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Research Article ISSN 2229 – 3795

ASIAN JOURNAL OF MANAGEMENT RESEARCH 463

Volume 6 Issue 3, 2016

From presence to purchase: An empirical study on student communities Ridhima Bhanot Sharma 1, Marshal Mukesh Sahni2

1- Research Scholar, Amity University

2- Dean Student Welfare, Amity University

[email protected]

ABSTRACT

The paper aims to understand social marketing, as the society specially the students

communities have become technology driven from education to communication and

entertainment to business. This research paper investigates the impact of the factors of social

marketing on the attitudes and buying intensions of the student communities. The three

extracted factors – Discovery, Peer Reviews and Sharing Purchases were further evaluated

based on the demographic variables – Income and Education Level of the student

communities in the National Capital Region of India. A paper-based questionnaire was used

containing five-point Likert type scale to explore students’ attitudes toward online shopping

through social marketing. The paper also examines how the marketer can convert student

communities’ presence into purchase. The findings of the research predict that there is no

significant interaction between education and income level with the said factors. However the

income level supports the effect of the ‘Discovery’ factor for the student communities.

Key words: Social Marketing, Student Communities, Internet, Shopping, E-commerce,

Consumer Behavior.

1. Introduction

“Student’s love shopping”; there’s no questioning about this statement. The point of

argument arises when the new medium “Online” comes into picture. The youth’s ease of

access of internet and their increasing preference for technology has definitely raised the

percentage of Online Shopping. As Burt and Sparks, 2003 says Internet has bought a

technological advancement that has changed the entire marketplace by 360 degrees. With the

onset of such evolution, the lifestyle has become more hassle free. Customers feel more

comfortable shopping at their ease.

As far as online marketing is concerned, the latest buzz word is Social Media. Social Media

connects over 2 billion people of the overall global population. Regardless of being the only

digital medium that brings and connects with countless number of people, Social Media

Marketing accounts only 9.9% of overall digital marketing budgets, as stated by The State of

Social Marketing 2015 report created by SimpleMeasured. However, industry experts have

estimated that by the next 5 years social media marketing will account up to 22.5% of the

overall digital marketing budgets.

One of the positive aspects of shopping online is the reduction in cost of labor, space,

electricity and equipment which on other other hand is not reflected in the price of the

product. As a result the customer has to pay way less than what he has to pay while buying it

offline (Lawrence et al., 1998). As per PwC Report, (2013) Asia-Pacific emerged as the

From presence to purchase: An empirical study on student communities

Ridhima Bhanot Sharma, Marshal Mukesh Sahni

ASIAN JOURNAL OF MANAGEMENT RESEARCH


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strongest business-to consumer (B2C) online shopping region in the world with sales of

around 567.3 billion USD, a growth of 45% over 2012, ranking ahead of Europe (482.3

billion USD) and North America (452.4 billion USD).

Quartz Reports (2015) supports the growth of social marketing, Facebook has seen

sumptuous growth since last 3 years when it became public. Facebook’s stock has jumped

roughly 30 percent and as result the company added more than $65 billion to its market value,

bringing it to more than $236 billion which is way more than the world’s largest economic

footprint Walmart who has grown by $235 billion. Technology and Internet has become an

obligatory requirement for students. The research by Internet Advertising Bureau (IAB) and

The Student Room (2014) showed that students are fully equipped with the latest

technologies. Evaluating their time spend on various activities came out to 80% time they are

on laptops which was way more compared to 57% on TV’s. A large chunk of students are

spending 50% of their time accessing the internet via smartphones.

Internet is attracting every strata of society as far as shopping is concerned (Teo, 2002). Wide

variety and quickness in shopping are becoming valuable characteristics of online shopping

(Järveläinen, 2007). Over the years shoppers have experienced a shift from the traditional

shopping to internet shopping (Seock & Norton, 2008). Stating from the Vendor’s point of

view, online shopping provides an opportunity to improve company’s recognition and reach

(Grabner-Kraeuter, 2002). Online Shopping gives marketers an opportunity to innovate their

product line and experiment with their marketing communication strategies at a lesser cost

(Swinyard & Smith, 2003).

