Các yếu tố tác động tới hành vi gia nhập hệ thống sản xuất rau an toàn tại các hợp tác xã của nông dân trên địa bàn thành phố Hà Nội

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FACTORS AFFECTING THE BEHAVIOR OF JOINING
THE SAFE VEGETABLE PRODUCTION SYSTEM
IN FARMERS’ COOPERATIVES IN HANOI

CÁC YẾU TỐ TÁC ĐỘNG TỚI HÀNH VI GIA NHẬP
HỆ THỐNG SẢN XUẤT RAU AN TOÀN TẠI CÁC HỢP TÁC XÃ
CỦA NÔNG DÂN TRÊN ĐỊA BÀN THÀNH PHỐ HÀ NỘI

Abstract

PhD. Nguyen Bao Ngoc - MBA. Nguyen Hoang Nam
Thuongmai University


The study aims to assess the impact of some factors on the farmers’ behavior to join safe
vegetable cooperatives in Hanoi. Through primary data collected from 177 farmer households
participating in safe vegetable production, by qualitative and quantitative research methods, the
research results have shown expected benefits, images enterprises, environmental concerns,
knowledge barriers and subjective norms have an impact on the behavior of farmers joining behaviour safe vegetable production in Hanoi.

Keywords: Safe vegetables; Farmer’s Behaviour; Development of safe vegetable production systems.

Tóm tắt

Nghiên cứu có mục đích đánh giá tác động của một số yếu tố tới hành vi gia nhập hợp tác
xã sản xuất rau an tồn của người nơng dân trên địa bàn Hà Nội. Thông qua bộ dữ liệu sơ cấp
được thu thập từ 177 chủ hộ nông dân đang tham gia sản xuất rau an toàn, bằng phương pháp
nghiên cứu định tính và định lượng, kết quả nghiên cứu đã chỉ ra lợi ích kì vọng, hình ảnh doanh

nghiệp, kiến thức về môi trường, rào cản kiến thức và chuẩn chủ quan có tác động tới hành vi
gia nhập sản xuất rau an tồn của người nơng dân trên địa bàn Hà Nội.
Từ khóa: Rau an tồn; Hành vi gia nhập; Phát triển hệ thống sản xuất rau an toàn.

1. Introduction

Implementing Decision No. 2261 / QD-TTG dated December 15, 2014, on the Program to
support the development of cooperatives in the period 2015 - 2020 and developing the Program
to support the development of collective economy and cooperatives. in the 2021 - 2025 period
by December 2018, 1,350 cooperatives (cooperatives) were established, of which 817 accounted
for over 60% of the total number of members in the agriculture-forestry-fishery sector, on average
126 members/cooperatives; in the handicraft industry, there were 265 cooperatives, accounting
for 20%; trade, service and other fields 268 cooperatives; by 2020, there will be 130,000
cooperative groups mainly operating in the fields of agriculture, credit, and services. The
maintenance and development of cooperative groups are becoming a necessary issue to create
high efficiency, especially in the application of high technology in agricultural production
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according to Decision No. 34/2019 / QD-TTG is an important project of the Government. Safe
vegetables Hanoi has 1000 hectares, the production value reaches 1 billion / VND / ha/year and
formed several chains from production to consumption, with stamps, identification labels,
traceability, being consumed through 18 businesses, 17 cooperatives supplying retail stores,
distribution points, collective kitchens and supermarkets with the production of nearly 20,000
tons/year (accounting for 5% of safe vegetable output, 3% production of vegetables, 2% of
consumption demand). Safe vegetables without stamps, labels identifying traceability for
consumption in wholesale markets, residential markets, residential areas with an output of over

