International Journal of Management Science and Business Administration
Volume 6, Issue 4, May 2020, Pages 30-41
The Influence of Social Media Applications on Youth Purchasing Decision at the University of Jordan
DOI: 10.18775/ijmsba.1849-5664-5419.2014.64.1003
URL: http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.64.1003
1 Basma Shamieh, 2 Mohamad Shehada
1 2 Talal Abu-Ghazaleh University College for Innovation, Jordan
Abstract: The research aims to find out “The Influence of Social Media Applications on Youth Purchasing Decision at the University of Jordan”. The data was collected using an online questionnaire. The questionnaire was distributed to a sample of 100 students at the University of Jordan via WhatsApp and Facebook pages. The response rate consisted of 88 respondents and the valid ones were 81. Statistical analysis was performed using Statistical Package for Social Sciences (SPSS) to find out the influence of social media applications on the youth purchasing decisions. The paper finds that there is a significant influence of the popular used social media applications (Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp) on the youth purchasing decisions at the University of Jordan.
Keywords: Social media applications, Purchasing decisions, Facebook, WhatsApp, Instagram, Snapchat, Twitter, YouTube
The Influence of Social Media Applications on Youth Purchasing Decision at the University of Jordan
1. Introduction
Social media is very popular with high usage rates among adult users worldwide, especially in Jordan. According to global research conducted by the “Pew Research Center” in 2018, social media usage is increasing in the developing countries, and Jordan was ranked number in terms social networking sites adult users, amounting to 75% (Pew Research Center, 2018). As Jordan is experiencing “youth bulge”, and the median age is 23, youth population using social media is increasing. There are many research papers wrote about social media. However, there is still a need to investigate their effectiveness as a tool influencing the youth purchasing decisions.
1.1 Research Model
Hypothesis:
Ho: There is no significant influence of the popular social media applications (Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp) on the youth purchasing decisions at the University of Jordan, at (0=0.5).
HO1: the Facebook application has no significant influence on the youth purchasing decisions at the University of Jordan, at (0=0.5).
HO2: the Instagram application has no significant influence on the youth purchasing decisions at the University of Jordan, at (0=0.5).
-HO3: the Snapchat application has no significant influence on the youth purchasing decisions at the University of Jordan, at (0=0.5).
HO4: the Twitter application has no significant influence on the youth purchasing decisions at the University of Jordan, at (0=0.5).
HO5: YouTube application has no significant influence on the youth purchasing decisions at the University of Jordan, at (0=0.5).
HO6: WhatsApp application has no significant influence on the youth purchasing decisions at the University of Jordan, at (0=0.5).
HO7: The influence of social media applications on the youth purchasing decisions makes no difference in terms of demographic factors (age, gender, and nationality) at the University of Jordan, at (0=0.5)
2. Literature Review
2.1 Social Media Applications
Social media is defined in Merriam-Webster, as “forms of electronic communication, such as websites for social networking and microblogging, through which users create online communities to share information, ideas, personal messages, and other content such as videos” (Merriam-Webster, 2004). Social media have been defined in a variety of ways. Terrell describes them as, “the different forms of online communication used by people to create networks, communities, and collectives to share information, ideas, messages, and other content, such as videos” (Terrell K., 2015).
Although social media seems like a new trend, it is thought to have emerged from the evolution of the internet in the 1970s (Terrell K., 2015). In his article “Complete History of Social Media”, Hendricks states that “Six Degrees” was the first social media site to be created in 1997, which enabled people to connect with other users. Terrell also confirms that Six Degrees was the first social media site that was launched in 1997 and lasted until 2001 (Terrell K., 2015). Following it, in 1999, the first blogging site was created, and it remains relevant. After that, Social media exploded became hit after sites like Myspace and LinkedIn were developed in the early 2000s. Many other social media sites became popular, such as YouTube, Facebook, Twitter, and Tumbler. Today, there is a wide variety of social networking sites and applications where users can communicate with other users and reach a large number of people easily (Hendricks D., 2013).
