In order to explore the public's awareness and demand for the development of new energy from
genetically modified microalgae, this article uses a questionnaire survey, based on the user
questionnaire data collected in the online survey in the survey, and passes reliability,
validity tests, project analysis, and independent chi-square tests. Other statistical
methods test the rationality of the questionnaire and prove that the survey results are true
and credible.
Based on the results of the questionnaire survey, descriptive statistical methods are used
to analyze the basic information of users, combined with Maslow’s demand theory, a user
demand model based on the CRITIC weighting method is established to study the user’s
acceptance of genetically modified microalgae and its products. The relationship between the
various levels of needs. Analyze the user's acceptance according to the user demand model,
use the K-means cluster analysis method to mine potential users, and deeply explore the
value of the four potential users and their personalized characteristics.
Finally, two conclusions of this article are given: in the analysis of user needs, it is
found that the user's demand for genetically modified microalgae and its products is mainly
derived from safety needs and emotional needs; out of potential user mining, it is believed
that enterprises need to focus on developing high education. Or potential users such as
middle-aged and elderly people with rich experience. According to the analysis of the
questionnaire, this article also proposes corresponding product development suggestions and
strategies.
Introduction
Since the beginning of the 21st century, with the development of molecular biology and the
improvement of genetic engineering, biomass energy has sprung up, and has continuously expanded
its
proportion in the energy structure. Bio-oil production is its main development direction. The
third-generation bio-oil production uses microalgae to produce bio-oil, which has the advantages
of
sustainability, carbon sequestration and emission reduction, strong stability, and high safety.
Among them, Phaeodactylum tricornutum, as a marine model diatom with short growth cycle, easy
cultivation, and high oil content, can accumulate 20% to 30% of its own fat. It is a potential
biodiesel resource algae species. Phaeodactylum as a culture substrate, using synthetic biology
to
increase the expression of oil-producing genes, can provide a novel direction for the
industrialization of bio-oil production, promote low-carbon and environmentally friendly life,
help
the green development of the whole society, and contribute to my country's carbon neutrality
strength.
However, genetically modified microalgae and their new energy products, as emerging products,
will
inevitably be questioned by the public. The public's unknown acceptance of microalgae may become
a
major obstacle to the development of microalgae. Therefore, by issuing questionnaires to the
public
for investigation and analysis, to study the public's understanding and acceptance of microalgae
products, and then analyze the needs of users, and provide certain references and suggestions
for
the future direction of microalgae products and publicity methods.
Investigation Plan and Implementation
Investigation Plan
(1) Purpose of Investigation
Collect the public's understanding of the development of new energy by genetically modified
microalgae, and collect the basic information of the surveyed persons, including data such
as gender, age, occupation, education, permanent city, etc., and analyze the degree of
understanding of different groups of microalgae.
Collect the user's motivation to use new bio-energy, microalgae products, and genetically
modified products in the survey, and analyze the public's acceptance of the three types of
products.
Collect users' attitudes and emotional components of new energy, microalgae, and genetically
modified products to provide a certain reference for product promotion and future promotion.
(2) Investigation Method
Affected by the new crown epidemic, this questionnaire survey uses the questionnaire star
platform, replacing traditional paper questionnaires with online survey electronic
questionnaires. Jump questions are set in the electronic questionnaires to effectively
target different groups of people with different questioning methods, eliminating data entry
links and avoiding A typographical error occurred.
(3) Survey Item
This survey mainly studies the public's awareness and demand analysis of genetically
modified microalgae. The survey is divided into three dimensions: cognitive component,
emotional component, and behavioral component. The cognitive component is the understanding
and knowledge of something; emotion; The component is the preference for something; the
behavior component is the expectation and intention of the future behavior or state.
Corresponding survey questions are set through these three dimensions, the respondents are
considered, and the survey framework of the questionnaire is constructed as shown in Table
1.
Table 1 Questionnaire Design Framework
Investigation Implementation
(1) Investigation Organization
Beginning in January 2021, we have conducted full team discussions and determined the
content and purpose of the survey: to study the public's understanding and demand for
the
development of new energy sources of genetically modified microalgae, and initially
designed
the content of the questionnaire. From February to April 2021, we conducted a two-month
pre-survey. By analyzing the pre-survey data, we screened out unqualified questions and
replaced them, thereby improving the questionnaire. After confirming the formal
questionnaire, we began to formally release the questionnaire to the public, and planned
the
time for questionnaire collection, data analysis, and report writing.
