INTRODUCTION:

Online advertising is a form of interactive communication. There is always a sender who posts some kind of information on the internet and there are users who feel addressed by some part of this data. online ads are meant to be directly activated.

This activation of advertising is a form of interaction, a kind of user response which provides evidence for the novel role of addressees. Different types of web ads allow different degrees of interactivity (Janoschka, 2004). Now-a-days Online Advertising has become an important tool for marketing communication worldwide. Because of the unique and versatile capabilities of the Web such as interactivity, global reach, multimedia capacity, and audience involvement, global advertisers and marketers are turning to online advertising (Wolin, Korgaokar, and Lund, 2002).

During the last decade online advertising market has grown rapidly since the advent of the first online advertisement in 1994 (Hollis, 2005). According to the report from the Interactive Advertising Bureau (IAB) and PricewaterhouseCoopers (PwC), Online advertising revenues in the United States through June 2015 totaled $27.5 billion, up 19.0% from the $23.1 billion reported in 2014 (IAB Report, 2015). Online advertising has received a great deal of attention in both business and academic arenas because of its rapid diffusion.

Little attention has been given to the subject of online advertising in Bangladesh even though it is one of the emerging E-markets of South Asia. The size of the advertisement market in Bangladesh including print, electronic, online and billboard is estimated at more than Tk 2,000 crore annually and it grows at 10 percent a year (thedailystar.net, 2012). Moreover, it has a rapidly growing 26.7% Internet penetration rate compared to India's 28.3% and Pakistan’s 14.6% (Internet World Stats 2015). As of September 2015, the total number of internet subscribers in Bangladesh stands at 54 millions, where 52 millions are regular mobile internet users (BTRC, 2015). As the number of internet users is increasing significantly, there is a great opportunity for e-marketers. Online shopping transactions in Bangladesh could increase ten-fold over the next three years. Annual value of the country's e-shopping may rise to Tk 2,000 crore in 2017 from Tk 200 crore today. Besides, the IT ecosystem has improved a lot in Bangladesh over the last several years. The country has launched 3G services, eased payment systems and introduced mobile banking. These will enhance the growth of e-trading (The Daily Star, 2014)

Consumers’ attitude towards online advertising (ATOA) can be indicated through consumer’s favourable or unfavourable response towards a particular advertisement. Consumer will form either positive or negative attitudes towards the advertisement after being exposed to it (Schiffman and Kanuk, 2000). According to MacKenzie and Lutz (1989), consumers' attitude towards online advertising is one of the factors that influence the effectiveness of online ads. Consumer’s cognitive ability towards the online ad is reflected on their thoughts and feelings and subsequently it influences their attitude towards online ads (MacKenzie and Lutz, 1989).

Online buying behavior refers to the process of purchasing products or services via internet. It also can be defined as final consumer behavior during the purchase. There are four types of buying behavior: Variety seeking buying behavior, complex buying behavior, and post-purchase tension reducing buying behavior (Kotler and Armstrong, 2010).

This research aims at examining the impact of online advertising on university students’ buying behavior and their overall attitude towards online advertising. Besides the study will try to Identify the factors that influence university students’ online buying behavior and the effect of online advertising on online and offline sales. The current university students are regarded as Net Generation, as they are generally technological savvy and rely strongly on the Internet for various purposes including online shopping (Valentine and Powers, 2013). Undoubtedly, university students are of particular interest to online marketers, especially due to the significant purchasing power and reference group power in the market. Besides, university students are basically heavy Internet users, and have the ability to control digital media and basic knowledge towards E- Commerce. In view of that, it is vital for consumer behavior researchers and e-retailers to have a deeper understanding on the factors that influence their online purchase intention. Moreover, there is a dearth of studies regarding the effect of online advertising in Bangladesh especially in Chittagong, commercial capital of the country.

