Volume 1

IMPACT OF CONSUMER ATTITUDE ON ONLINE VIDEO ADVERTISEMENT FACEBOOK AS A PLATFORM

 

Nadeem

Mujtaba

 

Abstract

Social media play a vital role in organization sales as well as also collect the information from customer through social media platform such as YouTube, Facebook, twitter etc. After collection of feedbacks they can make the product as per customer need. Past practices were different such as organization provides the information through “state of art website”, “static website”. “State of art website” which allows online transaction with distributor beside that “Static website” just provides the information about product such as pharmaceutical organizations. Aim to identify the consumer’s attitudes on the online video advertisement. Our research will show the reaction on 10 second advertisement while watching video or start the video. Aim to determine the consumer’sintension and attitude on online video advertisement through these variables entertainment, Informative, irritation, celebrity and credibility. Our research will be beneficial for advertisement agencies. We took 400 samples from Facebook users. We performed the testes and calculate the impact on dependent variable and their relations between them. And did this through CFA, EFA t-value significance, hypothesis, regression, correlation, reliability of model, alpha by software’s using excel, Amos, SPSS. We were conducted the research and took the data through social media plate such as Facebook, further social media platforms can be used and also increase the sample sizes and can be used the other areas as a respondent. This research will help you to make advertisement after reading the quantitative result of our research.

 

Keywords: consumer attitude, online video advertisement, consumers purchase behavior.

 

Introduction

Overview & Background

 

        Internet and social media have substantial influence of operational and business success (bennett, sue;, 2012). Few years ago, marketer were send information toward consumer using one way communication through Ads, newspaper and radio but now a days has the facility of two way communication means marketer can give the information about product and customer can give the feedback about product through social media and internet.(Parker, 2011; Boyd & Ellison, 2007). Internet gives the equal opportunity to each to use social media (Gruzd, Anatoliy; Wellman, Barry; Yuri, Takhteyev;, 2011), however social media provides the platform to interact with each other without physical meeting (Gruzd, Anatoliy; Wellman, Barry; Yuri, Takhteyev;, 2011). Social media is that platform where can every person share and access information (chen, Jianqing ; Xu, Andrew; Whinston, Andrew B, 2011a). Social media is an effective platform for social interaction and sharing information (Hsi, Lu -Peng; Hisao, Kuo -Lun;, 2010). Social media playing a vital role in new era everyone can send and receive the information easily (chen, Jianqing ; Xu, Andrew; Whinston, Andrew B, 2011a).

 

        Since 1990 internet are receiving high level of attention therefore most of the industry adopted it, therefore most of the organization are using State of art websitewhich allows online transaction with distributor, while other organization such as pharmaceutical are using static website which just provides information about product and most of the organization are using social media platform for advertisement and provides and receives information as well. (I.e. Facebook, twitter) and most of the organization hasn’t website and social media account (Shaltoni, 2017). SmallBusinesses are facing new challenges in new competitive era just because of that rising variety and uncertainty market demand as well as strong competition (Development, 2009; Commission, 2014). Therefore, Organization can send and receive information through social media and maintain their competitive position and build strong relationship with customer, it will help in sales performance (Harold, Bendavid, & Lefebvre, 2009; Harrigan, Ramsey, & Ibbotson, 2012; Nguyen & Waring, 2013; Román & Rodríguez, 2015; Abebe, 2014; Bocconcelli , et al., 2016).

 

        Social media is a novelty for business development and Business growth in academic and managerial (Ngai, Moon, Lam, Chin , & Tao, 2015; Heikki, Nora, & Pauliina, 2015)While, deeply research has been done in consumer relation and customer supplying process on the reference of large companies marketing behavior (Culnan, McHugh, & Zubillaga, 2010). Social mediaprovides various opportunities to firms, such as build brand popularity (De, Gensler, & Leeflang, 2012) as well as provides the facility word of mouth (Chen, Fay, & Wang, 2011b) helps in increase sales (Agnihotri, Kothandaraman, Kashyap, & Singh , 2012) sharing information as well (Lu & Hisao, 2010) as well as build social supports for consumer (Ali, 2011; Ballantine & Stephenson, 2011). Social media has become a major marketing force (Gensler, Völckner, Liu, & Wiertz, 2013) and provides the facility for business to become very attractive (Chen, Fay, & Wang, 2011b).

 

        Social Media keeps engage the consumer with organization as well as can interact with each other through internet (Hajli, 2014). Social networking sites are tremendous technology where we can interact with each other as well as can send the information and receive the information (Lu & Hisao, 2010). Social networking sites are playing a vital role in e-commerce in current era (Fue , Li , & Wenyu , 2009), where consumer interacts with each other and participates in activities (Mueller, Hutter, Fueller, & SC, 2011). However consumers have the information and experience about product and consumer are giving the information, sharing the experience of product and recommending through social media which is good sign that customer is marketing your product (Do, Jumin , & Ingoo, 2007).

