Research on the Influencing Factors of Heilongjiang Provincial

Government Data Openness in the Era of Big Data

Ping Liu

and Fangqi Li

Institute of Finance and Public Management, Harbin University of Commerce, Xuehai Street, Harbin, China

Keywords: Big Data Era, Open Government Data, Influencing Factors.

Abstract: With the advent of the era of big data and the rapid development of science and technology and the Internet,

government data openness is an important part of the digital transformation of the government. Government

data disclosure has become an important means of government reform. This paper uses the fuzzy set

qualitative comparison method (FSQCA) to analyze the factors affecting the data openness of the

Heilongjiang provincial government from the perspective of configuration, so as to improve the level of the

data openness of the Heilongjiang provincial government, improve the governance capacity of the

Heilongjiang provincial government, and promote the digital construction of Longjiang.

1 INTRODUCTION

Government data openness is an important part of

the government's innovative governance model in

the big data environment, and it is also the key to

building a digital government. Combined with the

background of the era of big data, actively realize

the openness of government data, improve the

utilization rate of government data resources, and

give full play to the value of government data

resources. In recent years, the Heilongjiang

provincial government has actively responded to

national policies and continuously implemented the

state's task of promoting government data openness.

In the 2021 Heilongjiang Provincial Government

Work Report, we continue to explore how to

improve the level of government governance faster

and provide more effective government services to

the public. (Pu, 2022) This paper mainly studies the

main influencing factors of Heilongjiang Provincial

Government Data Opening and its development path

model. Using some data from China Statistical

Yearbook and Fuzzy Qualitative Comparative

Analysis (FSQCA), the conditional configuration

analysis of 12 prefecture-level government data

open platforms in Heilongjiang Province was carried

out. Exploring the influencing factors of

https://orcid.org/0000-0001-8317-6906

https://orcid.org/0000-0002-9738-9061

Heilongjiang provincial government data disclosure,

exploring differentiated development paths

according to the influencing factors, and improving

the government's administrative efficiency and

service quality are the key measures to promote

Heilongjiang provincial government data openness.

2 THEORETICAL BASIS OF

OPEN GOVERNMENT DATA

Government data, also known as public data or

public service data, refers to the original data

actively or passively collected by government

departments or public departments in the process of

exercising public power, such as information

registered by individuals and organizations and

collected statistics, population, geography,

meteorology, medical care, social security,

education and other data. (Shangguan, 2022) Data

openness is a new trend in the field of information

and communication technology, especially for the

opening of government data, which has great

potential in improving government transparency,

strengthening supervision and accountability

mechanisms, and stimulating economic growth. (Tan

2018)

Data openness is a new trend in the field of

information and communication technology,

especially for the opening of government data,

Liu, P. and Li, F.

Research on the Inﬂuencing Factors of Heilongjiang Provincial Government Data Openness in the Era of Big Data.

DOI: 10.5220/0012072200003624

In Proceedings of the 2nd International Conference on Public Management and Big Data Analysis (PMBDA 2022), pages 211-217

ISBN: 978-989-758-658-3

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

211

which has great potential to improve government

transparency, strengthen supervision and

accountability mechanisms, and stimulate economic

growth. Based on the optimistic benefits and

positive effects of government data openness, more

and more countries are turning their attention to

creating greater social and business value and

improving social governance through data openness.

In the era of big data, government data openness has

set off a wave of heated discussions in the field of

public management. The research on the influencing

factors of government data openness has received

extensive attention from the academic community.

3 RESEARCH METHODS AND

DATA SOURCES

3.1 Research Methods

In this paper, 12 prefecture-level cities in

Heilongjiang Province are used as case samples, and

the fuzzy set qualitative comparison method

(FSQCA) is used to explore the robust relationship

between different explanatory variables and better

explore the research details of typical cases.

3.2 Data Sources and Calibration

Data cut-off date 2021. The data are mainly from the

China Statistical Yearbook 2021 and the China

Local Government Data Open Report 2021.

3.2.1 Result Variablestitle

Starting from the research logic of qualitative

comparative analysis of fuzzy sets, the data

openness level of each municipal government is the

result variable that needs to be explained, and the

government data openness index is selected as the

result variable to discuss the effectiveness of

government data openness. Using continuous

variable assignment can better present the

configuration effect of QCA analysis results.

