Updated: Jun 12th, 2024

Social Media and Shopping Behavior of Emirati College Students

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Table of Contents

Abstract
Introduction
Literature Review
Methodology
Data Analysis and Results
Conclusions
References

Abstract

Social media has transformed the information presented about different products and social media through the creation of a dynamic, systematic, and customer-oriented advertisement landscape. Through social media platforms, businesses in the UAE have unlimited opportunities to tap the trends set by youthful clients. The empirical and theoretical literature review has indicated that social media has the potential of cutting the thought patterns of customers during the process of decision making. This means that effective brand engagement information would catalyze the purchasing process. The findings of this study have addressed how, when, and why social media has an impact on the shopping behavior of Emirati college students.

Through a quantitative research design, the sample space of 100 respondents provided scientific data explaining how customers select, process, and attend to different messages on the social media platforms before deciding to purchase. The findings suggested that Emirati college students pursue a proactive and holistic role in online information search after which the results are subjected to a focused decision-making process. The respondents would then make a comparative analysis from several alternatives in a selective and subjective manner for optimal results. However, the findings and conclusions of this study are valid within the sampled population and might not be replicated in other regions or populations due to the dynamics and variances in the environmental factors.

Introduction

Research Background

The paradigm shift from traditional marketing to a Web 2.0-based approach has resulted in formidable development within the business environment. Specifically, social media as part of Web 2.0 has brought about a revolution in encouraging users to extend the focus on content through a shared network. For instance, in the last two decades, the impact of social media on commerce has resulted in revolutionary marketing approaches that appeal to the specific interests of clients and cue their minds towards focused thinking. At present, the use of social media in marketing has transformed the existing relationships among ultimate consumers, retailers, distribution channels, and marketers.

According to Reyaee and Ahmed (2015), businesses across the globe have resorted to generating digital data about products that are hosted on smartphones, social media sites, and other compatible devices. The rationale for using social media platforms is informed by their ability to reach millions of customers from a single location. This means that companies have become proactive in translating their traditional marketing approaches to the Internet platform due to its global accessibility among the targeted audience and affordability in the application. The social media technology has expanded the decision making options for customers and created a self-sustaining ‘consumer democracy’ movement characterized by expanded information sharing.

Since social media platforms are associated with constant stimuli bombardments, college students have become adept and cautious in consuming information about different products and services. Social media has the potential of putting customers at the center of business interaction and integration of information about a product (Battor & Battour, 2013). As social media communication becomes part and parcel of interaction in the present world, Emirati college students are not left behind. The students use social media as a tool for peer interaction and exchange of ideas on the latest trends. According to Reyaee and Ahmed (2015), social media is a communication tool that can be accessed through online platforms with the aid of mobile phone tablets, and computers. It is important to examine the impacts of social media on the shopping behavior of these youths. Therefore, the scope of this research is to establish the existing relationship between Emirati college students’ shopping behavior and social media usage.

Statement of the Problem

Social media usage in marketing has expanded over the years to gain a center stage in the global interaction between customers and products. Specifically, social media has become an invaluable tool for interaction and sharing information about products and services among people of all ages. At present, just at a push of the button, a potential customer is able to view and review a product or service before making the purchasing decision. For instance, it is now possible to capture live reviews and feedbacks from previous users about a product profile. Therefore, the proposed research will attempt to explicitly relate the shopping behavior of the Emirati college student to social media as an influencing factor. This information is necessary to associate specific shopping behaviors exhibited by this group to the dominance of social media in the current commerce environment.

Purpose/Objective of the Study

College students across the Middle East are currently connected to the Internet platform than before. According to Nazeer (2017), an average college student in the Middle East has more than 500 social ties. For instance, Facebook alone has more than 30 million daily youthful users in the Middle East who can access at least 1.5 million commerce-related pages. This translates to about 30 million individual content sharing every day. On the other hand, the youthful Middle East social media users send or receive at least 50 million tweets per day. The LinkedIn platform has at least 10 million active users in the region. On average, the youthful population in the Middle East spends between 6 and 10 hours per week on social media (Reyaee & Ahmed, 2015).

