Journal of Resources and Ecology ›› 2022, Vol. 13 ›› Issue (6): 1037-1047.DOI: 10.5814/j.issn.1674-764x.2022.06.009
• Tourism Resource and Ecotourism • Previous Articles Next Articles
LIU Jia1,2,*(), LI Jing1, AN Keke1
Received:
2021-10-15
Accepted:
2022-05-30
Online:
2022-11-30
Published:
2022-10-12
Contact:
LIU Jia
Supported by:
LIU Jia, LI Jing, AN Keke. The Effects of Tourism Industry Agglomeration on Tourism Environmental Carrying Capacity: Evidence from a Panel Threshold Model[J]. Journal of Resources and Ecology, 2022, 13(6): 1037-1047.
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URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764x.2022.06.009
Target | Subsystems | Indicators | Indicator interpretations |
---|---|---|---|
TECC | Driver (D) | GDP (D1) | Represents the driving force of economic aggregate on TECC |
Per capita disposable income of households (D2) | Represents the driving force of economic development level on TECC | ||
Ratio of the number of tourists to the number of residents (D3) | Represents the driving force of tourist crowding on TECC | ||
Turnover of passenger traffic (D4) | Represents the driving force of tourist turnover on TECC | ||
Number of tourists (D5) | Represents the driving force of tourist stay on TECC | ||
Pressure (P) | Energy consumption per unit of GDP (P1) | Represents the pressure of energy consumption on TECC | |
Electricity consumption per unit of GDP (P2) | Represents the pressure of electricity consumption on TECC | ||
Water consumption per unit of GDP (P3) | Represents the pressure of water consumption on TECC | ||
State (S) | Number of A-grade tourist attractions (S1) | Represents the number of tourism resources | |
Number of tourist attractions above AAAA-grade (S2) | Represents the quality of tourism resources | ||
Number of air quality standard days (S3) | Represents the quality of air | ||
Impact (I) | Total tourism revenue (I1) | Represents the impact of TECC on tourism economy | |
Tourism earnings as percentage of GDP (I2) | Represents the impact of TECC on industrial structure | ||
Tertiary industry product as percentage of GDP (I3) | Represents the impact of TECC on economic structures | ||
Number of tourism professionals (I4) | Represents the impact of TECC on regional employment | ||
Per capita consumption expenditure of households (I5) | Represents the impact of TECC on residents' consumption expenditure | ||
Response (R) | Number of cultural and art institutions (R1) | Represents the response of infrastructure to TECC | |
Ratio of waste water centralized treated of sewage work (R2) | Represents the response of water quality optimization to TECC | ||
Ratio of consumption on wastes treated (R3) | Represents the response of waste utilization to TECC | ||
Green covered area as percentage of built-up area (R4) | Represents the response of air quality optimization to TECC | ||
Investment in anti-pollution projects as percentage of GDP (R5) | Represents the response of government governance to TECC | ||
Actual utilization of foreign capital as percentage of GDP (R6) | Represents the response of regional openness to TECC | ||
Intramural expenditure on R&D as percentage of GDP (R7) | Represents the response of scientific research investment to TECC | ||
Number of taxis (R8) | Represents the response of infrastructure to TECC | ||
Number of hospitals (R9) | Represents the response of public services to TECC | ||
Per capita years of school attainment (R10) | Represents the response of tourism residents to TECC | ||
Number of students enrolled in regular institutions of higher education (R11) | Represents the response of practitioner quality to TECC |
Table 1 Evaluation index system of TECC
Target | Subsystems | Indicators | Indicator interpretations |
---|---|---|---|
TECC | Driver (D) | GDP (D1) | Represents the driving force of economic aggregate on TECC |
Per capita disposable income of households (D2) | Represents the driving force of economic development level on TECC | ||
