Impact of Online Advertising on Daily Users of Mobile Internet in Malaysia

Neel Wasantha1*, W.C. Dombepola2, F.A. Ibrahim2 & Raja Gopal2

1Uva Wellassa University 90000, Sri Lanka

2Lincoln University College 47301, Malaysia

*Corresponding Author’s Email: wasanthaneel@yahoo.com

Abstract

This dissertation researched impact of online advertising on daily users of mobile internet in Malaysia. Advertising using internet is a new platform for marketers to create awareness, increase brand loyalty and to identify the customers through their daily feedback. The aim of this paper is to examine the impact of online advertising on daily mobile internet users. Four features of online advertising are discussed and examined in the research, irritation, updating, respond, and personality of online advertisements to make the daily mobile users positive or negative thinkers and make them customers.

This study involving a survey of 100 sample size. The dataset underwent a statistical analysis, i.e., structural equation modeling (SEM). Findings reveal that features of online advertising do generate positive influence on purchase intentions. Results further reveal that the Pictures feature generates the highest possibility of consumers’ purchase intentions. Marketers will find these results useful as they can be used to maximize the impact of advertising efforts to generate purchase intentions especially in daily mobile internet users.

Keywords: Online Advertising; Mobile Internet; Mobile Users

Introduction

It's becoming increasingly tough to keep up with the rapid advancement of mobile phones. When we compare how things were in the past to how they are now, it is amazing to realize how much things have changed. With all their advantages, they have become indispensable in our life. Mobile phones, particularly smartphones, have become our constant companions in recent years. People can go without meals for a period but not without their mobile phones. The history of mobile phones, on the other hand, dates to 1908, when a US Patent for a wireless telephone was awarded in Kentucky. Engineers at AT&T developed cells for mobile phone base stations in the 1940s, which led to the invention of mobile phones. Although crude mobile telephones existed before the World War I, they were specifically modified two-way radios used by government or industry, with calls manually patched into the landline telephone network. Since the first cell phones were released, the evolution and history of the mobile phone have experienced a remarkable amount of change. Since then, many new cell phones or mobile phone systems have been introduced, as well as numerous enhancements in this sort of radio communications technology. Mobile phones, as well as supporting equipment such as base stations and other network equipment and cellular technologies, have gotten significantly less expensive and smaller.The rising market can grant business enterprise and advertising and selling potentialities to harness (Selvaraj, 2022).

Mobile phone users

The first mobile phones were exclusively available to the wealthy; however, with the rapid spread of mobile phone carriers and handset providers, along with improved technology at increasingly inexpensive rates, the majority now have access to basic devices. Like no other technological advancement, mobile phone technology has shrunk the gap between wealthy and middle/low-income countries. Low-income countries that lacked access to fixed-line technologies have jumped right to mobile communication. In terms of healthcare, the advancement of mobile phone technology has opened new opportunities in the medical area. The tale of the mobile phone and mobile communications is evolving to a new level, one that is less about the phone and more about how it is utilised. When mobile phones were widely available, the impact on our lives was immediate and profound: we could exchange critical information, frequently of a time-sensitive nature, without having to be at home or work, and without relying on the availability of a free phone line.

Online advertising

Online advertising is the way that the e-market finds an easy way to target regular customers by using internet as a medium to obtain website traffic and get the information and data colocation for next feature of product or service. The main target of online advertising is to deliver messages to the right customer. Online advertising includes distinguished advertising on banner ads, rich media ads, social network advertising, online classified advertising, and marketing email like spam ads. Online advertising provides many opportunities to improve consumer purchasing behavior by improving product identity or service information, qualifying direct multi-character evaluations, and lowering customer costs. Online advertising has an impact on consumer purchasing decisions by influencing factors such as security, privacy, and consumer perceptions. Consumers, on the other hand, must deal with salesperson they have never met and items that are intangible. This may lead to a reluctance to undertake business solely on the basis of information provided by EC merchants in the market, which may or may not be accurate. Traditional marketing philosophy has persisted in society despite changes, but the digital world has forced the current generation to embrace innovation. As a result, whatever marketing method was employed to acquire clients, consumer trust had to be built up.Advertisement can be defined as a paid form of promotion which is done through various mass mediums. With the help of advertising, marketers can create awareness and attitude about their product or service which leads to increase in sales, encourage customers and remind them to differentiate various brands and position them accordingly in their minds. Social media advertising has become one of the most important tools for promotion (Shubhangam et al., 2020).