This paper thus elucidates the gaining attraction of online shopping among the student

communities. The paper considerate the factors’ affecting the student’s online shopping

behavior. The price, quality, recommendation, convenience and keeping up with the latest

trends are some of the elements which are attracting student communities towards online

shopping as compared to high street shopping.

1.1 Understanding social marketing

Marketing is something that cannot be compiled in one single definition; there are various

approaches and various definitions available concerning different contexts. From defining it

as a business activity, a frame of mind, an economic process, process of exchanging or

transferring, a coordinative, an Integrative function in policy making, a trade phenomenon to

a process of consideration, equalization and dispersion, a process of adjusting demand and

supply. There are ‘n’ numbers of explanations available to us (Marketing Staff of the Ohio

State University, January, 1965). However, in the present times, a division of marketing that

is entrapping the customer’s lifestyle especially the student communities is Social Marketing.

Social marketing began to differentiate itself in its own way from the broader definition of

marketing in the early 1970s. According to Kotler and Zaltman (1971), social marketing is

process of designing, implementing, and controlling marketing programs that involve the

efforts to influence the acceptance of social ideas towards a specific market. Basically it is the

most important part of the product life cycle (Andreasen, 2002).

Social Marketing focusses on the demands and needs of the target audience as it has a lot to

do with the people and the market surrounding the product. It concentrates on behavioral

differences, intangible issues and evaluates factors like behavioral changes (McDermott,

Stead, and Hastings 2005). Henceforth, social marketing is a complex division of marketing





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using all the basic frameworks like consumer research, segmentation and targeting, objective

setting, and manipulation of varied principles and concepts of marketing.

1.2 Social marketing from student communities point of view

To understand social marketing from students view, it becomes a requirement to understand

the student communities’ behavior, patterns and trends followed by them. While

understanding student communities in this paper, we have put our focus on selecting

behaviors, identifying issues and opportunities, developing strategies and broad

implementation of marketing theories and concepts.

‘Nationally, almost a quarter of students don’t believe they receive the emotional help and

support needed from their families, friends and acquaintances,” said Shari Robinson, interim

director of UF’s Counseling and Wellness Center. “That’s why social marketing campaigns,

like UFlourish, are essential on college campuses to address the need for decreased stigma

and increased social support for students dealing with mental health concerns.’

Agreeing to this statement, the need is to understand different personality aspects of students.

Since the internet is available to communities 24 hours a day, seven days a week, 365 days a

year with the advancement in technology and launch of smartphones at affordable prices. As

per the Internet Stats Report, (2015) 92% smartphones have inbuilt Facebook, Twitter &

Instagram Applications. Students’ presence on these social medium applications has become

a necessity for students to connect with their friends and peers. Thus marketing on these

social mediums is a requirement to enhance the sales and returns.

2. Literature review

Online retailing/shopping has gained market share as consumers have the ease of shopping 24

hours a day, seven days a week, 365 days a year. As (Meeker & Pearson , 1997) says that the

different market sectors including travel, books, insurance, financial services, music, video,

automobiles, flowers have experienced growth in their online sales with the onset of Internet

Shopping. A perfect example to quote is Amazon.com. The company launched itself in 1995

and has attained the position of third largest bookseller in the U.S. (Lohse & Spiller, 1998).

An individual’s life in the current scenario is swayed by information and communication

technologies (Schwanen, Farag, Dijst, & Faber, 2007). The increased use of cell phones,

more computer and Internet simplifies information related work. (Shannon, Gardner ,

Forsythe, & Liu, 2006). Internet is now extending into every stratum, increasing the web

usage and becoming a powerful tool (Dijst, Farag, Schwanen, & Faber, 2007). There are 32

countries worldwide with the Internet penetration rate higher than 50%

(http://www.internetworldstats.com). In the prior age, desktops were the main medium for

Internet usage. While in the naïve times, with the upcoming models of mobile applications,

internet has extended its reach to communication, gaming, entertainment and shopping

experiences (Miyazaki & Fernandez, 2001). Henceforth, the increased user base of Internet

has directly widened the market opportunities (Chung & Lee, 2003). Internet has given

opportunities to display variety of product range with comparatively lesser investment

involved. Kiang et al., (2004) agrees to the fact Internet has increased reach among

consumers as well as (Chen, Huang, & Sung, 2009).

http://www.internetworldstats.com/





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Sandeep Ladda, Leader Technology, PwC India rightly states that competition in online

market is expected to further intensify with more and more players entering the domain. To

count a few Alibaba, Amazon, Ebay, Flipkart, Snapdeal are doing extremely well and getting

substantial returns. As a result government is eager to enhance its distribution channel seeing

the 280 crore INR transaction by Indian post on the cash of delivery (CoD) segment.

