How Does Information and Communication Technology Affect Geothermal Energy Sustainability?

Abstract

There are many advantages of geothermal energy, as an environmentally friendly resource, with some other problems to be addressed before the full potential of this sustainable and renewable resource, which is natural, could be harnessed. This research will aim to examine what effect ICT, that is, information and communication technology factors with sustainability in the economy, has on geothermal energy output among the considered 27 EU nations within the time frame 1990 to 2021. The novelty of this research is the ability to clarify the role of ICT toward geothermal power sustainability in the EU27 region. As well as the magnitude of effects of ICT on the geothermal power sustainability in EU13 developing countries and EU14 developed countries using the ARDL estimator. Autoregressive distributed lag (ARDL) was adopted, and the findings show that a significant increase in the geothermal energy industry sustainability can occur in EU14 emerged economies using ICT factors than among the 13 emerging economies. Among additional factors, human capital, economic sustainability, and institutional quality contribute more positively to geothermal energy sustainability in EU14 emerging economies than in EU13 emerging economies. Similarly, further results show that a remarkable decrease in carbon dioxide emissions can occur in EU13 emerging economies using geothermal energy output than in EU14 emerged economies. All these results outputs are an indication that geothermal power sustainability among the European Union countries could be remarkably boosted by increasing the level of ICT determinants to attain the 2030 energy union goals. This study recommends that the considered European countries should prioritize the good functionality of ICT indicators in attaining societal objectives and that of the environment as well.

1. Introduction

1.1. Background of Study

In no way is energy derived from fossil fuels sustainable, this is not only due to how scarce the resources are but also a result of its damaging effect on the climate. It was therefore a unanimous decision of the European Council that the EU zones need to significantly decarbonize the energy system in individual countries come the year 2050 [1]. To make the broadest source of energy choice available for citizens in Europe, several renewable energy and ICT facilities need to be available. This does not deviate from the target of further reduction up to 80–95% by 2050 [1]. This means that research in Energy is very broad, it encompasses varieties of technologies and spans different fields of endeavor, including geothermal energy [1]. Presently, geothermal power stations in Europe are up to 130, this is an increase of 5% to the statistics in 2019 [1]. In the next 5 to 8 years, the percentage could be in double fold. Studies like [2] make detailed insights into geothermal energy in Europe, by examining technological status, stage of development, policy factors, and market conditions. Research outcomes state that even if geothermal energy’s present market share in Europe is 0.2%, it still has a huge usage potential in Europe [2]. There are presently three forms of geothermal usage in Europe: ground source heat pumps (GSHP) with a capacity of 14.9 gigawatts (GW), 3 GW of which is a direct use, and geothermal power plants, which have an EU installed capacity of 0.95 GW [2]. The application of new technological breakthroughs, such as engineered geothermal systems (EGS), is vital for expanding the resource capacity of geothermal energy sustainable development [2]. What this technology does is that it fires up deep resources that are very hot, which could not have been possibly harnessed due to water shortage and fragmentations in rocks. This EGS technology could have up to 1200 GW to 12,000 GW installed capacity worldwide [3]. Come the year 2050, the estimated EU economic power generation prospect is around 2570 terawatt-hours (TWh) [3]. To juxtapose, geothermal global installed capacity stands at 60 GW [3], see Figure A1 in Appendix F.

However, with the aid of EGS technology, sustainable development capacity in the EU could be higher. Although the power sustainable development potential with the EGS technology in the EU is very high, the level of public awareness of geothermal is finite compared to other renewable energy-based technologies [3]. The EGS technology depends on rock stimulation in controlled conditions, which triggers quivering. This means that the modus operandi that promotes maintenance and safety in using EGS technology has to be designed and assessed in different geological situations [4]. With the costly nature of this testing, there could be a patterning of the reactions of the different sets of reservoirs [4]. One of the key issues with geothermal has to do with how to manage the hyper heat and temperature levels [4]. This signals that there are a lot of issues in the wells, and therefore to manage the wells, heat or temperature in wells needs to be stemmed down, in this manner, the good casing might be damaged as a result of expansion [4]. Concerning cost, geothermal has a lower cost of electricity in comparison to other forms of renewable energy [5]. Nevertheless, the low success rate at the commencement stage of geothermal installations often scares investors away from investing in geothermal, and this limits the rate of acceptability and technological advancement in the sector [5]. The cost of drilling could go far above 50% of the total cost and is the most pressing factor that dictates the level of investment in geothermal [5]. If the cost could be cut down, it will reduce the risk level investors have to face at the commencement stage of geothermal installation [5].

Geothermal being location-specific is another environmental issue with it. It must be situated in an area with good accessibility to energy, which means some areas are not energy-accessible [6]. Furthermore, even though geothermal is not a source of greenhouse gas emissions, some gases are stored underground that get released when digging into the earth [7]. Geothermal could trigger earthquakes because the earth’s structure is altered in the course of digging [8]. Investment in geothermal comes with a huge capital outlay, which makes it uncompetitive, it costs around USD 2–7 million to have a 1-megawatt capacity geothermal plant [5]. Furthermore, to maintain the sustainability of geothermal energy, fluid needs to be pumped back into the underground reservoirs faster than it is depleted. Nevertheless, geothermal power plants can have an impact on both water quality and consumption [9]. There are high sulfur and salt contents with other minerals in the hot water pumped out of underground reservoirs [9]. From another angle, geothermal also comes with social problems, this involves disagreement over land rights, Indigenous people could have their rights trampled upon, they could lose their means of sustenance, uncontrollable population sustainability, noise and odor pollution, road traffic disruption, and poor dialogue among stakeholders’ levels and disagreement over opportunities about employment and economic returns [10,11].

The main research questions were: (1) How do ICT factors improve the sustainability of the geothermal power industry in the EU region during the period between 1990 and 2021? (2) Which EU members are more vulnerable to the effects of geothermal energy industry sustainability caused by ICT factors? (3) In what way are ICT indicators contributing to geothermal sustainability among the 28 European nations? As a result of the important need to have an energy supply that is renewable and sustainable, coupled with the climate change conditions, it becomes paramount to understand the remarkable relationship between geothermal and ICT measures at the regional and sub-regional levels in the EU. This research has the following objectives: (1) To expatiate the influence of ICT on geothermal power sustainability in the EU region during the period between 1990 and 2021. (2) To provide a comprehensive review of the geothermal energy industry impacts of ICT determinants between emerging countries and emerged nations within the EU state within the time frame 1990 and 2021.

