New Focus For Industrialization 4.0: Economic Growth Through Industrial Energy Management
Abstract
The purpose of this article is to understand and elaborate on the impact of energy management through the use of solar energy systems in the industrial sector over the economic growth of developing countries. This study is based on Pakistan where the concept is in the infancy stage. Therefore, the significance of the study has many folds as the study will not only reflect the contemporary use of solar panels in the industrial sector but also reflect vividly upon the implications of the concept regarding the eastern and developing markets. The study collected data from employees of the energy sector to test the claim with a non-probability sampling technique and analysis has been made through incorporating SMART-PLS. The findings of the study reflect that there is a definite association between the use of solar panels in the production sector on energy efficiency as well as the sustainable economic growth of the country. Hence the study is also beneficial for fostering research work as well as to optimize the policy formulation for the use of solar energy systems in the production sector of developing countries of the world.
Keywords
energy management, energy efficiency, industrialization, sustainable economic growth, Pakistan, internet of things
INTRODUCTION
Recent studies have consistently highlighted the need for sustainable development. In reality, survival depends entirely on sustainability. As a result, the study noted a shift in emphasis in favor of obtaining clean and sustainable energy (Abbas, Waseem, & Yang, 2020). That was generally accomplished in the past by using resources like chemical and electrical etc. However, the change in energy production and management has been threatened (Abbas et al., 2020), due to barriers from policy-makers, human resources, technology as well as economic conditions, etc. (Irfan, Zhao, Ahmad, & Mukeshimana, 2019). Energy efficiency, however, might not even be sought despite its effects on society and the economy. Thus, policy development and understanding are essential in this regard as proper policies associated with energy efficiency may reduce barriers in front of progress in this under-explored area (Cantore, Calì, & Velde, 2016). Energy efficiency is extensively important for protecting society from climatic and environmental harms (Dołęga, 2019). Hence, there is a need to use measures like industrial energy management, home energy management, demand side management, smart metering, and integrated information and control technologies.
South Asia comprises 25% of the world’s population. The annual growth rate of the population is likely to reach 1.9% per annum but the probable increase in demand for energy is expected to be raised by 7.4% to 7.6%. Pakistan is the second most populous country in South Asia but suffering from blackouts since independence (Abbas et al., 2020). The country is still fulfilling major of its energy needs by using hazardous fossil fuels not only for the economy but also for the environment (Irfan et al., 2019). However, the country is trying hard to attain energy through the utilization of renewable energy sources. Though on the other side energy demand in Pakistan is expected to be raised by 50% of the current energy supply by 2050. Therefore, there is a need to utilize the sun's energy and fulfil energy requirements through solar energy. Pakistan also falls behind several Asian countries in terms of per capita energy consumption. 51 million people are still living without electricity (Irfan et al., 2019).
Hence, there is a steep concern about the installation of solar systems to capitalize on massive periods of daylight (Abbas et al., 2018). Therefore, the country is trying to expand the use of renewable energy resources to increase the capacity of the national electricity grid. The country is planning to add 9700 MW of energy from renewable energy resources by 2030 (Irfan et al., 2019). The potential of renewable energy resources has also been recognized by the government of Pakistan and the government is trying to increase economic growth by focusing on a renewable energy mix (Jan, Durrani, & Khan, 2021).
There is always a significant relationship between energy consumption and economic growth (Aqeel & Butt, 2001; Shaari, Hussain, & Ismail, 2013). Thus, the relationship has also been noticed by researchers and academicians. However, there is no clear evidence that may substantiate the relationship between energy efficiency and an increase in economic growth. The main obstacle to conducting studies on the relationship between energy efficiency and economic growth is a lack of data. Therefore, there is a need to investigate with reliable data that can clarify the picture (Lin & Zhou, 2022). Previously, surveys of the World Bank were used by Cantore et al. (2016), but the data only range from 2002 to 2004. Similarly, Jan et al. (2021), conducted a study based on hydro-power as the main source of renewable energy generation and declared that the unavailability of data associated with other forms of renewable energy is the main hindrance to the study. The study also mentioned the need for studies that may highlight the potential of other forms of renewable energy resources on economic growth. On the other side studies also reflected a significant linkage between the use of non-renewable energy resources and degradation of the environment and public health. Hence, various nations, especially developing countries are now getting focused on the use of renewable energy resources to increase economic growth as well as to protect against environmental degradation and public health (Fernando & Hor, 2017). Therefore, this study will be specially directed toward the exploration of the linkage between the use of solar panels in the production sector of Pakistan to assist policy making and to endorse the gap highlighted by Jan et al. (2021). This study is one of the premier ones to shed light on the use of solar panels for sustainable economic growth concerning Pakistan. Thus, the study is not only beneficial for students, academicians, and researchers but also a diverse set of stakeholders as well as policymakers for understanding the benefits of renewable energy from solar panels in the industrial sector of developing countries like Pakistan.