Online shopping being at a developing and growth phase, (Haque et al., 2006) believes that it

is very important to understand consumers behaviors and attitudes to get a hand on it. The

main factors affecting the potential of online shopping in today’s economy is shopper’s

attitude and choices. (Michieal, 1998).

(Bhatnagar and Ghose, 2004a, b; Garbarino and Strabilevitz, 2004) projects similar concepts

for traditional and online shopping - “Customers are king”. Understanding consumer

behaviors predicts the customer perception towards a good or a service. The benefits and

perceptions of online shopping being influenced by social marketing are judged by a

customer perspective (Huang et al., 2004; Liao and Cheung, 2001). Although Internet is

trapping every domain there is little known about the customers purchasing attitude towards

this new shopping channel and the factors which may influence their behavior (Haque,

Sadeghzadeh and Khatibi, 2006).

Social media has been an influential factor on the shoppers. There are varieties of reasons

why student communities have been embracing social media for shopping be it convenience,

peer reviews, finding ideas, sharing purchases, validating choices, inspiration, discovery,

selection and user experience. Many of the researches have been conducted on these factors.

(Pavlou, 2003) supports the fact that convenience, various selection, low price, original

services, personal attention, and easy access to information, among others are some of the

advantages attracting buyers towards online shopping over the traditional high streets.

Moreover, recognition and understanding of shopping behaviors is affected by various factors,

there are different shopping orientations that are considered (Korgaonkar and Wolin, 1999; Li

et al., 1999). The shopping orientations can be categorized as Hedonic Shopping, Utilitarian

Shopping and Online Shopping (Safavi, 2007; Swaminathan et al., 1999), thus helping the

marketers and brand managers to build their images (Shu-lng, 2003).

(Limayem et.al, 2003) has proposed the different theories to explain the shopping behaviors

based on broader aspects of Reasoned Action (Fishbein and Ajzen, 1975) and Acceptance

Model (Davis, 1989).

(Lina Zhou, Liwei Dai & Dongsong Zhang 2007) summarized individual factors and their

impact on consumer online shopping, they identified nine types of consumer factors,

including demographics, Internet experience, normative beliefs, shopping orientation,

shopping motivation, personal traits, online experience, psychological perception, and online

shopping experience.

There are different shopping orientations that customers possess. (Stone, 1954) defined

shopping orientation as a shopping lifestyle or shopper’s style encompassing shopping

activities, interests and opinions. (Visser and du Preez, 2001) believe that the different

orientations have number of interrelated variables which is why defining shopping orientation

is not possible. To conclude the theories by said researchers shopping orientation is “a

personal dimension (e.g. activities, interests, opinions, motives, needs and preferences) and a





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market behavior dimension or a general approach to acquiring goods and services. This

market behavior dimension reflects the personal dimension and indicates needs and

preferences for, inter alia, information sources, stores per se (patronage behavior) and store

attributes (including store image)”

Considering the online shopping, we will be studying the shopping orientations from both the

classified version – utilitarian and hedonic. As per the literature, utilitarian shopping is

considered to be the economic shopping whereas hedonic shopping is the recreational

shopping (Allard, Babin and Chebat, 2009; Bellenger and Korgaonkar, 1980; Dawson, Bloch

and Ridgway, 1990; Jones et al, 2006; Westbrook and Black, 198). Utilitarian shopping is

goal oriented, efficient and deliberate (Babin, Darden and Griffen, 1994). They are based on

rational necessity to buy a particular good or service (Kim and Sham, 2002). Therefore the

utilitarian online shoppers deliberately shop online for a rational efficient task (Wolfinbarger

and Gilly, 2001). Monsuwe et al. 2004 supports the argument by believing that such type of

shoppers do not waste time on searching, they are task oriented, and focus on efficient way to

achieve their goals (Falk and Campbell, 1997).

