Online Purchase Intention of Tablets (PC): Role of Social Media and Learning Style

Since the internet and other media have been adopted and integrated into the daily lives of an increasing number of young adolescents in most of the countries, scholars and commentators are debating the impact of these new media on the activities, social relationships, and worldviews of the younger generations. Controversies about whether technology shapes values, attitudes, and patterns of social behaviour are not new. In the recent past, the rapid expansion of television stimulated similar discussions of its cultural and social effects.

The websites of Social media provide an opportunity for companies to engage, actively involve and interact, network with the potential and current consumers, to encourage an increased sense of confidence of the customer relationship, and build all important meaningful relationships with consumers by winning their trust (Mersey, et al 2010) especially in today’s business situation when consumer loyalty can be wiped out at the smallest mistake, which can additionally have online negative broadcast of their unfortunate experience with a particular product, service, brand or company.

The emergence of online social networks influences people in various ways and moreover, the effect is predicted to be high on the young adolescents wherein it is found that target group who is more exposed themselves to the online social media. It is believed that the social networks influence the purchase intentions and therefore it is important to study the potential impact online social networks may have in this field. The present study attempts to investigate the relations between the communications on the social network platforms and its effect on the purchase intentions of the consumers and more specifically the young adolescents. Further, this study also attempts to investigate how these relationships vary across young people possessing different learning styles.

In compare to traditional sources of firm-created communication, social media communications have been acknowledged as bulk phenomena with widespread demographic demand (Kaplan and Heinlein 2010). This acceptance of the implementation of social media communication among companies can be explained by the viral broadcasting of information via the Internet on social media websites (Li and Bernoff 2011) and the larger capacity to reach to the local public when matched with the traditional media (Keller 2009).

Brand always aim at presenting their company in a positive direction, communication through traditional media and firm-created social media communication – both fully organised by the marketer – will always lead to positive brand-based communication content and positive review. Thus, it is anticipated that a positive assessment of the traditional tools of marketing communications and firm-created communication will positively influence brand consciousness, awareness, functional, and to brand image.

User-generated content abbreviated as (ugc) is a speedily growing factor for brand conversations and consumer perceptions (Christodoulides et al, 2012). From the study conducted by the Anindya et al, (2012) the concept of User-generated content on social media platforms and product search engines is fluctuating the way customers buy for products online.

The concept of brand equity is a strategic marketing strength (Styles and Ambler 1995) that can build a relationship that discriminates the links between a company and its costumer and that encourages long-term purchasing behaviour (Keller 2013). The study the understanding of brand equity and its development increases competitive obstacles and pushes brand prosperity (Yoo, Donthu, and Lee 2000). Although research and studies has been carried out extensively in the field of brand equity, the literature review on this topic is disjointed and inadequate (George Christodoulides and De Chernatony 2010).

The measurement of brand equity has been come up from two major viewpoints in the literature. Some studies has focused on the financial aspects of brand equity (Simon and Sullivan 1993), whereas other studies have highlighted the customer-based aspects (Aaker 1991; Keller 1993; Yoo and Donthu 2001). Thus, the main stream of study has been grounded in reasoning psychology, concentrating on memory arrangement (Aaker 1991; Keller 1993).

Olson and Mitchell (1981) defines brand attitude is identified as a “purchaser’s overall assessment of a brand”. Brand attitude is normally conceptualized as a world-wide evaluation that is based on positive or negative reactions to brand-related motivations or philosophies (Murphy and Zajonc 1993) research work contribute to the fact that the central factor to be considered in consumer-based brand equity and interpersonal exchanges (Lane and Jacobson 1995; Morgan and Hunt 1994).

Brand attitude is included in the proposed conceptual framework in this study which aims to enhance the understanding of the effects of social media communication on consumer perceptions of brands.

Kolb (1984) developed the experiential learning model abbreviated as (ELM) is connected with the different learning style which takes the information processing method to learning. Fundamentally, the ELM is a four phase’s cyclical process, where students who learn meritoriously will experience all four phases at different times in the learning procedure and can interchange backward and forward through the phases, depending on what is being taught and the technique used. However, the learner will generally have a predilection for one particular style and, as their learning progresses, which changes the preference of the learner to adopt different style (McCarthy2010).

It is proposed in the model below that User Generated and Firm Generated Communication will influence the Brand attitude and Brand equity. Further, brand equity and brand attitude affects the purchase decision of the consumer. The integrated model also suggests that the learning styles acts as the moderating variable.