         

           Social media is a way to communicate with internal and external source, and traditional mass media is also communicates but through TV, radio, newspaper it is known as conventional communication media (Jashari, 2017).  Social media is one of the tremendous opportunities for organizations; companies can engage the customer and interact with consumer directly and can build strong relationship with customer as well as convince the customer that our product can facilitate you as per your requirement (Mersey, Malthouse, & Calder, 2010).

 

Problem statement

 

Now days the social media is a very important part of life it’s commonly used by a big number of people. Every person has the virtual social life with the account on social media there are many website and platforms. we live in technological ages in that the social life on finger tips and access very easily almost everywhere to connect through the internet websites for free by the new update information technology (boyd & Ellison, 2008).As internet world stat reported that internet user in the global more than 3 billion in 2014 (internet world stat , 2014). The around 2.4 billion account made on social media by users reported in 2011 (Chitu & Tecau, 2012). The online video advertisement now a very common on the many platforms and sometime better than the TV advertisement and it’s a great opportunity for the companies. There is some normal and viral stealth video and advertisement People react on auto play video advertisement. A study focused online video advertisement and took the YouTube as a platform social media has many site and do different kind of promotion of video ads and that study had limitation of YouTube as a social media platform so it can be the further more platform to analyses the users behavior and attitude experience through other online video websites took the factor like irritation, information, attitude, entertainment(Yang, Huang, Yang, & Yang, 2017). Another study consumer behavior on social media marketing and the research paper is descriptive and exploratory, primary and secondary both data integrated through different areas of social media and researcher recommended for further studies in different way to market product and services through the popular present trend and techniques (HUSAIN, GHUFRAN, & CHAUBEY, 2016). One more research does on attitude toward social media. There was the study to analysis the behavior of consumer on the advertisement online social media so they have bound on limited variable and acceptance of ads on social network ads so it can be the online video advertisement also to analysis consumer behavior toward a platform (cretti, Furrer, & Arifine, 2015). So the researcher finds out the gap or problem is that the consumer behavior on the online video advertisement on the Facebook because the now a day the Facebook is the one of largest social media platform that most users communicate and connect to their social circle that also sharing of video and people used to watch videos, viral stealth video there is also an opportunity for the channel holders and companies or enterprise to earn profit and make a revenue. The factor and model we can use in that irritation, awareness, and information we can gather. That will be helpful to gather influence of consumers through online video advertisement on Facebook.

 

Research objective

 

To determine the consumer’s intention, behavior, and attitude on the online video advertisementAttitude will be defining the negative and positive feeling about concern activity and relationship with the purchase behavior, shopping intension and adoption also identify Consumers preferences about products which type of products consumers are interested. Our Research is descriptive with Qualitative data took from the user of social media plate form Facebook try to collect a big number of sample and took very exact result from the both gender and different age group. And how much they influence through the popular personalities, public figure celebrities and follow them. And result of the knowledge and information awareness, how much the consumer believing on that kind of advertisement as credibility and their attitude on a big impact is entertainment the message of video music with the uses of graphics or funny or serious messages. Starting and ending of the video advertisement, we analyzed the attitude of the consumer’s. How much the consumer irritates, disturb because the mind diverts some time when you watching your concern video or listing someone on a serious topic but suddenly the video comes in for the 10 second you have to watch then after 10 second you will be able to skip video and continue your concern video research will be providing nearest percentages of the irritation of consumers. Do consumers adopt or purchase the product after watching online video advertisement so what’s their percentage with some age groups because different age groups lead to different interest, intention influences. And how many consumers ignore the online advertisement so our research will show the behavior and attitude that why consumers are ignoring the online advertisement. Our study shows that the behavior of the consumer such as when consumers watch the advertisement on video so what do they feel. By considering these frameworks with variables, we will identify their preference or priorities on purchase attitude with the age group. We will be able to capture the clearer image of the consumers on this phenomenon of the work.

 

Literature Review

 

Celebrities

 

“Nowadays many companies use celebrity endorsement as an effective advertising strategy and one in four advertisements use celebrity endorsement to get the competitive advantage” ((Kamins, Brand, Hoeke, & Moe, 1989) and (Pughazhendi & Ravindran, 2012) that is the push to companies sales advertisement by a famous personality, public figure lead to makes word of mouth. “Using celebrities can help companies to create unique ads and engender a positive effect on the attitude and sales intention towards the brand”.(Ranjbarian, Shekarchizade, & Momeni, 2010), people like and what to do like their ideal and favorite personality and follow his/her way of doing things that leads to increase the sale of company by using celebrities. “Already in 1979 one in every six commercials used a celebrity and in 2001 that percentage grew to 25%”. (Erdogan, Baker, & Tagg, 2001), public figure, famous personalities in ads lead to increase the profit margin and views that increase to sales.

