Introduction
Of late media has become popular as many people has access to both smart phones and internet. Many people access internet for various reasons which may include and not limited to: education, entertainment, connecting with friends and relatives. These makes internet a source of numerous information. Besides these, internet forms a place where a seller can meet the buyer or the buyer meets the promoter who can influence them to buy a certain product or a certain line of products. (Kreutzer, 2012) (Viglia, 2014)
Today many business people meet their customers online, but since most customers do not go online to check products, they access internet for other reasons, sellers has come with ways in which they can be lured to check a certain product or read about it as the customer browse through the internet.
Most of the people do have celebrities who they follow both online and offline. They are fanatics of them to a level where they will try to associate with them in any way. How they walk, eat, dress, where they eat and many more. They see these celebrities as their idols and role models as the same time. This has made it easy for the sellers to use such celebrities to sell their products. They believe that if the fans see a their celeb putting on a certain cloth, eating a certain food in a given restaurant, drive a certain car, everyone associated with them will try to emulate them hence bringing about the sales of the product. (Maria Arbatskaya, 2004) (Yehoshua Liebermann, 2009)
Social media form the basis through which all these magic happens. The celebrities happens to be followed by many peoples, of which many are his fans. They can post a photo with a certain cloth, eating or standing next to a car. There is likely that many people who are following them in social media can be influenced and start living their lifestyle prompting them to buy the same products. The celebrities can also be used when launching a new product in the market. Since they are followed by many people, the product launch by them can reach many people after a short period of time. (Chan, 2011)
Social media such as Facebook, instagram, snapchat, youtube, blogs etc play a major role in doing all these. They form the major medium where many people visit whenever they can access to the internet. They see the new trends, news, meet friends and get to see what their friends have posted. While they do all these, they will see what has also been posted on the time timelines of the celebrities they follow. (Ceyp, 2013)
Scope of the study
The study targeted the consumers of the Singaporeans who are believed to be able to access internet in one way or the other.
Objective of the study
The main objective of the survey is to study the effectiveness of the broadcast media on the attitudes and behavior of the Singaporean customers.
Specific objectives
To study how the followers of influencers are affected on their choice of products by their influencers
To study some of the reasons why some people follow celebrities
To study the most relevant credibility for the reason of some fans following their influencers
To study some of the reasons that influence someone to go for a certain fashion
Data collection
Data was collected using the questionnaires with the closed ended questions. The questions were majorly covers the areas of interest in line with the laid objectives.
Data analysis
Data was analyzed using SPSS. The data was entered into Excel then imported into SPSS for proper analysis. We mainly focused on the descriptive statistics, cross tabulation and test statistics.
Hypothesis testing
Our null hypothesis for the study was: there is no effectiveness of broadcast media on attitude and behavior of Singaporean customers.
Alternative hypothesis was: there is effectiveness of broadcast media on the attitude and behavior of Singaporean customers
The following are the findings from the data collected
Age
On the age of the respondents; 17.2% (n=21) were between the age of 18-20 years, 67.2% (n=82) were between the age of 21-26 years, 13.9% (n=17) were between the age of 27-32 years and 1.6% (n=2) were 33 years and above as shown below.
Table 1 Age of the respondents
|
Frequencies |
Percent |
|
|
18-20 |
21 |
17.2 |
|
21-26 |
82 |
67.2 |
|
27-32 |
17 |
13.9 |
|
33 and above |
2 |
1.6 |
|
Total |
122 |
100.0 |
Gender
On the gender; 70.5% (n=86) were female while 29.5% (n=36) were male
Table 2Gender
|
Frequency |
Percent |
|
|
Male |
36 |
29.5 |
|
Female |
86 |
70.5 |
|
Total |
122 |
100.0 |
Employment status
On their employment status; 74.6% (n=91) were employed full time, 16.4% (n=20) were employed part time, both unemployed and self-employed had 3.3% (n=4), 1.6% (n=2) were students while 0.8% (n=1) was taken by apprenticeship.
