The Relationship with Ad Clicks and Purchase Intention: An Empiricial Study of Online Consumer Behaviour

1. Introduction

Consumers once had a limited number of media channels they obtained product information from word of mouth and print media to learn about products. Media channels increase in the 20th and 21st centuries and consumers could access information. Media contains all of the information anywhere, at any time after the advent of radio, television, internet and social media (Woo et al, 2015)

Especially social media affect to consumers’ purchase intentions. Consumers’ purchase intentions are driven by their perceived value. Word of mount affects the perceived value of goods or services. If consumers consider a product to be of high quality, they will show a higher willingness to buy it (Weisstein et al, 2014). Consumption motivation, congruity, attitudes to SNS advertising are important reasons to click ads on social media.

2. Theoretical Background of Ad Clicks, WOM and Purchase Intention

Tools and technologies for media and communication are undergoing major changes, based on economic transitions and digitisation (Pierson and Heyman). Especially, social media is commanding a larger share of advertising budgets, especially to reach the younger generation and affect their purchase intentions. It has become an imperative conduit for global marketing communications. Therefore, the value of advertising on social network sites such as Facebook, Youtube, LinkedIn, Twitter and others is of great interest to companies, managers and academics (Saxena & Khanna, 2013; Duffett, 2015).

Social media enable interactive information, user-created content and collaboration. It is classified social media by social presence and self-disclosure: personal blogs and micro-blogs, social networking sites, virtual worlds, collaborative projects and content communities (Kaplan and Haenlein, 2010). As consumers spend more time on social media, purchase decisions have become highly influenced by interactions through these networks. Thus, businesses are placing more emphasis on marketing strategies using two-way communication platforms to reach online consumers and take advantage of word-of-mouth (Song and Yoo, 2014; Heinrichs et al., 2011).

Social network sites have a cognitive function in product choice. Customers prefer to be guided by information from friends and other personal contacts rather than a company’s advertising department (Palmer and Lewis, 2009; Susskind, 2002; Harrison-Walker, 2001).

More than two-thirds of companies are using social media for marketing and service (Ma et al., 2015). Therefore, social media is exciting tool for marketers and managers. It has become preferred media all around the world and is influencing consumer behavior (Prasad, et al., 2017; Bernhardt et al., 2012). Social media has enabled people from anywhere to access companies any time through electronic devices, such as computers, mobile phones, etc. (Zhang and Mao, 2012)

Electronic devices are effective to click ads and purchase immediatedly as well. With the advance of the internet, through online advertising, companies communicate, interact with, and persuade online users in order to position a brand, which allows a company to promote both consumer awareness and preference in a customized and personalized way, and decrease the time needed to make a buying decision” (Hanafizadeh and Behboudi, 2012; Barreto, 2013). Furtermore, viral marketing uses by companies and defines marketing trend of the decade. Companies build awareness with viral campaigns and promote their products and services (Ferguson, 2008).

Word of mouth marketing has attracted both scholars and practitioners of marketing. It is investigated to understand its effect on companies and buying behavior, both online and offline (Brown et al., 2007). Especially, discussion forums, product reviews, emails and social network sites act as an source of information and opinions for WOM among consumers, serving as an important. These network sites have changed consumers to make purchase decisions, as they can easily and quickly exchange product-related information and opinions with personal contacts without geographic and time constraints (Kudeshia and Kumar, 2015; Graham and Havlena,2007).

Congruity

The congruency of advertisement, content and social network sites is important. Some kind of information that users do not look for when they visit these sites. Therefore, companies identify key consumers, generate content and prepare ads them to click ads and make purchase decision (Barreta, 20013) On the other hand, companies’ web site congruity with stores, banks, social network sites and etc. should be easy. Nowadays alluring and confusing applications affect consumer purchase intentions (Cummins et al., 2014).

The relationship congruency and content on social network sites to consumer click ads and comment about companies (Chang and Fan, 2017). Especially, fan page can give rise to hedonic consumption through fan sites (Turel et al., 2010). On the other hand, children and younger people are under the environment effects (Gunter et al., 2002). Therefore, companies have to take in consideration the values of the children and younger people (Furnham and Price, 2006).