From the literature review supports the concept that branding communication influences brand equity by increasing the likelihood that a brand will be combined into a consumer’s consideration set, thus assisting in the process of brand decision making and in the process of the choice becoming a habit (Yoo, Donthu, and Lee 2000). Nielsen (2009) study states that 70% of internet users believe the evaluations of consumers in the form of review on social media platforms.

In this study it was assume that a positive evaluation of firm created social media brand communication will positively influence brand equity. Thus, the following hypothesis formulated which states:

H1a. Firm-created social media communication positively influences brand equity.

From the effect of user-generated social media communication on brand equity, it must be standardised that UGC is not normally guided by marketing involvement or company control over the market (George Christodoulides and Jevons 2011). If the consumers review is positive content carry information about a product/brand or company that can be mostly useful for consumers in relations to consumer-based brand equity. Additionally, the effects of UGC on social media can lead to growth about the brand consciousness and brand associations, hence influencing the overall assessment of a brand. Consequently, leads to hypothesize as follows:

H2a. User-generated social media communication positively influences brand equity.

As per the effect of user-generated communication on serviceable and hedonic profits can be both positive and negative. In the situation of functional advantage, the impact of user-generated communication relates to content handling and mainly with the quality characteristics of the brand that can be arbitrated in both forms positively or negatively by consumers, thus prompting functional brand image either satisfactorily or disapprovingly. The same rational applies to the influence on a brand’s hedonic advantage.

Nevertheless, brand attitude may also comprise of the affect that is not apprehended in measurable characteristics, even when a large set of features is involved. Researchers conducting study on Brand building multi-attribute models of customer inclination have incorporated a general constituent of brand attitude that is not clarified by the brand attribute standards (Srinivasan 1979). Supposing that positive brand assessments of consumers can reproduce perceptions of exclusiveness, which add to brand equity, leads to following stated hypothesis;

H3. Brand attitude positively influences brand equity.

It’s expected that firm-created and user-generated social media communication to positively affect brand attitude. Because firm-created social media communication is proposed to be positive and to intensify brand awareness (Li and Bernoff 2011) and because positive user-generated social media communication, thus also intensify brand consciousness and brand associations (Burmann and Arnhold 2008), the following hypotheses is presented:

H1b. Firm-created social media communication positively influences the brand attitudes of consumers.

H2b. User-generated social media communication positively influences the brand attitudes of consumers.

The study conducted by Farquhar (1989) opinions that there are three elements that are important in structuring a strong brand with the user: positive brand assessment, positive brand attitude, and a reliable brand image. From the research of De Chernatony et al. (2005, 2006) found that organizational culture and workers’ values are likely to impact the group of values user perceive as constituting a service brand.

This indicates that positive attitudes are likely to endorse brand purchase, which is an outcome of brand equity. Faithful users tend to purchase more than moderately faithful or newly joined costumers (Yoo, Donthu, and Lee 2000). A positive attitude toward a brand impact a customer’s decision making and purchase intention (Keller and Lehmann 2003). This also includes more positive costumer perceptions of the superiority of a brand are related with stronger purchase intentions and decision making (Aaker 1991). Thus, the following hypothesis:

H4. Brand attitude positively influences purchase intention.

H5. Brand equity positively influences purchase intention.

To purchase online is the decisions which are usually made by the user based on the information and display provided by electronic catalogues available for choice online or the communications that takes place on the social network platform through chats and reviews. There are few studies carried out which emphasis on the impact of brand communication role in consumer learning on online shopping, the presentation, display of the products, designs and formats of these communications play an important role in preventing or enabling the decision –making to buy online (Li et al. 2003).

Social networks and websites can provide a high degree of interactivity, to satisfy consumers learning needs, and influence their purchasing decisions to buy product online. It is thus hypothesised that the learning styles influences the above listed hypothesis numbered H1 to H5.

The instrument development involved structured interviews followed by a pilot study. Different statistical techniques were used to assess and validate the constructs selected for the study. Subjective content validity (based on structured interviews), Reliability tests (using Cronbach α) and confirmatory factor analysis (CFA) for evaluating the factor structure and initial validity were used for the investigation.

A two phased research methodology was adopted for this study. In the first phase, the definitions of the constructs as well as the measurement items for each construct were established. This phase provided tentative indications of reliability and validity.

The second part was an exploratory and confirmatory factor analysis and the third being the structural equation modelling, which discarded those items which did not enable suitable dimensionality for the entire construct in the model.

Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) was used to test the present model using AMOS 21 software and basic calculations in statistics such as mean, standard deviation, factor analysis, correlation will be performed using SPSS 21.