Table 3. Employment status
|
Frequency |
Percent |
|
|
Employed full time |
91 |
74.6 |
|
Employed part time |
20 |
16.4 |
|
Unemployed |
4 |
3.3 |
|
Self employed |
4 |
3.3 |
|
Student |
2 |
1.6 |
|
Apprenticeship |
1 |
0.8 |
|
Total |
122 |
100.0 |
Site visited frequently
On the site visited frequently; 31.2% (n=107) said they frequently visit Instagram, 28.9% (n=99) frequently visited YouTube, 25.1% (n=86) frequently visited Facebook, 8.5% (n=29) frequently visited Twitter, 3.8% (n=13) frequently visited Dyre, 0.6% (n=2) frequently visited Snapchat, 1.7% (n=6) frequently visited Blog while 0.3% (n=1) visited reddit.
Table 4. Sites visited frequently
|
Frequency |
Percent |
|
|
|
107 |
31.2 |
|
YouTube |
99 |
28.9 |
|
|
86 |
25.1 |
|
|
29 |
8.5 |
|
Dyre |
13 |
3.8 |
|
Snapchat |
2 |
0.6 |
|
|
1 |
0.3 |
|
Blog |
6 |
1.7 |
|
Total |
343 |
100.0 |
Subscribed sites
On the subscribed sites to follow celebrities or popular accounts; 31.1% (n=102) subscribed to Instagram, 32.0% (n=105) subscribed to YouTube, 24.4% (n=80) subscribed to Facebook, 10.7% (n=35) subscribed to Twitter, 0.6% (n=2) subscribed to Lifestyle blogs while 1.2% (n=4) did not subscribed to any of the above.
Table 5. Subscribed sites to follow celebrities or popular accounts
|
Frequency |
Percent |
|
|
|
102 |
31.1 |
|
YouTube |
105 |
32.0 |
|
|
80 |
24.4 |
|
|
35 |
10.7 |
|
Lifestyles blogs |
2 |
0.6 |
|
None of the above |
4 |
1.2 |
|
Total |
328 |
100.0 |
Agreeing with the statements
On how they agree with statements:
On whether they find new trends on social media; 23.8% (n=29) strongly agreed, 50% (n=61) agreed, 19.7% (n=24) were not sure, 2.5% (n=3) disagreed while 4.1% (n=5) strongly disagreed.
On the statement on whether they make purchases on recommendations of online influencers; 9.8% (n=12) strongly agreed, 41% (n=50) agreed, 36.9% (n=45) were not sure, 10.7% (n=13) disagreed while 1.6% (n=2) strongly disagreed.
On the statement whether they read online review often; 33% (n=27) strongly agreed, 50.8% (n=62) agreed, 13.9% (n=17) were not sure, 3.3% (n=4) disagreed while 4.9% (n=6) strongly disagreed.
On the statement on whether if the influencer they follow recommend a brand they are likely to try it; 9.8% (n=12) strongly agreed, 41.8% (n=51) agreed, 36.9% (n=45) were not sure, 9% (n=11) disagreed while 2.5% (n=3) strongly disagreed.
Table 6. Agreeing with the following statements
|
Strongly disagree |
Disagree |
Neutral |
Agree |
Strongly agree |
Total |
|
|
I find new trends on social media |
5(4.1%) |
3(2.5%) |
24(19.7%) |
61(50%) |
29(23.8%) |
122 |
|
I make purchases based on recommendations of online influencers |
2(1.6%) |
13(10.7%) |
45(36.9%) |
50(41%) |
12(9.8%) |
122 |
|
I read online reviews often |
6(4.9%) |
4(3.3%) |
17(13.9%) |
62(50.8%) |
33(27%) |
122 |
|
If the influencers I follow recommend a brand, I am more likely to try it. |
3(2.5%) |
11(9%) |
45(36.9%) |
51(41.8%) |
12(9.8%) |
122 |
Perception on online influencers
On the statement regarding their perception on online influencers:
On whether the influencers will give honest reviews; 0.8% (n=1) strongly agreed, 28.6% (n=35) agreed, 43.4% (n=53) were not sure, 23.8% (n=29) disagreed while 3.3% (n=4) strongly disagreed.
On the statement on whether their favorite influencer paid for endorsement would not negatively impact their perception of their credibility; 3.3% (n=4) strongly agreed, 39.3% (n=45) agreed, 42.6% (n=52) were not sure, 15.6% (n=19) disagreed while 1.6% (n=2) strongly disagreed.
On the statement whether their peer reviews are more trustable than online influencers; 19.7% (n=24) strongly agreed, 40.9% (n=50) agreed, 33.6% (n=41) were not sure, 5.7% (n=7) disagreed while 0.0% (n=0) strongly disagreed.
