1Kirikkale Universty, Department of Business Administration, Kirikkale, Turkey, E-mail: [email protected]
2Kirikkale Universty, Department of Business Administration, Kirikkale, Turkey, E-mail: [email protected]
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Social Media, Consumer, Word of Mouth in Social Media
Understanding social media tools and consumption related behaviors in these communication areas are important for firms since usage rate of these tools increases day by day. Social media is seen as an important tool for integrated marketing communication and connecting with customers, which is a new phenomenon in marketing science (Alkhas, 2011) Social network sites like Facebook, Twitter, Myspace which is seen a huge market area affect purchasing decisions. Social media atmosphere can be described as a new marketing communication channel. Data that are sent by the user pages which contains videos, articles, photos, music, opinions etc. spread lots of people by the help of individual connections. At this point attractiveness of sender and reference groups are important factors in terms of reliability of these contents (Akar, 2010;107). Social communication tools lead users to be producers of information. The contents which created by users in social media consist of blogs (micoblogs, social bookmarking, social networks, forums etc.), simultaneous messaging tools (e-mail groups, chatting sites, video sharing sites etc.), video blogs (foto blog, RSS, document sharing etc.) (Maynacioglu, 2009;63).
Word of mouth behavior is one of the important information sources in purchasing behaviors and it affects firms in terms of image, reputation, relationships with community, promotion activities and etc. In addition, word of mouth is closely related with repurchasing and brand switching behaviors (Marangoz, 2007).
Consumption related behaviors in social media are investigated especially in terms of online word of mouth which affects purchasing behaviors. (Brown et all. 2007, Hu et all. 2007, Ye et all. 2011, Bambauer-Sachse and Mangold 2011). Duan, Gu and Whinston (2008) researches the internet word of mouth as a feedback mechanism for film sector and retail sales. Their study shows that volume of the word of mouth causes realizing higher sales volume. Online word of mouth is seen as an important component of shopping web sites, positively perceived by customers and affects customer behaviors. On these sites, the vast majority of customers primarily view comments and comparisons about products. And a significant relationship is seen between online communication and customer trust ( Hui, 2011).
Since social media tools are kind of web sites, they should be taken into consideration as web sites to examine them as a factor affecting word of mouth. At this point, the factors affecting web site performance need to be examined. Coyle and Thomson (2001) argue that telepresence (actually being there) perceptions of customers are positively affected by the vividness and interactivity of web sites. Moreover, vividness is positively related with stronger attitudes toward web site. So it can be expected that these kind of social media qualities are related with the online word of mouth tendencies and these relations had better be investigated.
Chakravarty and others (2009) investigate effects of online word of mouth and professional opinions on product evaluations of customers and the study shows that infrequent users are affected from communications more than frequent users. The same study indicates that frequent users of product are affected mostly by expert opinions rather than online word of mouth. At this point it would be wise to address source credibility concept for a better understanding of the issue which contains expertise, reliability and credibility dimensions. Moreover also social media using properties are other variables that have to be investigated.
Hui-Yi and Pi-Hsuan (2010) show that the variables like gender, age, education level, using frequency affect the reliability perceptions about messages. Furthermore results of the same study indicate that confidence level toward topics affects consumption behaviors in food sector. In other words, perceiving online communications as expert and reliable is an factor that influences positive perceptions about information and possibility of being affected in consumption behaviors.
Tsuifang et all. (2010) claims that power of information transferred in negative online word of mouth, expertise of sender and strength of the relationship between sender and receiver are effective in customer purchasing. Furthermore trust is a mediator between negative communication and purchasing decision.
Eastin (2001) express accuracy, believability and factualness as important factors that affect source credibility.
Kang (2010) conducted a study to measure the reliability of social media. The study scrutinizes source credibility with blogger credibility (knowledgeable, influential, passionate, transparent, reliable) and content credibility (fair, consistent, focused, accurate, timely, popular, informative, insightful, authentic). In addition to source and content credibility, the nature of relationships in social media also is also important factor affects credibility. So the relationship quality should be investigated in this regard.