There is a wide range of social media applications available. Some are used for messaging, such as WhatsApp. Others are Profile-based platforms such as Facebook and LinkedIn, or video portals like YouTube and Email Clients such as Gmail (Terrell K., 2015).
As the youth aged 12-30 makes up for one-third (30%) of Jordan population, OECD estimates it will remain to have a predominantly young population in the coming years (OECD Development Centre, 2018). Social media is considered fashionable, especially among adult users. For example, according to global research made by the “Pew Research Center” in 2018, social media usage is increasing in the developing countries and Jordan was ranked number one by the number of adult users, with a percentage of 75%. Moreover, across 39 countries included in the research, a global median of 53% showed they use social networking sites like Facebook or Twitter, while users in Jordan mainly use Facebook, Twitter, or Instagram. According to the study, as Jordan is experiencing “youth bulge”, with the median age of 23, a significant proportion of social media users are young adults (Pew Research Center, 2018). Therefore, in this research, we will study the impact of most popular social media applications among the youth nowadays, e.g. Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp.
Facebook is considered to be the largest social media networking site and, to some extent, the most widely used platform worldwide, including Jordan. According to NapoleonCat website, there were 5,800,000 registered Facebook users in Jordan in 2019. Most of them were aged 25 to 35, followed by the second largest population of users aged 18 to 24 (Napoleoncat, 2019), meaning, most users were young adults. Facebook was founded by Mark Zuckerberg, Eduardo Saverin, Andrew McCollom, Dustin Moskovitz, and Chris Hughes in 2004. It was initially designed to be a social media site exclusively for Harvard students. Then, after 2006, Facebook became available to anyone above the age of 13. Facebook grew fast and is indeed believed to be the most visited site worldwide. (Terrell K., 2015). According to an article published in the Jordan Times, Facebook was ranked as the most frequently used website in 2016 (Jordan Times, 2016).
Instagram was launched in 2010 by Kevin Systrom and Mike Krieger. This application was restricted to sharing photos and videos framed in a square. In the beginning, Systrom and his partner decided to create an application differing from other social media applications. They took off all features and left uploading photos/ videos, commenting, and liking. (Eudaimonia, 2017). Instagram also grew fast, “surpassing one million registered users in just two months“, and became the number one photography application reaching 1 billion active users in 2015 (Terrell K., 2015). According to NapoleonCat website, there were 1970, 600 Instagram users in Jordan in 2019. The largest group of users was also aged between 18 to 24 (Napoleoncat, 2019), meaning most of Instagram users are young adults.
Snapchat was started by Evan Spiegel, Bobby Murphy, and Reggie Brown in 2011. This application has a unique feature allowing its users to send photos, which disappear after a maximum of 10 seconds upon accessing. Recently, Snapchat has improved its features and allowed users to chat and share photo/video stories available for 24 hours. Although this application is popular among youth, it is believed that Snapchat will have a significant impact on its users in the future (Terrell K., 2015).
Twitter was created in 2006 by Jack Dorsey, Noah Glass, Biz Stone, and Evan Williams. It has the distinguishing feature of limiting users’ posts to 140 characters. However, after 2017 the application doubled characters limit. Twitter became popular in 2013 and had around 335 million monthly active users in 2015 (Terrell K., 2015).
YouTube, the world most popular online video community, was founded in 2005 by Chad Hurley, Steve Chen, and Jawed Karim, and more than 20 employees in PayPal, to share videos with their friends (Heldman C., 2009). After the launch in 2006, YouTube was acquired by Google Incorporate (Edosomwan S. O., 2011). YouTube is a site that helps people across the globe connect, share information, inspiration, or entertainment. It is considered to be the platform for video content creators, advertisers, or marketers (Edosomwan S. O., 2011).
WhatsApp messenger was created by Brian Acton and Jan Koum in 2009. It helps people communicate and share multimedia messaging more efficiently, faster and cheaper. An individual can contact friends and family all around the world using WhatsApp free of typical SMS charges. (Yeboah J., 2014).