Literature Review

Because of the rapid growth and spread of online technologies, the internet has become a valuable commercial asset for gaining competitive advantages (Kiang et al. 2000). In fact, the internet has evolved into a critical commercial infrastructure that aids marketers in understanding and satisfying a wide range of consumer wants (Constantinides, 2002). Different theories exist in the literature regarding online adverting and customers using mobile internet. These days, mobile internet users in worldwide are more persuasive (Internet World Stats, 2016). The rapid growth of the Universal Mobile Telecommunications System (UMTS) is an immense stimulator for this current trend. It is statistically proven that, in 2016, more than 50% of the worldwide population used a mobile device to connect to the internet. According to Campbell (2015), mobile device technology gives more opportunity to the market and customer without barriers to location and time in Western Europe. Gill (2014) reveals that the mobile innovation or penetration almost forecast in 2004 by reaching 90% was predicted to be 100%. However, at the end of 2004, the penetration almost exceeded 100% in several countries including Italy, Sweden, and the United Kingdom as customers used multiple phones, devices, and cards. However, what impact does this development have on mobile advertising? It is important to recognize that advertisements are the most important marketing tool (Kiang et al. 2000), and with the global expansion of the web as the ultimate communication medium (Eighmey & Mccord, 1998), it has opened a new chapter for online advertisements. With the current opportunities, online advertisements have become very popular, and a significant portion of the marketing budget has been allocated for online marketing purposes (Ngai, 2003). The most significant benefit is that advertising is free (Chatterjee et al. 2003). In the new millennium, the high exposure to online advertising became the highest factor in the success of mobile marketing (Amberg, Hirschmeier & Wehrmann, 2004; Heinonen & Strandvik, 2003). Also, the idea of permission marketing that requires the permission of the reliable customers generate lately with mobile advertising (Godin 1999). Moreover, according to Haghirian (2007), the communication of mobile advertising with the target audiences via a handset and the popularity of this form has changed over time. The growing number of internet users motivates businesses to develop marketing strategies that attract internet users to buy and spend more. Because online advertising is so important to online marketing, this study aims to discover and investigate the elements that influence online advertisement on consumers' intent to buy, particularly in developing countries (Internet World Stats News, 2011). According to the sources, online advertising is a type of marketing that uses the internet and the global web to distribute marketing messages to attract clients. Recently the research is keener on the behavior and the psychological aspect of online advertising, as par, it has been analyzed that the development of mobile advertising has led to changes in customers' habits over time (Deshwal, 2016). Advertisement or issues (Salomon, 2013), Individuals who utilize online advertising have a mental state that controls how they view their surroundings and how they respond (Tsang, Ho & Liang, 2004). Informativeness includes a good source of product information, the ability to supply relevant product information, and proven up-to-data information (Dracket & Carr, 2001).Students' exposure towards television advertisements, general cues and message cues shown in the television advertisements did not have any influence in their consumption of branded snacks and beverages which indicates that taste beats ads (Shabuz & Bexci, 2019).