370,000 tons/year (accounting for 92.5% of the production of safe vegetables, 61,67% of
vegetable production, 37% of consumption demand). The scale of the cooperative has been
somewhat recovered and the cooperative itself has the desire to achieve high efficiency in safe
vegetable production in the market of safe vegetables in big cities such as Hanoi, Ho Chi Minh
City. Da Nang has not met the quantity and quality of safe vegetables and the Government’s
expectations for this product. The topic of safe agricultural products is a topic of national stature
and safe vegetables belonging to a group of products are among the topics of interest to both
producers, distributors, consumers, and consumers. policy managers. Taking advantage of the
traditional form of production with a long history of being a cooperative is very practical to ensure
income sources for farmers and make use of long-standing communication agricultural
production. So, the topic of research on the behavior of joining the safe vegetable production
system in the cooperatives in Hanoi is even more practical.
2. Theoretical rramework and hypothese

2.1. Theory Reasoned Action and Theory of Planned Behavior

Theory Reasoned Action was developed by the Fishbein and Ajzen (1975) and tested in
many studies by groups of authors such as Bagozzi (1992); Cordano et al (2011) ... In this theory,
to affect to the behavior, the process is built on the following factors: Behavioral Intention;
Subjective Norms and Attitude Toward the Behavior.

Figure 1: Theory Reasoned Action Model (TRA)

Source: Fishbein and Ajzen, 1975

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The study of Ajzen (1991) indicated that the TRA model of Fishbein and Ajzen (1975) was
not complete, with the view that the TRA model was incomplete due to the lack of perceived
behavior control. According to Ajzen’s point of view, sometimes behavior is not dependent on
non-motivational factors such as resources, abilities...So the perceived control behavior is
considered as a necessary role. Behavioral intention factors indicate how difficult it is to proceed
with behavior and the appropriate level from intentions to behaviors. The planned behavioral
theory adds Perceived Behavioral Control, and this factor not only affects behavior indirectly
through behavioral intent (Intention) but also live-action.

Figure 2: Theory of Planned Behavior (TBP)

Source: Ajzen (1991)

2.2. Some decisive factors to the behavior of joining safe vegetable production

2.2.1 Expected Benefit

The benefit is considered an important criterion affecting human behavior. Benefits are
assessed under many criteria such as monetary benefits, non-monetary benefits such as reputation,
market share ... For research in the agricultural sector, Mamudu (2012) through 300 farmers in
Bawku West District (Ghana) pointed out the expected benefit has a strong impact on the decision
to adopt technologies in agricultural cultivation. Mohammed Al-Ali et al. (2015) pointed out that
money benefits have an impact on customer behavior. Issues are considered to measure
commercial interest related to profitability, business-oriented fit, resource suitability, and benefits
committed by stakeholders. From the above analysis, the authors propose the research hypothesis.
H1: The expected benefit has positive impact to joining behaviour of farmer.

2.2.2. Environmental Concern

According to modern marketing opinion, social ethics is an issue that is concerned not
only from the corporate perspective but also from the customer perspective. According to Dunlap
and Jone (2012), environmental awareness is related to the level of awareness of environmental
problems and efforts to assist in solving those problems. According to Albayrak (2013), customers

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are willing to pay for environmentally friendly products and knowledge of the environment has
a positive impact on this problem. According to N.H. Viet et al (2019), knowledge about the environment has a positive influence on the behavior of re-buying organic meat products in Vietnam.
From the above analysis, the authors propose the research hypothesis.

H2: Knowledge of the environment has a positive impact on the behavior of participating
in safe vegetable production

2.2.3. Subjective Norms

The Subjective norm in studies of planned behavioral theory (TPB) or rational action theory
(TRA), the subjective norm is the main factor and influences intent (Intention). According to
Fishbein and Ajzen (1975), the subjective norm is defined as an individual’s perception, with his
or her important references to whether a behavior should or should not be performed. The performance of subjective standard measurement is determined by normative beliefs for the expectation of appropriately performing individual behavior. From the above analysis and synthesis,
the authors propose the research hypothesis.