On the statement on whether their influencers wear a certain sponsored clothing brand to get free clothes in return; 4.9% (n=6) strongly agreed, 44.3% (n=54) agreed, 44.3% (n=54) were not sure, 6.6% (n=8) disagreed while 0.0% (n=0) strongly disagreed.
Table 7. Statements regarding the perception on online influencers
|
Strongly disagree |
Disagree |
Neutral |
Agree |
Strongly agree |
Total |
|
|
Influencers will only give their honest reviews |
4(3.3%) |
29(23.8%) |
53(43.4%) |
35(28.6%) |
1(0.8%) |
122 |
|
If my favorite influencer is paid for their endorsement, it would not negatively impact my perception of their credibility |
2(1.6%) |
19(15.6%) |
52(42.6%) |
45(39.3%) |
4(3.3%) |
122 |
|
Peer reviews are more trustable than online influencer reviews |
0 |
7(5.7%) |
41(33.6%) |
50(40.9%) |
24(19.7%) |
122 |
|
Influencers always wear a certain sponsored clothing brand to get free clothes in return |
0 |
8(6.6%) |
54(44.3%) |
54(44.3%) |
6(4.9%) |
122 |
What influence purchase
On what influences them most when purchasing fashion item; 45.1% (n=106) said sales promotion and discounts influences them most as 28.5% (n=67) are mostly influenced by trends while 26.4% (n=62) were mostly influenced by peer recommendations.
Table 8. What influence purchase
|
Frequency |
Percent |
|
|
Sales promotion and discounts |
106 |
45.1 |
|
Peer recommendations |
62 |
26.4 |
|
Trends |
67 |
28.5 |
|
Total |
235 |
100.0 |
How often purchase of clothing is done under influence of influencers
On how often they purchase the clothing items under the influence of influencers; 15.6% (n=19) said they often purchase clothing item, 36.1% (n=44) said they sometimes purchase clothing items, 32% (n=39) said they rarely purchase clothing item, 16.4% (n=20) said they never purchase clothing item under the influence of influencers.
Table 9.How often purchase of clothing is done under influence of influencers
|
Frequency |
Percent |
|
|
Often |
19 |
15.6 |
|
Sometimes |
44 |
36.1 |
|
Rarely |
39 |
32.0 |
|
Never |
20 |
16.4 |
|
Total |
122 |
100.0 |
Credibility of influencers
On the credibility of the influencers; 33.6% (n=41) find their influencers personality to be the most relevant credibility, 36.9% (n=45) find that the most relevant credibility of their influencers is because they share similar interest, 20.5% (n=25) find their frequent audience engagement to be the most relevant in the credibility of their influencers while 9% (n=11) found that the most relevant owing to the credibility of their influencers is the number of followers they have.
Table 10. Credibility of influencers
|
Frequency |
Percent |
|
|
Their personality |
41 |
33.6 |
|
Share similar interest |
45 |
36.9 |
|
Frequent audience engagement |
25 |
20.5 |
|
Number of followers |
11 |
9.0 |
|
Total |
122 |
100.0 |
Reason for following influencers
On the reasons why they follow their influencers; 29.9% (n=76) follow their influencers because of the fashion (clothing and accessories), 23.6% (n=60) follow their influencers due to their beauty (makeup), 22.4% (n=57) follow their influencer due to their travel inspiration, 21.7% (n=55) follow their influencers due to the food they eat while 0.4% (n=1) follow their influencers due to their hobby, news, lifestyle, games, IT appliances and even none.
Table 11. Reason for following influencers
|
Frequency |
Percent |
|
|
Beauty (makeup) |
60 |
23.6 |
|
Fashion (clothing, accessories) |
76 |
29.9 |
|
Travel inspirations |
57 |
22.4 |
|
Food |
55 |
21.7 |
|
News |
1 |
0.4 |
|
Hobby |
1 |
0.4 |
|
Lifestyle |
1 |
0.4 |
|
Games |
1 |
0.4 |
|
IT appliances |
1 |
0.4 |
|
None |
1 |
0.4 |
|
Total |
254 |
100.0 |
Brands
On whether they are particular on the brand they purchase, 50.8% (n=62) said they are particular on the brand they purchase while 49.2% (n=60) said they are not particular on the brand they purchase.