The questionnaire items were based on the studies conducted earlier by Hong (2012), Schivinski and Dąbrowski (2013), Rehmani and Khan (2011), Kolb (1985) and modified based on the experts commands. The questionnaire had three parts, Part A, B and C. Part A captured the basic descriptive details from the respondents on the personal information, their social media preferences, usage and perceptions on the purchase made using the social media information.

Part B captured the information on the five main constructs for apparels used in the study model viz., company generated social media communication, user generated social media communication, brand attitude, brand equity and brand purchase intention. The last part, PART C was aimed to collect the information pertaining to the learning styles of the respondents. It was based on the methodology proposed by Kolb (1985).

The sample size selected for the study was 301 students presently pursuing their business education from Mumbai and Bangalore. For each category, the respondent will be required to indicate a brand that he or she has “Liked” on social media from the selected three product categories. It was assumed that consumers have been exposed to social media communication from both companies and users from brands that they have “Liked” on any social media platform. The product categories and wide array of brands also reflect an extensive set of consumer products and should provide research generalizability.

As a requisite for the study, the respondents were required to receive news feeds both from the company and from other users with respect to the brand that they had previously “Liked” on the social network site and have developed a purchase intention. Each respondent was required to complete one version of the questionnaire evaluating only one brand. He had to fill different questionnaire for different brands.

As sample size depends on statistical tool as structural equation modelling (SEM) is used in this study. Sample size is decided based on two conditions: (N > p), where N is number of sample and p is observed variables (Schermelleh-Engel, and Moosbrugger, 2003); and with three more indicator per factor sample of 301 is sufficient for convergence and proper solution (Lacobucci, 2010). Hence total sample size of 301 respondents are considered, as number of observed variable for product category is 18 and makes a total of 54 variables for model testing.

The selected respondents represented 65% Male students and the other 35% female students. 21.5% percent of the respondents belonged to the commerce stream, 15.2% from Science, 27.9 % from Management and 24% from Engineering background. In terms of the present interaction with reference to the time spent on the social networking sites. Care was taken to have a representative distribution of the sample respondents. No respondent was selected for the study who doesn’t spend any time on these networks. Almost 65% of the selected respondents spent more than 7 hours per week on the social media sites.

The model with five critical variables Firm Created Communication (TPC_FCC), User Generated Social Media Communication (TPC_UGSMC), Overall Brand Equity (TPC_OBE), Brand Attitude (TPC_BA) and Brand Purchase Intention (TPC_BPI) identified from the literature had content validity because an extensive review of the literature was conducted in selecting the items.

The respondents were asked to give their responses keeping in mind a representative brand for the tablet PC so that the model validations can be carried out. The breakup of brands selected under the tablet PC product category is shown in figure below.

The reliability values for all constructs are all greater than .80, it was found that brand purchase intention got highest value of 0.895 which are considered acceptable (Nunnally, 1978). Table presents the statistical descriptive measures like mean, standard deviation and range of item correlations for the constructs selected in the study. From the ranges of item to item correlation (R2) it was interpreted that the items show high positive correlation with the each other. From the Table the ranges of item to item correlation (R2) it was interpreted that the items show high positive correlation with the each other, with a significant level of 0.05. The factors which have scored high value of correlation have shown considerable positive range of correlation amongst themselves. The percentage of variance is a popular and intuitive index of goodness of fit in multivariate data analysis the higher the percentage of variance a proposed model manages to explain, the more valid the model seems to be from the above table all the constructs are showing higher percentage of variance ranging between 72 to 82%.

Structural Equation Modelling (SEM) was used to test the relationship between the five constructs at α = 0.05, Firm Created Communication (TPC_FCC), User Generated Social Media Communication (TPC_UGSMC), Overall Brand Equity (TPC_OBE), Brand Attitude (TPC_BA) and Brand Purchase Intention (TPC_BPI)

Table below presents the regression weights for the various relationships. The relationships were found to be highly significant across all the selected constructs. It is found that the model fit is satisfactory. The model is accepted as good model with CFI = 0.802, GFI = 0.862, NFI = 0.881, RMR = 0.028, Cmin/Df = 5.141.

These relationships are depicted in graphical form as given by the AMOS output in the following figure.

It is found that the model fit is satisfactory though the cut off values are relatively low based on meeting the above standards used by the researchers for SEM, still the model is accepted as good model with CFI = 0.802, GFI = 0.862, NFI = 0.881, RMR = 0.028, Cmin/Df = 5.141. The significant relationships between the various constructs and the items used for defining the constructs can be found from the table given below.

The findings of the first phase revealed that majority of the respondents (almost 50% of them) followed the concrete learning style followed by reflective learning style and active learning styles. Surprisingly none of the student were identified to fall in the category of Abstract learning styles. This shows that the MBA students, when interacting on the social networking are highly action oriented and believe in either experiencing, reflecting or doing, then thinking.