H3: Subjective standards have a positive impact on the behavior of participating in safe vegetable production

2.2.4. Knowledge Barriers

Issues of barriers implementing behaviors are mentioned in the studies as knowledge barriers, price barriers, geographical barriers ... In the research on the agricultural production implementation. Raju Pinire et al (2018) has shown that knowledge barriers influence technology
application in rice production in Cambodia. The knowledge barrier problem is shown through
several specific issues as follows: The lack of knowledge for the new production process; The
lack of skills to operate a new production system; Lack of confidence in a new production model.
From the above analysis and synthesis, the authors propose the research hypotheses.

H4: The knowledge barrier has a negative impact on the behavior of entering the production
of safe vegetables

2.2.5. Farmers’ Cooperatives Image

Organizational image is the result of many factors such as experiences, beliefs, knowledge,
emotions, or impressions that people give to the organization (Kazoleas et al, 2001). A business
can create many messages to the public. The image of an organization is its striking power and
what is communicated (Kotler and Fox, 1995). According to Kenedy (1977), the organizational
image has two distinct components: function (related to intangible motivation) and emotional
(related to psychology). In the Vietnamese market, when participating in the safe vegetable production system, farmers tend to learn about the business they join through the level of prestige,
support for farmers, and brands. In Vietnam, the cooperatives are considered as a business model
(same as a company), including production and business.. ... From the above analysis, the research
team proposed the research hypothesis.

H5: Farmers’ image has a positive impact on the behavior of entering into safe vegetable production
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3. Research model and Research Methodology

3.1. Research Model

Based on the mentioned research hypotheses and combined with the studies of Fishbein
and Ajzen (1975) as well as Ajzen (1991). The authors propose the research model that described
in Figure 1.

Figure 1: The Proposal Research Model
3.2. Research Methodokogy

Source: Authors

Research methods applied include qualitative and quantitative research methods. In which
qualitative research is used in secondary data analysis and interviewing experts and farmers in
the process of conducting preliminary research. Quantitative research is used with primary data
analysis with IBM SPSS 22 software. The reliability test of the scale includes the EFA test, Cronbach Alpha test, correlation analysis Pearson, descriptive statistical analysis, and multiple regression analysis were conducted to evaluate the significance of the impact of the independent
variables on the dependent variables.

3.3. Measures

The research scale is built on the foundation of past studies and is considered the suitability
of the safe vegetable production environment in Hanoi. Also, to ensure the objectivity of the
scale, the research team conducted interviews with experts and conducted preliminary research
with the scale n = 24. After summarizing opinions and analyzing, the scale is extracted to 19 observed variables, including 5 independent variables and 1 dependent variable. The scale are described in Table 1.

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Table 1: Scale

No Variable

Content variable observed

Expected Benefit

1

BEN1

I believe that safe vegetable production will bring high profits in the future

2

BEN2

Safe vegetable production is the right direction for my family’s production

3
4
4
5
6

BEN3
BEN4

SNO1

SNO2
SNO3

method

The benefits that businesses are committed to are really attractive

People important to me all think that I should produce safe vegetables
People important to me willingly support me in safe vegetable production
Knowledge Barrier

8

KNOB2 I lack skills to operate safe vegetable production
Environmental Concern

ENCO1 Nature’s balance is fragile and can be easily disturbed

12

ENCO3 Man must maintain a balance with nature in order to survive

ENCO2 People are seriously abusing the environment

Farmers’ Cooperatives Image

IMA1

The safe vegetable production enterprise has a good reputation

16

IMA3

The enterprise is known for quality and value

IMA2

Enterprise is rated prestige

Farmer’s Behaviour

17

BEHA1 I myself have time to learn consider joining a network of safe vegetable production

19

BEHA3 For me, joining a network of safe vegetable production is easy

18

Raju Ghimire and Murari
Suvedi (2018)

Dunlap and Jones (2012)

ENCO4 Human intervention in nature often has disastrous consequences

14

15

(2012); Wang (2014)

