chinese consumers preferred foreign
over domestic IMF is cooling off. Consumers appear to have built confidence in the quality
and safety of domestic IMF. On the premise that basic quality and safety can be guaranteed,
consumers may then choose to reduce their monetary outlays (e.g., break the price–quality
heuristic). Some consumers could be expected to revert back to their preferences for
imported IMF products when the COVID-19 pandemic ends, but this may not necessarily
be widespread. As stated by respondents: “if my daughter doesn’t react negatively to
it [domestic IMF] we won’t necessarily go back to imported IMF, especially given the
variety and price of domestic brands and given no end in sight to the disruption caused
by the pandemic”; and another “I think the product of big domestic brand like Feihe is
sufficiently safe and good quality, which should be more suitable for our Chinese babies
than overseas IMF.” Thus, the pandemic shock may have forced new brand loyalties. Even

Foods 2022,11, 2689 12 of 15
if consumers don’t feel particularly loyal to a brand, they may still stick to it because of
status-quo bias [
63
]. This is especially the case for IMF as babies can take days to adapt to a
new formula [
64
] which parents may want to avoid. Thus, we argue that many Chinese
consumers are likely to stick with the domestic IMF even when the disruption of COVID-19
subsides.
6. Conclusions
This study is the first choice experiment conducted since the outbreak of COVID-19 on
the preferences of Chinese parents toward IMF. It found that Chinese parents continue to
pay close attention to quality and safety attributes, and also found an increased confidence
in domestic IMF. This is driven by supply-side developments in the Chinese dairy sector,
but the process has been greatly accelerated by COVID-19. Chinese parents continue to pri-
oritise the attributes of functional ingredients, organic labelling and traceability information.
This implies a demand for further development and delivery of these attributes for both
Chinese and foreign IMF companies. Considering China’s strict anti-COVID measures and
logistics management, it is recommended that international IMF suppliers take measures
to mitigate against further costumer loss. Investments in joint-venture farms in China
are also a means by which foreign companies can capitalise on the increasing demand of
domestically manufactured IMF. For all products, smart logistics and contactless delivery
are recommended, especially for private daigou and cross-border e-commerce platforms.
The study is subject to several limitations. The analysis of this paper was based on
data obtained from an online survey, with self-selection for respondents with internet
access that can fill in surveys online. This may bias results. For instance, we did not restrict
or exclude rural consumers to participate the survey, but most of our respondents were
from municipalities, provincial capitals or cities, with relatively high overall education
and income levels. In addition, the choice experiment study tested attributes at only
two levels (“with and without”) for functional ingredients, organic and traceability. More
disaggregated levels on attributes such as nutrition contents and degree/type of traceability
system were not included in this study. Thus, future research could investigate consumer
preferences to IMF in China through a larger and more diverse sample that includes rural
areas and tests attributes through more disaggregated indicators. A study in the medium-
term future that captures longitudinal change in consumer preferences towards IMF—and
the effects of the changing COVID-19 situation, the development of the domestic dairy
industry and changing consumer sentiment to foreign products—would be fascinating.
Author Contributions:
Conceptualization, J.Z. and X.D.; methodology, validation, and formal analy-
sis, J.Z.; investigation and resources, X.D. and S.W.; writing—original draft preparation, J.Z.; writing—
review and editing, S.W. and X.D. All authors have read and agreed to the published version of the
manuscript.
Funding:
This research was funded by the Ministry of Agriculture and Rural Affairs of the People’s
Republic of China, raw milk quality and safety supervision project (Grant No. A170202) and the
Agricultural Science and Technology Innovation Program (ASTIP) of CAAS (Grant No. CAAS-ASTIP-
2016-AII).
Institutional Review Board Statement:
The study was conducted in accordance with the Declara-
tion of Helsinki and was exempted from ethical review and approval as formal approval by the
Institutional Review Board of the local ethics committee was not applicable for this study.
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Data is contained within the article.
Conflicts of Interest: The authors declare no conflict of interest.

Foods 2022,11, 2689 13 of 15
References
1.
Xinhua News. China’s Three-Child Policy to Improve Demographic Structure. Available online: http://english.www.gov.cn/
statecouncil/ministries/202106/01/content_WS60b61ab7c6d0df57f98da86e.html (accessed on 15 July 2022).
2. Attané, I. China’s new three-child policy: What effects can we expect? Popul. Soc. 2022,596, 1–4. [CrossRef]
3.
Duan, Y.; Yang, Z.; Lai, J.; Yu, D.; Chang, S.; Pang, X.; Jiang, S.; Zhang, H.; Bi, Y.; Wang, J.; et al. Exclusive breastfeeding rate
and complementary feeding indicators in China: A national representative survey in 2013. Nutrients
2018
,10, 249. [CrossRef]
[PubMed]
4.