Attitudes to Ads

In the literature of advertising it has been proven that viewers show positive attitudes to informative ads on social networks. Entertaining ads also generate positive attitude towards company (Taylor et al.,2011) The entertaining nature of brand-related contents influences people to read or watch and comment (Muntinga et al., 2011). Humour appeal in advertising does attract viewers (Khan, 2016). Attitudes to Ads can be defined as consumer’s overall evaluation of an advertisement or company. The attitude of customer toward an advertisement has a significant effect on its purchase intention, as advertise attitude is the most important determinant of purchase intention (Kudeshia and Kumar, 2015; Olson and Mitchell, 2000). In recent years, social media has become a major factor in influencing various aspects of consumer behavior such as awareness, opinions, attitudes, purchase intention and post purchase communication and evaluation (Mangold and Faulds,2009). Since consumer accept and have a positive attitudes toward ads (Taylor et al., 2011), company ads should integrate with web site, forums, blogs, word-of-mouth forums and social network sites (Assimakopoulos et al., 2016).

Consumption Motivation

The information play the key role on consumption motivation. Information sharing is motivational factor affecting consumer’s opinions. Therefore, these factors help companies that are planning to use a social network site in information sharing (Vuori and Okkonen, 2012). The basic motivations are the increasing popularity of social media, the congnizant of other companies’s presence and low prices. Interact with companies, increasing new product awareness, payment by installments motivates consumer (Tsimonis and Dimitriadis, 2014). Consumer are motiveted with interactive ads strategies. The effectiveness of website and SNSs lead consumer to click ads (Rodgers et al., 2007). Motivation is positively connected with the loyalty of users. It motivates individuals to share knowledge in traditional way such as by word of month. Besides the engagement in information sharing on the internet or within social media channels motivate them. Social interaction with other users, such as posting, commenting and reviewing maintain relationships among members on SNSs.

3. Conceptual Framework and Hypotheses

Based on the previous research the following hypotheses have been listed to be tested.

H1: Congruity has an effect on Ad Clicks

H2: Attitudes to SNS Advertising has an effect on Ad Clicks

H3: Consumption Motivation has an effect on Ad Clicks

H4: WOM has an effect on Ad Clicks

H5: Ad Clicks has an effect on Purchase Intention

Figure 1. Conceptual Model

Based on these hypotheses, the research model is structured to explain how Congruity, Attitudes to SNS Advertising, Consumption Motivation and WOM affect Purchase Intention through Ad Clicks.

4. Methodology

Measures

A review of the literature yielded a number of measurement instruments that were employed to test the hypothesized model and each scale has a history of reliable measurement (See Table 2). All scales employed in this study were measured on five-point Likert scales ranging from 1 (strongly disagree) to 5 (strongly agree). In the process of translation, the techniques of back translation and parallel translation have been adopted with the help of a group of academicians fluent in English and Turkish. The final Turkish version of the questionnaire was further verified by the authors of this paper.

Table 1. Measurement items

Table 1. Measurement items (Continue)

Sampling and Data Collection

Data for this research was collected through a questionnaire survey. The survey screened the participants by asking whether they have used social media before. During six-week period, 350 respondents completed the survey. After sorting and removing duplicate submissions, a net sample of 333 usable questionnaires remained. The major demographics of the respondents were listed in Table 1.

Table 2. Demographic characteristics of survey respondents (N=333)

The sample comprised of 168 Female and 165 Male. Ages of the sample ranged between 18 to 46 with mean 22.12 standard deviation 3.70. Data obtained from questionnaires will be analyzed through the IBM SPSS 23.0 and AMOS statistical programs.

