Toward a Sustainable Development of E-Commerce in EU: The Role of Education, Internet Infrastructure, Income, and Economic Freedom on E-Commerce Growth
Abstract
:1. Introduction
2. Literature Review and Hypotheses Development
2.1. E-Commerce and Education
2.2. E-Commerce and Infrastructure Autonomy
2.3. E-Commerce and the Intensity of Internet Usage
2.4. E-Commerce and Income
2.5. E-Commerce and Institutional Quality
3. Research Data
4. Methodology and Results
- Cointegration: If the error correction term is statistically significant, it suggests that a long-run relationship (cointegration) exists between the variables in the model.
- Long-run effects: These are the impacts of changes in independent variables on the dependent variables over a longer period. They are represented by the coefficients of the levels of the variables. A positive coefficient indicates that an increase in the independent variables leads to an increase in the dependent variables in the long run, while a negative coefficient suggests the opposite.
- Short-run effects: These are the immediate impacts of changes in independent variables on the dependent variables. They are represented by the coefficients of the lagged differences of the variables. A positive coefficient indicates that an increase in the independent variables leads to an increase in the dependent variables in the short run, while a negative coefficient suggests the opposite.
- Error correction term (ECT): The ECT measures the speed at which the dependent variable returns to equilibrium after a change in the independent variable. A negative and statistically significant ECT indicates that any short-run disequilibrium will converge back to the long-run equilibrium.
5. Discussions
- For the long-run relationship between the ECOM—Percentage of enterprises with e-commerce sales (10 persons employed or more) and TEA—The share of the population aged 25–34 who have successfully completed tertiary studies (ISCED 2011, levels 5–8), population from 25 to 34 years:
- For the long-run relationship between the ECOM—percentage of enterprises with e-commerce sales (10 persons employed or more) and IPIU—percentage of individuals who used a portable computer or a handheld device to access the internet away from home or work:
- For the long-run relationship between the ECOM—percentage of enterprises with e-commerce sales (10 persons employed or more) and GDPc—gross domestic product, volume indices of real expenditure per capita (PPS_EU27_2020 = 100):
- For the long-run relationship between the ECOM—percentage of enterprises with e-commerce sales (10 persons employed or more) and IUI—internet use by individuals (percentage of individuals who have ever used the internet):
- For the long-run relationship between the ECOM—percentage of enterprises with e-commerce sales (10 persons employed or more) and EFR—Economic Freedom Rankings, overall score (out of 10):
Limitations
6. Conclusions
- (a)
- Prioritizing significant resources for investment in ICT infrastructure, especially in emerging economies to facilitate the technological catching-up process;
- (b)
- Creating EU-funded programs and dedicated courses aimed to improve digital skills of vulnerable groups;
- (c)
- Allocating funding and technical support for the expansion of internet infrastructure in rural and underdeveloped areas to bridge the digital divide and ensure equal access to e-commerce opportunities;
- (d)
- Implementing regulations, commercial practices, and standards to protect consumers and businesses in the e-commerce sector, including measures to combat fraud, protect personal data, and ensure fair competition;
- (e)
- Collaborating with national stakeholders to develop targeted strategies and initiatives aimed at maximizing the economic benefits of e-commerce for all EU member states, fostering innovation, and promoting digital inclusion.
- (a)
- Implementing policies to promote low and stable inflation rates: The EU should focus on implementing sound monetary policies that create a conducive and predictable business environment, especially under the circumstances of high levels of public deficit and external debt in many EU countries.
- (b)
- Lower marginal tax rates: The EU should consider implementing tax policies that aim to reduce the tax burden on disadvantaged groups such as low-income earners and small businesses. Lowering marginal tax rates for these groups can help promote economic inclusivity and stimulate entrepreneurship and innovation.