Gong, Q.; Jackson, P. Consuming anxiety? Parenting practices in China after the infant formula scandal. Food Cult. Soc.
2012
,15,
557–578. [CrossRef]
5.
Su, M.; Ouyang, Y.Q. Father ’s role in breastfeeding promotion: Lessons from a quasi-experimental trial in China. Breastfeed. Med.
2016,11, 144–149. [CrossRef] [PubMed]
6.
Qiao, G.; Guo, T.; Klein, K.K. Melamine and other food safety and health scares in China: Comparing households with and
without young children. Food Control. 2012,26, 378–386. [CrossRef]
7.
El Benni, N.; Stolz, H.; Home, R.; Kendall, H.; Kuznesof, S.; Clark, B.; Dean, M.; Brereton, P.; Frewer, L.J.; Chan, M.Y.; et al. Product
attributes and consumer attitudes affecting the preferences for infant milk formula in China–a latent class approach. Food Qual.
Prefer. 2019,71, 25–33. [CrossRef]
8.
Li, S.W.; Zhu, C.; Chen, Q.H.; Liu, Y.M. Consumer confidence and consumers’ preferences for infant formulas in China. J. Integr.
Agric. 2019,18, 1793–1803. [CrossRef]
9. UN Comtrade Database. Available online: https://comtrade.un.org/ (accessed on 22 July 2022).
10.
Barbieri, P.; Boffelli, A.; Elia, S.; Fratocchi, L.; Kalchschmidt, M.; Samson, D. What can we learn about reshoring after COVID-19?
Oper. Manag. Res. 2020,13, 131–136. [CrossRef]
11.
Chen, H.; Hsu, C.W.; Shih, Y.Y. The reshoring decision under uncertainty in the post-COVID-19 era. J. Bus. Ind. Mark.
2022
,
in press. [CrossRef]
12. Rao, A.R. The quality of price as a quality cue. J. Mark. Res. 2005,42, 401–405. [CrossRef]
13.
Agarwal, J.; DeSarbo, W.S.; Malhotra, N.K.; Rao, V.R. An interdisciplinary review of research in conjoint analysis: Recent
developments and directions for future research. Cust. Needs Solut. 2015,2, 19–40. [CrossRef]
14.
Carson, R.T.; Czajkowski, M. The discrete choice experiment approach to environmental contingent valuation. In Handbook of
Choice Modelling; Hess, S., Daly, A., Eds.; Edward Elgar Publishing: Cheltenham, UK, 2014; pp. 202–235. [CrossRef]
15.
Woo, J.; Chung, S.; Lee, C.Y.; Huh, S.Y. Willingness to participate in community-based renewable energy projects: A contingent
valuation study in South Korea. Renew. Sustain. Energy Rev. 2019,112, 643–652. [CrossRef]
16.
Van Loo, E.J.; Caputo, V.; Nayga, R.M., Jr.; Meullenet, J.F.; Ricke, S.C. Consumers’ willingness to pay for organic chicken breast:
Evidence from choice experiment. Food Qual. Prefer. 2011,22, 603–613. [CrossRef]
17.
Liao, F.; Molin, E.; van Wee, B. Consumer preferences for electric vehicles: A literature review. Transp. Rev.
2017
,37, 252–275.
[CrossRef]
18.
Huffman, W.E.; Shogren, J.F.; Rousu, M.; Tegene, A. Consumer willingness to pay for genetically modified food labels in a market
with diverse information: Evidence from experimental auctions. J. Agric. Resour. Econ. 2003,28, 481–502.
19.
My, N.H.; Demont, M.; Van Loo, E.J.; de Guia, A.; Rutsaert, P.; Tuan, T.H.; Verbeke, W. What is the value of sustainably-produced
rice? Consumer evidence from experimental auctions in Vietnam. Food Policy 2018,79, 283–296. [CrossRef]
20.
Canavari, M.; Drichoutis, A.C.; Lusk, J.L.; Nayga Jr, R.M. How to run an experimental auction: A review of recent advances. Eur.
Rev. Agric. Econ. 2019,46, 862–922. [CrossRef]
21.
Perni, Á.; Barreiro-Hurlé, J.; Martínez-Paz, J.M. Contingent valuation estimates for environmental goods: Validity and reliability.
Ecol. Econ. 2021,189, 107144. [CrossRef]
22.
Louviere, J.J.; Flynn, T.N.; Carson, R.T. Discrete choice experiments are not conjoint analysis. J. Choice Model.
2010
,3, 57–72.
[CrossRef]
23.
Bello, M.; Abdulai, A. Impact of ex-ante hypothetical bias mitigation methods on attribute non-attendance in choice experiments.
Am. J. Agric. Econ. 2016,98, 1486–1506. [CrossRef]
24.