3.2.2 Condition Variables

The diversity factor of the level of data openness of

the municipality is the conditional variable. In this

paper, four representative conditional variables are

selected, namely leadership support, public demand,

financial support and human support, so as to

facilitate the regular and comprehensive analysis and

interpretation of the effectiveness of government

data opening.

a. Leadership support

This article uses whether the government has

established a special data open management agency

to measure the importance of leaders, and the data

comes from the government's official website and

public news reports. The attention of key

government leaders has an important impact on the

level of data openness of local governments.

Existing studies have found that support from senior

leadership can drive governments to choose data

open strategies and promote sustainable

development goals. Leadership authority can

facilitate coordination and cooperation between

groups, and the influence of individual leaders will

affect the development of the organization.

b. Public demand

The era of big data has put forward new

requirements for the opening of government data.

The public's demand for government data has

strongly promoted the process of data openness. The

size of public demand is linked to the size of the

population. This paper uses the year-end population

of each province to express public demand, and the

data is from the China Statistical Yearbook 2021.

c. Financial support

With limited resources, the organization's day-to-

day administrative expenditures and necessary items

for the provision of public services will be

prioritized to meet basic public needs, while

innovative activities similar to open government

data will be limited. When the government's

financial resource capacity is strong, there are

enough surplus resources to invest in development

areas such as open data, so as to realize economic

and social value. This indicator is expressed in

general public budget revenue per capita in each

district.

d. Human support

Manpower is the backbone of improving the

level of government data openness, and manpower is

the most active and active production factor in an

organization. Human resources are measured by

calculating the proportion of employment in

information transmission, software and information

technology services in each province to total

employment. Data from China Statistical Yearbook

2021.

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3.2.3 Data Calibration

In this paper, direct calibration was chosen to

convert the data into fuzzy membership scores. The

calibration standard for the intersection of leadership

support, public demand, financial support, and

human support is 0.5 percentile, 0.75 for fully

subordinate and 0.25 for fully unaffiliated

calibration standards. (Yang, 2020)

Table 1

summarizes calibration information for each

condition and results.

Table 1: Selection and Calibration of Variables.

Conditional and result

variables

Calibration information

Full affiliation Intersection Not affiliated at all

Open level of

government data

41.645 11.723 6.625

Leadership support 1 / 0

Public demand 7732.7 4959 3223.8

Financial support 0.7629 0.5724 0.463

Human support 0.005 0.0032 0.00265

4 EMPIRICAL ANALYSIS AND

MODEL BUILDING

4.1 Empirical Analysis

4.1.1 Necessity Analysis of Conditional

Variables

Before performing a conditional configuration

analysis, analyze how well a single condition

variable explains the outcome variable. When the

consistency is greater than 0.9, the condition

variable is considered necessary for the result, and

vice versa, when the consistency is less than 0.9, the

variable needs to be interpreted in combination with

other variables. (Yang, 2020) The consistency and

coverage of each condition variable are shown in

Table 2. The level of agreement for all conditional

variables is below the cut-off value of 0.9 and

therefore does not constitute a necessary condition

for affecting the level of openness of government

data.

Table 2: Requirements analysis.

Condition variables consistency Coverage

High leadership support 0.874623 0.623784

Low leadership support 0.118267 0.132008

Strong public demand 0.540920 0.500027

Weak public demand 0.478231 0.478900

High financial support 0.612180 0.673512

Low financial support 0.492388 0.402817

High manpower support 0.692187 0.682630

Low human support 0.492039 0.412987

4.1.2 Adequacy Analysis of Conditional

Variables

The adequacy analysis of the conditioned

configuration attempts to reveal the influence of

different combinations of conditions on the results.

0.75 is the minimum acceptable consensus

threshold. In addition, frequency threshold is also an

important analysis and evaluation indicator. In this

paper, the consistency threshold is determined to be

0.8 and the frequency threshold to be 1. To reduce

the potential contradiction configuration, the PRI

(Proportional reduction in inconsistency) threshold

is introduced to filter the configuration. Truth table

rows with PRI greater than or equal to 0.75 are taken

into account. The intermediate and simplified

solutions that generate high-level data open paths in

FSQCA are shown as follows, as shown in Table 3

and Table 4.