KNOB3 I do not really believe in this production model

10

13

López-Mosquera et al

My relatives expect me to produce safe vegetables

KNOB1 I don’t think I have enough knowledge about growing safe vegetables

11

Zhou (2006)

Vegetable production will bring higher profits with my family’s current production

7

9

Source

BEHA2 I can join the safe vegetable chain if I want to

3.4. Collection of research data and samples

Zeithaml (1988)

Ajzen (2002)
Source: Results of data processing using SPSS 22

Research data includes secondary data collected from 2017-2020 on issues of the current
situation of safe vegetable production development. Primary data is collected through the direct
interview method through questionnaires. The study questionnaire was designed as an answer
on a 5-point Likert scale with values from 1-Strongly Disagree to 5-Strongly Agree. With the
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support of the cooperatives producing safe vegetables in Hanoi, the number of research papers
issued was 210 surveys and 197 surveys were collected. After reviewing and checking, 20 surveys
are not valid, so the official sample is 177. Applying sample collection method from Hair et al
(2006), at least 5 responses for each observed variable. For members, the minimum sample size
is 19x5 = 95, so the sample size is guaranteed. The sample characteristics are shown in Table 2.
Table 2. Demographic profile of the respondents.

Demographic Characteristic

Frequency

%

93

52.54

25-35 Years old

51

28.81

> 45 Years old

39

22.04

Gender
Male

Female
Age

35-45 Years old
Experience

84

87

47.46

49.15

1-3 Years

54

30.51

> 5 Years

45

25.42

3-5 Years

78

44.07

4. Data analysis

4.1 Testing the reliability of the scale

a. Explore factor analysis (EFA)

According to Hair and et al (1998), “Factor analysis is a statistical analysis method used to
reduce a set of many observed variables into a group so that they are more meaningful but still
contain most of the information. News of the original variable “

Principal Components extraction was used in conjunction with Varimax rotation, Bartlett
Test was performed to analyze the factors affecting the dependent variables, showing that in the
first analysis, the observed variable ECO4 has a Factor loading coefficient less than 0.5, the
variable ECO4 is excluded from the scale. The second EFA analysis results gave results KMO
coefficient = 0.799 (in the range of 0.5 -1), Sig’s Bartlett test is 0,000 (less than 0.05), the total
variance extracted is 70,287% (large more than 50%), factor loading coefficients of observed
variables are greater than 0.5. For the EFA analysis with the dependent variable being the behavior
of entering the production of safe vegetables, the coefficient KMO = 0.733 (in the range of 0.5 1), Bartlett-tested Sig = 0,000 (less than 0.05), the total Extracted variance is 78.852% (greater
than 50%), factor loading coefficients of observed variables are greater than 0.5.

b. Tested by Cronbach’s Alpha coefficients

The test results show that 19 observed variables all meet the requirements for reliability

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due to Cronbach Alpha coefficient> 0.6, Corrected item-total Correlation index is greater than
0.3, and Cronbach’s Alpha value if the variable type is not Cronbach’s Alpha is larger than the
independent variable
Table 3. Result of Cronbach Alpha and EFA Test

Variable

Content variable observed
Expected Benefit. a = 0,833

Factor

Loading

BEN1

I believe that safe vegetable production will bring high profits in the future

0,719

BEN3

Vegetable production will bring higher profits with my family’s current production

0,828

BEN2

Safe vegetable production is the right direction for my family’s production
method

0,764

BEN4

The benefits that businesses are committed to are really attractive

0,870

SNO1

People important to me all think that I should produce safe vegetables

0,883

SNO3

My relatives expect me to produce safe vegetables

0,786

SNO2

Subjective Norms. a = 0,814

People important to me willingly support me in safe vegetable production
Knowledge Barriers. a = 0,723