Market Communication

Rapidly changing mobile marketing around the world was influenced by a load of factors that can be the global connective. Abdullah (2004) said that the Malaysian young generation claimed to possess a mobile phone as a basic thing based in their life even in the early stage of internet development. This indicated the youth that is adapting technology beside the old tool for example meeting face to face (Ito, Okabe & Matsuda, 2004). The mobile market become a lifestyle that gives offers specially futility of technology into the customer throws their handphone (Rayfield, 2010). In the case of movie marketing, these social networks were taken seriously and viewed as a tool for electronically generating word of mouth and a new viral marketing method (Asur & Huberman, 2010). Nowadays, because it is well known that consumers have fundamentally accepted and embraced mobile living in the life cycle, the smartphone market is exploding thanks to the popularity of Apple's iPhone, RIM's Blackberry, and Google's Android.

Creating Consumer Demand

Because customers don't always know what they want and don't always have time to want what they know, marketers should advertise the product and make them aware as previously described. Modern web advertising is an excellent technique to communicate a product's USPs (unique selling points), hence stimulating demand. Consumer to company internet marketing is the final type of online marketing. Consumers can readily contact businesses in today's internet world. Consumers can drive transactions with firms rather than the other way around by using the internet. The most important component in this transaction is the price (Muzumdar, 2012). Priceline.com, for example, allows businesses to purchase airline tickets, hotel rooms, and other items that customers have listed on the website. Consumers can also use complaint websites to submit requests and concerns (Kotler & Armstrong, 2012). There are numerous social media platforms, each with its own set of functions and features. Social networking sites like Facebook and Twitter are among the most popular social media platforms. 'Social commerce' is a new and rapidly increasing trend in which online stores can link with other stores in the same online marketplace (Stephen & Toubia, 2009). Companies also utilize Facebook and Twitter to reach out to more customers and keep them informed. As a result, it is apparent that online advertising can enhance demand when it is placed right in front of the customers' eyes.

Research Methodology

All those methods/techniques that are used to conduct research are called research methods or techniques. The methodology is considered a "guideline for solving a problem". The methodology gives the way to find the solution for the gap that was raised. It may be understood as a science of studying how research is done scientifically concerning several various factors. For instance, the researcher's predictions and beliefs on whether there is just one reality to be uncovered the truth. Researchers must not only understand how to create certain indices or tests, calculate the mean, mode, median, standard deviation, or chi-square, and apply specific research techniques; but they must also understand which of these methods or techniques are relevant and which are not, and why they must be used. It may be understood as a science of studying how research is done scientifically concerning several various factors. For instance, the researcher's predictions and beliefs on whether there is just one reality to be uncovered the truth. Researchers must not only understand how to create certain indices or tests, calculate the mean, mode, median, standard deviation, or chi-square, and apply specific research techniques, but they must also understand which of these methods or techniques are relevant and which are not, and why they must be used.

Research design

This epistemology study has been adopted as descriptive research with the deductive approach as it is derived from many literature sources, further, this study develops a solution, for online advertising to reach the purchasing attention of the viewers. This relationship is developed by variables that could affect customer perception. This descriptive research involves data collection to test the hypothesis and answer the research questions considering the status of the focus of the study. The research was done mainly as a survey using an equipped questionnaire. Part A and Part B of the questionnaire were delivered separately. Part A of the survey asked participants about their backgrounds and general knowledge of the topic. The conceptual variables were the focus of Part B of the questionnaire. Each variable included two to five questions/statements in it. A five-point Likert scale, with 1 indicating strong disagreement and 5 indicating strong agreement was used. The study accepted the strategy for developing and systematic addressing the study utilizing the questionnaire, data collection, and the construction of the framework, and the study summarized the overall activities and methodologies that explored the results in this approach.

Survey Instrument

The survey contains several constructs related to the ward's attitude to mobile advertising and purchase intention, including product and services, price, and timing. This study explores the tests that approached the conceptual model. Some of the surveys were conducted by previous scholars. The research will contain several resources which are related to online advertising, customer mobile internet users, purchase intention, and subjective norms. This survey was cited by different articles from online journals, university lectures, newspapers to get mindful of attitudes towards purchase intention for the online advertising.

