Social and attitudinal determinants of viral marketing dynamics

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1 Social and attitudinal determinants of viral marketing dynamics Zahra Modiri-Delshad 1, AsgharMoshabaki 2 1 MA business Management, Department of Management, South Tehran Branch, Islamic Azad, Tehran, Iran 2 Business management, department of management, South Tehran Branch, Islamic Azad University, Tehran, Iran Abstract Cyberspace refers to new tools for marketers to improve the efficiency and effectiveness of marketing communications and offer new approaches to gain and retain customers. One of its aspects is online interpersonal influences. It can be said that viral marketing is an internet-based communication strategy that exploits the transmittable nature of information dissemination on the Internet. This study investigates the impact of attitudinal and social determinants to the dynamics of viral marketing. Statistical population involves students of three State Universities of Tehran,which is considered 391 students to test according to Morgan. In this study, sampling was done as random and accessible methods. Variables in the research model are the three social capital dimensions including structural (communication and interconnection), relational and cognitive, as well as positive and negative attitudes and viral dynamics. Data analysis was performed using the software SPSS 21 and LISREL. Cronbach's alpha is more than 0.70 in all variables and they had acceptable reliability. The findings suggest that there is a direct relationship between structural capital communication-receiving, structural capital-interconnection with "receiving, opening and sending ", the relational capital-opening and sending, a positive attitude - willingness to open the message. Also, there is an inverse relationship between negative attitude and a willingness to open and send viral and relevant assumptions are confirmed. However, there is no direct relationship between structural capital - sending, rational capital - receiving, positive attitude - willingness to sending message, and cognitive capital - opening and sending, so the relevant will be rejected. Keywords: Viral marketing, Viral dynamics, Social capital, marketing, WOM 1. Introduction Marketing and marketing strategies is heavily influenced by the contemporary technology and the technology throughout their life history. With the advent of the printing press, radio, television, computer and etc. marketing has played its own roles, and it is tried to use technological tools in order to achieve their goals.on one hand, information technology has transformed the nature of markets. Today, the markets are considered as online and virtual that theyare completely different from the physical markets (S.Javadin, Asfidani&Aghazadeh, 2007). Viral marketing, among emerging marketing, is located in the field of e-marketing.another major area that is proportional to viral marketing is the marketing communications.this approach focuses on expanding the message and its viral properties (Welker, 2002). If marketing can be described as war, then viral marketing can be called biological warfare, because ideas are released quickly and easily and almost nothing ecan stop them from the release and they are epidemic after traversing the boundaries around the world and suddenly it can be observed that all the people around the world are considering and are talking about the same issue (Silverman, 2001). 2. Research literature Given that today, most consumers are resistant against traditional marketing methods such as television, newspaper commercials etc., and so marketers have created alternative strategies such as viral marketing.viral marketing and viral advertising refer to marketing techniques that they use available social networks to increase brand awareness or other objectives such as increasing sale through virus process, like how to spread virus in computers and humans. However, this problem can be in two forms, as oral or through the Internet network effects (Howard, 2005). In fact, viral marketing of available social networking is exploitedby encouraging 441