This study provides an immense contribution to existing literature, this study promotes common ICT pointers to foster development that is sustainable among the EU countries and shows a clear relationship among the variables of this research. This analysis could assist the government of the EU nations in combating environmental pollution and changes in climatic conditions, by understanding the role of ICT in the geothermal energy sector. The methodology adopted in this research is particular to the EU region. Furthermore, the green energy source is the geothermal energy industry; this research operationalizes the geothermal power industry and ICT measures to ascertain if pre-design for a sustainable standard criterion is met to ensure further engagement of geothermal in the energy blend. This research put into consideration ICT pointers in the EU, by adopting controller measures and makes the following categorization of them: quality of institutional, human capital, sustainability of the economy, and carbon dioxide. If the arrays of socio-environmental problems of economic-related are looked into, the identified ICT pointers are assumed to influence the sustainability of geothermal among the 14 and 13 European nations. In this scope, this research will establish the link between these ICT pointers and the sustainability of the geothermal energy sector. Furthermore, the analysis of likely nexus and pinpointing ICT measures in this study can take records of what influence will improve technologies have on sustainable development. Which will help in fostering sustainable development and cutting down policy costs in the geothermal power sector among the 27 EU countries.

Several studies have examined the nexus between geothermal and technology, but just a few studies have examined the connection between ICT and geothermal energy sustainability. There was no agreement in all these studies so this current research will contribute to the body of knowledge by adopting ICT factors and referencing the impacts on geothermal industry sustainability in the EU region, emerged EU countries, and emerging EU countries in the considered time period of 1990 to 2021. About what the author knows, this research is one of the forefront studies that concurrently examine the impacts of ICT pointers on the sustainability of the geothermal energy sector by adopting the Auto-Regressive Distributed Lag (ARDL) regression. Furthermore, by emphasizing the sustainability hypothesis, this paper examines the nexus between other social-economic determinatives and environmental factors. In this current study, we have executed several boosts to our model and this is to ensure adequate coverage of the geothermal energy sector at the regional and sub-regional levels. Focusing on the EU, application-specific estimates relating to the economic prospect of geothermal in the long term have been crucially updated in line with temperature data of subsurface type, coined from the model developed by [12,13]. It is a remarkable adjustment to the model since the former version of the model has a rudimentary outlook on geothermal prospects. In three key ways, the findings of this study will make a significant contribution to the existing body of knowledge: in the area of geothermal prospects and their environmental applications, their geographical focus. The outline of the article is organized as follows: Section 1.2 and Section 1.3 provide a critical review of the existing literature. Section 2 presents the research methodology, including model specification and the estimation strategy. The empirical results and discussion are reported in Section 3. Finally, Section 4 concludes the article and elaborates on the implications.

1.2. Empirical Review

A comprehensive overview of potential environmental effects during the life cycle of geothermal power plants is presented using widely scattered available information from diverse literature sources such as [14,15,16,17,18]. While [19] research paper was prepared with the objective to provide an overview of the geothermal energy extraction from an abandoned oil well, it refers to various technical challenges and economic considerations of geothermal energy and regulation on the utilization of abandoned oil wells. Likewise, [4] researched the potential of geothermal energy sustainable development in Turkey using Monte Carlo simulation and point out that the contribution of geothermal energy in mixed energy sustainable development is significant. On the other hand, [20] researched the application of geothermal-based hybrid energy systems toward eco-friendly energy approaches, implying that geothermal does not suffer the intermittence of other renewable sources, and its extraction efficiency is fairly modest as compared to other sources. While [21] quantified the level to which geothermal could have expanded by the year 2050, the study made it known that this could be achieved through technological breakthroughs and policies relating to climate. The study further indicates that by the middle of the century geothermal energy plants could contribute approximately 4–7% to European electricity generation. While [22] researched geothermal energy technology and direct heat applications in five power plants, referring to the observation that cascade applications increase the thermal efficiency of the system and maximize the geo-fluid usage. Geothermal energy is important for sustainable development, yet multidimensional challenges exist for policymakers in transformations to sustainable energy systems [23] explored the cultural factors of sustainable energy development through a case study of geothermal energy in Iceland and Japan, indicating that culture influences the approach to geothermal energy development in both countries. Once it is a renewable source of energy, it will have some degree of influence on the environment, any type of renewable energy sustainable development will have some impact on the environment, the magnitude depends on the type of technology deployed [24]. Applications relating to geothermal, power sustainable development, and direct use, do influence air pollution. This must be pointed out, measured, and possibly curbed, to a minimal level to prompt compliance with environmental regulations [24].

Under the governance regulation, many studies such as; [25,26,27] developed integrated national energy and climate plans to cover the dimensions of the Energy Union related to decarburization, energy security, energy efficiency, internal energy market, research, innovation, and competitiveness. For example, [10], investigated how the residents of Korea perceive geothermal plants after the 2017 Pohang earthquake by applying the social representation theory, suggesting that Pohang residents had a significantly negative opinion of geothermal plants regardless of safety, climate change mitigation, and economic factors. Likewise, [28] searched the resource and policy-driven assessment of the geothermal energy potential across the islands of St. Vincent and the Grenadines, indicating that several policy approaches (such as; motivating partnership between the public and the private sector, high information certainty level, processes in regulations, and institutional efficiency) are pointed out as potent ways of fostering geothermal sustainability and building on the resource to foster demands for sustainable energy in the islands. In the same manner, [29] explored the configurations at the institutional level, ascertainable by examining the impact that energy in socio-material forms, will have on energy infrastructure and its administration, referring to norms and cultural peculiarities of the EU zones being considered to have impacted and regulated the influence of national regulatory schemes on geothermal energy implementation in Italy.

Trained human factors and knowledge can play an important role in conceptual models in the field of the sustainable development of the geothermal energy industry [30,31,32]. In this sense, [33] investigated the impact of human performance on the development of geothermal energy systems, claiming that the performance of a geothermal power system is related to both the natural physical parameters and human-controlled factors. In the same way, [34] searched the potential of hybrid geothermal power integration with a desalination system, suggesting that low human capital cost could minimize electricity sustainable development cost and boost value. Similarly, [34,35] explored the geothermal performance of the multiple-doublet system in Hot Sedimentary Aquifers, indicating that human input parameters in a multiple-doublet system significantly influence the fluid flow and heat transfer processes to achieve efficient geothermal power sustainable development.