Hypothesis

Today’s business opportunity is related to the innovation of the technical facility and the characterized of the transaction great customer self-service and produces independent direct employee involvement. Rapidly increasing technology innovation and strategy management forecast long-term business success and customer relationship. Zeithaml, Berry & Parasuraman (1996) described in their study that self-service reduces the barrier between the marketplace and the transaction buyer and seller. Mobile marketing gives the chance to the business as customer adapted smartphone which creates different devices to access the world.

H1: Irritation has a direct relationship that highly influences the purchasing decision of the mobile internet users

Missing Data

H2: Response has a direct relationship which highly influences the purchasing decision of the mobile internet users

H3: Updating has a direct relationship which highly influences the purchasing decision of the mobile internet users

H4: Information has a direct relationship which highly influences the purchasing decision of the mobile internet users

Sampling size

According to Holloway & Wheeler (2002), the sample size has no bearing on the study's value or quality, and there are no recommendations for establishing sample size in qualitative research. Qualitative researchers rarely know the exact number of persons who will participate in the study ahead of time; the sample size and composition may change as the study progresses. Sampling continues until saturation is reached, at which point no new information is generated (Holloway, 1997).

In this study, a quantitative method used the sample was decided as 130, but after the screening it became 105. So, for the studies, it had been used 105 respondents from random and convenient sampling from both males and females under different aging scales, 15-25, 26-35, 36-45, 46- 55 and above. Further, the sample was divided into certain qualifications as, employee, student, house worker, and self-employee. Two weeks had been used for data collection and universities - Lincoln, UPM and UNITAR for convenient sampling in LRT and a few supermarkets.

Resukt and Discussion

Earlier it has been manual systems and formulas for the analysis of data, but with the development of the technology, it was convenient, more accurate, and timesaving with the innovation of the technology, such as excel SPSS. SPSS version 20.0 was used as the analysis instrument of this study. Further, the descriptive analysis, frequency analysis, reliability test, normality test, correlation coefficient regression, etc. The tables, charts, and histograms were used to interpret the analysis. It will make the pathway for better results as expected in the final chapter. Missing some data is sometimes a problem in social science research. However, many projects obtain data using survey research when the amount of missing data exceeds almost 15 % the questionnaire of observation is typically removed from the data file (Hair et al. 2017). The cause of the losing data from the form can result firstly, make a declining power or the exactly statistical test which is about to bring a relationship in a dataset and secondly, the parameter estimates to develop biases (Hair et al. 2010). The missing data was already examined via SPSS, more than nine were rejected from subsequent analysis because the responders did not give the answers to more than 15 percent of the question, which translates that the number of missing date values per observation exceeds 15% (Hair et al. 2017). The total data distributed were 130. The remaining data after removed the error is 121.

Outliers

Outlier is related to the observations which have an unusual value for a single variable (Tabachnick & Fidell, 2012 ). Furthermore, outliers can be identified or present by their distinct and different characteristics such as high or low values on a variable or falling at the outer ranges of the distribution according to Hair et al (2010). From the survey, six data were removed because the respondents did not understand the questions or maybe the response was misguided. Then the total screen became 115 out of 121.

Expletory Factor Analysis

It is already known that the main objective of this study is to bring out a customer expectation which is a direct influence to purchase attention through the perceived online advertisement. These variables, however, were subjected to component analysis to identify the underlying common dimensions. Factor analysis is an interdependent technique that considers all variables at the same time. It is a multi-method data reduction and summarizing technique. The purpose of factor analysis is to find a simple solution that explains the observed association between variables with the fewest number of variables possible.

Figure 1: Screen Plot Source: Survey

The screen plot graphs the eigenvalue against the component number (refer to figure 1). This one prefers these values in the first. Eight columns of the table immediately above. From the ninth factor onwards, that one sees the line is almost flat, meaning each successive factor is accounting for moderate and moderate amounts of variance.

