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## Questions, Inferences & Findings

Question 1:

The first question in the questionnaire was asked to identify respondent’s gender. The answers are shown in table No.1 and figure.1 below.
Table No.1 Respondents gender
Gender Number of responses Frequency Frequency in percentage
Male 14 0.35 35%
Female 26 0.65 65%
Total 40 1 100%
Source: primary data
Figure.1

Inferences and findings of the first question:
This pie chart shows that we have both gender – male and female- in our respondents. Out of 40 persons were involved in our survey, we had 26 responses from female which represents the majority by 65% of our sample, and 14 responses from male which represents 35% of our sample. Therefore, we can conclude that female have a greater impact on our survey than male.

Question 2:

The second question in the questionnaire was asked to identify respondent’s age group. The answers are shown in table No.2 and figure.2 below.
Table No.2 Respondents age
Age Number of responses Frequency Frequency in percentage
20-29 years old 24 0.60 60%
30-39 years old 6 0.15 15%
40-49 years old 6 0.15 15%
50-59 years old 4 0.10 10%
Greater than 60 years old 0 0.00 0%
Total 40 1 100%
Source: primary data
Figure.2

Inferences and findings of the second question:
This pie chart shows that we have big variety of respondent’s ages. Out of 40 persons were involved in our survey, we had 24 responses from 20 to 29 years old people which represents the majority by 60% of our sample, and 6 responses from 30 to 39 years old people which represents 15% of our sample. Also, we had 6 responses from 40 to 49 years old people which represent 15% of our sample, and 4 responses from 50 to 59 years old people which represent 10% of our sample. However, we had no responses from people who are greater than 60 years old. Therefore, we can conclude that people who are between 20 and 29 years old have a greater impact on our survey than other groups.

Question 3:

The third question in the questionnaire was asked to identify respondent’s monthly income. The answers are shown in table No.3 and figure.3 below.
Table No.3 Respondents monthly income
Monthly Income Number of responses Frequency Frequency in percentage
Less than 3000 SR 18 0.45 45%
3000-5000 SR 9 0.23 23%
5000-7000 SR 1 0.03 3%
7000-9000 SR 3 0.08 8%
More than 9000 SR 9 0.23 23%
Total 40 1 100%
Source: primary data
Figure.3

Inferences and findings of the third question:

This pie chart shows that we have big variety of respondent’s income. Out of 40 persons were involved in our survey, we had 18 respondents who get less than 3000 SR as monthly income which represents the majority by 45% of our sample, and 9 respondents who get between 3000 and 5000 SR which represents 23% of our sample. Also, we had only one respondent who gets between 5000 to 7000 SR which represents 3% of our sample, and 3 respondents who get between 7000 to 9000 SR which represents 8% of our sample. Lastly, we had 9 responses from people who get more than 9000 SR which represents 23% of our sample. Therefore, we can conclude that people who get less than 3000 SR have a greater impact on our survey than other groups.

Q.4 I’m aware of green products and marketing in general
Table No.4
Numbers of Response Frequency Frequency in percentage
Strongly Agree 6 0.15 15%
Agree 16 0.4 40%
Uncertain 10 0.25 25%
Disagree 8 0.2 20%
Strongly Disagree 0 0 0%
Total 40 1 100%
Source: Primary Data

Figure.4

Inference and findings: We asked the respondents if they are aware of green products and marketing in general. 40% agree, 25% are uncertain, 20% disagree, 15% are strongly agreed, and none of them chose strongly disagree. This means that the majority of respondents have knowledge about green products and marketing.

Q.5 It might affect my purchasing intention if I knew that a product is eco-friendly
Table.5
Numbers of Response Frequency Frequency in percentage
Strongly Agree 7 0.175 18%
Agree 18 0.45 45%
Uncertain 5 0.125 13%
Disagree 8 0.2 20%
Strongly Disagree 2 0.05 5%
Total 40 1 100%
Source: Primary Data

Figure.5

Inferences and findings: We asked the respondents if the product is eco-friendly would affect their purchase or not. The chart indicated that 45% agree, 20% disagree, 18% strongly agree, 13% uncertain, and 5% strongly disagree. This means that almost half of respondents will purchase a product if it’s eco-friendly

Q.6 When I go shopping, I prefer buying environmentally friendly products.