On the contrary, hedonic shopping is a form in which a leisure, fun, joy, festive, information

is involved (Babin, Darden and Griffen, 1994) and (Falk and Campbell, 1997). It involves

more fantasy and escapism than work (Monsuwe et al., 2004). The purpose of browsing these

websites could be varied from price comparisons, checking out of offers, repurchases etc.

(Wolfinbarger and Gilly, 2001). Online shoppers are more attracted to break their

monotonous working routine so they browse different sites which leads to spontaneous

purchase. These are part of enjoyable experience (Sorce et al., 2005). Henceforth

understanding the hedonic online shopping attitude is a predictor of the analysis of the

purchase decisions of the shoppers (Childers et al., 2001).

Browsing behavior is a specific form of shopping behavior which can occur independently of

specific purchase occasions and is both a form of leisure activity and a form of external

search behaviour (Bloch and Richins, 1983). Thus, understanding the shopping orientations

are the need of the hour to judge online shopping intensions of the student communities

(Menon and Kahn, 2002).

Adopting this new channel of marketing by the students is also considered to be a part of

consumer innovativeness. (Rogers and Shoemaker, 1971) defines customer innovativeness as

the degree to which an individual accepts the change and the new idea. Supporting the

definition (Hirschman, 1980) defined consumer innovativeness is one of the personality trait

that relates to individual’s desire to seek new stimuli which comes out from student

communities attitude. (Vijayasarthy, 2003) defines attitude as an extent of like or dislike of

the individual toward online shopping. It is the need to evaluate this attitude to predict the

growth rate and the future of online shopping (Wu, 2003).

Taking into consideration the student communities, their strong purchasing power has

dominated the market in the current scenario. Therefore concerning the facts that 90% of

students have daily access to internet as reported by (Xu and Paulins, 2005), it is critical for

all the online stores and web shops to understand the student behavior, and the attitude and

perceptions of this population segment towards the social marketing.

(MacDonald et. al, 2008) quotes that the universities and educational institutions have also

become a focus of attention with the expansion of the education system. Henceforth, it is





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required that the marketers, the digital media managers shift their panorama also towards the

student communities in learning and understanding their shopping intensions so that their

strategies and students antecedents go hand in hand.

3. Research objectives

3.1 Issues and opportunities of social marketing

3.1.1 Discovery

Online shoppers have number of reasons to be driven by social marketing. The previous

studies have shown that student communities are mainly dependent on their pocket moneys,

so they tend to make very wise decisions when it comes to making a purchase decision. They

try to access all the possible information available for the product. Finding ideas through the

Internet is the most common phenomena; students have also adopted the similar trend and

have concentrated their focus on social mediums like Pininterest, Instagram, Facebook Pages,

Blogs to have a fair idea about the price range. They discover the new trends by comparing

various websites, checking pictures to make a purchase decision. Browsing through the social

media attracts them to make a purchase and get the delivery at the doorstep.

3.1.2 Peer review

Shoppers in today’s scenario are very much attracted towards the choices and the opinions of

the peers. Therefore referring to comments from the friends and peers has become a common

habit amongst the students; they highly value the choices and feedback his/her peers make.

Social media thus influence marketers of any industry be it fashion, travel, FMCG and many

more to sell products through social mediums.

3.1.3 Sharing purchases

Sharing and validating the purchase student’s buy has become more and more pertinent with

the onset of the Selfie Concept, where the person clicks oneself and share it with others. 37%

of purchases take place within 1 week of sharing or favoring the ultimately-purchased item as

per the Vision Critical Report from Share to Sale. Student Communities share prospective

purchases as part of their active social media presence. The report also communicates that

Posting Frequency by active users of social media is 38% which signifies sharing their

purchase directly or indirectly motivates the other connections to buy.

3.2 Hypotheses

H1: There exists no relation between the income level and the education level.

H2: There is no significant relationship between respondents categorized into different

income brackets.

H3: There exists no significant difference between the respondents of different education

qualification.