Moreover Awad and Ragowsky (2008)’s study pay attention the online word of mouth that firms use to build trust in customers. And it is seen that value and reliability of electronic word of mouth differs in terms of gender. Moreover related study shows women are more influenced from the reliability of online communication in terms of making online purchasing with respect to men.
Akar and Topçu (2011) examines the consumer attitudes toward marketing activities with social media which is defined as a new marketplace for marketers. In this context, determinants of attitudes toward social media marketing are specified as social media, social media using properties, social media knowledge, consumers’ following of social media, consumers’ foresight about social media, consumers’ fears of marketing with social media.
Hui (2011) emphasized the role of personality in the electronic word of mouth communication. The study shows extraverted customers pay attention to customer experiences and feelings of individuals. On the other hand introverted individuals are more interested in the after-sales activities of customers. Moreover the results of the same research indicate that extraverted customers are influenced from mostly product and price related opinions and introverted customers are influenced from mostly service related opinions. “Five Factor Model” is commonly used and reliable approach to detect and measure personality. According to this model, personality is expressed with five factors which are extraversion, emotional stability, consciousness, openness to experience and agreeableness (Bacanli et all. 2009). Cooper, Smillie ve Corr (2010) made an effort to develop valid and reliable mini-personality scale which consists of twenty questions based on five-factor model. To summarize, personality traits can also be thought among the factors that affect the word of mouth in social media. It can be expected that extraverted individuals use social media and they conduct word of mouth behaviors in social media more than others.
In addition to these factors, technology or computer using anxiety can be thought as other factor that can be effective in word of mouth behavior in social media. Because ability of using technological tools and keeping up with recent technological developments are related with technologic anxiety.
3.1 Goal and Method of the Research
The main goal of the research is identifying factors affect word of mouth behaviors in social media. Ta achieve this goal, possible factors are specified as social media using properties (frequency, daily using duration, experience), social media credibility, technological anxiety, positive attitudes toward social media, positive attitudes toward marketing with social media and extraverted personality level.
In this framework, initial data were gathered by conducting a survey on 380 undergraduate students of the Faculty of Economics and Administrative Sciences of Kirikkale University. So generalizing the findings of research to all consumers is not possible. Questionnaire was developed by the help of previous studies. Statistical analyses were made on obtained data namely reliability analysis, factor analysis and correlation analysis.
To identify the word of mouth behavior in social media, general word of mouth questions in the Marangoz (2007)’s study are used by adapting them into social media. Chen and Wells (1999)’s study was helpful for identifying the questions which is supposed to measure positive attitudes toward social media. The questions which is aimed to measure the perceived credibility of social media, the variables in Kang (2010)’s study were evaluated. To measure the extraverted personality level of participants, questions in the Cooper, Smillie and Corr (2010) mini-personality scale was helpful. Moreover Raub (1981)’s study was used to measure computer anxiety level of participants. At last in preparing the questions to depict the positive attitudes toward marketing with social media Akar ve Topçu (2011)’s study was helpful.
Research model is determined as in the following figure;
To achieve the goal of the research following hypotheses are developed.
