Influence of Media Advertisements on Purchase Intentio: Evidence from Sri Lankan Mobile Phone Market

Mubarak Kaldeen^1* and Mohamed Shareef Ishar Ali^2
*Correspondence: Mubarak Kaldeen, Department of Marketing Management, South Eastern University of Sri Lanka, Sri Lanka, Tel: +94769085211, Email: ,

Keywords

Advertisement • Consumer Behavior • Communication channels

Introduction

In today's business world, mobile phones have become one of the most powerful devices. Companies are attempting to attract a growing number of customers while also attempting to keep them on their network for as long as possible. New customers benefit from better word-of-mouth recommendations from existing customers. As a result, the operators provide more benefits to their current customers. In general, advertising has the ability to influence consumer purchase intent in a variety of ways [1-2]. It has now become the most effective tool for attracting new customers [3]. The goal of advertising media is to reach the intended audience. Companies can use a variety of methods, but they must be powerful enough to influence consumer decisions. It should persuade customers to switch from one product to another [4]. Furthermore, in today's world, mobile phones have evolved into highly personalized devices. Other than the owner, it is rarely used by anyone else. The advancement of technology allows for more advanced features to be added to the devices. It will aid in the recruitment of new customers. The mobile phone has evolved into a multipurpose device in recent years. Advertising gives you a better chance to get all of your messages across to your customers [5]. Consumer attitudes can be influenced by effective advertising. The ultimate goal of the advertisers is to sell their goods. One of the most important factors in consumer decisions is the customer's environment. Companies can use advertising to motivate customers [6].

In comparison to other regional markets, Sri Lanka has the fastest penetration of smart phones, which is growing around the world, according to global telecommunication officials. Customers in Sri Lanka who have had 3G, 4G (and now 5G) for a long time know how to get the most out of their smartphones. In Sri Lanka, approximately 63 percent of the population now owns a mobile phone. Despite being higher than South Asia (42%) and the developing world (67%) in terms of mobile ownership, Sri Lanka is still far behind mature markets, where rates of 60-80 percent are common. Subscriber growth in Sri Lanka has been fueled by a combination of three factors over the last five years: rising household incomes, rising GDP per capita, and rising consumer confidence. Expanded mobile network coverage, with 2G networks now covering up to 90% of the population and 3G and 4G networks covering 70%-75 percent of the population, and increased competition between mobile operators, which has resulted in lower prices for consumers.

People are more willing to purchase a brand new smart phone these days. However, there are more competitive brands that offer a variety of smart phone options. The fact is that different people spend different amounts of money on the same type of mobile phone. For example, both Huawei and Samsung smart phones are made in China, and their quality is similar in most cases. People, on the other hand, spend varying amounts on various smart phones.

In the mobile phone industry, Apple phones have a unique concept and approach. They are constantly attempting to transform the mobile phone industry through new technology. Vivo, Redmi, and Xiaomi use a variety of marketing strategies. As a result, there are some advertising influence factors to consider. As a result, the researcher decided to investigate the advertising factors and their impact on the Sri Lankan smart phone industry. The purpose of this study is to determine the impact of advertising on consumer purchase intentions in the Sri Lankan smart phone industry. It reflects how consumers respond to various types of mobile phone advertising.

Literature Review

Theories and models relevant with advertising

The communication process model was developed to demonstrate that communication is made up of several different elements that are constantly in contact with one another. The sender, message, receiver, feedback, channel, context or setting, and noise or interference are said to be the seven main elements in this process model. This group of seven is equally important in the communication process, and without one of them, the process would be incomplete. Advertisers must be aware of how their message may be received by customers on the market in order for advertising to be effective [7,8].

Academics and professionals have spent a long time trying to come up with theories and models that can show how customers respond to the advertising they are exposed to in order to make this easier. The advertiser can create a message that meets all requirements and is thus effective by understanding the different behavioral levels that customers pass through [9]. The communication process can be linked to these models. The communication process model was developed by Mc Guire (1999). Professionals in the advertising industry are still searching for the ideal model that can be applied to the real market and its customers. Models and theories are difficult to apply in real life at the moment. AIDA is a behavioral model developed by Strong in 1925 with the goal of ensuring that an advertisement raises awareness, stimulates interest, and leads the customer to desire and, eventually, action [2].