Geothermal energy is extracted from the earth without burning fossil fuels, and geothermal fields produce practically no emissions. This is consistent with previous research such as; [7,27,36]. For example, [37] investigated the geothermal technologies development and their role in reducing greenhouse gas (GHG) emissions in the USA, suggesting that existing geothermal heat and power technologies and emerging advanced closed-loop applications could deliver substantial cost-efficient base load energy, leading to long-term decarburization. Likewise, [38] researched the status and prospects of geothermal energy status in Middle-Eastern countries to reduce carbon dioxide (CO₂) emissions, stating that harnessing geothermal energy fully is reckoned as one of the routes to meeting their energy demands and curbing CO₂ release to the atmosphere to mitigate air pollution. In the same way, [39] explored geothermal energy reserve and potential in Saudi Arabia, points that geothermal power has the potential to contribute to fulfilling the country’s demands for being a part of an effective plan for reducing CO₂ emissions. Likewise, [39,40] searched the impact of emission reduction policy on other parts of the ecological footprint—energy and land—indicating that many low-carbon energy sustainable development methods require large areas of land, and this exacerbates current land-use competition, particularly concerning agricultural land.

On the other hand, previous research by [17,40] examined what relationship exists between geothermal energy sources and economic sustainability among identified South Asian countries, suggesting that geothermal power has more effects and influences on economic sustainability as compared to the other individual sources of renewable energy [41]. In the same manner, [42] referred that to attain a pathway that is sustainable for development, an assessment of technical and economic limitations must be looked into, in the context of environmental management, social and legal difficulties that emanate from the execution of geothermal projects. Likewise, [43] researched the economic feasibility of the geothermal energy system in Indonesia, and stated that despite all the cons caused by geothermal energy, the government still looks forward to turning Indonesia into the world’s largest geothermal electricity producer over the next 10 years.

1.3. Literature Gap

The overview of the literature shows a brief discussion of the relationships between geothermal energy usage, ICT, and economic sustainability, but there are no conclusions. The validity of some of these studies in terms of their estimated coefficients is questioned, and in terms of their elasticity, they do not rely on the appropriate quantitative frameworks when selecting their testing methods. For instance, most of the studies do not consider diagnostic statistics and specification tests, which are vital to showing objectivity and consistency in regression analysis.

The gaps between this study and others are: First, concurrently, the long-run effects of ICT factors on geothermal energy sustainability are estimated in EU emerging countries and EU emerged countries during the period between 1990 and 2021. Additionally, using the sustainability hypothesis, it examines the nexus between socioeconomic factors and geothermal energy consumption, so this investigation cannot be said to have been carried out in the EU between the time limit of 1990 and 2021. Moreover, results from diagnostic and specification tests are considered in this, which were hardly found to be used in previous studies. Lastly, recent panel data approaches permit investigation into unobserved parameters that are heterogeneous and cross-sectional dependent.

2. Methodology and Material

Extant literature employed the model of Impact, Population, Affluence, and Technology (IPAT) in their research to investigate the influence of technology on renewable energy [12]. It is a simple model that could be used to explain factors affecting renewable energy. So, this research adopts the model to examine the influence of ICT and national output on renewable energy usage. The “I” in the IPAT model stands for impact on renewable energy, P for Population, A is for affluence, and T is for technology. The model is expressed in Equation (1) below

I = f (P, A, T)

(1)

This study uses geothermal energy consumption to represent its influence on environmental protection. After all, it is one of the biggest parts of renewable power resources [3], and ICT represents technology [44]. Affluence is representing the gross domestic product (GDP), institutional quality is a proxy for governance, and human capital input represents population development. The first equation can be extended to equation two. This research employs panel data analysis. Eurostat and the World Bank are the sources of data retrieved. Several tests were carried out, such as the panel unit root, co-integration that is panel-based, and panel estimations, which are heterogeneous and dynamic and they are the pooled mean group (PMG) estimator, the mean group estimator (MG), and dynamic fixed-effect estimator (DFE). Specification of the model in Equation (2) is expressed below:

lnGT_it = β₀ + β₁ lnICT_it + β₂ lnEG_it + β₃ lnHC_it + β₄ lnIQ_it + β₅ lnCO_2it + ε_it

(2)

where GT represents geothermal energy and indicates inland consumption (Terajoule), EG represents the gross domestic product with respective measures of GDP sustainability annual %, HC represents several human capital inputs, IQ is the institutional quality with respective measures of worldwide governance indicator, CO₂ as the level of the carbon dioxide emission measured in metric tons per capita, and ICT is the information and communication technology input represented for innovation application trademark. Every one of the variables is changed into log form (see

Table 1. Summary of Variables.

Variable	Abbreviated	Data Source	Statistics/Expected Sign	Unit
Geothermal Output	GT	Eurostat	Dependent Variable	Terajoule
Information and Communication Technology	ICT	World Bank Datasets	Significant/+	Innovation application trademark (Direct resident %)
Human Capital	HC	Eurostat	Significant/+	Thousand
Institutional Quality	IQ	WBD	Significant/+	Worldwide Governance Indicator (%)
Carbon Dioxide	CO2	Eurostat	Significant/−	Metric tons per capita
Economic Sustainability	GDP	Eurostat	Significant/+	GDP sustainability (annual %)

). The criterion model in the equation was found in studies such as [18,45,46,47].

2.1. Unit Root Testing of Panel Type

This testing method was carried out for all variables in this study. It is to prevent false regression when using panel data. The key rationale behind using the panel unit root test is to address the problem of low power when Augmented Dickey–Fuller (ADF) is adopted. [48,49] asserted that how reliable an estimation is can be queried since there is low power with the unit root test and when the observation count in time series is below 50, such as in [48,49]. Adopting a unit root test of panel type can address this challenge since it has more power and there is asymptotic distribution, which is standard, so the test evidence can be relied upon. Furthermore, there is a higher level of efficiency with the unit root test than with the unit root test of a time series nature [50,51]. These methods have been widely used in previous studies on energy consumption [52,53,54,55,56,57,58].

