Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China
Abstract
:1. Introduction
2. Literature Review and Research Hypotheses
2.1. Industrial Convergence
2.2. The Impact of ICTs on Tourism and Culture
2.3. Research Hypotheses
3. Materials and Methods
3.1. Study Design and Data
3.2. Model Specification
3.3. Variable Measure
3.4. Estimation Method
4. Results: Data Analysis and Findings
4.1. Static and Dynamic Panel Data Analysis of Direct Effects
4.2. Static and Dynamic Econometric Analysis of Moderated Effect
4.3. Econometric Analysis of Threshold Effect
5. Discussion of Main Findings, Conclusions, and Implications
5.1. Theoretical Contribution
5.2. Policy Implications
5.3. Limitations and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Culture Industry | Tourism Industry | ||
---|---|---|---|
Primary indicators | Secondary indicators | Primary indicators | Secondary indicators |
Industrial structure | Number of companies in the cultural market | Industrial structure | Number of travel agencies |
Number of art performance venues | Number of star-rated hotels | ||
Number of mass cultural institutions | Number of scenic spots above 4A rating | ||
Number of employees in the cultural industry | Number of employees in the tourism industry | ||
Industrial performance | Total operating income of cultural market | Industrial performance | Domestic tourism income |
Financial expenditures for cultural undertakings | International tourism income | ||
Number of museum visitors | Number of domestic tourists | ||
Number of audience for art group performances | Number of International tourists |
Variables | Definition and Measurement | Expected Signs | Mean | SD | Min | Max |
---|---|---|---|---|---|---|
CONVERG | the degree of cultural and tourism industries’ convergence | 0.249 | 0.092 | 0.061 | 0.594 | |
ICT | internet penetration rate | + | 0.351 | 0.199 | 0.025 | 0.78 |
MARKET | the number of private enterprises and self-employed persons divide by the number of all types of employment | + | 0.441 | 0.108 | 0.182 | 0.732 |
LABOUR | years of education per capita | + | 8.611 | 1.221 | 3.738 | 12.56 |
OPEN | export value divide by regional GDP | + | 0.161 | 0.186 | 0.011 | 0.93 |
GOVERN | fiscal expenditures divide by regional GDP | − | 0.244 | 0.187 | 0.079 | 1.379 |
DE | logarithm of household consumption expenditure per capita | 9.277 | 0.369 | 8.525 | 10.33 |
Variables | Model1 | Model2 | Model3 | Model4 | Model5 |
---|---|---|---|---|---|
Pooled OLS | Fixed Effects | Random Effects | DIFF GMM | SYS GMM | |
ICT | 0.291 *** | 0.105 *** | 0.111 *** | 0.048 *** | 0.024 *** |
(0.028) | (0.011) | (0.012) | (0.004) | (0.005) | |
MARKET | 0.154 *** | 0.078 *** | 0.081 *** | 0.069 *** | 0.094 *** |
(0.035) | (0.016) | (0.017) | (0.008) | (0.010) | |
LABOUR | −0.040 *** | 0.015 *** | 0.014 *** | −0.007 ** | 0.003 *** |
(0.005) | (0.003) | (0.003) | (0.004) | (0.001) | |
OPEN | 0.097 *** | −0.011 | −0.003 | 0.014 *** | −0.009 ** |
(0.015) | (0.013) | (0.013) | (0.004) | (0.004) | |
GOVERN | −0.396 *** | −0.090 *** | −0.102 *** | −0.093 *** | −0.116 *** |
(0.027) | (0.016) | (0.015) | (0.010) | (0.014) | |
L.CONVERG | 0.517 *** | 0.694 *** | |||
(0.032) | (0.030) | ||||
CONSTANT | 0.501 *** | 0.071 *** | 0.078 *** | 0.036 *** | 0.033 *** |
(0.043) | (0.024) | (0.026) | (0.005) | (0.004) | |
F statistic | 100.2 *** | 273.72 *** | |||
Wald statistic | 1314.95 *** | 33489.09 *** | 30446.37 *** | ||
R-squared | 0.576 | 0.761 | 0.761 | ||
F test | 200.86 *** | ||||
Hausman test | 28.43 *** | ||||
AR(1) | 0.007 *** | 0.007 *** | |||
AR(2) | 0.597 | 0.479 | |||
Sargan test | 1 | 1 |
Variables | Model6 | Model7 | Model8 | Model9 | Model10 |
---|---|---|---|---|---|
Pooled OLS | Fixed Effects | DIFF GMM | SYS GMM | TRM FE | |
ICT | 0.295 *** | 0.114 *** | 0.073 *** | 0.047 *** | |
(0.027) | (0.012) | (0.006) | (0.007) | ||
MARKET | 0.148 *** | 0.073 *** | 0.042 *** | 0.069 *** | 0.069 *** |
(0.034) | (0.016) | (0.012) | (0.012) | (0.016) | |
LABOUR | −0.039 *** | 0.014 *** | 0.006 *** | 0.002 ** | 0.013 *** |
(0.004) | (0.003) | (0.001) | (0.001) | (0.003) | |
OPEN | 0.098 *** | −0.002 | 0.014 *** | −0.007 ** | 0.031 ** |
(0.016) | (0.013) | (0.004) | (0.004) | (0.014) | |
GOVERN | −0.390 *** | −0.092 *** | −0.086 *** | −0.125 *** | −0.089 *** |
(0.022) | (0.016) | (0.010) | (0.022) | (0.015) | |
L.CONVERG | 0.478 *** | 0.664 *** | |||
(0.036) | (0.026) | ||||
ICT×MARKET | 0.275 * | 0.103 ** | 0.189 *** | 0.149 *** | |
(0.147) | (0.045) | (0.020) | (0.018) | ||
ICT· | 0.112 *** | ||||
I(DE ≤ 9.822) | (0.011) | ||||
ICT· | 0.149 *** | ||||
I(DE > 9.822) | (0.013) | ||||
CONSTANT | 0.493 *** | 0.078 *** | 0.052 *** | 0.057 *** | 0.081 *** |
(0.041) | (0.024) | (0.007) | (0.008) | (0.023) | |
F statistic | 100.2 *** | 231.23 *** | 252.09 *** | ||
Wald statistic | 17022.74 *** | 21200.19 *** | |||
R-squared | 0.579 | 0.764 | 0.779 | ||
F test | 201.38 *** | ||||
Hausman test | 27.26 *** | ||||
AR(1) | 0.008 *** | 0.007 *** | |||
AR(2) | 0.677 | 0.494 | |||
Sargan test | 1 | 1 |
Threshold Model | Critical Value | ||||
---|---|---|---|---|---|
F-Statistics | p-Value | 1% | 5% | 10% | |
Single-threshold | 36.92 | 0.023 | 43.263 | 28.905 | 25.058 |
Double-threshold | 12.49 | 0.303 | 24.795 | 20.235 | 17.308 |
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Zhou, C.; Sotiriadis, M. Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China. Sustainability 2021, 13, 11769. https://doi.org/10.3390/su132111769
Zhou C, Sotiriadis M. Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China. Sustainability. 2021; 13(21):11769. https://doi.org/10.3390/su132111769
Chicago/Turabian StyleZhou, Chunbo, and Marios Sotiriadis. 2021. "Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China" Sustainability 13, no. 21: 11769. https://doi.org/10.3390/su132111769