This means that variation in Emirati college students’ behavior as influenced by social media is an intriguing concept that should be examined. Acknowledging the expansive nature of consumer behavior, the researcher has narrowed down on the aspect of shopping behavior among Emirati college students as influenced by social media. The objective is to explain how, when, and why social media has influenced the shopping behavior of these college students. This means that the findings of the research will facilitate the identification of pitfalls and opportunities for businesses in influencing shopping behavior via the social media platform. Moreover, it might present the ideal product visualization and presentation strategies via social media to guarantee optimal intake by these college students and the general public at large.

Significance of the Study

Comprehensive research on the impact of social media on a focused population, which is Emirati college students, marketers, and businesses within the UAE are likely to have a lucid assessment of the right social media strategies for optimal impact on the shopping behavior. Specifically, the proposed research will attempt to address the interaction between college students on social media and how it impacts their decision making to buy or reject a product. Thus, this quant study will reveal the effectiveness of the social media platform in cuing the minds of youthful customers towards acceptance of a product. The interest of the study is reporting different social media communication strategies in the presentation of products and services within the UAE and how they motivate the purchasing decision process. Thus, through a qualitative research approach, this proposal will reveal the significant trends in shopping behavior among college students are facilitated by different social media platforms.

Research Questions

Since the proposed study is focused on a specific population, the following questions were formulated to address the research topic.

How do college students, process, attend, and select the information present on social media before making the decision to purchase?
What changes had social media facilitated to the college students in the stages of decision making when shopping online?

In order to properly answer the above research questions, the researcher will use semi-structured interviews guided by closed-ended questions aimed at identifying trends and frequency of using social media in a population sample of 100 Emirati college students.

Definition of Terms

Social Media: Applications or online websites that allow users to share, create, and participate in a social network.

Emirati college students: Persons above 18 years who are enrolled in institutions of higher learning across the UAE.

Shopping behavior: The study of activities of an individual or group associated with the process of purchasing a product or service. The behavior incorporates the emotional, behavioral, and mental responses to a stimulus.

Internet: A worldwide computer network that provides communication and information facilities to interconnected networks through a standardized protocol.

Literature Review

Introduction

This part of the study examines the past literature on the impact of different social media platforms on the purchasing or shopping behavior of the youthful population from different regions. This section is divided into theoretical and empirical literature that is related to the research topic, Impact of Social media on Shopping Behavior of Emirati College Students. The researcher will carry out a comparative review of the theories and empirical studies related to the topic in order to isolate the existing literature gap. The researcher will then aim at filling this gap.

Theoretical Framework(s) Underlying the Research Purpose

Within the marketplace, consumers are the main actors who interact with different information to influence their perception of a product or service. According to the consumer decision theory, consumers are end-users who are inspired by perceived or actual benefits in the dynamic and multifaceted decision-making process (Battor & Battour, 2013). This theory states that the process of making a decision to either accept or reject a product is controlled by the transparency, accuracy, and accessibility of information available for consumption by a potential buyer. The consumer decision-making theory focuses on the 5-stage model (Homburg, Jozic, & Kuehnl, 2017). The notable stages are problem recognition, information search, evaluation, purchase decision, and post-purchase behavior (see figure 1).

Fig. 1. The five-stage decision-making model. (Source: Bansal et al., 2017).

The Engel, Kollat, and Blackwell (EKB) ultimate consumer behavior model discerns the consumer purchasing decision process as commencing with problem recognition and ending with the post-purchase decision (Lukas, Whitwell, & Heide, 2013). The problem recognition stage is characterized by isolation and recognition of variances between actual and desired needs to act and proactively arouses the decision process. This means that problem recognition is triggered by external or internal stimuli to initiate information search about a product or service. The external triggers include visual advertisements that expose the customer to filter the information presented to identify the needs or desires associated with a product.

For instance, social media adverts have the potential of triggering problem recognition (Park, Lee, & Kim, 2014). The information search stage involves identification of the options available, review of information about the selected option, and selecting the best alternative associated with optimal outcome (Rahimi, 2017). The third stage is the evaluation of alternatives in order to compare perfect substitutes for extra benefits. The criterion for evaluation is dependent on the goals or motives. For instance, on the basis of other users’ testimonies, a social media user is in a position to track the positive and negative feedbacks to confirm the reliability of the anticipated product (Elder & Krishna, 2013). Therefore, comparing direct and indirect experiences might facilitate the effective assessment of different alternatives to create a systematic formula for internalizing beliefs on intentions, attitudes, and ultimate choice from presented alternatives.