Ratio of the number of tourists to the number of residents (D3) | Represents the driving force of tourist crowding on TECC | ||
Turnover of passenger traffic (D4) | Represents the driving force of tourist turnover on TECC | ||
Number of tourists (D5) | Represents the driving force of tourist stay on TECC | ||
Pressure (P) | Energy consumption per unit of GDP (P1) | Represents the pressure of energy consumption on TECC | |
Electricity consumption per unit of GDP (P2) | Represents the pressure of electricity consumption on TECC | ||
Water consumption per unit of GDP (P3) | Represents the pressure of water consumption on TECC | ||
State (S) | Number of A-grade tourist attractions (S1) | Represents the number of tourism resources | |
Number of tourist attractions above AAAA-grade (S2) | Represents the quality of tourism resources | ||
Number of air quality standard days (S3) | Represents the quality of air | ||
Impact (I) | Total tourism revenue (I1) | Represents the impact of TECC on tourism economy | |
Tourism earnings as percentage of GDP (I2) | Represents the impact of TECC on industrial structure | ||
Tertiary industry product as percentage of GDP (I3) | Represents the impact of TECC on economic structures | ||
Number of tourism professionals (I4) | Represents the impact of TECC on regional employment | ||
Per capita consumption expenditure of households (I5) | Represents the impact of TECC on residents' consumption expenditure | ||
Response (R) | Number of cultural and art institutions (R1) | Represents the response of infrastructure to TECC | |
Ratio of waste water centralized treated of sewage work (R2) | Represents the response of water quality optimization to TECC | ||
Ratio of consumption on wastes treated (R3) | Represents the response of waste utilization to TECC | ||
Green covered area as percentage of built-up area (R4) | Represents the response of air quality optimization to TECC | ||
Investment in anti-pollution projects as percentage of GDP (R5) | Represents the response of government governance to TECC | ||
Actual utilization of foreign capital as percentage of GDP (R6) | Represents the response of regional openness to TECC | ||
Intramural expenditure on R&D as percentage of GDP (R7) | Represents the response of scientific research investment to TECC | ||
Number of taxis (R8) | Represents the response of infrastructure to TECC | ||
Number of hospitals (R9) | Represents the response of public services to TECC | ||
Per capita years of school attainment (R10) | Represents the response of tourism residents to TECC | ||
Number of students enrolled in regular institutions of higher education (R11) | Represents the response of practitioner quality to TECC |
Variables | Attributes | Measurements |
---|---|---|
Tourism environmental carrying capacity (TECC) | Dependent variable | Entropy weight method |
Tourism industry agglomeration (TIA) | Independent variable | Location quotient |
Economic development level (ECO) | Control variable | Per capita disposable income |
Tourist density (DEN) | Control variable | Ratio of the number of tourists to the number of residents |
Tourism ecological efficiency (EFF) | Control variable | Super-efficiency SBM model |
Technological progress level (TEC) | Control variable | Science and technology expenditure/local government financial expenditure |
Environmental regulation strength (ERS) | Control variable | Investment in anti-pollution projects as percentage of GDP |
Table 2 Definitions of variables
Variables | Attributes | Measurements |
---|---|---|
Tourism environmental carrying capacity (TECC) | Dependent variable | Entropy weight method |
Tourism industry agglomeration (TIA) | Independent variable | Location quotient |
Economic development level (ECO) | Control variable | Per capita disposable income |
Tourist density (DEN) | Control variable | Ratio of the number of tourists to the number of residents |
Tourism ecological efficiency (EFF) | Control variable | Super-efficiency SBM model |
Technological progress level (TEC) | Control variable | Science and technology expenditure/local government financial expenditure |