 

Irritation

 

“Irritation has the potential to divert attention from worthy social goals, that annoyed loses the focus intention of the consumer and message will ignore”. (Galbraith & Crook, 1958), “dilutes human experiences that reduce the uses” (Boorstin, D.J., Wright, J.S., Mertes, & J.E., 1974)“and exploits human anxiety and fondly possessed hopes” it lead to change the mind and negative impact (Schudson, 2013). It can be caused by the organization of a website which confuses and distracts consumers it don let the consumer to attention to what is the purpose and for what it is. (Chen, 1999)(Gao & Koufaris, 2006). “Suggested that an unintended outcome from visiting a website may be a user’s feeling of irritation, that divert the mind and the mentality on that” (Ducoffe, 1996) “thought that consumers were likely to perceive advertisements as an unwanted irritation if they used annoying, offensive, insulting or overly manipulative techniques, and identified the annoyance or irritation they caused as the main reason why people did not like advertisements”. Consumer and people ignore usually that kind of suddenly come the messages in their own working or it irritate very much main goal of the advertisement destroyed.

 

Credibility

        

        “the extent to which the recipient sees the source as having relevant knowledge, skills, or experience and trusts the source to give unbiased, objective information”(Belch & Belch, 1994), it depend on the visual message and how try to convey the message and what kind of basis using with neutral and true way. According to (Brackett & Carr, 2001) and(Erkan & Evans, 2016), “credibility refers to whether or not people trust the content of advertisement” what is the point consumer or people belief in your product or services. “It also indicates the trustworthiness or usefulness of advertising. It has been postulated that credibility has a direct relationship with both advertising value and attitudes toward advertisements” (Eighmey, 1997).how much to consumer trust on your advertisement and what way you use to get trust of the consumers.

 

Entertainment

 

(McQuail, 2010) “indicated that the value of entertainment lies in its ability to fulfill audiences' needs for escapism, diversion, aesthetic enjoyment or emotional release; a view which is also extended from the UGT” to let them some enjoyment to take their attention toward your product by enjoying that kind of message. (Ducoffe, 1996) “Also confirmed that the ability of advertising to entertain can enhance the experience of advertising exchanges for consumers”. That is good way to change their emotion and people want some diversion and out of “idea things other researchers have found that pleasant or likeable advertisements can have positive impacts on brand attitudes”(Mitchell & Olson, 1981).that influence their way of doing thing and uses of product or services.

 

In formativeness

 

Means that “consensus exists with regard to the ability of advertising to inform consumers of product alternatives”, “and accordingly, the satisfying decision of purchasing can be made” (Schlosser, A.E, Shavitt, S, Kanfer, & A., 1999), a way to give information according to your product makes easy to make acquiring decision. “The concept is extended from the users and gratification theory (UGT). The UGT is an approach to realizing why and how people actively seek out specific media to satisfy specific needs”. How the people fulfillment of their desire comes through the information? “The UGT is an audience centered approach to understanding mass communication. It assumes that video viewers are not passive consumers of media. Rather, these viewers have power over their media consumption and assume an active role in interpreting and integrating media into their own lives” (Luo, 2002), how the advertisement convey the message and what kind of informative giving in ad for what target market is concern. Unlike other theoretical perspectives, the UGT assumes that audiences are responsible for choosing media to meet their desires and needs to achieve gratification (Ruggiero, 2000), “must be the good way to satisfy consumers by the way they want to inform. Many studies have shown the importance of in formativeness to attitudes toward online advertisements”(Andrews, 1989) it is the compulsory to inform about the product properly to fulfill the consumer’s desire.

 

Relationship Between the Variables

 

All variables are based on human feelings that if consumer watches the advertisement so what doeshe feel, feels entertainment, irritation, informative either credibility, these all are the variable of attitude.

 

 Relationship between attitude, intension, and behavior

 

A person intention comes from his or her behavior and behavioral intention comes from both the attitude of a person and the subjective norm related to the behavior (webster, Trevino, & Ryan, 1994). Beside that theory is showing the relationship between attitudes and behavior within human activity. So its means that attitude is defined as a positive and negative feelings of a person about making an action (webster, Trevino, & Ryan, 1994). Most of the researches are providing the evidence of the relationship between behavior and attitude (Ajzen, 1991).

H1: There is a significant relationship between B and ATT

H2: There is a significant relationship between AD and INT

H3: There is a significant relationship between INT and ATT

 

Impact of behavior, Attitude and adoption

 

Adoption behavior has been defined as the degree to which an individual adopts a new product relatively earlier than other members in his or her social system(Rogers & Shoemaker, 1971). The expectancy-value model states that attitudes develop from the beliefs that people hold about the objects of those attitudes. In this study, “attitude” refers to an individual’s favorable or unfavorable evaluation of adoption (Fishbein & Ajzen, 1975)

H1: There is a significant relationship between AD and B

H2: There is a no significant relationship between AD and ATT

 

Relationship between informative, irritation, information’s, credibility, celebrity, and attitude

 

Informative means that informs about the existing product either alternative or substitute product, this information will help in purchasing decision (Schlosser, Shavitt, & Kanfer, 1999). Most of the previous studies have already shown that relationship between attitude and informative (Andrews, 1989).

 

Irritation can divert the intention (Galbraith & Crook, 1958) mix-up human experiences (Boorstin, Wright, & Mertes, 1974) and exploit human anxiety (Schudson, 2013) so according to the research irritation has closely relationship with attitude.