Every day, more than 80% of Sri Lanka's population watches television. Advertisers need sophisticated data on viewer habits and audience profiles to ensure their TV commercials reach the right people at the right time, which has become more difficult due to the proliferation of channels. Radio advertisements are transmitted through the air via radio waves from a transmitter to an antenna and, ultimately, to a receiving device [10]. In exchange for airing the commercials, a station or network sells airtime. Despite the fact that radio is limited to sound, proponents of radio advertising often tout this as a benefit. Radio is a growing medium that can be found both on the air and online.

Social network advertising, also known as social media targeting, is a term for various types of online advertising that target social networking sites. One of the most significant advantages of advertising on a social networking site (e.g., Facebook, WhatsApp, Instagram, Myspace, Friendster, Bebo, Orkut, etc.) is that advertisers can use demographic information about users to better target their ads [11].

Social media targeting combines existing targeting options (such as geotargeting, behavioral targeting, socio-psychographic targeting, and so on) to allow for more precise target group identification. Advertisements are distributed to users via social media targeting based on information gathered from target group profiles. Advertising on social networks is not always the same as advertising on social media. The method of optimizing social media advertising by using profile data to deliver advertisements directly to individual users is known as social media targeting. The process of matching social network users to advertiser-specified target groups is known as social media targeting [12].

Advertising in a printed medium, such as a newspaper, magazine, or trade journal, is known as press advertising. This includes everything from widely circulated media, such as a major national newspaper or magazine, to more narrowly focused publications, such as local newspapers and trade journals covering highly specialized subjects. Classified advertising is a type of press advertising that allows private individuals or businesses to buy a small, narrowly targeted ad for a low cost to promote a product or service. Another type of press ad is the Display Ad, which is a larger ad (with or without photographs) that typically appears in a newspaper's article section [7,8]. Newspaper advertising, magazine advertising, and in-flight magazine advertising are some of the types of press advertising a firm can provide.

A billboard (also known as a hoarding) is a large outdoor advertising structure (a billing board) that is commonly found in high-traffic areas like along busy roads. Passing pedestrians and drivers are exposed to large advertisements on billboards [13]. Billboards are highly visible in the top designated market areas, usually featuring large, ostensibly witty slogans and distinctive visuals [14]. The largest standard-size billboards are bulletins. They have high-density consumer exposure because they are primarily located on major highways, expressways, or main arterials (mostly to vehicular traffic). Bulletins provide the best visibility, not only because of their size, but also because they allow for creative "customizing" via extensions and embellishments. The other common type of billboard advertising is posters, which are mostly found along primary and secondary arterial roads. Residents and commuter traffic, with some pedestrian exposure, see posters, which are a smaller format than bulletins.

Theoretical aspects of consumer Purchase intention

People think, feel, and act differently, according to Hofstede G, et al. [15]. They've looked into these psychological aspects. It's important to remember that certain groups or individuals may act differently depending on their culture. The words "global marketing," "technology," "consumers," and "communication" are all used interchangeably around the world. Consumer behavior and advertising are also linked. Because the local dimension of advertising differs from the international, advertising that is relevant to global businesses acts as a cultural bridge. Coca-cola is an example of a common example. It is a globally recognized brand, but when advertisers deliver messages to customers, it cannot be done in a standard manner. There should be no disconnecting between the message and their values. Mooij Consumers' decision-making processes are influenced by cultural and subcultural factors. When launching new products in different countries, marketers must exercise extreme caution. Acceptance of the products is influenced by religion, nationalities, and regional groups, among other factors. Family, role, and status are also influencing factors in consumer purchasing behavior. Consumer decision-making is also influenced by some personal factors. Personal factors include a person's lifestyle, income, age, and occupation. Aside from that, some psychological factors have an impact on consumer behavior. Perception, attitudes, motivation, and belief are all part of it.