Haghani, M.; Bliemer, M.C.; Rose, J.M.; Oppewal, H.; Lancsar, E. Hypothetical bias in stated choice experiments: Part I. Macro-
scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and
neuroimaging. J. Choice Model. 2021,41, 100309. [CrossRef]
25.
Haghani, M.; Bliemer, M.C.; Rose, J.M.; Oppewal, H.; Lancsar, E. Hypothetical bias in stated choice experiments: Part II.
Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods. J. Choice Model.
2021,41, 100322. [CrossRef]
26.
Goldberg, I.; Roosen, J. Scope insensitivity in health risk reduction studies: A comparison of choice experiments and the contingent
valuation method for valuing safer food. J. Risk Uncertain. 2007,34, 123–144. [CrossRef]
27.
Corrigan, J.R.; Depositario, D.P.T.; Nayga Jr, R.M.; Wu, X.; Laude, T.P. Comparing open-ended choice experiments and experimen-
tal auctions: An application to golden rice. Am. J. Agric. Econ. 2009,91, 837–853. [CrossRef]
28.
He, J.; Dupras, J.; Poder, G.T. The value of wetlands in Quebec: A comparison between contingent valuation and choice
experiment. J. Environ. Econ. Policy 2017,6, 51–78. [CrossRef]
29.
Bennett, J.; Blamey, R. The Choice Modelling Approach to Environmental Valuation; Edward Elgar Publishing: Cheltenham, UK, 2001.

Foods 2022,11, 2689 14 of 15
30.
Wu, L.; Yin, S.; Xu, Y.; Zhu, D. Effectiveness of China’s organic food certification policy: Consumer preferences for infant milk
formula with different organic certification labels. Can. J. Agric. Econ. 2014,62, 545–568. [CrossRef]
31.
Yin, S.; Li, Y.; Xu, Y.; Chen, M.; Wang, Y. Consumer preference and willingness to pay for the traceability information attribute of
infant milk formula: Evidence from a choice experiment in China. Br. Food J. 2017,66, 557–569. [CrossRef]
32.
Yin, S.; Lv, S.; Chen, Y.; Wu, L.; Chen, M.; Yan, J. Consumer preference for infant milk-based formula with select food safety
information attributes: Evidence from a choice experiment in China. Can. J. Agric. Econ. 2018,66, 557–569. [CrossRef]
33.
Quan, S.; Zeng, Y.; Yu, X.; Bao, T. WTP for baby milk formula in China: Using attribute nonattendance as a priori information to
select attributes in choice experiment. Agribusiness 2018,34, 300–320. [CrossRef]
34.
Shan, L.C.; Li, C.; Yu, Z.; Regan, Á.; Lu, T.; Wall, P. Consumer perceptions on the origin of infant formula: A survey with urban
Chinese mothers. J. Dairy Res. 2021,88, 226–237. [CrossRef]
35. Verma, M.; Naveen, B.R. COVID-19 impact on buying behaviour. Vikalpa 2021,46, 27–40. [CrossRef]
36.
Loxton, M.; Truskett, R.; Scarf, B.; Sindone, L.; Baldry, G.; Zhao, Y. Consumer behaviour during crises: Preliminary research on
how coronavirus has manifested consumer panic buying, herd mentality, changing discretionary spending and the role of the
media in influencing behaviour. J. Risk Financ. Manag. 2020,13, 166. [CrossRef]
37.
Segovia, M.; Grashuis, J.; Skevas, T. Consumer preferences for grocery purchasing during the COVID-19 pandemic: A quantile
regression approach. Br. Food J. 2021, ahead-of-print. [CrossRef]
38.
Kwon, M.; Manikas, A.S.; Barone, M.J. (Not) Near and Dear: COVID-19 Concerns Increase Consumer Preference for Products
That Are Not “Near Me”. J. Assoc. Consum. Res. 2022,7, 8–16. [CrossRef]
39.
Probst, L.; Houedjofonon, E.; Ayerakwa, H.M.; Haas, R. Will they buy it? The potential for marketing organic vegetables in the
food vending sector to strengthen vegetable safety: A choice experiment study in three West African cities. Food Policy
2012
,37,
296–308. [CrossRef]
40.
Teuber, R.; Dolgopolova, I.; Nordström, J. Some like it organic, some like it purple and some like it ancient: Consumer preferences
and WTP for value-added attributes in whole grain bread. Food Qual. Prefer. 2016,52, 244–254. [CrossRef]
41.
Scozzafava, G.; Gerini, F.; Boncinelli, F.; Contini, C.; Marone, E.; Casini, L. Organic milk preference: Is it a matter of information?
Appetite 2020,144, 104477. [CrossRef] [PubMed]
42.
Ortega, D.L.; Wang, H.H.; Wu, L.; Olynk, N.J. Modeling heterogeneity in consumer preferences for select food safety attributes in
China. Food Policy 2011,36, 318–324. [CrossRef]
43.