LITERATURE REVIEW:

Several studies, both in developed countries and developing countries, have all made significant contributions to our understanding of the different aspects of online advertising. However, there is a lack of study in this regard in Bangladesh especially in Chittagong. Among very few researchers, a study by Uddin, J. M. and Sultana, T. (2015) shows that consumers have positive attitude towards online advertising and convenience, age, gender , income, profession, family structure and ICT familiarity are the factors which influences consumers for preferring online shopping (Uddin and Sultana, 2015). In a study, Ferdous and Jahan (2015) found that convenience, interactivity and aesthetic presentation of online ads influences consumers’ online purchasing intentions (Ferdous and Jahan, 2013). Rahman (2014) studied trends, patterns and preferences of consumer to online buying were studied on a very small sample that limits the scope of generalization of the result (Rahaman, 2014). In an empirical study Zaman et al. (2013) found that majority of the respondents have intentions to purchase from the internet because of the convenience and security (Zaman, Ahmed, and Nehal, 2013).

A study by pi Strategy Consulting on e-Commerce in Bangladesh points that e-Commerce market is still at a relatively early stage in development which is largely Dhaka-centric and it caters to a small segment of the population. However, trusts with online payment mechanisms are the most critical hurdle for growth. About half of the population of the study has used e-Commerce at least once in the preceding three months. Of those who are e-Commerce users, over 80% are less than 30 years old, and more than half of them are female. Most of them are either university students (33%) or young professionals (44%). Over 90% of them are based in Dhaka. Most of the products sold through e-Commerce in Bangladesh today are clothing and beauty products (34%). Other prevailing product categories include: books (12%), travel tickets (11%), airtime top-up (8%), and food delivery (6%). The overwhelming majority (over 80%) uses cash-on-delivery as a payment method (thedailystar.net, 2014).

A study by Ahmed (2013) reveals that students have positive judgment about the economic impact of advertising. However, they have negative judgment about the ethical and social consequences of advertising. The students demand more regulations to control the advertising. The study recommends that advertisers should design fact oriented, entertainment and excitement based advertising which may contain some sorts of emotional messages keeping in mind the traditions of Bangladesh (Ahmed, 2013).

Korgaokar and Wolin (2002) explored the differences between heavy, medium, and light Internet users in terms of their beliefs about online advertising, attitudes toward Online advertising, and online purchasing patterns. They found that heavy Internet users tended to have more positive attitudes toward online advertising than those of medium and light Internet users (Wolin, Korgaokar, and Lund, 2002). A study by Ducoffe (1996) showed that informativeness and entertainment were positively related to ATOA whereas irritation was negatively related to advertising value.

University students representing a segment of the general public should receive special attention. Romany (2006) suggested that though advertising helped students to get product information but these did not necessarily increase their buying confidence and could not manipulate them. Dan and Sidin (2006) made a survey of 124 students in a Malaysian university which showed that students have positive attitudes on the economic effect, student effect and audience effect of advertising while showing attitudes in relation to the price effect and portrayal aspects of advertising. Their findings suggested that the students’ attitudes towards advertising depend on possible consequences of advertising to them. The positive attitudes of the students suggest the important influence and the persuasive message effect of advertising.

Munusamy and Hoo (2007) had used regression analysis and examined the belief factors to see their ability to predict attitude towards advertising. The result showed that students’ attitude towards advertising is very much influenced by one of their belief factors, Product Information. They believed that advertising is a useful tool for them to get product information (Munusamy and Hoo, 2007). Shen and Chen (2007) investigated the relationships among demographic variables and experiences, beliefs, and attitudes. They found that younger students have more positive beliefs and attitudes toward advertising and those with higher levels of education tend to have more positive attitudes and beliefs (Shen and Chen, 2007). The results of another study show that age, gender, geographic distribution, income, family, and work can be influencing factors which affect consumers’ buying behavior Which is almost similar to this study (Korgaokar and Wolin, 1999).

CONCEPTUAL FRAMEWORK:

A number of theories and constructs can be helpful in explaining various aspects of impact of online ads on buying behavior of university students. Various empirical research following media uses and gratification tradition suggest that, people “select media contents to gratify certain needs—such as the need to keep informed about significant events, to escape from everyday problems, to regulate affective and arousal states, to reinforce existing beliefs and attitudes, or simply, to satisfy habit” (Vettehen, Konig, Westerik, and Beentjes, 2012). Using the same theory Ferdous and Jahan (2015) found that if ads fail to fulfill the demands and hampers consumers’ regular activities then they avoid online ads (Ferdous and Jahan, 2013).