Table.6
Numbers of Response Frequency Frequency in percentage
Strongly Agree 7 0.175 18%
Agree 11 0.275 28%
Uncertain 9 0.225 23%
Disagree 13 0.325 33%
Strongly Disagree 0 0 0%
Total 40 1 100%
Source: Primary Data
Figure.6

Inferences and findings: We asked the respondents if they prefer to purchase environmental products or not. The chart indicates that 33% disagree, 28% agree, 23% uncertain, 18% strongly agree, and none of them strongly disagree. Since the majority are disagrees, this means that many of respondents don’t prefer to buy green products.
Question 7: I am motivated to buy green products because I have knowledge about global warming and other environmental concerns.
Table.7
Numbers of Response Frequency Frequency in percentage
Strongly Agree 7 0.175 18%
Agree 14 0.35 35%
Uncertain 8 0.2 20%
Disagree 8 0.2 20%
Strongly Disagree 3 0.075 8%
Total 40 1 100%
Source: Primary Data
Figure.7

Inference and findings: We asked the respondents if they motivated to buy green products because I have knowledge about global warming and other environmental concerns. 35% agree, 20% are uncertain, 20% disagree, 18% are strongly agreed, and 8% strongly disagree.

Table.8
Numbers of Response Frequency Frequency in percentage
Strongly Agree 23 0.575 58%
Agree 8 0.2 20%
Uncertain 4 0.1 10%
Disagree 5 0.125 13%
Strongly Disagree 0 0.0 0%
Total 40 1 100%
Source: Primary Data
Figure.8

Inference and findings: We asked the respondents if the companies need to make more advertisements to aware consumer about their green products. 20% agree, 10% are uncertain, 13% disagree, 58% are strongly agreed, and none of them are strongly disagree.

Question 9: It would motivate me to buy a green product if it has a clear green labeling (example: this material is recyclable).
Table.9
Numbers of Response Frequency Frequency in percentage
Strongly Agree 10 0.25 25%
Agree 20 0.5 50%
Uncertain 8 0.2 20%
Disagree 2 0.05 5%
Strongly Disagree 0 0.0 0%
Total 40 1 100%
Source: Primary Data

Figure.9

Inference and findings: We asked the respondents if It would motivate me to buy a green product if it has a clear green labeling (example: this material is recyclable). 50% agree, 20% are uncertain, 5% disagree, 25% are strongly agreed, and none of them are strongly disagree.

J number of respondents frequency frequency in%
Strongly Agree 0 0 0.00%
Agree 7 0.175 17.50%
Uncertain 9 0.225 22.50%
Disagree 17 0.425 42.50%
Strongly Disagree 7 0.175 17.50%
Total 40 1 100.00%

Conclusion of the tenth question:
From the above bar chart, it can be observed that none of the respondents strongly agree ,17.5% agreed, 22.5% are uncertain, 42.5% disagreed , and 17.5% strongly disagreed that increase in the price won’t defect their buying behavior.

K number of respondents frequency frequency in%
Strongly Agree 12 0.3 30%
Agree 19 0.475 48%
Uncertain 5 0.125 13%
Disagree 3 0.075 8%
Strongly Disagree 1 0.025 3%
Total 40 1 100%

Conclusion of the eleventh question:

From the above bar chart, it can be observed that 30% of the respondents strongly agree ,48% agreed, 13% are uncertain, 8% disagreed , and 3% strongly disagreed that the most restrictions regarding green product are expensive and limited availability.

L number of respondents frequency frequency in%
Strongly Agree 4 0.1 10%
Agree 14 0.35 35%
Uncertain 6 0.15 15%
Disagree 12 0.3 30%
Strongly Disagree 4 0.1 10%

Conclusion of the twelfth question:

From the above bar chart, it can be observed that 10% of the respondents strongly agree ,35% agreed, 15% are uncertain, 30% disagreed , and 10% strongly disagreed that the they consider the effect on the environment as a consumer before purchasing general daily products.