 

Entertainment helps to fulfill audience needs through emotional and funniest advertisement, (McQuail, 2010) beside that previous study found that pleasant and emotional advertisement can be positive impacts on brand equity (Mitchell & Olson, 1981).

 

Credibility indicates trustworthiness of advertisement and credibility refers that consumer trust the content of advertisement or not (Brackett & Carr, 2001) and (Erkan & Evans, 2016). Credibility has a direct relationship between advertising and attitude (Eighmey, 1997).

 

Celebrity (Martin, Cayanus, McCutcheon, & Maltby, 2003)suggested that self-efficacy relates to cognitive flexibility, thus it is hypothesized that there is a relationship between attitudes towards celebrities and self-efficacy beliefs

H1: There is a significant positive relationship between ATT and E

H2: There is no significant relationship between ATT and INF.

H3: There is a significant relationship between ATT and IRR

H4: There is a significant relationship between ATT and CRE

H5: There is a significant relationship between ATT and CEL

 

 

Methodology

 

Method of data collection

 

In that research we are going to collect data secondary approach and by the questionnaire based on our variables and model and our respondents are social media users specific to Facebook. We took data from different people, are university students and office workers male female both above age 16. We took that data for benefits to the marketing. And make the social media marketing more effective and improve the sales of the product and services. We took the data online and by physically the accurate data is not easy given so we started meet people. We put more effort to collect actual data and total questionnaire we distribute were the around 400 most were youth between 18 to 26 and received 300 then we excluded around 135 are invalid and doubt some was incomplete so we finalized included the data of 165. That was difficult to took actuate data from respondent now a day’s people are very busy in their activities. No our people do not respond social activities and do not give importance so that why not easy to took the data, we requested some people in different offices are work on social media and user of Facebook, but they do not give the data first time we visited two to three times and took data from them but again some gave incomplete data. Then we go to the universities and ask for the data and showed the request letter from the university, they allowed us 2 classes around 50 students and only 15 was the accurate, for the accurate data we meet in break time individually and took the data. Then also took data from our university and friend who are Facebook users and very up-to-date knowledge seekers, from them we took the accurate and detailed data and also we took the data from the student in lobby and meet and interact individually and took their data.

 

Sampling        

 

        We distributed 400 questionnaire papers on social media (Facebook) as well as distributed in the premises of the KASBIT (lobby). Participant was voluntary taking a part and approximately we took two days for all the process of data collection.

 

        We received 300 responses from respondent, and 135 were invalid so removed that from questionnaire, we were left with 165 usable questionnaires. We took data from both boys and girls, whose uses the social media platform such as Facebook.

 

Statistical Techniques

           

 We applied two-way approaches; we checked the reliability and validity of the variable and also found the beta of direct and indirect relationship as well as applied statistical tools, regression, alpha, coefficient of variance through SPSS & Amos.

 

Result

 

Descriptive Analysis

 

Frequency Table

 

Age Group

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Below 20 Years

29

17.6

17.6

17.6

21 to 30 Years

118

71.5

71.5

89.1

31 to 40 Years

10

6.1

6.1

95.2

41 to 50 years

5

3.0

3.0

98.2

51 and Above

3

1.8

1.8

100.0

Total

165

100.0

100.0

 

 

 

 

 

 

 

Gender

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

106

64.2

64.2

64.2

Female

59

35.8

35.8

100.0

Total

165

100.0

100.0

 

 

 

 

 

 

 

Qualification

 

Frequency

Percent

Valid Percent

Cumulative Percent

 

 

 

Valid

Metric

13

7.9

7.9

7.9

Intermediate

40

24.2

24.2

32.1

Bachelor

72

43.6

43.6

75.8

 

 

 

 

 

Master

27

16.4

16.4

92.1

Diploma Certificate

13

7.9

7.9

100.0

Total

165

100.0

100.0

 

 

 

 

 

 

 

 

 

 

The demographic variable age consists of 17.6% below 20 years, 21-20year are 71.5%, 31-40years are 6.0%, 41-50years are 3.0%, above 50years are 1% and but not part of our research that’s why we never used we took data from both gender with 35.8%females and 64.2% males we have big numbers of male because the female irritates and do not want to participate in that kind of researches feel some insecure. also got the data about the qualification of our respondent’s percentage of metric 7.9%, intermediate 24.2%, bachelor 43.6%, master 16.4% and diploma certificate are 7.9% location we took from data are SMCHS are majority and other from different areas in Karachi SHAHFAISAL model colony, KORANGI, steel town and SADDAR area

 

Construct reliability

 

CFA (confirmatory analysis)

 

 The results are accurate as they show Cornbrash’s Alpha values to be above than 0.7. It shows that the questionnaires internal consistency to predict the results is better. Whereas, AVE values are above 0.50, CR values are also above 0.7 which shows accurateness, while the discriminant validity i.e. ASV is also as per the required standard but some values of MSV shows in accurateness.