|H1: Positive word of mouth in s.m. is meaningfully related with technology using anxiety.|
|H2: Negative word of mouth in s.m. is meaningfully related with technology using anxiety.|
|H3: Positive word of mouth in s.m. is meaningfully related with positive attitudes toward s.m.|
|H4: Negative word of mouth in s.m. is meaningfully related with positive attitudes toward s.m.|
|H5: Positive word of mouth in s.m. is meaningfully related with credibility of information generated in s.m.|
|H6: Negative word of mouth in s.m. is meaningfully related with credibility of information generated s.m.|
|H7: Positive word of mouth in s.m. is meaningfully related with attitudes toward marketing with s.m.|
|H8: Negative word of mouth in s.m. is meaningfully related with attitudes toward marketing with s.m.|
|H9: Positive word of mouth in s.m. is meaningfully related with credibility of friends in s.m.|
|H10: Negative word of mouth in s.m. is meaningfully related with credibility of friends in s.m.|
|H11: Positive word of mouth in s.m. is meaningfully related with credibility of relationships in s.m.|
|H12: Negative word of mouth in s.m. is meaningfully related with credibility of relationships in s.m.|
|H13: Positive word of mouth in s.m. is meaningfully related with extraverted personality.|
|H14: Negative word of mouth in s.m. is meaningfully related with extraverted personality.|
|H15: Positive word of mouth in s.m. is meaningfully related with daily social media using duration.|
|H16: Negative word of mouth in s.m. is meaningfully related with daily social media using duration.|
|H17: Positive word of mouth in s.m. is meaningfully related with social media using experience.|
|H18: Negative word of mouth in s.m. is meaningfully related with social media using experience.|
|H19: Positive word of mouth in s.m. is meaningfully related with quantity of friends in s.m.|
|H20: Negative word of mouth in s.m. is meaningfully related with quantity of friends in s.m.|
|s.m.; Social Media|
Table 1: Research Hypotheses
3.2. Findings of the Research
3.2.1. General Findings and Reliability Analysis
As the answers are evaluated which is about frequency of social media using frequency; % 45 of the respondents uses social media tools several times in a day and %28 of the respondent uses several times in a week. Moreover % 90 of the participants uses social media less than two hours in a day. Furthermore % 44 of the research participants uses social media tools since 5 years and more. And average friend quantity of a participant is about 100 – 300 with a % 62.
Alpha model (Cronbach Alfa (α) Coefficient), which is used in reliability analysis, shows the homogeneity of research questions. It takes values between 0 and 1 and as it closers to 1 the reliability of questionnaire form increases (Kalaycı et all., 2009). Under this framework the alpha coefficients of the variables and survey form are as follows;
|Extraversion Personality Level||,85|
|Technology Using Anxiety||,92|
|Attitudes toward Marketing with Social Media||,92|
|Positive Attitudes toward Social Media||,86|
|Credibility of Social Media||,88|
|Word of Mouth (positive;0,92 negative; 0,89)||,93|
Table 2: Alpha Coefficients
3.2.2. Factor Analysis
Kaiser-Meyer-Olkin coefficient is specified as 0,80 which shows suitability of research questionnaire for factor analysis. Moreover Bartlett is seen as meaningful. Specified factors are named as; first factor; “Technology Anxiety”, second factor; “Positive Word of Mouth in Social Media”, third factor; “Attitudes toward Marketing with Social Media”, fourth factor; “Perceived Credibility of Social Media Generated Information”, fifth factor; “Positive Attitudes toward Social Media”, sixth factor; “Credibility of Friends in Social Media”, seventh factor; “Negative Word of Mouth in Social Media”, eight factor; “Reliability of Relationships in Social Media”, and ninth factor; “Extraverted Personality Level”.
Factors and their components are seen in the following table;
Extraction Method: Principal Component Analysis.
Table 3: Rotated Component Matrix
Questions which represent the factors are seen in the following sentences;
* Technology Using Anxiety;
• I fear making irrecoverable mistakes when using technological products.
• Understanding technological issues is difficult for me.
• I can not keep up with the technological products and developments.
• I refrain from technology since I am not familiar.
• I worry about the deterioration of technological tools when using them.
• I refrain from using technological devices.
• Learning abilities about technology is difficult for me.
• Understanding technological terminology is difficult for me.
* Positive Word of Mouth in Social Media;
• I suggest products that I satisfied to my friends in social media tools.
• I tell positive product experiences to my friends in social media tools.
• I make positive product ratings in social media.
• I comment on successful products and brands in social media.
• I talk with my friends about positive features of products in social media.
• I talk about my product satisfactions in social media.
• I make sharing about successful products in social media.
* Attitudes toward Marketing with Social Media;
• Marketing products by the help of social media is attractive.
• Marketing with social media applications is a good idea.
• All firms should engage in marketing with social sharing sites like facebook, twitter.
• I like marketing activities which is made by social media.
• Firms should use social media for marketing.
• I think that marketing with social media will be future of marketing.
* Credibility of Information Generated in Social Media;
• Product related information in social media is consistent.