2 consumers to share their friends the information about the product (Sweeney, 2008). Viral marketing was first mentioned in an article in User in 1989.But it was renowned on the Internet in late 1998 (Helm, 2000). Today, the Internet is an important channel for marketing and advertising; this could be due to the ability of the Internet to cut costs and providing easy access to online services. Also Propagandists can easily access a multitude of users and communicate with them at low cost (Lages, 2004). marketing is one of the most powerful as well as understanding tools in marketing world (Jenkins, 2010). In this study, the concept of viral marketing is defined as transmission of word of mouth by recipients of a message on the Internet. In fact, it means publishing and sending s received by one person to others and the concept of word of mouth is as going hand in hand of by Internet users. Dynamics of viral marketing also includes "receiving - opening -sending" process of viral. Nahapiet and Ghoshal (1998) define social capital as the sum of internal actual and potential resources, available through, and derived from a social unit or an individual social relationships network. From their perspective social capital is an important organizational capabilities and assetsthat can significantly assist organizations in creating and sharing knowledge and provide sustainable business advantage for them compared with other organizations. In other words, they have addressed the concept social capitalfrom an organizational perspective.theyconsider social capital as structural, relational and cognitive dimensions. A structural element refers to the overall pattern of contacts between individuals;this means whom and how you access to. The most important aspect of this isnetwork relationships among individuals, network configuration, and appropriate organization.social capital theory is mainly recommended that network relationships are able to provide access to resources (e.g. knowledge).the general configuration of social network relationship forms an important aspect of social capitalthat can affect on the development of intellectual capital and knowledge management, and their performance improvement.appropriate community organizations canprovide a potential access network to people and their resources including information and knowledgeand they may guarantee motivation and capability to exchange through the cognitive and relational dimensions (Ghelichli&Moshabaki, 2006). The cognitive element of social capital refers to resourcesproviding representations, interpretation and shared meaning systems among groups (Chen et al., 2004). Two basic elements of cognitive aspect include shared codes and language and shared narratives (Nahapiet and Ghoshal, 1998). It can be said that attitude is a theory offering about people, things, or events and it reflects how a person feel about one thing (Rabins, 1995). Individuals intentions for participating in the process of viral marketing will be determined by their attitudes to viral message.people belief to viral is an important motivational factor to open and resend them. The main question of this study is: How social and attitudinal factors affect on viral marketing dynamics? 2.1 Research Hypothesis H 1 The more often individuals receive viral, the moreoften they forward them (H 1 a).the frequency with which individualsopen acts as a mediating factor in the process ofreceiving-sending (H 1 b). H 2 The greater the individual s connectedness in the network, the greater the frequency with which they receive (H 2 a) and forward (H 2 b) viral. H 3 The greater the individual s integration in the network, the greater the frequency with which they receive (H 3 a), open (H 3 b) and forward (H 3 c) viral. H 4 The greater the individual s relational social capital, the greater the frequency with which they receive (H 4 a), open (H 4 b) and forward (H 4 c) viral. H 5 Individuals attitude toward viral impacts their intention to open them (H 5 a) and forward them (H 5 b). H 6 The greater the individual scognitive social capital, the greater the frequency with which they receive (H 6 a), open (H 6 b) and forward (H 6 c) viral. 442

3 2.2 Research Conceptual Model 2.3 Research Review Chiu, Lee, and Chen (2007), in a study on "viral marketing: Investigating the behavior of spreading based on gender" concluded that men are significantly influenced by negative sources of, while women are more affected by positive ones. It was determined that women are more inclined to send with fun and enjoyable content. Wiedemann, Haunstetter and Pousttchi (2008), in a study about Analysis of the essential elements of viral marketing via cell phone: An experimental study, found that there is a positive relationship between the presence of most people interested in sending on-line content and their dependence on communication techniques of cell phoneby increasing the online content and growing older was not considered to reduce online content; also, there is no significant differences between men and women on sending online content. Dobele, Toleman and Beverland (2005), in a study as Electronic Dialogue: spreading the brand message through viral marketing, concluded that there is a way for marketers that make their satisfied and current customers interest in sending pleasant through appropriate communication due to their favoritecriteria, and thereby the users voluntarily are willing to deliver the message to others.marketers are able to change the brand position and mental image of the brand by appropriate use of viral marketing and cause to promote the company position in the market in lower cost. 3. Methodology This research is applied research based on objective, and it is descriptive in terms of method. Appropriate sample size is 384 subjects based on The Morgan and there are 391 final questionnaires completed by male and female students. In this study, sampling methods are random and accessible. Statistical population consists of three state universities (Sharif, Tehran and TMU). In this study, the data was collected by questionnaire and library method as well as Likert scale and semantic differential was used to measure the variables.content validity of the questionnaire was verified and evaluate according to experts. But in order to take advantage of the respondents comments in relation to nominal credit, comments were collected In terms of Yes and No. Statistical analysis was done using "SPSS 21" and LISREL.Research demographic and basic variables were described using frequency tables and Mean Statistics, Median and Standard Deviation. Reliability was measured using Cronbach's alpha and internal compatibility; also validity was assessed by confirmatory factor analysis and data normality using Shapiro Wilk test. Hypothesis test and research model and Structural Equation Modeling techniques were performed using Pearson correlation coefficient and Lisrel, respectively. 4. Data analysis The findings are presented as both descriptive and inferential. 443

4 4.1 Descriptive Findings Demographic characteristics In this section we examine the demographic characteristics of respondentsincluding gender, age and education. Gender Respondents were 63% female and 37% male. Education Subjects fall in five groups according to education: Diploma, Associate Degree, BA, MA and Ph.D.The results show that Frequency distribution of subjects with Diploma, Associate Degree, BA, MA and Ph.D degrees are 2%, 1%, 12%, 67% and 18%, respectively. Age Subjects were divided into five categories based on their age: (2%), (30%), (48%), 30-35(16%) and above 35 years old (4%). 4.2 Inferential findings Investigating the status of data normality Table 4.1. Shapiro Wilk test and analysis of the skewness and kurtosis of the data to evaluate its normality Variable Significance level (Shapiro Wilk test) skewness Kurtosis Positive attitude towards receiving viral Negative attitude towards receiving viral Viral dynamics 0.001<P Receiving viral Opening viral Forwarding viral 0.001<P Cognitive social capital 0.001<P Structural social capital Connectedness 0.001<P Integration Relational social capital Variables correlation matrix Table 4.2 reports research Variables Correlation. Pearson's correlation coefficient was used to evaluate the variables correlation. 444