The influences of consumer decision making

One of the main goals of marketers is to satisfy the needs of their target customers. Understanding the needs of customers and treating them better than the competition is critical. Consumer buying behavior is influenced by culture, subculture, and social class, according to Kotler. In addition, customers' lifestyles, social factors, and personal factors all influence their purchasing decisions. As a result, the marketer must determine the customer's level of need.

According to a previous study of advertising and consumer purchasing behavior, there are three factors that have a significant impact on the consumer decision-making process. External, internal, and marketing influences are examples of these factors. Advertising can be classified as a marketing influence because it has an impact on both internal and external factors. It went on to say that consumers' decision-making is influenced by both emotional responses and the influence of audio, video, and text advertisements. There are numerous factors that are directly related to the chosen issue rather than advertising. Purchasing a smart phone is not a major decision at this time. The possession of a smart phone has become fashionable among the younger and middle generations.

Research Methodology

Research design

This research is being conducted in order to find solutions to the problem at hand. It will also benefit from previous research, models, and theories that are relevant to the chosen topic. Primary data will be gathered, analyzed, and presented with the conclusion in accordance with the research design in order to meet the study's objectives.

Unit of analysis

According to Sekaran, the study's unit of analysis is the level of aggregation of the data collected during the subsequent data analysis stages. As a result, an individual is the unit of analysis for this study. The individual can then be classified as a smart phone user who is concerned about the device's use.

Sample design

Consumers who use a smart phone, both men and women, between the ages of 18 and 50, are included in the study's population. A single member of the population under study can be defined as a sampling element. The sampling element should be representative of In order to collect the data needed for the study, a total of 150 respondents were chosen. In this study, the researcher uses a convenience sampling method to collect primary data from respondents. The 150-person sample includes both male and female participants of various ages and occupational categories with varying average monthly income levels. The convenience sampling method is used to take into account the results of easy access to respondents and the researcher's convenience.

Data collection

Secondary data is information that has already been collected and is available for any other reason. Although the purpose of gathering this information was different, we were still able to use it for our research. Some data was incomplete and not in a satisfactory state. The primary benefit of secondary data was its low price. At the same time, it had already been collected, and there was a high level of availability. The quality of the research was harmed when it relied on secondary data. At the same time, the study's accuracy, completeness, and timeliness should be considered.

Primary data, according to Kotler, is information that is collected for the first time. Observation, focus groups, surveys, behavioral data, and experiments were used to collect primary data. The use of a primary data collection method allowed us to collect only the information we needed. It was narrowed in on a few key issues or findings. Those conclusions were drawn from the original data. The most significant disadvantage of collecting primary data was the lack of time. It was necessary to make additional arrangements for data collection. The most important part of the study, primary data, was collected using a quantitative approach. A structured questionnaire was used to collect data from 150 people who were interested in the topic.

Research Instrument

To collect data for measuring construct concepts, the researcher used a self-administered questionnaire. The questionnaire was divided into three sections, each of which dealt with the operationalization of key construct concepts. The questionnaire is divided into three sections, as shown below. The first section of the questionnaire collects information about respondents' smart phones, including brand, condition, and value. Four questions about the demographic information of the respondents In addition, this section has been designed to identify respondents' demographic data, such as gender, age, occupation category, and average income level. The second section of the questionnaire covered the advertising media construct concepts, which were operationalized using questions and used six dimensions. Furthermore, the second part of the questionnaire is solely focused on determining the construct concept of) smart phone purchase intention. To measure those dimensions of advertising media and purchase intention, the researcher used a five-point Likert scale (strongly agree, agree, neither agree nor disagree, disagree, strongly disagree).

Data presentation and Analysis

Reliability of the study: According to Cavana et al, the study reliability test is used to ensure the study's stability and consistency. Hair et al., also point out that a scale can be reliable if measurements are repeated and the results are consistent. Cronbach alpha reliability analysis test would be used to evaluate construct reliability for consistency reliability of items among constructs. Cronbach's alpha is considered acceptable and good if it is greater than 0.70 (Table 1). The alpha coefficient all variables are greater than 0.70. It means that the data collected from the survey is reliable.