2.2 Purchase Decision
The term “purchase decision” has many different definitions. Generally it refers to the decisions regarding choosing or obtaining a product (Jaakkola E., 2007). According to Philip Kotler and Sidney J. Levy, a purchase decision signifies a behavior exhibited by decision-making individuals to buy, use, and set goods and services (Kotler P., 1969). In other words, purchase decision refers to the action of evaluating, acquiring, or use disposing of products and services (Ngoc M., 2016). Stankevich Also defined customer behaviour as “the process by which individuals search for, select, purchase, use, and dispose of goods and services, in satisfaction of their needs and wants” (Stankevich A., 2017). Stankevich also mentioned another definition of other authors about consumer behaviour “the study of individuals process to select, secure, use, and dispose of products, to satisfy needs impacting consumer and society” (Stankevich A., 2017).
Alek Flekel explained the five steps of the decision-making process. First, “a need or a want is recognized, search process, comparison, product or service selection, and evaluation of decision” (Flekel A., 2013). The instructor JC Wright explained in his lesson “Purchase Decision: Definition and Hierarchy” that there are “five stages of consumer purchase decision-making, namely: Problem/need recognition, Information search, evaluation of alternatives, purchase decision, and post-purchase behaviour” (Purchase Decision: Definition and Hierarchy, 2013).
Kardes et al., explain the five steps for the consumer decision-making process as the Central part of consumer behaviour. First, recognition occurs when a consumer recognizes a need for a product or service. Second, information search includes searching for information about the goods checking different sources such as friends or family, commercials, media, etc. Third, Evaluation of Alternative relates to evaluating the goods or products alternatives to ensure the correct choice. Fourth, purchase decisions refer to the decision to buy the product after being subjected to others’ attitudes or situational factors. Lastly, post-purchase decisions refer to consumer’s act of determining satisfaction or dissatisfaction with the product being purchased. (Kardes, et al., 2011) as cited in ( (Darban A. and Li, 2012).
Customers are exposed to varieties of product choices that increase their purchase decisions. Although decision-making differs among individuals, it is also influenced by customer behaviour factors (Gizaw A., 2014).
Knowledge about purchase decision making is essential as every person is engaged in this process daily. Everyone falls into a category of purchase decisions making customer. Therefore, it is important to identify factors influencing people’s buying decisions. Marketers can benefit from this study as it will help them target customers more effectively and improve their business plan and meet their goals (Ngoc M., 2016).
2.2.1 Social Media Influence on Youth Purchase Decision
Nowadays, with an increase in technology usage can identify consumers’ needs without asking. Technology and social media applications are part of people lives, which made them focus on marketers’ attention (Stankevich A., 2017). As the Johnson states in his article “What’s the biggest influence in consumer Purchase Decisions?” Many businesses turned to social media applications to influence consumers buying decisions and gain more customers. Also, it is crucial to consider that the youth are the key social media audience nowadays. They consume content from different social media platforms. It is vital for marketers to consider how this demographic consumes information and how to reach them through the right marketing way, he added (Johnson W., 2014)
In a study conducted on a sample of undergraduate students at two Southern universities, Pate et al. found that social networking sites and posts made by their friends using these sites influence respondents aged 18 to 24. Authors assure that “Participants would be more likely to purchase items “liked” by “friends” on social networking sites” (Pate et al., 2013). They also state that “When reviewing the frequency of the purchases of items “liked” by “friends”, the majority of respondents purchased 1– 5 items” (Pate et al., 2013)
The idea that social media influences the buying behaviour of the customers is confirmed recently by Sangurde R. in 2019. The sample of his research targeted the youth in Mumbai and out of the 233 respondents, 122 agree that social media influence their buying decision. Moreover, 127 of the youth showed that they are using social media for shopping, among other purposes (Sangurde R., 2019).