5 Table4.2. Research variables correlation matrix Variables Positive atitude towards receives viral - Negative atitude towards receives viral ** Viral dynamics ** ** Cognitive social capital ** Structural social capital ** * Connectedness Integration Relational social capital ** Research Model Test ** ** ** ** ** ** * ** ** ** ** ** * <P و ** 0.05<Note: * P Figure 4.3 indicates research model on the coefficients and significance levels. Associated with t-test, ift>1.96, the obtained correlation could be significant at error level (p<0.05); if t>2.58then, correlation could be significant on error level that is less than 0.01 (p<0.01) Fitting Indexes 0.01<P ** Note: Figure 4.3. Research Conceptual Model Test on standardized coefficients and t-value RMSEA, PGFI, CFI, and NFI were measured 0.067, 0.66, 0.96, and 0.95, respectively. In general, assessing the fitting parameters can be inferred that obtained fitting indexes are acceptable; and totally indicating a proper data fitting with the model. chi-square Table 4.4. A conceptual(original) research model fitting indexes Df chi square /df p-value RMSEA GFI PGFI CFI NFI Research Hypothesis Test test results of the research are shown in Table 4.5Standardized direction coefficient and t- test value are presented. It can be observed the study of relationship and conceptual model shows 445

6 that 9 hypotheses have been approved (P 0.05) and 8 ones have not (P>0.05), among them. The coefficient of determination (R 2 ) was obtained 0.54 for viral message and it indicates that 54% variations of sending viral message are explained by the independent variables of the model. It was obtained 0.15 for receiving viral messaging indicating the independent variables of the model explain 15% variations of receiving viral message. This was obtained 0.44 for opening viral messaging indicating the independent variables of the model explain 44% variations of opening viral message. In following, it is presented the results of test.hypothesis test is based on Structural Model. Table 4.5. Hypothesis Test, Standardized Coefficients and t-value of original model Relationship type standardized coefficient significance level (t value) result direct relationship between receiving and forwarding viral Interfacing for opening direct relationship between connectedness and receiving viral direct relationship between connectedness and forwarding viral direct relationship between integration and receiving viral direct relationship between integration and opening viral direct relationship between integration and forwarding viral direct relationship between relational social capital and receiving viral direct relationship between relational social capital and opening viral direct relationship between relational social capital and forwarding viral positive relationship between positive attitude and intention to open the negative relationship between negative attitude and intention to open the positive relationship between positive attitude and intention to forward the negative relationship between negative attitude and intention to forward the direct relationship between cognitive social capital and receiving viral direct relationship between cognitive social capital and opening viral direct relationship between cognitive social capital and forwarding viral ** ** 0.20 ** 0.16 ** ** 0.11 ** 0.10 ** 0.25 ** ** <P ** Note: Research Empirical Model 446

7 In a modified or empirical model, all relationship and directions are significantand Model Integrity is confirmed. Modified model of research has obtained by elimination of non-significant relationships in the initial model and then presented.all directions listed in the empirical model is significant among the variables. Note: ** P<0.01 Figure 4.1. Research Empirical Model on standardized coefficients and t-value Generally, evaluating fitting indexesand comparing it with the original model fitting indexes, it can be concluded thatfiting indexes are slightly improved and data have better fitting with the modified model. Table 4.6.Research model fitting indexes Chi-square Df Chi-square/ df p-value RMSEA GFI PGFI CFI NFI Coefficient of determination (R2) for sending viral message, receiving viral message, and opening viral message was obtained 0.53, 0.14, and 0.43, respectively. Coefficient of determination of sending viral message was achieved 0.53; that is, the independent variables of the model are able to explain 53% variations of sending viral message. There is little reduction in coefficient of determination of modified model compared to the original model caused by eliminating some the variables and relationships in original model. Standardized coefficients and their significance are presented in Table 4.7.All coefficients are significant (p<0.01). Table 4.7. Hypothesis Test, Standardized Coefficients and significance level of original model Relationship type Positive relation between connectedness and receiveing viral message standardized coefficient 0.25 significance level (t value) 4.89 Positive relation between integration and receiving viral Positive relation between integration and opening viral Positive relation between integration and forwarding viral Positive relation between relational social capital and opening viral