THEORETICAL FRAMEWORK
Pakistan has the massive potential of attaining energy efficiency through solar energy and in most parts of Sindh, Punjab and Baluchistan the sunshine remains brighter almost throughout the year. Hence the potential to capitalize on solar energy is much high. 45 MW to 83 MW of energy can be generated from an area of 100 m2 (Adnan, Khan, Haider, & Mahmood, 2012). Thus, factories may utilize renewable energy sources to gain energy efficiency (Dincer, 2011) as energy produced by renewable energy resources is much higher than non-renewable energy sources (Goswami & Kreith, 2007). A similar was found true for the use of solar energy as the use of solar panels in industries may foster the percentage of energy produced as well as quality (Mekhilef, Saidur, & Safari, 2011). Thus to increase economic growth the use of solar energy might be preferred. Hence this study uses energy management through solar energy as the predictor variable, energy efficiency as the mediator, and sustainable economic growth of the country as the dependent variable.
The use of energy management via solar panels is valid as most of the prior studies e.g. Jan et al. (2021), indicated that data for other resources of renewable energy except hydro power was not available. In fact, to evident the impact of renewable energy on economic growth there is a need for reliable data (Lin & Zhou, 2022), as the other studies e.g.,Cantore et al. (2016) are based on data that is from early 2000. Thus, the use of energy management from solar panels and its impact on energy efficiency in the production sector is a legitimate postulate to be evaluated. However, the use of the Internet of things is mandatory for the effective monitoring and management of energy achieved from solar energy (Katyarmal, Walkunde, Sakhare, & Rawandale, 2018).
MAJOR RESEARCH QUESTIONS
Q 1: Why do solar panels have major significance for the industrial sector?
Q2: What is energy efficiency?
Q3: What is the significance of energy efficiency for the economy of Pakistan?
LITERATURE REVIEW
There is a direct linkage between the availability of electric energy to the entire population and the increase in economic growth of the country. Thus, efforts are made by several leading countries of South-East Asia to electrify all of their population but none of these became able to do that except Maldives. Thus, the concern is towards taking advantage of renewable energy resources to enhance power generation capabilities (Abbas et al., 2020). On the other side studies e.g., Lin and Zhou (2022), also reflected that using non-renewable energy resources is harmful to the environment as well as public health. Thus, overall the usage is not beneficial for sustainable economic growth and therefore instead of gas and oil, the surge is towards the use of renewable energy resources to lure with a series of benefits associated with energy and non-energy categories. On the other side, it has also been determined by the World Bank that energy efficiency is one of the major contributors to sustainable development goals. Moreover, turning towards renewable energy resources will provide us with a bright and low-carbon future. This may also foster the level of productivity. Renewable energy resources are found to be directly associated with an increase in per-unit productivity (Chen, Shi, & Zhao, 2022).
Energy Consumption and Economic Growth
World Bank has identified energy efficiency as a vital enabler for most of the SDGs. Moreover, boosting energy efficiency will provide a pathway to benefit the most vulnerable by enhancing their productive opportunities arising from the transition towards a low-carbon future. Renewable energy is directly linked to improvement in energy efficiency, which is an increase in productivity per unit of energy use (Chen et al., 2022).
The discussion over benefits was pretty well-established, only a few studies have addressed the possible negative impacts of the adoption of energy efficiency measures (Cagno, Moschetta, & Trianni, 2019). However, some of the past studies also highlighted a symmetric relationship between the use of energy resources and economic growth, and the relationship is majorly based on different stages of the economic cycle. Similarly, a study byLee and Chang (2007) from Taiwan reflected U-shaped relationship exists between energy consumption and economic growth.