4. Research Methodology

4.1 Data collection





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The research paper focusses at exploring the factors affecting the increasing influence of

social marketing amongst the student communities. The data collection was done through a

structured questionnaire. The questionnaire is a 5 minute quick survey on judging the

attitudes of students towards different aspects of social marketing. It consisted of 3 different

subscales to judge the different attributes of students. The familiarity anxiety towards social

marketing is judged in the first subscale (Yao & Lee, 2001). The second subscale focusses on

the hassle free, convenience, and financial aspects (Shannon & Gardner, 2006). The last

subscale was included to judge the perceived consequence, intension and innovativeness

(Limayen, Khalifa & Frini, 2000).

The target audience is selected from the National Capital Region in India. The region is

divided into 4 zones. In the north zone we selected the Vishwavidalaya Metro Station,

concerning the South – AIIMS Metro Station and Moti Bagh Bus stop was selected, in the

East the Mayur Vihar Metro Station foot fall was surveyed, in the West – Pitampura and Raja

Garden areas bus stops is selected. The surveys are conducted in the month of May 2015 to

July 2015, since these are the months in which admissions to the colleges and the Universities

happen and the capital region receives students from across the country and overseas.

4.2 Sample Size

Approximately 55 respondents were surveyed in each 4 zones resulting in the sample size of

220 of which 18 surveys were incomplete. The resultant sample size is thus 202. The

questionnaire is designed concerning the demographic variables – gender, education level,

residence, income level, payment mode, frequency of shopping, connection time to internet,

credit card ownership.

The factors concerning social marketing were quantified by 26 statements/attributes judged

on 5 point Likert scale. The design of the questionnaire was to compare the attitude of

students towards social marketing based on their education and income level. The factors

were selected basis the influential effect of social marketing on the student community’s

perception and purchase intension. The selected factors are – Inspiration, Discovery, Peer

Reviews, Convenience, User Experience, Selection, Finding Ideas, Sharing Purchases,

Unbiased Comments, and Validating Choices.

4.3 Analysis & Interpretation

Table 1: Component Matrixa

Component

1 2 3

Inspiration .921 .241 -.077

Discovery .969 -.098 .000

Peer Reviews -.394 .732 .097

Convenience .882 .432 .018

User Experience -.948 -.169 -.146

Selection .320 -.382 -.766





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In the first step factor analysis was conducted to get smaller set of variables which are

relatively uncorrelated from the larger set of variables. After getting a manageable size

Principal Component Factoring was performed to extract the related factors followed by

Varimax rotation to get simpler interpretations of the factors. The 3 factors extracted after

conducting the rotation analysis are – Discovery, Peer Reviews and Sharing Purchases

(Table 2).

Table 2: Descriptive statistics

4.4 Univariate analysis of the sample

Out of 202 respondents 72% were females and rest 28% were males. The other demographic

dimensions of the questionnaire consist of Education level, Family Income, Age and Marital

Status. Education Level was categorized into Secondary School, Senior Secondary,

Graduation, Post-Graduation, and Doctoral Program whereas the Family Income had a range

of 5 brackets starting from less than INR 50,000 a month to more than INR 500,000 a month.

Demographics and the lifestyle characteristics of the student communities play an important

role in determining the buying habits (Mahmood, Bagchi & Ford, 2004). The two-away

Finding Ideas .953 .162 .144

Sharing Purchases -.216 -.314 .852

Unbiased Comments -.936 .183 -.212

Validating Choices .394 -.782 .121

Extraction Method: Principal Component Analysis.

a. 3 components extracted.





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ANOVA process was further used to analyse the factor scores against the variables –

education level and income bracket. Previous studies have reported that Literacy and

maturity level have an important influence on the shopping experience; it also affects attitude

toward online shopping (Hashim, Ghani and Said 2009).

Table 3: represents the correlation matrix for the various interrelated factors.