- (c)
- Increase digitalization of public services: The EU should prioritize efforts to increase the digitalization of public services to enhance efficiency, accessibility, and transparency. By investing in digital infrastructure and technology, the EU can improve the delivery of public services, streamline administrative processes, and create new opportunities for innovation and growth in the digital economy.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Variables | Symbol | Data Source |
---|---|---|
Percentage of enterprises with e-commerce sales (10 persons employed or more). | ECOM | Eurostat, https://ec.europa.eu/eurostat/databrowser/view/isoc_ec_esels/default/table?lang=en |
The share of the population aged 25–34 who have successfully completed tertiary studies (ISCED 2011, levels 5–8), population from 25 to 34 years. | TEA | Eurostat, https://ec.europa.eu/eurostat/databrowser/view/sdg_04_20/default/table |
Percentage of individuals who used a portable computer or a handheld device to access the internet away from home or work. | IPIU | Eurostat, https://ec.europa.eu/eurostat/databrowser/view/isoc_ci_ifp_pu$defaultview/default/table |
Level of internet access: percentage of households. | LIA | Eurostat, https://ec.europa.eu/eurostat/databrowser/view/tin00134/default/table |
Percentage of individuals who used the internet daily. | IWUI | Eurostat, https://ec.europa.eu/eurostat/databrowser/product/view/isoc_ci_ifp_fu |
Internet use by individuals: Percentage of individuals who have ever used the internet. | IUI | Eurostat, https://ec.europa.eu/eurostat/databrowser/view/tin00028/default/table |
Gross domestic product, volume indices of real expenditure per capita (PPS_EU27_2020 = 100). | GDPc | Eurostat, https://ec.europa.eu/eurostat/databrowser/view/tec00114/default/table |
Economic Freedom Rankings, overall score (out of 10). | EFR | Fraser Institute, https://www.fraserinstitute.org/economic-freedom/dataset?geozone=world&page=dataset&filter=1&sort-field=country&sort-reversed=0&date-type=range&max-year=2021&min-year=2010 |
Dependent Variable: ECOM | |||
---|---|---|---|
Excluded | Chi-sq | df | Prob. |
TEA | 1.257259 | 1 | 0.2622 |
IPIU | 0.570617 | 1 | 0.4500 |
IWUI | 9.253724 | 1 | 0.0024 |
GDPc | 1.981208 | 1 | 0.1593 |
EFR | 1.449184 | 1 | 0.2287 |
LIA | 7.577376 | 1 | 0.0059 |
IUI | 1.266025 | 1 | 0.2605 |
All | 21.22833 | 7 | 0.0034 |
Correlation (t-Statistic) | ECOM | TEA | IPIU | IWUI | GDPC | EFR | LIA | IUI |
---|---|---|---|---|---|---|---|---|
ECOM | 1 | |||||||
TEA | 0.4005 | 1 | ||||||
(8.154) | ||||||||
IPIU | 0.6133 | 0.4892 | 1 | |||||
(11.252) | (8.129) | |||||||
IWUI | 0.5918 | 0.5060 | 0.8637 | 1 | ||||
(14.198) | (10.942) | (24.831) | ||||||
GDPC | 0.3307 | 0.4733 | 0.4913 | 0.5256 | 1 | |||
(6.279) | (9.640) | (8.175) | (11.068) | |||||
EFR | 0.3599 | 0.2516 | 0.4562 | 0.3621 | 0.4693 | 1 | ||
(6.911) | (4.664) | (7.428) | (6.960) | (9.129) | ||||
LIA | 0.5904 | 0.4177 | 0.8590 | 0.9395 | 0.5420 | 0.3708 | 1 | |
(13.022) | (7.869) | (24.312) | (48.909) | (11.041) | (6.525) | |||
IUI | 0.6251 | 0.4656 | 0.8466 | 0.9424 | 0.5497 | 0.4518 | 0.9523 | 1 |
(14.326) | (9.020) | (23.053) | (50.487) | (11.283) | (8.276) | (55.678) |
Variable | Coeff. | Std. Error | Prob. | Variable | Coeff. | Std. Error | Prob. |
---|---|---|---|---|---|---|---|
Exogenous variable: TEA Sample: 2011–2022 Included observations: 322 | Exogenous variable: IPIU Sample: 2013–2019 Included observations: 183 | ||||||
Long-Run Equation | Long Run Equation | ||||||
TEA | 0.19262 | 0.05007 | 0.0001 | IPIU | 0.36975 | 0.00531 | 0.0000 |
Short-Run Equation | Short Run Equation | ||||||
Cointegr. | −0.25218 | 0.07476 | 0.0009 | Cointegr. | −0.47159 | 0.11612 | 0.1021 |
d(TEA) | −0.12146 | 0.09274 | 0.1914 | d(IPIU) | 0.00677 | 0.10373 | 0.6714 |
intercept | 3.71011 | 0.97641 | 0.0002 | trend | −0.31587 | 0.12629 | 0.0136 |