According to a study made by Alzyoud M. in 2018 conducted on the sample of 400 female social media users in Jordan, the results of the questionnaire show that social media marketing has a significant impact on buyer behaviour, making them more willing to buy from online sources as a result of online advertisements (Alzyoud M. F., 2018).
On the other hand, Alnsour M. explored more deeply the effect of social media benefits on the customer buying intention. He classified benefits into five categories, “functional, monetary, hedonic, psychological and social benefits of social media” and analyzed their influence on buying intention when buying online tickets from Jordanian airline companies. Alnsour conducted a study of 311 respondents in Amman, and the results state that the hedonic and monetary benefits have the most substantial influence on buying intentions of customers (Alnsour M., 2018).
University of Jordan
The University of Jordan (UJ) was established in 1962. It is considered the largest university in Amman, Jordan. It provides a variety of academic programs for students around the world. According to the University of Jordan’s official website, it “offers 250 programs from 24 schools in various disciplines. UJ offers 94 bachelors in different programs in Medicine, Dentistry, Pharmacy, Nursing, Rehabilitation Science, Science, Agriculture, Engineering, Information Technology, Art, Business Administration, Shari’a, Educational Sciences, law, Physical Education, Arts and Design, International Studies, Foreign Languages, Archaeology and Tourism”. (The University of Jordan, 2019). Moreover, UJ provides 38 doctoral programs, 111 master programs, 16 higher specialization programs and three diploma programs” (The University of Jordan, 2019).
The number of students at the University of Jordan is approximately 45,000 (Wikipedia, 2019).
3. Research Methodology
3.1 Nature of the Research
This study follows a descriptive and analytical approach where information is classified. Variables related to social media applications, purchase decisions, and the University of Jordan are identified by referring to previous studies and history. Data for the literature review were collected through online resources containing published books, journals, and websites. The research also follows the quantitative approach by conducting an online questionnaire to collect data from a sample of the University of Jordan students. A bilingual online questionnaire in English and Arabic was sent via WhatsApp to Jordan University students’ groups and posted on Facebook. The questionnaire contained three demographic factors (gender, age, and nationality). 5-point Likert scale (Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree) was used to classify the answers. After excluding the invalid questionnaire, a statistical analysis is made using the Statistical Package for Social Sciences (SPSS) to analyze the descriptive statistics and performing regression and T-Tests to test the model hypothesis.
3.2 Population and Sample of the Study
The population of this study are the University of Jordan students amounting to approximately 45,000 students (Wikipedia, 2019). A random sample of 100 students was chosen to answer the questionnaire. The response rate was 88 and 7 responses were excluded due to missing information; therefore, the statistical analysis was done on 81 valid questionnaires Reliability and Validity: (Cronbach Alpha)
Table 1: Reliability Statistics:
| Cronbach’s Alpha | No. of Items |
| .779 | 27 |
3.3 Limitations
There are many limitations we faced while doing this research paper. Firstly, the number of the University of Jordan students is approximately 45,000 (Wikipedia, 2019). It was hard to find a random sample and distribute the questionnaire among the designated students. Secondly, the responses received were only 88 and the valid questionnaires for analysis were only 81. Third, while the literature review contains a lot of information about social media, it was difficult to find previous research on this topic in any university in Jordan. Most of the research studies discuss the influence of social media networks in general on purchase behaviour or decisions.
3.4 Statistical Analysis
The demographic statistics show that most of the participants in the study were females 72 (88.9%), while the males were only 9 (11.1%), as shown in Figure 1. Regarding age, young adult respondents were divided into two categories, most of the participants were between the ages of 18-21 years old rating 55 (67.9%), while those aged from 22-25 years old were recorded 26 (32.1 %) as shown in Figure 2. Finally, the maximum number of students 87 (96.3%) were Jordanians with only 3 (3.7%) of other nationalities, as shown in Figure 3.