• Product related information in social media is clear.
• Product related information in social media is real.
• Product related information in social media is true.
• Product related comments are informative which are made in social media.
• Product related information in social media is up to date.
* Positive Attitudes toward Social Media;
• Social media is a good way to communicate with friends.
• Social media tools make communications easy.
• Social media is a good tool for spending time.
• I use social media in future.
• I satisfied with the services of social media.
• I feel relaxed when dealing with social media.
* Credibility of Friends in Social Media;
• People that I communicate by social media are clear.
• People that I communicate by social media are decisive.
• People that I communicate by social media are knowledgeable.
• People that I communicate by social media are effective.
• People that I communicate by social media are reliable.
* Negative Word of Mouth in Social Media;
• I share unsuccessful firm activities in social media.
• I share unsuccessful ads in social media.
• I talk about products and firms that I dissatisfied in social media.
• I share unsuccessful products with my friends in social media.
* Credibility of Relationships in Social Media;
• I built sincere relationships thorough social media.
• I built close relationships thorough social media.
• The relationships that I built in social media are powerful.
* Extraverted Personality Level;
• Am the life of the party.
• I talk to a lot of different people at parties.
• I talk a lot generally.
• I never keep in the background.
3.3.3. Research Findings
When general averages of the research variables are analyzed it is seen that positive word of mouth average in social media (2,24 over 5) is higher than negative word of mouth (1,87 over 5) (1 to 5; never – always) which means that people have higher tendency to conduct positive communications in social media rather than negative. Moreover word of mouth behaviors of participants are about seldom which indicates that social media tools are used for word of mouth for secondary purposes.
|1||Technology Using Anxiety||2,24|
|2||Positive Word of Mouth in Social Media||2,25|
|3||Attitudes toward Marketing with Social Media||3,40|
|4||Credibility of Information Generated in Social Media||2,87|
|5||Positive Attitudes toward Social Media||3,81|
|6||Credibility of Friends in Social Media||3,06|
|7||Negative Word of Mouth in Social Media||1,87|
|8||Credibility of Relationships in Social Media||2,95|
Table 4: General Averages
Correlation analysis shows that there is a negative and meaningful relationship between technology using anxiety and positive word of mouth and there is not a significant relationship between technology anxiety and negative word of mouth. As supposed technological anxiety is negatively related with positive word of mouth in social media which means that stressful people are reluctant to share their satisfactions about products in social media. But this negative relationship is not seen in terms of negative word of mouth, which refers to technological anxiety is not an determinant that affect negative word of mouth in social media. Correlation analysis results support first hypothesis but do not support second.
Moreover the level of positive attitudes toward social media is positively and meaningfully related with both positive and negative word of mouth behavior in social media. So the third and fourth hypotheses are accepted. Furthermore perceived credibility of information that generated in social media is also positively related with positive and negative word of mouth in social media. By this result, fifth and sixth hypotheses are accepted.
Furthermore attitude toward marketing with social media is positively related with positive word of mouth but it is not related with negative word of mouth significantly. So seventh hypothesis is supported and eighth hypothesis is rejected.
What is more credibility of friends is significantly relate with both positive and negative word of mouth which supports the ninth and tenth hypotheses. Related with the credibility factor; credibility of relationships in social media is also meaningfully related with word of mouth behaviors and eleventh and twelfth hypotheses are accepted.
As an individual dimension extraverted personality is significantly related with positive and negative word of mouth behavior in social media which makes hypothesis thirteenth and fourteenth be accepted.
Daily social media using duration is an important factor that affects positive and negative word of mouth behaviors which means as daily using time increases, word of mouth behaviors of consumers increases as expected. And fifteenth and sixteenth hypotheses are supported. Furthermore social media using experience is also another factor that positively related with word of mouth behaviors. The correlation values support the seventeenth and eighteenth hypotheses. At last average friend number of participants is another factor that related with word of mouth behavior in social media and nineteenth and twentieth hypotheses are also accepted.