Table 12. Being particular on the brand
|
Frequency |
Percent |
|
|
Yes |
62 |
50.8 |
|
No |
60 |
49.2 |
|
Total |
122 |
100.0 |
CROSS TABULATION BETWEEN SOME IMPORTANT SELECTED VARIABLES
|
Count |
|||||||
|
What are your perceptions of online influencers? [If my favorite influencer is paid for their endorsement, it would not negatively impact my perception of their credibility.] |
Total |
||||||
|
Strongly disagree |
Disagree |
Neutral |
Agree |
Strongly agree |
|||
|
Which of the following online sites do you visit frequently? (Tick all that apply) |
|
1 |
3 |
3 |
17 |
9 |
33 |
|
Youtube |
0 |
3 |
1 |
21 |
6 |
31 |
|
|
|
0 |
1 |
3 |
26 |
11 |
41 |
|
|
|
0 |
4 |
2 |
8 |
4 |
18 |
|
|
Total |
1 |
11 |
9 |
62 |
29 |
122 |
|
Chi-Square Tests |
|||
|
Value |
df |
Asymptotic Significance (2-sided) |
|
|
Pearson Chi-Square |
1.143a |
2 |
.565 |
|
Likelihood Ratio |
1.530 |
2 |
.465 |
|
Linear-by-Linear Association |
.143 |
1 |
.705 |
|
N of Valid Cases |
122 |
|
Symmetric Measures |
|||||
|
Value |
Asymptotic Standardized Errora |
Approximate Tb |
Approximate Significance |
||
|
Interval by Interval |
Pearson’s R |
.143 |
.158 |
.354 |
.736c |
|
Ordinal by Ordinal |
Spearman Correlation |
.181 |
.185 |
.450 |
.668c |
|
N of Valid Cases |
122 |
||||
|
a. Not assuming the null hypothesis. |
|||||
|
b. Using the asymptotic standard error assuming the null hypothesis. |
|||||
|
c. Based on normal approximation. |
|
Count |
|||||||
|
What are your perceptions of online influencers? [Influencers always wear a certain sponsored clothing brand to get free clothes in return] |
Total |
||||||
|
Strongly disagree |
Disagree |
Neutral |
Agree |
Strongly agree |
|||
|
How much do you agree with the following statements? [I find new trends on social media] |
Strongly disagree |
1 |
4 |
3 |
7 |
1 |
16 |
|
Disagree |
4 |
3 |
5 |
9 |
4 |
25 |
|
|
Neutral |
3 |
3 |
4 |
15 |
3 |
28 |
|
|
Agree |
4 |
3 |
6 |
23 |
6 |
42 |
|
|
Strongly agree |
3 |
4 |
2 |
10 |
2 |
21 |
|
|
Total |
15 |
17 |
20 |
54 |
16 |
122 |
|
Chi-Square Tests |
|||
|
Value |
df |
Asymptotic Significance (2-sided) |
|
|
Pearson Chi-Square |
7.000a |
8 |
.537 |
|
Likelihood Ratio |
8.318 |
8 |
.403 |
|
Linear-by-Linear Association |
3.153 |
1 |
.076 |
|
N of Valid Cases |
122 |
||
|
a. 15 cells (100.0%) have expected count less than 5. The minimum expected count is .25. |
|
Value |
Asymptotic Standardized Errora |
Approximate Tb |
Approximate Significance |
||
|
Interval by Interval |
Pearson’s R |
.671 |
.150 |
2.218 |
.068c |
|
Ordinal by Ordinal |
Spearman Correlation |
.668 |
.158 |
2.198 |
.070c |
|
N of Valid Cases |
122 |
||||
|
a. Not assuming the null hypothesis. |
|||||
|
b. Using the asymptotic standard error assuming the null hypothesis. |
|||||
|
c. Based on normal approximation. |
The mean and standard deviation of the different variables
|
N |
Min |
Max |
Mean |
Std. Dev |
|
|
What is your age group |
122 |
1 |
4 |
1.88 |
.354 |
|
What is your gender |
122 |
1 |
2 |
1.00 |
0.000 |
|
Which of the following best describes your current employment status? |
122 |
1 |
5 |
1.88 |
.354 |
|
Which of the following online sites do you visit frequently? |
122 |
3 |
6 |
3.13 |
.354 |
|
Which of the following sites you subscribed to follow celebrity or popular accounts? |
122 |
1 |
5 |
3.13 |
1.126 |
|
I find new trends on social media |
122 |
1 |
5 |
3.38 |
1.408 |
|
I make purchases based on recommendations of online influencers |
122 |
1 |