Research on the Inﬂuencing Factors of Heilongjiang Provincial Government Data Openness in the Era of Big Data

213

Table 3: Intermediate path results for high-level government data openness.

Model: Open data=f (leader, public, fiscal, human)

Algorithm: Quinc-McCluske

---INTERMEDIATE SOLUTION---

Frequency cutoff 1

Consistency cutoff:0.896211

Raw unique

Coverage coverage consistency

~fiscal*~human*~leader 0.177239 0.177239 0.177239

fiscal*~public*~leader 0.27239 0.0257295 0.929176

fiscal*~human*~public 0.0428255 0.0428255 0.921811

*~leader

solution coverage: 0.628876

solution consistency: 0.864399

Table 4: Produces simple path results that produce a high level of government data openness.

Model：Open data=f（leader，public，fiscal，human）

Algorithm：Quinc-McCluskey

---INTERMEDIATE SOLUTION---

Frequency cutoff 1

Consistency cutoff：0.896211

Raw unique

Coverage coverage consistency

human*~leader 0.628173 0.543211 0.879665

fiscal*~public*~leader 0.155538 0.0611132 0.977654

solution coverage: 0.728192

solution consistency: 0.842938

Table5 results show that the path to a high level

of government data openness is diverse, with three

different conditional configurations. The consistency

of the solution is 0.864399 and the coverage of the

solution is 0.628876, both above the critical value.

The three configurations can be regarded as

sufficient combination of conditions, and the high

degree of government data openness is a

differentiated synergy relationship of common path

and multiple concurrency.

Table 5: Configuration analysis of high-level government data openness.

Condition

variables

untie

Configuration

one

Configuration

two

Configuration

three

Leadership

support

√ √ √

Public

deman

╳ √ √

Financial

ort

√ ╳ √

Human

ort

√ √ √

consistency 0.934793 0.915572 0.9

Original coverage 0.27239 0.177239 0.0428255

Unique coverage 0.0257295 0.198843 0.0428255

Consistency of solutions 0.864399

The covera

e of the solution 0.681967

Note: √ indicates that the condition exists, ╳ indicates that the condition is absent.

Condition 1 shows that for the government with

both good financial resources and human resources,

if more leadership attention can be devoted to the

behavior of data openness, the government can also

have good data open performance.

Condition 2 shows that leadership support plays a

central role, and the existence of public demand

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plays a supporting role. For the topic of government

data openness, if the government does not have

sufficient financial resources and human resources

support, relying on the great attention of the main

leaders to the government data openness, it can bring

a higher level of government data opening

performance, thereby bringing better data opening

performance.

Condition 3 shows that the performance of the

government with a high degree of open data

development is in the forefront in all aspects, which

is generated by the joint efforts of various

conditional elements. The superior conditions in all

aspects have laid a solid foundation for good

government data opening performance. If the main

leaders attach more importance to the open data

work, a special data open management organization

has been established. Governments governed by the

dynamics of competition and cooperation will

enhance the autonomy and initiative of governments

to develop the region's economy. The formation of

open government data platforms with high levels of

utilization is possible.

4.1.3 Robustness Test

Fuzzy set qualitative comparison studies may vary

depending on the threshold, so a robust test is

required for the above results. Drawing on the

existing research experience, this paper adjusts the

PRI threshold to perform a robust test. The

difference between the necessity analysis results of a

single condition and the original result is small, and

there are only slight changes between the

consistency and coverage of the single configuration

and the overall solution and the original result in the

analysis results of the conditioned configuration. In

view of this, we can judge that the impact of the

above combination of conditions on the level of

local government data openness is robust.

4.1.4 Study Results

According to the core conditions contained in the

above three condition combinations, this paper

further determines the differentiated matching

relationship to promote a high level of government

data openness. Combined with the actual situation,

two data opening paths of the Heilongjiang

provincial government are summarized:

organization-driven and coordinated with guarantee

elements.

4.2 Model Building

4.2.1 Organization-Driven

Organized-driven governments are able to

demonstrate a high level of data openness even

without good economic and human resources. The

support of government leaders and the needs of the

public In the process of government public

governance, the support and decision-making of

leaders will promote the effective solution of many

things. (Zhou, 2017)

Therefore, leadership support

can be understood as a realistic form of governance.