2.2. Estimation of Panel Type

The pooled mean group estimator can yield estimation in the long run as well as intercept, adjustment speed, and making error variance heterogeneous. The slope coefficient, in the long run, is confined to being homogenous. This approach is efficient and reliable in capturing the existence of the long-run nexus. Despite this, the error correction term coefficient still has to be lower than 2 and negative. Other than that, the vital assumption is that estimations need to be consistent and the residual error correction model should be free of serial correlations, which makes explanatory variables have inhomogeneity. The requirements will be met once the lags (p, q) are factored in for the dependent (p) and independent (q) variables. The approach requires big sizes of T and N, and the T must be bigger than N. In the work of [53], the N quantity is rounded to 20–30 countries. The mean group is the second considered estimator proposed by [54]. It has the convenience of yielding different regression coefficients for each country. It has a meager difference from the pooled mean group and is not confined to the processes of estimators [59]. In both the long and the short run, the estimator can yield a coefficient that is different and heterogeneous for each of the countries. The dynamic fixed effect is the third estimator and it is similar to the pooled mean group [60,61,62,63,64,65,66,67,68]. The coefficient of vector co-integration is limited across all panels in the long run. Aside from this, the short-run coefficient is the same because speed adjustment is limited, and it yields a coefficient for the specific panel. The mean group relationship, in the long run, is expressed in Equation (3) below:

lnGT_it = θ_i+ δ_0ilnGT_t−1 + δ_1ilnICT_it + δ_2ilnEG_it + δ_3ilnIQ_it + δ_4ilnHC_it + δ_5ilnCO_2it + ε_it

(3)

For as much that, the pooled mean group and the dynamic fixed effect model depicting long-run relationship is expressed in Equation (4) below

$${\mathrm{lnGT}}_{\mathrm{it}}={\omega }_{\mathrm{i}}+{\sum }_{\mathrm{j}=1}^{\mathrm{p}}{\Omega }_{\mathrm{ij}}{\mathrm{lnGT}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{p}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnICT}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnEG}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnIQ}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnHC}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnCO}}_{2\mathrm{i},\mathrm{t}-\mathrm{j}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(4)

In which, i stands for countries which number 1 to 27, t stands for the year (1990–2021), j represents optimum time lag, and fixed effect is represented by ${\omega }_{\mathrm{i}}$. Error correction models expressing short-run relationship is shown in Equation (5) below:

$$\begin{gathered} ∆{\mathrm{lnGT}}_{\mathrm{it}}={\omega }_{\mathrm{i}}+{\partial }_{\mathrm{i}}({\mathrm{lnGT}}_{\mathrm{i},\mathrm{t}-1}-{\Omega }_1{\mathrm{lnICT}}_{\mathrm{i}\mathrm{t}}-{\Omega }_2{\mathrm{lnEG}}_{\mathrm{i}\mathrm{t}}-{\Omega }_3{\mathrm{lnIQ}}_{\mathrm{i}\mathrm{t}}-{\Omega }_4{\mathrm{lnHC}}_{\mathrm{i}\mathrm{t}}-{\Omega }_5{\mathrm{lnCO}}_{2\mathrm{i}\mathrm{t}})+{\sum }_{\mathrm{j}=1}^{\mathrm{p}}{\Omega }_{\mathrm{ij}}{\mathrm{lnGT}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+ \\ {\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnICT}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnEG}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnIQ}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnHC}}_{\mathrm{i},\mathrm{t}-\mathrm{j}}+{\sum }_{\mathrm{j}=1}^{\mathrm{q}}{\mathsf{\delta }}_{\mathrm{ij}}{\mathrm{lnCO}}_{2\mathrm{i},\mathrm{t}-\mathrm{j}}+{\mathsf{\epsilon }}_{\mathrm{it}} \end{gathered}$$

(5)

2.3. Durbin–Wu–Hausman Test

The Durbin–Wu–Hausman test is significant in making the selection between the pooled mean group, mean group, and the dynamic fixed effect [55]. To select between the pooled mean group and the mean group, the pooled mean group will be selected as being more efficient than the mean group if the null hypothesis formulated is accepted and when the null hypothesis is rejected, then the mean group is favored over the pooled mean group. Considering the pooled mean group and dynamic fixed effect, the pooled mean group is considered more efficient and is selected if the null hypothesis is accepted, and if it is rejected, then the dynamic fixed effect is considered over the pooled mean group [56].

3. Results and Discussion

3.1. Results

This research adopts the pooled mean group, the mean group, and the dynamic fixed effect to examine the influence of ICT factors on geothermal energy sustainability in EU region nations on the yardstick of economic development level, the nations were classified into two clusters; EU14 emerged economies (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxemburg, Netherland, Portugal, Spain, and Sweeten) and EU13 emerging economies (Croatia, Bulgaria, Czech, Cyprus, Hungry, Estonia, Lithuania, Latvia, Malta, Malta, Romania, Slovenia, and Slovakia). Levin, Lin, and Chu (LLC), and Im, Pesaran and Shin (IPS) unit root tests are carried out to ascertain the presence of stationarity in the variables data (lnGT, lnICT, lnHC, lnEG, lnIQ, and lnCO₂). So, it becomes paramount to find the integration order of all variables in this study. Results of the two tests were displayed in

Table 2. Panel Unit Root Test results for the EU Region in 1990–2021.

Variable	Level		First Level
	LLC	IPS	LLC	IPS
GT	8.665 *** (0.000)	9.744 *** (0.000)	41.509 *** (0.000)	64.504 *** (0.000)
ICT	1.767 *** (0.000)	3.393 *** (0.000)	20.869 *** (0.000)	21.832 *** (0.000)
HC	2.394 *** (0.008)	3.190 *** (0.000)	23.588 *** (0.000)	23.749 *** (0.000)
EG	2.387 *** (0.000)	5.339 *** (0.008)	17.832 *** (0.000)	19.796 *** (0.000)
IQ	1.903 *** (0.000)	2.757 *** (0.000)	18.928 *** (0.000)	19.640 *** (0.000)
CO2	12.597 *** (0.000)	15.615 *** (0.006)	32.235 *** (0.000)	44.065 *** (0.000)

Remark: *** refers to importance at the 1%, scale. Levin, Lin, and Chu test (LLC) and Im, Pesaran, and Shin W-stat test (IPS).

and it can be deduced that all the variables are stationary at the level and first difference for both LLC and IPS. This shows that the variables are in a mixed order of integration (I (I) and I (0)). Based on these findings, the panel ARDL can be applied.

Preliminary testing was used to start the estimation process summary of statistics as seen in the Table in Appendix A. A normal distribution is seen in all the variables. Table in Appendix B displayed results measuring relationships. To measure the presence of a relationship among independent variables or multicollinearity, variance inflation factor analysis is considered germane [57,58]. It is to avoid false regression or inferences of bigotry in nature. As seen in

Table 3. Regression analysis.