Demographic profile analysis: The total number of people who took part in this study was 150. Female respondents outnumber male respondents. Male respondents make up 40.7 percent of the total sample. That's a total of 61 people who responded. Females make up the majority of the sample. That equates to 59.3 percent of the total sample size of 89 respondents. The total number of people who took part in this study was 150. The age range 18-25 respondents are higher than the other respondents, according to the Table 1. Respondents in the 18-25 age range make up 66.7 percent of the total sample. That's a total of 100 people who responded. The sample size for respondents aged 26 to 35 is 23.3 percent, or 35 people. Respondents in the 46-56 age range account for 5.3 percent of the total, or 8 people. Respondents in the 46- 55 age group account for 2.7 percent of the total, or 4 people. The remainder of the sample consists of respondents aged 56 and above is 3 because it includes 2% of the total sample number of respondents.

Monthly income range Below 10000 is the highest than the other respondents. That represents 46.7% and that equal to 70 respondents. Monthly income range between 10000-20000 there are 27 respondents that equal to 18%. Monthly income range between 20000-50000 and 50000- 100000 there are 34 and 6 respondents & that equal to 22.7% & 8.7% of total respondents.100000 and above monthly income that represent minimum responds in the monthly income range. The number of respondents of this research was 150. According to Table 1, undergraduates are the higher respondents are than the other respondents.56.7% and equal 85 respondents of total respondents. Private sector Occupational Category that represents 26 respondents and that equal 17.3%. Students and Government sector 12.7% & 8% According to research data Business/Self-employed 5.3% are the minimum level.

The Samsung brand was used by the greatest number of respondents (37.3%) in this study, as shown in Table 1. This represents 56 people out of the total number of people who responded. Huawei is the second most popular brand, with 23.3 percent of respondents using it. The Apple brand is in third place, with a 20% market share. Sony is the brand with the lowest number of respondents, with 2 respondents out of 150 totals, or 1.3 percent. According to the research data most of respondents are used Brand new mobile phones.129 respondents are using the brand-new mobile phones that represent the 86% and 14% using the used mobile phones. Total respondents of the research are 150 respondents. However, most of the respondents are buy 20000-30000 cost range mobile phones. That represents 34%. Secondly most of respondents are buying 30000-50000 cost range mobile phones. (30%).18% respondents are buying 10000-20000 cost range mobile phones, & that represent 27 respondents. 11.3% & 5.3% that represent the 50000- 100000 range and more than 100000 range. Below 10000 is the minimum buying range that represent 1.3% and that equal to 2 respondents.

Dimensions of smart phone purchase intention

Measurements of purchase intention, which are the research's independent variables, are required to meet the research's objectives and test hypotheses. The Mean, Standard Deviation, and Variance values for purchase intention variables are shown in Table 1. According to question 2.1 of the questionnaire, the researcher determines how far the respondent's response to television advertising with regard to smart phone purchases intention. To assess role ambiguity, three items on a five-point Likert scale ranging from strongly disagree (scale 1) to strongly agree (scale 5) were used.

The mean values of TV advertising variables are 3.93, 4.18, and 4.15, respectively, and fall within the range of 3.5=X5. Tv advertising has a standard deviation of 1.204, 0.954, and 1.026, respectively. This shows that nearly all of the participants agree with the current state of those dimensions of television advertising on purchase intent. The mean values of radio advertising variables are 4.01, 4.18, and 4.15, respectively, and fall within the range of 3.5=X5. Radio advertising has standard deviations of 0.850, 0.977, and 1.026, respectively. This shows that almost all of the participants are in agreement with the current state of those dimensions of radio advertising on purchase intent.

The mean values of online advertising variables are 3.71, 4.31, 4.31, and 3.72, respectively, and fall within the range of 3.5=X5. Online advertising's standard deviations are 1.752, 0.539, 0.590, and 1.733, respectively. This shows that nearly all participants agree with the current state of those dimensions of online advertising on purchase intent.

The mean values of social media advertising variables are 3.93, 4.18, and 4.15, respectively, and fall within the range of 3.5=X5. Standard deviation of Social media advertising is 1.097, 0.977 and 1.026 respectively. This shows that almost all of the participants are in agreement with the current state of those dimensions of social media advertising on purchase intent.