Reliability

Reliability explained the degree to which examining the data collection method will harvest consistent conclusions for this study by other researchers. Cooper & Schindler (2003) have classified reliability as many things too many people, however, the context is related to the notion. Reliability always measures what suppliers give consistent same phenomenon. Reliability is a necessary contributor to validity but is not a sufficient condition for validity.

Table 1: Reliability Statistics

Source: Survey

The four items have an alpha coefficient of 0.828 in Table 1. This indicates that the items have a high level of internal consistency. The reliability test evaluates the consistency of several measurements of the same variable. Cranach's Alpha is the most extensively used measurement tool, with a lower limit of 0.7 that is widely agreed upon. In most social science study situations, a dependability coefficient of 0.70 or above is regarded as "acceptable". N equals 25 items, c-bar equals the average inter-items covariance among the items, and v-bar equals the average variance among the items. 0.822 Cronbach's Alpha. Furthermore, because the average inter-item correlation is low, the Alphas will be low. Cronbach's Alpha increases when the average inter- item correlation grows while the number of items remains constant, according to the study. It may be worthwhile to study the dimensionality of the scales in addition to estimating the Alpha coefficient dependability. It can make use of the research's reassurance (see below table 2).

Table 2: Correlation

Source: Computed Data Analysis
**Correlation is significant at the 0.01 level (1-tailed).

Key: ivi: information, ivir, irratation: responset, ivr: update, ivu: purchase intion

Hypothesis 1

There is no significant value (0.055) between the dependent variable purchasing attention and information. That means there is no strong relationship between purchasing attention and information. It has shown that the Alternative hypothesis has not been accepted and null hypothesis is accepted.

Hypothesis 2

There is a significant value (0.214) between purchasing attention and irritation. That means there is a relationship between purchasing attention and irritation. It has an emphasis that the Null hypothesis has been rejected and the Alternative hypothesis has been accepted.

Hypothesis 3

There is no significant value (0.102) between customer satisfaction and responsibility. That means there is no strong relationship between purchasing attention and response to the customer. It has revealed that the Alternative hypothesis has been rejected and the Null hypothesis has been accepted.

Hypothesis 4

There is no significant value (0.005) between purchasing attention and updating. That means there is no significant relationship between customer satisfaction and assurances. It has shown that the Alternative hypothesis has been accepted and the Null hypothesis has been rejected.

Summary

This chapter starts by presenting the data screening through missing values, outliers, and suspicious response patterns. Then it focuses on the descriptive statistics of constructs, normality test, and response rate. After that, it discusses the correlation matrix between variables, multicollinearity issue, and common method variance, followed by the assessment of the structural models. The following chapter will examine the results reported in this chapter and the present study’s contributions to the existing body of knowledge. Key empirical findings will be evaluated to examine their implications for academics and practitioners. The limitations of the current study will also be presented and finally, consideration for future research will be outlined as it results in tree null hypotheses significant main hypothesis significant relationship it brings the alarming sign for the marketers for prepare to break up new ice break in the society as what ever the updating there is one key, irritating on the red colour.

Recommendation for Further Study

The research just focused on the people who are using mobile internet 24/7. All of them gave their opinion for the survey so the limitation of the study was that the research didn’t touch the customer, non-mobile internet users. Although they used mobile internet, those who are adapted to online internet with their handphone, however, the survey the just forced one area of Selangor east and the south Selangor, to achieve the general goal, so the future research will be made. The survey can be done globally through an online survey to get the respondents of the world also it would expand the whole Malaysia around unlikely only for one area, further the research could take much time to do personal interviews visiting hose by the house could get a high result than this. Furthermore, it can be collected some qualitative part for the research as well.

Developing purchase attention with four dimensions.