Variable	Coefficient	Prob.	VIF
ICT	0.069 ***	0.002	1.87
HC	0.941 ***	0.000	1.85
EG	0.059	0.220	1.81
IQ	1.068 *	0.240	1.99
CO2	1.001 ***	0.000	2.03
C	0.344 ***	0.000

Note: *** and * indicate significance at the 1% and 10% levels, respectively.

, before the variance inflation factor was tested, linear regression was used in this research. Analysis in the table shows no correlation, and the general rule is that if the variance inflation factor is below 5 [57,58,59], it means there is no relationship, that is, no correlation among the variables.

The study seeks to examine the impact of ICT pointers on the sustainability of geothermal energy sectors and so this study uses three estimators, and they are the pooled mean group, the mean group, and the dynamic fixed effect. The Durbin–Wu–Hausman test becomes vital to making a selection among the pooled mean group or means group followed by pooled mean group/mean group or dynamic fixed effect. Hausman test results on the pooled mean group and mean group, favor the pooled mean group over the mean group, that is, the null hypothesis is accepted. Similarly, the pooled mean group is also favored over the dynamic fixed effect because the null hypothesis is accepted using the Hausman test. Results of the three estimators (PMG, MG, and DFE) using the Hausman test are seen in

Table 4. Summary of Panel Regression for the EU Region from 1990–2021.

Model 1. Long-Run Estimation for EU Region 1990–2021
Long-Run Coefficient	PMG		MG		DFE
	Coefficient	Prob.	Coefficient	Prob.	Coefficient	Prob.
ICT	0.056 **	0.013	0.035	0.449	0.023	0.908
HC	0.251 ***	0.000	0.095	0.645	0.122 ***	0.000
EG	0.057 ***	0000	0.057	0.303	0.031	0.362
IQ	0.029 ***	0.007	0.025	0.430	0.548	0.434
CO2	−0.043 ***	0.000	−0.016	0.969	−0.094 *	0.073
Hausman Test	2.52	0.774			0.95	0.966

Note: ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. Values in parentheses are p-values.

. Estimation of the pooled mean group model is in Table 4 with those of the mean group and dynamic fixed effect, which gives a comprehensive check.

In Model 1 (see Table 4), at a 5% level, ICT shows optimism and a significant impact on the geothermal energy sector. So, when there is a 1% incline in ICT, geothermal power sustainable development will be aided by 0.013%. This finding supports the views of [13,14,15,16,17], which suggest invigorating the exploitation of green ICT development and achieving the benefits from the significant influence of economic sustainability and a clean environment through the geothermal energy sustainability and sustainability. Findings from this study show that an increased level of investment in ICT geothermal will fasten the geothermal energy supply in the European zone. Sustainability in geothermal energy sustainable development being aspired by the EU could be attained by improving on ICT that births smart grids, better efficiency levels, and productivity, and an infrastructural base that equips entrepreneurs in the sustainable development of relevant local content and services. Furthermore, human capital input has a 1% significant coefficient, which is also positive in the long run. Precisely, when human capital inclines by 1%, it will create a 0.251% boost in the geothermal energy sector. The level of sustainability being craved by the EU in geothermal energy supply could be achieved by adding value to the renewable energy industry in the area of human capital resource skills and knowledge. This corroborates with [30,31,32,33,34]. The implication is that geothermal sustainability at the micro level could be qualitatively assessed as sustainable from the angle of boosting the well-being of the community. This research shows that when resource value is added to human capital, it will boost the geothermal energy supply in the European zone.

Additionally, the coefficient on economic sustainability output is found positive but statistically significant at a 1% statistical level, in the long run, suggesting a positive relationship between economic sustainability output and geothermal energy industry development in the EU region. This implies that an increase in economic sustainability output increases geothermal energy development in the EU zones. Specifically, when economic sustainability inclines by 1%, there will be a boost of 0.057% in geothermal energy sustainability. This corroborates with [40,41,42,43,66]. This result is a hint that the European states could attain their renewable targets on geothermal sustainable development by broadening activities and function levels at the economic level.

Institutional quality enters with a positive and significant coefficient at a 1% level in long run, which means when a 1% increase is attained in institutional quality, the impact on the geothermal energy supply will be 0.029%. These results corroborate with [10,25,26,27,28,29]. This means that an incline in institutional quality could boost the geothermal energy supply in the EU. That is, just by broadening activities on three pointers of a conducive environment, emotional, outdoor and indoor environment, these European countries could achieve sustainability in their geothermal energy industry.

Conversely, the coefficient on carbon dioxide (CO₂) emissions yields negative results but at a 1% statistical level, it is statistically significant. It means there is a negative relationship between geothermal energy consumption and emissions coming from CO₂ among European countries in the long run. An increased level of geothermal consumption will therefore reduce emissions from carbon dioxide in the EU zones. Specifically, when geothermal energy consumption inclines by 1%, there will be a 0.043% reduction in CO₂ emissions. This shows consistency with [7,27,36,37,38,39,60]. This result is an indication that when the EU regions increased their consumption of geothermal energy, they could achieve curbing pollution and the sustainable environment being craved. They could attain the desired level of CO₂ emissions by increasing the level of geothermal energy sustainable development.

In showing the effect of ICT pointers on making geothermal energy sustainable, this research adopts the pooled mean group, the mean group, and the dynamic fixed effect. This is seen in

Table 5. Summary of Panel Regression for EU14 Emerged Countries from 1990–2021.

Model 2. Long-Run Estimation for EU14 Emerged Countries 1990–2021
Long-Run Coefficient	PMG		MG		DFE
	Coefficient	Prob.	Coefficient	Prob.	Coefficient	Prob
ICT	0.112 ***	0.000	0.057 *	0.063	0.054	0.756
HC	0.768 ***	0.000	0.585 ***	0.001	0.658 ***	0.000
EG	0.170 **	0.011	0.107	0.397	0.091	0.390
IQ	0.421 ***	0.005	0.094	0.911	0.039	0.887
CO2	−0.302 ***	0.001	−0.019	0.934	−0.478 ***	0.000
Hausman Test	0.27	0.412			0.20	0.752

Note: ***, ** and * indicate significance at the 1%, 5%, and 10% levels, respectively. Values in parentheses are p-values.