Effectiveness is the only way to measure whether the advertising is successful or not. Besides, it is a result of the media audience reaction to advertising. Lavidge and Steiner (1961) proposes a marketing communication model in order to measure advertising effectiveness by consumer’s hierarchy of effects, stair-step from paying attention to advertised product, to be interested in it, like and prefer it, then finally to be the real consumer. This model becomes a widely accepted way to measure effectiveness of traditional advertising (Lavidge and Steiner, 1961). The measurement is largely based on a one-way view of communication; the marketer’s communication and consumer’s respond (Stewart and Pavlou, 2002). In this research a conceptual framework has been used which was similar to the study by Yaakop et al. (2012). In that study perceived interactivity, advertising avoidance, credibility and privacy were found influential factors for consumers’ attitude towards facebook advertising (Yaakop, Anuar, Omar, and Liung, 2012).

Table-1: Impact of Online Advertising on University Students’ Buying Behavior by demographic and other characteristics

Independent variables	Impact of Online Advertising on University Students’ Buying Behavior
	Total	Never %	Sometimes %	Regular-Often %	p-value %
Gender of Respondent					0.345
Female	58	48.3	46.6	5.2
Male	92	37.0	58.7	4.3
Age of Respondent (yr)					0.852
18-20	51	45.1	51.0	3.9
21-23	72	41.7	54.2	4.2
24-26	27	33.3	59.3	7.4
Income of Respondent (BDT)					0.624
00-3500	105	44.8	51.4	3.8
3501-7000	31	35.5	61.3	3.2
7001-10500	07	28.6	57.1	14.3
10501-14000	05	50.0	50.0	0.0
Above 14000	02	41.3	54.0	4.7
Respondents’ Web Experience					0.043^*
6 Months- 1Year	27	59.3	40.7	0.0
1 Year- 3 Years	55	43.6	54.5	1.8
3 Years- 5 Years	38	39.5	55.3	5.3
More than 5 Years	30	23.3	63.3	13.3
Weekly Internet Use					0.492
Less than 5 hours	41	43.9	51.2	4.9
5hours- 10 hours	28	39.3	60.7	0.0
10 hours-15 hours	32	40.6	59.4	0.0
15 hours- 20 hours	12	50.0	41.7	8.3
More than 20 hours	37	37.8	51.4	10.8
Attitude towards online advertising					0.218
Don’t like at all	4	50.0	25.0	25.0
Don't Like	21	57.1	38.1	4.8
Like	114	39.5	57.0	3.5
Like very Much	11	27.3	63.6	9.1
Involvement in the purchase decision making by help of online advertising					0.000^***
Never	43	95.3	4.7	0.0
Sometimes	93	21.5	73.1	5.4
Often	11	9.1	81.8	9.1
Most of the time	03	0.0	66.7	33.3

Note: Rows sum to 100%. P values are based on Chi-square test.*p < 0.05, ***p < 0.001

Two hundred questionnaires were sent and 160 of them returned, allowing a response rate of 80 percent. Ten of them were not suitable for analysis, since they were not fully completed. Among the respondents 92 were male and 58 were female. The questionnaire sought the Respondents’ attitude towards online advertising and the impact of online ads on their buying behavior. The first section of the questionnaire gathered demographic information from the respondents including gender, age, and income level. The second section was about respondents’ web experience and internet usage pattern. The other sections were about university students’ attitude towards online advertising and the impact of online advertising on university students’ buying behavior. A five-point Likert scale was used in the questionnaire. Data were entered and analyzed by SPSS version 16.0. Descriptive statistics using cross tabulation and chi-square (χ2) were used to see the overall percentage distribution of the study for impact of online advertising on university students’ buying behavior.

