How does green technology innovation affect green growth in ASEAN-6 countries? Evidence from advance panel estimations

Highlights

• We examine the effect of green technology innovation on green growth in ASEAN-6 countries.

• Green technology has a negative impact on CO₂ emission and production based CO₂ emission.

• Non-renewable energy has a positive effect on green growth in ASEAN-6 countries.

Abstract

The ASEAN region is still majorly dependent on non-renewable sources, which emit more greenhouse emissions and are ranked as 3rd biggest emitter of greenhouse gases. Therefore the objective of the present study is to understand the role of green technology innovation and its effect on green growth. For said purpose, after accounting for the heterogeneity of the slope, cross section dependence, stationarity and cointegration on the dataset having yearly observations from 1992 to 2018, the application of CS-ARDL was made known for generating robust and consistent results by addressing the aforementioned statistical biases. The findings of CS-ARDL revealed that the relationship between technology innovation and renewable energy with carbon emissions and production-based carbon emissions was found to be negative. In contrast, non-renewable energy has a positive impact on carbon emissions and production-based carbon emissions. Moreover, the results were also validated by the AMG and CCEMG for both criterion variables, which are carbon emissions and production-based carbon emissions. Based on the findings, it is suggested that there is a need to channelize the research and development in order to improve the number of technological patents which help in controlling environmental degradation. The results and recommendations are discussed in further detail, where directions for future researchers are also proposed.

Introduction

The earth's temperature is gradually rising, which is also termed global warming and has attracted recent research to explore the possibilities and strategies for countering and controlling the adverse effects caused to the atmosphere and ecological environment (Sharif et al., 2020, Anwar et al., 2022). There are various reasons which have caused the deterioration of the environmental well-being, among which the human activities are the major factor which requires a more significant consideration by the social scientists in general and environmental scientists in particular in order to have the optimization within such activities (Farooq et al., 2022). The extent of air pollution can be assessed because, according to (Health Effects Institute, 2020), over 6.6 million people had early death in 2019. In contrast, in the same year, more than 476,000 babies died within the first month, which is not just disturbing but quite alarming.

There are various potential solutions by which the persistent environment deterioration can be controlled and/or minimized; however, it requires serious participation from the relevant stakeholders (Chien et al., 2022). At the downstream, environmental costs can be controlled by creating awareness among the end-consumers regarding preservation and optimizing the consumption, including efficiently disposing of the waste like electronic waste, disposing plastics and so on. For this purpose, organizations need to have an efficient and productive infrastructure which eventually complements the ecological well-being (Suki et al., 2022). On the other hand, at the upstream, organizations need to have compliance with green management, which helps them in reducing the harm to the environment and also improves their operational excellence.

The consumption of resources and energy, in particular, is a two-edged sword. The avoidance of positive aspects is imperative and cannot be possible as these help in generating finished goods and utilities for consumers; however, it has the negative aspects as well, which are the emissions of greenhouse gases, including carbon dioxide, which eventually leads to an unexpected and unanticipated change in the weather conditions resulting in increased temperature of the earth, excessive melting of ice glaciers, unusual droughts and intensive rainfall etc (Suki et al., 2022, Balsalobre-Lorente et al., 2018, Destek and Sarkodie, 2019). Therefore, organizations need to improve the efficiency of the utilization of resources by which the negative aspects can be minimized (Khan et al., 2022) (Khan et al., 2022, Du and Li, 2019). There are several possible ways by which the operational excellence can be achieved by having the least probable cost to the environment, including shifting the consumption of inputs from non-renewable to renewable bringing innovation into the existing infrastructure in order to improve the productivity, and pursuit towards cleaner production are few to mention (Gu et al., 2019, Godil et al., 2021, Danish and Ulucak, 2020).

When the global demand for the products is increasing, organizations are forced to meet the demand at the cost of the environment. Moreover, in the said process, the damage caused to the environment and life is because by greenhouse gas generation. In contrast, a significant portion of such emissions are represented by carbon emissions (Mohiuddin et al., 2016). According to (Owusu and Asumadu-Sarkodie, 2017), while comparing the data from the last 130 years, the global carbon emissions have reached 45 %. Moreover, 40 % of the total emissions since 1750 is only emitted in the previous 40 years (OECD, 2016). Therefore environment and operations scientists need to figure out an efficient solution which helps in improving productivity with minimal impact on the environment. In order to eliminate the carbon from the economies production, the Paris Climate Conference (Conference of the Paris or COP-21), Kyoto Protocols and most recently COP-26 were arranged in which countries agreed to control, minimize and eliminate the causes that emit carbon and daunt the progress towards Sustainable Development Goals (SDGs) (OECD, 2016, Khan et al., 2021).