5 |
3.38 |
1.408 |
|
I read online reviews often |
122 |
1 |
5 |
4.00 |
.756 |
|
If the influencers I follow recommend a brand, I am more likely to try it. |
8 |
3 |
5 |
3.63 |
.744 |
|
Influencers will only give their honest reviews |
8 |
1 |
3 |
2.38 |
.744 |
|
If my favorite influencer is paid for their endorsement, it would not negatively impact my perception of their credibility. |
122 |
1 |
5 |
2.75 |
.707 |
|
Peer reviews are more trustable than online influencer reviews |
122 |
1 |
5 |
4.13 |
.641 |
|
Influencers always wear a certain sponsored clothing brand to get free clothes in return |
122 |
1 |
5 |
3.00 |
.756 |
|
Which of the following influence you most when purchasing fashion items? |
122 |
1 |
4 |
2.13 |
1.126 |
|
How often do you purchase clothing items under the influence of influencers? |
122 |
1 |
4 |
2.38 |
.916 |
|
Which of the following do you find the most relevant in the credibility of an influencer’s given opinion/review? |
122 |
1 |
4 |
1.88 |
.641 |
|
What do you usually follow the influencers for? |
122 |
1 |
4 |
2.50 |
1.414 |
|
Are you particular about the brands that you purchase? |
8 |
1 |
2 |
1.38 |
.518 |
TESTING THE DIFFERENCE
|
What are your perceptions of online influencers? [Influencers will only give their honest reviews ] |
Statistic |
Bootstrapc |
|||||
|
Bias |
Std. Error |
95% Confidence Interval |
|||||
|
Lower |
Upper |
||||||
|
What is your age group |
Strongly disagree |
N |
1 |
||||
|
Mean |
1.00 |
.00d |
.00d |
1.00d |
1.00d |
||
|
Std. Deviation |
1.798E+308f |
.000f |
.000f |
.000f |
|||
|
Std. Error Mean |
|||||||
|
Disagree |
N |
3 |
|||||
|
Mean |
2.00 |
.00e |
.00e |
2.00e |
2.00e |
||
|
Std. Deviation |
0.000 |
.000g |
.000g |
.000g |
.000g |
||
|
Std. Error Mean |
0.000 |
|
Levene’s Test for Equality of Variances |
t-test for Equality of Means |
|||||||||
|
F |
Sig. |
t |
df |
Sig. (2-tailed) |
Mean Difference |
Std. Error Difference |
95% Confidence Interval of the Difference |
|||
|
Lower |
Upper |
|||||||||
|
What is your age group |
Equal variances assumed |
2 |
-1.000 |
0.000 |
-1.000 |
-1.000 |
||||
|
Equal variances not assumed |
-1.000 |
|
Mean Difference |
Bootstrapa |
|||||
|
Bias |
Std. Error |
95% Confidence Interval |
||||
|
Lower |
Upper |
|||||
|
What is your age group |
Equal variances assumed |
-1.000 |
.000b |
.000b |
-1.000b |
-1.000b |
|
Equal variances not assumed |
-1.000 |
.000b |
.000b |
-1.000b |
-1.000b |
References
Ceyp, M. S. J.-P., 2013. Erfolgreiches Social Media Marketing || Stellenwert von Social Media Marketing im Rahmen der Unternehmenskommunikation.
Chan, N. L. G. B. D., 2011. Investigation of Social Media Marketing: How Does the Hotel Industry in Hong Kong Perform in Marketing on Social Media Websites?. : How Does the Hotel Industry in Hong Kong Perform in Marketing on Social Media Websites, p. 24.
Kreutzer, R. T., 2012. Praxisorientiertes Online-Marketing || Instrumente des Online-Marketings. p. 337.
Maria Arbatskaya, M. R. B., 2004. Are prices ‘sticky’ online? Market structure effects and asymmetric responses to cost shocks in online mortgage markets. p. 20.
Viglia, G., 2014. Pricing, Online Marketing Behavior, and Analytics || Online Marketing Communication Channels. p. 17.
Yehoshua Liebermann, S. S., 2009. Determinants of online shopping: Examination of an early-stage online market. Examination of an early-stage online market, p. 16.
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