Fig.1 Time Progression Diagram
(2) The Quality Control
In the formal questionnaire given, we set up a set of jump questions. Starting from the
question "Do you know something about microalgae?", according to the different answers
of
users, two different sets of survey questions are given. This measure can It effectively
distinguishes user categories and is more targeted. Conducting research in the form of
electronic questionnaires can reduce the cost of printing and binding paper
questionnaires.
Pre-survey Data Testing
Credit Analysis
Reliability refers to the reliability or consistency of the measurement results. The higher
the reliability, the more consistent or stable the measurement results. This questionnaire
uses the analysis based on Kronbach’s Alpha coefficient method for reliability analysis.
When the Alpha coefficient is greater than 0.7, the sample reliability is high. We divided
the questionnaire into three aspects: bio-new energy, algae products, genetically modified
technology, etc. to ask questions for users. Among them, two sets of questioning methods
were set up in algae products, and SPSS software was used to check the reliability of
different users. Consistency of the scale.
Table 2 Reliability Test
It can be clearly seen from the table that the coefficients of new bio-energy, algae
products, and genetically modified technology are all greater than 0.8, and the
questionnaire has high reliability.
Validity Test
Validity refers to the degree to which a measurement tool or means can accurately
measure
the things to be measured, and exploratory factor analysis is used to test the validity.
The
validity test is mainly divided into two steps:
Step 1: Perform KMO measurement and Bartlett ball test to check whether the data can be
used
for factor analysis;
Step 2: Rotate the factor analysis to obtain the factor load value of each option, and
calculate the cumulative variance to explain the overall variance.
The KMO measure is used to check the partial correlation between variables, and the
value is
between 0-1. The closer the KMO value is to 1, the stronger the partial correlation
between
variables and the better the effect of factor analysis. KMO value above 0.9 is very
suitable
for factor analysis, above 0.8 is suitable for factor analysis, above 0.7 is acceptable,
above 0.6 is acceptable, above 0.5 is not suitable, and below 0.5 is very unsuitable. In
actual application, above 0.7, the effect is better; below 0.5, it is not suitable to
apply
factor analysis. [1]
The Bartlett sphere test is used to judge whether the correlation matrix is a unit
matrix,
that is, whether each variable has a strong version correlation. P<.05, does not obey the
sphere test, and the assumption that each weight variable is independent should be
rejected, that is, there is a strong correlation between the variables; when P>
.05, the
sphere test is obeyed, and the variables are independent of each other, so factor
analysis cannot be done.
Table 3 KMO and Bartlett Test
The above table is the result of the validity test. The KMO value of the four
variables
is between 0.7-0.9, and the validity result is excellent. The P value is all < 0.05, and
there is a strong correlation between the variables. Therefore, the structure
classification of the scale is reasonable.
Project Analysis and Inspection
Item analysis can test the distinction of each item in the scale. Specifically, it
is to test whether some of the surveyed objects can give high scores in the scale,
and some surveyed can also give high scores in the scale. A low score means that
each item in the scale has better distinguishability. The essence is to explore the
differences in each item of subjects with high and low scores.
Take the question of "Your Attitudes to Biodiesel" as an example for project
analysis. There are 5 options in the question. The answer to each option is set from
"strongly disagree-strongly agree" to 1-5 points, and the setting is less than 27%.
Those with higher than 73% are classified as low groups, and those with higher than
73% are classified as high groups. The item analysis test is performed, and the
results are shown in the table. The significance level of the high and low groups is
P< 0.05, indicating that the setting of questions has a higher degree of discrimination and
can distinguish the attitudes of different respondents. At the same time, the project
analysis of other topics is passed, that is, the questionnaire has a good degree of
discrimination and discrimination.
Table 4 Subjective Attitude
Chi-square Independent Test
The independence test can be used to determine whether the two variables are
related to each other or independent of each other. Taking the two variables
of
"Do you know anything about algae products?" and "Will you recommend family
members, relatives or friends to use algae products" as an example, perform
a
chi-square independence test. The hypothesis test questions are:
H0: Two variables are unrelated
H1: Two variables are related
Table 5 Chi-square Independent Test
The progressive significance is less than 0.05, so the null hypothesis can
be
rejected, indicating that there is a correlation between the two variables,
that
is, people who know about algae are likely to recommend algae products to
people
around them. As a result, by performing chi-square independence tests on
other
variables in turn, it can be found that there is a correlation between most
of
the variables.