. The Hausman test is vital to selecting among the pooled mean group or the mean group, or between the pooled mean group and the dynamic fixed effect. Analysis from the Hausman test on the pooled mean group and mean group reveals the pooled mean group is considered over the mean group because the null hypothesis is accepted. Similarly, Hausman test results on the pooled mean group and dynamic fixed effect reveal an accepted null hypothesis, which makes the pooled mean group to be favored over the dynamic fixed effect. In Table 5, statistics of the analysis of the three estimators (PMG, MG, and DFE) using Hausman tests are seen. Results of the model estimation of the panel mean group and those of the mean group and dynamic fixed effect are detailed in Table 5, which gives a comprehensive check.

In Model 2 (see Table 5), ICT at a 1% level, produces optimism and significant influence on the geothermal energy sector. This means that when there is a 1% level incline on ICT, it will boost geothermal to the tune of 0.012% among the 14 EU countries. This finding supports the view of [14,15,16,17,18,61], which allude to the increased level of harnessing development in green ICT, attaining the potential from the remarkable influence of sustainability in the economy, and an enabling environment with the aid of sustainable sustainability in the geothermal industry. Findings in the study show that increased ICT sustainability aids geothermal sustainable development sustainability among the 14 EU countries. The EU 14 nations could achieve their desired sustainability in geothermal supply by boosting ICT pointers that foster smart grids, increased levels of efficiency and productivity, and shared infrastructure to enable entrepreneurs to build locally relevant content and services.

Furthermore, at a 1% level, human capital input produces remarkable eco-efficiency, which is also positive in the long run. Precisely, when human capital grows by 1%, there will be a 0.768% incline in the geothermal energy industry sustainability. By increasing the level of knowledge acquisition and skills of the human capital in the geothermal industry, the 14 EU nations could earn sustainability in their geothermal energy sector. This supports the views of [30,31,32,33,34]. What this implies is that geothermal energy sustainability at the micro-level can be assessed in qualitative form, on sustainability as per boosting the general well-being of the community. This finding suggests that when resource value is added to human capital, it could boost geothermal sustainable development in the 14 EU nations.

Furthermore, at a 5% statistical level, economic sustainability yields positive and statistically significant results in the long run. Which interprets a positive correlation between economic sustainability and geothermal industry development in the 14 European countries. It means that when economic sustainability output grows, the geothermal industry’s sustainable development will as well increase in the 14 EU economies. Specifically, when economic sustainability output increases by 1%, there will be 0.170% sustainability in the geothermal energy sustainability. This supports the views of [40,41,61]. These results show the 14 EU nations have the potential of attaining their desired level of targets on renewable energy and geothermal by boosting the level of economic functions and activities.

Additionally, institutional quality enters with a positive and significant coefficient at a 1% level in long run, implying that an increase in institutional quality by 1% results in an incline in geothermal energy supply by 0.421% in the EU14 members. This finding substantiates [10,25,26,27,28,29]. It suggests that geothermal energy industry sustainability in the EU 14 members rises with an increase in institutional quality. In other words, the EU 14 could attain the desired geothermal power industry by widening the scope on three pointers of enabling environment—the emotional aspect of the environment, the outdoor, and the indoor environment.

Conversely, a negative relationship is seen between CO₂ emission and geothermal energy supply among the 14 European countries, but it is statistically significant at 1% in the long run. This means when the level of geothermal usage in the EU14 is increased it will scale down the rate of CO₂ emissions. Specifically, if geothermal consumption is increased by 1% there will be a 0.302% decline in the rate of carbon dioxide emissions. This supports the views of [7,27,36,37,38,39,60]. The results, therefore, show that the 14 European countries could curb pollution and have a sustainable environment by increasing their level of geothermal usage. These countries could therefore achieve their desired level of CO₂ emission by boosting their geothermal sustainable development capacity.

To estimate the effects of ICT factors on geothermal energy sustainable sustainability, this research adopts three estimators and they are the pooled mean group, the mean group, and the dynamic fixed effect. As shown in

Table 6. Summary of Panel Regression for Emerging Countries from 1990–2021.

Model 3. Long-Run Estimation for Emerging Countries 1990–2021
Long-Run Coefficient	PMG		MG		DFE
	Coefficient	Prob.	Coefficient	Prob.	Coefficient	Prob.
ICT	0.057 ***	0.000	0.011	0.795	0.011	0.892
HC	0.752 ***	0.000	0.342	0.383	0.100 ***	0.003
EG	0.023 ***	0.000	0.351	0.283	0.037	0.145
IQ	0.032 ***	0.004	0.444	0.605	0.664	0.916
CO2	0.074 ***	0.000	0.196	0.441	0.013 *	0.077
Hausman Test	0.85	0.813			0.52	0.933

Note: *** and * indicate significance at the 1% and 10% levels, respectively. Values in parentheses are p-values.

, the study used the Hausman test to make a selection between the pooled mean group and the mean group and the pooled mean group/mean group or the dynamic fixed effect. In the pooled mean group and mean group, outcomes from the analysis show that the pooled mean group is chosen over the mean group because the null hypothesis is accepted. Similarly, between the pooled mean group and the dynamic fixed effect, the pooled mean group is also preferred over the dynamic fixed effect because the null hypothesis is also accepted. The outcome of the three estimators (PMG, MG, and DFE) using Hausman tests is seen in Table 6. Table 6 further shows the results estimation of the Panel pooled mean group model with results of those of mean group and dynamic fixed effect, which provides a comprehensive check.

In Model 3 (see Table 6), at 1%, ICT produces an optimism and significant influence on the geothermal power industry. This suggests that a 1% incline in ICT will bring about a 0.057% boost in geothermal sustainable development among the 13 EU nations. These findings support earlier studies such as [13,14,15,16,17] which suggest boosting efforts to exploit green ICT development and attaining the potentials from the remarkable influence of sustainability in the economy and an environment that is clean leveraging on sustainable sustainability in geothermal energy. Findings from this research show that further developmental efforts in ICT will aid geothermal power sustainable development among the 13 EU countries. A sustainable geothermal energy sector being craved for by the 13 EU countries could be attained by boosting ICT that facilitates a smart grid, increased level of efficiency and productivity, and a strong infrastructural base that assists the sustainable development of local contents and services by an entrepreneur. Also, human capital input, at a 1% statistical level, yields a positive significant coefficient. Precisely, when human capital inclines by 1%, it will lead to a 0.752% boost in the sustainability of the geothermal industry. The aspired level of geothermal sustainability being craved by the EU could be achieved among the 13 European countries, by increasing knowledge and skills of human capital resources in the geothermal energy sector. This supports the views of [62,63,64,65]. The implication is that geothermal power development in the EU zones could be assessed qualitatively as being sustainable from the angle of the well-being of the community. These findings reveal that an increased level of human capital resources will boost geothermal sustainable development among the 13 EU nations.