In defining the components of the final decision process, Kotler and Keller (2016) proposed the two-step alternative evaluation model in the purchasing process. The model states that preference formulation, intention, and purchase decision are correlated and joined by the attitude from anticipated benefits associated with a product from available information (see figure 2). For instance, information on a social media platform about a product or service might result in readjusting a customer’s intention to make the purchasing decision. The final decision model concludes that “consumers are undoubtedly influenced by the informediaries who publish their evaluations (customer reviews on Amazon.com, blogs, bulletin boards, and so on)” (Goodman, 2014, p. 45). The two stages in the final decision process are cyclical in nature due to loops in information evaluation and search.

Fig. 2. The final decision model. (Source: Kotler & Keller, 2016).

Finally, the post-purchase decision stage is characterized by individual evaluation of the product experiences based on the level of expected and actual satisfaction. This means that this stage is angled on dissonance and satisfaction matrices from the initial information about a product or service. For instance, in the event of a dissonance experience, the customer will ‘evaluate’ the purchasing decision and would commence a fresh information search for other better alternatives in the future decision process (Goodman, 2014). This means that any other buying would be triggered by the new behavior motivated by a poor satisfaction level.

Another theory associating the purchasing behavior to information available about a product is the information processing premise. Proposed by Bettman in 1979, the information processing theory is angled on the psychological and attitudinal components of the decision-making process. Specifically, the theory operates on the tenets of performing, evaluating, and reevaluating the post-decision process that might result in a purchase or rejection of a product. This theory has a framework consisting of six components, that is, “processing capacity, motivation, attention and perception encoding, information acquisition and evaluation, decision processes, and effects of consumption and learning” (Kotler & Keller, 2016, p. 33). The element of exposure captures the available information on the social media platform from which a passive or active response is activated.

However, due to the faster rate of information delivery, it often negatively impact on customer attention through disrupting the cognitive elaboration (Nasser & Al-Jenaibi, 2013). The active response is associated with the initiative process of seeking for information rather than bumping on the same. According to Kotler and Keller (2016), “most prospects are unwilling to take in relatively low priority new knowledge” (p. 38). This means that customers are subjected to information overload via social media platforms, which makes it harder for businesses to focus on specific demand dynamics of different consumer segments. For instance, due to excessive information on social media, encoding and decoding available information might be complex, especially where there are several available perfect substitute products. Moreover, the buying decision is quick meaning that customers are likely to reduce their perspectives on the relevant dimensions considered before selecting a brand choice (Goodman, 2014). Thus, the exposure dimension tunes the active information selection and processing among potential customers visiting social media sites.

The second element of the information processing theory is motivation, which postulates that customer choices are dependent on the purpose or intentions. Since choices are made on a daily basis, the motivational aspect has a direct impact on the intensity of behavior and direction. As a result, a customer is able to define his or her capacity to make decisions on the basis of self-conviction and perception of others (Goodman, 2014). The third element is the attention and perception encoding. In the information distribution, creating a perception and capturing attention are critical elements in exploring the selected message and its intention. Thus, continuous exposure to focused information via social media has the potential of capturing a recipient’s attention. According to Nasser and Al-Jenaibi (2013), “attention refers to the amount of mental effort or cognitive capacity allocated by an individual to the stimulus environment or task at hand” (p. 75). This means that an effective process of information dissemination is dependent on the magnitude of attention it can capture. In the end, the recipient will be in a position to draw towards the appropriate information that is consistent within internal thought patterns. The interpretation of stimuli on the basis of perception has the potential of influencing the direction of attention allocated to such information.

The information acquisition and evaluation component of the information processing theory interprets consumers’ media selection as determined by the nature and type of information they are exposed to (Reyaee & Ahmed, 2015). The information selection process is selective and actively influenced by the dynamics of intention or purchase goals when encoding and decoding messages on social media platforms. For instance, the perceived cost and value of information are critical in making a choice (Nazeer, 2017). Therefore, advertisements on social media are “considered as an interruption that leads to a goal reordering-for instance, the consumer may purchase a product, which is broadcasted on social media” (Kotler & Keller, 2016, p. 65). The decision processes aspect of the theory relates to the purchasing procedure as commencing with information selection and ending at the point of comparing the alternatives in order to settle on the best. This means that the decision process is a cyclic procedure that does not have a sequential flow since the choices can be altered at any point (Goodman, 2014). Lastly, the effects of consumption and learning address current and future purchase decisions are dependent on how information is interpreted from the experienced outcomes.