The research proved that major dimension irritation is positively related to customer expectation and all the dimensions are not fully significant, but they cannot simply be neglected. The technology and updating would need to increase innovation of online advertisement in the future. Rejection does not mean it doesn’t have an objective in state of without this three-dimension. The customer they are not reaching the purchase but for the study customers their eyes just for announcing fact which they said service is always irritated, so purchase attention and the irritation has the significant relationship according to the final cut in this present time in this particular area. Thus, the development of mobile advertising has led to changes in customers habits over time (Deshwal, 2016), so as technology updates, give fast information, and the feedback needs to control customer mind by reducing the manipulated service.

Conclusion

The above endeavour which is expanded nearly two months has given significant results while changing the major ideas of purchasing attention of mobile users and the online advertisement which contracting all the dimensions of the irritation that are highlighted as the main driving force of online advertising. It is clear in the questionnaire that it would be tested whether the respondents that undergone irritation in this era that no one likes irritation. As they are leading humdrum lifestyle no one need to see that mobile advertising manipulating them. In other words, things that irritate them are ahead so if they get an idea that mobile advertising is irritating in their daily lifestyle, they will neglect the mobile advertisement. Therefore, it is a red light for marketers and advertising companies to change their policies and approach techniques, and any other appeals when they reach their viewers. On the other hand, as the results give another hypothesis a null but means standard deviations, it is proven that they cannot be forgotten the updating technology and the response over the advertisements should be maintained in the high- level expectation of purchasing attention while prioritising of minimizing the irritation. This research is done with the purpose of further enhancement of the practical knowledge of scientific research and highly believe that this could open the path for many more types of research in the future.

Conflict of Interests

The authors declare that they have no conflict of interests.

Acknowledgement

The authors are thankful to the institutional authority for completion of the work.

References

Abdullah, M.Y.H. (2004). Adoption of cellular phone among young adults: A study among youths in the Klang Valley, Malaysia. Korean Broadcasting Society Seminar and Report, 305- 312.

Amberg, M., Hirschmeier, M. & Wehrmann, J. (2004). The Compass Acceptance Model for the analysis and evaluation of mobile services. Journal of Mobile Communications, 2(3), 248-259. https://doi.org/10.1504/IJMC.2004.005163

Asur, S., & Huberman, B. A. (2010, August). Predicting the future with social media. In 2010 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology (Vol. 1, pp. 492-499). IEEE. https://doi.org/10.1109/WI-IAT.2010.63

Brackett, L.K., & Carr, B.N. (2001), Cyberspace advertising vs. other media: Consumer vs. mature student attitudes. Journal of Advertising Research, 41(5), 23-32. https://doi.org/10.2501/JAR-41-5-23-32

Campbell, S. (2015). Mobile Communication and Network Privatism: A Literature Review of the Implications for Diverse, Weak, and New Ties. Review of Communication Research, 3(1), 1- 21. https://doi.org/10.12840/issn.2255-4165.2015.03.01.006

Chatterjee, P., Hoffman, D.L. & Novak, T.P. (2003). Modeling the Clickstream: Implications for Web-Based Advertising Efforts. Marketing Science, 22(4), 520-541. https://doi.org/10.1287/mksc.22.4.520.24906

Constantinides, E. (2002). The 4S web-marketing mix model. Electronic commerce research and applications, 1(1), 57-76. https://doi.org/10.1016/S1567-4223(02)00006-6

Deshwal, P. (2016). Online advertising and its impact on consumer behavior. International Journal of Applied Research, 2(2), 200-204.

Eighmey, J., & McCord, L. (1998). Adding Value in the Information Age: Uses and Gratifications of Sites on the World Wide Web. Journal of Business Research, 41(3), 187-194. https://doi.org/10.1016/S0148-2963(97)00061-1

Gill, R. (2014). Public Relations and the New Stakeholder Management Environment, International. Journal of Academic Research in Business and Social Sciences, 4(10), pp 100-106. https://doi.org/10.6007/IJARBSS/v4-i9/1211

Godin, S. (1999). Permission marketing: Turning strangers into friends and friends into customers. Simon and Schuster.