Data Processing and Analysis
Data Statistics and Processing
(1) Data Output
Through the questionnaire star platform, the user's detailed information can be
exported to
an excel file. In the exported data file, according to the order of the options,
the user's
answer to each question is shown in numerical order from small to large.
(2) Data Cleaning
Exclude the samples that did not complete the required answers, that is, the
samples that
did not complete the questionnaire;
According to the user's submission time, the samples with too short or too much
response
time will be eliminated.
Descriptive Statistics
(1) Age Distribution of Sample Persons
Fig.2 Age Distribution Map
Among the interviewees, six age groups were covered. The survey population is
mainly
concentrated between the ages of 18 and 25. At the same time, this group of
people is also
the main recipient and consumer of emerging things. Their attitude and
acceptance of
genetically modified microalgae to develop new energy sources can reflect the
development
trend of the industry in the next few years to a certain extent.
(2) The distribution of academic qualifications of the sample
Fig.3 Educational Qualifications Distribution Map
Among the respondents, there are a total of 7 academic backgrounds, and
the majority
of them have a bachelor's degree or above. The specific account is as shown in
the figure
above. In the surveyed population, undergraduate and above accounted for the
majority. This
population has more relevant knowledge and can give a more correct judgment on
the new
energy of microalgae. The data can well represent the high-level knowledge of
the population
of genetically modified microalgae. Attitude to produce new energy.
(3) Occupation distribution of sample personnel
Fig.4 Occupation Distribution Map
For the investigators, the CCP includes eight types of occupations, of which
students
account for the majority. In all occupations, the understanding rate of
microalgae in all
occupations, except for state agencies, party organizations, and public
institutions, has
reached 58%, and the understanding rate of microalgae in other occupations is
less than 50%,
and the average understanding rate is only 39.9%. The lack of understanding of
algae may
affect the promotion of the microalgae industry.
User Behavior Analysis Based on Demand Hierarchy Model
Hierarchy of Needs
According to Maslow’s "Needs Theory", the most basic human needs are divided into five
levels:
physiological needs, safety needs, emotional needs, respect needs, and self-realization
needs.
We combine the information available in the questionnaire with these needs One-to-one
correspondence. [2]
First, physiological needs, as the first demand that arises, when facing a new thing, you
first
need to have a basic understanding of him, which can be described in the questionnaire as
knowledge of genetically modified microalgae products, which is beneficial to users Go
choose
microalgae products.
Second, safety requirements. When users choose genetically modified microalgae products,
they
will first have questions about their health and require the products to be safe. Therefore,
they are described in the questionnaire as the safety and nutritional value of the product.
Third, emotional needs. Out of the needs of emotion, friendship and belonging, the public
often
needs to communicate with relatives, friends, colleagues and other relationships to obtain
corresponding emotional supplements. Therefore, we describe this need in the questionnaire
as
Are you willing to share genetically modified microalgae products with your relatives and
friends?
Fourth, respect needs. For this purpose, users hope to get the attention of others and
the
recognition of the society. This is reflected in that the users themselves have high
professional knowledge of microalgae products, and they have a strong influence on obtaining
more knowledge. interest.
Fifth, self-realization needs, as the highest level of needs in the theory of needs, when
people
meet other needs, they will pursue self-realization, that is, they can have a certain impact
on
the society, which can be reflected in the questionnaire as users Evaluate the current
social
phenomena of microalgae products and look forward to their future development trends.
Demand Model
(1) CRITIC Method to Calculate Weight
In order to study what kind of demand among the five major needs when users are willing to
accept genetically modified new energy products.
By analyzing the degree of influence of the topic on the user's degree of product demand,
the
CRITIC weight method is used to measure the objective weight of the topic, and the
variability
of the topic is considered while taking into account the correlation between the topics. For
example, the standard deviation is used to indicate the fluctuation of the value of each
option.