The Web 2.0 framework or social media is “the business revolution in the computer industry caused by the move to the Internet as a platform, and any attempt to understand the rules for success on that new platform” (Al-Badi, 2014). This means that social media has the potential of harnessing a collective and expanded intelligence through the integration of user-generated content at individual and group levels. In application, the social media model consists of content, social interaction, and communication media (Kotler, Kartajaya, & Setiawan, 2016). Over the years, social media has resulted in a paradigm shift in the socialization of online information through enhanced communication flow (see figure 3).

Fig. 3. Social network site. (Source: Kotler et al., 2016).

The activities of a typical social media framework include practices, behaviors, and interactive processes that enable users to share knowledge, information, and opinions through conventional sites. This means that social media is an ideal tool for expediting information flow by encouraging feedback and contribution from all users. This process involves a two-way conversation as opposed to the one-sided traditional media (Bansal et al., 2017). In the end, users are encouraged to create, comment, edit, and share information on any topic to create a democratized interaction module. The main types of social media outlets are media sharing, social news, social networking sites, microblogging, and blogs (see figure 4). Each outlet has unique experiences and features to meet the needs of users within the social media field.

Fig. 4. The components of social media. (Source: Kotler et al., 2016).

Apparently, the theoretical literature review suggests that social media has the potential of influencing the purchasing behavior of a customer through cuing the mind from the information presented. In application, the theoretical perspective considers the purchasing decision or behavior as influenced by the motives, information available, perception of others, perceived and actual benefits, and the cost implication when compared to other alternatives. However, the theoretical literature review is general and not focused on a specific population despite the fact that dynamics in each customer segment are different.

Thorough Review of Relevant Empirical Studies and/or Qualitative Research

In relation to this study, the empirical review is based on social networking sites (SNSs) and their impacts on the purchasing or shopping behavior. According to Kotler et al. (2016), SNSs “are generic terms for sites that are used to connect users with similar backgrounds and interests” (p. 56). A lot of literature is available on the impact of social media and its development across the globe. The Middle Eastern region is not left behind in the usage of the SNSs. According to the Arab Social Media Outlook report for the year 2017, social media is at the edge of replacing traditional or conservative methods of information sharing. Specifically, more than 3 million people within the UAE are active subscribers, equivalent to almost 50% of the entire population (see table 1 and pie-chart 1) (Al-Badi, 2014). The impact of social media within the UAE and the Gulf region was experienced during the infamous Arab Spring when it was used to fuel the uprising by the youthful population. Although the UAE government has put in place some policies to regulate the SNSs usage, it has resulted in a multiplier effect, especially among the youthful population who use social media as an ideology tool to create social bonds.

Table 1: SNSs and the number of users in the UAE. (Source: Stat Counter, 2018, p. 2).

Name of the SNS	Percentage Market Share of Users (January 2017)	Description
Twitter	11.14	Social networking
Facebook	85.47	Social networking
YouTube	0.13	Video sharing
Google	0.44	Social networking
LinkdIn	0.08	Business networking
Pinterest	0.84	Visual discovery tool
Others	1.9

Pie Chart 1: SNSs market share in the UAE. (Stat Counter, 2018, p. 2).

The data collected by the Stat Counter in 2017 indicate that Facebook is the most dominant SNSs followed by YouTube and Twitter (graph 1).

Graph 1: SNS market share in the UAE. (Source: Stat Counter, 2018, p. 6).

Several previous studies have been carried out by reputable scholars aimed at understanding and predicting the primary factors motivating the interest and usage of social media among the youths. For instance, according to Reyaee and Ahmed (2015), social media is one of the most common communication platforms for youths consisting of Emirati male college students. In research by Reyaee and Ahmed (2015)aimed at establishing the popularity of social media among the youth population, the findings revealed that more than 60% of the young Emiratis have active access to social media and its usage in online shopping. Reyaee and Ahmed (2015) further noted that the young population spends almost three hours on a daily basis online on different social media platforms to watch news, blog, and get entertainment. The authors concluded that the high percentage of social media access among Emirati youths could be attributed to its affordability and ease of use in group interaction.

