3 MATERIALS AND METHODS
3.1 Sources of Materials
The purpose of this paper is to explore the dilemma
of involution of community emergency management
under public safety emergencies by taking the
practice of emergency management in Community C
as a cut-off point. In order to gain insight into the
situation of community C’s epidemic prevention and
control work, this paper, on the one hand, based on
volunteer practice, records and analyzes the
community C's pandemic prevention and control
work from December 2019 to May 2020 in R city, G
province, and conducts semi-structured interviews
with community workers.
3.2 Assessment of Emergency
Management of Community C
3.2.1 Study Assumptions
As far as this study is concerned, the target is the
community residents, so the residents can be regarded
as the "customers" of the community for epidemic
prevention and control, and satisfaction is the attitude
and psychological experience of the customers who
are satisfied with all aspects of the service after
comparing the gap between the actual value and
demand or expectation according to the cognitive
evaluation of the community epidemic prevention
and control. Thus, we can evaluate the
implementation effect of community outbreak
prevention and control services from the perspective
of customer satisfaction. The level of resident
satisfaction directly affects the effectiveness of
epidemic prevention and control. High-quality
community epidemic prevention and control services
can achieve a reasonable allocation of limited
resources, improve the efficiency of resource
utilization, and maximize the effect of epidemic
prevention and control. In this paper, the CSI method
is used to evaluate the fullness of farmers' policies,
but two assumptions need to be determined.
a) Community outbreak prevention and control
services are felt and perceived by residents (Wang,
Luo 2010).
b) Residents are free to express their judgment in
their entirety. That is, strategic behavior has less
impact on the CSI approach (in line with the
Brookshire fascite) through proper design of the
problem. It is also said that the resident's answers to
each question are consistent with the cumulative
normal distribution function.
3.2.2 Model Selection
An important objective of the resident satisfaction
survey is to measure the current level of satisfaction
of the rural residents. This article is rated using the
Likert 5-point scale and calculated using arithmetic
weighted average (Liu 2004):
=
=
n
i 1
ii
XWCSI
(1)
CSI in the formula: customer (residents)
satisfaction index;
W
i:
Weight of the first measurement indicator;
X
i
: Customer (Residents) evaluation of the ith
satisfaction indicator.
3.2.3 Weight Design of Indicators under
Analytic Hierarchy Process
According to customer satisfaction, emergency
management and other related theories, from the
community epidemic prevention measures, the
physical and mental health of residents, residents of
epidemic prevention activities, three aspects to build
residents' satisfaction evaluation of community
epidemic prevention services, see Table 1(Peng
2018). The evaluation section uses Likert 5-point
scale to score.
In this paper, based on the index system of related
studies, the hierarchical analysis method is used to
construct an index system for evaluating the
residents’ satisfaction of community pandemic
prevention and control in community C. The analytic
hierarchy process, proposed by Saaty, an American
operations researcher, is a decision making method
that decomposes the elements related to decision
making into levels such as objectives, criteria and
programs, on the basis of which qualitative and
quantitative analysis is carried out (Wang 2003).
There are four calculation methods i thins method,
and considering the realistic operability and data
characteristics, this study selects the arithmetic
average method (summation method) for the
calculation of questionnaire index weights, and the
calculation steps are: ① normalize the elements of
the judgment matrix by column; ② add the
normalized columns; ③ divide the summed vector
by n to obtain the weight vector(Deng, Zeng, Chen,
Zhao 2012).
Step 1: through two comparisons, to determine the
relative importance between the secondary indicators,