Similarly, the analysis ofLin and Xu (2020) based on provincial data from China also reflected a nonlinear relationship. Adding to this study byKouton (2019) from the continent of Africa, found that the relationship between energy utilization and economic growth was non-linear. However, most of the studies are still highlighting energy as the main ingredient of economic growth. On the other side studies also reflected the increase in energy consumption as one of the major threats as it is reversely related to human health (Lin & Zhou, 2022). However, the actual purpose of energy management in the production sector is to foster economic as well as environmental growth cohesively (Meng, Yang, Chung, Lee, & Shao, 2018).
Solar Energy and Energy Efficiency
Therefore, it is optimal to consider solar energy which encompasses various forms of renewable energy resources e.g., solar, wind, hydropower, geothermal, and marine energy, etc. All these forms of energy are potent sources of energy supply that produce no or least hazardous impact on the environment and society as well as on future energy. This form of energy is generated through the conversion of thermal energy into electricity via photovoltaic cells of solar thermal systems. The conversion may yield an unlimited amount of energy that is especially effective for developing countries that do not have access to other forms of competitive energy (Meng et al., 2018). Similarly, mentioned by (Renna & Materi, 2021) the use of renewable resources in the production sector resulted in a decrease in CO2 liberation as well as an increase in energy efficiency. However, attaining energy efficiency it is not possible to ignore the importance of the Internet of Things that may substantiate energy efficiency in production firms (May & Kiritsis, 2017).
Energy Efficiency and Sustainable Economic Growth
Energy efficiency is much more important than energy saving but minimal research work is available at the junction of both of these broader concepts termed sustainable manufacturing and smart manufacturing respectively (Meng et al., 2018). Although for the manufacturing sector energy management is significantly important (Gahm, Denz, Dirr, & Tuma, 2016) that leads to energy efficiency. Also became the best and most efficient way to protect the environment and also assists firms' financial and non-financial objectives (Fernando & Hor, 2017). In fact, recent studies also confirm the positive association between energy efficiency and sustainable economic growth. In line with SDGs and the vision of 2030, it is almost necessary to relay most upon renewable energy resources in order to produce a positive impact on environment as well as to decrease cost for individuals, households, and businesses (Zakari, Khan, Tan, Alvarado, & Dagar, 2022).
Internet of Things (IoT), Energy Efficiency & Sustainable Economic Growth
Katyarmal et al. (2018), indicated that the role of IoT is exemplary in relating the energy achieved through solar panels to economic growth and betterment. In fact, through advanced algorithms and the use of IT infrastructure monitoring and use of energy might be improved.Villiers, Kuruppu, and Dissanayake (2021) also indicated the need of IoT in factories to use energy from solar panels effectively and efficiently that may lead to sustainable economic growth
HYPOTHESES
H1: There is a relationship between energy management through solar panels in the production sector and energy efficiency.
H2: There is a relationship between energy efficiency and sustainable economic growth of the country
H3: Energy efficiency mediates the relationship between energy management through solar panels in the production sector and sustainable economic growth of the country
H4: IoT moderates the relationship between energy efficiency and sustainable economic growth of the country
RESEARCH METHODOLOGY
Research Methodology is not only used to make readers understand the technique(s) that are used in any study but also assist researchers in attaining planned objectives and goals associated with the study (Tellis, 1997). Research Methodology may have two major breakdowns i.e., research design and sampling design as indicated by Sekaran and Bougie (2016).
Research Design
For this study, researchers adopted a closed-ended questionnaire to relate the use of solar energy panels in production factories with the economic growth of the country. Previously some of the studies likeCantore et al. (2016) were based upon secondary data collected from surveys of the World Bank for 29 developing countries including Pakistan and India from 2002 to 2004. On the other side, studies are also highlighting the causal relationship between energy consumption and declining social and human health. However, in recent times some countries have taken measures to upset the relationship between economic growth and well-being of their citizens (Fernando & Hor, 2017).
Thus, the optimal choice is to collect data from personnel of the energy sector to gain information associated with the use of solar panels in the production sector on energy efficiency and its reflection upon the economic growth of the country. Therefore, the purpose of the research is correlational (Sekaran & Bougie, 2016) as it relates energy management via the mediating role of energy efficiency on the economic growth of the country. The philosophy of research is epistemology as it is conducted to build knowledge (Saunders et al., 2007). The philosophical stance used to relate research philosophy with research approaches and methodological choices (Saunders, Lewis, Thornhill, & Bristow, 2015) is post-positivism. That is associated with quantitative as well as qualitative research work (Manjikian, 2013). However, mostly this stance applies to quantitative studies (Žukauskas, Vveinhardt, & Andriukaitienė, 2018).
