54.3% solar systems whereas 38.0% of the respondents

54.3% of the respondents indicated they have never received any formal or
informal training on solar systems whereas 38.0% of the respondents have received
formal or informal training on solar systems through Shopkeepers, 4.3% of the
respondents have received formal or informal training on solar systems through neighbours
and 3.3% of the respondents have
received formal or informal training on solar systems through friends. This
result indicated that more of households have received formal or informal
training on solar systems through shopkeepers.

 

4.5.
Numbers of Hours of Load Shedding Of WAPDA Electricity Daily

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In this section, the researcher sought to examine that how many numbers of hours of load shedding of WAPDA electricity
faced by households daily. Their
responses are highlighted in the Table 4.12.8% of the respondent’s responses
that they faced 0-4 hours of load shedding of WAPDA electricity daily, 35.7%
of the respondents
indicated that they faced 5-8 hours of load shedding of WAPDA electricity daily,
20.3% of the respondents
indicated that they faced more than 9-12 hours of load shedding of WAPDA
electricity daily while 36% of the respondents indicated that they faced more than more than 12 hours
of load shedding of WAPDA electricity daily. This implies that the majority of
households faced more than 12 hours of load shedding of WAPDA electricity
daily.4.6.
Monthly Income Level of RespondentsThe researcher goal was
to examine how income of households effects the adoption of solar technology in
Village Regi. They were asked questions based on the source of income and level
of income earned.4.6.1.
Source of Income of Respondents

In this section, the researcher sought to know the
respondents source of income. Their responses are highlighted in table 4.13.Here 21% of household’s
sources of monthly income were jobs, 24.3% of household’s sources of income
were business, 13.7% of household’s sources of
income were agriculture, 35.7% of household’s
sources of income were labour and 5.0% of
household’s sources of income were remittances. From
the responses, this implies that more of household’s sources of monthly
income were labours.This figure 2 displays
that most of the households source of income was labor. This implies that most
of households are poor in this village.4.6.2.
Level of Income of Respondents

In this section, the researcher sought to know the
respondents level of income. Their responses are highlighted in table 4.14.From table 4.14, 40.0%
of household’s level of income were 0-5000, 6.7% of household’s level of income
were 5001-10,000, 10.7% of household’s level
of income were 10,001-15,000, 21.7% of
household’s level of income were 15,001-20,000 and 21.0%
of household’s level of income were Above 20,001.
From the responses, this implies that more of household’s levels of
income were0-5000.The above
Figure 3 shows that more of household’s levels of income were
0-5000. This implies that the majority of households
earned low income.4.7.
Availability of Substitute The goal of this
section was to examine the objective that aimed at finding how the availability
of substitute power source effects the adoption of solar technology in Village
Regi. The respondents were asked questions based on whether they were using energy choice for Lighting, Energy choice for
heating and any other source of energy.5.7.1 Energy source as
a substitute of solar using for Lighting

In this section, the
researcher tried to know the responses of the respondent’s energy choice for
lighting. Their responses are shown in the Table 4.15.Table 4.15.1 shows that 100% of the respondents were choice
WAPDA electricity as a
substitute of solar using for
lighting.Table 4.15.2 shows that 78% of the respondents did not
choice gas as a substitute
of solar using for lighting
while 22% choice gas as
a substitute of solar using for
lighting. Table 4.15.3: UPSTable 4.15.3 shows that 47% of the respondents did not
choice UPS as a substitute
of solar using for lighting
while 53% choices UPS as a substitute of solar using for lighting.Table 4.15.4 shows that 56.3% of the respondents did not choice
generator as a substitute
of solar using for lighting
while 43.7% choice gas as a substitute of solar using for lighting.4.8.
Recommend Use of Solar Technology to OthersIn this segment, the researcher tried to find out from the respondents
that whether they would recommends use of solar system to other people. Their
responses are shown in the following table 4.16. 