 

 

 

 

Construct/Indicators

 

Standardized Factor Loading

(CFA-AMOS)

Construct Reliably

Construct Validity

Cronbach’s alpha

Composite Reliability

(CR)

Convergent Validity

Discriminant

Validity

Average

Variance Extracted

(AVE)

Maximum Shared Variance (MSV)

Average

Shared Variance (ASV)

ENTERTAINMENT

0.924

 

0.922

 

 

0.798

0.4628

0.3283

1

.88

2

.91

3

.89

INFORMATION

0.889

0.894

0.678

 

 

0.3844

0.2705

1

.77

2

.86

3

.83

4

.83

IRRITATION

0.892

0.915

0.781

 

0.0049

0.074

1

.89

2

.92

3

.84

CREDIBILITY

 

0.835

0.850

0.655

 

0.3844

0.25028

1

.77

2

.90

3

.75

CELEBRITY

 

0.840

0.839

0.635

 

0.5184

 

0.2961

1

.81

2

.82

3

.76

ATTITUDE

 

0.731

0.732

0.578

 

0.5776

 

0.4148

1

.74

2

.78

BEHAVIOR

0.751

0.766

0.623

 

0.5041

 

0.2513

1

.70

2

.87

INTENTION

 

0.762

0.767

0.524

 

0.5929

 

0.4023

1

.77

2

.71

3

.69

ADOPTION

 

0.746

0.751

0.603

0.5929

0.3309

1

.73

2

.82

Reliability and Construct Validity Thresholds:

[Suggested by Fornell and Larcker (1981)]

α > 0.70

(Nunnaly,1967)

CR > 0.70

i) AVE > 0.50

ii)   CR > AVE

MSV < AVE

ASV < AVE

 

 

     ,     

Where λ=Standardized Factor Loading; n=number of items;δ= error variance = (1- multiple correlation coefficient) =

Share Variance (SV): Square of the Correlation, If the correlation between two variables is “X”, their shared variance will be “”.

 

Ref: Fornell, Claes and David F. Larker (1981), “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, 18, 39-50.

 

Model Fitness

 

In order to measure the model there are some standards or mark set. This study has taken seven indices which are Chi-square/df, P. Value, Goodness-of-Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index, Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA). Mostly the values reached threshold i.e. of CITATION Hai \l 1033 (Hair, Black , Babin, Anderson , & Tatham , 2006)CITATION Hai \l 1033 (Hair, Black , Babin, Anderson , & Tatham , 2006). After modification CFI, TLI, P value and Chi-square reached threshold level while RMSEA GFI and AGFI showed better results that are near threshold values.

 

MODEL FITNESS TEST:

 

Chi- square/df

P-Value

GFI

AGFI

CFI

TLI

RMSEA

1.670

0.000

0.843

0.787

0.936

0.920

0.064

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

After model fitness test

 

Chi- square/df

P-Value

GFI

AGFI

CFI

TLI

RMSEA

1.570

0.000

0.853

0.799

0.946

0.932

0.059

 

Table 04 hypothesis testing using mediation analysis:

 

 

Two Tailed Test

 

Indirect Effect

 

In order to test the mediation, we have taken Entertainment, Information, Irritation, Credibility and Celebrity as Sub variables and Attitude as Independent variable whereas we have taken Adoption as a Dependent variable and Behavior, Intension as a mediator. The indirect effect of IV is showing significant relationship at 0.05 confidences. Thus, the model proposed show Full mediation, Result are shown below

 

 

We have tested the data and we have found that in the presence of mediator (B) and (Int) there is no impact of IV (Att) on DV (Adp). Thus shows no direct effect.

 

 

Hypothesis(es) Assessment

 

 

R2

Beta

P value

ATT ß E

 

 

 

 

        .56

.663

.000

ATT ß INF

.124

.072

ATT ß IRR

.186

.009

ATT ß CRE

.385

.000

ATT ß CEL

.634

.000

B      ß  ATT

.508

.000

INT   ß  ATT

.740

.000

AD    ß  ATT

.001

.994

AD    ß  B

.298

.007

AD    ß INT

.583

.002

 

 

Hypothesis

Accepted / Rejected

H1: There is a significant positive relationship between ATT and E

Accepted

H2: There is no significant relationship between ATT and INF.

Rejected

H3: There is a significant relationship between ATT and IRR

Accepted

H4: There is a significant relationship between ATT and CRE

Accepted

H5: There is a significant relationship between ATT and CEL

Accepted

H6: There is a significant relationship between B and ATT

Accepted

H7: There is a significant relationship between INT and ATT

Accepted

H8: There is a no significant relationship between AD and ATT

Rejected

H9: There is a significant relationship between AD and B

Accepted

H10: There is a significant relationship between AD and INT

Accepted

 

Conclusion and Discussion

 

Our study shows that the proposed model which explain the variances in term of attitude toward advertisements on sites providing online video services such as FACEBOOK. We have used the model about to analysis the online video advertisement on Facebook as a platform social media we investigate consumer buying behavior and model we have used the gives the result about factors affecting consumer buying and his through the advertisement we took the factor variable which is checked irritation in formativeness, credibility, celebrity and entertainment have effect or persuade consumer attitude and then behavior and adoption of consumers. All variables are showing positive relationship with Attitude except information as well as positive relationship with behavior, intension and adoption. Most of the variables are showing significant result except information relation with attitude. Results are showing that independent variable is significant and dependent variable is insignificant so it is a full mediation. After the conducting the data from consumer then we used the data in CFA, Mediator and both are showing good result which are given above.