Structural Equation Modeling was used to test the effect of learning styles on the SMBM model. The model was run for the three groups identified in our study namely. Concrete Learning Style, Reflective Learning Styles and Active Learning Style. The regression weights estimated for the three groups are shown in Table a, b and c. the significant tested model with modifications are presented in figure a, b and c.

The following observations are made from the findings presented in the above tables:

• Concrete Learning Style

All the relationships were found to be statistically significant with the Firm Generated Communication having the maximum effect (0.794) on the brand attitude compared to the effect of the User generated Communication on the brand image.

• Reflective Learning Style

Surprisingly in this case also it was found that the All the relationships were found to be statistically significant with the Firm Generated Communication having the maximum effect (0.805) on the brand attitude compared to the effect of the User generated Communication on the brand image.

• Active Learning Style

In this group also the Firm generated communication helped to have a very strong influence (0.716) on the brand attitude as compared to the influence of the User Generated communication directly on the brand equity.

Overall we can say that the Firm generated information plays a very important role in developing a brand attitude leading to brand equity and purchase intentions irrespective of the learning styles adopted by the person.

The result reported in this paper contribute to the literature on the influence of firm created social media communication & user generated social media communication on brand attitude which in turn influence brand equity and subsequently purchase intention by making explicit the mediating/moderating role of learning style on the antecedents of brand attitude. Thus the following suggestions can be extracted for the practitioners.

Companies should engage with multiple blogs, forums and wikis covering issues relating to their product or brand. There has to be frequent comment and should try to create a dialogue with the social media users. This will help to form a chain reaction on the internet and may lead viewers of other blog back to your blog or the media company is using. It is required that the marketers should have the detailed twitter profile included on the company URL. Company should strive to tweet minimum twice a day and aim to increase the follow up with the online viewers. It is also recommended to have a YouTube channel which points to the blog and twitter and should sponsor or develop webcasts to help the college students with any areas they are struggling with related to the product or brand. Videos should be uploaded regularly.

Companies don’t necessarily need to engage with the people who have the largest number of apparent connections. These people might not necessarily have the greatest number of strong relationship amongst their connections. Monitoring their blogs, status updates and forum entries will give a good idea of how they interact within their social circle.

Company also needs to consider their people inside the organization. They need to identify evangelists, enthusiasts, pragmatists and any detractors inside the organization. These are the people who might have already be speaking publically about the brand. Make sure that they are prepared to communicate externally with an effective, practical and workable social media policy.

The rapid rise of social media may be the most important evolution to impact marketing in decades. It has changed almost everything. It enables businesses to influence new buyers (rather than sell to them), interact and engage with customers (instead of having a one-way dialogue), and it puts the consumer in control of shaping and influencing a brand (not marketers).

Around the world. Social networks, blogs, media aggregators, and dozens of different types of digital media provide channels for consumers to have their voices heard. This has changed the entire landscape of marketing, and the bottom line is that power has shifted to consumers who now have the ability to interact and influence brands. Consumers can influence how fast a new product is adopted and liked, and they can bring a company to its knees when they set out to damage a brand. When videos like the “Comcast sleeping technician” are posted and shared, it’s easy to see how the power of one consumer-generated video can affect a brand.

Consumer-generated media is everywhere. YouTube gives users power and control to upload, download, post, and share videos to inform, persuade, educate, and entertain others. Media sites like Digg and Stumblupon give consumers the power to review and vote on content they believe is the most important or interesting. On sites like Wikipedia, content is completely created by a community of users. What drives the popularity of consumer-generated media? At the most basic level is the emotional need to be heard. People that feel “wronged” want to be heard as much as they want to evangelize what they love. The Internet and social media is so accessible and easy to use, it provides a platform for those that want to connect, communicate, and drive change.

o Because of time limitation and to keep the model at a manageable size, this research did not consider the factors inhibiting the use of social media on the teens and youngsters like age restrictions, restrictions by the parents to use social media etc. future studies may address these issues.

o Future study may develop additional measurement constructs in the model such as demographic profiles of the users or the effect of technology adoption like perceived usefulness or ease of use components of the social media. Even it would be interesting to evaluate the effect of peer pressure in using the social media and its effect on the purchase decisions.

o It would also be interesting to carry out the research both in developing countries and developed countries and study the implications for social media on the brand managers in these economies, specific to the product categories selected in this study.

o The social media landscape and practices are changing with the competitive environment as discussed in the previous section and hence with changing times it is required to get the selected practices and the measures validated from the practitioners.