Furthermore, the economic sustainability coefficient is found to be positive but statistically significant at a 1% statistical level, in the long run, suggesting a positive relationship between economic sustainability output and geothermal energy industry development in the EU 13 members. This implies that an increase in economic sustainability output increases geothermal energy development in the EU 13 members. Specifically, a 1% level of economic sustainability incline will boost geothermal energy sustainability by 0.023%. This result is showing consistency with [40,41,42,43,66]. This result is an indication that the 13 EU countries have the potential of attaining the renewable goals of geothermal by boosting the spate of activities and functions in their economies.

Institutional quality enters with a positive and significant coefficient at a 1% level in long run, this suggests that when 1% occurs in institutional quality geothermal energy supply will incline by 0.032% among the 13 EU countries. These results corroborate with [10,25,26,27,28,29]. It suggests that geothermal energy industry sustainability in the EU 13 members rises with an increase in institutional quality. In another word, the desired level of sustainable geothermal being aspired by the 13 EU countries could be attained by accelerating three key areas of enabling environment, which are the emotional, outdoor, and indoor environment.

On the other hand, a negative correlation is seen between carbon dioxide emission and geothermal sustainable development even though it is statistically significant at a 1% level, in the long run, this means that among the 13 EU countries, there is a negative relationship between CO₂ emission and geothermal energy sustainability. That is, increasing geothermal consumption will cut down the rate of CO₂ emission among the 13 EU countries. Specifically, when there is a 1% boost in geothermal energy consumption, a 0.074% decline is expected in emissions coming from carbon dioxide. These results support the views of [7,27,35,36,37,38,39,60,67,68,69,70,71,72,73]. This means that the 13 EU countries have the potential of curbing pollution and attaining sustainability in their environmental targets by boosting the level of geothermal consumption. The desired level of cut down on CO₂-related emissions could be achieved by boosting the level at which sustainable development processes are powered by geothermal energy.

3.2. Discussion

This research proposes a framework that is theoretical, on the yardstick of which regional grouping of these European nations was made in line with the spate of development and activities in their economies, and the level to which development is sustainable [18]. Categorization of these European countries could be carried out based on this framing, in line with the level at which they are influenced by the reactions to the particular clusters of economic and environmental features of the producer on the supply side and consumer on the demand side [13]. This type of grouping is useful because it gives background knowledge concerning the proportionate attachment to producers and consumers of the combined economic and environmental features peculiar to each cluster [13]. This has implications for shaping the structure and scope of environmental and regional policies in the European Union [13,18]. The evaluation pinpointed two clusters of countries with shared similar attributes (developed countries and developing countries) and the right blend of policies on the environment and regions in each of the considered EU nations [18]. To determine the effect of ICT factors on geothermal energy output among the considered EU states, a measure was taken from their level of economic buoyancy, and the countries were grouped based on the binary categorization of 14 developed nations and 13 developing nations [70,71,72,73]. The 14 European Union developed nations and the European Union states are Germany, France, Poland, Italy, United Kingdom, Spain, Belgium, Austria, Denmark, Finland, Ireland, Greece, Luxemburg, Portugal, Netherlands, and Sweden, and the 13 EU developing countries among the European states are Croatia, Bulgaria, Cyprus, Cyprus, Hungry, Estonia, Malta, Latvia, Poland, Lithuania, Romania, Slovenia, and Slovakia.

To see the short-run effects, the pooled mean group, the mean group, and the dynamic fixed effect estimators were used. The results findings of the estimators are displayed in Tables in Appendix C, Appendix D and Appendix E. There is a negative value of error correct term (ECT) and at 1%, it is significant for the three estimators which assert the occurrence of a relationship in the long run. Model 1 (see Table 4) displayed results on estimations of the influence of ICT factors on geothermal energy industry sustainability in the EU region members for the period 1990–2021. While Model 2 (see Table 5) shows estimation results on what influence will ICT factors have on geothermal energy industry sustainability in the EU14 economies for the period 1990–2021. Likewise, Model 3 (see Table 6) shows the result of the estimated impact of ICT factors on geothermal energy industry sustainability in the EU13 economies for the period 1990 to 2021. The results from Table 5 and Table 6 both reveal that ICT factors have a significant positive effect on geothermal energy sustainability.

Results findings show that there is a higher level of optimism over the remarkable impact of ICT on geothermal power sector sustainability among the 14 established EU countries than among the 13 classified as establishing countries. Notably, the magnitude of the influence is 0.112 and 0.057 for the 14 EU developed economies and the 14 EU developing economies, respectively. Leveraging green ICT development, this shows that a significant boost in geothermal energy sector development could be achieved more among the 14 EU established countries than the 13 EU establishing nations.

Furthermore, the result findings pinpoint that there is more optimism about the significant impact of human capital on geothermal power sector sustainability among the 14 EU established nations than among the 13 EU establishing nations. Notably, the magnitude of the effect is 0.768 and 0.752 for the 14 EU developed world and the 13 EU developing world, respectively. Leveraging human capital inputs, therefore, means that a significant boost in the development of human capital could be better achieved among the 14 EU established countries than among the 13 EU establishing nations.

Furthermore, the outcome of the results showed another higher level of optimism among the 14 EU established countries than among the 13 EU establishing countries on the significance of economic sustainability on geothermal power sector development. Notably, the magnitude of the effect is 0.170 and 0.023 for the 14 EU developed nations and 13 EU developing nations, respectively. It, therefore, means that significant sustainability in the geothermal power sector boost could be better facilitated in EU 14 established nations than in EU 13 establishing nations utilizing the economic out sustainability factors.

Furthermore, result findings show that the institutional effect on the geothermal energy sector sustainability has a higher level of significant optimism impact in the EU 14 economies than among the EU 13 developing economies. Notably, the magnitude of the impact is 0.421 and 0.032 for the 14 developed European countries and the 13 developing European countries. This suggests that a landmark sustainability in the development of the geothermal sector sustainability could be better facilitated among the 14 European established countries than among the 13 European establishing nations leveraging on institutional quality utilizing the institutional quality dimension.