Another result of the correlation analysis is that; factors affecting word of mouth behavior is more effective for positive word of mouth than negative word of mouth except for quantity and credibility of friends. This shows that the factors are more significant for positive word of mouth generally. On the other hand, changes in the credibility of friends and average friend number lead more changes in negative word of mouth. In other words, positive word of mouth elasticity of specified variables is generally higher than negative word of mouth.
The correlation analysis result is seen in table 5;
|Pearson Correlation||Positive Word of Mouth in Social Media||Negative Word of Mouth in Social Media|
|Technology Using Anxiety||-,095*||,026|
|Positive Attitudes toward Social Media||,341**||,155**|
|Credibility of Information Generated in Social Media||,329**||,227**|
|Attitudes toward Marketing with Social Media||,199**||,008|
|Credibility of Friends in Social Media||,128**||,156**|
|Credibility of Relationships in Social Media||,096*||,082*|
|Daily Social Media Using Duration||,172**||,126**|
|Social Media Using Experience||,241**||,159**|
|Quantity of Friends in Social Media||,141**||,190**|
* Correlation is significant at the 0.05 level (1-tailed).
Table 5: Correlation Analysis
As correlation analyses is indicated above hypotheses and their evaluation results are in seen in Table 6;
|H1: PWOM in s.m. is meaningfully related with technology using anxiety.||Accept|
|H2: NWOM in s.m. is meaningfully related with technology using anxiety.||Reject|
|H3: PWOM in s.m. is meaningfully related with positive attitudes toward s.m.||Accept|
|H4: NWOM in s.m. is meaningfully related with positive attitudes toward s.m.||Accept|
|H5: PWOM in s.m. is meaningfully related with credibility of information generated in s.m.||Accept|
|H6: NWOM in s.m. is meaningfully related with credibility of information generated s.m.||Accept|
|H7: PWOM in s.m. is meaningfully related with attitudes toward marketing with s.m.||Accept|
|H8: NWOM in s.m. is meaningfully related with attitudes toward marketing with s.m.||Reject|
|H9: PWOM in s.m. is meaningfully related with credibility of friends in s.m.||Accept|
|H10: NWOM in s.m. is meaningfully related with credibility of friends in s.m.||Accept|
|H11: PWOM in s.m. is meaningfully related with credibility of relationships in s.m.||Accept|
|H12: NWOM in s.m. is meaningfully related with credibility of relationships in s.m.||Accept|
|H13: PWOM in s.m. is meaningfully related with extraverted personality.||Accept|
|H14: NWOM in s.m. is meaningfully related with extraverted personality.||Accept|
|H15: PWOM in s.m. is meaningfully related with daily social media using duration.||Accept|
|H16: NWOM in s.m. is meaningfully related with daily social media using duration.||Accept|
|H17: PWOM in s.m. is meaningfully related with social media using experience.||Accept|
|H18: NWOM in s.m. is meaningfully related with social media using experience.||Accept|
|H19: PWOM in s.m. is meaningfully related with quantity of friends in s.m.||Accept|
|H20: NWOM in s.m. is meaningfully related with quantity of friends in s.m.||Accept|
s.m., social media, PWOM; Positive Word of Mouth, NWOM; Negative Word of Mouth
Table 6: Hypothesis Testing
As an important information source, word of mouth is an important factor that affects customer behaviors. In recent years social media is a widely used communication tool especially among young people. Like any other communication types, this new communication area makes people interact with each other about their consuming behaviors inevitably. Word of mouth communication in social media is one of the consumptiona related behavior in social media. This study is conducted to illuminate the nature and determinants of the word of mouth behavior in social media tools.
As a result of study, word of mouth behaviors of participants is seen about “seldom” which means that people use social media predominantly for other communication needs. Moreover the factors affecting word of mouth behavior are pointed out as; positive attitudes toward social media, credibility of information generated in social media, social media using experience, attitudes toward marketing with social media, extraverted personality level, daily social media using duration, quantity of friends in social media, credibility of friends in social media, credibility of relationships in social media and technology using anxiety. These results are useful for firms while determining social media strategies to encourage positive word of mouth and prevent negative word of mouth.
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