Another study by Nazeer (2017) on the impact of social networking sites on college students revealed that social media has positive and negative impacts on shopping behavior. Through a social survey design, the findings indicated that social media promote positive youth development as they are exposed to different online shopping platforms. Moreover, Nazeer (2017) noted that social media had helped college students to build high self-confidence since these platforms encourage open discussions without fear of straining family relations or drawing controversy when shopping for different products and services. This means that social media is a bridge to knowledge acquisition and dissemination to aid in accurate decision making on what to purchase online. Nazeer (2017) also identified the negative impacts of social media such as impulse buying or purchasing explicit material.

Hajli (2014) studied the impact of social media on consumers and the findings revealed that this platform is laden with opportunities for customers to directly engage others through Internet interaction. Through a multidisciplinary model angled on technological acceptance, the data from a primary survey indicated that social media a sustainable social interaction between customers, leading to improved intention and trust to buy. The author concluded that the perceived usefulness of an SNS is an essential element in facilitating the interaction. These findings have validated the author’s assumption that social media is the primary driving force that has transformed e-commerce into social commerce. Another study Hajli (2013) on the primary framework for social commerce integration established that different social media platforms have resulted in increased product acceptance among customers. Through a survey study, Hajli (2013) the findings indicated that the use of social media has grown tenfold is currently one of the most popular tools for passing information about businesses and products. Through a review of social media usage in the UAE, the author concluded that the SNSs have created affordable, expansive, and easy to use marketing platforms for displaying information about products and services to the targeted customers. The findings further revealed that social media is a leading platform for promoting illicit products that have the potential of poisoning the minds of customers in a positive and negative.

Summary

The theoretical and empirical literature review suggests that social media has an impact on the purchasing behavior of customers since it presents a myriad of information about products and services from which decisions are derived. The impact could be positive or negative, depending on the authenticity of the information provided on social platforms. However, little research has been focused on a specific population in terms of how social impacts their purchasing behavior. Thus, the proposed research will fill this literature gap by attempting to quantify the impacts of social media on the shopping behavior of Emirati college students.

Methodology

Quantitative Study

Since the proposed study is dynamic, subjective, and focused, the researcher selected the quantitative approach since it accommodates different data analysis tools within a reasonable error margin (Saunders, Lewis, & Thornhill, 2016). The quantitative study will provide an ideal environment for a comparative analysis in order to establish the relationship between the dependent and independent variables. In relation to this study, the dependent variable is social media while the independent variable is shopping behavior. The researcher intends to use closed-ended questions to carry out a systematic survey aimed at capturing the guided insights on the impacts of social media on the shopping behavior of college students. Data collection will be carried out through the use of a 12 item questionnaire prepared to integrate a 7-point Likert scale (Saunders et al., 2017). The use of questionnaires in carrying out a quantitative survey will enable the respondents to stick within the theme.

Research Design

The research was conducted through a primary survey of Emirati college students as respondents. Since the scope of the research was subjective and focused, the researcher opted for a systematic quantitative survey to capture potential insights from the respondents (Saunders et al., 2017). In order to minimize potential biases associated with quantitative survey design, the researcher opted for closed-ended questions as guidance for framing responses. The respondents were selected through the snowballing sampling strategy (Saunders et al., 2017). The research was careful to balance the demographic characteristics of this sample space such as gender and age bracket.

Population and Sample or Participants

The targeted population consisted of 100 Emirati college students. The researcher selected this number since it is appropriate to provide a true picture of the situation on the ground. The participants were selected through a systematic but random sampling to capture different demographic characteristics (Saunders et al., 2017). Among the traits that qualified a potential respondent to participate in the study included being a college student, having an active presence on the social media platforms, and at least participating in the online-based purchase of products. These bare minimum traits were designed to avoid biases associated with the poor selection of the respondents.

Instrumentation

The researcher opted for the analysis of variance (ANOVA) tool to establish the existing statistical variation in collected data (Saunders et al., 2017). The first element in ANOVA analysis will be variance between the mean of different social media platforms

while the second element will be the mean of the respondents on how their shopping behavior is altered

Therefore, the proposed null and alternative hypothesis for the ANOVA analysis will be;

Null hypothesis

Ho: µ₁ = µ₂

The null hypothesis indicates that the sample selected means on impact of social media on shopping behavior of Emirati college students for one platform is equivalent to the mean for other platforms within the UAE.