 

Limitations and Recommendations

 

There is several boundaries limitations in our study we selected the Facebook plate form from the social media to analysis people behavior attitudes specifically Facebook its combination of photo links and also huge plate form of sharing videos there are many other platform and sites  about streaming videos also we took only the online videos advertisements we limited to took data 165 sample and the majority were the student and took data from online internet and universities also some common people.

We recommended that further platforms about video advertisement can be done on DAILYMOTION, INSTAGRAM etc. And the sample sizes increased with another target market, model also improved by putting more variables for better results.

 

References

 

 BIBLIOGRAPHY Abebe, M. (2014). Electronic commerce adoption, entrepreneurial orientation and small-and medium-sized enterprise (SME) performance. Journal of Small Business and Enterprise Development, 21, 100-116.

 

Agnihotri, R., Kothandaraman, P., Kashyap, R., & Singh , R. (2012). Bringing ‘social’ into sales: the impact of salespeople’s social media use on service behaviors and value creation. Journal o f Personal Selling & Sales Management, 32(3), 333-348.

 

Ajzen, I. (1991). The theory of planned behavio. Organizational Behavior and Human Decision Processes, 50(2), 179-211.

 

Akhtar, M. N., Bal, M., & Long, L. (2016). Exit, voice, loyalty, and neglect reactions to frequency of change, and impact of change: A sensemaking perspective through the lens of psychological contract. Employee Relations, 38(4), 536-562.

 

Ali, H. (2011). Exchanging value within individuals’ networks: social support implications for health marketers. Journal of Marketing Management, 27(3/4), 316-335.

 

Andrews, J. C. (1989). The dimensionality of beliefs toward advertising in genera. journal of advertising, 18(1), 26-35.

 

Andrews, M. C., Kacmar, M., & Kacmar, C. (2014). The mediational effect of regulatory focus on the relationships between mindfulness and job satisfaction and turnover intentions. Career Development International,, 19(5), 494-507.

 

Arshadi, N. (2011). The relationships of perceived organizational support (POS) with organizational commitment, in-role performance, and turnover intention: Mediating role of felt obligation. Social and Behavioral Sciences.

 

Arumugam, S. (2014). Examining the impact of overqualification on employees’ job attitudes and behavior: evidence from banking sector employees in Srilanka. International Journal of Economics, Commerce and Management, 2(5).

 

Ballantine, R., & Stephenson, R. J. (2011). Help me, I’m fat! Social support in online weight loss networks. Journal o f Consumer Behaviour, 10(6), 332-337.

 

Barnett, B. R., & Bradley, L. (2007). The impact of organisational support for career development on career satisfaction. Career Development International, 12(7), 617-636.

 

bennett, s. (2012). ''social media is making a big impact on small business''. journal of small business and enterprisedevelopment, 611-632.

 

bennett, sue;. (2012). ''Impact of social media on small businesses''. JOURNAL OF SMALL BUSINESS AND ENTERPRISE DEVELOPMENT, 22(4), 611-632.

 

Bocconcelli , R., Cioppi , M., Fortezza, F., Francioni, B., Pagano , A., Savelli , E., et al. (2016). SMEs and Marketing: A Systematic Literature Review. International Journal of Management Reviews, 1-28.

 

Boorstin , D. J., Wright, J. S., & Mertes, J. E. (1974). The Thinner Life of Things. West Publishing, St. Paul,MN.

 

Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230.

 

boyd, d., & Ellison, N. B. (2008). history and scholarship. Journal of Computer-Mediated Communication, 13, 210-230.

 

Brackett, L. K., & Carr, B. N. (2001). Cyberspace advertising vs other media: consumer vs mature student attitudes. Journal of Advertising Research, 15(3), 23-32.

 

Caesens, G., Stinglhamber, F., & Ohana, M. (2016). Perceived organizational support and well-being: a weekly study. Journal of Managerial Psychology, 31(7), 1214-1230.

 

chen, Jianqing ; Xu, Andrew; Whinston, Andrew B. (2011a). Moderated online communities and quality of user-generated content. Journal of Management Information Systems, 28(2), 237-268.

 

Chen, Y., Fay, S., & Wang, Q. (2011b). The role of marketing in social media: how online consumer reviews evolve. Journal of Interactive Marketing, 25(2), 85-94.

 

Chen, Y., Friedman, R., & Simons, T. (2014). The gendered trickle-down effect: How mid-level managers’ satisfaction with senior managers’ supervision affects line employee’s turnover intentions. Career Development International, 19(7), 836-856.

 

Chitu, I. B., & Tecau, A. S. (2012, january 01). social media network advertisement. Bulletin of the Transilvania University of Brasov. Economic Sciences. Series V, 5(1), 31.

 

Commission, E. (2014). European Competitiveness Report 2014. Helping Companies to Grow, Commission Staff Working Document SWD (2014) 277.

