This sample will let you know about:
- Discuss about the Hypothesis Testing.
- Discuss about the Dependent Variable.
Hypothesis Testing
Testing of Hypotheses can be defined as the determination of acceptance or rejection of null hypothesis (H0) and rejection or acceptance of alternate hypothesis (H1) on the basis of statistical evidences. In the context of given research study, the following results have been analyzed in order to determine whether or not the hypotheses constructed are accepted or rejected:
Hypotheses 3: Consumers are more likely to share user generated emotionally branded content
H1: Consumers are more likely to share user generated emotionally branded content
H0: Consumers are more likely to not share user generated emotionally branded content
This particular research study aims to analyse the content marketing tactics which are used by various Instagram users to generate emotionally branded content for their further sharing by their followers on this particular social media platform. Here, it is important to note that employment of content marketing technique is not to increase selling of particular product or service range but to enhance communication. In order to analyse the aforementioned hypotheses, the emotionally branded content which is mainly done by other Instagram accounts is analysed. The given questionnaire which aimed at the collection of primary data included several images on the basis of which various negative and positive emotions were analysed. For this hypotheses test, mainly, information related to images generated by Instagram user accounts were taken into account which were related to Q16, Q19, Q22 and Q25 have been analysed by performing Simple Linear Regression using SPSS. The related data has been interpreted as under:
Model Summary |
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Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
Change Statistics |
|||||
R Square Change |
F Change |
df1 |
df2 |
Sig. F Change |
||||||
1 |
.123a |
.015 |
-.024 |
.364 |
.015 |
.389 |
4 |
101 |
.816 |
|
Predictors: (Constant), Would you share this content?7, Would you share this content?6, Would you share this content?4, Would you share this content?5 |
From the above table it can be ascertained that there is a week positive correlation (R=0.123)has been recorded between consumers and their likeliness to share such content. This means that sharing of emotionally branded content which is mainly user generated is not likely to be impacted much. This is also evidenced through the coefficient of determination(R2=0.015)which is again very weak. Get online coursework help from our experts!
ANOVA |
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Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|||||
1 |
Regression |
.206 |
4 |
.052 |
.389 |
.816b |
||||
Residual |
13.379 |
101 |
.132 |
|||||||
Total |
13.585 |
105 |
||||||||
a. Dependent Variable: Have you ever been emotionally touched by content on Instagram? b. Predictors: (Constant), Would you share this content?7, Would you share this content?6, Would you share this content?4, Would you share this content?5 |
The aforementioned ANOVA Table again asserts a p-value more than 0.05 (p-value = 0.337) which is a clear indicator of the fact that for consumers it does not matter much whether the emotionally branded content is user generated or not.
Coefficients |
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Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||||||||
B |
Std. Error |
Beta |
||||||||||
1 |
(Constant) |
.995 |
.185 |
5.380 |
.000 |
|||||||
Would you share this content?4 |
-.005 |
.090 |
-.005 |
-.050 |
.960 |
|||||||
Would you share this content?5 |
.002 |
.096 |
.003 |
.021 |
.983 |
|||||||
Would you share this content?6 |
.075 |
.076 |
.105 |
.995 |
.322 |
|||||||
Would you share this content?7 |
.037 |
.101 |
.048 |
.368 |
.713 |
|||||||
a. Dependent Variable: Have you ever been emotionally touched by content on Instagram? |
The p-values here also state that there is a significant impact contributed by the statement âwould you share this content?â is less than p-value threshold (p-value = 0.000) which is clear in evidencing that consumers are likely to share content which emotionally touches them. However, it does not matter that such content is generated by user does not matter as all the p-values relating to those images which have been provided in the questionnaire, viz. Q16, Q19, Q22 and Q25 have a p-value more than 0.05.
Hypotheses 4: Consumers are more likely to share company generated emotionally branded content
This hypotheses aims to provide the acceptance or rejection of null hypotheses which has been constructed as under:
Model Summary |
||||||||||
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
Change Statistics |
|||||
R Square Change |
F Change |
df1 |
df2 |
Sig. F Change |
||||||
1 |
.180a |
.032 |
.004 |
.359 |
.032 |
1.139 |
3 |
102 |
.337 |
|
a. Predictors: (Constant), Would you share this content?3, Would you share this content?, Would you share this content?2 |
From the above table it can be observed that
ANOVA |
||||||||||
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|||||
1 |
Regression |
.440 |
3 |
.147 |
1.139 |
.337b |
||||
Residual |
13.145 |
102 |
.129 |
|||||||
Total |
13.585 |
105 |
||||||||
a. Dependent Variable: Have you ever been emotionally touched by content on Instagram? b. Predictors: (Constant), Would you share this content?3, Would you share this content?, Would you share this content?2 |
Coefficients |
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Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||||||||
B |
Std. Error |
Beta |
||||||||||
1 |
(Constant) |
.852 |
.179 |
4.769 |
.000 |
|||||||
Would you share this content? |
.092 |
.073 |
.126 |
1.262 |
.210 |
|||||||
Would you share this content?2 |
.041 |
.090 |
.047 |
.448 |
.655 |
|||||||
Would you share this content?3 |
.055 |
.075 |
.077 |
.739 |
.462 |
|||||||
a. Dependent Variable: Have you ever been emotionally touched by content on Instagram? |
Hypotheses 5 and 6:
In the context of this particular investigation, the branded content, in the context of Instagram specifically, relates to Photo and Video Sharing, Instagram Stories, IGTV and Instagram Live. In order to analyse whether or not males and females are likely to generate emotionally branded content, a cross-tab descriptive analysis has been performed using SPSS. This provides a systematic bifurcation of whether or not content would be shared or not on the basis of gender of respondents and is presented as under:
Would you share this content? * How would you describe gender Crosstabulation |
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Count |
||||||
How would you describe gender |
Total |
Total |
||||
Male |
Female |
|||||
Would you share this content? |
Yes/Maybe |
18 |
27 |
45 |
||
No |
28 |
33 |
61 |
|||
Total |
46 |
60 |
106 |
Hypotheses 5: Are male Instagram users more likely to share emotional branded content?
H1: Male Instagram users more likely to share emotional branded content
H0: Male Instagram users are more likely to not share emotional branded content
Based on the above generated output, it is determined that the null hypotheses (H0)is accepted. This means that the Male Instagram users are more likely to not share emotional branded content. The above research indicates that out of 106 respondents, 46 are male from which 61% of them are more likely to not share such content even though it is branded emotionally.
Hypotheses 6: Are female Instagram users more likely to share emotional branded content?
H1: Female Instagram users more likely to share emotional branded content
H0: Female Instagram users are more likely to not share emotional branded content
Based on the above generated output, it is determined that the null hypotheses (H0) is accepted. This means that female Instagram users who responded to this research study were more likely to not share emotionally branded content. The above research indicates that out of 106 respondents, 60 are female from which 55% of them are more likely to not share such content even though it is branded emotionally.
Thus, in both cases, null hypotheses 5 and 6 are rejected while alternative hypotheses are accepted.
References
- Amiri, S. and Woodside, J. M., 2017. Emerging markets: the impact of ICT on the economy and society. Digital Policy, Regulation and Governance. 19(5). pp.383-396.
- Gomez, R. and Pather, S., 2012. ICT evaluation: are we asking the right questions?.The Electronic Journal of Information Systems in Developing Countries. 50(1). pp.1-14.
- Wastiau, P. and et.al., 2013. The Use of ICT in Education: a survey of schools in E urope.European Journal of Education.48(1). pp.11-27.