Here the respondents
were ask whether they would recommends
use of solar system to other people; 100% of the respondents give their
positive responses and recommended the use of solar system to others. Their
positive responses that why people adopted this solar system is highlighted in
the following table 4.16.1Here 9% of the respondents gave positive response and
recommended to installed the solar system because it decreases crime rate in night time, 18.3 of the respondents also recommended
to installed the solar system because it helps
in increasing the conforms of life, 2.7% of the respondents also recommended to installed the
solar system because it help in increase the
security level, 4% of the respondents also recommended to installed the solar system because it helps in increasing the study hours of kids in night
time, 6% of the
respondents also recommended to installed the solar system because it help in increase the sleeping hours at day time, 29.3% of
the respondents also
recommended to installed the solar system because it help in increase it helps in increases the education level which
leads to increase the standard of life, 5% of the respondents also recommended to installed the
solar system because it helps in increasing
the rest, 5.7% of the
respondents also recommended to installed the solar system because  it helps in
increasing the education level by providing light especially in night time, 20%
of the respondents
also recommended to installed the solar system because it helps in reducing crime rate in night time.4.9.
Binary Logistic Regression for Affecting the Adoption of Solar Technology

This study has applied the binary
logit model to estimate the factors affecting the adoption of solar technology
and these are presented here below. Table 4.17 and 4.18 provides the binary
logistic regression result and the marginal effects are presented that makes
the interpretation much easier.  Table 4.17 shows that total number
of respondents is 300 and also presents p- value is equal to 5% it means that
the overall model is statistically significant.Table 4.18 portrays the summary of
estimation of logic model 1 where dependent variable is adoption of solar
energy while independent variables are initial cost (icost_1) which is proxy of
price, load shedding (ls_2), numbers of years of education (edu_2) which is
proxy of knowledge and awareness, purposes of solar energy (purp) and
alternative of solar energy available (As) which is proxy of Number of
substitutes available.From the above findings, initial
cost (Icost-1) is negatively insignificant. It indicates that initial
instalment cost has no affect on adoption of solar energy. By observing the
results, LS-2 is positively significant at 1% and 10% change in dependent
variable is due to one unit change in independent variable that is 10% increase
in adoption of solar energy is due to one unit increase in load shedding of
electricity it means that more the load shedding, the more will be adoption of
solar energy. Education is positively insignificant. It indicates that numbers
of years of education has no affect on adoption of solar energy because the
literate and less educated people also use the solar energy for their daily proposes.
Purposes of solar energy (purp) is positively significant at 10% and 3% change
in dependent variable is due to one unit change in independent variable that is
3% increase in adoption of solar energy is due to one unit increase in purposes
of solar energy it implies that more the number of appliances usage, the more
will be adoption of solar energy. Alternative of solar energy available (As) is
also positively significant at 10% and 4% change in dependent variable is due
to one unit change in independent variable that is 4% increase in adoption of
solar energy is due to one unit increase in alternative of solar energy it
depicts that more the number of alternative of solar energy available, the more
will be adoption of solar energy because solar energy is relatively cheaper
than other energy.4.10.
Binary Logistic Regression for Affecting the Sustainability of Solar Technology
Table 4.19 illustrates that total
number of respondents is 300 and also presents p- value are equal to 5% which
depicts that the overall model is statistically significant. Table 4.20 shows the summary of
estimation of logic model 2 where dependent variable is sustainability of solar
system (s1) while independent variables are income of respondents (y2_1), maintenance
cost on solar system (mcost_1), durability of solar system (d) and numbers of
years of education (edu_2) which is proxy of knowledge and awareness. From the
above findings the overall model is statistically significant.

From the above findings, it is
found that income (y2_1) has positively significant impact on sustainability of
solar system at 10% and 0.000037% change in dependent variable is due to one
unit change in independent variable that is 0.000037% increase in
sustainability of solar system is due to one unit increase income level of
respondents.  Maintenance cost (mcost_1)
has a positive impact on sustainability of solar system and is statistically
significant at 5%.  While 0.00049% change
in dependent variable is due to one unit change in independent variable that is
one unit increase in maintenance cost will bring 0.00049% increase in
sustainability of solar system. Durability (d) has also a positive impact on
sustainability of solar system but is statistically significant and 1.7% change
in dependent variable is due to one unit change in independent variable that is
1.7% increase in sustainability of solar system is due to one unit increase in
durability. And Education (edu_2) has found to be positively insignificant.
This implies that more the people are educated does not have impact on
sustainability of solar energy. 

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