The mean values of Billboard advertising variables are 3.93, 4.01, and 4.15, respectively, and fall within the range of 3.5=X5. Billboard advertising has standard deviations of 1.024, 0.850, and 1.026, respectively. This shows that almost all of the participants are in agreement with the current state of those dimensions of billboard advertising on purchase intent.

The mean values of Press advertising variables are 4.25, 4.11, and 4.15, respectively, and fall within the range of 3.5=X5. Press advertising has a standard deviation of 0.485, 0.625, and 0.538, respectively. This shows that almost all of the participants are in agreement with the current state of those dimensions of press advertising on purchase intent.

Analysis of relationship of advertising media on purchase intention

To determine the impact of advertising media (television commercials, radio commercials, online commercials, social media commercials, billboard commercials, and press commercials) on consumer purchase intentions for smart phones in Sri Lanka. Through correlation analysis, researchers can examine the relationship between advertising media (television, radio, and online, social media, billboard, and press advertisements) and consumer purchase intention.

Correlations

Since the person correlation is 0.138, there is a week positive relationship between TV advertisement and Smart phone Purchase intention. The correlation of radio advertisement and purchase intention is 0.121, implying that there is a week positive relationship between radio advertisement and purchase intention.

The relationship between online advertising and purchase intent is 0.020, there is a week positive relationship between online advertisement and purchase intention. The correlation between advertising on social media and purchase intent is 0.138, there is a strong positive relationship between social media advertising and purchase intent.

According to data analysis, there is a 0.123 correlation between billboard advertisements and purchase intent, there is a week positive relationship between Billboard advertising and purchase intent. The correlation between the press release and the intention to buy is -0.012., there is a week positive relationship between press release and purchase intention.

Hypotheses testing

To examine the impact of advertising media on purchase intention of Smart phone in Sri Lanka, the following hypotheses was developed.

H0: Advertising media (television advertisement, Radio advertisement, online advertisement, social media & press advertisement) has a not a significant impact on consumer purchase intention of Smart phone in Sri Lanka

H1: Advertising media (television advertisement, Radio advertisement, online advertisement, social media advertisement, bill board advertisement, & press advertisement) has a significant impact on consumer purchase intention of Smart phone in Sri Lanka advertisement, bill board advertisement, and press advertisement.

According to ANOVA (Table 2) significant value is 0.421 that is explain the significant of the model and also it is more than 0.05so we can identify the model is significant

According to coefficient Table 3 significant value of radio advertisement is 0.732 and it is more than 0.05 therefore it implies that there is not a significant impact of radio advertisement on purchase intention. Also considering beta value of radio advertisement -0.316, there is a week negative impact of radio advertisement on purchase intention.

According to coefficient Table 3 significant value of online advertisement is 0.929 and it is more than 0.05 therefore it implies that there is not a significant impact of online advertisement on purchase intention. Also considering beta value of online advertisement (0.029), there is a week positive impact of online advertisement on purchase intention.

According to coefficient Table 3 significant value of social media advertisement is 0.378 and it is less than 0.05 therefore it implies that there is a significant impact of social media advertisement on purchase intention. Also considering beta value of social media advertisement 0.962, there is a positive impact of social media advertisement on purchase intention.

According to coefficient Table 3 significant value of billboard advertisement is 0.869 and it is more than 0.05 therefore it implies that there is not a significant impact of billboard advertisement on purchase intention. Also considering beta value of billboard advertisement -0.109, there is a week negative impact of billboard advertisement on purchase intention.

According to coefficient Table 3 significant value of press advertisement is 0.254 And it is less than 0.05 therefore it implies that there is a significant impact of press advertisement on purchase intention. Also considering beta value of press advertisement (-0.531), there is a week positive impact of press advertisement on purchase intention. According to coefficient (Table 3), the intercept of model is 3. 310. We can fit the model for relationship using Beta value of advertising media tools.