Research Sample
Muzammil, Akhund, and Channa (2022) posited that Karachi is the largest city and contributes 25% of the GDP of Pakistan. Thus serving 2.5 million consumers in Karachi is much more challenging for K-Electric and therefore relying on renewable energy resources is the need of time. Especially relying on solar and wind energy is much more effective as Karachi is situated in an area where it has ample sunlight as well as wind energy. Thus, collecting data from personnel of the energy sector is legitimate, and previous work e.g., Irfan et al. (2019), has also done the same to portray the significance of solar energy over diversified stakeholders.
Therefore, by capitalizing on non-probability sampling likeAbdullah et al. (2017) and using the method of quota sampling like Irfan et al. (2019), this study collects primary data from the energy industry. Hence, the data has been collected based on perceptions from reputed employees of K-Electric ranging from middle to higher management. The total sample size for the study is 100 as the study is based upon the reflection of energy efficiency in the industrial sector on the economic development of Pakistan. The sample size is adequate to be used for SEM-based analysis through SMART-PLS as indicated by (Singkheeprapha, Jumani, & Sukhabot, 2022). The sample size was also been justified by previous studies likeKeith (2019) where the analysis through multiple regression was made on the sample of 100 students. However, initially, 150 questionnaires were circulated but the received number of questionnaires was only 122. Out of 122 questionnaires, 22 were not filled adequately. Hence, the response rate for this study is 75%.
Research Instrument
Research Instrument that is used in this study is a closed-ended adopted questionnaire that is a hybrid of several studies (Chien, 2022; Fernando & Hor, 2017; Lawrence, Nehler, Andersson, Karlsson, & Thollander, 2019; Purwania, Kumara, & Sudarma, 2020; Sola & Mota, 2020; Zhang, Wang, & Lai, 2015)
Statistical Technique and Software
Chien (2022), is one of the latest studies that use SMART-PLS to implement structural equation modeling to assess the mediation role of energy efficiency. The study also relates the mediation analysis with economic benefits. Similar has the purpose of this study and therefore the use of the software as well as statistical technique is justified.
STATISTICAL TESTING
It is better to use SEM as compared to regressions (Günzler, 2013) and the implementation of SEM became more efficient with the use of SMART-PLS (Andreev, Heart, Maoz, & Pliskin, 2009). SEM through SMART-PLS is based upon two models i.e., the inner model and the outer model. The inner model is used to highlight the relationship between variables of interest. However, the outer model is used to indicate the relationship between indicators and latent variables (Wong, 2013). These models have the purpose to shed light on inferential and descriptive statistical analysis that may substantiate the to provide a more rigorous view of statistical analysis (Ogwiji & Lasisi, 2022) by highlighting all the related paths and interrelated effects (Vijayabanu & Arunkumar, 2018). Hence, implementation of SEM through SMART-PLS resulted in the formulation of two different models namely the outer model and inner model. The outer model is used to reflect the relationship between elements and latent variables while the inner model is used to indicate the relationship between major research variables (Wong, 2013).
Figure 2 shows outer loading for each of the elements associated with any of the variables used in the process of research. The loading is the same as of factor loading and it is used to authenticate the inclusion of any indicator (Afthanorhan, 2013). The preferred range of outer loading started from 0.70 although the researcher may include elements with outer loading between 0.60 and 0.70 perhaps the inclusion of these elements may not disturb overall convergent criteria (Sander & Teh, 2014). Therefore, considering Figure 2 it is optimum to declare that figure is reflecting outer loading as none indicator has a value lesser than 0.766.
|
Cronbach alpha |
Composite reliability (rho_a) |
Composite reliability (rho_c) |
AVE |
|
|---|---|---|---|---|
|
Energy Efficiency |
0.949 |
0.951 |
0.963 |
0.868 |
|
Energy Management through solar panel in factories |
0.928 |
0.934 |
0.949 |
0.822 |
|
Internet of Things |
0.927 |
0.960 |
0.947 |
0.818 |
|
Sustainable Economic Growth |
0.813 |
0.831 |
0.876 |
0.639 |
Table 1 reflects determinants of model fitness e.g., construct reliability and convergent validity. Specifically indicating Cronbach’s Alpha along with Goldstein rho and composite reliability are used to reflect construct reliability. Similarly, composite reliability and average variance extracted (AVE) are used to highlight convergent validity. However, to assure construct reliability as well as convergent validity there is a need to assure some rules and criteria. Specifically, the minimum acceptable value for Cronbach Alpha is 0.40 and for Composite reliability it is 0.60 (Vijayabanu & Arunkumar, 2018). On the other side use of average variance extracted (AVE), alone with value of 0.50 or above is sufficient to reflect convergent validity.
