Does information and communication technologies improve environmental quality in the era of globalization? An empirical analysis

Haseeb, Abdul; Xia, Enjun; Saud, Shah; Ahmad, Anjum; Khurshid, Hamid

doi:10.1007/s11356-019-04296-x

Cited by 246 publications

(128 citation statements)

References 91 publications

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“…Over the past two decades, the influence of ICTs and innovation, economic growth, and carbon emission gets enormous consideration in environmental literature. The researchers are separated into two distinct groups, the first group of research considered that ICTs have made a positive contribution to improving the overall environment by decreasing carbon emission through improving energy efficiency (Batool et al, 2019; Haseeb, Xia, Saud, Ahmad, & Khurshid, 2019; Khan, 2019). The second series of studies suggested that the use of ICTs harms the environment by discharging an enormous sum of CO 2 emissions through use and consumption effect (Lee & Brahmasrene, 2013; Park et al, 2018; Salahuddin, Alam, & Ozturk, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Asymmetric role of tourism development and technology innovation on carbon dioxide emission reduction in the Chinese economy: Fresh insights from QARDL approach

Razzaq

Sharif

Ahmad

et al. 2020

Sustainable Development

189

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This study examines the association between tourism development, technology innovation, and carbon emissions by simultaneously testing Environment Kuznets Curve (EKC) hypothesis in China. The study develops and uses a novel composite index of tourism development and technology innovation. Utilizing quarterly data from 1995Q1 to 2017Q4, the study employs QARDL (Quantile Autoregressive Distributive Lag) approach and Granger causality‐in‐quantiles. The outcome of the study reveals that the observed relationship is quantile‐dependent, which may disclose misleading results in previous studies using traditional linear methodologies (such as OLS/ARDL) that address the averages. Primarily, the findings indicate that tourism development (TOR) and technology innovation (TII) significantly mitigate the level of carbon dioxide emissions (CO2) in the long run at lower‐higher (0.05–0.95) emissions quantiles and higher‐highest (0.7–0.95) emissions quantiles, respectively. Economic growth (GDP) and globalization (GLO) exert a positive asymmetric influence on CO2 only at lower‐medium (0.05–0.40) emissions quantiles and medium‐higher emissions quantiles (0.50–0.95), respectively. In the short run, TII, and GDP2 possess an insignificant impact across all emissions levels, while TOR shows a positive influence on CO2 only at lowest‐lower (0.05–0.20) emissions quantiles. The study confirms the presence of the EKC hypothesis at lower‐higher (0.05–0.70) emissions quantiles in the long run. Moreover, the outcomes of Granger causality in quantiles confirm asymmetric bidirectional quantile causality between TOR, TII, GLO, and CO2, while a unidirectional causality running from GDP to CO2. The results recommend that the Chinese government should implement integrated “tourism‐technology” policies based on the asymmetric emissions‐reduction effects of tourism and technology innovation in the long run.

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Section: Literature Reviewmentioning

confidence: 99%

Asymmetric role of tourism development and technology innovation on carbon dioxide emission reduction in the Chinese economy: Fresh insights from QARDL approach

Razzaq

Sharif

Ahmad

et al. 2020

Sustainable Development

189

View full text Add to dashboard Cite

show abstract

“…Salahuddin and Alam (2016) nd that electricity consumption per capita increases by 0.026% if Internet users increase by 1% by using a panel data of OECD countries. Haseeb et al (2019) observe a unidirectional causality from ICT toward energy consumption in BRICS countries. Zhou et al (2019) show that the ICT sector contributes a large amount of carbon emissions due to its energy consumption and intermediate inputs of energy-intensive products.…”

Section: Literature Reviewmentioning

confidence: 81%

“…Considerable literature on the nexus between industrial digital transformation and environmental performance is available, but empirical studies show con icting results (Berkhout and Hertin, 2001;Haseeb et al, 2019;Kunkel and Matthess, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

How Does Industrial Digitalization Affect Enterprise Environmental Performance?

Wen

Song

2021

Preprint

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Despite the increasing use of digital technology in industrial production, how industrial digitalization affects the environmental performance of production activities remains unclear. This research contributes to the literature on the relationship between industrial digitalization and enterprise environmental performance by employing a large sample of Chinese manufacturing enterprises. Results indicate that the environmental performance of manufacturing enterprises has been significantly improved in the process of industrial digital transformation. Structural and technology effects are the influencing mechanisms. Industrial digitalization reduces the production scale of heavy polluting enterprises and improves product innovation and green total factor productivity, but it has an insignificant effect on total factor productivity. Moreover, industrial digitalization improves enterprise environmental performance by introducing front-end cleaner production technologies, rather than by increasing pipe-end pollutant treatment facilities.JEL Classification: Q56, O13, L86

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“…Jonathan et al [23] acknowledged the importance of information technology (IT) in enabling global strategy, enhancing coordination and reducing costs. Haseeb et al [24] concluded that the information and communication technologies can improve our environment in the era of globalization. Qureshi [25] explained the importance of information technology to economic development from the perspective of development.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Development of Information Technology and the Real Economy in China Based on Provincial Panel Data

Zhang

Qian

et al. 2020

Sustainability

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The deep integration of information technology (IT) and the real economy contributes to China’s high-quality economic sustainable development. From the perspective of efficiency, this paper aims to build an evaluation index system, with 30 provinces in China from 2011 to 2017 being taken as the research objects, conduct static and dynamic analysis by using the super-efficiency data envelopment analysis (DEA)-Malmquist index, and draw a spatial distribution diagram to reflect its changes. This study reveals that the integrated development of information technology and the real economy is unbalanced in China. The eastern region performs better with a development slowdown, while the central and western regions lag behind with a lot of room for improvement. The effect of regional agglomeration is obvious, which can be evidenced by the fact that those provinces with a high-efficiency value produce a radiation effect on their neighboring provinces. On the whole, the total factor productivity is increasing annually, with the technical progress being the main factor that affects the total efficiency. According to the results, the countermeasures and suggestions are put forward in this paper to provide reference for a better sustainability development of information technology and the real economy.

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Does information and communication technologies improve environmental quality in the era of globalization? An empirical analysis

Cited by 246 publications

References 91 publications

Asymmetric role of tourism development and technology innovation on carbon dioxide emission reduction in the Chinese economy: Fresh insights from QARDL approach

Asymmetric role of tourism development and technology innovation on carbon dioxide emission reduction in the Chinese economy: Fresh insights from QARDL approach

How Does Industrial Digitalization Affect Enterprise Environmental Performance?

Integrated Development of Information Technology and the Real Economy in China Based on Provincial Panel Data

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