Inspiration DiscoveryPeer

ReviewsConvenience

User

ExperienceSelection

Finding

Ideas

Sharing

Purchases

Unbiased

Comments

Validating

Choices

Inspiration 1.000 .864 -.153 .925 -.861 .310 .866 -.281 -.807 .170

Discovery .864 1.000 -.484 .814 -.881 .320 .886 -.188 -.927 .430

Peer

Reviews-.153 -.484 1.000 -.032 .269 -.343 -.221 .001 .466 -.518

Convenience .925 .814 -.032 1.000 -.894 .118 .895 -.289 -.740 .011

User

Experience-.861 -.881 .269 -.894 1.000 -.102 -.985 .164 .870 -.255

Selection .310 .320 -.343 .118 -.102 1.000 .122 -.467 -.238 .337

Finding

Ideas.866 .886 -.221 .895 -.985 .122 1.000 -.165 -.882 .304

Sharing

Purchases-.281 -.188 .001 -.289 .164 -.467 -.165 1.000 -.060 .217

Unbiased

Comments-.807 -.927 .466 -.740 .870 -.238 -.882 -.060 1.000 -.506

Validating

Choices.170 .430 -.518 .011 -.255 .337 .304 .217 -.506 1.000

Correlation

a. Determinant = 1.843E-007

Correlation Matrixa

On the similar ground, Income levels equally affect the student communities online purchase

intension (Zukowski and Brown, 2007). Monsuwe, Dellaert and Ruyter (2004) reported that

consumers with higher household income intend to shop more on internet than lower income

consumers do. Teo (2006) found that online shopping adopters tend to have higher income

level than non- adopters. The resultant 3 factors extracted from the factor analysis were

plotted against the demographic variables under study – income and education level (Table 4

and 5) followed by 2-way ANOVA. The purpose of the research paper is to evaluate the role

of education and income level against each factor attribute (Table 6). As per the tables 4 and

5 comparing means of the factors against the income level and education level. The results

predict that 10th grade students are more interested in sharing their purchases amongst their

contacts (=3.19), the post graduates and the doctoral candidates are more interested in

discovering and finding ideas through social marketing (= 3.25), on the contrary the 12th

grades students are little more mature and are inclined towards the peer reviews (=2.38).

Thus social marketing is the intriguing offspring of “Social Shopping” which results in

growing up the business, the marketer’s just need to leg up and concentrate on the factors that

are involved. Henceforth it is undoubtedly concluded as Online Research and Discovering

Ideas received from social marketing leads to purchase; peer reviews and recommendations

delivers credibility to the student population. As per table 5 the students with higher

household income intend to shop more online than lower income consumers. As seen in

Table 6, there exists no relation between Family Income and the Education Level for all the

three extracted factors as the p value is not less than .05 in any of the cases. The level of

significance varied from .028 to .667 for the three factors which is greater than .05 for all the

cases except the Discovery factor and the Family Income.





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Table 4: Discovery peer reviews sharing purchase*_Education_level

Table 5: Discovery peer reviews sharing purchase*_family income





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Table 6: 2 - way ANOVA Tests of Between-Subjects Effects

Source

Type

III Sum

of

Squares

df Mean

Square F Sig.

Dependent

Variable :

Discovery

Education_Level 3.249 4 .812 .789 .543

26.177 25.432 1.029b

Family_Income 9.987 3 3.329 3.251 .028

59.347 57.951 1.024c

Education_Level

*

Family_Income

11.405 11 1.037 1.021 .429

Dependent

Variable :

Peer

Reviews

Education_Level 3.361 4 .840 .784 .547

24.834 23.161 1.072b

Family_Income 2.178 3 .726 .705 .554

51.874 50.375 1.030c

Education_Level

*

Family_Income

12.477 11 1.134 1.184 .301

175.374 183 .958d

Dependent

Variable :

Sharing

Purchases

Education_Level 4.209 4 1.052 .790 .541

41.383 31.059 1.332b

Family_Income 10.770 3 3.590 2.531 .063

107.488 75.791 1.418c

Education_Level

*

Family_Income

13.277 11 1.207 .772 .667

285.956 183 1.563d

Thus, it can be said that there exists a relationship between the discovery of particular good

or service online and the Family Income. Henceforth accepting the Hypothesis 1, there

existed no relation between Education Level and Income Level. The interaction between the

other factors could not be established as there is no value less than .05; the variables thus

need more in-depth analysis. Considering the Discovery Factor, which signifies finding and

researching ideas online on varied social mediums, the p value for income level is less

than .05, which signifies that a relationship existed between the family income and the

respondents thus we reject Hypothesis 2 for the foresaid factor.