Thus, through considering these criteria the table is not only assuring construct reliability but also convergent validity as the minimum value for Cronbach’s Alpha is 0.813 that is much higher than the threshold value and similar is the case for composite reliability and convergent validity where the minimum values in the table are 0.876 and 0.639. Hence, the table is substantially reflecting that the model has construct reliability as well as convergent validity.
|
1 |
2 |
3 |
4 |
5 |
|
|---|---|---|---|---|---|
|
1. Energy Efficiency |
_ |
_ |
_ |
_ |
_ |
|
2. Energy Magt through solar panel in factories |
0.491 |
_ |
_ |
_ |
_ |
|
3. IOT |
0.531 |
0.337 |
_ |
_ |
_ |
|
4. Sustainable Economic Growth |
0.695 |
0.420 |
0.577 |
_ |
_ |
|
5. IOT x Energy Efficiency |
0.300 |
0.187 |
0.378 |
0.353 |
_ |
Table 2 highlights discriminant validity. However, among three of the major measure used to reflect discriminant validity i.e., Heterotrait-Monotrait ratio (HTMT), Cross-Loading & Fornell and Larker criterion $ this study is using HTMT. HTMT is the most preferred measure to reflect heterotrait-monotrait ratio and to assure the presence of discriminant validity the table must not contain any value higher than 0.85 (Hair & Sarstedt, 2019). Therefore, Table 2 shows discriminant validity in the model as there is no value in the table that is higher than 0.695.
|
R-square |
R-square adjusted |
|
|---|---|---|
|
Energy Efficiency |
0.583 |
0.561 |
|
Sustainable Economic Growth |
0.413 |
0.402 |
|
Original sample |
Sample mean |
Standard deviation (STDEV) |
T stats. (|O/STDEV|) |
P values |
|
|---|---|---|---|---|---|
|
Energy Efficiency -> Sustainable Economic Growth |
0.476 |
0.476 |
0.062 |
7.734 |
0.000 |
|
Energy Magt through solar panel in factories -> Energy Efficiency |
0.464 |
0.463 |
0.075 |
6.184 |
0.000 |
|
IOT -> Sustainable Economic Growth |
0.242 |
0.248 |
0.073 |
3.298 |
0.001 |
|
IOT x Energy Efficiency -> Sustainable Economic Growth |
0.198 |
0.412 |
0.039 |
5.076 |
0.000 |
Table 3 indicates the quality criteria through the path coefficient. The tool is also known as the coefficient of determination. In fact, the purpose is to reflect the predictive accuracy of the independent variable which is donated by R-square. In actual predictive accuracy is based upon the reliability of the outer (structural) and inner (measurement) models (Purwanto, Asbari, Santoso, Paramarta, & Sunarsi, 2020). There are three different criteria to assess the impact of independent variables over the dependent variables i.e., 0.25, 0.50, and 075 that are perceived as low, moderate, and substantial impacts (Wong, 2013). Thus, in light of the given criteria, the model used in the study is effective in assuring the impact of renewable energy through solar systems in the production sector over energy efficiency as well as on sustainable economic growth of Pakistan. In fact, the values are moderate for mediating (indirect) relations and substantially above the lowest criteria for predictive accuracy for the dependent variable.
In Table 4, path coefficient is used to reflect the relationship of variables that are included in the measurement model of PLS-SEM through SMART-PLS (Silaparasetti, Rao, & Khan, 2017). Hence legitimate to declare that the table is a part of the inferential statistical side and it works upon the defined criteria of p-values and t-values. No relationship can be validated if the t-value is not greater than or equal to 1.97 and the p-value is lesser than or equal to 0.05.