8 Positive relation between relational social capital and forwarding viral Positive relation between positive attitude and intention to open viral Negative relation between negative attitudes and intention to open viral Negative relation between negative attitudes and intention to forward viral Positive relation between receiving and opening viral Positive relation between opening and forwarding viral 0.54 Note: All coefficients are significant at error level in less than 0.01 (p<0.01) Conclusions and discussion 5.1. Results from research analysis Coefficient of determination for sending viral message, receiving viral message, and opening viral messagewere obtained 0.54, 0.15, and 0.44 indicating 54%, 15%, and 0.44% thier variations are explained by independence variables of model, respectively. In following, it is investigated the results of confirmed and rejected.hypothesis test is based on Structural Model Viral dynamics There is no positive relationship between receiving and sending and therefore 1a is rejected. In fact, riceiving more viral does not show that people send more. Mediation in opening viral is rejected in relationship between sending and receiving viral. Therefore, there is no relationship between sending and receiving viral. Mediation in opening viral is rejected due to not be relationship between sending and receiving viral. Therefore 1b was rejected Structural social capital (communication) Structural social capital-communication is positively related to viral message, thus 2a is confirmed. In fact, more communication between people in network makes receiving more for them. Structural social capital (communication) has no positive relationship with sending viral, therefore 2b is rejected. In fact, more communication between people in network does not makethem send more Structural social capital (interconnection) Structural social capital (interconnection) is positively related to receiving viral message; therefore 3a is rejected. In fact, more interconnection between people make them receive more. Structural social capital (interconnection) is positively related to opening viral message; therefore 3a is confirmed. In fact, more interconnection between people make them open more. Structural social capital (interconnection) is positively related to sending viral message; therefore 3a is confirmed. In fact, more interconnection between people make them send more Relational Social Capital 448

9 There is no positive relationship between relational social capital and receiving viral message; therefore 4a is rejected. In fact, relationship between people does not cause to receive more viral. During the study, relationship between people via network had been periodically than frequently. Relational social capital is positively related to opening viral message; therefore, 4a is rejected. In fact, relationship between people via network meke them open more viral and more close relationship between individuals in network is reliable, friendly and personal. Relational social capital is positively related to sending viral message; therefore, 4c is confirmed. In fact, relationship between individuals via network meke them send more viral to others and more close relationship between individuals is reliable, friendly and personal in network Positive and negative attitudes There is positive relationship between receiving viral message and willing to open ; therefore, 5a is confirmed. In fact, if the attitudetoward receiving viral message is more positive, they highly tend to open and read these. There is negative relationship between receiving viral message and a willingness to open ; therefore, 5a is confirmed. In fact, if the attitudetoward receiving viral message is more negative, they are less inclined to open and read these. There is no positive relationship between a positive attitude toward receiving viral message and a willingness to send the.thus, the first part of 5b is rejected.in fact, no matter how much the attitude toward receiving viral message is positive, because it is not a reason in order to send this message to others. There is negative relationship between negative attitude against toward receiving viral message and a willingness to send. Thus, the second part of 5b is confirmed.. In fact, if the individuals attitudetoward receiving viral message is more negative, they are less inclined to send these cognitive social capital There is no positive relationship between cognitive social capital and receiving viral messageand thus 6 is rejected. In fact, more cognitive social capital is, more is not received by people. There is no positive relationship between cognitive social capital and opening viral messageand therefore 6b is rejected. In fact, if there is more cognitive social capital, it does not make people open and read more. There is no positive relationship between cognitive social capital and sending viral message; therefore, 6c is rejected. In fact, if there is more cognitive social capital, it does not make people send more. References [1]Camarero, C., San Jose, R., (2011), Social and attitudinal determinants of viral marketing dynamics, Computers in Human Behavior, Vol. 27, pp [2]Chen, J., Zhu, Z. and H.Y. Xie., (2004), Measuring intellectual capital: a new model and empirical study, Journal of Intellectual Capital, Vol. 5, No. 1, pp [3]Chiu, H., Lee, M., Chen, J., (2007), Viral Marketing: A study of Spreading Behavior Across Gender, Journal of Website Promotion, Vol. 2(3/4), pp [4]Dobele, A., Toleman, D., Beverland, M., (2005), Controlled infection! Spreading the brand message through viral marketing, Business Horizons, Vol. 48, pp [5]Ghelichli, B. and A. Moshabaki., (2006), The role of social capital in the creation of intellectual capital, Management Knowledge, Vol. 19, pp [In Persian] [6]Helm,S.,(2000), ViralMarketingEstablishingCustomer Relationships by Word-of-mouth, Electronic Markets, Vol. 10, No. 3, pp [7]Howard, T., (2005), Viral Advertising Spreads Through Marketing Plans, USA TODAY, June 23, 6B, available at: x.htm 449

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