Y= 3.310+0.000TA-0.316RA+0.029OA+0.962SA-0.109BA-0.531PA

Y= Purchase Intention; TA= Television Advertisement; RA= Radio Advertisement; OA= Online Advertisement; SA= Social Media Advertisement; BA= Billboard Advertisement; PA= Press Advertisement

According to the model there is 0% slope between purchase intention and TV advertisement. It implies that dependency of purchase intention on TV advertisement is 0%also there is negative -31.6% slop between purchase intention and radio advertisement. It says that negative dependency of

purchase intention on radio advertisement is 19.5%. Also, there is 2.9% slope between purchase intention and Online Advertisement. It implies that dependency of purchase intention on Online Advertisement is 2.9%.

Also there is 96.2% positive slope between purchase intention and social media advertisement. It implies that dependency of purchase intention on social media advertisement is 96.2%. Also there is -10.9% negative slope between purchase intention and billboard advertisement. It implies that dependency of purchase intention on billboard Advertisement -10.9%. Also, there is -53.1% negative slope between purchase intention and press advertisement. It implies that dependency of purchase intention on press Advertisement is -53.1% (Table 4).

The coefficient of R square varies between 0-1. According to model summary (Table 4), R square value is 0.183 18.3% of purchase intention is explained by advertising media (television advertisement, Radio advertisement, online advertisement, social media advertisement, bill board advertisement, press advertisement.)

Recommendations

According to the findings of Bi-variate correlation analysis correction coefficient is positive 0.138 Hence it can be concluded that there is a weak positive relationship between the TV advertisement and purchase intention in Smart phone industry in Sri Lanka.

According to the findings of Bi-variate correlation analysis correction coefficient is 0.121. Hence it can be concluded that there is a week positive relationship between radio advertisement and purchase intention in Smart phone industry in Sri Lanka. According to the findings of Bi-variate correlation analysis correction coefficient is 0.020. Hence it can be concluded that there is a week positive relationship between online advertisement and purchase intention in Smart phone industry in Sri Lanka. According to the findings of Bi-variate correlation analysis correction coefficient is 0.138. Hence it can be concluded that there is a weak positive relationship between social media advertising and purchase intention in Smart phone industry in Sri Lanka. According to the findings of Bi-variate correlation analysis correction coefficient is 0.123. Hence it can be concluded that there is a weak positive relationship between billboard advertisement and purchase intention in Smart phone industry in Sri Lanka.

According to the findings of Bi-variate correlation analysis correction coefficient is -0.012. Hence it can be concluded that there is a weak positive relationship between press advertisement and purchase intention in Smart phone industry in Sri Lanka.

Conclusion

According to the regression table at significant level 0.05. “b” value of TV advertisement is 0.068,” b” value of Radio advertisement is -0.316, “b” value of online advertisement is 0.029,” b” value of social media advertisement is 0.962 “b” value of billboard advertisement is -0.109” b” value of press advertisement is -0.531 “b”. According to R square value of model summary table, 34% of purchase intention explained by advertising media variables. Finally, researcher can be concluded that, this model is suitable for explain the impact between purchase intentions and advertising media in smart phone industry in Sri Lanka.

The purpose of the study was to determine the impact of advertising media on the Sri Lankan smart phone industry. According to the R Square value, 34 percent of purchase intention is explained by advertising media. However, three factors have a negative impact: radio commercials, billboard advertisements, and newspaper advertisements. When other factors (online advertisements, social media advertisements) are taken into account, the purchase intention in the Smart phone industry is positively influenced. According to the smart phone industry, marketers must use social media advertising as a means of promoting their devices. People can easily assess for online advertisement as soon as they need it, which is one of the main reasons for choosing social media. The social media advertisement has a "b" value of 0.962. Online advertising is also a powerful tool. People can easily access online advertisements because they are easily accessible.

Recommendations for Further Research

Basically, the focus of this research is on the impact of advertising media on purchase intent in the Sri Lankan smart phone industry. As a result of time limitation this research is only focusing to collecting data from only one district and online social media (face book, Viber and email) as further research can be guided with covering large sample and more districts. It also aids in gaining a clear understanding of the impact of advertising media on purchase intent in the Smart phone industry as a whole. According to the findings, social media advertisements have the greatest impact on purchase intent. In addition, the growth of online advertising and the decline of radio and social media advertising have been identified by the researchers. As a result, the researchers propose that the impact of social media advertisements on purchase intent be measured from various perspectives.

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