The larger the standard deviation, the greater the numerical difference of the option, the
more
information can be displayed, and the stronger the influence of the option itself. The
correlation coefficient is used to indicate the correlation between indicators. The stronger
the
correlation with other options, the less conflicting this option with other options, the
more
the same information is reflected, and the weaker the option to a certain extent. Influence。
Therefore, first select the options related to the people’s demand for the product in the
questionnaire, such as "Will you recommend family members, relatives or friends to use algae
products?" It has great prospects for application in the food, medical, and industrial
fields."
The higher the value of these options, the higher the acceptance of the product by the
masses.
The lower the value, the lower the acceptance of the product by the masses. The larger the
standard deviation, the greater the numerical difference of the option, and the greater the
influence of the choice of the option on whether to accept algae products. The larger the
correlation coefficient, the more the same information it reflects with other options, which
means that the choice of this option has less influence on whether to accept the product.
Therefore, considering the two factors, the amount of information is calculated and the
weight
is obtained. Specific steps are as follows:
The weight calculation results are shown in Table 6:
Table 6 The Weight of the Five Major Needs
(2) User Acceptance Prediction
User Behavior Analysis
Different users will always have a certain kind of demand occupying an important position at
different stages of life, which will dominate their personal behavior. Explore the user
scores
corresponding to each need level, and it can be found that the two most important sources of
user scores are security needs. And emotional needs.
In the data set, 66.48% of users’ scores mainly come from safety requirements, that is, it
is
hoped that genetically modified microalgae and its products can meet their safety
requirements.
When the product meets the user’s safety requirements, the corresponding score will rise
relatively. High, these users have a certain degree of recognition for the safety of
genetically
modified products, which is the fundamental reason why they choose genetically modified
microalgae products.
At the same time, 24.73% of users’ scores are due to the satisfaction of their emotional
needs.
The most important reason why these users choose to accept genetically modified microalgae
and
its products is because of emotional communication with family, relatives or friends, and
sharing products to promote Mutual communication.
In addition to this, there are other users who choose to accept genetically modified
microalgae products out of physiological needs, respectful needs, and self-realization
needs.
Self-actualization needs are the most advanced needs in Maslow's theory, and accordingly
fewer
people choose products out of this need.
Fig.5 User Needs
Potential User Mining Model Based on Cluster Analysis
Potential User Definitions
In the questionnaire setting, in order to strengthen the pertinence of the
questionnaire,
we set up a jump question for users who have different answers based on the question "Do you
know anything about algae products?" Among users, dig out potential users among them.
Through the above demand model, we can find a group of users who do not understand
algae
products, but are willing to accept algae due to various needs, and may become buyers and
users
of algae products in the future. Class group, we define as the potential user group that is
most
likely to be tapped at present.
Potential User Model
(1) Cluster Analysis Based on AGEPU
To perform cluster analysis on the questions of potential users in the questionnaire,
the
first choice is to select a clustering factor. We start from the characteristics of
consumers,
combined with the prediction of user demand models and do not understand the acceptance of
algae
products, and set five cluster analysis indicators: A, G, E, P, U
Table 7 Potential Task Indicaor Meaning Table
Analyze the collected user data, calculate the relationship between k and SSE, divide
users
into 5 categories, and perform cluster analysis through python.
Fig.6 The relationship between k and SSE
(2) The composition of potential users
The user data is clustered, and the clustering results are shown in Table 8.
Table 8 Clustering Result
Draw a radar chart of each category of users, and analyze the situation of the five
categories of users on each attribute. From the figure, it can be found that each user group
has
significantly different performance characteristics: User group 1 is the largest in age and
acceptance attributes. Occupation and gender attributes are the smallest; user group 2 has
the
largest acceptance attribute and the smallest in age attribute; user group 3 has the largest
occupation and gender attributes and has the smallest education attribute; user group 4 has
the
largest education and gender attributes; users Group 5 has the smallest acceptance
attribute.
Fig 6 Radar Map
Based on the feature description, this article defines four levels of user categories:
important
potential users, important development users, general users, and low-value potential users.
The
characteristics of each customer type are as follows:
1. Important potential users: Mainly the first group of people. The biggest feature is
higher education and older age. The analysis may be college teachers or high-educated
middle-aged and elderly people, who have rich experience and pay more attention to and
understand the environment and other new energy knowledge. The acceptance of microalgae
products
is relatively high.
2. Important development users: mainly the second group of people. This group of people
has
high education, but is young, and most of them are college students receiving higher
education.