Wu, L.; Wang, S.; Zhu, D.; Hu, W.; Wang, H. Chinese consumers’ preferences and willingness to pay for traceable food quality
and safety attributes: The case of pork. China Econ. Rev. 2015,35, 121–136. [CrossRef]
44.
Liu, R.; Gao, Z.; Nayga Jr, R.M.; Snell, H.A.; Ma, H. Consumers’ valuation for food traceability in China: Does trust matter? Food
Policy 2019,88, 101768. [CrossRef]
45.
Zhou, X.; Xu, Z. Traceability in food supply chains: A systematic literature review and future research directions. Int. Food
Agribus. Manag. Rev. 2022,25, 173–196. [CrossRef]
46.
Wang, E.; Gao, Z.; Heng, Y.; Shi, L. Chinese consumers’ preferences for food quality test/measurement indicators and cues of
milk powder: A case of Zhengzhou, China. Food Policy 2019,89, 101791. [CrossRef]
47. Lancaster, K.J. A new approach to consumer theory. J. Political Econ. 1966,74, 132–157. [CrossRef]
48. McFadden, D. The measurement of urban travel demand. J. Public Econ. 1974,3, 303–328. [CrossRef]
49. National Bureau of Statistics. China Statistical Yearbook; China Statistics Press: Beijing, China, 2021.
50.
Wei, L.; Pei, J.; Zhang, A.; Wu, X.; Xie, Y.; Yang, Y. Application of stochastic Bayesian modeling to assess safety status of baby
formulas and quantify factors leading to unsafe products in China market. Food Control. 2020,108, 106826. [CrossRef]
51. Jianakoplos, N.A.; Bernasek, A. Are women more risk averse? Econ. Inq. 1998,36, 620–630. [CrossRef]
52.
China Daily. Beijing Cluster Linked to Overseas Mail. Available online: https://global.chinadaily.com.cn/a/202203/18/WS623
3bf66a310fd2b29e519be.html (accessed on 18 July 2022).
53.
BBC News. COVID: Beijing City Urges End to Overseas Deliveries Over Omicron. Available online: https://www.bbc.com/
news/world-asia-china-60023968 (accessed on 25 June 2022).
54.
Global Times. China Takes Strict Anti-COVID-19 Measures for International Mail. Available online: https://www.globaltimes.
cn/page/202203/1255299.shtml (accessed on 25 June 2022).
55. Allenby, G.M.; Rossi, P.E. Marketing models of consumer heterogeneity. J. Econom. 1998,89, 57–78. [CrossRef]
56.
Koemle, D.; Yu, X. Choice experiments in non-market value analysis: Some methodological issues. For. Econ. Rev.
2020
,2, 3–31.
[CrossRef]
57.
Rao, A.R.; Monroe, K.B. The effect of price, brand name, and store name on buyers’ perceptions of product quality: An integrative
review. J. Mark. Res. 1989,26, 351–357. [CrossRef]
58.
Chang, H.H. The behavioral science behind baby milk formula. Straits Times
2018
,2, 1–4. Available online: https://ink.library.
smu.edu.sg/lkcsb_research/5640 (accessed on 18 July 2022).
59.
Tian, Y.; Peng, H.; Dong, X.; Li, L.; Zhu, W. Consumers’ Brand Preferences for Infant Formula: A Grounded Theory Approach.
Sustainability 2022,14, 7600. [CrossRef]
60.
Zhang, Q.; Zhang, X.; Cui, Q.; Cao, W.; He, L.; Zhou, Y.; Li, X.; Fan, Y. The unequal effect of the COVID-19 pandemic on the labour
market and income inequality in China: A multisectoral CGE model analysis coupled with a micro-simulation approach. Int. J.
Environ. Res. Public Health 2022,19, 1320. [CrossRef] [PubMed]

Foods 2022,11, 2689 15 of 15
61.
Pei, J. Study on the Influence Of The Adjustment Of Birth Policy On The Demand Of Infant Formula And The Welfare Of
Consumers—A Case Study of Inner Mongolia Urban. Ph.D. Dissertation, Inner Mongolia Agricultural University, Hohhot, China,
December 2021.
62.
China Customs. China Customs Statistics Online Query Platform. Available online: http://43.248.49.97/indexEn (accessed on 18
July 2022).
63. Samuelson, W.; Zeckhauser, R. Status quo bias in decision making. J. Risk Uncertain. 1988,1, 7–59. [CrossRef]
64.
Abrams, S. With the Baby Formula Shortage, What Should I Do If I Can’t Find Any? Available online: https://www.catalystkids.
org/wp-content/uploads/2022/05/With-the-baby-formula-shortage-what-should-I- do-if-I-cant-find-any.pdf (accessed on 18
July 2022).