34 Social Equity and Lifestyle Conscious Policy Making …
515
pollutants and resource mining risk footprints, the emerging social equity gap due
to household consumption is estimated. In addition, householder preferences underpinning factor weighting are assessed through a national survey in Japan and applied
to the both the quantification of the social equity gap, and the potential for its future
amelioration.
34.2 Methodology
The method employed in this research consists of two steps. First, using Japanese
household consumption data from 1990 to 2005, environmental footprints are estimated and then projected from 2010 to 2040 using 2005 consumption patterns applied
to future demographic trends and stakeholder proactiveness preferences. Second, the
extent of social inequity is quantified using a combination of estimated and projected
or ‘virtual’ household footprints. Step one relies on environmentally extended inputoutput analysis (EEIOA; (Huppes 2006)) while step two utilizes an adapted EPSEF
(Chapman and Shigetomi 2018). The combination of these two precedential evaluation approaches is referred to as the Input-Output Sustainability Evaluation Framework (IOSEF) which demonstrates both the basis of social inequity (e.g. the origin
of household consumption induced environmental burdens) and the identification of
how each household footprint creates inequities within society. Stakeholder preferences (identified through a national survey) are used as a proxy for future stakeholder
behavior to aid in the reduction of environmental footprints. These preferences are
applied to the ‘virtual’ footprints, demonstrating stakeholder priority impacts.
This approach is the first attempt at demonstrating societal outcomes through the
lens of inequity, underpinned by lifestyle related public bads.
Figure 34.1 describes the approach to quantifying lifestyle-based consumption
burden and social inequity levels.
Public bad (PB) values are calculated using Eq. 34.1.
PB
(t)
j =
Q
(t)
jk
Max Q k
× p
(t)
jk
(34.1)
where t is the time period, j is the household attribute for both the quantity (Q) of
each footprint, k and stakeholder preferences, p.
The polygon consists of seven rectangles based on the share of total consumption
and the normalization of multiple public bads scores by income bracket. In Fig. 34.1,
the upper-middle income level is highlighted as an example.
515
pollutants and resource mining risk footprints, the emerging social equity gap due
to household consumption is estimated. In addition, householder preferences underpinning factor weighting are assessed through a national survey in Japan and applied
to the both the quantification of the social equity gap, and the potential for its future
amelioration.
34.2 Methodology
The method employed in this research consists of two steps. First, using Japanese
household consumption data from 1990 to 2005, environmental footprints are estimated and then projected from 2010 to 2040 using 2005 consumption patterns applied
to future demographic trends and stakeholder proactiveness preferences. Second, the
extent of social inequity is quantified using a combination of estimated and projected
or ‘virtual’ household footprints. Step one relies on environmentally extended inputoutput analysis (EEIOA; (Huppes 2006)) while step two utilizes an adapted EPSEF
(Chapman and Shigetomi 2018). The combination of these two precedential evaluation approaches is referred to as the Input-Output Sustainability Evaluation Framework (IOSEF) which demonstrates both the basis of social inequity (e.g. the origin
of household consumption induced environmental burdens) and the identification of
how each household footprint creates inequities within society. Stakeholder preferences (identified through a national survey) are used as a proxy for future stakeholder
behavior to aid in the reduction of environmental footprints. These preferences are
applied to the ‘virtual’ footprints, demonstrating stakeholder priority impacts.
This approach is the first attempt at demonstrating societal outcomes through the
lens of inequity, underpinned by lifestyle related public bads.
Figure 34.1 describes the approach to quantifying lifestyle-based consumption
burden and social inequity levels.
Public bad (PB) values are calculated using Eq. 34.1.
PB
(t)
j =
Q
(t)
jk
Max Q k
× p
(t)
jk
(34.1)
where t is the time period, j is the household attribute for both the quantity (Q) of
each footprint, k and stakeholder preferences, p.
The polygon consists of seven rectangles based on the share of total consumption
and the normalization of multiple public bads scores by income bracket. In Fig. 34.1,
the upper-middle income level is highlighted as an example.