Figure 1: Gender Statistics
Figure 2: Age Statistics
Figure 3: Nationality Statistics
Table 2: One-Sample Statistics of the model variables
| Model Variables | N | Mean | Std. Deviation | Std. Error Mean | Skewness | t |
| 81 | 3.24 | .697 | .077 | -.343 | 41.858 | |
| 81 | 3.68 | .764 | .085 | -.836 | 43.411 | |
| Snapchat | 81 | 2.63 | .962 | .107 | -.072 | 24.555 |
| 81 | 1.91 | 1.074 | .119 | 1.157 | 15.967 | |
| YouTube | 81 | 2.92 | .766 | .085 | .175 | 34.326 |
| 81 | 2.82 | .728 | .081 | .122 | 34.826 | |
| Purchasing Decision | 81 | 2.40 | .665 | .074 | -.061 | 32.423 |
By performing the T-Test analysis of the model variables, the results shown in (Table 2) indicate that the data of the population are normally distributed. Most of the data values are distributed around the mean of the independent variables used in the study. Facebook has the mean of 3.24 and a standard deviation of .697. Instagram has a mean of 3.68 and a standard deviation of .764. Snapchat has a mean of 2.63 and a standard deviation of .962. Twitter has a mean of 1.91 and a standard deviation of 1.074. YouTube and WhatsApp got close results of the mean of 2.92 and a standard deviation of .766 for the first and mean of 2.82 and a standard deviation of .728 for the other. Last, Purchase decision which is the dependent variable in the study, has the mean 2.40 and standard deviation of .665. (Figures of the variables, distribution in appendix).
4. Regression Test of the Hypothesis
Ho: There is no significant influence of the popular used social media applications (Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp) on youth purchasing decision at the University of Jordan. (α=0.05)
Table 3: Model Summary of the Main Hypothesis (H0)
| Model | R | R² | Adjusted R Square | Std. Error of the Estimate | F | Sig. |
| Ho
|
.623 | .388 | .381 | .524 | 50.173 | .000 |
| Coefficients | Unstandardized Coefficients | Standardized Coefficients |
t |
Sig. |
||
| B | Std. Error | Beta | ||||
| (Constant) | -.393 | .398 | -.986 | .327 | ||
| Social Media Applications | .973 | .137 | .623 | 7.083 | .000 | |
After performing a regression analysis of the main hypothesis, generally, the model of the research shows it is significant as (F= 50.173) and the p-value = .000 < 0.05 with R= .623 and R² = .388. This explains that there is a 38.8% correlation between the independent and dependent variables, as shown in (Table 3) above. The findings result in rejecting the main hypothesis. So, there is a significant influence of the popular used social media applications (Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp) on the youth purchasing decision.
A simple regression test was made for each of the Sub-hypothesis (Ho1, Ho2, Ho3, Ho4, Ho5, and Ho6) to be tested individually. (α=0.05)
The results are summarized and displayed in (Tables 4 and 5) bellow:
Table 4: Model Summary of sub-hypothesis regression test
| Model | R | R² | Adjusted R Square | Std. Error of the Estimate | F | Sig. |
| 1. Facebook | .185a | .034 | .022 | .658 | 2.791 | .099 |
| 2. Instagram | .238a | .057 | .045 | .650 | 4.763 | .032 |
| 3. Snapchat | .435a | .189 | .179 | .603 | 18.407 | .000 |
| 4. Twitter | .346a | .120 | .108 | .628 | 10.727 | .002 |
| 5. YouTube | .410a | .168 | .158 | .611 | 16.004 | .000 |
| 6. WhatsApp | .245a | .060 | .048 | .649 | 5.034 | .028 |
Table 5: Coefficient of sub-hypothesis regression test
| Model: 1 | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |
| B | Std. Error | Beta | |||
| (Constant) | 1.825 | .350 | 5.217 | .000 | |
| .176 | .106 | .185 | 1.671 | .099 | |
| (Constant) Instagram | 1.632
.208 |
.358
.095 |
.238 |
4.557
2.182 |
.000
.032 |
| (Constant)
Snapchat |
1.608
.301 |
.196
.070 |
.435 |
8.214
4.290 |
.000
.000 |
| (Constant)
|
1.989
.214 |
.143
.065 |
.346 |
13.924
3.275 |
.002
.002 |
| (Constant)
YouTube |
1.355
.356 |
.269
.089 |
.410 |
5.038
4.001 |
.000
.000 |
| (Constant)
|
1.767
.224 |
.290
.100 |
.245 |
6.093
2.244 |
.000
.028 |
From the above tables:
- The hypothesis “Facebook has no significant influence on youth purchasing decision” is tested. The results show that the model is not significant as F=2.791 and the p-value = .099 > 0.05. Therefore, the first hypothesis is retained, and the Facebook application was found to have no significant influence on youth purchasing decision with t=1.671 and p-value = .099 > 0.05.