For the Peer Reviews factor, it is very prominent that there is no relation between both the

demographic variable – family income and education factor. The p values for the peer review

sector varied from (p=.30 to p=.55) which is way higher than .05, thus signifying no

interaction. In other words, there existed no difference between the students’ responses

coming from different income brackets or studying at varied educational level with respect to

their purchase intension from Peer reviews point of view. Both the students groups accepted

that they give importance to the reviews, comments and feedbacks of the friends and peers

posted on social mediums while considering any purchase online. Taking into account the

factor - Sharing Purchases, there is no relation between family income and education level,

(p=.6676) signifying that regardless of the income bracket the students fall in and the level of

education they are pursuing, they are inclined towards sharing what they have bought on

different social mediums. The might share by posting pictures of the product or taking selfies





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with it. However, the family income had a p value .063 which is very close at 5 percent

significance level, thus it can be stated that the higher pocket moneys students get more are

their chances of sharing their purchases on social mediums Summarizing, there was no

interaction effect between income level and educational level in all the factors that were

evaluated. Hypothesis 1 was thus supported. For income level, main effect existed in the

‘Discovery’ issue only. Hypothesis 2, which stated that there existed no difference between

students from different income level, was supported for 2 factors only – Peer Reviews and

Sharing Purchases. For income level, a significant interaction existed for Sharing Purchases

which is one of the 3 factors. In context of this, Hypothesis 3 was partially supported for

Sharing Purchases amongst respondents for students with different household income.

4.5 Recommendations

Previous research has been conducted to explain the strategies and predictors of online

behavior (Bellman, Lohse and Johnshon, 1999). There are studies which elucidate the online

shopping trends and positive attitudes of students (Acilar, 2012) (Rahaman 2014). This

research focusses on converting the mere presence of student communities on social media

into their purchase decisions. It will also help marketers, brand managers and strategists to

work upon the attitudes student communities possess while making a purchase whist being

present on varied social mediums.

It is very well known, in this day and age how social mediums has become the new

communication tool surpassing even the emails. Henceforth the requirement is to effectively

manage and strategically implement this naïve medium in context of student communities.

4.6 Limitations

1. The study is based on survey of student communities in National Capital Region of India,

which means there are other significant market factors like culture, competitors which

have not been touched upon in this research paper.

2. The surveys are based on non-probability sampling.

3. Majority percentage of students fall under graduates, therefore the information provided

is not evenly distributed among all the segments.

5. Conclusion

Social Marketing has influenced the student communities in variety of positive aspects –

convenience, user experience, selection and so on. The primary purpose of social marketing

is thus gaining a higher value in today’s economy as a consumer is heavily attracted by the

choices his/her peer makes which has in turn influenced marketers to sell their products

through social mediums.

With this research it was sure that social medium has dominated every aspect of purchase

considerate student communities. From searching ideas on Pininterest to researching reviews

on mediums like Blogs, Facebook and Twitter to sharing the pictures of their purchases on

Instagram, the complete process of online shopping is driven by Social Marketing. Social

marketing is a more complex form of marketing that brings together all of the different

aspects including behavioral changes. It adds the psychological part to the fundamentals and

concepts of marketing.





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Henceforth, when we look at student communities, social marketing and online shopping are

attracted like the two opposite poles of the magnet; the attraction force will only be effective

if the two are placed in the purview of each other. The presence of students on social

mediums should be focused and effectively managed to convert this presence into purchase.

Thus, it is rightly said that understanding of behavior and perception of students on social

media sites is the key to a lock called online marketing.

5.1 Future Work

During the work with this research paper, some questions suitable for the future research

were raised. Firstly, during our first limitation we only covered one Metropolitan of India.

There are several other cities where students’ perception and experiences may vary. The

different areas therefore can be studied. Also the research has left us wondering what

marketing and digital media marketing strategies could be adopted to attract more students

through these channels of shopping. Can these social media channels be considered as touch

points? Can we adopt the touch point management strategies for varied social mediums?

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