Recently the researchers have highlighted the phenomena of green growth, which is referred to as the least possible emissions as the output of the production, by the implementation of environment-friendly technologies, which helps in transforming the existing supply chain into a green supply chain and is comparatively cleaner production (Hossain et al., 2022, Wiebe and Yamano, 2016). In addition to this, in such extensive environmental deterioration, the concept of green growth emerged as the potential solution for countering the carbon emissions (Gu et al., 2019), and preservation of energy resources by improving the operational excellence and mitigating the environment degradation (Zhao et al., 2022). However, for said green growth, there is a heavy reliance on innovation in technology and its respective infrastructure in order to have environment-friendly operations and processes (Suki et al., 2022, Sun et al., 2022b).

To reduce the significant level of carbon emissions, it is essential to improve the technical side (Kwon et al., 2017). Such improvement includes innovation for better operational efficiency and productivity complemented by renewable energy (Godil et al., 2021). Moreover, the phenomena of green growth are still under studied and require further exploration (Sun et al., 2022b). In addition to this, (Aghion et al., 2016) also suggested eliminating non-renewable energy and implementing environmental taxes. This highlights the importance of increasing the number of patents for green innovation and technological advancements that can help mitigate carbon emissions. Therefore, it is identified that for a better understanding of green growth, the role of green technology and the use of renewable and non-renewable energy resources is crucial (Danish and Ulucak, 2020, Razzaq et al., 2021a, Razzaq et al., 2021b).

As discussed earlier, the world is facing continuous environmental threats. Therefore the global perspective is shifting from traditional and conventional economic growth to the sustainable development and growth (Razzaq et al., 2021b), which is only possible because of the advancement and change on the technical side; otherwise, the traditional approach will lead to the future environmental disaster (Kwon et al., 2017, Acemoglu et al., 2016). This signifies the importance of having an environmental orientation when it comes to innovating the technology, which further strengthens the transformation toward renewable resources, which eventually have both economic and environmental benefits in a shorter and more prolonged period of time (Sun et al., 2022a).

The geographical context of the present study is ASEAN countries due to several reasons. Firstly, this region accommodates a 654 million population with a real economy of USD 3.1 trillion and is comprised of some good performing economies like Singapore, Malaysia and Vietnam etc. Despite being a region having emerging economies, the region's maximum dependence is still on non-renewable sources, which emit more greenhouse emissions and are ranked as 3rd biggest emitter of greenhouse gases (Ahmed et al., 2017). In contrast, the energy demand is anticipated to increase by 80 % before 2035 (Nathaniel and Khan, 2020). In such a situation, green technology innovation can make a difference in the ASEAN region in progressing green growth (Rani et al., 2022). Hence the potential of the region for economic prosperity and the imbalance between renewable and non-renewable energy resources are the motivations behind selecting this region for research purposes. Fig. 1 shows the overall trend of green technology innovation in the ASEAN region.

In addition to exploring the context of ASEAN countries, the present study has some other contributions as well. Firstly, the uniqueness in exploring the link of green growth with the help of technology innovation and the use of renewable and non-renewable energy resources. Secondly, the earlier studies have used conventional panel estimations, which have the ignorance of countering several estimation biasness including multi-correlation, cross-sectional dependency, heteroscedasticity and so on. In contrast, the technique used in the present study is known for generating robust and consistent results by addressing the aforementioned statistical biasness whereas it also efficiently causes the outcomes by having predictors integrated at different levels (Bai and Carrion-I-Silvestre, 2009) and is recently validated while exploring the related phenomena in BRICS countries (Danish and Ulucak, 2020).

Nevertheless, the organization of the study is the next section discusses the literature review, followed by the section discussing data, model and methodology, and whereas in last estimations and findings based on the estimates are discussed and accordingly concluded.