- The hypothesis test of “Instagram has no significant influence on youth purchasing decision” shows that the model is significant as F=4.763 and the p-value = .032 < 0.05. Therefore, the second hypothesis is rejected, and we found Instagram application has a significant influence on youth purchasing decision with t=2.182 and p-value = .032< 0.05.
- The hypothesis test of “Snapchat has no significant influence on youth purchasing decision” show that the model is significant as F= 18.407 and the p-value = .000 < 0.05. Therefore, the Snapchat application has a significant influence on youth purchasing decision with t=4.290 and p-value = .000 < 0.05.
- The hypothesis test of “Twitter has no significant influence on youth purchasing decision” show that the model is significant as F= 10.727 and the p-value = .002 < 0.05. Therefore, the Snapchat application has a significant influence on youth purchasing decision with t=3.275 and p-value = .002 < 0.05.
- The hypothesis test of “YouTube has no significant influence on youth purchasing decision”. They show that the model is significant as F= 16.004 and the p-value = .000 < 0.05. Therefore, YouTube application has a significant influence on youth purchasing decision with t= 4.001 and p-value = .000 < 0.05.
- The hypothesis test of “WhatsApp has no significant influence on youth purchasing decision”. They show that the model is significant as F= 5.034 and the p-value = .028 < 0.05. Therefore, WhatsApp application has a significant influence on youth purchasing decision with t = 2.244 and p-value = .028 < 0.05 as shown in (Table 5 and 6) above.
Independent Sample T-Test of Demographic Hypothesis:
Ho7: A two independent sample T-Test was conducted to test the hypothesis “The influence of social media applications on youth purchasing decision have no difference when it comes to demographic factors (age, gender, and nationality). (α=0.05)
Table 6: Independent Sample Test (Gender)
| Variables | t | Df | Sig. (2-tailed) | Mean
difference |
Std. Error Difference |
| .243 | 79 | .809 | .060 | .248 | |
| -1.954 | 79 | .054 | -.519 | .265 | |
| Snapchat | -.352 | 79 | .726 | -.120 | .342 |
| 1.728 | 79 | .088 | .648 | .375 | |
| YouTube | .323 | 79 | .748 | .088 | .272 |
| .952 | 79 | .344 | .245 | .258 |
As shown in (Table 6) above, the influence of social media applications (Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp) on youth purchasing decision have no significant difference in the level of gender as all p-values > 0.05
Table 7: Independent Sample Test (Age)
| Variables | t | Df | Sig. (2-tailed) | Mean
difference |
Std. Error Difference |
| -.233 | 79 | .816 | -.039 | .167 | |
| 1.932 | 79 | .057 | .345 | .179 | |
| Snapchat | -1.343 | 79 | .183 | -.306 | .228 |
| -2.716 | 79 | .008 | -.668 | .246 | |
| YouTube | -.422 | 79 | .674 | -.077 | .183 |
| -1.779 | 79 | .079 | -.304 | .171 |
As shown in (Table 7) above, the influence of social media applications (Facebook, Instagram, Snapchat, YouTube, and WhatsApp) on youth purchasing decision have no significant difference in the level of age as all p-values > 0.05. However, there is a significant influence of Twitter application on the ages (22-25) as it got higher mean = 2.36 while the mean of ages (18-21) = 1.69 and p-value < 0.05
Table 8: Independent Sample Test (Nationality)
| Variables | t | Df | Sig.(2-tailed) | Mean
difference |
Std. Error Difference |
| 1.180 | 79 | .242 | .483 | .409 | |
| .038 | 79 | .970 | .017 | .452 | |
| Snapchat | .738 | 79 | .463 | .419 | .568 |
| 1.125 | 79 | .264 | .709 | .631 | |
| YouTube | .585 | 79 | .560 | .265 | .453 |
| 1.179 | 79 | .242 | .504 | .428 |
As shown in (Table 8) above, the influence of social media applications (Facebook, Instagram, Snapchat, Twitter, YouTube, and WhatsApp) on youth purchasing decision have no significant difference in the level of nationality as all p-values > 0.05
Correlation test:
Table 9: Correlations between variables.