RESULTS AND DISCUSSIONS:

The percentage distribution of the frequency of impact of online advertising on university students’ buying behavior by selected demographic and others characteristics of respondents were presented in Table-1. It shows that overall 58.6% students buy products online. Among them 38.6% were male and 20% were female. Pearson’s chi-square test limns the association between impact of online advertising on university students’ buying behavior, demographic and other attitudinal variables. Impact of online ad on university students’ buying behavior was highly significantly associated with university students’ involvement in making purchase decision by help of online ads (p < 0.001). In addition, impact of online advertising on university students’ buying behavior was also positively related with their web experience (p < 0.05). It was evident that the higher the respondents’ were experienced with the internet the more they purchased products online. Table-1 also illustrates that students belonging to the age group 20-23 years had experience of buying products online at 58%. Overall 83.33% respondents had positive attitude towards online advertising. Besides, 71.33% respondents took help from online ads while they made purchase decision. Moreover, heavy internet users had positive attitude towards online advertising. It was also found that gender and income influenced university students’ buying behavior as male students had more purchase experience than their female counterparts. No association was evident between age and impact of online advertising on university students’ buying behavior.

Table-2 demonstrates that the range of correlation between the variables (gender, age, level of Income, level of web experience, level of weekly internet use, level of attitude towards online advertising and, level of involvement in purchase after being exposed to online advertising) is -.11 to .54, which indicates weak to strong relationship between the variables. The correlation between gender and age of respondent is the highest (r=.540) among all variables and on the other hand, there is the lowest value (r=-.117) between age and level of weekly internet use. Moreover, significant correlation has been shown between level of income and age of respondent (r=.418). In addition, there are positive association between level of income and level of web experience (r=.371), level of income and gender of respondent (r=.348). There was also positive relationship between level of attitude towards online advertising and level of involvement in purchase decision making by help of online advertising (r=.299), gender and level of web experience (r=.292), age and level of web experience (r=.268) and, level of weekly internet use and level of web experience (r=.250). Furthermore, there is weak correlation between level of web experience and level of involvement in purchase decision making by help of online advertising (r=.169), age and level of involvement in purchase decision making by help of online advertising (r=.131). However, there are negative correlation between level of weekly internet use and gender (r=-.038), level of weekly internet use and age (r=-.117), and level of weekly internet use and level of involvement in purchase decision making by help of online advertising (r=-.63). So, the findings highlight that online advertising had positive influence on university students’ attitude and buying behavior.

Table -2: Correlations between Gender, Age, Level of Income, Level of Web Experience, Level of Weekly Internet Use, Level of Attitude towards online ads and Selecting, Involve in purchase decision making by help of online ads

Variables	1	2	3	4	5	6	7
1. Gender	_
2. Age	0.540^**	_
3. Level of income	0.348^**	0.418^**	_
4. Level of web experience	0.292^**	0.268^**	0.371^**	_
5. Level of weekly internet use	-0.038	-0.117	0.073	0.250^**	_
6.Level of attitude towards online ads	0.026	0.105	0.103	0.054	0.088	_
7. Involvement in purchase decision making by help of online ads	0.084	0.131	0.097	0.169^*	-0.63	0.299^**	_

Note: ** Correlation is significant at the 0.01 level (2-tailed)

*Correlation is significant at the 0.05 level (2-tailed)

CONCLUSION:

This research is a modest attempt to understand the university students’ overall attitude towards online advertising and the impact of online ads on their buying behavior in Bangladesh context. The findings of this research showed an overall positive reaction of university students’ towards online advertising. It has been found that gender, web experience, attitude towards online advertising play important role on consumers’ buying behavior. Online shopping in Bangladesh is still at a relatively early stage in development which is largely Dhaka-centric. There are not sufficient studies on the impact of online advertising on university students’ buying behavior. This study adds to a small contribution regarding this and attempts to help e-marketers to improve the quality of online advertisements to attract consumers effectively. There is also scope for research on university students’ attitude towards facebook advertising as the number of facebook users in Bangladesh are increasing rapidly.

This investigation has several limitation that raise questions for future research. There are many factors determining online buying behavior. But in this study the researcher didn’t appropriately examine all those factors because of time constraints. Besides, the methodologies of this study for analyzing the data may not be able to assess university students’ buying behavior based on discussed variables.

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Received on 03.12.2015 Modified on 13.12.2015

Int. J. Rev. & Res. Social Sci. 3(4): Oct. - Dec., 2015; Page 163-168

Gender		University students’ buying behavior
Age
Income
Web Experience
Weekly Internet Use
Attitude Towards Online Advertising
Involvement in making Purchase Decision by help of Online Ads