 

Costigan, R. (2012). A Four-Country Study of the Relationship of Affect-Based Trust to Turnover. Journal of Applied Social Psychology, 42(5), 1123-1142.

 

cretti, c., Furrer, O., & Arifine, G. (2015, september 04). Consumers’ attitude. Faculty of Economics and Social Sciences.

 

Culnan, M. J., McHugh, P. J., & Zubillaga, E. I. (2010). How large US companies can use Twitter and other social media to gain business value. MIS Quarterly Executive, 9(4), 243-259.

 

De, V. L., Gensler, S., & Leeflang, E. H. (2012). Popularity of brand posts on brand fan pages: an investigation of the effects of social media marketing. Journal o f Interactive Marketing, 26(2), 83-91.

 

Development, O. f. (2009). The Impact of the Global Crisis on SME and Entrepreneurship Financing and Policy Responses, Centre for Entrepreneurship, SMEs and Local Development.

 

Do, H. P., Jumin , L., & Ingoo, H. (2007). The effect of on-line consumer reviews on consumer purchasing intention: the moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125-148.

 

Eddleston, K. A. (2009). The effects of social comparisons on managerial career satisfaction and turnover intentions. Career Development International, 14(1), 87-110.

 

Eisenberger, R., Armeli, S., Rexwinkel, B., Lynch, D. P., & Rhoades, L. (2001). Reciprocation of perceived organizational support. Journal of Applied Psychology, 86(1), 42-51.

 

Erdogan, B. Z., Baker, M. J., & Tagg, S. (2001). Selecting celebrity endorser: the practitioner’s Prospective. Journal of Advertising Research, 41(3), 39-48.

 

Erkan, I., & Evans, C. (2016). The influence of eWOM in social media on consumers’ purchase intentions: an extended approach to information adoption. Computers in Human Behavior, 61, 47-55.

 

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude intension And Behavior. An introduction to theory and research, Reading MA: Addison Wesley.

 

Fue , Z., Li , H., & Wenyu , D. (2009). Social factors in user perceptions and responses to advertising in online social networking communities. Journal o f Interactive Advertising, 10(1), 1-13.

 

Galbraith, J. K., & Crook, A. (1958). The Affluent Society, Houghton Miffin. Boston,MA.

 

Gensler, S., Völckner, F., Liu, -T. Y., & Wiertz, C. (2013). Managing brands in the social media environment. Journal of Interactive Marketing, 27(4), 242-246.

 

Gruzd, Anatoliy; Wellman, Barry; Yuri, Takhteyev;. (2011). A study of the impact of social media on consumers. International journal of market research, 56(3), 1294-1318.

 

Guerrero, L., & Hatala, J.-P. (2015). Antecedents of perceived overqualification: a three-wave study. Career Development International, 20(4), 409-423.

 

Hair, J., Black , W., Babin, B., Anderson , R., & Tatham , R. (2006). Uppersaddle River, N.J.: Pearson Prentice Hall. Multivariate data analysis (6th ed.).

 

Hajli, M. N. (2014). A study of the impact of social media. International journal of marketing research, 56(3), 387-404.

 

Harhara, A., Singh, S., & Matloub, H. (2015). Correlates of employee turnover intentions in oil and gas industry in the UAE. International Journal of Organizational Analysis, 23(3), 493-504.

 

Harold, B., Bendavid, y., & Lefebvre, E. (2009). B2B e-commerce adaptation for SME supplier. Journal of Business and Industrial Marketing, 24(8), 561-574.

 

Harrigan, P., Ramsey, E., & Ibbotson, P. (2012). Enterpreneurial Marketing in SMEs: the key capabilities of e-CRM. Journal of Research in marketing and Enterpreneurship, 14(1), 40-64.

 

Heikki, K., Nora, M., & Pauliina, U. (2015). The role of digital channels in industrial marketing communications. Journal of Business & Industrial Marketing, 30(6), 703-710.

 

Hsi, Lu -Peng; Hisao, Kuo -Lun;. (2010). The influence of extro/introversion on the intention to pay for social networking sites. Information & Management, 47(3), 150-157.

 

HUSAIN, S., GHUFRAN, D. A., & CHAUBEY, D. D. (2016, august). CUSTOMERS’ BEHAVIOUR TOWARDS SOCIAL MEDIA. ZENITH International Journal of Business Economics & Management Research, 6(8), 58-68.

 

Jashari, F. (2017). The impact of social media on consumer. Journal of Knowledge Management, Economics and Information Technology, 7(1), 258.

 

Johnson, J. G., & Johnson, R. W. (2002). Perceived overqualification, positive and negative affectivity and satisfaction with work. Journal of Social Behavior and Personality, 167-184.

 

Lobene, E., & Meade, A. (2013). The effects of career calling and perceived overqualification on work outcomes for primary and secondary school teachers. Journal of Career Development, 40(6), 508-530.

 

Lu, H. -P., & Hisao, K. -L. (2010). The influence of extro/introversion on the intention to pay for social networking sites. Information & Management, 47(3), 150-157.