Alternative hypothesis

Ho: µ₁ ≠ µ₂

The alternative hypothesis indicates that sample selected mean on impact of social media on shopping behavior of Emirati college students for one platform is not equivalent to the mean for other platforms within the UAE.

The null hypothesis will only be rejected with the F-critical is smaller than F-calculated.

The estimated confidence interval for the study is at 99%.

Sample statistic + Z value * standard error / √n

b₁ = 7.1175 ± 2.57 * 0.9631 / √133

= 7.1175 ± 2.57 * 0.9631 / 11.5326

= 7.1175 ±0.2146

= 6.9029 ≤ b₁ ≤ 7.3321

At 95%

b₁ = 7.1175 ± 1.96 * 0.9631 / √133

= 7.1175 ± 1.96 * 0.9631 / 11.5326

= 7.1175 ± 0.1635

= 6.954 ≤ b₁ ≤ 7.281

At 90%

b₁ = 7.1175 ± 1.64 * 0.9631 / √133

= 7.1175 ± 1.64 * 0.9631 / 11.5326

= 7.1175 ± 0.1368

= 6.981 ≤ b₁ ≤ 7.254

From the calculations, the confidence intervals are estimated at 6.981 ≤ b₁ ≤ 7.254 of 90%, 6.954 ≤ b₁ ≤ 7.281 of 95%, and 6.9029 ≤ b₁ ≤ 7.3321 of 99%. These values indicate that the estimated confidence intervals increase as interval levels decrease.

Procedures

The researcher begun by drawing a questionnaire consisting of 12 closed-ended questions revolving around social media and purchasing behavior. The questions were pretested through a pilot survey consisting of 10 respondents and adjustments made from the findings. The researcher then hand-delivered the 100 questionnaires to randomly participants who were expected to fill and return the same within 7 days. The researcher ensured that due diligence and permission for the study was granted by the relevant authority. Each questionnaire was accompanied by a consent letter detailing the aim and scope of the researcher (Saunders et al., 2017). The researcher was careful to include contact details to enable respondents seek clarification during the course of the study. After five days, the researcher followed-up on the progress in filling the questionnaires. The duly filled questionnaires were collected back through the dean of student’s offices within the sampled institutions of higher learning. The researcher then proceeded to code the collected data after which a comprehensive transcription was carried out.

Data Analysis

After data transcription, analysis will be carried out through cross tabulation by using the SPSS package (Saunders et al., 2017). The researcher will concentrate on ANOVA and correlation analysis to establish the trends in mean, standard deviation, and rank for each variable.

Data Analysis and Results

Demographic Summary of the Findings

The rate of response from the survey study was 100%, that is, all the targeted respondents duly filled their questionnaires and forwarded them on time (see table 3 and 4). The respondents accurately filled their questionnaires and there were no cases of participant disqualification.

Table 3. Summary of the response rate against gender.

Respondent groups	Number	Percentage (%)
Female participants	50	50
Male participants	50	50
Total	100	100

Table 4. Summary of response rate against age bracket.

Age group	Number	Percentage (%)
18-22 years	50	50
23+ years	50	50
Total	100	100

For the 100 respondents, the researcher carried out data coding on preference of different social media platforms for standard deviation, rank, and mean (see table 5). The main social media platforms considered were Facebook, Twitter, Linkerdln, and Google.

Table 5. Summary of the standard deviation, rank, and mean of responses for each social media platform.

Social Media Site	Sample size	Mean	Standard deviation	Rank
Facebook	100	5.2939	0.9095	1
Twitter	100	4.8559	1.1121	2
Google	100	4.4896	0.8644	3
Linkerdln	100	4.1757	1.1321	4

The results summarized in table 5 indicate that Facebook site has the highest cumulative mean of 5.2939 followed by Twitter at 4.8559. The third and fourth positions in terms of social media popularity are occupied by Google (4.4896) and Linkerdln (4.1757). The results also fall within the same digit, which is an indication that there was general consistency in the responses gathered. In terms of standard deviation, Google had the lowest score at 0.8644 while Linkerdln had the highest score of 1.1321.

Correlation Analysis of Social Media Platforms and Shopping Behavior

In scientific data analysis, correlation review gives an insight into the magnitude of association between the dependent and independent variables, that is, social media and shopping behavior (see table 6). Since the data analysis was focused on two variables, the correlation analysis was performed to test the validity of the following hypotheses.