Environmental regulation strength (ERS) | Control variable | Investment in anti-pollution projects as percentage of GDP |
Variables | TIA | ECO | DEN | EFF | TEC | ERS |
---|---|---|---|---|---|---|
TIA | 1.0000 | |||||
ECO | 0.2431 | 1.0000 | ||||
DEN | 0.0029 | 0.0140 | 1.0000 | |||
EFF | 0.5018 | 0.6258 | -0.0095 | 1.0000 | ||
TEC | 0.0288 | 0.6843 | 0.0225 | 0.3638 | 1.0000 | |
ERS | 0.1151 | 0.0737 | 0.0024 | 0.2215 | 0.0099 | 1.0000 |
Table 3 Matrix of correlations
Variables | TIA | ECO | DEN | EFF | TEC | ERS |
---|---|---|---|---|---|---|
TIA | 1.0000 | |||||
ECO | 0.2431 | 1.0000 | ||||
DEN | 0.0029 | 0.0140 | 1.0000 | |||
EFF | 0.5018 | 0.6258 | -0.0095 | 1.0000 | ||
TEC | 0.0288 | 0.6843 | 0.0225 | 0.3638 | 1.0000 | |
ERS | 0.1151 | 0.0737 | 0.0024 | 0.2215 | 0.0099 | 1.0000 |
Type of threshold test | 95% confidence interval | F-statistic | P-value | Threshold estimate | Critical value | ||
---|---|---|---|---|---|---|---|
1% | 5% | 10% | |||||
Single threshold model | [1.194, 1.217] | 19.832** | 0.022 | 1.217 | 21.426 | 17.807 | 15.074 |
Double threshold model | [0.974, 2.460]; [0.931, 1.064] | 57.151*** | 0.000 | 0.991; 1.626 | -12.300 | -18.261 | -21.545 |
Table 4 Test of the threshold effect
Type of threshold test | 95% confidence interval | F-statistic | P-value | Threshold estimate | Critical value | ||
---|---|---|---|---|---|---|---|
1% | 5% | 10% | |||||
Single threshold model | [1.194, 1.217] | 19.832** | 0.022 | 1.217 | 21.426 | 17.807 | 15.074 |
Double threshold model | [0.974, 2.460]; [0.931, 1.064] | 57.151*** | 0.000 | 0.991; 1.626 | -12.300 | -18.261 | -21.545 |
Year | Across the first threshold 0.991 | First threshold crossing rate (%) | Across the second threshold 1.626 | Second threshold crossing rate (%) |
---|---|---|---|---|
2000 | 5 | 19.23 | 1 | 3.85 |
2001 | 4 | 15.39 | 0 | 0 |
2002 | 4 | 15.39 | 0 | 0 |
2003 | 5 | 19.23 | 1 | 3.85 |
2004 | 5 | 19.23 | 1 | 3.85 |
2005 | 7 | 26.92 | 1 | 3.85 |
2006 | 9 | 34.62 | 1 | 3.85 |
2007 | 10 | 38.46 | 2 | 7.69 |
2008 | 8 | 30.77 | 2 | 7.69 |
2009 | 10 | 38.46 | 2 | 7.69 |
2010 | 10 | 38.46 | 2 | 7.69 |
2011 | 9 | 34.62 | 2 | 7.69 |
2012 | 11 | 42.31 | 2 | 7.69 |
2013 | 15 | 57.69 | 2 | 7.69 |
2014 | 15 | 57.69 | 3 | 11.54 |
2015 | 15 | 57.69 | 4 | 15.39 |
2016 | 15 | 57.69 | 4 | 15.39 |
2017 | 14 | 53.85 | 5 | 19.23 |
2018 | 16 | 61.54 | 5 | 19.23 |
Table 5 Numbers and proportions of the 26 sample cities in the two threshold value intervals
Year | Across the first threshold 0.991 | First threshold crossing rate (%) | Across the second threshold 1.626 | Second threshold crossing rate (%) |
---|---|---|---|---|
2000 | 5 | 19.23 | 1 | 3.85 |
2001 | 4 | 15.39 | 0 | 0 |
2002 | 4 | 15.39 | 0 | 0 |
2003 | 5 | 19.23 | 1 | 3.85 |
2004 | 5 | 19.23 | 1 | 3.85 |
2005 | 7 | 26.92 | 1 | 3.85 |
2006 | 9 | 34.62 | 1 | 3.85 |
2007 | 10 | 38.46 | 2 | 7.69 |
2008 | 8 | 30.77 | 2 | 7.69 |
2009 | 10 | 38.46 | 2 | 7.69 |
2010 | 10 | 38.46 | 2 | 7.69 |
2011 | 9 | 34.62 | 2 | 7.69 |
2012 | 11 | 42.31 | 2 | 7.69 |
2013 | 15 | 57.69 | 2 | 7.69 |
2014 | 15 | 57.69 | 3 | 11.54 |
2015 | 15 | 57.69 | 4 | 15.39 |
2016 | 15 | 57.69 | 4 | 15.39 |
2017 | 14 | 53.85 | 5 | 19.23 |
2018 | 16 | 61.54 | 5 | 19.23 |
Variable | Regression coefficient | T-statistic | P value |
---|---|---|---|
ECO | 0.001* | 1.80 | 0.072 |
DEN | 0.001*** | 6.73 | 0.000 |
ERS | 1.373*** | 4.84 | 0.000 |
TEC | 0.466*** | 3.75 | 0.000 |
EFF | 0.024** | 2.10 | 0.036 |
TIA≤0.991 | 0.028*** | 2.58 | 0.010 |
0.991<TIA≤1.626 | 0.053*** | 6.85 | 0.000 |
TIA>1.626 | 0.023*** | 5.72 | 0.000 |
Table 6 Test results of the double threshold of TIA
Variable | Regression coefficient | T-statistic | P value |
---|---|---|---|
ECO | 0.001* | 1.80 | 0.072 |
DEN | 0.001*** | 6.73 | 0.000 |
ERS | 1.373*** | 4.84 | 0.000 |
TEC | 0.466*** | 3.75 | 0.000 |
EFF | 0.024** | 2.10 | 0.036 |
TIA≤0.991 | 0.028*** | 2.58 | 0.010 |
0.991<TIA≤1.626 | 0.053*** | 6.85 | 0.000 |
TIA>1.626 | 0.023*** | 5.72 | 0.000 |
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