These users are in the new development force of society and have a high degree of acceptance
of
new things. , But the demand is not great, and it may develop into important potential users
in
the future.
3. General users: This type of user group is relatively complex, consisting of the third
and
fourth clusters. According to user characteristics, there are mainly two types of users,
namely,
freelancers, people with lower education levels, and younger male mass groups.
4. Low-value potential users: The fifth group of people is mainly male. This type of user
has a
high degree of education, and there is no feature that can be described more significantly
different from other users for the time being.
Conclusions and Strategies
Research Conclusion
In this paper, the user data obtained through online questionnaires, starting from the
user's cognitive components, emotional components, and behavioral components, in-depth
research
on the public's demand for genetically modified microalgae and its new energy products. The
research viewpoints and conclusions of this article are as follows:
The user's demand for genetically modified microalgae and its products mainly comes from
safety needs and emotional needs. On the one hand, when users believe that the safety of
genetically modified microalgae and its products are up to standard, the corresponding
acceptance will be high. This shows that in the sales process of genetically modified
microalgae
products, safety is the fundamental reason for users to choose products, and it is necessary
for
companies Strengthen the safety control of the product; on the other hand, due to the needs
of
emotional communication and interpersonal communication, users will also choose to recommend
genetically modified microalgae and their products to their relatives and friends.
Therefore,
companies should improve on the level of emotional needs The publicity method can
effectively
expand the market scale of genetically modified microalgae products.
In tapping potential users, companies need to focus on developing middle-aged and
elderly
people with high education or rich experience. Such users are important customers receiving
genetically modified microalgae and its products. At the same time, college students
receiving
higher education should be included in the next step of developing customers. , To prepare
for
the next promotion of genetically modified microalgae products.
Suggestions
(1) Expand Product Promotion Channels
Strengthen the popularization of science: Users’ low acceptance of genetically modified
microalgae products is largely due to their lack of understanding of microalgae products and
lack of knowledge of genetically modified technology. Companies should pay attention to the
popularization of genetically modified microalgae products and get through system
information.
Dissemination channels, maintain mass media: such as TV, newspapers and periodicals,
strengthen
new media platforms such as WeChat public accounts, Weibo and other positions to promote,
effectively supervise and control the dissemination of pseudo-scientific information, and
ensure
the strong credibility and credibility of product publicity authoritative.[3]
Focus on key groups: In the face of different groups' understanding of microalgae-related
information and their willingness to demand, microalgae companies should focus on the
cognitive
differences of different groups of people and form a point-to-face information dissemination
situation to improve the efficiency of publicity.[4]
Establish a publicity method oriented by emotional needs: In Maslow's demand model,
users
who can accept microalgae products are more in emotional needs. The general public often
communicates with relatives, friends, colleagues, etc. for the needs of emotion, friendship
and
belonging. Microalgae products are used as a communication medium to allow users to obtain
corresponding emotional supplements. At the current stage, strengthening the promotion of
emotional needs can make users willing to share genetically modified microalgae products
with
their relatives and friends, thereby promoting the production and marketing of microalgae
products.
(2) Ensure Product Safety and Improve Laws and Regulations
Improve the detection technology of microalgae products: Testing of genetically modified
microalgae products is a necessary means to ensure their quality and safety. With the
continuous
development of genetically modified foods, countries and relevant international
organizations
are actively developing genetically modified product testing technologies. At present, the
most
mature technology for genetically modified products testing methods is PCR technology.
Enterprises should build on various international and domestic technologies. Look for more
accurate, faster and safer detection technologies, strengthen the safety assessment of
genetically modified products, and allow users to use genetically modified microalgae
products
with confidence.
Improve relevant laws and regulations: To promote genetically modified microalgae
products,
it is necessary to strengthen the improvement of relevant laws and regulations, and strictly
control the scientific use of genetically modified products and species. Not only must
consumers’ legitimate rights and interests such as the right to know and the right to choose
be
reimbursed, but also attention must be paid to the control of microalgae. As algae harm the
ecological environment, it is strictly forbidden for enterprises or factories to make
operations
that affect or even endanger the ecological environment system for profit.[5]
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[3]. Chen Guirong, Public Understanding and Acceptance of GM Food -- Investigation and
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[4] MAO Xinzhi, Wang Peipei and Zhang Meng, Investigation and Analysis of Public's
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