Null hypothesis, H_o: There is no existing relationship between social media and shopping behavior of Emirati college students.

Alternative hypothesis, H₁: There is an existing relationship between social media and shopping behavior of Emirati college students.

The researcher tabulated the results of the correlation analysis to quantify the possible relations between the primary variables.

Table 6. Findings of the correlation analysis.

	Purchasing Behavior	Facebook	Twitter	Google	Linkerdln
Purchasing Behavior	1
Facebook	0.678	1
Twitter	0.652	0.521	1
Google	0.439	(0.467)	(0.385)	1
Linkerdln	0.498	(0.457	(0.397)	0.309	1

The results displayed in table 6 indicated that there exists a positive correlation between shopping behavior of Emirati college students and different social media platforms. The coefficient of correlation between Facebook site and shopping behavior was calculated as 0.678, which is actually the highest when compared to other sites. This was followed by Twitter and Linkerdln at 0.652 and 0.498, respectively. The coefficient for Google platform was the least. The positive correlation for all social media sites is an indication the dependent and independent variables are related. In order to establish the specific correlation between social media platforms used by Emirati college students, the researcher integrated ANOVA analysis to enable multivariate testing of the variables in place (see table 7).

Table 7. Result of the correlation in use of social media platforms and their dominance.

Social media platform	In terms of gender			In terms of age			In terms of social orientation
	Mean	S.D	Rank	Mean	S.D	Rank	Mean	S.D	Rank
Facebook	5.62	0.74	1	6.45	1.53	1	7.71	1.34	1
Twitter	5.61	0.31	2	4.21	1.04	3	6.63	0.96	2
Google	4.73	1.24	4	3.42	0.75	4	3.06	0.97	4
Linkerdln	4.92	1.05	3	5.72	1.15	2	4.76	1.09	3

Facebook as a platform was the most preferred social media site for the three variables of gender, age, and social orientation. This is evident by its highest score in terms of mean and standard deviation. This was followed by Twitter, Google, and Linkerdln. The scores for Linkerdln were lowest when compared to the other three social media platforms. In order to quantify the degree of freedom for the primary research indicators, the researcher used ANOVA from the earlier proposed null and alternative hypothesis summarized below.

Null hypothesis

Ho: µ₁ = µ₂= µ₃: The null hypothesis means that there exist no differences in the preference of social media platforms in from the perspectives of gender, age, and social orientation of the Emirati college students.

Alternative hypothesis

Ho: µ₁ ≠ µ₂≠ µ₃: The alternative hypothesis means that there are differences in the preference of social media platforms in from the perspectives of gender, age, and social orientation of the Emirati college students.

The ANOVA analysis results were tabulated to establish a clear trend for the three variables of gender, age, and social orientation among the Emirati college students (see table 8). The results indicated that there is a positive correlation among and between these variables.

Table 8. Degree of freedom for the three variables or indicators.

Variable	F-ratio	Degrees of freedom	P-value
Social Media Platforms	4.21	7.102	0.001
Analysis of the indicators
Gender	9.42	94	0.000
Age	6.92	94	0.004
Social orientation	5.99	94	0.003

The results displayed in table 8 indicate that the F-value is 4.21 while the P-value is 0.001. These findings suggest that the null hypothesis does not hold at degree of confidence of 99%. This is a clear confirmation that the social media use and its impact on purchasing behavior among the Emirati college students vary with age, gender, and social orientation. Thus, it is accurate to confer that social media indictors are instrumental in determining the magnitude or impact on purchasing behavior of Emirati college students. Specifically, the aspect of gender had the highest influence in the use of social media in making decisions to buy or reject a product from the presented advertisement messages.

Impacts of Social Media on Shopping Behavior Analysis

The researcher summarized the responses to the 12 questions in part B of the questionnaire and tabulated the results (see table 9 and 10). The findings indicated a clear trend in the responses to each of the questions. Specifically, the highest score for each question is an indication of consistency in the responses.

Final Questionnaire

Which is your most preferred social media platform?

1. Facebook 2. Twitter 3. Google 4. LinkedIn 5. Others

Which site has the most reliable information when it comes to the advertisements it hosts?

1. Facebook 2. Twitter 3. Google 4. LinkedIn 5. Others

I turn to social media whenever I want to shop for stuff online.