0,864

KNOB1 I don’t think I have enough knowledge about growing safe vegetables

0,781

KNOB3 I do not really believe in this production model

0,753

KNOB2 I lack skills to operate safe vegetable production

Environment Concern. a = 0,771

0,863

ENCO1

Nature’s balance is fragile and can be easily disturbed

0,813

ENCO3

Man must maintain a balance with nature in order to survive

0,743

ENCO2

People are seriously abusing the environment

Farmers’ Cooperatives Image. a = 0,824

0,834

IMA1

The safe vegetable production cooperatives has a good reputation

0,789

IMA3

The cooperatives is known for quality and value

0,792

IMA2

Farmers’ Cooperatives is rated prestige

Farmer’s Behavior. a = 0,866

0,821

BEHA1

I myself have time to learn consider joining a network of safe vegetable production

0,905

BEHA3

For me, joining a network of safe vegetable production is easy

0,878

BEHA2

I can join the safe vegetable chain if I want to

0,880

Source: Results of data processing using SPSS 22

Through EFA analysis for groups of observed variables in the group of independent variables and a group of observed variables in the group of dependent variables as well as testing
Cronbach’s Alpha coefficient, according to Hair et al. (2010), the model is consistent with the
collected data. security and reliability.

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4.2. Correlation analysis

Pearson’s correlation analysis will help check the linear relationship between the component variables through EFA factor analysis, which shows that the results of the correlation coefficient are all less than 0.85, indicating that potentially exists between 2 pairs of variables. In
addition to the correlation relationship of Knowledge Barrier with a Sig greater than 0.05, it
means that there is no correlation between this factor to the other variables, the result has a Sig
value of less than 0.05. The pairs of variables are correlated and statistically significant excluding
pairs of variables related to the Knowledge Barrier. However, in order to conclude whether or
not the multicollinearity occurs, the study will clarify in the next section when relying on the VIF
coefficient in multiple regression analysis. The results of the correlation analysis are described
in Table 4.
Table 4: Pearson correlation analysis
IMA

BEN

ENCO

KNOB

BEHA

IMA

Pearson Correlation

SNO

Pearson Correlation

.385**

1

BEN

Pearson Correlation

.368**

.322**

1

ENCO

Pearson Correlation

.458**

.191*

.217**

1

KNOB

Pearson Correlation

.143

.099

.052

.058

1

-.010

BEHA

Pearson Correlation

.645**

.509**

.573** .411**

-.010

1

Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)
Sig. (2-tailed)

4.3. Multiple regression analysis

1

SNO

.000
.000
.000
.057
.000

.000

.011

.189
.000

.004
.490
.000

.443
.000

.898

.898

Source: Results of data processing using SPSS 22

Linear regression models are used to test and explain causality. Multiple linear regression
is often used as a conclusion tool to test hypotheses and predict research population values in
addition to descriptive functions. Therefore, regression is a suitable method to test research
hypotheses. Detailed results are illustrated in Table 4

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Variable

Table 4: Results of multiple regression analysis

Beta

Sig

T-value

VIF

BEN

0,315

0,000

6,344

KNOB

-0,102

0,000

-2,374

1,023

IMA

0,378

0,000

6,699

Dependent

BEHA

Independent

ENCO

0,110

SNO

0,237

0,025

2,255

0,019

4,563

1,269

1,214

1,231
1,531

R2 adjusted= 0,604; F-value=54,915; Sig F=0,000

Source: Results of data processing using SPSS 22

The results of the regression analysis showed that all 5 independent variables have an
impact on the independent variable and meet the requirement of the Sig value. <0.05. F-value =
54,915, F-test significance = 0,000. The VIF indexes are all less than 2, so it can be concluded
that the multicollinearity phenomenon does not occur. Based on the standardized beta coefficient,
the order of impact on the independent variables in descending order is: Enterprise image with =
0.378; Expected benefit with = 0.315; Subjective standards with = 0.237; Knowledge of the environment with = 0.110 and finally the knowledge barrier affects the negative beta coefficient (=
- 0.10). That is, the knowledge barrier has the effect of hindering the farmers’ behavior to join
safe vegetable production. Index R2 = 0.604 shows that the independent variables can explain
60.4% of the variation of the dependent variable, while 39.6% of the remaining variation is due
to errors and other factors. Based on the results of the regression analysis, the standardized regression equation is:
BEHA= 0,315*BEN + 0,110*ENCO - 0,102*KNOB + 0,237*SNO + 0,378*IMA

