Damages to return with a possible occurrence of eco-technology innovation measured by DEA environmental assessment

Toshiyuki Sueyoshi ()
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Toshiyuki Sueyoshi: New Mexico Institute of Mining and Technology

Journal of Economic Structures, 2017, vol. 6, issue 1, 1-14

Abstract: Abstract Environmental assessment and pollution protection are important concerns in modern business and policy. Consumers are interested in corporate efforts on not only their products but also environmental protections and pollution preventions. To attain a high level of sustainability (i.e., economic success and pollution prevention), all entities in private and public sectors need to pay attention to green technology innovation. This study considers that eco-technology innovation can combat the global warming and climate change, which the world is now facing as a major policy issue, along with its related business and policy supports. It is clear that any engineering and science efforts cannot attain any policy goal on the climate change without supports from social science perspectives, including business and economics. An important concern discussed in this study is how to identify an effective decision on eco-technology innovation and its influence on sustainability. To discuss the global issue at the world level, this study is first interested in measuring the performance of their operational and environmental achievements and then pays attention to Damages to Return (DTR). The economic concept indicates a level of change of undesirable outputs (e.g., CO2) by increasing one unit of a desirable output (e.g., oil production). To assess the magnitude of DTR, this study proposes a use of Data Envelopment Analysis (DEA). The proposed DEA assessment theoretically provides corporate leaders and policy makers with information regarding how to invest in eco-technology innovation for abatement of undesirable outputs, so enhancing the level of corporate or social sustainability.

Keywords: Environment; Eco-technology innovation; Sustainability; Data Envelopment Analysis (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1186/s40008-017-0067-x

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