5. Analysis and Findings

The main purpose of the study is structured to explain how Congruity, Attitudes to SNS Advertising, Consumption Motivation and WOM affect Purchase Intention through Ad Clicks.To identify and test the underlying structure of the scales exploratory factor analyses (EFA) were employed to each measurement as the initial step. The EFA results were further validated with confirmatory factor analyses (CFA). Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett test of sphericity tests were performed to test the appropriateness of data for conducting factor analyses (Sharma, 1996)

Table 3. EFA and CFA results

Results of the tests were satisfactory. Principal Component Factoring and Varimax rotation were employed to the data set. Factors with eigenvalues over one were retained and items with factor loadings below 0.50 and items with high cross loadings were excluded (Hair et. al., 2006).

As can be seen from Table 3., reliabilities for factors were 0.500 and 0.839 respectively. EFA results of Congruity, Attitudes to SNS Advertising, Consumption Motivation, WOM, Ad Clicks and Purchase Intention showed that all six scales were uni-dimentional as expected. Reliabilities for each construct were 0.734, 0.790, 0.500, 0.767 and 0.839 respectively. To test the internal consistency of factors, Cronbach’s coefficient alpha reliabilities were estimated. As it is shown the reliability measures of constructs ranged from 0.839 to 0.931, which shows satisfactory levels of internal consistency (See Table 3).

Then confirmatory factor analyses (CFA) were conducted using IBM SPSS AMOS 23.0 program to validate the factors proposed by EFAs. Chi-square test statistics are usually quite sensitive to sample size (Hair et. al. 2006), therefore in this study; Goodness of Fit Index (GFI), Comparative Fit Index (CFI), Normed Fit Index (NFI), Tucker Lewis Index (TLI) and Root Mean Square Error Approximation (RMSEA) were considered.

Results of EFA and CFA for each construct are explained below. The procedures to check for convergent validity and discriminant validity were practiced (Anderson and Gerbing, 1988; Fornell and Larcker, 1981). Construct reliabilities of 0.910, 0.863, 0.891, 0.931, 0.839, and 0.915 indicated high internal consistency of the dimensions (Hair et al. 2006; Netemeyer et al. 2003). Average variance extracted (AVE) values, which reflect the overall amount of variance accounted for by the latent constructs, were all above 0.50 threshold; AVEs ranged between 0.559 to 0.919 (Fornell and Larcker 1981). Items under each construct, factor loadings, Cronbach’s alpha and construct reliabilities are given in Table 3. The various fit indices for the CFA suggested good fit to the data x²(137, N=333) = 356.960, p= 0.000, Goodness of Fit Index (GFI)=0.896, Comparative Fit Index (CFI)=0.955, Normed Fit Index (NFI)=0.929, Tucker-Lewis Index (TLI)=0.944, Root Mean Square Error Approximation (RMSEA)=0.07).

There is no standard for acceptable GFI, but rule of thumb is GFI greater than 0.90 (Lattin et al., 2003) and RMSEA values of 0.08 and less have been advocated as indicative of acceptable fit (Hu and Bentler 1999; Lattin et al., 2003). Consequently, goodness of fit indexes supported the proposed model as fit.

Structural Model

Since the objective of this study was to identify dimensions that increased Intention to shop online, a structural model was tested. The result of the path analysis showed a good fit of the model (x² (143 )= 381.595, p=0.00; GFI=0.903, CFI=0.936, NFI=0.903, TLI=0.957, RMSEA=0.068).

Figure 2. Graphical representation of path model

Table 4. Result of Path Analysis

As a result of the path analysis it was found that the Congruity, Attitudes to SNS Advertising, Consumption Motivation and WOM affect Purchase Intention through Ad Clicks.

6. Conclusion

The paper finds that congruity, attitudes to ads and consumption motivation are efficient to click ads. Word of mount marketing lead to ad clicks, which respectively affect to purchase intention aswell. The importance of consumer behaviour and advertising on SNSs such as Facebook, Youtube, LinkedIn, Twitter and others come to exist in the study. Companies reserve a share of advertising budgets, especially to reach the chiildren and younger generation and affect their purchase intentions. Consequently, in the study all variables are positively related to each other and shows satisfactory levels. These results suggest that marketers need to take into account and manage actively social media and specifically their social network sites.

References