Hence, in light of the mentioned criteria, the use of renewable energy from the use of solar panels in the production sector is a significant predictor of energy efficiency. Energy efficiency is also found to be beneficial for sustainable economic growth and moderation of the Internet of Things (IoT) with energy efficiency also found to have a positive impact on sustainable economic growth.
|
Original sample |
Sample mean |
Standard deviation (STDEV) |
T statistics (|O/STDEV|) |
P values |
|
|---|---|---|---|---|---|
|
Energy Magt through solar panel in factories -> Energy Efficiency -> Sustainable Economic Growth |
0.221 |
0.222 |
0.051 |
4.318 |
0.000 |
Table 5 reflects specific indirect effects.reflects the mediation analysis for the inferential section of the analysis. However, the table also uses the same criteria of t-values and p-values as used by Table 4 to reflect the relationship(s). Hence, it is effective to reflect those criteria developed byHair, Hult, Ringle, Sarstedt, and Thiele (2017) are not only valid for path coefficient but also for specific indirect effects as indicated by Hair and Sarstedt (2019). Thus, the specific indirect effect of energy management through solar panels in factories is also found to be positively associated with sustainable economic growth. Hence, based on the analysis, all of the postulates, relationships, and hypotheses are found to be true. . Moreover, the value for moderation analysis is found to be higher in comparison to the serial mediation analysis which confirms the use of moderation, i.e., (IoT) for relating energy produced by solar panels to sustainable economic growth
Conclusion And Discussion
This study is one of the premier studies from the context of developing countries like Pakistan and statistical testing proves all the relationships and claims formulated through this study. Therefore, it is optimal to discuss initially the model's fitness, reliability, validity, and predictive accuracy. At the beginning of the analysis, the findings of the study are consistent with (Dincer, 2011) as the use of renewable energy is also recommended for the industrial sector of developing countries like Pakistan. The amount of energy produced from solar energy can cause energy efficiency that is consistent with the indications of Mekhilef et al. (2011).
In fact, by considering the work of Goswami and Kreith (2007); Mekhilef et al. (2011) the use of energy management through solar panels and mediation of energy efficiency has been proven. This also signifies the selection of IoT as the moderator to check and verify the use of IT resources for better energy use. In fact, the higher-value for moderation analysis also indicated the significance of IoT for sustainable economic growth and it is also in line with the indications made by Katyarmal et al. (2018)
Similarly reliability, validity, model fitness, and predictive accuracy of the model also confirm the use of sustainable economic growth as the dependent variable as indicated by Jan et al. (2021). Relating the section of discussion with the inferential section of the study it has been observed that the findings of the study are consistent withChen et al. (2022) as energy generated with renewable energy resources like solar panels is found to increase energy efficiency. The use of renewable energy resources like solar panels is especially important for developing countries of the world. Moreover, these resources also can produce an ample amount of energy required for energy efficiency. Hence, the findings are also consistent withMeng et al. (2018); Renna and Materi (2021). Last but not the least findings of the study also reflect that the use of IoT is beneficial for economic development. Thus, found consistent with the indications of Gahm et al. (2016).
Policy implications
The findings of this study indicated that the production sector must use solar panels for attaining energy efficiency and to support sustainable economic growth. Hence, government must provide some incentives or provide solar panels at discounted prices to the production sector. Similar was recommended byShahsavari and Akbari (2018) with special emphasis on developing countries. However, the importance of research and development cannot be undermined and therefore study also recommends research and development must be emphasized to lure with the advantages of renewable resources (Dincer, 2011).
Recommendations and future direction
After detailed statistical testing, it has been recommended that production sector firms must develop proper policies to take advantage of available renewable energy resources. However, in addition to the proper policy formulation, there is also a need to use a proper and well-developed IT network to take full advantage of the resources and attain energy efficiency through effectively utilizing energy. For this purpose, there is a need for continuous research in this vein and therefore there is a need to analyze the impact of solar energy on other sectors as well like telecommunication, media, banking and higher education, etc. Moreover, the use of expanded construct for energy management may also be found fruitful to understand the mediation as well as serial mediation impact of related variables over sustainable economic growth.
Conflict of interest
The authors unequivocally affirm that there are no existing financial or personal conflicts of interest that could influence the outcome of this study. Additionally, no financial assistance or remuneration has been received for the execution of this research or the composition of this article. We also confirm that we have no direct financial or personal affiliations that could potentially bias the results or interpretations presented herein.