| Snapchat | YouTube | Purchasing Decision | ||||||
| Pearson Correlation | 1 | .094 | .027 | .064 | .057 | .315** | .185 | |
| Sig. (2-tailed) | .403 | .807 | .568 | .615 | .004 | .099 | ||
| Pearson Correlation | .094 | 1 | .179 | .136 | .047 | .065 | .238* | |
| Sig. (2-tailed) | .403 | .111 | .227 | .675 | .562 | .032 | ||
| Snapchat | Pearson Correlation | .027 | .179 | 1 | .022 | .129 | .271* | .435** |
| Sig. (2-tailed) | .807 | .111 | .847 | .250 | .015 | .000 | ||
| Pearson Correlation | .064 | .136 | .022 | 1 | .200 | .020 | .346** | |
| Sig. (2-tailed) | .568 | .227 | .847 | .073 | .856 | .002 | ||
| YouTube | Pearson Correlation | .057 | .047 | .129 | .200 | 1 | .059 | .410** |
| Sig. (2-tailed) | .615 | .675 | .250 | .073 | .601 | .000 | ||
| Pearson Correlation | .315** | .065 | .271* | .020 | .059 | 1 | .245* | |
| Sig. (2-tailed) | .004 | .562 | .015 | .856 | .601 | .028 | ||
| Purchasing Decision | Pearson Correlation | .185 | .238* | .435** | .346** | .410** | .245* | 1 |
| Sig. (2-tailed) | .099 | .032 | .000 | .002 | .000 | .028 | ||
| **. Correlation is significant at the 0.01 level (2-tailed). |
| *. Correlation is significant at the 0.05 level (2-tailed). |
A correlation test was made to test the relation between the independent variables and the dependent variables. From (Table 9) above, we can indicate that the most effective social media applications influencing youth purchasing decision are (Snapchat, Twitter, and YouTube) in the level of <0.01. Snapchat has 43.5% correlation with purchasing decision. Twitter has 34% correlation with purchasing decision, and YouTube has 41% correlation with purchasing decision. On the other hand, the most effective social media application influencing youth purchasing decision are Instagram (23.8%) and WhatsApp (24.5%) in the level of <0.05.
5. Conclusion
The findings show that there is a significant influence of the popular social media applications on the youth purchasing decision. However, Facebook application proved to be not influencing the youth purchasing decision. Instagram, Snapchat, Twitter, YouTube, and WhatsApp applications proved to have an influence on youth purchasing decision at the University of Jordan. The most effective social media applications influencing the youth purchasing decisions are Instagram and WhatsApp as there was a strong correlation between them and the youth purchasing decisions.
5.1 Recommendations and Future Research
The study was conducted only on the youth at the University of Jordan. It would be recommended that future research be performed on a larger number of youth or other ages for more precise results. The University of Jordan can target its students on all the applications used in the study. A replication of this study on another sample would benefit the research.
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Appendices
Variables’ Normal Distribution