Conversely, results findings show the level of optimism over the significant effect of the geothermal energy sector on CO₂ emission is higher among the 13 EU establishing countries than among the 14 EU established nations. Notably, the magnitude of the impacts is −0.074 and −0.302 for the 13 European developing nations and the 14 European developed nations. This means that significant progress in curbing pollution could be achieved among the 13 EU establishing nations than among the 14 European Union established nations leveraging on geothermal energy output sustainability.

4. Conclusions

This research investigates the relationships between Information and Communication technology, human capital, economic sustainability, institutional quality, and carbon dioxide emissions with geothermal energy sustainability in the context of the EU region. This research adopts the model of Auto-Regressive Distributive Lag to analyze data cut from 1990 to 2021 in the EU region. The geothermal power source is found to be green energy, clean, and free of pollution and could aid in decarbonizing the EU’s economy.

The study reveals a stronger positive Impact of information and communication technology and human capital input on geothermal energy sustainability in the economies of EU14 emerged countries than in EU13 emerging economies. Specifically, the result findings show that there is a higher level of optimism over the remarkable impact of ICT on geothermal power sector sustainability among the 14 established EU countries than among the 13 classified as establishing countries. Notably, the magnitude of the influence is 0.112 and 0.057 for the 14 EU developed economies and the 14 EU developing economies, respectively. The result findings pinpoint that there is more optimism on the significant impact of human capital on geothermal power sector sustainability among the 14 EU established nations than among the 13 EU establishing nations. Notably, the magnitude of the effect is 0.768 and 0.752 for the 14 EU developed world and the 13 EU developing world, respectively.

In the same manner, the study shows a stronger positive effect of economic sustainability and institutional quality on the geothermal energy industry in EU14 emerged economies than in EU13 emerging economies. Furthermore, the outcome of the results showed another higher level of optimism among the 14 EU established countries than among the 13 EU establishing countries on the significance of economic sustainability on geothermal power sector development. Notably, the magnitude of the effect is 0.170 and 0.023 for the 14 EU developed nations and 13 EU developing nations, respectively. Furthermore, results findings show that the institutional effect on geothermal energy sector sustainability has a higher level of significant optimism impact in the EU 14 economies than among the EU 13 developing economies. Notably, the magnitude of the impact is 0.421 and 0.032 for the 14 developed European countries and the 13 developing European countries.

On the other hand, the study reveals a stronger negative effect of geothermal energy sustainability on carbon dioxide emission in EU13 emerging economies than in EU14 emerged economies. Conversely, results findings show the level of optimism over the significant effect of the geothermal energy sector on CO₂ emission is higher among the 13 EU-establishing countries than among the 14 EU-established nations. Notably, the magnitude of the impacts is −0.074 and −0.302 for the 13 European developing nations and the 14 European developed nations.

Authorities in government in the 13 European Union countries should focus more on promoting eco-friendly green information and communication market determining factors such as the finished goods, consultants-related services, human capital-based market, financial system operations, and volume of market size which will foster the development of geothermal energy sector among the 13 EU underdeveloped economies. Similarly, enhancing institutional quality is also very important and must be promoted by the government of the 13 EU countries, the focus should be on institutional factors such as level of accountability, stability in political activities, effectiveness in governance, quality in regulatory processes, application of the law, and putting corrupt tendencies into check, as this will boost the level of efficiency in the EU13 geothermal energy sector sustainable development. Conversely, on the other hand, the governments of EU14 developed members can concentrate on improving the carbon dioxide mitigation strategies and plans such as motivating and encouraging foreign direct investment into geothermal energy sustainable development from foreign investors to increase geothermal outputs and mane energy development sustainable and this will curb pollution by increased usage of renewable power source

This study recommends an increased level of financial appropriations in human capital indicators such as level of expertise and community well-being to boost the progress of geothermal in the renewable energy sector of the 13 EU countries. Exposure to sophisticated knowledge and pieces of training will foster attaining energy safety levels and minimize the demand for other sources of contaminated energy supply. Having said all this, expertise in the workforce is also a cogent factor that could shape the sustainability of the geothermal energy sector, increased levels of electricity outputs from geothermal could substitute for fossil fuel energy outputs and geothermal energy sources could be used in making an increased level of sustainable development of goods and services on a large scale which will aid the attainment of the 2030 EU energy goals. EU 13 constituted authorities could pay more attention to the sustainability of information and communication technology in areas such as industrial robustness and creative strength.

It will assist in modifying the 13 EU countries to be secured in green energy and geothermal energy sectors methods. Also, by improving the general standard of living and motivating the involvement of all members of the EU zones to make contributions and be beneficiaries of the prospects. Furthermore, inculcating information and communication technology into the geothermal energy sector will make development sustainable as well as strategies on environmental matters in 14 European Union countries and 13 European countries. Conversely, good quality and adequately administered physical environment are Germany for the progress and sustainability of the geothermal energy sector through various dimensions. When the information communication and technology tools are appropriately deployed, they cut down costs, and productivity is enhanced through good usage of geothermal energy sustainable development. Additionally, a qualitative level of green information and communication technology support will promote good living in the workforce, it will prevent sickness because pollution and other forms of degradation in the environment could no doubt reduces the level at which human could be productive. Conclusively, green information and communication technology indicators could minimize the level of degradation in the environment, and boost sustainable development in the renewable energy sector like the geothermal energy industry, which will increase outputs and the country will become potentially viable in meeting the energy needs of their population and also becoming secured energy-wise. It is important to note that, in all efforts toward boosting productivity and sustainability in the geothermal energy sector through ICT measures, the conservation of the natural state of the environment should not be overlooked since the foundation of geothermal power is resources in underground water, which, if mismanaged, could make earth life diversities deteriorate in value, changes in land topography, degradation in the quality of underground water, and the spate of insecurity.

Just like other evidence-based research, this research comes with limitations. The extent to which it could be generalized is limited, and another limitation is the small data sample due to cases of missing data, which warrants using some econometric methods to test the formulated hypotheses. The background of this study could be leveraged for future studies on open platforms for smart grids and how they could be factored into managing geothermal energy trends in the economies. Particularly, the financial aspect of it should be researched as to who will finance it and the expected rate of returns on the investment. Aside from this, the requirement for executing the platform enunciated in this study could be further evaluated to ascertain if the conditions could prompt the successful implementation of the platform. The research has a scope of Information and Communication Technology businesses as the users of the platform. Future studies could factor in regulators and ordinary household levels, to expand the usage and usefulness of the open platform in a sustainable geothermal energy sector. Studies in the future time could leverage the background and findings of this study to embark on similar studies in other top sectors aside geothermal energy sector.