 

Martin, M. M., Cayanus, J. L., McCutcheon, L. E., & Maltby, J. (2003). Celebrity Worship and Cognitive Flexibility. North American Journal Of Psychology, 5(1), 75-80.

 

Martinez, P. G., Lengnick-Hall, M. L., & Kulkarni, M. (2014). Overqualified? A conceptual model of managers’ perceptions of overqualification in selection decisions. Personnel Review, 43(6), 957-974.

 

Maynard, C. D., Joseph, A. T., & Maynard, M. A. (2006). Underemployment, job attitudes, and turnover intentions. ournal of Organizational Behavior, 27(4), 509-536.

 

McQuail, D. (2010). McQuail's Mass Communication Theory. SagePublications.

 

Meisler, G. (2013). Empirical exploration of the relationship between emotional intelligence, perceived organizational justice and turnover intentions. Employee Relations, 35(4), 441-455.

 

Mersey, R. D., Malthouse, E. C., & Calder, B. J. (2010). Engagement with Online Media. Journal of Media Business studies, 7(2), 39-56.

 

Mitchell, A. A., & Olson, J. C. (1981). Are product attribute beliefs the only mediator of advertising effects on brand attitude? journal of marketing research, 18(3), 318-332.

 

Mueller, J., Hutter, K., Fueller, J., & SC, M. K. (2011). Virtual worlds as knowledge management platform - a practice-perspective. Information Systems Journal, 21(6), 479-501.

 

Nazir, S., Shafi, A., Wang, Q., Nazir, N., & Tran, Q. (2016). Influence of organizational rewards on organizational commitment and turnover intentions. Employee Relations, 38(4), 596-619.

 

Neves, P., & Eisenberger, R. (2014). Perceived organizational support and risk taking. Journal of Managerial Psychology, 29(2), 187-205.

 

Ngai, E. W., Moon, K. K., Lam, S. S., Chin , E., & Tao, S. (2015). Social media models, technologies, and applications: An academic review and case study. Industrial Management & Data Systems, 115(5), 769-802.

 

Nguyen, T. H., & Waring, T. S. (2013). The adoption of customer relationship management (CRM) technology in SMEs: An empirical study. Journal of Small Business and Enterprise Development, 24(4), 824-848.

 

Parker, C. (2011). 301 Ways To Use Social Media To Boost Your Marketing. New York: McGraw Hill.

 

Purohit, B. (2018). Salesperson performance: role of perceived overqualification and organization type. Marketing Intelligence & Planning, 36(1), 79-92.

 

Ranjbarian, B., Shekarchizade, & Momeni, Z. S. (2010). Endorser Infl uence on Attitude Toward Advertisement And Brand. European Journal of Social Science, 13(3), 399-407.

 

Rogers, E. M., & Shoemaker, F. F. (1971). Communication of innovation. The Free Press, NEW YORK, YN .

 

Román, S., & Rodríguez, R. (2015). The influence of sales force technology use on outcome performance. Journal of Business & Industrial Marketing, 30(6), 771-783.

 

Schlosser, A. E., Shavitt, S., & Kanfer, A. (1999). Survey of internet users’ attitudes toward internet advertising. Journal of Interactive Marketing, 13(3), 34-54.

 

Schudson, M. (2013). Advertising, The Uneasy Persuasion (RLE Advertising. Its Dubious Impact on American Society, Routledge. .

 

Shaltoni, A. M. (2017). From websites to social media: exploring the adoption of internet marketing in emerging industrial markets. Journal of Business & Industrial Marketing, 32(7), 1009-1019.

 

Thirapatsakun, T., Kuntonbutr, C., & Mechida, P. (2015). The Relationships Among Four Factors and Turnover Intentions at Different Levels of Perceived Organizational Support. Journal of US-China Public Administration, 12(2), 89-104.

 

Tuzun, I. K., Kalemci, R. A., & '. (2012). Organizational and supervisory support in relation to employee turnover intentions. Journal of Managerial Psychology, 27(5), 518-534.

 

Tuzun, K. I., & Kalmeci, A. R. (2011). Organizational and supervisory support in relation to employee turnover intentions. Journal of Managerial Psychology, 27(5), 518-534.

 

Verhaest, D., & Omey, E. (2010). The determinants of overeducation: different measures, different outcomes? International Journal of Manpower, 31(6), 608-625.

 

webster, J., Trevino, L. K., & Ryan, L. (1994). “The dimensionality and correlates of flow in humancomputerinteractions”. Computers in human behavior, 9(4), 411-426.

 

Yang, C. C., Huang, C. H., Yang, C., & Yang, S. Y. (2017). Consumer attitudes toward online video advertisement. 849-853.

 

Ye, X., Li, L., & Tan, X. (2017). Mechanisms to affect perceived overqualification on turnover intentions: a study of Chinese repatriates in multinational enterprises. Employee Relations, 39(7), 918-934.

 

Zeffane, R., & Melhem, S. J. (2017). Trust, job satisfaction, perceived organizational performance and turnover intention: A public-private sector comparison in the United Arab Emirates. Employee Relations, 39(7), 1148-1167.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

<<Back