Exogenous variable: IWUI Sample: 2011–2023 Included observations: 347 | Exogenous variable: GDPc Sample: 2012–2022 Included observations: 295 | ||||||
Long-Run Equation | Long Run Equation | ||||||
IWUI | 0.20564 | 0.01332 | 0.0000 | GDPc | 0.14439 | 0.00315 | 0.0000 |
Short-Run Equation | Short Run Equation | ||||||
Cointegr. | −0.37023 | 0.06798 | 0.0000 | Cointegr. | −0.48555 | 0.07270 | 0.0000 |
d(IWUI) | 0.01208 | 0.02868 | 0.6739 | d(GDPc) | −0.03236 | 0.09414 | 0.7313 |
intercept | 2.17017 | 0.46385 | 0.0000 | trend | 0.47483 | 0.07271 | 0.0000 |
Exogenous variable: LIA Sample: 2013–2023 Included observations: 290 | Exogenous variable: IUI Sample: 2013–2023 Included observations: 293 | ||||||
Long-Run Equation | Long Run Equation | ||||||
LIA | 0.19895 | 0.00382 | 0.0000 | IUI | 0.22273 | 0.00404 | 0.0000 |
Short-Run Equation | Short Run Equation | ||||||
Cointegr. | −0.19678 | 0.07916 | 0.0135 | Cointegr. | −0.45924 | 0.07239 | 0.0000 |
d(LIA) | 0.18122 | 0.09130 | 0.0482 | d(IUI) | −0.08151 | 0.12005 | 0.4978 |
trend | 0.24112 | 0.07871 | 0.0024 | ||||
Exogenous variable: EFR Sample: 2011–2023 Included observations: 295 | Symbols: ECOM—Enterprises with E-commerce sales TEA—Tertiary education IPIU—Percentage of individuals who used a portable computer or a handheld device to access the internet IWUI—Percentage of individuals who used the internet daily. LIA—Level of internet access: percentage of households GDPc—Gross domestic product per capita IUI—Internet use by individuals EFR—Economic Freedom Rankings | ||||||
Long-Run Equation | |||||||
EFR | 1.90530 | 0.07150 | 0.0000 | ||||
Short-Run Equation | |||||||
Cointegr. | −0.33850 | 0.05979 | 0.0000 | ||||
d(EFR) | −0.28077 | 1.93059 | 0.8845 | ||||
trend | 0.30440 | 0.06433 | 0.0000 |
Hypothesis | Short-Term Relation | Long-Term Relation | Coefficient of Cointegration | Probability |
---|---|---|---|---|
H1: TEA positively influences ECON | Not significant | ECOMt = 0.19262·TEA | −0.25218 | 0.0009 |
H2.1: IPIU positively influences ECON | Not significant | ECOMt = 0.36975·IPIU | −0.47159 | 0.1000 |
H2.2: LIA positively influences ECON | 0.181223 × d(LIA) | ECOMt = 0.198945·LIA | −0.196778 | 0.0001 |
H3.1: IWUI positively influences ECON | 0.063165 × d(IWUI) + 3.70 + 0.273839 × trend | ECOMt = 0.180074·IWUI | −0772396 | 0.0001 |
H3.2: IUI positively influences ECON | Not significant | ECOMt = 0.22273·IUI | −0.45924 | 0.0001 |
H4: GDPc positively influences ECON | Not significant | ECOMt = 0.14439·GDPc | −0.48855 | 0.0001 |
H5: EFR positively influences ECON | Not significant | ECOMt = 1.90530·EFR | −0.33850 | 0.0001 |
Variable | Coefficient | Standardized Coefficient | Elasticity at Means |
---|---|---|---|
TEA | 0.192624 | 0.236494 | 0.393723 |
IPIU | 0.369753 | 1.016403 | 1.130767 |
IWUI | 0.205641 | 0.411326 | 0.725394 |
GDPC | 0.144390 | 0.828002 | 0.739876 |
LIA | 0.198945 | 0.265359 | 0.822629 |
IUI | 0.222725 | 0.283840 | 0.931964 |
EFR | 1.905299 | 0.084265 | 0.774517 |
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Jula, N.M.; Staicu, G.I.; Moraru, L.C.; Bodislav, D.A. Toward a Sustainable Development of E-Commerce in EU: The Role of Education, Internet Infrastructure, Income, and Economic Freedom on E-Commerce Growth. Sustainability 2024, 16, 3809. https://doi.org/10.3390/su16093809
Jula NM, Staicu GI, Moraru LC, Bodislav DA. Toward a Sustainable Development of E-Commerce in EU: The Role of Education, Internet Infrastructure, Income, and Economic Freedom on E-Commerce Growth. Sustainability. 2024; 16(9):3809. https://doi.org/10.3390/su16093809
Chicago/Turabian StyleJula, Nicolae Marius, Gabriel Ilie Staicu, Liviu Cătălin Moraru, and Dumitru Alexandru Bodislav. 2024. "Toward a Sustainable Development of E-Commerce in EU: The Role of Education, Internet Infrastructure, Income, and Economic Freedom on E-Commerce Growth" Sustainability 16, no. 9: 3809. https://doi.org/10.3390/su16093809