Haghirian, P. & Inoue, A. (2007). An advanced model of consumer attitudes toward advertising on the mobile internet. International Journal of Mobile Communications, 5(1), 48–67.https://doi.org/10.1504/IJMC.2007.011489

Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E. (2010). Multivariate Data Analysis (7th ed.). Pearson.

Hair, J.F., Hult, G.T.M., Ringle, C.M. & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications Inc.

Heinonen, K. & Strandvik, T. (2003). Consumer Responsiveness to Mobile Marketing. International Journal of Mobile Communications, 5(6), 603-617.https://doi.org/10.1504/IJMC.2007.014177

Holloway, I. (1997). Basic concepts for qualitative research. Wiley-Blackwell. Holloway, I., & Wheeler, S. (2002). Qualitative research in nursing. Wiley-Blackwell.

Internet World Stats News. (2011, February 8). New 2011 Year-End World Stats. https://www.internetworldstats.com/pr/edi069.htm#:~:text=New%202011%20Year%2DEnd%20

World%20Stats&text=Today%20the%20message%20is%20short,the%20penetration%20rate%2 0is%2032.7%25.

Internet World Stats. (2016). World Internet Usage, 2016. https://www.infoplease.com/math- science/computers-internet/world-internet-usage-2016

Ito, M.E., Okabe, D.E., & Matsuda, M.E. (2005). Personal, portable, pedestrian: Mobile phones in Japanese life. Boston Review.

Kiang, M., Santanam, R., Huei, K. & Shang, M. (2000). Marketing on the Internet- who can benefit from an online marketing approach? Decision Support Systems, 27(4), 383-393. https://doi.org/10.1016/S0167-9236(99)00062-7

Kotler, P., & Armstrong, G. (2012). Principles of marketing 14th edition. New Jearsey: Pearson Education Inc, 67.

Muzumdar, P. (2012). Online bookstore-A new trend in textbook sales management for services marketing. Journal of Management and Marketing Research, 9, 122-135.

Ngai, E.W.T. (2003) Selection of Web Sites for Online Advertising Using the AHP. Information & Management, 40(4), 233-242. https://doi.org/10.1016/S0378-7206(02)00004-6

Rayfield, D. (2010). Get your business moving: 9 types of mobile marketing. Retrieved from http://harpsocial.com/2010/03/get-your-business-moving-9-types-of-mobile-marketing/

Salomon, D. (2013). Moving on from Facebook: Using Instagram to connect with undergraduates and engage in teaching and learning. College & Research Libraries News, 74(8), 408-412. https://doi.org/10.5860/crln.74.8.8991

Selvaraj, N. (2022). Deficiencies in Banking Services and Improvement in Banking Services in Tamil Nadu. International Journal of Management and Human Science (IJMHS), 6(1), 31-40.https://doi.org/10.31674/ijmhs.2022.v06i01.003

Shabuz, J. I., & Bexci, M. S. (2019). Dwindling influences of television advertisements on the consumption of branded snacks and beverages. Int. J. Innov. Technol. Explor. Eng, 8, 686-690.

Shubhangam, K., Srivastava, M., Ravi, R., & Singh, R. (2020). Influence of Social Media Advertisement on Customer’s Purchase Decision: A Literature Review. International Journal on Recent Trends in Business and Tourism (IJRTBT), 4(4), 25-31.

Stephen, A. T., & Toubia, O. (2010). Deriving value from social commerce networks. Journal of Marketing Research, 47(2), 215-228.

Tabachnick, B.G. & Fidell, L.S. (2012). Using Multivariate Statistics (6th ed.). Pearson Education.

Tsang, M.M., Ho, S. & Liang, T. (2004). Consumer Attitudes Toward Mobile Advertising: An Empirical Study. International Journal of Electronic Commerce, 8(3), 65-78.

Zeithaml, V.A., Berry, L.L. & Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60(2), 31. https://doi.org/10.2307/1251929