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Exploring Relationships between Environmental Performance, E-Government and Corruption: A Multivariate Perspective

Authors: Carmen C. Rodríguez-Martínez; Isabel María García-Sánchez; Purificación Vicente-Galindo; Purificación Galindo-Villardón;

Exploring Relationships between Environmental Performance, E-Government and Corruption: A Multivariate Perspective

Abstract

In order to improve environmental performance, the participation of effective and transparent citizens and governments that help counteract corruption in environmental matters is crucial. In this sense, this work focuses on exploring relationships between e-participation, e-government, the corruption index and environmental performance indicators. To this end, a sample comprising 116 countries from varying geographic regions is used in conjunction with indicators of environmental performance, e-participation, e-government and the corruption index. Through the use of the HJ-biplot and STATIS multivariate statistical techniques, it will be possible to observe the role that these variables play in countries’ behavioural patterns with respect to environmental performance. The results show a correlation between the indicator ‘perception of corruption’ and environmental performance; therefore, the lower the level of corruption, the higher the environmental performance index. We conclude that countries that exhibit more e-participation, lower levels of corruption and better level income are more likely to follow policies and programmes aimed at achieving better environmental performance.

Keywords

hj-biplot, corruption, TJ807-830, TD194-195, Renewable energy sources, e-participation, environmental performance, HJ-biplot, GE1-350, statis, Environmental effects of industries and plants, sustainability, Environmental sciences, multivariate analysis, STATIS

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    23
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Average
Top 10%
gold