The government's implementation and continuous

promotion of data openness is a good demonstration

of leadership. Government actions are always rule-

based and lack sensitivity and responsiveness to the

needs of the public. Harbin has built a unified data

open platform for the whole city, opened 53

government functional departments,3.17million data

in 14 fields, and led the level of openness, basically

achieving full coverage of data openness, thanks to

the government's great attention to the construction

of the data open platform.

4.2.2 Guarantee Element Coordination

The performance of government data openness is

mainly facilitated by rich financial support and

human support, and appropriate resource

redundancy provides the government with flexibility

to seize opportunities and grasp the market.

Government data openness is a new public

governance activity aimed at promoting the

development and utilization of data resources, better

meeting high-level needs, and enhancing public

interests, whether such interests are political or

economic. Government data openness is a kind of

government innovation, which requires financial

support. At the same time, considering that

innovation does not happen overnight, especially in

the short term, and that organizations need to be

strong and able to bear the risks and costs associated

with it, financial investment is essential.

5 RESEARCH CONCLUSIONS

AND RECOMMENDATIONS

5.1 Conclusion of the Study

Based on the above analysis, the following

conclusions can be drawn.

Research on the Inﬂuencing Factors of Heilongjiang Provincial Government Data Openness in the Era of Big Data

215

First, local government data openness is a

coordinated development of multiple factors, and

leadership support, market demand, financial

support and human support cannot be used as

necessary conditions for influencing local

government data openness alone. The behavior of

local government data openness is the result of a

combination of conditions. There are three different

paths to promote high-level local government data

openness, and each path is composed of multiple

factors, and the effective integration and interaction

between different factors have increased the degree

of government data openness.

Second, organizational drive is a key condition

for promoting local government data openness. That

is, the support of government leadership and the

needs of the public play an important role. The

emphasis on senior leadership brings innovation to

the public policy agenda, and the two work together

to implement open government data. The overall

level of data opening of the Heilongjiang provincial

government is not high, and it is still in the early

stage of high-quality development as a whole.

Third, ensuring resources is an important driving

force for promoting the opening of local government

data. Any local government can be regarded as a

resource aggregate, and appropriate resource

redundancy enables the government to seize more

innovation opportunities and better promote the

implementation of local government data openness.

The government's own diversified organizational

resources, the attention and support of senior

leaders, and the external environmental pressure

jointly drive the implementation of data openness

behavior and promote sustainable development.

5.2 Suggestion

In order to promote the opening of government data

in Heilongjiang Province, this study puts forward the

following two suggestions.

5.2.1 Optimize the Differentiated

Decision-Making Mechanism of the

Government

For Harbin, Qiqihar, Mudanjiang, Jiamusi, Daqing

and Jixi in Heilongjiang Province, the key factor of

government data openness lies in the integration and

optimal allocation of resources. For the

underdeveloped areas of Shuangyashan, Yichun,

Qitaihe, Hegang, Heihe and Suihua cities, the

attention of government leaders is crucial due to the

lack of support from resources and capacity.

Government data openness is a kind of government

innovation, and the government needs to base on the

actual situation, choose a suitable development path

and targeted measures according to its own resource

conditions and external development conditions, and

ultimately realize the balanced development of

governance capacity in Heilongjiang Province.

5.2.2 Improve the Supply Capacity of

Guarantee Factors

The performance of government data openness is

mainly promoted by rich financial support and

human support, so the construction of the

government's own ability to guarantee factors is

crucial. The government is not only concerned with

opening up capabilities, but also emphasizing the

use of capabilities. First of all, the government needs

to regulate the open data work, ensure the smooth

development of relevant work, and promote the

implementation of the open government data work

with the normative and mandatory force of the law.

Secondly, the government explores an

informatization promotion system suitable for the

city, integrates data resources and comprehensively

coordinates the data sharing and application of

multiple subjects by establishing a special big data

management organization. Finally, the government

needs to improve the data capabilities of department

personnel, improve the performance appraisal and

supervision mechanism of data openness, and

promote the digitalization process of local

governments in the above ways.

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