4.4. Thống kê mô tả
IMA

N

SNO
BEN

ENCO

KNOB
BEHA

Valid N (listwise)

Mean

Std. Deviation

178

3.4794

178
178
178

.65175

3.3174

.65931

3.5150

178

3.7004

178
178

3.8670

3.6442

.63375
.68347
.70162
.62747

Source: Results of data processing using SPSS 22

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Enterprise image has an average value of 3,867, the highest value among the variables
shows that the importance of enterprise image is a factor of great concern by the cooperative producing safe vegetables. Knowledge barriers in the production of safe vegetables account for a
rather high value of 3,7004, claiming that the cooperatives pay attention to knowledge to produce
standard safe vegetables. The behavior of joining the safe vegetable production chain is desirable
and the cooperative itself has enough confidence to supply safe vegetables to the market with a
value of 3.6442. Environmental concern factors have been fully explored by the cooperatives because the environmental concern impact has a great impact on safe vegetable products with a
value of 3,515. The values of the cooperative subjective standard with the value 3.4794 showed
a change in attitude and the importance of safe vegetables to the cooperative. Safe vegetables
and market requirements affecting cooperatives with the lowest expected benefit value among 6

variables with the value 3.3174.

5. Some conclusions, policy implications, and further research directions

5.1. Conclusion

The study has completed the task of assessing the impact of 5 groups of factors on the behavior of farmers joining safe vegetable production. The results show that 5 research hypotheses
are accepted, of which 4 independent variables have a positive effect and the other one has a negative impact on the dependent variable. From the research results, some important conclusions
are drawn including:

Firstly, corporate image and expected benefits are playing an important role in the entry
behavior of farmers with a much higher coefficient than others.
Second, subjective standards have significant impact showing that farm owners always
consult with those around them in making final decisions.

Third, environmental awareness positively influences accession behavior, showing that
farmers are not only interested in benefits, but also have perceptions of business development
associated with environmental benefits.

Fourthly, knowledge limitations are becoming a barrier to the farmers’ entry into safe vegetable production.

5.2. Implications

Based on research results, the authors propose a number of policy implications to help cooperatives develop safe vegetable production systems:

Firstly, building a business image on the basis of development orientation is associated
with social responsibility.

Second, focus on cooperation to ensure benefits not only for farmers but also to ensure environmental issues.

Third, taking measures to ensure environmental conditions when conducting farming and
operating production models.
Fourth, focus on activities to guide and supplement knowledge for farmers in the operation
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and improve farming skills to break down the knowledge barrier of farmers intending to join the
system. safe vegetable production system.

5.3. Further research orientation

Despite trying to complete the research objectives, but due to the time and space limitations,
there are still limitations, from these limitations opening up many research directions in the
future.

Firstly, the sample size is limited and the type of research considered is a cooperative model.
Therefore, the research results are not highly representative. Therefore, in the future, it would be
ideal if the research is to be modeled and to conduct research on other diverse subjects besides a
cooperative model.

Second, the index R2 = 0.604 shows that nearly 40% of the variation of the independent
variable has not been discovered. This means that it is necessary to consider adding new factors
to the model such as the resources of farmers, support from agricultural development policies...

Thirdly, the study has not been able to conduct multi-group tests to assess the differences
between study groups. Criteria of years of farming experience, age, financial capacity, and cultivated land area have many potential discoveries if they are conducted in multi-group tests.

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